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Abstract Glutathione Peroxidase 1 (GPx1) gene has been reported for its role in cellular redox homeostasis, and the dysregulation of its expression is linked with the progression of diverse cancers. Non-synonymous single nucleotide polymorphism (nsSNPs) have been emerged as the crucial factors, playing their role in GPx1 overexpression. To understand the deleterious mutational effects on the structure and function of GPx1 enzyme, we delved deeper into the exploration of possibly damaging nsSNPs using in-silico based approaches. Eight widely utilized computational tools were employed to roughly shortlist the deleterious nsSNPs. Their damaging effects on structure and function of the genes were evaluated by using different bioinformatics tools. Subsequently, the three final proposed deleterious mutants including mutations rs373838463, rs2107818892, and rs763687242, were docked with their reported binder, TNF receptor-associated factor 2 (TRAF2). The lowest binding affinity and stability of the docked mutant complexes as compared to the wild type GPx1 were validated by molecular dynamic simulation. Finally, the comparison of RMSD, RMSF, RoG and hydrogen bond analyses between wild-type and mutant’s complexes validated the deleterious effects of proposed nsSNPs. This study successfully identified and verified the possibly damaging nsSNPs in GPx1 enzyme, which may be linked the progression of various types of cancer. Our findings underscore the value of in-silico approaches in mutational analysis and encourage further preclinical and clinical trials.

Abstract Background 17.9 million deaths worldwide were attributable to cardiovascular diseases. Basic life support is one of the crucial strategies that could increase chances of cardiac arrest victims’ survival rate by nurses and other healthcare providers. Aim The aims of this study was to examine the retention of the BLS knowledge among nurses in Palestine. Methods A descriptive cross-sectional design was used to collect data from 108 nurses between February 2022 and April 2022 from two AHA-ITCs in Palestine. The instrument consisted of two sections; demographics and knowledge test which was developed by the researcher and contain a written examination containing 25 multiple-choice questions. Results Out of 160 distributed questionnaires, 108 were completed by nurses as a convenience sampling technique. Over half of the participants were male (54.6%), and the majority had a bachelor’s degree in nursing (75%). Analysis identified that there was a significant difference (t (107) = 18.02, p

Abstract The industrial sector of Pakistan is currently facing severe load-shedding, which ultimately affects its unit production. The greater dependency on conventional energy resources (Thermal, Nuclear, etc.) results in higher production costs and environmental pollution. A sustainable, cost-effective, and environment-friendly solution can help the industrial growth of Pakistan. This article proposes an optimal hybrid energy system (HES) for the industrial sector of Pakistan to overcome the mentioned challenges. The proposed HES is developed in HOMER Pro. Three different energy cases (Case I: Existing energy system including a utility grid and diesel generator, Case II: On-grid Biogas system, and Case III: On-grid PV system with batteries) are considered for the Gourmet food Industry in the Sundar Industrial estate, Pakistan. The Load profile of the selected site was calculated through on-site visits and data provided by the designated utility grid feeder. The analysis shows that Case III is more effective than other cases, indicating reduced Net Present Cost (NPC), Cost of Energy (COE), and Operating Cost (OC) to $ 19.2 million, $0.034/kWh, and $ 573,371/year respectively. Moreover, the On-grid PV system with batteries (Case III) provides an environmentally friendly solution by reducing 63.82% $$\:C{O}_{2}$$ by and 62.22% $$\:{NO}_{x}$$ . Comparing the sensitivity analysis for various grid sell-back prices ($0/kWh, $0.043/kWh, $0.061/kWh, and $0.09/kWh), Case III is more cost-effective than Case II. The revenue generation in Case III is $128,499.41/yr, considering the supply of excess electricity into nearby small industrial loads at $0.065/kWh, this indicates that installing optimal HES in industries will not only help in overall cost reduction but also support in mitigating environmental pollution and load shedding.

Abstract Due to the extraordinary capacity of artificial intelligence (AI) to process rich information from various sources, an increasing number of enterprises are using AI for the development of ecosystem-based business models (EBMs) that require better orchestration of multiple stakeholders for a dynamic, sustainable balance among people, plant, and profit. However, given the nascency of relevant issues, there exists scarce empirical evidence. To fill this gap, this research follows the affordance perspective, considering AI technology as an object and the EBM as a use context, thereby exploring how and whether AI technologies afford the orchestration of EBMs. Based on data from Chinese A-share listed companies between the period from 2014 to 2021, our findings show an inverted U-shape quadratic relationship between AI and EBM, moderated by knowledge spillover. Our results enhance the understanding of the role of AI in configuring EBMs, thus providing novel insights into the mechanisms between AI and a specific business practice with societal concerns (i.e., EBM).

Synovial sarcomas are a rare and aggressive subtype of soft tissue sarcomas that typically affects young adults and involves the extremities. Synovial sarcoma of the kidney is a rare and aggressive tumor with a poor prognosis, accounting for only 1% of all renal tumors. The imaging features of this tumor often overlap with those of other renal tumors, and a definitive diagnosis can only be made through immunohistochemical analysis. In this case report, we present the case of a 55-year-old female with left flank pain, who was diagnosed with primary renal synovial sarcoma following a left-sided radical nephrectomy. Despite initial successful surgical intervention, restaging scans showed local recurrence and metastatic disease, which was subsequently managed with 6 cycles of chemotherapy followed by radiation therapy with palliative intent. This case underscores the importance of early detection and aggressive management of rare renal tumors to improve patient outcomes.

Offshore wind power generation equipped with conventional grid following controls challenges the power system stability by reducing the inertia of the grid and weakening the AC offshore grid. To overcome this vulnerability a promising solution could be equipping the wind turbines with grid-forming (GFM) control schemes. Many methodologies have been presented in the literature for GFM inverters. In spite of this, their applications for WTGs have not been thoroughly explored. This paper presents the study of fault handling capability of wind turbines with several grid-forming control strategies. In this context, four different control schemes i.e. Visynch, P/f droop, Q/f droop and conventional grid following control are considered. The performance of these control strategies is assessed and compared during a three-phase symmetrical fault on the point of common coupling of an offshore wind farm. A case study which consists of two wind turbines connected to the main converter of an offshore substation equipped with grid-forming control is also considered. The results indicate that, during faults, each of the four control strategies (Visynch, P/f droop, Q/f droop, and Gfol) effectively limits the current and restores normal operation. A significant advantage of Q/F droop control is its reduced sensitivity to variations in system and fault parameters, adjustable frequency response, and independence from existing Phase-Locked Loops (PLLs). On the other hand, the P/f droop control provides greater voltage support during faults due to its voltage controllers. However, post-fault oscillations result from the stiff voltage controller. Visynch control, on the other hand, shows a lower margin of stability. The advantages and weaknesses of each control scheme is revealed using the simulation results.

Cyberspace faces unparalleled threats due to the rapid rise in botnet attacks and their profound repercussions. Utilizing AI-assisted systems emerges as a potent solution for detecting and neutralizing such attacks. Existing research on botnet attack detection revolves around dataset creation, amplifying the detection methods’ efficacy and precision via sophisticated machine learning models, and a behaviour-centric analysis. A discerning review of current datasets reveals their limitations: the obsolescence of some datasets, their limited relevance to certain attack types, and an imperative lack of ground truth. Addressing these gaps, we introduce a ground truth, the BotLab-DS1 dataset, featuring 5,279 real-world active botnet samples spanning 12 botnet families and 3,000 benign instances. This paper’s core is threefold; initially, we delineate a thorough review of existing datasets and their inherent shortcomings. Subsequently, we unfold a holistic data creation strategy and leverage advanced feature engineering methods on static, behavioural, and network-centric attributes. Finally, the research involves training diverse machine learning algorithms using the BotLab-DS1 dataset for enhanced botnet detection. Our empirical findings underline that BotLab-DS1, when paired with the random forest algorithm, attains 98.6% accuracy and 99.0% precision. In contrast, gradient boosting trails closely, registering 96.34% accuracy and 96.0% precision. We believe our study will pioneer new pathways for dataset formulation and algorithmic scrutiny, enriching the research landscape and backing the global initiative to thwart botnet incursions effectively.

Objective: To assess the current trends in the field of artificial intelligence in medicine by analysing 100 most cited original articles relevant to the field. Methods: The systematic review was conducted in September 2022, and comprised literature search on Scopus database for original articles only. Google and Medical Subject Headings databases were used as resources to extract key words. In order to cover a broad range of articles, original studies comprising human as well as non-human subjects, studies without abstract and studies in languages other than English were part of the inclusion criteria. There was no specific time period applied to the search and no specific selection was done regarding the journals in the database. The screening was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to extract the top 100 most cited articles in the field of artificial intelligence usage in medicine. Data was analysed using SPSS 23. Results: Of the 11,571 studies identified, 100(0.86%) were analysed in detail. The studies were published between 1986 and 2021, with a median of 43 citations (IQR 53) per article. The journal ‘Artificial Intelligence in Medicine’ accounted for the highest number 9(9%)) of articles, and the United States was the country of origin for most of the articles 36(36%). Conclusion: The trends, development and shortcomings in field of artificial intelligence usage in medicine need to be understood to conduct an effective research in areas that still need attention, and to guide the authorities to direct their funding accordingly.

Extreme ultraviolet lithography (EUVL) is a leading technology in semiconductor manufacturing, enabling the creation of high-resolution patterns essential for advanced microelectronics. This review highlights recent progress in inorganic metal-oxide-based photoresists, with a focus on their applications in EUVL. The unique properties of zinc-based, tin–oxygen, and IVB group inorganic photoresists are examined, showcasing their enhanced chemical reactivity and precise patterning capabilities. Key advancements include the development of zinc oxide and tin oxide nanoparticles, which demonstrate significant improvements in photon absorption and solubility under extreme ultraviolet exposure. Additionally, the review delves into the photochemical reactions of tin–oxygen clusters and the influence of various ligands on film density and cross-linking. The findings suggest that these inorganic photoresists not only improve photolithographic performance but also hold potential for broader applications, such as pyroelectric infrared sensors and 3D printing. Future research directions are outlined, including the optimization of process parameters, the exploration of new ligand and metal combinations, and the evaluation of the environmental benefits of inorganic photoresists over traditional organic ones. These advancements are poised to further enhance the resolution and patterning capabilities required for next-generation semiconductor devices.

Maize bran is a by-product obtained after the milling of maize kernels and separated as by-product. The current research aimed to extract and characterize the arabinoxylans (AXs) and their gels from maize bran. Initially, maize bran was evaluated for its proximate composition and dietary fiber profile. Then, AXs were extracted through alkali extraction method, and in vitro gelation of AXs was performed through enzymes (laccase from Termites versicolor). Their structure was characterized through Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). Further, the phenolic compounds and their activity was assessed through three different assays including diphenyl picryl hydrazyl (DPPH), ferric reducing antioxidant power (FRAP), and ABTS+. The results regarding the chemical composition of maize bran showed that maize bran majorly comprised moisture, ash, crude fat, fiber, crude protein and nitrogen-free extract with 10.13 ± 0.46, 1.87 ± 0.15, 1.26 ± 0.26, 7.53 ± 1.00, 12.67 ± 0.75, and 66.54 ± 0.82 g/100 g of the sample. Further, dietary fiber profile showed that maize bran comprised 6.97 ± 0.5 and 35.20 ± 4.1% soluble and insoluble fractions of dietary fibers. Then, the structural characterization of maize bran through FTIR spectroscopy showed a typical spectrum and presented the peaks at different wavelengths, which was similar to structural features as described in previous studies. Surface morphology of gel through SEM showed micrographs with small pores, which according to our information was formed due to laccase (enzymes) activity. However, quantification of polyphenols including total phenolic content and total flavonoid content showed the results including 6.42 ± 0.18 GAE/g and 1.84 ± 0.66 CE/g and their activity assessed through DPPH, FRAP, and ABTS+ assays showed the values including 31.62 ± 0.16, 34.87 ± 0.18, and 14.21 ± 0.18 μmol TE/g, respectively. The results in this study showed that maize bran AXs and their gels showed an interesting trend in their structural and antioxidant potential.

The current research aimed to extract and characterize arabinoxylans (AX) from psyllium seeds husk for their nutritional and structural properties. For this purpose, psyllium husk (PH) was procured from the local market and subjected for the nutritional profile, dietary fiber (DF) composition, and AXs extraction. The extraction of AXs from psyllium seed husk was done through enzymatic method and Fourier transform infrared (FTIR) spectroscopy was used for its structural characterization. Further, the antioxidant activity of AXs was also elucidated using ferric reducing antioxidant power (FRAP) and diphenyl picryl hydrazyl (DPPH) assays. Results showed that psyllium seed husk is a good source of DFs (61.5 ± 2.6%) and the proximate composition including moisture, ash, crude fat, crude protein, crude fibers, and Nitrogen free extract (NFE) was 4.9 ± 0.01, 4.1 ± 0.01, 1.2 ± 0.01, 3.9 ± 0.05, 20.23 ± 0.4 and 78.2 ± 4.01 g/100 g, respectively. Furthermore, AXs content was 68.29 ± 3.4 g/100 g of PH. Different monosaccharides including xylose, arabinose, rhamnose, glucose, and galactose contents in PHAXs were 64.23 ± 1.04%, 13.38 ± 0.16%, 1.43 ± 0.04%, 1.89 ± 0.05%, and 3.64 ± 0.07%, respectively. FTIR absorption peaks from 900 to 1100 cm−1 showed spectra of AXs with the highest peak from 980 to 1015 cm−1 reflecting arabinose and xylose ratio. Additionally, the substitution positions on the xylan backbone were 2800–3400 cm−1 of O-H stretching vibrations and peaks of C-H stretching at 2853 and 2923 cm−1. The antioxidant activity of PHAXs exhibited that the FRAP value of extracted AXs was 1.39 ± 0.06 μmol Fe2+/g and the DPPH value was 3.01 ± 0.15 Trolox mg/g. It is depicted that PH is a good source of AXs (non-starch polysaccharide) with better antioxidant potential.

The main factor determining differentiation of bipotential gonads into testes or ovaries is the presence or absence of SRY (sex-determining region on Y chromosome) gene. De la Chapelle syndrome is a chromosomal anomaly with chromosomal makeup of a female (46, XX) and phenotypic presentation of a male. Previously known as XX sex reversal, it is now called 46, XX testicular disorders of sexual development (DSD). Although rare, it presents as a major chromosomal anomaly, with SRY gene crossover proposed as an underlying aetiology in most patients. We report the case of a 25-year-old male who presented with infertility and was diagnosed with De 46, XX testicular DSD. He has a previous history of resected dysembryoplastic neuroepithelial tumour (DNT). The differential diagnosis of 46, XX DSD and possible association/coincidental finding of DNT have been discussed. ---Continue

The fast growth of the world’s energy demand in the modernized world has stirred many countries around the globe to focus on power generation by abundantly available renewable energy resources. Among them, wind energy has attained significant attention owing to its environment-friendly nature along with other fabulous advantages. However, wind-integrated power systems experience numerous voltage instability complexities due to the sporadic nature of wind. This paper comprehensively reviews the problems of voltage instability in wind-integrated power systems, its causes, consequences, improvement techniques, and implication of grid codes to keep the operation of the network secure. Thorough understanding of the underlying issues related to voltage instability is necessary for the development of effective mitigation techniques in order to facilitate wind integration into power systems. Therefore, this review delves into the origin and consequences of voltage instability, emphasizing its adverse impacts on the performance and reliability of power systems. Moreover, it sheds light on the challenges of integrating wind energy with existing grids. This manuscript provides a comprehensive overview of the essential features required for critical analysis through a detailed examination of Voltage Stability Indices (VSIs). To address voltage stability issues in wind-integrated power systems, this review examines diverse techniques proposed by researchers, encompassing the tools utilized for assessment and mitigation. Therefore, in the field of power system operation and renewable energy integration, this manuscript serves as a valuable resource for researchers by comprehensively addressing the complexities and challenges associated with voltage instability in wind-integrated power systems.

Introduction and Objectives: Alcohol-associated hepatitis (AH) is a severe entity associated with high mortality. Corticosteroids might be used in cases with severe disease and several dynamic models can predict mortality and response to corticosteroids in AH patients. However, there is no consensus on the best of them. This study aimed to evaluate dynamic models to predict response to corticosteroid treatment based on short-term mortality in patients with severe AH based on a worldwide cohort. Materials and Methods: A retrospective cohort study of patients with severe AH (between 2009 – 2019). We included patients who received corticosteroid treatment and calculated the Lille model of day 4 (Lille-4), day 7 (Lille-7) (cut-off value ≥0.45), and the Trajectory of Serum Bilirubin (TSB)(cut-off value ≥0.8 of the ratio between bilirubin at admission and day 7) to predict mortality. We estimated up to 30-day survival using Kaplan-Meier curves, and we performed multivariable analyzes using Cox regression. Specifically, we constructed two models to compare Lille-4 vs. TSB and Lille-7 vs. TSB, adjusting by well-known clinical variables associated with higher mortality in AH (age, sex, and creatinine at admission). Results: 1,066 patients were included (30 centers, 10 countries), age 47.7 ± 10.9 years, 30% women. The MELD score on admission was 25 [21-30]. Responders were considered by Lille-4 49.1%, Lille-7 46.6%, and TSB 55.4%. In the first Cox regression, we observed that Lille-4 and TSB predicted 30-day mortality (HR 3.0, 95%CI: 1.7-5.1; p

The classical problem of islanding detection in distributed generation falls into the commonly used categories known as passive, active, and hybrid techniques. These approaches vary in terms of their accuracy, security, and dependability. Detecting islanding in modern inverter-based distribution systems is of the utmost importance to ensuring the protection of equipment, ensuring the safety of workers, and preventing operational and cascaded faults when the system is specially subjected to renewable integration. This research paper presents a technical comparison of the aforementioned techniques, discussing their detection rate, Non-Detection Zone (NDZ), distinct topologies, and their effectiveness in integration for low-frequency grids. The review offers a thorough analysis comparing the key attributes found in the current literature while also highlighting the forthcoming needs for advanced management, optimization, and control technologies. These technologies are crucial to effectively tackling the difficulties that arise from integrating renewable energy sources into established grid systems.

Drones are unmanned aerial vehicles (UAV) utilized for a broad range of functions, including delivery, aerial surveillance, traffic monitoring, architecture monitoring, and even War-field. Drones confront significant obstacles while navigating independently in complex and highly dynamic environments. Moreover, the targeted objects within a dynamic environment have irregular morphology, occlusion, and minor contrast variation with the background. In this regard, a novel deep Convolutional Neural Network(CNN) based data-driven strategy is proposed for drone navigation in the complex and dynamic environment. The proposed Drone Split-Transform-and-Merge Region-and-Edge (Drone-STM-RENet) CNN is comprised of convolutional blocks where each block methodically implements region and edge operations to preserve a diverse set of targeted properties at multi-levels, especially in the congested environment. In each block, the systematic implementation of the average and max-pooling operations can deal with the region homogeneity and edge properties. Additionally, these convolutional blocks are merged at a multi-level to learn texture variation that efficiently discriminates the target from the background and helps obstacle avoidance. Finally, the Drone-STM-RENet generates steering angle and collision probability for each input image to control the drone moving while avoiding hindrances and allowing the UAV to spot risky situations and respond quickly, respectively. The proposed Drone-STM-RENet has been validated on two urban cars and bicycles datasets: udacity and collision-sequence, and achieved considerable performance in terms of explained variance (0.99), recall (95.47%), accuracy (96.26%), and F-score (91.95%). The promising performance of Drone-STM-RENet on urban road datasets suggests that the proposed model is generalizable and can be deployed for real-time autonomous drones navigation and real-world flights.

This paper deals with the combined economic emission load dispatch (CEELD) problem with and without the integration of renewable energy sources (RESs), in some more rational test scenarios of single CEELD and multi-objective CEELD (MO-CEELD) optimization. Hence, an efficient and coherent approach is presented to minimize the generation and emission cost using one of the bio-inspired metaheuristic algorithms named flower pollination algorithm (FPA). The evolution of a power system along with the integration of RESs demands equal advancement in the operation and control algorithms of the power grid. Therefore, the proposed approach in this paper offers an evolutionary single and multi-objective optimization process based on a bio-inspired FPA. Further, it has been validated by achieving the best compromise solution (BCS) using the Pareto categorizing process and fuzzy membership function. Moreover, different study cases comprising eleven and fifteen thermal units with and without considering RESs are tested with the proposed technique. Finally, the effectiveness of the proposed approach is tested by comparing the simulation results with some already existing techniques in terms of overall fuel and emission cost. Significantly, it has been noticed from the results that it outperforms all the previously presented approaches like PSO, DE, GSA, AEO, BA, and dBA, thus justifying its applicability.

Objective. To evaluate the prevalence, severity, and associated factors of temporomandibular disorder (TMD) among dental students. Methods. This cross-sectional study was performed on undergraduate dental students from four dental colleges in Punjab, Pakistan. Fonseca’s questionnaire was used to measure the prevalence and severity of the TMD among the study participants. Bivariate and multiple logistic regression analyses were performed. Results. Of 364 dental students, 323 returned the completed questionnaires and the response rate of the study was 88.7%. The study included 52.6% males and 47.4% females. The prevalence of TMD was 66.9% with mild TMD in 40.90%, moderate TMD in 14.6%, and severe TMD in 11.50% of the participants. Psychological stress (29.6%), malocclusion (20%), and hypersensitivity (19.5%) were common among participants. The mean TMD score of the sample was 31.54 ± 24.86 which was significantly higher among participants with no/school-educated mothers (P=0.021) and fathers (P=0.002). The participants with arthritis (72.81 ± 32.19) and malocclusion (59.46 ± 31.09) and those who received orthodontic treatment (53.21 ± 34.21) demonstrated higher TMD. After controlling for other study variables, the participants with arthritis were 4.71 times more likely to have moderate/severe TMD (P=0.042) than those without arthritis. Similarly, the participants with malocclusion had significantly higher odds (OR = 3.57, P=0.029) of having moderate/severe TMD than those without malocclusion. Conclusion. This sample of dental students demonstrated a high prevalence and severity of TMD. The participants with arthritis and malocclusion demonstrated higher TMD. The study findings underscore the importance of prevention, early diagnosis, and management of TMD among the dental students.

With the innovation of embedded devices, the concept of smart marketplace came into existence. A smart marketplace is a platform on which participants can trade multiple resources, such as water, energy, bandwidth. Trust is an important factor in the trading platform, as the participants would prefer to trade with those peers who have a high trust rating. Most of the existing trust management models for smart marketplace only provide a single aggregated trust score for a participant. However, they lack the mechanism to gauge the level of commitment shown by a participant while trading a particular resource. This work aims to provide a fine-grained trust score for a participant with respect to each resource that it trades. Several parameters, such as resource availability, success rate, and turnaround time are used to gauge the participant’s level of commitment, specific to the resource being traded. Moreover, the effectiveness of the proposed model is validated through security analysis against ballot-stuffing and bad-mouthing attacks, along with simulationbased analysis and a comparison in terms of accuracy, false positive, false negative, computational cost and latency. The results indicate that the proposed trust model has 7% better accuracy, 30.13% lower computational cost and 31.74% less latency compared to the existing benchmark model.

Objectives: To assess the clinical characteristics of COVID-19 Virus disease in the pediatric population in Pakistan. Study Design: Cross-sectional study. Place and Duration of Study: Pak Emirates Military Hospital, Rawalpindi Pakistan, from Mar 2020 to Jan 2021. Methodology: All children presenting to the department with symptoms consistent with COVID-19 disease were tested for the virus. Patients who tested positive on the PCR were included in the study. Patients with non-consistent symptoms of COVID-19 and those who tested negative on the PCR were excluded from the study. All clinical data, including the age of the child, the onset of symptoms, the gap between the onset of symptoms and presentation as well as clinical symptoms, were documented on a predefined proforma. Results: A total of 106 patients were enrolled on the study. The mean age of patients was 5.6±2.5 years. The most frequent symptoms were fever (63, 59.6%) and cough (49, 46.2%). There were 3(2.9%) cases with severe or critical illness. The most frequent abnormal laboratory findings were leukopenia (29, 27.4%) and increased creatine kinase (38, 36.0%). Ground-glass opacities were observed in the HRCT chest of 17(65.3%) cases, out of 26 children diagnosed with pneumonia. The majority (70, 66%), had a positive exposure history. 88(83%) cases did not abide by the precautionary measures against the COVID-19 disease. Conclusions: The current study indicates that children usually present with mild symptoms but can present as severe diseases, as observed in this study.

Objective: To look for the associative factors in avoidance of exclusive and non-exclusive breastfeeding among mothers after lower segment Caesarean section. Study Design: Cross-sectional study. Place and Duration of Study: Paediatrics department, Pak Emirates Military Hospital, Rawalpindi Pakistan from Oct to Mar 2020. Methodology: Mothers bringing their infants for vaccination at six weeks of age with babies born with lower segment caesarean section were included in the study. They were asked simple questions regarding exclusive or non-exclusive breastfeeding. Relevant socio-demographic factors were also recorded and compared among mothers breastfeeding their babies and those avoiding it. Results: A total of 500 mothers were included in the study. The mean age of the study participants was 33.576±9.174 years. 336(67.2%) women were primiparous, while 164(32.8%) were multiparous. 208(41.6%) women were actively breastfeeding their child, while 292(58.4%) avoided breastfeeding their babies. 150(72.1%) women were non-exclusively breastfeeding, while 58(27.9%) showed an exclusive breastfeeding pattern. Pearson chi-square test revealed that low education and working outside the home had a statistically significant association with the avoidance of breastfeeding the babies among our target population (p-value

Malaria is a potentially fatal disease which is caused by Plasmodium parasite. These parasites are transmitted to humans through the bites of female Anopheles mosquitoes which play the role of disease vector. Five types of plasmodium cause malaria named P. Falciparum, P. Vivax, P. Ovale, P. Knowlesi, and P. Malariae, Among the Plasmodium parasites, Falciparum and Vivax are particularly lethal to humans. Therefore, early detection of malaria is mandatory to avoid the loss of human life. Different automatic/semi-automatic malaria detection techniques are available in the literature, which reduces the chance of human errors in the prognosis of malaria. In recent years, deep learning-based methods have proven to be effective for object detection. Therefore, such methods have caught the attention of researchers to use for the detection of malarial parasites in human blood. In this paper, we proposed a Convolutional Neural Network (CNN) model, which detects malarial parasites in microscopic images of human blood samples with high accuracy. The proposed model comprises 15 layers. It has 8 convolution layers with ReLu activation function, 4 max-pooling layers, 1 flattening layer, and 2 fully connected layers. The proposed method has been evaluated using various statistical measures against existing state-of-the-art methods. The quantitative measures show the effectiveness of the proposed model. It has a 97.42% testing accuracy, 97.42% sensitivity, 97.41% specificity, 97.70% precision, 97.42% recall , 97.97% F1-score , 97.41% Area Under Curve (AUC), and 94.82% Mathews correlation coefficient.

Low yields of isolated natural compounds halt the drug discovery process as they can only be used for structure elucidation studies and basic biological screening. Metabolite profiling via chromatographic means for optimized selection of biomass and extraction medium can help resolve the issue. In line with this, the project is focused on metabolite profiling of Datura innoxia regarding its two bioactive principals i.e., withametelin and daturaolone. Samples (840) were prepared via collection of five parts (leaves, stem, fruit, root, flowers) from two geographically different regions of Pakistan i.e., Islamabad and Muzaffargarh for six months (May-October) and extraction in fourteen solvent systems of varied polarity range, respectively. Six months agroclimatology data (temperature, humidity, soil wetness, UV irradiance) was also obtained. TLC co-detection method (n-hexane: ethyl acetate; 7:3) of withametelin and daturaolone was developed and analysis was performed on all samples. RP HPLC method was developed for withametelin (Linearity = R2;0.9) and daturaolone (linearity: R2;0.9) and 118 samples which showed detections in TLC analysis were quantified. Withametelin was mostly detected in leaves with a maximum quantified value of 5.12 ± 0.28 µg/mg dry plant powder when collected in June from arid Muzaffargarh region and extracted with Ethyl acetate + Ethanol (1:1). Distribution of daturaolone is mostly found in fruits with a maximum quantified value of 5.18 ± 0.45 µg/mg dry plant powder when collected in August from mountainous Islamabad region and extracted with Ethyl acetate + Ethanol (1:1). The study states that the presence and quantitative variations of withametelin and daturaolone depend on the plant’s part, extraction medium, geographical location, weather conditions and soil wetness. Use of a controlled environment research to determine the quantitative relationship between different parameters is proposed.

Safe preclinical dose determination is predictive of human toxicity and can have a profound impact on the overall progress of the compound in early drug discovery process. In this respect, current study sought to investigate for the first time the acute and subacute oral toxicity of two pharmacologically active natural compounds i.e., withametelin and daturaolone in Sprague Dawley rats following OECD guideline 420 and 407, respectively. As per acute toxicity studies, withametelin and daturaolone were characterized as Globally Harmonized System (GHS) category 4 and 5 compounds, respectively. Sub-acute daily dose of withametelin was 5, 2.5, and 1.25 mg/kg but, for daturaolone, it was 10, 5, and 2.5 mg/kg. High dose (5 and 2.5 mg/kg) withametelin groups showed dose dependent changes in the general, hematological, biochemical and histopathological parameters in both sexes, the most prominent being hyperthyroidism while no toxicity was observed at lower doses (1.25 and 0.75 mg/kg), No Observable Adverse Effect Level (NOAEL) being 1.25 mg/kg. Daturaolone was comparatively safer and showed dose dependent significant changes in hepatic enzyme (Alanine Transaminase), bilirubin, creatinine, and glucose levels while histological changes in testes were also observed. Lower doses (5, 2.5, and 1.25 mg/kg) of daturaolone showed no significant toxic effects and 5 mg/kg was declared as its NOAEL. Depending upon our findings, starting effective oral dose levels of 1.25 mg/kg/day for withametelin and 5 mg/kg/day for daturaolone are proposed for repeated dose (up to 28 days) preclinical pharmacological evaluation models. Long term studies with more behavioral, biochemical, histopathological and hormonal parameters are proposed to strengthen the findings.

Phosphorus (P) constraint can be alleviated by increasing C inputs, which can help to improve crop production and P fertilizer use efficiency. However, the effects of different manures on soil microbial biomass P (MBP) and P fractions as well as C fractions in calcareous soils remain poorly understood. Soil MBP pool involves the P mineralization and immobilization processes, potentially changing P fractions and P availability. Therefore, the effects of different manures on soil microbial biomass (MBP, MBC) pool, P, and C fractions and crop P utilization were evaluated in greenhouse experiments with maize plantation. Treatments included no manure (control), poultry manure (PM), cow manure (CM), goat manure (GM), mixed manure (MM), and three inorganic P (Pi) rates; P0: 0 mg kg-1, P50: 50 mg kg-1, and P100: P100 mg kg-1 (P2O5). For plant growth comparison, crop physiological growth indices, shoot P contents and total P uptake were increased by PM and P100 as compared to other treatments. The PM with P100 significantly increased the plant growth by inducing P uptake of ∼18% compared with control. The results exhibited that Pi (P100) combined with manure (PM) significantly (p < 0.05) increased the soil physicochemical properties, that is, 683.76 mg kg-1 total P, 21.5 mg kg-1 Olsen P, 4.26 g kg-1 SOC, 2.41 g kg-1 POC, as well as microbial biomass C and P increased by 152.84 mg kg-1 and 36.83 mg kg-1, respectively. Consequently, we concluded that PM with Pi (P100) application builds up soil microbial biomass, which is more beneficial for promoting P utilization for maize.

The remote monitoring of patients using the internet of things (IoT) is essential for ensuring continuous observation, improving healthcare, and decreasing the associated costs (i.e., reducing hospital admissions and emergency visits). There has been much emphasis on developing methods and approaches for remote patient monitoring using IoT. Most existing frameworks cover parts or sub-parts of the overall system but fail to provide a detailed and well-integrated model that covers different layers. The leverage of remote monitoring tools and their coupling with health services requires an architecture that handles data flow and enables significant interventions. This paper proposes a cloud-based patient monitoring model that enables IoT-generated data collection, storage, processing, and visualization. The system has three main parts: sensing (IoT-enabled data collection), network (processing functions and storage), and application (interface for health workers and caretakers). In order to handle the large IoT data, the sensing module employs filtering and variable sampling. This pre-processing helps reduce the data received from IoT devices and enables the observation of four times more patients compared to not using edge processing. We also discuss the flow of data and processing, thus enabling the deployment of data visualization services and intelligent applications.

Objective: To assess the frequency, variants, clinical profile and outcome of patients admitted with the diagnosis of GuillianBarre Syndrome at neurology unit of a tertiary care teaching hospital of Pakistan. Study Design: Cross-sectional study. Place and Duration of Study: Neurology department, Pak Emirates Military Hospital Rawalpindi, from Jan to Dec 2018. Methodology: This study was conducted on 42 patients of Guillian-Barre Syndrome admitted in hospital. Demographic profile included age, gender, and the symptoms with which the patient presented. Medical and neurological complications were also documented among the target population. Outcomes included recovery, shifting to intensive care unit and death. Results: Out of 42 patients included in the final analysis 25 were male and 17 were female. Most of the patients presented with lower limb weakness followed by numbness. Acute inflammatory demyelinating polyneuropathy was the commonest while cranial nerve variant was least reported. Motor deficit were the commonest complication faced by the patients followed by respiratory involvement. Out of 42 patients, 34 (80.9%) recovered, 4 (9.5%) were shifted to the intensive care unit and 4 (9.5%) died. Conclusion: This study gives an insight into the pattern of a fairly common neurological illness which if diagnosed and managed in time has a good outcome in our set up. Management of critically ill Guillian-Barre Syndrome patients involves a multidisciplinary team with a need of intensive care unit during the course of management. Variety of types and presentations should be part of training of neurology doctors as well as internal medicine doctors.

Objective: To determine the impact of physician led life style modifications (diet and daily step count by using pedometer) on glycemic control of type II diabetic patients Study Design: Quasi experimental study. Place and Duration of Study: Pak Emirates Military Hospital, Rawalpindi, Aug 2018 to Feb 2019. Methodology: The sample population comprised of 200 diabetic patients reporting for the routine follow-up at a tertiary care hospital in Rawalpindi. Patients were divided into two groups by random method. Group A had the patients with continuation of the routine anti-diabetic medication while group received the physician led life style modifications in addition to the routine anti diabetic medication. Values of HBA1c among the groups were compared three months after the start of study. Results: Mean age of the patients was 42.19 ± 6.175 years. Mean duration of DM in the study participants was 4.52 ± 4.166 years. Out of 115 patients were male while 85 were female. HBA1c in the intervention group was 7.96% ± 0.39 while in the control group was 7.04% ± 0.81. Difference between the two groups was statistically significant (p-value

Barley broth (Talbinah) is prepared by combining barley syrup, milk, and honey. The Prophet Mohammad (PBUH) recommended Talbinah for sadness and heart relief in sorrows. Talbinah has a promising nutritional and therapeutic impact on human health. It is a rich source of many nutrients and some bioactive moieties. Regular consumption imparts in maintaining better gut and acts as anti-depressive, anti-diabetic, anti-oxidant, anti-inflammatory, antidiabetic and antihypercholesterolemic. Moreover, it is the most effective food for supplying nutrients and removing toxins from human cells. In this review, the production technology, nutrition, therapeutic potential, proposed prospects, role as a functional food and current knowledge on the subject have been discussed comprehensively. Conclusively, Talbinah as functional food could be a way in preventing various health maladies.

Encapsulation technology is gaining attention across the world owing to its promising protection of active ingredients under hostile conditions. Various wall materials are used in the encapsulation of these sensitive ingredients. However, the legume proteins (LPs) are emerging and unique carriers for the delivery of bioactive owed to their biocompatibility, film formation and functional attributes. Legume proteins loaded with active ingredients can be used for the development of various functional foods. Modification strategies are making the legume proteins effective wall materials against various hostile conditions for the protection of probiotics and other sensitive ingredients. The present review describes the promising potential of legumes for the protection of active ingredients. Additionally, the effect of various modification processes on the functional properties of legumes has been reviewed.

Withanolides are natural medicinal agents whose safety and therapeutic profiles make them valuable to mankind. Among multiple withanolides, withametelin is underexplored. The present study was aimed to create a general biological profile of isolated withametelin from Datura innoxia Mill. targeting different biological models. In-silico studies include drug-likeliness, pharmacokinetics, toxicity, molecular targets and cytotoxicity to cancer cell lines predictions. In silico directed preliminary in-vitro evaluation comprised of cancer/normal cell cytotoxicity, DPPH and protein kinase inhibition assays while in-vivo bioactivities include antiinflammatory, analgesic, antidepressant and anticoagulant assays. Pharmacological findings were strengthened by molecular docking studies to check interactions with various proteins and to propose the future path of studies. Results indicated compliance with Lipinski drug-likeliness rule (score −0.55). ADMET prediction showed strong plasma protein binding, GI absorption (Caco-2 cells permeability = 46.74 nm/s), blood brain barrier penetration (Cbrain/Cblood = 0.31), efflux by P-glycoprotein, metabolism by CYP1A2, CYP2C19 and CYP3A4, medium hERG inhibition and non-carcinogenicity in rodents. Predicted molecular targets included mainly receptors (glucocorticoid, kappa opioid, delta opioid, adrenergic and dopamine), oxidoreductase (arachidonate 5-lipoxygenase and cyclooxygenase-2), enzymes (HMG-CoA reductase) and kinase (NFκb). Withametelin was more cytotoxic to cancer cells (DU145 IC50 7.67 ± 0.54 µM) than normal lymphocytes (IC50 33.55 ± 1.31 µM). It also showed good antioxidant and protein kinase inhibition potentials. Furthermore, withametelin (20 mg/kg) significantly reduced inflammatory paw edema (68.94 ± 5.55%), heat-induced pain (78.94 ± 6.87%) and immobility time (50%) in animals. Molecular docking showed hydrogen bonding interactions (binding energies: −11.3 to −7.8 kcal/mol) with arachidonate 5 lipoxygenase, NFκb and glucocorticoid receptor. Withametelin has potential for advance investigations for its cytotoxic, anti-inflammatory, analgesic and antidepressant activities.

A novel technique for conversion of DC power to AC power is introduced using solar powered sine wave generation system is presented. DC power extracted from solar system is made utilitarian for driving the BLDC (brushless DC) motor with constant speed constraints. The back EMF signals of each phase of the BLDC motor facilitated the development of technique for the sine wave generation from solar system without battery backup. This motor is coupled with AC generator, which yields the AC power on demand. The constant speed constraint indispensable for fixed electrical frequency at the output of generator. A new control technique is rendered for reference tracking speed control of BLDC motor using Lyapunov theory by changing switching frequency, and also maintaining the voltage level at the output of converter driving BLDC by regulating the switching frequency of the zeta converter. The proposed methodology for generation of AC power from solar power system is also tested on prototype. The comparison of conventional technique for generation of sine wave power and proposed scheme is mentioned at later section of this paper for describing the efficacy of newly presented scheme.

Abstract Background Cancer is a horrific disease relentlessly affecting human population round the globe. Genus Datura encompasses numerous species with reported medicinal uses. However, its potential as a source of natural anticancer agents is yet to be determined. Datura stramonium (DS) and Datura inoxia (DI) are the two species chosen for this study. Methods Total phenolic and flavonoid content (TPC and TFC) as well as antioxidant activity were assessed through colorimetric method. Polyphenolic quantification was done by RP-HPLC. Following extract standardization ethyl acetate leaf extracts of both species (DSL-EA and DIL-EA) were chosen for anticancer studies. In vitro cytotoxicity using various models including cancer cell lines was monitored. Following toxicity studies, benzene (0.2 ml) was used to induce leukemia in Sprague-Dawley rats. Extracts were orally administered to preventive (100 and 200 mg/kg) and treatment (200 mg/kg only) groups. The antileukemic potential of extracts was assessed through haematological, biochemical, endogenous antioxidants and histological parameters. Results Significant TPC and TFC were estimated in DSL-EA and DIL-EA. RP-HPLC quantified (μg/mg extract) rutin (0.89 ± 0.03), gallic acid (0.35 ± 0.07), catechin (0.24 ± 0.02) and apigenin (0.29 ± 0.09) in DSL-EA while rutin (0.036 ± 0.004) and caffeic acid (0.27 ± 0.03) in DIL-EA. Both extracts exhibited significant brine shrimp cytotoxicity (LC50

Abstract Background In the present study, the poncirin which is flavonoid-7-o-glycosides (isolated from the Poncirus trifoliata) in nature was evaluated against the Carbon tetra chloride (CCL4)-induced liver injury. The poncirin have been reported for various anti-inflammatory, analgesic activity etc. Based on the previous studies it was anticipated that the poncirin will ameliorate CCL4-induced liver injury. Methods The CCL4-induced acute and chronic liver injury model (albino BALB/c mice) was used. Following the induction of the liver injury various parameters such as food and water intake, body weight and weight to dry ratio changes were assessed. Furthermore, various hematological, biochemical parameters and histological studies such as hemotoxylin and eosin (H and E) staining were performed. The poncirin treatment was also evaluated against the pro-inflammatory cytokines such as interleukin-1β (IL-1β), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) using enzyme link immunosorbant assay (ELISA). The Swiss Target prediction software was used to investigate interaction of the poncirin on the various hepatic enzymes. Results The poncirin treatment markedly improved the behavioral parameters such as food and water intake. The liver weight variation was attenuated and total body was improved markedly. The hematological and biochemical parameters were significantly improved compared to the CCL4 treated groups. The anti-oxidants were induced, while oxidative stress markers were reduced promisingly. The H and E staining showed that poncirin treatment significantly improved the histology of liver compared to the CCL4 treated group. Furthermore, the poncirin treatment also evidently decreased the inflammatory mediators. Conclusions The poncirin treatment showed marked improvement in behavioral, biochemical and histological parameters following CCL4-induced liver injury. Additionally, the poncirin treatment also markedly improved the antioxidant enzymes, attenuated the oxidative stress markers and inflammatory cytokines.

Country olive forests are one of the major contributors with economic aspects. Spain is the leading country in the world which produced around 45% of olive oil compared to the total production in the world. The value of 2.4 million hectares of land is dedicated to olive cultivation in the country, which made it a huge olive oil producer in the world. Olive crop widely spread over large extensive areas; manual counting of trees is humanly infeasible. To address this problem, we propose an automatic scheme for the detection and enumeration of olive trees. The proposed technique comprises of multi-step image processing techniques applied over a single band of imagery. The single red band once extracted from the color spectrum of acquired images, is then sharpened and edges are detected. The closed edges formed by the tree boundaries are transformed into white blobs using morphological reconstruction. Resulting circular blobs are then filtered out based on their shape and size. Blobs with circular geometry and in-range radius are considered as olive trees, which are then mapped with the existing ground information. Results have been generated over the diverse images capturing the ground truth information with an estimation error of 1.27%.

The COVID-19 pandemic has led to mortality and morbidity since December 2019. Many possible treatment options have been advised till date. The role of ivermectin in the treatment of COVID-19 disease remains controversial. The aim of our study was to evaluate the effect of ivermectin in hospitalized patients with non-severe and severe COVID-19 disease. We conducted a retrospective cohort study that compared outcomes in 2 groups of COVID-19 patients hospitalized at the largest tertiary care center of Pakistan. The study group was given ivermectin along with standard treatment of covid-19 disease; the comparison group was not. Data on mortality, inflammatory markers such as C-reactive protein (CRP) and ferritin, length of hospital stay and baseline characteristics were collected from Aga Khan University’s database from October 2020 till February 2021. Statistical analysis was done to determine the effectiveness of ivermectin in non-severe and severe COVID-19. Comparison of effectiveness of Ivermectin in both the genders was also conducted. The cohort included 188 patients out of which 90 were treated with ivermectin. Mortality and length of hospitalization was not found to be significantly different in the study group compared with the control group (5.6% vs 5.1%; p=0.87 and 5 days vs 4 days; p=0.27). Analysis of secondary outcomes did not yield statistically significant results, apart from ferritin levels which were significantly less in patients treated with ivermectin (547.1 vs 756.7; p=0.03). The ferritin and CRP levels in affected males were higher than in females on admission and discharge. Our findings suggest ivermectin does not significantly affect all-cause mortality, length of hospitalization and CRP levels in hospitalized COVID-19 patients. Large scale randomized controlled trials (RCTs) are required to further evaluate the role of ivermectin in covid-19 disease.

The validation of underexplored traditional plant remedies represents a reservoir of novel leads for drug discovery. In line with this, in vitro total phenolics and flavonoids content, multimode antioxidants, antimicrobial, cytotoxicity, and protein kinase inhibition assays were conducted on C. ambrosioides seed extracts in addition to RP-HPLC. Methanol extract exhibited highest total phenolics (64.6±0.6 μg gallic acid equivalent/mg) and flavonoids (50.9±0.5 μg quercetin equivalent/mg) content. RP-HPLC quantified rutin (1.98 μg/mg) in methanol extract whereas quercetin (0.322 μg/mg) and kaempferol (2.86 μg/mg) in methanol-distilled water extract. Methanol extract exhibited highest ascorbic acid equivalent (AAE) free radical (DPPH) scavenging (IC50 of 110.7±5 μg/ml), total antioxidant capacity (110.6±2.2 μg AAE/mg), and total reducing power (94.30±0.46 μg AAE/mg). Highest antibacterial activity against K. pneumonia (14±1.61 mm ZOI) and antifungal activity against F. solani (17±1.38 mm ZOI) were shown by n-hexane and chloroform extracts, respectively. Ethyl acetate extract exhibited highest brine shrimps cytotoxicity (LC50 of 125 μg/ml). A noteworthy protein kinase inhibitory potential was shown by ethanol extract with a 20±1.27 mm bald zone. Therapeutic potential of medicinal plants can be completely explored by using multiple solvent system. This study makes C. ambrosioides, a resourceful prospect for the bioactivity-guided isolation of lead compounds.

The pentacyclic triterpenoids (PTs) of plant origin are reputed to restrain prostate cancer (PCa) cell proliferation. This study aims to assess 3-epifriedelinol (EFD) isolated from aerial part of Ipomoea batatas against PCa and its potential mechanism, in vitro and in vivo. Molecular docking affirms good binding affinity of the compound with target proteins exhibiting binding energy of −7.9 Kcal/mol with BAX, −8.1 Kcal/mol (BCL-2), −1.9 Kcal/mol (NF-κB) and −8.5 Kcal/mol with P53. In the MTT assay, EFD treatment (3–50 µM) showed a significant (p < 0.05 and p < 0.01) dose and time dependent drop in the proliferative graph of DU145 and PC3, and an upsurge in apoptotic cell population. EFD displayed substantial IC50 against DU145 (32.32 ± 3.72 µM) and PC3 (35.22 ± 3.47 µM). According to Western blots, EFD administration significantly enhanced the cleavage of caspases and PARP, elevated BAX and P53 and decreased BCL-2 and NF-κB expression, thereby triggering apoptosis in PCa cells. When male Sprague Dawley rats were intoxicated with Bisphenol A (BPA), an apparent increase in prostate mass (0.478 ± 0.08 g) in comparison to control (0.385 ± 0.03 g) indicates prostatitis. Multidose treatment of EFD (10 mg/kg) significantly reduced prostate size (0.404 ± 0.05 g). EFD exhibited substantial curative potential in vivo, as hematological, hormonal and histopathological parameters have been significantly improved. Reduced peroxidation (TBARS), and suppression of inflammatory markers i.e., NO, IL-6 and TNF-α, signposts substantial antiinflammatory potential of the compound. Overall, EFD has shown better binding affinity with target molecules, acceptable ADMET profile, potent antiproliferative and apoptotic nature and significant reduction in inflamed prostate mass of rats. The present study demonstrates acceptable physicochemical and pharmacokinetic properties of the compound with excellent drugable nature, hence EFD in the form of standardized formulation can be developed as primary or adjuvant therapy against PCa and toxins-induced gonadotoxicity.

This study was conducted to find the association between pronunciation self-efficacy sources and pronunciation self-efficacy beliefs. It was quantitative in nature using a correlational research design. A sample of 155 Malaysian ESL university students was selected from two Malaysian universities by employing proportionate stratified random sampling. Two questionnaires were used to collect the data related to pronunciation self-efficacy sources and self-efficacy beliefs. In order to analyze the collected data, the correlational analysis was carried out with a statistical software named Smart PLS 3.0. Findings indicated that all the self-efficacy sources were significantly and positively correlated with pronunciation self-efficacy beliefs, except physiological state, which was significantly but negatively correlated with pronunciation self-efficacy beliefs. Based on the outcomes of this study, implications for ESL instructors and educational policymakers were presented.

Gas sensing for dimethyl sulfoxide (DMSO) based on rotational absorption spectroscopy is demonstrated in the 220–330 GHz frequency range using a robust electronic THz-wave spectrometer. DMSO is a flammable liquid commonly used as a solvent in the food and pharmaceutical industries, materials synthesis, and manufacturing. DMSO is a hazard to human health and the work environment; hence, remote gas sensing for DMSO environmental and process monitoring is desired. Absorption measurements were carried out for pure DMSO at 297 K and 0.4 Torr (53 Pa). DMSO was shown to have a unique rotational fingerprint with a series of repeating absorption bands. The frequencies of transitions observed in the present study were found to be in good agreement with spectral simulations carried out based on rotational parameters derived in prior work. Newly, intensities of the rotational absorption lines were experimentally observed and reported for DMSO in this study. Measured intensities for major absorption lines were found in very good agreement with relative line intensities estimated by quantum mechanical calculations. The sensor developed here exhibited a detection limit of 1.3 × 1015–2.6 × 1015 DMSO molecules/cm3 per meter of absorption path length, with the potential for greater sensitivity with signal-to-noise improvements. The study illustrates the potential of all electronic THz-wave systems for miniaturized remote gas sensors.

A novel technique for conversion of DC power to AC power is introduced using solar powered sine wave generation system is presented. DC power extracted from solar system is made utilitarian for driving the BLDC (brushless DC) motor with constant speed constraints. The back EMF signals of each phase of the BLDC motor facilitated the development of technique for the sine wave generation from solar system without battery backup. This motor is coupled with AC generator, which yields the AC power on demand. The constant speed constraint indispensable for fixed electrical frequency at the output of generator. A new control technique is rendered for reference tracking speed control of BLDC motor using Lyapunov theory by changing switching frequency, and also maintaining the voltage level at the output of converter driving BLDC by regulating the switching frequency of the zeta converter. The proposed methodology for generation of AC power from solar power system is also tested on prototype. The comparison of conventional technique for generation of sine wave power and proposed scheme is mentioned at later section of this paper for describing the efficacy of newly presented scheme.

BackgroundAlcoholic hepatitis (AH) is a unique syndrome characterized by high short-term mortality. The impact of the academic status of a hospital (urban and teaching) on outcomes in AH is unknown.MethodsNational Inpatient Sample dataset (2006–2014) on AH admissions stratified to academic center (AC) or non-academic center (NAC) and analyzed for in-hospital mortality (IHM), hospital resource use, length of stay in days (d), and total charges (TC) in United States dollars (USD). Admission year was stratified to 2006–2008 (TMI), 2009–2011 (TM2), and 2012–2014 (TM3).ResultsOf 62,136 AH admissions, the proportion at AC increased from 46% in TM1 to 57% in TM3, Armitage trend, p < 0.001. On logistic regression, TM3, younger age, black race, Medicaid and private insurance, and development of acute on chronic liver failure (ACLF) were associated with admission to an AC. Of 53,264 admissions propensity score matched for demographics, pay status, and disease severity, admissions to AC vs. NAC (26,622 each) were more likely to have liver disease complications (esophageal varices, ascites, and hepatic encephalopathy) and hospital-acquired infections (HAI), especially Clostridioides difficile and ventilator-associated pneumonia. Admissions to AC were more likely transfers from outside hospital (1.6% vs. 1.3%) and seen by palliative care (4.8% vs. 3.3%), p < 0.001. Use of endoscopy, dialysis, and mechanical ventilation were similar. With similar IHM comparing AC vs. NAC (7.7% vs. 7.8%, p = 0.93), average LOS and number of procedures were higher at AC (7.7 vs. 7.1 d and 2.3 vs. 1.9, respectively, p < 0.001) without difference on total charges ($52,821 vs. $52,067 USD, p = 0.28). On multivariable logistic regression model after controlling for demographics, ACLF grade, and calendar year, IHM was similar irrespective of academic status of the hospital, HR (95% CI): 1.01 (0.93–1.08, p = 0.70). IHM decreased over time, with ACLF as strongest predictor. A total of 63 and 22% were discharged to home and skilled nursing facility, respectively, without differences on academic status of the hospital.ConclusionAdmissions with AH to AC compared to NAC have higher frequency of liver disease complications and HAI, with longer duration of hospitalization. Prospective studies are needed to reduce HAI among hospitalized patients with AH.

Video recorders record the output of each security camera. After an incident, the video footage can be used for evidence by locating a suspect or criminal for a crime. A manual scan of the video footage requires a considerable amount of manpower and time, a luxury which cannot be afforded when tracking down a person of interest (POI). An automated system is proposed in this paper which aims at finding the desired POI through the available volume of video data quickly and accurately. It is visualized to go through all the available videos and detect the POI using facial recognition. Thereafter, it would create a video montage of all the desired frames and incorporate time and location information to produce a path map followed by the POI. The proposed system reduces the human burden, human error and reduces the time taken when searching the POI manually. Validation has been performed on various video data collected by ourselves as well. The results depict that the proposed system is able to correctly identify POI with an accuracy of 86% for video data captured in a constrained environment. Videos captured by a cell phone in an unconstrained environment result in an accuracy of around 80%. Real video tested in our university campus revealed the proposed system is capable of generating tracking information for POI effectively.

Cultivation of olive trees for the past few years has been widely spread across Mediterranean countries, including Spain, Greece, Italy, France, and Turkey. Among these countries, Spain is listed as the largest olive producing country with almost 45% of olive oil production per year. Dedicating land of over 2.4 million hectares for the olive cultivation, Spain is among the leading distributors of olives throughout the world. Due to its high significance in the country's economy, the crop yield must be recorded. Manual collection of data over such expanded fields is humanly infeasible. Remote collection of such information can be made possible through the utilization of satellite imagery. This paper presents an automated olive tree counting method based on image processing of satellite imagery. The images are pre-processed using the unsharp masking followed by improved multi-level thresholding-based segmentation. Resulting circular blobs are detected through the circular Hough transform for identification. Validation has been performed by evaluating the proposed scheme for the dataset formed by acquiring images through the “El Sistema de Información Geográfica de Parcelas Agrícolas”viewer over the region of Spain. The proposed algorithm achieves an accuracy of 96% in detection. Computation time was recorded as 24 ms for an image size of 300 × 300 pixels. The less spectral information is used in our proposed methodology resulting in a competitive accuracy with low computational cost in comparison to the state-of-the-art technique.

Solubility of phytoconstituents depends on the polarity of the extraction medium used, which might result in the different pharmacological responses of extracts. In line with this, ethnomedicinally important food plant (i.e., Caralluma tuberculata extracts) have been made in fourteen distinct solvent systems that were then analyzed phytochemically via total phenolic amount estimation, total flavonoid amount estimation, and HPLC detection and quantification of the selected polyphenols. Test extracts were then subjected to a battery of in vitro assays i.e., antioxidants (DDPH scavenging, antioxidant capacity, and reducing power estimation), antimicrobial (antibacterial, antifungal, and antileishmanial), cytotoxic (brine shrimps, THP-1 human leukemia cell lines and normal lymphocytes), and protein kinase inhibition assays. Maximum phenolic and flavonoid contents were computed in distilled water–acetone and acetone extracts (i.e., 16 ± 1 μg/mg extract and 8 ± 0.4/mg extract, respectively). HPLC-DAD quantified rutin (0.58 µg/mg extract) and gallic acid (0.4 µg/mg extract) in methanol–ethyl acetate and methanol extracts, respectively. Water–acetone extract exhibited the highest DPPH scavenging of 36 ± 1%. Total reducing potential of 76.0 ± 1 μg/mg extract was shown by ethanol chloroform while maximum total antioxidant capacity was depicted by the acetone extract (92.21 ± 0.70 μg/mg extract). Maximal antifungal effect against Mucor sp., antileishmanial, brine shrimp cytotoxicity, THP-1 cell line cytotoxicity, and protein kinase inhibitory activities were shown by ethyl acetate-methanol (MIC: 50 µg/disc), n-hexane (IC50: 120.8 ± 3.7 µg/mL), ethyl acetate (LD50: 29.94 ± 1.6 µg/mL), distilled water–acetone (IC50: 118 ± 3.4 µg/mL) and methanol–chloroform (ZOI: 19 ± 1 mm) extracts, respectively. Our findings show the dependency of phytochemicals and bioactivities on the polarity of the extraction solvent and our preliminary screening suggests the C. tuberculata extract formulations to be tested and used in different ailments, however, detailed studies remain necessary for corroboration with our results.

A worldwide increase in the incidence of fungal infections, emergence of new fungal strains, and antifungal resistance to commercially available antibiotics indicate the need to investigate new treatment options for fungal diseases. Therefore, the interest in exploring the antifungal activity of medicinal plants has now been increased to discover phyto-therapeutics in replacement to conventional antifungal drugs. The study was conducted to explore and identify the mechanism of action of antifungal agents of edible plants, including Cinnamomum zeylanicum, Cinnamomum tamala, Amomum subulatum, Trigonella foenumgraecum, Mentha piperita, Coriandrum sativum, Lactuca sativa, and Brassica oleraceae var. italica. The antifungal potential was assessed via the disc diffusion method and, subsequently, the extracts were assessed for phytochemicals and total antioxidant activity. Potent polyphenols were detected using high-performance liquid chromatography (HPLC) and antifungal mechanism of action was evaluated in silico. Cinnamomum zeylanicum exhibited antifungal activity against all the tested strains while all plant extracts showed antifungal activity against Fusarium solani. Rutin, kaempferol, and quercetin were identified as common polyphenols. In silico studies showed that rutin displayed the greatest affinity with binding pocket of fungal 14-alpha demethylase and nucleoside diphosphokinase with the binding affinity (Kd, −9.4 and −8.9, respectively), as compared to terbinafine. Results indicated that Cinnamomum zeylanicum and Cinnamomum tamala exert their antifungal effect possibly due to kaempferol and rutin, respectively, or possibly by inhibition of nucleoside diphosphokinase (NDK) and 14-alpha demethylase (CYP51), while Amomum subulatum and Trigonella foenum graecum might exhibit antifungal potential due to quercetin. Overall, the study demonstrates that plant-derived products have a high potential to control fungal infections.

Exploration of leads with therapeutic potential in inflammatory disorders is worth pursuing. In line with this, the isolated natural compound daturaolone from Datura innoxia Mill. was evaluated for its anti-inflammatory potential using in silico, in vitro and in vivo models. Daturaolone follows Lipinski’s drug-likeliness rule with a score of 0.33. Absorption, distribution, metabolism, excretion and toxicity prediction show strong plasma protein binding; gastrointestinal absorption (Caco-2 cells permeability = 34.6 nm/s); no blood–brain barrier penetration; CYP1A2, CYP2C19 and CYP3A4 metabolism; a major metabolic reaction, being aliphatic hydroxylation; no hERG inhibition; and non-carcinogenicity. Predicted molecular targets were mainly inflammatory mediators. Molecular docking depicted H-bonding interaction with nuclear factor kappa beta subunit (NF-κB), cyclooxygenase-2, 5-lipoxygenase, phospholipase A2, serotonin transporter, dopamine receptor D1 and 5-hydroxy tryptamine. Its cytotoxicity (IC50) value in normal lymphocytes was >20 µg/mL as compared to cancer cells (Huh7.5; 17.32 ± 1.43 µg/mL). Daturaolone significantly inhibited NF-κB and nitric oxide production with IC50 values of 1.2 ± 0.8 and 4.51 ± 0.92 µg/mL, respectively. It significantly reduced inflammatory paw edema (81.73 ± 3.16%), heat-induced pain (89.47 ± 9.01% antinociception) and stress-induced depression (68 ± 9.22 s immobility time in tail suspension test). This work suggests a possible anti-inflammatory role of daturaolone; however, detailed mechanistic studies are still necessary to corroborate and extrapolate the findings.

Genus Ficus belongs to family Moraceae having 40 genera and over 1000 species worldwide. Different methods have been used for phytochemical screening of medicinal plants like total phenolics content (TPC) and total flavonoids content (TFC) assays to quantify phenolics and flavonoids. The phytochemical analysis exhibited highest total phenolics content in M extract of stem and total flavonoids content in ethyl acetate (EA) extract of leaves i.e. 61.2±1.3 µg GAE/mg extract and 25.1±0.9 µg QE/mg extract respectively. Total reduction power and total antioxidant capacity were maximum in the M extract of stem i.e. 243.89±1.6 µg AAE/mg extract and 127.08±2.7 µg AAE/mg extract respectively.

Current study is intended to investigate the antimicrobial and antidiabetic potential of Bombax ceiba L. Antileishmanial potential was assessed via MTT colorimetric method while antifungal activities were found out through disc diffusion method. The antidiabetic potential was investigated by α-amylase inhibition assay. Considerable antifungal activity (in the range of 10-12 mm ZOI) was demonstrated by CH: M extracts of both flower and stem bark, and CH extract of root bark against A. niger Whereas M: EA, AC extracts of leaf, EA extract of stem bark, NH, CH:E, M:EA extracts of root bark and NH extract of root wood exhibited the antifungal potential (ZOI from 10-12 mm) against F. solani. The most potent α-amylase inhibitory activity was shown by EA extract of leaf part with 66.69 ± 0.95% inhibition (IC50 190 ± 4.5 µg/ml). Selected plant is a potential source of antileishmanial, antifungal and antidiabetic agents. This information can be further utilized for the purpose of bioactivity guided isolation of biologically active principles of B. ceiba L.