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Abstract VANET is a category of MANET that aims to provide wireless communication. It increases the safety of roads and passengers. Millions of people lose their precious lives in accidents yearly, millions are injured, and others incur disability daily. Emergency vehicles need clear roads to reach their destination faster to save lives. Video streaming can be more effective as compared to textual messages and warnings. To address this issue, we proposed a methodology to use visual sensors, cameras, and OBU to record emergency videos. Initially, the frames are detected. After re-recording, the frames detection algorithm detects the specific event from the video frames. Blockchain encrypts an emergency or specific event using hashing algorithms in the second layer of our proposed framework. In the third layer of the proposed methodology, encrypted video is broadcast with the help of 5G wireless technology to the connected nodes in the VANET. The dataset used in this research comprises up to 72 video sequences averaging about 120 seconds per video. All videos have different traffic conditions and vehicles. The ResNet-50 model is used for the feature extraction process of extracted frames. The model is trained using Tensorflow and Keras deep learning models. The Elbow method finds the optimal K number for the K Means model. This data is split into training and testing. 70% is reserved for training the support vector machine (SVM) model and test datasets, while 30%. 98% accuracy is achieved with 98% precision and 99% recall as results for the proposed methodology.

This study aimed to evaluate the potential of integrating Photovoltaic (PV) with commercial load and examine the impact on distribution networks. To estimate the hourly PV output power, 13 years of historical weather data were used. Furthermore, a beta probability density function was modeled to handle large amounts of data and generate a 24-hour predicted PV curve. Particle Swarm Optimization (PSO) was used to determine the location and size of multiple PV units, ranging from 1 to 3. PV performance was tested on IEEE 33-bus and 69-bus test systems using time-varying commercial load, with power loss index (PLI) set as the objective function. PV penetration level was also calculated. The results showed a significant power loss reduction and PV penetration levels when 3 PV units were integrated into the system compared to a single PV unit. Specifically, the power loss reduction improved from 32.71% to 45.37% and 43.80% to 48.08%, producing PV penetration levels of 43.08% and 40.15% in 33-bus and 69-bus systems, respectively. The results indicated that the integration of multiple PV units was better than the single PV integration. The proposed model using PSO determined the impact of considering weather-dependent PV generation simultaneously with time-varying loads. It also provided knowledge to model the optimal location and sizing of multiple PV units in the distribution networks based on the generated solar irradiance patterns.

Abstract Background Pakistan grapples with the issue of an inadequate neurosurgery workforce but the reasons for such a disparity remain uncertain. Previous studies have highlighted how various factors including medical school experiences have an impact on career choice, but no study has delved into the impact of medical school exposure among Pakistani medical students, especially for the field of neurosurgery. This study aims to evaluate the impact of neurosurgery exposure, mentorship, and interest groups on medical students' decision to pursue neurosurgery. Methods A national cross-sectional survey was conducted in Pakistan, collecting data from medical students, interns, and medical officers over a one-month period. Ethical approval was obtained from the Ethical Review Committee at Aga Khan University, Pakistan. The data was analyzed using SPSS version 26. Results Out of 2618 participants, 38.0% were male and 62.0% were female, with an average age of 21.82 years (± 2.65). Among them, only 358 (13.6%) were interested in pursuing neurosurgery as a career, while the remaining 2,260 (86.3%) were not. More females (58.9%) than males (41.1%) expressed interest in pursuing neurosurgery as their intended career. Most medical students interested in pursuing neurosurgery were in the early years of their medical school (1st Year: 19.6%, 2nd Year: 26.0%, 3rd Year: 20.9%). In our study, students from public sector institutions (52.2%) showed more interest in neurosurgery as a career choice compared to those from private sector institutions (44.1%). The main deterrents for choosing neurosurgery were intense training (42.2%), work-life balance (39.9%), limited residency slots (56.7%), medical knowledge (34.1%), and surgical skills (36.6%). Conclusion This study highlights the need for increased student engagement to inculcate the decision to pursue neurosurgery among medical students in Pakistan. A significant gap is highlighted, with the majority of interested students in early years. Public sector students show higher interest than their private sector counterparts. However, barriers like intense training, limited residency slots, and work-life balance concerns influence career choice. Targeted interventions like mentorship programs are crucial for fostering future neurosurgeons and advancing patient care and research. By addressing the identified disparities in experiences and promoting a supportive educational environment, it is possible to cultivate a future generation of skilled and dedicated neurosurgeons who can contribute to advancements in patient care and research in the field.

α-Synuclein (α-syn) is a small protein that is involved in cell vesicle trafficking in neuronal synapses. A progressive aggregation of this protein is the expected molecular cause of Parkinson's disease, a disease that affects millions of people around the world. A growing body of evidence indicates that phospholipids can strongly accelerate α-syn aggregation and alter the toxicity of α-syn oligomers and fibrils formed in the presence of lipid vesicles. This effect is attributed to the presence of high copies of lysines in the N-terminus of the protein. In this study, we performed site-directed mutagenesis and replaced one out of two lysines at each of the five sites located in the α-syn N-terminus. Using several biophysical and cellular approaches, we investigated the extent to which six negatively charged fatty acids (FAs) could alter the aggregation properties of K10A, K23A, K32A, K43A, and K58A α-syn. We found that FAs uniquely modified the aggregation properties of K43A, K58A, and WT α-syn, as well as changed morphology of amyloid fibrils formed by these mutants. At the same time, FAs failed to cause substantial changes in the aggregation rates of K10A, K23A, and K32A α-syn, as well as alter the morphology and toxicity of the corresponding amyloid fibrils. Based on these results, we can conclude that K10, K23, and K32 amino acid residues play a critical role in protein-lipid interactions since their replacement on non-polar alanines strongly suppressed α-syn-lipid interactions.

African swine fever is a hemorrhagic disease of pigs with high mortality rates. Since its first characterization in 1921, there has been sufficient information about African swine fever virus (ASFV) and related diseases. The virus has been found and maintained in the sylvatic cycle involving ticks and domestic and wild boars in affected regions. The ASFV is spread through direct and indirect contact with infected pigs, their products and carrier vectors especially Ornithodoros ticks. Severe economic losses and a decline in pig production have been observed in ASFV affected countries, particularly in sub-Saharan Africa and Europe. At the end of 2018, the ASFV adversely affected China, the world’s leading pork-producer. Control strategies for the disease remained challenging due to the unavailability of effective vaccines and the lack of successful therapeutic measures. However, considerable efforts have been made in recent years to understand the biology of the virus, surveillance and effective control measures. This review emphasizes and summarizes the current state of information regarding the knowledge of etiology, epidemiology, transmission, and vaccine-based control measures against ASFV.

For the growth of sustainable energy, increasing the efficiency of photovoltaic/thermal (PV/T) systems is still essential. Particularly ternary hybrid nanofluids have shown promise as a means of improving the systems' electrical and thermal performance. This study delves deeply into the exploration of a three-dimensional annulus-type Photovoltaic Thermal (PV/T) system, centering on its cooling function through the utilization of ternary hybrid nanofluids featuring diverse nanomaterial shapes. The system structure involves a circular cylinder enveloped within glass, silicon, and copper layers, forming the core of the PV panel. The investigation employs COMSOL Multiphysics 6.0 with boundary conditions like radiative heat flux on the upper domain. Nanofluids with varied shapes (spherical, brick-like, cylindrical, platelet, and blade-shaped) comprising copper, aluminum oxide, and micro-wall carbon Nanotubes suspended in water are scrutinized as the base fluid. Using COMSOL Multiphysics, our simulation employs a conjugate heat transfer interface to solve the intricate three-dimensional Navier-Stokes equations and energy equations, addressing the combined convection challenges in the system. Analyzing parameters such as Reynolds number (100–1500), aspect ratios (0.1, 0.15, 0.2), shape factors (3–8.9), and total volume fractions of nanomaterials (1%–10 %), we noted a significant decline (21–28 %) in the average Nusselt number as nanoparticle concentration increased. This trend highlights strengthened convection processes, notably observable with increased flow pipe diameter or aspect ratio. This decrease suggests that the system's convective heat transfer efficiency has decreased. Nonetheless, because the PV cells are better cooled, the decrease in convective heat transfer is accompanied by an increase in the electrical efficiency of the system. The practical implication of this trend is that even though the thermal performance in terms of heat removal may decline, the overall cooling effect still helps to keep the PV cells' temperature down, thereby raising their electrical output. The study revealed enhanced electrical efficiency (up to 9.3834 %) with blade-shaped particles under specific conditions: Re = 1500, 10 % volume fraction, and an aspect ratio of 0.1. Additionally, the investigation suggests a potential for achieving a maximum thermal efficiency of 85.62 %. These findings underline the promising impact of nanomaterial manipulation on both electrical and thermal efficiencies within the PV/T system while the maximum temperature at the outlet reaced to 5.470 C.

Afghanistan is known for its long history of war and conflict. Since the invasion of the Soviets, the country has been facing subsequent invasions from other powers as well as internal conflicts among different religious sects and political groups for gaining power. Due to this history of turmoil and conflicts, the people of Afghanistan were severely affected. Many of them were displaced and migrated to other countries while those who remained suffered from the horrors and brutalities of war. It also caused them great physical, economic, and mental losses. During this era of absurdity, mental depression, and chaos writers felt the urge to express new experiences and realities in new ways, and thus war became a dominant theme in the writings of many Afghan writers. One among such leading authors is Khalid Husseini who has realistically and boldly reflected the life of Afghans during wartime and brutal realities of war in his novels. The current study probes into the author’s dealing with the war subject through the use of imagery in his novel ‘A Thousand Splendid Suns’ published in 2007. The study's main objective is to highlight how imagery has been a useful tool in the hand of the novelist to depict the brutalities and horrors of war. For this purpose, a qualitative research approach is adopted, including an introspective and contrapuntal reading of different quotations and excerpts from the novel in light of the theoretical framework adopted by Cuddon (1994). The key findings of the study are that imagery has been a useful tool in the hands of the writer for revealing the horrors and brutalities of war such as; mental trauma and chaos of characters, the portrayal of War Driven Landscape, nostalgia for the lost Cultural Heritage, separation of the loved ones and disintegration of social fabrics and physical violence against the civilians.

In this paper, we constructed a novel Lie group by using oblate spheroidal coordinates. First, we took the metric tensor of oblate spheroidal coordinates, then found its Killing vectors by using the Killing equation. After solving a system of partial differential equations, we obtained the Killing vectors. With the help of these Killing vectors, we first constructed finite Lie algebra and then proved that Killing vectors form a Lie group. Also, we described the geometric properties in which this Lie group forms a regular surface, defined the differential map and differential of normal vector field, and found the gaussian and mean curvatures.

Abstract Background Tick control is mostly hampered by the rise of acaricide-resistant tick populations. Significant efforts have focused on developing alternative control methods, including cross-species protective and/or cocktail-based anti-tick vaccines, to achieve protection against various tick species. Methods In this study, full-length open reading frames encoding subolesin (SUB) from Rhipicephalus microplus and ferritin 2 (FER2) from Hyalomma anatolicum as well as the partial 60S acidic ribosomal protein (P0) from R. microplus were cloned, expressed in Escherichia coli and used as vaccine antigens against Rhipicephalus sanguineus sensu lato (R. sanguineus s.l.) infestation in rabbits. Results In silico analyses revealed that the SUB, P0 and FER2 proteins were antigenic and displayed limited similarity to the host's homologous proteins. The proteins shared identities of 97.5%, 100% and 89.5% with their SUB, P0 and FER2 R. sanguineus s.l. orthologous sequences, respectively. Antibodies against each recombinant protein cross-recognized the native proteins in the different tissues and developmental stages of R. sanguineus s.l. Overall efficacy of the SUB, FER2 and cocktail (SUB+FER2+P0) vaccines against R. sanguineus s.l. infestation was 86.3%, 95.9% and 90.9%, respectively. Conclusions Both mono-antigen and the cocktail anti-tick vaccines affected the biological parameters of R. sanguineus s.l. infestation in the rabbit model, which could be extrapolated to its infested host under natural conditions. These findings support the possibility of using mono-antigenic and cocktail-based vaccines for large-scale anti-tick vaccine development against multiple tick species. Graphical Abstract

Curves are the leading cause of road departure crashes that turn into deaths and severe injuries. Most crashes occur on curved roads because they have different geometrical circumstances from straight roads. A sharp turn on the road creates more difficulty for the driver than a normal curve road. To Avoid crashes on the curved road, there is a prerequisite to identify the curved road for drivers that this turn is problematic. Responding intelligently to save precious human life and the country’s gross domestic product is necessary. Our paper proposed a Curve Crash Avoidance Protocol (2CAP) in Vehicular Ad-hoc Network (VANET). The Intelligent Curve Crash Avoidance Algorithm is proposed to avoid disastrous vehicle crashes. The sensing Node Operation algorithm works for multiple sensors embedded in the Onboard Unit to gather information on vehicles and road environments. On the other side, road-side unit requests for this collected data via a secure communication channel for processing. A Linear Regression machine learning technique implements the intelligent Unit Operations algorithm. The Intelligent Unit decides to notify the onboard Unit based on gathered data and trained dataset. We implement the scheme using the Linear Regression Machine Learning Model. Multiple sensors, Global Positioning Systems, and Global Information systems use the dataset methodology to classify and predict results. The proposed model is expected to be effective for proper coordination with wireless sensor network equipment.

The genus Amblyomma contains the highest percentage of reptile-associated ticks, and comprises approximately nine subgenera. One of these subgenera is Adenopleura, which also encompasses Amblyomma javanense, and its type species Amblyomma compressum. This study describes a new Amblyomma species associated with Bengal monitor lizards (Varanus bengalensis) based on morphology and its mitogenome in Khyber Pakhtunkhwa, Pakistan. Reptiles belonging to different genera were examined for Amblyomma ticks and only the monitor lizard was infested with ticks in the District Bajaur. Collected Amblyomma cf. javanense ticks were analyzed and formally described as a new species. Overall, 57 A. cf. javanense ticks were collected on monitor lizards (4/27) with a 15% prevalence of infestation, 2.1 mean abundance, and 14.3 mean intensity. Ticks comprised males (n = 23, 40%), females (n = 14, 25%) and nymphs (n = 20, 35%), while no larvae were found. BLAST analysis of A. cf. javanense sequences showed the following maximum identities; 98.25% with undetermined Amblyomma species based on 12S rRNA, 96.07% with A. javanense based on 16S rRNA, 99.56% and 90.95% with an Amblyomma sp. and A. javanense, respectively, based on ITS2. Moreover, the mitochondrial genome of A. cf. javanense showed maximum identities of 80.75%, 80.48% and 79.42% with Amblyomma testudinarium, A. javanense, and Amblyomma sp., respectively. The phylogenetic analysis of A. cf. javanense revealed that its 12S rRNA and 16S rRNA are closely related to an Amblyomma sp. and A. javanense, respectively, from Sri Lanka, its ITS2 is closely related to A. javanense from China and an Amblyomma sp. from Sri Lanka, and its mitogenome is closely related to A. javanense and Amblyomma sp. from China. The pairwise distance analysis resulted in divergence of 0–1.71% (12S rRNA), 0–17.5% (16S rRNA), 0–9.1% (ITS2) and 0–20.5% (mitochondrial genome). We also contributed the full-length mitochondrial genome sequence of A. compressum and showed that this species does not share a most recent common ancestor with A. javanense. As the subgenus Adenopleura is paraphyletic, this study could help to understand the systematics and phylogeny of this taxon.

Economic growth—through growth affordability, growth investments, and growth-awareness associations—may lead to increased access to clean fuel and technologies for cooking (ACF&T). The current paper presents the trend and comparative analyses regarding GDP per capita, access to clean fuels and technologies for cooking, and renewable energy consumption (REC) in the South Asian economies. The data from Bangladesh, India, and Pakistan between 2000 and 2020 shows a strong positive correlation between GDP per capita and access to clean cooking technologies. India has made the most significant improvements, followed by Pakistan and Bangladesh. All three economies negatively correlate GDP per capita and renewable energy consumption. Bangladesh shows the steepest decline, followed by India and Pakistan, indicating a more pronounced shift towards nonrenewable energy sources as economic prosperity increases. The study concludes that economic development often involves transitioning from traditional renewable energy sources (such as biomass) to more modern, nonrenewable energy sources (such as fossil fuels), often more efficient and reliable for industrial and large-scale energy needs. Hence, developing infrastructure and industrial sectors might lead to higher consumption of nonrenewable energy sources. This points to a potential challenge for sustainable development, as increased economic prosperity might be accompanied by more significant environmental impact unless there are concerted efforts to promote renewable energy sources.

LoRa technology contributes to green energy by enabling efficient, long-range communication for the Internet of Things (IoT). This paper addresses the challenges related to coverage range in outdoor monitoring systems utilizing LoRa, where the network performance is affected by the density of gateways (GWs) and end devices (EDs), as well as environmental conditions. To mitigate interference, data throughput losses, and high-power consumption, the proposed spreading factor (SF) and hybrid (data rate|SF) models dynamically adjust the transmission parameters. The orchestration of concurrent data modifications within the network server (NS) is crucial for uninterrupted communication between GWs and EDs, especially in monitoring electric vehicle (EV) stations to reduce traffic congestion and pollution. Employing K-means and density-based spatial clustering of applications with noise (DBSCAN) algorithms optimizes ED allocation, averts data congestion, and improves the signal-to-interference noise ratio (SINR). These methods ensure seamless information reception by meticulously allocated EDs across various GW combinations. To estimate the free-space losses (FSL), a log-distance path loss model (log-PL) is used. Exploring various bandwidths (BWs), bidirectional communications, and duty cycles (DCs) helps to prevent saturation, thus prolonging the operational lifespan of EDs. Empirical findings reveal a notable packet rejection rate (PRR) of 0% for the DBSCAN (hybrid model). In contrast, the K-means exhibits a PRR ranging from 5% (hybrid model) to 35.29% (SF model) for the ten GWs combination. Notably, the network saturation is reduced to 10.185% and 9.503%, respectively, highlighting an improvement in the average efficiency of slotted ALOHA (91.1%) and pure ALOHA (90.7%). These enhancements increase the lifespan of EDs to 15,465.27 days.

Synchronous reluctance motors offer promising advantages for industrial applications, including improved efficiency and reduced maintenance requirements. However, their widespread adoption is hindered by design complexities and performance limitations. This study focuses on addressing these challenges by developing a customized 24kW synchronous reluctance motor for industrial use, with a specific emphasis on centrifugal pumps. The research introduces a novel rotor design incorporating carefully designed flux barriers and flux carriers. Comprehensive machine analysis is conducted using the finite element method and Motor Solve software, while particle swarm optimization techniques are employed to enhance performance. Extensive simulations explore various machine parameters, and practical testing is conducted to validate the results and determine the optimized torque achievement. The results demonstrate significant improvements in the motor's performance. Compared to conventional induction motors used in similar applications, the optimized synchronous reluctance motor exhibits enhanced efficiency and smoother operation. The motor achieves notable advancements in terms of speed, efficiency, and torque characteristics, making it a valuable solution for industrial applications. The findings highlight the potential of the developed synchronous reluctance motor for industrial use. The motor design showcases excellent thermal performance, consistent steady-speed operation, and improved efficiency. This study contributes to the advancement of synchronous reluctance motor technology, showcasing its effectiveness and viability in diverse industrial settings. By addressing design complexities and optimizing performance, this research bridges the gap between the potential of synchronous reluctance motors and their practical implementation in industrial applications. Valuable insights are provided for the development of efficient and reliable synchronous reluctance motors in industrial systems.

Pollen grains are the male reproductive part of the flowering plants. It is collected by forager honey bees and mixed with their salivary secretions, enzymes, and nectar, which form fermented pollen or “bee bread” which is stored in cells of wax honeycombs. Bee pollen (BP) is a valuable apitherapeutic product and is considered a nutritional healthy food appreciated by natural medicine from ancient times. Recently, BP has been considered a beneficial food supplement and a value-added product that contains approximately 250 different bioactive components. It contains numerous beneficial elements such as Mg, Ca, Mn, K, and phenolic compounds. BP possesses strong antioxidant, anti-inflammatory, antimicrobial, antiviral, analgesic, immunostimulant, neuroprotective, anti-cancer, and hepatoprotective properties. It is used for different purposes for the welfare of mankind. Additionally, there is a growing interest in honey bee products harvesting and utilizing for many purposes as a natural remedy and nutritive function. In this review, the impacts of BP on different organisms in different ways by highlighting its apitherapeutic efficacy are described.

Melatonin (MT) participates in plants' responses in plants’ response to cadmium (Cd) tolerance, although its work model remains elusive. Here, the function of MT in adjusting Cd accumulation in Gossypium hirsutum (CCRI12) was investigated. In this research we observed that exogenous 50 μM MT significantly reduced the Cd accumulation under 100 μМ Cd stress for 7 days of treatment in cotton seedlings. Cd markedly induced the ROS (H2O2, O2-) accumulation and elevated the expression of transporters for Cd uptake and translocation. After application of MT reduced ROS and MDA accumulation in response to high induction of antioxidant defense system; the genes encoding superoxide dismutase (GhSOD), catalase (GhCAT), and peroxidase (GhPOD), ascorbate peroxidase (GhAPX), and glutathione S-transferase (GhGST) were significantly upregulated accompanied by their level of content. Furthermore, MT down-regulated transporters for Cd uptake include Natural Resistance-Associated Macrophage Protein 1 (GhNRAMP3), Zinc/Iron-regulated transporter-like protein (GhZIP1/4/6), Heavy Metal ATPase gene (GhHMA2), and ATP-binding Cassette sub family C (GhABCC3/2). Exogenous application of MT raised the hemicelluloses, cellulose and pectin content accompanied by their expression levels, xyloglucan endotransglucosylase/hydrolase (GhXTH28/6/9/B), cellulose synthase like (GhCSLG1/2) and COBRA-like (GhCOBL4), pectin acetylesterases (GhPAE8/7), pectin methylesterases (GhPME31) which in turn increased the cell wall's binding capacity to Cd.

This case presents a diagnostic challenge in a 28-year-old male initially evaluated for severe abdominal pain, vomiting, and constipation, leading to the presumption of post-appendectomy complications. Clinical examination revealed abdominal distension, tenderness, and signs of peritonism, along with a reducible inguinal hernia. On subsequent CT scan, a large, inflamed area of omentum localized to the right abdomen extending up to the defect in the inguinal region with mild ascites was revealed. Upon exploration, it was discovered that the patient’s initial surgery had focused solely on an appendix deemed mildly inflamed by the operating surgeon, while a concurrent diagnosis of secondary omental torsion was missed. This oversight underscores the challenges in diagnosing abdominal pathologies, with the initial misdiagnosis leading to ongoing patient distress. Meticulous adhesiolysis and omentectomy were performed, resulting in the resolution of the patient’s symptoms.

Objective: To find out the mode of presentation and severity of cardiac involvement in children presented with established rheumatic heart diseases (RHD) at first presentation at a tertiary care setup. Study Design: Cross-sectional study. Place and Duration of the Study: Department of Pediatric Cardiology, National Institute of Cardiovascular Disease, Karachi Pakistan, from Jul 2020 to Jun 2021. Methodology: One hundred seven children of genders aged 3 to 18 with a confirmed diagnosis of RHD were included. Demographic features, chief presenting complaints, possible reasons for late presentation, and echocardiographic findings were noted. Results: In 107 patients with RHD, 63(58.9%) were male. The sensation of the rapid pounding of heartbeat (palpitation) was observed among 72(67.3%) children, while a similar number of cases, 72(67.3%), presented with breathlessness. There were 33(30.8%) children who were diagnosed for the first time with RHD. The most common reason for late diagnosis was socioeconomic factors in children (18, 26.1%). Primary prophylaxis for acute rheumatic fever (ARF)/RHD was noted to be given in 11(10.3%) patients. Mitral regurgitation was the most common echocardiographic finding in 103(96.3%), followed by aortic regurgitation in 99(92.5%). Conclusion: The majority of children with RHD are diagnosed late, which exposes them to an increased risk of undiagnosed valvular disorders. Palpitation, orthopnea and breathlessness were RHD most frequent presenting clinical features. Mitral regurgitation and aortic regurgitation were the most common echocardiographic findings.