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Cobalt is a key metallic element required in the manufacture of lithium-ion batteries in the electric car industry, which has led to increased demand for cobalt globally. Cobalt is found associated with laterite nickel deposits but generally at lower levels. This study aims to analyze the distribution of cobalt in the laterite zone, determine cobalt-rich zones, determine cobalt-forming minerals in the limonite, saprolite and bedrock zones. As well as determining the average cobalt content in each nickel laterite zone, and determining the correlation between Co and Ni in the laterite zone. The research methodology was carried out by conducting petrographic analysis on bedrock samples to determine cobalt-forming minerals. Furthermore, X-Ray Diffraction analysis was carried out on limonite and saprolite zone samples to determine the mineral content and cobalt-forming minerals. Furthermore, conduct X-Ray Fluorescence analysis at 12 drill points to determine the percentage of cobalt elements in each laterite zone. Based on the research results, it is known that the distribution of cobalt at 12 drill points has levels in the limonite zone ranging from 0.05-0.12% Co, saprolite zone 0.02-0.05% Co, and the bedrock zone ranges from 0.01-0.04% Co. So it can be concluded that the highest cobalt distribution is in the limonite zone and the average cobalt content in the limonite zone is 0.082%; saprolite zone is 0.029%; and bedrock zone is 0.02%. The mineral identified as the cobalt-forming mineral in the bedrock samples in the study area is the mineral antigorite. The Co-Ni correlation coefficient values range from 0.01 to 0.22.

Abstract Diabetes mellitus (DM) is a rapidly prevailing disease throughout the world that poses boundless risk factors linked to several health problems. Vildagliptin is the standard dipeptidyl peptidase-4 (DPP-4) inhibitor type of medication that is used for the treatment of diabetes anti-hyperglycemic agent (anti-diabetic drug). The current study aimed to synthesize vildagliptin-loaded ZnO NPs for enhanced efficacy in terms of increased retention time minimizing side effects and increased hypoglycemic effects. Herein, Zinc Oxide (ZnO) nanoparticles (NPs) were constructed by precipitation method then the drug vildagliptin was loaded and drug loading efficiency was estimated by the HPLC method. X-ray diffraction analysis (XRD), UV–vis spectroscopy, FT-IR, scanning electron microscope (SEM), and EDX analysis were performed for the characterization of synthesized vildagliptin-loaded ZnO NPs. The UV–visible spectrum shows a distinct peak at 363 nm which confirms the creation of ZnO NPs and SEM showed mono-dispersed sphere-shaped NPs. EDX analysis shows the presence of desired elements along with the elemental composition. The physio-sorption studies, which used adsorption isotherms to assess adsorption capabilities, found that the Freundlich isotherm model explains the data very well and fits best. The maximum adsorption efficiency of 58.83% was obtained. Further, In vitro, anti-diabetic activity was evaluated by determining the α-amylase and DPP IV inhibition activity of the product formed. The formulation gave maximum inhibition of 82.06% and 94.73% of α-amylase and DPP IV respectively. While at 1000 µg/ml concentration with IC50 values of 24.11 μg/per ml and 42.94 μg/ml. The inhibition of α-amylase can be ascribed to the interactive effect of ZnO NPs and vildagliptin.

In the industrial revolution 4.0, everything is becoming digital. Additionally, the COVID-19 pandemic, and the difficulty of meeting face to face at that time, pushed everything to be done electronically or online. This is no exception for notaries, who have difficulty adapting to this all-electronic era. This research is doctrinal research which uses materials, namely literature and statutory regulations. The research results show that the Information and Electronic Transactions Law has accommodated the existence of electronic documents and information, but the Law on Notary Positions cannot expressly recognize the existence of electronic documents to be included in authentic deeds. Where other countries have adapted this cyber notary, Indonesia has not been able to apply it due to obstacles in these regulations. The exceptions contained in the Information and Electronic Transactions Law can be removed to provide space for cyber notaries in Indonesia, but the Notary Position Law must also be adjusted to provide clear guidelines for the implementation of cyber notaries.

The scientific and industrial communities now consider surface modification of steel-based alloys to be essential. One effective method of altering these alloys' surfaces is tungsten inert gas (TIG) cladding.The purpose of this study is to investigate how the surface characteristics of austenitic stainless steel substrates are affected by TIG-deposited composite coatings made of tungsten carbide and nickel (WC-Ni). The study also intends to investigate the influence of the WC-Ni composite coatings' travel speed, and as a result, the heat input usually has significant effects on the microstructure. The coating layers were deposited at different travel speeds (67, 107, and 122 mm/min) using pre-placed composite pastes that were 1 mm thick and contained the same weight percentage of WC (65). The clad layers showed a variety of microstructures in optical and scanning electron microscopy, primarily nickel solid solution dendrites with WC particles scattered throughout the matrix. The dendrites at various locations across the clad layers were few or dense, finer or coarser, equiaxial or columnar, densely or less densely branched, depending on the cooling rates and the density of WC in the composite. Energy dispersive spectroscopy demonstrated that the Fe element that was transferred from the substrate material to the molten pool was primarily concentrated in the matrix, not the dendrites, while the dendrite locations and orientations were amply demonstrated by the distribution of the W element.

Climate change, driven by the natural process of global warming, is a worldwide issue of significant concern because of its adverse effects on livestock output. The increasing trend of environmental temperature surging has drastically affected meat production and meat product quality, hence result in economic losses for the worldwide livestock business. Due to the increasing greenhouse gas emissions, the situation would get prolonged, and heat exposure-related stress is expected to worsen. Heat exposure causes metabolic and physiological disruptions in livestock. Ruminants and monogastric animals are very sensitive to heat stress due to their rate of metabolism, development, and higher production levels. Before slaughter, intense hot weather triggers muscle glycogen breakdown, producing pale, mushy, and exudative meat with less water-holding capacity. Animals exposed to prolonged high temperatures experience a decrease in their muscle glycogen reserves, producing dry, dark, and complex meat with elevated final pH and increased water-holding capacity. Furthermore, heat stress also causes oxidative stresses, especially secondary metabolites from lipid oxidation, severely affects the functionality of proteins, oxidation of proteins, decreasing shelf life, and food safety by promoting exfoliation and bacterial growth. Addressing the heat-related issues to retain the sustainability of the meat sector is an essential task that deserves an inclusive and comprehensive approach. Considering the intensity of the heat stress effects, this review has been designed primarily to examine the consequences of hot environment temperatures and related stresses on the quality and safety of meat and secondarily focus on cutting edge technology to reduce or alleviate the situational impact.

Background Insulin resistance (IR) is the key pathological basis of many metabolic disorders. Lack of asialoglycoprotein receptor 1 (ASGR1) decreased the serum lipid levels and reduced the risk of coronary artery disease. However, whether ASGR1 also participates in the regulatory network of insulin sensitivity and glucose metabolism remains unknown. Methods The constructed ASGR1 knockout mice and ASGR1-/- HepG2 cell lines were used to establish the animal model of metabolic syndrome and the IR cell model by high-fat diet (HFD) or drug induction, respectively. Then we evaluated the glucose metabolism and insulin signaling in vivo and in vitro. Results ASGR1 deficiency ameliorated systemic IR in mice fed with HFD, evidenced by improved insulin intolerance, serum insulin, and homeostasis model assessment of IR index, mainly contributed from increased insulin signaling in the liver, but not in muscle or adipose tissues. Meanwhile, the insulin signal transduction was significantly enhanced in ASGR1-/- HepG2 cells. By transcriptome analyses and comparison, those differentially expressed genes between ASGR1 null and wild type were enriched in the insulin signal pathway, particularly in phosphoinositide 3-kinase-AKT signaling. Notably, ASGR1 deficiency significantly reduced hepatic gluconeogenesis and glycogenolysis. Conclusion The ASGR1 deficiency was consequentially linked with improved hepatic insulin sensitivity under metabolic stress, hepatic IR was the core factor of systemic IR, and overcoming hepatic IR significantly relieved the systemic IR. It suggests that ASGR1 is a potential intervention target for improving systemic IR in metabolic disorders.

Abstract The protein Bcl-2, well-known for its anti-apoptotic properties, has been implicated in cancer pathogenesis. Identifying the primary gene responsible for promoting improved cell survival and development has provided compelling evidence for preventing cellular death in the progression of malignancies. Numerous research studies have provided evidence that the abundance of Bcl-2 is higher in malignant cells, suggesting that suppressing Bcl-2 expression could be a viable therapeutic approach for cancer treatment. In this study, we acquired a compound collection using a database that includes constituents from Traditional Chinese Medicine (TCM). Initially, we established a pharmacophore model and utilized it to search the TCM database for potential compounds. Compounds with a fitness score exceeding 0.75 were selected for further analysis. The Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis identified six compounds with favorable therapeutic characteristics. The compounds that successfully passed the initial screening process based on the pharmacodynamic model were subjected to further evaluation. Extra-precision (XP) docking was employed to identify the compounds with the most favorable XP docking scores. Further analysis using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method to calculate the overall free binding energy. The binding energy between the prospective ligand molecule and the target protein Bcl-2 was assessed by a 100 ns molecular dynamics simulation for curcumin and Epigallocatechin gallate (EGCG). The findings of this investigation demonstrate the identification of a molecular structure that effectively inhibits the functionality of the Bcl-2 when bound to the ligand EGCG. Consequently, this finding presents a novel avenue for the development of pharmaceuticals capable of effectively addressing both inflammatory and tumorous conditions.

Abstract Reservoir simulation is crucial for understanding the flow response in underground reservoirs, and it significantly helps reduce uncertainties in geological characterization and optimize methodologies for field development strategies. However, providing efficient and accurate solutions for the strong heterogeneity remains challenging, as most of the discretization methods cannot handle this complexity. In this work, we perform a comprehensive assessment of various numerical linearization techniques employed in reservoir simulation, particularly focusing on the performance of the nonlinear solver for problem dealing with fluid flow in porous media. The primary linearization methods examined are finite difference central (FDC), finite forward difference (FDF), and operator-based linearization (OBL). These methods are rigorously analyzed and compared in terms of their accuracy, computational efficiency, and adaptability to changing reservoir conditions. The results demonstrate that each method has distinct strengths and limitations. The FDC method is more accurate particularly in complex simulations where strong heterogeneity are introduced but is generally slower in convergence. The OBL on the other hand, is more efficient and converges quickly, which makes it suitable for scenarios with limited computational resources and simple physics, while the FDF method provides a balanced combination of precision and computational speed, contingent upon careful step size management of the derivative estimations. This paper aims to guide the selection of appropriate linearization techniques for enhancing nonlinear solvers’ accuracy and efficiency in reservoir simulation .

Abstract Cervical cancer is still the leading cause of cancer mortality worldwide even after introduction of vaccine against Human papillomavirus (HPV), due to low vaccine coverage, especially in the developing world. Cervical cancer is primarily treated by Chemo/Radiotherapy, depending on the disease stage, with Carboplatin/Cisplatin-based drug regime. These drugs being non-specific, target rapidly dividing cells, including normal cells, so safer options are needed for lower off-target toxicity. Natural products offer an attractive option compared to synthetic drugs due to their well-established safety profile and capacity to target multiple oncogenic hallmarks of cancer like inflammation, angiogenesis, etc. In the current study, we investigated the effect of Bergenin (C-glycoside of 4-O-methylgallic acid), a natural polyphenol compound that is isolated from medicinal plants such as Bergenia crassifolia, Caesalpinia digyna, and Flueggea leucopyrus. Bergenin has been shown to have anti-inflammatory, anti-ulcerogenic, and wound healing properties but its anticancer potential has been realized only recently. We performed a proteomic analysis of cervical carcinoma cells treated with bergenin and found it to influence multiple hallmarks of cancers, including apoptosis, angiogenesis, and tumor suppressor proteins. It was also involved in many different cellular processes unrelated to cancer, as shown by our proteomic analysis. Further analysis showed bergenin to be a potent-angiogenic agent by reducing key angiogenic proteins like Galectin 3 and MMP-9 (Matrix Metalloprotease 9) in cervical carcinoma cells. Further understanding of this interaction was carried out using molecular docking analysis, which indicated MMP-9 has more affinity for bergenin as compared to Galectin-3. Cumulatively, our data provide novel insight into the anti-angiogenic mechanism of bergenin in cervical carcinoma cells by modulation of multiple angiogenic proteins like Galectin-3 and MMP-9 which warrant its further development as an anticancer agent in cervical cancer.

In vitro embryo production (IVEP) encompasses a series of three basic steps, namely in vitro maturation (IVM), in vitro fertilisation (IVF), and in vitro embryo culture. IVEP approach has shown to be a valuable tool in advancing our comprehension of early mammalian development and expediting genetic enhancement in livestock. The aim of this research was to compare the impact of small and large follicles on the total number of oocytes recovered through the IVEP process. Therefore, 305 Ewe genitalia were collected at the Al-Fallujah abattoir in the Al-Anbar province. The follicles were identified, and their diameter was measured using an automated vernier calliper. Subsequently, the oocytes were classified into three distinct groups, namely excellent (A), acceptable (B), and poor (C). The results of the maturation rate of large follicles were 43.9% (51/116) and small follicles 30.7% (20/65). There was a statistical difference in maturation rate (p

Abstract Revolutionizing construction, the concrete blend seamlessly integrates human hair (HH) fibers and millet husk ash (MHA) as a sustainable alternative. By repurposing human hair for enhanced tensile strength and utilizing millet husk ash to replace sand, these materials not only reduce waste but also create a durable, eco-friendly solution. This groundbreaking methodology not only adheres to established structural criteria but also advances the concepts of the circular economy, representing a significant advancement towards environmentally sustainable and resilient building practices. The main purpose of the research is to investigate the fresh and mechanical characteristics of concrete blended with 10–40% MHA as a sand substitute and 0.5–2% HH fibers by applying response surface methodology modeling and optimization. A comprehensive study involved preparing 225 concrete specimens using a mix ratio of 1:1.5:3 with a water-to-cement ratio of 0.52, followed by a 28 day curing period. It was found that a blend of 30% MHA and 1% HH fibers gave the best compressive and splitting tensile strengths at 28 days, which were 33.88 MPa and 3.47 MPa, respectively. Additionally, the incorporation of increased proportions of MHA and HH fibers led to reductions in both the dry density and workability of the concrete. In addition, utilizing analysis of variance (ANOVA), response prediction models were created and verified with a significance level of 95%. The models' R2 values ranged from 72 to 99%. The study validated multi-objective optimization, showing 1% HH fiber and 30% MHA in concrete enhances strength, reduces waste, and promotes environmental sustainability, making it recommended for construction.

Abstract Protein-ligand binding affinity plays a pivotal role in drug development, particularly in identifying potential ligands for target disease-related proteins. Accurate affinity predictions can significantly reduce both the time and cost involved in drug development. However, highly precise affinity prediction remains a research challenge. A key to improve affinity prediction is to capture interactions between proteins and ligands effectively. Existing deep-learning-based computational approaches use 3D grids, 4D tensors, molecular graphs, or proximity-based adjacency matrices, which are either resource-intensive or do not directly represent potential interactions. In this paper, we propose atomic-level distance features and attention mechanisms to capture better specific protein-ligand interactions based on donor-acceptor relations, hydrophobicity, and $$\pi $$ π -stacking atoms. We argue that distances encompass both short-range direct and long-range indirect interaction effects while attention mechanisms capture levels of interaction effects. On the very well-known CASF-2016 dataset, our proposed method, named Distance plus Attention for Affinity Prediction (DAAP), significantly outperforms existing methods by achieving Correlation Coefficient (R) 0.909, Root Mean Squared Error (RMSE) 0.987, Mean Absolute Error (MAE) 0.745, Standard Deviation (SD) 0.988, and Concordance Index (CI) 0.876. The proposed method also shows substantial improvement, around 2% to 37%, on five other benchmark datasets. The program and data are publicly available on the website https://gitlab.com/mahnewton/daap. Scientific Contribution Statement This study innovatively introduces distance-based features to predict protein-ligand binding affinity, capitalizing on unique molecular interactions. Furthermore, the incorporation of protein sequence features of specific residues enhances the model’s proficiency in capturing intricate binding patterns. The predictive capabilities are further strengthened through the use of a deep learning architecture with attention mechanisms, and an ensemble approach, averaging the outputs of five models, is implemented to ensure robust and reliable predictions.

The partial discharge (PD) event in high-voltage insulation releases energy, exerts mechanical pressure, and generates elastic waves. Detecting and locating these PD events through short-duration acoustic pulses is well established, particularly in gas-insulated systems and oil-insulated transformers. However, its full potential remains untapped in solid insulation systems, where the propagation capability of the acoustic pulse and the acoustic reflections pose fundamental challenges to the acoustic emission (AE) detection technique. This study investigates the influence of reflections and multiple paths on the propagating acoustic pulse in polymeric insulating materials using a finite element method (FEM) in COMSOL. It was observed that the reflections from the boundary influence the propagating pulse’s shape, peak magnitude, and arrival time. An analytical MATLAB model further quantifies the impact of multiple propagation paths on the shape, magnitude, and arrival time of the pulse travelling in a cylinder. Additionally, a Perfect Matched Layer (PML) was implemented in the COMSOL model to eliminate the reflections from the boundary, and it revealed that the acoustic pulse magnitude decreases with distance following the inverse square law. In essence, the models aid in measuring how reflections contribute to the observed signals, facilitating the precise identification of the source of the PD event in the tested system.

Green supplier selection has been an important technique for environmental sustainability and reducing the harm of ecosystems. In the current climate, green supply chain management (GSCM) is imperative for maintaining environmental compliance and commercial growth. To handle the change related to environmental concern and how the company manages and operates, they are integrated the GSCM into traditional supplier selection process. The main aims of this study were to outline both traditional and environmental criteria for selecting suppliers, providing a comprehensive framework to assist decision-maker in prioritizing green supplier effectively. In order to address issue to simulate decision-making problems and manage inaccurate data. A useful technique of fuzzy set was proposed to handle uncertainty in various real-life problems, but all types of data could not be handled such as incomplete and indeterminate. However, several extensions of fuzzy set were considered, such as intuitionistic fuzzy set, Pythagorean fuzzy set, q-rung orthopair fuzzy set, and q-rung orthopair fuzzy soft set considering membership and nonmember ship grade to handle the uncertainty problem. However, there was a lack of information about the neutral degree and parameterization axioms lifted by existing approaches, so to fill this gap and overcome the difficulties Ali et al. proposed a generalized structure by combining the structure of picture fuzzy set and q-rung orthopair fuzzy soft set, known as q-rung orthopair picture fuzzy soft sets, characterized by positive, neutral and negative membership degree with parameterization tools and aggregation operator to solve the multi criteria group decision-making problem. Additionally, the TOPSIS method is a widely utilized to assist individuals and organizations in selecting the most appropriate option from a range of choices, taking into account various criteria. Finally, we demonstrate an illustrative example related to GSCM to enhance competitiveness, based on criteria both in general and with a focus on environmental consideration, accompanied by an algorithm and flow chart.

Introduction: Fine needle aspiration cytology of head and neck region is well-accepted as a diagnostic procedure. It is a safe, simple, rapid, cost-effective, and minimally invasive way of diagnosing inflammatory, noninflammatory and neoplastic lesions. Aim : To study the role of FNAC in diagnosing head & neck lesions in the paediatric age group. Material and Method: This is the hospital-based study of 120 lesions of the head and neck region belonging to the age group of 0-18 years. Cytological results are interpreted and analyzed according to anatomical site and then categorized based on interpretation. Result: Out of 120 cases 20 % cases belong to the age group 0-5yrs, 24.16% belong to 6-10yrs & 55.83% belong to the 11-18yrs age group. According to the anatomical distribution of lesions maximum cases accounting for 81.67% are lymph node lesions followed by thyroid lesions, miscellaneous, and then least salivary gland lesions which account for 2.5%. In the lymph node, thyroid, salivary gland, and miscellaneous lesions predominant lesions are respectively reactive lymphoid hyperplasia (71.42%), thyroiditis (42.85%), sialadenitis (33.34%) &epidermal cyst (40%) Conclusion: FNAC in resource-limited settings, healthcare providers should realize the importance of FNAC as an initial screening tool for superficial lesions in paediatric population. The presumptive diagnosis after FNAC of palpable lesions in paediatric age group avoids the unnecessary definitive operative procedure. Thus, FNAC is an easy, simple, rapid, and cost-effective diagnostic procedure for paediatric age group.

Recently, max-min fuzzy relation inequalities (FRIs) have been used to model a (peer-to-peer) P2P network system. Any feasible scheme in the P2P network system is reflected by a solution of the max-min FRIs. One of the objectives of system managers is to decrease network congestion. To satisfy this objective, we attempt to minimize a weighted minimax function motivated by existing research. As a consequence, we establish a weighted minimax programming model in which the constraint is the max-min FRIs. Our goal in this work is to develop an effective algorithm to obtain the optimal solution of the optimization model. The so-called SCP-based algorithm is proposed to find the optimal solution. A numerical example shows the efficiency of our proposed SCP-based algorithm.

Child care involves parents, namely father and mother, as parties who have responsibility for their children. As time goes by, sometimes disputes occur between husband and wife which result in divorce. The purpose of this writing is to find out about child maintenance after divorce according to statutory regulations. Child care after divorce is regulated in Law Number 35 of 2014 concerning Child Protection and Law Number 1 of 1974 concerning Marriage. Child maintenance after marriage in the case study of Decision Number 395/Pdt.G/2021/PN Jkt.Utr. It started with the Plaintiff (Wife) and the Defendant (Husband) who divorced, they had two sons, namely Brother A and Brother B. In this case there has been a divorce, then the parents, either father or mother, are obliged to provide maintenance for their children. until they are adults or able to stand on their own. These children's rights are supported by Article 14 of the Child Protection Law where children have the right to meet directly or have personal contact with their parents, children have the right to receive care, maintenance, education and protection for the growth and development process from their parents according to their abilities, talents and interests, the right to receive living expenses from both parents, and the right to obtain other children's rights. So that the two children of the Plaintiff and Defendant are entitled to receive maintenance in the form of a place to live with the mother because she is the closest person to the child and receives support and education from father to adult.

Abstract In this paper, we propose a fractional-order mathematical model to explain the role of glucagon in maintaining the glucose level in the human body by using a generalised form of a fractal fractional operator. The existence, boundedness, and positivity of the results are constructed by fixed point theory and the Lipschitz condition for the biological feasibility of the system. Also, global stability analysis with Lyapunov’s first derivative functions is treated. Numerical simulations for fractional-order systems are derived with the help of Lagrange interpolation under the Mittage-Leffler kernel. Results are derived for normal and type 1 diabetes at different initial conditions, which support the theoretical observations. These results play an important role in the glucose-insulin-glucagon system in the sense of a closed-loop design, which is helpful for the development of artificial pancreas to control diabetes in society.

Traditional infant monitoring systems are evolving into intelligent solutions, offering real-time notifications and automation to cater to the demands of multitasking parents. However, most IoT solutions in parental care focus solely on monitoring, lacking automatic smartphone control. In response to this gap, we developed an IoT-based system for automatic cradle monitoring. This system not only enables smartphone-based monitoring but also allows parents to control the cradle's swing speed and receive notifications through a mobile application. Our solution integrates PIR and sound sensors, an ESP8266 microcontroller, and a Wi-Fi module to create a robust monitoring system that tracks a baby's movements and sounds, sending instant notifications to the smartphone. The user can activate the system and adjust the cradle's motion using a slider based on sensor data. This IoT-enabled smart baby cradle enhances convenience and reduces parental stress, ensuring infant well-being and safety. A survey conducted among Universiti Teknologi MARA instructors revealed that 70% preferred automatic swing cradles over traditional ones, and 80% expressed the need for IoT integration in infant cradles, highlighting the growing demand for such advanced solutions.

The underwater environment is harsh and challenging for human life, prompting companies and researchers to develop advanced technologies for exploration. Building on previous work that applied a CNN-based method for underwater object classification, this paper focuses on the design and implementation of an interactive embedded system for a compact Remotely Operated Vehicle (ROV) with specific dimensions and weight. The primary goal is to capture real-time underwater video using remote control communication via Ethernet. The ROV is powered by five brushless motors controlled by a smart PID controller. Precise pulse-width modulation signals enhance stability during movements along three axes, enabling high-resolution video capture. The system utilizes the Raspberry Pi 3's computing power for motion control, positioning, temperature monitoring, and video acquisition. Experimental results demonstrate the system's capability to process 42 frames per second. A user-friendly graphical interface allows for remote ROV control across various operating systems. With a depth rating of 100 meters and speed of 0.148 m/s. This ROV surpasses human divers' limitations and holds significant potential for applications in surveillance, operations, maintenance, and measurement tasks underwater. The proposed ROV contributes to the advancement of underwater exploration technology by combining high performance with cost-effectiveness.

Rolling bearings are essential components in a wide range of equipment, such as aeroplanes, trains, and wind turbines. Bearing failure has the potential to result in complete system failure, and it accounts for approximately 45 %–50 % of failures in rotating machinery. Hence, it is imperative to establish a thorough and accurate predictive maintenance program that can efficiently foresee and prevent mishaps or malfunctions. The literature has employed a variety of techniques and approaches, from conventional methods to contemporary machine learning (ML) and ML-integrated IoT-based solutions, to categorise bearing faults. This article provides an overview of the most recent research and models used in the classification of bearing faults. The literature summary highlights various significant challenges in current models, such as issues with the classification function, complexities in the neural network structure, unrealistic datasets, dynamic working conditions of rotating machines, noise in the dataset, limited data availability, and imbalanced datasets. In order to tackle the problems, researchers have endeavored to improve and apply different methods, such as convolutional neural networks, deep belief neural networks, and LiNet, among others. Researchers have primarily developed these approaches using datasets from publicly accessible sources. This study also identified research gaps and deficiencies, including limited data availability, data imbalance, and difficulties in data integration. The nascent technologies in the field of problem diagnosis and predictive maintenance are acknowledged as Internet of Things-based ML and vision-based deep learning techniques, which are currently in their initial phases of advancement. Ultimately, the study puts forth several prospective suggestions and recommendations.

Papaver somniferum L. produces therapeutically-useful alkaloids like morphine, codeine, papaverine, and thebaine that accumulate in the latex of its capsule. Apart from its alkaloids, the edible seeds of the plant have high nutritional value and culinary use, with the seed oil being rich in the health-promoting unsaturated fatty acids. Sujata is low alkaloid-producing latex-less culinary variety of P. somniferum developed from an alkaloid-rich gum harvest parent (Sampada) for curtailing the narcotic menace of morphine and opium (dried latex). Earlier, it has been shown that the expression of stearoyl-acyl-carrier protein desaturase (PsSAD) in the young capsule and the proportion of unsaturated fatty acids in the seeds are higher in Sujata as compared to Sampada. Here, we studied bacterial endophytes isolated from Sujata tissues for their role in defining the fatty acid (saturated stearic versus unsaturated oleic) profile in its leaves and seeds. Besides, a potyvirus infecting P. somniferum was characterized through its coat protein gene sequencing and transmission electron microscopy and the two genotypes (Sujata and Sampada) contrasting in their phenotypes (oil/fatty acid, alkaloid and latex profiles) were compared for their susceptibility towards it through indicator plant- and qRT-PCR-based virus infectivity assays. In both the assays, Sujata was found to have higher susceptibility to the potyvirus, as compared to Sampada. The most plausible reason for this could be the higher PsSAD expression in the leaves of Sujata, which resulted in higher relative levels of oleic acid and lower relative levels of stearic acid in its leaves as compared to that of Sampada.

Objective: To determine the risk factors for early post-operative arrhythmias in children undergoing congenital heart surgeries at a tertiary care hospital. Study Design: Prospective longitudinal study. Place and Duration of Study: National Institute of Cardiovascular Disease, Karachi Pakistan, from Jan to Jul 2020. Methodology: We included 143 patients of both genders undergoing open heart surgery for congenital heart diseases. We noted all patients' pre-operative, intra-operative, and post-operative clinical characteristics. Patients were monitored in the pediatric cardiac intensive care unit. We analyzed the development of postoperative arrhythmias and the factors associated with them. Results: In 143 patients, the mean age at the time of surgery was 7.52±6.0 years. There were 83(58.0%) male patients. Tetralogy of Fallot was the most common type of congenital heart disease noted in 57(39.0%) patients. The mean cardiopulmonary bypass time was 83.9±25.5 minutes, while the mean aortic cross-clamp time was 58.1±21.9 minutes. Post-operatively, arrhythmia was observed in 39(27.3%) children. Intra-operative arrhythmias (p

Objective: To compare the surgical outcome of Tetralogy of Fallot patients with and without right ventricular diastolic dysfunction after repair. Study Design: Quasi-experimental study. Place and Duration of Study: Department of Cardiology, National Institute of Cardiovascular Disease, Karachi Pakistan, from May to Oct 2021. Methodology: Patients above 5 months of age, of either gender, undergoing surgery for Tetralogy of Fallot were enrolled. Patients were divided into two groups according to the Gatzoulis’ criterion for right ventricular restriction i.e. Group-A had right ventricle with restriction, and Group-B had right ventricle without restriction. Velocities of E and A waves was recorded, and their ratio (E/A) was calculated. The outcome such as aortic cross clamp, cardiopulmonary bypass time, ventilation time, intensive care unit stay, drain time, and transannular patch was noted. Results: Of 54 patients, restrictive physiology patients had significantly higher mean for aortic cross-clamp (p-value 0.004, 95%CI 3.54 - 17.35), ventilation time (p-value

Millions of people in developing countries lack access to modern energies and for long, these countries have relied on energy subsidies to scale up their access rate. However, there is no evidence that those energy subsidies contribute to energy poverty reduction. Similarly, while good governance and strong institutions are touted as critical for implementing energy policy and improving access rate, empirical evidence of their impact remains very scanty. This study assesses the impact of energy subsidies and institutional quality on access to electricity in selected developing countries. Result from the Praise-Winston regression revealed that energy subsidies as a policy tool for achieving universal electrification do not hold in the selected developing countries. We also found that energy subsidies accompanied by a strong governance mechanism can help developing countries scale up their electricity access rate. We recommend practical ways to help developing countries achieve universal access to modern energy solution.

Randomized response scrambling techniques have been in existence for over fifty years. These scrambling methods are very useful in sample surveys where researchers deal with sensitive variables. Out of many available scrambling techniques, survey researchers often need to evaluate these techniques to choose the best technique for real-world surveys. In the current literature, only a limited number of model-evaluation metrics are available for analyzing the performance of different scrambling methods. This leaves a big research gap for the development of new unified evaluation measures which can quantify all aspects of a scrambling technique. We develop a novel unified metric for evaluation of randomized response models and compare it with the existing unified measure. The proposed measure can quantify the efficiency and the level of the respondents’ privacy of any scrambling technique. Being less sensitive to sample sizes than the existing unified measure, the proposed measure can be used with small sample sizes to evaluate models.

In a variety of industries, including transportation, agriculture, and manufacturing, diesel engines are often employed. Due of rising prices and environmental concerns, researchers examined whether biodiesels might replace diesel. The current study looks into American Saffron Oil's feasibility as a feedstock for biodiesel production. The transesterification technique is used to extract American saffron oil methyl este(ASOME), which is then examined for its physical and chemical properties in accordance with ASTM standards. Diesel fuel and American Saffron Oil methyl ester are mixed on a volume basis to create a variety of fuel blends, including B20, B40, and B60. The test results showed that the 20 % ASOME mix had better performance and reduced emissions. Also, utilizing DIESEL-RK simulation software, diesel engine tests are conducted for the B20, B40, and B60 under identical operating circumstances. Moreover, diesel engine testing for the B20, B40, and B60 are carried out using DIESEL-RK simulation software under comparable operating circumstances. Results of simulation software tests show improved engine performance and reduced pollutants. When experimental data is compared to DIESEL-RK modeling software, it is found that brake thermal efficiency increased by 5.7 % and emissions of hydrocarbon and carbon monoxide decreased by 2.5 % and 14.3 %, respectively.

This study introduces innovative operational laws, Einstein operations, and novel aggregation algorithms tailored for handling q-spherical fuzzy rough data. The research article presents three newly designed arithmetic averaging operators: q-spherical fuzzy rough Einstein weighted averaging, q-spherical fuzzy rough Einstein ordered weighted averaging, and q-spherical fuzzy rough Einstein hybrid weighted averaging. These operators are meticulously crafted to enhance precision and accuracy in arithmetic averaging. By thoroughly examining their characteristics and interrelations with existing aggregate operators, the article uncovers their distinct advantages and innovative contributions to the field. Furthermore, the study illustrates the actual implementation of these newly constructed operators in a variety of attribute decision-making scenarios employing q-SFR data, yielding useful insights. Our suite of decision-making tools, including these operators, is specifically designed to address complex and uncertain data. To validate our approach, this study offers a numerical example showcasing the real-world applicability of the proposed operators. The results not only corroborate the efficacy of the proposed method but also underscore its potential significance in practical decision-making processes dealing with intricate and ambiguous data. Additionally, comparative and sensitivity analyses are presented to assess the effectiveness and robustness of our proposed work relative to other approaches. The acquired knowledge enriches the current understanding and opens new avenues for future research.

Arsenic (As) contamination of agricultural soils poses a serious threat to crop productivity and food safety. Zinc oxide nanoparticles (ZnONPs) have emerged as a potential amendment for mitigating the adverse effects of As stress in plants. Soybean crop is mostly grown on marginalized land and is known for high accumulation of As in roots than others tissue. Therefore, this study aimed to elucidate the underlying mechanisms of ZnONPs in ameliorating arsenic toxicity in soybean. Our results demonstrated that ZnOB significantly improved the growth performance of soybean plants exposed to arsenic. This improvement was accompanied by a decrease (55%) in As accumulation and an increase in photosynthetic efficiency. ZnOB also modulated hormonal balance, with a significant increase in auxin (149%), abscisic acid (118%), gibberellin (160%) and jasmonic acid content (92%) under As(V) stress assuring that ZnONPs may enhance root growth and development by regulating hormonal signaling. We then conducted a transcriptomic analysis to understand further the molecular mechanisms underlying the NPs-induced As(V) tolerance. This analysis identified genes differentially expressed in response to ZnONPs supplementation, including those involved in auxin, abscisic acid, gibberellin, and jasmonic acid biosynthesis and signaling pathways. Weighted gene co-expression network analysis identified 37 potential hub genes encoding stress responders, transporters, and signal transducers across six modules potentially facilitated the efflux of arsenic from cells, reducing its toxicity. Our study provides valuable insights into the molecular mechanisms associated with metalloid tolerance in soybean and offers new avenues for improving As tolerance in contaminated soils.

Abstract N‐methyl‐D‐aspartate receptor (NMDAR)‐positive allosteric modulators (PAMs) represent a potential therapeutic strategy for cognitive impairment in disorders associated with NMDAR hypofunction, including Huntington's disease (HD) and Alzheimer's disease. Dalzanemdor (SAGE‐718) is a novel, investigational NMDAR PAM being evaluated for the potential treatment of cognitive impairment in these disorders. We report first‐in‐human, phase I, double‐blind, dose‐finding studies to assess the safety, tolerability, and clinical pharmacology of dalzanemdor. A single‐ascending dose study (dalzanemdor 0.35, 0.75, 1.5, or 3.0 mg vs. placebo) was conducted in healthy participants and included food effects. A multiple‐ascending dose study (14 days) was conducted in healthy participants (dalzanemdor 0.5 or 1.0 mg vs. placebo) and HD participants (open‐label dalzanemdor 1.0 mg) and included exploratory pharmacodynamics on cognitive performance. Dalzanemdor was generally well tolerated with no adverse events leading to discontinuation. Dalzanemdor exhibited pharmacokinetic parameters appropriate for once‐daily dosing. Following single and multiple doses in healthy participants, median terminal half‐life was 8–118 h, and the median time to reach maximum plasma concentration was 4–7 h. Exposures were dose‐proportional after single dose (6–46 ng/mL) and more than dose‐proportional after multiple doses (6–41 ng/mL). With multiple dosing, a steady state was achieved after 11 days in healthy participants and 13 days in HD participants. Dalzanemdor exposure decreased slightly with food. In HD participants, results suggest that dalzanemdor may improve cognitive performance on tests of executive function. These results support continued clinical development of dalzanemdor for the potential treatment of cognitive impairment in disorders of NMDAR hypofunction.

Nowadays, thermal comfort is becoming a major problem for people due to increasing global warming and climatic changes, but it can be resolved by the concept of Heating, Ventilation, and Air Conditioning (HVAC) systems. The purpose of HVAC is to provide occupants with a comfort zone so that they can feel comfortable according to their thermal comfort. The core objective of this study is to design and propose an HVAC system as per actual design conditions for the University Auditorium located in Karachi, Pakistan. A direct Expansion (DX – Type) system is installed in the Auditorium that has exceeded the lifespan of twenty years, refrigerant R-22 which is currently being used has been obsolete due to its high GWP (Global Warming Potential) and ODP (Ozone Depletion Potential) values which are 1810 and 0.05 respectively. To achieve the objective of this study, two approaches are employed. Cooling Load Temperature Difference (CLTD) method & Hourly Analysis Program (HAP) software. The cooling load calculated from the CLTD method is 202 kW equivalent to 57.5 Ton of Refrigeration (TR). On the other side, the cooling load calculated from HAP software is 192.8 kW equivalent to 55 TR. By considering the calculated cooling load for the University Auditorium, two different HVAC systems are proposed, based on Water cooled and Air-cooled Vapor Compression Cycle. After this study, engineers will be able to design an HVAC system for any facility as per design conditions. Also, they can propose different cost-effective and energy-efficient HVAC systems for that particular space.

As the demand for energy continues to rise unabated, an examination of the constraints posed by finite fossil fuel reserves becomes crucial. There is need to explore and underscore the imperative shift towards renewable energy resources, where, solar energy is widely available and can readily be used in different applications, especially in water desalination applications. In the present research, photothermal performance of water based nanofluids containing graphene oxide (GO), zinc oxide (ZnO), iron oxide (FeO), and their composites (GO-ZnO and GO-FeO) have been studied under the natural sun to determine the potential for water desalination applications. All type of the nanofluid are prepared through a two-step method and are characterized morphologically using a scanning electron microscope (SEM). UV–visible spectroscopy is used to assess the optical absorbance of prepared nanofluids. The outcomes of this study show that pure GO nanofluids exhibited excellent absorption in the visible and near-infrared regions as compared to other nanofluids used in this research study, which makes them efficient nanofluids in converting solar energy into heat. For more assessment, a direct or volumetric solar thermal collector was used to evaluate the photothermal efficiency of water based nanofluids GO, ZnO, FeO, and their binary composites of GO-ZnO, and GO-FeO under natural solar flux at weight concentrations (0.01 wt%). The sensible heating efficiency due to the rise in temperature and latent heat of evaporation efficiency due to mass loss of nanofluid samples contributed towards photothermal efficiency. Pure GO nanofluids showed the highest photothermal efficiency, which is 71 % among all the nanofluids used in this study due to their carbon-based structure, highest optical absorption peak, excellent dispersion stability, and highest thermal conductivity. This experimental work also revealed that binary nanofluids containing composites of (GO-ZnO) and (GO-FeO) showed higher photothermal efficiency as compared to individual nanofluids ZnO and FeO except graphene oxide GO. According to the results and observation of this experimental work, pure GO-based nanofluids are potential candidates for direct absorption solar collection used in water desalination applications.

Background: Gaming is a new phenomenon and there are increasing concerns over its negative impact. After the official recognition by diagnostic and statistical manual-5 and International Classification of Disorder-11, much of the research is directed toward understanding the different constructs of the gambling disorder. Peer influence is an established factor in substance use but less researched in gaming. Aims of the Study: The aim of this study is to explore and understand the influence of peer pressure on Internet gaming. Materials and Methods: Individuals between 15 and 35 years were asked to participate after explaining the study objectives and assessed on the Peer Pressure Scale and Internet Gaming Disorder (IGD) Scale. Responses were analyzed using the R language with R studio as the integrated development environment. Generalized additive model was used to identify the best-fit model. The Akaike information criterion was used to select the best model. Results: Battle Ground Mobile India is the most played game. Peer pressure alone accounts for 46.2% of the variability in Internet gaming and along with factors such as student; real friends; strategy games; online mode of playing, night time playing; and hours spent playing, increasing it to 56%. Peer pressure is positively correlated with IGD (P < 0.001, R = 0.65). Conclusions: Peer pressure is directly associated and plays a role in developing Internet gaming along with factors such as being a student; playing with real friends; strategy game genre; online mode of playing games; and nightly playing. Substance use such as tobacco may influence peer pressure and Internet gaming, acting as a co-factor for both.

We presented a methodology for detecting acute lymphoblastic leukemia (ALL) based on image data. The approach involves two stages: Feature extraction and classification. Three state-of-the-art transfer learning models, InceptionResnetV2, Densenet121, and VGG16, were utilized to extract features from the images. The extracted features were then processed through a Global Average Pooling layer and concatenated into a flattened tensor. A linear support vector machine (SVM) classifier was trained and tested on the resulting feature set. Performance evaluation was conducted using metrics such as precision, accuracy, recall, and F-measure. The experimental results demonstrated the efficacy of the proposed approach, with the highest accuracy achieved at 91.63% when merging features from VGG16, InceptionResNetV2, and DenseNet121. We contributed to the field by offering a robust methodology for accurate classification and highlighted the potential of transfer learning models in medical image analysis. The findings provided valuable insights for developing automated systems for the early detection and diagnosis of leukemia. Future research can explore the application of this approach to larger datasets and extend it to other types of cancer classification tasks.

Passing is one of the fundamental techniques in football. Good passing skills enable players to participate in the game effectively and maintain possession of the ball. Paired short passing drills also help improve individual skills. This research aims to find out whether short passing training in pairs can increase the accuracy of soccer passing in adolescent soccer players. The quantitative method used in the research is a pre-experimental design through one group pretest and posttest. The research instrument used a ball passing accuracy test for 30 seconds and used the short passing practice method in pairs. The population in this study consisted of 20 male Rekminers Club soccer players aged 15-17 years. The sample was selected using a total sampling technique, and the entire population sampled was 20 players. The data analysis technique uses the t-test to test the hypothesis to increase soccer passing accuracy in the pretest and posttest treatment using SPSS version 26. Based on the results of hypothesis testing using the t-test in paired short passing exercises with football passing accuracy ability, there is a significant influence based on pretest and posttest data analysis of 0.000 < 0.05. This exercise was successfully carried out to improve the accuracy of football passing. The research results show that short passing training in pairs is an effective method for improving the passing accuracy of football players.

Objectives: Keeping in view the economic and veterinary public health importance of brucellosis, this research was conducted to determine its seroprevalence and associated risk determinants in small ruminants in district Khanewal, Southern Punjab, Pakistan. Materials and Methods: Two-stage cluster sampling technique was used for sampling, and the sample size was calculated using C-survey 2.0. Accordingly, sera samples (n = 392) were collected from small ruminants in the study area from October 2022 to July 2023. All the samples were tested for the presence of anti-Brucella antibodies by Rose Bengal Plate Test (RBPT), followed by confirmation of all the samples using an enzyme linked immunosorbent assay (ELISA) kit (ID.vet®, France; sensitivity and specificity=100%, each). Results: The seropositivity rate of brucellosis was 7.14% [n = 28/392; 95% confidence interval (CI) = 4.87%–10.12%] by RBPT, whereas the results of ELISA showed an overall seroprevalence rate of 7.40% (n = 29/392; 95% CI = 5.11%–10.37%) in the study population. Univariate analysis of risk factors revealed that abortion history (AH), retained fetal membranes (RFMs), repeat breeding, flock size (FS), educational status of farmers (ESFs), awareness about brucellosis (AB), and farm hygiene had a significant association with the seroprevalence of brucellosis (p < 0.05). The multivariate analysis using a binary logistic regression model revealed that variables including tehsil, FS, AH, RFM, ESF, AB, and farming system were significant factors (p < 0.05) associated with brucellosis in the target population. Conclusion: Brucellosis is prevalent in small ruminants in Khanewal, Pakistan. The disease burden can be reduced by improving the reproductive health of animals, farm hygiene, and farmers' awareness about the diseases. Further studies are needed on a larger scale to devise stringent disease control strategies to avoid losses associated with brucellosis at regional, national, and global levels. [J Adv Vet Anim Res 2024; 11(1.000): 9-18]

Groundwater is very important part of life and source of survival on earth; and the clean water is one of the most important issues of the developed or developing world. In addition to other secondary problems such as solid waste and resource waste management, wastewater management is a major environmental obstacle to the development of the textile industry. Textile industry is the largest industrial sector of the world and hold very important part for the development of economy in all countries. Although the industry generates a lot of chemicals, including dyes in the form of wastewater. The textile industry is most fresh water consuming industry; simultaneously it discharges the huge load of contamination in our environment. The textile industry is the largest producer of wastewater during its different production processes. The wastewater creates several problems such as health problems, aquatic life including water pollution. The textile industry wastewater is treated by different methods such as coagulation, adsorption, membrane, and biological treatment. This paper reviews the different treatment technologies for textile wastewater along with its advantages and disadvantages. The objective of this study is to contribute a summary on the best and latest treatment techniques for textile industry effluent.

Abstract Background Early pregnancy nutritional status can be associated with adverse birth outcomes such as small-for-gestational age (SGA) and low birth weight (LBW). BMI (Body Mass Index) and MUAC (Mid-upper arm circumference) are easy to use assessments and are indicative of the pre-pregnancy nutritional status if obtained in the first trimester. This study primarily assesses the association of maternal nutritional status using BMI and MUAC with SGA in a community-based cohort of Pakistani women. It also aims to determine the predictive ability of MUAC and BMI in predicting SGA. Secondarily, we assessed the association between maternal nutrition and large for gestational age (LGA) and LBW. Methods This study is a secondary analysis of an ongoing pregnancy cohort “Pregnancy Risk Infant Surveillance and Measurement Alliance (PRISMA)“in Ibrahim Hyderi and Rehri Goth, Karachi. PRISMA participants who were enrolled between January 2021 to August 2022 were included given they had a gestational age

Objectives: Tanzania observed a gradual increase in the number of measles cases since 2019 with a large outbreak recorded during 2022. This study describes the trend of measles in Tanzania over a 5-year period from 2018-2022. Methods: This was a descriptive study conducted using routine measles case-based surveillance system including 195 councils of the United Republic of Tanzania. Results: Between 2018 and 2022 there were 12,253 measles cases reported. Out of 10,691 (87.25%) samples tested by enzyme-linked immunosorbent assay, 903 (8.4%) were measles immunoglobulin M positive. The highest number of laboratory-confirmed measles cases was in 2022 (64.8%), followed by 2020 (13.8%), and 2019 (13.5%). Out of 1279 unvaccinated cases, 213 (16.7%) were laboratory-confirmed measles cases compared to 77/723 (10.6%) who were partially vaccinated and 71/1121 (6.3%) who were fully vaccinated (P 90% since 2013 while MCV2 increased gradually reaching 88% in 2022. Conclusions: Accumulation of susceptible children to measles due to suboptimal measles vaccination coverage over the years has resulted in an increase in the number of laboratory-confirmed measles cases in Tanzania with more cases recorded during the COVID-19 pandemic. Strengthening surveillance, routine immunization, and targeted strategies are key to achieving the immunity levels required to interrupt measles outbreaks.

Multi-criteria decision-making (MCDM) approaches prove to be effective and reliable in addressing problems under uncertain conditions. The q-spherical fuzzy rough set (q-SFRS) represents the latest advancement in fuzzy set theory. This article aims to introduce a novel approach, q-spherical fuzzy rough Combinative Distance-based Assessment (q-SFR-CODAS), by integrating CODAS with q-SFR set to address MCDM problems. The method utilizes the Hamming distance as the primary measure and the Euclidean distance as the secondary measure to assess the desirability of alternatives, calculated concerning the negative-ideal solution. Additionally, an illustrative example is presented to demonstrate the applicability of the proposed methodology. A comprehensive sensitivity analysis is conducted to validate the results of q-SFR-CODAS, comparing them with existing MCDM methods.

This review explores the potential of floating waterwheel power generation systems as a sustainable source of energy. With increasing concerns about environmental degradation and the need for renewable energy sources, the utilization of flowing water for power generation presents an attractive solution. By analyzing existing literature and case studies, this review assesses the feasibility and effectiveness of floating waterwheel systems in harnessing energy from rivers and streams. Key metrics, including the total potential of floating hydro generation systems and their contribution to renewable energy, are evaluated to provide insights into the scalability and impact of this technology. Furthermore, the review identifies the most viable types of generating systems and highlights the environmental benefits they offer. This paper outlines the significant potential of floating hydro generation systems, with an estimated contribution of up to 10% of global renewable energy production. Among these systems, tidal barrage technology stands out as the most viable option, offering predictability and high energy density. By harnessing the power of moving rivers and tides, this technology addresses the pressing demand for clean energy while minimizing environmental impact compared to traditional dams. By addressing these aspects, this study aims to contribute to the advancement of eco-friendly energy solutions and provide valuable insights for policymakers, researchers, and industry professionals working in the field of renewable energy.

This paper presents a geometry-based three-dimensional Probability of Line of Sight $(P_{\mathrm {LoS}})$ model for generic urban environments. The existing $P_{\mathrm {LoS}}$ models are mostly empirical, based on measurements or ray-tracing simulations at specific environments. To enable Unmanned Aerial Vehicle (UAV) communication in various environments, it is urgently necessary to develop an analytical model with high parameter scalability. Through introducing the ITU model that describes a built-up environment with three parameters, we derive a closed-form $P_{\mathrm {LoS}}$ model with the inputs of city built-up parameters, UAV altitude, elevation $\theta $ and azimuth $\varphi $ angles between UAV and User Equipment (UE). Furthermore, we develop a geometry-based simulator to validate the proposed analytical model. The results show good agreements between the simulated results, analytical results, and 3GPP $P_{\mathrm {LoS}}$ measurements. We demonstrate that the existing models provide less accurate results, which calls for re-evaluating the use cases and performance of UAV-mounted communication equipment in urban environments.

Background: The design of majority of commercially available knee implants has their basis on data obtained from the European population. Anthropometric research has demonstrated a difference in the shape and size of proximal tibia and distal femur between the genders and ethnic groups. Underfit or overhang of prosthetic components can result in poor clinical and functional outcomes with need for revision. This study compares the dimensions of the knee in multiple racial groups to observe if significant racial and gender differences occur. Methodology: Morphometric parameters of the knee of adult patients (>18 years) in four population groups (Native Emirati, East Asian, Indian, and Caucasian) were measured using magnetic resonance imaging. Knee parameters were obtained from 368 patients (179 females and 189 males). Results: Males have larger femoral and tibial parameters compared to females (P < 0.01). For any specified anteroposterior length of knee, females demonstrate narrower mediolateral widths compared to males. Significant differences exist in knee parameters between the racial groups in both genders (P < 0.01). Conclusion: Adult knee parameters show significant variation between the genders and racial groups showing strong evidence for a race- and gender-specific knee arthroplasty system.

Hypertension is the leading risk factor for preventable cardiovascular diseases and all-cause mortality globally, with majority of the hypertension-attributed deaths occurring in low- and middle-income countries like India. Several international and national clinical practice guidelines (CPGs) provide evidence-informed recommendations to achieve optimal control. CPGs produced by the World Health Organization, International Society for Hypertension, American (AHA/ACC-2017), and European (ESC/ESH-2018) are “major” as they are widely used and are highly cited. We compared the main recommendations for the pharmacological management of hypertension among the major CPGs and the two existing Indian CPGs for similarities and shortcomings. Several deviations from the major CPGs were observed among Indian CPGs. Important shortcomings pertain to Indian CPGs’ low priority for initial combination therapy and the use of single pill combinations. Having multiple CPGs providing conflicting recommendations might discourage the adoption of evidence-based practices. There is a need for updating Indian CPGs based on up-to-date evidence.

Abstract Background Brucellosis is a zoonotic disease caused by a bacterial pathogen belonging to the genus Brucella. It is one of the most frequent bacterial zoonoses globally but unfortunately, it is still considered as a neglected disease in the developing world. Keeping in view, this study was conducted to determine the prevalence and risk determinants of brucellosis in large ruminants of peri-urban and rural areas of district Multan-Pakistan. For this purpose, blood samples (n = 490) were collected from the cattle (n = 245) and buffalo (n = 245) population of the study area and subjected to preliminary screening of brucellosis using local and imported RBPT reagents. All the samples were further analyzed using commercially available multi-specie indirect ELISA kit followed by their confirmation by PCR using genus and species-specific primers. Data obtained from lab analysis and questionnaires were subjected to statistical analysis for Pearson Chi-square, Odds Ratio and Confidence intervals (95%). Results The results showed that the maximum seropositivity was recorded with local RBPT reagent (VRI, Pakistan; 12.45%; 95%CI = 9.72–15.65%) followed by RBPT-IDEXX (12.24%; 95%CI = 9.52–15.45%) and RBPT-ID.vet (11.84%; 95%CI = 9.18–14.95%) however statistical difference was non-significant (P = 0.956). The ELISA results showed an overall seroprevalence rate of 11.22% (95%CI = 8.59–14.33%) with comparatively higher rate in cattle (12.65%; 95%CI = 8.82–17.44%) as compared to buffaloes (9.80%; 95%CI = 6.49–14.15%). The PCR analysis confirmed the presence of genus Brucella in all seropositive samples whereas frequency of B. abortus and B. melitensis in seropositive samples was 80% and 20%, respectively. The co-existence of both species was also observed in 5.45% samples. The statistical analysis showed a significant association of bovine brucellosis with herd size, breed, reproductive disorders, mode of insemination, educational status and farmers’ awareness about brucellosis (P 0.05). Conclusion In conclusion, brucellosis is prevalent in large ruminants of district Multan, Pakistan. It is suggested to devise and implement stringent policies for the effective control and prevention of brucellosis in the region. Further, the current situation also warrants the need to strengthen interdisciplinary coordination among veterinarians and physicians in one health perspective to ensure and strengthen the human and animal health care systems in the region.