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1. Contrasting and comparing the efficacy of non-pharmaceutical interventions on air-borne and vector-borne diseases

Author

Poudyal, Bibandhan, Panõs, David Soriano, and Ghoshal, Gourab

Subjects
Physics - Physics and Society, Quantitative Biology - Populations and Evolution
Abstract

Non-pharmaceutical interventions (NPIs) aimed at limiting human mobility have demonstrated success in curbing the transmission of airborne diseases. However, their effectiveness in managing vector-borne diseases remains less clear. In this study, we introduce a framework that integrates mobility data with vulnerability matrices to evaluate the differential impacts of mobility-based NPIs on both airborne and vector-borne pathogens. Focusing on the city of Santiago de Cali in Colombia, our analysis illustrates how mobility-based policies previously proposed to contain airborne disease can make cities more prone to the spread of vector-borne diseases. By proposing a simplified synthetic model, we explain the limitations of the latter policies and exploit the synergies between both types of diseases to find new interventions reshaping the mobility network for their simultaneous control. Our results thus offer valuable insights into the epidemiological trade-offs of concurrent disease management, providing a foundation for the design and assessment of targeted interventions that reshape human mobility., Comment: 25 pages, 5 figures, 63 references. Supplementary material included

Published
2024

2. EEG-based AI-BCI Wheelchair Advancement: A Brain-Computer Interfacing Wheelchair System Using Machine Learning Mechanism with Right and Left Voluntary Hand Movement

Author

Paneru, Biplov, Paneru, Bishwash, and Poudyal, Khem Narayan

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Signal Processing
Abstract

This paper presents an Artificial Intelligence (AI) integrated novel approach to Brain-Computer Interface (BCI)-based wheelchair development, utilizing a voluntary Right Left Hand Movement mechanism for control. The system is designed to simulate wheelchair navigation based on voluntary right and left-hand movements using electroencephalogram (EEG) data. A pre-filtered dataset, obtained from an open-source EEG repository, was segmented into arrays of 19x200 to capture the onset of hand movements. The data was acquired at a sampling frequency 200Hz in the laboratory experiment. The system integrates a Tkinter-based interface for simulating wheelchair movements, offering users a functional and intuitive control system. Various machine learning models, including Support Vector Machines (SVM), XGBoost, random forest, and a Bi-directional Long Short-Term Memory (Bi-LSTM) attention-based model, were developed. The random forest model obtained 79% accuracy. Great performance was seen on the Logistic Regression model which outperforms other models with 92% accuracy and 91% accuracy on the Multi-Layer Perceptron (MLP) model. The Bi-LSTM attention-based model achieved a mean accuracy of 86% through cross-validation, showcasing the potential of attention mechanisms in BCI applications.

Published
2024

3. First operation of LArTPC in the stratosphere as an engineering GRAMS balloon flight (eGRAMS)

Author

Nakajima, R., Arai, S., Aoyama, K., Utsumi, Y., Tamba, T., Odaka, H., Tanaka, M., Yorita, K., Aramaki, T., Asaadi, J., Bamba, A., Cannady, N., Coppi, P., De Nolfo, G., Errando, M., Fabris, L., Fujiwara, T., Fukazawa, Y., Ghosh, P., Hagino, K., Hakamata, T., Hijikata, U., Hiroshima, N., Ichihashi, M., Ichinohe, Y., Inoue, Y., Ishikawa, K., Ishiwata, K., Iwata, T., Karagiorgi, G., Kato, T., Kawamura, H., Krizmanic, J., Leyva, J., Malige, A., Mitchell, J. G., Mitchell, J. W., Mukherjee, R., Nakazawa, K., Okuma, K., Perez, K., Poudyal, N., Safa, I., Sasaki, M., Seligman, W., Shirahama, K., Shiraishi, T., Smith, S., Suda, Y., Suraj, A., Takahashi, H., Takashima, S., Tandon, S., Tatsumi, R., Tomsick, J., Tsuji, N., Uchida, Y., Watanabe, S., Yano, Y., Yawata, K., Yoneda, H., Yoshimoto, M., and Zeng, J.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

GRAMS (Gamma-Ray and AntiMatter Survey) is a next-generation balloon/satellite experiment utilizing a LArTPC (Liquid Argon Time Projection Chamber), to simultaneously target astrophysical observations of cosmic MeV gamma-rays and conduct an indirect dark matter search using antimatter. While LArTPCs are widely used in particle physics experiments, they have never been operated at balloon altitudes. An engineering balloon flight with a small-scale LArTPC (eGRAMS) was conducted on July 27th, 2023, to establish a system for safely operating a LArTPC at balloon altitudes and to obtain cosmic-ray data from the LArTPC. The flight was launched from the Japan Aerospace Exploration Agency's (JAXA) Taiki Aerospace Research Field in Hokkaido, Japan. The total flight duration was 3 hours and 12 minutes, including a level flight of 44 minutes at a maximum altitude of 28.9 km. The flight system was landed on the sea and successfully recovered. The LArTPC was successfully operated throughout the flight, and about 0.5 million events of the cosmic-ray data including muons, protons, and Compton scattering gamma-ray candidates, were collected. This pioneering flight demonstrates the feasibility of operating a LArTPC in high-altitude environments, paving the way for future GRAMS missions and advancing our capabilities in MeV gamma-ray astronomy and dark matter research.

Published
2024

4. How a Space-Time Singularity Helps Remove the Ultraviolet Divergence Problem

Author

Henheik, Joscha, Poudyal, Bipul, and Tumulka, Roderich

Subjects
Mathematical Physics, General Relativity and Quantum Cosmology, Quantum Physics
Abstract

Particle creation terms in quantum Hamiltonians are usually ultraviolet divergent and thus mathematically ill defined. A rather novel way of solving this problem is based on imposing so-called interior-boundary conditions on the wave function. Previous papers showed that this approach works in the non-relativistic regime, but particle creation is mostly relevant in the relativistic case after all. In flat relativistic space-time (that is, neglecting gravity), the approach was previously found to work only for certain somewhat artificial cases. Here, as a way of taking gravity into account, we consider curved space-time, specifically the super-critical Reissner-Nordstr\"om space-time, which features a naked timelike singularity. We find that the interior-boundary approach works fully in this setting; in particular, we prove rigorously the existence of well-defined, self-adjoint Hamiltonians with particle creation at the singularity, based on interior-boundary conditions. We also non-rigorously analyze the asymptotic behavior of the Bohmian trajectories and construct the corresponding Bohm-Bell process of particle creation, motion, and annihilation. The upshot is that in quantum physics, a naked space-time singularity need not lead to a breakdown of physical laws, but on the contrary allows for boundary conditions governing what comes out of the singularity and thereby removing the ultraviolet divergence., Comment: 38 pages LaTeX

Published
2024

5. Local strain inhomogeneities during electrical triggering of a metal-insulator transition revealed by X-ray microscopy.

Author

Salev, Pavel, Kisiel, Elliot, Sasaki, Dayne, Gunn, Brandon, He, Wei, Feng, Mingzhen, Li, Junjie, Tamura, Nobumichi, Poudyal, Ishwor, Islam, Zahirul, Takamura, Yayoi, Frano, Alex, and Schuller, Ivan

Subjects
X-ray microdiffraction, dark-field X-ray microscopy, in operando microscopy, metal–insulator transition, resistive switching
Abstract

Electrical triggering of a metal-insulator transition (MIT) often results in the formation of characteristic spatial patterns such as a metallic filament percolating through an insulating matrix or an insulating barrier splitting a conducting matrix. When MIT triggering is driven by electrothermal effects, the temperature of the filament or barrier can be substantially higher than the rest of the material. Using X-ray microdiffraction and dark-field X-ray microscopy, we show that electrothermal MIT triggering leads to the development of an inhomogeneous strain profile across the switching device, even when the material does not undergo a pronounced, discontinuous structural transition coinciding with the MIT. Diffraction measurements further reveal evidence of unique features associated with MIT triggering including lattice distortions, tilting, and twinning, which indicate structural nonuniformity of both low- and high-resistance regions inside the switching device. Such lattice deformations do not occur under equilibrium, zero-voltage conditions, highlighting the qualitative difference between states achieved through increasing temperature and applying voltage in nonlinear electrothermal materials. Electrically induced strain, lattice distortions, and twinning could have important contributions in the MIT triggering process and drive the material into nonequilibrium states, providing an unconventional pathway to explore the phase space in strongly correlated electronic systems.

Published
2024

6. Solar Power Prediction Using Satellite Data in Different Parts of Nepal

Author

Nepal, Raj Krishna, Khanal, Bibek, Ghimire, Vibek, Neupane, Kismat, Pokharel, Atul, Niraula, Kshitij, Tiwari, Baburam, Bhattarai, Nawaraj, Poudyal, Khem N., Karki, Nawaraj, Dangi, Mohan B, and Biden, John

Subjects
Physics - Atmospheric and Oceanic Physics, Computer Science - Machine Learning
Abstract

Due to the unavailability of solar irradiance data for many potential sites of Nepal, the paper proposes predicting solar irradiance based on alternative meteorological parameters. The study focuses on five distinct regions in Nepal and utilizes a dataset spanning almost ten years, obtained from CERES SYN1deg and MERRA-2. Machine learning models such as Random Forest, XGBoost, K-Nearest Neighbors, and deep learning models like LSTM and ANN-MLP are employed and evaluated for their performance. The results indicate high accuracy in predicting solar irradiance, with R-squared(R2) scores close to unity for both train and test datasets. The impact of parameter integration on model performance is analyzed, revealing the significance of various parameters in enhancing predictive accuracy. Each model demonstrates strong performance across all parameters, consistently achieving MAE values below 6, RMSE values under 10, MBE within |2|, and nearly unity R2 values. Upon removal of various solar parameters such as "Solar_Irradiance_Clear_Sky", "UVA", etc. from the datasets, the model's performance is significantly affected. This exclusion leads to considerable increases in MAE, reaching up to 82, RMSE up to 135, and MBE up to |7|. Among the models, KNN displays the weakest performance, with an R2 of 0.7582546. Conversely, ANN exhibits the strongest performance, boasting an R2 value of 0.9245877. Hence, the study concludes that Artificial Neural Network (ANN) performs exceptionally well, showcasing its versatility even under sparse data parameter conditions., Comment: 20 pages, 12 figures, 5 tables

Published
2024

9. Real-time Geoinformation Systems to Improve the Quality, Scalability, and Cost of Internet of Things for Agri-environment Research

Author

Runck, Bryan C., Schulz, Bobby, Bishop, Jeff, Carlson, Nathan, Chantigian, Bryan, Deters, Gary, Erdmann, Jesse, Ewing, Patrick M., Felzan, Michael, Fu, Xiao, Greyling, Jan, Hogan, Christopher J., Hollman, Andrew, Joglekar, Ali, Junker, Kris, Kantar, Michael, Kaunda, Lumbani, Krishna, Mohana, Lynch, Benjamin, Marchetto, Peter, Marsolek, Megan, McKay, Troy, Morris, Brad, Niaghi, Ali Rashid, Pamulaparthy, Keerthi, Pardey, Philip, Piotrowski, Ann, Poudyal, Christina, Prather, Tom, Raghavan, Barath, Reiter, Maggie, Rosen, Lucas, Salazar, Benjamin, Scobbie, Andrew, Sharma, Vasudha, Silverstein, Kevin A. T., Singh, Gurparteet, Strock, Jeff, Subedi, Samikshya, Tang, Evan, Turturillo, Gianna, Watkins, Eric, Webster, Blake, and Wilgenbusch, James

Subjects
Quantitative Biology - Quantitative Methods
Abstract

With the increasing emphasis on machine learning and artificial intelligence to drive knowledge discovery in the agricultural sciences, spatial internet of things (IoT) technologies have become increasingly important for collecting real-time, high resolution data for these models. However, managing large fleets of devices while maintaining high data quality remains an ongoing challenge as scientists iterate from prototype to mature end-to-end applications. Here, we provide a set of case studies using the framework of technology readiness levels for an open source spatial IoT system. The spatial IoT systems underwent 3 major and 14 minor system versions, had over 2,727 devices manufactured both in academic and commercial contexts, and are either in active or planned deployment across four continents. Our results show the evolution of a generalizable, open source spatial IoT system designed for agricultural scientists, and provide a model for academic researchers to overcome the challenges that exist in going from one-off prototypes to thousands of internet-connected devices., Comment: 20 pages, 5 figures, 1 table

Published
2024

10. On the Asymptotic Normality of Trimmed and Winsorized L-statistics

Author

Poudyal, Chudamani

Subjects
Mathematics - Statistics Theory, Statistics - Applications, Statistics - Methodology
Abstract

There are several ways to establish the asymptotic normality of $L$-statistics, which depend on the choice of the weights-generating function and the cumulative distribution selection of the underlying model. In this study, we focus on stablishing computational formulas for the asymptotic variance of two robust $L$-estimators: the method of trimmed moments (MTM) and the method of winsorized moments (MWM). We demonstrate that two asymptotic approaches for MTM are equivalent for a specific choice of the weights-generating function. These findings enhance the applicability of these estimators across various underlying distributions, making them effective tools in diverse statistical scenarios. Such scenarios include actuarial contexts, such as payment-per-payment and payment-per-loss data scenarios, as well as in evaluating the asymptotic distributional properties of distortion risk measures. The effectiveness of our methodologies depends on the availability of the cumulative distribution function, ensuring broad usability in various statistical environments.

Published
2024

11. A Comprehensive Study of the Current State-of-the-Art in Nepali Automatic Speech Recognition Systems

Author

Ghimire, Rupak Raj, Bal, Bal Krishna, and Poudyal, Prakash

Subjects
Computer Science - Sound, Computer Science - Computation and Language, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

In this paper, we examine the research conducted in the field of Nepali Automatic Speech Recognition (ASR). The primary objective of this survey is to conduct a comprehensive review of the works on Nepali Automatic Speech Recognition Systems completed to date, explore the different datasets used, examine the technology utilized, and take account of the obstacles encountered in implementing the Nepali ASR system. In tandem with the global trends of ever-increasing research on speech recognition based research, the number of Nepalese ASR-related projects are also growing. Nevertheless, the investigation of language and acoustic models of the Nepali language has not received adequate attention compared to languages that possess ample resources. In this context, we provide a framework as well as directions for future investigations., Comment: Accepted in International Conference on Technologies for Computer, Electrical, Electronics & Communication (ICT-CEEL 2023)

Published
2024

12. Robust Estimation of the Tail Index of a Single Parameter Pareto Distribution from Grouped Data

Author

Poudyal, Chudamani

Subjects
Statistics - Methodology, Mathematics - Statistics Theory, Quantitative Finance - Risk Management, Statistics - Computation, Statistics - Machine Learning, 62F35, 62P05
Abstract

Numerous robust estimators exist as alternatives to the maximum likelihood estimator (MLE) when a completely observed ground-up loss severity sample dataset is available. However, the options for robust alternatives to MLE become significantly limited when dealing with grouped loss severity data, with only a handful of methods like least squares, minimum Hellinger distance, and optimal bounded influence function available. This paper introduces a novel robust estimation technique, the Method of Truncated Moments (MTuM), specifically designed to estimate the tail index of a Pareto distribution from grouped data. Inferential justification of MTuM is established by employing the central limit theorem and validating them through a comprehensive simulation study., Comment: 18 pages, 1 figure, 6 tables

Published
2024

13. Cybersecurity Challenges and Awareness of the Multi-Generational Learners in Nepal

Author

Raj Kumar Dhungana, Lina Gurung, and Hem Poudyal

Abstract

Increased exposure to technologies has lately emerged as one of the everyday realities of digital natives, especially K-12 students, and teachers, the digital immigrants. Protection from cybersecurity risks in digital learning spaces is a human right, but students are increasingly exposed to high-risk cyberspace without time to cope with cybersecurity risks. This study, using a survey (N-891 students and 157 teachers) and in-depth interviews (27 students and 14 teachers), described the students' cybersecurity-related experiences and challenges in Nepal. This study revealed that the school's cybersecurity support system is poor and teachers has very low awareness and competencies to protect students from cybersecurity-related challenges. To create a safe cyberspace for learners, it is urgent to enhance the cybersecurity awareness and skills of teachers, as the existing infrastructure is weak and there is a significant gap related to the cybersecurity awareness between students and teachers. Poor cybersecurity is one of the significant barriers to the quality of education in Nepal. In the age of information and technology, effective collaboration among parents, teachers, and students, the multigenerational learners, is the prerequisite for ensuring children's rights to learn in all settings including cyberspace.

Published
2023

14. Local strain inhomogeneities during the electrical triggering of a metal-insulator transition revealed by the x-ray microscopy

Author

Salev, Pavel, Kisiel, Elliot, Sasaki, Dayne, Gunn, Brandon, He, Wei, Feng, Mingzhen, Li, Junjie, Tamura, Nobumichi, Poudyal, Ishwor, Islam, Zahir, Takamura, Yayoi, Frano, Alex, and Schuller, Ivan K.

Subjects
Condensed Matter - Materials Science
Abstract

Electrical triggering of a metal-insulator transition (MIT) often results in the formation of characteristic spatial patterns such as a metallic filament percolating through an insulating matrix or an insulating barrier splitting a conducting matrix. When the MIT triggering is driven by electrothermal effects, the temperature of the filament or barrier can be substantially higher than the rest of material. Using x-ray microdiffraction and dark-field x-ray microscopy, we show that electrothermal MIT triggering leads to the development of an inhomogeneous strain profile across the switching device, even when the material does not undergo a 1st order structural phase transition coinciding with the MIT. Diffraction measurements further reveal evidence of lattice distortions and twinning occurring within the MIT switching device, highlighting a qualitative distinction between the electrothermal process and equilibrium thermal lattice expansion in nonlinear electrical systems. Electrically induced strain development, lattice distortions, and twinning could have important contributions in the MIT triggering process and could drive the material into non-equilibrium states, providing an unconventional pathway to explore the phase space of strongly correlated electronic systems.

Published
2023

17. Nature’s contribution to poverty alleviation, human wellbeing and the SDGs

Author

Poudyal, Mahesh, Kraft, Franziska, Wells, Geoff, Das, Anamika, Attiwilli, Suman, Schreckenberg, Kate, Lele, Sharachchandra, Daw, Tim, Torres-Vitolas, Carlos, Setty, Siddappa, Adams, Helen, Ahmad, Sate, Ryan, Casey, Fisher, Janet, Robinson, Brian, Jones, Julia P. G., Homewood, Katherine, Bluwstein, Jevgeniy, Keane, Aidan, Macamo, Celia, and Mugi, Lilian Mwihaki

Published
2024
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18. Caudal regression syndrome with incidental brain tumor in a woman: A case report

Author

Kapil Dawadi, MD, Ongden Yonjen Tamang, MD, Rudra Prasad Upadhyaya, MD, and Binuda Poudyal, MD

Subjects
Caudal regression syndrome, Low lying tethered cord, Brain tumor, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Caudal regression syndrome is a rare inherited neural tube disorder. It may be associated with urological, gastrointestinal, and other spine malformations. It usually presents with variable neurological deficits of varying severity. Maternal diabetes mellitus has been postulated to be a significant risk factor for this syndrome. Most of the cases are diagnosed in antenatal or early childhood with very few cases been reported in adulthood. We have tried to illustrate a rare case of caudal regression syndrome in a 31-year female presenting with low back pain with incidental finding of brain tumor.

Published
2024
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19. Solitary fibrous tumor of the Pelvic cavity: A rare entity with review of literature

Author

Sudeep KC, MD and Himani Poudyal, MBBS

Subjects
Immunohistochemistry, Mesenchymal neoplasm, Solitary fibrous tumor, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Solitary fibrous tumor (SFT) arising from adult mesenchymal stem cells is an uncommon vascular tumor of pelvic cavity. While initially thought to be confined to the pleura, pericardium, or peritoneum, recent studies have revealed that SFTs can develop in different areas of the body. Typically, SFTs grow slowly and may not present noticeable symptoms. In this 2 case study, we describe the clinical situation of a 46-year-old female patient and 68 years old male patient who complained of persistent pelvic pain and urinary symptoms respectively. Imaging tests revealed solitary fibrous tumor in the pelvic cavity which was confirmed on histopathology, an unusual location for this type of tumor. This case reports focusses on importance of early recognition and treatment in dealing with this rare tumor.

Published
2024
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20. High-Resolution Full-field Structural Microscopy of the Voltage Induced Filament Formation in Neuromorphic Devices

Author

Kisiel, Elliot, Salev, Pavel, Poudyal, Ishwor, Baptista, Fellipe, Rodolakis, Fanny, Zhang, Zhan, Shpyrko, Oleg, Schuller, Ivan K., Islam, Zahir, and Frano, Alex

Subjects
Physics - Applied Physics, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Neuromorphic functionalities in memristive devices are commonly associated with the ability to electrically create local conductive pathways by resistive switching. The archetypal correlated material, VO2, has been intensively studied for its complex electronic and structural phase transition as well as its filament formation under applied voltages. Local structural studies of the filament behavior are often limited due to time-consuming rastering which makes impractical many experiments aimed at investigating large spatial areas or temporal dynamics associated with the electrical triggering of the phase transition. Utilizing Dark Field X-ray Microscopy (DFXM), a novel full-field x-ray imaging technique, we study this complex filament formation process in-operando in VO2 devices from a structural perspective. We show that prior to filament formation, there is a significant gain of the metallic rutile phase beneath the metal electrodes that define the device. We observed that the filament formation follows a preferential path determined by the nucleation sites within the device. These nucleation sites are predisposed to the phase transition and can persistently maintain the high-temperature rutile phase even after returning to room temperature, which can enable a novel training/learning mechanism. Filament formation also appears to follow a preferential path determined by a nucleation site within the device which is predisposed to the rutile transition even after returning to room temperature. Finally, we found that small isolated low-temperature phase clusters can be present inside the high-temperature filaments indicating that the filament structure is not uniform. Our results provide a unique perspective on the electrically induced filament formation in metal-insulator transition materials, which further the basic understanding of this resistive switching., Comment: 29 pages, 10 figures; 19 pages main text, 3 figures; 10 pages Supplementary material, 7 figures

Published
2023

21. Resilience assessment and planning in power distribution systems:Past and future considerations

Author

Paul, Shuva, Poudyal, Abodh, Poudel, Shiva, Dubey, Anamika, and Wang, Zhaoyu

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Over the past decade, extreme weather events have significantly increased worldwide, leading to widespread power outages and blackouts. As these threats continue to challenge power distribution systems, the importance of mitigating the impacts of extreme weather events has become paramount. Consequently, resilience has become crucial for designing and operating power distribution systems. This work comprehensively explores the current landscape of resilience evaluation and metrics within the power distribution system domain, reviewing existing methods and identifying key attributes that define effective resilience metrics. The challenges encountered during the formulation, development, and calculation of these metrics are also addressed. Additionally, this review acknowledges the intricate interdependencies between power distribution systems and critical infrastructures, including information and communication technology, transportation, water distribution, and natural gas networks. It is important to understand these interdependencies and their impact on power distribution system resilience. Moreover, this work provides an in-depth analysis of existing research on planning solutions to enhance distribution system resilience and support power distribution system operators and planners in developing effective mitigation strategies. These strategies are crucial for minimizing the adverse impacts of extreme weather events and fostering overall resilience within power distribution systems., Comment: 27 pages, 7 figures, submitted for review to Renewable and Sustainable Energy Reviews

Published
2023

22. Satellite-pose estimation using IMU sensor data and Kalman filter with RF-433 Mhz powered communication and helical antenna design for ground station

Author

Biplov Paneru, Ankit Adhikari, Bishwash Paneru, Krishna Bikram Shah, Sanjog Chhetri Sapkota, Ramhari Poudyal, and Khem Narayan Poudyal

Subjects
Helical antenna, RF433, CubeSat, Bno-055, Kalman filter, Electric apparatus and materials. Electric circuits. Electric networks, TK452-454.4
Abstract

Space research relies heavily on satellites, and technological developments are critical to the success of these missions. In order to estimate satellite pose, a simulation of an IMU sensor using Matplotlib is presented in this study. A roll, pitch, and yaw value analysis is performed on data obtained from the BNO-055 IMU sensor. A prototype ground station's helical antenna is used to investigate these parameters. For effective communication between the satellite body and ground station setup, a low-cost transceiver module RF-433Mhz module is connected to the ground station. IMUsensors are essential for inertial measurements in spacecraft, which support ground station monitoring. This study makes use of a four-turn helical antenna that is built for deployment and designed using the 4nec2 simulation program for RF-based satellite-ground station communication. The antenna's VSWR is 1.432, and its directivity is 18.581. Matplotlib is utilized to model variations in roll, pitch, and yaw values. Roll, pitch, and yaw ranges that are observed are −0.375 to 0.25, −0.375 to 0.5625, and −0.3125 to 0.1875, in that order. These ranges are useful in effectively visualizing the body pose of the CubeSat when connecting via PySerial to a Matplotlib-developed program.

Published
2024
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23. Unveiling the anomaly: Scimitar syndrome in a middle-aged female patient

Author

Kapil Dawadi, MD, Prajwal Dahal, MD, Rudra Prasad Upadhyaya, MD, and Binuda Poudyal, MD

Subjects
Anomalous pulmonary venous return, Lung hypoplasia, Scimitar, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Hypogenetic lung syndrome, commonly known as Scimitar syndrome, is a rare cardiopulmonary anomaly characterized primarily by anomalous pulmonary venous return and lung hypoplasia. While it is most frequently diagnosed in infancy or early childhood, cases in adulthood are exceedingly rare. We present a case of a middle-aged female who was diagnosed with Scimitar syndrome.

Published
2025
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25. Credibility Theory Based on Winsorizing

Author

Zhao, Qian and Poudyal, Chudamani

Subjects
Statistics - Applications, Mathematics - Statistics Theory, Statistics - Computation, Statistics - Methodology
Abstract

The classical B\"{u}hlmann credibility model has been widely applied to premium estimation for group insurance contracts and other insurance types. In this paper, we develop a robust B\"{u}hlmann credibility model using the winsorized version of loss data, also known as the winsorized mean (a robust alternative to the traditional individual mean). This approach assumes that the observed sample data come from a contaminated underlying model with a small percentage of contaminated sample data. This framework provides explicit formulas for the structural parameters in credibility estimation for scale-shape distribution families, location-scale distribution families, and their variants, commonly used in insurance risk modeling. Using the theory of \(L\)-estimators (different from the influence function approach), we derive the asymptotic properties of the proposed method and validate them through a comprehensive simulation study, comparing their performance to credibility based on the trimmed mean. By varying the winsorizing/trimming thresholds in several parametric models, we find that all structural parameters derived from the winsorized approach are less volatile than those from the trimmed approach. Using the winsorized mean as a robust risk measure can reduce the influence of parametric loss assumptions on credibility estimation. Additionally, we discuss non-parametric estimations in credibility. Finally, a numerical illustration from the Wisconsin Local Government Property Insurance Fund indicates that the proposed robust credibility approach mitigates the impact of model mis-specification and captures the risk behavior of loss data from a broader perspective.

Published
2023
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26. Characterizing network circuity among heterogeneous urban amenities

Author

Poudyal, Bibandhan, Ghoshal, Gourab, and Kirkley, Alec

Subjects
Physics - Physics and Society, Computer Science - Social and Information Networks
Abstract

The spatial configuration of urban amenities and the streets connecting them collectively provide the structural backbone of a city, influencing its accessibility, vitality, and ultimately the well-being of its residents. Most accessibility measures focus on the proximity of amenities in space or along transportation networks, resulting in metrics largely determined by urban density alone. These measures are unable to gauge how efficiently street networks can navigate between amenities, since they neglect the circuity component of accessibility. Existing measures also often require ad hoc modeling choices, making them less flexible for different applications and difficult to apply in cross-sectional analyses. Here we develop a simple, principled, and flexible measure to characterize the circuity of accessibility among heterogeneous amenities in a city, which we call the pairwise circuity (PC). The PC quantifies the excess travel distance incurred when using the street network to route between a pair of amenity types, summarizing both spatial and topological correlations among amenities. Measures developed using our framework exhibit significant statistical associations with a variety of urban prosperity and accessibility indicators when compared to an appropriate null model, and we find a clear separation in the PC values of cities according to development level and geographic region.

Published
2023
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27. Low-Volume Electrochemical Sensor Platform for Direct Detection of Paraquat in Drinking Water

Author

Durgasha C. Poudyal, Manish Samson, Vikram Narayanan Dhamu, Sera Mohammed, Claudia N. Tanchez, Advaita Puri, Diya Baby, Sriram Muthukumar, and Shalini Prasad

Subjects
electrochemical sensors, electrochemical impedance spectroscopy (EIS), cyclic voltammetry, label-free detection, paraquat detection, pesticides in water, Industrial electrochemistry, TP250-261
Abstract

Direct testing of pesticide contaminants in drinking water is a challenge. Portable and sensitive sensor platforms are desirable to test water contaminants directly at farm and consumer levels. In this study, we have demonstrated the feasibility of an electrochemical sensor for the direct detection of paraquat (PQ) in drinking water samples. An immunoassay-based sensing platform was fabricated using PQ-specific antibody immobilized on the surface of the electrochemically reduced graphene oxide (rGO) modified screen-printed carbon electrode (rGO-SPCE). Using non-faradaic electrochemical impedance spectroscopy (EIS) as a detection tool, the sensor platform demonstrated a dynamic response for PQ concentration in drinking water ranging from 0.05 ng/mL to 72.9 ng/mL (0.19 to 243.8 nM), with a coefficient of determination (r2) of 0.997 and a limit of detection of 0.05 ng/mL (0.19 nM). Percentage recovery within ±20% error was obtained, and the sensor cross-reactivity test showed a selective response against glyphosate antigen. With the flexibility to use single-frequency EIS and low sample volume, the developed sensor demonstrated testing in water samples directly without any sample pre-processing. This low-volume electroanalytical sensor platforms can be translated into portable testing tools for the detection of various water contaminants.

Published
2024
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28. Unveiling Wildfire Dynamics: A Bayesian County-Specific Analysis in California

Author

Shreejit Poudyal, Alex Lindquist, Nate Smullen, Victoria York, Ali Lotfi, James Greene, and Mohammad Meysami

Subjects
California wildfires, environmental factors, wildfire dynamics, Bayesian methodologies, county-level analysis, Science
Abstract

Recently, the United States has experienced, on average, costs of USD 20 billion due to natural and climate disasters, such as hurricanes and wildfires. In this study, we focus on wildfires, which have occurred more frequently in the past few years. This paper examines how various factors, such as the PM10 levels, elevation, precipitation, SOX, population, and temperature, can influence the intensity of wildfires differently across counties in California. More specifically, we use Bayesian analysis to classify all counties of California into two groups: those with more wildfires and those with fewer wildfires. The Bayesian model incorporates prior knowledge and uncertainty for a more robust understanding of how these environmental factors impact wildfires differently among county groups. The findings show a similar effect of the SOX, population, and temperature, while the PM10, elevation, and precipitation have different implications for wildfires across various groups.

Published
2024
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29. Diagnostic accuracy of smartphone corneal photography for detection of corneal opacities in a resource-limited setting: a community-based study.

Author

Cao, Binh, Giri, Puspa, Byanju, Raghunandan, Pradhan, Sangita, Bhandari, Gopal, Bhandari, Sadhan, Kandel, Ram Prasad, Poudyal, Bimal, Gonzales, John A, Srinivasan, Muthiah, Upadhyay, Madan, Whitcher, John P, O'Brien, Kieran S, Lietman, Thomas M, and Keenan, Jeremy D

Subjects
Biomedical and Clinical Sciences, Health Sciences, Ophthalmology and Optometry, Clinical Research, Eye Disease and Disorders of Vision, Clinical Trials and Supportive Activities, Prevention, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Eye, Corneal opacity, community, diagnostic accuracy, smartphone photography
Abstract

PurposeTo evaluate the diagnostic accuracy of smartphone corneal photography in detecting corneal opacities in a community-based setting.MethodsA case-control, diagnostic accuracy study was nested in a cluster-randomized trial of a corneal ulcer prevention intervention in Nepal. Smartphone corneal photography was performed annually on community members self-reporting a potential risk factor for a corneal infection. Corneal photographs were graded for the presence or absence of an opacity. All cases with an opacity on smartphone photography and an equal number of controls were invited for a comprehensive eye examination with a slit lamp biomicroscope at an eye hospital. A mobile team visited participants unable to come to the hospital, conducting a limited examination with a penlight.ResultsOf 1332 study participants (666 cases and 666 controls), 1097 had a penlight examination (535 cases and 562 controls) and 191 had a slit lamp examination (120 cases and 71 controls). When penlight examination was considered the reference standard, smartphone diagnosis of a corneal opacity had a positive predictive value (PPV) of 47% (95% confidence interval 43-52%) and negative predictive value (NPV) of 95% (93-97%). When slit lamp examination was considered the reference standard, the overall PPV and NPV were 71% (62-78%) and 80% (70-88%), respectively. The NPV was greater for detection of opacities > 1mm, estimated at 95% (90-98%).ConclusionsCorneal photography performed in a resource-limited community-based setting using a smartphone coupled to an external attachment had acceptable diagnostic accuracy for detection of corneal opacities large enough to be clinically meaningful.

Published
2023

30. Enhancing healthcare with AI: Sustainable AI and IoT-Powered ecosystem for patient aid and interpretability analysis using SHAP

Author

Biplov Paneru, Bishwash Paneru, Sanjog Chhetri Sapkota, and Ramhari Poudyal

Subjects
Artificial intelligence, Patient health monitoring, SVM, Internet of things (IoT), Blynk, BPM, Electric apparatus and materials. Electric circuits. Electric networks, TK452-454.4
Abstract

The healthcare industry has blossomed into one of the most pivotal and technologically advanced sectors in the past decade. Individuals grapple with the peril of untimely demise from diverse ailments as patients suffer from delayed treatment. The paramount objective is to forge a dependable patient care system utilizing the Internet of Things (IoT), enabling physicians to monitor patients' well-being within medical facilities or even the confines of their homes. The system aids in tracking the patient's SpO2 level, body temperature, pulse rate (beats per minute), room temperature, and humidity, then trains the data with machine learning algorithms for the patient and finally monitors it through the Blynk IoT system. The cloud-stored data can be harnessed to ascertain and supervise one's health and predict forthcoming perils. This study unveils an efficacious decision-making model custom-tailored for Internet of Things (IoT) ventures, and the proposed trained algorithm satiates these requirements, offering efficiency and precision, rendering it appropriate for numerous IoT applications. Finally, the Shapley Additive Explanations (SHAP) is used here for finding out the most influential parameters, and Explainable AI (XAI) is utilized with the help of SHAP values for enhanced information on affecting parameters. The SVC model's hyperparameter is properly adjusted, yielding a testing accuracy of 98.83 % and a training accuracy of 98.71 %. On cross-validation, the lightweight Sklearn model achieved a mean accuracy of almost 99 %. And with a SHAP weightage magnitude of 1.38, 0.91, and 0.44 for Class ‘Good’, Class ‘Poor’, and Class ‘Bad’, respectively, patients SpO2 level is the most significant feature.

Published
2024
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31. Full-Field Nanoscale X-ray Diffraction-Contrast Imaging using Direct Detection

Author

Kisiel, Elliot, Poudyal, Ishwor, Kenesei, Peter, Engbretson, Mark, Last, Arndt, Basak, Rourav, Zaluzhnyy, Ivan, Goteti, Uday, Dynes, Robert, Miceli, Antonino, Frano, Alex, and Islam, Zahir

Subjects
Physics - Instrumentation and Detectors, Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Optics
Abstract

Recent developments in x-ray science provide methods to probe deeply embedded mesoscale grain structures and spatially resolve them using dark field x-ray microscopy (DFXM). Extending this technique to investigate weak diffraction signals such as magnetic systems, quantum materials and thin films proves challenging due to available detection methods and incident x-ray flux at the sample. We present a direct detection method focusing on DFXM studies in the hard x-ray range of 10s of keV and above capable of approaching nanoscale resolution. Additionally, we compare this direct detection scheme with routinely used scintillator based optical detection and achieve an order of magnitude improvement in exposure times allowing for imaging of weakly diffracting ordered systems., Comment: 8 pages, 6 figures

Published
2022

32. Spatiotemporal Impact Analysis of Hurricanes and Storm Surges on Power Systems

Author

Poudyal, Abodh, Wertz, Charlotte, Nguyen, Amy Mi, Mahmud, Sajjad Uddin, Gunturi, Vibha, and Dubey, Anamika

Subjects
Physics - Physics and Society, Electrical Engineering and Systems Science - Systems and Control
Abstract

This paper develops a spatiotemporal probabilistic impact assessment framework to analyze and quantify the compounding effect of hurricanes and storm surges on the bulk power grid. The probabilistic synthetic hurricane tracks are generated using historical hurricane data, and storm surge scenarios are generated based on observed hurricane parameters. The system losses are modeled using a loss metric that quantifies the total load loss. The overall simulation is performed on the synthetic Texas 2000-bus system mapped on the geographical footprint of Texas. The results show that power substation inundation due to storm surge creates additional load losses as the hurricane traverses inland., Comment: 5 pages, 9 figures, submitted to 2023 IEEE Power and Energy Society General Meeting for review

Published
2022

33. Sensitivity Analyses of Resilience-oriented Risk-averse Active Distribution Systems Planning

Author

Poudyal, Abodh and Dubey, Anamika

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

This paper presents sensitivity analyses of resilience-based active distribution system planning solutions with respect to different parameters. The distribution system planning problem is formulated as a two-stage risk-averse stochastic optimization model with conditional value-at-risk (CVaR) as the risk measure. The probabilistic scenarios are obtained using regional wind profiles, and Monte Carlo simulations are conducted to obtain failure scenarios based on component fragility models. The planning measure includes advanced distribution grid operations with intentional islanding measures. The three main parameters used in this work for sensitivity analysis are the number of scenarios, risk preference, and planning budget allocation. Such analysis can provide additional information to system operators on dispatching the planning budget and available resources properly to enhance the grid's resilience., Comment: 5 pages, 12 figures, submitted to 2023 IEEE Power and Energy Society General Meeting for review

Published
2022

34. Dark Field X-ray Microscopy Below Liquid-Helium Temperature: The Case of NaMnO2

Author

Plumb, Jayden, Poudyal, Ishwor, Dally, Rebecca L., Daly, Samantha, Wilson, Stephen D., and Islam, Zahir

Subjects
Condensed Matter - Materials Science
Abstract

Dark field X-ray microscopy (DFXM) is an experimental technique employed to investigate material properties by probing their 'mesoscale,' or microscale structures, in a bulk-sensitive manner using hard X-rays at synchrotron radiation sources. However, challenges remain when it comes to applications of this technique to examine low-temperature phenomena in quantum materials, which exhibit complex phase transitions at cryogenic temperatures. One such material is NaMnO2, which hosts an antiferromagnetic transition at 45 K that is suspected to coincide with local structural transitions from its majority monoclinic phase to nanoscale triclinic domains. Direct observation of local heterogeneities and this effect at low temperatures in NaMnO2 is an important step in understanding this material, and serves as an ideal candidate study for expanding the DFXM experimental design space. This paper details a foundational high-resolution DFXM study, down to liquid-helium temperature and below, conducted to explore phase transitions in NaMnO2. The outlined experiment ushers in the evaluation of other functional materials at low temperatures using this technique., Comment: 9 pages, 7 figures

Published
2022
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35. A general method for multiresolutional analysis of mesoscale features in dark-field x-ray microscopy images

Author

Abulshohoud, Omar, Poudyal, Ishwor, McChesney, Jessica, Zhang, Zhan, Qiao, Zhi, Welp, Ulrich, and Islam, Zahir

Subjects
Condensed Matter - Materials Science
Abstract

Dark-field x-ray microscopy utilizes Bragg diffraction to collect full-field x-ray images of "mesoscale" structure of ordered materials. Information regarding the structural heterogeneities and their physical implications is gleaned through the quantitative analyses of these images. Namely, one must be able to extract diffraction features that arise from lattice modulations or inhomogeneities, quantify said features, and identify and track patterns in the relevant quantitative properties in subsequent images. Due to the necessity to track features with a wide array of shapes and length scales while maintaining spatial resolution, wavelet transforms were chosen as a potent signal analysis tool. In addition to addressing multiple length scales, this method can be used in conjunction with other signal processing methods such as image binarization for increased functionality. In this article, we demonstrate three effective use of wavelet analyses pertaining to DFXM. We show how to extract and track smooth linear features-which are diffraction manifestations of twin boundaries-as the sample orientation changes as it is rotated about momentum transfer. Secondly, we show that even the simplest wavelet transform, the Haar transform, can be used to capture the primary features in DFXM images, over a range of length scales in different regions of interest within a single image enabling localized reconstruction. As a final application, we extend these techniques to determine when a DFXM image is in focus.

Published
2022

36. Pump-probe Dark-field X-ray Microscopy

Author

Poudyal, Ishwor, Qiao, Zhi, Last, Arndt, Armstrong, Michael R., and Islam, Zahir

Subjects
Condensed Matter - Materials Science, Physics - Optics
Abstract

A pump-probe dark-field X-ray microscopy (DFXM) experiment was carried out at the Advanced Photon Source (APS) with nanosecond drive laser pulses and hybrid mode X-ray probe pulses. We observe a thermal decay due to laser-induced heat diffusion in a Germanium single crystal which matches the theoretical prediction. The single pulse DFXM imaging in combination with the laser-pump X-ray probe method could reveal thermal strain formation and propagation of the acoustic wave "on-the-fly" generated by a laser-induced lattice deformation. This will open a new avenue of materials research on laser-induced dynamic phenomena in solids at sub-nanosecond time scales., Comment: Updated Author list on the page consistent with the pdf

Published
2022

38. Inclusion of Students with Developmental Disabilities in Japan: Barriers and Promising Practices in Primary and Secondary Education

Author

Ito, Hiro, Chang-Leung, Cherice, and Poudyal, Hemant

Abstract

Despite Japan's recent efforts toward inclusive education and increased support for students with disabilities, evidence indicates that many students with developmental disabilities do not receive adequate support in the general classroom. Through a review of the literature, we identified four main potential barriers to successful inclusive education in Japan: (a) policy limitations, (b) limited specialization of school psychology, (c) teacher capacity, and (d) stigmatization. We also proposed Multi-Tier Systems of Support, Universal Design for Learning, and hiring Education Assistants as promising strategies to address the needs of a subset of underserved students in the general classroom. These strategies can promote a more equitable distribution of resources and support systems across the entire education system.

Published
2023
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39. COVID-Pandemic in Nepal: An Opportunity to Institutionalise Local Governance in School Education

Author

Adhikari, Devendra, Sharma Poudyal, Chandra, and Binayek Pasa, Rajan

Abstract

The 2015 constitution of Nepal declared Nepal to be a Federal, Democratic, and Republic nation. The constitution has provided local governments the right to manage school education, and the 2017 Local Government Operation Act of Nepal has outlined the roles and responsibilities of local governments in taking guardianship of school education. Since 2017, Nepal has been in the process of institutionalising decentralised governance practices, but this is proceeding at a slow pace. Unprecedently, from early 2020, the COVID-pandemic hit hard the lives of Nepali people, and Nepali education suffered greatly. The pandemic has brought several opportunities for the government to devolve the management system of school education to local levels. This article is based upon the analysis of the six newly introduced plans, regulations, and guidelines in Nepali education, that aim to continue school education amid the COVID-pandemic. These newly introduced polices have significantly acknowledged and mobilised the local strengths in educational management. This research supports a new academic discussion on governance ideas of the Nepalese education system, induced by the COVID-19 pandemic.

Published
2023
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40. Beneficial Plant–Microbe Interactions and Stress Tolerance in Maize

Author

Saroj Burlakoti, Ananta R. Devkota, Shital Poudyal, and Amita Kaundal

Subjects
abiotic and biotic stress, beneficial microbes, stress tolerance, maize, plant growth-promoting rhizobacteria (PGPR), AMF, Microbiology, QR1-502
Abstract

Beneficial microbes are crucial for improving crop adaptation and growth under various stresses. They enhance nutrient uptake, improve plant immune responses, and help plants tolerate stresses like drought, salinity, and heat. The yield potential of any crop is significantly influenced by its associated microbiomes and their potential to improve growth under different stressful environments. Therefore, it is crucial and exciting to understand the mechanisms of plant–microbe interactions. Maize (Zea mays L.) is one of the primary staple foods worldwide, in addition to wheat and rice. Maize is also an industrial crop globally, contributing 83% of its production for use in feed, starch, and biofuel industries. Maize requires significant nitrogen fertilization to achieve optimal growth and yield. Maize plants are highly susceptible to heat, salinity, and drought stresses and require innovative methods to mitigate the harmful effects of environmental stresses and reduce the use of chemical fertilizers. This review summarizes our current understanding of the beneficial interactions between maize plants and specific microbes. These beneficial microbes improve plant resilience to stress and increase productivity. For example, they regulate electron transport, downregulate catalase, and upregulate antioxidants. We also review the roles of plant growth-promoting rhizobacteria (PGPR) in enhancing stress tolerance in maize. Additionally, we explore the application of these microbes in maize production and identify major knowledge gaps that need to be addressed to utilize the potential of beneficial microbes fully.

Published
2024
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41. Exploring the Nexus of User Interface (UI) and User Experience (UX) in the Context of Emerging Trends and Customer Experience, Human Computer Interaction, Applications of Artificial Intelligence

Author

Biplov Paneru, Bishwash Paneru, Ramhari Poudyal, and Krishna Bikram Shah

Subjects
human computer interaction, ui, ux, artificial intelligence, Information technology, T58.5-58.64, Computer engineering. Computer hardware, TK7885-7895
Abstract

The complexities of User Interface (UI) and User Experience (UX) design are explored in this research paper, along with their respective functions, areas of overlap, and the changing field of customer experience. In the digital age, where technology is developing at a rapid pace, designing innovative and user-focused digital products requires an understanding of the dynamic interplay between UI and UX. This research also examines how emerging trends in the UI/UX field will affect overall customer satisfaction. Additionally, this paper delves into applications of artificial intelligence (AI) in the domains of human-computer interaction (HCI), user experience (UX), and emerging trends in these fields

Published
2024
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42. Search for central exclusive production of top quark pairs in proton-proton collisions at s $$ \sqrt{s} $$ = 13 TeV with tagged protons

Author

The CMS collaboration, A. Tumasyan, W. Adam, J. W. Andrejkovic, T. Bergauer, S. Chatterjee, K. Damanakis, M. Dragicevic, A. Escalante Del Valle, P. S. Hussain, M. Jeitler, N. Krammer, L. Lechner, D. Liko, I. Mikulec, P. Paulitsch, F. M. Pitters, J. Schieck, R. Schöfbeck, D. Schwarz, S. Templ, W. Waltenberger, C.-E. Wulz, M. R. Darwish, T. Janssen, T. Kello, H. Rejeb Sfar, P. Van Mechelen, E. S. Bols, J. D’Hondt, A. De Moor, M. Delcourt, H. El Faham, S. Lowette, S. Moortgat, A. Morton, D. Müller, A. R. Sahasransu, S. Tavernier, W. Van Doninck, D. Vannerom, B. Clerbaux, G. De Lentdecker, L. Favart, D. Hohov, J. Jaramillo, K. Lee, M. Mahdavikhorrami, I. Makarenko, A. Malara, S. Paredes, L. Pétré, N. Postiau, E. Starling, L. Thomas, M. Vanden Bemden, C. Vander Velde, P. Vanlaer, D. Dobur, J. Knolle, L. Lambrecht, G. Mestdach, M. Niedziela, C. Rendón, C. Roskas, A. Samalan, K. Skovpen, M. Tytgat, N. Van Den Bossche, B. Vermassen, L. Wezenbeek, A. Benecke, G. Bruno, F. Bury, C. Caputo, P. David, C. Delaere, I. S. Donertas, A. Giammanco, K. Jaffel, Sa. Jain, V. Lemaitre, K. Mondal, J. Prisciandaro, A. Taliercio, T. T. Tran, P. Vischia, S. Wertz, G. A. Alves, E. Coelho, C. Hensel, A. Moraes, P. Rebello Teles, W. L. Aldá Júnior, M. Alves Gallo Pereira, M. Barroso Ferreira Filho, H. Brandao Malbouisson, W. Carvalho, J. Chinellato, E. M. Da Costa, G. G. Da Silveira, D. De Jesus Damiao, V. Dos Santos Sousa, S. Fonseca De Souza, J. Martins, C. Mora Herrera, K. Mota Amarilo, L. Mundim, H. Nogima, A. Santoro, S. M. Silva Do Amaral, A. Sznajder, M. Thiel, F. Torres Da Silva De Araujo, A. Vilela Pereira, C. A. Bernardes, L. Calligaris, T. R. Fernandez Perez Tomei, E. M. Gregores, P. G. Mercadante, S. F. Novaes, Sandra S. Padula, A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova, G. Sultanov, A. Dimitrov, T. Ivanov, L. Litov, B. Pavlov, P. Petkov, A. Petrov, E. Shumka, T. Cheng, T. Javaid, M. Mittal, L. Yuan, M. Ahmad, G. Bauer, Z. Hu, S. Lezki, K. Yi, G. M. Chen, H. S. Chen, M. Chen, F. Iemmi, C. H. Jiang, A. Kapoor, H. Liao, Z.-A. Liu, V. Milosevic, F. Monti, R. Sharma, J. Tao, J. Thomas-Wilsker, J. Wang, H. Zhang, J. Zhao, A. Agapitos, Y. An, Y. Ban, C. Chen, A. Levin, C. Li, Q. Li, X. Lyu, Y. Mao, S. J. Qian, X. Sun, D. Wang, J. Xiao, H. Yang, J. Li, M. Lu, Z. You, X. Gao, D. Leggat, H. Okawa, Y. Zhang, Z. Lin, C. Lu, M. Xiao, C. Avila, D. A. Barbosa Trujillo, A. Cabrera, C. Florez, J. Fraga, J. Mejia Guisao, F. Ramirez, M. Rodriguez, J. D. Ruiz Alvarez, D. Giljanovic, N. Godinovic, D. Lelas, I. Puljak, Z. Antunovic, M. Kovac, T. Sculac, V. Brigljevic, B. K. Chitroda, D. Ferencek, D. Majumder, M. Roguljic, A. Starodumov, T. Susa, A. Attikis, K. Christoforou, G. Kole, M. Kolosova, S. Konstantinou, J. Mousa, C. Nicolaou, F. Ptochos, P. A. Razis, H. Rykaczewski, H. Saka, M. Finger, A. Kveton, E. Ayala, E. Carrera Jarrin, S. Elgammal, A. Ellithi Kamel, M. A. Mahmoud, Y. Mohammed, S. Bhowmik, R. K. Dewanjee, K. Ehataht, M. Kadastik, T. Lange, S. Nandan, C. Nielsen, J. Pata, M. Raidal, L. Tani, C. Veelken, P. Eerola, H. Kirschenmann, M. Voutilainen, S. Bharthuar, E. Brücken, J. Havukainen, M. S. Kim, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Lehti, T. Lindén, M. Lotti, L. Martikainen, M. Myllymäki, J. Ott, M. m. Rantanen, H. Siikonen, E. Tuominen, J. Tuominiemi, P. Luukka, H. Petrow, T. Tuuva, C. Amendola, M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J. L. Faure, F. Ferri, S. Ganjour, P. Gras, G. Hamel de Monchenault, P. Jarry, V. Lohezic, J. Malcles, J. Rander, A. Rosowsky, M. Ö. Sahin, A. Savoy-Navarro, P. Simkina, M. Titov, F. Beaudette, A. Buchot Perraguin, P. Busson, A. Cappati, C. Charlot, F. Damas, O. Davignon, B. Diab, G. Falmagne, B. A. Fontana Santos Alves, S. Ghosh, R. Granier de Cassagnac, A. Hakimi, B. Harikrishnan, G. Liu, J. Motta, M. Nguyen, C. Ochando, L. Portales, J. Rembser, R. Salerno, U. Sarkar, J. B. Sauvan, Y. Sirois, A. Tarabini, E. Vernazza, A. Zabi, A. Zghiche, J.-L. Agram, J. Andrea, D. Apparu, D. Bloch, G. Bourgatte, J.-M. Brom, E. C. Chabert, C. Collard, D. Darej, U. Goerlach, C. Grimault, A.-C. Le Bihan, P. Van Hove, S. Beauceron, C. Bernet, B. Blancon, G. Boudoul, A. Carle, N. Chanon, J. Choi, D. Contardo, P. Depasse, C. Dozen, H. El Mamouni, J. Fay, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, I. B. Laktineh, M. Lethuillier, L. Mirabito, S. Perries, V. Sordini, L. Torterotot, M. Vander Donckt, P. Verdier, S. Viret, G. Adamov, I. Lomidze, Z. Tsamalaidze, V. Botta, L. Feld, K. Klein, M. Lipinski, D. Meuser, A. Pauls, N. Röwert, M. Teroerde, S. Diekmann, A. Dodonova, N. Eich, D. Eliseev, M. Erdmann, P. Fackeldey, D. Fasanella, B. Fischer, T. Hebbeker, K. Hoepfner, F. Ivone, M. y. Lee, L. Mastrolorenzo, M. Merschmeyer, A. Meyer, S. Mondal, S. Mukherjee, D. Noll, A. Novak, F. Nowotny, A. Pozdnyakov, Y. Rath, W. Redjeb, H. Reithler, A. Schmidt, S. C. Schuler, A. Sharma, L. Vigilante, S. Wiedenbeck, S. Zaleski, C. Dziwok, G. Flügge, W. Haj Ahmad, O. Hlushchenko, T. Kress, A. Nowack, O. Pooth, A. Stahl, T. Ziemons, A. Zotz, H. Aarup Petersen, M. Aldaya Martin, P. Asmuss, S. Baxter, M. Bayatmakou, O. Behnke, A. Bermúdez Martínez, S. Bhattacharya, A. A. Bin Anuar, F. Blekman, K. Borras, D. Brunner, A. Campbell, A. Cardini, C. Cheng, F. Colombina, S. Consuegra Rodríguez, G. Correia Silva, M. De Silva, L. Didukh, G. Eckerlin, D. Eckstein, L. I. Estevez Banos, O. Filatov, E. Gallo, A. Geiser, A. Giraldi, G. Greau, A. Grohsjean, V. Guglielmi, M. Guthoff, A. Jafari, N. Z. Jomhari, B. Kaech, A. Kasem, M. Kasemann, H. Kaveh, C. Kleinwort, R. Kogler, M. Komm, D. Krücker, W. Lange, D. Leyva Pernia, K. Lipka, W. Lohmann, R. Mankel, I.-A. Melzer-Pellmann, M. Mendizabal Morentin, J. Metwally, A. B. Meyer, G. Milella, M. Mormile, A. Mussgiller, A. Nürnberg, Y. Otarid, D. Pérez Adán, A. Raspereza, B. Ribeiro Lopes, J. Rübenach, A. Saggio, A. Saibel, M. Savitskyi, M. Scham, V. Scheurer, S. Schnake, P. Schütze, C. Schwanenberger, M. Shchedrolosiev, R. E. Sosa Ricardo, D. Stafford, N. Tonon, M. Van De Klundert, F. Vazzoler, A. Ventura Barroso, R. Walsh, D. Walter, Q. Wang, Y. Wen, K. Wichmann, L. Wiens, C. Wissing, S. Wuchterl, Y. Yang, A. Zimermmane Castro Santos, R. Aggleton, A. Albrecht, S. Albrecht, M. Antonello, S. Bein, L. Benato, M. Bonanomi, P. Connor, K. De Leo, M. Eich, K. El Morabit, F. Feindt, A. Fröhlich, C. Garbers, E. Garutti, M. Hajheidari, J. Haller, A. Hinzmann, H. R. Jabusch, G. Kasieczka, R. Klanner, W. Korcari, T. Kramer, V. Kutzner, J. Lange, A. Lobanov, C. Matthies, A. Mehta, L. Moureaux, M. Mrowietz, A. Nigamova, Y. Nissan, A. Paasch, K. J. Pena Rodriguez, M. Rieger, O. Rieger, P. Schleper, M. Schröder, J. Schwandt, H. Stadie, G. Steinbrück, A. Tews, M. Wolf, J. Bechtel, S. Brommer, M. Burkart, E. Butz, R. Caspart, T. Chwalek, A. Dierlamm, A. Droll, N. Faltermann, M. Giffels, J. O. Gosewisch, A. Gottmann, F. Hartmann, M. Horzela, U. Husemann, P. Keicher, M. Klute, R. Koppenhöfer, S. Maier, S. Mitra, Th. Müller, M. Neukum, G. Quast, K. Rabbertz, J. Rauser, D. Savoiu, M. Schnepf, D. Seith, I. Shvetsov, H. J. Simonis, N. Trevisani, R. Ulrich, J. van der Linden, R. F. Von Cube, M. Wassmer, M. Weber, S. Wieland, R. Wolf, S. Wozniewski, S. Wunsch, G. Anagnostou, P. Assiouras, G. Daskalakis, A. Kyriakis, A. Stakia, M. Diamantopoulou, D. Karasavvas, P. Kontaxakis, A. Manousakis-Katsikakis, A. Panagiotou, I. Papavergou, N. Saoulidou, K. Theofilatos, E. Tziaferi, K. Vellidis, E. Vourliotis, I. Zisopoulos, G. Bakas, T. Chatzistavrou, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis, A. Zacharopoulou, K. Adamidis, I. Bestintzanos, I. Evangelou, C. Foudas, P. Gianneios, C. Kamtsikis, P. Katsoulis, P. Kokkas, P. G. Kosmoglou Kioseoglou, N. Manthos, I. Papadopoulos, J. Strologas, M. Csanád, K. Farkas, M. M. A. Gadallah, S. Lökös, P. Major, K. Mandal, G. Pásztor, A. J. Rádl, O. Surányi, G. I. Veres, M. Bartók, G. Bencze, C. Hajdu, D. Horvath, F. Sikler, V. Veszpremi, N. Beni, S. 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Sexton-Kennedy, N. Smith, A. Soha, L. Spiegel, J. Strait, L. Taylor, S. Tkaczyk, N. V. Tran, L. Uplegger, E. W. Vaandering, H. A. Weber, I. Zoi, P. Avery, D. Bourilkov, L. Cadamuro, V. Cherepanov, R. D. Field, D. Guerrero, M. Kim, E. Koenig, J. Konigsberg, A. Korytov, K. H. Lo, K. Matchev, N. Menendez, G. Mitselmakher, A. Muthirakalayil Madhu, N. Rawal, D. Rosenzweig, S. Rosenzweig, K. Shi, Z. Wu, T. Adams, A. Askew, R. Habibullah, V. Hagopian, R. Khurana, T. Kolberg, G. Martinez, H. Prosper, C. Schiber, O. Viazlo, R. Yohay, J. Zhang, M. M. Baarmand, S. Butalla, T. Elkafrawy, M. Hohlmann, R. Kumar Verma, M. Rahmani, F. Yumiceva, M. R. Adams, H. Becerril Gonzalez, R. Cavanaugh, S. Dittmer, O. Evdokimov, C. E. Gerber, D. J. Hofman, D. S. Lemos, A. H. Merrit, C. Mills, G. Oh, T. Roy, S. Rudrabhatla, M. B. Tonjes, N. Varelas, X. Wang, Z. Ye, M. Alhusseini, K. Dilsiz, L. Emediato, R. P. Gandrajula, G. Karaman, O. K. Köseyan, J.-P. Merlo, A. Mestvirishvili, J. Nachtman, O. Neogi, H. Ogul, Y. Onel, A. Penzo, C. Snyder, E. Tiras, O. Amram, B. Blumenfeld, L. Corcodilos, J. Davis, A. V. Gritsan, L. Kang, S. Kyriacou, P. Maksimovic, J. Roskes, S. Sekhar, M. Swartz, T. Á. Vámi, A. Abreu, L. F. Alcerro Alcerro, J. Anguiano, P. Baringer, A. Bean, Z. Flowers, S. Khalil, J. King, G. Krintiras, M. Lazarovits, C. Le Mahieu, J. Marquez, M. Murray, M. Nickel, C. Rogan, R. Salvatico, S. Sanders, E. Schmitz, C. Smith, G. Wilson, B. Allmond, S. Duric, R. Gujju Gurunadha, A. Ivanov, K. Kaadze, Y. Maravin, T. Mitchell, A. Modak, K. Nam, J. Natoli, D. Roy, F. Rebassoo, D. Wright, E. Adams, A. Baden, O. Baron, A. Belloni, A. Bethani, S. C. Eno, N. J. Hadley, S. Jabeen, R. G. Kellogg, T. Koeth, Y. Lai, S. Lascio, A. C. Mignerey, S. Nabili, C. Palmer, C. Papageorgakis, M. Seidel, L. Wang, K. Wong, D. Abercrombie, R. Bi, W. Busza, I. A. Cali, M. D’Alfonso, J. Eysermans, C. Freer, G. Gomez-Ceballos, M. Goncharov, P. Harris, M. Hu, D. Kovalskyi, J. Krupa, Y.-J. Lee, K. Long, C. Mironov, C. Paus, D. Rankin, C. Roland, G. Roland, Z. Shi, G. S. F. Stephans, Z. Wang, B. Wyslouch, R. M. Chatterjee, B. Crossman, A. Evans, J. Hiltbrand, Sh. Jain, B. M. Joshi, C. Kapsiak, M. Krohn, Y. Kubota, J. Mans, M. Revering, R. Rusack, R. Saradhy, N. Schroeder, N. Strobbe, M. A. Wadud, L. M. Cremaldi, K. Bloom, M. Bryson, D. R. Claes, C. Fangmeier, L. Finco, F. Golf, C. Joo, I. Kravchenko, I. Reed, J. E. Siado, G. R. Snow, W. Tabb, A. Wightman, F. Yan, A. G. Zecchinelli, G. Agarwal, H. Bandyopadhyay, L. Hay, I. Iashvili, A. Kharchilava, C. McLean, M. Morris, D. Nguyen, J. Pekkanen, S. Rappoccio, A. Williams, G. Alverson, E. Barberis, Y. Haddad, Y. Han, A. Krishna, J. Lidrych, G. Madigan, B. Marzocchi, D. M. Morse, V. Nguyen, T. Orimoto, A. Parker, L. Skinnari, A. Tishelman-Charny, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood, J. Bueghly, Z. Chen, A. Gilbert, T. Gunter, K. A. Hahn, Y. Liu, N. Odell, M. H. Schmitt, M. Velasco, R. Band, R. Bucci, S. Castells, M. Cremonesi, A. Das, R. Goldouzian, M. Hildreth, K. Hurtado Anampa, C. Jessop, K. Lannon, J. Lawrence, N. Loukas, L. Lutton, J. Mariano, N. Marinelli, I. Mcalister, T. McCauley, C. Mcgrady, K. Mohrman, C. Moore, Y. Musienko, H. Nelson, R. Ruchti, A. Townsend, M. Wayne, H. Yockey, M. Zarucki, L. Zygala, B. Bylsma, M. Carrigan, L. S. Durkin, B. Francis, C. Hill, A. Lesauvage, M. Nunez Ornelas, K. Wei, B. L. Winer, B. R. Yates, F. M. Addesa, B. Bonham, P. Das, G. Dezoort, P. Elmer, A. Frankenthal, B. Greenberg, N. Haubrich, S. Higginbotham, A. Kalogeropoulos, G. Kopp, S. Kwan, D. Lange, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, D. Stickland, C. Tully, S. Norberg, A. S. Bakshi, V. E. Barnes, R. Chawla, S. Das, L. Gutay, M. Jones, A. W. Jung, D. Kondratyev, A. M. Koshy, M. Liu, G. Negro, N. Neumeister, G. Paspalaki, S. Piperov, A. Purohit, J. F. Schulte, M. Stojanovic, J. Thieman, F. Wang, R. Xiao, W. Xie, J. Dolen, N. Parashar, D. Acosta, A. Baty, T. Carnahan, M. Decaro, S. Dildick, K. M. Ecklund, P. J. Fernández Manteca, S. Freed, P. Gardner, F. J. M. Geurts, W. Li, B. P. Padley, R. Redjimi, J. Rotter, W. Shi, E. Yigitbasi, L. Zhang, X. Zuo, A. Bodek, P. de Barbaro, R. Demina, J. L. Dulemba, C. Fallon, T. Ferbel, M. Galanti, A. Garcia-Bellido, O. Hindrichs, A. Khukhunaishvili, E. Ranken, R. Taus, G. P. Van Onsem, K. Goulianos, B. Chiarito, J. P. Chou, Y. Gershtein, E. Halkiadakis, A. Hart, M. Heindl, D. Jaroslawski, O. Karacheban, I. Laflotte, A. Lath, R. Montalvo, K. Nash, M. Osherson, S. Salur, S. Schnetzer, S. Somalwar, R. Stone, S. A. Thayil, S. Thomas, H. Wang, H. Acharya, A. G. Delannoy, S. Fiorendi, T. Holmes, E. Nibigira, S. Spanier, O. Bouhali, M. Dalchenko, A. Delgado, R. Eusebi, J. Gilmore, T. Huang, T. Kamon, S. Luo, S. Malhotra, R. Mueller, D. Overton, D. Rathjens, A. Safonov, N. Akchurin, J. Damgov, V. Hegde, K. Lamichhane, T. Mengke, S. Muthumuni, T. Peltola, I. Volobouev, A. Whitbeck, E. Appelt, S. Greene, A. Gurrola, W. Johns, A. Melo, F. Romeo, P. Sheldon, S. Tuo, J. Velkovska, J. Viinikainen, B. Cardwell, B. Cox, G. Cummings, J. Hakala, R. Hirosky, M. Joyce, A. Ledovskoy, A. Li, C. Neu, C. E. Perez Lara, B. Tannenwald, P. E. Karchin, N. Poudyal, K. Black, T. Bose, S. Dasu, I. De Bruyn, P. Everaerts, C. Galloni, H. He, M. Herndon, A. Herve, C. K. Koraka, A. Lanaro, A. Loeliger, R. Loveless, J. Madhusudanan Sreekala, A. Mallampalli, A. Mohammadi, G. Parida, D. Pinna, A. Savin, V. Shang, W. H. Smith, D. Teague, H. F. Tsoi, W. Vetens, S. Afanasiev, V. Andreev, Yu. Andreev, T. Aushev, M. Azarkin, A. Babaev, V. Blinov, E. Boos, D. Budkouski, V. Bunichev, O. Bychkova, M. Chadeeva, V. Chekhovsky, A. Dermenev, T. Dimova, I. Dremin, M. Dubinin, L. Dudko, V. Epshteyn, G. Gavrilov, V. Gavrilov, S. Gninenko, V. Golovtcov, N. Golubev, I. Golutvin, I. Gorbunov, A. Gribushin, Y. Ivanov, V. Kachanov, L. Kardapoltsev, V. Karjavine, A. Karneyeu, V. Kim, M. Kirakosyan, D. Kirpichnikov, M. Kirsanov, V. Klyukhin, D. Konstantinov, V. Korenkov, A. Kozyrev, N. Krasnikov, E. Kuznetsova, A. Lanev, P. Levchenko, A. Litomin, O. Lukina, N. Lychkovskaya, V. Makarenko, A. Malakhov, V. Matveev, V. Murzin, A. Nikitenko, S. Obraztsov, V. Okhotnikov, I. Ovtin, V. Palichik, P. Parygin, V. Perelygin, M. Perfilov, G. Pivovarov, V. Popov, E. Popova, O. Radchenko, V. Rusinov, M. Savina, V. Savrin, D. Selivanova, V. Shalaev, S. Shmatov, S. Shulha, Y. Skovpen, S. Slabospitskii, V. Smirnov, D. Sosnov, A. Stepennov, V. Sulimov, A. Terkulov, O. Teryaev, I. Tlisova, M. Toms, A. Toropin, L. Uvarov, A. Uzunian, E. Vlasov, P. Volkov, A. Vorobyev, N. Voytishin, B. S. Yuldashev, A. Zarubin, I. Zhizhin, A. Zhokin, The TOTEM collaboration, G. Antchev, P. Aspell, I. Atanassov, V. Avati, J. Baechler, C. Baldenegro Barrera, V. Berardi, M. Berretti, V. Borshch, E. Bossini, U. Bottigli, M. Bozzo, H. Burkhardt, F. S. Cafagna, M. G. Catanesi, M. Deile, F. De Leonardis, M. Doubek, D. Druzhkin, K. Eggert, V. Eremin, A. Fiergolski, F. Garcia, V. Georgiev, S. Giani, L. Grzanka, J. Hammerbauer, T. Isidori, V. Ivanchenko, M. Janda, A. Karev, J. Kašpar, B. Kaynak, J. Kopal, V. Kundrát, S. Lami, R. Linhart, C. Lindsey, M. V. Lokajíček, L. Losurdo, F. Lucas Rodríguez, M. Macrí, M. Malawski, N. Minafra, S. Minutoli, K. Misan, T. Naaranoja, F. Nemes, H. Niewiadomski, E. Oliveri, F. Oljemark, M. Oriunno, K. Österberg, S. Ozkorucuklu, P. Palazzi, V. Passaro, Z. Peroutka, O. Potok, J. Procházka, M. Quinto, E. Radermacher, E. Radicioni, F. Ravotti, C. Royon, G. Ruggiero, H. Saarikko, V. D. Samoylenko, A. Scribano, J. Široký, J. Smajek, W. Snoeys, R. Stefanovitch, C. Taylor, E. Tcherniaev, N. Turini, O. Urban, V. Vacek, O. Vavroch, J. Welti, J. Williams, and J. Zich

Subjects
Hadron-Hadron Scattering, Top Physics, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract A search for the central exclusive production of top quark-antiquark pairs ( t t ¯ $$ \textrm{t}\overline{\textrm{t}} $$ ) is performed for the first time using proton-tagged events in proton-proton collisions at the LHC at a centre-of-mass energy of 13 TeV. The data correspond to an integrated luminosity of 29.4 fb −1. The t t ¯ $$ \textrm{t}\overline{\textrm{t}} $$ decay products are reconstructed using the central CMS detector, while forward protons are measured in the CMS-TOTEM precision proton spectrometer. An observed (expected) upper bound on the production cross section of 0.59 (1.14) pb is set at 95% confidence level, for collisions of protons with fractional momentum losses between 2 and 20%.

Published
2024
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43. Integration of passive sensing technology to enhance delivery of psychological interventions for mothers with depression: the StandStrong study

Author

Alastair van Heerden, Anubhuti Poudyal, Ashley Hagaman, Sujen Man Maharjan, Prabin Byanjankar, Dörte Bemme, Ada Thapa, and Brandon A. Kohrt

Subjects
Medicine, Science
Abstract

Abstract Psychological interventions delivered by non-specialist providers have shown mixed results for treating maternal depression. mHealth solutions hold the possibility for unobtrusive behavioural data collection to identify challenges and reinforce change in psychological interventions. We conducted a proof-of-concept study using passive sensing integrated into a depression intervention delivered by non-specialists to twenty-four adolescents and young mothers (30% 15–17 years old; 70% 18–25 years old) with infants (

Published
2024
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44. Enhancement of Biogas (Methane) Production from Cow Dung Using a Microbial Electrochemical Cell and Molecular Characterization of Isolated Methanogenic Bacteria

Author

Puja Bhatt, Pranita Poudyal, Pradip Dhungana, Bikram Prajapati, Suman Bajracharya, Amar Prasad Yadav, Tribikram Bhattarai, Lakshmaiah Sreerama, and Jarina Joshi

Subjects
biogas, methanogens, microbial electrochemical cell (MEC), electromethanogenesis, anaerobic digestion, Biotechnology, TP248.13-248.65
Abstract

Biogas has long been used as a household cooking fuel in many tropical counties, and it has the potential to be a significant energy source beyond household cooking fuel. In this study, we describe the use of low electrical energy input in an anaerobic digestion process using a microbial electrochemical cell (MEC) to promote methane content in biogas at 18, 28, and 37 °C. Although the maximum amount of biogas production was at 37 °C (25 cm3), biogas could be effectively produced at lower temperatures, i.e., 18 (13 cm3) and 28 °C (19 cm3), with an external 2 V power input. The biogas production of 13 cm3 obtained at 18 °C was ~65-fold higher than the biogas produced without an external power supply (0.2 cm3). This was further enhanced by 23% using carbon-nanotubes-treated (CNT) graphite electrodes. This suggests that the MEC can be operated at as low as 18 °C and still produce significant amounts of biogas. The share of CH4 in biogas produced in the controls was 30%, whereas the biogas produced in an MEC had 80% CH4. The MEC effectively reduced COD to 42%, whereas it consumed 98% of reducing sugars. Accordingly, it is a suitable method for waste/manure treatment. Molecular characterization using 16s rRNA sequencing confirmed the presence of methanogenic bacteria, viz., Serratia liquefaciens and Zoballella taiwanensis, in the inoculum used for the fermentation. Consistent with recent studies, we believe that electromethanogenesis will play a significant role in the production of value-added products and improve the management of waste by converting it to energy.

Published
2024
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45. Evaluating Preparedness and Overcoming Challenges in Electricity Trading: An In-Depth Analysis Using the Analytic Hierarchy Process and a Case Study Exploration

Author

Suraj Regmi, Abhinav Rayamajhi, Ramhari Poudyal, and Sanjeev Adhikari

Subjects
Analytic Hierarchy Process (AHP), cross-border energy trade, hydropower, Multi-Criteria Decision Making, Electricity, QC501-721
Abstract

The economy of South Asia is experiencing growth, yet it faces constraints due to heavy reliance on fossil fuels and frequent power outages. Access to diverse energy sources, particularly electricity, is crucial for sustaining this growth. One feasible solution involves neighbouring countries engaging in the trade of renewable electrical energy. Hydropower stands as one of the many energy sources available in South Asia. However, sectorial constraints pose significant challenges to energy trade initiatives. This study utilises the Analytic Hierarchy Process (AHP) to evaluate Nepal’s readiness and identify obstacles to its cross-border energy trade with India and Bangladesh. A comprehensive analysis of these obstacles is imperative for formulating effective strategies and policies. Additionally, this study offers recommendations for enhancing preparedness and resolving issues related to energy trading, which may apply to similar cross-border situations. This study ranks energy trading obstacles with neighbouring nations using the AHP, offering key insights for stakeholders and policymakers. Using a non-probabilistic purposeful sampling technique, 25 expert respondents from the energy sector and prominent academicians were selected as part of the data collection procedure. At every level of the interview process, their perspectives were invaluable in guaranteeing a thorough and rigorous investigation.

Published
2024
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46. Search for a new resonance decaying into two spin-0 bosons in a final state with two photons and two bottom quarks in proton-proton collisions at s $$ \sqrt{s} $$ = 13 TeV

Author

The CMS collaboration, A. Tumasyan, W. Adam, J. W. Andrejkovic, T. Bergauer, S. Chatterjee, K. Damanakis, M. Dragicevic, A. Escalante Del Valle, P. S. Hussain, M. Jeitler, N. Krammer, L. Lechner, D. Liko, I. Mikulec, P. Paulitsch, F. M. Pitters, J. Schieck, R. Schöfbeck, D. Schwarz, M. Sonawane, S. Templ, W. Waltenberger, C.-E. Wulz, M. R. Darwish, T. Janssen, T. Kello, H. Rejeb Sfar, P. Van Mechelen, E. S. Bols, J. D’Hondt, A. De Moor, M. Delcourt, H. El Faham, S. Lowette, S. Moortgat, A. Morton, D. Müller, A. R. Sahasransu, S. Tavernier, W. Van Doninck, S. Van Putte, D. Vannerom, B. Clerbaux, G. De Lentdecker, L. Favart, D. Hohov, J. Jaramillo, K. Lee, M. Mahdavikhorrami, I. Makarenko, A. Malara, S. Paredes, L. Pétré, N. Postiau, L. Thomas, M. Vanden Bemden, C. Vander Velde, P. Vanlaer, D. Dobur, J. Knolle, L. Lambrecht, G. Mestdach, C. Rendón, A. Samalan, K. Skovpen, M. Tytgat, N. Van Den Bossche, B. Vermassen, L. Wezenbeek, A. Benecke, G. Bruno, F. Bury, C. Caputo, P. David, C. Delaere, I. S. Donertas, A. Giammanco, K. Jaffel, Sa. Jain, V. Lemaitre, K. Mondal, A. Taliercio, T. T. Tran, P. Vischia, S. Wertz, G. A. Alves, E. Coelho, C. Hensel, A. Moraes, P. Rebello Teles, W. L. Aldá Júnior, M. Alves Gallo Pereira, M. Barroso Ferreira Filho, H. Brandao Malbouisson, W. Carvalho, J. Chinellato, E. M. Da Costa, G. G. Da Silveira, D. De Jesus Damiao, V. Dos Santos Sousa, S. Fonseca De Souza, J. Martins, C. Mora Herrera, K. Mota Amarilo, L. Mundim, H. Nogima, A. Santoro, S. M. Silva Do Amaral, A. Sznajder, M. Thiel, A. Vilela Pereira, C. A. Bernardes, L. Calligaris, T. R. Fernandez Perez Tomei, E. M. Gregores, P. G. Mercadante, S. F. Novaes, Sandra S. Padula, A. Aleksandrov, G. Antchev, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova, G. Sultanov, A. Dimitrov, T. Ivanov, L. Litov, B. Pavlov, P. Petkov, A. Petrov, E. Shumka, S. Thakur, T. Cheng, T. Javaid, M. Mittal, L. Yuan, M. Ahmad, G. Bauer, Z. Hu, S. Lezki, K. Yi, G. M. Chen, H. S. Chen, M. Chen, F. Iemmi, C. H. Jiang, A. Kapoor, H. Liao, Z.-A. Liu, V. Milosevic, F. Monti, R. Sharma, J. Tao, J. Thomas-Wilsker, J. Wang, H. Zhang, J. Zhao, A. Agapitos, Y. An, Y. Ban, A. Levin, C. Li, Q. Li, X. Lyu, Y. Mao, S. J. Qian, X. Sun, D. Wang, J. Xiao, H. Yang, M. Lu, Z. You, N. Lu, X. Gao, D. Leggat, H. Okawa, Y. Zhang, Z. Lin, C. Lu, M. Xiao, C. Avila, D. A. Barbosa Trujillo, A. Cabrera, C. Florez, J. Fraga, J. Mejia Guisao, F. Ramirez, M. Rodriguez, J. D. Ruiz Alvarez, D. Giljanovic, N. Godinovic, D. Lelas, I. Puljak, Z. Antunovic, M. Kovac, T. Sculac, V. Brigljevic, B. K. Chitroda, D. Ferencek, D. Majumder, S. Mishra, M. Roguljic, A. Starodumov, T. Susa, A. Attikis, K. Christoforou, M. Kolosova, S. Konstantinou, J. Mousa, C. Nicolaou, F. Ptochos, P. A. Razis, H. Rykaczewski, H. Saka, A. Stepennov, M. Finger, A. Kveton, E. Ayala, E. Carrera Jarrin, S. Elgammal, A. Ellithi Kamel, A. Lotfy, M. A. Mahmoud, S. Bhowmik, R. K. Dewanjee, K. Ehataht, M. Kadastik, T. Lange, S. Nandan, C. Nielsen, J. Pata, M. Raidal, L. Tani, C. Veelken, P. Eerola, H. Kirschenmann, K. Osterberg, M. Voutilainen, S. Bharthuar, E. Brücken, F. Garcia, J. Havukainen, M. S. Kim, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Lehti, T. Lindén, M. Lotti, L. Martikainen, M. Myllymäki, J. Ott, M. m. Rantanen, H. Siikonen, E. Tuominen, J. Tuominiemi, P. Luukka, H. Petrow, T. Tuuva, C. Amendola, M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J. L. Faure, F. Ferri, S. Ganjour, P. Gras, G. Hamel de Monchenault, V. Lohezic, J. Malcles, J. Rander, A. Rosowsky, M. Ö. Sahin, A. Savoy-Navarro, P. Simkina, M. Titov, C. Baldenegro Barrera, F. Beaudette, A. Buchot Perraguin, P. Busson, A. Cappati, C. Charlot, F. Damas, O. Davignon, B. Diab, G. Falmagne, B. A. Fontana Santos Alves, S. Ghosh, R. Granier de Cassagnac, A. Hakimi, B. Harikrishnan, G. Liu, J. Motta, M. Nguyen, C. Ochando, L. Portales, R. Salerno, U. Sarkar, J. B. Sauvan, Y. Sirois, A. Tarabini, E. Vernazza, A. Zabi, A. Zghiche, J.-L. Agram, J. 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Schuh, C. H. Shepherd-Themistocleous, I. R. Tomalin, T. Williams, R. Bainbridge, P. Bloch, S. Bonomally, J. Borg, C. E. Brown, O. Buchmuller, V. Cacchio, C. A. Carrillo Montoya, V. Cepaitis, G. S. Chahal, D. Colling, J. S. Dancu, P. Dauncey, G. Davies, J. Davies, M. Della Negra, S. Fayer, G. Fedi, G. Hall, M. H. Hassanshahi, A. Howard, G. Iles, J. Langford, L. Lyons, A.-M. Magnan, S. Malik, A. Martelli, M. Mieskolainen, D. G. Monk, J. Nash, M. Pesaresi, B. C. Radburn-Smith, D. M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, R. Shukla, A. Tapper, K. Uchida, G. P. Uttley, L. H. Vage, T. Virdee, M. Vojinovic, N. Wardle, S. N. Webb, D. Winterbottom, K. Coldham, J. E. Cole, A. Khan, P. Kyberd, I. D. Reid, S. Abdullin, A. Brinkerhoff, B. Caraway, J. Dittmann, K. Hatakeyama, A. R. Kanuganti, B. McMaster, M. Saunders, S. Sawant, C. Sutantawibul, M. Toms, J. Wilson, R. Bartek, A. Dominguez, R. Uniyal, A. M. Vargas Hernandez, R. Chudasama, S. I. Cooper, D. Di Croce, S. V. Gleyzer, C. Henderson, C. U. Perez, P. Rumerio, C. West, A. Akpinar, A. Albert, D. Arcaro, C. Cosby, Z. Demiragli, C. Erice, E. Fontanesi, D. Gastler, S. May, J. Rohlf, K. Salyer, D. Sperka, D. Spitzbart, I. Suarez, A. Tsatsos, S. Yuan, G. Benelli, B. Burkle, X. Coubez, D. Cutts, M. Hadley, U. Heintz, J. M. Hogan, T. Kwon, G. Landsberg, K. T. Lau, D. Li, J. Luo, M. Narain, N. Pervan, S. Sagir, F. Simpson, E. Usai, W. Y. Wong, X. Yan, D. Yu, W. Zhang, S. Abbott, J. Bonilla, C. Brainerd, R. Breedon, M. Calderon De La Barca Sanchez, M. Chertok, J. Conway, P. T. Cox, R. Erbacher, G. Haza, F. Jensen, O. Kukral, G. Mocellin, M. Mulhearn, D. Pellett, B. Regnery, Y. Yao, F. Zhang, M. Bachtis, R. Cousins, A. Datta, D. Hamilton, J. Hauser, M. Ignatenko, M. A. Iqbal, T. Lam, E. Manca, W. A. Nash, D. Saltzberg, B. Stone, V. Valuev, R. Clare, J. W. Gary, M. Gordon, G. Hanson, G. Karapostoli, O. R. Long, N. Manganelli, W. Si, S. Wimpenny, J. G. Branson, S. Cittolin, S. Cooperstein, D. Diaz, J. Duarte, R. Gerosa, L. Giannini, J. Guiang, R. Kansal, V. Krutelyov, R. Lee, J. Letts, M. Masciovecchio, F. Mokhtar, M. Pieri, B. V. Sathia Narayanan, V. Sharma, M. Tadel, E. Vourliotis, F. Würthwein, Y. Xiang, A. Yagil, N. Amin, C. Campagnari, M. Citron, G. Collura, A. Dorsett, V. Dutta, J. Incandela, M. Kilpatrick, A. J. Li, P. Masterson, H. Mei, M. Oshiro, M. Quinnan, J. Richman, U. Sarica, R. Schmitz, F. Setti, J. Sheplock, P. Siddireddy, D. Stuart, S. Wang, A. Bornheim, O. Cerri, I. Dutta, A. Latorre, J. M. Lawhorn, J. Mao, H. B. Newman, T. Q. Nguyen, M. Spiropulu, J. R. Vlimant, C. Wang, S. Xie, R. Y. Zhu, J. Alison, S. An, M. B. Andrews, P. Bryant, T. Ferguson, A. Harilal, C. Liu, T. Mudholkar, S. Murthy, M. Paulini, A. Roberts, A. Sanchez, W. Terrill, J. P. Cumalat, W. T. Ford, A. Hassani, G. Karathanasis, E. MacDonald, F. Marini, A. Perloff, C. Savard, N. Schonbeck, K. Stenson, K. A. Ulmer, S. R. Wagner, N. Zipper, J. Alexander, S. Bright-Thonney, X. Chen, D. J. Cranshaw, J. Fan, X. Fan, D. Gadkari, S. Hogan, J. Monroy, J. R. Patterson, D. Quach, J. Reichert, M. Reid, A. Ryd, J. Thom, P. Wittich, R. Zou, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, L. A. T. Bauerdick, D. Berry, J. Berryhill, P. C. Bhat, K. Burkett, J. N. Butler, A. Canepa, G. B. Cerati, H. W. K. Cheung, F. Chlebana, K. F. Di Petrillo, J. Dickinson, V. D. Elvira, Y. Feng, J. Freeman, A. Gandrakota, Z. Gecse, L. Gray, D. Green, S. Grünendahl, D. Guerrero, O. Gutsche, R. M. Harris, R. Heller, T. C. Herwig, J. Hirschauer, L. Horyn, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, T. Klijnsma, B. Klima, K. H. M. Kwok, S. Lammel, D. Lincoln, R. Lipton, T. Liu, C. Madrid, K. Maeshima, C. Mantilla, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, J. Ngadiuba, D. Noonan, V. Papadimitriou, N. Pastika, K. Pedro, C. Pena, F. Ravera, A. Reinsvold Hall, L. Ristori, E. Sexton-Kennedy, N. Smith, A. Soha, L. Spiegel, J. Strait, L. Taylor, S. Tkaczyk, N. V. Tran, L. Uplegger, E. W. Vaandering, I. Zoi, P. Avery, D. Bourilkov, L. Cadamuro, P. Chang, V. Cherepanov, R. D. Field, E. Koenig, J. Konigsberg, A. Korytov, E. Kuznetsova, K. H. Lo, K. Matchev, N. Menendez, G. Mitselmakher, A. Muthirakalayil Madhu, N. Rawal, D. Rosenzweig, S. Rosenzweig, K. Shi, Z. Wu, T. Adams, A. Askew, N. Bower, R. Habibullah, V. Hagopian, T. Kolberg, G. Martinez, H. Prosper, O. Viazlo, M. Wulansatiti, R. Yohay, J. Zhang, M. M. Baarmand, S. Butalla, T. Elkafrawy, M. Hohlmann, R. Kumar Verma, M. Rahmani, F. Yumiceva, M. R. Adams, R. Cavanaugh, S. Dittmer, O. Evdokimov, C. E. Gerber, D. J. Hofman, D. S. Lemos, A. H. Merrit, C. Mills, G. Oh, T. Roy, S. Rudrabhatla, M. B. Tonjes, N. Varelas, X. Wang, Z. Ye, M. Alhusseini, K. Dilsiz, L. Emediato, G. Karaman, O. K. Köseyan, J.-P. Merlo, A. Mestvirishvili, J. Nachtman, O. Neogi, H. Ogul, Y. Onel, A. Penzo, C. Snyder, E. Tiras, O. Amram, B. Blumenfeld, L. Corcodilos, J. Davis, A. V. Gritsan, S. Kyriacou, P. Maksimovic, J. Roskes, S. Sekhar, M. Swartz, T. Á. Vámi, A. Abreu, L. F. Alcerro Alcerro, J. Anguiano, P. Baringer, A. Bean, Z. Flowers, T. Isidori, J. King, G. Krintiras, M. Lazarovits, C. Le Mahieu, C. Lindsey, J. Marquez, N. Minafra, M. Murray, M. Nickel, C. Rogan, C. Royon, R. Salvatico, S. Sanders, C. Smith, G. Wilson, B. Allmond, S. Duric, A. Ivanov, K. Kaadze, A. Kalogeropoulos, Y. Maravin, T. Mitchell, A. Modak, K. Nam, D. Roy, F. Rebassoo, D. Wright, A. Baden, O. Baron, A. Belloni, A. Bethani, S. C. Eno, N. J. Hadley, S. Jabeen, R. G. Kellogg, T. Koeth, Y. Lai, S. Lascio, A. C. Mignerey, S. Nabili, C. Palmer, C. Papageorgakis, L. Wang, K. Wong, D. Abercrombie, W. Busza, I. A. Cali, Y. Chen, M. D’Alfonso, J. Eysermans, C. Freer, G. Gomez-Ceballos, M. Goncharov, P. Harris, M. Hu, D. Kovalskyi, J. Krupa, Y.-J. Lee, K. Long, C. Mironov, C. Paus, D. Rankin, C. Roland, G. Roland, Z. Shi, G. S. F. Stephans, Z. Wang, B. Wyslouch, T. J. Yang, R. M. Chatterjee, B. Crossman, J. Hiltbrand, B. M. Joshi, C. Kapsiak, M. Krohn, Y. Kubota, J. Mans, M. Revering, R. Rusack, R. Saradhy, N. Schroeder, N. Strobbe, M. A. Wadud, L. M. Cremaldi, K. Bloom, M. Bryson, D. R. Claes, C. Fangmeier, L. Finco, F. Golf, C. Joo, R. Kamalieddin, I. Kravchenko, I. Reed, J. E. Siado, G. R. Snow, W. Tabb, A. Wightman, F. Yan, A. G. Zecchinelli, G. Agarwal, H. Bandyopadhyay, L. Hay, I. Iashvili, A. Kharchilava, C. McLean, M. Morris, D. Nguyen, J. Pekkanen, S. Rappoccio, A. Williams, G. Alverson, E. Barberis, Y. Haddad, Y. Han, A. Krishna, J. Li, J. Lidrych, G. Madigan, B. Marzocchi, D. M. Morse, V. Nguyen, T. Orimoto, A. Parker, L. Skinnari, A. Tishelman-Charny, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood, J. Bueghly, Z. Chen, A. Gilbert, K. A. Hahn, Y. Liu, N. Odell, M. H. Schmitt, M. Velasco, R. Band, R. Bucci, M. Cremonesi, A. Das, R. Goldouzian, M. Hildreth, K. Hurtado Anampa, C. Jessop, K. Lannon, J. Lawrence, N. Loukas, L. Lutton, J. Mariano, N. Marinelli, I. Mcalister, T. McCauley, C. Mcgrady, K. Mohrman, C. Moore, Y. Musienko, R. Ruchti, A. Townsend, M. Wayne, H. Yockey, M. Zarucki, L. Zygala, B. Bylsma, M. Carrigan, L. S. Durkin, C. Hill, M. Joyce, A. Lesauvage, M. Nunez Ornelas, K. Wei, B. L. Winer, B. R. Yates, F. M. Addesa, P. Das, G. Dezoort, P. Elmer, A. Frankenthal, B. Greenberg, N. Haubrich, S. Higginbotham, G. Kopp, S. Kwan, D. Lange, A. Loeliger, D. Marlow, I. Ojalvo, J. Olsen, D. Stickland, C. Tully, S. Norberg, A. S. Bakshi, V. E. Barnes, R. Chawla, S. Das, L. Gutay, M. Jones, A. W. Jung, D. Kondratyev, A. M. Koshy, M. Liu, G. Negro, N. Neumeister, G. Paspalaki, S. Piperov, A. Purohit, J. F. Schulte, M. Stojanovic, J. Thieman, F. Wang, R. Xiao, W. Xie, J. Dolen, N. Parashar, D. Acosta, A. Baty, T. Carnahan, S. Dildick, K. M. Ecklund, P. J. Fernández Manteca, S. Freed, P. Gardner, F. J. M. Geurts, W. Li, B. P. Padley, R. Redjimi, J. Rotter, E. Yigitbasi, A. Bodek, P. de Barbaro, R. Demina, J. L. Dulemba, C. Fallon, M. Galanti, A. Garcia-Bellido, O. Hindrichs, A. Khukhunaishvili, P. Parygin, E. Popova, R. Taus, G. P. Van Onsem, K. Goulianos, B. Chiarito, J. P. Chou, Y. Gershtein, E. Halkiadakis, A. Hart, M. Heindl, D. Jaroslawski, O. Karacheban, I. Laflotte, A. Lath, R. Montalvo, K. Nash, M. Osherson, H. Routray, S. Salur, S. Schnetzer, S. Somalwar, R. Stone, S. A. Thayil, S. Thomas, H. Wang, H. Acharya, A. G. Delannoy, S. Fiorendi, T. Holmes, E. Nibigira, S. Spanier, O. Bouhali, M. Dalchenko, A. Delgado, R. Eusebi, J. Gilmore, T. Huang, T. Kamon, S. Luo, S. Malhotra, R. Mueller, D. Overton, D. Rathjens, A. Safonov, N. Akchurin, J. Damgov, V. Hegde, K. Lamichhane, T. Mengke, S. Muthumuni, T. Peltola, I. Volobouev, A. Whitbeck, E. Appelt, S. Greene, A. Gurrola, W. Johns, A. Melo, F. Romeo, P. Sheldon, S. Tuo, J. Velkovska, J. Viinikainen, B. Cardwell, B. Cox, G. Cummings, J. Hakala, R. Hirosky, A. Ledovskoy, A. Li, C. Neu, C. E. Perez Lara, B. Tannenwald, P. E. Karchin, N. Poudyal, A. Aravind, K. Black, T. Bose, S. Dasu, I. De Bruyn, P. Everaerts, C. Galloni, H. He, M. Herndon, A. Herve, C. K. Koraka, A. Lanaro, R. Loveless, J. Madhusudanan Sreekala, A. Mallampalli, A. Mohammadi, G. Parida, D. Pinna, A. Savin, V. Shang, W. H. Smith, D. Teague, H. F. Tsoi, W. Vetens, A. Warden, S. Afanasiev, V. Andreev, Yu. Andreev, T. Aushev, M. Azarkin, A. Babaev, V. Blinov, E. Boos, V. Borshch, D. Budkouski, V. Bunichev, M. Chadeeva, V. Chekhovsky, R. Chistov, A. Dermenev, T. Dimova, I. Dremin, M. Dubinin, L. Dudko, V. Epshteyn, G. Gavrilov, V. Gavrilov, S. Gninenko, V. Golovtcov, N. Golubev, I. Golutvin, I. Gorbunov, A. Gribushin, Y. Ivanov, V. Kachanov, L. Kardapoltsev, V. Karjavine, A. Karneyeu, V. Kim, M. Kirakosyan, D. Kirpichnikov, M. Kirsanov, V. Klyukhin, O. Kodolova, D. Konstantinov, V. Korenkov, A. Kozyrev, N. Krasnikov, A. Lanev, P. Levchenko, A. Litomin, N. Lychkovskaya, V. Makarenko, A. Malakhov, V. Matveev, V. Murzin, A. Nikitenko, S. Obraztsov, A. Oskin, I. Ovtin, V. Palichik, V. Perelygin, M. Perfilov, S. Petrushanko, S. Polikarpov, V. Popov, O. Radchenko, M. Savina, V. Savrin, V. Shalaev, S. Shmatov, S. Shulha, Y. Skovpen, S. Slabospitskii, V. Smirnov, D. Sosnov, V. Sulimov, E. Tcherniaev, A. Terkulov, O. Teryaev, I. Tlisova, A. Toropin, L. Uvarov, A. Uzunian, A. Vorobyev, N. Voytishin, B. S. Yuldashev, A. Zarubin, I. Zhizhin, and A. Zhokin

Subjects
B Physics, Hadron-Hadron Scattering, Higgs Physics, Photon Production, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract A search for a new boson X is presented using CERN LHC proton-proton collision data collected by the CMS experiment at s $$ \sqrt{s} $$ = 13 TeV in 2016–2018, and corresponding to an integrated luminosity of 138 fb −1. The resonance X decays into either a pair of Higgs bosons HH of mass 125 GeV or an H and a new spin-0 boson Y. One H subsequently decays to a pair of photons, and the second H or Y, to a pair of bottom quarks. The explored mass ranges of X are 260–1000 GeV and 300–1000 GeV, for decays to HH and to HY, respectively, with the Y mass range being 90–800 GeV. For a spin-0 X hypothesis, the 95% confidence level upper limit on the product of its production cross section and decay branching fraction is observed to be within 0.90–0.04 fb, depending on the masses of X and Y. The largest deviation from the background-only hypothesis with a local (global) significance of 3.8 (below 2.8) standard deviations is observed for X and Y masses of 650 and 90 GeV, respectively. The limits are interpreted using several models of new physics.

Published
2024
Full Text
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47. Breaking barriers: supporting hematopoietic stem cell transplant program through collaborative radiation therapy service from a physically distant center

Author

Subhas Pandit, Simit Sapkota, Abish Adhikari, Prakriti Karki, Roshani Shrestha, Deepak Suman Jha, Rajan Prajapati, Kanchan Sarga Nyaichyai, Bishesh Sharma Poudyal, Bishal Poudel, and Anjani Kumar Jha

Subjects
Low-dose total body irradiation, Hematopoietic stem cell transplant, Graft-versus-host disease, Conditioning regimen, Low- and middle-income country, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Total body irradiation (TBI) for hematopoietic stem cell transplant (HSCT) has certain distinct advantages, such as uniform dose distribution and lack of drug resistance, but it is not widely available in resource-constrained settings. To overcome the limitations of in-house radiotherapy services in hematology centers, we evaluated the feasibility of conducting HSCT programs in coordination with two physically distant centers using a reduced-intensity TBI protocol. Methods Thirty-two patients with a median age of 20.5 years were included in the study. Fifteen patients were diagnosed with aplastic anemia, 10 patients with acute myeloid leukemia (AML), 3 patients with acute lymphocytic leukemia (ALL), and 4 patients with other hematological conditions. Conditioning regimens used were fludarabine plus cyclophosphamide in 29 cases, fludarabine-cytarabine ATG in 2 cases, and busulfan plus fludarabine in 1 case. The TBI dose was 3 Gy in 28 cases and 2 Gy in 4 cases. Patients were followed monthly after TBI, and the major toxicities were recorded. Results The median follow-up was 22 months. The most common acute complication was acute graft-versus-host disease (GVHD), which occurred in 15.6% of patients. The major late complications were chronic GVHD (9.3%), Cytomegalovirus (CMV) infection (34.3%), and CMV-induced secondary graft failure (6.2%). Seventy-five percent of patients were alive, 21.9% were dead, and 1 patient was lost to follow-up. Conclusions HSCT based on TBI is feasible even if the center lacks a radiotherapy facility by coordinating with a remote radiotherapy facility. without compromising the patient's outcome.

Published
2024
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48. Digital Learning Initiatives, Challenges and Achievement in Higher Education in Nepal amidst COVID-19

Author

Acharya, Ashis, Subedi, Srijana, Gyawali, Narayan, Poudyal, Nabaraj, Lamichhane, Ganesh, Bastola, Govinda, Aryal, Babita, Bhattarai, Bibek Raj, Adhikari, Bikash, Marahatha, Rishab, Bhatta, Madhabi, Paudel, Mohan, and Parajuli, Niranjan

Abstract

The COVID-19 pandemic has affected higher education institutions (HEIs) worldwide and reshaped the existing educational system. Due to travel constraints and physical separation, there has been a global shift toward distance learning, and Nepal is no exception. This research intends to assess the practicality of online education by evaluating learners' experiences amidst COVID-19. A cross-sectional study was directed among HEIs students in Nepal using self-structured questionnaires. Our study revealed that 64.6% of the respondents were unsatisfied with online classes. More than half of the respondents (53.4%) use cell phones for online studies. Online education was reported to be unappealing to 28.8% of respondents. Variables such as age group (p = 0.05), enjoying class (p < 0.001), hours spent for an online class in a day (p = 0.05), and period for educational work using an electronic device (p = 0.1) were found significant with satisfaction level using both bivariate test and inferential test of univariate binary logistics regression. The challenges and opportunities encountered among students and faculties are highlighted along with the recommendations for fortifying communication in online-based teaching/learning.

Published
2021

49. A differentiable forward model for the concurrent, multi-peak Bragg coherent x-ray diffraction imaging problem

Author

Maddali, S., Frazer, T. D., Delegan, N., Harmon, K. J., Sullivan, S. E., Allain, M., Cha, W., Dibos, A., Poudyal, I., Kandel, S., Nashed, Y. S. G., Heremans, F. J., You, H., Cao, Y., and Hruszkewycz, S. O.

Subjects
Condensed Matter - Materials Science, Electrical Engineering and Systems Science - Signal Processing, Physics - Computational Physics
Abstract

We present a general analytic approach to spatially resolve the nano-scale lattice distortion field of strained and defected compact crystals with Bragg coherent x-ray diffraction imaging (BCDI). Our approach relies on fitting a differentiable forward model simultaneously to multiple BCDI datasets corresponding to independent Bragg reflections from the same single crystal. It is designed to be faithful to heterogeneities that potentially manifest as phase discontinuities in the coherently diffracted wave, such as lattice dislocations in an imperfect crystal. We retain fidelity to such small features in the reconstruction process through a Fourier transform -based resampling algorithm designed to largely avoid the point spread tendencies of commonly employed interpolation methods. The reconstruction model defined in this manner brings BCDI reconstruction into the scope of explicit optimization driven by automatic differentiation. With results from simulations and experimental diffraction data, we demonstrate significant improvement in the final image quality compared to conventional phase retrieval, enabled by explicitly coupling multiple BCDI datasets into the reconstruction loss function., Comment: 30 pages, 23 figures

Published
2022

50. Search for central exclusive production of top quark pairs in proton-proton collisions at s = 13 TeV with tagged protons

Author

Tumasyan, A., Adam, W., Andrejkovic, J. W., Bergauer, T., Chatterjee, S., Damanakis, K., Dragicevic, M., Escalante Del Valle, A., Hussain, P. S., Jeitler, M., Krammer, N., Lechner, L., Liko, D., Mikulec, I., Paulitsch, P., Pitters, F. M., Schieck, J., Schöfbeck, R., Schwarz, D., Templ, S., Waltenberger, W., Wulz, C.-E., Darwish, M. R., Janssen, T., Kello, T., Rejeb Sfar, H., Van Mechelen, P., Bols, E. S., D’Hondt, J., De Moor, A., Delcourt, M., El Faham, H., Lowette, S., Moortgat, S., Morton, A., Müller, D., Sahasransu, A. R., Tavernier, S., Van Doninck, W., Vannerom, D., Clerbaux, B., De Lentdecker, G., Favart, L., Hohov, D., Jaramillo, J., Lee, K., Mahdavikhorrami, M., Makarenko, I., Malara, A., Paredes, S., Pétré, L., Postiau, N., Starling, E., Thomas, L., Vanden Bemden, M., Vander Velde, C., Vanlaer, P., Dobur, D., Knolle, J., Lambrecht, L., Mestdach, G., Niedziela, M., Rendón, C., Roskas, C., Samalan, A., Skovpen, K., Tytgat, M., Van Den Bossche, N., Vermassen, B., Wezenbeek, L., Benecke, A., Bruno, G., Bury, F., Caputo, C., David, P., Delaere, C., Donertas, I. S., Giammanco, A., Jaffel, K., Jain, Sa., Lemaitre, V., Mondal, K., Prisciandaro, J., Taliercio, A., Tran, T. T., Vischia, P., Wertz, S., Alves, G. A., Coelho, E., Hensel, C., Moraes, A., Rebello Teles, P., Aldá Júnior, W. L., Alves Gallo Pereira, M., Barroso Ferreira Filho, M., Brandao Malbouisson, H., Carvalho, W., Chinellato, J., Da Costa, E. M., Da Silveira, G. 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