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Fast Radio Bursts (FRBs) are enigmatic, millisecond-duration extragalactic transients discovered only in the late 2000s. Though the exact nature of their origin is unknown, their extremely short-duration emission endows several unique qualities that make them uniquely useful as probes of foreground matter. Chief among such properties is their dispersion. As FRB light propagates through plasma, their radio frequencies are dispersed, resulting in higher frequencies arriving before lower frequencies at Earth. The dispersion is directly proportional to the line-of-sight integral of the electron density weighted by the cosmological scale factor, i.e., the Dispersion Measure (DM). The DM of each FRB can be measured extremely precisely (~1%) by radio telescopes during detection. Thus, FRB DMs precisely probe foreground ionized matter, especially the warm, hot intergalactic medium (WHIM), a previously difficult-to-detect phase of matter. In this manuscript, I first describe the detection of the so-called "missing" baryons, a long-standing cosmological conundrum with FRBs. Then, I present work I have led that establishes the technique of foreground mapping, i.e., leveraging optical observations of foreground galaxies to constrain DM contributions from intervening foreground structures such as halos and cosmic-web filaments. Finally, I present the results of the FLIMFLAM survey, a statistical treatment of the foreground observation of several FRB sightlines to produce novel constraints on gas fractions within halos and filaments. I conclude with prospects for a FLIMFLAM-like analysis with a significantly larger sample of FRB sightlines expected to be detected within the next three years.

BackgroundBipolar disorder (BD) conveys the highest risk of suicide of all mental disorders. We sought to externally validate a risk calculator (RC) of suicide attempts developed in youth with BD from the Course and Outcome of Bipolar Youth (COBY) study in an adult sample.MethodsA prospective cohort of adults with BD from the National Institute of Mental Health Collaborative Depression Study (CDS; N = 427; mean (+/- SD) age at intake (36 +/- 13 years)) was secondarily analyzed to validate the COBY RC for one-year risk of suicide attempts/deaths. Nine of the ten predictor variables from the COBY RC were available in the CDS and used: age, age of mood disorder onset, first and second (partial) degree family history of suicide, history of psychotic symptoms, substance use disorder, prior suicide attempt, socioeconomic status, and non-suicidal self-injury (prospectively, incompletely at baseline).ResultsOver a mean (SD) follow-up of 19 (10) years, 29 % of the CDS sample attempted suicide. The RC predicted suicide attempts/deaths over one-year follow-up with an area under the receiver operating characteristic curve (AUC) of 0.78 (95 % CI 0.75-0.80). The RC performed slightly better in those with a younger age of mood disorder onset.LimitationsClinical samples may limit generalizability; the RC does not assess more acute suicide risk.ConclusionsOne-year risk of suicide attempts/deaths can be predicted with acceptable accuracy in youth and adults with BD, comparable to commonly used RCs to predict cardiovascular risk. This RC may help identify higher-risk individuals with BD for personalized treatment and research. https://cobysuicideattemptsrc.shinyapps.io/Shiny.

An accurate assessment of nitrate leaching is important for efficient fertiliser utilisation and groundwater pollution reduction. However, past studies could not efficiently model nitrate leaching due to utilisation of conventional algorithms. To address the issue, the current research employed advanced machine learning algorithms, viz., Support Vector Machine, Artificial Neural Network, Random Forest, M5 Tree (M5P), Reduced Error Pruning Tree (REPTree) and Response Surface Methodology (RSM) to predict and optimize nitrate leaching. In this study, Urea Super Granules (USG) with three different coatings were used for the experiment in the soil columns, containing 1 kg soil with fertiliser placed in between. Statistical parameters, namely correlation coefficient, Mean Absolute Error, Willmott index, Root Mean Square Error and Nash–Sutcliffe efficiency were used to evaluate the performance of the ML techniques. In addition, a comparison was made in the test set among the machine learning models in which, RSM outperformed the rest of the models irrespective of coating type. Neem oil/ Acacia oil(ml): clay/sulfer (g): age (days) for minimum nitrate leaching was found to be 2.61: 1.67: 2.4 for coating of USG with bentonite clay and neem oil without heating, 2.18: 2: 1 for bentonite clay and neem oil with heating and 1.69: 1.64: 2.18 for coating USG with sulfer and acacia oil. The research would provide guidelines to researchers and policymakers to select the appropriate tool for precise prediction of nitrate leaching, which would optimise the yield and the benefit–cost ratio., Validerad;2024;Nivå 2;2024-04-08 (marisr);Full text license: CC BY 4.0

An accurate assessment of nitrate leaching is important for efficient fertiliser utilisation and groundwater pollution reduction. However, past studies could not efficiently model nitrate leaching due to utilisation of conventional algorithms. To address the issue, the current research employed advanced machine learning algorithms, viz., Support Vector Machine, Artificial Neural Network, Random Forest, M5 Tree (M5P), Reduced Error Pruning Tree (REPTree) and Response Surface Methodology (RSM) to predict and optimize nitrate leaching. In this study, Urea Super Granules (USG) with three different coatings were used for the experiment in the soil columns, containing 1 kg soil with fertiliser placed in between. Statistical parameters, namely correlation coefficient, Mean Absolute Error, Willmott index, Root Mean Square Error and Nash–Sutcliffe efficiency were used to evaluate the performance of the ML techniques. In addition, a comparison was made in the test set among the machine learning models in which, RSM outperformed the rest of the models irrespective of coating type. Neem oil/ Acacia oil(ml): clay/sulfer (g): age (days) for minimum nitrate leaching was found to be 2.61: 1.67: 2.4 for coating of USG with bentonite clay and neem oil without heating, 2.18: 2: 1 for bentonite clay and neem oil with heating and 1.69: 1.64: 2.18 for coating USG with sulfer and acacia oil. The research would provide guidelines to researchers and policymakers to select the appropriate tool for precise prediction of nitrate leaching, which would optimise the yield and the benefit–cost ratio., Validerad;2024;Nivå 2;2024-04-08 (marisr);Full text license: CC BY 4.0

Point canonical transformation (PCT) has been used to find out new exactly solvable potentials in the position-dependent mass (PDM) framework. We solve $1$-D Schr\"{o}dinger equation in the PDM framework by considering two different fairly generic position-dependent masses $ (i) M(x)=\lambda g'(x)$ and $(ii) M(x) = c \left( {g'(x)} \right)^\nu $, $\nu =\frac{2\eta}{2\eta+1},$ with $\eta= 0,1,2\cdots $. In the first case, we find new exactly solvable potentials that depend on an integer parameter $m$, and the corresponding solutions are written in terms of $X_m$-Laguerre polynomials. In the latter case, we obtain a new one parameter $(\nu)$ family of isochronous solvable potentials whose bound states are written in terms of $X_m$-Laguerre polynomials. Further, we show that the new potentials are shape invariant by using the supersymmetric approach in the framework of PDM., Comment: 17 pages, 5 Figs, Latex

"Current Trends and Advances in Agricultural Sciences Vol. 1" delves into the forefront of agricultural innovation, offering a comprehensive exploration of cutting-edge methodologies and technologies shaping the field. Divided into chapters, the book encompasses a diverse array of topics crucial to modern agricultural practices. It consists of chapters on Geographic Information Systems (GIS) and Remote Sensing (RS) which elucidates how these technologies revolutionize agricultural management by providing precise spatial data for decision-making. It highlights their role in optimizing resource utilization, monitoring crop health, and mitigating environmental risks. Hydroponics and aquaponics, another featured chapter, spotlight sustainable cultivation methods. It unveils the potentials of soilless farming and integrated aquaculture, offering insights into maximizing yield while minimizing resource consumption and environmental impact. Artificial Intelligence emerges as a transformative force in agriculture, driving efficiency and productivity. This chapter explores AI applications ranging from predictive analytics for crop management to autonomous machinery for precision farming, ushering in a new era of smart agriculture. Genetically Modified (GM) crops take centre stage in the book, addressing controversies and advancements in genetic engineering. It discusses the potential of GM crops to enhance resilience, nutritional content, and yield, alongside ethical and regulatory considerations. Moreover, the exploration of hydrogels presents innovative solutions for water management and soil conditioning, crucial for sustainable agriculture in the face of climate change. Moreover, many important trends and advances in the field of agriculture have also been mentioned here in the form of book chapters. Hence, "Current Trends and Advances in Agricultural Sciences Vol. 1" serves as a beacon for researchers, practitioners, and policymakers, offering invaluable insights into t

Selective root canal retreatment has demonstrated positive success, but the process is challenging because imprecision compromises the tooth's structural durability. As there is a lack of literature on selective retreatment using DNS, this in-vitro study was designed for comparative evaluation of tooth tissue loss and time taken in locating mesiobuccal (MB)canal using the dynamic navigation system (DNS; Navident, ClaroNav, Toronto, ON, Canada ) to the freehand (FH) method. The null hypothesis was that both methods would have similar tooth tissue loss and time required for the procedure. Twenty root canal-treated human mandibular molar teeth were mounted on Navident manikin. Using the Navident programme, the drilling path and depth were virtually designed using cone-beam computed tomographic (CBCT) scans. A minimal access cavity for locating the MB root was prepared with dynamic navigation in the DNS group and with freehand in the FH group. Volumetric tooth tissue loss was evaluated with the help of postoperative CBCT and On-demand software. Statistical analysis was done with an independent-sample T Test (p<0.05). The time taken for the procedure was recorded with a stopwatch. The tooth tissue loss was significantly less with the DNS group (35.83 mm3) compared to the FH group (52.84 mm3) with a P value of 0.001. The time taken for the DNS group was less with the DNS group (29.00 seconds) compared to the FH group (53.60 seconds) with statistical significance with a P value of 0.001. The DNS resulted in minimal tooth tissue loss with a shorter time compared to the FH group. This technique can be practised for predictable selective retreatment in endodontics., El retratamiento selectivo del conducto radicular ha demostrado ser exitoso, pero el proceso es un desafío porque la imprecisión compromete la estructura del diente. Así, este estudio in vitro fue diseñado para evaluar de forma comparativa la pérdida de tejido dental y el tiempo necesario para localizar el canal mesiobucal (MB) usando el sistema de navegación dinámica (DNS; Navident, ClaroNav, Toronto , ON, Canadá ) con el método a mano alzada (FH). La hipótesis nula fue que ambos métodos tendrían una pérdida de tejido dental y un tiempo similares. Se utilizaron veinte molares mandibulares humanos tratados con conducto radicular en un maniquí Navident. Utilizando el programa Navident, la ruta de perforación y la profundidad se diseñó virtualmente mediante exploraciones por tomografía computarizada de haz cónico (CBCT). Se preparó una cavidad de mínimo acceso para localizar la raíz del MB con navegación dinámica en el grupo DNS y con mano alzada en el grupo FH. La pérdida volumétrica de tejido dental se evaluó con la ayuda de CBCT postoperatoria y software. El análisis estadístico se realizó con una prueba T para muestras independientes (p<0,05). El tiempo empleado en el procedimiento se registró con un cronómetro. La pérdida de tejido dental fue significativamente menor con el grupo DNS (35,83 mm3) en comparación con el grupo FH (52,84 mm3) con un valor de P de 0,001. El tiempo necesario para el grupo DNS fue menor con el grupo DNS (29,00 segundos) en comparación con el grupo FH (53,60 segundos) con significación estadística con un valor de P de 0,001. La DNS resultó en una pérdida mínima de tejido dental con un tiempo más corto en comparación con el grupo FH. Esta técnica se puede practicar para un retratamiento selectivo predecible en endodoncia.

The ongoing evolution of SARS-CoV-2 to evade vaccines and therapeutics underlines the need for innovative therapies with high genetic barriers to resistance. Therefore, there is pronounced interest in identifying new pharmacological targets in the SARS-CoV-2 viral life cycle. The small molecule PAV-104, identified through a cell-free protein synthesis and assembly screen, was recently shown to target host protein assembly machinery in a manner specific to viral assembly. In this study, we investigate the capacity of PAV-104 to inhibit SARS-CoV-2 replication in human airway epithelial cells (AECs). We show that PAV-104 inhibits >99% of infection with diverse SARS-CoV-2 variants in immortalized AECs, and in primary human AECs cultured at the air-liquid interface (ALI) to represent the lung microenvironment in vivo. Our data demonstrate that PAV-104 inhibits SARS-CoV-2 production without affecting viral entry, mRNA transcription, or protein synthesis. PAV-104 interacts with SARS-CoV-2 nucleocapsid (N) and interferes with its oligomerization, blocking particle assembly. Transcriptomic analysis reveals that PAV-104 reverses SARS-CoV-2 induction of the type-I interferon response and the maturation of nucleoprotein signaling pathway known to support coronavirus replication. Our findings suggest that PAV-104 is a promising therapeutic candidate for COVID-19 with a mechanism of action that is distinct from existing clinical management approaches.

An estimated 38 million people live with human immunodeficiency virus (HIV) worldwide and are at excess risk for multiple cancer types. Elevated cancer risks in people living with HIV (PLWH) are driven primarily by increased exposure to carcinogens, most notably oncogenic viruses acquired through shared transmission routes, plus acceleration of viral carcinogenesis by HIV-related immunosuppression. In the era of widespread antiretroviral therapy (ART), life expectancy of PLWH has increased, with cancer now a leading cause of co-morbidity and death. Furthermore, the types of cancers occurring among PLWH are shifting over time and vary in their relative burden in different parts of the world. In this context, the International Agency for Research on Cancer (IARC) and the US National Cancer Institute (NCI) convened a meeting in September 2022 of multinational and multidisciplinary experts to focus on cancer in PLWH. This report summarizes the proceedings, including a review of the state of the science of cancer descriptive epidemiology, etiology, molecular tumor characterization, primary and secondary prevention, treatment disparities and survival in PLWH around the world. A consensus of key research priorities and recommendations in these domains is also presented.

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.

Modification of lignin in feedstocks via genetic engineering aims to reduce biomass recalcitrance to facilitate efficient conversion processes. These improvements can be achieved by expressing exogenous enzymes that interfere with native biosynthetic pathways responsible for the production of the lignin precursors. In-planta expression of a 3-dehydroshikimate dehydratase (QsuB) in poplar trees reduced lignin content and altered their monomer composition, which enabled higher yields of sugars after cell wall polysaccharide hydrolysis. Understanding how plants respond to such genetic modifications at the transcriptional and metabolic levels is needed to facilitate further improvement and field deployment. In this work, we amassed fundamental knowledge on lignin-modified QsuB poplar using RNA-seq and metabolomics. The data clearly demonstrate that changes in gene expression and metabolite abundance can occur in a strict spatiotemporal fashion, revealing tissue-specific responses in the xylem, phloem, or periderm. In the poplar line that exhibits the strongest reduction in lignin, we found that 3% of the transcripts had altered expression levels and ~19% of the detected metabolites had differential abundance in the xylem from older stems. Changes affect predominantly the shikimate and phenylpropanoid pathways as wells as secondary cell wall metabolism, and result in significant accumulation of hydroxybenzoates derived from protocatechuate and salicylate.

Potato is a globally significant crop, crucial for food security and nutrition. Assessing vital nutritional traits is pivotal for enhancing nutritional value. However, traditional wet lab methods for the screening of large germplasms are time- and resource-intensive. To address this challenge, we used near-infrared reflectance spectroscopy (NIRS) for rapid trait estimation in diverse potato germplasms. It employs molecular absorption principles that use near-infrared sections of the electromagnetic spectrum for the precise and rapid determination of biochemical parameters and is non-destructive, enabling trait monitoring without sample compromise. We focused on modified partial least squares (MPLS)-based NIRS prediction models to assess eight key nutritional traits. Various mathematical treatments were executed by permutation and combinations for model calibration. The external validation prediction accuracy was based on the coefficient of determination (RSQexternal), the ratio of performance to deviation (RPD), and the low standard error of performance (SEP). Higher RSQexternal values of 0.937, 0.892, and 0.759 were obtained for protein, dry matter, and total phenols, respectively. Higher RPD values were found for protein (3.982), followed by dry matter (3.041) and total phenolics (2.000), which indicates the excellent predictability of the models. A paired t-test confirmed that the differences between laboratory and predicted values are non-significant. This study presents the first multi-trait NIRS prediction model for Indian potato germplasm. The developed NIRS model effectively predicted the remaining genotypes in this study, demonstrating its broad applicability. This work highlights the rapid screening potential of NIRS for potato germplasm, a valuable tool for identifying trait variations and refining breeding strategies, to ensure sustainable potato production in the face of climate change.

Potato is a globally significant crop, crucial for food security and nutrition. Assessing vital nutritional traits is pivotal for enhancing nutritional value. However, traditional wet lab methods for the screening of large germplasms are time- and resource-intensive. To address this challenge, we used near-infrared reflectance spectroscopy (NIRS) for rapid trait estimation in diverse potato germplasms. It employs molecular absorption principles that use near-infrared sections of the electromagnetic spectrum for the precise and rapid determination of biochemical parameters and is non-destructive, enabling trait monitoring without sample compromise. We focused on modified partial least squares (MPLS)-based NIRS prediction models to assess eight key nutritional traits. Various mathematical treatments were executed by permutation and combinations for model calibration. The external validation prediction accuracy was based on the coefficient of determination (RSQexternal), the ratio of performance to deviation (RPD), and the low standard error of performance (SEP). Higher RSQexternal values of 0.937, 0.892, and 0.759 were obtained for protein, dry matter, and total phenols, respectively. Higher RPD values were found for protein (3.982), followed by dry matter (3.041) and total phenolics (2.000), which indicates the excellent predictability of the models. A paired t-test confirmed that the differences between laboratory and predicted values are non-significant. This study presents the first multi-trait NIRS prediction model for Indian potato germplasm. The developed NIRS model effectively predicted the remaining genotypes in this study, demonstrating its broad applicability. This work highlights the rapid screening potential of NIRS for potato germplasm, a valuable tool for identifying trait variations and refining breeding strategies, to ensure sustainable potato production in the face of climate change.

Objective: The nasal cavity effectively captures the particles present in inhaled air, thereby preventing harmful and toxic pollutants from reaching the lungs. This filtering ability of the nasal cavity can be effectively utilized for targeted nasal drug delivery applications. This study aims to understand the particle deposition patterns in three age groups: neonate, infant, and adult. Materials and methods: The CT scans are built using MIMICS 21.0, followed by CATIA V6 to generate a patient-specific airway model. Fluid flow is simulated using ANSYS FLUENT 2021 R2. Spherical monodisperse microparticles ranging from 2 to 60 µm and a density of 1100 kg/m3 are simulated at steady-state and sedentary inspiration conditions. Results: The highest nasal valve depositions for the neonate are 25 for 20 µm, for infants, 10 for 50 µm, 15 for adults, and 15 for 15 µm. At mid nasal region, deposition of 15 for 20 µm is observed for infant and 8 for neonate and adult nasal cavities at a particle size of 10 and 20 µm, respectively. The highest particle deposition at the olfactory region is about 2.7 for the adult nasal cavity for 20 µm, and it is <1 for neonate and infant nasal cavities. Discussion and conclusions: The study of preferred nasal depositions during natural sedentary breathing conditions is utilized to determine the size that allows medication particles to be targeted to specific nose regions.

Objective: The nasal cavity effectively captures the particles present in inhaled air, thereby preventing harmful and toxic pollutants from reaching the lungs. This filtering ability of the nasal cavity can be effectively utilized for targeted nasal drug delivery applications. This study aims to understand the particle deposition patterns in three age groups: neonate, infant, and adult. Materials and methods: The CT scans are built using MIMICS 21.0, followed by CATIA V6 to generate a patient-specific airway model. Fluid flow is simulated using ANSYS FLUENT 2021 R2. Spherical monodisperse microparticles ranging from 2 to 60 µm and a density of 1100 kg/m3 are simulated at steady-state and sedentary inspiration conditions. Results: The highest nasal valve depositions for the neonate are 25 for 20 µm, for infants, 10 for 50 µm, 15 for adults, and 15 for 15 µm. At mid nasal region, deposition of 15 for 20 µm is observed for infant and 8 for neonate and adult nasal cavities at a particle size of 10 and 20 µm, respectively. The highest particle deposition at the olfactory region is about 2.7 for the adult nasal cavity for 20 µm, and it is <1 for neonate and infant nasal cavities. Discussion and conclusions: The study of preferred nasal depositions during natural sedentary breathing conditions is utilized to determine the size that allows medication particles to be targeted to specific nose regions.

Potato is a globally significant crop, crucial for food security and nutrition. Assessing vital nutritional traits is pivotal for enhancing nutritional value. However, traditional wet lab methods for the screening of large germplasms are time- and resource-intensive. To address this challenge, we used near-infrared reflectance spectroscopy (NIRS) for rapid trait estimation in diverse potato germplasms. It employs molecular absorption principles that use near-infrared sections of the electromagnetic spectrum for the precise and rapid determination of biochemical parameters and is non-destructive, enabling trait monitoring without sample compromise. We focused on modified partial least squares (MPLS)-based NIRS prediction models to assess eight key nutritional traits. Various mathematical treatments were executed by permutation and combinations for model calibration. The external validation prediction accuracy was based on the coefficient of determination (RSQexternal), the ratio of performance to deviation (RPD), and the low standard error of performance (SEP). Higher RSQexternal values of 0.937, 0.892, and 0.759 were obtained for protein, dry matter, and total phenols, respectively. Higher RPD values were found for protein (3.982), followed by dry matter (3.041) and total phenolics (2.000), which indicates the excellent predictability of the models. A paired t-test confirmed that the differences between laboratory and predicted values are non-significant. This study presents the first multi-trait NIRS prediction model for Indian potato germplasm. The developed NIRS model effectively predicted the remaining genotypes in this study, demonstrating its broad applicability. This work highlights the rapid screening potential of NIRS for potato germplasm, a valuable tool for identifying trait variations and refining breeding strategies, to ensure sustainable potato production in the face of climate change.

Potato is a globally significant crop, crucial for food security and nutrition. Assessing vital nutritional traits is pivotal for enhancing nutritional value. However, traditional wet lab methods for the screening of large germplasms are time- and resource-intensive. To address this challenge, we used near-infrared reflectance spectroscopy (NIRS) for rapid trait estimation in diverse potato germplasms. It employs molecular absorption principles that use near-infrared sections of the electromagnetic spectrum for the precise and rapid determination of biochemical parameters and is non-destructive, enabling trait monitoring without sample compromise. We focused on modified partial least squares (MPLS)-based NIRS prediction models to assess eight key nutritional traits. Various mathematical treatments were executed by permutation and combinations for model calibration. The external validation prediction accuracy was based on the coefficient of determination (RSQexternal), the ratio of performance to deviation (RPD), and the low standard error of performance (SEP). Higher RSQexternal values of 0.937, 0.892, and 0.759 were obtained for protein, dry matter, and total phenols, respectively. Higher RPD values were found for protein (3.982), followed by dry matter (3.041) and total phenolics (2.000), which indicates the excellent predictability of the models. A paired t-test confirmed that the differences between laboratory and predicted values are non-significant. This study presents the first multi-trait NIRS prediction model for Indian potato germplasm. The developed NIRS model effectively predicted the remaining genotypes in this study, demonstrating its broad applicability. This work highlights the rapid screening potential of NIRS for potato germplasm, a valuable tool for identifying trait variations and refining breeding strategies, to ensure sustainable potato production in the face of climate change.

Sharing Internet of Things (IoT) data across different sectors, such as in smart cities, becomes complex due to heterogeneity. This poses challenges related to a lack of interoperability, data quality issues and lack of context information, and a lack of data veracity (or accuracy). In addition, there are privacy concerns as IoT data may contain personally identifiable information. To address the above challenges, this paper presents a novel semantic technology-based framework that enables data sharing in a GDPR-compliant manner while ensuring that the data shared is interoperable, contains required context information, is of acceptable quality, and is accurate and trustworthy. The proposed framework also accounts for the edge/fog, an upcoming computing paradigm for the IoT to support real-time decisions. We evaluate the performance of the proposed framework with two different edge and fog–edge scenarios using resource-constrained IoT devices, such as the Raspberry Pi. In addition, we also evaluate shared data quality, interoperability and veracity. Our key finding is that the proposed framework can be employed on IoT devices with limited resources due to its low CPU and memory utilization for analytics operations and data transformation and migration operations. The low overhead of the framework supports real-time decision making. In addition, the 100% accuracy of our evaluation of the data quality and veracity based on 180 different observations demonstrates that the proposed framework can guarantee both data quality and veracity.

As the world continues to urbanize at an unprecedented rate, pursuing sustainable cities has become imperative. Achieving sustainability within this complex context necessitates the em-ployment of comprehensive assessment methods. The study delves into a comprehensive review of prominent urban sustainability assessment methods, including LEED for Neighborhood Develop-ment, BREEAM Communities, and GRIHA for cities. It identifies commonalities and differences in their assessment criteria, data sources, and evaluation techniques. In conclusion, this research paper provides a crucial foundation for advancing the cause of sustainable cities by comprehensively ex-amining and evaluating the tools and methods available to urban planners, policymakers, and stakeholders.

Urban resilience has emerged as an imperative response to the growing challenges of rapid urbanization, climate change, hazards, and other complex shocks and stressors. The enhance-ment of urban resilience predominantly depends on its operationalization, especially through the norms and regulations that define the built environment in cities. Therefore, analyzing the existing norms and regulations shaping urban resilience in cities is essential. This article critically reviews the norms and regulations defining urban resilience in the context of Indian cities. The urbanization trajectory in India has been remarkable, but it has also exposed cities to vulnerabilities and risks. This research seeks to unravel the intricate web of norms and regulations that influence the resili-ence of Indian cities. By employing a comprehensive approach, we scrutinize the legal, administra-tive, and policy frameworks that govern urban development in Indian cities. This study explores various dimensions of urban resilience for evaluating the current alignment of norms and regula-tions with respect to the goal of strengthening urban resilience in cities. Through this examination, we aim to offer insights for policymakers, urban planners, and researchers on fortifying urban re-silience in the Indian context. Our findings underscore the need for a holistic approach that ad-dresses the interplay between norms, regulations, and the multifaceted nature of resilience. In con-clusion, this critical review contributes to the discourse on urban resilience. It provides a nuanced understanding of how norms and regulations can be harnessed to safeguard and enhance the resil-ience of Indian cities. The findings of this study have implications not only for India but also for urban contexts worldwide facing similar challenges.

It is commonly held that quantum states with energy $E = 0$ would belong to the continuum. However, several situations have been reported when a zero-energy state becomes bound subject to certain restrictions on the coupling constants defining the potential. In the present work, we present another evidence of the existence of regular zero-energy normalizable solutions for a system of QES potentials that correspond to rationally extended many-body truncated Calogero-Sutherland model. Our procedure is based upon the potential group approach with an underlying so$(2, 1)$ structure that utilizes the three cases guided by it on profitably carrying out a point canonical transformation. We deal with each case separately by suitably restricting the coupling parameters., Comment: 12 Pages, 4 Figs

For the total doctorate awarded in India in 2013, the male-to-female ratio was 63:37. This ratio improved to 57:43 in favour of women in 2021. In absolute terms, the number of women awarded doctorates almost doubled in 2021 compared with 2013. In this study, we examine the progress made by Indian women in doctoral education based on annual reports from the All India Survey on Higher Education. The improved ratios and numbers reflect the adoption of an action-oriented approach in dealing with the concepts of equality and inclusion. The reasons for the progress and ways to improve were investigated based on secondary data and interviews with 15 expert senior female research supervisors. The interviews reveal that apart from the mandatory requirement of a PhD qualification for academic progression, other initiatives have been taken by the Government that have encouraged more women to opt for doctoral education. However, more needs to be done to make research easy for women in India, and such areas, as pointed out by the panel of experts, have been discussed. These findings can be used by other nations that want to bring more inclusivity to doctoral education.

Introduction: Skin cancer is currently the most common cancer type worldwide, and numbers are rapidly increasing. To improve primary prevention, individualised prevention strategies may be of interest as this enhances the chance of long-term behavioural change. The Sun Exposure and Protection Index (SEPI), previously validated in multiple languages, is a tool that could help identify individuals with risky behaviour and tailor interventions to the persons propensity to change. The aim of the present study was to investigate the reliability and validity of a Dutch version of the SEPI for both usage in daily clinical practice and research. Methods: Patients were included at primary care settings and dermatology outpatient settings in a 1:1 ratio. Participants were asked to fill out the SEPI together with some baseline characteristics and the previously validated FACE-Q Skin Cancer - Sun Protection module. Construct validity was tested by comparing SEPI part I and the FACE-Q module using Spearmans Rho. Internal consistency was assessed with Cronbachs Alpha for both SEPI parts separately. To assess test-retest reliability, the SEPI was again filled out three weeks later, and scores were compared with Cohens weighted Kappa. Results: Of the 171 participants completing the first questionnaire, 147 (86.0%) participants also completed the follow-up questionnaire. Comparison between the corresponding SEPI part I and FACE-Q module questions showed good correlations regarding sun exposure habits (correlation coefficients ranging from 0.61 to 0.85). Internal consistency of SEPI part I was 0.63 and SEPI part II was 0.65. The test-retest analysis indicated reproducibility over time (weighted Kappa ranging from 0.38 to 0.76). Conclusion: In conclusion, the Dutch version of the SEPI is shown to be a valid and reliable tool for both usage in daily clinical practice and research to evaluate individual UV exposure and measure a persons propensity to limit it.

Lithium-rich, cobalt-free oxides are promising potential positive electrode materials for lithium-ion batteries because of their high energy density, lower cost, and reduced environmental and ethical concerns. However, their commercial breakthrough is hindered because of their subpar electrochemical stability. This work studies the effect of aluminum doping on Li1.26Ni0.15Mn0.61O2 as a lithium-rich, cobalt-free layered oxide. Al doping suppresses voltage fade and improves the capacity retention from 46% for Li1.26Ni0.15Mn0.61O2 to 67% for Li1.26Ni0.15Mn0.56Al0.05O2 after 250 cycles at 0.2 C. The undoped material has a monoclinic Li2MnO3-type structure with spinel on the particle edges. In contrast, Al-doped materials (Li1.26Ni0.15Mn0.61-xAlxO2) consist of a more stable rhombohedral phase at the particle edges, with a monoclinic phase core. For this core-shell structure, the formation of Mn3+ is suppressed along with the material's decomposition to a disordered spinel, and the amount of the rhombohedral phase content increases during galvanostatic cycling. Whereas previous studies generally provided qualitative insight into the degradation mechanisms during electrochemical cycling, this work provides quantitative information on the stabilizing effect of the rhombohedral shell in the doped sample. As such, this study provides fundamental insight into the mechanisms through which Al doping increases the electrochemical stability of lithium-rich cobalt-free layered oxides.

Introduction: Skin cancer is currently the most common cancer type worldwide, and numbers are rapidly increasing. To improve primary prevention, individualised prevention strategies may be of interest as this enhances the chance of long-term behavioural change. The Sun Exposure and Protection Index (SEPI), previously validated in multiple languages, is a tool that could help identify individuals with risky behaviour and tailor interventions to the persons propensity to change. The aim of the present study was to investigate the reliability and validity of a Dutch version of the SEPI for both usage in daily clinical practice and research. Methods: Patients were included at primary care settings and dermatology outpatient settings in a 1:1 ratio. Participants were asked to fill out the SEPI together with some baseline characteristics and the previously validated FACE-Q Skin Cancer - Sun Protection module. Construct validity was tested by comparing SEPI part I and the FACE-Q module using Spearmans Rho. Internal consistency was assessed with Cronbachs Alpha for both SEPI parts separately. To assess test-retest reliability, the SEPI was again filled out three weeks later, and scores were compared with Cohens weighted Kappa. Results: Of the 171 participants completing the first questionnaire, 147 (86.0%) participants also completed the follow-up questionnaire. Comparison between the corresponding SEPI part I and FACE-Q module questions showed good correlations regarding sun exposure habits (correlation coefficients ranging from 0.61 to 0.85). Internal consistency of SEPI part I was 0.63 and SEPI part II was 0.65. The test-retest analysis indicated reproducibility over time (weighted Kappa ranging from 0.38 to 0.76). Conclusion: In conclusion, the Dutch version of the SEPI is shown to be a valid and reliable tool for both usage in daily clinical practice and research to evaluate individual UV exposure and measure a persons propensity to limit it.

A prolonged crustal history from Archean through Proterozoic to Cambrian, spanning more than half of the Earth’s evolution through time is preserved in the rock record in East Antarctica. Geological field studies have been conducted in Dronning Maud Land and Enderby Land of East Antarctica as part of the scientific program of Japanese Antarctic Research Expedition (JARE). Late Neoproterozoic to Cambrian (>600-520 Ma) high-grade metamorphic terranes, developed as major orogenic belts during the Gondwana supercontinent formation, are recognized in central Dronning Maud Land, Sør Rondane Mountains, Belgica and Yamato Mountains (Yamato-Belgica Complex), Lützow-Holm Bay-Prince Olav Coast region (Lützow-Holm Complex) to western Enderby Land (Western Rayner Complex) over 2000 km from west to east along the coast-inland of the Antarctic continent. Relatively narrow and sporadic Meso-Neoproterozoic (1000-900 Ma) high-grade blocks (Hinode Block and Niban-nishi Rock - granulite-facies; Akebono Rock - amphibolite-facies) are identified in Prince Olav Coast geographically within the Lützow-Holm Complex. Archean high-grade-UHT granulites and gneisses of the Napier Complex represent the largest regional terrain covering 400 × 200 km² area in Enderby Land, along with widespread Meso-Neoproterozoic granulite-facies zone of Rayner Complex from Enderby Land through Kemp Land, McRobertson Land toward east to Prydz Bay region. Thus, the continental crustal domain investigated by the Japanese Antarctic expeditions is key in understanding the Archean-Proterozoic-Cambrian deep crustal history and processes. In this special issue we summarize the recent progress in the mineralogical, petrological, geochemical, and geochronological studies carried out in East Antarctica.

Introduction: Skin cancer is currently the most common cancer type worldwide, and numbers are rapidly increasing. To improve primary prevention, individualised prevention strategies may be of interest as this enhances the chance of long-term behavioural change. The Sun Exposure and Protection Index (SEPI), previously validated in multiple languages, is a tool that could help identify individuals with risky behaviour and tailor interventions to the persons propensity to change. The aim of the present study was to investigate the reliability and validity of a Dutch version of the SEPI for both usage in daily clinical practice and research. Methods: Patients were included at primary care settings and dermatology outpatient settings in a 1:1 ratio. Participants were asked to fill out the SEPI together with some baseline characteristics and the previously validated FACE-Q Skin Cancer - Sun Protection module. Construct validity was tested by comparing SEPI part I and the FACE-Q module using Spearmans Rho. Internal consistency was assessed with Cronbachs Alpha for both SEPI parts separately. To assess test-retest reliability, the SEPI was again filled out three weeks later, and scores were compared with Cohens weighted Kappa. Results: Of the 171 participants completing the first questionnaire, 147 (86.0%) participants also completed the follow-up questionnaire. Comparison between the corresponding SEPI part I and FACE-Q module questions showed good correlations regarding sun exposure habits (correlation coefficients ranging from 0.61 to 0.85). Internal consistency of SEPI part I was 0.63 and SEPI part II was 0.65. The test-retest analysis indicated reproducibility over time (weighted Kappa ranging from 0.38 to 0.76). Conclusion: In conclusion, the Dutch version of the SEPI is shown to be a valid and reliable tool for both usage in daily clinical practice and research to evaluate individual UV exposure and measure a persons propensity to limit it.

Refractory high-entropy alloys (RHEAs) are of interest for ultrahigh-temperature applications. To overcome their drawbacks — low-temperature brittleness and poor creep strength at high temperatures — improved fundamental understanding is needed. Using experiments, theory, and modeling, we investigated prototypical body-centered cubic (BCC) RHEAs, TiZrHfNbTa and VNbMoTaW. The former is compressible to 77 K, whereas the latter is not below 298 K. Hexagonal close-packed (HCP) elements in TiZrHfNbTa lower its dislocation core energy, increase lattice distortion, and lower its shear modulus relative to VNbMoTaW whose elements are all BCC. Screw dislocations dominate TiZrHfNbTa plasticity, but equal numbers of edges and screws exist in VNbTaMoW. Dislocation cores are compact in VNbTaMoW and extended in TiZrHfNbTa, and different macroscopic slip planes are activated in the two RHEAs, which we attribute to the concentration of HCP elements. Our findings demonstrate how ductility and strength can be controlled through the ratio of HCP to BCC elements in RHEAs.

BackgroundSARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice.MethodsThis is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure.ResultsNine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout.There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management.ResultsNine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout.There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits

Plastic foams, such as Styrofoam, protect items during transport. Recognising the recycling challenges of these foams, there's a growing interest in developing alternatives from renewable resources, particularly cellulose fibres, for packaging. A deep understanding of its structure, specifically achieving a uniform distribution of small pore sizes, is crucial to enhancing the mechanical properties of the foam. Prior works highlight the need for improvement in X-ray techniques and image-processing techniques to address challenges in data acquisition and analysis. In this study, X-ray Microtomography equipment was used to capture images of the fibre foam sample, and software like XMController and XMReconstructor obtained 2D projection images at different magnifications (2X, 4X, 10X, and 20X). ImageJ and Python algorithms were then used to distinguish pores and fibres from the obtained images and characterize the pores, which included Bilateral filtering, that helped reduce background noise and preserve fibres in the grayscale images. The Threshold Otsu method converted the grayscale image to a binary image, and the inverted binary image aided in Local thickness image formation. The Local thickness image represented fibres with pixel value zero and blown-up spheres of different intensities representing the pores and their characteristics. As the magnification of the Local thickness images increased, the Pore Area, Pore Volume, Pore Perimeter, and Total Pores decreased, indicating a shift towards a more uniform distribution of smaller pores. Histograms, scatter plots, and pore intensity distribution histograms visually represented this trend. Similarly, characteristics like pore density increased, porosity decreased, and specific surface area remained constant with increasing magnification, suggesting a more compact structure. Objective measurements of image quality metrics, such as PSNR, RMSE, SSIM, and NCC, were used. Grayscale images of different magnifications were, Plastskum, som frigolit, skyddar föremål under transport. Att känna igenåtervinningsutmaningar för dessa skum, finns det ett växande intresse för att utveckla alternativ frånförnybara resurser, särskilt cellulosafibrer, för förpackningar. En djup förståelse för detstruktur, specifikt att uppnå en enhetlig fördelning av små porstorlekar, är avgörande förförbättring av skummets mekaniska egenskaper. Tidigare arbeten belyser behovet avförbättring av röntgentekniker och bildbehandlingstekniker för att möta utmaningar idatainsamling och analys. I denna studie användes röntgenmikrotomografiutrustning för attta bilder av fiberskumprovet och programvara som XMController ochXMReconstructor erhöll 2D-projektionsbilder med olika förstoringar (2X, 4X, 10X,och 20X). ImageJ och Python-algoritmer användes sedan för att skilja porer och fibrer frånde erhållna bilderna och karakterisera porerna, vilket inkluderade bilateral filtrering, som hjälpteminska bakgrundsbrus och bevara fibrer i gråskalebilderna. The Threshold Otsumetoden konverterade gråskalebilden till en binär bild, och den inverterade binära bilden hjälpte tilli lokal tjocklek bildbildning. Den lokala tjockleksbilden representerade fibrer med pixelvärde noll och uppblåsta sfärer med olika intensitet som representerar porerna och derasegenskaper. När förstoringen av bilderna med lokal tjocklek ökade, ökade porområdet,Porvolym, poromkrets och totala porer minskade, vilket indikerar en förskjutning mot en merjämn fördelning av mindre porer. Histogram, spridningsdiagram och porintensitetsfördelninghistogram representerade visuellt denna trend. På liknande sätt ökade egenskaper som pordensitet,porositeten minskade och den specifika ytarean förblev konstant med ökande förstoring,föreslår en mer kompakt struktur. Objektiva mätningar av bildkvalitetsmått, t.exsom PSNR, RMSE, SSIM och NCC, användes. Gråskalebilder med olika förstoringarjämfördes, och det noterades att när antalet projektioner ökade, 10X vs. 20Xoch 2X vs. 4X par p

Introduction: Skin cancer is currently the most common cancer type worldwide, and numbers are rapidly increasing. To improve primary prevention, individualised prevention strategies may be of interest as this enhances the chance of long-term behavioural change. The Sun Exposure and Protection Index (SEPI), previously validated in multiple languages, is a tool that could help identify individuals with risky behaviour and tailor interventions to the persons propensity to change. The aim of the present study was to investigate the reliability and validity of a Dutch version of the SEPI for both usage in daily clinical practice and research. Methods: Patients were included at primary care settings and dermatology outpatient settings in a 1:1 ratio. Participants were asked to fill out the SEPI together with some baseline characteristics and the previously validated FACE-Q Skin Cancer - Sun Protection module. Construct validity was tested by comparing SEPI part I and the FACE-Q module using Spearmans Rho. Internal consistency was assessed with Cronbachs Alpha for both SEPI parts separately. To assess test-retest reliability, the SEPI was again filled out three weeks later, and scores were compared with Cohens weighted Kappa. Results: Of the 171 participants completing the first questionnaire, 147 (86.0%) participants also completed the follow-up questionnaire. Comparison between the corresponding SEPI part I and FACE-Q module questions showed good correlations regarding sun exposure habits (correlation coefficients ranging from 0.61 to 0.85). Internal consistency of SEPI part I was 0.63 and SEPI part II was 0.65. The test-retest analysis indicated reproducibility over time (weighted Kappa ranging from 0.38 to 0.76). Conclusion: In conclusion, the Dutch version of the SEPI is shown to be a valid and reliable tool for both usage in daily clinical practice and research to evaluate individual UV exposure and measure a persons propensity to limit it.

Thermus thermophilus bacteriophage P23-45 encodes a giant 5,002-residue tail tape measure protein (TMP) that defines the length of its extraordinarily long tail. Here, we show that the N-terminal portion of P23-45 TMP is an unusual RNA polymerase (RNAP) homologous to cellular RNAPs. The TMP-fused virion RNAP transcribes pre-early phage genes, including a gene that encodes another, non-virion RNAP, that transcribes early and some middle phage genes. We report the crystal structures of both P23-45 RNAPs. The non-virion RNAP has a crab-claw-like architecture. By contrast, the virion RNAP adopts a unique flat structure without a clamp. Structure and sequence comparisons of the P23-45 RNAPs with other RNAPs suggest that, despite the extensive functional differences, the two P23-45 RNAPs originate from an ancient gene duplication in an ancestral phage. Our findings demonstrate striking adaptability of RNAPs that can be attained within a single virus species.

Introduction: Skin cancer is currently the most common cancer type worldwide, and numbers are rapidly increasing. To improve primary prevention, individualised prevention strategies may be of interest as this enhances the chance of long-term behavioural change. The Sun Exposure and Protection Index (SEPI), previously validated in multiple languages, is a tool that could help identify individuals with risky behaviour and tailor interventions to the persons propensity to change. The aim of the present study was to investigate the reliability and validity of a Dutch version of the SEPI for both usage in daily clinical practice and research. Methods: Patients were included at primary care settings and dermatology outpatient settings in a 1:1 ratio. Participants were asked to fill out the SEPI together with some baseline characteristics and the previously validated FACE-Q Skin Cancer - Sun Protection module. Construct validity was tested by comparing SEPI part I and the FACE-Q module using Spearmans Rho. Internal consistency was assessed with Cronbachs Alpha for both SEPI parts separately. To assess test-retest reliability, the SEPI was again filled out three weeks later, and scores were compared with Cohens weighted Kappa. Results: Of the 171 participants completing the first questionnaire, 147 (86.0%) participants also completed the follow-up questionnaire. Comparison between the corresponding SEPI part I and FACE-Q module questions showed good correlations regarding sun exposure habits (correlation coefficients ranging from 0.61 to 0.85). Internal consistency of SEPI part I was 0.63 and SEPI part II was 0.65. The test-retest analysis indicated reproducibility over time (weighted Kappa ranging from 0.38 to 0.76). Conclusion: In conclusion, the Dutch version of the SEPI is shown to be a valid and reliable tool for both usage in daily clinical practice and research to evaluate individual UV exposure and measure a persons propensity to limit it.

Programmed death-ligand 1 (PD-L1) is overexpressed in squamous cervical cancer (SCC) and can be used for targeted immunotherapy. The highest mortality rates of SCC are reported in sub-Saharan Africa, where Human immunodeficiency virus (HIV) prevalence is high. In Mozambique most SCC patients present at advanced stages. Thus, there is a need to introduce new treatment options. However, immunocompromised patients were frequently excluded in previous clinical trials. Our aim was to determine if PD-L1 expression in SCC is as prevalent among women living with HIV (WLWH) as among other patients. 575 SCC from Maputo Central Hospital were included. HIV status was available in 266 (46%) cases PD-L1 expression was scored through tumour proportion score (TPS) and combined positive score (CPS). PD-L1 was positive in 20.1% of the cases (n = 110), TPS (score ≥ 25%) and in 26.3% (n = 144), CPS (score ≥ 1). Stratifying according to the HIV status, WLWH were TPS positive in 16.7%, compared to 20.9%, p = 0.43, and concerning CPS 21.1% versus 28.7%, p = 0.19, respectively. PD-L1 status was not influenced by stage, Ki-67 or p16, CD8 expression influenced only CPS status. Our data indicates that the documented effect of PD-L1 therapy on SCC should be confirmed in randomized clinical trials in an HIV endemic milieu.

Plastic foams, such as Styrofoam, protect items during transport. Recognising the recycling challenges of these foams, there's a growing interest in developing alternatives from renewable resources, particularly cellulose fibres, for packaging. A deep understanding of its structure, specifically achieving a uniform distribution of small pore sizes, is crucial to enhancing the mechanical properties of the foam. Prior works highlight the need for improvement in X-ray techniques and image-processing techniques to address challenges in data acquisition and analysis. In this study, X-ray Microtomography equipment was used to capture images of the fibre foam sample, and software like XMController and XMReconstructor obtained 2D projection images at different magnifications (2X, 4X, 10X, and 20X). ImageJ and Python algorithms were then used to distinguish pores and fibres from the obtained images and characterize the pores, which included Bilateral filtering, that helped reduce background noise and preserve fibres in the grayscale images. The Threshold Otsu method converted the grayscale image to a binary image, and the inverted binary image aided in Local thickness image formation. The Local thickness image represented fibres with pixel value zero and blown-up spheres of different intensities representing the pores and their characteristics. As the magnification of the Local thickness images increased, the Pore Area, Pore Volume, Pore Perimeter, and Total Pores decreased, indicating a shift towards a more uniform distribution of smaller pores. Histograms, scatter plots, and pore intensity distribution histograms visually represented this trend. Similarly, characteristics like pore density increased, porosity decreased, and specific surface area remained constant with increasing magnification, suggesting a more compact structure. Objective measurements of image quality metrics, such as PSNR, RMSE, SSIM, and NCC, were used. Grayscale images of different magnifications were, Plastskum, som frigolit, skyddar föremål under transport. Att känna igenåtervinningsutmaningar för dessa skum, finns det ett växande intresse för att utveckla alternativ frånförnybara resurser, särskilt cellulosafibrer, för förpackningar. En djup förståelse för detstruktur, specifikt att uppnå en enhetlig fördelning av små porstorlekar, är avgörande förförbättring av skummets mekaniska egenskaper. Tidigare arbeten belyser behovet avförbättring av röntgentekniker och bildbehandlingstekniker för att möta utmaningar idatainsamling och analys. I denna studie användes röntgenmikrotomografiutrustning för attta bilder av fiberskumprovet och programvara som XMController ochXMReconstructor erhöll 2D-projektionsbilder med olika förstoringar (2X, 4X, 10X,och 20X). ImageJ och Python-algoritmer användes sedan för att skilja porer och fibrer frånde erhållna bilderna och karakterisera porerna, vilket inkluderade bilateral filtrering, som hjälpteminska bakgrundsbrus och bevara fibrer i gråskalebilderna. The Threshold Otsumetoden konverterade gråskalebilden till en binär bild, och den inverterade binära bilden hjälpte tilli lokal tjocklek bildbildning. Den lokala tjockleksbilden representerade fibrer med pixelvärde noll och uppblåsta sfärer med olika intensitet som representerar porerna och derasegenskaper. När förstoringen av bilderna med lokal tjocklek ökade, ökade porområdet,Porvolym, poromkrets och totala porer minskade, vilket indikerar en förskjutning mot en merjämn fördelning av mindre porer. Histogram, spridningsdiagram och porintensitetsfördelninghistogram representerade visuellt denna trend. På liknande sätt ökade egenskaper som pordensitet,porositeten minskade och den specifika ytarean förblev konstant med ökande förstoring,föreslår en mer kompakt struktur. Objektiva mätningar av bildkvalitetsmått, t.exsom PSNR, RMSE, SSIM och NCC, användes. Gråskalebilder med olika förstoringarjämfördes, och det noterades att när antalet projektioner ökade, 10X vs. 20Xoch 2X vs. 4X par p

The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.

Objectives: The goal of the research was to assess the quantitative relationship between median progression-free survival (PFS) and median overall survival (OS) specifically among patients with relapsed/refractory multiple myeloma (RRMM) based on published randomized controlled trials (RCTs). Methods: Two bibliographic databases (PubMed and Embase, 1970–2017) were systematically searched for RCTs in RRMM that reported OS and PFS, followed by an updated search of studies published between 2010 and 2022 in 3 databases (Embase, MEDLINE, and EBM Reviews, 2010–2022). The association between median PFS and median OS was assessed using the nonparametric Spearman rank and parametric Pearson correlation coefficients. Subsequently, the quantitative relationship between PFS and OS was assessed using weighted least-squares regression adjusted for covariates including age, sex, and publication year. Study arms were weighted by the number of patients in each arm. Results: A total of 31 RCTs (56 treatment arms, 10,450 patients with RRMM) were included in the analysis. The average median PFS and median OS were 7.1 months (SD 5.5) and 28.1 months (SD 11.8), respectively. The Spearman and Pearson correlation coefficients between median PFS and median OS were 0.80 (P < 0.0001) and 0.79 (P < 0.0001), respectively. In individual treatment arms of RRMM trials, each 1-month increase in median PFS was associated with a 1.72-month (95% CI 1.26–2.17) increase in median OS. Conclusion: Analysis of the relationship between PFS and OS incorporating more recent studies in RRMM further substantiates the use of PFS to predict OS in RRMM.

Amnah Al Hanaei,1 Fatima AlKindi,2 Aysha Alkhemeiri,2 Satish Chandrasekhar Nair3 1Division of Gastroenterology, Tawam Hospital, Al Ain, Emirate of Abu Dhabi, United Arab Emirates; 2Department of Internal Medicine, Tawam Hospital, Al Ain, Emirate of Abu Dhabi, United Arab Emirates; 3Department of Academic Affairs, Tawam Hospital & the College of Medicine UAE University, Al Ain, Emirate of Abu Dhabi, United Arab EmiratesCorrespondence: Satish Chandrasekhar Nair, Department of Academic Affairs, Tawam Hospital, Al Ain, United Arab Emirates, Tel +97137074736, Email satchi2000@outlook.comIntroduction: Gastrointestinal bleeding in COVID-19-infection poses unique challenges to patients owing to the high risk of concomitant respiratory failure. However, endoscopic care providers are prone to transmission. This study aimed to understand the risk and management outcomes of gastrointestinal bleeding in COVID-19-infected patients.Methods: Data were abstracted from electronic patient medical records, using ICD 10 codes, and demographic and clinical data were collected, for COVID-19-infected patients who developed gastrointestinal (GI) bleeding. Complications related to COVID-19 infection and management outcomes of GI bleeding were studied. Statistically, descriptive analysis was used because of the small sample size.Results: Eighteen COVID-19-infected patients developed episodes of GI bleeding, yielding a prevalence of 0.45%. Their mean age was 74.8 years, 55.5% were female, and 66.6% of patients (n=12) had upper GI bleeding symptoms, predominantly melena (55.5%), followed by coffee ground nasogastric aspirates (n=2). Only two patients (11.11%) had episodes of lower GI bleeding, and the remaining four patients (22.2%) had recurrent acute anemia requiring blood transfusion. The Glasgow-Blatchford score (GBS) at presentation ranged between 6 to 16 (mean 8.8) and seven patients (38.8%) underwent endoscopic evaluation for GI bleeding. The predominant comorbid conditions included

Potato is a globally significant crop, crucial for food security and nutrition. Assessing vital nutritional traits is pivotal for enhancing nutritional value. However, traditional wet lab methods for the screening of large germplasms are time- and resource-intensive. To address this challenge, we used near-infrared reflectance spectroscopy (NIRS) for rapid trait estimation in diverse potato germplasms. It employs molecular absorption principles that use near-infrared sections of the electromagnetic spectrum for the precise and rapid determination of biochemical parameters and is non-destructive, enabling trait monitoring without sample compromise. We focused on modified partial least squares (MPLS)-based NIRS prediction models to assess eight key nutritional traits. Various mathematical treatments were executed by permutation and combinations for model calibration. The external validation prediction accuracy was based on the coefficient of determination (RSQexternal), the ratio of performance to deviation (RPD), and the low standard error of performance (SEP). Higher RSQexternal values of 0.937, 0.892, and 0.759 were obtained for protein, dry matter, and total phenols, respectively. Higher RPD values were found for protein (3.982), followed by dry matter (3.041) and total phenolics (2.000), which indicates the excellent predictability of the models. A paired t-test confirmed that the differences between laboratory and predicted values are non-significant. This study presents the first multi-trait NIRS prediction model for Indian potato germplasm. The developed NIRS model effectively predicted the remaining genotypes in this study, demonstrating its broad applicability. This work highlights the rapid screening potential of NIRS for potato germplasm, a valuable tool for identifying trait variations and refining breeding strategies, to ensure sustainable potato production in the face of climate change.

Insurance is a dynamic world with cut-throat competition among the insurers. Each insurer is constantly trying to get more customers to buy their products while trying to keep their costs to a minimum. However, since there is no singular factor that affects the demand for insurance in a country, a major factor that the insurers have control over is the claim settlement ratio. With better and faster claim settlement, it is assumed that customers will be more satisfied and thus more likely to buy and recommend the insurance products, thus boosting the sales of the insurers. This study aims to find the connection between these two factors to identify the relationship between them and to suggest changes that the insurers can implement to improve the demand for their product, through analysis using means such as Chi-Square and Regression.

Insurance is a dynamic world with cut-throat competition among the insurers. Each insurer is constantly trying to get more customers to buy their products while trying to keep their costs to a minimum. However, since there is no singular factor that affects the demand for insurance in a country, a major factor that the insurers have control over is the claim settlement ratio. With better and faster claim settlement, it is assumed that customers will be more satisfied and thus more likely to buy and recommend the insurance products, thus boosting the sales of the insurers. This study aims to find the connection between these two factors to identify the relationship between them and to suggest changes that the insurers can implement to improve the demand for their product, through analysis using means such as Chi-Square and Regression.

BackgroundProkinetics are a class of pharmacological drugs designed to improve gastrointestinal (GI) motility, either regionally or across the whole gut. Each drug has its merits and drawbacks, and based on current evidence as high-quality studies are limited, we have no clear recommendation on one class or other. However, there remains a large unmet need for both regionally selective and/or globally acting prokinetic drugs that work primarily intraluminally and are safe and without systemic side effects.PurposeHere, we describe the strengths and weaknesses of six classes of prokinetic drugs, including their pharmacokinetic properties, efficacy, safety and tolerability and potential indications.

The goal of field boundary delineation is to predict the polygonal boundaries and interiors of individual crop fields in overhead remotely sensed images (e.g., from satellites or drones). Automatic delineation of field boundaries is a necessary task for many real-world use cases in agriculture, such as estimating cultivated area in a region or predicting end-of-season yield in a field. Field boundary delineation can be framed as an instance segmentation problem, but presents unique research challenges compared to traditional computer vision datasets used for instance segmentation. The practical applicability of previous work is also limited by the assumption that a sufficiently-large labeled dataset is available where field boundary delineation models will be applied, which is not the reality for most regions (especially under-resourced regions such as Sub-Saharan Africa). We present an approach for segmentation of crop field boundaries in satellite images in regions lacking labeled data that uses multi-region transfer learning to adapt model weights for the target region. We show that our approach outperforms existing methods and that multi-region transfer learning substantially boosts performance for multiple model architectures. Our implementation and datasets are publicly available to enable use of the approach by end-users and serve as a benchmark for future work., Comment: Accepted for 2023 AAAI Workshop on AI to Accelerate Science and Engineering

Multi-Agent Path Finding (MAPF), which involves finding collision-free paths for multiple robots, is crucial in various applications. Lifelong MAPF, where targets are reassigned to agents as soon as they complete their initial targets, offers a more accurate approximation of real-world warehouse planning. In this paper, we present a novel mechanism named Caching-Augmented Lifelong MAPF (CAL-MAPF), designed to improve the performance of Lifelong MAPF. We have developed a new type of map grid called cache for temporary item storage and replacement, and created a locking mechanism to improve the planning solution's stability. A task assigner (TA) is designed for CAL-MAPF to allocate target locations to agents and control agent status in different situations. CAL-MAPF has been evaluated using various cache replacement policies and input task distributions. We have identified three main factors significantly impacting CAL-MAPF performance through experimentation: suitable input task distribution, high cache hit rate, and smooth traffic. In general, CAL-MAPF has demonstrated potential for performance improvements in certain task distributions, map and agent configurations.

COVID-19 pandemic has brought unprecedented challenges to the world, and vaccination has been a key strategy to combat the disease. Since Twitter is one of the most widely used public microblogging platforms, researchers have analysed COVID-19 vaccines and vaccination Twitter discourse to explore the conversational dynamics around the topic. While contributing to the crisis informatics literature, we curate a large-scale geotagged Twitter dataset, GeoCovaxTweets Extended, and explore the discourse through multiple spatiotemporal analyses. This dataset covers a longer time span of 38 months, from the announcement of the first vaccine to the availability of booster doses. Results show that 43.4% of the collected tweets, although containing phrases and keywords related to vaccines and vaccinations, were unrelated to the COVID-19 context. In total, 23.1% of the discussions on vaccines and vaccinations were classified as Pro, 16% as Hesitant, 11.4% as Anti, and 6.1% as Informative. The trend shifted towards Pro and Informative tweets globally as vaccination programs progressed, indicating a change in the public's perception of COVID-19 vaccines and vaccination. Furthermore, we explored the discourse based on account attributes, i.e., followers counts and tweet counts. Results show a significant pattern of discourse differences. Our findings highlight the potential of harnessing a large-scale geotagged Twitter dataset to understand global public health communication and to inform targeted interventions aimed at addressing vaccine hesitancy.

We present HiRA-Pro, a novel procedure to align, at high spatio-temporal resolutions, multimodal signals from real-world processes and systems that exhibit diverse transient, nonlinear stochastic dynamics, such as manufacturing machines. It is based on discerning and synchronizing the process signatures of salient kinematic and dynamic events in these disparate signals. HiRA-Pro addresses the challenge of aligning data with sub-millisecond phenomena, where traditional timestamp, external trigger, or clock-based alignment methods fall short. The effectiveness of HiRA-Pro is demonstrated in a smart manufacturing context, where it aligns data from 13+ channels acquired during 3D-printing and milling operations on an Optomec-LENS MTS 500 hybrid machine. The aligned data is then voxelized to generate 0.25 second aligned data chunks that correspond to physical voxels on the produced part. The superiority of HiRA-Pro is further showcased through case studies in additive manufacturing, demonstrating improved machine learning-based predictive performance due to precise multimodal data alignment. Specifically, testing classification accuracies improved by almost 35% with the application of HiRA-Pro, even with limited data, allowing for precise localization of artifacts. The paper also provides a comprehensive discussion on the proposed method, its applications, and comparative qualitative analysis with a few other alignment methods. HiRA-Pro achieves temporal-spatial resolutions of 10-1000 us and 100 um in order to generate datasets that register with physical voxels on the 3D-printed and milled part. These resolutions are at least an order of magnitude finer than the existing alignment methods that employ individual timestamps, statistical correlations, or common clocks, which achieve precision of hundreds of milliseconds.

Streaming applications are becoming widespread across an extensive range of business domains as an increasing number of sources continuously produce data that need to be processed and analysed in real time. Modern businesses are aggressively using streaming data to generate valuable knowledge that can be used to automate processes, help decision-making, optimize resource usage, and ultimately generate revenue for the organization. Despite their increased adoption and tangible benefits, support for the automated deployment and management of streaming applications is yet to emerge. Although a plethora of stream management systems have flooded the open source community in recent years, all of the existing frameworks demand a considerably challenging and lengthy effort from human operators to manually and continuously tune their configuration and deployment environment in order to reach and maintain the desired performance goals. To address these challenges, this article proposes a vision for creating Deep Reinforcement Learning (DRL)-based methods for transforming stream processing engines into self-managed serverless solutions. This will lead to an increase in productivity as engineers can focus on the actual development process, an increase in application performance potentially leading to reduced response times and more accurate and meaningful results, and a considerable decrease in operational costs for organizations., Comment: 21 pages, 10 figures

The amount of data being produced at every epoch of second is increasing every moment. Various sensors, cameras and smart gadgets produce continuous data throughout its installation. Processing and analyzing raw data at a cloud server faces several challenges such as bandwidth, congestion, latency, privacy and security. Fog computing brings computational resources closer to IoT that addresses some of these issues. These IoT devices have low computational capability, which is insufficient to train machine learning. Mining hidden patterns and inferential rules from continuously growing data is crucial for various applications. Due to growing privacy concerns, privacy preserving machine learning is another aspect that needs to be inculcated. In this paper, we have proposed a fog enabled distributed training architecture for machine learning tasks using resources constrained devices. The proposed architecture trains machine learning model on rapidly changing data using online learning. The network is inlined with privacy preserving federated learning training. Further, the learning capability of architecture is tested on a real world IIoT use case. We trained a neural network model for human position detection in IIoT setup on rapidly changing data., Comment: Conference paper accepted at BDA 2021