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Randomized Trials of Psychotherapeutic Treatment for Psychogenic Seizures: Scoping Review
Background: Psychotherapy improves seizure frequency and psychosocial aspects in psychogenic nonepileptic seizures (PNES). Although randomized controlled trials (RCTs) on different psychotherapies have been conducted for almost two decades now, no review has exclusively assessed RCTs of different psychotherapies. Methods: The objective was to review RCTs of psychotherapy for PNES, to understand the impact of different psychotherapies. Eligibility criteria included full-text articles, English articles, published between years 2000 and 2020, randomized trials of psychotherapy, and the adult population. Databases included PubMed, ProQuest, Google Scholar, ScienceDirect, EBSCO, PsycINFO, Cochrane, and a random google search was conducted. Rayyan software was used to include articles that met our eligibility criteria. The search was carried out independently by two researchers Results: Based on the eligibility criteria, seven studies were found. Amongst them, cognitive behavioral therapy (CBT) was the most researched and seemed more effective when paired with standard medical care (SMC) or sertraline. Comparisons of CBT and brief psychodynamic therapy did not reveal significant differences. Other psychotherapies included motivational interview+psychotherapy, which significantly reduced seizure frequency and improved psychosocial functioning. Paradoxical intention therapy also reduced PNES symptoms; however, it has not been researched in the last 15 years. Group psychoeducation seems to have an impact only on psychosocial functioning and not on seizure frequency. Conclusion: CBT paired with SMC or sertraline and MI along with psychotherapy yields the most effective results for PNES in reducing seizure frequency and improving psychosocial functioning. 2021 Indian Psychiatric Society - South Zonal Branch. -
Yoga Hand Mudra Classification using Zernike Moments
This study introduces a novel approach to classifying yoga hand mudras using Zernike Moments, emphasizing their relevance in balancing the Tridoshas - Vata, Pitta, and Kapha, as per Ayurvedic philosophy. A dataset of 1,200 images was collected from yoga practitioners in Bangalore, representing six mudras in both correct ("RIGHT") and incorrect ("WRONG") positions, ensuring a balanced distribution. Zernike Moments were used to extract rotation-invariant shape features from the images. However, due to their lack of scale invariance, Scale-Adaptive Zernike Moments (SAZM) were introduced by incorporating a scaling factor to normalize object size. Image preprocessing involved resizing, Gaussian blur for noise reduction, and normalization. Feature extraction was followed by labeling, scaling, and classification using a Support Vector Machine (SVM). Comparative analysis showed that standard Zernike Moments achieved an accuracy of 55.32%, serving as the baseline. In contrast, SAZM significantly improved classification accuracy to 71.01%, highlighting the importance of scale invariance in gesture recognition. This work demonstrates how computational techniques can complement traditional knowledge, offering a promising direction for yoga-based wellness solutions. While SAZM showed superior performance, future work will address challenges like complex transformations to enhance model accuracy and applicability. 2025 IEEE. -
Machine Learning Based Recession Prediction Analysis Using Gross Domestic Product (GDP)
This research article aims to explore the prediction and analysis of recessions, with a particular focus on Gross Domestic Product (GDP). The study examines the impact of recessions on different countries, namely India, USA, Germany, China, and Bangladesh, while also considering the influence of the COVID-19 pandemic on these nations in relation to the recessionary effects. Furthermore, the study lists many machine learning techniques that could be used to anticipate recessions. This research mainly focuses on predicting recession using different machine learning models. The research not only provides an in-depth analysis of the recessionary impacts on different economies but also serves as a foundation for future implementation of these algorithms for accurate recession prediction and proactive economic decision-making. This research study mainly focuses on machine learning algorithms like Random Forest, Support Vector Machines and Regression Model. The GDP prediction comparison is taking last twenty years data. This is mainly compared before and after COVID-19 situation. 2023 IEEE. -
Gender and Ethnicity Recognition System Based on Convolutional Neural Networks
The classification of Gender and Ethnicity has been utilized in diverse scenarios, specifically in the realm of human-computer interaction, visual surveillance, and electronic customer services. Predicting the gender and ethnicity of individuals presents a significant obstacle due to its complex characteristics. The escalating prevalence of social media has emphasized the utmost importance of independently predicting gender and race. In this research endeavor, a framework is utilized which utilizes a Convolutional Neural Network to forecast gender and ethnicity by utilizing various outputs starting from the initial stage. The models performance was evaluated using different metrics, including the F1-score, accuracy, precision, recall, and accuracy. The methodology is evaluated using the UTKFace dataset for predicting gender and ethnicity, and compared the model with previous study to understand which model is giving better accuracy. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Digital Thinking Skills to Develop Twenty-first Century Skills of the Students in ELT Classroom
The prominence of developing twenty-first century skills has become inevitable in this digitalized era. The pivotal components of twenty-first century skills are problem-solving, critical thinking, collaboration, communication and creativity. The enhancement of these skills is immensely associated with thinking skills. Accordingly, the chapter aims to discuss the significance of implementing digital thinking skills in ELT classroom for fostering students twenty-first century skills in the digital scenario. Additionally, the chapter suggests the use of digital tools and techniques say digital writing and blogging, digital storytelling, online discussion forums, and multimedia projects in the English language classroom through activity-based pedagogy that can facilitate students to enhance their twenty-first century skills. As a result, this will enhance the student engagement in the classroom and have a positive impact on their motivation. Eventually, the chapter concludes that the incorporation of digital thinking in the English language classroom that would enhance the students learning experience and guides them to acquire the necessary skills to attain competent digital literacy. The chapter highlights the importance of integrating digital thinking skills into classroom teaching to prepare the students to encounter the challenges of the future. 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
GST and its Impact on Small and Medium Scale Enterprises - A Study of Peenya Industrial Area in Banglaore, Karnataka
The introduction of Goods and Service Tax on 1st July, 2017 has revamped the tax structure and carved out a new path for the Indian economy. The new tax regime was envisioned to be free of all the problems of the previous tax system but, however since its proposal it has received mixed reviews from industries, academia and others. With extensive changes aimed at One Nation One Tax, it has left massive impact on the Small Scale Industries too. Hence this paper critically analyses the impact of Goods and Service Tax (GST) on Small Scale Industries specifically in Karnataka. Existing literature says that GST shall reduce the cost of doing business, increases transparency, decreases prices of product, increase tax compliance and improve ease of doing business. This paper proves some of these assertions through a primary data research and further identifies the need of reforms with respect to separation of definition of job work and labour work, penalties for non-payment of GST, dual administration and issues pending from the previous tax regime. It has also clearly established that composition scheme has been a non-performer and the reverse charge mechanism must be re-introduced later or revamped to balance its costs and benefits. Thus the study has implications for policy makers, industries and academia and also provides a better understanding of the new tax system itself. 2021 Lichchavi Harishekar et al., published by Sciendo 2021. -
Copper Nanoparticles: A Review on Synthesis, Characterization and Applications
An emerging field of science Nanotechnology which is involved in manipulation of atoms and molecules has shown great potential in all fields of sciences. Nanotechnology deals with nanoparticles ranging from size 1 to 100 nm in diameter, due to small size and high surface area eventually increases the state of activity. This review focuses on metal and metal oxide nanoparticles and mainly on green synthesis, characterization and application of copper nanoparticles. Green synthesis of copper and copper oxide (Cu and CuO) is economically beneficial and ecofriendly. Copper nanoparticles are used in diverse fields such as biomedicine, pharmaceuticals, bioremediation, molecular biology, bioengineering, genetic engineering, dye degradation, catalysis, cosmetics and textiles. Structural properties and biological effects of copper nanoparticles have promising effectivity in field of life sciences 2020. All rights reserved. -
Impact of hot rolling on the mechanical characteristics and microstructure of copper-based metal matrix composites reinforced with titanium carbide
Copper-based metal matrix composites reinforced with varying weight percentages (0, 2, 5, 7, and 10 wt%) of powdered titanium carbide (TiC) particles were successfully fabricated using stir casting, followed by hot rolling as a secondary processing route to enhance their mechanical performance. The microstructural evolution, phase characteristics, and mechanical behaviour of both as-cast and hot-rolled composites were systematically studied. Microstructural examination revealed a dendritic grain structure with non-uniform grain size distribution in as-cast composites, whereas hot-rolled composites exhibited a refined lath-shaped grain structure with uniform TiC particle distribution, attributed to the plastic deformation induced during rolling. XRD analysis confirmed the presence of high-intensity copper matrix peaks in hot-rolled composites and relatively stronger TiC peaks in as-cast composites due to the fragmentation of coarse reinforcement particles during rolling. Mechanical testing demonstrated that hot rolling significantly enhanced both hardness and tensile strength compared to the as-cast condition. The Brinell hardness of the hot-rolled Cu-10 wt% TiC composite reached 59.54 BHN, representing a 42.1% improvement over as-cast pure copper (41.9 BHN). Similarly, the ultimate tensile strength (UTS) of the hot-rolled Cu-10 wt% TiC composite achieved 182.5 MPa, corresponding to a 50.3% improvement over as-cast pure copper (121.4 MPa). However, ductility decreased progressively with increasing TiC content and hot rolling, from 71.56% in as-cast pure copper to 48.69% in hot-rolled Cu-10 wt% TiC, owing to strain hardening effects and grain boundary restriction by TiC particles. The optimal combined strength-ductility balance, assessed through the strain hardening parameter (UTS % elongation), was achieved at 5 wt% TiC reinforcement in both as-cast and hot-rolled conditions. Fractographic analysis revealed a progressive transition from ductile dimple fracture to mixed-mode and predominantly brittle fracture with increasing TiC content, consistent with the observed mechanical trends. 2026 The Authors. -
Digital transformation for business: Enablers, framework and challenges
Technology has disrupted many industries from the start of Industrialization era to the Industry 4.0 era. There has been an exponential growth in the technological front and people are talking about Industry 5.0. Digital transformation is a critical direction in which organizations will have to move toward in order to succeed in this competitive world. To make a smooth transition, firms must understand the basic building blocks of the digital transformation process and the key areas it touches upon namely customer experience, operational process and dynamic business models. Organizations will also have to identify the enablers of digital transformation which they can work on to smoothen the transformative process. Firms will also need the framework of digital transformation spelling out the roadmap for effective digital transformation. Firms on the urge to go for digital transformation will face numerous challenges in all the stages of implementation namely the initiation phase, the execution phase and the governance phase. A clear understanding of these challenges will help the firms to overcome or mitigate these challenges and be successful in their digital transformation process. 2023 by V. Harish, A. Mansurali and D. Krishnaveni. All rights reserved. -
Effect of face sheet on the flexural and tensile characteristics in GLARE laminates
The present study is carried out to study Glass Fibre Reinforced Aluminium Laminate (GLARE) structures and to evaluate their flexural and tensile properties. The GLARE specimens were fabricated using hand layup with vacuum bag moulding process wherein the aluminium sheets and E-Glass fibre woven mats of fixed thickness are bonded together by application of epoxy resins. Three different thicknesses of aluminium alloy (0.2 mm, 0.3 mm and 0.4 mm) Al-2024 T3 are used for the purpose of the study. The aluminium sheets are stacked together by application of epoxy resin between the sheets and are cured under a compression moulding machine under constant pressure. The overall thickness of the specimen is maintained constant for 2 mm. The samples were subjected to a three-point bending and tensile test as per ASTM D790 and ASTM D3039 standards, respectively, to evaluate their mechanical properties. The results indicate that the tensile strength of the composites is maximum for the specimen with aluminium 2024 T3 face sheet with a minimum thickness of 0.2 mm; however, with the increase in the thickness, the tensile strength is found to be decreasing. 2021 Engineers Australia. -
Experiment investigations of effect of laminate thickness on flexural properties of GLARE and GFRP laminates
The study focuses on the fabrication of Glass Fiber Reinforced Aluminum (GLARE) laminates and evaluation of their flexural properties. Aluminum 2024 (T3) sheets were used for the fabrication of GLARE laminates along with E-glass fiber in the form of chopped strand mat and epoxy resin. Different thickness of aluminum sheets ranging from 0.2 mm to 3.5 mm was used to fabricate the GLARE laminates. Hand layup technique is used to bond together aluminum sheets and epoxy/E-glass fiber laminates under different configurations. The test specimens were prepared as per ASTM standards, and standard three-point bending test was carried out to evaluate different bending characteristics. An increase of 60% in load-bearing capacity was observed when aluminum sheet thickness was an increase from 0.2 mm to 0.35 mm. Similar The results were compared with similar glass fiber reinforced plastic (GFRP) laminates to analyze improvements, whereas, the maximum deflection of the laminate decreased. There were not many improvements in case of bending strength and bending modulus when aluminum sheet thickness was varied. Fracture surface analysis indicated three modes of failure namely, interfacial delamination, delamination bonding, and fiber breakage. When compared with glass fiber reinforced plastics of similar configuration, a substantial increase in bending strength was observed. 2018 IOP Publishing Ltd. -
Stress analysis of the vertical tail skin joint and estimation of fatigue life due to fluctuating side loads
Vertical tail VT is one of the main components of the airframe. VT is attached with a rudder, which is the control surface, which is used for controlling the yawing motion of the aircraft. The deflection of the rudder introduces side load on the VT. Without rudder deflection, the aerodynamic load will not be applied to the VT. The load due to the deflection of the rudder is the major load for the VT. From a design point of view side, gust load is also important in transport aircraft. The present study is on a critical region with a riveted joint in the VT skin. A stiffened panel of the vertical tail with the spliced skin will be considered for the identification of the critical location. FEM will be used for the analysis of the component. In this study, loads of small transport aircraft will be considered. The maximum stress location and distribution of stresses on the stiffened panel are conducted by the FEM method. To obtain the mesh independent magnitude of stress, a refined local analysis is conducted. The tensile stresses on the skin are caused by the side loads of VT on the stiffened panel. Rivet holes are the stress concentration locations. The locations for fatigue crack initiation is the rivet holes. Fatigue damage estimation is calculated by the use of Miners rule. Fluctuating loads due to rudder deflection will be considered for damage calculation. SN data curve of the aluminium alloy material used for the VT skin will be considered for stress-based damage calculation. TJPRC Pvt. Ltd. -
A review on power quality issues in electric vehicle interfaced distribution system and mitigation techniques
Electric vehicles (EV) penetration in the distribution systems is evident and intended to grow day by day. Power quality issues pop up in the distribution system with an increase in EV penetration. Distribution networks need to consider the power quality issues developed due to the penetration of EVs for planning and designing the system. The power quality issues, including voltage imbalance, total harmonic distortion, distribution transformer failure, and related issues, are anticipated due to EV penetration in distribution systems. Detailed review of power quality issues and mitigation techniques are detailed in this paper. Discussion on the effect of these power quality issues on the distribution systems and corresponding mitigation measures are detailed. Power quality impact mitigation techniques have been discussed recently, which exploits the bidirectional power flow of vehicle to grid vehicle to grid (V2G) and grid to vehicle grid-to-vehicle (G2V). Methods and methodologies that mitigate power quality problems in the EV penetrated distribution system is discussed. Bidirectional power flow during EV charging and discharging and power quality issues in this topology is detailed in this review paper. A discussion on future trends and different possible future research paradigms is discussed as the review's conclusion. 2022 Institute of Advanced Engineering and Science. All rights reserved. -
Comparison of DQ Method with I cos? Controller in Solar Power System Connected to Grid with EV Load
Electric Vehicles and Photovoltaic power generation integrated to grid introduces power quality issues. Power quality issues during power integration needs improvement. Control of grid interfaced converters improves grid side power quality in integrated solutions. Power injection to the grid is controlled to get rid of power quality issues. Control techniques that can improve the power injection to the grid needs to be analyzed. This paper compares DQ and I cos ? controller while PV and EVs with non-linear loads are also connected in the power grid. Performance evaluation of both controllers are analyzed by comparing power injection to the grid. 2022 IEEE. -
Power quality disturbance mitigation in grid connected photovoltaic distributed generation with plug-in hybrid electric vehicle
In the last twenty years, electric vehicles have gained significant popularity in domestic transportation. The introduction of fast charging technology forecasts increased the use of plug-in hybrid electric vehicle and electric vehicles (PHEVs). Reduced total harmonic distortion (THD) is essential for a distributed power generation system during the electric vehicle (EV) power penetration. This paper develops a combined controller for synchronizing photovoltaic (PV) to the grid and bidirectional power transfer between EVs and the grid. With grid synchronization of PV power generation, this paper uses two control loops. One controls EV battery charging and the other mitigates power quality disturbances. On the grid connected converter, a multicarrier space vector pulse width modulation approach (12-switch, three-phase inverter) is used to mitigate power quality disturbances. A Simulink model for the PV-EV-grid setup has been developed, for evaluating voltage and current THD percentages under linear and non-linear and PHEV load conditions and finding that the THD values are well within the IEEE 519 standards. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Photovoltaic Power Plant Performance Improvement with Electric Vehicle Integration: Integrated Control Strategies
The combination of Photovoltaic (PV) systems and Electric Vehicles (EVs) holds enormous promise in an era characterized by growing environmental consciousness and sustainable energy solutions. PV technology is a clean, sustainable energy source that produces electricity by utilizing solar energy. Concurrently, EVs electrification of transportation is a critical step in the direction of lower greenhouse gas emissions and more energy efficiency. Through the use of advanced control systems, this research aims to push the boundaries of current practice in the area of PV and EV integration. Specifically, it focuses on the Icos? controller and dq controller to regulate voltage, minimize Total Harmonic Distortion (THD), and facilitate bidirectional power flow. A thorough Simulink model is created, simulating a complicated PV-EV-grid system, in order to evaluate the effectiveness of different control mechanisms. This model accommodates the unique characteristics of Plug-in Hybrid Electric Vehicles (PHEVs) and enables a detailed assessment of the percentages of voltage and current THD under different operating situations. It can handle both linear and non-linear loads. Most importantly, the studys findings showthattheTHDvaluesmeetthestrictrequirementsoutlinedinIEEE519, highlighting the efficiency of the integrated control approaches. The research not only contributes to the advancement of PV and EV technologies but also paves the way for grid-compatible, high-quality power distribution. This endeavor facilitates sustainable energy integration while simultaneously reducing the environmental footprint, making substantial strides toward a greener and more energy-efficient future. 2024 Seventh Sense Research Group -
Enhanced power quality control of a photo voltaic power plant integrated with multiple electric vehicle
As there is a great need for high-quality electricity on the distribution side, distribution side generation (DSG) has become increasingly important. The increased weight of EVs on the distribution side is the cause of this. There are numerous power quality mitigation techniques employed to address this type of issue, but many of the solutions suggest the usage of a separate device, such as an active power filter. But while construction the DSG the solution to this problem may be addressed using the proposed solution in this paper. Power quality (PQ) problems are being caused by the grids integration of Photo-Voltaic (PV) and its application to all connected loads. With the aid of Direct Quardrature (DQ) controller and Multicarrier Space Vector Pulse Width Modulation (SVPWM) technology, the overall power quality disturbance is decreased. A Simulink model for the PV-EV-Grid system was built to measure voltage and current Total Harmonic Distortion (THD) percentages under linear, non-linear, and Plug in Hybrid Vehicle (PHEV) load situations. The model shows that the THD values are well within the IEEE 519. Indian Academy of Sciences 2024. -
Depletion studies in the interstellar medium
We report interstellar Si depletion and dust-phase column densities of Si along 131 Galactic sight lines using previously reported gas-phase Si II column densities, after correcting for the differences in oscillator strengths. With our large sample, we could reproduce the previously reported correlations between depletion of Si and average density of hydrogen along the line of sight () as well as molecular fraction of hydrogen (f(H2). We have also studied the variation of amount of Si incorporated in dust with respect to different extinction parameters. With the limitations we have with the quality of data, we could find a strong relation between the Si dust and extinction. While we cannot predict the density dependent distribution of size of Si grains, we discuss about the large depletion fraction of Si and the bigger size of the silicate grains. 2013 AIP Publishing LLC. -
SILICON DEPLETION in the INTERSTELLAR MEDIUM
We report interstellar silicon (Si) depletion and dust-phase column densities of Si along 131 Galactic sight lines using archival observations. The data were corrected for differences in the assumed oscillator strength. This is a much larger sample than previous studies but confirms the majority of results, which state that the depletion of Si is correlated with the average density of hydrogen along the line of sight ( (H) as well as the fraction of hydrogen in molecular form ( f(H2)). We also find that the linear part of the extinction curve is independent of Si depletion. Si depletion is correlated with the bump strength (c3/RV) and the FUV curvature (c4/RV) suggesting that silicon plays a significant role in both the 2175 bump and the FUV rise. 2016. The American Astronomical Society. All rights reserved. -
In silico studies of viral protein inhibitors of Marburg virus using phytochemicals from Andrographis paniculata
The Marburg virus is a causative agent of Marburg hemorrhagic fever, which was discovered in Marburg, Germany, in 1967. It is a highly contagious and fatal disease transmitted by body fluids. The reservoir host is African fruit bats. Currently, there is no vaccine available to control this disease. Medicinal plants possess many phytochemicals of great therapeutic value. Many have antiviral properties and have been identified as promising drug molecules against various viral diseases proven with an in silico approach. The current research uses the in silico approach to identify the phyto-derived drugs from Andrographis paniculata to treat the Marburg virus. Twenty-four bioactive molecules from the A. paniculata plant were investigated against the targets VP35 and VP40 of Marburg viral proteins using the AutoDock Vina 1.1.2 tool. Out of 24 compounds, Andrographidine C, Andrographidine A, Andrographolactone, and 7-O-methylwogonin showed best docking scores for the target VP40 dimer while Bisandrographolide A, Luteolin Andrographolide, and Andrographiside showed best docking scores with VP35 protein. To determine the druglikeness, pharmacokinetic and pharmacodynamic properties and toxicity for each targets highest docking score compound was assessed using the Swiss absorption, distribution, metabolism, and excretion (ADME) and pkCSM tool. Andrographidine C and Andrographolide performed well in all the parameters of ADME and toxicity. These compounds are recommended as effective inhibitors of VP35 and VP40 of Marburg virus and potential antiviral drugs to treat the hemorrhagic disease. Furthermore, in vitro and in vivo studies can be used to examine the effectiveness and mode of action against the proteins of the Marburg virus. 2023 R. Hariprasath et al