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Introduction: Dyslipidemia comprises disorders of lipoprotein metabolism, which is usually characterized by increased plasma levels of total cholesterol (TC), triglycerides (TG), low-density lipoproteins (LDL), or reduced plasma level of high-density lipoprotein (HDL). Dyslipidemia is commonly found in Type 2 Diabetes Mellitus (T2DM) patients causing an increased risk of atherosclerosis and cardiovascular disease. Many studies done previously show variable prevalence of dyslipidemia (68 to 85 %) in known diagnosed patients of T2DM (with unknown history of onset), however, only limited studies have been done for finding prevalence of dyslipidemia in newly detected T2DM patients. AIM: This study is a cross-sectional observational study done in a tertiary care hospital in Mumbai (India), aiming to study prevalence and pattern in newly detected T2DM patients. The secondary objective is to compare the prevalence and pattern of dyslipidemia in newly detected T2DM patients with non-diabetic controls. Material and Method: For this, 100 newly detected T2DM patients were chosen along with 100 cases of age & gender-matched non-diabetic controls. Their clinical profile and lipid profile of both groups were observed and compared. Result: Results showed higher prevalence of dyslipidemia in newly detected T2DM patients (64%) which was significantly more than the control group (32%). Moreover, the pattern of dyslipidemia showed greater mean levels of TC, TG, and LDL and low mean levels of HDL in T2DM patients compared to the control group. Conclusion: These findings show that there is an increased risk of Dyslipidemia in new onset T2DM patients.

Background: Periprosthetic Joint Infection (PJI) is a nightmare for both patient and surgeon. Despite advances made in arthroplasty still incidence is 1-2%. Many of our understanding regarding PJI come from registry data. Despite performing large number of joint replacement surgeries there is a lack of optimal registry data from this part of world. We retrospectively analysed PJI data in four NABH accredited hospital of around 5370 patients and tried to identify common risk factors in them and proposed a clinical scoring system for assessing risk of PJI. Materials and Methods: The study population was patients requiring surgical intervention in the form of arthroplasty. PJIs were defined as patients requiring procedure at the operated site within 2 years of index surgery. We retrospectively analysed patients’ data from hospital records and lab investigations done at the time of surgery. Results: We found that statistical significant risk factor in our study were number of joint replacement performed, poor blood glucose and serum albumin, increase duration and complexity of surgeries, Rheumatoid Arthritis (RA), Chronic Kidney Disease (CKD) and chronic liver disease and use of allogenic blood transfusion. Relative risk (RR) of diabetes (RR 2.4), liver disease (RR 1.6), connective tissue and rheumatic diseases (RR 1.5), serum albumin (RR 2.1), allogenic blood transfusion (RR 2.3), Increase duration for surgery (RR2.1), CKD (RR1.3) was there with PJI. Conclusions: Our research consistently identified the most significant risk factors for PJI across all cases. We propose a patient-based scoring system to estimate individual PJI risk. By addressing modifiable risk factors before joint replacement, we can potentially reduce the incidence of PJI.

Palatal fistula is a complication of cleft palate surgery. It can be due to suture dehiscence, hematoma, infection, or flap necrosis. Palatal fistula treatment is a challenge to surgeons. Treatment of fistula depends on its size, location, and surgeon experience. Because of a paucity of nearby tissue, it usually demands the incorporation of extra tissue from the surroundings for a successful outcome. Tongue flaps and buccal myomucosal flaps can be employed to add tissue from the surroundings. In this study, we describe a patient with a large palatal fistula repaired in stages with a good surgical outcome.

Background: Median arcuate ligament syndrome (MALS), also known as Dunbar syndrome or celiac artery (CA) compression syndrome, is a rare condition characterized by persistent post-meal or post-exercise abdominal discomfort, often more pronounced during expiration. Additional symptoms include nausea, vomiting, and weight loss. Aims and Objectives: To document the clinical presentation, diagnostic process, and treatment outcomes of seven patients diagnosed with MALS and to evaluate the effectiveness of surgical release of the median arcuate ligament (MAL) over a follow-up period of at least six months. Materials and Methods: The study included seven patients diagnosed with MALS from 2019 to 2021. Diagnosis was based on the presence of chronic abdominal pain and associated symptoms, absence of alternative diagnoses after various clinical assessments, and angiographic evidence of CA compression. The primary treatment involved surgical decompression of the CA by releasing the MAL through either open or laparoscopic techniques. Results: All seven patients underwent successful surgical release of the MAL. The patients were followed up for at least six months post-surgery. The study evaluated the persistence of symptoms and the need for additional interventions such as revascularization techniques. Conclusion: Surgical release of the MAL is the primary treatment for MALS, providing relief for many patients. However, long-term follow-up is essential as some patients may continue to experience symptoms post-surgery, necessitating further interventions.

The integration of multiple technical, economic, environmental, and social criteria establishes Multi-Criteria Decision Analysis (MCDA) as a dependable decision-making tool in the context of interdisciplinary research. This study employs a literature-based methodology to illustrate how MCDA, particularly utilizing the Analytical Hierarchy Process (AHP) and TOPSIS models, has been utilized to tackle intricate decision-making issues. It also highlights the noteworthy discoveries derived from real-world applications, drawing upon previous research and case studies. This study explores the methodologies employed in the commonly utilized AHP and TOPSIS approaches, highlighting their broad applicability across various industries from 2000 to 2023. Additionally, a comprehensive examination of the applications of MCDA has been organized into five distinct sectors, namely supply chain, healthcare, business, resource management, and engineering & manufacturing.

Abstract Water molecules confined in nanoscale spaces of 2D graphene layers have fascinated researchers worldwide for the past several years, especially in the context of energy storage applications. The water molecules exchanged along with ions during the electrochemical process can aid in wetting and stabilizing the layered materials resulting in an anomalous enhancement in the performance of supercapacitor electrodes. Engineering of 2D carbon electrode materials with various functionalities (oxygen (─O), fluorine (─F), nitrile (─C≡N), carboxylic (─COOH), carbonyl (─C═O), nitrogen (─N)) can alter the ion/water organization in graphene derivatives, and eventually their inherent ion storage ability. Thus, in the current study, a comparative set of functionalized graphene derivatives—fluorine‐doped cyanographene (G–F–CN), cyanographene (G–CN), graphene acid (G–COOH), oxidized graphene acid (G‐COOH (O)) and nitrogen superdoped graphene (G–N) is systematically evaluated toward charge storage in various aqueous‐based electrolyte systems. Differences in functionalization on graphene derivatives influence the electrochemical properties, and the real‐time mass exchange during the electrochemical process is monitored by electrochemical quartz crystal microbalance (EQCM). Electrogravimetric assessment revealed that oxidized 2D acid derivatives (G–COOH (O)) are shown to exhibit high ion storage performance along with maximum water transfer during the electrochemical process. The complex understanding of the processes gained during supercapacitor electrode charging in aqueous electrolytes paves the way toward the rational utilization of graphene derivatives in forefront energy storage applications.

The present report is about the successful surgical retrieval of eye worms in 15 horses. Most of the animals were presented with lacrimation, photophobia, and varying degrees of corneal opacity. On ophthalmic examination, worms appeared like moving white threads in the anterior chamber. Animals were restrained with xylazine-ketamine general anesthesia. Regional nerve blocks were given to minimize eyeball movements and a 2-3 mm clear corneal incision near the limbus at the 10-2 O'clock position of the eyeball was given to retrieve worms. With a single incision, worms were successfully removed in all the cases. Bolus of Ivermectin was given orally along with analgesic and antibiotics eye drops postoperatively. The vision was restored and corneal opacity subsided within 10-20 days post-surgery.

Plant growth regulators (PGRs) are artificially synthesized substances that control growth, development, and other various physiological processes in plants. Synthesized auxins, ethylene, abscisic acid, cytokinin, and gibberellins are only a few of the key PGRs that have been studied and used for quite a long period of time. brassinosteroids, salicylic acid, jasmonic acid, CPPU (N-(2-chloro-4-pyridyl)-N'-phenylurea), putrescine, hexanal, triacontanol, melatonin, and other chemicals have been added to the list of PGRs. These PGRs can be considered the new generation of plant growth regulators. These relatively novel hormones are critical for a plant's growth and development. They aid in the increase of not only the quantity (fruit set, length, weight, yield, volume, pulp percentage, and so on) but also the quality of fruit crops (fruit colour, firmness, total soluble solids, total sugar, ascorbic acid content, etc). They also help to prolong the shelf life of certain fruits and minimize the losses after harvesting. As a result, these new-generation PGRs can be used to boost an orchard's productivity and income while minimizing pre and post-harvest losses to the greatest extent possible. Hence, this extensive review discusses the impact of these new-generation PGRs on fruit crops.

Traditional global sensitivity analysis (GSA) neglects the epistemic uncertainties associated with the probabilistic characteristics (i.e. type of distribution type and its parameters) of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model response. This paper proposes an augmented Bayesian multi-model inference (BMMI) coupled with GSA methodology (BMMI-GSA) to address this issue by estimating the imprecision in the moment-independent sensitivity indices of rock structures arising from the small size of input data. The methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input properties. The estimated uncertainties are propagated in estimating imprecision in moment-independent Borgonovo's indices by employing a reweighting approach on candidate probabilistic models. The proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of India. The proposed methodology was superior to the conventional GSA (neglects all epistemic uncertainties) and Bayesian coupled GSA (B-GSA) (neglects model uncertainty) due to its capability to incorporate the uncertainties in both model type and parameters of properties. Imprecise Borgonovo's indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates, which makes the user more informed in the data collection efforts. Analyses performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample sizes. The accurate importance ranking of properties was only possible via samples of large sizes. Further, the impact of the prior knowledge in terms of prior ranges and distributions was significant; hence, any related assumption should be made carefully.

The green synthesis of nanoiron particles as a source of nutrition for crops has gained greater importance due to its multifunctional applications and easy and eco-friendly process. Deficiency of iron is a serious nutritional problem in aerobic rice production, and this problem can be solved by using green synthesised nanoiron fertiliser as a nutritional source. The aim of the present study is to prepare green leaf extracts, synthesise and characterise iron nanoparticles, and evaluate seed priming effects on germination and yield of aerobic rice. In the present study, nanoiron particles have been synthesised using leaf extract of Bidens pilosa and characterised using various instruments, viz. UV-visible spectroscopy, particle size analyzers, scanning electron microscopy (SEM), SEM-EDS, and atomic force microscopy (AFM). Further synthesised nanoiron was used as a seed priming and folair application for boosting the germination of aerobic rice.

BackgroundError-related potentials (ErrPs) are electrophysiological responses that naturally occur when humans perceive wrongdoing or encounter unexpected events. It offers a distinctive means of comprehending the error-processing mechanisms within the brain. A method for detecting ErrPs with high accuracy holds significant importance for various ErrPs-based applications, such as human-in-the-loop Brain-Computer Interface (BCI) systems. Nevertheless, current methods fail to fulfill the generalization requirements for detecting such ErrPs due to the high non-stationarity of EEG signals across different tasks and the limited availability of ErrPs datasets.MethodsThis study introduces a deep learning-based model that integrates convolutional layers and transformer encoders for the classification of ErrPs. Subsequently, a model training strategy, grounded in transfer learning, is proposed for the effective training of the model. The datasets utilized in this study are available for download from the publicly accessible databases.ResultsIn cross-task classification, an average accuracy of about 78% was achieved, exceeding the baseline. Furthermore, in the leave-one-subject-out, within-session, and cross-session classification scenarios, the proposed model outperformed the existing techniques with an average accuracy of 71.81, 78.74, and 77.01%, respectively.ConclusionsOur approach contributes to mitigating the challenge posed by limited datasets in the ErrPs field, achieving this by reducing the requirement for extensive training data for specific target tasks. This may serve as inspiration for future studies that concentrate on ErrPs and their applications.

Bhagandara is a well known ailment due to its high recurrence rate and complexity in management. Sambukavarta Bhagandara classifies it as an Asadhyaya ailment and describes it as a Tridoshaj Bhagandara. In present terminology, it is a synonym for Fistula in Ano. Here, the authors present a 45-year-old female with an anal fistula who had never received therapy or undergone surgery. In her case, an innovative technique called ‘Interception of Fistulous Tract with Application of Ksharsutra (IFTAK)’ was used for the Ksharasutra application. Five mL of Chandanbalalakshadi Tail Basti was administered every day. The patient was completely cured four to six weeks after the procedure. In situations with a horseshoe-shaped anal fistula, Ksharasutra therapy utilising the Windows (IFTAK) technique is exceptionally successful, resulting in less scar development, a shorter hospital stay, allowing patients to return to work sooner, causing fewer complications following surgery, and reducing the risk of recurrence.

This article presents a novel multilevel inverter (MLI) based on a basic unit of switched capacitor structure(SCS). The proposed SCS produces a multi-step DC-boosted output voltage using a few devices. This basic SCS unit is then used to develop a cross-switched structure. A crossed-switch structure combines several basic units to develop a larger unit that can produce a greater step level of output for a better sinusoidal signal and makes the system self-polarity change. The proposed system is configured by combining two SCS units, which produce less total standing voltage (TSV) across switches than other earlier proposed systems and generate 17-level output voltage with a boosting of 4 times. A simple pulse width modulation system is created to control the gating switches using logic gates. This work introduces the working principle of the basic unit topology, determines the required capacitance, power loss calculation, and efficiency curve, and presents experimental results on a scaled-down laboratory prototype to confirm the feasibility of the proposed design. After comparing the suggested converter to other current topologies, a thorough analysis shows that it is superior.

Industrial Internet of Things (IIoT), also known as Industry 4.0 is a major revolution in the industry and it is designed for enhancement of productivity and reliability. Security is a prime concern in the implementation of IIoT technology along with other concerns like patch management. An inefficient or insecure security mechanism would permit rogue (illegitimate) devices to access crucial data and resources in the network. In order to reduce the involvement of malicious devices in IIoT networks and ensure the security of crucial data, we suggest a device authentication and session key generation scheme for devices in IIoT networks. The proposed mechanism is based on the bitwise XOR operation, one-way hash function, and concatenation operation. In this scheme, the server and node generate the session key independently, and it cannot be generated by any third entity. The proposed mechanism is scrutinized for its security using AVISPA and ProVerif tools (automatically) and BAN logic (mathematically) and it has been determined from the generated results that the proposed scheme is safe and immune to any security threats. Performance of the proposed scheme has been verified through experimental analysis and from the result generated. It has been proved that it consumes less resources with maximum throughput. Hence it is efficient and secure.

An exponential growth and complexity in diverse distribution systems have contributed to protection coordination challenges. Initially, protection coordination schemes were achieved by means of conventional techniques; however, the utilisation of such methods is based on trial-and-error principles and laborious. Consequently, current studies have adopted the utilisation of particle swarm optimization, artificial intelligence models, and genetic algorithms to optimise overcurrent relay selectivity and operational speed. Particle swarm optimization, artificial intelligence, and genetic algorithms are optimization techniques that at times converges prematurely due to poor selection of control parameters and lack of optimal values, which results in increased computational time. Therefore, this paper presents a comprehensive review of recent developments in terms of parametric sensitivity analysis, selection of artificial intelligence models based on data availability, and the likelihood of solving overcurrent relay coordination problems. The reviewed literature shows that particle swarm optimization performance is greatly influenced by inertia weight and swarm size, while the number of iterations has insignificant effect. The findings also indicate that crossover rate, mutation probability, and population size affect genetic algorithms behaviour. Artificial intelligence models lack sensitivity study for parametric tuning, that is, number of hidden layers, membership functions, epsilon in support vector machine, and number of fuzzy rules affects the models’ performance.

Abstract In this paper we study the shear free spherical symmetric gravitational collapse of a charged radiating star. All the physical quantities including pressure, density are regular. Energy conditions are satisfied throughout the interior of the matter configuration. The luminosity is time independent and mass is radiated linearly. The causal and non causal temperature remain greater than that of the uncharged collapsing scenario.

Wind attribute analysis is a crucial aspect of meteorological and environmental research, with applications ranging from renewable energy generation to weather forecasting. However, existing models encounter several challenges in accurately and comprehensively characterizing wind positions. In this context, the proposed Incremental Tuned Generative Adversarial Network model (incremental GAN model), based on an unsupervised learning approach, introduces innovative solutions to overcome these challenges and enhance the precision and reliability of wind position analysis. This research aims to enhance the reliability and efficiency of wind energy generation by analyzing wind conditions and providing accurate data for decision-making. It introduces an Incremental GAN that refines parameters based on various factors. This GAN model learns and predicts these parameters over time, improving its performance. It incorporates advanced techniques like a 2-level fused discriminator and self-attention for precise predictions of wind characteristics. The GAN model generates important parameters such as droop gain, which influences generator output in response to load or generation changes, aiding grid stability. It also optimizes the frequency control of different types of generators in the presence of wind farms. The model continuously monitors wind farm conditions, adjusting power injection into the grid as needed for efficient and reliable wind energy utilization.

COVID-19 caused by a novel agent SARS-CoV-2 progressed to a pandemic condition and resulted in a major public health concern worldwide, leading to social and economic issues at the same time. Vaccinated people getting infected with SARS-COV2 brings a dilemma among the population whether to get vaccinated or not. The primary objective of this study is to evaluate the impact of vaccination by comparing the lung involvement in vaccinated and un vaccinated Covid – 19 patients. Retrospective anonymised data of COVID-19 inpatients who underwent HRCT scan during the second wave of pandemic were collected through a validated data collection form, from the medical records of tertiary care private medical college hospital. Vaccinated and non-vaccinated COVID-19 positive participants of 33 each were included in the study. CT severity score (CTS), D-dimer, IL-6 level, oxygen requirement and duration of hospital stay were statistically analysed using appropriate methods. The mean age of the study participants were 56.93 ± 16.01 years. There was no statistical significance between both the groups with respect to gender distribution in vaccinated and unvaccinated groups. There was a statistically significant difference in mean CTS score(p

An augmented methodology is developed to estimate the reliability of deep excavations along spatially variable massive rock masses using the cohesion weakening friction strengthening (CWFS) model. Sensitive parameters of the CWFS model were initially identified using Sobol’s global sensitivity analysis based on their influence on the displacements and excavation damage zone around excavations. The probability of failure was estimated by performing Mont–Carlo Simulations on random finite difference models of excavations generated via MATLAB-FLAC2D coupling, considering the spatial variation of these sensitive parameters. Spatial variation was modeled by generating anisotropic random fields of sensitive CWFS parameters via the recently developed Fourier series method and updated correlations suggested by Walton (2019). The proposed methodology was demonstrated for a proposed deep nuclear waste repository to be located in Canada. Results from the developed methodology were systematically compared with those of traditional reliability (ignoring spatial variation) and deterministic methods (ignoring uncertainty). Although the developed methodology was computationally complex, it was judged to be the most realistic due to the realistic consideration of heterogeneous distributions of rock properties. Traditional methodologies underestimate/overestimate the excavation performance due to negligence of uncertainty and spatial variability. Finally, a parametric analysis was performed using developed methodology by varying the initial friction angle, scale of fluctuations (SOFs) and dilation angle. The effect of initial friction angle was observed to be more pronounced on the probability of failures as compared to SOFs and dilation angle. Similar observations were made related to the excavation damage zone (EDZ) development quantified using yield area ratio.

In this manuscript, a direct current (DC) boost converter based on a switched-capacitor circuit with closed-loop control, tailored for applications with high-voltage gain, is introduced. The converter utilizes a network with switching capacitors to enhance voltage gain without relying on inductors, making it ideal for high-voltage scenarios. An active disturbance rejection control (ADRC)-based control scheme is used to maintain output voltage stability in the presence of disturbances. The proposed converter’s functionality and performance are assessed through simulations and experimental tests under various load conditions. A loss analysis, considering the losses from switches and diodes, is provided to determine the net efficiency. The results from both simulations and experiments show that the proposed converter achieves a high-voltage gain, excellent load regulation, and rapid transient response, highlighting its potential for applications that require a high-voltage boosting operation.

This study provides a thorough examination of the important intersection of Wireless Sensor Networks (WSNs) with machine learning (ML) for improving security. WSNs play critical roles in a wide range of applications, but their inherent constraints create unique security challenges. To address these problems, numerous ML algorithms have been used to improve WSN security, with a special emphasis on their advantages and disadvantages. Notable difficulties include localisation, coverage, anomaly detection, congestion control, and Quality of Service (QoS), emphasising the need for innovation. This study provides insights into the beneficial potential of ML in bolstering WSN security through a comprehensive review of existing experiments. This study emphasises the need to use ML’s potential while expertly resolving subtle nuances to preserve the integrity and dependability of WSNs in the increasingly interconnected environment.

Electric power is crucial for economic growth and the overall development of any country. The efficient planning of distribution system is necessary because all the consumers mainly rely on the distribution network to access the power. This paper focuses on addressing distribution system challenges and meeting consumers’ fundamental needs, such as achieving an improved voltage profile and minimizing costs within an environmentally sustainable framework. This work addressed the gap in the existing research by analysing the performance of both balanced and unbalanced systems within the same framework, specifically using the IEEE 33-bus and IEEE 118-bus test systems. Unlike prior studies that focused solely on either balanced or unbalanced systems, this work redistributed balanced loads into three-phase unequal unbalanced loads to create a more challenging unbalanced distribution network. The primary objective is to compare the effects of balanced and unbalanced loads on system the performances and to identify strategies for mitigating unbalanced load issues in each phase. Six optimization methods (PSO, TLBO, JAYA, SCA, RAO, and HBO) were employed to minimize losses, voltage variations, and other multi-objective function factors. Additionally, the study compared the cost of energy loss (CEL), emission factors, costs associated with distributed clean energy resources (DCER), and active and reactive power losses. Phase angle distortions due to unbalanced loads were also analysed. The results showed that among the optimization techniques tested (PSO, TLBO, JAYA, SCA, RAO, and HBO), the HBO method proved to be the most effective for the optimal allocation of distributed clean energy resources, yielding the lowest PFMO values and favourable outcomes across the technical, economic, and environmental parameters.

Supracondylar femur fracture in twelve dogs were managed using rush pinning technique. Post-operative radiographs displayed good anatomical alignment and reduction of fracture fragments without any pin migration. All the eight dogs showed normal gait without any limp on last reappraisal day. Rush pinning yielded good clinical outcomes in the management of supracondylar femur fractures with minimum complications.

Study was carried out to design and evaluate clinical application of caps for intramedullary pinning to mange long bone fractures in dogs. Cannulated cancellous caps made of 316 L stainless steel with dimensions of 10 mm × 25 mm (length) cap for 4 mm, 4.5 mm and 5 mm steinmann pin and 8 mm × 25 mm (length) cap for 2.5 mm and 3 mm steinmann pin were designed. A total of 14 cases of dogs presented with simple transverse, short oblique fractures of long bones were equally divided into groups A and B having 7 animals in each. Simple intramedullary pinning was done in group A, whereas, in group B designed caps were fixed at entry point at trochanteric fossa after intramedullary pinning to prevent proximal migration of pins. Posture, gait, perception of pain and lameness scores were assessed during 15, 30 and 60 day, postoperatively. Caps offered rigid fixation along with intramedullary pin resulting in mild or moderate callus formation. Excellent postoperative functional recovery without any pin migration, seroma formation and valgus limb deformity were observed in group B. Results of present preliminary study suggested that designed capped intramedullary pinning offers stable internal fixation and prevented pin migration, sciatic injury and seroma formation.

In smart enterprise systems, augmented IoT can efficiently improve the decision-making, handling, and generation of a huge amount of information during communication. However, Augmented Internet-of-Things (AIoT) leads to various security and trust issues when transmitting information through intermediate devices. In a case where malicious devices can easily integrate with legitimate devices, it can further affect and interfere with the overall performance of the network system. Though various security surveys have been illustrated and schemes have been proposed by scientists, however, all of them are in their early stages. This paper proposes a trusted decision-making mechanism called Active Recognition Trust (ART), using AIoT for handling smart enterprise systems. The proposed mechanism integrates active recognition and associated reference mechanisms to improve the efficiency and effectiveness of the secure transmission process by computing a trust value for each device using impact factors of function fusion systems before information exchanges. Simulation results show that the proposed mechanism can efficiently enhance performance while improving the accuracy of recognizing legitimate devices by reducing or eliminating interference from malicious devices. The proposed mechanism is evaluated using the transmission ratio, identification accuracy, average trust, and run cycle compared to the existing mechanisms. Further, the proposed mechanism achieves approximately 89% better improvement than the baseline approach.

This article describes a 17-level switched-capacitor-based eight-times-boosting gain inverter. The inverter is made up of a DC power source, thirteen switches, three diodes, and three capacitors. The inverter produces seventeen steps during each cycle and crosses the zero line two times in one complete cycle. The proposed inverter has its polarity change mechanism; it is not necessary to use an H-bridge. Three self-balancing capacitors make up this construction. The capacitors automatically balance voltage by connecting in series/parallel to the input voltage source. Logic gates can generate gate pulses with the phase disposition pulse-width modulation technique, which helps to preserve capacitor voltage balance at the same time. The proposed structure was compared to recent papers, analyzing factors including voltage gain, DC sources, semiconductor devices, cost function, and TSV. The proposed configuration offers cost effectiveness and fewer semiconductor devices for providing a 17-level output with sufficient voltage gain. Also, to reduce the capacitor inrush current, soft charging is used. Additionally, the proposed structure’s power losses were examined, confirming its efficiency. Finally, an experimental prototype was tested to analyze and validate the suggested structure’s performance under various situations. Results show the proposed structure performs well under steady and dynamic situations.

The HMG-CoA reductase inhibitors, statins, are drugs used globally for lowering the level of cholesterol in the blood. Different clinical studies of statins in cancer patients have indicated a decrease in cancer mortality, particularly in patients using lipophilic statins compared to those on hydrophilic statins. In this paper, we selected two structurally different statins (simvastatin and pravastatin) with different lipophilicities and investigated their effects on the proliferation and apoptosis of hepatocellular carcinoma cells. Lipophilic simvastatin highly influences cancer cell growth and survival in a time- and concentration-dependent manner, while pravastatin, due to its hydrophilic structure and limited cellular uptake, showed minimal cytotoxic effects.

Abstract Background Motor impairment is a common consequence of stroke causing difficulty in independent movement. The first month of post-stroke rehabilitation is the most effective period for recovery. Movement imagination, known as motor imagery, in combination with virtual reality may provide a way for stroke patients with severe motor disabilities to begin rehabilitation. Methods The aim of this study is to verify whether motor imagery and virtual reality help to activate stroke patients’ motor cortex. 16 acute/subacute (< 6 months) stroke patients participated in this study. All participants performed motor imagery of basketball shooting which involved the following tasks: listening to audio instruction only, watching a basketball shooting animation in 3D with audio, and also performing motor imagery afterwards. Electroencephalogram (EEG) was recorded for analysis of motor-related features of the brain such as power spectral analysis in the $$\alpha$$ α and $$\beta$$ β frequency bands and spectral entropy. 18 EEG channels over the motor cortex were used for all stroke patients. Results All results are normalised relative to all tasks for each participant. The power spectral densities peak near the $$\alpha$$ α band for all participants and also the $$\beta$$ β band for some participants. Tasks with instructions during motor imagery generally show greater power spectral peaks. The p-values of the Wilcoxon signed-rank test for band power comparison from the 18 EEG channels between different pairs of tasks show a 0.01 significance of rejecting the band powers being the same for most tasks done by stroke subjects. The motor cortex of most stroke patients is more active when virtual reality is involved during motor imagery as indicated by their respective scalp maps of band power and spectral entropy. Conclusion The resulting activation of stroke patient’s motor cortices in this study reveals evidence that it is induced by imagination of movement and virtual reality supports motor imagery. The framework of the current study also provides an efficient way to investigate motor imagery and virtual reality during post-stroke rehabilitation.

A focus has been placed particularly on the description of breast abscesses (sthana vidradhi in Ayurveda terms). Breast inflammation known as mastitis has the potential to develop into a breastabscess in the future. The term “stana roga,'' refers to breast disorders and describes breast abscesses, is mentioned in the ancient works Sushruta Samhita, Madhava Nidana, and Bhavaprakasha. Breast abscesses are typically treated surgically by making an incision over the area of greatest fluctuation (or pain) and breaking the abscess septa with digits. For a few days, the abscess chamber is left untreated or gauze-packed, with dressing changes made as needed to facilitate wound granulation. The current report was aimed at management of the breast abscess through an integrated approach comprising surgical and medicinal intervetions as mentioned in Ayurveda classics. A 32-year-old female patient with pain and swelling in right breast was diagnosed with breast abscess in Shalya (Surgery) OPD and managed primarily by incision and drainage which was followed by regular dressing and ayurvedic medications which encouraged appreciable granulation in a short period of time with complete healing of the abscess. This case study presents the successful management of breast abscesses with both surgical & Ayurvedic management.

Abstract Quantum coherence is pivotal in various applications ranging from chemical control to quantum computing. An example of its manifestation in molecular dynamics is inversion symmetry breaking in the photodissociation of homonuclear diatomic molecules. On the other hand, the dissociative attachment of an incoherent electron also induces such coherent dynamics. However, these processes are resonant and occur for projectiles with a specific energy. Here we present the most general scenario of non-resonant inelastic electron scattering inducing such a quantum coherence in molecular dynamics. The ion-pair formation (H+ + H─) that proceeds after the electron impact excitation of H2 shows a forward-backward asymmetry about the incoming electron beam. Simultaneous transfer of multiple angular momentum quanta during the electron collision induces the underlying coherence in the system. The non-resonant nature of this process makes this effect generic and points to its possible prevalent role in particle collision processes, including electron-induced chemistry.

Functionalized nanocellulose is a promising drug carrier, however, studying surface functionalization at the atomic scale remains challenging due to spectroscopic methodology limitations. Here, the authors use dynamic nuclear polarization enhanced 13C and 15N solid-state NMR to optimize the drug loading on nanocellulose using aqueous heterogeneous chemistry.

Our study assessed patterns of Asiatic black bear (Ursus thibetanus)–human conflicts within the Guthichaur rural municipality, Jumla, Nepal. Through semi-structured interviews with villagers, focus group discussions (FGDs), and key informant interviews (KIIs), we gathered black bear–human conflict information from 2009 to 2019. We identified three primary types of black bear–human interactions: crop damage, livestock depredation, and human injuries. Of these, crop damage (77.03%) emerged as the most prevalent issue. Notably, peak occurrences were observed during autumn (September–October) typically between 9 PM and 3 AM. Livestock depredations were more frequent during nighttime in April–August, with cows/ox (70.12%) being the most depredated animal. Our data also revealed five recorded cases of black bear attacks on humans, which transpired from September to October, primarily in farmland areas in varying years. Despite a prevailing negative perception of bears, a notable level of support exists for their conservation efforts among local communities. Furthermore, these conflicts could be mitigated by reinforcing indigenous crop protection methods and implementing targeted mitigation strategies, as observed in other regions with successful black bear–human interaction management.

In this work, evidence of isothermal magnetic entropy change (∆SM) over a broad temperature region is presented in a series of La1.4Sr1.6Mn2−xNbxO7 Ruddlesden–Popper compounds with niobium modification (Nb) (0.0 ≤ x ≤ 0.15) at the manganese (Mn) site. The ceramic samples were obtained through a solid-state sintering method in optimized conditions. All compounds predominantly possessed Ruddlesden–Popper phase while a few additional reflections were resolved in Nb-doped compounds which indicates the separation of structural phases. These peaks are assigned to a separate layered perovskite and single perovskite with tetragonal symmetry and hexagonal symmetry, respectively. The microstructure of the pure sample reveals uniform grain morphology but in Nb-doped specimens chiefly three types of grains were found. It was assumed that the inter-connected large particles were of R-P phase which is dominant in both parent and x = 0.05 compounds, while the hexagonal and polygonal morphology of grains in higher concentrations of dopants directly corroborates with the symmetry of single perovskite and additional layered perovskite phases, respectively. The parent compound exhibits a single ∆SM curve, whereas all Nb-substituted samples display bifurcated ∆SM curves. This indicated two transition regions with multiple magnetic components, attributed to distinct structural phases. The highest ∆SM values obtained for components corresponding to the R-P phase are 2.32 Jkg−1k−1, 0.75 Jkg−1k−1, 0.58 Jkg−1k−1 and 0.43 Jkg−1k−1 and for the second component located around room temperature are 0.0 Jkg−1k−1, 0.2 Jkg−1k−1, 0.28 Jkg−1k−1 and 0.35 Jkg−1k−1 for x = 0.0, 0.05, 0.10 and 0.15 compositions, respectively, at 2.5 T. Due to the collective participation of both components the ∆SM was expanded through a broad temperature range upon Nb doping.

The built environment is a significant contributor to global energy consumption and greenhouse gas emissions. Advancements in the adoption of environmentally friendly building technology have become crucial in promoting sustainable development. These advancements play a crucial role in conserving energy. The aim is to achieve an optimal design by balancing various interrelated factors. The emergence of innovative techniques to address energy conservation have been witnessed in the built environment. This review examines existing research articles that explore different metaheuristic optimization techniques (MOTs) for energy conservation in buildings. The focus is on evaluating the simplicity and stochastic nature of these optimization techniques. The findings of the review present theoretical and mathematical models for each algorithm and assess their effectiveness in problem solving. A systematic analysis of selected algorithms using MOT is conducted, considering factors that influence wellbeing, occupant health, and indoor environmental quality. The study examines the variations among swarm intelligence MOTs based on complexity, advantages, and disadvantages. The algorithms’ performances are based on the concept of uncertainty in consistently providing optimal solutions. The paper highlights the application of each technique in achieving energy conservation in buildings.

Background Distal colostogram and ileostogram are commonly performed radiological procedures in the pediatric population. It is sometimes difficult to identify the distal stoma while performing these procedures.

Background: Syphilis is a sexually transmitted infection caused by Treponema pallidum. High prevalence of syphilis was observed among human immunodeficiency virus (HIV)-positive patients. Atypical serological responses such as high antibody titers leading to frequent false-negative reactions have been reported with nonspecific treponemal tests. Simultaneous infection of syphilis and HIV in pregnant women increases the risk of HIV transmission from mother-to-child. Aim: The aim of the study was to assess the seroprevalence of syphilis in HIV patients including pregnant women and to know the efficiency of serological tests in detecting syphilis among HIV patients. Materials and Methods: The present study was a hospital-based cross-sectional study conducted among 500 HIV-reactive patients, including 100 HIV-reactive pregnant women attending the Outpatient Department of Dermatology, Venereology and Leprosy in a tertiary care center were enrolled in the study and were tested for the presence of syphilis using rapid plasma reagin (RPR) and T. pallidum hemagglutination assay (TPHA). Results: Among 500 samples, 58 (11.65%) were positive for syphilis. The most common age group was 30–39 years. Both RPR and TPHA were reactive in 25% of cases, TPHA reactive in 60.2% of cases, and only RPR reactive in 14.7% of cases. Seropositivity among pregnant women was 7%. The sensitivity and specificity of RPR test was 29.3% and 97.7%, respectively, in comparison with TPHA. Positive and negative predictive values of the same were found to be 62.9% and 91.3%, respectively, compared to TPHA. Conclusion: In all symptomatic and asymptomatic cases of syphilis, both RPR and TPHA should be performed for laboratory diagnosis of syphilis. It is advocated that all patients with newly diagnosed HIV should be suggested for syphilis serology and vice versa.

Currently, there is no international unanimity regarding the timings, the optimal cut-off points, and standardized methods of screening or diagnosis of gestational diabetes mellitus (GDM). The screening guidelines and recommendations for GDM evolved over time; concise information has been presented here in the review. We searched electronic databases for various guidelines for screening of GDM in PubMed, Medical Literature Analysis and Retrieval System Online (MEDLINE), Embase, Cochrane, Google Scholar, Scopus, Guidelines International Network (GIN library), National Guidelines Clearinghouse (NGC); Web sites of relevant organizations; and trial registries. The mesh headings derived after reviewing the articles and were used to further search the articles are: (”Screening Guidelines GDM” or “Screening Criteria for GDM”) and (”Glucose Intolerance in Pregnancy” or “Gestational Diabetes Mellitus”). The articles published from 1960 till December 2022 were included. Key outcomes included the prevalence of GDM is 14.6% according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria and 13.4% according to Diabetes in Pregnancy Study Group India (DIPSI) criteria, making the DIPSI criterion a cost-effective method for low-resource settings. The IADPSG) criterion diagnoses and treats GDM earlier, thus reducing the complications associated with GDM in the mother and newborn. The IADPSG criteria at a cut-off of ≥140 mg/dL have a sensitivity of 81% and specificity of 93%, whereas the World Health Organization (2013) criteria at the same cut-off has a lower sensitivity of 59% and specificity of 81%. The risk factors of having GDM are family history, history during past pregnancy, medical history, multiple current pregnancies, and raised hemoglobin A1c. The screening guidelines have been developed by different organizations and institutions over the years. The guidelines with the threshold values for screening and their standardization for detecting GDM in Indian mothers are yet to be established.

Goal: The purpose of this work is to improve malaria diagnosis efficiency by integrating smartphones with microscopes. This integration involves image acquisition and algorithmic detection of malaria parasites in various thick blood smear (TBS) datasets sourced from different global regions, including low-quality images from Sub-Saharan Africa. Methods: This approach combines image segmentation and a convolutional neural network (CNN) to distinguish between white blood cells, artifacts, and malaria parasites. A portable system integrates a microscope with a graphical user interface to facilitate rapid malaria detection from smartphone images. We trained the CNN model using open-source data from the Chittagong Medical College Hospital, Bangladesh. Results: The validation process, using microscopic TBS from both the training dataset and an additional dataset from Sub-Saharan Africa, demonstrated that the proposed model achieved an accuracy of 97.74% ± 0.05% and an F1-score of 97.75% ± 0.04%. Remarkably, our proposed model with AlexNet surpasses the reported literature performance of 96.32%. Conclusions: This algorithm shows promise in aiding malaria-stricken regions, especially those with limited resources.

Introduction: Sepsis is the leading cause of mortality, and various scoring systems have been developed for its early identification and treatment. The objective was to test the ability of quick sequential organ failure assessment (qSOFA) score to identify sepsis and predict sepsis-related mortality in the emergency department (ED). Methods: We conducted a prospective study from July 2018 to April 2020. Consecutive patients with age ≥18 years who presented to the ED with a clinical suspicion of infection were included. Sensitivity, specificity, positive predictive value (PPV), negative predictive values (NPV), and odds ratio (OR) for sepsis related mortality on day 7 and 28 were measured. Results: A total of 1200 patients were recruited; of which 48 patients were excluded and 17 patients were lost to follow-up. 54 (45.4%) of 119 patients with positive qSOFA (qSOFA >2) died at 7 days and 76 (63.9%) died at 28 days. A total of 103 (10.1%) of 1016 patients with negative qSOFA (qSOFA score

For power grids with high penetration of distributed energy resources (DERs), microgrids can provide operation and control capabilities for clusters of DERs and load. Furthermore, microgrids enhance resilience of the hosting bulk power grid if they are enabled to serve critical load beyond the jurisdiction of the microgrids. For widespread deployment of microgrids, a modular and standardized Microgrid Building Block (MBB) is essential to help reduce the cost and increase reliability. This paper proposes the conceptual design of an MBB with integrated features of power conversion, control, and communications, resulting in a systemwide controller for the entire microgrid. The results of a feasibility study indicate that, in a utility-connected mode, MBB-based microgrids can exchange power with the hosting power grid while serving regulation and optimal dispatch functions. In a resiliency (islanded) mode when the microgrid is disconnected from the utility system, the MBB control system acts to stabilize the system frequency and voltage under small or large disturbances. The microgrid controller is supported by a communication system that meets the latency requirements imposed by the microgrid dynamics as well as data acquisition time. The extended IEEE 13-node system is used as a microgrid model to validate the proposed MBB design and functionality.

The uncontrolled and metastatic nature of cancer makes it worse and more unpredictable. Hence, many therapy and medication are used to control and treat cancer. However, apart from this, many medications cause various side effects. In America, nearly 8% of patients admitted to the hospital are due to side effects. Cancer is more seen in people residing in developed countries related of their lifestyle. There are various phytoconstituents molecules in which resveratrol (RSV) is the best-fitted molecule for cancer due to its significantly less adverse effect on the body. RSV inhibits the initiation and progression of cell proliferation due to the modulation of various pathways like the phosphoinositol 3 kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway. RSV downgraded cell cycle-regulated proteins like cyclin E, cyclin D1, and proliferating cell nuclear antigen (PCNA) and induced the release of cytochrome c from the mitochondria, causing apoptosis or programmed cell death (PCD). A great benefit comes with some challenges, hence, RSV does suffer from poor solubility in water i.e. 0.05 mg/mL. It suffers from poor bioavailability due to being highly metabolized by the liver and intestine. Surprisingly, RSV metabolites also induce the metabolism of RSV. Hence, significantly less amount of RSV presented in the urine in the unchanged form. Due to some challenges like poor bioavailability, less aqueous solubility, and retention time in the body, researchers concluded to make the nanocarriers for better delivery. Adopting the technique of nano-formulations, increased topical penetration by up to 21%, improved nano-encapsulation and consequently improved bioavailability and permeability by many folds. Hence, the present review describes the complete profile of RSV and its nano-formulations for improving anti-cancer activity along with a patent survey.

Abstract Background Eukaryotic genome is compartmentalized into structural and functional domains. One of the concepts of higher order organization of chromatin posits that the DNA is organized in constrained loops that behave as independent functional domains. Nuclear Matrix (NuMat), a ribo-proteinaceous nucleoskeleton, provides the structural basis for this organization. DNA sequences located at base of the loops are known as the Matrix Attachment Regions (MARs). NuMat relates to multiple nuclear processes and is partly cell type specific in composition. It is a biochemically defined structure and several protocols have been used to isolate the NuMat where some of the steps have been critically evaluated. These sequences play an important role in genomic organization it is imperative to know their dynamics during development and differentiation. Results Here we look into the dynamics of MARs when the preparation process is varied and during embryonic development of D. melanogaster. A subset of MARs termed as “Core-MARs” present abundantly in pericentromeric heterochromatin, are constant unalterable anchor points as they associate with NuMat through embryonic development and are independent of the isolation procedure. Euchromatic MARs are dynamic and reflect the transcriptomic profile of the cell. New MARs are generated by nuclear stabilization, and during development, mostly at paused RNA polymerase II promoters. Paused Pol II MARs depend on RNA transcripts for NuMat association. Conclusions Our data reveals the role of MARs in functionally dynamic nucleus and contributes to the current understanding of nuclear architecture in genomic context.

We analyze the interaction between an interplanetary coronal mass ejection (ICME) detected in situ at the L1 Lagrange point on 2016 October 12 with a trailing high-speed stream (HSS). We aim to estimate the region in the interplanetary (IP) space where the interaction happened/started using a combined observational-modeling approach. We use minimum variance analysis (MVA) and the Walen test to analyze possible reconnection exhaust at the interface of ICME and HSS. We perform a graduated cylindrical shell reconstruction of the CME to estimate the geometry and source location of the CME. Finally, we use a two-step drag-based model (DBM) model to estimate the region in IP space where the interaction took place. The magnetic obstacle observed in situ shows a fairly symmetric and undisturbed structure and shows the magnetic flux, helicity, and expansion profile/speed of a typical ICME. The MVA together with the Walen test, however, confirms reconnection exhaust at the ICME–HSS boundary. Thus, in situ signatures are in favor of a scenario where the interaction is fairly recent. The trailing HSS shows a distinct velocity profile which first reaches a semi-saturated plateau with an average velocity of 500 km s ^−1 and then saturates at a maximum speed of 710 km s ^−1 . We find that the HSS's interaction with the ICME is influenced only by this initial plateau. The results of the two-step DBM suggest that the ICME has started interacting with the HSS close to Earth (∼0.81 au), which compares well with the deductions from in situ signatures.

Preterm babies have immature immunity and skin barrier functions. To cope up with these, many times they are kept under observation in neonatal care unit (NICU) for months until they attain their normal physiological age, weight, and immune functions along with other vital capacities. We are reporting such a curious case of 1-month-old preterm child who presented with the sequence of blackish blue to yellowish discoloration of thumb nails in both the hands.

An efficient resampling reliability approach was developed to consider the effect of statistical uncertainties in input properties arising due to insufficient data when estimating the reliability of rock slopes and tunnels. This approach considers the effect of uncertainties in both distribution parameters (mean and standard deviation) and types of input properties. Further, the approach was generalized to make it capable of analyzing complex problems with explicit/implicit performance functions (PFs), single/multiple PFs, and correlated/non-correlated input properties. It couples resampling statistical tool, i.e. jackknife, with advanced reliability tools like Latin hypercube sampling (LHS), Sobol's global sensitivity, moving least square-response surface method (MLS-RSM), and Nataf's transformation. The developed approach was demonstrated for four cases encompassing different types. Results were compared with a recently developed bootstrap-based resampling reliability approach. The results show that the approach is accurate and significantly efficient compared with the bootstrap-based approach. The proposed approach reflects the effect of statistical uncertainties of input properties by estimating distributions/confidence intervals of reliability index/probability of failure(s) instead of their fixed-point estimates. Further, sufficiently accurate results were obtained by considering uncertainties in distribution parameters only and ignoring those in distribution types.

The study was conducted to evaluate clinical effect of working length and rod size for plate rod fixation of diaphyseal femoral fracture repair in dogs. Twenty four dogs with femur fracture were randomly divided into four Groups viz. A, B, C and D having six animals in each group. Three bicortical screws in proximal and three in distal fragments with minimum two empty holes at the center were fixed for short plate working length (SPWL) in Groups A and B with intramedullary rod (IMR) occupying 30% and 40% of medullary canal, respectively. Two bicortical screws in proximal and two in distal fragments were fixed with minimum four empty holes at the center for long plate working length (LPWL) in Groups C and D with IMR occupying 30% and 40% of medullary canal, respectively. Fracture healing progress in all the Groups was assessed using clinical, photographic and radiographic observations. All the Groups showed good functional, radiographic outcome at the end of 14 week post-surgery. The time taken to show complete mobility and weight bearing was non-significantly less in Groups A and B. The functional, radiographic and outcomes of repair were excellent in Groups A and B without any major complications. Short plate working length with IMR occupying 40% of medullary canal of plate rod fixation provided comparatively better stability with fewer complications for femoral fracture repair in dogs.

Abstract The increasing level of atmospheric carbon dioxide (CO2), and the resultant global warming is a matter of growing concern among scientists, environmentalists, and climate experts across the globe over the past several decades. Numerous attempts are being undertaken today that seek solutions to mitigate this global crisis. This includes designing functional catalysts, devices and reactors to convert greenhouse gasses such as CO2 into useful products like low‐carbon fuels and chemicals, thereby reducing the amount of CO2 considerably in the atmosphere. Advancements in emerging technologies like 3D‐printing can effectively aid in the fabrication of electrodes and devices to tackle the rising CO2 concerns. Low cost, rapid prototyping ability, and printing simple and complex structure are few of the significant merits of this technology. Thus, in this perspective article, discussions on fabricating 3D‐printed (electro)catalysts, customized devices, reactors, etc., via multiple strategies are put forward with emphasis on the electrochemical reduction of CO2. Also, a detailed discussion on the post‐printing treatments, catalyst modifications, and other CO2 mitigation strategies is provided as well. Although studies in this direction are scarcely reported, observations made hitherto show promising possibilities of broadening this field for large scale CO2 reduction reaction applications, and similar catalytic applications in the near future.

This study was executed in the clinical setup to investigate the effects of Rocuronium and its reversal by Neostigmine and Glycopyrrolate (Myopyrolate) combination in Propofol-Isoflurane anaesthetized dogs. Rocuronium-induced neuromuscular blockade was applied to 21 clinical cases. Out of which, 19 cases were of orthopaedic surgeries and 2 cases of ovariohysterectomy. After the animal had stabilized on the mixture of isoflurane and oxygen, the relaxation of muscle was induced using Rocuronium @ 0.5 mg/kg b.wt. Immediately IPPV was provided in volume control mode. Neuromuscular blockade was reversed using a single syringe combination drug having both Neostigmine and Glycopyrrolate (Myopyrolate) @ 0.05 mg/kg b.wt and @ 0.01 mg/kg b.wt, respectively. Rocuronium caused the centering of the ocular globe gradually in less than 30 sec. During orthopaedic surgeries, the reduction of fractured ends became easy without much tissue trauma. In ovariohysterectomy surgeries, the appropriate level of abdominal muscle relaxation further helped in the easy exteriorization of the ovarian stump. The onset time for Rocuronium was 17.64±1.10 sec and its duration of action was 27.82±0.72 min. The use of Rocuronium along with IPPV caused minimal alteration of the physiological parameters with no clinical consequences and thus can be considered a complication-free anaesthetic protocol for interventions demanding muscle relaxation.

BN50/NiO50 and Au-loaded BN50/NiO50 nanocomposite films were separately fabricated on the glass substrates for carrier transport and photoconductivity properties. X-ray diffraction pattern of the films show the hexagonal structure of BN and presence of defect states by Nelson Riley factor analysis. Morphological images show spherical shaped particles with highly porous structure. The incorporation of NiO may hindered growth of BN layers and resulted in spherical particles. Temperature-dependent conductivity describes semiconductor transport behaviour for deposited nanocomposite films. Thermal activation conduction with low activation energy (∼0.308 eV) may be responsible for the resulting conductivity. Further, the light intensity dependent photoelectrical properties of BN50/NiO50 and Au-loaded BN50/NiO50 nanocomposites have been explored. The effect of Au nanoparticles loading on enhanced photo-conductivities (∼22% increase) than bare nanocomposite film has been elaborated by proposed mechanism. This study provided the insightful information for carrier transport and photoconductivity of BN-based nanocomposites.