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Background: The menstrual cycle pattern in women is related to high variability in cycle length of 21–35 days, flow lasts 4–7 days with an average loss of 15–80 ml of blood. The abnormal menstrual pattern is influenced by several factors, including dietary habits, physical exercises, family history of obesity and anthropometric parameters. Objectives: This research was carried out to establish numerous risk elements that depict abnormal menstrual cycle patterns amongst school-going adolescent girls in urban areas of Rishikesh, India. Methods: An age-matched case–control research was implemented in schools in the urban areas of Rishikesh between May and December 2019. A simple random sampling technique was carried out to choose urban wards and schools, and data were assembled in two steps. Adolescent girls (10–19 years) studying in the government and private schools (both Hindi and English medium) of urban Rishikesh areas were included and screened for abnormal menstrual patterns. Equal numbers of age-matched controls were also selected. Data were assembled using a self-scrutinised pre-designed pre-tested semi-structured questionnaire. The independent t-test, Mann–Whitney test, McNemar test, Chi-square test and Fisher’s exact tests were applied for data analysis using the SPSS software version 23.0. Results: A total of 200 school-going adolescent girls (100 cases and 100 age-matched controls) were included in this study. The strength of getting symptoms of menstruation was high amongst cases, and it was found that adolescent girls with high menstrual symptoms had more chances of developing menstrual abnormalities (odds ratio = 6.6; confidence interval = 2.9–17.2). Menstrual abnormality was found significantly associated (P < 0.05) with reduced physical activity, unhealthy dietary patterns and family history of obesity amongst school-going adolescent girls. Conclusions: Unhealthy lifestyles, improper diet, reduced physical activity and family history of obesity were strongly associated with the abnormal menstrual cycle pattern.

In this study, wavelet method has been proposed to solve fractal-fractional differential equations (FFDEs) with power law kernel (FFDPL) and exponential decay kernel (FFDED). The proposed method is based on scale 3 Haar wavelets with collocation method, and fractional integral operational matrices for derivatives of Caputo and Caputo–Fabrizio sense are derived to solve FFDPL and FFDED. The applicability of the proposed method is shown by solving some numerical examples, and the obtained results are compared with available solutions in the literature. The solutions are presented in the graphical and tabular forms also.

Prashant Singh,1 Gregory S Sayuk,2 David P Rosenbaum,3 Susan Edelstein,3 Kenji Kozuka,3 Lin Chang4 1Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; 2Department of Medicine, Washington University School of Medicine, St Louis, MO, USA; 3Ardelyx, Inc, Waltham, MA, USA; 4Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USACorrespondence: Prashant Singh, Department of Internal Medicine, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI, 48109, USA, Tel +1 734 647 9252, Fax +1 734 936 9849, Email singhpr@med.umich.eduBackground: Patients with irritable bowel syndrome with constipation (IBS-C) experience persistent abdominal pain, a common symptom leading to greater healthcare utilization and reports of treatment non-response. Clinically significant improvements in abdominal pain were observed in clinical trials of tenapanor, a first-in-class inhibitor of sodium/hydrogen exchanger isoform 3 (NHE3), for the treatment of IBS-C in adults.Aim: This narrative review reports the current knowledge about visceral hypersensitivity as a mechanism for abdominal pain in patients with IBS-C and explores the published evidence for hypothesized mechanisms by which tenapanor may reduce visceral hypersensitivity leading to the observed clinical response of decreased abdominal pain.Findings: Abdominal pain is experienced through activation and signaling of nociceptive dorsal root ganglia that innervate the gut. These sensory afferent neurons may become hypersensitized through signaling of transient receptor potential cation channel subfamily V member 1 (TRPV1), resulting in reduced action potential thresholds. TRPV1 signaling is also a key component of the proinflammatory cascade involving mast cell responses to macromolecule exposure following permeation through the intestinal epithelium. Indirect evidence of this pathway is supported by observations of higher pain in association with increased intestinal permeability in patients with IBS. Tenapanor reduces intestinal sodium absorption, leading to increased water retention in the intestinal lumen, thereby improving gastrointestinal motility. In animal models of visceral hypersensitivity, tenapanor normalized visceromotor responses and normalized TRPV1-mediated nociceptive signaling.Conclusion: By improving gastrointestinal motility, decreasing intestinal permeability and inflammation, and normalizing nociception through decreased TRPV1 signaling, tenapanor may reduce visceral hypersensitivity, leading to less abdominal pain in patients with IBS-C. Therapies that have demonstrated effects on visceral hypersensitivity may be the future direction for meaningful abdominal pain relief for patients with IBS-C.Keywords: IBS-C, NHE3, abdominal pain, TRPV1, sodium absorption, intestinal permeability

Bhumi Chaturvedi,1 Sourav Debnath,1 Hemant Bareth,1 Preeti Raj,2 Pratima Singh,3 Mahaveer Singh,4 Deepak Nathiya,1,5,6 Balvir Singh Tomar5– 7 1Department of Pharmacy Practice, National Institute of Medical Sciences and Research, Jaipur, Rajasthan, India; 2School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; 3Public Health and Preventive Medicine, University of Alberta, Edmonton, AB, Canada; 4Department of Endocrinology, National Institute of Medical Sciences and Research, Jaipur, Rajasthan, India; 5Department of Clinical Studies, Fourth Hospital of Yulin (Xingyuan), Yulin, Shaanxi, People’s Republic of China; 6Department of Clinical Sciences, Shenmu Hospital, Shenmu, Shaanxi, People’s Republic of China; 7Institute of Pediatric Gastroenterology and Hepatology, National Institute of Medical Sciences and Research, Jaipur, Rajasthan, IndiaCorrespondence: Mahaveer Singh, Department of Endocrinology, National Institute of Medical Sciences and Research, Nims University, Jaipur, Rajasthan, India, Email drms.mamcmed@gmail.comIntroduction: The ongoing repercussions of the COVID-19 pandemic include potentially deleterious impacts on bone health.Aim: This research aimed to ascertain the effects of COVID-19 on the bone health of obese and non-obese Indian individuals.Methods: We executed a case-control study enrolling individuals who recovered from COVID-19. Participants were stratified into obese and non-obese groups based on their BMI. Comprehensive assessments encompassed anthropometric evaluations, laboratory tests, and bone mineral density (BMD) measurements using dual-energy X-ray absorptiometry (DEXA).Results: From April to July 2022, we enrolled obese (n = 27, mean BMI = 30.54 ± 4.51 kg/m 2) and non-obese (n = 23, mean BMI = 21.97 ± 2.20 kg/m 2) individuals. The cohort’s average age was 36.08 ± 15.81 years, with a male-to-female ratio of 1.6:1. There was a difference in BMD, especially at the total hip, between the two groups. BMD at the spine (L1-L4), the neck of the femur, and ultra-distal radius were consistent across both groups. Weight exhibited a significant positive correlation with BMD at L1-L4 (r = 0.40, p = 0.003) and the left femur total (r = 0.27, p = 0.001). Haemoglobin levels were lower in the obese group compared to their non-obese counterparts (12.3 ± 2.0 vs 13.6 ± 1.9, p = 0.01). Multivariate analysis underscored weight as a crucial predictor for BMD at the spine (L1-L4, p = 0.003) and total hip (p = 0.001).Conclusion: Even with advanced age, obese post-COVID-19 individuals demonstrate a higher bone mineral density (BMD) at the hip than non-obese subjects.Keywords: COVID-19, obesity, bone mineral density, osteopenia, fracture risk

C16H14N2OS, monoclinic, P21/n (no. 14), a = 13.8369(4) Å, b = 15.8967(4) Å, c = 13.8600(4) Å, β = 109.983(1)°, V = 2865.11(14) Å3, Z = 8, R gt(F) = 0.0439, wR ref(F 2) = 0.1091, T = 296.15 K.

The present study was carried out to assess the water quality of Lakhota Lake. Objective water samples from five different sites were collected and analyzed from January 2023 to December 2024. Furthermore, the data obtained were processed to calculate the water quality index (WQI). The values obtained were compared with the guidelines for drinking purposes suggested by the World Health Organization and Bureau of Indian Standard. The results revealed that all the studied parameters were within the permissible limits except turbidity, TDS and EC, which exceeded the permissible limits. Among all the sites, site 5 was more heavily polluted than all the other sites. Among the heavy metals, iron was found above the permissible limits at Site 3, Site 4 and Site 5. Eight water quality parameters were used in the WQI approach to estimate the integrated groundwater quality. The WQI values ranged from 63.8 to 81.9, indicating that the Lakhota Lake water is not suitable for drinking water, including water from both humans and animals. At sites 1-4, the WQI falls in the poor category, while at site 5, it falls under the very poor category. There is a need for proper wastewater management in and around Lakhota Lake to protect the water quality and aesthetic properties of the lake. It is finally suggested that vegetation should also be planted at the boundaries of the lake, which will work as a natural purifier for the water of the lake.

Background: Medical education needs to be adjusted to meet the fast- changing expectations of society and the resulting demands on daily medical practice. The Medical Council of India (MCI) has updated the Medical Curriculum based on CBME. Objectives: 1. To assess the perceptions of the faculty members of the Medical college on the competency-based medical education curriculum for the MBBS course 2. To assess the readiness to incorporate competency-based medical education in the medical education curriculum among faculty members Methodology: This cross-sectional study was set in Kasturba Medical College, Mangalore, among teaching staff of pre-clinical, para-clinical, and clinical departments. A total of 93 (pre-clinical-29, para-clinical-31, clinical=33) faculty members were requested to fill out the questionnaire. Results: Our study highlights inter-department coordination, time demands, and lack of faculty training as the major barriers to the implementation of CBME. Among all participants around 60% were females. Most of the participants had teaching experiences between 0-5 years. Almost 95% of the participants were aware of the new MCI 2019 curriculum. The majority of the participants rated their knowledge about CMBE as moderate level (38.7%). 61.3% of the faculty members consider themselves to be ready to incorporate CBМЕ. According to most faculty members, a moderate amount (50%) of training is required and sessions and workshops (68.8%) are the most preferred type of training. Conclusion: Most of the faculty members found that the CBME pattern will be effective in imparting skills to undergraduates. Most of the participants identified inter-department coordination, demands of time, and lack of training in evaluation and feedback to be the major barriers to implementing the CBME pattern. Most of the faculty members consider themselves to be ready for this change even though a lot of them find the implementation of CBME to be a difficult task.

In order to efficiently and accurately diagnose train electrical faults, we propose a fault diagnosis method for electrical equipment based on virtual simulation technology. First, Creo software was used to build a subway train model. Then, 3DMAX software was used to make animation and demonstrate the working principle and action process of the train electrical system. Finally, using Unity 3D software, a human–computer interaction mechanism was established, achieving presence and realism. This system realizes the functions of knowledge learning, student assessment, principal display, and troubleshooting of the electrical system of subway trains and is compared with the method of manual diagnosis. Experimental results show that in the designed fault diagnosis system, the detection time for various types of faults is shorter than 30 s, whereas the diagnosis time of the manual diagnosis method is 30–52 s. It shows that the electrical equipment fault diagnosis system based on virtual simulation has the advantages such as short fault diagnosis time and high efficiency. In addition, the highest diagnostic accuracy of the manual diagnosis method is 75.48%, which is far lower than the accuracy of the diagnostic system. Conclusion: It is proved that the designed fault diagnosis system has the advantages such as short detection time and high accuracy and can meet the safety requirements of industrial production.

In the present work, aluminium alloy-based composites were developed for automobile applications. Aluminium-based functionally graded material (FGM) was developed by adding 2.5, 5 and 7.5 wt% of nanoparticles of alumina. The composites were made using gravity casting in an open hearth furnace with the surface temperature of FGM maintained at 750, 850 and 1,000°C. The microstructure of the samples was studied using scanning electron microscopy and particle distribution. The particle distribution was higher at the bottom in all compositions, which can be attributed to more solidification time. As the wt% of the Al2O3 increased, the volume fraction of particles also increased from the top surface to the bottom surface of the samples. After adding 7.5 wt% of Al2O3 and heating up to 1,000°C led to the grain refinement of the alloy. The increase in hardness from the top surface to the bottom surface of the sample verified the development of FGM. Due to increase in the solidification temperature, better reinforcement was observed in the developed FGM.

Background: Breast cancer is the most common cancer among women; however, the majority of them visit hospitals at an advanced stage. Knowledge of pathway of care will aid in timely intervention and better prognosis. Objectives: To find the pathway of health care for breast cancer and its correlates among the patients who have attended AIIMS Patna. To identify the reasons for seeking delayed definitive care. Methodology: A mixed-method cross-sectional design with quantitative and qualitative parts was conducted at AIIMS Patna between March 2021 and December 2022 among breast cancer patients. A total of 171 breast cancer patients were enrolled in this study. Piloted study tools were used. Descriptive analysis for quantitative part and manual thematic analysis for qualitative part were performed. Results: Out of total 171 participants, 88.9% (83.3–92.77%) had visited AIIMS Patna indirectly. About 60 (20.6%) visited informal providers or quacks, and 60 (39.5%) of the study participants visited more than one hospital before arriving at AIIMS Patna. The place of residence, treatment delay, and stage of cancer were found to be independent predictors of the pathway of healthcare for breast cancer. The reasons behind seeking delayed definitive care were identified under two major themes: presentation delay (misunderstanding or difficulty in identifying symptom, neglect of disease, lack of awareness about the disease, family support, financial constraints) and treatment delay (misdiagnosis, multiple referrals, dissatisfaction with the treatment, COVID-19 lockdown, informal providers/quacks) Conclusion: 9 out of 10 breast cancer patients had not come directly for definitive care, and among them, 3 out of 5 had visited multiple healthcare providers. So, it is important to educate the public on breast cancer, make systematized referral pathways, orient the private sector, and have trained manpower for screening purposes.

Background: Planning the waste management of all waste generated in healthcare facilities is a crucial task to reduce the hazards and risks to individuals and the community. Objectives: To assess the knowledge and practices regarding bio-medical waste management among paramedical staff and Group IV workers. Methods: In this cross-sectional study, 210 paramedical staff working at hospitals affiliated with Kasturba Medical College, Mangalore were assessed regarding their knowledge and practices regarding BMW. Institutional Ethics Committee permission was obtained before the commencement of the study. Data was analysed using IBM SPSS for Windows version 25.0, Armonk, New York, 25.0. Results: Among the total participants, there were 127 nurses, 6 lab technicians and 77 Group IV workers. 98.1% of healthcare providers were aware that their hospital has a waste management plan. 87.6% of healthcare providers follow hospital policies every time while disposing of waste. 92% of healthcare providers are aware of diseases transmitted by biomedical waste. The majority of the participants preferred using all five protective measures - gloves, goggles, masks, boots, and gowns while dealing with biomedical waste. Conclusion: The majority of the paramedical staff in our study were aware of the BMW management practices.

Saif Aldeen AlRyalat,1 Praveer Singh,2 Jayashree Kalpathy-Cramer,2 Malik Y Kahook2 1Department of Ophthalmology, The University of Jordan, Amman, 11942, Jordan; 2Department of Ophthalmology, University of Colorado School of Medicine, Sue Anschutz-Rodgers Eye Center, Aurora, CO, USACorrespondence: Malik Y Kahook, Department of Ophthalmology, University of Colorado School of Medicine, Sue Anschutz-Rodgers Eye Center, Aurora, CO, USA, Email Malik.Kahook@cuanschutz.eduAbstract: There has been a recent surge in the number of publications centered on the use of artificial intelligence (AI) to diagnose various systemic diseases. The Food and Drug Administration has approved several algorithms for use in clinical practice. In ophthalmology, most advances in AI relate to diabetic retinopathy, which is a disease process with agreed upon diagnostic and classification criteria. However, this is not the case for glaucoma, which is a relatively complex disease without agreed-upon diagnostic criteria. Moreover, currently available public datasets that focus on glaucoma have inconstant label quality, further complicating attempts at training AI algorithms efficiently. In this perspective paper, we discuss specific details related to developing AI models for glaucoma and suggest potential steps to overcome current limitations.Keywords: artificial intelligence, glaucoma, deep learning, optic disc, segmentation

The morphological and molecular characterisations of two lance nematode species isolated from the rhizosphere of banana, Hoplolaimus seinhorsti and H. pararobustus, are provided based on an integrative study that includes light and scanning electron microscopy, phylogenetic analysis and two tree-based molecular species delimitation methods (GMYC and bPTP). Nineteen new sequences were obtained, including 5 partial 18S rRNA, 6 D2-D3 of 28S rRNA, 1 ITS rRNA and 7 COI mtDNA (the first COI sequences of H. seinhorsti and H. pararobustus), and an updated morphological character comparison of 37 Hoplolaimus species is presented. The tree-based molecular species-delimitation approaches employed gave markedly differing results, and also showed remarkable discrepancies among the investigated genes, although the bPTP output was found to agree well with established morphological species delimitations. Both species-delimitation approaches did, however, provide the same output for the COI mtDNA sequences, and the COI mtDNA gene sequence was also found to correspond better to established morphological species. It is therefore recommended by this paper as representing the most suitable barcode marker for Hoplolaimus species identification. This integrative study also resulted in the corrective reassignment of 17 gene sequences that were previously unidentified or incorrectly classified, as well as concluding that H. pararobustus consists of two cryptic species.

Study aim: To study knock knee deformity and the body mass index among male school students of Chandigarh, India. The study also intended to evaluate the association of knock knee deformity with BMI.

With the wide popularization of Internet of Things (IoT) technology, the design and implementation of intelligent speech equipment have attracted more and more researchers’ attention. Speech recognition is one of the core technologies to control intelligent mechanical equipment. An industrial IoT sensor-based broadcast speech recognition and control system is presented to address the issue of integrating a broadcast speech recognition and control system with an IoT sensor for smart cities. In this work, a design approach for creating an intelligent voice control system for the Robot operating system (ROS) is provided. The speech recognition control program for the ROS is created using the Baidu intelligent voice software development kit, and the experiment is run on a particular robot platform. ROS makes use of communication modules to implement network connections between various system modules, mostly via topic-based asynchronous data transmission. A point-to-point network structure serves as the communication channel for the many operations that make up the ROS. The hardware component is mostly made up of the main controller’s motor driving module, a power module, a WiFi module, a Bluetooth module, a laser ranging module, etc. According to the experimental findings, the control system can identify the gathered sound signals, translate them into control instructions, and then direct the robot platform to carry out the necessary actions in accordance with the control instructions. Over 95% of speech is recognized. The control system has a high recognition rate and is simple to use, which is what most industrial controls require. It has significant implications for the advancement of control technology and may significantly increase production and life efficiency.

This research article explores the viability of biodegradable nanomaterials for sustainable food packaging applications. The study involves a thorough analysis of the materials, including material characterisation, mechanical testing, barrier testing, and biodegradation tests. The material characterisation demonstrates a consistent distribution of nanoparticles throughout the polymer matrix, as validated by SEM and TEM examination. XRD analysis also indicates the presence of crystalline phases in the nanomaterials. FTIR spectroscopy is a technique that can identify specific functional groups and chemical bonds in a substance, allowing us to get knowledge about its composition and compatibility. Ongoing research and development are crucial to enhance the efficiency and economic feasibility of packaging materials made from biodegradable nanomaterials. This will help advance the sustainability of the food packaging sector.

In order to tackle the worldwide problems of water pollution and shortage, this work explores the green synthesis of nanocomposite membranes for sustainable water filtering. Graphene oxide, cellulose nanocrystals, and silver nanoparticles were used as nanofillers in the fabrication of nanocomposite membranes, which were made using renewable polymer matrix (PES, PVDF, PAN). By including different polymer matrices and nanofillers, the composition analysis demonstrated the adaptability of nanocomposite membrane manufacturing, enabling the customization of membrane characteristics. Improved membrane shape and structural integrity were shown to result from the homogeneous dispersion of nanofillers inside the polymer matrix, according to characterization tests. Nanocomposite membranes demonstrated high flux rates and rejection rates for different pollutants, confirming their excellent performance in filtration experiments. The membranes' improved fouling resistance also increased their service life and decreased the frequency of maintenance needs. Supporting the eco-friendliness of nanocomposite membrane production, an environmental impact evaluation found that it used less energy and generated less trash than traditional techniques. All things considered, nanocomposite membranes have shown great promise as long- term water treatment solutions due to their superior performance, durability, and environmental friendliness, as well as their effective production and characterisation. More study is needed to perfect membrane characteristics and solve the remaining problems that prevent their broad use in water treatment systems.

Biodiesel manufacturing from waste cooking oil has emerged as a potential alternative in the search of sustainable energy. This process helps mitigate environmental pollution and reduces reliance on fossil fuels. This research examines the catalytic efficiency of environmentally friendly catalysts in this process, with a specific emphasis on catalysts based on enzymes. It assesses their effectiveness in terms of the production of biodiesel, the rate of the chemical reactions, cost efficiency, and their influence on the environment. Experimental evidence demonstrates that enzyme-based catalysts have enhanced catalytic activity, leading to an average biodiesel production of 90%, outperforming traditional catalysts such as solid acids, bases, and heterogeneous metal catalysts. Moreover, enzyme catalysts exhibit enhanced reaction rates due to their unique enzymatic activity and gentle reaction conditions. The cost study shows that the manufacturing costs for enzyme catalysts are competitive, with an average total cost of $800, which is equivalent to traditional catalysts. Environmental impact evaluation emphasizes the sustainability of enzyme catalysts by demonstrating their lower energy consumption, waste production, and greenhouse gas emissions compared to traditional alternatives. The results highlight the capacity of green catalysts, namely enzyme-based catalysts, to enhance sustainable biodiesel production methods, hence promoting a more eco-friendly and robust energy framework.

This research explores the transformative part of nanomaterials in progressing urban maintainability through the integration of renewable vitality frameworks. Synthesized quantum dabs, carbon nanotubes, and graphene were characterized and connected over assorted applications, counting solar vitality saddling, wind vitality improvement, vitality capacity, and urban foundation improvement. In solar cells, the integration of quantum specks resulted in an eminent increment in control transformation proficiency (PCE), with an 85% change in short-circuit current thickness (J sc) and a 20% increment in open-circuit voltage (Voc). Wind turbine edges upgraded with carbon nanotubes displayed a momentous 21% rise in control yield and a 40% advancement in soundness, emphasizing the potential of nanomaterials in optimizing wind vitality frameworks. Graphene-based supercapacitors illustrated a multiplied particular capacitance and a 10% increment in cyclic solidness, underscoring the adequacy of nanomaterials in vitality capacity applications. The consolidation of nanocomposite building materials showcased a 44% diminishment in warm conductivity, contributing to made strides cover for maintainable urban foundations. Nanosensors, coordinated into smart frameworks, showed a prevalent 80% increment in affectability and a 50% lessening in reaction time compared to customary sensors.

The incidence of hospital and community acquired infections has globally increased worldwide. The concentration of the disinfectants is important to give its higher efficacy against pathogens or microorganisms. Microorganisms are part of or environment cause major or severe diseases to reduce the risk of these diseases we generally clean surrounding by using cleaning agents like soaps, antiseptics or disinfectants. So to check weather these disinfectants are performs there work against specific bacteria or microorganism we performed this test to check the effectiveness of disinfectants against specific microorganism and fungus. Five bacterial types that are frequently acquired in hospitals from which two are gram positive organism, two are gram negative organism and single strain of fungus ‘(Pseudomonas aeruginossa, Klebsiella pneumoniae, Staphylococcus aureus (MRSA), Acinetobacter baumannii, Candida tropicalis) (clinical isolates) were examined for their susceptibility against 3 commonly used disinfectants hospitals Chlorine releasing agent, Quaternary ammonium compound and Aldehyde free disinfectant). The turbidity in the nutrient broth and the growth in culture media showed that all three disinfectants had lowered the microbial growth of every clinical strain. In general, the reference strains have lower growth and turbidity than the clinical strains. When combined, our results demonstrated that every product we examined had a high disinfection killing rate against microorganisms from various sources, indicating the excellent caliber of these goods. In response to rising disinfectant usage, hand sanitizer production has expanded to keep up with demand. Normal flora or microorganisms are part of our body in everyday life in which some are necessary some are unnecessary and can cause major or severe diseases to avoid from these diseases we generally clean our self and surrounding by using cleaning agents like soaps, antiseptics or disinfectants. So, to check weather these sterilizing agents are performed their work against specific bacteria or microorganism we performed this test to check the effectiveness of disinfectants against specific microorganism and fungus.

The heme oxygenase-1 (HMOX1) gene is a very critical player in cell homeostasis and takes part in heme catabolism. The HMOX1 gene possesses antioxidant, antiapoptotic anti-inflammatory, and antithrombotic properties. This study aimed to identify the deleterious SNPs which may alter the functional and structural attributes of the HMOX1 protein.

This paper analyses the climate change mitigation strategies adopted by industries from the first commitment period of Kyoto Protocol (2008) till present day (2023). A systematic literature review was conducted using the AND operator to customise articles published in Scopus database of 15 years of first commitment period of Kyoto Protocol (2009–2023). Findings show that all the climate change mitigation strategies (CCMS) identified can broadly be classified into managerial and technological. These strategies span from carbon offsets to start-up (ex. renovation in construction industries) to hydrogen as an energy source. VOSviewer network analysis of research paper showed that large number of countries are working closely on CCMS with USA in the forefront. Keywords like climate change, sustainability, greenhouse gas (GHG) were found to be most common in the research articles. This study confirms the significance of adopting managerial and technological strategies in industries for sustainability management. In addition, finance for climate policy and mitigation in terms of cost effectiveness, trade-offs, pollution tax, investments seem to possess a considerable influence on the climate governance.

Blockchain, an emerging technology reshaping numerous industries, has garnered significant attention from researchers due to its myriad benefits and the plethora of research opportunities it presents across various sectors. With the rapid evolution of blockchain research publications, there's a growing demand for thorough investigative studies to assess the current knowledge landscape in this field. While a few review articles have addressed recent developments and challenges in blockchain technology, there hasn't been any bibliometric analysis utilizing the Web of Science (WoS) as a dataset to gauge the assertiveness of the art inblockchain research. Hence, conducting a comprehensive bibliometric study becomes imperative. This study focused on analyzing all unionidentifications, and articles, and examiningdocuments on blockchain indexed by WoS from [7] to [19], categorizing them into five research topics. The findings yielded valuable insights, including trends in annual journals and quotes, popular seekfields, first-leading papers, preferred journalboards, and notable funding sources. The study's conclusions offer various recommendations that can serve as a benchmark for both novice and qualified researchers embarking on blockchain research endeavours’. can be used as a benchmark before beginning a blockchain study development in the prospect.

This study focuses on fabrication of SAF2507 similar joints with modified microwave hybrid heating (MHH) method and optimization of the elemental constitution based on energy dispersive spectroscopy (EDS) results. Major input parameters were in this work were filler powder (P), number of graphite rods (R) and process time (T). Each input parameter was varied to three different levels; such as P1, P2 and P3 being no powder, nickel powder and SS304 powder respectively; R1, R2 and R3 being 6, 8 and 10 number of graphite rods respectively; T1, T2 and T3 being 480, 540 and 600 seconds respectively. Experiments were performed as per L9 array based experimental design. EDS based elemental constitution results were used during optimization purpose. Weight percent of Cr, C and Ni have been considered for optimization. Additionally, the mechanical characterization of joints has also been carried out using micro-hardness tests.

Results on collisions of 16O nuclei performed at the Relativistic Heavy Ion Collider (RHIC) have been presented for the first time at Quark Matter 2023 by the STAR collaboration. 16O+16O collisions are also expected to take place in the near future at the Large Hadron Collider (LHC) at much higher beam energies. We explore the potential of beam-energy-dependent studies for this system to probe small-x dynamics and QCD evolution. We perform 3 + 1D IP-Glasma simulations to predict the rapidity dependence of the initial geometry of light-ion collisions, focusing on 16O+16O and 20Ne+20Ne collisions at √SNN = 70 GeV and 7 TeV. The choice of 20Ne is motivated by its strongly elongated geometry, which may respond differently to the effect of the highenergy evolution compared to the more spherical 16O. We find that smearing induced by soft gluon production at high energy causes mild variations in the initial-state eccentricities as a function of the collision energy. These effects could be resolved in future experiments and deserve further investigation.

This study focuses on the possible transformative effects that green nanotechnology has in the healthy energy applications and the repression of nature`s negative impacts. By means of environmentallyfriendly production of these nanomaterials, including silver nanoparticles (AgNPs) and quantum dots, the current research produced the marked increase in efficiency of solar cells, with a jump to 53% in efficiency compared to traditional solar cells. Moreover, the dopping of lithium-ion cells with silicon nanoparticles brought about a great enhancement, exhibiting a 50% specific capacity progress contrasted with the batteries that continued traditional anodes. Hence, these excellent findings demonstrate the effectiveness of nanotechnology in transforming energy that gathers and holds technology. The paper did an LCA that entailed a detailed analysis of the life cycle of green nanomaterials in order to measure the impact on the environment. The analysis presented by the LCA indicated the application of alternative materials that resulted in a significant reduction of GHG’s (32%), energy of 33%, and In TP of 37%) in comparison with conventional ones. This highlights the sustainability gains that will be obvious by the use of green nanotechnology as a technology of choice, in energy applications. The findings provide numerous beneficial principles for development of green technologies.

The popularity of anime is increasing exponentially in every part of the world due to its unique storyline, nonstop entertainment, fights, and similar type of content that can hold viewers and keeps them at the edge of their seats. However, with the increase of popularity in anime there has also been an exponential increase in violence and brutality in anime videos. Violent scenes have become much more common in anime videos when compared to generic cinema. This survey paper presents a comprehensive view on the detection of violence in movies and different scenarios using various techniques. Most commonly to automate detection of violence, machine learning is used for training the machine to detect violence. Convolution neural networks (CNN) are used very commonly to understand image pattern recognition with high accuracy. Moreover, use of other different methods such as LSTM and Markov models are also used to detect violence. The main goals kept in mind while working is to detect violence with high accuracy and to use less computation or to perform the action at a high-speed rate.

The COVID-19 outbreak has punctured every part of a person's life, along with how people perform, enjoy, study, work out, and interact with one another. The debunking industry has tried to lessen the enormous spread of false information in modern society due to the growth of social media. Current research investigates debunked fallacious content relating to COVID-19 in India, intending to understand the key themes and trends in fabricated content for health literacy. The study is exploratory and uses supervised machine learning for the purpose of classification. The study uses thematic analysis techniques to look at the 506 claims of false information about COVID-19 that Indian fact-checking platforms have refuted. The results discern specific trends and health literacy within the range. The tendency toward fallacious content starts with anger toward China and creates communal hatred against India's minority group. Political propaganda, then false health information, was the main subject of such content. Moreover, many misrepresented and refuted claims came from the mainstream media.

Cancer is a wide-spreading disease. Its count goes on increasing and became the second leading cause of death in respect of diseases. New cancer-targeting molecules are explored. In this study, we tried to collect information about one such molecule, OTX015. Articles were searched across reputed search engines and publishers such as Cochrane, EMBASE, The Lancet, PubMed, GoogleScholar, ScienceDirect, Wiley Online, Springer and Bentham Science by using different keywords: “OTX015”, “Cancer”, “Small molecule PROTACs”, “BRD/BET” and “BET inhibitors”. The quality papers were retrieved, studied, categorized into different sections, analyzed, and used for article writing.OTX015 is a novel molecule in clinical trials. It showed some promising results in various cancers as well as other diseases like latent-HIV with the least side-effects.This article will give an insight into Small Molecules as PROTACs, their advantages and disadvantages, OTX015 and its PROTAC ARV- 825. It is advised that more research/studies are required to be carried out to know more about OTX015 and other PROTACs, their advancements, receptors, and mechanism/ mode of action to know their abilities to work against proteins involving diseases.

In software development, defects influence the quality and cost in an undesirable way. Software defect prediction (SDP) is one of the techniques which improves the software quality and testing efficiency by early identification of defects(bug/fault/error). Thus, several experiments have been suggested for defect prediction (DP) techniques. Mainly DP method utilises historical project data for constructing prediction models. SDP performs well within projects until there is an adequate amount of data accessible to train the models. However, if the data are inadequate or limited for the same project, the researchers mainly use Cross-Project Defect Prediction (CPDP). CPDP is a possible alternative option that refers to anticipating defects using prediction models built on historical data from other projects. CPDP is challenging due to its data distribution and domain difference problem. The proposed framework is an effective two-stage approach for CPDP, i.e., model generation and prediction process. In model generation phase, the conglomeration of different pre-processing, including feature selection and class reweights technique, is used to improve the initial data quality. Finally, a fine-tuned efficient bagging and boosting based hybrid ensemble model is developed, which avoids model over -fitting/under-fitting and helps enhance the prediction performance. In the prediction process phase, the generated model predicts the historical data from other projects, which has defects or clean. The framework is evaluated using25 software projects obtained from public repositories. The result analysis shows that the proposed model has achieved a 0.71±0.03 f1-score, which significantly improves the state-of-the-art approaches by 23 % to 60 %.

Fatima Bawany,1 Gayin Lee,2 Yasmine Nousari,3 Christopher Ritchlin,2 Partik Singh,4 Francisco Tausk2,4 1Department of Dermatology, New York University, New York, NY, USA; 2Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA; 3Mongan Institute, Massachusetts General Hospital, Boston, MA, USA; 4Department of Dermatology, University of Rochester Medical Center, Rochester, NY, USACorrespondence: Francisco Tausk, Department of Dermatology, University of Rochester Medical Center, 601 Elmwood Ave, Box 697, Rochester, NY, 14642, USA, Email Francisco_Tausk@urmc.rochester.eduAbstract: We present the first case of a patient with indolent polyarteritis nodosa who suffered severe exacerbations following significant emotional stressors. This report highlights the close relationship between emotions and autoimmune diseases mediated by the deleterious effects of stressors presumptively by skewing immunity from Type 1 to Type 2.Keywords: psychology, autoimmunity, vasculitis, stressors

The aim of this article was to discuss the modeling and control method of quadrotor unmanned aerial vehicle (UAV). In the process of modeling, mechanism modeling and experimental testing are combined, especially the motor and propeller are modeled in detail. Through the understanding of the body structure and flight principle of the quadrotor UAV, the Newton–Euler method is used to analyze the dynamics of the quadrotor UAV, and the mathematical model of the UAV is established under the small angle rotation. Process identifier (PID) is used to control it. First, the attitude angle of the model is controlled by PID, and based on this, the speed in each direction is controlled by PID. Then, the PID control of the four rotor aircraft with the center of gravity offset is simulated by MATLAB. The results show that the pitch angle and roll angle can be controlled by 5 degrees together without center of gravity deviation, and the PID can effectively control the control quantity and achieve the desired effect in a short time. Classical BP algorithm, classical GA-BP algorithm, and improved GA-BP algorithm were trained, respectively, with a total of 150 sets of training data, training function uses Levenberg-Marquardt (trainlm), and performance function uses mean squared error (MSE). In the background of the same noise, the improved GA-BP algorithm has the highest detection rate, classical GA-BP algorithm is the second, and classical BP algorithm is the worst. The simulation results show that the PID control law can effectively control the attitude angle and speed of the rotor UAV in the case of center of gravity deviation.

Acharya Balkrishna,1,2 Kuldeep Singh,3 Gurpreet Oberoi,3 Pratima Singh,1,4 Preeti Raj,1 Anurag Varshney1,2,5 1Clinical Research Division, Patanjali Research Institute, Haridwar, Uttarakhand, India; 2Department of Allied and Applied Sciences, University of Patanjali, Haridwar, Uttarakhand, India; 3Dental Clinic & Research Center, Patanjali Bharatiya Ayurvigyan Evam Anusandhan Sansthan, Haridwar, Uttarakhand, India; 4School of Public Health, University of Alberta, Edmonton, Canada; 5Special Centre for Systems Medicine, Jawaharlal Nehru University, New Delhi, IndiaCorrespondence: Anurag Varshney, Email anurag@prft.co.inIntroduction: COVID-19 pandemic has imposed nation-wide lock-downs which severely impacted day-to-day lifestyle and caused anxiety, stress and fear among patients taking medical care including dental treatments. These psychological behaviors have also been observed during the strategic relaxation of social restrictions (Unlock). However, potential effect of these psychological behavior in endodontic cases have not been probed. Here, it is of great interest to explore the magnitude and buffering effect of two important psychological resources: satisfaction-with-life, and confidence in hospital-infection-control-policy in relation with COVID-19 risk perception on psychological impact due to fear for COVID-19.Methods: Patients visiting Dental Clinic & Research Center for endodontic procedures were randomly asked to fill survey questionnaire, and were later enrolled as per the study criteria. The study carried out in two phases: from 15 Sept 2020 to 15 Dec 2020 (restrained confinement; Unlock 1.0); and from 16 Dec 2020 to 12 Feb 2021 (mild confinement; Unlock 2.0) with total sample size of 136. We used data collection tools such as fear-of-COVID-19 scale (FCV-19), perceived-stress-scale (PSS), modified-dental-anxiety-scale (MDAS), satisfaction-with-life scale (SWLS), COVID-19 risk perception, and confidence in hospital-infection-control-policy for COVID-19.Results: A double moderation and dual moderated mediation structured model were used to establish the correlation of various parameters using SPSS (version 25.0) software suite. Confidence in hospital-infection-control-policy and SWLS were negatively correlated with FCV-19, MDAS, and PSS. Risk perception of COVID-19 was found to positively associated with FCV-19, MDAS, and PSS.Discussion: Patient’s confidence in hospital-infection-control-policy for COVID-19 and SWLS acted as independent moderator for FCV-19 and mental distress. FCV-19 and risk perception were found to be lower during mild confinement (Unlock 2.0), and were also the positive predictors of PSS; and negative predictors of SWLS. The higher SWLS correlated very well with lower COVID-19 risk perception, concerning PSS and MDAS.Keywords: fear for COVID-19, risk perception of COVID-19, perceived stress, dental surgical procedures, satisfaction with life

In order to realize and design a software monitoring and early warning system for the Internet of Things (IoT), this paper establishes a “trinity” control platform integrating PLC, WINCC, and MATLAB based on nonlinear technology and realizes the proportion integration differentiation (PID) control based on the RBF neural network tuning on this platform. Based on the framework of the trinity control platform, the PID control system set by the radial basis function (RBF) neural network and the STEP7 virtual object programming of the control platform are designed and realized. The experimental data update cycle is 0.5 s to record 1,000 data item objects, U is the control quantity, which is associated with the U communication driver variable in WINCC, and the corresponding storage address in the PLC is MD200; Yout is the controlled quantity, which is related to the Yout communication driver variable in WINCC, and the corresponding storage address in the PLC is MD100; start is the control switch, associated with the start communication driver variable in WINCC, corresponding to the storage address in the PLC of M0.1; reset is the reset control switch, It is associated with the reset communication driver variable in WINCC, and corresponds to the storage address in the PLC as M0.0. KP, KI, KD, and TIME correspond to three real-time PID parameters and are the cycle time in MATLAB (used for the X-axis of trend graphing), and are the variables of the communication driver. The addresses in the PLC are MD20, MD24, MD28, and MD32. It shows that for these three software programs, the update cycle of the data in the respective storage areas must be consistent, the program control cycles in MATLAB and PLC need to be consistent, and the transmission of parameters must be correctly implemented in a control cycle according to the programming logic sequence, in order to realize the design of an IoT software monitoring and early warning system.

A new root-knot nematode (RKN) species, Meloidogyne karsseni n. sp., associated with sweet pepper from Mexico, and a population of M. paranaensis from Guatemala, are described using data from morphological, biochemical (isozyme enzymes), molecular, and phylogenetic analyses. Meloidogyne karsseni n. sp. can be morphologically diagnosed using the combined features of the second-stage juveniles, viz. body length (345 to 422 μm), a conical rounded head region, a post-labial annule lacking transverse striation, a thin stylet 11 to 12 μm long, rounded to oval and backwardly sloping knobs, dorsal gland orifice (DGO) at 5.2 to 6.0 μm from the knobs, a hemizonid just above the secretory-excretory (SE) pore, a tapering tail with finely rounded terminus and one or two very weak constrictions at hyaline tail tip; the female characters viz. oval-to-rounded perineal pattern with coarse striation on lateral sides around the anus, low dorsal arch with finer striations, and distinctly visible lateral lines; and the male characteristics viz. a rounded and continuous head, a post-labial annule without transverse striations, a robust stylet 20 to 24 μm long, rounded-to-oval and slightly backwardly sloping knobs, and a DGO at 2.4 to 2.9 μm from the knobs. In all the studied males of M. paranaensis, a characteristic sclerotization around the duct of SE-pore was also observed for the first time. Sequences of 18S, D2–D3 of 28S, and ITS of rDNA, and cox1 of mtDNA were generated for the two species, and in the phylogenetic trees based on these genes, both species appeared in the tropical RKN species complex clade.