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Background: The assessment of lung function, particularly lung volumes and gas transfer, recorded initially upon patient presentation and subsequent follow-up evaluations, along with high-resolution computed tomography (HRCT) of the chest, can facilitate the evaluation of the natural history of the disease or provide insights to guide therapy in interstitial lung disease (ILD). The utilization of available data related to connective tissue-related ILD (CTD-ILD), gastroesophageal reflux disease (GERD), smoke exposure, as well as any potential correlation of treatment with changes in lung functions, can offer valuable insights. Objectives: The main aim of this study was to study the changes in lung functions of ILD patients over one year apart, and whatever observations could be noticed based on case record form. Methodology: The study was conducted in a Tertiary Care Centre to evaluate changes in lung functions in patients with Interstitial Lung Disease (ILD) over one-year period, specifically assessing increases or decreases in lung function values. The data was collected on ILD patients over 18 years of age who had undergone two Pulmonary Function Tests (PFTs) one year apart, between 2013 and 2015, from the PFT register available in the Centre's PFT lab. Results: This study revealed that 81.25% of patients fell within the age range of 40-70 years. Furthermore, it was found that 77.5% of the patients experienced lung function restrictions. In fact, 95% of the patients exhibited HRCT chest images consistent with Nonspecific Interstitial Pnuemonia (NSIP), while 5% displayed Usual Interstitial Pnuemonia (UIP) patterns. Additionally, within the study group, 47.75% were diagnosed with connective tissue related ILDs. Notably, patients with a history of GERD experienced a median fall in FVC of 130ml/year, compared to 170ml/year in 15 patients without GERD. Conclusion: Thus the findings of the study hold the potential to improve the clinical care and outcomes of interstitial lung disease patients. [ABSTRACT FROM AUTHOR]

Objectives: Problematic substance use is one of the most stigmatized health conditions leading research to examine how the labels and models used to describe it influence public stigma. Two recent studies examine whether beliefs in a disease model of addiction influence public stigma but result in equivocal findings--in line with the mixed-blessings model, Kelly et al. (2021) found that while the label "chronically relapsing brain disease" reduced blame attribution, it decreased prognostic optimism and increased perceived danger and need for continued care; however, Rundle et al. (2021) conclude absence of evidence. This study isolates the different factors used in these two studies to assess whether health condition (drug use vs. health concern), etiological label (brain disease vs. problem), and attributional judgment (low vs. high treatment stability) influence public stigma toward problematic substance use. Method: Overall, 1,613 participants were assigned randomly to one of the eight vignette conditions that manipulated these factors. They completed self-report measures of discrete and general public stigma and an indirect measure of discrimination. Results: Greater social distance, danger, and public stigma but lower blame were ascribed to drug use relative to a health concern. Greater (genetic) blame was reported when drug use was labeled as a "chronically relapsing brain disease" relative to a "problem." Findings for attributional judgment were either inconclusive or statistically equivalent. Discussion: The labels used to describe problematic substance use appear to impact discrete elements of stigma. We suggest that addiction is a functional attribution, which may explain the mixed literature on the impact of etiological labels on stigma to date. [ABSTRACT FROM AUTHOR]

In this work, a real-time label-free microwave sensing mechanism for glucose concentration monitoring using a planar biosensor configured with an inset fed microstrip patch antenna has been demonstrated. A microstrip patch antenna with the resonating frequency of 1.45 GHz has been designed and is fabricated on the Flame Retardant (FR-4) substrate. Due to the intense electromagnetic field at the edges of the patch antenna, edge length has been used as the detecting area where the sample under test (SUT) interacts with the electromagnetic field. The Poly-Dimethyl-Siloxane (PDMS) with the trench in the centre has been employed as the sample holder. Here, the SUT is the glucose dissolved in DI (de-ionized) water with the concentration range of 0.2 to 0.6 g/mL. The dielectric constant dependency on the glucose concentration has been used as the distinguishing factor which results in a shift in the S-parameter. The experimentally measured RF parameters were observed closely which showed the shift in S11 magnitude from -40 to -15 dB and resonant frequency from 1.27 to 1.3 GHz w.r.t the SUT solution of 0.2 to 0.6 g/mL with linear regression coefficient of 0.881, and 0.983 respectively. [ABSTRACT FROM AUTHOR]

In the ever-expanding landscape of academic research, bibliometrics has emerged as a powerful tool to analyse and understand the scholarly output within a specific field. By harnessing the power of data, bibliometric studies provide valuable insights into publication trends, citation patterns and collaborative publishing models. Bibliometric analysis provides valuable quantitative insights, for use in conjunction with qualitative assessment and peer review to obtain a comprehensive understanding of research impact and quality. The article delved into a bibliometric review of research articles of 50 years of Indian Journal of Criminology from 19/3 to 2022 to explore how bibliometric analysis shed light on the growth and development of this esteemed journal over half a century. The study's analysis the patterns and characteristics Of 646 research papers and 948 contributors and revealed that 890/ references cited across all papers, with the highest reference cited. Out of the seventeen countries examined, India was found to publish the most articles, with 88./1% contributors. The study found that N. Pitchandi the first of editor of the journal provided immense contribution by editing 16 volumes over fifty years and S.M. Diaz contributed to a significant highest (1/) research papers, the rise in citations and publications each year showed a wider scope for research. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ETo) plays an important role in agriculture applications such as irrigation scheduling, crop simulation, water budgeting, and reservoir operations. Therefore, the accurate estimation of ETo is essential for optimal utilization of available water resources on regional and global scales. The present study was conducted to estimate the monthly ETo at Nagina (Uttar Pradesh State) and Pantnagar (Uttarakhand State) stations by employing the three ML (machine learning) techniques including the SVM (support vector machine), M5P (M5P model tree), and RF (random forest) against the three empirical models (i.e., Valiantzas-1: V-1, Valiantzas-2: V-2, Valiantzas-3: V-3). Three different input combinations (i.e., C-1, C-2, C-3) were formulated by using 8-year (2009–2016) climatic data of wind speed (u), solar radiation (Rs), relative humidity (RH), and mean air temperature (T) recorded at both stations. The predictive efficacy of ML and the empirical models was evaluated based on five statistical indicators i.e., CC (correlation coefficient), WI (Willmott index), EC (efficiency coefficient), RMSE (root mean square error), and MAE (mean absolute error) presented through a heatmap along with graphical interpretation (Taylor diagram, time-series, and scatter plots). The results showed that the SVM-1 model corresponding to the C-1 input combination outperformed the other ML and empirical models at both stations. Moreover, the SVM-1 model had the lowest MAE (0.076, 0.047 mm/month) and RMSE (0.110, 0.063 mm/month), and highest EC (0.995, 0.999), CC (0.998, 0.999), and WI (0.999, 1.000) values during validation period at Nagina and Pantnagar stations, respectively, and closely followed by the M5P model. Consequently, the ML model (i.e., SVM) was found to be more robust, and reliable in monthly ETo estimation and can be used as a promising alternative to empirical models at both study locations. [ABSTRACT FROM AUTHOR]

Ensuring accurate estimation of evaporation is weighty for effective planning and judicious management of available water resources for agricultural practices. Thus, this work enhances the potential of support vector regression (SVR) optimized with a novel nature-inspired algorithm, namely, Slap Swarm Algorithm (SVR-SSA) against Whale Optimization Algorithm (SVR-WOA), Multi-Verse Optimizer (SVR-MVO), Spotted Hyena Optimizer (SVR-SHO), Particle Swarm Optimization (SVR-PSO), and Penman model (PM). Daily EP (pan-evaporation) was estimated in two different agro-climatic zones (ACZ) in northern India. The optimal combination of input parameters was extracted by applying the Gamma test (GT). The outcomes of the hybrid of SVR and PM models were equated with recorded daily EP observations based on goodness-of-fit measures along with graphical scrutiny. The results of the appraisal showed that the novel hybrid SVR-SSA-5 model performed superior (MAE = 0.697, 1.556, 0.858 mm/day; RMSE = 1.116, 2.114, 1.202 mm/day; IOS = 0.250, 0.350, 0.303; NSE = 0.0.861, 0.750, 0.834; PCC = 0.929, 0.868, 0.918; IOA = 0.960, 0.925, 0.956) than other models in testing phase at Hisar, Bathinda, and Ludhiana stations, respectively. In conclusion, the hybrid SVR-SSA model was identified as more suitable, robust, and reliable than the other models for daily EP estimation in two different ACZ. [ABSTRACT FROM AUTHOR]

This article focuses on the trends of law journals published by law schools in India. The article comprises a short overview of the free access to law movement around the world, and it is an attempt to showcase the growing open access to law movement in India. The article visualizes results of the responses received over the publications of legal scholarship in journals by 23 Indian law schools. The article appends recommendations for greater visibility of AW journals published by law schools in India. [ABSTRACT FROM AUTHOR]

Visible light photocatalysis by semiconductor nanomaterials is one of the promising methods due to its sustainable nature and cost effectiveness. Co-doping in TiO2 by metal as well as non-metal ion is an effective way to make it an efficient visible light photocatalyst. In this work, highly competent nanostructured Ta/N-TiO2 has been standardised by following sequential trials on series of tantalum and nitrogen co-doped TiO2 and characterised by PXRD, UV-Vis-DRS, SEM-EDAX, TEM and XPS. Diffuse reflectance-UV-Vis spectroscopy (UV-Vis-DRS) of the particles revealed that optical band gaps were decreasing only up to 20 mol% of the Ta content. It was observed, the doping percentage of Ta was found to significantly control the extent of N incorporation into the particles. Sunlight stimulated photocatalytic dye degradation experiments were performed over aqueous methylene blue (MB) and the Ta/N co-doped TiO2 particles containing 20 mol% of Ta displayed the paramount photocatalytic activity. Photocatalytic disinfection also performed over E. coli, S. aureus and Bacillus employing 20 mol% of Ta/N-TiO2. Significant amount of inhibition found in E. coli and S. aureus and possible killing mechanism are discussed in 'Result and discussion' section. The co-doped TiO2 has dual advantage to act both as a visible light active photocatalyst and antibacterial agent. [ABSTRACT FROM AUTHOR]

Background and Objectives: Spinal Cord Injury (SCI) is one of the most devastating neurological disorders which involve damage to the central nervous system (CNS). It is followed by structural and functional reorganization and result in recovery of sensory- motor functions. This process can be enhanced through exposing the CNS to one of the technique of motor imagery (MI) with Mental practice. MI has been studied for various neurological disorders including SCI but due to lack in the proper guideline and procedure the research available for SCI is inconclusive with mixed therapeutic benefits. So, this clinical trial was conducted with the aim to develop a structured protocol and to find out the effects on hand function and manual dexterity of incomplete SCI subjects. Materials and methods: Forty Cervical SCI (C-SCI) subjects within 6 month of duration were assigned to the MI group (n = 20) or the conventional group (n = 20). Both group received the same conventional rehabilitation programs and additionally respective intervention i.e. MI group received MI with physical practice (PP) and conventional group received usual upper extremity exercises for 30 minutes per session, 5 days a week for 3 weeks. The Box and Block test (BBT), Action reach arm test (ARAT), Jabsen hand function test (JHFT) and Nine hole peg test (NHPT) were used as an outcome measure to assess gross manual dexterity, motor recovery of upper extremity and hand function at pre and post intervention. Result: At baseline subjects of both group showed no significant differences regarding BBT, ARAT, JHFT and NHPT scores but after 3 weeks of intervention, subjects of both group showed statistically significant improvements in all the variables measured (p<0.05). Moreover subjects of the MI with PP group had greater improvement in the BBT, ARAT values compared to CT group. Conclusion: The present study confirms that structured protocol used for MI with PP is an effective treatment technique to improve upper extremity motor recovery and hand function in C-SCI subjects compare to CT. It is cost effective, easy and safe method for rehabilitation and most important can be easily administered at home by the subjects. [ABSTRACT FROM AUTHOR]

The central library of National Law University Delhi has rich collection of law e-books from various publishers. These e-books were available to the faculty and students through different publisher platforms and it was difficult to find them subject-wise. Library is currently using LIBSYS-7 automation software. The paper depicts detailed experiment carried out to weave these e-books into library catalogue through LIBSYS-7. The whole technical process is described step by step and searching e-books through OPAC. The e-books can be searched subject-wise along-with print books and their full text can be downloaded through OPAC. This experiment establishes library catalogue as core source of information of all library resources. Users get benefitted to a great extent in finding their desired e-book through library catalogue. Other libraries having rich e-book collection may adopt this practice for the benefit of their end-users. [ABSTRACT FROM AUTHOR]

Plagiarism is a very serious issue especially in the digital age of information revolution where the intellectual assets of others can easily be used by the simple click of a mouse. But the phenomenon that 'Life by itself searches the way of Living' is the best example of introduction of plagiarism checking and preventing mechanism to protect intellectual assets. This article gives an overview of a number of plagiarism software available in commercial platform as well as free to use available in open access/public domain. At the same time, the article overwhelms a brief survey among different level of clientele of National Law University, Delhi, accessing various points-of-view to check awareness and applicability of plagiarism mechanism used in the University to enhance quality in education and research activities. [ABSTRACT FROM AUTHOR]

Abstract Introduction Methods Results Conclusion Tremor is a disabling symptom of multiple sclerosis (MS), with limited treatment modalities. Thalamic ventral-intermediate-nucleus (VIM) deep brain stimulation (DBS) is a method of neuromodulation. We describe the long-term outcomes of our carefully selected patients who underwent VIM DBS for their MS-associated tremor.Patients were referred from the regional neurology units. Pre-operative assessments included suitability for anesthesia, tremor quantification by the Fahn–Tolosa–Marin scores, and quality-of-life (EQ5D) measures. Exclusion criteria included prominent cerebellar symptoms such as ataxia and dysmetria, intracranial pathology such as ventriculomegaly, cerebellar plaques and thalamic abnormality, and comorbid psychiatric symptoms. Seven patients (3M:4F) underwent DBS for MS-associated tremor between September 2013 and February 2019. Mean age was 42 years (±SD 8 years). DBS was performed at a mean of 13 years (±SD 9 years) after diagnosis of MS.There were no postoperative surgical complications. All patients showed improvement in FTM tremor scores, by up to 61% at 6 months postoperatively. There was an improvement of 30–175% in quality-of-life scores at 6 months. Improvement of tremor and quality of life, over baseline, was sustained over a long period of follow-up (mean 26.6 months ± SD 20.7 months), including our longest duration at 72 months.With careful selection, DBS is a safe, efficacious intervention for MS-tremor and can positively impact on tremor and quality of life, with effects over a long period. As patients live longer with MS and the advent of new therapies, DBS should be considered for selected patients. [ABSTRACT FROM AUTHOR]

Summary. Leptin concentrations are altered in favour of pro health after periodontal therapy. Background. Leptin, a non-glycosylated peptide hormone, not only maintains fat stores, but is also an integral part of host defense repertoire. Leptin levels have been found to be altered in an array of inflammatory diseases including chronic periodontitis (CP), but the role of non-surgical periodontal therapy (NSPT) in altering the leptin concentrations in saliva and serum of CP patients is yet to be ascertained. The aim of the present study is to quantify leptin levels in CP patients having normal body mass index (BMI) pre-therapy as compared to periodontally healthy controls and to address whether successful NSPT alters leptin concentration in serum and saliva. Materials and methods. Twenty-two saliva (modified draining method) and serum samples (by venipuncture) were collected from CP patients with normal BMI ( n = 22), before and at 4 and 12 weeks after completion of NSPT, and periodontally healthy, age- and gender-matched controls ( n = 22). Leptin levels were estimated using enzyme linked immunosorbent assay kits. Results. At baseline, CP patients had significantly different periodontal clinical parameters and the leptin concentrations in saliva of CP patients were found to be significantly lower than periodontally healthy volunteers (4710.10 ± 1133.21 vs 8721.10 ± 1019.58 pg/ml) ( p < 0.05), whereas in serum the leptin concentrations were significantly higher than healthy controls (10749 ± 2062.24 vs 8085.00 ± 2859.68 pg/ml). Significant improvement in periodontal parameters, serum and salivary leptin levels were observed in CP patients at 4 and 12 weeks post-therapy ( p < 0.01). Conclusion. Altered concentrations of leptin in serum and saliva are observed in CP patients which can be restored in favor of health after periodontal therapy. [ABSTRACT FROM AUTHOR]

The growth of electronic repositories (e-repositories) has been found remarkable in facilitating global open access to legal scholarship. Legal repositories are evolved as reference tool by the law schools to manage legal scholarship, working paper series, peer reviewed articles and other kinds of learning objects. These kinds of services; developed over a decade, improve the visibility and sustainability of scholarly produced literature, and help in winding information gaps between information rich and information poor researchers.The article traces the initiatives in support of open access to scholarly literature and examines how e-repositories improve communication access and bridges channels for legal scholarship. The article finds that certain primary crucial points like policy and standards, perceivable formats, accessibility and management of rights for digital materials, economic facts should be considered before implementing e-repositories. The study concludes that internationally there are number of initiatives supporting institutional and disciplinary repositories in support of legal scholarship, but lack in developing countries like India where no single law institution has approached the repository route of open access publishing. [ABSTRACT FROM AUTHOR]

Accurate monitoring and forecasting of drought are crucial. They play a vital role in the optimal functioning of irrigation systems, risk management, drought readiness, and alleviation. In this work, Artificial Intelligence (AI) models, comprising Multi-layer Perceptron Neural Network (MLPNN) and Co-Active Neuro-Fuzzy Inference System (CANFIS), and regression, model including Multiple Linear Regression (MLR), were investigated for multi-scalar Standardized Precipitation Index (SPI) prediction in the Garhwal region of Uttarakhand State, India. The SPI was computed on six different scales, i.e., 1-, 3-, 6-, 9-, 12-, and 24-month, by deploying monthly rainfall information of available years. The significant lags as inputs for the MLPNN, CANFIS, and MLR models were obtained by utilizing Partial Autocorrelation Function (PACF) with a significant level equal to 5% for SPI-1, SPI-3, SPI-6, SPI-9, SPI-12, and SPI-24. The predicted multi-scalar SPI values utilizing the MLPNN, CANFIS, and MLR models were compared with calculated SPI of multi-time scales through different performance evaluation indicators and visual interpretation. The appraisals of results indicated that CANFIS performance was more reliable for drought prediction at Dehradun (3-, 6-, 9-, and 12-month scales), Chamoli and Tehri Garhwal (1-, 3-, 6-, 9-, and 12-month scales), Haridwar and Pauri Garhwal (1-, 3-, 6-, and 9-month scales), Rudraprayag (1-, 3-, and 6-month scales), and Uttarkashi (3-month scale) stations. The MLPNN model was best at Dehradun (1- and 24- month scales), Tehri Garhwal and Chamoli (24-month scale), Haridwar (12- and 24-month scales), Pauri Garhwal (12-month scale), Rudraprayag (9-, 12-, and 24-month), and Uttarkashi (1- and 6-month scales) stations, while the MLR model was found to be optimal at Pauri Garhwal (24-month scale) and Uttarkashi (9-, 12-, and 24-month scales) stations. Furthermore, the modeling approach can foster a straightforward and trustworthy expert intelligent mechanism for projecting multi-scalar SPI and decision making for remedial arrangements to tackle meteorological drought at the stations under study. [ABSTRACT FROM AUTHOR]

Appropriate input selection for the estimation matrix is essential when modeling non-linear progression. In this study, the feasibility of the Gamma test (GT) was investigated to extract the optimal input combination as the primary modeling step for estimating monthly pan evaporation (EPm). A new artificial intelligent (AI) model called the co-active neuro-fuzzy inference system (CANFIS) was developed for monthly EPm estimation at Pantnagar station (located in Uttarakhand State) and Nagina station (located in Uttar Pradesh State), India. The proposed AI model was trained and tested using different percentages of data points in scenarios one to four. The estimates yielded by the CANFIS model were validated against several well-established predictive AI (multilayer perceptron neural network (MLPNN) and multiple linear regression (MLR)) and empirical (Penman model (PM)) models. Multiple statistical metrics (normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency (NSE), Pearson correlation coefficient (PCC), Willmott index (WI), and relative error (RE)) and graphical interpretation (time variation plot, scatter plot, relative error plot, and Taylor diagram) were performed for the modeling evaluation. The results of appraisal showed that the CANFIS-1 model with six input variables provided better NRMSE (0.1364, 0.0904, 0.0947, and 0.0898), NSE (0.9439, 0.9736, 0.9703, and 0.9799), PCC (0.9790, 0.9872, 0.9877, and 0.9922), and WI (0.9860, 0.9934, 0.9927, and 0.9949) values for Pantnagar station, and NRMSE (0.1543, 0.1719, 0.2067, and 0.1356), NSE (0.9150, 0.8962, 0.8382, and 0.9453), PCC (0.9643, 0.9649, 0.9473, and 0.9762), and WI (0.9794, 0.9761, 0.9632, and 0.9853) values for Nagina stations in all applied modeling scenarios for estimating the monthly EPm. This study also confirmed the supremacy of the proposed integrated GT-CANFIS model under four different scenarios in estimating monthly EPm. The results of the current application demonstrated a reliable modeling methodology for water resource management and sustainability. [ABSTRACT FROM AUTHOR]

Jalili syndrome (JS) (MIM#217080) is a rare genetic disorder characterized by the comorbid appearance of cone-rod dystrophy (CORD) and amelogenesis imperfecta (AI). JS is an autosomal recessive inherited disorder caused by different mutations, all with a linkage at achromatopsia locus 2 q11 on the metal transporter gene CNNM4. The case report presented here describes JS with distinct phenotypic variations such as situs inversus totalis (SIT) along with additional ophthalmic findings such as keratoconus and ectopia lentis. It is the first case of JS reported from the Indian subcontinent, affecting a male patient of Muslim faith from an area having high fluoride levels in the ground water. A positive history of consanguineous marriage among his family members of past generations was also evident. [ABSTRACT FROM AUTHOR]