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Background: Karachi one of the largest and fastest-growing cities in the world, the city faces severe water scarcity and aggravated by climate change, excessive groundwater extraction in dense urban areas and inefficient water distribution systems. The Hub Dam, along with the Keenjhar Lake, is the source of water for Karachi's population as well as for the industrial and urban agricultural sectors. It is therefore important to have current information on the dam's storage capacity, its topographic features and the hydrological dynamics of its catchment area, which remains poorly understood to date. Objectives: This study's primary objectives are (1) to assess the hydrography of Hub Dam using global bathymetric and remote sensing data and (2) to create a detailed 3D model of the dam to facilitate analysis of its hydrological features. (3) Also generate data-driven insights to guide improvements in Karachi’s urban water management policies. Methods: The methodology integrates global bathymetric data with remote sensing and Google Earth Engine (GEE) for analysing Hub Dam’s hydrological and topographic characteristics. Data processing and visualization were conducted in Google Colab by python codes. This process enabling an efficient workflow for handling and analysing large datasets. Results: Hub Dam 3D model is developed. The approaches is enhancing visualization of the dam's water volume and terrain features to support detailed hydrological analysis. 3D volumetric analysis estimates with total water volume at approximately 79.954 · 106 m3. It was found that currently, the Hub Dam reservoir has enough water to fulfil Karachi needs for 503 days, a critical reserve for urban planning, resource management. Using a topographic analysis that includes surrounding slopes and watershed features, key elements affecting dam performance were identified. This result helps to adjust the filling of the dam with water. The Hub Dam's ability to store water was confirmed through a preliminary volume assessment. Conclusion: The study successfully achieved its objectives. The results obtained highlight the importance of adaptive well informed strategies for sustaining well managed water resources in response to environmental pressures. The current study further advance rational water management by integrating remote sensing and data-driven methodologies into this area of knowledge. That is, the effectiveness of Using Remote Sensing and Global Bathymetry Data has been repeatedly proven by other studies in different areas of knowledge. However, in the current study, this scientific approach has successfully demonstrated the efficient and rapid acquisition of accurate, up-to-date information on reservoir capacity and hydrological characteristics, which opens up new opportunities for efficient water management.

The Moon, as the closest celestial body to the Earth, plays a pivotal role in the progression of deep space exploration, and the establishment of research outposts on its surface represents a crucial step in this mission. Lunar lava tubes are special underground caves formed by volcanic eruptions and are considered as ideal natural shelters and scientific laboratories for lunar base construction. This paper begins with an in-depth overview of the geological origins, exploration history, and distribution locations of lunar lava tubes. Subsequently, it delves into the presentation of four distinctive advantages and typical concepts for constructing bases within lava tubes, summarizing the ground-based attempts made thus far in lunar lava tube base construction. Field studies conducted on a lava tube in Hainan revealed rock compositions similar to those found during the Apollo missions and clear lava tube structures, making it a promising analog site. Lastly, the challenges and opportunities encountered in the field of geotechnical engineering regarding the establishment of lunar lava tube bases are discussed, encompassing cave exploration technologies, in-situ testing methods, geomechanical properties under lunar extreme environments, base design and structural stability assessment, excavation and reinforcement techniques, and simulated Earth-based lava tube base.

Background: The strength of the binding between brackets and tooth surfaces has a major impact on how well orthodontic therapy works. The shear bond strength of orthodontic brackets may be strengthened by the invention of bonding agents supplemented with nanoparticles, thanks to recent developments in nanoparticle technology. Materials and Methods: In order to perform a randomized controlled experiment, 90 human premolars were excised for orthodontic purposes. Three groups of 30 teeth were randomly assigned to each group: Group A used a bonding agent augmented with nanoparticles of titanium dioxide (TiO2), Group B used nanoparticles of zirconium dioxide (ZrO2), and Group C used a standard bonding agent as a reference. The appropriate bonding chemicals were used to attach the brackets to the teeth, and a universal testing equipment was used to measure the shear bond strength. Stereomicroscopic analysis was used to evaluate the failure mechanisms. To do statistical analysis, Tukey’s post hoc test and analysis of variance were used. Results: There were significant differences (P < 0.05) in the mean shear bond strength values across the groups. The average shear bond strength for Group A (TiO2) was 18.5 ± 2.3 MPa, that for Group B (ZrO2) was 17.2 ± 2.6 MPa, and that for Group C (control) was 14.8 ± 2.4 MPa. In comparison to Groups B and C, Group A exhibited a statistically greater bond strength, although Group B also showed an improvement over the control. According to the failure mode analysis, the control group had mostly adhesive failures, whereas the nanoparticle groups saw mixed failures. Conclusion: When TiO2 and ZrO2 nanoparticles are added to bonding agents, the shear bond strength of orthodontic brackets is greatly increased in comparison to traditional bonding agents. TiO2-reinforced materials performed better, pointing to possible benefits for orthodontic applications. It is advised that further study be done to examine the long-term impacts and therapeutic implications of these results.

Exploring substantial solar irradiation and recuperating excess heat generated during photovoltaic energy conversion is a critical issue. The efficiency of photovoltaic systems (PV) is significantly depend on the increased operating temperatures encountered by solar radiation. One conceivable option for improving the conversion of solar energy is to integrate a photovoltaic (PV) panel with a thermal-electric generator (TEG) material module to create a hybrid system. This study proposed a parallel PV-TEG hybrid module that effectively harvests the maximum solar energy spectrum while maximizing the use of heat generated by the thermoelectric material to improve the overall system efficiency. The proposed module consists of a photovoltaic unit, thermoelectric material module and passive cooling of fluid channels. The aim of this work was to develop a PV-TEG hybrid system and create an energy simulation model in a MATLAB environment to analyze the model's performance under various operational conditions by applying both theoretical and experimental approaches. Findings showed considerable concurrence. At 13:00, when the PV surface temperature was 54 °C, the PV efficiency reached to its lowest value of 12.0 %. Nevertheless, the highest TEG efficiency recorded was 4.7 % at 12:00 h. The efficiency of the TEG module was significantly affected by weather conditions, inlet cooling water temperature, and fluid flow rate in comparison to both the PV efficiency and the thermal efficiency.

An increasing amount of land is becoming unsuitable for citrus cultivation, mainly due to water scarcity. This study evaluated the physiological and biochemical performance of trifoliate orange (Poncirus trifoliata) and rough lemon (Citrus jambhiri) seedlings subjected to water deficit for 12 days. Under these conditions, trifoliate orange was more sensitive than rough lemon and exhibited significant changes in LRWC (64.8% vs 36.7%), gas exchange parameters (71.7% vs 54.3% on average), leaf surface area (18.2% vs 4.9%), chlorophyll fluorescence in dark- and light-adapted leaves (44.5% vs 33.3% on average) and non-photochemical quenching (94.3% vs 28.2%). Moreover, oxidative stress indicators, such as malondialdehyde or hydrogen peroxide, indicated significantly higher values in trifoliate orange than in rough lemon seedlings. They also showed lower antioxidant defense activation. Other biochemical parameters, such as proline, glycine betaine, antioxidant capacity, phenolic content, and total soluble proteins, showed higher levels in rough lemon than in trifoliate orange seedlings. Overall, the better performance of rough lemon in arid conditions could be attributed to its improved ability to prevent water loss and maintain tissue water content. In addition, rough lemon has a more robust antioxidant defense to keep production of reactive oxygen species at low levels.

A field experiment was performed to assess the impact of potassium co-amended with boron at different application rates on organic matter, nitrogen, phosphorus, potassium and boron in the soil, also in terms of plant height, spike length, pedicel length, leaf area, spike weight, grain weight, biological yield, fresh biomass and dry biomass of wheat under the dry climate of Uthal. Randomized complete block design (RCBD) was used with the combined application of both K and B fertilizers with a replicate of three times, treatments were T0 control, T1 70 K kg×ha–1 and 0.6 B kg×ha–1, T2 140 K and 1.2 B kg×ha–1, T3 210 K and 1.8 B kg×ha–1 of potassium and boron respectively. Furthermore, boron was applied in three split doses (time of sowing, maturity of plant, and booting stage); whereas potassium was used in two split doses (before sowing and maturity). The obtained results demonstrated that plant height was increased, ranging from 77.68 to 83.00 cm, with T3, biological yield 14,150.0–19,186.67 kg×ha–1 with T3, in-soil N 0.04–0.069% with T3, in-soil P 3.42–3.89 mg×kg–1 with T3, in-soil K 82.00–120.00 mg×kg–1 with T3, in-soil B 0.11–0.22 mg×kg–1 with T3 than control treatment. The uptake NPK, and B by the wheat plant was increased, ranging from 1.17–1.66% with T3, 0.33–0.54 mg×kg–1 with T3, 2.32–2.72 mg×kg–1 with T3, and 1.12–1.14 mg×kg–1 with T3 as compared with the control treatment. The plant fresh and dry biomasses and soil organic matter were increased at T3 over that of the control soil. Overall, the findings of this study indicated that the co-application of potassium and boron at 210 and 1.8 kg×ha–1 doses can be successfully used to enhance grain and yield parameters of wheat, particularly those cultivated in dry climatic conditions.

Populus spp. belongs to the deciduous flowering plants in the family Salicaceae, primarily located in the Northern Hemisphere, including Trans-Himalayan, cold arid desert Ladakh. In Ladakh, it is predominantly cultivated in irrigated land patches along the riverbanks. This plant holds significant economic value as its wood is extensively used in furniture-making and house constructions. Recently, a highly successful pest, identified as Pheosia albivertex (Hampson 1983), was observed infesting the Populus plantations, marking a new record of insect infestation. The pest causes complete defoliation, particularly during midsummer, which is the prime foliage period. The initial sighting of this insect occurred in Dyanguchay village, Suru-valley, Kargil district of the union territory of Ladakh. However, during a thorough three-year-and-five-month investigation from April 2019 to August 2022, it was found spreading to neighbouring areas. Consequently, without timely control measures, it poses a significant threat to the popular plantation in Ladakh and other adjoining areas.

Background: Major surgeries can develop metabolic acidosis during the perioperative period. Any clinical condition leading to decreased tissue oxygenation causes lactate levels to rise proportionally. Aims and Objectives: This study was aimed at evaluating perioperative serum lactate as a predictor of length of hospital stay and in-hospital mortality in patients undergoing emergency major abdominal surgeries. Materials and Methods: Adult patients posted for emergency abdominal surgical procedures were enrolled for 2 years. Patients were observed intraoperatively and lactate levels were measured. In post-operative period lactate levels were recorded for 24 h. Relationship of lactate with hospital length of stay and in-hospital mortality was analyzed. Results: Total of 93 patients were enrolled for 2 years. Mean age was 50.4 years. Mean baseline lactate was 2.95 mmol/L. Total in-hospital mortality was 16.1%. Thirteen patients had perioperative serum lactate level of ≤ 2 mmol/l, with a mean hospital length of stay of 8.6 days and no mortality. Fifty-one patients having perioperative serum lactate between 2 and 4 mmol/L, with a mean hospital length of stay of 11.2 days and mortality of 13.3%. Twenty-nine patients had serum lactate of >4 mmol/L, with a mean hospital length of stay of 17.3 days and mortality of 86.7%. Elevated serum lactate was associated with a longer length of hospital stay, with lactate at 12 h having the highest predictive value (area under curve 0.987). Similarly, lactate at 12 h had the highest accuracy at predicting mortality as per receiver operating characteristic (AUC 0.895). Conclusion: Serum lactate was associated with increased in-hospital mortality and longer length of hospital stay in emergency abdominal surgeries.

Abstract Canola (Brassica napus L. and B. rapa L. [Brassicales: Brassicaceae]) is a major oilseed crop grown globally as a source of vegetable oil, animal feed and biofuel feedstock. The global demand for canola oil as a biofuel feedstock has increased due to recent regulations in the European Union, United States, and Canada. In North America, canola production is centered on the northern Great Plains where it is challenged by two highly destructive flea beetle species, the crucifer (Phyllotreta cruciferae Goeze, 1777) and the striped (Phyllotreta striolata Fabricius, 1803) flea beetles. In the spring, adult P. cruciferae and P. striolata begin feeding on canola seedlings, creating a ‘shot hole’ appearance, which can reduce the plant's photosynthetic capacity leading to uneven plant emergence and growth, reduced plant stand density, and reduced seed yield. Losses resulting from flea beetles are estimated in the tens of millions of dollars annually. At present, the principle means for flea beetle control are insecticides applied as systemic seed treatments and/or subsequent foliar sprays. The continued use of these products is being questioned due to environmental concerns and acquisition of resistance. As such, significant research effort is being directed toward the development of an integrated pest management system for these abundant and hard to manage pests of canola. Here, we review the ecology, pest status, and management of flea beetles in North America and discuss future research needed to promote flea beetle management and sustainable canola production.

Nowadays, for controlling crime, surveillance cameras are typically installed in all public places to ensure urban safety and security. However, automating Human Activity Recognition (HAR) using computer vision techniques faces several challenges such as lowlighting, complex spatiotemporal features, clutter backgrounds, and inefficient utilization of surveillance system resources. Existing attempts in HAR designed straightforward networks by analyzing either spatial or motion patterns resulting in limited performance while the dual streams methods are entirely based on Convolutional Neural Networks (CNN) that are inadequate to learning the long-range temporal information for HAR. To overcome the above-mentioned challenges, this paper proposes an optimized dual stream framework for HAR which mainly consists of three steps. First, a shots segmentation module is introduced in the proposed framework to efficiently utilize the surveillance system resources by enhancing the lowlight video stream and then it detects salient video frames that consist of human. This module is trained on our own challenging Lowlight Human Surveillance Dataset (LHSD) which consists of both normal and different levels of lowlighting data to recognize humans in complex uncertain environments. Next, to learn HAR from both contextual and motion information, a dual stream approach is used in the feature extraction. In the first stream, it freezes the learned weights of the backbone Vision Transformer (ViT) B-16 model to select the discriminative contextual information. In the second stream, ViT features are then fused with the intermediate encoder layers of FlowNet2 model for optical flow to extract a robust motion feature vector. Finally, a two stream Parallel Bidirectional Long Short-Term Memory (PBiLSTM) is proposed for sequence learning to capture the global semantics of activities, followed by Dual Stream Multi-Head Attention (DSMHA) with a late fusion strategy to optimize the huge features vector for accurate HAR. To assess the strength of the proposed framework, extensive empirical results are conducted on real-world surveillance scenarios and various benchmark HAR datasets that achieve 78.6285%, 96.0151%, and 98.875% accuracies on HMDB51, UCF101, and YouTube Action, respectively. Our results show that the proposed strategy outperforms State-of-the-Art (SOTA) methods. The proposed framework gives superior performance in HAR, providing accurate and reliable recognition of human activities in surveillance systems.

Background: A combination of carvedilol and Simvastatin have recognized their role as rescue therapy for carvedilol non-responders in chronic liver disease (CLD)-associated portal hypertension. However, there are scarce data regarding its role in specific subclasses, and stratification of response according to the computed tomographic perfusion (CTP) score has never been seen before. Aims and Objective: (1) To compare hemodynamic response and side effects of a combination therapy in decompensated and compensated patients. (2) Stratify the effect of combination therapy according to CTP score. Materials and Methods: In 102 consecutive patients of CLD with esophageal varices, the hepatic venous pressure gradient was measured at baseline and after 3 months of dose optimization of carvedilol. Simvastatin was added to non-responders and hemodynamics repeated at 1 month of dual therapy. The response of compensated CLD was compared with decompensated patients and was stratified as per the CTP on follow-up. Results: Overall, out of 43 compensated patients, 21 responded acutely and response increased to 29 (67.44%) at 3 months. While 31 of 59 (52.54%) decompensated patients responded acutely but dose escalation did not increase response significantly after 3 months. The addition of Simvastatin did increase the response, although side effects were more in decompensated group. The addition of Simvastatin also decreased decompensation in the high-risk compensated group and maintained their MELD.Na. Conclusion: Response in compensated CLD patients was more than in decompensated patients; however, it was statistically insignificant. Attrition was more in patients with CTP >10 due to drug intolerance, side effects, or deaths.

Abstract Background The efficacy of the erector spinae plane (ESP) block in mitigating postoperative pain has been shown for a range of thoracic and abdominal procedures. However, there is a paucity of literature investigating its impact on postoperative analgesia as well as its influence on weaning and subsequent recovery in comparison to thoracic epidural analgesia (TEA) in median sternotomy-based approach for open-cardiac surgeries and hence the study. Methods Irrespective of gender or age, 74 adult patients scheduled to undergo open cardiac surgery were enrolled and randomly allocated into two groups: the Group TEA (thoracic epidural block) and the Group ESP (bilateral Erector Spinae Plane block). The following variables were analysed prospectively and compared among the groups with regard to pain control, as determined by the VAS Scale both at rest (VASR) and during spirometry (VASS), time to extubation, quantity and frequency of rescue analgesia delivered, day of first ambulation, length of stay in the intensive care unit (ICU), and any adverse cardiac events (ACE), respiratory events (ARE), or other events, if pertinent. Results Clinical and demographic variables were similar in both groups. Both groups had overall good pain control, as determined by the VAS scale both at rest (VASR) and with spirometry (VASS) with Group ESP demonstrating superior pain regulation compared to Group TEA during the post-extubation period at 6, 9, and 12 h, respectively (P > 0.05). Although statistically insignificant, the postoperative mean rescue analgesic doses utilised in both groups were comparable, but there was a higher frequency requirement in Group TEA. The hemodynamic and respiratory profiles were comparable, except for a few arrhythmias in Group TEA. With comparable results, early recovery, fast-track extubation, and intensive care unit (ICU) stay were achieved. Conclusions The ESP block has been found to have optimal analgesic effects during open cardiac surgery, resulting in a decreased need for additional analgesic doses and eliminating the possibility of a coagulation emergency. Consequently, it presents itself as a safer alternative to the potentially invasive thoracic epidural analgesia (TEA).

Background: Post-induction hypotension associated with various agents is well-known in adults undergoing general anesthesia for various procedures. However, this phenomenon has not been addressed well in pediatric patients. We studied the incidence of postinduction hypotension in patients 1–5 years using inhalational induction with sevoflurane, intravenous induction with propofol, and co-induction with sevoflurane plus propofol. Aims and Objectives: To compare three different induction techniques in children 1–5 years undergoing various infra-umbilical surgeries under general anesthesia with laryngeal mask airway using sevoflurane induction, propofol induction, and sevoflurane plus propofol co-induction. Materials and Methods: Out of 150 patients observed in this study, 50 patients (group S) received inhalational induction with sevoflurane, 50 (group P) patients received intravenous induction with propofol, and 50 (group SP) patients received co-induction with propofol and sevoflurane. Results: Intravenous induction with propofol resulted in maximum hemodynamic changes Inhalational induction was responsible for significant changes in heart rate whereas co-induction with propofol (1–1.5 mg/kg) and sevoflurane 5% yielded minimum hemodynamic variations with least adverse effects. Conclusion: We conclude that co-induction with propofol (1–1.5 mg/kg) plus Sevoflurane 5% provided better hemodynamic stability with the least adverse effects.

This paper introduces a novel energy-efficient lightweight, void hole avoidance, localization, and trust-based scheme, termed as Energy-Efficient and Trust-based Autonomous Underwater Vehicle (EETAUV) protocol designed for 6G-enabled underwater acoustic sensor networks (UASNs). The proposed scheme addresses key challenges in UASNs, such as energy consumption, network stability, and data security. It integrates a trust management framework that enhances communication security through node identification and verification mechanisms utilizing normal and phantom nodes. Furthermore, a 6G communication module is deployed to reduce network delay and enhance packet delivery, contributing to more efficient data transmission. Leveraging Autonomous Underwater Vehicles (AUVs), the EETAUV protocol offers a lightweight approach for node discovery, identification, and verification while ensuring a high data transmission rate through a risk-aware strategy including at low computational cost. The protocol’s performance is evaluated through extensive simulations and compared against state-of-the-art methods across various metrics, including network lifetime, throughput, residual energy, packet delivery ratio, mean square error, routing overhead, path loss, network delay, trust, distance, velocity, Computational Cost of Routing, and data security. The results demonstrate the superior cumulative performance of the proposed EETAUV scheme, making it a robust solution for secure, efficient, and reliable communication in UASNs.

The rapid urbanization, economic growth, and improved living standards in developing countries are causing a significant increase in the amount of solid waste generated. To ensure a healthy environment for city residents and effectively manage waste resources, it is crucial to employ scientific methods as decision-making tools. However, the lack of competent institutions, financial and technical capabilities, and irresponsible social behavior hinder the implementation of an integrated and sustainable solid waste management (SWM) system. To address these challenges, researchers have proposed an optimized solution using mathematical modeling and GIS. This solution aims to enhance collection efficiency, optimize transportation, and maximize resource recovery and waste processing. By using linear mathematical modeling and the Arc-GIS Network Analyst tool, the study achieved a 13% route optimization in Phase 7 Hayatabad, indicating the potential for a more sustainable and cost-effective municipal solid waste (MSW) collection system in urban Peshawar. The study also explored different scenarios, such as increasing waste collection efficiency and implementing waste-to-energy technologies, which resulted in improved economic viability and reduced payback periods. Overall, the research highlights the need for adaptive strategies and policy reforms to establish sustainable and efficient waste management systems in rapidly growing cities, fostering a cleaner and more environmentally responsible urban future.

Magnetic quantum sensors based on trapped ions utilize properties of quantum mechanics which have optimized precision and beat current limits in sensor technology. Trapped ions are highly sensitive in a large span of signal ranging from DC or static B-field to the radiofrequency range in 100s of MHz and can attain the sensitivity in the range of pT/Hz to sub-pT/Hz. They are tuneable to frequencies of interest and can be used as a lock-in frequency detector. This modelling and simulation based study presents an innovative design of Surface Paul Traps, enabling the use of trapped ions as ultra-sensitive sensors for magnetic field detection and precise measurement of magnetic field gradients at a sub-millimeter spatial resolution. The novel design features multiple trapping regions, allowing for the mapping of magnetic fields across various ion-trapping zones. The study demonstrates groundbreaking advancements in ion manipulation and confinement through innovative chip architecture.

Background: Despite the emergence of many novel minimally invasive techniques including percutaneous nephrolithotomy, ureteroscopy, extracorporeal shock wave lithotripsy, many urologists still prefer open surgery for the management of ureteric stones. The present study compared the efficacy of extracorporeal shockwave lithotripsy (ESWL) with ureteroscopy (URS) for the treatment of distal ureteral calculi. Methods: A single-blinded, randomized controlled trial, which was conducted between January 2018 to June 2019 at the Sindh Institute of Urology and Transplantation, Karachi, Pakistan. All patients diagnosed with unilateral, solitary, and distal ureteral stones were randomized in two groups. The patients in Group A underwent with ESWL and group B underwent ureteroscopy. The outcome of procedures was assessed after 3 months. Data was analyzed via Statistical Package for the Social Sciences (SPSS version 25). Chi-squared test was applied to compare the clinical efficacy of both techniques. A p

Traditionally, projects have been scheduled with a primary focus on optimizing economic bene-fits, often at the expense of environmental considerations. However, in today’s context, there is an increasing societal demand for organizations to incorporate sustainability practices into their project management policies. This research aims to address this pressing issue by developing a comprehensive mathematical model that takes into account two crucial objectives: project net present value (NPV) and greenhouse gas (GHG) emissions. This model introduces carbon emission constraints on a per-period basis, alongside the usual precedence and resource constraints. the problem represented by this model is proven to be NP-hard, which adds complexity to its solution. To tackle this challenge, two multi-objective metaheuristic algorithms, specifically the Modified Grey Wolf Optimizer (MGWO) and the Strength Pareto Evolutionary Algorithm 2 (SPEA2), have been employed to solve the model. Extensive comparative analyses of these me-ta heuristics across various multi-objective performance measures indicate that MGWO consistently outperforms SPEA2 in most scenarios. To illustrate the practical applicability of the pro-posed model, a real-world case study has been utilized. The results of this case study offer compelling insights, showing that project NPV can be significantly improved with only a marginal increase in GHG emissions. This finding highlights the model’s potential to provide pragmatic solutions and valuable trade-off options for project planners and practitioners striving to balance economic objectives with environmental sustainability.

The aim present work was to examined the alone and combined impact of press mud compost and fuller earth at 0.5 and 1 % dosage on immobilization of Pb and Cd in Sharafi Goth and Malir polluted soils and reduce their uptake by sorghum plant. The results revealed that sorghum dry biomass yield was observed by 41.47 and 58.8 % with press mud compost (PMC) 1 % + fuller earth (FE) 1 % in Sharafi Goth soil and in Malir polluted soils than control. The immobilization of Pb was observed by 88.0 and 93.52 % with PMC 1 % + FE 1 %, and Cd was immobilized by 90.36 with PMC 1 % + FE 1 % and 78.0 % with PMC 0.5 % + FE 0.5 % in Sharafi Goth and Malir polluted soils than control. The uptake of Pb and Cd in shoot and root by sorghum was reduced both soils with application additives. The studied amendments increased the soil chemical properties such as electrical conductivity (EC), pH, cation exchange capacity (CEC), organic matter (O.M) and CaCO3 than control soil. The results of redundancy analysis showed that soil O.M had positive correlation with plant dry biomass, whereas EC, pH, CEC, O.M and CaCO3 showed negative correlation with Pb and Cd in soil and Pb and Cd in plant soot and root biomass. The results of present study indicated that press mud compost alone and in combined form shown positive impact on plant growth, immobilize Pb and Cd in both soils and reduced their uptake by sorghum plant. Future long-term field experiments must be carried out in multi-metals polluted soils and cultivate different genotypes.

Abstract Membrane distillation (MD) is a hybrid thermal-membrane desalination process that can use either low-grade waste heat and/or solar energy with hydrophobic membranes to desalinate high-salinity brines and produce high quality distillate. A research consortium was launched to investigate the application of the MD process, at lab and pilot scale, for desalination of concentrated brines. Bench scale results showed the presence of antiscalants in the concentrated brines minimized the scale precipitation potential and offered stable membrane permeability performance. Various MD technologies were screened, and two suitable technologies were selected for field-testing. Pilot unit A was based on multi-effect vacuum showed a stable flux of 6.2 LMH with excellent salt rejection (> 99.9%) from the concentrated brine discharged from thermal desalination plant in Qatar. That pilot unit was also field tested on hypersaline groundwater in Texas (USA) to generate fresh water for reservoir fracking in unconventional oil production operations. The MD unit was coupled with humidification/dehumidification (HDH) unit to achieve zero liquid discharge (ZLD) for inland applications. The MD unit was operated at 40% recovery producing distillate of

Introduction: Balance impairments and an increased fall risk are common concerns among individuals with various health conditions. Resistance exercise has shown potential in improving balance and reducing fall risk. Aim: To determine the effects of home-based Thera-Band resistance training in reducing the risk of falls among the geriatric population and to compare it with weight-cuff resistance training. Materials and Methods: A Randomised Controlled Trial (RCT) was conducted at the Amity Institute of Health and Applied Science, Noida, India, from November 2022 to April 2023. The intervention period spanned four weeks, and a total of thirtythree subjects were enrolled in the study. The participants were divided into three groups: Group A, Group B, and Group C. Group A performed resistance exercises using weight cuffs combined with standard balance training, Group B performed resistance training with Thera-Band combined with standard balance training, and Group C received standard balance exercises alone. The effects of the interventions on fall risk reduction were assessed using the Berg Balance Scale (BBS), Timed Up and Go (TUG), and Fall Efficacy Scale (FES) among the geriatric population. Paired t-tests were employed to compare pre- and post-intervention data within each group, determining significant changes within each group over the intervention period. Analysis of variance (ANOVA) was utilised to assess between-group effects of the different interventions. Results: The FES scores were assessed pre- and postintervention for each group. Group B (Thera-Band) demonstrated significantly better outcomes in fall efficacy compared to Group A (Weight-cuff) (p

Background: The occurrence of emergence agitation (EA) is the most common and practical problem faced in the immediate post-operative period during the process of Extubation under General Anaesthesia. Dexmedetomidine, an α2 adrenoceptor agonist is an excellent drug that has been shown effective to decrease the preoperative anxiety and smooth induction and emergence. Aims and Objectives: To assess the effect of intravenous dexmedetomidine primarily on EA and other complications that may occur during emergence from general anesthesia. Materials and Methods: 80 patients of either gender aged 18–65 years with ASA status I and II, undergoing various elective general and urological surgeries under general anesthesia were included in the study. Patients receiving adjuvant drug dexmedetomidine, were labelled as Group D (n=40) and those who didn’t receive any adjuvant were labelled as group C (n=40). Dexmedetomidine was given at 1 μg/kg and then maintained at infusion of 0.4 μg/kg/h till the end of the surgery for group D. The hemodynamic parameters and SpO2 were measured during the intraoperative period at various intervals of time till the end of surgery and also on arrival to the recovery room till patient was discharged from post-anesthesia care unit in both the groups. Results: The use of IV dexmedetomidine has proved significantly effective in prevention of incidence of EA with the overall incidence of agitation of 7.5% in Group D as compared to 42.5% in group C. Conclusion: Intraoperative administration of intravenous dexmedetomidine decreased the incidence of EA and other emergence phenomena like cough, pain and PONV with stable hemodynamics, safety profile, good analgesic properties and opioids sparing side effects.

Daily increases in electricity prices accompany daily increases in energy consumption and use. An effective load-balancing scheduling system is necessary for the lowest cost of use and the lowest cost. Despite these devices having a significant capacity for power consumption, they must find a means to balance the load at a low price. Even if lowering the voltage is challenging, it is possible to do it at the lowest cost. Hybrid Whale Differential Evolution (HWDE) is a new optimization method that combines the well-known approaches of the Whale Optimization Algorithm (WOA) and Enhanced Differential Evolution (EDE). By balancing the required Real-Time Price (RTP) and Critical Peak Price (CPP) loads, WOA and EDE capabilities can save costs and ensure the device receives sufficient voltage. The three most recent performance indicators are kWh per charge, energy usage, and the maximum-average ratio. Existing models are evaluated according to their expenses (in rupees), energy consumption, cost per kilowatt-hour, and total cost. All simulation results indicate that HWDE is the optimal solution in every circumstance. In MATLAB simulations, HWDE consistently outperforms its rivals.

Background: Compassion satisfaction and compassion fatigue is the element of professional quality of life which plays an integral role in compassionate care. Compassion fatigue can lead to poor job performance, high turnover rate, absenteeism, lack of interest in patients, and poor patient outcome. Objective: This study aimed to determine the burden of compassion fatigue, compassion satisfaction, and burnout among nurses working in specialty-based critical care areas. Methods: A cross-sectional study was accomplished at Dow University Hospital from December 2020 to March 2021. A structured, and validated tool, ProQol was utilized for data collection. Data were entered and analyzed in SPSS version 24.0. Binary logistic regression was applied to establish the association between the variables. The level of significance was considered with a p-value ≤0.05. Results: A total of 140 nurses working in critical areas were approached and responded to this survey. The average score was 40.77 ± 6.26 for compassion satisfaction, 22.47 ± 5.46 for burnout, and 26.14 ±6.20 for secondary traumatic stress. On multivariable regression analysis, the likelihood of average compassion satisfaction was significantly lower among nurses who had BSN degrees. Nurses with work experience of 6 months to

Human Activity Recognition (HAR) plays a crucial role in communication and the Internet of Things (IoT), by enabling vision sensors to understand and respond to human behavior more intelligently and efficiently. Existing deep learning models are complex to deal with the low illumination, diverse viewpoints, and cluttered backgrounds, which require substantial computing resources and are not appropriate for edge devices. Furthermore, without an effective video analysis technique it processes entire frames, resulting inadequate performance. To address these key challenges, a cloud-assisted IoT computing framework is proposed for HAR in uncertain low-lighting environments, which is mainly composed of two tiers: edge and cloud computing. Initially, a lightweight Convolutional Neural Network (CNN) model is developed which is responsible to enhance the low-light frames, followed by the human detection algorithm to process the selective frames, thus enabling efficient resource utilization. Next, these refined frames are then transmitted to the cloud for accurate HAR, where dual stream CNN and transformer fusion network extract both short-and long-range spatiotemporal discriminative features followed by proposed Optimized Parallel Sequential Temporal Network (OPSTN) with squeeze and excitation attention to efficiently learn HAR in complex scenarios. Finally, extensive experiments are conducted over three challenging HAR datasets to deeply examine the proposed framework from various perspectives such as complex activity recognition, lowlighting, etc., where the results are outperformed compared with the state-of-art methods.

Introduction: Cephalometry is the study of skull measurements for clinical evaluation, diagnosis, and surgical planning. Machine learning (ML) algorithms have been used to accurately identify cephalometric landmarks and detect irregularities related to orthodontics and dentistry. ML-based cephalometric imaging reduces errors, improves accuracy, and saves time. Method: In this study, we conducted a meta-analysis and systematic review to evaluate the accuracy of ML software for detecting and predicting anatomical landmarks on two-dimensional (2D) lateral cephalometric images. The meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for selecting and screening research articles. The eligibility criteria were established based on the diagnostic accuracy and prediction of ML combined with 2D lateral cephalometric imagery. The search was conducted among English articles in five databases, and data were managed using Review Manager software (v. 5.0). Quality assessment was performed using the diagnostic accuracy studies (QUADAS-2) tool. Result: Summary measurements included the mean departure from the 1–4-mm threshold or the percentage of landmarks identified within this threshold with a 95% confidence interval (CI). This meta-analysis included 21 of 577 articles initially collected on the accuracy of ML algorithms for detecting and predicting anatomical landmarks. The studies were conducted in various regions of the world, and 20 of the studies employed convolutional neural networks (CNNs) for detecting cephalometric landmarks. The pooled successful detection rates for the 1-mm, 2-mm, 2.5-mm, 3-mm, and 4-mm ranges were 65%, 81%, 86%, 91%, and 96%, respectively. Heterogeneity was determined using the random effect model. Conclusion: In conclusion, ML has shown promise for landmark detection in 2D cephalometric imagery, although the accuracy has varied among studies and clinicians. Consequently, more research is required to determine its effectiveness and reliability in clinical settings.

The objective of the present study was to investigate the impact of MgO 0.5 g/kg loaded in different organic waste materials on the properties of the modified biochars obtained. The waste materials included tea waste, wood waste, water chestnut peel, and pomegranate peel, which were used to create tea waste MgO-modified biochar (TWMgO-MBC), wood waste MgO-modified biochar (WSMgO-MBC), water chestnut peel MgO-modified biochar (WCMgO-MBC), and pomegranate peel MgO-modified biochar (PPMgO-MBC). All the MgO-modified biochars were prepared at 600 °C for 2 h and applied at 0.5 and 1% doses for the immobilization of Ni, Cu, Pb, and Cr in stone crushing and mining-polluted soil and the reduction in their uptake by pearl millet (Pennisetum glaucum) plant. The greatest fresh and dry biomasses were observed at 45.04% and 31.29%, respectively, with the application of TWMgO-MBC 1% in stone-crushing-polluted soil. The highest degree of immobilization of Ni (76.67%) was observed for the WSMgO-MBC 1% treatment, Cu (73.45%) for WCMgO-MBC 1%, Pb (76.78%) for WSMgO-MBC 1%, and Cr (70.55%) for WCMgO-MBC 1%, in comparison with the control. The maximum uptake of Ni, Cu, Pb, and Cr in the shoot of pearl millet was reduced by 78.43% with WSMgO-MBC 1%, 75.06% with WSMgO-MBC 1%, 90.81% with WCMgO-MBC 1%, and 85.71% with WSMgO-MBC 1% as compared with the control. The greatest reduction in Ni, Cu, Pb, and Cr in the root of pearl millet was observed at 77.81% with WSMgO-MBC 1%, 68.09% with WCMgO-MBC 1%, 84.03% with WCMgO-MBC 1%, and 88.73% with WCMgO-MBC 1%, in comparison with the control. The present study demonstrated that the TWMgO-MBC 1% treatment was highly effective for improving plant growth, while the WSMgO-MBC 1%, and WCMgO-MBC 1% treatments were found to be highly effective for immobilizing heavy metals in polluted soils, thus facilitating safe crop cultivation. Future studies should concentrate on the long-term application of MgO-modified biochars for the remediation of multimetal-polluted soils.

A sequence of dye-sensitized solar cells is proposed, utilizing TiO2@Zn/Al-layered double hydroxide (LDH) as their starting materials, in which Ruthenizer N719 was used as a photon absorber. The anticipated system was turned into sheet-like TiO2@mixed metal oxide (MMO) via post-processing treatment. The crystal quality indicated a relation to power conversion efficiency (PCE); this was combined with a comparable morphology profile. In detail, the optimum DSSC device exhibited average sheet-like thickness and a dye loading amount of 43.11 nm and 4.28 ×10−3 mM/cm−2, respectively. Concurrently, a considerable PCE enhancement of the optimum DSSC device (TiO2@MMO-550°) was attained compared to pristine MMO (0.91%), which could be due to boosted electron transfer efficiency. Of the fabricated devices, DSSC fabricated at 550° exhibited the highest PCE (1.91%), with a 35.6% enhancement compared to that obtained at 450°, as a result of its increased open-circuit voltage (3.29 mA/cm2) and short-circuit current (0.81 V). The proposed work delivers an enhanced efficiency as compared to similar geometries.

Since the first human case in 2013, H7N9 avian influenza viruses (AIVs) have caused more than 1500 human infections with a mortality rate of approximately 40%. Despite large-scale poultry vaccination regimes across China, the H7N9 AIVs continue to persist and evolve rapidly in poultry. Recently, several strains of H7N9 AIVs have been isolated and shown the ability to escape vaccine-induced immunity. To assess the zoonotic risk of the recent H7N9 AIV isolates, we rescued viruses with hemagglutinin (HA) and neuraminidase (NA) from these H7N9 AIVs and six internal segments from PR8 virus and characterized their receptor binding, pH of fusion, thermal stability, plaque morphology and in ovo virus replication. We also assessed the cross-reactivity of the viruses with human monoclonal antibodies (mAbs) against H7N9 HA and ferret antisera against H7N9 AIV candidate vaccines. The H7N9 AIVs from the early epidemic waves had dual sialic acid receptor binding characteristics, whereas the more recent H7N9 AIVs completely lost or retained only weak human sialic acid receptor binding. Compared with the H7N9 AIVs from the first epidemic wave, the 2020/21 viruses formed larger plaques in Madin-Darby canine kidney (MDCK) cells and replicated to higher titres in ovo, demonstrating increased acid stability but reduced thermal stability. Further analysis showed that these recent H7N9 AIVs had poor cross-reactivity with the human mAbs and ferret antisera, highlighting the need to update the vaccine candidates. To conclude, the newly emerged H7N9 AIVs showed characteristics of typical AIVs, posing reduced zoonotic risk but a heightened threat for poultry.

Magneto hydrodynamic flow over a wedge-shaped channel is often seen in geothermal applications, microelectronic, energy systems, and pumping systems. The slip condition is a normally recognized condition for the fluid flow occurs along lubricated, coated, wall channels. The best examples of such flows are the blood flow in arteries with plaque layer arteries. Flow configuration within channel is anticipated by using Carreau nanofluid injection at inlet. The intersecting wall of channel is inclined with respect to horizontal plane to make convergent angle of −α and divergent angle of α. The mathematical equations for energy and nanofluid concentration are established using well-known Navier–Stokes Equation with conservation equations invoking modified Buongiorno model. The temperature differences between the wall and core region leads to entropy. By using distinguishing amendments, system of equations are remodeled into system of ordinary differential equations (ODE's), which are numerically solved by Bvp4c technique of MATLAB for realistic conditions of under discussed phenomena. Simple shear close to the wall admit compression in local flow topology in zones of channel (divergent). The temperature field increases along thermal radiation, Brinkman number, nanoscale effects and heat source. Entropy is minimal and can be minimized with optimal angle and slip velocity.

AbstractSupply chain (SC) performance is being advanced through digitalization, automation, and real-time visibility, leading to improved operational efficiency, optimized inventory management, and proactive solutions for problems. This study focuses on managing SC performance by developing a real-time Microsoft Power BI dashboard using the ADR method. The aim is to help small business owners effectively and affordably manage their supply chains. The research analyzed data from Ly Foods Ltd. and utilized Microsoft Power BI to create the dashboard. The study highlights how this state-of-the-art dashboard enhances the measurement of operational and decision-making processes by providing efficient, visible, accessible, and shareable information. The findings demonstrate the potential benefits of leveraging advanced technologies to enhance supply chain management (SCM) practices. This research makes a significant contribution to the field of SCM by illustrating how SC performance can be managed using the ADR method and the SC key performance indicators (KPIs). The results of this study have important implications for businesses of all sizes, as they enhance SC efficiency and profitability.

The purpose of the article is on the deglobalization processes currently taking place in international economic interactions, and also attempts to examine how the trade blocs of the major economies affect the rest of globalization. The Kinked Exponential Model was used to determine decadal growth rates based on 31 years of panel data from 1990 to 2020 for 15 large countries (gross domestic product). Three different regression models i.e., Pooled OLS, Fixed- and Randomeffect models were estimated to examine the effects of trade blocs and wars between nations on the world economy. Over the study period, disparities and increasing economic inequality between variables have widened. In addition, international conflicts have had a negative impact on international trade and have significantly affected globalization. More importantly, trade blocs, particularly the OECD, APEC, and BRICS have slowed trade with the rest of the world, reflecting a process known as regionalization, in which countries cooperate rather than at the global level. In particular, during the third decade of the twentieth century, when the growth rate of trade flows among major countries declined rapidly by 8.8 per cent, this regionalization did not stop and expanded significantly.

Abstract Background The value of local and regional landscapes for avian conservation requires a thorough understanding of the diversity and structure of bird communities. Avifauna serves as an important biological indicator in monitoring the health of an ecosystem or environment. The present study was conducted to examine the relationship between avian diversity, richness, composition and habitat characteristics at the Rajparian Wildlife Sanctuary. Results Using geographic information systems and remote sensing techniques, we analyzed habitat heterogeneity based on land use and land cover classification. For sampling birds, extensive surveys were conducted in different land-use types from 2019 to 2021, following the line transect method. During the study period, 102 bird species were recorded from the five studied vegetation types of the study area, including one near threatened (Bearded Vulture) and one vulnerable (Kashmir Flycatcher) bird species. The highest numbers of avian species were recorded from the forest (71 species) (42.61 ± 16; mean ± SD) and the lowest from the rocky land-use type (12 species) (7.83 ± 1.95). The individual rarefaction and extrapolation curves showed higher species richness for forest and the lowest for rocky habitats. Numerous pairwise comparisons revealed significant differences in species richness among studied habitat types, except for riverine vs. grassland, scrub vs. grassland and rocky vs. riverine land uses. The partitioning of the spatio-temporal β-diversity patterns revealed a relatively large contribution of the turnover component to the observed overall dissimilarity compared to the nestedness component. Conclusions It can be concluded that avian communities in the Rajparian Wildlife Sanctuary are influenced by habitat heterogeneity, topography, and the availability of water. The results of the present study indicate that the Rajparian Wildlife Sanctuary provides an important habitat for the conservation of birds, as it harbors a rich avian diversity. The study is the first scientific survey of the avian habitat associations in the protected area and will serve as a baseline for future avian research, as well as for management implications in the region.

Background: The prognosis of patients with hepatocellular carcinoma (HCC) is poor due to its non-specific presentation, underlying liver disease, and advanced stage at presentation. There are limited HCC data from India, and no major studies are available from North India. Objectives: To study the epidemiology, etiological factors, clinical profiles, and treatment patterns of patients with HCC at our center. Materials and Methods: This was a retrospective analysis of prospectively collected data of patients with HCC from January 2016 to December 2020, conducted in the Department of Medical Oncology and Gastroenterology at the Sher-i-Kashmir Institute of Medical Sciences (SKIMS), a tertiary center in North India. Patient data and treatment details were collected and analyzed. Results: We enrolled 127 patients in the study. Males constituted the majority (91; 71.7%), with a mean age of 58 ± 12 years. The majority (100; 78%) of patients had cirrhosis; the common etiological factors included hepatitis B virus infection (30; 23.6%), non-alcoholic steatohepatitis (29; 22.8%), and hepatitis C virus infection (22; 17.3%). Although etiology was unknown in 45 (35.4%) patients, around one-third (36.4%) had diabetes mellitus. Most (91; 71.7%) patients had liver-limited disease and the majority (53; 41.7%) presented with Barcelona Clinic Liver Cancer (BCLC) stage C disease, followed by BCLC A (33; 26%), BCLC B (25; 19.7%), and BCLC D (16; 12.6%). Portal vein thrombosis was noted in 40 (32.3%) patients. Liver-directed therapies, including surgery, ablation, and trans-arterial chemoembolization, were received by 17 (13.4%) patients. The most commonly used systemic treatments were sorafenib (32; 25.2%) and lenvatinib (7; 5.5%), but a substantial number of patients (56/127; 44.1%) either did not adhere to, refused therapy or were given best supportive care. Conclusion: The majority of patients with HCC at our center are males and present at a mean age of 58 years. Hepatitis B virus is the most frequent etiological agent. Patients with HCC present with advanced stage disease and are often not considered suitable for curative intent treatment. Sorafenib is the most commonly administered systemic treatment; however, just under half the patients (44.1%) are either unfit for or refuse treatment.

The video retrieval system refers to the task of retrieving the most relevant video collection, given a user query. By applying some feature extraction models the contents of the video can be extracted. With the exponential increase in video data in online and offline databases as well as a huge implementation of multiple applications in health, military, social media, and art, the Content-Based Video Retrieval (CBVR) system has emerged. The CBVR system takes the inner contents of the video frame and analyses features of each frame, through which similar videos are retrieved from the database. However, searching and retrieving the same clips from huge video collection is a hard job because of the presence of complex properties of visual data. Video clips have many frames and every frame has multiple properties that have many visual properties like color, shape, and texture. In this research, an efficient content-based video retrieval system using the AlexNet model of Convolutional Neural Network (CNN) on the keyframes system has been proposed. Firstly, select the keyframes from the video. Secondly, the color histogram is then calculated. Then the features of the color histogram are compared and analyzed for CBVR. The proposed system is based on the AlexNet model of CNN and color histogram, and extracted features from the frames are together to store in the feature vector. From MATLAB simulation results, the proposed method has been evaluated on benchmark dataset UCF101 which has 13320 videos from 101 action categories. The experiments of our system give a better performance as compared to the other state-of-the-art techniques. In contrast to the existing work, the proposed video retrieval system has shown a dramatic and outstanding performance by using accuracy and loss as performance evaluation parameters.

This work studies the impact of electromagnetic fields on the degradation of agricultural land. During the analysis of available sources of information, it was found that in the scientific publications by domestic authors, there is no mention of such a factor of land degradation as the action of electromagnetic fields (EMF) of man-made origin. Numerous scientific works by foreign experts present the results of experimental studies that confirm the negative impact of electromagnetic radiation (EMR) of power lines (PL) on agricultural land. The application of mathematical methods of modelling the dynamics of the distribution of the number of microorganisms or other soil components in the irradiation zone of power lines can be the basis for biomonitoring in the system of construction technologies to protect agricultural land from electromagnetic pollution. The paper presents statistical models designed to assess the impact of electromagnetic fields on pollution of agricultural land and conduct appropriate biomonitoring. The dependence of the number of fungi in the soil on the distance to the 110 kV power line at different seasons and the dynamics of the intensity of adaptation processes in the soil at different distances from the power line (PL) was constructed. The methods of regression, variance and cluster analysis were usedin the development of models, and the corresponding elasticity functions were constructed. It is shown that the application of modern data processing methods allows obtaining additional information even from the alreadypublished results of work performedby various researchers.

Electrocatalytically active nanocomposites play a vital role in energy generation, conversion, and storage technologies. Transition metal-based catalysts such as nickel and iron and their pnictide (phosphide), and chalcogenide (selenide) compounds exhibit good activity for hydrogen evolution reaction (HER) in the alkaline environment. In this study, transition metals-based catalysts (Ni-P-Se, Fe-P-Se, and Ni-Fe-P-Se) solutions were prepared using a simple one-pot method. Prepared solutions were deposited on Ni foam, and different characterization techniques were used to determine the composition, structure, and morphology of as-prepared catalysts. Furthermore, it was found that Ni-Fe-P-Se as a cathode material showed better HER performance compared to other investigated materials with the overpotential value of 316 mV at 10 mA cm-2 current density and 89 mV dec-1 Tafel slope value. The stability tests of the as-prepared catalyst confirmed that the synergistic effect between various elements enhances the electrocatalytic performance for up to 24 hours, providing a fair, stable nature of Ni-Fe-P-Se based sample.

Mobile Ad-hoc Networks (MANETs) are a kind of networks comprised of nodes which are mobile from place to place in nature, hence the name is MANET. Being an ad-hoc network, it does not need a centralised control infrastructure. Along with the mobile nodes, these type of networks also deals with the radio propagation models in which the nodes communicate with one another using different propagation models. These propagation models have their own kind of communication scenarios in which direct Line of Sight (LoS), Non-Line of Sight (N-LoS), two ray ground reflection etc. By communicating with one another, these propagation models undergo issues like going away from each other in which the distance increases and it directly affects their efficiency. In this paper, two-ray ground and free-space radio waves propagation models have been taken into consideration to check the distance-based scenarios in different distance ranges. With the help of Ad-hoc On-demand Distance Vector (AODV) routing scheme the simulations have been performed in NS-2 by taking the performance evaluation metrics that are average throughput, average latency and average packet drop. The simulations revealed that distance has a direct impact on the performance of propagation models. It has been concluded that two ray ground gives the best performance in contrast with the free space propagation model. The main reason is that two ray ground uses the two-way ground reflection in which it communicates via LOS and N-LOS. The simulations results have revealed that the proposed radio wave propagation models have a huge impact with the distance-based scenario to evaluate the performance of AODV routing scheme.

The concept of data mining is to classify and analyze the given data and to examine it clearly understandable and discoverable for the learners and researchers. The different types of classifiers are there exist to classify a data accordingly for the best and accurate results. Taking a primary data, and then classifying it into different portions of parts, then to analyze and remove any ambiguities from it and finally make it possible for understanding. With this process, that data will become secondary from primary and will called information. So, the classifiers are doing the same strategy for the solution and accuracy of the data. In this paper, different data mining approaches have been used by applying different classifiers on the taken data set. The data-set consists of 500 candidates’ segregated data for the analysis and evaluation to perfectly classify and to show the accurate results by using the proposed Algorithms. The data mining approaches have been used in which HUGO (Highly Undetectable steGO) Algorithm, Naïve Bayes Classification, k-nearest neighbors and Logistic Regression are used with the extension of the other classification methods that are Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) as classifiers. These classifiers are given names for further analysis that are Classifier-1 and Classifier-2 respectively. Along with these, a tool is used named WEKA (Waikato Environment for Knowledge Analysis) for the analysis of the classifier-1 and 2. For performance evaluation and analysis the parameters are used for best classification that which classifier has given best performance and why. These parameters are RRSE (Root Relative Square Error), RAE (Relative Absolute Error), MAE (Mean Absolute Error), and RMSE (Root Mean Square Error). For the best and outstanding accuracy of the proposed work, these parameters have been tested under the simulation environment along with the incorrect, correct classifying and the %age has been witnessed and calculated. From simulation results based on RRSE, RAE, MAE and RMSE, it has been shown that classifier-1 has given outstanding performance among the others and has been placed in highest priority.

Flying Ad-hoc Network (FANET) is a special member/class of Mobile Ad-hoc Network (MANET) in which the movable nodes are known as by the name of Unmanned Aerial Vehicles (UAVs) that are operated from a long remote distance in which there is no human personnel involved. It is an ad-hoc network in which the UAVs can more in 3D ways simultaneously in the air without any onboard pilot. In other words, this is a pilot free ad-hoc network also known as Unmanned Aerial System (UAS) and the component introduced for such a system is known as UAV. There are many single UAV applications but using multiple UAVs system cooperating can be helpful in many ways in the field of wireless communication. Deployments of these small UAVs are quick and flexible which overcome the limitation of traditional ad hoc networks. FANETs differ from other kinds of ad hoc networks and envisioned to play an important role where infrastructure operations are not available and assigned tasks are too dull, dirty, or dangerous for humans. Moreover, setting up to bolster the range and performance of small UAV in ad hoc network lead to emergent evolution with its high stability, quick deployment, and ease-of-use for the formation of the network. Routing and task allocation are the challenging research areas of the network with ad hoc nodes. The paper overview based on the study of biological inspired routing protocols (Moth-and-Ant and Bee Ad-Hoc) routing protocols.

Clustering is the unsupervised machine learning process that group data objects into clusters such that objects within the same cluster are highly similar to one another. Every day the quantity of Urdu text is increasing at a high speed on the internet. Grouping Urdu news manually is almost impossible, and there is an utmost need to device a mechanism which cluster Urdu news documents based on their similarity. Clustering Urdu news documents with accuracy is a research issue and it can be solved by using similarity techniques i.e., Jaccard and Dice coefficient, and clustering k-mean algorithm. In this research, the Jaccard and Dice coefficient has been used to find the similarity score of Urdu News documents in python programming language. For the purpose of clustering, the similarity results have been loaded to Waikato Environment for Knowledge Analysis (WEKA), by using k-mean algorithm the Urdu news documents have been clustered into five clusters. The obtained cluster’s results were evaluated in terms of Accuracy and Mean Square Error (MSE). The Accuracy and MSE of Jaccard was 85% and 44.4%, while the Accuracy and MSE of Dice coefficient was 87% and 35.76%. The experimental result shows that Dice coefficient is better as compared to Jaccard similarity on the basis of Accuracy and MSE.

Objective: To look for the relationship between absolute eosinophil count and post-bronchodilator reversibility in chronic obstructive pulmonary disease patients at Pak Emirates Military Hospital, Rawalpindi Pakistan. Study Design: Cross sectional study. Place and During of Study: Pulmonology Department, Pak Emirates Military Hospital Rawalpindi (PEMH) from Jul to Dec 2019. Methodology: The study was conducted on 150 patients suffering from chronic obstructive pulmonary disease admitted in the Medical Ward or reporting in the Outpatient Department. Lung function was assessed using spirometry pre- and postbronchodilation. The presence and severity of chronic obstructive pulmonary disease were assessed using modified Global Obstructive Lung Disease (GOLD) criteria. The presence of significant bronchodilator responsiveness was taken as ≥12% improvement in the forced expiratory volume (FEV) (1) or the forced vital capacity. Results: Of 150 patients in the final analysis, 95 (63.3%) were male, and 55(36.7%) were female. The mean duration of COPD in our target population was 9.13±1.23 years. 68 (45.3%) had >12% improvement after bronchodilator administration, while 82(54.7%) had

In this paper, we designed and investigated a parallel double-E shaped structure based on double negative (DNG) metamaterial (MTM) both numerically and experimentally, which can be utilized for multiband applications. We used the Computer Simulation Technology (CST) Microwave Studio electromagnetic simulator to design the MTM and obtain the numerical results. The proposed MTM has a unit cell dimension of 8 × 8 × 1.57 mm3, and Rogers RT 5880 was used as the substrate, resulting in a high effective medium ratio (EMR) value of 15.61. The DNG metamaterial can cover multiband frequencies (S and C bands) and produce three resonance frequencies of 2.40, 4.50, and 7.24 GHz. Parametric studies were performed for different configurations by changing the type of substrates, substrate thicknesses, split gaps, and unit cell arrays to optimize the proposed design. An equivalent circuit was validated using the advanced design system (ADS) software and compared to the CST simulated results, which showed good agreement. The proposed structure is highly significant due to its low profile (small size) and ordinary resonator arrangement, which produced double negative properties with a high EMR over a wide range of frequencies. The recommended structure can be useful for different applications such as wireless communications, weather radar, satellite communication, and wireless sensor networks.

Globally, fuel energy has become a crucial issue in fulfilling energy demand; new oil/gas wells should be drilled safely and efficiently to achieve the well target. Cutting transport in deviated wells is directly affected by influencing parameters such as viscosity, annulus velocity of drilling mud, and hole inclination. As cuttings transport significantly affects drilling costs, time, and oil/gas well integrity. Poor hole cleaning efficiency could cause many drilling issues, including excessive torque and drag, Pipe washout and jamming, bit balling and washout, etc. Therefore, hole cleaning investigation requires a deep understanding of all influential parameters.The results of this study were utilized to investigate cutting transport performance, employing three different kinds of drilling mud. The investigational work was performed by a 10-feet elongated invisible pipe of 5-inch diameter and a steel pipe of 2-inch diameter as the test section. The cutting transport performance (CTP) was computed based on weight data for every single test. At different flow regimes, viscosity was examined in addition to two other influential parameters, namely fluid velocity and hole inclination. At all angles, during turbulent flow, Cutting Transport performance has enhanced up to 10% by increasing viscosity while keeping velocity constant.Nevertheless, an increasing additional amount of viscosity will turn the flow condition from turbulent to transient or laminar flow, resulting in a 14% reduction in CTP. It also shows that increasing hole angle above 60 degrees with mud-2 positively affects cuttings transport performance. It will be improved up to 45%. Moreover, a maximum of 96 percent CTP can be attained by drilling fluid velocity. Therefore, this study properly investigates the influence of viscosity, velocity, and hole inclination on cutting transporter performance, as a result saving drilling time and reducing hidden costs, as well as lead to a prediction of the carrying capacity of fluids and facilitating the optimum design of vertical and directional wells. Moreover, this study provides a guideline to analyze and enable the adjustment of drilling parameters to optimize the overall drilling process.

Objective: To determine the pattern of electrolyte imbalance and associated etiological factors among the unconscious patients hospitalized at Pak Emirates Military Hospital. Study Design: Cross-sectional study Place and Duration of Study: Pak Emirates Military Hospital, Rawalpindi Pakistan from Sep 2019 to Feb 2020 Methodology: A total of 240 cases were included in this study in liaison with other departments where the admitted patients became unconscious. Patients with a Glasgow coma scale score

Background: Cohen syndrome (CS) is caused by an autosomal recessive (AR) mutation of the vacuolar protein sorting 13 homolog B (VPS13B) gene on chromosome 8q22.2. It is characterized by hypotonia, obesity, prominent incisors, and mental retardation. It is diagnosed by the satisfaction of various systems of clinical diagnostic criteria. Molecular confirmation is by clinical exome sequencing. Clinical Description: We reported three siblings from a Kashmiri family with a positive history of consanguinity. The index case, a 26-month-old boy, was diagnosed with neutropenia during the workup for recurrent respiratory infections. He was also noted to have developmental delay, short stature, obesity, microcephaly, and facial dysmorphism. Retinitis pigmentosa was found. The diagnosis of CS was established on the detection of a pathogenic novel homozygous frameshift variant in the VPS13B gene. Evaluation of the family identified two other siblings, an 11-year-old boy and a 9-year-old girl, who satisfied the clinical criteria. Management and Outcome: The parents underwent genetic counseling. The affected children are under follow-up by a multidisciplinary team with regular monitoring of various parameters as per standard recommendations. Conclusion: Pediatricians should consider the application of diagnostic criteria of CS in a child with neutropenia, short stature, developmental delay, and microcephaly, if there is a setting of consanguinity. The diagnosis should be confirmed by genetic testing.

Background: Tuberculosis (TB) is the 10th leading cause of death globally and is leading cause of death from a single infectious disease. The objectives of our study were to determine the distribution of drug sensitive tuberculosis (DS-TB) by sex, age groups and type of disease in DS-TB population of District D.I.Khan, Pakistan. Materials Methods: This cross-sectional study was conducted in Department of Community Medicine, Gomal Medical College, D.I.Khan, Pakistan from January 5, 2021 to January 25, 2021. The data of 3,916 patients was retrieved from District Health Office, D.I.Khan for the period from January 1, 2019 to December 31, 2020. Sex, age groups and type of disease were categorical variables and analyzed by count and percentage with CI at 95%CL. Distribution of DR-TB by sex, age groups and type of disease was analyzed separately by chi-square goodness-of-fit test at alpha .05. Results: Out of 3,916 patients with DS-TB, women 2,110 (53.88%, 95% CI 52.32-55.44) were more than men 1,806 (46.12%, 95%CI 44.55-47.67), with most common age group of 15-44 years 1,948 (49.74%, 95%CI 48.17-51.31), and with more pulmonary 2,877 (73.47%, 95%CI 72.08-74.85%) than extrapulmonary 1,039 (26.53%, 95%CI 25.14-27.91) cases. Our observed prevalence of DS-TB in men was lower 46.12% than expected 51.72% and in women it was higher 53.88% than expected 48.28% (p.00001). Our observed distribution of DS-TB in different age groups was not similar to expected (p.00001). Our observed prevalence of pulmonary TB was lower 73.47% than expected 80.35% and in extrapulmonary TB it was higher 26.53% than expected 19.65% (p.00001). Conclusions: Drug sensitive tuberculosis was more common in women than men in DS-TB population of District D.I.Khan, Pakistan. It was highest in age group 15-44 years and higher for pulmonary TB than extrapulmonary TB. Our observed prevalence in men was lower than expected and in women it was higher than expected. Our observed prevalence for drug sensitive TB in various age groups was different than expected. Our observed prevalence for pulmonary TB was lower than expected and for extrapulmonary TB it was higher than expected.

Introduction: Burkholderia is an important opportunistic pathogen in hospitalised and immunocompromised patients. It is responsible for approximately 0.6% of all Ventilator Associated Pneumonia (VAP). Burkholderia cepacia (B. cepacia) is a resilient organism, capable of survival in environments devoid of significant nutritional resources. Authors have come across many cases of B.cepacia in hospital for the last six years. Aim: To know the prevalence and microbiological profile of Burkholderia infection in tertiary care hospital, Srinagar, India. Materials and Methods: The present retrospective study was carried out in the Department of Microbiology, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India, from January 2013 to October 2018. The records of all patients diagnosed with B.cepacia in Intensive Care Unit (ICU), wards, and Outpatient Department (OPD) were reviewed. Identification was done by Vitek 2. Descriptive analysis was done and data was presented as percentages. Results: The number of cases showed a steady rise from 2013 through 2016 and the peak number of cases occurred in the year 2016. Then, again the numbers started to decline. Surgical ICU was the most common location (n=490) where the cases were detected. Most of the isolates were sensitive to cotrimoxazole, ceftazidime, tigecycline and levofloxacin and moderately sensitive to minocycline and meropenem. Conclusion: Burkholderia is no longer restricted to patients with Cystic Fibrosis (CF) and can affect patients in ICU setting and that the mortality from the infection remains high in our part of the world. Further studies are needed to be carried out to address this issue.

Objective: To determine the factors of iron deficiency anaemia among the post-menopausal women in our population. Study Design: Cross-sectional study. Place and Duration of Study: Department of Medicine, Pak Emirates Military Hospital, Rawalpindi Pakistan, from Aug 2019 to Jan 2020. Methodology: A total of 300 post-menopausal women were included in this study. Menopausal status was taken as one year after the last menstrual period. Iron deficiency anaemia was diagnosed, based on haemoglobin and ferritin levels. In addition,the relationship of age, age at menopause, comorbid medical illnesses and duration of menopause was assessed with the presence of iron deficiency anaemia among the post-menopausal women participating in this study. Results: Out of 300 post-menopausal women studied in the given period, 124(41.3%) had no anaemia, while 176(58.7%) had the iron deficiency anaemia. Furthermore, 225(75.0%) had menopause after the age of forty, while 75(25.0%) had menopause after the age of forty. After applying the binary logistic regression analysis, we found that advancing age, longer duration since menopause and presence of medical comorbidities had a statistically significant association with anaemia in the target population. Conclusion: This study showed a high frequency of iron deficiency anaemia among post-menopausal women. In addition, women with longer duration since menopause, advanced age and other medical illnesses were more at risk of having iron deficiency anaemia s compared to other women.