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Perceived stress and fatigue in software developers: Examining the benefits of gratitude
Software development demands creativity and adept problem-solving skills. However, long-term stress and fatigue might impede these skills in software developers. From the perspective of positive psychology, this cross-sectional study investigated the effects of gratitude, age, and gender on stress and fatigue in 421 participants, 244 males (58 %) and 177 females (42 %), aged between 21 and 57 years (M = 36.20; SD = 7.56). The tools employed included the multi-component gratitude measure, perceived stress scale and fatigue assessment scale. Multiple linear regressions confirmed the beneficial effects of gratitude, and they indicated higher levels of perceived stress and fatigue in women and younger professionals. These findings have positive implications for organisational psychologists, as they signify the favourable impacts of gratitude in mitigating stress and fatigue in software developers. The authors recommend that organisational practitioners should focus on enhancing the professionals' well-being by strategizing and implementing gratitude training programmes. 2022 Elsevier Ltd -
IIRM: Intelligent Information Retrieval Model for Structured Documents by One-Shot Training Using Computer Vision
Various information retrieval algorithms have matured in recent years to facilitate data extraction from structured (with a predefined template) digital document images, primarily to manage and automate different organizations invoice and bill reimbursement processes. The algorithms are designated either rule-based or machine-learning-based. Both approaches have respective advantages and disadvantages. The rule-based algorithms struggle to generalize and need periodic adjustments, whereas machine learning-based supervised approaches need extensive data for training and substantial time and effort for manual annotation. The proposed system attempts to address both problems by providing a one-shot training approach using image processing, template matching, and optical character recognition. The model is extensible for any structured documents such as closing disclosure, bill, tax receipt, besides invoices. The model is validated against six different structured document types obtained from a reputed title insurance (TI) company. The comprehensive analysis of the experimental results confirms entity-wise extraction accuracy between 73.91 and 100% and straight through pass 81.81%, which is within business acceptable precision for a live environment. Out of total 32 tested entities, 17 outperformed all state-of-the-art techniques, where max accuracy has been 93 % with only invoices or sales receipts. The system has been set operational to assist the robotic process automation of the TI mentioned above based on the experimental results. 2022, King Fahd University of Petroleum & Minerals. -
Discovering patterns of live birth occurrence before in vitro fertilisation treatment using association rule mining
According to estimates, in-vitro fertilisation (IVF) is credited for the delivery of over 9 million children globally, constituting it to be a highly remarkable as well as commercialised advanced healthcare treatment. Nonetheless, the majority of IVF treatments are now constrained by factors such as expense, access and most notably, labour-intensive, technically demanding processes carried out by qualified professionals. Advancement is thus crucial to maintaining the IVF markets rapid growth while also streamlining current procedures. This might also improve access, cost, and effectiveness while also managing therapeutic time efficiently and at a reasonable cost. IVF has become a renowned technique for addressing problems like endometriosis, poor embryo development, hereditary diseases of the parents, issues with the biological function, problems with counteracting agents that harm either eggs or sperm, the limited capacity of semen to penetrate cervical bodily fluid, and lower sperm count that lead to infertility in humans. Copyright 2023 Inderscience Enterprises Ltd. -
Decolonising the Gateway of India
This article interrogates how a colonial monument, the Gateway of India in Mumbai, former Bombay, continues to carry and be endowed with a title that is a misplaced embodiment of Indian social histories. Built in the 1920s, this monument, definitely a work of architectural grandeur, continues to carry its erroneous rendition and confines Indias vast social histories to the colonial moment, with an anglo-centric focus. As the monument symbolises the memory of the colonial regime, it also signifies its oppression as well as its exit from the subcontinent, rather than witnessing anyone coming to India, except King George in 1911, as the monuments title seems to suggest. A mnemonic device of colonialism, this misleading label needs to be seriously revisited, for it not only romanticises the colonial past but also fails to lead our memories back to certain crucial episodes in earlier social histories, from which the monument and its specific place, Mumbai, are more or less fully absent. 2023 The Author(s). -
Effective time context based collaborative filtering recommender system inspired by Gowers coefficient
The fast growth of Internet technology in recent times has led to a surge in the number of users and amount of information generated. This substantially contributes to the popularity of recommendation systems (RS), which provides personalized recommendations to users based on their interests. A RS assists the user in the decision-making process by suggesting a suitable product from various alternatives. The collaborative filtering (CF) technique of RS is the most prevalent because of its high accuracy in predicting users' interests. The efficacy of this technique mainly depends on the similarity calculation, determined by a similarity measure. However, the traditional and previously developed similarity measures in CF techniques are not able to adequately reveal the change in users' interests; therefore, an efficient measure considering time into context is proposed in this paper. The proposed method and the existing approaches are compared on the MovieLens-100k dataset, showing that the proposed method is more efficient than the comparable methods. Besides this, most of the CF approaches only focus on the historical preference of the users, but in real life, the people's preferences also change over time. Therefore, a time-based recommendation system using the proposed method is also developed in this paper. We implemented various time decay functions, i.e., exponential, convex, linear, power, etc., at various levels of the recommendation process, i.e., similarity computation, rating matrix, and prediction level. Experimental results over three real datasets (MovieLens-100k, Epinions, and Amazon Magazine Subscription) suggest that the power decay function outperforms other existing techniques when applied at the rating matrix level. 2022, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden. -
Doable production of highly fluorescent, heteroatom-doped graphene material from fuel coke for cellular bioimaging: An eco-sustainable cradle-to-gate approach
The manifold usage of fluorescent materials and their pliable association with optical imaging techniques have made great strides in unfolding the incredible potential of biotechnological research, particularly in cancer treatment, from point-of-care assay to clinical applications. Enlarged nuclei or numerous counts often indicate tumor growth activity, and these expressions can be visualized with the aid of fluorescence imaging. Therefore, developing highly fluorescent, biocompatible, and sustainable biomarkers for imaging is a vital necessity for their extensive application in cancer diagnosis and therapy. In this work, we have demonstrated the cradle-to-gate transformation of abundant and cheap fossil fuel coke into a fluorescent probe for bioimaging. Herein, for the first time, a facile strategy for modulating the emission characteristics of coke-derived graphene system via doping of heteroatoms has been reported. It is found that the doping of nitrogen atoms could strongly influence photophysical properties, giving rise to increased quantum yield (16%), extended fluorescence lifetime (8.51 ns), and higher photostability (92%). Moreover, the as-synthesized nitrogen-doped graphene derivative is used as a potential labelling agent for the cellular imaging of cancerous cells, as well as normal cells, at concentrations ranging from 0 to 100 ?g/mL. For 24h incubation, the cells cultured with a concentration of 25 ?g/mL were observed to have an appreciable fluorescence accompanied by significant biocompatibility, with a viability value of ?85%. Considering the heteroatom-induced emission characteristics and bioanalytical acuities, it is prospective that the coke-derived graphene system can be further explored to elucidate its significance in biomedical applications, without compromising on economic and environmental sustainability. 2022 Elsevier Ltd -
Research on secure workload execution scheme in heterogeneous cloud environment
The increasing demand for the hardware, software and infrastructure is playing a big role in the information technology domain towards the need of customers specific requirements. Cloud computing is a major backbone for providing such services over the internet. It includes the services such as applications, storage, network, scalability, sharing, virtualization, confidentiality, security, authentication, and integrity. A large number of data intensive workflow applications uses heterogeneous cloud environment for communication and computation operation. An intruder/attacker will utilize these environments for their benefit by flooding malicious links, unwanted information and others. In cloud environment, detecting a malicious device/packet during workflow execution is a critical and challenging task. The various workflow method with security, service level agreement (SLA) and quality of service (QoS) have been modelled in recent time; However, these models are not efficient in detecting malicious users and maintaining high level of QoS or workflow applications. This article focus is on addressing research future direction, issues and challenges of work in meeting secure and efficient workflow execution model for heterogeneous cloud environment. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Network Based Detection of IoT Attack Using AIS-IDS Model
In recent days Internet of Things attained more familiarity. Although it is a promising technology, it tends to lead to a variety of security issues. Conventional methods such as IoT ecosystem based solutions were not suitable to give dilemmas to the system. A new system model called adaptive and intelligent Artificial Immune System (AIS) imitates the process of human being an immune system that consists of eligible properties of this varying environment. Therefore, it enhanced IoT security. Conventionally classifiers such as Random Forest Classifier, Recurrent Neural Network and K-nearest neighbours are used to classify the signals as normal or abnormal and predict malicious attacks. But unfortunately, these classifiers generated a high false alarm rate. Thus, a framework with maximum accuracy and minimum false alarm rate was required. In this work, the AIS model adopts the benefits of the Hopfield Neural Network (HNN) for classification. HNN classifier has a fixed weight, as it cannot be changed for its backpropagation property. This work optimally selects the fixed weight using Fast- Particle Swarm Optimization (F-PSO) and helps to enhance the accuracy of the HNN classifier. This classifier model then differentiates IoT attacks with a high detection rate and normal signal. Three datasets are taken to execute the proposed model and define its accuracy. The proposed Artificial Immune system using HNN for Intrusion Detection System (AIS-IDS) model exhibits 99.8% accuracy for the first dataset and minimum error value. The false alarm rate was minimized using danger theory and its high activation function; thus, the false alarm rate was minimized by up to 8% more than previous classifiers. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Prioritizing the Essentials: The MBA Aspirants Dilemma
Objective decision-making while choosing an appropriate college for a Master in Business Administration (MBA) is only half-done. It is critical that the student be able to find the best placement at the end of the course by acquiring the most critical skills/specializations affecting placements and involves data-driven decision-making based on past placement trends. Viti and Vania have done their preliminary selection, of ABC College for their MBA course, based on the colleges credence quality. However, they are trying to understand the key success factors (KSFs) affecting placements at ABC to focus their next two years on getting most placement-ready. Having been provided with the placement details of the outgoing batch, they are looking to analyze the data to discover the most critical parameters affecting placements. NeilsonJournals Publishing 2023. -
Genotoxic repercussion of high-intensity radiation (x-rays) on hospital radiographers
Recent technological advances in the medical field have increased the plausibility of exposing humans to high-intensity wavelength radiations like x-rays and gamma rays while diagnosing or treating specific medical maladies. These radiations induce nucleotide changes and chromosomal alterations in the exposed population, intentionally or accidentally. A radiological investigation is regularly used in identifying the disease, especially by the technicians working in intensive care units. The current study observes the genetic damages like chromosomal abnormalities (CA) in clinicians who are occupationally exposed to high-intensity radiations (x-rays) at their workplaces using universal cytogenetic tools like micronucleus assay (MN), sister chromatid exchange and comet assay. The study was conducted between 100 exposed practitioners from the abdominal scanning, chest scanning, cranial and orthopedic or bone scanning department and age-matched healthy controls. We observed a slightly higher rate of MN and CA (p <.05) in orthopedic and chest department practitioners than in other departments concerning increasing age and duration of exposure at work. Our results emphasize taking extra precautionary measures in clinical and hospital radiation laboratories to protect the practitioners. 2022 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals LLC on behalf of Environmental Mutagen Society. -
Experimental investigation and influence of filling ratio on heat transfer performance of a pulsating heat pipe
Experimental investigation of the two-phase system of a pulsating heat pipe taken into account useful heat transfer In the field of thermal management, many new prospective concepts and techniques have been developed, one of which is the pulsating heat pipe, a classic heat transfer technique. The PHP is constructed from 8 turns of copper tubes with inner diameters of 2 mm, wall widths of 1 mm, and a total length of 5324 mm. The CLPHP uses ethylene glycol as the functioning liquid at different fill proportions of 45 %, 55 %, 65 %, 75 %, and 85 % of its amount. The evaporator section is heated electrically by a plate heater ranging from 120 W to 600 W, and the condenser section is cooled by a continuous flow of cooling water. The results thermal resistance decreases gradually with an increase in heat transfer rate. It is apparent that a lower rate of thermal resistance is by a fill ratio of 55 %. The evaporator temperature is 181.57 C and the condenser temperature is 41.06 C for ethylene glycol measured for calculating heat transfer performance at 600 W, thermal resistance is 0.136 C/W, heat transfer coefficient is 526.45 W/m2-C, and enhanced heat transfer is thus good, exhibiting good improvement at a full percentage of 55 % and when compared with CFD results. 2023 Elsevier Ltd -
Design of a fractional-order atmospheric model via a class of ACT-like chaotic system and its sliding mode chaos control
Investigation of the dynamical behavior related to environmental phenomena has received much attention across a variety of scientific domains. One such phenomenon is global warming. The main causes of global warming, which has detrimental effects on our ecosystem, are mainly excess greenhouse gases and temperature. Looking at the significance of this climatic event, in this study, we have connected the ACT-like model to three climatic components, namely, permafrost thaw, temperature, and greenhouse gases in the form of a Caputo fractional differential equation, and analyzed their dynamics. The theoretical aspects, such as the existence and uniqueness of the obtained solution, are examined. We have derived two different sliding mode controllers to control chaos in this fractional-order system. The influences of these controllers are analyzed in the presence of uncertainties and external disturbances. In this process, we have obtained a new controlled system of equations without and with uncertainties and external disturbances. Global stability of these new systems is also established. All the aspects are examined for commensurate and non-commensurate fractional-order derivatives. To establish that the system is chaotic, we have taken the assistance of the Lyapunov exponent and the bifurcation diagram with respect to the fractional derivative. To perform numerical simulation, we have identified certain values of the parameters where the system exhibits chaotic behavior. Then, the theoretical claims about the influence of the controller on the system are established with the help of numerical simulations. 2023 Author(s). -
The LimbuTamang Communities of Sikkim History and Future of Their Demand for Reservation
Since its merger in 1975 with the Indian union, one of the major sociopolitical issues in Sikkim has been the demand for reservation in the state legislative assembly for two communitiesLimbu and Tamang. The demand of reservation for the Limbus and Tamangs crystallised in Sikkim when these communities were notified as Scheduled Tribes under the Scheduled Castes and Scheduled Tribes Orders (Amendment) Act, 2002. The history and future of this political demand has been analysed. 2023 Economic and Political Weekly. All rights reserved. -
LiST: A Lightweight Framework for Continuous Indian Sign Language Translation
Sign language is a natural, structured, and complete form of communication to exchange information. Non-verbal communicators, also referred to as hearing impaired and hard of hearing (HI&HH), consider sign language an elemental mode of communication to convey information. As this language is less familiar among a large percentage of the human population, an automatic sign language translator that can act as an interpreter and remove the language barrier is mandatory. The advent of deep learning has resulted in the availability of several sign language translation (SLT) models. However, SLT models are complex, resulting in increased latency in language translation. Furthermore, SLT models consider only hand gestures for further processing, which might lead to the misinterpretation of ambiguous sign language words. In this paper, we propose a lightweight SLT framework, LiST (Lightweight Sign language Translation), that simultaneously considers multiple modalities, such as hand gestures, facial expressions, and hand orientation, from an Indian sign video. The Inception V3 architecture handles the features associated with different signer modalities, resulting in the generation of a feature map, which is processed by a two-layered (long short-term memory) (LSTM) architecture. This sequence helps in sentence-by-sentence recognition and in the translation of sign language into text and audio. The model was tested with continuous Indian Sign Language (ISL) sentences taken from the INCLUDE dataset. The experimental results show that the LiST framework achieved a high translation accuracy of 91.2% and a prediction accuracy of 95.9% while maintaining a low word-level translation error compared to other existing models. 2023 by the authors. -
Knowledge of sexual abuse and resistance ability among children with intellectual disability
Background: Sexual abuse is a global concern among children with intellectual disabilities. Sexual abuse is frequent and long-lasting when the victim is a child with an intellectual disability. Moreover, the rate of sexual abuse is two to eight times the rate in the general population. Objective: This study aimed to investigate the knowledge of sexual abuse and resistance ability among children with intellectual disabilities. Participants and setting: The study was conducted among 120 children with mild or moderate intellectual disabilities attending twelve schools for specific purposes. Methods: We adopted a cross-sectional design to assess knowledge and resistance ability. Personal Safety Questionnaire and Modified What If Situation Test were administered verbally during individual interviews. Institutional Ethics Committee approved our study. Results: Current study suggests that children with intellectual disabilities have average knowledge (M = 6.6, SD = 1.6) regarding sexual abuse. More than 90 % of children demonstrated poor reporting skills. Although children exhibited good knowledge in differentiating appropriate from inappropriate touch requests, most children reported they would not disclose this incident to anyone. Conclusions: This study strongly suggests the need for a structured training program for children with intellectual disabilities to prevent sexual abuse. 2022 Elsevier Ltd -
Evaluation of tea (Camellia sinensis L.) phytochemicals as multi-disease modulators, a multidimensional in silico strategy with the combinations of network pharmacology, pharmacophore analysis, statistics and molecular docking
Tea (Camellia sinensis L.) is considered as to be one of the most consumed beverages globally and a reservoir of phytochemicals with immense health benefits. Despite numerous advantages, tea compounds lack a robust multi-disease target study. In this work, we presented a unique in silico approach consisting of molecular docking, multivariate statistics, pharmacophore analysis, and network pharmacology approaches. Eight tea phytochemicals were identified through literature mining, namely gallic acid, catechin, epigallocatechin gallate, epicatechin, epicatechin gallate (ECG), quercetin, kaempferol, and ellagic acid, based on their richness in tea leaves. Further, exploration of databases revealed 30target proteins related to the pharmacological properties of tea compounds and multiple associated diseases. Molecular docking experiment with eight tea compounds and all 30proteins revealed that except gallic acid all other seven phytochemicals had potential inhibitory activities against these targets. The docking experiment was validated by comparing the binding affinities (Kcalmol?1) of the compounds with known drug molecules for the respective proteins. Further, with the aid of the application of statistical tools (principal component analysis and clustering), we identified two major clusters of phytochemicals based on their chemical properties and docking scores (Kcalmol?1). Pharmacophore analysis of these clusters revealed the functional descriptors of phytochemicals, related to the ligandprotein docking interactions. Tripartite network was constructed based on the docking scores, and it consisted of seven tea phytochemicals (gallic acid was excluded) targeting five proteins and ten associated diseases. Epicatechin gallate (ECG)-hepatocyte growth factor receptor (PDB id 1FYR) complex was found to be highest in docking performance (10kcalmol?1). Finally, molecular dynamic simulation showed that ECG-1FYR could make a stable complex in the near-native physiological condition. Graphical abstract: [Figure not available: see fulltext.]. 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Broad-band mHz QPOs and spectral study of LMC X-4 with AstroSat
We report the results of broad-band timing and spectral analysis of data from an AstroSat observation of the high-mass X-ray binary LMC X-4. The Large Area X-ray Proportional Counter (LAXPC) and Soft X-ray Telescope (SXT) instruments onboard the AstroSat observed the source in 2016 August. A complete X-ray eclipse was detected with the LAXPC. The 340 keV power density spectrum showed the presence of coherent pulsations along with a ?26 mHz quasi-periodic oscillation feature. The spectral properties of LMC X-4 were derived from a joint analysis of the SXT and LAXPC spectral data. The 0.525 keV persistent spectrum comprised of an absorbed high-energy cut-off power law with photon index of ? ? 0.8 and cut-off at ?16 keV, a soft thermal component with kTBB ? 0.14 keV, and Gaussian components corresponding to Fe K?, Ne IX, and Ne X emission lines. Assuming a source distance of 50 kpc, we determined 0.525 keV luminosity to be ?2 1038 erg s?1 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Excited-state intramolecular proton transfer (ESIPT) salicylaldehyde Schiff bases: ratiometric sensing of ammonia and biologically relevant ions in solution and solid state
The intricate molecular architecture of ESIPT salicylaldehyde Schiff bases facilitates dynamic processes, inducing tunable photoluminescent properties. Notably, their halochromic nature, exhibiting colour changes in response to external stimuli, adds a vibrant dimension to their molecular repertoire. This sensitivity extends to environmental factors, making them valuable indicators for alterations in surroundings. The compound (E)-N-(3,5-dibromo-2-hydroxybenzylidene)-4-methylbenzohydrazide (PTBH) demonstrates exceptional sensitivity to ammonia, enabling real-time detection (LOD = 0.14 nM) in both solution (ratiometric) and the solid state. Moreover, their metal chelation capability allows simultaneous sensing of Mg2+ and Fe2+ ions, addressing environmental hazards. Exploiting molecular recognition, the fluorescent probe serves as sensors for amino acids, opening new avenues in biomedical diagnostics. The study introduces a novel solid-state emissive Schiff base, highlighting its stimuli-responsive photoluminescent properties and diverse applications, emphasising its potential in intelligent fluorescent materials for analytical and sensing technologies. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
An hybrid technique for optimized clustering of EHR using binary particle swarm and constrained optimization for better performance in prediction of cardiovascular diseases
The significant adoption of Electronic Health Records (EHR) in healthcare has furnished large new quantities of information for statistical machine gaining knowledge of researchers in their efforts to version and expects affected person health popularity, doubtlessly permitting novel advances in treatment. Unsupervised system learning is the project of studying styles in facts where no labels are present. In comparison to loads of optimization problems, an most beneficial clustering end result does not exist. One-of-a-kind algorithms with special parameters produce special clusters, and none can be proved to be the quality answer given that numerous good walls of the records might be found. In the previous work, a novel Two-fold clustering technique which uses the Long Short Term Memory (LSTM) technique (TFC: LSTM) for the prediction of Cardiovascular Disease (CVD) was proposed. The proposed model was fond to be experimentally efficient; however when applied to large EHR data, the model suffered from optimization issues on the number of clusters formed and time complexity. In order to overcome the drawbacks, this paper proposes a hybrid method of optimization using the Binary Particle Swarm (BPS) and Constrained Optimization (CO) for optimizing the number of clusters produced and to increase the efficiency in terms of decreasing the time complexity. 2022 The Authors -
Student-managed investment funds (SMIFs) in India: the perspectives of student fund managers
Purpose: This paper aims to explore how the student fund managers perceive the benefits of being part of the fund. Furthermore, this paper examines the country-specific challenges of setting up and managing a student-managed investment fund (SMIF) in India. Design/methodology/approach: Qualitative content analysis technique is used to identify, compare and retrieve critical themes about the present state of SMIF clubs in India. The data collection method involved structured, in-depth online interviews with ten student fund managers from various higher educational institutions in India. Findings: Some of the studys key findings indicate that the existence of SMIFs as part of learning facilitates group decision-making and peer learning. Additionally, this study brings to light specific issues related to registration, incorporating real-world practices and integrating SMIF into the academic curriculum. Social implications: The outcomes of this study shall be of use to students and the teaching fraternity across Indian colleges and universities who aspire to set up SMIFs as part of experiential learning. This study will also help existing SMIF clubs in India understand how their counterparts work and can consequently improvise their organizational structure and functioning. Originality/value: To the best of the authors knowledge, this is the first interview-based evaluation of the present structure of SMIFs structured as clubs in India. 2022, Emerald Publishing Limited.