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Retinitis pigmentosa (RP), a heterogenous group of inherited retinal disorder, causes slow progressive vision loss with no effective treatments available. Mutations in the rhodopsin gene (RHO) account for ~25% cases of autosomal dominant RP (adRP). In this study, we describe the disease characteristics of the first-ever reported mono-allelic copy number variation (CNV) in RHO as a novel cause of adRP. We (a) show advanced retinal degeneration in a male patient (68 years of age) harboring four transcriptionally active intact copies of rhodopsin, (b) recapitulated the clinical phenotypes using retinal organoids, and (c) assessed the utilization of a small molecule, Photoregulin3 (PR3), as a clinically viable strategy to target and modify disease progression in RP patients associated with RHO-CNV. Patient retinal organoids showed photoreceptors dysgenesis, with rod photoreceptors displaying stunted outer segments with occasional elongated cilia-like projections (microscopy); increased RHO mRNA expression (quantitative real-time PCR [qRT-PCR] and bulk RNA sequencing); and elevated levels and mislocalization of rhodopsin protein (RHO) within the cell body of rod photoreceptors (western blotting and immunohistochemistry) over the extended (300 days) culture time period when compared against control organoids. Lastly, we utilized PR3 to target NR2E3, an upstream regulator of RHO, to alter RHO expression and observed a partial rescue of RHO protein localization from the cell body to the inner/outer segments of rod photoreceptors in patient organoids. These results provide a proof-of-principle for personalized medicine and suggest that RHO expression requires precise control. Taken together, this study supports the clinical data indicating that RHO-CNV associated adRPdevelops as a result of protein overexpression, thereby overloading the photoreceptor post-translational modification machinery.

Short food supply chains are essential for building strong relationships between regional producers and customers, promoting sustainability, supporting local economies, and guaranteeing easy access to premium, fresh goods. However, the mismatch between producer supply and consumer demand presents difficulties for this vital industry, preventing it from reaching its full potential for development (Cirone et al., 2023). Increased focus on sustainability in food chains has come from a wide range of stakeholders, including suppliers, policy officials, researchers, consumers, and food producers. The fact that short food supply chain (SFSC) efforts have grown significantly and provide an alternative to the globalized food chains that are now common in the food business is further proof of this growing interest (Paciarotti& Torregiani, 2021).The objective of this study is to explore consumer awareness and satisfaction regarding short food supply chains. The research methodology employed a simple random sampling technique to collect data from respondents in Coimbatore city through surveys. The collected data were analyzed using simple percentage analysis, factor analysis using SPSS, and path analysis via AMOS. The study aims to measure the sustainability of short food supply chains by exploring consumer satisfaction qualitatively. The findings provide insights into the effectiveness of local food systems in meeting consumer expectations and promoting sustainable practices.

Short food supply chains are essential for building strong relationships between regional producers and customers, promoting sustainability, supporting local economies, and guaranteeing easy access to premium, fresh goods. However, the mismatch between producer supply and consumer demand presents difficulties for this vital industry, preventing it from reaching its full potential for development (Cirone et al., 2023). Increased focus on sustainability in food chains has come from a wide range of stakeholders, including suppliers, policy officials, researchers, consumers, and food producers. The fact that short food supply chain (SFSC) efforts have grown significantly and provide an alternative to the globalized food chains that are now common in the food business is further proof of this growing interest (Paciarotti& Torregiani, 2021).The objective of this study is to explore consumer awareness and satisfaction regarding short food supply chains. The research methodology employed a simple random sampling technique to collect data from respondents in Coimbatore city through surveys. The collected data were analyzed using simple percentage analysis, factor analysis using SPSS, and path analysis via AMOS. The study aims to measure the sustainability of short food supply chains by exploring consumer satisfaction qualitatively. The findings provide insights into the effectiveness of local food systems in meeting consumer expectations and promoting sustainable practices.

BACKGROUND: Colorectal cancer is a common condition with an uncommon burden of disease, heterogeneity in manifestation, and no definitive treatment in the advanced stages. Renewed efforts to unravel the genetic drivers of colorectal cancer progression are paramount. Early-stage detection contributes to the success of cancer therapy and increases the likelihood of a favorable prognosis. Here, we have executed a comprehensive computational workflow aimed at uncovering the discrete stagewise genomic drivers of colorectal cancer progression.METHODS: Using the TCGA COADREAD expression data and clinical metadata, we constructed stage-specific linear models as well as contrast models to identify stage-salient differentially expressed genes. Stage-salient differentially expressed genes with a significant monotone trend of expression across the stages were identified as progression-significant biomarkers. The stage-salient genes were benchmarked using normals-augmented dataset, and cross-referenced with existing knowledge. The candidate biomarkers were used to construct the feature space for learning an optimal model for the digital screening of early-stage colorectal cancers. The candidate biomarkers were also examined for constructing a prognostic model based on survival analysis.RESULTS: Among the biomarkers identified are: CRLF1, CALB2, STAC2, UCHL1, KCNG1 (stage-I salient), KLHL34, LPHN3, GREM2, ADCY5, PLAC2, DMRT3 (stage-II salient), PIGR, HABP2, SLC26A9 (stage-III salient), GABRD, DKK1, DLX3, CST6, HOTAIR (stage-IV salient), and CDH3, KRT80, AADACL2, OTOP2, FAM135B, HSP90AB1 (top linear model genes). In particular the study yielded 31 genes that are progression-significant such as ESM1, DKK1, SPDYC, IGFBP1, BIRC7, NKD1, CXCL13, VGLL1, PLAC1, SPERT, UPK2, and interestingly three members of the LY6G6 family. Significant monotonic linear model genes included HIGD1A, ACADS, PEX26, and SPIB. A feature space of just seven biomarkers, namely ESM1, DHRS7C, OT

BACKGROUND: Colorectal cancer is a common condition with an uncommon burden of disease, heterogeneity in manifestation, and no definitive treatment in the advanced stages. Renewed efforts to unravel the genetic drivers of colorectal cancer progression are paramount. Early-stage detection contributes to the success of cancer therapy and increases the likelihood of a favorable prognosis. Here, we have executed a comprehensive computational workflow aimed at uncovering the discrete stagewise genomic drivers of colorectal cancer progression.METHODS: Using the TCGA COADREAD expression data and clinical metadata, we constructed stage-specific linear models as well as contrast models to identify stage-salient differentially expressed genes. Stage-salient differentially expressed genes with a significant monotone trend of expression across the stages were identified as progression-significant biomarkers. The stage-salient genes were benchmarked using normals-augmented dataset, and cross-referenced with existing knowledge. The candidate biomarkers were used to construct the feature space for learning an optimal model for the digital screening of early-stage colorectal cancers. The candidate biomarkers were also examined for constructing a prognostic model based on survival analysis.RESULTS: Among the biomarkers identified are: CRLF1, CALB2, STAC2, UCHL1, KCNG1 (stage-I salient), KLHL34, LPHN3, GREM2, ADCY5, PLAC2, DMRT3 (stage-II salient), PIGR, HABP2, SLC26A9 (stage-III salient), GABRD, DKK1, DLX3, CST6, HOTAIR (stage-IV salient), and CDH3, KRT80, AADACL2, OTOP2, FAM135B, HSP90AB1 (top linear model genes). In particular the study yielded 31 genes that are progression-significant such as ESM1, DKK1, SPDYC, IGFBP1, BIRC7, NKD1, CXCL13, VGLL1, PLAC1, SPERT, UPK2, and interestingly three members of the LY6G6 family. Significant monotonic linear model genes included HIGD1A, ACADS, PEX26, and SPIB. A feature space of just seven biomarkers, namely ESM1, DHRS7C, OT

Understanding the structure of antibody-antigen (Ab-Ag) interactions is crucial for various scientific applications. Computational methods have emerged as efficient tools for studying these interactions, offering advantages over traditional methods. However, existing computational docking methods face challenges in accurately predicting Ab-Ag structures. One key limitation is the scoring function, designed for rigid and well-characterized protein structures, which often falls short in practice despite optimizations for Ab-Ag in programs. Rosetta is a widely used program for Ab-Ag docking.To address this issue, a proposed solution involves using decoy distribution as a valuable indicator for assessing the goodness of fitting in docking simulations. A decoy, representing an lternative binding pose or conformation, is plotted on a distribution graph that showcases energy scores versus Root Mean Square Deviation (RMSD) values. This decoy distribution becomes crucial for evaluating existing scoring functions and seeking more optimized parameters, essential for accurately predicting Ab-Ag structures.The thesis comprises four chapters. The first chapter provides background information, while the second chapter evaluates specific parameters within Rosetta-derived scoring functions, focusing on the energy landscape of generated structures. The third chapter develops models within the Rosetta framework to optimize scoring function parameters, using quantitative evaluations of decoy distributions to refine parameters for each Ab-Ag complex. This chapter introduces a novel approach to customizing scoring functions, potentially advancing drug discovery and deepening our understanding of molecular-level Ab-Ag interactions. The fourth chapter summarizes key findings, discusses further applications, and suggests areas for future investigation.The application of the decoy distribution revealed that the default Rosetta approach proved ineffectual in 88 out of 100 cases, showcasing th

We present CrystalBox, a novel, model-agnostic, posthoc explainability framework for Deep Reinforcement Learning (DRL) controllers in the large family of input-driven environments which includes computer systems. We combine the natural decomposability of reward functions in input-driven environments with the explanatory power of decomposed returns. We propose an efficient algorithm to generate future-based explanations across both discrete and continuous control environments. Using applications such as adaptive bitrate streaming and congestion control, we demonstrate CrystalBox's capability to generate high-fidelity explanations. We further illustrate its higher utility across three practical use cases: contrastive explanations, network observability, and guided reward design, as opposed to prior explainability techniques that identify salient features.

Despite their role as innate sentinels, macrophages can serve as cellular reservoirs of chikungunya virus (CHIKV), a highly-pathogenic arthropod-borne alphavirus that has caused large outbreaks among human populations. Here, with the use of viral chimeras and evolutionary selection analysis, we define CHIKV glycoproteins E1 and E2 as critical for virion production in THP-1 derived human macrophages. Through proteomic analysis and functional validation, we further identify signal peptidase complex subunit 3 (SPCS3) and eukaryotic translation initiation factor 3 subunit K (eIF3k) as E1-binding host proteins with anti-CHIKV activities. We find that E1 residue V220, which has undergone positive selection, is indispensable for CHIKV production in macrophages, as its mutation attenuates E1 interaction with the host restriction factors SPCS3 and eIF3k. Finally, we show that the antiviral activity of eIF3k is translation-independent, and that CHIKV infection promotes eIF3k translocation from the nucleus to the cytoplasm, where it associates with SPCS3. These functions of CHIKV glycoproteins late in the viral life cycle provide a new example of an intracellular evolutionary arms race with host restriction factors, as well as potential targets for therapeutic intervention.

As the world is reeling under the effects of the COVID-19 pandemic, most people have faced the shift to online modes of communication in spheres like education, work from home and even entertainment. Students turned to over-the-top (OTT) platforms in order to relax and relieve stress. The present study attempts to measure the usage of OTT platforms and its effect on students’ academic lives concerning academic performance, concentration and productivity, health issues, time-management, and their socio-demographic profile. The study employed explanatory descriptive research designs and sent out instruments measuring usage of OTT and other variables to 800 students across India. The study obtained 535 successful responses from the students pursuing 11th grade to post-graduation. Data analysis included descriptive statistics, parametric t-test, ANOVA and MANOVA. The study revealed that students used OTT platforms extensively for entertainment. Descriptive data gave a detailed account of their academic lives during the COVID-19 crisis. Usage of OTT affected their academic performance, concentration and productivity, health and time management. The study recommends future researchers to find the positive and negative effects of OTT usage on the youth in the post-pandemic scenario., Mientras el mundo se tambalea bajo los efectos de la pandemia COVID-19, la mayoría de las personas se han enfrentado al cambio hacia modos de comunicación en línea en esferas como la educación, el trabajo desde casa e incluso el entretenimiento. Los estudiantes recurrieron a plataformas over-the-top (OTT) para relajarse y aliviar el estrés. El presente estudio intenta medir el uso de plataformas OTT y su efecto en la vida académica de los estudiantes en relación con el rendimiento académico, la concentración y la productividad, los problemas de salud, la gestión del tiempo y su perfil sociodemográfico. El estudio empleó diseños de investigación descriptivos explicativos y utilizó instrumentos que miden el uso de OTT y otras variables a 800 estudiantes de toda la India. El estudio obtuvo 535 respuestas exitosas de los estudiantes que cursaban desde el 11º grado hasta el posgrado. El análisis de datos incluyó estadística descriptiva, prueba t paramétrica, ANOVA y MANOVA. El estudio reveló que los estudiantes utilizaban ampliamente las plataformas OTT para entretenerse. Los datos descriptivos dieron cuenta detallada de su vida académica durante la crisis de la COVID-19. El uso de OTT afectó a su rendimiento académico, concentración y productividad, salud y gestión del tiempo. El estudio recomienda a futuros investigadores encontrar los efectos positivos y negativos del uso de OTT en los jóvenes en el escenario pospandémico.

Dharani Ramamurthy,1 Sangeetha Srinivasan,2 Sruthi Chamarty,3 Tharaniy Velappan,1 Pavan Kumar Verkicharla,3 Angeline Kirubha Samuel Paulraj4 1Department of Optometry, Faculty of Medical & Health Sciences, SRM Medical College Hospital & Research Centre, SRM Institute of Science and Technology, Chennai, Tamil Nadu, 603203, India; 2Vision Research Foundation, Chennai, Tamil Nadu, 600006, India; 3Myopia Research Lab, Brien Holden Institute of Optometry and Vision Sciences, Prof Brien Holden Eye Research Centre, L V Prasad Eye Institute, Hyderabad, 500034, India; 4Department. of Biomedical Engineering, College of Engineering & Technology, SRM Institute of Science and Technology, Chennai, Tamil Nadu, 603203, IndiaCorrespondence: Dharani Ramamurthy, Department of Optometry, SRM Medical College Hospital & Research Centre, Faculty of Medical & Health Sciences, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India, Tel +91-44-47432650 ; +91-44-47432393, Email dharanir@srmist.edu.inAbstract: There is a huge unmet need for eye care with more than a hundred million people living without basic eye care services and facilities. There is an exigency to deploy adequate resources in terms of manpower and equipment to address this. The usage of smart devices in optometry and eye care practice has been gaining momentum for last half a decade, due to the COVID-19 pandemic and technological advancements in telemedicine. These smart devices will help facilitate remote monitoring of important visual functions, ocular signs and symptoms, thus providing better eye care services and facilities and promoting outreach services. Smart devices in optometry exist in the form of gadgets that can be worn in the wrist, and spectacle-mounted or head-mounted devices. On the other hand, with the ubiquitous nature of smartphones, a large number of smartphone applications have been developed and tested for advanced optometry and primary eye care practice, w

Despite repeated calls for improved measures of marriage as a process in sub-Saharan Africa, large-scale surveys continue to rely on static marital status. As a result, there is an incomplete understanding of the effects of marriage on outcomes of interest. We use qualitative and survey data from a longitudinal study of 1,203 young mothers residing in informal settlements of Nairobi, Kenya, to (1) describe the development of an innovative measure of union formalization (UF) defined as the steps through which a union attains social legitimacy; (2) compare UF with a conventional current marital status measure; (3) examine the distribution of UF steps across union history; and (4) examine the sequence and timing of pregnancy and childbearing within the UF process. We find UF steps indicative of both increasing individualization of marriage and the ongoing importance of kin involvement hold meaning. We demonstrate extensive heterogeneity in the sequence and extent of UF steps completed and interrogate the classification of premarital childbearing using sequence analysis. We argue that measuring UF is feasible and necessary for the next generation of family demography in Africa; UF measures facilitate understanding the linkages among family dynamics, health, and social stratification within the context of ongoing socioeconomic change.

Diabetes typ 2 är en folksjukdom och faktorer som kan vara bidragande till utvecklingen av diabetes typ 2 är kopplade till livsstilsvanor. Sjukdomen börjar smygande, där flera patienter inte får några symtom eller tecken på att de har drabbats av sjukdomen. Egenvård har en viktig roll i behandling av diabetes typ 2 som innebär livsstilsförändringar för att minska risken för framtida komplikationer. Ett förebyggande arbete leder till mindre kostnader för samhället. Sjuksköterskors roll är att hjälpa patienter till lämpliga strategier vid egenvård. Syfte: Är att belysa vuxna patienters upplevelser av egenvård vid diabetes typ 2. Metod: Denna litteraturöversikt är baserad på kvalitativa data, artikelsökningen genomfördes i databaserna CINAHL, MEDLINE och PubMed. Datainsamlingen resulterade i sexton vetenskapliga artiklar som granskats och analyserats enligt Fribergs (2022) modell för granskning av kvalitativa studier. Resultat: Resultatet visade att patienter upplevde utmaningar i det vardagliga livet på grund av okunskap och otillräcklig information om egenvård. Att anpassa sig till nya rutiner upplevdes påfrestande och detta skapade även rädsla och oro för framtida komplikationer. Slutsatser: I resultatet framkom det att patienter är i behov av personcentrerad vård utifrån behov och förväntningar. Patienter behöver mer utbildningar för att öka motivationen till egenvård och samtidigt bli mer delaktiga i sin vård.

Ett samhälle som snabbt förändras av digitaliseringens transformerande kraft är en omfattande och debatterad fråga i vår nutid. Trots de möjligheter den ger, kvarstår utmaningar, särskilt inom IT-säkerhet. Befintlig forskning betonar främst de tekniska aspekterna och försummar det avgörande mänskliga inslaget inom IT-säkerhet. Det rådande forskningsgapet belyser det mänskliga elementet som en betydande sårbarhet för att upprätthålla säkra digitala miljöer. Medan teknologiska skydd är nödvändiga visar de sig ofta otillräckliga utan hänsyn till mänskliga faktorer. Den tänkta studien syftar till att undersöka forskningsläget kring mänskliga faktorer inom IT-säkerhet. Genom en kvalitativ litteraturstudie som primär forskningsstrategi granskas och analyseras vetenskaplig forskning och litteratur systematiskt inom det valda ämnesområdet. Resultatet presenterar i vilken omfattning olika koncept relaterade till mänskliga faktorer inom IT-säkerhet undersöks. Studien bidrar således till en teoretisk kunskapsutveckling för att stärka och skydda digital information och infrastruktur genom att identifiera områden som forskningen är begränsad kring. Denna studie strävar efter att fylla forskningsgapet genom att belysa mänskliga sårbarheter inom IT-säkerhet och vilka koncept som bör undersökas vidare. På så sätt kan studien bidra till en holistisk förståelse av IT-säkerhet, med en balans mellan teknologiska och människocentrerade tillvägagångssätt., A society rapidly transformed by the transformative power of digitization is a comprehensive and debated issue in our contemporary times. Despite the opportunities it presents, challenges persist, particularly in IT security. Existing research primarily emphasizes the technical aspects while neglecting the crucial human element within IT security. The current research gap highlights the human element as a significant vulnerability in maintaining secure digital environments. While technological safeguards are necessary, they often prove insufficient without consideration of human factors. The intended study aims to investigate the current state of research on human factors in IT security. Through a qualitative literature review as the primary research strategy, scientific research and literature within the chosen subject area are systematically examined and analyzed. The findings present the extent to which various concepts related to human factors in IT security are explored. Thus, the study contributes to theoretical knowledge development to strengthen and protect digital information and infrastructure by identifying areas where research is limited. This study seeks to fill the research gap by highlighting human vulnerabilities in IT security and which concepts should be further investigated. In doing so, the study may contribute to a holistic understanding of IT security, balancing technological and human-centered approaches.

Diabetes typ 2 är en folksjukdom och faktorer som kan vara bidragande till utvecklingen av diabetes typ 2 är kopplade till livsstilsvanor. Sjukdomen börjar smygande, där flera patienter inte får några symtom eller tecken på att de har drabbats av sjukdomen. Egenvård har en viktig roll i behandling av diabetes typ 2 som innebär livsstilsförändringar för att minska risken för framtida komplikationer. Ett förebyggande arbete leder till mindre kostnader för samhället. Sjuksköterskors roll är att hjälpa patienter till lämpliga strategier vid egenvård. Syfte: Är att belysa vuxna patienters upplevelser av egenvård vid diabetes typ 2. Metod: Denna litteraturöversikt är baserad på kvalitativa data, artikelsökningen genomfördes i databaserna CINAHL, MEDLINE och PubMed. Datainsamlingen resulterade i sexton vetenskapliga artiklar som granskats och analyserats enligt Fribergs (2022) modell för granskning av kvalitativa studier. Resultat: Resultatet visade att patienter upplevde utmaningar i det vardagliga livet på grund av okunskap och otillräcklig information om egenvård. Att anpassa sig till nya rutiner upplevdes påfrestande och detta skapade även rädsla och oro för framtida komplikationer. Slutsatser: I resultatet framkom det att patienter är i behov av personcentrerad vård utifrån behov och förväntningar. Patienter behöver mer utbildningar för att öka motivationen till egenvård och samtidigt bli mer delaktiga i sin vård.

In the organic market which is saturated in nature, the organic food consumption is seen to be growing to a considerable level. With such a prevalence, the market share for organic products has been seen to be increasing. The main element for the successful growth of the organic sector is the optimistic image which most of the consumers attribute to the organic products. Such an optimistic image is created through the labels possessed in the organic products. In this regard, the current study explores the influence of organic product label over the consumer perception regarding the organic products. The respondents of the study are the consumers of organic products in Chennai. They have been selected through simple random sampling as the respondents of the study. The size of the sample is 100 and the instrument for data collection is questionnaire. Regression has been adopted for data collection. Findings of the study reveal that product label strongly influence on consumer perception towards organic products.

In the organic market which is saturated in nature, the organic food consumption is seen to be growing to a considerable level. With such a prevalence, the market share for organic products has been seen to be increasing. The main element for the successful growth of the organic sector is the optimistic image which most of the consumers attribute to the organic products. Such an optimistic image is created through the labels possessed in the organic products. In this regard, the current study explores the influence of organic product label over the consumer perception regarding the organic products. The respondents of the study are the consumers of organic products in Chennai. They have been selected through simple random sampling as the respondents of the study. The size of the sample is 100 and the instrument for data collection is questionnaire. Regression has been adopted for data collection. Findings of the study reveal that product label strongly influence on consumer perception towards organic products.

In recent times, the producers and the consumers exhibit more concern regarding the effect of production process of goods over the environment. From the previous decades, it can be seen that there is an enhancement of the organic trend, both in production and consumption. The study presented here has been undertaken to depict the effect of environment concern over the consumer preference for the organic food products. The information needed for the study has been collected with the help of questionnaire and the number of responses got is 100. Simple random sampling has been adopted for selecting the respondents. The sample population comprises of the consumers of organic products. Findings show that there is a relationship of environmental concern with the consumer preference for the organic products.

The present study is an attempt to explore the effect of consumer perception over their purchase intention. The study has been done with reference to organic products. The sample population comprises of the consumers of organic products at Chennai. The method used for selecting the respondents is simple random sampling and the sample size of the study is 100. Multiple regression has been applied to the collected data for analysis. The results of analysis reveal that the purchase intention of the consumers is highly affected by their perception towards the organic products.

The present study is an attempt to explore the effect of consumer perception over their purchase intention. The study has been done with reference to organic products. The sample population comprises of the consumers of organic products at Chennai. The method used for selecting the respondents is simple random sampling and the sample size of the study is 100. Multiple regression has been applied to the collected data for analysis. The results of analysis reveal that the purchase intention of the consumers is highly affected by their perception towards the organic products.

The present study is an attempt to explore the effect of consumer perception over their purchase intention. The study has been done with reference to organic products. The sample population comprises of the consumers of organic products at Chennai. The method used for selecting the respondents is simple random sampling and the sample size of the study is 100. Multiple regression has been applied to the collected data for analysis. The results of analysis reveal that the purchase intention of the consumers is highly affected by their perception towards the organic products.

In recent times, the producers and the consumers exhibit more concern regarding the effect of production process of goods over the environment. From the previous decades, it can be seen that there is an enhancement of the organic trend, both in production and consumption. The study presented here has been undertaken to depict the effect of environment concern over the consumer preference for the organic food products. The information needed for the study has been collected with the help of questionnaire and the number of responses got is 100. Simple random sampling has been adopted for selecting the respondents. The sample population comprises of the consumers of organic products. Findings show that there is a relationship of environmental concern with the consumer preference for the organic products.

Ett samhälle som snabbt förändras av digitaliseringens transformerande kraft är en omfattande och debatterad fråga i vår nutid. Trots de möjligheter den ger, kvarstår utmaningar, särskilt inom IT-säkerhet. Befintlig forskning betonar främst de tekniska aspekterna och försummar det avgörande mänskliga inslaget inom IT-säkerhet. Det rådande forskningsgapet belyser det mänskliga elementet som en betydande sårbarhet för att upprätthålla säkra digitala miljöer. Medan teknologiska skydd är nödvändiga visar de sig ofta otillräckliga utan hänsyn till mänskliga faktorer. Den tänkta studien syftar till att undersöka forskningsläget kring mänskliga faktorer inom IT-säkerhet. Genom en kvalitativ litteraturstudie som primär forskningsstrategi granskas och analyseras vetenskaplig forskning och litteratur systematiskt inom det valda ämnesområdet. Resultatet presenterar i vilken omfattning olika koncept relaterade till mänskliga faktorer inom IT-säkerhet undersöks. Studien bidrar således till en teoretisk kunskapsutveckling för att stärka och skydda digital information och infrastruktur genom att identifiera områden som forskningen är begränsad kring. Denna studie strävar efter att fylla forskningsgapet genom att belysa mänskliga sårbarheter inom IT-säkerhet och vilka koncept som bör undersökas vidare. På så sätt kan studien bidra till en holistisk förståelse av IT-säkerhet, med en balans mellan teknologiska och människocentrerade tillvägagångssätt., A society rapidly transformed by the transformative power of digitization is a comprehensive and debated issue in our contemporary times. Despite the opportunities it presents, challenges persist, particularly in IT security. Existing research primarily emphasizes the technical aspects while neglecting the crucial human element within IT security. The current research gap highlights the human element as a significant vulnerability in maintaining secure digital environments. While technological safeguards are necessary, they often prove insufficient without consideration of human factors. The intended study aims to investigate the current state of research on human factors in IT security. Through a qualitative literature review as the primary research strategy, scientific research and literature within the chosen subject area are systematically examined and analyzed. The findings present the extent to which various concepts related to human factors in IT security are explored. Thus, the study contributes to theoretical knowledge development to strengthen and protect digital information and infrastructure by identifying areas where research is limited. This study seeks to fill the research gap by highlighting human vulnerabilities in IT security and which concepts should be further investigated. In doing so, the study may contribute to a holistic understanding of IT security, balancing technological and human-centered approaches.

The agriculture industry has radically transformed over the past 50 years. Advances in machinery have expanded the scale, speed, and productivity of farm equipment, leading to more efficient cultivation of more land. Seed, irrigation, and fertilizers also have vastly improved, helping farmers increase yields. This book covers technologies that are extremely useful for the day-to-day operation of a farm or garden. The potential of new digital technologies in agriculture is astonishing. Linking farmers digitally would allow them to organize and share equipment, facilitate the sharing or exchanging of fields and support alternative supply and production channels, as well as promoting solidarity. Everything that can be measured can be improved. The agricultural plots are managed on the basis of observation, measurement and action against inter and intra-crop variability. Based on this reflection, agricultural experience is also gradually growing hand in hand with technology. Its smart tools and services enable the development of true precision agriculture. The precision-agriculture approach can also help reduce inefficiencies and waste. It works by refining current practices and does not encourage the exploration of alternatives. This is what scientists call "technological lock-in", with precision approaches reinforcing pesticide use rather than eliminating it. IoT sensors enable precision agriculture, helping farmers use as little water, power, and other resources as possible. Agriculture is in the early days of yet another revolution, at the heart of which lie data and connectivity. Artificial intelligence, analytics, connected sensors, and other emerging technologies could further increase yields, improve the efficiency of water and other inputs, and build sustainability and resilience across crop cultivation and animal husbandry. Technological innovations have greatly shaped agriculture throughout time. The technology of drones in agriculture is rising day by day fo

Low Earth Orbit (LEO) satellite networks are rapidly gaining traction today. Although several real-world deployments exist, our preliminary analysis of LEO topology performance with the soon-to-be operational Inter-Satellite Links (ISLs) reveals several interesting characteristics that are difficult to explain based on our current understanding of topologies. For example, a real-world satellite shell with a low density of satellites offers better latency performance than another shell with nearly double the number of satellites. In this work, we conduct an in-depth investigation of LEO satellite topology design parameters and their impact on network performance while using the ISLs. In particular, we focus on three design parameters: the number of orbits in a shell, the inclination of orbits, and the number of satellites per orbit. Through an extensive analysis of real-world and synthetic satellite configurations, we uncover several interesting properties of satellite topologies. Notably, there exist thresholds for the number of satellites per orbit and the number of orbits below which the latency performance degrades significantly. Moreover, network delay between a pair of traffic endpoints depends on the alignment of the satellite's orbit (Inclination) with the geographic locations of endpoints.

A resilient Internet infrastructure is critical in our highly interconnected society. However, the Internet faces several vulnerabilities, ranging from natural disasters to human activities, that can impact the physical layer and, in turn, the higher network layers, such as IP links. In this paper, we introduce Xaminer, the first Internet cross-layer resilience analysis tool, to evaluate the interplay between physical- and network-layer failures. Using a cross-layer Internet map and a failure event model, Xaminer generates a risk profile encompassing a cross-layer impact report, critical infrastructure identification at each layer, and the discovery of trends and patterns under different failure event settings. Xaminer's key strengths lie in its adaptability to diverse disaster scenarios, the ability to assess risks at various granularities, and the capability to generate joint risk profiles for multiple events. We demonstrate Xaminer's capabilities in cross-layer analysis across a spectrum of disaster event models and regions, showcasing its potential role in facilitating well-informed decision-making for resilience planning and deployments.

Migration research tends to treat childrearing as a secondary role for migrants. By prioritising the economic objectives of migration, most models present migrants as either delaying childbearing or, if they have young children, not living with them. However, migration has become increasingly feminised, the types of mobility more varied, while the returns to migration remain uncertain at best. At the same time, norms around childrearing are shifting, and the capacity of kin to take care of children may be weakening. In such contexts, migrants may not want to or be able to be separated from their children. Confronting such difficult decisions and their consequences may be reflected in poor sleep health for the migrant parent. We draw on data from the Migration and Health Follow-Up Study (MHFUS) in South Africa to examine the following questions: (i) To what extent is children's coresidence associated with sleep health for migrant parents? (ii) Do effects vary by sex of migrant? and (iii) Do effects vary by location of migrant? Results from propensity score matching confirm that migrants who coreside with all their young children are more likely to experience healthy sleep compared to those who have nonresident or no young children. However, stratified analysis shows that these effects are only significant for women and those not living in Gauteng province. The value of these findings is underscored by the need for research on the well-being of migrant parents who are negotiating multiple agendas in economically precarious and physically insecure destinations.

California is home to nearly 40 million people of different incomes, ages, and racial and ethnic backgrounds, and who live in different regions. Every year since 2019, the California Health Care Foundation has conducted a representative, statewide survey of residents' views and experiences on a variety of health care topics, some of which are tracked to detect meaningful shifts over time.The California Health Care Foundation and NORC at the University of Chicago, a nonpartisan research organization, conducted the survey again in late 2022. Results are reported and, where applicable, compared to the prior annual survey, which was conducted in late 2021.Key findings from this year's survey include:Health care costs. Like prior years, half of Californians (52%) report skipping or delaying health care due to cost in the past 12 months. Of those who skipped or delayed care, half of them (50%) say their condition got worse as a result.Medical debt. More than 1 in 3 (36%) report having medical debt, and of those, 1 in 5 (19%) report owing $5,000 or more. Californians with lower incomes (52%) are more likely than those with higher incomes (30%) to report medical debt.

In this study an attempt was made to formulate cosmetic gel using Maranta arundinacea (arrowroot powder) Arrowroot contains flavonoids which is known for its anti-inflammatory properties, antibacterial properties from long time. It has earned a reputation as an elegant, lightweight, all-natural absorbent powder with added skin-nourishing, reduce oiliness, anti-inflammatory properties, anti-irritant properties and for treating wounds from historical times. The rhizome of the plant was processed to obtain arrowroot powder. The cosmetic gel was developed using two polymers carbopol 934 and sodium carboxy methyl cellulose (sodium CMC) in different ratios as gelling agents using dispersion method. The formulated gel was evaluated for various physicochemical factors like physical appearance, homogeneity, spread ability, pH and viscosity measurements. Cosmetic gel prepared using carbopol 934 by dispersion method in 1: 5 ratio showed better results in all parameters compared with sodium carboxy methyl cellulose. The best formulation F3 was tested for its antimicrobial property against Staphylococcus aureus by comparing the zone of inhibition with the standard drug (Azithromycin) and blank gel. F3 formulation showed a zone of inhibition of 15.2 mm above the minimum inhibitory concentration. Stability studies for 3 months gave promising results. Thus, cosmetic gel of arrow root with Carbopol 934 in the ratio of 1:5 was found to be ideal gel for acne treatment and skin rejuvenating purpose. Keywords: Flavonoids, Rhizome, Staphylococcus aureus, Minimum inhibitory concentration, Zone of inhibition, Dispersion method.

Methyl-coenzyme M reductase (MCR) catalyzes the formation of methane, and its activity accounts for nearly all biologically produced methane released into the atmosphere. The assembly of MCR is an intricate process involving the installation of a complex set of posttranslational modifications and the unique Ni-containing tetrapyrrole called coenzyme F430. Despite decades of research, details of MCR assembly remain largely unresolved. Here, we report the structural characterization of MCR in two intermediate states of assembly. These intermediate states lack one or both F430 cofactors and form complexes with the previously uncharacterized McrD protein. McrD is found to bind asymmetrically to MCR, displacing large regions of the alpha subunit and increasing active-site accessibility for the installation of F430-shedding light on the assembly of MCR and the role of McrD therein. This work offers crucial information for the expression of MCR in a heterologous host and provides targets for the design of MCR inhibitors.

Diabetes is a chronic disease with the potential to cause a worldwide health care crisis. Diabetes is an illness caused because of high glucose level in a human body. Diabetes should not be ignored if it is untreated then Diabetes may cause some major issues in a person like: heart related problems, kidney problem, blood pressure, eye damage and it can also affect other organs of human body. Diabetes can be controlled if it is predicted earlier. Diabetes is one of the fastest-growing diseases in the world and requires constant monitoring. To verify this, we are exploring different machine learning algorithms that will help with this baseline prediction. achieve this goal this project work we will do early prediction of Diabetes in a human body or a patient for a higher accuracy through applying, Various Machine Learning Techniques. Machine learning techniques Provide better result for prediction by constructing models from datasets collected from patients. In this work we will use Machine Learning Classification and ensemble techniques on a dataset to predict diabetes. We are using Random Forest (RF) for model building. The Project work gives the accurate or higher accuracy model shows that the model is capable of predicting diabetes effectively. We are expecting our result to show that Random Forest achieved higher accuracy. The accuracy of this model is above 90%.

Diabetes is a chronic disease with the potential to cause a worldwide health care crisis. Diabetes is an illness caused because of high glucose level in a human body. Diabetes should not be ignored if it is untreated then Diabetes may cause some major issues in a person like: heart related problems, kidney problem, blood pressure, eye damage and it can also affect other organs of human body. Diabetes can be controlled if it is predicted earlier. Diabetes is one of the fastest-growing diseases in the world and requires constant monitoring. To verify this, we are exploring different machine learning algorithms that will help with this baseline prediction. achieve this goal this project work we will do early prediction of Diabetes in a human body or a patient for a higher accuracy through applying, Various Machine Learning Techniques. Machine learning techniques Provide better result for prediction by constructing models from datasets collected from patients. In this work we will use Machine Learning Classification and ensemble techniques on a dataset to predict diabetes. We are using Random Forest (RF) for model building. The Project work gives the accurate or higher accuracy model shows that the model is capable of predicting diabetes effectively. We are expecting our result to show that Random Forest achieved higher accuracy. The accuracy of this model is above 90%.

Background and aimsPruritus is associated with multiple liver diseases, particularly those with cholestasis, but the mechanism remains incompletely understood. Our aim was to evaluate serum IL-31 as a putative biomarker of pruritus in clinical trials of an farnesoid X receptor (FXR) agonist, cilofexor, in patients with NASH, primary sclerosing cholangitis (PSC), and primary biliary cholangitis (PBC).Approach and resultsSerum IL-31 was measured in clinical studies of cilofexor in NASH, PSC, and PBC. In patients with PSC or PBC, baseline IL-31 was elevated compared to patients with NASH and healthy volunteers (HVs). IL-31 correlated with serum bile acids among patients with NASH, PBC, and PSC. Baseline IL-31 levels in PSC and PBC were positively correlated with Visual Analog Scale for pruritus and 5-D itch scores. In patients with NASH, cilofexor dose-dependently increased IL-31 from Week (W)1 to W24. In patients with NASH receiving cilofexor 100 mg, IL-31 was higher in those with Grade 2-3 pruritus adverse events (AEs) than those with Grade 0-1 pruritus AEs. IL-31 weakly correlated with C4 at baseline in patients with NASH, and among those receiving cilofexor 100 mg, changes in IL-31 and C4 from baseline to W24 were negatively correlated. IL-31 messenger RNA (mRNA) was elevated in hepatocytes from patients with PSC and NASH compared to HVs. In a humanized liver murine model, obeticholic acid increased IL-31 mRNA expression in human hepatocytes and serum levels of human IL-31.ConclusionsIL-31 levels correlate with pruritus in patients with cholestatic disease and NASH, with FXR agonist therapy resulting in higher serum levels in the latter group. IL-31 appears to derive in part from increased hepatocyte expression. These findings have therapeutic implications for patients with liver disease and pruritus.

Periodontal disease is more common in individuals with rheumatoid arthritis (RA) who have detectable anti-citrullinated protein antibodies (ACPAs), implicating oral mucosal inflammation in RA pathogenesis. Here, we performed paired analysis of human and bacterial transcriptomics in longitudinal blood samples from RA patients. We found that patients with RA and periodontal disease experienced repeated oral bacteremias associated with transcriptional signatures of ISG15+HLADRhi and CD48highS100A2pos monocytes, recently identified in inflamed RA synovia and blood of those with RA flares. The oral bacteria observed transiently in blood were broadly citrullinated in the mouth, and their in situ citrullinated epitopes were targeted by extensively somatically hypermutated ACPAs encoded by RA blood plasmablasts. Together, these results suggest that (i) periodontal disease results in repeated breaches of the oral mucosa that release citrullinated oral bacteria into circulation, which (ii) activate inflammatory monocyte subsets that are observed in inflamed RA synovia and blood of RA patients with flares and (iii) activate ACPA B cells, thereby promoting affinity maturation and epitope spreading to citrullinated human antigens.

PURPOSE: There is a growing interest in extracellular vesicles (EVs) for ocular applications as therapeutics, biomarkers, and drug delivery vehicles. EVs secreted from mesenchymal stem cells (MSCs) have shown to provide therapeutic benefits in ocular conditions. However, very little is known about the properties of bioreactor cultured-3D human retinal organoids secreted EVs. This study provides a comprehensive morphological, nanomechanical, molecular, and proteomic characterization of retinal organoid EVs and compares it with human umbilical cord (hUC) MSCs. METHODS: The morphology and nanomechanical properties of retinal organoid EVs were assessed using Nanoparticle tracking analysis (NTA) and Atomic force microscopy (AFM). Gene expression analysis of exosome biogenesis of early and late retinal organoids were compared using qPCR. The protein profile of the EVs were analyzed with proteomic tools. RESULTS: NTA indicated the average size of EV as 100-250 nm. A high expression of exosome biogenesis genes was observed in late retinal organoids EVs. Immunoblot analysis showed highly expressed exosomal markers in late retinal organoids EVs compared to early retinal organoids EVs. Protein profiling of retinal organoid EVs displayed a higher differential expression of retinal function-related proteins and EV biogenesis proteins than hUCMSC EVs, implicating that the use of retinal organoid EVs may have a superior therapeutic effect on retinal disorders. CONCLUSION: This study provides supplementary knowledge on the properties of retinal organoid EVs and suggests their potential use in the diagnostic and therapeutic treatments for ocular diseases.

Large constellations of bright artificial satellites in low Earth orbit pose significant challenges to ground-based astronomy 1. Current orbiting constellation satellites have brightnesses between apparent magnitudes 4 and 6, whereas in the near-infrared Ks band, they can reach magnitude 2 (ref. 2). Satellite operators, astronomers and other users of the night sky are working on brightness mitigation strategies 3,4. Radio emissions induce further potential risk to ground-based radio telescopes that also need to be evaluated. Here we report the outcome of an international optical observation campaign of a prototype constellation satellite, AST SpaceMobile’s BlueWalker 3. BlueWalker 3 features a 64.3 m 2 phased-array antenna as well as a launch vehicle adaptor (LVA) 5. The peak brightness of the satellite reached an apparent magnitude of 0.4. This made the new satellite one of the brightest objects in the night sky. Additionally, the LVA reached an apparent V-band magnitude of 5.5, four times brighter than the current International Astronomical Union recommendation of magnitude 7 (refs. 3,6); it jettisoned on 10 November 2022 (Universal Time), and its orbital ephemeris was not publicly released until 4 days later. The expected build-out of constellations with hundreds of thousands of new bright objects 1 will make active satellite tracking and avoidance strategies a necessity for ground-based telescopes., Astrodynamics & Space Missions

The Internet of Medical Things (IoMT) is a state-of-the-art paradigm that revolutionizes healthcare by fusing the strength of medical devices, sensors, and networks with Internet of Things (IoT) technology. By offering real-time data gathering, analysis, and networking, IoMT is positioned to alter the healthcare sector. This will ultimately improve patient care, improve diagnostics, and boost the effectiveness of healthcare systems. This article describes the idea of IoMT, applications, and its architecture while highlighting both its potential advantages and limitations for the healthcare ecosystem.

Diabetes prevalence achieved 470B in 2021. Diabetics are looking for foods that allow them to better manage the postprandial glycemia. Owing to its large amylose fraction, pea starch may contribute to formulate recipes with a lower glycemic index (GI). This study measured the rapidly, slowly digested and resistant fractions in pea starch and in a powder mix recipe. Starch fractions were determined according to the Englyst methodology. A nonblind repeat measure crossover design trial in healthy humans was used to study the GI of pea starch and maltodextrin powder mix recipes against glucose. Gastrointestinal symptoms were measured. Thirteen healthy volunteers aged 18–60 years with body mass index <30 kg/m2 and fasting blood glucose <6.1 mmol/L participated in the study. They consumed 25 g available carbohydrate portions of the test products. Blood glucose was measured at −5 and 0 min before consumption till 180 min after starting to eat. The slow digestible starch (SDS) content of native pea starch was 30% of the total starch content. The pea-based powder mix recipe contained 25% SDS in comparison with 9% for the maltodextrin-based recipe. The glucose response after pea starch was significantly lower compared with maltodextrin. The glucose response after pea starch recipe was significantly lower compared with maltodextrin recipe. There was no significant difference in mean scores for well-being and gastrointestinal symptoms after consumption of pea starch and maltodextrin or between the two recipes. In conclusion, this study has demonstrated the presence of high SDS content in pea starch, which reduced postprandial glycemic response compared with maltodextrin. The pea starch recipe did not induce any negative gastrointestinal symptoms. Pea starch may, therefore, prove to be a beneficial ingredient in developing food products for improving glycemic control without undesirable side effects.

Non-PR, IFPRI5; DCA; 4 Transforming Agricultural and Rural Economies; 5 Strengthening Institutions and Governance; Cross-cutting gender theme, Development Strategies and Governance (DSG); Transformation Strategies, In the Indian family setting, women play a crucial role in the overall development of the households. Hence, development agencies and government programs mainly target women, assuming that empowering women would improve families. Given this background, we aim to construct a women's empowerment index (WEI) that encompasses all these domains and captures nutrition improvement for their and their family members. We assigned the weights based on principal component analysis (PCA). Then, we examine the extent of empowerment and nutrition outcomes of the family members across the wealth category and place of residence (rural-urban setting). Finally, we validate the WEI by analyzing the relationship between WEI and nutrition outcomes of family members through logit analysis. We used Uttar Pradesh data from National Family Health Survey (NFHS) -5 conducted in 2019-21 for the study. We found a positive relationship between household wealth and women's empowerment, indicating the vulnerability of women in poor families, especially in rural areas. Our results also suggested that women's empowerment differs across educational backgrounds and places of residence. Finally, we found that the prevalence of malnutrition is negatively associated with women's empowerment, especially children and women. These findings highlight the need for promoting women's empowerment-based policies and interventions to address the malnutrition problem

Sentiment analysis is a branch of analysis that uses disorganized written language to infer the opinions and emotions of people's critiques and attitudes toward entities and its features. In order to produce acceptable results, the majority of sentiment analysis models that employ supervised learning algorithms require a large amount of labeled information during the training stage. This is typically costly and results in significant labor expenses when used in practical applications. In this study, an intelligent and unique sentiment prediction system is developed for accurately classifying the positive, negative, and neutral comments from the social media dataset. Data preprocessing, which entails noise reduction, tokenization, standardization, normalization, stop word removal, and stemming, is done to ensure that the data is of a high enough quality for efficient sentiment prediction and analysis. The preprocessed data is then used to extract a mix of features, including hash tagging, Bag of Words (BoW), and Parts of Speech (PoS). Consequently, in order to choose the best features and speed up the classifier, a new hybrid optimization method called Aquila merged Arithmetic Optimization (AIAO) is used. Furthermore, an Auto-Encoder based Long Short Term Memory (AuE-LSTM), an innovative and clever ensemble learning technique, is used to precisely anticipate and classify user feelings based on the chosen data. This study uses a variety of open source social media datasets to evaluate the performance of the suggested AIAO integrated AuE-LSTM model.

Sentiment analysis is a branch of analysis that uses disorganized written language to infer the opinions and emotions of people's critiques and attitudes toward entities and its features. In order to produce acceptable results, the majority of sentiment analysis models that employ supervised learning algorithms require a large amount of labeled information during the training stage. This is typically costly and results in significant labor expenses when used in practical applications. In this study, an intelligent and unique sentiment prediction system is developed for accurately classifying the positive, negative, and neutral comments from the social media dataset. Data preprocessing, which entails noise reduction, tokenization, standardization, normalization, stop word removal, and stemming, is done to ensure that the data is of a high enough quality for efficient sentiment prediction and analysis. The preprocessed data is then used to extract a mix of features, including hash tagging, Bag of Words (BoW), and Parts of Speech (PoS). Consequently, in order to choose the best features and speed up the classifier, a new hybrid optimization method called Aquila merged Arithmetic Optimization (AIAO) is used. Furthermore, an Auto-Encoder based Long Short Term Memory (AuE-LSTM), an innovative and clever ensemble learning technique, is used to precisely anticipate and classify user feelings based on the chosen data. This study uses a variety of open source social media datasets to evaluate the performance of the suggested AIAO integrated AuE-LSTM model.

Bronchial and alveolar remodeling and impaired epithelial function are characteristics of chronic respiratory diseases. In these patients, an increased number of mast cells (MCs) positive for serine proteases, tryptase and chymase, infiltrate the epithelium and alveolar parenchyma. However, little is known regarding the implication of intraepithelial MCs on the local environment, such as epithelial cell function and properties. In this study, we investigated whether MC tryptase is involved in bronchial and alveolar remodeling and the mechanisms of regulation during inflammation. Using novel holographic live cell imaging, we found that MC tryptase enhanced human bronchial and alveolar epithelial cell growth and shortened the cell division intervals. The elevated cell growth induced by tryptase remained in a pro-inflammatory state. Tryptase also increased the expression of the anti-apoptotic protein BIRC3, as well as growth factor release in epithelial cells. Thus, our data imply that the intraepithelial and alveolar MC release of tryptase may play a critical role in disturbing bronchial epithelial and alveolar homeostasis by altering cell growth–death regulation., Bronchial and alveolar remodeling and impaired epithelial function are characteristics of chronic respiratory diseases. In these patients, an increased number of mast cells (MCs) positive for serine proteases, tryptase and chymase, infiltrate the epithelium and alveolar parenchyma. However, little is known regarding the implication of intraepithelial MCs on the local environment, such as epithelial cell function and properties. In this study, we investigated whether MC tryptase is involved in bronchial and alveolar remodeling and the mechanisms of regulation during inflammation. Using novel holographic live cell imaging, we found that MC tryptase enhanced human bronchial and alveolar epithelial cell growth and shortened the cell division intervals. The elevated cell growth induced by tryptase remained in a pro-inflammatory state. Tryptase also increased the expression of the anti-apoptotic protein BIRC3, as well as growth factor release in epithelial cells. Thus, our data imply that the intraepithelial and alveolar MC release of tryptase may play a critical role in disturbing bronchial epithelial and alveolar homeostasis by altering cell growth–death regulation.

Several studies have reported magnetic field fluctuations associated with umbral shock waves. We aim to study the properties and origin of magnetic field fluctuations in the umbral chromosphere. Temporal series of spectropolarimetric observations were acquired with the GREGOR telescope. The chromospheric and photospheric conditions were derived from simultaneous inversions of the He I 10830 \AA\ triplet and the Si I 10827 \AA\ line using HAZEL2. The oscillations are interpreted using wavelet analysis and context information from UV observations acquired with SDO/AIA and IRIS. The chromospheric magnetic field shows strong fluctuations in the sunspot umbra, with peak field strengths up to 2900 G. Magnetic field and velocity umbral oscillations exhibit a strong coherence, with the magnetic field lagging the shock fronts detected in the velocity fluctuations. This points to a common origin of the fluctuations in both parameters, whereas the analysis of the phase shift between photospheric and chromospheric velocity is consistent with upwards wave propagation. These results suggest that the strong inferred magnetic field fluctuations are caused by changes in the response height of the He I 10830 \AA\ line to the magnetic field, which is sensitive to high photospheric layers after the shock fronts. The coronal activity seen in EUV data could possibly have some impact on the inferred fluctuations, but it is not the main driver of the magnetic field oscillations since they are found before EUV events take place. Chromospheric magnetic field fluctuations measured with the He I 10830 \AA\ triplet arise due to variations in the opacity of the line. After shocks produced by slow magnetoacoustic waves, the response of the line to the magnetic field can be shifted down to the upper photosphere. This is seen as remarkably large fluctuations in the line of sight magnetic field strength., Comment: Accepted for publication in A&A. Abstract abridged due to arXiv's 1920 character limit

Cotton, a vital global cash crop, influences the economy and sustainability. Natural farming is a cost-effective, eco-friendly method. This study examines Natural Farming's effects on cotton yield and the economics of cotton compared to Integrated and organic farming. Field experiments were conducted during 2021-22 and 2022-23 at Tamil Nadu Agricultural College, Coimbatore. The experiment consisted of eight treatments, laid out in Randomized Block Design and replicated thrice. The treatments consist of control (T1), various Indian Natural farming practices including Beejamirit as a seed treatment, Ghanajeevamirit as basal, Jeevamirit with irrigation water, crop residue mulch, intercroping with pulses (T2 to T5), Organic farming practices (T6), Integrated crop management (ICM) practices with organic pest control (T7) and ICM with chemical pest (T8). The results indicated a significant increase in yield components: sympodial branches plant-1 (12.85 and 13.40), number of squares (29.28 and 31.28), bolls plant-1 (10.74 and 11.32), and boll weight (4.30 and 4.38 g) under Integrated Crop Management practices in 2021-22 and 2022-23, respectively. However, organic farming practices, followed by natural farming practices, were at par with integrated crop management. Integrated crop management practices resulted in significantly higher seed cotton yields (2178 and 2232 kg/ha in 2021-22 and 2022-23, respectively) than organic and natural farming practices with a higher cost of cultivation and a gross return. Complete natural farming outperformed organic and integrated farming in cotton, yielding higher net returns and B: C ratios. This approach holds promise for enhancing yield, economic viability and environmental sustainability in cotton cultivation.

India is one of the most vulnerable countries to climate change and its impact on agricultural production and livestock. Sorghum (Sorghum bicolor) is an important food crop of India cultivated in tropical and subtropical climates, especially the semiarid tropics; varying environmental attributes significantly affect its duration and yield. Therefore, the present research aimed to evaluate the potential of dual-purpose sorghum under varying sowing windows and crop geometry. The experiment was conducted in Eastern block farm of Tamil Nadu Agricultural University during the summer season- 2022. The experiment was laid out in strip plot design with three different dates of sowing in the main plot, i.e., D1 - First fortnight of February, D2 - First fortnight of March and D3 - First fortnight of April and six different crop geometries in the subplot viz., 45 x 15 cm (S1),45 x 10 cm(S2), 45 x 5 cm (S3), 30 x 15 cm (S4),30 x 10 cm (S5) and 30 x 5 cm (S6) and replicated thrice.The results revealed that sowing during the first fortnight (I FN) of April with a spacing of 45x 15 cm resulted in maximum grain yield(2585 kg/ha) and for fodder yield, April I FN sowing with a crop geometry of 30x 5 cm resulted in maximum green biomass (43.6 t/ha) as well as dry matter production. So, spacing of 30x 5 cm helps in better utilization of resources along with maximum fodder yield.

In this study an attempt was made to formulate cosmetic gel using Maranta arundinacea (arrowroot powder) Arrowroot contains flavonoids which is known for its anti-inflammatory properties, antibacterial properties from long time. It has earned a reputation as an elegant, lightweight, all-natural absorbent powder with added skin-nourishing, reduce oiliness, anti-inflammatory properties, anti-irritant properties and for treating wounds from historical times. The rhizome of the plant was processed to obtain arrowroot powder. The cosmetic gel was developed using two polymers carbopol 934 and sodium carboxy methyl cellulose (sodium CMC) in different ratios as gelling agents using dispersion method. The formulated gel was evaluated for various physicochemical factors like physical appearance, homogeneity, spread ability, pH and viscosity measurements. Cosmetic gel prepared using carbopol 934 by dispersion method in 1: 5 ratio showed better results in all parameters compared with sodium carboxy methyl cellulose. The best formulation F3 was tested for its antimicrobial property against Staphylococcus aureus by comparing the zone of inhibition with the standard drug (Azithromycin) and blank gel. F3 formulation showed a zone of inhibition of 15.2 mm above the minimum inhibitory concentration. Stability studies for 3 months gave promising results. Thus, cosmetic gel of arrow root with Carbopol 934 in the ratio of 1:5 was found to be ideal gel for acne treatment and skin rejuvenating purpose. Keywords: Flavonoids, Rhizome, Staphylococcus aureus, Minimum inhibitory concentration, Zone of inhibition, Dispersion method.

This article describes how to improve the stability of a multimachine power system by simultaneously adjusting the PSS and static VAR compensator parameters with a Particle Swarm Optimized NeuroFuzzy controller. The controller works to enhance the dampening of the rotor speed deviations of its nearby generators by providing a reference voltage signal for the PSS & SVC. The field of intelligent control involves creating control algorithms by modeling specific traits of intelligent biological systems. The controller is trained offline by PSO and simulation results that describe the performance of the NeuroFuzzy controller are provided in order to provide nonlinear optimum control during abnormal operating circumstances of the power systems.

This article describes how to improve the stability of a multimachine power system by simultaneously adjusting the PSS and static VAR compensator parameters with a Particle Swarm Optimized NeuroFuzzy controller. The controller works to enhance the dampening of the rotor speed deviations of its nearby generators by providing a reference voltage signal for the PSS & SVC. The field of intelligent control involves creating control algorithms by modeling specific traits of intelligent biological systems. The controller is trained offline by PSO and simulation results that describe the performance of the NeuroFuzzy controller are provided in order to provide nonlinear optimum control during abnormal operating circumstances of the power systems.