The use of motion capture has increased from last decade in a varied spectrum of applications like film special effects, controlling games and robots, rehabilitation system, animations etc. The current human motion capture techniques use markers, structured environment, and high resolution cameras in a dedicated environment. Because of rapid movement, elbow angle estimation is observed as the most difficult problem in human motion capture system. In this paper, we take elbow angle estimation as our research subject and propose a novel, markerless and cost-effective solution that uses RGB camera for estimating elbow angle in real time using part affinity field. We have recruited five (5) participants of (height, 168 ± 8 cm; mass, 61 ± 17 kg) to perform cup to mouth movement and at the same time measured the angle by both RGB camera and Microsoft Kinect. The experimental results illustrate that markerless and cost-effective RGB camera has a median RMS errors of 3.06° and 0.95° in sagittal and coronal plane respectively as compared to Microsoft Kinect.

Models of subsurface structures are important for successful deposit exploration but are challenged by the need to integrate data from different geophysical methods. In the present study, we evaluated a method of joint inversion in which audio-magnetotelluric (AMT) and dual frequency induced polarization (DFIP) data sets are inverted simultaneously to produce a consistent 2D resistivity model to show a clear image of subsurface structures. To achieve the objectives, we conducted AMT and DFIP surveys first on the same survey line within the Dongjun lead-zinc deposit in inner Mongolia by developing 31 AMT survey sites with an interstation separation of 40 m on a 1440 m survey track and operated in fifty-three frequencies in the range 1–10,400 Hz to record the resistivity distribution of subsurface to depths exceeding 800 m. The same survey setup up was applied to the DFIP method by utilizing the SQ-3C model with a pole-dipole array configuration and conducted measurements at frequencies of 4 Hz and 4/13 Hz. We first separately inverted AMT and DFIP measurements. The two-dimensional (2D) model obtained from AMT data revealed distinct low resistivity anomalies in the middle of the 2D inversion model. In contrast, the DFIP inversion model showed a high resistive body in the same region. In response to the discrepancies observed in the separate 2D inversion models, we implemented a joint inversion for both the AMT and DFIP datasets. The joint inversion resistivity model shows surficial conducting bodies and a high conductive body along the profile with relatively high Percent Frequency Effect (PEF) indicating high chargeability. The final joint inversion resistivity model clearly images the large silica alteration zone and the Pb-Zn mineralization. This study demonstrates the feasibility of a joint inversion methodology and highlights the value of integrating geophysical methods through joint inversion for enhanced characterization and exploration of lead-zinc ores.

The Qiushuwan Cu-Mo deposit, located in the East Qinling molybdenum belt, which is a major mining site recognized for its enormous reserves of medium-sized molybdenum. In order to enhance our comprehension and ascertain supplementary mineral resources, it is critical to conduct an in-depth investigation of both the deep and peripheral regions. The primary goal of this study is to investigate the Qiushuwan Copper Molybdenum Mine, which is located in Zhenping County, Henan Province. The spread spectrum-induced polarization (SSIP) method is utilized as a means of conducting mining exploratory analysis. Significant findings have been obtained through the collection of SSIP data, geological analysis, and electrical parameter study of rock and ore samples along profile-80. By conducting a meticulous examination of the SSIP data at suitable frequencies, two prominent conductive ore bodies, specifically C2 and C4, have been successfully discovered. C2 exhibits a correlation with granite porphyry and molybdenum veins, while C4 is linked to a skarn deposit that contains a concentration of copper ore. The spatial differences in conductivity within the research area have been precisely characterized using resistivity models obtained from the SSIP data. The precision and dependability of our conclusions have been confirmed through the integration of borehole data and the matching of geological sections with inversion models. The recovered core samples show a diverse range of minerals, containing both valuable ores and minerals that have undergone alteration. Pyrite constantly appears with molybdenite in the majority of samples. The aforementioned results provide a strong foundation for future exploration initiatives and sustainable resource exploitation, enabling informed decision-making in the effective use and administration of natural resources. This study adds to the existing body of knowledge on the Qiushuwan Cu-Mo deposit and improves exploration methods in the region by utilizing the SSIP approach. The findings are a useful asset for geologists, mining experts, and stakeholders, offering essential knowledge for future exploration and sustainable utilization of resources.

Hydrothermal /super critical processes are important process to synthesize materials which are otherwise difficult to form under normal conditions. A mathematical model is developed using standard transport equations to calculate the time for heating of hydrothermal reactor and computer simulation of the model was carried out in SOLIDWORKS® to validate it. The materials used to form reactor vessel were stainless steel (outer body) and TEFLON (PFA) (inner vessel). It was shown that composite wall, its geometry, construction & properties greatly affect the time and pattern of heat transfer. The time calculated and pattern generated were found to be in good agreement with experimental values.

The study investigates the evolution of soil pore structure and shear strength deterioration in compacted clayey soil under controlled wetting and drying (wd) cycles, which are expected to become more frequent due to climate change. Thirty soil samples were compacted at optimal moisture content and 90% of maximum dry density. These samples were then subjected to 0, 1, 5, 10, and 15 controlled wd cycles from saturation to the wilting point, and volumetric changes were recorded during each cycle. After the wd treatment, the soil samples were scanned using X-ray Computed Tomography (CT) at 50 μm resolution and then sheared under unconsolidated-undrained and consolidated-undrained conditions in a triaxial test. Significant shrinkage and swelling of soil samples were observed during wd cycles, with average volumetric strain fluctuating between +12% at saturation and -5% at the wilting point. X-ray CT visualisation and analysis revealed higher porosity, more prominent pores and increased pore length in soil samples with increasing wd cycles. Both undrained and effective soil shear strength markedly decreased with increasing wd cycles. CT-derived macroporosity and pore length were significant predictors of the soil's undrained and effective shear strength when exposed to wd cycles. The findings emphasise the considerable impact of climate change, specifically wd cycles, on clayey soil, highlighting the need for consideration in the design of earth-based infrastructure.

Immobilization of enzymes is a good field of study to expand the life of enzyme in and lowering the cost of the chemical processes such as separation processes. Urease is an important enzyme with medical and industrial applications. The aim of the present study is to prepare an immobilized urease on a strong cation exchange resin (Amberlite IR120 -Na) and study of its activity and stability. We monitored the liberation of Na ions in the collected fractions and searching for protein in the fractions as an indicators of immobilization by ion exchange phenomenon. Sodium is measured using atomic absorption spectroscopy techniques, while protein tested by Bradford’s method. Immobilized urease activity was evaluated by salicylate-hypochlorite method. The results indicated a complete immobilization of urease enzyme on the resin surface with reserving 92% of the activity of free enzyme. The immobilized urease enzyme on resin showed good stability and it has a 62% of its activity after 154 days of storage at room temperature. It is concluded that a new immobilized urease enzyme system is prepared with good enzyme activity and stability.

Black hole's quasinormal frequencies are basically the complex numbers which provide information about the relaxation of perturbations and depend on the characteristics of the spacetime and types of perturbations. In this paper, we evaluate the quasinormal modes of Hayward black hole in Einstein Gauss-Bonnet gravity, Hayward black hole in anti-de Sitter space (AdS) spacetime, and 4-dimensional black hole in Einstein-Lovelock gravity. By utilizing the WKB resonance technique, we examine the quasinormal modes frequencies $\omega$ by shifting the charge parameter $Q$ (it is also identified with the cosmological constant), circular harmonic index $l$, and mass of scalar field $m$. We also study the relaxation rate for those black holes and find out that the relaxation rate increases with increasing values of $Q$. We observe that real and imaginary components of the quasinormal modes are not linear functions as similar to Reisnner Nordstr\"{o}m-AdS. For large values of charge, quasinormal ringing becomes slower to settle down to thermal equilibrium and hence the frequency of the oscillation becomes smaller.

This paper presents a framework to recognize the affective state of children with Autism Spectrum Disorder (ASD) in an in-the-wild setting using Heart Rate (HR) information. Our algorithm classifies a child’s emotion into positive, negative, or neutral states by analyzing the heart rate signal. The HR signal is obtained from a smartwatch in real-time using our smartwatch application. The heart rate data is acquired when the child learns to code a robot while interacting with an avatar that assists the child in communications skills and programming the robot. In this paper, we also present a comparison of using HR data for the classification of emotions with classification based on features extracted from HR signals using Discrete Wavelet Transform (DWT). Our experimental results show that the proposed method produces a comparable performance with the state-of-the-art HR-based emotion recognition techniques, despite the fact that our experiments are performed in an uncontrolled setting as opposed to a lab environment. This work contributes to real-world affect analysis of children with ASD using HR information.

The present study was designed to check the prevalence of cancer in residents of District Bannu, Khyber Pakhtunkhwa. Patients' data were collected from three consulted Institutes during the year 2005-09. The data was analyzed for different parameters; year-wise, age-wise prevalence, gender-wise, occupation wise and marital status wise prevalence, addiction status, type of cancer, site affected, diagnostic tests performed and treatment of cancer. Results revealed that during 2005, a high number of cancer patients were present. A total of 172 patients were in the age group of 51-60 years, while only 11 patients were in the age group of 80 plus years. Female patients were more as compared to males. Married people were highly affected than unmarried. Patients addicted to smoking were highly affected than non-addicted patients. Malignancy was high in patients as compared to benign cancer. The most affected site was the blood system. The most affected people occupation wise were housewives followed by the farmer. A biopsy was mostly conducted for the diagnosis of cancer. Most of the patients were treated with chemotherapeutic agents. It has been revealed that the number of cancer patients decreased per annum. Moreover, the study should be conducted on the general population of Bannu as well as of the Khyber Pakhtunkhwa to sort out the total number of patients. The government should launch preventive, diagnostic programs so that prevalence may be minimized.

This study investigated the ability of a HYDRUS 1D model for predicting the vertical distribution of potassium iodine (200 ppm) in soil columns after amendment with five different common remediation materials (gypsum, lime, fly ash, charcoal and sawdust) at a rate of 2.5% (w/w), relative to an unamended control soil. Results shows that relative to the unamended soil, iodine leaching was decreased by all amendments but that the magnitude of the decreases varied with the soil amendment applied. Iodine content was highest in the upper layer of the soil columns and decreased progressively with soil depth. The model was evaluated via comparison of the model simulated values with measured values from the soil column studies. The results showed that the HYDRUS 1D model efficiency was near to 1, indicating that the stimulated results were near to the measured values. Therefore, this study showed that iodine leaching through a soil could be ascertained well using a HYDRUS 1D model. The model over predicted iodine leaching, resulting to a weak correspondence between the simulated and the measured results for iodine leaching. This suggests that the HYDRUS-1D model does not explain accurately different organic and inorganic amended soil and the preferential flow that occurs in these columns. This may be due to the fact that Freundlich isotherm, which is part of the transport equations, does not sufficiently describe the mechanism of iodine adsorption onto the soil particles. This study would help to select amendments for an effective management strategy to reduce exogenous iodine losses from agro-ecosystems. This would also improve understanding of iodine transport in soil profile.

The vehicular ad hoc network (VANET) when augmented with internet is called internet of vehicles (IoV). In the IoV, vehicles have on board units (OBUs), use communication technologies and customized software to communicate with infrastructure around them. The vehicles can have permanent connectivity and global network awareness based on cloud computing. IoV technologies are still being assessed to ensure that the network is protected from attacks, supports a dynamic vehicular mobility scenarios and meets the low latency communication requirements between the vehicles and the surrounding infrastructure. To meet these strict Quality of Service (QoS) demands, Unmanned Aerial Vehicles (UAVs) play a vital role in IoV ecosystems. An UAV can serve as a mobile roadside unit (mRSU) to transmit data between vehicles, stationery RSUs and other UAVs. The UAVs have better line of sight (LOS) connections which result in better channel states and lower path loss than fixed RSUs. Although the inclusion of UAVs in vehicular networks has improved the system performance by providing better resource management and routing solutions, the traditional optimization techniques with their limitations are often not applicable. Therefore, in recent years, research community is integrating Artificial Intelligence (AI) and Machine Learning (ML) into UAV based IoV ecosystem to better manage resource allocation, routing and mobility management issues to optimize the overall network performance. In this survey paper we review the existing research done in AI/ML based UAV-IoV networks and communications with focus on resource management and routing from year 2019 to 2023. We have studied different AI techniques, their training attributes and architectures in various research works. The limitations of AI-based approaches in terms of required computational resources, availability of real world data and AI models’ complexity for the UAV-IoV environment are also discussed. Finally, the future directions for UAV-IoV research opportunities that can leverage the full potential of AI are presented.

This study addresses the central question that how can a precise measurement of the gluon Parton Distribution Function (PDF) be attained, thereby enhancing our understanding of the intricate quark-gluon composition within nucleons? Through a dual approach involving Quantum Chromodynamics (QCD) and high-energy particle collisions, the research combines computational tools and experimental techniques, focusing on protons and neutrons. Scattering experiments and advanced detectors are utilized to probe nucleon structure. Theoretical frameworks like QCD equations and the Momentum Sum Rule investigate Parton Distribution Functions at specific momentum fractions and energy scales. The primary goal is to achieve an accurate measurement of the gluon PDF, crucial for unraveling strong force complexities and internal nucleon dynamics. The study's theoretical plots and equations illustrate hypothetical behaviors of gluon distribution, quark distribution, and splitting functions, contributing to a deeper understanding of fundamental particles.

This study reports the design of a dielectric resonator (DR) metasurface-based terahertz biosensor for rapid and accurate detection of different kinds of viruses (H1N1, SARA-COV-2, etc.). The characterization of the sensor is done by analyzing its absorbance properties with and without the presence of the H1N1 virus layer of different concentrations and electrical properties in the frequency range of 2.4 THz to 3 THz. A full-wave EM model of the sensor is designed using CST MWS software. The geometrical parameters of the proposed biosensor, as well as its dielectric constant of the virus swab, are varied to achieve good performance with an absorption level close to 1 (100%). A significant change in the resonating pick-up frequency owing to the variation in the effective refractive index of the realized sensor ensures the detection and classification of the different concentrations of the same or different viruses. The presented design could be used for the rapid detection of viruses with the added advantages of contactless, label-free, and accurate identification of different concentrations of viruses.

We study the validity of quantum Fisher information (QFI) as a faithful quantum coherence and correlation quantier by drawing a comparison with subsystem's coherence measure, rst-order coherence (FOC) and the entanglement measure, Negativity to study the behavior of thermal quantum coherence and correlations in two qubit Heisenberg XXX model, placed in independently controllable magnetic eld by systematically varying the coupling parameter, magnetic eld and bath temperature for ferromagnetic and antiferromagnetic case. After carefully observing the prole of quantum coherence and correlation measures, we propose an inequality relations which shows that there may exist a quantitative relationship between QFI, Negativity and FOC in which, the equality exists at zero temperature. We identify QFI to be a more useful coherence quantier, as it quanties coherence of individual subsystems and correlations among the subsystems. On the other hand, FOC identies coherence present in the individual subsystems only. A reciprocal relationship between Negativity and FOC is also observed in dierent cases. We also observe the existence of entanglement in ferromagnetic case, in contrast to simple Heisenberg XXX model in uniform magnetic eld. We show that in the ferromagnetic case, a very small inhomogeneity in magnetic eld is capable of producing large values of thermal entanglement. This shows that the behavior of entanglement in the ferromagnetic Heisenberg system is highly unstable against inhomogeneity of magnetic elds, which is inevitably present in any solid state realization of qubits.

The reconstructive ladder is a well-established concept in Plastic Surgery proposed to achieve wound closure using a stepladder approach from simple to complex procedures and it continues to evolve from when it was presented for the first time. We describe a new surgical technique that allows skin excision and primary wound closure avoiding donor site morbidity from skin grafts and avoiding large scars from loco-regional flaps: the parallelogram excision technique. Fifteen patients with skin lesions underwent this procedure. Six months' follow-up results showed a) good scar healing, b) total excision of lesions, and c) patient acceptance and satisfaction from the usage of this technique. We conducted a geometrical analysis of the parallelogram’s design to study the optimal geometrical condition to achieve all these three factors. We propose that the parallelogram excision of skin lesions proves to be a unique new wound closure technique that may add a new rung to the reconstructive ladder.

Background. Nanotechnology is promising field for generating new applications. A green synthesis of nanoparticles through biological methods using plant extract have a reliable and ecofriendly approach to improve our global environment. Methods. Silver nanoparticles (AgNPs) were synthesized using aqueous extract of Anagalis arvensis L and silver nitrate and were physicochemically characterized. Results. The stability of AgNPs toward acidity, alkalinity, salinity and temperature showed that they remained stable at room temperature for more than two months. The SEM and TEM analysis of the AgNPs showed that they have a uniform spherical shape with an average size in the range of 40–78 nm. Further 1-Dibhenyl-2-Picrylhydrazl radical in Anagalis arvensis L.mediated AgNPs showed a maximum activity of 98% at concentration of 200μg/mL. Hydrogen peroxide scavenging assay in Anagalis arvensis L. mediated AgNPs showed a maximum activity of 85% at concentration of 200μg/mL. Reducing power of Anagalis arvensis L.Ag NPs exhibited a higher activity of 330 μg/mL at concentration of 200 μg/mL. These NPs have cytotoxic effects against brine shrimp (Artemia salina) nauplii with a value of 53% LD 178.04μg/mL. Conclusion. The AgNPs synthesized using Anagalis arvensis L. extract demonstrate a broad range of applications.

Traditional marketing tactics have been significantly challenged by marketers, especially in the food sector. Companies have been engaging in covert and overt advertisements as an emerging marketing communication strategy to circumvent customer skepticism, build a good image, and create value for the brand. But there is a lack of literature regarding integrating traditional and new marketing tactics in building intention and ecologically conscious consumer behavior. Therefore, the purpose of the present study is to provide empirical evidence concerning the integration of different marketing tactics, i.e., Green Product Features, Green Pricing, Covert Advertisement, Overt Advertisement and Guerrilla Marketing, and their effects on Purchase Intention and Ecologically Conscious Consumer Behavior. The study also employs moderation of Brand Evangelism, Environmental Knowledge and Habitat Attitude between intention and behavior building. A visual appraisal technique was used by showing a video or picture as a sample of covert or overt marketing tactics before filling out a close-ended questionnaire to get accurate responses. The data from 568 customers of the frozen food industry were analyzed using the co-variance-based structure equation modeling technique with the help of AMOS. The findings of the study elaborate that parallel to the significant impact of conventional marketing mix tactics, covert, overt and guerrilla marketing are strong antecedents for intention building, which eventually develops Ecologically Conscious Consumer Behavior (ECCB). The results also affirm that intention can lead to ECCB significantly through brand evangelism and environmental knowledge. These findings reflect the importance of shifting marketers from conventional marketing tactics to novel hidden marketing techniques.

The present study investigates the decision-making process of investors on the Pakistan Stock Exchange with regard to portfolio construction, explicitly focusing on the incorporation of ESG concerns. The present study employed SmartPLS and structural equation modeling (SEM) to quantitatively assess data received from a sample of 393 out of 400 respondents. Based on the available data, investors participating in the Pakistan Stock Exchange are notably impacted by ESG aspects. The findings of this study hold significance for emerging economy firms, regulators, and investors, both in terms of theoretical and practical ramifications. The study's findings demonstrate a clear indication of investors' significant emphasis on ESG matters. Furthermore, it provides valuable insights for stakeholders who are involved in the ever-evolving realm of sustainable finance within developing countries

Irrigation water management components evaluation is mandatory for sustainable irrigated agriculture production in the era of water scarcity. In this research spatio-temporal distribution of irrigation water components were evaluated at canal command area in Indus Basin Irrigation System (IBIS) using remote sensing based geo-informatics approach. Satellite derived MODIS product-based Surface Energy Balance Algorithm for Land (SEBAL) was used for the estimation of the Actual Evapotranspiration (ETa). Satellite derived SEBAL based ETa was calibrated and validated using the ground data-based advection aridity method (AA). Statistical analysis of the SEBAL based ETa and AA shows the mean 87.1 mm and 47.9 mm and, 100 mm and 77 mm, Standard deviation of 27.7 mm and 15.9 mm and, 34.9 mm and 16.1 mm, R of 0.93 and 0.94, NSE of 0.72 and 0.85, PBIASE -12.9 and -4.4, RMSE 34.9 and 5.76 for the Kharif and Rabi season, respectively. Rainfall data was acquired from the Tropical Rainfall Measuring Mission (TRMM). TRMM based rainfall was calibrated with the point observatory data of the Pakistan Metrological Department Stations. Canal water data was collected from the Punjab Irrigation department for the assessment of canal water availability. Water The water balance approach was applied in the unsaturated zone for the quantification of the gross and net Groundwater irrigation. Mmonthly variation of ETa with the minimum average value of 63.3 mm in January and the maximum average value of 110.6 mm in August was found. While, the average annual of four cropping years (2011-12 to 2014-15) ETa was found 899 mm. Average of the sum of Net Canal Water Use (NCWU) and Rainfall during the study period of four years was only 548 mm (36% of ETa) and this resulted the 739.6 mm of groundwater extraction. While the annual based variation in groundwater extraction of 632 mm and 780 mm was found. Seasonal analysis revealed 39% and 61% of groundwater extraction proportion during Rabi and Kharif season, respectively. The variation in four cropping year’s monthly groundwater extraction was found 28.7 mm to 120.3 mm. This variation was high in the 2011-12 to 2012-13 cropping year (0 mm to 148.7 mm), dependent upon the occurrence of rainfall and crop phenology. Net groundwater irrigation, estimated after incorporating the efficiencies was 503 mm year-1 on average for the four cropping years.

Use of rhizosphere microorganisms provides an alternative or supplement to conventional plant breeding to improve water deficit tolerance of tomato plants. Experiment was carried out to explore the effect of two microbial species, AMF (Rhizophagus irregularis) and Bacillus subtilis, in single and co-application, on growth, colonization, and molecular aspects of tomato plants under drought stress. Co-inoculated plants showed less reduction in growth traits, photosynthetic pigments, colonization rate, and increased compatible solutes like proline which help in sustaining relative water content than non-inoculated plants. Inoculation considerably enhanced proline dehydrogenase activity, and significantly reduced both Δ1-pyrroline-5-carboxylate reductase Δ1-pyrroline-5-carboxylate synthetase activity causing lower proline accumulation in inoculated plants under drought stress. Co-inoculated plants showed obvious upregulation of antioxidant system, thus facilitating amelioration of oxidative stress through exclusion of reactive oxygen species. No inoculation under drought stress upregulated abscisic acid related genes expression but have no effect in plants inoculated either sole or mixed inoculation. Expression of aquaporin genes was upregulated in plants co-inoculated and with AMF alone under normal condition. However the expression of aquaporin genes were decreased or unaffected in plants inoculated with Bacillus subtilis but increased in non-inoculated plants. Co-applied AMF and bacillus subtilis substantially increase drought tolerance by upregulating proline metabolism, antioxidant enzymes and aquaporin genes. Therefore our results suggest that co-inoculation mediated drought tolerance is linked with increased proline accumulation, enhanced antioxidant enzyme activities and differential regulation of ABA biosynthetic and aquaporin genes, which is vital for osmotic adjustment of host plant.

This work presents the design and analysis of a novel metal-insulator-insulator-metal (MIIM) rectenna with an added meta lens on top of it for efficient and robust infrared (IR) energy harvesting at 28.3 THz. To ensure maximum transfer of the captured IR radiations by an antenna with better impedance matching, the log-spiral antenna terminals are used as rectenna electrodes while two different insulators are placed between its feeding terminals to form the MIIM rectenna. A split ring-based resonating metasurface is designed and placed on the top of the MIIM rectenna to focus the incoming electromagnetic radiations. The characterization of the MIIM rectenna with added meta lens, in terms of absorbed E-field, is performed for the four different work function metals (gold aluminum, silver, and copper) as well as four combinations of aluminum oxide, titanium oxide, zinc oxide, and copper oxide as insulators. The focusing of illuminating IR radiations by the integrated meta lens to the rectenna structure enhances its field-capturing characteristic by more than 400% as compared to conventional structures. In addition, the proposed design shows improved rectification properties in terms of better impedance matching and rectification efficiency, particularly for the best configuration of Au-Al2O3-Cu2O-Cu rectenna with added metasurface. Future applications of this study include the development of efficient IR energy harvesting systems for remote sensing, wireless communication, and other IoT devices.

This study assesses the pursued impacts of Tulsi value chain development intervention on the livelihoods of rural poor in Uttarakhand state of India. Tulsi as an alternative livelihood, particularly for the rural poor, is less explored. With increased crop depredation of major cereal crops grown in the district by wild animals and pests, and decreasing availability of water agriculture, attempts were made to improve earnings from Tulsi as an alternative livelihood. Findings suggest that the average households’ gross profit from Tulsi farming increases by more than double within a span of two years. Total crop income of beneficiary farmers’ increases by 0.8 percent for every 1 percent increase in Tulsi income. Intervention helped enhance productivity of Tulsi, thereby enhancing earnings from Tulsi farming. Most importantly, intervention has shown a tremendous adoption rate. Towards the end of the intervention, the value chain work was out-scaled to another 19 villages in Chamoli district, thereby reaching out to more than 400 households.

Purpose: Data on Eosinophilic esophagitis in Israel is sparse. We appraised the clinical, endoscopic, and histological characteristics of 50 Israeli adults with EoE. Methods: Medical records of 50 adult patients with established diagnoses of EoE who were referred to our center from 2020 until 2023 at Bnai Zion Medical Center, Haifa, Israel, were reviewed. Results: Fifty patients with EoE were included, the mean age at diagnosis was 34±9.5 years. The sex ratio of males to females was approximately 2:1 with 34 males (68%) and 16 females (32%). Twenty-two of the 50 patients had a history of allergic diseases, Symptoms at diagnosis were as follows: Dysphagia was the primary presenting symptom observed (n=25, 50%), followed by food impaction (n=17, 34%) and GERD-like symptoms (n=14, 28%). Less frequent symptoms included vomiting, nausea, and chest pain. The most common endoscopic findings were normal mucosa (n=21, 42%) followed by Trachealization (n=17, 34%), esophagitis (n=7, 14%), and exudates (n=5, 10%). 66% of the subjects were initially treated with proton-pump inhibitors (PPIs). Nine patients (18%) were asymptomatic without any treatment. The remaining eight patients (16%) were given topical steroids. Clinical and histological resolution was detected in 50% of the patients who underwent a second EGD after 6–8 weeks of PPI. Conclusion: Our current study depicts the clinical features of adult patients with EoE in north Israel. This is the first demographic study in Israel that defines the clinical, endoscopic, and histological manifestations of EoE in the adult population.

This paper discusses the design and implementation of a portable IoT station. Communication and data synchronization issues in several installations are addressed here, making possible a detailed analysis of the entire system during its operation. The system proposed is interpreted as an additional tool which can be utilized in several applications, where the system operator requires a synchronized data stream, combining multiple communication protocols into one single time stamp. The hardware selected for the portable IoT station complies with the International Electrotechnical Commission (IEC) industrial standards. A short discussion regarding interface customization shows how easily the hardware can be modified so that it is integrated with almost any system. A Programmable Logic Controller enables the Node-Red to be utilized. This open-source programming tool employs flows to define operations for each global variable nominated in the Modbus register. Two applications are presented and discussed in this paper, each application has a distinct methodology utilized to publish and visualize the acquired data. The portable IoT Station is highly customizable, consisting of a modular structure and providing the best platform for future research and development of dedicated algorithms.

Novel severe acute respiratory syndrome coronavirus 2 infection (SARS-Cov-2) is an acute respiratory and infectious disease. This perspective aims to provide the basic understanding of the inflammation caused by SARS-Cov-2 and relation to trigeminal ganglion (TG). Virus enters through the mucous membranes of orofacial region and reach the TG where it resides and take control of its peptides including Substance P (SP).SP is the main neuropeptide, neuromodulator and neuro-hormone of TG, associated with nociception and inflammation under noxious stimulus. SP release is triggered and consequently, it affects the immune cells, blood vessels to release the mediators for inflammation. Cytokine storming is initiated and cause respiratory distress, bronchoconstriction and death in complicated cases. Neurokinin-1 Receptor (NK-1R) antagonist and glucocorticoids may be used to alleviate the symptoms and treat this infection. SP is the main culprit seem to be involved in the triggering of inflammatory pathways in SARS-Cov-2 infection. It has direct association with cardiorespiratory rhythm, sleep-wake cycle, nociception, ventilator responses and regulates many important physiological and pathological roles. Its over-secretion should be blocked by NK-1R antagonist. However, experimental work leading to clinical trials are mandatory for further confirmation.

Mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome is one of the most frequent maternally inherited mitochondrial disorders.MELAS syndrome is a multi-organ disease that presents with a wide range of symptoms, such as dementia, epilepsy, lactic acidemia, myopathy, hearing loss, stroke-like episodes, diabetes, short stature, and myopathy. MELAS primarily affects tissue with high energy demands such as the brain, muscles, and heart. With 65–76% of affected people presenting at or before the age of 20, childhood is the typical age of onset. Genetic testing, imaging tests such as magnetic resonance imaging (MRI) scans, and other techniques, tests of blood, urine, and cerebrospinal fluid in addition to muscle biopsy (if necessary) may be used to diagnose MELAS syndrome. Management of MELAS remains largely supportive, focusing on symptom alleviation and metabolic stabilization. The long-term prognosis of MELAS is variable, influenced by factors such as age of onset, severity of symptoms, and presence of comorbidities. While some patients experience a relatively stable course with intermittent exacerbations, others may exhibit progressive neurological deterioration and multiorgan involvement. Early recognition, prompt intervention, and close monitoring are essential for optimizing outcomes and mitigating complications.Presenting here a case report of an occurrence of MELAS in a 31-year old male patient with chief complaints of perspiration, uneasiness and weight loss with increase in appetite and past history of bilateral hearing loss and vision loss in left eye.

In this research work the study of Buongiorno Model Darcy Forchheimer flow of Hybrid nanofluid flow on isothermal permeable stretch/shrink sheet with homogeneous and heterogeneous reaction is investigated. The effects of MHD, thermal radiation, viscous dissipation, Joule heating, and heat generation/absorption are taken into account. Hybrid nanofluids can act as a medium for heterogeneous-homogeneous reactions. The nanoparticles dispersed in the fluid can influence reaction kinetics and species transport, potentially, altering reaction rates and pathways. The applications of HNF in reactions, both homogeneous and heterogeneous, lie in leveraging their enhanced thermal properties, catalytic potential, and improved mixing capabilities to optimize reaction efficiency and control reaction conditions. Similarity transformation is used to convert a set of PDEs into a set of ODEs. HAM is used for the solution of the obtained ODEs system. In a heterogeneous reaction, the concentration gradient is amplified; in a homogeneous reaction, the impact is opposite. Moreover, at higher compositions of HNPs, the concentration and velocity rise while the temperature falls. Furthermore, as the values of homogeneous and heterogeneous reactions increase, the concentration falls. It is reliable with the idea that a greater reaction rate lowers the diffusion rate. Nevertheless, these parameters do not affect temperature or velocity.

Glacial meltwater has been lifeline of agriculture in Gilgit-Baltistan for centuries which is being effected by the climatic changes and associated challenges. The government line institutions and development agencies have been investing to sustain and further extend the cultivated areas by leveraging the available glacial meltwater source. However, approximately 13% arable land, laying mainly along river banks, has limited access to glacial meltwater. Moreover, already cultivated areas also need alternate and sustainable irrigation water supplies to insurefood security. Hence, there is need to explore more potential options to address these challenges and bringing arable land under irrigation for regional prosperity and environmental gains. The International Centre for Integrated Mountain Development (ICIMOD) and its partners piloted solutions for aforementioned issues in Gojal, District Hunza. These solutions included river water lifting through solar and Hydraulic Ram Pumps, uphill water storages and application through drip irrigation systems. In order to assess the technical and economical viabilities of these piloted systems, a semi-structured questionnaire survey, field observation visits to collect data and economic assessment studies were carried out in Morkhun and Khyber. Both piloted systems have been proven as climate resilient, adaptable, environment friendly and economically viable. The cost to benefit ratio for solar powered drip irrigation and Hydraulic Ram Pump drip irrigation systems are 2.96 and 4.21 respectively, with payback period of 9.21 and 8.25 years respectively. The drip irrigation systems at Khyber and Morkhun sites have exhibited excellent hydraulic performance with Coefficient of Uniformity 92.61 and 93 % respectively. However, the field application efficiency of drip irrigation systems estimated for Khyber and Morkhun sites are 85.24 and 88.88% which are lower than the optimal value mainly due to lesser water holding capacity. The Hydraulic Ram Pump can lift four times more water to greater height, while comparing to solar pump of approximately similar capacity and higher capital costs. Both water lifting systems have some limitations and requires local customization for sustainable use.

In this research, a computation algorithm is established for a fractional order 2D fuzzy heat equation. In this study, Elzaki transform and HPM fusion is produced. Computing the desired outcome in series yields a fast convergence on an appropriate response. Examples are provided to support the conclusions, which are then compared with a particular approach to show the effectiveness and potential of the suggested approach. Two crisp equations—one for the lower bound solution and one for the upper bound solution are constructed from the input fuzzy fractional heat equation. The contour and surface representations of the approximate and exact results are offered for the lower and upper-bound solutions. The l∞-error norm is used in this study to validate the numerical convergence aspect. Together with the absolute inaccuracy, the approximate and exact solutions are matched. It has been demonstrated that the proposed regime will make it feasible to work with fuzzy fractional partial differential equations in a wide range of dimensions.

The significance of arts incorporated with culture inclusion makes the arts a matter of pressing interest. The arts are vital elements of a healthy society that benefits the nations even in difficult social and economic times. Based on the previous studies this research was conducted for the first time in Pakistan to explore the historical background of public art correlated with cultural and religious ethics. Though, Pakistan has a rich cultural history yet the role of modern public art is new and often used unintentionally. Our findings of different surveys conducted in Pakistan including oldest cities such as Lahore, Peshawar and newly developed, the capital city, Islamabad concluded that Public art has a rich cultural and historical background and the local community are enthusiastically connected to it. Different community groups prefer different types of public art in their surroundings depends on the city’s profile, cultural background, and religious mindset of the local community. Overall, the sculptures and depiction of animated beings are not considering right and debatable among the Pakistani societies. On the other hand, the cultural and historical monuments are highly appreciated and welcomed by the local community of Pakistan. This study may create scope for future estimation and development of public art in Pakistan in association with Islamic laws and cultural norms of the local society.

The supramolecular based macrocyclic amphiphiles have attracted great attention in the field of drug delivery due to their unique self-assembling nature. Therefore, these macrocycles are used as nanocarriers for the delivery of poor water soluble drugs, and also for those which have lower permeability, and cannot cross the barrier to reach the desired site. Herein, we design and synthesized a new supramolecular amphiphilic macrocycle to overcome these problems. The macrocycle was synthesized in two steps. In first step 4-hydroxybenzaldehyde was treated with 1-bromotetradecane to obtain a derivatized product which was then treated with resorcinol to cyclize and get calix(4)resorcinarene based supramolecular amphiphilic macrocycle. The synthesized macrocycle and intermediate products were characterized by Mass spectrometry, IR and 1H-NMR spectroscopic techniques. The amphiphile was screened for biocompatibility studies, vesicles formation, and then Amphotericin-B was loaded in the supramolecular amphiphile based vesicles and was characterized for shape, size, homogeneity, surface charge, drug entrapment, in-vitro release profile and stability through atomic force microscopy (AFM), Zetasizer, HPLC and FT-IR. Amp-B loaded macrocycle based vesicles were investigated for in-vivo bioavailability in rabbits. The synthesized macrocycle was nontoxic in cancer cells, hemo-compatible and safe in mice. The drug-loaded macrocycle based vesicles appeared spherical, nano-ranged, and homogeneous in size with negative surface charge and were able to load an increased amount of drug. The vesicles are stable upon storage and when incubated with gastric simulated fluid. Amp-B increased oral bioavailability was achieved when delivered in synthesized macrocycle based vesicles. These results point out that the synthesized supramolecular amphiphile is an efficient nanocarrier to enhance the oral bioavailability of lipophilic drugs

Hepatitis B virus (HBV) infection remains a global public problem despite the availability of effective vaccine. In the past decades, nonalcoholic fatty liver disease (NAFLD) has surpassed HBV as the most common cause of chronic liver disease worldwide. The prevalence of concomitant chronic hepatitis B (CHB) and NAFLD, thus, reaches endemic in geographic regions where both conditions are common. Patients with CHB and NAFLD are at increased risk of liver disease progression to cirrhosis and hepatocellular carcinoma. Due to complexity of the pathogenesis, accurate diagnosis of NAFLD in CHB patients can be challenging. Liver biopsy is considered the gold standard for diagnosing and determining the disease severity, but it is an invasive procedure with potential complications. There is a growing body of literatures on the application of novel noninvasive serum biomarkers and advanced radiological modalities to diagnose and evaluate NAFLD, but most have not been adequately validated especially for patients with CHB. Currently, there is no approved therapy for NAFLD though many new agents are in different phases of development. This review provides a summary of the epidemiology, clinical features, diagnosis and management of the NAFLD and highlights the unmet needs in the areas of CHB and NAFLD coexistence.

Abstract: The empirical soil loss model, RUSLE, was used with a conjunction of remotely sensed data and geographic information system technology to delineate the soil erosion and watershed priorities in terms of conservation practices at seven boundary sub-watersheds (labeled as SW-00, SW-01, …, SW-06) between Iraq and Iran at Ali Al-Gharbi area, southern Iraq. The six factors of the RUSLE model, ie. the rainfall erosivity, the soil erodibility, the slope steepness length, the crop management, and management practice, were calculated or estimated using information from different data sources such as remotely sensed data and previous studies. The finding showed that the annual soil erosion loss ranges from 0 - 1890 (tons h-1 y-1) with an average of 0.66 (tons h-1 y-1). Values of soil erosion were classified into five classes: very low, low, moderate, high, and very high. The potential soil loss in the high and very high classes ranges from 14.84 to 1890 (tons h-1 y-1), and these classes occupy only 27 km2 of the study area, indicating that the soil loss is very low in the area being examined. In terms of the spatial distribution of soil loss, the northern and northeastern parts (mountains and hills) of the sub-watersheds where the slope is steeper are more likely to erode than the plain area in the southern and southeastern portions, indicating that slope, in addition to rainfall erosivity, has a dominant effect on the soil erosion rate. The study of soil erosion in the watersheds under consideration reveals that only the northern portions of the SW-00, SW-02, and SW-04 watersheds require high priority conservation plans; however, these portions are primarily located in mountain regions, making conservation plans implementation in these areas impractical. Due to low soil loss, other sub-watersheds, particularly SW-01, SW-03, SW-05, and SW-06, are given low priority.

Cartilage degeneration is a characteristic of osteoarthritis (OA) which is often observed in aging populations. This degeneration is due to the breakdown of articular cartilage (AC) mechanical and tribological properties, primarily attributed to lubrication failure. Understanding the reasons behind these failures and identifying potential solutions could have significant economic and societal implications, ultimately enhancing the quality of life. This review provides an overview of developments in the field of AC, focusing on its mechanical and tribological properties. The emphasis is on the role of lubrication in degraded AC, offering insights into its structure and function relationship. Further it explores the fundamental connection between AC mechano-tribological properties and the advancement of its degradation and puts forth recommendations for strategies to boost its lubrication efficiency.

The most important plastic resins used for wire coating are Polyvinyl Chloride (PVC), Nylon, Polysulfone and Low-high density polyethylene (LDPE / HDPE). In this article,the coating process is performed using elastic-viscous fluid as a coating material for wire coating in a pressure type coating die. The elastic-viscous fluid is electrically conducted in the presence of an applied magnetic field. The governing non-linear equations are modeled and then solved analytically by utilizing an Adomian decomposition method (ADM). The convergence of the series solution is established. The results are also verified by Optimal Homotopy Asymptotic Method (OHAM). The effect of different emerging parameters such as non-Newtonian parameters α and β, magnetic parameter M and the Brinkman number Br on solutions (velocity and temperature profiles) are discussed through several graphs. Additionally, the current result also compares with the published work already available in the literature.

This article explores the transformative role of neural networks in the realm of biology, particularly within microscopy image processing and illustrations. Neural networks have revolutionized cell segmentation and analysis, enabling precise delineation of cell boundaries and tracking of cellular behaviours. They excel in detecting subcellular structures, unravelling intricate organelle interactions. In 3D image reconstruction, neural networks navigate volumetric datasets, enhancing our understanding of spatial cellular architecture. These networks enhance disease diagnosis by identifying anomalies and irregularities, potentially revolutionizing early detection and classification. Moreover, neural networks restore and enhance microscopy images, unveiling hidden details. Lastly, they bridge art and science, fostering captivating biological art and enriching science communication. As neural networks evolve, they promise a future of limitless possibilities, weaving together technology, science, and art to illuminate the microscopic realm in unprecedented ways.

Peste des Petits Ruminants (PPR) is one of the major transboundary animal diseases that severely impact livestock production and trade worldwide. An investigation was carried into the seroprevalence and risk factors of PPR in small ruminants, camels, and wild ruminants in Bahrain. A total of 1240 serum samples were collected from 119 sheep flocks and 1224 serum samples from 125 goat herds. In addition, 100 sera from camels and 38 sera from wild ruminants, were collected. Serum samples were tested for the presence of PPR specific antibodies using a competitive ELISA. Flock management and health information of the flocks and herds were collected using a semi-structured questionnaire. The individual prevalence of PPR in sheep and goats was 26% and 25.5%, respectively. The flock or herd level prevalence of PPR was 22.7% and 29.6% in sheep and goats, respectively. None of the tested camels or wild ruminants were positive for PPR-specific antibodies. Sheep and goats from the Northern governorate were more likely to be seropositive to PPR than in other governorates. On the individual animal level, the univariate analysis suggested; age (<12 months), sex (male), and health status (weak animals) as risk factors for PPR seropositivity. On the flock/herd level, the multivariable logistic regression analysis identified large flock/herd size and semi-intensive farming as risk factors for PPR seropositivity.

The mortality rate of women during the gestation period or after delivery is very high worldwide. ToRCH pathogens [Toxoplasma gondii (T.gondii), Rubella Virus (RV), Cytomegalovirus (CMV), and Herpes Simplex Virus (HSV)] are transmitted vertically and are associated with mortality and complications both in the mother and the fetus or children. Therefore, this study is designed to investigate the ToRCH pathogen-induced histopathological changes in placental tissues and associated post-obstetric complications in Pakistani women. Women (N = 68) included in this study were divided into Group A (women with current abortion and bad obstetric history-BOH) and Group B (women with normal delivery and BOH). The venous blood collected was analyzed for ToRCH antibodies through ELISA. A small piece of placenta tissue taken after delivery or abortion was subjected to nucleic acid (NA) detection through PCR using ToRCH pathogen-specific primers. The placental tissue was analyzed for histopathological changes under a microscope. The data obtained were analyzed using percentages and the Chi square test. Overall ToRCH antibody positivity was 64.70% (44/68). Of these, IgM (Immunoglobulin M) was found in 17.65% (12/68), IgG (Immunoglobulin G) in 45.59% (31/68), and one case (1.47%) was seropositive for both IgM and IgG. The NA was detected in 66.18% (45/68) of the placental tissues of the study population. The higher prevalence of antibodies for T.gondii and RV (23.53% each) and NA for RV, CMV, and HSV (17.99% each) was observed in the study population. The ToRCH infection (antibodies and NA) with BOH complications was statistically found to be non-significant (p> 0.05). Overall discrepancies in ToRCH antibodies and NA positivity were found in 86.76% (59/68) of cases, especially for RV (26.47%). Chorionic villitis (CV) in placental tissues was observed in 20.59% (14/68), i.e., 13.23% of Group A and 7.35% of Group B. Of the total, four women with T.gondii, six with RV, and three each with CMV and HSV infection were found with CV. The most common BOH complications observed were recurrent spontaneous abortions (RSAs) (47.05%, 32/68), stillbirth (22.05%, 15/68), congenital abnormalities (14.70%, 10/68), etc. It was observed that RSAs were associated with CV (10.29%) in the study population. The BOH complication and CV were found to be statistically non-significant (p> 0.05). It is concluded that ToRCH pathogens are prevalent in the study population, and CV was the only histopathological change found and associated with BOH complications.

In the search of potent α-amylase inhibitors, we have synthesized seventeen derivatives of 2-mercaptobenzimidazole bearing sulfonamide (1-17) and evaluated for their α-amylase inhibitory potential. All compounds display a variable degree of α-amylase activity having IC50 values ranging between 0.90 ± 0.05 to 11.20 ± 0.30 µM when compared with the standard drug acarbose having IC50 value 1.70 ± 0.10 µM. Compound 1, 2, 11, 12 and 14 having IC50 values 1.40 ± 0.10, 1.30 ± 0.05, 0.90 ± 0.05, 1.60 ± 0.05 and 1.60 ± 0.10 µM respectively were found many folds better than the standard drug acarbose. The remaining analogs showed good inhibitory potentials. All the synthesized compounds were characterized by HREI-MS, 1H and 13C-NMR. Structure activity relationship (SAR) has been recognized for all newly synthesized analogs. Through molecular docking study, binding mode of active analogs with α-amylase enzyme was confirmed.

This research paper aims to examine the various aspects of cryptocurrencies, from their inception to their current status in the financial market, using a multidisciplinary approach that incorporates mathematical and psychological methods to explore the factors that contribute to the success of celebrity endorsements and the potential risks associated with them. The first section (1.1) of this research paper will provide an overview of cryptocurrencies, exploring their history, functionality, and impact on the global financial market. This will involve examining the technical details behind cryptocurrencies, such as blockchain technology, and the differences between various types of virtual assets. The research will also discuss the potential advantages and disadvantages of investing in cryptocurrencies, as well as the regulatory challenges they face. The second section (2.1) of the research paper will focus on the psychological aspect of cryptocurrency investing, analyzing the connection between personality traits and the likelihood of purchasing a cryptocurrency based on a celebrity endorsement. This will involve investigating Howard Gardner's theory of multiple intelligences to understand the qualities that make people more susceptible to investing in a cryptocurrency without prior knowledge (Gardner, 1983). The third section (3.1) of the research paper will delve into the mathematical side of cryptocurrency investing, examining the factors that contribute to the success of celebrity endorsements and the artificial growth of cryptocurrencies. This will involve developing software to calculate the artificial growth of a cryptocurrency over a 24-hour period and analyzing the data to understand the underlying factors driving its value. By taking a multidisciplinary approach, this research will shed light on the complexities of investing in virtual assets and help inform investors of the potential risks and benefits of investing in cryptocurrencies through qualitative and quantitative analyses and through the use of a Multi-Level Latent Class Analysis (LCA).

Recent years have witnessed significant advances in reinforcement learning (RL), which has registered remarkable success in solving various sequential decision-making problems in machine learning. Most of the successful RL applications, e.g., the games of Go and Poker, robotics, and autonomous driving, involve the participation of more than one single agent, which naturally fall into the realm of multi-agent RL (MARL), a domain with a relatively long history, and has recently re-emerged due to advances in single-agent RL techniques. Although, typically, the communication protocol between agents is manually specified and not altered during training, recently, some papers have shown signs of trying to emerge a communication between agents on the one hand and, on the other hand, to understand what is exchanged between agents. So, there is a growing body of literature on this topic which includes qualitative and quantitative studies and the ones that apply mixed methods. This study presents the scoping review of the methodological strategies undertaken in a total of 16 research articles. The results present the critical appraisal of quantitative methods in terms of validity and reliability and for qualitative methods considering four trustworthiness factors. In the end, relevant insights are further explored with implications and reflections on how they can benefit one's research in the field.

Neurology is a quickly evolving specialty that requires clinicians to make precise and prompt diagnoses and clinical decisions based on the latest evidence-based medicine practices. In all Neurology subspecialties, Stroke and Epilepsy in particular, clinical decisions affecting patient outcomes depend on neurologists accurately assessing patient disability. Artificial intelligence (AI) can predict the expected neurological impairment from an AIS (Acute Ischemic Stroke), the possibility of ICH (IntraCranial Hemorrhage) expansion, and the clinical outcomes of comatose patients. This review article informs readers of artificial intelligence principles and methods. The article introduces the basic terminology of artificial intelligence before reviewing current and developing AI applications in neurology practice. AI holds promise as a tool to ease a neurologist’s daily workflow and supply unique diagnostic insights by analyzing data simultaneously from several sources, including neurological history and examination, blood and CSF laboratory testing, CNS electrophysiologic evaluations, and CNS imaging studies. AI-based methods are poised to complement the other tools neurologists use to make prompt and precise decisions that lead to favorable patient outcomes.

In recent times, BERT based transformer models have become an inseparable part of the 'tech stack' of text processing models. Similar progress is being observed in the speech domain with a multitude of models observing state-of-the-art results by using audio transformer models to encode speech. This begs the question of what are these audio transformer models learning. Moreover, although the standard methodology is to choose the last layer embedding for any downstream task, but is it the optimal choice? We try to answer these questions for the two recent audio transformer models, Mockingjay and wave2vec2.0. We compare them on a comprehensive set of language delivery and structure features including audio, fluency and pronunciation features. Additionally, we probe the audio models' understanding of textual surface, syntax, and semantic features and compare them to BERT. We do this over exhaustive settings for native, non-native, synthetic, read and spontaneous speech datasets

With the increase of the Artificial Neural Network (ANN), machine learning has taken a forceful twist in recent times. One of the most spectacular kinds of ANN design is the Convolutional Neural Network (CNN). The Convolutional Neural Network (CNN) is a technology that mixes artificial neural networks and up to date deep learning strategies. In deep learning, Convolutional Neural Network is at the center of spectacular advances. This artificial neural network has been applied to several image recognition tasks for decades and attracted the eye of the researchers of the many countries in recent years as the CNN has shown promising performances in several computer vision and machine learning tasks. This paper describes the underlying architecture and various applications of Convolutional Neural Network.

Type 2 diabetes mellitus (T2DM) is frequently accompanied by affective disorders with a prevalence of comorbid depression of around 25%. Nevertheless, the biomarkers of affective symptoms including depression and anxiety due to T2DM are not well established.Aims: This study was conducted to delineate the serum biomarkers predicting affective symptoms due to T2DM above and beyond the effects of insulin resistance and atherogenicity. Methods: The present study delineated the effects of serum levels of copper, zinc, β-arrestin-1, FBXW7, lactosylceramide (LacCer), serotonin, albumin, calcium, magnesium, IR and atherogenicity on severity of depression and anxiety in 58 men with T2DM and 30 healthy male controls. Severity of affective symptoms was assessed using the Hamilton Depression and Anxiety rating scales.Results: We found that 61.7% of the variance in affective symptoms was explained by the multivariate regression on copper, β-arrestin-1, calcium, and insulin resistance coupled with atherogenicity, while 44.4% of the variance in the latter was explained by copper, β-arrestin-1, LacCer (all positively) and calcium and FBXW7 (both negatively). Copper and LacCer (positive) and calcium and BXW7 (inverse) had significant specific indirect effects on affective symptoms which were mediated by insulin resistance and atherogenicity. Copper, β-arrestin-1, and calcium were associated with affective symptoms above and beyond the effects of insulin resistance and atherogenicity.Discussion: T2DM and affective symptoms share common pathways namely increased atherogenicity, insulin resistance, copper, and β-arrestin-1, and lowered calcium, whereas copper, β-arrestin-1, calcium, LacCer, and FBXW7 may modulate depression and anxiety symptoms by affecting T2DM.

Cellular aging has drawn the attention of researchers, scientists, and biotech businesses for the treatment of a number of medical conditions. Cellular aging is primarily defined by consistent cessation of proliferative development in response to internal and external stressors, including DNA damage, telomere shortening, mitochondrial dysfunction, and regulation of the senescence-associated secretory phenotype (SASP). Disturbances involving these factors may contribute to age-related disease development. Therefore, the current review aims to explore anti-aging factors targeting DNA damage response and SASP regulation and their detailed signaling networks. In addition, it provides an opportunity for researchers to identify not only anti-aging targets, but also anti-aging therapeutic strategies based on identified and non-identified targets.

Nigeria is the most populous country in the African continent. The aim of this study was to analyze risk factors for COVID-19 prevalence and deaths in all 6 geopolitical regions and 37 states in Nigeria. We analyzed the data retrieved from various sources, including Nigeria CDC, Nigeria National Bureau of Statistics, Unicef-Nigeria multiple indicator cluster survey and the Institute of Health Metrics and Evaluation, University of Washington. We examined 4 clinical risk factors (prevalence of TB, HIV, smoking and BCG vaccination coverage) and 5 sociodemographic factors (age ≥65, population density, literacy rate, unemployment and GDP per capita). Multivariate modeling was conducted using generalized linear model. Our analysis showed that the incidence of confirmed COVID-19 cases differed widely across the 37 states, from 0.09 per 100,000 in Kogi to 83.7 in Lagos. However, more than 70% of confirmed cases were concentrated in just 7 states: Lagos, Abuja, Oyo, Kano, Edo, Rivers and Delta. Case mortality rate (CMR) per million population also varied considerably, with Lagos, Abuja and Edo having CMR above 9. On bivariate analysis, higher CMR correlated positively with GDP and to a lesser extent with TB and population density. On multivariate analysis, which is more definitive, states with higher HIV prevalence and BCG coverage had lower CMR, while high GDP states had a greater CMR. This study indicates that COVID-19 has disproportionately affected certain states in Nigeria. Population susceptibility factors include higher economic development but not literacy or unemployment. Death rates were mildly lower in states with higher HIV prevalence and BCG vaccination coverage.

This study examined the effect of colleagues uncivil behavior on extra-role performance of teachers. The study further explored the mediating role of emotional exhaustion to intensify the effect. In parallel, moderation of psychological hardiness to absorb the negative shocks was also determined. For examining the direct, mediating, and moderating effects, primary data were collected through mailed questionnaires. To overcome the issues of common method biases, dyadic and time lagged approaches were used for collection of data. Responses were collected in three phases, with appropriate time intervals. Data of independent, mediating, and moderating variables were collected from teachers while of dependent variable form their immediate supervisors, i.e. HoDs. The study found a significant effect of colleagues’ discourteous behavior on extra-role performance of victims at job. Significant mediation of emotional exhaustion in the effect was also observed. In the meantime, hardiness of targets absolutely moderated the effect to minimize the associated consequences. Based on results, several policy implication and interventions were suggested.

Systemic amyloidosis is a multisystem illness characterized by fibrillary protein deposition, which causes dysfunction in the afflicted organ systems. Its diagnosis is frequently delayed since the disease's symptoms are unpredictable and non-specific. Its two main variants are light chain (AL) amyloidosis and transthyretin-related ATTR amyloidosis, which has both a sporadic (wildtype, ATTRwt) and hereditary (mutated, ATTRv) subtype. We discuss a case of Amyloidosis emerging in the kidneys and heart as a result of chronic inflammation caused by failure to treat TB, as well as its typical radiological characteristics, clinical presentation, imaging and instrumental evaluations, and therapeutic plan. This case report serves as a good reminder to medical personnel to ensure thorough patient follow-up in order to avoid extremely unusual and late complications resulting from treatment default.

(1) Background: Colon polyps are common protrusions in the colon’s lumen with potential risks of developing colorectal cancer. Early detection and intervention of these polyps are vital for reducing colorectal cancer incidence and mortality rates. This research aims to evaluate and compare the performance of three machine-learning image classification models’ performance in detecting and classifying colon polyps. (2) Methods: The performance of three machine learning image classification models, Google Teachable Machine (GTM), Roboflow3 (RF3), and You Only Look Once version 8 (YOLOV8), in the detection and classification of colon polyps were evaluated. The study used a dataset of colonoscopy images of normal colon, polyps, and resected polyps. The study assessed the models’ ability to correctly classify the images into their respective classes using precision, recall, and F1 score generated from confusion matrix analysis and performance graphs. (3) Results: All three models successfully distinguished between normal colon, polyps, and resected polyps in colonoscopy images. GTM achieved the highest accuracies: 0.99, with consistent precision, recall, and F1 scores of 1.00 for the `normal’ class, 0.97 - 1.00 for `polyps,’ and 0.97 - 1.00 for `resected polyps.’ While GTM exclusively classified images into these three categories, both YOLOV8 and RF3 extended their capabilities to detect normal colonic tissue, polyps, and resected polyps, with YOLOV8 and RF3 achieving overall accuracies of 0.84 and 0.87, respectively. (4) Conclusions: Machine learning, particularly models like GTM, shows promising results in ensuring comprehensive detection of polyps during colonoscopies.

Although automated Acute Lymphoblastic Leukemia (ALL) detection is essential, it is challenging due to the morphological correlation between malignant and normal cells. The traditional ALL classification strategy is arduous, time-consuming, often suffers inter-observer variations, and necessitates experienced pathologists. This article has automated the ALL detection task, employing deep Convolutional Neural Networks (CNNs). We explore the weighted ensemble of deep CNNs to recommend a better ALL cell classifier. The weights are estimated from ensemble candidates' corresponding metrics, such as accuracy, F1-score, AUC, and kappa values. Various data augmentations and pre-processing are incorporated for achieving a better generalization of the network. We train and evaluate the proposed model utilizing the publicly available C-NMC-2019 ALL dataset. Our proposed weighted ensemble model has outputted a weighted F1-score of 88.6%, a balanced accuracy of 86.2%, and an AUC of 0.941 in the preliminary test set. The qualitative results displaying the gradient class activation maps confirm that the introduced model has a concentrated learned region. In contrast, the ensemble candidate models, such as Xception, VGG-16, DenseNet-121, MobileNet, and InceptionResNet-V2, separately produce coarse and scatter learned areas for most example cases. Since the proposed ensemble yields a better result for the aimed task, it can experiment in other domains of medical diagnostic applications.

Hyperlipidemia is an identified risk factor for metabolic syndrome, obesity and cardiovascular complications characterized by elevated levels of lipids in blood. The present study aimed to inhibit HMG-CoA reductase with 15-oxoursolic acid through in-vivo and in-silico assessments. HFD-induced hyperlipidemia in rats was developed with a marked increase in total cholesterol (58.34 ± 0.21 mg/dl), triglycerides (45.45 ± 0.39 mg/dl), LDL-c (66.12 ± 0.10 mg/dl), VLDL-c (19.34 ± 0.16 mg/dl), and a decrease in HDL-c (10.34 ± 0.18 mg/dl). The oral administration of 15-oxoursolic acid at a concentration of 30 mg/Kg b.w significantly reduced the serum concentration of total cholesterol (42.65 ± 0.54 mg/dl), triglycerides (32.33 ± 0.16 mg/dl), LDL-c (50.34 ± 0.15 mg/dl) and VLDL-c (13.15 ± 0.45 mg/dl) respectively and an increased in the serum HDL-c (18.56 ± 0.34 mg/dl). 15-oxo ursolic acid also caused a decrease in the coronary risk index and atherogenic risk index. In-silico studies of 15-oxoursolic acid with HMG-CoA reductase showed significant interaction capability with binding energy (-9.26805 Kcal/mol). It is concluded that 15-oxoursolic acid could significantly reduce the total cholesterol, triglycerides and LDL levels in HFD-induced hyperlipidemia rats which might lead to new medication with significant hypolipidemic potential.

Neuro-rehabilitation services are essential in reducing post-stroke impairments, enhancing independence, and improving recovery in hospital and post-discharge. However these services are therapist-dependent and resource intensive. Patients’ disengagement and boredom in stroke units are common which adversely affect functional and psychological outcomes. Novel techniques such as use of iPads™ are increasingly researched to overcome such challenges. The aim of this review is to determine the feasibility, effectiveness, acceptability, and barriers to the use of iPads™ in stroke neuro-rehabilitation. Four databases and manual literature search were used to identify published studies using the terms “iPad”, “Stroke”, and “neuro-rehabilitation”. Studies were included in accordance with the review selection criteria. A total of 16 articles were included in the review. The majority of the studies focused on iPads use in speech and language therapy. Although of small scale, the studies highlighted that iPads are feasible, have the potential to improve rehabilitation outcomes, and can improve patient’s social isolation. Patients’ stroke severity and financial limitations are some of the barriers highlighted in this review. This review presents preliminary data supportive for the use of iPad technology in stroke neuro-rehabilitation. However, further research is needed to determine impact on rehabilitation goals acquisition, clinical efficacy, and cost-efficiency.

Lyme disease, the leading vector-borne ailment in the U.S., annually affects an estimated 476,000 individuals, predominantly in the Northeast and Upper Midwest. Despite its increasing incidence, the evaluation of risk within U.S. cities, including natural public lands, remains inadequate. This study focuses on blacklegged tick occurrences and Borrelia burgdorferi infection prevalence in 24 Staten Island parks, aiming to assess Lyme disease exposure risk. Monthly acarological risk index (ARI) calculations from 2019 to 2022 revealed elevated values (0.16-0.53) in specific parks, notably Wolfe’s Pond Park, High Rock Park, Clay Pit Pond Park, Clove Lake Park, and Fair View Park. June (0.36) and November (0.21) consistently exhibited heightened ARIs, aligning with peak tick collection months. Despite stable yearly infection rates at 28.97%, tick densities varied significantly between parks and years. Identifying a high transmission risk in specific parks in Staten Island, a highly urbanized part of New York City, emphasizes the continuous necessity for Lyme disease risk management, even within the greenspaces of large cities.

Background: The burden of resistant fungal infection is rising in patients with pulmonary disease. Options for antifungal therapy are limited, and the only orally-available antifungals, the triazoles, demonstrate inter and intra-patient variability, non-linear kinetics, toxicity, drug interactions and increasing antifungal resistance. Therapeutic drug monitoring (TDM) of itraconazole, voriconazole and posaconazole has been necessary to ensure their safety and efficacy, but is considered unnecessary for the newest triazole isavuconazole, use of which is increasing. Aims: To characterise isavuconazole susceptibility of Aspergillus fumigatus isolates in a tertiary respiratory referral centre to understand prevalence of isavuconazole antimicrobial resistance. To retrospectively review experience of isavuconazole use in this setting, assessing tolerability and therapeutic drug monitoring. Methods: A retrospective observational analysis of adult patients with respiratory disease in a tertiary hospital setting between Sept 2016 and Aug 2021. Clinical cultures were collected and triazole Minimum inhibitory concentration (MIC) were recorded (based on Clinical & Laboratory Standards Institute (CLSI method)). Isavuconazole trough drug levels were carried out as part of the standard of care. Clinical outcomes of treatment were evaluated, along with drug tolerance and TDM. Results: During the study period, isavuconazole susceptibility testing was performed on 26 Aspergillus spp isolates. 80.8% of Aspergillus fumigatus isolates were non-wild type and had isavuconazole MIC > 1mg/L, and 73.0% had MIC above the EUCAST (European Committee on Antimicrobial Susceptibility Testing) epidemiological cut-off (ECOFF) of 2mg/L. There was good correlation between isavuconazole MIC and voriconazole MIC (r =0.7, p=0.0002). 54 patients had isavuconazole therapy over the study period with a median duration of 7.7 months (IQR 0.79 - 16.42). 67% of patients were able to tolerate isavuconazole, despite toxicity with prior azole treatment being the primary indication for use (in 61.8%). Increased age (r=0.29; p=0.03 (95%CI 0.02,0.52)) and gender (r for female sex=-0.31; p=0.027 (95%CI -0.52,0.036) were associated risk factors for development of adverse events (AEs). 127 Isavuconazole TDM levels were performed over the study period with 90% >1mg/L and 72% >2mg/L. Dose change from manufacturer’s dose recommendation, however, was required in 15% of patients to achieve a serum drug concentration above the EUCAST ECOFF or Area of technical uncertainty (ATU) value of 2mg/L. Conclusion: In our study, we show use of Isavuconazole as salvage therapy in chronic pulmonary fungal disease setting with high prevalence of azole resistance. Isavuconazole MICs demonstrated good correlation with voriconazole MICs suggesting the latter could be a useful surrogate marker for isavuconazole susceptibility. Although Isavuconazole achieved excellent serum drug concentrations at standard dose compared to other azole drugs, we highlight the importance of antifungal stewardship and TDM monitoring to optimise therapy in this setting.

Mitochondrial Ca2+ ([Ca2+]M) uptake through Ca2+ uniporter (MCU) is central to many cell functions such as bioenergetics, spatiotemporal organization of Ca2+ signals, and apoptosis. MCU activity is regulated by several intrinsic proteins including MICU1, MICU2, and EMRE. While significant details about the role of MICU1, MICU2, and EMRE in MCU function have emerged recently, a key challenge for the future experiments is to investigate how these regulatory proteins modulate mitochondrial Ca2+ influx through MCU in intact cells under pathophysiological conditions. This is further complicated by the fact that several variables affecting MCU function change dynamically as cell functions. To overcome this void, we develop a data-driven model that closely replicates the behavior of MCU under a wide range of cytosolic Ca2+ ([Ca2+]C), [Ca2+]M, and mitochondrial membrane potential values in WT, MICU1 knockout (KO), and MICU2 KO cells at the single mitochondrion and whole-cell levels. The model is extended to investigate how MICU1 or MICU2 KO affect mitochondrial function. Moreover, we show how Ca2+ buffering proteins, the separation between mitochondrion and Ca2+-releasing stores, and the duration of Ca2+-releasing channels affect mitochondrial function under different conditions. Finally, we demonstrate an easy extension of the model to single channel function of MCU.

Background: Currently, limited number of therapeutic options are available to treat Diabetes mellitus, and to find a potential candidate, laboratory work takes time and also needs animal studies. So, the aim of this study was to determine the efficacy of some natural phytocompounds with the aid of molecular docking, bioinformatics and in silico drug design approaches. Method: Two proteins (Human CYP3A4 linked to metformin and Human dipeptidyl peptidase-IV) were selected and molecular docking studies were conducted using Pymol, AutoDock Vina, PyRx, and Discovery Studio. Different important pharmacokinetic parameters like ADME and toxicity data were obtained from online databases SwissADME and pkCSM program. Results: It was found that human dipeptidyl peptidase-IV (PDB ID: 4A5S) has exhibited a maximal affinity of -9.7 Kcal/mol for bryonolic acid and hesperidin, but only -6.7 kcal/mol for metformin hydrochloride. Similarly, the highest affinity of hesperidin for human CYP3A4 bound to metformin (PDB ID: 5G5J) is -10.7 Kcal/mol compared to metformin hydrochlor (-6.3 Kcal/mol). Besides, all the compounds have been documented outstanding ADMET profile, and accepted by drug-likeness or Lipinski rule. Conclusions: The present study suggested that these compounds can be further investigated in vitro and in vivo to establish them as lead compounds against Diabetes mellitus..

Pakistan relies mostly on fossil fuel for fulfilling its energy demand which is expensive as 11 well as not friendly for the environment. The need of the hour is to shift from fossil fuels to renew-12 able energy resources like geothermal, wind, solar etc. to cater for global warming issues. Pakistan 13 has a lot of potential geothermal sites because of several fault lines and hot springs. A sound 14 knowledge of ground temperature is essential to use geothermal energy, which is obtained by drill-15 ing boreholes and putting sensors making it an expensive procedure. Thus, to avoid huge cost for 16 drilling bore holes, particularly for ground temperature analysis, a numerical approach has been 17 considered for determining ground temperature. Furthermore, correlation charts between air and 18 ground temperatures have been developed as there were no proper studies on the ground temper-19 ature of Pakistan. Then, with the help of a boreholes drilled in National University of Sciences and 20 Technology Islamabad Pakistan, the actual ground and numerically calculated temperatures have 21 been compared which shows an error margin in the range between 0.27% for higher depths to 7.3% 22 near surface. Thus, it is shown that the proposed method is easy to implement and better than large 23 scale testing methods for the depths at which geothermal energy is extracted.

Transposable elements (TEs) ubiquitously exist in the human genome, and some have the ability to copy and paste themselves to other locations, resulting in new insertions. Organisms have evolved with mechanisms and machineries to repress such activity. TEs are also co-opted for beneficial functions by the host and are thus maintained in the genome. During the lifetime of humans, aberrant TE activity might cause or contribute towards diseases including neurological conditions such as Alzheimers Disease (AD) and cancer. While inflammatory pathways linked to TEs may be a part of the disease pathology, on the other hand altered TE activity involving inflammatory pathways could be recognised by disease suppression mechanisms. For this reason, TEs could be targeted for therapeutic applications aiming to prevent TE activity or reduce initial inflammatory pathways as well as to activate disease suppression mechanisms. In this review, we describe the contributory and potential preventative roles of TEs in neurological conditions and cancer from a molecular and evolutionary perspective. Evolutionary paradigms both at the unicellular and organismal level aid understanding the role of TEs in disease. These observations could pave the way for the development of novel therapeutic approaches targeting TEs.

As the world endures the coronavirus disease 2019 (COVID-19) pandemic, conditions of 35 million vulnerable individuals struggling with substance use disorders (SUDs) worldwide have not received sufficient attention for their special health and medical needs. Many of these individuals are complicated by underlying health conditions, such as cardiovascular and lung diseases and undermined immune systems. During the pandemic, access to the healthcare systems and support groups is greatly diminished. Current research on COVID-19 has not addressed the unique challenges facing individuals with SUDs, including the heightened vulnerability and susceptibility to the disease. In this systematic review, we will discuss the pathogenesis and pathology of COVID-19, and highlight potential risk factors and complications to these individuals. We will also provide insights and considerations for COVID-19 treatment and prevention in patients with SUDs.

The software industry has adopted component-based software development (CBSD) to rapidly build and deploy large and complex software systems with significant savings at minimal engineering effort, cost, and time. However, CBSD encounters issues on security trust, mainly with respect to dependability attributes. A system is considered dependable when it can produce the outputs for which it was designed with no adverse effect on its intended environment. Dependability consists of several attributes that imply availability, confidentiality, integrity, reliability, safety, and maintainability. Dependability attributes must be embedded in a CBSD model to develop dependable component software. Motivated by the importance of these attributes, this paper pursues two objectives: to design a model for developing a dependable system that mitigates the vulnerabilities of software components, and to evaluate the proposed model. The model proposed in this study is labelled as developing dependable component-based software (2DCBS). To develop this model, the CBSD architectural phases and processes must be framed and the six dependability attributes embedded according to the best practice method. The expert opinion approach was applied to evaluate 2DCBS framing. In addition, the 2DCBS model was applied to the development of an information communication technology (ICT) portal through an empirical study method. Vulnerability assessment tools (VATs) were employed to verify the dependability attributes of the developed ICT portal. Results show that the 2DCBS model can be adopted to develop web application systems and to mitigate the vulnerabilities of the developed systems. This study contributes to CBSD and facilitates the specification and evaluation of dependability attributes throughout model development. Furthermore, the reliability of the dependable model can increase confidence in the use of CBSD for industries.

The use of Supplementary Cementitious Material (SCM) is widely used in production of sustainable concrete. Blended cements, incorporating SCM such as Pulverized Fly Ash (PFA) and Ground Granulated Blast Furnace Slag (GGBFS) have been widely used to reduce the cement contents and avoid adverse environmental impacts of CO2 produced during cement manufacturing. The analysis of various structural properties of concrete such as compressive strength, flexural strength and modulus of elasticity is important for its structural application. In this research, flexural strength of 100mmx100mmx500mm beams made from blended cement were tested under three curing conditions i.e. winter, summer and under water and the flexural strength was calculated using EN-12390-5 at the ages of 28 days and 56 days. For modulus of elasticity, concrete cylinders 150mmx300mm were tested as per procedure described in BS 1881-121(1983) at the age of 28 days. The compressive strength, flexural strength and modulus of elasticity for blended cement incorporating PFA and GGBFS has been increased under summer curing environment. The experimental values of Modulus of Elasticity are compared with the provision of BS 1881.

Crosstalk between the BMP and TGF-β signaling pathways regulates many complex developmental processes from the earliest stages of embryogenesis throughout adult life. In many situations, the two signaling pathways act reciprocally. For example, TGF-β signaling is generally pro-fibrotic whereas BMP signaling is anti-fibrotic and pro-calcific. Sex-specific differences occur in many diseases including cardiovascular pathologies. Differing ratios of fibrosis and calcification in stenotic valves suggests that BMP/TGF-β signaling may vary in men and women. In this review, we focus on the current understanding of the interplay between sex and BMP/TGF-β signaling and pose several unanswered questions.

Background: Thyroid nodules are common, affecting nearly 65% of the general population. While they are widespread, it's crucial to recognize that the majority of these nodules are not cancerous and can be effectively managed through careful monitoring. Thyroid ultrasound is commonly used to evaluate thyroid nodules owing to its low cost, wide availability and technical ease of application. In sonography, it's crucial to assess characteristics and vascular flow. Yet, conventional color and power Doppler ultrasound may not always effectively capture small vessels and low velocities due to their limitations. Superior Microvascular Imaging can display the blood flow of small vessels and low-velocity blood flow, which is difficult to visualize with conventional Doppler ultrasound. Meanwhile other thyroid scans, that utilize either [99mTc] pertechnetate or (18)F-fluorodeoxyglucose, can categorize nodules as hyperactive ('hot'), exhibiting normal activity ('warm'), or having reduced/no activity ('cold'). Thus, the main goal of screening and tracking thyroid nodules is to improve the management of potentially worrisome thyroid malignancies. Methodology: The study was conducted within the structural framework of a network meta-analysis, with the index tests being - SMI, Radionuclide Scanning and Color Doppler, and the general link between them being the reference gold standard. The data collection involved searching for all pertinent literature using PubMed, Google Scholar, and the Cochrane Library databases. The essential data was extracted following the application of specific inclusion and exclusion criteria.This meta-analysis included 7 RCTs with 1,152 patients for Radionuclide Scanning, 10 RCTs with 1,847 patients for SMI and 8 RCTs with 4,480 patients for Color Doppler. They were analyzed using the QualSyst tool and the risk of bias was evaluated by using QUADAS-2 analysis.The statistical software packages MetaDiSc 1.4, RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20) and Excel in Stata 14 were used to perform the statistical analyses. Result: According to the findings, the sensitivity for Radionuclide Scanning is calculated as 0.79 (range: 0.76 to 0.81) and specificity as 0.55 (range: 0.50 to 0.60) with a 95% confidence interval. The overall diagnostic odds ratio (DOR) for Radionuclide Scanning Is 10.54.Additionally, with a 95% confidence interval, SMI exhibits a sensitivity of 0.82 (with a range of 0.79 to 0.84) and a specificity of 0.86 (with a range of 0.84 to 0.88), while the overall DOR is approximately 25.73. Color Doppler demonstrates a calculated sensitivity of 0.71 (ranging from 0.69 to 0.74) and specificity of 0.81 (ranging from 0.79 to 0.83) with a 95% confidence interval, while its DOR is 13.48.Conclusion: As evidenced by this meta-analysis, blood flow dependent imaging techniques are superior in their abilities to be used as diagnostic tests, especially in conjunction with their use in detecting thyroid nodules. This study offers a starting point for delving deeper into the utilization of Radionuclide Imaging, Superior Microvascular Imaging and Color Doppler in diagnosing thyroid nodules in a clinical setting. Key Words: - Thyroid Nodule, Radionuclide Scanning, Superior Microvascular Imaging, Color Doppler Diagnosis, Sensitivity, Specificity, Diagnostic imaging

Herbal Coffee is getting more popular due to its unique flavor and higher concentration of bioactive compounds, mainly polyphenols. Rosemary is a unique herb with potent antioxidant properties. A green technique called ultrasound aids in releasing bioactive substances from the plant cell wall. In this context, ultrasound-assisted herbal coffee prepared and their anti-diabetic, anti-Alzheimer, and antioxidant activities were measured while the LC/MS was used to determine the bioactive components from the herbal coffee infusion. A total of 95 secondary metabolites were putatively reported, including alkaloids, phenolic acids, and flavonoids, which we identified in the herbal coffee infusion. The total phenolic content (61.5 ± 5.1 mg GAE/g), total flavonoid content (19.3 ± 0.9 mg QE/g), and total condensed tannin (7.6 ± 0.7 mg CE/g) of herbal coffee infusion were observed to be highest of the two remaining samples. The herbal coffee extracts were used to determine all samples' antioxidant, anti-diabetic, and anti-Alzheimer activities. Using LC-MS/MS, we semi-quantified 19 phenolic metabolites. The results show numerous bioactive components in herbal coffee infusion with more potent antioxidant, antidiabetic, and anti-Alzheimer potential. Moreover, more studies must be conducted to confirm how the metabolomic profile of herbal coffee affects its flavor profile.

One of the challenges in Content-Based Image Retrieval (CBIR) is to reduce the semantic gaps between low-level features and high-level semantic concepts. In CBIR, the images are represented in the feature space and the performance of CBIR depends on the type of selected feature representation. Late fusion also known as visual words integration is applied to enhance the performance of image retrieval. The recent advances in image retrieval diverted the focus of research towards the use of binary descriptors as they are reported computationally efficient. In this paper, we aim to investigate the late fusion of Fast Retina Keypoint (FREAK) and Scale Invariant Feature Transform (SIFT). The late fusion of binary and local descriptor is selected because among binary descriptors, FREAK has shown good results in classification-based problems while SIFT is robust to translation, scaling, rotation and small distortions. The late fusion of FREAK and SIFT integrates the performance of both feature descriptors for an effective image retrieval. Experimental results and comparisons show that the proposed late fusion enhances the performances of image retrieval.

The paper portrays predictive models for dissolved oxygen (DO) levels in an urban lake using common water quality parameters like Temperature, pH, Conductivity and ORP at a time. Data were sampled using three real-time, industry-standard sensors, OPTOD, CTZN, and PHEHT, and then interpolated using the ArcGIS kriging technique. Correlation studies were analyzed through the ML algorithm, the correlation study signified a highly positive correlation between DO and other water parameters and the model was corroborated by R-score in order to create the linear regression model. In addition, an artificial neural network- a machine learning method using the Levenberg-Marquardt algorithm was developed to build a model to predict the do as well. Then, the performance of the models was validated and also the R² accuracy was checked of the predicted data against the actual data. Thus, the appropriateness of the ANN model for the forecasting of investigated attributes is indicated by the fact that the discrepancy between the forecasted and real ANN model is significantly lesser than that of the regression model. However, the model can be used to reveal DO data from unknown urban lake water.

A significant attention has been made to the accurate detection of diabetes which is a big challenge for the research community to develop a diagnosis system to detect diabetes in a successful way in the IoT e-healthcare environment. Internet of Things (IOT) has emerging role in healthcare services which delivers a system to analyze the medical data for diagnosis of diseases applied data mining methods. The existing diagnosis systems have some drawbacks, such as high computation time, and low prediction accuracy. To handle these issues, we have proposed a IOT based diagnosis system using machine learning methods, such as preprocessing of data, feature selection, and classification for the detection of diabetes disease in e- healthcare environment. Model validation and performance evaluation metrics have been used to check the validity of the proposed system. We have proposed a filter method based on the Decision Tree (Iterative Dichotomiser 3) algorithm for highly important feature selection. Two ensemble learning Decision Tree algorithms, such as Ada Boost and Random Forest are also used for feature selection and compared the classifier performance with wrapper based feature selection algorithms also. Machine learning classifier Decision Tree has been used for the classification of healthy and diabetic subjects. The experimental results show that the Decision Tree algorithm based on selected features improves the classification performance of the predictive model and achieved optimal accuracy. Additionally, the proposed system performance is high as compared to the previous state-of-the-art methods. High performance of the proposed method is due to the different combinations of selected features set and GL, DPF, and BMI are more significantly important features in the dataset for prediction of diabetes disease. Furthermore, the experimental results statistical analysis demonstrated that the proposed method would be effectively detected diabetes disease and can easily be deployed in IOT wireless sensor technologies based e-healthcare environment.

This report elucidates a case of papillary carcinoma of the Thyroglossal Duct Cyst in a 19-year-old female. The swelling at presentation was suprahyoid, fixed and non-mobile with deglutition or tongue protrusion. Papillary carcinoma was diagnosed post-op through histopathological examination and a follow-up total thyroidectomy was planned. As the origin of TGDC papillary carcinoma is highly debated, no evidence-based guidelines yet exist as to the best line of treatment, however, Sistrunk’s procedure followed by total/near total thyroidectomy is widely considered the standard management practice in such cases.

This study investigates the pivotal areas where Artificial Intelligence (AI) integration in healthcare warrants further exploration, leveraging insights from Boston Specialists, a forefront healthcare provider in AI adoption. Employing a qualitative case study approach, enriched by in-depth interviews and comprehensive literature reviews, we identify three main domains for potential AI expansion: scheduling efficiency, clinical documentation, and AI-driven medical research. Our results underscore the substantial enhancements AI brings to operational workflows and patient care, notably through improved scheduling systems, accuracy in medical documentation, and the facilitation of data-driven research methodologies. These findings suggest a critical need for healthcare institutions to further invest in AI technologies, focusing on these key areas to harness AI's full potential in personalizing care, optimizing efficiency, and advancing medical knowledge. The study concludes with a call for continued investigation into AI's integration within healthcare settings, emphasizing the importance of a supportive organizational infrastructure, ethical considerations, and data security in realizing AI's transformative impact on healthcare delivery and patient outcomes.

This paper explores the capability of various machine learning algorithms, including Random Forests and advanced gradient boosting techniques such as XGBoost, LightGBM, and CatBoost, to predict customer churn in the telecommunications sector. For this analysis, a dataset available to the public was employed. The performance of these algorithms was assessed using recognized metrics, including Accuracy, Precision, Recall, F1-score, and the Receiver Operating Characteristic Area Under Curve (ROC AUC). These metrics were evaluated at different phases: subsequent to data preprocessing and feature selection; following the application of SMOTE and ADASYN sampling methods; and after conducting hyperparameter tuning on the data that had been adjusted by SMOTE and ADASYN. The outcomes underscore the notable efficiency of upsampling techniques such as SMOTE and ADASYN in addressing the imbalance inherent in customer churn prediction. Notably, the application of random grid search for hyperparameter optimization did not significantly alter the results, which remained comparatively unchanged. The algorithms' performance post- ADASYN application marginally surpassed that observed after SMOTE application. Remarkably, LightGBM achieved an exceptional F1-score of 89% and an ROC AUC of 95% subsequent to the ADASYN sampling technique. This underlines the effectiveness of advanced boosting algorithms and upsampling methods like SMOTE and ADASYN in navigating the complexities of imbalanced datasets and intricate feature interdependencies.

Optimizing the nitrogen (N) timings and rate can improve nutrient uptake, and nutrient-efficiencies, especially of N in wheat under the changing climate scenario. Climatic stress in the form of high temperature and drought resulted in the decreased crop physiology and, ultimately, grain yield. Taking the example of rainfed wheat, we quantified the impact of N application rates as full and split-dose at three variable sites of rainfed Pothwar, Pakistan by conducting field experiments for two years (2013-14 and 201-15). Treatments include, T₁ = Control (No fertilizer applied), full dose of N applied at the time of crop sowing, i.e. T₂ = 50 kg N ha^-1, T₃ = 100 kg N ha^-1 and T₄ = 150 kg N ha^-1 and split application of N at different timings during different stages of the crop called as split application of N, i.e. T₅: Application of 50 kg N ha^-1 (15 kg N ha^-1 (Sowing) : 20 kg N ha^-1 (Tillering) :15 kg N ha^-1 (Anthesis), T₆: Application of 100 kg N ha^-1 (30 kg N ha^-1 (Sowing): 40 kg N ha^-1 (Tillering) : 30 kg N ha^-1 (Anthesis) and T₇: Application of 150 kg N ha^-1(45 kg N ha^-1 (Sowing) : 60 kg N ha^-1 (Tillering) : 45 kg N ha^-1 (Anthesis). Three study sites include viz. Islamabad (High rainfall with optimum temperature), University Research Farm (URF)-Koont (Medium rainfall with moderate temperature), and Talagang (low rainfall with high temperature). Results showed that the highest stomatal conductance (0.80 mole m^-2 sec^-1), net photosynthetic rate (20.07 μmole m^-2s^-1), transpiration rate (9.58 mmole m^-2s^-1), intercellular CO₂ concentration (329.25 μmole CO₂ mol^-1 air), SPAD values (58.86 %) and proline contents (35.42 μg g^-1) were obtained for split application of N (T₆ = Split N₁₀₀) compared to control and full dose of N treatments. Among sites, these physiological traits remained highest at Islamabad and lowest at Talagang, while among years, maximum values of the measured parameters were obtained in 2013-14. A similar trend was observed for crop total N, N efficiencies, and agronomic traits of the crop. Our results suggest that optimum N application rate and its suitable timings can help to harvest real benefits of N as in our findings, split dose resulted in the maximum performance of the crop from physiological parameters to the agronomic traits of the rainfed wheat crop.

Scientists observe, discover, justify and eventually share their findings with the scientific community. Dissemination is an integral aspect of scientific discovery since discoveries which go unnoticed have no or little impact on science. Today, peer-review is part of this process of scientific dissemination as it contributes proactively to the quality of a scientific article. As the numbers of scientific journals and scientific articles published therein are increasing steady, processes such as the single-blind or double-blind peer review are facing a near collapse situation. In fact, these traditional forms of reviewing have reached their limits and, because of this, are also increasingly considered as unfair, sloppy, superficial and even biased. In this manuscript we propose forms of Post Publication Public Peer Review (P4R) as valuable alternatives to the traditional blind peer review system. We describe how the journal Sci has explored such an approach and provide first empirical evidence of the benefits and also challenges such a P4R approach is facing.

This study was performed to evaluate the efficacy of nicotinic acid against Streptococcus pneumoniae biofilm. The experimental results indicate that S. pneumoniae forms biofilms, particularly at the liquid-air interface, as evidenced by the pellicle assay. Nicotinic acid demonstrated significant inhibition of S. pneumoniae biofilm formation at 6 h and 18 h, with higher concentrations leading to lower biofilm biomass, suggesting a concentration-dependent response. However, minimal biofilm inhibition was observed at 12 h. Treatment with nicotinic acid induced FTIR spectral changes in protein biomolecules of S. pneumoniae biofilm at 6 h and 18 h, evidenced by alterations in spectral peaks at 750 cm-1, 906 cm-1, 1540 cm-1, 1548 cm-1, and 1644 cm-1. Notably, no FTIR spectral changes were detected in 12 h S. pneumoniae biofilm following exposure to nicotinic acid. These findings suggest that nicotinic acid inhibits biofilm formation in a time and concentration-dependent manner, possibly by altering the structure of protein biomolecules within the biofilm.

In this study, an alternative method to conventional production methods involving thin section copper permanent mould casting (rapid solidification), hot rolling and heat treatment processes to manufacture AISI DC 53 cold work tool steel, has been investigated. In this new method, solidification of the AISI DC 53 was done in the thin section copper mould instead of traditional ingot casting. After solidification, thin slabs obtained was homogenized to 1150 ^oC and hold at this temperature for one hour and then hot rolling was be applied. During hot rolling process, about % 30 reduction in thickness of slab was obtained. After hot rolling, heat treatment (austenitizing, quenching and tempering) have been applied to thin slab. The samples have been taken as cast, as rolled and as heat treated (austenitized and tempered) and the microstructural analysis, hardness tests, retained austenite quantity measurement by XRD method have been performed. The heat treatment and tests have been performed for a commercially available AISI DC 53 which is manufactured by thick section ingot casting and rolling. Hardness values of the AISI DC 53 steels produced by traditional route is in the range of 52-54 HRC after austenitization at 1025 ^oC for one hour and quenched in compressed air and tempered twice at 525 ^oC for 120 mins. On contrary the permanent mould cast AISI DC 53 after homogenization at 1150 ^oC and immediately hot rolling then air cooling and austenitized at 1025 ^oC for one hour then quenched by compressed air and tempered twice at 525 ^oC for 120 mins have hardness valeus in the range of 55-57 HRC. Experiments have revealed that the properties of new rapid solidified steel in permanent copper mould are better than the commercially available steel and have a more refined microstructure than commercially produces alternative. Therefore, the new proposed method can be used as an alternative manufacturing method for cold-work tool steels.

Heat stress affects the yield of medicinal plants and can reduce biomass and/or metabolite production. In order to evaluate the effect of heat-induced stress on the essential oil production in Mentha x piperita L. var. Mitcham (Mitcham mint) and Mentha x arvensis var. piperascens Malinv. ex L. H. Bailey (Japanese mint), we studied the chemical composition of the oils of the two mint species under different heat shock stress in growth chambers. The antibacterial activity of the essential oils was also evaluated; microscopic observation (fluorescence and electron transmission) was used to assess the effect of the tested samples on bacterial growth. The results obtained shed light on the mint essential oils composition and biological activity in relation to heat stress.

Majority of published articles have talked about the challenges faced by students in learning online however, little has been talked about what the teachers have gone through especially during these times of the pandemic. This paper discusses the factors university teachers face when teaching online. These factors include accessibility to the internet, level of interaction between teachers and students, costs incurred, availability of training and academic policies kept in place to enhance effectiveness of teaching online. These are further divided into personal, social and economic factors where the teachers’ age, gender, remuneration, availability of resources, location and the economic status of the country is discussed in relation to the effectiveness of online learning. Upon carrying out a literature review on articles written on the effectiveness of online learning with the main focus being teachers, it was noted that the main factors affecting the effectiveness of online learning was the availability of internet connection and training provided to teachers. In Kenya, majority of the rural areas lack access to the internet and devices to learn online which makes it difficult for a teacher to teach effectively given the pandemic constraints. This study sheds light on the need for institutions and governments to take input from their teachers and train them on how to make online learning more effective. It also shows the status of universities in Kenya which had to shift to learning online due to the pandemic. Majority of them took time to adapt to this new change due to the discussed factors. Therefore it is recommended that the Government should train teachers and address the issue of lack of internet and electricity in Kenya.

The occurrence and ability of Salmonella typhimurium to withstand the effects of various antibiotics has been extensively recorded. This highlights the necessity for alternative methods to combat Salmonella infections. The current investigation aimed to ascertain the impact of benzoic acid on the extent of surface coverage and biomass of S. typhimurium biofilm after 48 and 72 hours. The findings indicated that all the different doses of benzoic acid (ranging from 3.125% to 50%) resulted in a decrease in the extent of biofilm surface coverage. Benzoic acid exhibited a substantial inhibitory effect on the biofilm biomass at all concentrations. Higher concentrations of benzoic acid led to a decrease in biofilm biomass, suggesting a concentration-dependent response. This finding implies that benzoic acid is effective in managing Salmonella infections.

Background: Appendicitis is a common cause of emergency department visits and appendectomies in the US, with 250,000 appendectomies performed annually. Current diagnostic methods, such as clinical findings, lead to inaccuracies and missed diagnoses, increasing morbidity and mortality. The only solution is surgery, but current hematological tests are not reliable and may lead to unnecessary surgery if the underlying etiology is self-limiting or requires medical treatment. This study explores the role of MRI as a diagnostic modality that can replace US/CT and supplement traditional clinical diagnostic signs while avoiding ionizing radiation and intravenous contrast medium. The purpose of this meta-analysis is to determine the accuracy of MRI as a diagnostic modality in diagnosing appendicitis, addressing concerns about diagnostic modalities and their adverse effects, and addressing the necessity and success of relevant interventions. Methods: Medical literature was comprehensively searched and reviewed without restrictions to particular study designs, or publication dates using PubMed, Cochrane Library, and Google Scholar databases for all relevant literature formulated in English. The extraction of necessary data proceeded after specific inclusion and exclusion criteria were applied. Meta Analysis was performed for 5206 patients, with 35 RCTs being selected. Analysis was done using the QualSyst tool, wherein two writers independently assessed the caliber of each study as well as the use of the Cochrane tool for bias risk apprehension. The statistical software packages RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20), and Excel in Stata 14 were used to perform the statistical analyses along with other analytical software. Results: MRI had an overall sensitivity of over 95%, an overall specificity of 94.2% with a PPV of 0.875 in comparison to CT scan in the diagnosis and intervention regarding appendicitis. Conclusion: These findings strongly suggest that MRI is a reasonable alternative to CT for the diagnosis of appendicitis in hospitals with appropriate access to this technology for reasons about accuracy, reliability, and reproducibility as well as addressing safety concerns.

Arrhythmia is a cardiac condition characterized by an irregular heart rhythm that hinders the proper circulation of blood, posing a severe risk to individuals’ lives. Globally, arrhythmias are recognized as a significant health concern, accounting for nearly 12 percent of all deaths. As a result, there has been a growing focus on utilizing artificial intelligence for the detection and classification of abnormal heartbeats. In recent years, self-operated heartbeat detection research has gained popularity due to its cost-effectiveness and potential for expediting therapy for individuals at risk of arrhythmias. However, building an efficient automatic heartbeat monitoring approach for arrhythmia identification and classification comes with several significant challenges. These challenges include addressing issues related to data quality, determining the range for heart rate segmentation, managing data imbalance difficulties, handling intra- and inter-patient variations, distinguishing supraventricular irregular heartbeats from regular heartbeats, and ensuring model interpretability. In this study, we propose the Reseek-Arrhythmia model, which leverages deep learning techniques to automatically detect and classify heart arrhythmia diseases. The model combines different convolutional blocks and identity blocks, along with essential components such as convolution layers, batch normalization layers, and activation layers. To train and evaluate the model, we utilized the MIT-BIH and PTB datasets. Remarkably, the proposed model achieves outstanding performance with an accuracy of 99.35% and 93.50% and an acceptable loss of 0.688 and 0.2564, respectively.

In this study, we introduce the dynamics of a Hepatitis B virus (HBV) model with the class of asymptomatic carriers and conduct a comprehensive analysis to explore its theoretical aspects and examine the crossover effect within the HBV model. To investigate the crossover behavior of the operators, we divide the study interval into two subintervals. In the first interval, the classical derivative is employed to study the qualitative properties of the proposed system, while in the second interval, we utilize the ABC fractional differential operator. Consequently, the study is initiated using the piecewise Atangana-Baleanu derivative framework for the systems. The HBV model is then analyzed to determine the existence, Hyers-Ulam (HU) stability, and disease-free equilibrium point of the model. Moreover, we showcase the application of an Adams-type predictor-corrector (PC) technique for Atangana-Baleanu derivatives and an extended Adams-Bashforth-Moulton (ABM) method for Caputo derivatives through numerical results. Subsequently, we employ computational methods to numerically solve the models and visually present the obtained outcomes using different fractional-order values. This network is designed to provide more precise information for disease modeling, considering that communities often interact with one another, and the rate of disease spread is influenced by this factor.

Introduction: Biliary Atresia (BA) is a common cause of neonatal cholestatic jaundice which, if recognized and treated early, can be life-saving for the infant. If the liver biopsy suggests the presence of BA, exploratory laparotomy is then carried out to confirm the diagnosis, along with the Kasai procedure to provide drainage to the bile secreted by the liver. The purpose of this study is to get a deep dive into all the various imaging modalities that can diagnose BA more effectively and with absolute certitude, thus helping prevent several children from a grave prognosis.Methodology: For the collection of the data, a search was done by two individuals using PubMed, Google Scholar, and Cochrane Library databases for all relevant literature. Each qualifying paper was evaluated independently by two reviewers. Each article was analyzed for the number of patients, their age, procedure modality, complexity of ethology, and incidence of the pre-decided complications. The statistical software packages RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20), Google Sheets, and Excel in Stata 14 were used to perform the statistical analyses. The data was obtained and entered into analytic software.Results: A total of 39 studies with 3,679 subjects were selected for the study, out of which 7 studies showed sensitivity above or equal to 95%, and an astounding 14 studies showed specificity above 95%. The value of True Positive (TP) was 1280, that of True Negative (TN) was 1817, that of False Positive (FP) was 239, and that of False Negative (FN) was 343. With a confidence interval of 95%, sensitivity, specificity, and positive predictive values were calculated. The sensitivity of Ultrasonography for Biliary Atresia is 0.79, with a CI of 95% in a range of 0.77 to 0.81. The specificity of Ultrasonography for Biliary Atresia is 0.88, with a CI of 95% in a range of 0.87 to 0.90. Conclusion: Even though several radiological techniques at present help to detect BA, USG of the abdomen proves to be an effective diagnostic and a modest screening test for the detection of BA.

Persistent Organic Pollutants (POP) such as dichlorodimethyltrichloroethane (DDT) are present and ubiquitous in the environment due to their resilient nature. DDT is a prevalent endocrine disruptor still found in detectable amounts in organisms and the environment even after its use was banned in the 1970s. Studies show that exposure to DDT can cause adverse health effects in humans and animals, impairing fertility and increasing the risk of developing cancer. The aim of this work is to provide a comprehensive overview of the available literature on the effect of DDT and its metabolites on female reproductive tract, leading to infertility and cancer. Medline and Google Scholar were systematically searched to detect all relevant animal and human studies published in the last 20 years (January 2003 to February 2023) in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. In total, 38 studies were included for qualitative synthesis. This systematic search and review indicated that exposure to DDT is associated with female reproductive health decline and that DDT acts as a sufficient carcinogen instigating reproductive cancers.

Carrageenan (car-), used in the pharmaceutical as well as food industry, is marine sulfated polysaccharides. The carrageenan blends (CB) of kappa (κ-), iota (ι-), and lambda (λ-) of 50/50 weight by weight are multipurpose and biocompatible hydrophilic polymers. They were subjected to adsorption of copper (Cu2+) ions. The aim of the study was to conduct extensive rheological and mechanical studies rendering them suitable for biological purposes. The rheology was conducted at various temperatures using a frequency curve, frequency sweep, loss modulus, and storage modulus analysis. Models of rheology like Ostwald, Bingham, and Modified Bingham models were utilized. The rheological results demonstrated non-Newtonian/pseudo-plastic behavior at various temperatures. The models of rheology demonstrated good flow properties and rheological performance of these materials. These materials could be exploited for their application in pharmaceuticals, food, and cosmetics. Thus, our study reflects that these CB can be safely exploited in the healthcare, pharmaceutical, and food industry. However, further studies should be conducted to evaluate their effectiveness in clinical studies.

An increase in the use of smartphones has laid to the use of the internet and social media platforms. The most commonly used social media platforms are Twitter, Facebook, WhatsApp and Instagram. People are sharing their personal experiences, reviews, feedbacks on the web. The information which is available on the web is unstructured and enormous. Hence, there is a huge scope of research on understanding the sentiment of the data available on the web. Sentiment Analysis (SA) can be carried out on the reviews, feedbacks, discussions available on the web. There has been extensive research carried out on SA in the English language, but data on the web also contains different other languages which should be analyzed. This paper aims to analyze, review and discuss the approaches, algorithms, challenges faced by the researchers while carrying out the SA on Indigenous languages.

The aim of this work is to analyze and investigate the shape preserving properties of ternary 4-point non-stationary interpolating subdivision schemes constructed by Beccari et al. [1] with a tension parameter !k+1 which can reproducing exponential. Moreover, the conditions on the initial control points are developed that allow user to generate shape preserving limit curves after a nite number of subdivision steps and generalize these results in limiting case. Signicance of derived conditions are illustrated through graphs and the whole discussion is followed by examples.

ntroduction: Respiratory tract Infections are the greatest cause of death worldwide. Since its outbreak in 2019, the coronavirus pandemic (COVID-19) has been a challenge to humans in terms of treatment and prevention of this respiratory viral infection. The re-emergence of respiratory viral infections like influenza, pose a serious hazard to global public health because they occur seasonally. Creating broad-spectrum antiviral compounds for rapid action in the case of an outbreak crisis, as well as bioweapon defences, is critical. Human galectin-3 is found in high concentrations in activated T lymphocytes, epithelial and endothelial cells, and fibroblasts. ProLectin -I and ProLectin -M are both galectin antagonists. Blocking viral entry with a complex polysaccharide component "ProLectin-M" has downstream effects on viral reproduction enabling it to be used as a therapeutic tool and a safe alternative to conventional anti-viral medicines. Methods: In total, 3 cell based assays have been conducted to evaluate antiviral efficacy of ProLectin–I and ProLectin-M against SARS-CoV-2 virus, Influenza-A (H1N1), and human respiratory syncytial virus (hRSV) strain A2. ProLectin-M and ProLectin-I were evaluated for their anti-viral potency using SARS-CoV2 virus strain by viral RNA Extraction and qRT-PCR assays. The plaque assays were carried out to determine the antiviral activity of the test products (ProLectin-I and ProLectin-M) against ‘Influenza-A (H1N1)-A/PR/8/34 (TC adapted)’ and ‘Human respiratory syncytial virus (hRSV) strain A2’ in a cell based in vitro setting. As eference standard, "Oseltamivir Phosphate" and "Remdesivir" were used to determine antiviral activity of test products against H1N1 and hRSV strains respectively.Results: The IC_{50 of} ProLectin-M and ProLectin-I against SARS-CoV-2 virus was found to be 6248 ng/ml (6.2µg/ml) and 4207 ng/ml (4.2μg/ml) respectively. The CC₅₀ value was similar in both the test products i.e. >100 µg/ml. Against Influenza A (H1N1) strain, ProLectin-M exhibited 95 % reduction in the viral load at the test concentration of 21.8 µg/mL with an IC₅₀ value of 5.4 µg/mL whereas, ProLectin-I did not show any cytotoxicity till 250 µg/mL concentration. Against 'human respiratory syncytial virus (hRSV) strain A2, ProLectin-M exhibited 65 % reduction in the viral load at the test concentration of 43.75 µg/mL with an IC₅₀ value of 27.41 µg/mL whereas, ProLectin- I did not show any cytotoxicity till 250 µg/mL concentration. Conclusion: Both ProLectin-I and ProLectin-M have been reported to exhibit broad-spectrum antiviral activity in ‘in-vitro’ setting. ProLectin-M reducing influenza-A virus by 95% and hRSC strain A2 by 65%. To better understand broad spectrum antiviral activity of ProLectin-I and ProLectin-M, further pre-clinical research is warranted.

According to published descriptions, one of the most incapacitating forms of orofacial pain is trigeminal neuralgia (TN). At its core, trigeminal neuropathic pain (TN) is still a clinical diagnostic that has to be differentiated from other forms of TN and face pain linked to other neuralgias or headache disorders. Imaging can only help with the cause of the pain, whether it’s a vascular origin or not. It is becoming more and more evident that there is no one-size-fits-all medication or surgical procedure that can effectively treat every patient with trigeminal neuralgia (TN). This is probably because TN is a diverse collection of conditions that all present with face discomfort. Medical therapy using anticonvulsants like carbamazepine is still the first-line treatment for TN. If this doesn't work for the patient, surgical treatments are available. Microvascular decompression is often a safe, efficient operation with results that are both rapid and long-lasting. Patients who may benefit from percutaneous techniques such as radiofrequency ablation, glycerol ablation, balloon compression, or a combination, include those who cannot undergo general anesthesia or whose medical conditions prohibit a suboccipital craniectomy. Radiosurgery may be a great option for patients with bleeding diathesis brought on by blood-thinning medications who are not eligible for invasive procedures or who do not want to undergo open surgical procedures, as long as the patient is aware that achieving maximum pain relief may take several months. In conclusion, peripheral neurectomies persist in offering a low-cost and resource-saving substitute for pain management to those residing in areas with restricted financial and healthcare resources. In the end, developing a better understanding of the molecular processes behind trigeminal neuralgia will lead to new, less intrusive, and more effective treatments.

The natural and man-made landscape settings in the Khyber Pakhtunkhwa (KPK) province of Northern Pakistan have significantly changed in the last decade due to increasing demands of urbanized populace, migration, two major natural disasters, and climate change. The aim of this study is to analyze land possession, income and land-use diversification of KPK administered Charsadda district. Field data is collected through a sample survey. Furthermore, freely available Landsat 7 satellite images are used to classify land-use classes (e.g. vegetation, built-up) for two different years (e.g. 2005 and 2017) for cross-verification and comparison. The highest 45% of 80% land-owners occupy land-area between 1-10 hectares. Annually, the highest 57.5% of the total farmers / employed in-habitants of surveyed regions earn more than Rs. 100,000 or ~ $ 970 from agriculture activities. About 41.9% land-area covered by agricultural-land is transformed into built-up area since 2007, which is attributed to the increasing demand for buildings and commercial markets. The highest diversification is reported in Naguman area of Charsadda district followed by Rajjar and Niami. Population growth and huge migration of displaced persons from neighboring tribal areas are likely to be few factors which contributed to such a drastic change in land-use pattern since 2007 to 2017. Urgent attention of the policy makers, agricultural experts and society is required to minimize land degradation and to thwart further agricultural-land loss.

Artery of Percheron Infarct (AOP) is a rare congenital anatomical vascular variant supplying the paramedian thalamus and the rostral midbrain. It arises from either proximal segment of the posterior cerebral artery (P1). The symptoms of an AOP infarction might vary, although they typically manifest as memory loss, altered mental status, and supranuclear vertical gaze palsy. Most of the time, the initial CT scan fails to diagnose the AOP infarct. Most of these diagnoses are made when ischemic stroke patients are not eligible for thrombolytic therapy. We report a case of a 40-year-old female with a history of well-managed hypertension, who presented in the ER with chief complaints of altered behavior, altered gaze palsy, and drowsiness. Initially, the CT scan did not show pathological changes. The diagnosis was made the next hospital day by MRI. Our case presents an unusual presentation and the lack of evidence of AOP infarction on a CT scan does not exclude its diagnosis. An infarcted Percheron artery requires a thorough clinical and radiological examination.

Water pollution is the main problem in the current scenario which is being faced by mankind due to the industrial and commercial effects. Industrial effluents contain heavy metals and inorganic ions like nitrates and phosphate ions. These ions are being included in waterways through industrial runoff. When the concentration of these hazardous pollutants increases in aquatic flora and fauna causes severe health problems. So remediation of these toxicants from water reserves is of chief importance. Conventional processes along with modern processes are being used for the treatment of industrial wastes. Photo-degradation is a modern method used for the degradation of inorganic ions due to its environmentally friendly nature and cost-effectiveness. In a recent study Aluminum oxide (Al2O3) nanoparticles were synthesized via a green approach at different pH by using Cymbopogan citratus (lemongrass) plant extract and these nanoparticles were used for the removal of inorganic ions from wastewater. The nanoparticles of different pH showed different % degradation of the inorganic ions in acidic medium removal of inorganic waste was less, in basic media % degradation was more as compared to acidic media but maximum % degradation was observed in neutral media like that average % degradation 91% and 81% was observed for nitrate and phosphate ions. The maximum absorbance occurred at 212nm and Al2O3 nanoparticles showed absorbance from 210nm-217nm. The R2 values of pseudo1st, 2nd, and BMG models were 0.956, 0.837, 0.7007 0.95, 0.896, and 0.756 for the nitrate and phosphate ions. Characterizations of synthesized particles were investigated by using UV-visible spectroscopy and other analytical methods like X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). The statistical analyses were done using Simple Linear regression (SLR).

The natural and man-made landscape settings in the Khyber Pakhtunkhwa (KPK) province of Northern Pakistan have significantly changed in the last decade due to increasing demands of urbanized populace, migration, two major natural disasters, and climate change. The aim of this study is to analyze land possession, income and land-use diversification of KPK administered Charsadda district. Field data is collected through a sample survey. Furthermore, freely available Landsat 7 satellite images are used to classify land-use classes (e.g., vegetation, built-up) for two different years (e.g., 2005 and 2017) for cross-verification and comparison. The highest 45% of 80% land-owners occupy land-area between 1–10 hectares. Annually, the highest 57.5% of the total farmers / employed in-habitants of surveyed regions earn more than Rs. 100,000 or ~$970 from agriculture activities. About 41.9% land-area covered by agricultural-land is transformed into built-up area since 2007, which is attributed to the increasing demand for buildings and commercial markets. The highest diversification is reported in Naguman area of Charsadda district followed by Rajjar and Niami. Population growth and huge migration of displaced persons from neighboring tribal areas are likely to be few factors which contributed to such a drastic change in land-use pattern since 2007 to 2017. Urgent attention of the policy makers, agricultural experts and society is required to minimize land degradation and to thwart further agricultural-land loss.

This comparative research paper examines the difference between sugarcane harvesting practices in Thailand and India. The objective of research was to investigate and compare current pattern of sugar harvesting and its impact of these approaches on labor health conditions in the sugarcane industry of both the countries as India and Thailand. Data were collected from target population groups (40 each) from study areas, namely Kanchanaburi and Saraburi provinces in Thailand and Beed District of Maharashtra state from India. The data showed that comparatively in Thailand, adoption of mechanized harvesting was seen more. However in India, mechanized harvesting was seen increasing but still people were largely involved in sugarcane harvesting and it had ill effects on the overall health of female workers specially. The result clearly indicated that there was drastic difference in harvesting system and labor health conditions in Thailand and India. The findings underscore the multifaceted impact of their occupation on various aspects of health including general well-being of female sugarcane cutters. The strenuous nature of sugarcane cutting, coupled with inadequate protective measures and limited access to healthcare has contributed to a range of health care challenges among female sugarcane cutters in India.

Presenting a case report on the occurrence of IgA nephropathy with hepatitis B infection in a 32-year-old male patient with main complaints of generalized weakness, easy fatigue, and bilateral swelling of the lower extremities. IgA nephropathy (IgAN), or Berger’s disease, is the most common primary glomerulonephritis worldwide. It is characterized by the formation of IgA1-containing circulating immune complexes and their deposition in the glomerular mesangium. Its etiology remains multifactorial and often idiopathic. IgA nephropathy alone does not have an infectious etiology; instead, it usually develops in conjunction with an infectious condition that triggers a dysregulated immune response. There is no proof that any particular infectious agent is the secondary cause of IgA nephropathy. Hepatitis B virus (HBV) infection is an infectious agent associated with renal complications, including IgA nephropathy. Symptoms include gross haematuria and mild proteinuria indicative of renal involvement. Laboratory investigations and serological tests are followed by imaging studies such as ultrasound and renal biopsy to confirm the diagnosis. The challenges encountered during the diagnostic process included overlapping symptoms and limitations of available diagnostic tests, highlighting the need for comprehensive diagnostic evaluation and multidisciplinary management approaches in similar cases. This case underscores the importance of recognizing and managing both conditions simultaneously to prevent long-term complications such as end-stage renal disease.

In order to address the issues of weight, cost and sustainability issues associated with the application of glass fibre in structural composites, plant fibres are proposed as an alternative to reduce and replace the usage of glass fibres. Despite this, there is still a gap in comprehensive research on plant fibre composites, especially with regard to their durability in real structural applications. This research investigates the fatigue and impact properties of pultruded hybrid polyester composites reinforced with glass fibre and kenaf, tailored for structural applications. Utilising kenaf fibres in mat form, unidirectional glass fibre direct roving yarns and unsaturated polyester resin as key components, pultruded kenaf/glass hybrid profiles were meticulously fabricated. Comparative cost and weight analyses were conducted between pultruded hybrid and non-hybrid profiles. The study showed that the pultruded kenaf/glass alternative laminates exhibit commendable fatigue and impact resistance, making them suitable for use in moderately loaded structural applications. Moreover, the use of kenaf as a hybrid alternative shows significant cost and weight reductions. This research provides a basis for the development of sustainable and efficient structural materials and highlights the significant role of material design in shaping the future of engineering applications.

Endopolygalacturonase (EndoPGase) is one of the crucial pectinases belonging to the class of carbohydrase. The catalytic action of EndoPGase captivate the attention for production of this extremely valuable catalyst of industrial sector. The main focus was to ascertain a potential bacterial candidate for endoPGase production. The isolated bacterial strain was further identified by 16S rDNA gene sequencing. A genomic library was constructed by using Lambda ZAP II vector system to investigate the pectinolytic potential of the expressed genes. The parameters for enzyme biosynthesis were optimized by single as well as multiple factor approach at a time. The results of our investigation led to the identification of a potent strain of Bacillus subtilis NR2. The strain was found active for pectic enzyme activity under shaking- flask fermentation at pH 5.0 and 50 °C temperature of incubation. Among all monomeric and polymeric substrates, citrus pectin followed by wheat bran was considered the best enzyme inducers at 1 % concentration. Moreover, an increasing trend in enzyme activity was observed with the increasing inducer concentration. The combined effect of three variables (pH, substrates, and substrate concentration) was explored by response surface methodology involving Box Benken Design (BBD). The study concluded that the soil isolated B. subtilis can be utilized for commercial scale pectinase enzyme production.

Increasing demand for electricity and modernization of power systems within competitive markets induce power systems to operate close to their stability limits. Therefore, a power system continuous monitoring and control by using voltage stability indices are known exigence. This is the first-ever effort, examined more than 40 voltage stability indices thorough an exhaustive study based in on their formulation, application, performance, and assessment measures. Which is conducted based on a logical and chronological order considering the most recent worldwide applied voltage stability indices. However, the generalizability of such an immense diversity of these indices in term of multivariable objectives subjects to a certain limitation to summate into a deciphered outcome. Despite all these obstacles, this study systematically reviews available indices in the literature within the past three decades to set out an integrated knowledge with an insight up-to-date exposition. That followed with a comparative analysis in term of their similarity, functionality, applicability, formulation, merit, demerit, and overall performances. Also, a broad categorization of voltage stability indices is addressed. This study with an immediate implication in practice as an exhaustive roadmap can be counted a planning and operation reference in the context of voltage stability for students, researchers, scholars, and practitioners.

Synthetic materials such as Carbon, Kevlar, and Glass fibers are extensively utilized in various industries due to their superior characteristics including high stiffness, great strength, low den-sity, and high wear resistance, these advantages contributed to making them widespread in ap-plications like; aerospace, automobile, civil and electronics. This research is carried out to enhance the creep compliance of epoxy composite material by considering two types of fibers as reinforcement. A composite material is produced by combining two fibers, Kevlar fiber mixed with sika epoxy resin, along with Carbon fiber also mixed with sika epoxy resin using a Hand-Layup process. Experiments and numerical modeling are examined to offer a comprehensive understanding creep behavior of epoxy composite material in different weight ratios. Burger and Prony models are used to represent stress relaxation and creep strain of Visco-elastic material. According to the results, sika epoxy resin reinforced with Kevlar and Carbon fibers exhibits enhancement in the mechanical properties compared with pure epoxy. The use of Kev-lar/Sika epoxy composite results in higher creep compliance and modulus of elasticity compared with Carbon/Sika epoxy composite.

An increasing number of studies have proposed that corporate social responsibility (CSR) performance depends on how companies apply their resources and capabilities to implement CSR. A firm’s ability to integrate, build, and reconfigure internal and external competencies to respond to environmental changes is its dynamic capability. Implementation of CSR at the strategic level will contribute to a firm’s sustainability. However, the research on strategic CSR is incipient. This study explores possible mechanisms to investigate how dynamic capability influences the performance of strategic CSR in China. By analyzing 134 Chinese listed companies in the period 2017–2019, in this study, we found that firms with a high level of dynamic capability were less likely to adopt strategic CSR practices, and had a low strategic CSR adoption performance. The results confirmed the loss aversion channel, indicating that firms with a high dynamic capability level were loss averse and that managers had a decreasing sensibility in decision-making and allocated fewer company resources in CSR projects. These results can help companies to better understand the dynamic capability and how dynamic capability contributes to the adoption of strategic CSR and performance over time. The policy implications of the study are also discussed.

Fertility preservation technologies have existed for decades, and the field is rapidly advancing; limited data exist regarding the use of these technologies by transgender patients. Many options are available for transgender patients who wish to preserve fertility before transitioning. These options include the cryopreservation of gametes, ovarian tissue, or embryos. Currently, ejaculated, or testicular sperm, immature oocytes, and ovarian tissue can be preserved for later use, but no such use option exists for immature testicular tissue. Many financial, sociological, and legal barriers and a lack of awareness among physicians and patients also hindered the utilization of these fertility preservation services. While options are abundant, usage rates are relatively low. The initial data regarding the successful use of preserved tissues appears promising, with birth rates not dissimilar to non-transgender patients. Further investigations into this area are needed. In addition, counseling regarding fertility preservation options should become a significant part of the provider-patient conversation before transitioning therapies.; fertility; transgender; reproductive technology.