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Despite various studies addressing the retention of α phase in thermal sprayed alumina coatings, a noticeable research gap persists regarding the impact of feedstock morphology on phase retention and properties. In this work, we explored this simple way to enhance the retention of the α phase and studied its impact on mechanical and dielectric properties. To achieve this, we deposited alumina powders with two different morphologies (such as angular and spherical) with similar particle size using plasma spraying. After deposition, we quantified the retention of α phase present in the coatings using the Rietveld refinement method. From this analysis, we noticed that spherical morphology (SM) powder exhibited the highest percentage of α phase retention (82.81 %) as compared to angular morphology (AM) powder (48.8 %). In turn, SM-coating demonstrated superior mechanical properties, with improvements in hardness, elastic modulus and fracture toughness of 21.9 % 13.7 % and 25 % respectively, compared to AM-coating. This improved mechanical properties in SM-coating is attributed to high α phase retention, synergistic effect of both fully melted (FM) and partial melted (PM) regions of coating microstructure which hindered the crack propagation. Furthermore, the SM-coating exhibited superior dielectric properties, with a dielectric strength 9.9 % higher than the AM-coating. This dielectric performance is ascribed to high retained α phase and generation of discontinuous crack due to presence of PM regions in the SM-coating. These findings suggest the impact of feedstock powder morphology on coating performance and offer avenues for optimizing coating processes in diverse technological fields. [ABSTRACT FROM AUTHOR]

Domination in graphs and coloring of graphs are two main areas of investigation in graph theory. Power domination is a variant of domination in graphs introduced in the study of the problem of monitoring an electric power system. Based on the notions of power domination and coloring of a graph, the concept of power dominator coloring of a graph was introduced. The minimum number of colors required for power dominator coloring of a graph G is called the power dominator chromatic number χpd(G) of G, which has been computed for some classes of graphs. Here we compute the power dominator chromatic number for splitting graphs of certain classes of graphs. [ABSTRACT FROM AUTHOR]

Nanocomposites containing mixed transition metal oxides demonstrate significant promise as materials for supercapacitors, specifically due to their enhanced surface area, synergistic effect of multiple metal cations, excellent electrical conductivity, and improved electrochemical properties. In this study, we synthesized a nanocomposite with a nanograss array morphology consisting of SnO 2 /CoFe 2 O 4 /Fe 3 O 4 using an in-situ sol-gel method. For comparison, we synthesized a composite (CoFe 2 O 4 /Fe 3 O 4) without SnO 2. Through a systematic characterization employing various analytical techniques, we examined the structural, morphological, and textural attributes of the resulting composites. The results reveal that the phase percentages of CoFe 2 O 4 , SnO 2 , and Fe 3 O 4 were 38%, 33%, and 29% in the SnO 2 /CoFe 2 O 4 /Fe 3 O 4 composite. Also, the nanograss array of SnO 2 /CoFe 2 O 4 /Fe 3 O 4 is composed of nano-sized primary particles, while CoFe 2 O 4 /Fe 3 O 4 showed spherical-like nanoparticle morphology. The BET surface area of the SnO 2 /CoFe 2 O 4 /Fe 3 O 4 composite was found to be seven times higher than that of CoFe 2 O 4 /Fe 3 O 4. We also evaluated the electrochemical performance of the SnO 2 /CoFe 2 O 4 /Fe 3 O 4 composite as a cathode material for battery-type supercapacitors. The synergistic combination of SnO 2 and CoFe 2 O 4 /Fe 3 O 4 in the SnO 2 /CoFe 2 O 4 /Fe 3 O 4 electrode resulted in a high specific capacity of 465C g−1 at 1 A g−1, which is 2.5 times higher than the CoFe 2 O 4 /Fe 3 O 4 electrode. Additionally, the SnO 2 /CoFe 2 O 4 /Fe 3 O 4 electrode exhibited a remarkable rate capability of 87% at 10 A g−1 and excellent cyclic performance with 96% capacity retention after 5000 cycles. A hybrid supercapacitor was fabricated, featuring a cathode composed of a composite electrode consisting of SnO 2 /CoFe 2 O 4 /Fe 3 O 4 and an anode comprising activated carbon (AC). This fabricated SnO 2 /CoFe 2 O 4 /Fe 3 O 4 //AC HSC device configuration exhibited impressive performance characteristics, boasting a notable energy density of 38.4 Wh kg−1 at 1468.2 W kg−1. These findings underscore the significant impact of SnO 2 on the physio/electrochemical properties of the CoFe 2 O 4 /Fe 3 O 4 composite. The outstanding electrochemical performance of this electrode underscores its potential for application in next-generation hybrid supercapacitors. [ABSTRACT FROM AUTHOR]

Chicken nuggets prepared by incorporating three different levels of brown rice flour along with other non-meat ingredients. The formulations prepared were -- Control (0% brown rice flour), T1 (2% brown rice flour), T2 (4% Brown rice flour), T3 (6% Brown rice flour). Among different treatments, brown rice flour at 6% produced significantly (P<0.05) higher emulsion stability, water holding capacity, pH and better sensory scores than rest of the formulations. Proximate composition of the study revealed significant (P<0.05) increase in moisture, protein, fiber and ash content. The texture profile analysis studies revealed a significant (P<0.05) increase in some parameters, which are gumminess, springiness and cohesiveness. The microbiological studies revealed that products were acceptable up to 9 days. Based on the results obtained in the study it might be concluded that chicken nuggets could be prepared satisfactorily on addition up to 6% brown rice flour without adverse effect on the quality of the products. [ABSTRACT FROM AUTHOR]

Background: Congenital anomalies in dogs are the defects present at birth and often lead to perinatal death if it involves any vital organ or system like cardiovascular system. Some dogs may remain asymptomatic or may have non cardiac manifestations and hence, undetected until later in life, so the percentage of dogs with congenital heart diseases that survive to adulthood can be rather high. Atrial septal defect (ASD) is an unusual congenital heart disease in dogs that is characterized by communication between the two atria due to a defect in the interatrial septum. Methods: A thorough clinical examination followed by physical examination, thoracic radiography and 2d-echocardiography was performed to determine the septal defect. Doppler evaluation of ASD dogs was carried out to confirm the blood flow direction through the septal defect, which was managed medically. Result: In the present study, ASD (secundum type) was diagnosed in 7dogs (7.5%) aged between 2y-6y. Boxer, German shepherd, Cocker spaniel, Daschund and Pomeranian were the breeds affected. Soft systolic murmur on left heart base and pulmonic valve area, low intensity heart sounds, distended jugular vein, jugular pulse and ascites were the significant findings on physical examination. Though few dogs (21%) were asymptomatic, exercise intolerance, dyspnoea, general weakness, cough and syncope were the presenting signs among other cases. Enlarged right heart, pleural effusion and pulmonary overcirculation were radiographic findings. 2d-echocardiographic evaluation determined the presence of the defect as a loss of echogenicity at the interatrial septum and presence of interatrial communication of varied size, enlargement of main pulmonary artery and thick atrio-ventricular valves but with normal left atrium:aorta base ratio, increased fractional shortening, systolic function and paradoxal septal motion. The colour flow Doppler study demonstrated a continuous flow with left-to-right shunt. [ABSTRACT FROM AUTHOR]

The Akshara Deepam (The Light of Letters) project, a collaborative endeavour between Choornikkara Panchayat Library, Kerala State Literacy Mission and Kudumbashree Mission, represents a pioneering model for community literacy and empowerment, with a strong focus on women's participation and empowerment. Initiated in May 2023, this innovative initiative aims to integrate literacy applications into daily life by delivering curated book kits to 720 households through 60 Kudumbashree Neighbourhood Groups, empowering women volunteers to combat poverty through literacy. Recognising its transformative potential, Rajagiri College of Social Sciences (RCSS) plans to integrate academic expertise into the project through a forthcoming MOU with Choornikkara Panchayat. Post-MOU, RCSS envisions a comprehensive approach, drawing from successful experiences, to integrate academic expertise into community engagement initiatives, particularly emphasising enhancing women's empowerment through literacy. To maximise impact, the Akshara Deepam project incorporates perception-level surveys, literacy practices and contributions from various RCSS departments. It provides diverse book collections tailored to the evolving needs of digital library usage. As an opportune intervention in changing literacy paradigms, RCSS intends to assess its efficacy and feasibility for rural replication in light of its initial results. This approach blends theory, community actions and academic involvement, empowering women and enriching communities globally. [ABSTRACT FROM AUTHOR]

The global pandemic of coronavirus disease 2019 (COVID-19) causes severe respiratory problems in humans. The Chest X-ray (CXR) imaging technique majorly assists in detecting abnormalities in the chest and lung areas caused by COVID-19. Hence, developing an automatic system for CXR-based COVID-19 detection is vital for disease diagnosis. To accomplish this requirement, an enhanced Residual Network (ResNet) model is proposed in this paper for accurate COVID-19 detection. The proposed model combines the Depthwise Separable Convolutional ResNet and Pyramid dilated module(DSC-ResNet-PDM) for deep feature extraction. Employing the DSC layer minimizes the number of parameters to mitigate the overfitting issue. Further, the pyramid dilated module is used for extracting multi-scale features. The extracted features are finally fed into the optimized Medium Gaussian kernel Support Vector Machine classifier (MGKSVM) for COVID-19 detection. The proposed model attained an accuracy of 99.5%, which is comparatively higher than the standard ResNet50 and ResNet101 models. [ABSTRACT FROM AUTHOR]

AbstractAddressing the need for sustainable construction materials that minimize environmental impact and reduce CO2 emissions, particularly in OPC compositions. Assessing alccofine and metakaolin in OPC compositions to determine their impact on concrete strength, durability, and microstructure in alkaline environments for sustainable material development. Experimental investigation involved incorporating alccofine and metakaolin into OPC concrete mixes, creating binary and ternary blended systems. Modified concrete specimens were subjected to various alkaline attacks using diluted solutions of magnesium sulfate (MgSO4), sodium sulfate (Na2SO4), and sodium chloride (NaCl) both individually (5%) and in combination (2.5%), resulting in significant improvements in concrete strength and durability. The modified concrete exhibits enhanced resistance to alkaline attacks, reduced weight and compression strength loss, and superior performance in Base Durability Factor (BDF) and Base Attack Factor (BAF) compared to conventional specimens. Scanning electron microscopy (SEM) study of the altered concrete’s microstructure shows that it has a densely packed microstructure, which increases its load-bearing capability. Mineral admixtures aid pore clogging, leading to denser, more alkali-resistant concrete due to finer particles. Notably, Alccofine and metakaolin offer effective solutions for sustainable construction materials, aiding in the decrease of CO2 releases during cement production and addressing critical gaps in sustainable material development. [ABSTRACT FROM AUTHOR]

Security is vital issues to be communicated for execution of e-healthcare scheme. Till now data hiding has most powerful instrument that can handle previous challenges. Reversible data hiding (RDH) planned to embed secret message in cover image at receiving end, both secret message and original cover image is recovered. Previous RDH methods designed for higher embedding rate. In this work, Deep Neural Rhombus Histogram based Dual Reversible Data Hiding (DNRH-DRDH) is proposed method for addressing both embedding rate as well as visual quality. It utilizes interpolated images reversible data hiding with Block Truncated Rhombus Prediction. Prediction error histogram generated embedded with secret data for obtaining stego images of corresponding interpolated pixels. Lastly, classification output is generated by ReLU activation function in extracted part for secured communication among users. Simulation carried on medical test images. Study reveals of proposed method gives higher embedding rate with superior image quality than existing methods. [ABSTRACT FROM AUTHOR]

The internet is the greatest innovation of this era. The innovation of the internet has revolutionized the planet entirely by bringing the people and machines closer to each other than ever. The recent development in computing and networking technologies brings the next generation of internet which is called as Internet of Things (IoT). As the industrialization and the population are increasing the movement of people towards urbanization is also increasing. Therefore, cities are converting up into smart cities that can be accomplished with the service of the IoT. Water is one of the crucial resources for the existence of human life, so efficient supervision of water systems plays a significant role in smart cities. This paper uses three different modules of smart water management in context to smart cities. In this work three different sensors such as water flow sensor, water temperature sensor, and ultrasonic sensors are used to monitor water consumption. These sensors are interfaced with microcontrollers such as Raspberry Pi and NodeMCU. The sensors data can be observed on the Thing speak cloud server. This system helps in monitoring the leakage of water as well as to control the unnecessary use of water. Also, this module provides data in real-time for each user and that data can be used for monthly billing of water usage. Hence, the consumer will have to pay for the amount of water he/she can use only. Therefore, this model will allow the users to manage the water consumption efficiently. [ABSTRACT FROM AUTHOR]

Primary pediatric lung tumors are uncommon and have many overlapping clinical and imaging features. In contrast to adult lung tumors, these rare pediatric neoplasms have a relatively broad histologic spectrum. Informed by a single-institution 13-year retrospective record review, we present an overview of the most common primary pediatric lung neoplasms, with a focus on the role of positron emission tomography (PET), specifically 18F-fluorodeoxyglucose (FDG) PET and 68Ga-DOTATATE PET, in the management of primary pediatric lung tumors. In addition to characteristic conventional radiographic and cross-sectional imaging findings, knowledge of patient age, underlying cancer predisposition syndromes, and PET imaging features may help narrow the differential. While metastases from other primary malignancies remain the most commonly encountered pediatric lung malignancy, the examples presented in this pictorial essay highlight many of the important conventional radiologic and PET imaging features of primary pediatric lung malignancies. [ABSTRACT FROM AUTHOR]

The assessment of performance is the key role factor for the gearboxes in the field of wind turbine industry. The thermal performance depends upon the viscous forces of the oil; bearing with stand capacity of the gearboxes and unnecessary irrotational forces or movements caused during the rotation of the gears at intermediate stage and high speed stage. The generation of the power starts from 15 m/s to 25 m/s with the starting rpm of 15 rpm to 1150 rpm; from initial stage to high speed stage of the gearbox. Hence the reduction of torque at higher revolutions may tends to complete reduction in power; owing to the thermal performance drop occurred due to the reduction of oil viscosities; improper maintenance during the high load conditions. This may lead to cause higher maintenance costs for the investors who is coming in front to invest huge amount of money. This present experimental work deals with latest sensors utilization to analyse the data from master gear box to slave gear box. From the results it is observed that the implementation of latest technology sensors tends to improves the maintanence costs by 20% as compared to conventional sensors. Hence it is adviced to implement the latest technology sensors which is capable to measure the wind speed loads of 20 m/s to 45 m/s. This gives range of resolution for downloading the past data and predicting the futurized data for evaluating the thermal performance drop; leads to save the maintanence costs 20% as compared to conventional methods. [ABSTRACT FROM AUTHOR]

About half of hip fractures in the elderly are caused by intertrochanteric fractures, of which more than 50% are unstable. Restoring mobility safely, effectively, and as close to the patient's pre-operative state as possible are the main objectives of treatment for any intertrochanteric fracture. Over the past 20 years, the dynamic hip screw (DHS) has become widely accepted and is now the gold standard for outcome comparison. Recently, proximal femoral nailing (PFN) is the intramedullary device that has frequently been claimed to have helped with these fractures, hence reducing the lever arm aspect on the implant. The Objectives of the present study is to compare the functional outcomes between dynamic hip screw versus proximal femoral nailing for the treatment of inter-trochanteric fractures of hip. Methods: The present study was conducted in the department of orthopedics, the study included a total of 80 patients presented with hip fractures based on inclusion and exclusion criteria after taking informed consent. These patients were randomized by simple random sampling into two groups DHS and PFN group. The functional outcomes using HHS was compared between the two groups at 6th, 12th and 24 weeks respectively. Results: The comparison of mean scores between DHS and PFN group at 6th, 12th and 24 week followup shows that the mean scores were statistically significantly better in PFN group at 12 weeks and 24 weeks, there was no significant differences found between the two groups at 6th week, as presented in Table 3. The functional outcomes were evaluated between the two groups, it is found that 12 (30%), 18 (45%), 8 (20%) and 2 (5%) patients had Excellent, Good, Fair and Poor outcomes in DHS group, whereas in PFN group 17 (42.5%), 19 (47.5%), and 4 (10%) patients had Excellent, Good and Fair outcomes in PFN group and none of them had poor outcome in PFN group as represented in Table 4. Discussion and conclusion: It can be inferred from the study that PFN performed better in intertrochanteric fractures than DHS fixation, based on the functional outcome determined by the Harris Hip Score. This was determined by looking at the end result, movement range, and HHS. Comparing the PFN group to the DHS group, the PFN group's subjects had a higher percentage of excellent to good results, and none of them had poor results. At 12 weeks, 24 weeks, and the Conclusion: of the follow-up, the PFN group's HHS scores were higher. With fewer complications, PFN offers a quicker recovery and a better functional outcome for all kinds of intertrochanteric fractures. [ABSTRACT FROM AUTHOR]

Automatic voice pathology detection enables an objective assessment of pathologies that influence the voice production strategy. By utilizing the conventional pipeline model as well as the modern deep learning-centric end-to-end methodology, numerous pathological voice analyzing techniques have been developed. The conventional methodology is still a valid choice owing to the lack of enormous amounts of training data in the study region of pathological voice. In the meantime, obtaining higher precision, higher accuracy, and stability is still a complicated task. Therefore, by amalgamating the nonlinear measure, the pathological voices are analyzed to abate such risks. The viability of six nonlinear discriminating measures derived from the phase space realm, involving healthy and pathological voice signals, is studied in this work. The analyzed parameters are Singularity spectrum coefficients ( α min , α max , γ 1 and γ 2 ). Correlation entropy at optimum embedding dimension ( K 2 m ) and correlation dimension at optimum embedding dimension ( D 2 m ). Analyzing the pathological voices with better accuracy rates is the major objective of the proposed methodology. Here, the Support Vector Machine (SVM) was utilized as the classifier. Experimentations were performed on VOiceICarfEDerico (VOICED) databases subsuming 208 healthy, as well as pathological voices, amongst these 50 samples, were utilized. Here, the model obtained 97% of accuracy with 99% as of the classifier with Gaussian kernel function. Therefore, to differentiate normal as well as pathological subjects, the six proposed characteristics are highly beneficial; in addition, they will be supportive in pathology diagnosis. [ABSTRACT FROM AUTHOR]

Sequential recommendation involves suggesting subsequent items in a series of user activities. When recommending relevant items to users within the same account, the challenge lies in discerning diverse user behaviours to provide tailored recommendations based on individual preferences and timing. Cross‐domain sequential recommendation (CDSR) focuses on accurately extracting cross‐domain user preferences from both within‐sequence and between‐sequence interactions among items. Current approaches typically concentrate on learning preferences within a single domain using intra‐sequence item interactions, followed by a transfer module for cross‐domain preferences. However, this sequential process and implicit method are constrained by the effectiveness of the transfer module and may overlook inter‐sequence item associations. In this study, we propose an optimal cluster with attention‐based shared‐account cross‐domain sequential recommendation (O‐SCSR) system using deep reinforcement learning techniques. Our approach commences by formulating a modified hummingbird optimization (MHO) algorithm for clustering, effectively identifying latent users who share the same account to enhance the understanding of user interactions within shared‐account scenarios. Additionally, we design a domain filter based on quantum classic deep reinforcement learning (QCDRL), intelligently selecting interactions contributing to O‐SCSR. By quantifying rewards from transferred domain knowledge, the QCDRL‐based filter retains only valuable interactions for the task of SCDR. Finally, we validate the efficacy of our proposed O‐SCDR method using real‐world datasets, namely HVIDEO and HAMAZON. Through simulation results comparing the O‐SCDR system with existing state‐of‐the‐art systems, we demonstrate its effectiveness and legitimacy. [ABSTRACT FROM AUTHOR]

Background: The physiological and psychological distinctions between children and adults pose challenges for pediatric anesthesia. The backbone of pediatric surgeries has always been general anesthesia; however, toxic consequences, especially in younger children, have prompted a reevaluation of anesthetic procedures. This concern has led to research into alternatives such as regional and neuraxial procedures. The purpose of the study is to investigate how various anaesthetic techniques affect paediatric outcomes. Material and Methods: This is prospective observational research with 120 paediatric patients having surgery that is elective. Patients who underwent general, regional, neuraxial, anaesthetic procedures were divided into 3 groups. Data on demographics, intraoperative parameters, and postoperative results gathered and analysed. Results: A total of 120 study participants were chosen for the study in order to investigate the effects of different anaesthetic techniques. Patients in Group B (regional anaesthesia) experienced 25% less postoperative pain than those in Group A (general anaesthesia) (p < 0.05). On the other hand, Group A saw a 20% greater incidence of emerging delirium than Group B (p < 0.05). Group C (neuraxial procedures) and Group A did not show statistically significant differences in postoperative pain evaluations. Instead, the scores were determined to be similar. Conclusion: Our study unfolds the importance of assessing different anaesthetic procedures in paediatric surgery. While general anaesthesia was associated with a higher incidence of emerging delirium, regional anaesthesia demonstrated improved pain control. Postoperative pain results from neuraxial surgeries were similar to those from general anaesthesia. In order to maximize patient care and outcomes, our data highlight the significance of personalized anaesthetic techniques in paediatric surgery. [ABSTRACT FROM AUTHOR]

Background: Suspected cases of pediatric abuse often involve the administration of anaesthetic drugs, posing significant risks to the well-being of affected children. Understanding the patterns and clinical implications of anaesthetic drug usage in such cases is crucial for effective detection and intervention. This study aimed to analyze the prevalence, types, dosage patterns, clinical presentations, and forensic implications of anaesthetic drug usage in suspected cases of pediatric abuse. Material and Methods: A comprehensive observational study was conducted, involving the analysis of 100 suspected cases of pediatric abuse. Anaesthetic drug usage was meticulously examined, and data were collected regarding the types of drugs administered, dosage patterns, clinical presentations, and forensic implications. Results: Among the suspected cases, 65% exhibited evidence of anaesthetic drug usage, with Propofol being the most prevalent (40%), followed by Ketamine (30%) and Benzodiazepines (20%). High dosage administration was observed in 25% of cases, while 15% involved low dosage administration. Respiratory depression (60%) and CNS depression (45%) were the most common clinical presentations associated with anaesthetic drug usage. Additionally, 45% of cases involved the simultaneous administration of multiple anaesthetic drugs. Forensically, the identification of specific anaesthetic drugs and their dosage patterns served as crucial evidence in cases of suspected pediatric abuse. Conclusion: Anaesthetic drug usage is prevalent in suspected cases of pediatric abuse, with significant clinical and forensic implications. Our findings underscore the importance of vigilance among healthcare providers and the implementation of robust child protection measures to detect and intervene in cases involving anaesthetic drugs. Enhanced awareness and understanding of these patterns are essential for safeguarding the well-being of vulnerable children. [ABSTRACT FROM AUTHOR]

Objectives: Globally, stroke is known to be one of the major health problems, resulting in disability among an aging population. Rehabilitation is a process of re-learning of skills, lost due to brain injury. Many factors influence motor learning post neurological insult and practice is one of the key factors which influence relearning or reacquisition of lost motor skills. Practice can be varied concerning order (blocked or random), scheduling (massed or distributed), or whole and part practice. The study observed the effect of variations in practice schedules on motor and functional recovery. Materials and Methods: Thirty-two acute stroke subjects were recruited and equally divided into two groups (16 in massed and 16 in distributed). Both groups received an accelerated skill acquisition program (ASAP) for six sessions a week for 2 weeks. Pre- and post-outcome measures included stroke rehabilitation assessment of movement (STREAM) for motor recovery, modified Barthel index (MBI) for functional recovery, and brain-derived neurotrophic factor (BDNF) for neuroplasticity. Results: The median scores of participants in the massed practice group before the intervention, of STREAM total, MBI, and BDNF were 23.5, 19, and 0.65, respectively, whereas post values of STREAM total, MBI, and BDNF were 40.5, 60.5, and 0.75, respectively. The median scores of the distributed practice group of the pre-STREAM total, MBI, and BDNF were 23.5, 6.5, and 0.70, respectively, whereas the post-STREAM total, MBI, and BDNF were 41, 45.5, and 0.80, respectively. P-value was reported to be <0.05 while comparing pre- and post-values of STREAM, MBI, and BDNF within both intervention groups. The median change scores of STREAM, MBI, and BDNF reported P ≥ 0.05 when compared between the groups. Conclusion: Both the groups had significant recovery post-intervention designed based on ASAP, about impairment mitigation, pursuing skilled movement leading to significant functional gains. Appropriate timing along with optimal dosage became an active ingredient in functional recovery in acute stroke subjects. The distributed practice might have added effect of spacing, resulting in easier learning and accuracy of skills. The study reveals that distributed practice can be part of regular clinical practice to enhance functional recovery in acute stroke rehabilitation. [ABSTRACT FROM AUTHOR]

A growth of the uncontrollable cells in a body causes cancer, which is one among deadly diseases. It can be developed at any parts of human body that may comprise of numerous cellules. The most frequently occurring cancer type is referred to skin cancer that develops in uppermost layer of skin. Skin cancer is a hazardous type of cancer, which affects millions of peoples each year. Detection of skin cancer in earlier phases is challenging and highly expensive process. Thus, DeepSegNet + Fuzzy cognitive map (FCM) is devised newly for skin cancer segmentation and detection. Here, pre-processing of an input skin cancer image is carried out by adaptive bilateral filtering. The segmentation of skin cancer image is performed by DeepSegNet. However, DeepSegNet is formed by incorporating DeepJoint segmentation and SegNet. After that, image augmentation is conducted with segmented image, wherein few augmentation techniques are utilized. Then, features are extracted from augmented image, which includes texture features, statistical features, Local Neighborhood Difference Pattern (LNDP) and also, new feature termed discrete wavelet transform (DWT) based Local Directional Pattern (LDP). Finally, detection of skin cancer is done utilizing FCM, which showed perfect detection output in terms of skin cancer. Furthermore, DeepSegNet achieved maximal dice coefficient value of 0.920 whereas DeepSegNet + FCM attained maximal values of accuracy as 93.3%, NPV as 89.6%, PPV as 91.5%, sensitivity as 94% and specificity as 92.6%. [ABSTRACT FROM AUTHOR]

We investigate the sharp bound of certain coefficient functionals associated with a Hankel determinant of the second kind for the inverse function when f belongs to the class of starlike functions with respect to symmetric points. [ABSTRACT FROM AUTHOR]

Rice (Oryza sativa L.), a semi-aquatic crop cultivated in diverse environments from sea coasts to high altitudes, faces submergence issues impacting one-third of global cultivation. Effectively choosing superior offspring with a range of genetic traits is vital for improving yield stability, particularly in the development of submergence-tolerant varieties. This is accomplished by comprehending gene action through the generation mean analysis. This experimental material comprised six generations (P1, P2, F1, F2, B1, and B2) obtained from two rice crosses viz., ADT 45 x APD 19002 and CO 54 x APD 19002 involving three parents, examining twelve traits. In the cross ADT 45 x APD 19002, traits like days to fifty per cent flowering, plant height, number of productive tillers per plant, flag leaf width, total number of grains per panicle, number of filled grains per panicle, and single plant yield exhibited opposite signs of dominance (h) and dominance x dominance (l), indicating a prevalence of duplicate epistasis. Simultaneously, additive(d) and additive x additive(i) gene effects were displayed by days to fifty per cent flowering, total number of tillers per plant, panicle length, flag leaf width, total number of grains per panicle, and single plant yield. In cross CO 54 x APD 19002, traits such as days to fifty per cent flowering, plant height, flag leaf width, number of filled grains per panicle, spikelet fertility, and single plant yield suggested predominance of duplicate epistasis. Meanwhile, additive and additive x additive gene effects predominantly influenced the days to fifty per cent flowering, spikelet fertility, and single plant yield. These findings propose the potential for improvement through later-generation selection, emphasizing the integration of selection with screening for submergence tolerance to develop high-yielding submergence-tolerant varieties. [ABSTRACT FROM AUTHOR]

Introduction: Shoulder pain, ranking third among musculoskeletal issues, hampers diagnostics due to test limitations. The present study explores the potential of the Shoulder Symptom Modification Procedure (SSMP) as an intervention. Influential factors in physiotherapy outcomes, including kinesiophobia, are linked to shoulder pain. A knowledge gap remains on the impact of SSMP on pain and kinesiophobia in individuals with shoulder pain, contributing insights to musculoskeletal interventions. Aim: To investigate the effect of SSMP on pain and kinesiophobia in patients with shoulder pain. Materials and Methods: A single-blinded quasi-experimental study was conducted in the Department of Musculoskeletal Physiotherapy on 35 participants aged 40-60 years experiencing shoulder pain, recruited from R.V. College of Physiotherapy, Bengaluru, Karnataka, India, over a six month period from February 2022 to July 2022. Pain was measured using the Numerical Pain Rating Scale (NPRS), and kinesiophobia was measured with the Tampa Scale for Kinesiophobia (TSK). The researcher, blinded to pre- and post-test results of TSK-11 and NPRS, conducted a shoulder symptom modification assessment. The procedure's response-guided treatment was administered twice a week for three weeks, with each session lasting 30 minutes. Pre-assessment of TSK-11 and NPRS was performed by an assessor, with the same assessor re-evaluating outcomes after three weeks. Data underwent statistical analysis using a paired t-test in R Software version 4.1.0, with significance attributed to results having a p-value <0.05. Results: The mean age of the study participants was 52±7.74 years. There was a significant reduction in NPRS from 7.54±1.146 to 3.74±1.70 post-intervention and TSK-11 scores from 27.20±5.12 to 23.17±4.83 in subjects with shoulder pain after three weeks of intervention. The study showed a significant improvement in pain (p<0.001*) and kinesiophobia (p<0.001*) in patients with shoulder pain. Conclusion: The SSMP was found to be effective in reducing pain and kinesiophobia in patients with shoulder pain. Further research should be conducted in the future, taking large samples and varied techniques into account for the identification of optimal strategies in improving health-related outcomes. [ABSTRACT FROM AUTHOR]

This commentary comprises of three sections. The first section summarizes Sinha's perspective and approach to the development of Indian psychology. The second section provides a bird's eye view of a few major developments in the field of science in general and in psychology in particular. This section also elaborates on the need for developing Indian psychology (IP) not just for the Indian context but for its global relevance. The third section documents some of the developments that have taken place in India in the past six decades since the publication of Sinha's paper. [ABSTRACT FROM AUTHOR]

This article used an improved version of the Flow Direction Algorithm (FDA) with acceleration coefficients named Modified Flow Direction Algorithm (MFDA) for simultaneous Optimal Network Reconfiguration (ONR) and Optimal Distribution Generation's (ODG) installation to reduce the Active Power Losses (APL), maximize the Voltage Profile (VP) and stability of the Distribution System (DS). FDA is motivated by the simulation of the direction of water flow into a drainage basin at a lower elevation area. The neighboring flow and its slope also affect the direction of the water flow; its slope was obtained using the D8 method. FDA has a low convergence rate, stuck with local optima. This article proposed acceleration coefficients to acquire the proper balance between exploration and exploitation, accelerate the global convergence rate, and avoid getting stuck with local optima. The efficiency of the MFDA is evaluated based on its performance on 16 standard benchmark functions and is also used to solve the simultaneous ONR and ODG installation. Two DSs consisting of 33 and 69 bus test systems are considered to solve the problem. There are three methodologies to reduce the APL and maximize the VP and stability: ONR, ODG, and simultaneous ONR and ODG installation. This article uses four case studies with different load levels to show the proposed method's reliability. The analysis shows a better way to minimize the power loss by solving simultaneous ONR and ODG installation rather than only optimizing reconfiguration or installation of DG. It has been discovered that the results achieved are superior to those produced using the ISCA, FWA, HSA, etc. So, the MFDA shown can be a potentially useful way to solve 16 standard benchmark functions and simultaneous ONR and ODG installation. [ABSTRACT FROM AUTHOR]

Materials informatics (MI) is aimed to accelerate the materials discovery using computational intelligence and data science. Progress of MI depends on the strength of database and artificial intelligence protocols comprising machine learning (ML) and deep learning (DL) frameworks. Conventional ML models are simple and interpretable, relying on statistical techniques and algorithms to learn patterns and make predictions with limited data. Conversely, DL, an advancement of ML, employs mathematical neural networks to automatically extract features and handle intricate data at the cost of data size and computational complexity. This work aims to provide a state-of-the-art understanding of the tools, data sources and techniques used in MI and their benefits and challenges. We evaluate the growth of MI through its subfields and track the main path of its advancement for artificial intelligence-driven materials discovery. The advancements in computational intelligence via machine learning and deep learning algorithms in different fields of materials science are discussed. As a specific example, understanding of materials properties using microstructural images is reviewed. Future demands and research prospects in materials science utilizing materials informatics have also been comprehensively analyzed. [ABSTRACT FROM AUTHOR]

This study addresses challenges in road extraction from remote sensing imagery by introducing a novel approach leveraging Dilated Convolution-based layers and Vision Transformer (ViT). ViT extracts features from image patches, capturing relationships via self-attention and refining with a feedforward neural network. The model incorporates dilated convolution for an enlarged receptive field without increased parameters, enhancing road extraction. Fusion of Dilated Convolution-based layers with ViT forms feature representation, enabling the encoder-decoder architecture to predict roads pixel-wise. Experimental results on the DGR dataset showcase the approach’s high performance (F1 score: 98%, recall: 96.5%, specificity: 96.7%, accuracy: 98.8%, precision: 97.75%), demonstrating resilience across dataset sizes and geographical regions. This approach holds promise for real-world applications and future advancements in remote sensing research. [ABSTRACT FROM AUTHOR]

AbstractThis research looks at the flow of hybrid nanoparticles across a wedge-shaped surface. In addition to this, Brownian motion and thermal stratification are used to model how heat moves through a system. The mass expression also deals with the thermophoresis effect and mass stratification. The governing equations involve the continuity, momentum, energy, and mass equation of hybrid nanofluids that are modified into ODE's by applying similarity transformation. The solutions are obtained from two well-known numerical routines, RKF-45 and the profiles embodying f′(η),θ(η), and P(η) are interpreted under the influence of several physical parameters. The results showed that as the Prandtl number goes up, temperature profiles of fluid flow go down, and as Brownian motion factors go up, temperature profiles go up. It is found that the fluid’s thermal flow rate slows down as the Brownian motion and thermophoretic elements get stronger. On the other hand, the thermal flow rate of fluid goes up as the thermal stratification parameter goes up. [ABSTRACT FROM AUTHOR]

This work emphasizes the development and examination of a Hybrid Luo Converter integrated with a unified Maximum Power Point Tracking (MPPT) for both grid and independent hybrid systems. The primary objectives of this hybrid system are to efficiently harness power from intermittent and variable renewable sources while elevating low-voltage energy inputs to utility-grade levels. Unlike previous studies employing specific MPPT algorithms for solar and wind sources, this work aims to simplify the control system by utilizing a unified MPPT controller. This research also introduces a novel approach involving dual-lift hybrid Luo converters to create hybrid systems, operating exclusively or concurrently based on the availability of renewable resources. To maximize power generation from all renewable sources, a unified MPPT algorithm is developed. The hybrid system, incorporates 500 W wind and 560 W PV systems, the innovative Luo converter, and the unified MPPT controller. A comprehensive comparative analysis is presented, comparing the hybrid system's performance with that of traditional control algorithms, such as the Perturb & Observe, and Radial Basis Function Network controllers. The successful prototype of the converter validates the practicality of the proposed approach. [ABSTRACT FROM AUTHOR]

Artocarpus hirsutus Lam. is a tropical, endemic, keystone tree species of the Western Ghats commercially utilized for its valuable timber. The seeds are reported to be recalcitrant, but its exact physiology and the hormonal changes during development and germination has not been well studied. The present study was intended to understand the hormonal dynamics and their interaction to get an idea about the up and down regulation during seed development and germination. Fifteen hormones were simultaneously analyzed using LC MS/MS technique. Our results showed that during histodifferentiation IAA, GA4, cytokinins (tZ and tZR), JA and 24-epibrassinolide (24-epiBL) were found in higher levels, but during seed expansion all these plant hormones began to decrease. However salicylic acid and cis jasmone were found elevated during germination. Like other recalcitrant seeds ABA was found in higher level during early embryogeny but declined sharply in the later embryogeny and germination. JA showed strong positive correlation with IAA (0.997**), ABA (0.955*), tZ (0.997**) and tZR (0.975*) possibly acts as an inducer of all these hormones, but no significant relationship with other hormones. However SA, which was found in extremely higher level during development and germination, did not show any significant relationship with other hormones, possibly functioning in defense mechanism. 24-epiBL was found in significant level, but showed insignificant relationship with hormones. Natural desiccation had a negative impact on the synthesis/accumulation of PGRs. Electrical conductivity studies revealed that cell membrane damage of the embryonic tissue was responsible for the loss of viability of these recalcitrant seeds. [ABSTRACT FROM AUTHOR]

Background: Rice is the world's third most important food crop, particularly in Asia. Drought stress has varying degrees of impact on its production. New plant growth regulators have been studied in recent years as a way to overcome physiological limitations and increase productivity. Melatonin has been investigated for its potential advantages in boosting plant resistance to environmental stresses. In this study, the precise processes and functions of melatonin with respect to germination and early seedling establishment during drought were investigated. Methods: Rice seeds were subjected to different pretreatment of melatonin (0, 50, 100, 150, 200 and 250 µM) prior to experiencing drought stress characterized by a water potential of -0.4 MPa. Germination and physiological traits, including germination speed, shoot length, root length, promptness index, vigor index, stress index, fresh and dry weight were assessed. Result: These findings demonstrated that pretreatment of melatonin effectively mitigated the detrimental impacts of drought stress by enhancing germination percentage, seedling growth and physiological traits. Among the various concentration, 200 µM of melatonin proved to be the ideal concentration that has the ability to improve rice seed germination, early seedling growth and minimize the negative consequences of drought stress. [ABSTRACT FROM AUTHOR]

Purpose: A study was carried out to understand the carbon sequestration potential of the coastal acid sulfate soils of wetland agroecosystems Kari and Kayal of Kuttanad, Kerala. Methods: Soil profiles excavated in these lands were studied for their physico-chemical and morphological properties and classified according to USDA based soil taxonomy. Results: The soils were very deep with moderately deep (97 cm) and moderately shallow (75 cm) solum thickness and both the soils were acidic,sulfuric and/or sulfidic and saline.The BaCl2 acidity,exchangeable Al,total exchangeable bases and cation exchange capacity were higher in Kari soils.Both the soils recorded high sulfate S,which was higher in Kari soils.Based on the USDA soil taxonomy, Kari soils were classified to ferrihumic, euic, isohyperthermic, Typic Sulfohemists and Kayal soils to loamy, mixed, super-active, isohyperthermic, Salidic Sulfaquepts at the family level. Conclusion: The organic carbon stock was higher in the sub-surface layer (30-100 cm) which recorded 2769.63 and 645.45 Mgha− 1 in Kari and Kayal lands respectively. The soil carbon sequestration potential was higher in Kari soils and the highest rate of C sequestration was at the depth 30–60 cm(656.09 kgm− 3) and soil layer was proved to have the capacity to hold 20.40 TgC with a total of 58.86 TgC in 11,250 ha of Kari lands for a thickness of 150 cm, while Kayal soils recorded the maximum at the depth 60-90 cm (163.43 kgm− 3) with a capacity to hold 3.29 TgC with a total of 21.02 TgC in 13,000 ha of Kayal lands for a thickness of 150 cm in 13,000 ha of Kayal lands. [ABSTRACT FROM AUTHOR]

Hydrogen has been identified as a clean and renewable energy source that has a significant potential to replace fossil fuels. The effective production of hydrogen on a commercial scale, however, presents a vital obstacle in today's world. Water splitting electrolysis, which offers high energy conversion and storage capabilities, has emerged as a promising approach for achieving the efficient hydrogen production to address this issue. This experimental research focuses on the production of hydrogen-oxygen gas through the electrolysis process. HHO gas provides promising benefits in terms of better combustion and lower emissions. Therefore, it also focuses on how best HHO gas can be utilized in diesel engines to improve the performance and to reduce the emissions. HHO gas produced at 60 L per hour through electrolysis process is mixed with air in a mixing chamber. Also, Palm munja methyl ester of 10% and diesel fuel of 90% was volumetrically blended to get B10 biodiesel. Therefore, totally four test fuels (Diesel, Diesel + HHO, B10, and B10 + HHO) were tested on a single-cylinder Kirloskar water-cooled direct injection diesel engine under different engine speeds ranging from 1447 to 1550 rpm. The engine injector pressure was varied from 200, 220, and 240 bar during the experiments with an interval of 20 bar. The engine has been modified for hydrogen and oxygen inlet at the entrance manifold 6 cm away at an angle of 30°. The results shows that at 200 bar injection pressure with B10 + HHO blend exhibits better performance and released lower emissions. The performance results also show that the brake thermal efficiency was improved up to 14.16%, and the brake power was increased by 3.22%, while the brake-specific fuel consumption is reduced by 11.53%. The emission results show that CO, HC, NOx, and CO 2 emissions were reduced by 20.87%, 11.47%, 1.96%, and 5.22%, respectively. Therefore, it can be concluded that B10 + HHO provides better performance and the lowest emissions compared with other blends. • Hydroxyl gas HHO gas was produced by the electrolysis process. • Produced HHO gas introduced to the diesel engine. • Performed the variation of injection pressure and engine loads. • Detailed discussion on the engine performance, and emission behaviours. [ABSTRACT FROM AUTHOR]

In the present study, a facile and simple hydrothermal technique was employed for the preparation of reduced graphene oxide (rGO) incorporated NiCo 2 S 4 and analyzed the hydrogen evolution reaction (HER) activity in alkaline media. The face centered cubic crystal structure is confirmed from the X-ray diffraction analysis and hexagonal cage like structure of NiCo 2 S 4 was visualized by FESEM analysis. With the increased number of facets in hexagonal cage structure, the electrochemical-active surface area (ECSA) gets increased, and the HER performance gets increased for bare NiCo 2 S 4. The additional ECSA is caused by the existence of rGO in the case of ternary nanocomposite (rGO-NiCo 2 S 4). The obtained small over potential (370 mV) and small Tafel slope (139 mV/dec) proves the excellent HER activity of rGO-NiCo 2 S 4 nanocomposite. The optimized rGO-NiCo 2 S 4 as excellent HER electrocatalyst provides a highly stable polarization curve up to 10 h and it can be more useful to replace the high-cost platinum noble electrocatalyst. [Display omitted] • A simple one step hydrothermal method was adopted to prepare pure and rGO incorporated NiCo 2 S 4. • A hexagonal cage like structure provides the large number of facet as well as high electrochemical-active surface area. • A small over potential of 370 mV and a small Tafel slope of 139 mV/dec was realized at 10 mA/cm2. [ABSTRACT FROM AUTHOR]

The power consumption of datacenters is multiplying, and several survey reports stated that the power consumption of datacenters will reach approximately 8000 TWh by 2030 if do not utilize cloud resources effectively. To use allocated cloud resources effectively, one of the prominent solutions is the VM consolidation technique. VM consolidation technique manages cloud resources effectively while simultaneously satisfying the objectives of cloud users and providers. Additionally, it helps to increase servers' performance while reducing the high power consumption of datacenters. However, unnecessary actions of VM consolidation technique cause unsuitable VM selection and inappropriate VM placement, which degrades resource management performance, poor QoS, and SLA violations. To overcome this issue, this paper proposed a resource, SLA, power-aware proactive VM consolidation technique by using an improved LSTM network to manage the allocated resources effectively. The proposed proactive VM consolidation technique helps reduce the high power consumption of datacenters while maximizing resource management performance and avoiding SLA violations. Finally, the authors measure the proposed methodology effectiveness by considering the benchmark dataset of NASA servers, and experimental results proved that an improved LSTM network can able to achieve an average accuracy rate of up to 94% with minimum prediction error rate. Proactive VM consolidation technique minimized nearly 30% of the power consumption of datacenters compared with conventional VM consolidation technique. [ABSTRACT FROM AUTHOR]