Search

In this paper, a multi-objective grey wolf optimization (GWO) algorithm based Bidirectional Long Short Term Memory (BiLSTM) network machine learning (ML) model is proposed for finding the optimum sizing of distributed generators (DGs) and shunt capacitors (SHCs) to enhance the performance of distribution systems at any desired load factor. The stochastic traits of evolutionary computing methods necessitate running the algorithm repeatedly to confirm the global optimum. In order to save utility engineers time and effort, this study introduces a BiLSTM network-based machine learning model to directly estimate the optimal values of DGs and SHCs, rather than relying on load flow estimates. At first, a multi-objective grey wolf optimizer determines the most suitable locations and capacities of DGs and SHCs at the unity load factor and the same locations are used to obtain optimum sizing of DGs and SHCs at other load factors also. The base case data sets consisting of substation apparent power, real power load, reactive power load, real power loss, reactive power loss and minimum node voltage at various load factors in per unit values are taken as input training data for the machine learning model. The optimal sizes of the DGs and SHCs for the corresponding load factors obtained using GWO algorithm are taken as target data sets in per unit values for the machine learning model. An adaptive moment estimation (adam) optimization approach is employed to train the BiLSTM ML model for identifying the ideal values of distributed generations and shunt capacitors at different load factors. The efficacy of the proposed ML-based sizing algorithm is demonstrated via simulation studies. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is growing rapidly in an exponential manner due to its versatility in technology. This has led to many challenges in securing the IoT environment. Devices in IoT environments are vulnerable to various cyberattacks. Botnet-based attacks are predominant and widespread in nature. Due to insufficient memory and computational power, the IoT environment cannot handle the botnet attack that affects security. Identifying intrusions in IoT environments is another challenge for researchers. Finding unknown patterns in the data generated through IoT networks helps improve security in the IoT environment. Machine learning (ML) is a platform that helps identify patterns in the provided data. In this study, we present our research on classifying incoming data from the IoT as malicious or benign using machine learning techniques. We propose an ML-based botnet attack detection framework for nine commercial IoT devices that primarily target BASHLITE and Mirai botnet attacks. Rigorous pragmatic research was conducted on the N-BaIoT dataset, which was extracted from realtime IoT devices connected to a network. Using this framework, the results have been depicted, which can efficiently detect botnet attacks and can also be applied to any other types of attacks. [ABSTRACT FROM AUTHOR]

Ovarian cancer ranks as the sixth deadliest cancer in the United States, underscoring the urgent need for a nonsurgical diagnostic assay with both high sensitivity and specificity. Such a breakthrough would greatly accelerate treatment and enhance the quality of life for affected individuals. In this research, an automated framework was created using optical coherence tomography (OCT) recordings to look for signs of ovarian cancer in transgenic mice. This study was carried out to aid in the remedying of this problem. In order to evaluate temporally ordered sequences of optical coherence tomography (OCT) tomograms, this advanced approach employs neural networks. Three distinct neural network-based strategies were employed, including a VGG-supported feed-forward network, a 3D convolutional neural network, and a convolutional LSTM (Long Short-Term Memory) network. Regarding the noise that is present in all OCT images, the results show that these models achieve high performance with no adjusting or feature creation needed. What a surprising discovery. The best model is a convolutional LSTM-based neural network, with a mean area under the curve (± standard error) of 0.86 ± 0.052. To our knowledge, no previous literature documents the use of machine learning to interpret depth-resolved OCT images of entire ovaries, hence this study represents an important first step in this direction. As a result, this study stands out as an innovative one. This diagnostic technique has enormous prospects for early identification and intervention in the case of this extremely deadly condition since it has the potential to be transferred from transgenic mice to human tissue. Transgenic mice are currently used as the only diagnostic tool for this disease. [ABSTRACT FROM AUTHOR]

The Spectroscopic Investigation of Nebular Gas (SING) is a near-ultraviolet (NUV) low-resolution spectrograph payload designed to operate in the NUV range, 1400 Å – 2700 Å, from a stable space platform. SING telescope has a primary aperture of 298 mm, feeding the light to the long-slit UV spectrograph. SING has a field of view (FOV) of 1 ∘ , achieving a spatial resolution of 1.33 arcminute and spectral resolution of 3.7 Å( R ∼ 600 ) at the central wavelength. SING employs a micro-channel plate (MCP) with a CMOS readout-based photon-counting detector. The instrument is designed to observe diffuse sources such as nebulae, supernova remnants, and the interstellar medium (ISM) to understand their chemistry. SING was selected by the United Nations Office for Outer Space Affairs to be hosted on the Chinese Space Station. The instrument will undergo qualification tests as per the launch requirements. In this paper, we describe the hardware design, optomechanical assembly, and calibration of the instrument. [ABSTRACT FROM AUTHOR]

Pancreatic intraepithelial neoplasias (PanINs) are the most common precursors of pancreatic cancer, but their small size and inaccessibility in humans make them challenging to study1. Critically, the number, dimensions and connectivity of human PanINs remain largely unknown, precluding important insights into early cancer development. Here, we provide a microanatomical survey of human PanINs by analysing 46 large samples of grossly normal human pancreas with a machine-learning pipeline for quantitative 3D histological reconstruction at single-cell resolution. To elucidate genetic relationships between and within PanINs, we developed a workflow in which 3D modelling guides multi-region microdissection and targeted and whole-exome sequencing. From these samples, we calculated a mean burden of 13 PanINs per cm3 and extrapolated that the normal intact adult pancreas harbours hundreds of PanINs, almost all with oncogenic KRAS hotspot mutations. We found that most PanINs originate as independent clones with distinct somatic mutation profiles. Some spatially continuous PanINs were found to contain multiple KRAS mutations; computational and in situ analyses demonstrated that different KRAS mutations localize to distinct cell subpopulations within these neoplasms, indicating their polyclonal origins. The extensive multifocality and genetic heterogeneity of PanINs raises important questions about mechanisms that drive precancer initiation and confer differential progression risk in the human pancreas. This detailed 3D genomic mapping of molecular alterations in human PanINs provides an empirical foundation for early detection and rational interception of pancreatic cancer.Quantitative multimodal 3D reconstruction of human pancreatic tissue at single-cell resolution reveals a high burden of multifocal, genetically heterogeneous pancreatic intraepithelial neoplasias in the normal adult pancreas. [ABSTRACT FROM AUTHOR]

The global GDP has witnessed a significant upswing, majorly due to the growth of the construction industry. Embracing the whole-life costing (WLC) approach, the construction sector strategically manages expenses across a construction project's life cycle. However, despite its widespread adoption, accurate cost forecasting remains a major challenge. The intricate interplay of various influencing factors has not been fully explored, leading to inaccurate cost estimations. A comprehensive understanding of specific factors and their interrelationships is crucial to address this issue. Therefore, it is imperative to conduct further research to identify and explore the subtle nuances of these factors that impact whole-life cost estimation. Our study fills this gap, analysing 51 factors from 84 papers across prominent repositories. We assess interrelationships using a systematic literature review and pairwise comparison as in the analytical hierarchy process. The International Construction Measurement Standards (ICMS) framework structures these relationships and is represented in the causal loop diagrams (CLDs). The pioneering CLDs are a notable contribution, illustrating interrelationships and polarities among the 51 WLC factors. Six reinforcing loops and one balancing loop provide valuable insights into their dynamic nature. Importantly, lower-level factors do not always directly connect with upper-level factors. Instead, they interact within the same level before linking to top-level factors. These findings are significant for professionals, such as cost estimators, quantity surveyors and scholars, offering a comprehensive understanding of the WLC system. [ABSTRACT FROM AUTHOR]

In the fields of autonomous navigation and vehicle safety, accurately predicting potential collision field points between moving objects is a significant challenge. A novel computing technique to enhance trajectory interception analysis is presented in this paper. Our objective is to develop a field model that can accurately forecast collision zones, improving road transportation safety and the use of autonomous cars. Our main contribution is a binary classification model called PCSMO (Prediction of Collision Scope between Moving Objects), which is based on zero-shot learning. Gann angles, which are typically 45 degrees, are used to analyze the trajectories of moving objects. This method is inspired by GANN (Gann Angle Numeric Nomenclature). Compared to earlier techniques, this model more accurately identifies potential collision collision interception zones. The technique computes Gann angles for trajectory analysis and extracts GPS coordinates of moving objects from video data using OpenCV. It offers a more sophisticated comprehension of object movement patterns and points of interception. To assess the precision, recall, F1-score, and prediction accuracy of our model, we employ 10-fold cross-validation. Comparing the PCSMO model to existing models, these metrics demonstrate how well the PCSMO model predicts potential collision zones. Our approach, we discovered, enhances trajectory analysis--a critical component of safer autonomous navigation systems. With potential applications in autonomous vehicle and UAV safety, the PCSMO model improves field interception classification. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to highlight the prominent cognitive biases that influence Lean practices in organisations that have a multi-cultural work environment which will aid the organisational managers and academics in enhancing the understanding of the human thought process and mitigate them suitably. Design/methodology/approach: A multiple case study was conducted in organisations that were previously committed to Lean practices and had a multi-cultural work environment. This research was conducted on five companies based on 99 in-depth semi-structured interviews and seven process observations that sought to establish the system-wide cognitive biases present in a multi-cultural Lean environment. Findings: The novel findings indicate that nine new biases influence Lean implementation and practices in a multi-cultural environment. This study also found strong connectivity between Lean practices and 45 previously identified biases that could affect positively or negatively the lean methodologies and their implementation. Biases were resilient enough that their influence on Lean in multi-cultural workplaces, even with transient populations, did not demonstrate cultural differentiation. Research limitations/implications: Like any qualitative research, constructivism and narrative analyses are subjected to understanding based on knowledge gained on the subject, and data may have been interpreted differently. Constructivist co-recreation of process scenarios based result limitations is therefore acknowledged. The interactive participation in exploring the knowledge sought after and interaction that could have a probable influence on the participant need to be acknowledged. However, the research design, multiple methods of data collection, generalisation based on data collection and analysis methods limit the effects of these and findings are reliable to a greater extent. Practical implications: The results can provide an enhanced understanding of biases and insights into a new managerial approach to take remedial steps on biases' influence on Lean practices that can result in improved productivity and well-being from a business process perspective. Understanding and mitigating the prominent biases can aid Lean manufacturing processes and support decision makers and line managers in improving lean methodologies' effectiveness and productivity. The biases can be negated and used to implement decisions with ease. The influence of biases and the model could be used as a basis to counter implementation barriers. Originality/value: To the best of the authors' knowledge, this is the first study that connects the cognitive perspectives of Lean business processes in a multi-cultural environment to identify the cognitive biases that influence Lean practices in organisations that were previously committed to Lean practices. The novel findings indicate that nine new biases and 45 previously identified biases influence Lean implementation and practices in a multi-cultural environment. The second novelty of this study shows the connection between cognitive biases, Lean implementation and practices in multi-cultural business processes. [ABSTRACT FROM AUTHOR]

Sleep is a key component of life to maintain our health, performance, safety and quality of life. In fact, sleep has been implicated in the optimal functioning of all organ systems – brain, heart, lung, metabolism, immune function, and hormonal balance too. One of the most common reasons for poor-quality sleep in children is a group of conditions termed sleep disordered breathing (SDB). Obstructive sleep apnea (OSA) is the most severe form of SDB. A good history and clinical examination is likely to reveal features of SDB including snoring, restless sleep, morning sleepiness, irritability or exhibit signs of hyperactivity. Examination may also reveal evidence of underlying pathology e.g., Craniofacial abnormalities, obesity and neuromuscular disorders that creates higher risk of developing SDB. Further investigation using polysomnography (PSG) is considered a gold-standard assessment of SDB and allows for scoring using Obstructive Apnoea-Hypopnea scale. Adenotonsillectomy is used as the first-line management in patients who otherwise have normal anatomy. Parents often approach their pediatricians with concerns regarding their child's sleeping habits and given the significant role sleep has on child development, it is essential that doctors are equipped to provide good care and advice for this population. This article aims to summarise presentation of SDB and common risk factors, investigations and management options to aid clinicians in managing SDB. [ABSTRACT FROM AUTHOR]

Doppler sodar measurements were made at the tropical Indian station, i.e., Gadanki (13.5° N, 79. 2° E). According to wind climatologies, the wind pattern changes from month to month. In July and August, the predominant wind direction during the monsoon season was the southwest. In September, it was the northwest and south. While the winds in November came from the northeast, they came from the northwest and southwest in October. The winds in December were out of the southeast. The diurnal cycle of winds at 60-m above the ground was visible, with disturbed wind directions in September and October. This may be connected to the Indian subcontinent's southeastern monsoon recession. To better understand the monsoon circulation on a monthly basis, the present work is innovative in that it uses high-resolution winds measured using the Doppler sodar at the atmospheric boundary layer. The convergence of a sea breeze and the background wind might result in a sudden change in wind direction, and forecasting such a chaotic atmospheric event is crucial in the aviation sector. As a result, the wind shear that is produced may pose a serious threat to airplanes that are landing. In the current study, we present a few cases of sea breeze intrusions. The physics underlying these intrusions may help modelers better understand these chaotic wind structures and use them as inputs in their models. Based on surface-based atmospheric characteristics, there have been two reports of deep sea breeze intrusions that we report in this research. The sea breeze days were marked by substantial (moderate) drops in temperature (dewpoint temperatures) and increased wind speed and relative humidity. The India Meteorological Department (IMD) rainfall data showed a rise in precipitation over this location on 23 July (4.8 mm) and 24 July (9.5 mm) when sea breeze intrusions over Gadanki were noticed. Sea breeze intrusions could have brought precipitation (intrusion-laden precipitation) to this area due to conducive meteorological conditions. A simple schematic model is proposed through a diagrammatic illustration that explains how a sea breeze triggers precipitation over adjacent locations to the seacoast. The skew-T log-P diagrams have been drawn using the balloon-borne radiosonde measured atmospheric data over Chennai (a nearby location to Gadanki) to examine the thermodynamic parameters to gain insights into the underlying mechanisms and meteorological conditions during sea breeze intrusion events. It is found that the convective available potential energy (CAPE), which is presented as a thermos diagram, was associated with large values on 23 July and 24 July (898 J/kg and 1250 J/kg), which could have triggered thunderstorms over Chennai. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to address the pressing problem of prediction concerning shipment times of therapeutics, diagnostics and vaccines during the ongoing COVID-19 pandemic using a novel artificial intelligence (AI) and machine learning (ML) approach. Design/methodology/approach: The present study used organic real-world therapeutic supplies data of over 3 million shipments collected during the COVID-19 pandemic through a large real-world e-pharmacy. The researchers built various ML multiclass classification models, namely, random forest (RF), extra trees (XRT), decision tree (DT), multilayer perceptron (MLP), XGBoost (XGB), CatBoost (CB), linear stochastic gradient descent (SGD) and the linear Naïve Bayes (NB) and trained them on striped datasets of (source, destination, shipper) triplets. The study stacked the base models and built stacked meta-models. Subsequently, the researchers built a model zoo with a combination of the base models and stacked meta-models trained on these striped datasets. The study used 10-fold cross-validation (CV) for performance evaluation. Findings: The findings reveal that the turn-around-time provided by therapeutic supply logistics providers is only 62.91% accurate when compared to reality. In contrast, the solution provided in this study is up to 93.5% accurate compared to reality, resulting in up to 48.62% improvement, with a clear trend of more historic data and better performance growing each week. Research limitations/implications: The implication of the study has shown the efficacy of ML model zoo with a combination of base models and stacked meta-models trained on striped datasets of (source, destination and shipper) triplets for predicting the shipment times of therapeutics, diagnostics and vaccines in the e-pharmacy supply chain. Originality/value: The novelty of the study is on the real-world e-pharmacy supply chain under post-COVID-19 lockdown conditions and has come up with a novel ML ensemble stacking based model zoo to make predictions on the shipment times of therapeutics. Through this work, it is assumed that there will be greater adoption of AI and ML techniques in shipment time prediction of therapeutics in the logistics industry in the pandemic situations. [ABSTRACT FROM AUTHOR]

Lead is considered one of the most prevalent environmental and biologically hazardous toxicants among metallic elements. It severely affects human health and especially the male reproductive system by causing reproductive organ dysfunction leading to infertility. Natural dietary antioxidants are studied for their ability to ameliorate the cells' miscellaneous damage. The current study was designed to explore the effect of Vitis vinifera (Linn.) (grape) seed extract (GSE) on lead acetate (LA)‐induced oxidative damage on testis and sperm quality in rats. Twenty‐four male Wistar rats were allocated into four equal groups. Group I received distilled water; Group II received LA 50 mg/kg body weight (Bw); Group III received LA 50 mg/kg + GSE 200 mg/kg Bw; and Group IV received LA 50 mg/kg + GSE 400 mg/kg Bw (orally once a day for 28 days). After 28 days, levels of malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and reduced glutathione (GSH) were estimated in the testicular tissue. The cauda of the epididymis was used to study the characteristics of the sperm, such as sperm count, motility, viability, tail‐coiled sperm, and morphology. The hematoxylin and eosin staining method was used to study histomorphology. Results revealed that LA induction significantly increased MDA concentration and decreased the levels of SOD, CAT, GPx, and GSH. It also reduced the weight of the testis and testosterone hormone levels, declined the quality of sperm, and increased morphologically abnormal sperm. Moreover, LA severely altered the histomorphology of the testis, such as atrophy of the seminiferous tubule, degeneration of germinal epithelium, and increased interstitial space, compared with the control group. In Groups III and IV, coadministration of LA with GSE reduced the MDA concentration, preserved the antioxidant enzyme system and testosterone hormonal levels, restored the sperm characteristics, reduced the abnormal sperm, and improved histomorphological alterations in the testis compared with the LA‐induced group. In conclusion, GSE has a potent natural antioxidant that provides promising protection against LA‐induced testicular oxidative damage on testis and sperm quality in rats. Research highlights: Phytoscreening analysis of GSE revealed that the antioxidants present, including proanthocyanidins, phenols, flavonoids, saponins, tannins, glycosides, and triterpenoids, were identified as having the most effect on LA‐induced testicular toxicity and were thus considered as further ameliorating agents for lead acetate‐induced testicular alterations. [ABSTRACT FROM AUTHOR]

Background: Health care workers (HCWs) are at risk of acquiring tuberculosis (TB) infection and disease due to occupational exposure. But there are no national guidelines on routine screening for TB (active case finding (ACF)) among HCWs and understand its implementation and feasibility. Methods: This study was conducted among HCWs in a teaching hospital in India. We used symptom screening to identify those with presumptive TB and were further evaluated for diagnosis of TB. Results: A total of 1,001 HCWs were screened over a period of 18 months. In our study, 51 (5.1%) HCWs were found to have presumptive TB and on further evaluation, 5 (0.5%) of these patients were diagnosed with active TB. The number needed to screen (NNS) for one active TB among the HCWs was 200. Alcohol use was significantly associated with both presumptive TB (P = 0.037) and active TB (P = 0.035) among HCWs, and exposure to active TB patients (P = 0.014) in the family and workplace and increased frequency of exposures (P = <0.001) were associated with presumptive TB. Conclusion: ACF for TB among HCWs had a good yield in our study. ACF utilizing routine national TB program guidelines is feasible to be implemented among HCWs to aid in the early diagnosis and treatment of TB in this high-risk group. [ABSTRACT FROM AUTHOR]

In this paper, a Pareto multiobjective and grasshopper optimization algorithm (GOA) based optimum proportional–integral–derivative (P–I–D) controller design is proposed for improving the vehicle active suspension system dynamics under road disturbance conditions. The Pareto objectives considered are minimization of sprung mass suspension deflection, tyre deflection, sprung mass acceleration minimization and eigenvalue-based objective function. State space model for quarter vehicle active suspension system with P–I–D controller is developed for analyzing the stability and dynamic performance of the system. The sinusoidal-based bump road disturbances are used for testing the robustness of the proposed control technique. Simulation results have been presented to show the advantage of the proposed Pareto multiobjective and GOA-based P–I–D controller over the weighted multiobjective and genetic algorithm-based P–I–D controller in terms of stability and dynamics of the active suspension system. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to present a large-scale real-world comparative study using pre-COVID lockdown data versus post-COVID lockdown data on predicting shipment times of therapeutic supplies in e-pharmacy supply chains and show that our proposed methodology is robust to lockdown effects. Design/methodology/approach: The researchers used organic data of over 5.9 million records of therapeutic shipments, with 2.87 million records collected pre-COVID lockdown and 3.03 million records collected post-COVID lockdown. The researchers built various Machine Learning (ML) classifier models on the two datasets, namely, Random Forest (RF), Extra Trees (XRT), Decision Tree (DT), Multi-Layer Perceptron (MLP), XGBoost (XGB), CatBoost (CB), Linear Stochastic Gradient Descent (SGD) and the Linear Naïve Bayes (NB). Then, the researchers stacked these base models and built meta models on top of them. Further, the researchers performed a detailed comparison of the performances of ML models on pre-COVID lockdown and post-COVID lockdown datasets. Findings: The proposed approach attains performance of 93.5% on real-world post-COVID lockdown data and 91.35% on real-world pre-COVID lockdown data. In contrast, the turn-around times (TAT) provided by therapeutic supply logistics providers are 62.91% accurate compared to reality in post-COVID lockdown times and 73.68% accurate compared to reality pre-COVID lockdown times. Hence, it is clear that while the TAT provided by logistics providers has deteriorated in the post-pandemic business climate, the proposed method is robust to handle pandemic lockdown effects on e-pharmacy supply chains. Research limitations/implications: The implication of the study provides a novel ML-based framework for predicting the shipment times of therapeutics, diagnostics and vaccines, and it is robust to COVID-19 lockdown effects. Practical implications: E-pharmacy companies can readily adopt the proposed approach to enhance their supply chain management (SCM) capabilities and build resilience during COVID lockdown times. Originality/value: The present study is one of the first to perform a large-scale real-world comparative analysis on predicting therapeutic supply shipment times in the e-pharmacy supply chain with novel ML ensemble stacking, obtaining robust results in these COVID lockdown times. [ABSTRACT FROM AUTHOR]

Growing demand for energy and concerns about environmental pollution has increased the use of renewable energy sources for electricity generation. Among all the renewable energy sources, solar energy is considered the most popular because of its huge benefits. This paper addresses two different problems with using photovoltaic (PV) systems in different applications. One of which is poor tracking performance, especially under partially shaded conditions (PSC). Therefore for global maximum power point (GMPP) tracking, a swarm intelligence-based maximum power point tracking (MPPT) method is used, which includes a particle swarm optimization (PSO) algorithm under the PSC, thereby improving the tracking efficiency of the PV system. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to highlight the system-wide potential relationships between forms of human bias, selected Lean tools and types of waste in a manufacturing process. Design/methodology/approach: A longitudinal single-site ethnographic case study using digital processing to make a material receiving process Lean was adopted. An inherent knowledge process with internal stakeholders in a stimulated situation alongside process requirements was performed to achieve quality data collection. The results of the narrative analysis and process observation, combined with a literature review identified widely used Lean tools, wastes and biases that produced a model for the relationships. Findings: The study established the relationships between bias, Lean tools and wastes which enabled 97.6% error reduction, improved on-time accounting and eliminated three working hours per day. These savings resulted in seven employees being redeployed to new areas with delivery time for products reduced by seven days. Research limitations/implications: The single site case study with a supporting literature survey underpinning the model would benefit from testing the model in application to different industries and locations. Practical implications: Application of the model can identify potential relationships between a group of human biases, 25 Lean tools and 10 types of wastes in Lean manufacturing processes that support decision makers and line managers in productivity improvement. The model can be used to identify potential relationships between forms of human biases, Lean tools and types of wastes in Lean manufacturing processes and take suitable remedial actions. The influence of biases and the model could be used as a basis to counter implementation barriers and reduce system-wide wastes. Originality/value: To the best of the authors' knowledge, this is the first study that connects the cognitive perspectives of Lean business processes with waste production and human biases. As part of the process, a relationship model is derived. [ABSTRACT FROM AUTHOR]

Summary: In this article, a novel and compact multiband quad port asymmetric coplanar strip‐fed triangular lamp post shaped printed multiple‐input and multiple‐output (MIMO) antenna has been presented. The proposed MIMO antenna is designed and developed on a FR‐4 (εr = 4.4) dielectric (40 × 40 × 1.6) mm3. The proposed MIMO antenna utilizes the pattern diversity technique to obtain the desired isolation among closely spaced radiators. Simulated and measured results indicate that |S11| of proposed lamp post shaped MIMO antenna array < −10 dB, that assures the operation in three frequency bands, namely, (2.27–2.42), (3.38–3.62), and (4.5–6.23) GHz, which are the operating bands of WiBro, Bluetooth, WiMAX, and WLAN/WiMAX, respectively. A peak radiation gain of 5.1 dBi is observed alongside with a maximal radiation efficiency close to 92% in operating band for the proposed MIMO antenna. A minimal isolation of −18 dB between the antenna elements has been observed in all three operating bands, which is necessary for improved performance to achieve high data transfer rates. Performance critical diversity characteristics such as diversity gain (DG), envelope correlation coefficient (ECC), total active reflection coefficient (TARC), mean effective gain (MEG), and channel capacity (CC) of the compact proposed lamp post shaped MIMO antenna have been calculated and found that the correlation coefficient was <0.001 with higher diversity gain > 9.95 dB and achieved better CCL < 0.4 bits/s/Hz in the respective operating bands. With these results, the proposed triangular lamp post shaped MIMO array is suitable for high data rate applications, which is one of the main concerns of 5G and beyond networks. [ABSTRACT FROM AUTHOR]

This paper presents a new hybrid passive control device, consisting of a viscoelastic and a friction damper connected in parallel, to mitigate the effects of wind and seismic events. The two components are synergized with the aid of a novel locking mechanism, which enables the action of one or both the components depending upon the device deformation. This provides an innovative two-phase energy dissipation capacity, and exploiting the individual strengths of the two dampers together. The response of a single degree of freedom (SDOF) hybrid damped system is represented in terms of a linear system using equivalent linearization technique, which includes all associated parameters such as the added stiffness, the added damping and the locking mechanism. In order to ascertain the influence of various parameters of the hybrid device, normalized force and normalized displacement are defined in terms of linear SDOF hybrid damped system and further used to obtain force reduction factor for multi degree freedom (MDOF) system with hybrid device. The proposed design methodology of controlling the structural response using the hybrid device is then applied on a six-story reinforced concrete (RC) building. The response of the conventional moment resisting frame (MRF) system and moment resisting frame system with hybrid device (MRHDF) are compared using the nonlinear time history analysis. The performance of the MRHDF system is found to be superior than the MRF system. The hybrid device can effectively reduce the dynamic response of the building, especially in terms of inter story drift, residual drift, base shear and floor acceleration. In addition the proposed design methodology is very simple as compared to the response modification factor approach. This configuration of hybrid device shows improved performance for meeting multiple objectives under wind/seismic events of real-life structures. [ABSTRACT FROM AUTHOR]

Asthma is the most common disease of childhood globally and acute asthma is the most significant risk factor for asthma-related death and chronic complications. This article will aim to synthesize the most up-to-date research and translate it into a more practical guide to managing acute asthma on a more daily basis. The use of clinical severity score is reviewed alongside the use of history and clinical findings in making objective assessments of patients presenting with acute asthma. Practical evidence-based pathways and a stepwise approach are provided for management of acute asthma in the home, outpatient, emergency, and intensive care settings. In doing so, popular myths are dispelled and practices in relation to management of acute asthma and use of asthma related medications are clarified. Having a standardized approach to management of acute asthma will bring us one step closer to reducing exacerbations and achieving the goal of having zero tolerance towards exacerbations. [ABSTRACT FROM AUTHOR]

This article presents, an ACS-fed compact Trophy shaped four-port multiband MIMO antenna system for various wireless applications namely 2.3 GHz WiBro, WiMAX, and WLAN respectively. The proposed MIMO antenna structure has been etched on a cost affordable FR-4 substrate (εr = 4.4 and loss tangent = 0.02) with dimensions of 50 × 50 × 1.6 mm3. Mutual coupling reduction between the radiators has been achieved by placing the elements orthogonal to each other. With all these arrangements the ACS MIMO system operates with a peak gain of 4 dB with minimum isolation below − 17 dB. The proposed antenna operates in the frequency bands of (2.25–2.42, 3.36–3.72, 5.0–6.5) GHz with an ECC < 0.001 and channel capacity loss < 0.4 bps/Hz. Various parameters like DG, TARC, MEG, which are used to check diversity performance have been calculated and presented in the article. [ABSTRACT FROM AUTHOR]

Tofacitinib has an important role in pediatric rapidly progressive interstitial lung disease (ILD) associated with juvenile dermatomyositis (JDM), an otherwise potentially fatal condition. It may be useful in induction of remission and can be used safely to maintain remission. Serum ferritin and interleukin‐18 are useful markers for tracking activity and response of JDM‐associated ILD. [ABSTRACT FROM AUTHOR]

The most possible alpha-accompanied ternary fission fragment of 217-219Ac are studied using Coulomb and proximity potential model. We have studied driving potential (V-Q), logarithmic half-lives and relative yield of all possible fission fragments. From the present work, the minimum driving potential, maximum relative yield and minimum half-lives are observed for the fragment combination of 4He+209-211Ac+4He for the nuclei 217-219Ac. Hence, this fission fragment combination is considered as most possible fission fragments due to presence of doubly magic nuclei. This study is important in near future experiments. [ABSTRACT FROM AUTHOR]

Schwannomas are the most common tumor of peripheral nerves. It comprises 1 to 2% of total thoracic tumor. Posterior mediastinum is the most common site in thorax. Hereby we are reporting two cases of schwannoma with different sites of origin. The classical presentation of schwannoma is an asymptomatic mass found on chest radiograph. This tumor is usually benign and slow growing. Imaging followed by histopathological examination is key to the diagnosis of this neoplasm. Resection of tumor cure the disease. [ABSTRACT FROM AUTHOR]

Background: The natural history of childhood rhinitis is not well described. Objective: This study aimed to identify different rhinitis trajectories in early childhood and their predictors and allergic associations. Methods: Rhinitis symptoms were ascertained prospectively from birth until 6 years using standardized questionnaires in 772 participants. Rhinitis was defined as one or more episodes of sneezing, runny and/or blocked nose >2 weeks duration. Latent trajectories were identified using group‐based modelling, and their predictive risk factors and allergic associations were examined. Results: Three rhinitis trajectory groups were identified: 7.6% (n = 59) were termed early transient rhinitis, 8.6% (n = 66) late transient rhinitis, and 6.6% (n = 51) persistent rhinitis. The remaining 77.2% (n = 596) were classified as non‐rhinitis/reference group. Early transient rhinitis subjects were more likely of Indian ethnicity, had siblings, reported childcare attendance, early wheezing and eczema in the first 3 years of life. Late transient rhinitis was associated with antenatal exposure to smoking, higher maternal education levels, and wheezing at age 36‐72 months. Persistent rhinitis was associated with male gender, paternal and maternal history of atopy, eczema, and house dust mite sensitization. Conclusions & Clinical Relevance: Risk factors for early transient rhinitis involve a combination of genetic and early environmental exposures, whereas late transient rhinitis may relate to maternal factors and early respiratory infections independent of atopy. In contrast, persistent rhinitis is strongly associated with atopic risk and likely represents the typical trajectory associated with allergic disorders. Allergic rhinitis symptoms may commence as early as the first year of life and may inform development of early interventive strategies. [ABSTRACT FROM AUTHOR]

Primary pulmonary lymphoma (PPL) is a rare clonal proliferation of lymphoid tissue involving one or both lungs. It is of two types, B-cell and T-cell lymphomas among which T-cell lymphoma is a rare entity and it is sparsely considered as a differential diagnosis in neoplastic lesions of the lung. Here, we are reporting a case of primary pulmonary T-cell lymphoma. PPL is a rare disease and can present with nonspecific symptoms. Radiologically, it can easily be confused with more common malignancies such as bronchogenic carcinoma with or without metastases. PPL carries different therapeutic and prognostic implications. Therefore, physicians should make every effort to achieve histopathological diagnosis before prognosticating a patient presenting with lung cancer. [ABSTRACT FROM AUTHOR]

Melioidosis is caused by an environmental Gram‐negative bacilli Burkholderia pseudomallei. Diabetes mellitus, occupational exposure to soil and water, pre‐existing renal diseases and thalassemia are significant independent risk factors for melioidosis. A 30‐year‐old male carpenter and smoker had a history of accidental aspiration of foreign body 2 months prior. On presentation, he had cough with expectoration and low‐grade intermittent fever for 1 month. His chest x‐ray displayed left lower zone consolidation with cavitation and presence of foreign body in the left lower lobe bronchus. Bronchoalveolar lavage inoculated onto 5% sheep blood agar and MacConkey agar grew B. pseudomallei. Melioidosis due to foreign body aspiration is rare. To the best of our knowledge, there have not been reports of melioidosis infection associated with foreign body inhalation. Hence, pulmonary melioidosis can be considered as a differential diagnosis in cases of foreign body with secondary infection even in immunocompetent host. [ABSTRACT FROM AUTHOR]

To analyse the postoperative hearing results of patients undergoing type III tympanoplasty using sculptured homologous spur cartilage. This prospective study included 156 patients of chronic otitis media (COM), between the ages 10–60 years. All cases underwent type III tympanoplasty with ossiculoplasty using homologous spur cartilage. The study sample of 156 patients contained 107 cases of mucosal type and 49 cases of squamosal type COM. Type III A tympanoplasty was done for 71 cases and type III B tympanoplasty was done for 85. Pure tone audiometry (PTA) was done pre and postoperatively, in all the cases. The patients were followed up for 6 months postoperatively. The average preoperative mean air–bone–gap (ABG) was 43.64 dB, whereas in type III A cases it was 39.7 dB and in type III B it was 46.9 dB. The mean ABG at 6th month follow up was 18.9 dB in the study group. In type III A cases, mean ABG was 15.2 dB and in type III B cases it was 22.11 dB. Homogenous spur cartilage graft can be used for ossicular chain reconstruction with the advantage of very low extrusion rate, technically easy to perform with less risk of residual disease. [ABSTRACT FROM AUTHOR]

The airway of a child can be easily obstructed because of its small size and there are myriad conditions that may obstruct it. Though asthma is the most common condition causing reversible obstruction of the airway; there are a large number of conditions which can obstruct the airway both reversibly and irreversibly. These asthma mimics can present as clinical problems from the neonatal period through adolescence. This article presents an overview of the clinical situations that must be kept in mind when the child presents with subtly unusual clinical features or a deviant course. This is followed by a brief description of the common mimickers along with clinical clues to their diagnosis. Clinicians will need a high index of suspicion for diagnosing these conditions. Prompt recognition and optimal case management and referral will ensure the best outcomes in these children. [ABSTRACT FROM AUTHOR]

The interlinked cycle (IC) structure that generalizes cycles and cliques was defined by Thapa, Ong, and Johnson. Interlinked-cycle-cover (ICC) scheme that leverages IC structures in digraphs to construct scalar linear index codes was proposed. A class of infinitely many digraphs, where the proposed scalar linear codes based on ICC scheme are optimal were characterized by Thapa et. al. In this paper, we provide an addition to this class by providing optimal length index codes for IC structures with one cycle among non-inner vertex set. [ABSTRACT FROM PUBLISHER]

Introduction: Acute pancreatitis is the sudden onset of reversible inflammation of pancreas in which pancreatic enzymes cause autodigestion of the gland. Acute pancreatitis varies from mild (mortality rate <1%; usually resolves in several days) to severe (mortality rate can be up to 30%). Aim: The aim of the study was to study the clinical profile, detection of amylase, lipase for diagnosis, progression to pancreatic necrosis and chronic pancreatitis, and Neutrophil Lymphocyte Ratio (NLR) in prognostication of outcome. Materials and Methods: The retrospective study analysed data of patients admitted with acute pancreatitis or presented to outpatient department (previous medical records) with pancreatitis between January 2011 and September 2016. A total of 339 patients fulfilled the clinical and diagnostic criteria of pancreatitis, of which 252 patients had acute pancreatitis and 78 patients had chronic pancreatitis. Nine patients of acute pancreatitis group were excluded due to lack of complete data and consents. Results: Acute pancreatitis is about six times more common in males than females. The sensitivity and specificity of lipase in our study was 98.41% and 99.19% respectively. The sensitivity and specificity of amylase in our study for the diagnosis of acute pancreatitis was 86.90% and 98.79% respectively. In severe acute pancreatitis, the NLR remains well above normal level for 3-4 days with peak in first or second day indicating ongoing inflammatory process. Conclusion: Serum lipase levels are more sensitive and specific than serum amylase levels and some cases of pancreatitis can be missed if serum amylase alone was measured. Dynamic NLR monitoring i.e., neutrophilia and lymphopenia is a cost effective, easy to perform, repeatable and accurate marker for prognosis in severe acute pancreatitis. [ABSTRACT FROM AUTHOR]

Heavy rainfall triggered landslides are on the rise along the Western Ghats making it a matter of priority to identify landslide-prone areas well in advance. The present effort is aimed at identifying landslide susceptible villages (LSV) around the Kalsubai region of Deccan volcanic province (DVP), Maharashtra, India from 8 weighted landslide parameters- rainfall, slope, lithology, land use and land cover (LULC), soil properties, relative relief, aspect and lineament. These parameters were combined with advanced remote sensing (RS) data and processed in geographical information system (GIS) as well as in image processing software, which are an integral part of geospatial techniques. Out of the total 59 villages, the study identified 9 villages are situated in very high, 13 in high, 12 in moderate, 11 in low and 14 in very low risk zones. Our data reveals incessant heavy rains and steep slopes are the dominant factors in triggering landslides, exacerbated by anthropogenic activity prevalent in the study area. The spatial and non-spatial database created will help to take effective steps in preventing and/or mitigating landslide disasters in the study area. The methodology can be applied to identify other landslide prone areas in a cost effective way. [ABSTRACT FROM AUTHOR]

Posterior reversible encephalopathy syndrome (PRES) is a clinico-radiological syndrome characterized by a headache, seizures, altered mental status and visual loss and characterized by white matter vasogenic edema affecting the posterior occipital and parietal lobes of the brain predominantly. This clinical syndrome is increasingly recognized due to improvement and availability of brain imaging specifically magnetic resonance imaging (MRI). A 35-year-old female with the history of unsafe abortion and massive blood transfusion 10 days ago was brought to the emergency room with three episodes of generalized tonic-clonic seizures, urinary incontinence and altered sensorium since 3 hours. MRI brain showed bilateral occipital, parietal, frontal cortex and subcortical white matter T2/Fluid-attenuated inversion recovery hyperintensities, suggestive of PRES. The patient improved after management with intravenous fluids, antibiotics, antiepileptics and monitoring of blood pressure. If recognized and treated early, the clinical syndrome commonly resolves within a week. PRES can be a major problem in rapid and massive blood transfusion. A high index of suspicion and prompt treatment can reduce morbidity, mortality and pave the path for early recovery. [ABSTRACT FROM AUTHOR]

Malakoplakia is an unusual inflammatory disease with uncertain pathogenesis affecting any organ in the body, but predominantly genitourinary tract, with specific predilection to the bladder. We report a rare case of isolated malakoplakia of the urachus in a 29-year-old male patient who presented with lower urinary tract symptoms without any hematuria. Investigations revealed sterile pyuria with no bacterial growth in urine. Radiological investigations revealed a mass in the urachal region. The patient underwent cystoscopy with biopsy followed by pelvic lymph node dissection and partial cystectomy with excision of the urachal mass. Histopathological examination of the mass revealed malakoplakia. Postoperative course was uneventful. To the best of our knowledge, this is the first ever case report of isolated urachal malakoplakia without any concomitant malignancy or bladder involvement reported in our country and one of the very few reported worldwide. [ABSTRACT FROM AUTHOR]

Dengue fever is a mosquito-borne arthropod-borne viral (arboviral) tropical disease in humans affecting 50-528 million people worldwide. The acute abdominal complications of dengue fever are acute appendicitis, acute pancreatitis, acute acalculous cholecystitis and non-specific peritonitis. Acute pancreatitis with new onset diabetes in dengue shock syndrome (DSS) is very rarely reported. We describe a case of 30-year-old man admitted in intensive care unit and was diagnosed with DSS with RT-PCR, NS1 antigen and dengue IgM antibody being positive. Abdominal ultrasound and computerized tomography confirmed acute pancreatitis. Patient required insulin after recovery. Diabetes mellitus caused by DSS is underreported and lack of awareness may increase mortality and morbidity. [ABSTRACT FROM AUTHOR]

Objective: To develop the UV-spectrophotometric method and to apply the Chemometric designs to the developed method for the simultaneous estimation of Atorvastatin calcium (ATR) and Aspirin (ASP) in intact capsule dosage form without further extraction. Methods: The UV-Spectrophotometric method was developed by using methanol as solvent for both the drugs and the data generated from the absorption spectra was mined by two Chemometric designs which were based on the principles of linear regression analysis method (LRC) and Crammer's matrix method (CRM). The wavelengths selected for linear regression analysis and crammers'matrix methods were 245 nm (wavelength of maximum absorption; λmax of ATR) and 275 nm (wavelength of maximum absorption; λmax of ASP). Results: Both the methods hold good linearity for ATR from 4-20 µg/ml and for ASP from 20-120 µg/ml with regression coefficient values of 0.9999 and 0.9991 respectively. The intraday and inter-day precision was found to be less than 2% RSD. The percentage recovery was in the range of 100.1-102.65 for Atorvastatin calcium and 99.95-101.15 for Aspirin by both the methods. The percentage assay was found to be 102.52 for ATR and 98.9 for ASP by LRC method and 101.62 for ATR and 98.84 for ASP by CRM method. Conclusion: The developed methods neither require any cumbersome separation procedure nor complex derivatization procedures for the analysis of the two drugs and moreover they are effective in minimizing the errors in analysis, simple and economical. [ABSTRACT FROM AUTHOR]

Neuromyelitis optica (NMO or Devic's syndrome) is a rare demyelinating disease of the CNS that predominantly affects the spinal cord and optic nerves and sharesmany clinical and radiological featureswithmultiple sclerosis (MS). The association of NMOwith autoimmune thyroiditis has been reported very rarely. Early differentiation between NMO and MS is very important because they have different natural courses and treatment regimens. We report a case regarding a 53-year-oldwomanwhowas admitted initially with hiccups and paraesthesias, but was not evaluated during first two episodes and presented with severe progression of NMO. Patient was found to have autoimmune thyroiditis with lymphocytic infiltration of thyroid which progressed to hypothyroidism. NMO was diagnosed with seropositivity for NMO-IgG and longitudinally extensive spinal cord lesions (three or more spinal segments). Patient poorly responded to treatment due to the lack of early diagnosis and aggressive immunosuppressant therapy. [ABSTRACT FROM AUTHOR]