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Modern-day power systems are highly stressed and operate close to the stability limit. The bus voltage variation in power systems generally infringes on the researcher's mind about voltage stability. The main focus of this manuscript is the voltage stability problem and voltage security assessment rather than the angle stability problem. Voltage security can be determined by running a full-load AC load flow with contingency analysis. In real-time analysis, running thousands of contingencies in online mode is quite a cumbersome task, so here in this manuscript, we have proposed a functional link-based ANN for voltage security assessment and then predicted the weakest voltage control area by the entropy concept along with the placement of FACTS devices according to the voltage control area weakness factor and contingencies ranking. The novel technique is then tested with IEEE-14 Bus and IEEE-30 Bus systems with voltage stability performance indicators.

This paper analyzes the effect of different types of dust on the reduction of PV systems' performance. The PV system installed on the field gives maximum output. However, in a real-time scheme, the PV system fails to generate the desired power output due to various realistic and unavoidable factors like soiling. Different dust particles accumulating on photovoltaic (PV) modules result in shadowing and reduced irradiance, impacting power production. The study investigates eight dust samples (ash, dirt, cement, brick powder, putty, wood dust, sand, and salt) in indoor and outdoor environments. It evaluates the decrease in power at solar irradiance levels of 500, 700, and 1000 W/m². The soiling experiments conducted indoors show that the maximum% reduction in power is 39.21 % in the case of Ash, while a minimum of 8.32 % in the case of red soil. The outdoor experiments suggest that red soil, sand, and brick dust can create huge power losses in the PV system, followed by ash powder, wood dust, putty dust, salt, and cement powder. The advantages of this research lie in its thorough analysis of several forms of dust and their impact on photovoltaic (PV) systems under different circumstances. Furthermore, the study emphasizes the crucial need for implementing dust control measures to maximize system performance, thereby providing insightful information for system design and maintenance procedures. The novelty of this study is to investigate the performance impact of various kinds of dust on PV systems, offering significant insights for improving system efficiency in real-world circumstances. The research enhances the reliability and applicability of its results by thoroughly assessing outdoor and indoor conditions, bridging the gap between laboratory results and practical applications.

The trend of integrating different distributed generation sources into the existing grid have increased the probability of power quality disturbances to a threatening level. Eventually, detection, protection and mitigation of these disturbances are even more challenging. In this regard, the article presents an intelligent power quality disturbance classification scheme using a 2D convolutional neural network designed from a systematic and structural standpoint. A total of 8 singular, 5 complex power quality events are simulated and voltage data collection is made from a test system designed in MATLAB Simulink environment. The three-phase voltage data is converted to a single signal arrangement through a newly proposed Unique Clark’s Transformed Sequence. In addition to that, the scheme completely eliminates the worry of a signal processing stage by proposing a novel scaled matrix image created out of 2-cycle data collected at 6.4kHz sampling frequency that acts as input to the CNN architecture designed in the PYTHON environment. Further, the novelty extended to design a pseudo-real-time setup where the MATLAB environment continuously runs the test system, producing scaled matrix images. These images are saved to a shared directory, enabling a PYTHON loop for prompt event classification through the trained CNN model. The model performance is found to be 100% under ideal conditions. It has also tested under three different noise conditions of 40dB, 30dB and 20dB and obtained an overall accuracy of 98.86% with singular events. Further, the method is also verified for complex and unsymmetrical dataset and found to be equally effective. Additionally, the validation is likewise made with a trivial set of real-time simulated data using OPAL-RT 4510 setup. Finally, the proposed PQ detection scheme is compared with recently published work to express its superiority over other similar studies in terms of classification accuracy.INDEX TERMS Convolutional neural network, deep learning, power quality disturbance classification, scaled matrix image, unique Clark’s transformed sequence.

The modern era power system is constantly undergoing constructive changes and implementations both in source and load side. Certainly, the distributed generators, unconventional/nonlinear loads, charging stations etc are mostly integrated through power electronics interfaces. As a result, frequent power quality disturbances appear in the system that is to be mitigated at the earliest. Since detection is the prerequisite for mitigation, therefore the article presents a novel intelligent power quality detection scheme to detect and classify the PQ Events. At first, the energy feature of the 5 band limited modes are calculated from variational mode decomposed voltage signals. Then the mode energy features are utilized to train a novel Hybrid Arithmetic Whale Optimized light gradient boosting machine classifier. A total of 15 different PQ events have been investigated and exceptional classification results have obtained with optimum computational complexity, both under noiseless and noisy conditions. Moreover, the accuracy of the proposed PQ classification schemes found to be towering against other related pre-published works. Finally, the ability of the proposed detection scheme is validated in real time though OPAL-RT 4510 and grid simulator hardware in loop setup.

The power loss in the arrays due to non-uniform irradiances in the site is the most common scenario observed in a PV system. The irradiance non-uniformity occurs due to obstacles between actual irradiance and modules caused by dust and shadow of clouds, trees, and buildings in some portions of the array. This results in complications like mismatch, power reduction, deformed characteristics curves, failure of power tracking algorithms, and sometimes physical damage to the PV modules. Numerous solutions are present for mitigating the above complications among which the array reconfiguration gained a huge audience for ease of implementation, lower cost, and higher reliability but, each technique exhibits certain drawbacks. In this paper, a harmony search reconfiguration (HSR) algorithm for dynamic reconfiguration is proposed that has advantages in terms of simplicity, adaptability, convergence speed, reduced switch count, and arbitrary array application. The modeling and validation are done in the MATLAB platform using $5 \times 5$ , $9 \times 9$ , $9 \times 5$ , and $3 \times 3$ arrays under various shading cases and compared with the 22 existing conventional, static, and dynamic techniques. The depth investigation shows the higher performance of the HSR with 24.64% and 12.28% higher performance than conventional and static techniques with lowest actual power deviation of −1.10% and equivalent performance to that of existing techniques with reduced complexities.

This paper develops the Gaussian Mutation Based Teaching-Learning Optimization (GMBTLO) to solve different reactive power dispatch problems. In GMBTLO, Gaussian random variables are instituted, which includes both the ‘Teacher phase’ as well as ‘Learner phase’ helps to improve the efficiency of searching. Simultaneously, it ensures more feasibility to obtain the global optimal. Gaussian random variables are presented in GMBTLO, where both the ‘Teacher phase’ as well as ‘Learner phase’ is considered. This advances searching competence and guarantee a great possibility of achieving global optimum without affecting the convergence speed. In this paper, GMBTLO is implemented to enhance solution quality as well as convergence speed. Developed GMBTLO is exploited for obtaining the control variables settings including terminal voltages of a generator, transformer taps, as well as output power of shunt VAR compensators (reactive) for achieving a reduced loss in real power transmission and enhanced voltage profile. GMBTLO is validated by taking IEEE 30-bus, 57-bus along with 118-bus test systems. Also, test outcomes are matched with the results already acquired from other implemented evolutionary techniques. It is concluded that the suggested GMBTLO extends a better solution.

Magnetic nanoparticles (MNPs) owing to its broad application spectrum are gaining popularity in recent years. The current review article offers a one-stop-reference for young scientists as it encompasses the literature reports on method of synthesis and functionalization of MNPs based systems and their potential applications spectrum in diverse fields. This review summarizes in details about different methods reported in literature for the synthesis of MNPs, need of functionalization of MNPs, immobilization of active species onto the surface of functionalized MNPs and their applications in carrying out biologically important organic transformation. Applications of MNPs are not only restricted to the field of catalysis but also showed potential applications in different sectors. Over the last few decades, there has been increasing global concern over public health issues due to contamination of water bodies with harmful dyes and toxic metals. Monitoring and subsequent removal of these harmful dyes and toxic metals from the contaminated water is one of the major environmental remediation interests today. In this context, MNPs based absorbents have shown exuberant potential to remove deleterious pollutants from water bodies owing to their high removal efficiency, low cost, faster kinetics, easy accessibility and design flexibility. Besides, MNPs have also proved their potential in the field of enzyme and pharmaceutical industries. MNPs being the major class of nanoscale materials are revolutionizing the current clinical diagnostic and therapeutic techniques and are currently employed as next generation drug carriers. Furthermore, Magnetic NP-Based Biosensors was also employed for detection of the presence of SARS-CoV-2, a ribonucleic acid (RNA) virus responsible for nearly 6.1 million deaths occurred due to COVID-19 pandemic. MNPs based system also showed their potential in fuel industry as it is used in the production of biodiesel which emerges as a promising alternative to fossil fuel derived energy sources because it is eco-friendly, clean and biodegradable in nature. In short, we have provided in-depth details about the MNPs, their synthesis, functionalization and their applications in diverse fields.

Traveling Wave Tubes (TWT) are most widely used in civil, defense, and space applications as power amplifiers over a wide range of frequency. When a TWT works at a higher bandwidth, it suffers from nonlinearities, which affects the overall performance of the tube and hence the required results aren't achieved. So, optimization of a TWT is required, mainly in terms of its power characteristics. Power characteristics of the TWTs are specified in terms of output power at different input drive levels, AM/PM transfer and AM/PM conversions, input, and output back-off, gain at saturation, etc. Some of the linearity factors like 3rd order inter modulation product (IMP), and the 1 dB compression point are also optimized. An exhaustive study has been made to achieve the optimum performance of a 140W TWT in Ku-Band. The result has been validated by experimental results.

Juvenile Dermatomyositis (JDM) is a rare autoimmune disorder which mainly affects the skin and skeletal muscles. Characteristic features of this rare disorder include Gottron papules, heliotrope rashes and proximal muscle weakness. MDA5 positive JDM is usually associated with interstitial lung disease in later part of life. The authors report a case of an 11-year-old male child who presented to the Paediatric Department with complaints of rashes over extensor surfaces, Gottron papules and pain and weakness in all limbs. The child was on treatment from the Dermatology Department as a case of psoriasis for last six months. During hospital stay after detailed work-up, the child was diagnosed to have JDM. Anti-melanoma Differentiation-Associated gene 5 (Anti-MDA5) antibodies were positive in the present case. The child was treated with immunosuppressive drugs with supportive care and is currently on treatment for the last one and a half years and is largely asymptomatic. JDM requires meticulous clinical examination and specific investigations so that timely diagnosis can be made to ensure appropriate treatment. In the present index case, the authors describe the typical clinical presentation, newer investigative modalities like myositis specific antibody and treatment outcomes of this rare condition.

This work discusses the frequency and voltage stabilization in a stand-alone self-excited induction generator system (SEIGs) using a fuel cell (FC)-based generation unit. The proposed SEIG acts as the power generator in a microhydro system. Variations in load create fluctuations in voltage and frequency, which have to be stabilized. In this work, authors have proposed integrating a FC-based generation unit with the existing SEIGs to improve its voltage and frequency profiles. For this work, a proton exchange membrane fuel cell (PEMFC) has been considered. Modeling of a 36 kW PEMFC is taken for the proposed work, which has to be integrated with the 22 kW self-excited induction generator. The design of the system and converter parameters have also been included in the work. Authors have proposed an orthogonal current component-based controlstructure that provides independent control of active and reactive power in the system. Considering the FC system working conditions, this article aims to assure optimum power transfer capability between the self-excited induction generator, fuel cell system, and the time-varying loads. The system is exposed to time-varying RL loads dynamic load switching, and the performance is evaluated in real-time. OP 4510 real-time simulator verifies the proposed system's dynamic model created using Matlab/Simulink.

Background: Breast cancer is triggered by uncontrollable breast cell development. These metals may build up in human serum and tissues, causing estrogenic/malignant consequences. Therefore, metals are being studied to investigate whether they enhance the risk of endocrine-related malignancies like breast cancer. Methods: This study assessed the level of metals such as Cd, As, Pb, Ni, Cr, Zn, and Fe in 120 women undergoing breast cancer surgery in the Malwa region of Punjab. Subjects having malignant breast lesions (n = 83) were grouped in the cancer case group whereas subjects with benign breast lesions (n = 37) were separated as a control group. From each case, blood, breast tumor, surrounding adipose tissue samples were obtained, and metal analysis was carried out using inductively coupled plasma mass spectrometry (ICP-MS). Results: In malignant cases, the amount of metals ranges from 0.04 to 139.18 μg/kg in tumor. Whereas in adipose tissues and blood, it ranges from 0.04 to 1164.0 μg/kg and from 0.02 to 276.61 μg/kg, respectively. In control group, the total amount ranges from 0.05 to 332.72 μg/kg in the tumor, from 0.13 to 125.61 μg/kg in adipose tissues, and from 0.01 to 121.76 μg/kg in the blood. The level of Cd, Cr, Zn, Fe, Ni, and Pb were observed to be statistically significant/extremely significant whereas Arsenic was detected in no groups. Conclusion: The results indicate that Cd, Cr, Zn, Fe, Ni, and Pb may play a significant role in the development of breast cancer. The parenchymal component of tumor tissues accumulates heavy metals at a higher rate.

Solar photovoltaic (PV) power system consists of numerous modules connected in series and parallel to generate a certain range of voltage and current outputs. However, the modules are highly vulnerable to the frequently occurring scenario of partial shading that results in severe losses of power, hotspot, system performance reduction, and permanent damage to the modules. These problems are mainly diminished through reconfiguration strategies that disperse the intensity of shading among the modules to reduce current mismatch and increase the power output of the system. But the pre-existing reconfiguration techniques exhibit one major demerit toward the limited application in symmetrical or square arrays that are quite uncommon in the real-time scenario. Hence, this paper presents a Dimension-Independent Array Relocation (DIAR) approach for the modules connected to asymmetrical arrays that enhance the output power of the system during all patterns of partial shading scenarios. The methodology is simple, easy to implement, cost-effective, and a one-time arrangement for the modules of the system that ensures lower power losses and higher reliability during partial shading. The methodology has been tested for $6\times 3$ , $5\times 7$ , $20\times 4$ , and $4\times 3$ (experimental analysis) asymmetrical arrays and compared with conventional connections under numerous partial shading cases in the MATLAB/Simulink environment. Additionally, the application of the proposed methodology to symmetrical arrays has been validated under partial shading and compared to three pre-existing reconfiguration strategies. From the depth investigation, the average efficiency of power conversion has been noted as 98.04% with an average power enhancement of 18.34% than conventional techniques.

Shopping malls are visited for both functional as well as entertainment values. They provide emotional comfort and escape from boredom and stress to the shoppers. This study investigates the relationship of ambiance, layout, and utility of a mall with escapism and repurchase intention using the Stimulus-Organism-Response (SOR) model. Using a survey instrument, a convenience sampling procedure was adopted to obtain data from 316 respondents (mall visitors of the Delhi National capital Region in India). Delhi is the mall capital of India, with the highest population density in the world. The relationships between utility-escapism (β = .0265, p = .018), layout-escapism (β = 0.269, p = .012), layout-utility (β = 0.776, p < 0.001), utility-ambiance (β = 0.480, p < 0.001), layout-ambiance (β = 0.407, p < 0.001), and escapism-repurchase intention (β = 0.708, p < 0.001) are validated. However, the relationship between ambiance-escapism (β = 0.073, p = .509) is not supported. The results indicate that mall layout facilitates escapism followed by utility, whereas ambiance does not play a vital role. The purpose of the mall visit moderates this effect. Mall managers can create engaging shopping experiences to help shoppers escape boring routines/stress through improved layouts and enhanced functional values. The study establishes a strong linkage between mall layout, utility, and escapism.

This work is based on the evaluation of a super-twisting sliding mode controller for power control in an isolated multi-source renewable generation system. The hybrid multi-source system taken into consideration, in this case, is made up of three different generation units. The main generation unit is a 22kW micro-hydro system with a self-excited induction generator. To this, a 7.5kW doubly fed induction generator-based wind energy conversion system is integrated. An 18kW solar PV system connected to a battery energy storage system is connected at the dc-link. All the above systems are integrated through a bidirectional nine-switch converter. The autonomous hybrid system's power control is solely done by the nine-switch converter. In this work, efforts have been made to combine the robustness and accuracy of super-twisting sliding mode controllers with the reliability and flexibility of the nine-switch converters. The performance evaluation of the above combination is done with various load and source side disturbances. The system's uninterrupted power supply capability has also been examined in this work. Using the MATLAB environment, the system's performance is evaluated, examined, and the same has been verified using an OPAL-RT 4510 real-time simulator.

PV systems connected to the grid are primarily designed to generate clean energy to fulfil the rising energy demand. To predict the performance and efficacy of PV systems, several installation aspects are employed, such as location, local meteorological data, orientation, optimal tilt angle, varying losses, and energy yield estimation. Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar (Latitude 20.24°N and Longitude 80.85°E) has taken one such initiative by installing a 13 kWp rooftop grid-connected solar photovoltaic system in one of its institutional buildings. The solar PV system is fixed at an angle of 21° and is installed on the rooftop of a 25-m height building. The measured performance characteristics were analysed and compared to those of PVSyst software to determine its feasibility in campus buildings. From the result, the annual electricity supplied to the grid is 17.79 MWh, final yield of 3.80 h/d, reference yield of 4.62 h/d and performance ratio of 0.82. The solar PV system installed at the institution is predicted to have reduced 17443.02 kg of CO2, 22.07 kg of SO2, and 46.1 kg of NOx from the atmosphere per year. The lebelised cost of energy (LCOE) of the installed PV system is 9.408 INR/kWh with a payback of 9.8 years. This study provides the techno-economic feasibility of installing grid-connected solar PV systems on the roof of an institutional building and help the solar installers in establishing the most efficient solar photovoltaic system’s sizing and design.

Aim The aim of the study is to determine improvements in perinatal mortality at the end of the first 2 years from the initiation of the Samrakshan program of the Indian Radiological and Imaging Association. Methods Samrakshan is a screening program of pregnant women that uses trimester-specific risk assessment protocols including maternal demographics, mean arterial pressure, and fetal Doppler studies to classify women as high risk or low risk for preterm preeclampsia (PE) and fetal growth restriction (FGR). Low dose aspirin 150 mg daily once at bedtime was started for pregnant women identified as high risk in the 11–136/7 weeks screening. The third-trimester screening focused on the staging of FGR and protocol-based management for childbirth and risk assessment for PE. Outcomes of childbirth including gestational age at delivery, development of PE, and perinatal mortality outcomes were collected. Results Radiologists from 38 districts of 16 states of India participated in the Samrakshan program that screened 2,816 first trimester, 3,267 second trimester, and 3,272 third trimester pregnant women, respectively. At 2 years, preterm PE was identified in 2.76%, preterm births in 19.28%, abnormal Doppler study in 25.76% of third trimester pregnancies, and 75.32% of stage 1 FGR delivered at term. The neonatal mortality rate was 9.86/1,000 live births, perinatal mortality rate was 18.97/1,000 childbirths, and maternal mortality was 58/100,000 live births compared with 29.5, 36, and 113, respectively in 2016. Conclusion Fetal Doppler integrated antenatal ultrasound studies in Samrakshan led to a significant reduction in preterm PE rates, preterm birth rates, and a significant improvement in mean birth weights. Perinatal, neonatal, and maternal mortality rates are significantly better than the targets for 2030 set by the Sustainable Development Goals-3.

The awareness of making decisions in an imprecise environment has resulted in considering the inventory system under a fuzzy approach. The effects of uncertain demand have been finding increased application in many inventory systems. Uncertainty creates complicated situations for the manufacturer in making decisions. Markets have become more competitive as a result of technological advancements. The effect of inflation on the overall cost of the inventory system is useful in providing a tool for the analysis of inventory decisions. This study intended to estimate the effect of different fuzzy numbers on a manufacturer's annual joint expected total cost. The comparative study of this proposed model has been considered for two different fuzzy numbers with the defuzzification technique as the centroid method. The optimization technique has been used to minimize the producer's joint expected total cost under the condition mentioned earlier, and the model is validated numerically. (original abstract)

Partial shading is the most unexpected scenario encountered by the arrays that degrade the performance causing power reduction, non-convex characteristics curves, losses, hotspot, module damage, and system failure. The adoption of various reconfiguration techniques has recently provided relief to the PV array to reduce power losses during partial shading. However, these techniques exhibit vulnerabilities such as reliable operation, ease of implementation and, higher cost and complexity due to the requirement of abundant manpower, labour, complex algorithms, dynamic operation, switches and sensors that cause additional power losses. Hence, this paper presents a low cost and less complex reconfiguration technique for PV arrays to effectively increase the power generation during partial shading scenarios. The proposed reconfiguration does not require any manpower, labour, algorithms or additional devices to reduce the losses in arrays during shading. The efficacy of the technique is tested using two array sizes under various shading scenarios using MATLAB modelling and real-time field experiments. Also, for better analysis, the performance of the proposed technique is compared with conventional configurations and Sudoku reconfiguration. The investigation proclaimed that the proposed reconfiguration technique has an average power enhancement of 20% higher than any other conventional configurations.

MADS-box genes encode transcription factors that play important roles in the development and evolution of plants. There are more than a dozen clades of MADS-box genes in angiosperms, of which those with functions in the specification of floral organ identity are especially well-known. From what has been elucidated in the model plant Arabidopsis thaliana, the clade of FLC-like MADS-box genes, comprising FLC-like genes sensu strictu and MAF-like genes, are somewhat special among the MADS-box genes of plants since FLC-like genes, especially MAF-like genes, show unusual evolutionary dynamics, in that they generate clusters of tandemly duplicated genes. Here, we make use of the latest genomic data of Brassicaceae to study this remarkable feature of the FLC-like genes in a phylogenetic context. We have identified all FLC-like genes in the genomes of 29 species of Brassicaceae and reconstructed the phylogeny of these genes employing a Maximum Likelihood method. In addition, we conducted selection analyses using PAML. Our results reveal that there are three major clades of FLC-like genes in Brassicaceae that all evolve under purifying selection but with remarkably different strengths. We confirm that the tandem arrangement of MAF-like genes in the genomes of Brassicaceae resulted in a high rate of duplications and losses. Interestingly, MAF-like genes also seem to be prone to transposition. Considering the role of FLC-like genes sensu lato (s.l.) in the timing of floral transition, we hypothesize that this rapid evolution of the MAF-like genes was a main contributor to the successful adaptation of Brassicaceae to different environments.

In this article, a chemoselective reduction process of various aldehydes to their corresponding alcohols is described. An aqueous solution of various aromatic and allylic aldehydes was treated with NaBH4 and tetrabutylammonium iodide as a phase transfer catalyst by choosing appropriate concentrations to give their respective alcohols in good to moderate yield. This methodology offered several advantages, including simple environmentally benign experimental procedure, good yields, short reaction time, and no toxic by-product. DOI: http://dx.doi.org/10.17807/orbital.v13i4.1576

As heterocyclic nitrogen molecules, tetrahydropyridines have been recognized as significant constituents of many natural and synthetic compounds, many of which have interesting biological and pharmacological properties. Tetrahydropyridines (THPs) play a pivotal role in synthesizing a range of remedial compounds. They have exhibited impressive curative efficacy for the treatment of numerous diseases. Due to this reason, they are attractive synthetic targets for organic chemists. Several techniques and schemes have been adopted for the synthesis of these molecules. Among these, multicomponent reactions (MCRs) are proved to be one of the best tools for achieving compounds containing complex diversity in a single step and production of their vast libraries. Along with this, the employment of various catalysts makes this technique more vibrant. This review article discussed different catalysts adopted in the synthesis of tetrahydropyridine derivatives via multicomponent reactions to provide information for the development of new-fangled processes aiming at less reaction time, better yield, and minimum side effects. DOI: http://dx.doi.org/10.17807/orbital.v13i4.1585

Background: Investigating the underlying psychosocial factors is a cornerstone of planning need-based intervention for adult males accused of rape. Unresolved debates on its etiology, mediation, or interaction among causal psychosocial variables fuel curiosity to scrutinize it further. Hence, we studied potential influence of and relation between adverse childhood experiences, aggression, empathy, and psychopathology in adult males accused of rape in India and investigated the risk factors for the same. Methods: With a correlational research design, 40 literate and consenting adult males medically confirmed for rape were recruited using convenient sampling. The assessment was done on Adverse Childhood Experiences, Aggression Questionnaire, Symptom Checklist-90, and Interpersonal Reactivity Index. Descriptive statistics, Pearson’s product–moment correlation, and stepwise linear regression analysis were calculated. Results: Approximately 75% of the participants experienced at least one category of Adverse Childhood Experiences. Scores above cut-off points were obtained on anger, hostility, fantasy, and personal distress. Significant correlations were obtained between adverse childhood experiences and psychopathology; between hostility and psychopathology, perspective taking, and personal distress; and in case of indirect aggression, with perspective taking and empathetic concerns. Regression analysis revealed that an increase in Symptom Checklist-90 global scores increases hostility and that lower personal distress predicts higher scores on hostility on Aggression Questionnaire. Conclusions: Adverse childhood experiences, aggression, and psychopathology play a critical role and, therefore, should be included as core components of the prevention of rape or relapse prevention programs at the community level.

Background: Substance use among adolescents is increasing rapidly and becoming a global health concern worldwide. Because of the changing trends and rising magnitude in India, there is an urgent need to adapt and validate instruments to assess adolescents’ substance use. The study translated the Teen-Addiction Severity Index (T-ASI) into Hindi and assessed the psychometric properties. Methods: The instrument (T-ASI) was translated from English to Hindi using: (a) forward translation: translation from the source language into the target one, (b) comparison and synthesis of the two translated versions, (c) blind backward translation, (d) comparison of the two back-translated versions and development of prefinal version, (e) conceptual evaluation of items and pilot study, and (f) assessing the psychometric properties. Results: The content validity of Hindi T-ASI was quite high (0.97). A significant positive correlation r = 0.439* (0.014) between the T-ASI family functioning domain and the organization scale of the Family Environment Scale (FES) demonstrated good concurrent validity. Youth self-report substance use domain correlated well with youth self-report behavior problems scale r = 0.385 (0.033) and the psychiatric status domain correlated with all three internalizing 0.606 (

Purpose: The study aims to examine the mediating effect of psychological well-being (PWB) on the relationship between teamwork skills and student engagement (SE) in higher education institutional setups. Design/methodology/approach: The study used a triangulation mixed-methods approach. Data were collected from final-year students pursuing post-graduation and graduation in private colleges in India. In the main study, quantitative data was gathered from 276 students through a survey. The relationship among the variables-teamwork skills, SE and PWB was empirically validated through path analysis; mediation was also conducted. In the auxiliary study, qualitative data was gathered through focus group sessions and was analyzed using thematic analysis. Findings: Results depicted that teamwork skills positively predict students' engagement with their academic program. Additionally, PWB partially mediates the relationship between teamwork skills and SE. Originality/value: The study was conducted to expand understanding of aspects related to promoting students' engagement in HEIs in Delhi and Haryana through being attentive toward teamwork skills development and through taking care of students' PWB.