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Background: Globally, the aging population is expanding rapidly, impacting every aspect of the society. In developing nations like India, where family members primarily serve as caregivers for older adults, inadequate knowledge about their complex needs increases caregiver burden. The topic of caregiving has been extensively studied worldwide, mainly focused on the negative aspects of caregiving. The present study aims to assess the knowledge, attitude, practice, and burden of family caregivers providing care to older adults at homes in South India. Methods: This was a descriptive, observational study, which was conducted using a questionnaire-based approach. In this study, a purposive sampling technique was used, and a total of 56 family caregivers participated, who were caregivers to the patients admitted to a tertiary hospital in South India. Data Collection: A prevalidated questionnaire from previous studies was used to explore the knowledge, practices, and attitudes of caregivers of older patients.Caregiver burden was measured using Zarit Burden Interview. Results: The data were analyzed using SPSS v21. Caregiver burden was found to be high among those who cohabited with the patient (P < 0.05). Sons/daughters and grandchildren had a better grasp about the medical conditions of older people, P < 0.05. Attitude toward caring for older adults was strongly positive irrespective of the age category. Conclusion: Our study revealed that caregivers’ knowledge on the medical needs of the older population was inadequate. This study could pave the way for developing hospital policies, as well as planning action research, training, and counseling programs to strengthen family caregiver capacity and promote active and healthy aging.

Raw and citric acid chemically treated date palm stone agro-waste biomass (RDSB and CA-MDSB) powders were used to remove an important class of emerging industrial pollutants, i.e., 2,4,6-trichlorophenol (2,4,6-TCP) from aqueous solutions towards sustainable waste utilization to develop cost-effective technology for treating wastewater. The biomass characterization was performed by using different analytical techniques such as CHN elemental analysis, particle size, BET, FTIR, and SEM-EDX, TGA analysis. The FTIR spectral analysis revealed that the main chemical groups (N–C, O=C, H-O, H-C, and O–C) were involved in trapping 2,4,6-TCP. The highest adsorption was achieved with a contact time of 150 and 120 min, an initial concentration of 50-200 mg/L, and a biosorbent dosage ranging from 0.1 to 1.0 g/L RDSB and CA-MDSB, respectively. The experimental kinetic data of the adsorption process for both adsorbents (RDSB and CA-MDSB) fitted very well with the pseudo-second-order kinetic model and Langmuir equilibrium data. The 2,4,6-TCP maximum monolayer adsorption capacities were 53.7, and 123.8 mg/g for RDSB and CA-MDSB, respectively. The present research confirms that the date palm stone biomass could be used as an effective and low-cost biosorbent for the remediation of 2,4,6-TCP from an aqueous environment.

A high-temperature polymer electrolyte membrane fuel cell (PEMFC) has enormous potential to produce clean energy with minimal environmental pollution along with high energy density and conversion efficiency. In the present work, anhydrous proton-conducting polymer electrolyte membranes for prospective high-temperature fuel cell application were successfully prepared using different protic ionic liquids (PILs) and sulfonated poly(ether ether ketone) (SPEEK). The protic ionic liquids (PILs), 2-hydroxyethylammonium formate, diethylmethyl ammonium triflate, 1-ethylimidazolium bis(trifluoromethylsulfonyl)imide, 1,2-dimethyl imidazolium bis(trifluoro methylsulfonyl)imide, and diethylmethylammonium methanesulfonate were selected based on their favorable physicochemical properties. The effect of the incorporation of the PIL on the structural, thermal, and electrical transport properties of the composite SPEEK polymer electrolyte membranes was studied. The prepared polymer electrolyte membranes (PEMs) were characterized using Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), X-ray diffractometry (XRD), and electrochemical impedance spectroscopy (EIS) techniques. FTIR results indicated an interaction between the PIL and the SPEEK, which resulted in homogeneous and flexible membranes. The DSC results confirmed good miscibility and elucidated plasticizing effect of the incorporated PIL on the SPEEK polymer matrix. All the PEMs showed good thermal stability and high-temperature anhydrous proton conductivity, achieving best proton conductivity, ≈8 × 10–3 S cm−1 at 120 °C and low activation energy ≈0.26 eV, making it suitable for prospective high-temperature PEMFC applications.

Evidence of cross-domain spillover into the moral domain has been limited to altruistic and consumption behaviors. Building on the literature on spillover effects and domain-general decision processes, we predicted that choice behavior in the economic domain would affect subsequent choices in sacrificial moral dilemmas. We tested this prediction using hypothetical risky gambles and vignettes for moral dilemmas. We found that prior exposure to risky gambles increased utilitarian responses toward sacrificial moral dilemmas. Mediation analysis suggests that this is due to the spillover of a cost–benefit mindset. This mindset increases the probability of making utilitarian-type choices when faced with moral dilemmas but does not affect moral judgment. These results suggest that moral decisions are susceptible to cross-domain spillover effects. Moral values might get easily traded off in transactional scenarios in which cost–benefit analysis is a dominant decision strategy.

Background: Alopecia areata (AA) is a disease of hair loss with multiple treatment options. Physicians play an important role in guiding patients during the decision-making process. Objective: Assess physicians’ values and attitudes when helping patients choose an AA treatment. Methods: Semi-structured qualitative interviews were conducted with dermatologists of varying practice type and location. Each interview was coded independently twice using inductive thematic analysis. Interrater reliability and code frequencies were determined. Results: Fourteen participants were interviewed. Interrater reliability was κ = 0.85 to 0.97. Dermatologists wanted patients to consider various treatment factors (ie, efficacy, safety, convenience of use, accessibility) and also assessed patients’ AA clinical severity and personality traits. Participants often encountered various barriers to effective communication with patients, which may be mitigated by shared decision-making. Shared decision-making tools were perceived to potentially improve patient care and communication, although physicians expressed concern about lack of individualization, limitations of time, and the appropriateness of information. Conclusion: AA treatment decision-making is a complex process that often utilizes the expertise of a dermatologist, during which shared decision-making tools may be of value to both patients and physicians.

The function of a protein is most of the time achieved due to minute conformational changes in its structure due to ligand binding or environmental changes or other interactions. Hence the analysis of structure of proteins should go beyond the analysis of mere atom contacts and should include the emergent global structure as a whole. This can be achieved by graph spectra based analysis of protein structure networks. GraSp-PSN is a web server that can assist in (1) acquiring weighted protein structure network (PSN) and network parameters ranging from atomic level to global connectivity from the three dimensional coordinates of a protein, (2) generating scores for comparison of a pair of protein structures with detailed information of local to global connectivity, and (3) assigning perturbation scores to the residues and their interactions, that can prioritise them in terms of residue clusters. The methods implemented in the server are generic in nature and can be used for comparing networks in any discipline by uploading adjacency matrices in the server. The webserver can be accessed using the following link: https://pople.mbu.iisc.ac.in/.

Background: Alopecia areata (AA) is a disease of hair loss in which patients may benefit from comprehensive understanding of AA’s disease process and therapeutic options during treatment decision-making. Objective: Determine factors influencing patients’ AA treatment decision-making. Methods: Qualitative interviews were conducted using semi-structured interview guides. Interviews were coded using inductive thematic analysis. Results: Twenty-one participants with AA were interviewed. Coding interrater reliability was κ = 0.87-0.91, indicating strong-almost perfect agreement. Participants faced multiple barriers, including lack of access to health care (n = 10, 47.6%) and lack of transparency about their condition and treatment options (n = 9, 42.9%). Information about AA was sought from primarily the internet (n = 15, 71.4%) and physician recommendation (n = 15, 71.4%). When choosing AA treatments, patients often considered treatment efficacy (n = 21, 100%), safety (n = 21, 100%), and convenience of use (n = 20, 95.2%). Limitations: Referral and regional biases may be present and limit generalizability. Conclusions: Patients with AA face various challenges including medical uncertainty and lack of information. Patients need trustworthy and accessible sources of information regarding their treatment that also take into consideration their preferences and values.

Despite a high primary school enrollment in India, the overall learning levels have been low, and the dropout level in secondary school and beyond has been high. One reason for low learning levels and high drop-out rates is the student's lack of motivation to learn in the classroom. We suggest that curiosity may be a useful tool to improve student motivation. We look at some important variables that have been found to affect curiosity in the classroom: self-determination needs, information relevance, coherence, concreteness, ease of comprehension, fantasy, belief about interest malleability, and information gap. Finally, we suggest ways to incorporate them in the classroom to improve student motivation.

Adenosine to inosine (A to I) editing is mediated by adenosine deaminases acting on RNA (ADAR) enzymes. Inosines are interpreted as guanosines by the translational machinery. Consequently, A to I editing in mRNAs can lead to their recoding and the formation of proteins not encoded in the genome. Filamin A is an actin-crosslinking protein. A to I editing in the filamin pre-mRNA leads to the exchange of a glutamine to an arginine in a highly interactive domain of the protein. However, the consequences of this editing event are still poorly understood. Here we show, using transgenic mice expressing either constitutively edited or constitutively uneditable filamin A that filamin A editing critically controls angiogenesis in tumors but also in a mouse ischemia model. Hyper-editing reduces angiogenesis, while hypoediting leads to increased angiogenesis, possibly by altering vascular endothelial growth factor receptor 2 (VEGFR2) turnover. Further, FLNA editing of the tumor itself seemingly affects its metastatic potential by changing its interaction with the extracellular matrix. We therefore identify filamin A editing as a critical component for angiogenesis, tumor growth, and metastasis formation.

Abstract The aim of our study was to investigate whether self-reported feeling of loneliness (FoL) and COVID-19-specific health anxiety were associated with the presence of depressive symptoms during the first coronavirus disease 2019 (COVID-19) wave. Questionnaires of 603 persons of the Swiss Multiple Sclerosis Registry (SMSR) were cross-sectionally analyzed using descriptive and multivariable regression methods. The survey response rate was 63.9%. Depressive symptoms were assessed by the Beck Depression Inventory-Fast Screen (BDI-FS). COVID-19-specific health anxiety and FoL were measured using two 5-item Likert scaled pertinent questions. High scoring FoL (2.52, 95% confidence interval (CI) (2.06—2.98)) and/or COVID-19 specific health anxiety (1.36, 95% CI (0.87–1.85)) were significantly associated with depressive symptoms. Further stratification analysis showed that the impact of FoL on depressive symptoms affected all age groups. However, it was more pronounced in younger PwMS, whereas an impact of COVID-19 specific health anxiety on depressive symptoms was particularly observed in middle-aged PwMS. FoL and COVID-19-specific health anxiety were age-dependently associated with depressive symptoms during the first COVID-19 wave in Switzerland. Our findings could guide physicians, health authorities, and self-help groups to better accompany PwMS in times of public health crises.

Malnutrition in the elderly has been associated with deleterious effects on health care outcomes such as functional decline, cognitive impairment, depression, increased hospital stays, and increased morbidity and mortality. This cross-sectional study aims to determine the association of malnutrition with functional status and cognition and duration of hospitalization among 200 elderly patients admitted to medical wards of a tertiary care hospital in India. The nutritional screening was done using Mini Nutritional assessment- short form (MNA-SF). The functional activity was assessed using the Barthel’s Index. Cognitive assessment and screening for depression was done using the Mini-cog test and Geriatric Depression score – 4 respectively. Descriptive analyses were used to estimate the prevalence of malnutrition and associations were assessed using the Pearson chi square test. Among the total patients, 136 (68%) were malnourished. Of these, 45 (22.5%) were severely undernourished. The malnourished patients had poorer functional scores (p

BackgroundThe increasing availability of “real-world” data in the form of written text holds promise for deepening our understanding of societal and health-related challenges. Textual data constitute a rich source of information, allowing the capture of lived experiences through a broad range of different sources of information (eg, content and emotional tone). Interviews are the “gold standard” for gaining qualitative insights into individual experiences and perspectives. However, conducting interviews on a large scale is not always feasible, and standardized quantitative assessment suitable for large-scale application may miss important information. Surveys that include open-text assessments can combine the advantages of both methods and are well suited for the application of natural language processing (NLP) methods. While innovations in NLP have made large-scale text analysis more accessible, the analysis of real-world textual data is still complex and requires several consecutive steps. ObjectiveWe developed and subsequently examined the utility and scientific value of an NLP pipeline for extracting real-world experiences from textual data to provide guidance for applied researchers. MethodsWe applied the NLP pipeline to large-scale textual data collected by the Swiss Multiple Sclerosis (MS) registry. Such textual data constitute an ideal use case for the study of real-world text data. Specifically, we examined 639 text reports on the experienced impact of the first COVID-19 lockdown from the perspectives of persons with MS. The pipeline has been implemented in Python and complemented by analyses of the “Linguistic Inquiry and Word Count” software. It consists of the following 5 interconnected analysis steps: (1) text preprocessing; (2) sentiment analysis; (3) descriptive text analysis; (4) unsupervised learning–topic modeling; and (5) results interpretation and validation. ResultsA topic modeling analysis identified the following 4 distinct groups based on the topics participants were mainly concerned with: “contacts/communication;” “social environment;” “work;” and “errands/daily routines.” Notably, the sentiment analysis revealed that the “contacts/communication” group was characterized by a pronounced negative emotional tone underlying the text reports. This observed heterogeneity in emotional tonality underlying the reported experiences of the first COVID-19–related lockdown is likely to reflect differences in emotional burden, individual circumstances, and ways of coping with the pandemic, which is in line with previous research on this matter. ConclusionsThis study illustrates the timely and efficient applicability of an NLP pipeline and thereby serves as a precedent for applied researchers. Our study thereby contributes to both the dissemination of NLP techniques in applied health sciences and the identification of previously unknown experiences and burdens of persons with MS during the pandemic, which may be relevant for future treatment.

The date palm tree is extensively cultivated in Middle Eastern countries such as Saudi Arabia, generating a large amount of waste in the form of leaves, seeds, and fibrous materials. This study examined the feasibility of using raw date palm fiber (RDPF) and NaOH chemically modified date palm fiber (NaOH–CMDPF) obtained from discarded agricultural waste for the removal of phenol in an aqueous environment. The adsorbent characterization was performed by using different techniques, i.e., particle size analysis; elemental analyzer (CHN); and BET, FTIR, and FESEM-EDX analysis. The FTIR analysis revealed the presence of various functional groups on the surface of the RDPF and NaOH–CMDPF. The results showed that chemical modification by NaOH increased the phenol adsorption capacity that was well-fitted by the Langmuir isotherm. Higher removal was obtained with NaOH–CMDPF (86%) than with the RDPF (81%). The RDPF and NaOH–CMDPF sorbents’ maximum (Qm) adsorption capacities were more than 45.62 mg/g and 89.67 mg/g and were comparable to the sorption capacities of various other types of agricultural waste biomass reported in the literature. The kinetic studies confirmed that the adsorption of phenol followed the pseudo-second-order kinetic process. The present study concluded that the RDPF and NaOH–CMDPF were eco-friendly and cost-effective in promoting sustainable management and the reuse of the Kingdom’s lignocellulosic fiber waste material.

Introduction: With the exponential increase in India's elderly population, the medical students of today need to be well prepared for the demographic changes of tomorrow. Training and attitude of future physicians in elderly care should develop concurrently with the rise in qualifying medical graduates. Objectives: The aim of this study is to determine the knowledge and attitudes of medical students entering internships, toward older people at a teaching hospital in Thrissur, Kerala. Methodology: Medical students of a medical college in Kerala, who were to enter the residency program were enrolled in the study. Sixty-nine students, who voluntarily participated, were asked to complete two questionnaires, the Revised Facts on Aging Quiz, a 25-item multiple-choice test on aging, and the University of California at Los Angeles (UCLA) Geriatric Attitudes Scale, a 14-item questionnaire consisting of a mixture of positively and negatively worded questions answered on a five-point Likert scale. The data obtained were assessed using SPSS version 21. Results: The results indicate that although the medical students entering residency showed a moderately positive attitude (UCLA score 49.67 ± 5.02) toward older people, almost one-third (n = 20, 29%) of these 69 students had poor knowledge (25%–50% score), and the rest (n = 49, 71%) had minimal knowledge (51%–75% scores) on aging. Conclusion: These findings suggest that training in geriatrics is inadequate for MBBS students. More geriatric based content needs to be incorporated into the undergraduate curriculum to address the changing population demographics.

Despite a high primary school enrollment in India, the overall learning levels have been low, and the dropout level in secondary school and beyond has been high. One reason for low learning levels and high drop-out rates is the student’s lack of motivation to learn in the classroom. We suggest that curiosity may be a useful tool to improve student motivation. We look at some important variables that have been found to affect curiosity in the classroom: self-determination needs, information relevance, coherence, concreteness, ease of comprehension, fantasy, belief about interest malleability, and information gap. Finally, we suggest ways to incorporate them in the classroom to improve student motivation.

Background: Multiple sclerosis (MS) symptoms are expected to aggregate in specific patterns across different stages of the disease. Here, we studied the clustering of onset symptoms and examined their characteristics, comorbidity patterns and associations with potential risk factors.Methods: Data stem from the Swiss Multiple Sclerosis Registry, a prospective study including 2,063 participants by November 2019. MS onset symptoms were clustered using latent class analysis (LCA). The latent classes were further examined using information on socio-demographic characteristics, MS-related features, potential risk factors, and comorbid diseases.Results: The LCA model with six classes (frequencies ranging from 12 to 24%) was selected for further analyses. The latent classes comprised a multiple symptoms class with high probabilities across several symptoms, contrasting with two classes with solitary onset symptoms: vision problems and paresthesia. Two gait classes emerged between these extremes: the gait-balance class and the gait-paralysis class. The last class was the fatigue-weakness-class, also accompanied by depression symptoms, memory, and gastro-intestinal problems. There was a moderate variation by sex and by MS types. The multiple symptoms class yielded increased comorbidity with other autoimmune disorders. Similar to the fatigue-weakness class, the multiple symptoms class showed associations with angina, skin diseases, migraine, and lifetime prevalence of smoking. Mononucleosis was more frequently reported in the fatigue-weakness and the paresthesia class. Familial aggregation did not differ among the classes.Conclusions: Clustering of MS onset symptoms provides new perspectives on the heterogeneity of MS. The clusters comprise different potential risk factors and comorbidities. They point toward different risk mechanisms.

The crystallization behavior of polyolefins continues to gain much attention for the prediction of suitable processing conditions. This study aims to understand the influence of biochar (BC) particles on the crystallization behavior of the selected semi-crystalline polypropylene (PP). For this purpose, BC samples were prepared from waste biomass at various pyrolysis temperature. The prepared BC samples were used to fabricate PP composites via melt processing technique. The crystallization behavior of these composites was studied by differential scanning calorimetry (DSC) calorimetry and validated using Avrami analysis in a non-isothermal conditions. It was observed that BC particles act as nucleating agents and accelerate the overall rate of crystallization. Avrami theory analysis indicated that the addition of BC particles provides polypropylene (PP) composites with a higher crystallization rate, i.e. about one order of magnitude higher than the neat PP. The results of the TGA analysis showed that the BC particles enhanced the thermal stability of the BC/PP composites, and is up to 80 °C higher than the neat PP sample.

Connectomics is essential for understanding large-scale brain networks but requires that individual connection estimates are neurobiologically interpretable. In particular, a principle of brain organization is that reciprocal connections between cortical areas are functionally asymmetric. This is a challenge for fMRI-based connectomics in humans where only undirected functional connectivity estimates are routinely available. By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation.Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently. Furthermore, graph-theoretical analyses of directed connectivity estimates identify functional roles of motor areas more accurately than undirected functional connectivity estimates. These results, which can be achieved in an entirely unsupervised manner, demonstrate the feasibility of inferring directed connections in whole-brain networks and open new avenues for human connectomics.

ObjectiveEvidence for the management of acute otitis externa (AOE) is limited, with unclear diagnostic criteria and variably reported outcome measures that may not reflect key stakeholder priorities. We aimed to develop 1) a definition, 2) diagnostic criteria and 3) a core outcome set (COS) for AOE.Study designCOS development according to Core Outcome Measures in Effectiveness Trials (COMET) methodology and parallel consensus selection of diagnostic criteria/definition.SettingStakeholders from the United Kingdom.Subjects and methodsComprehensive literature review identified candidate items for the COS, definition and diagnostic criteria. Nine individuals with past AOE generated further patient-centred candidate items. Candidate items were rated for importance by patient and professional (ENT doctors, general practitioners, microbiologists, nurses, audiologists) stakeholders in a three-round online Delphi exercise. Consensus items were grouped to form the COS, diagnostic criteria, and definition.ResultsCandidate COS items from patients (n = 28) and literature (n = 25) were deduplicated and amalgamated to a final candidate list (n = 46). Patients emphasised quality-of-life and the impact on daily activities/work. Via the Delphi process, stakeholders agreed on 31 candidate items. The final COS covered six outcomes: pain; disease severity; impact on quality-of-life and daily activities; patient satisfaction; treatment-related outcome; and microbiology. 14 candidate diagnostic criteria were identified, 8 reaching inclusion consensus. The final definition for AOE was 'diffuse inflammation of the ear canal skin of less than 6 weeks duration'.ConclusionThe development and adoption of a consensus definition, diagnostic criteria and a COS will help to standardise future research in AOE, facilitating meta-analysis. Consulting former patients throughout development highlighted deficiencies in the outcomes adopted previously, in particular concerning the impact of AOE on daily life.

Bigels are biphasic semisolid systems that have been explored as delivery vehicles in the food and pharmaceutical industries. These formulations are highly stable and have a longer shelf-life than emulsions. Similarly, cellulose-based hydrogels are considered to be ideal for these formulations due to their biocompatibility and flexibility to mold into various shapes. Accordingly, in the present study, the properties of an optimized guar gum hydrogel and sesame oil/candelilla wax oleogel-based bigel were tailored using date palm-derived cellulose nanocrystals (dp-CNC). These bigels were then explored as carriers for the bioactive molecule moxifloxacin hydrochloride (MH). The preparation of the bigels was achieved by mixing guar gum hydrogel and sesame oil/candelilla wax oleogel. Polarizing microscopy suggested the formation of the hydrogel-in-oleogel type of bigels. An alteration in the dp-CNC content affected the size distribution of the hydrogel phase within the oleogel phase. The colorimetry studies revealed the yellowish-white color of the samples. There were no significant changes in the FTIR functional group positions even after the addition of dp-CNC. In general, the incorporation of dp-CNC resulted in a decrease in the impedance values, except BG3 that had 15 mg dp-CNC in 20 g bigel. The BG3 formulation showed the highest firmness and fluidity. The release of MH from the bigels was quasi-Fickian diffusion mediated. BG3 showed the highest release of the drug. In summary, dp-CNC can be used as a novel reinforcing agent for bigels.

There is a demand for long afterglow composites due to their potential applications in nighttime signal boards, sensors, and biomedical areas. In this study, Polypropylene (PP)/strontium aluminate-based composites [SrAl2O4:Eu2+/Dy3+ (SAO1) and Sr4Al14O25: Eu+2, Dy+3 (SAO2)] with maleic anhydride grafted PP compatibilizer (PRIEX) were prepared, and their auto-glowing properties were examined. After UV excitation at 320 nm, the PP/5PRIEX/SAO1 composites showed green emission at 520 nm, and blue emission was observed for PP/5PRIEX/SAO2 around 495 nm. The intensity of phosphorescence emission and phosphorescence decay was found to be proportional to the filler content (SAO1 and SAO2). The FTIR analysis excluded the copolymerization reaction between the SAO1 and SAO2 fillers and the PP matrix during the high-temperature melt mixing process. The SAO1 and SAO2 fillers decreased the overall crystallinity of the composites without affecting the Tm and Tc (melting and crystallization temperature) values. The thermal stability of the composites was slightly improved with the SAO1 and SAO2 fillers, as seen from the TGA curve. Due to the plasticizing effect of the compatibilizer and the agglomeration of the SAO1 and SAO2 fillers, the tensile modulus, tensile strength, and storage modulus of the composites was found to be decreased with an increase in the SAO1 and SAO2 content. The decreasing effect was more pronounced, especially with the bulk-sized SAO2 filler.

In the present work, six protic ionic liquid (PIL) compounds based on p-toluene sulfonic acid [PTSA] anion along with different cations viz. tetraethylenepentammonium [TEPA], triethylammonium [TEA], pyridinium [Py], N-methylpiperidinium [Pip], 1-methylimidazolium [Im], and N-methylpyrrolidinium [Pyrr] were synthesized using the standard neutralization reaction method. The structural characterization of these compounds was achieved using FTIR, 1H and 13C NMR spectroscopies. Thermal behavior was studied using differential scanning calorimetry to determine the melting point (Tm) and crystallization (Tc) temperatures. Thermogravimetric analysis was carried out to determine the thermal stability and degradation temperatures (Tdec) and to ascertain the hygroscopic or hydrophobic nature of the synthesized compounds. Structural effects on the outcome of various properties were witnessed and discussed in detail. Electrochemical impedance spectroscopy was utilized to study the electrical transport properties of the PILs at different temperatures. Cyclic voltammetry was performed to analyze the electrochemical stability of these PILs. Low values of activation energy indicating easy proton transportation along with good electrochemical stability make the PILs a potential candidate for use in the preparation of polymer electrolytes membranes for fuel cell applications.

The current study delineates the use of date-palm-derived cellulose nanocrystals (dp-CNCs) as reinforcing agents. dp-CNCs were incorporated in varying amounts to poly(vinyl alcohol)/guar-gum-based phase-separated composite films. The films were prepared by using the solution casting method, which employed glutaraldehyde as the crosslinking agent. Subsequently, the films were characterized by bright field and polarizing microscopy, UV-Vis spectroscopy, FTIR spectroscopy, and mechanical study. The microscopic techniques suggested that phase-separated films were formed, whose microstructure could be tailored by incorporating dp-CNCs. At higher levels of dp-CNC content, microcracks could be observed in the films. The transparency of the phase-separated films was not significantly altered when the dp-CNC content was on the lower side. FTIR spectroscopy suggested the presence of hydrogen bonding within the phase-separated films. dp-CNCs showed reinforcing effects at the lowest amount, whereas the mechanical properties of the films were compromised at higher dp-CNC content. Moxifloxacin was included in the films to determine the capability of the films as a drug delivery vehicle. It was found that the release of the drug could be tailored by altering the dp-CNC content within the phase-separated films. In gist, the developed dp-CNC-loaded poly(vinyl alcohol)/guar-gum-based phase-separated composite films could be explored as a drug delivery vehicle.

Mindfulness Based Cognitive Therapy (MBCT) was developed to combine methods from cognitive behavioral therapy and meditative techniques, with the specific goal of preventing relapse in recurrent depression. While supported by empirical evidence from multiple clinical trials, the cognitive mechanisms behind the effectiveness of MBCT are not well understood in computational (information processing) or biological terms.This article introduces a testable theory about the computational mechanisms behind MBCT that is grounded in “Bayesian brain” concepts of perception from cognitive neuroscience, such as predictive coding. These concepts regard the brain as embodying a model of its environment (including the external world and the body) which predicts future sensory inputs and is updated by prediction errors, depending on how precise these error signals are.This article offers a concrete proposal how core concepts of MBCT—(i) the being mode (accepting whatever sensations arise, without judging or changing them), (ii) decentering (experiencing thoughts and percepts simply as events in the mind that arise and pass), and (iii) cognitive reactivity (changes in mood reactivate negative beliefs)—could be understood in terms of perceptual and metacognitive processes that draw on specific computational mechanisms of the “Bayesian brain.” Importantly, the proposed theory can be tested experimentally, using a combination of behavioral paradigms, computational modelling, and neuroimaging. The novel theoretical perspective on MBCT described in this paper may offer opportunities for finessing the conceptual and practical aspects of MBCT.

BackgroundIn recent years, YouTube has become a recognized source of medical information for health care consumers. Although YouTube has advantages in this context, there are potential dangers as videos may contain nonscientific, misleading, or even harmful information. ObjectiveAs little is known about YouTube as a source of information on atopic dermatitis (AD), we investigated the content-related quality of AD videos and their perception among YouTube users. MethodsThe quality of the 100 most viewed AD videos was assessed by using the Global Quality Scale (GQS) and the DISCERN instrument. Videos were classified as “useful,” “misleading,” and “potentially harmful,” and the correlations of viewers’ ratings (likes) with the GQS and DISCERN scores were assessed. ResultsAmong the 100 videos, 68.0% (68/100) and 62.0% (62/100) were of poor and very poor scientific quality, respectively. Additionally, 32.0% (32/100) of the videos were classified as useful, 48.0% (48/100) were classified as misleading, and 34.0% (34/100) were classified as potentially harmful. Viewers’ ratings did not correlate with the GQS and DISCERN scores. Overall, 50.0% (50/100) of the videos were posted by private individuals and promoters of complementary/alternative treatments, 42.0% (42/100) by therapeutical advertisers, and only 8.0% (8/100) by nonprofit organizations/universities. ConclusionsOur study demonstrated that two-thirds of the videos analyzed were below acceptable medical quality standards and that many videos were disseminating misleading or even dangerous content. Subjective and anecdotal content was overrepresented, and viewers did not appear to be able to distinguish between high- and low-quality videos. Health promotion strategies by professional medical organizations are needed to improve their presence and visibility on YouTube.

Background: Multiple sclerosis (MS) is the most common chronic, non-traumatic, neurologic disease in young adults. While approximate values of the disease burden of MS are known, individual drivers are unknown.Objective: To estimate the age-, sex-, and disease severity-specific contributions to the disease burden of MS.Methods: We estimated the disease burden of MS using disability-adjusted life years (DALYs) following the Global Burden of Disease study (GBD) methodology. The data sources consisted of the Swiss MS Registry, a recent prevalence estimation, and the Swiss mortality registry.Results: The disease burden of MS in Switzerland in 2016 was 6,938 DALYs (95%-interval: 6,018-7,955), which corresponds to 97 DALYs per 100,000 adult inhabitants. Morbidity contributed 59% of the disease burden. While persons in an asymptomatic (EDSS-proxy 0) and mild (EDSS-proxy >0–3.5) disease stage represent 68.4% of the population, they make up 39.8% of the MS-specific morbidity. The remaining 60.2% of the MS-specific morbidity stems from the 31.6% of persons in a moderate (EDSS-proxy 4–6.5) or severe (EDSS-proxy ≥7) disease stage.Conclusions: Morbidity has a larger influence on the disease burden of MS than mortality and is shared in a ratio of 2:3 between persons in an asymptomatic/mild and moderate/severe disease stage in Switzerland. Interventions to reduce severity worsening in combination with tailored, symptomatic treatments are important future paths to lower the disease burden of MS.

In this work, HDPE/strontium aluminate-based auto glowing composites (SrAl2O4: Eu, Dy (AG1) and Sr4Al14O25: Eu, Dy (AG2)) were prepared, and their phosphorescence studies were conducted. In HDPE/AG1 composites, the green emission was observed at ~500 nm after the UV excitation at 320 nm. The HDPE/AG2 has a blue emission at ~490 nm and, in both cases, the intensity of emission is proportional to the AG1 and AG2 content. The DSC data show that the total crystallinity of both the composites was decreased but with a more decreasing effect with the bulky AG2 filler. The melting and crystallization temperatures were intact, which shows the absence of any chemical modification during high shear and temperature processing. This observation is further supported by the ATR-FTIR studies where no new peaks appeared or disappeared from the HDPE peaks. The tensile strength and modulus of HDPE, HDPE/AG1, and HDPE/AG2 composites were improved with the AG1 and AG2 fillers. The rheological studies show the improvement in the complex viscosity and accordingly the storage modulus of the studied phosphorescent HDPE composites. The SEM images indicate better filler dispersion and filler–matrix adhesion, which improves the mechanical characteristics of the studied HDPE composites. The ageing studies in the glowing composites show that there is a decrease in the intensity of phosphorescence emission on exposure to drastic atmospheric conditions for a longer period and the composites become more brittle.

Cellulosic polysaccharides have increasingly been recognized as a viable substitute for the depleting petro-based feedstock due to numerous modification options for obtaining a plethora of bio-based materials. In this study, cellulose triacetate was synthesized from pure cellulose obtained from the waste lignocellulosic part of date palm (Phoenix dactylifera L.). To achieve a degree of substitution (DS) of the hydroxyl group of 2.9, a heterogeneous acetylation reaction was carried out with acetic anhydride as an acetyl donor. The obtained cellulose ester was compared with a commercially available derivative and characterized using various analytical methods. This cellulose triacetate contains approximately 43.9% acetyl and has a molecular weight of 205,102 g·mol−1. The maximum thermal decomposition temperature of acetate was found to be 380 °C, similar to that of a reference sample. Thus, the synthesized ester derivate can be suitable for fabricating biodegradable and “all cellulose” biocomposite systems.

Conflicts involving caste issues, mainly concerning the lowest caste rights, pervade modern Indian society. Caste affiliation, being rigorously enforced by the society, is an official contemporary reality. Although caste identity is a major social discrimination, it also serves as a necessary condition for affirmative action like reservation policy. In this article, we perform an original and rigorous analysis of the discourse involving the theme “caste” in India newspapers. To this purpose, we have implemented a computational analysis over a big dataset of the 2016 and 2017 editions of three major Indian newspapers to determine the most salient themes associated with “caste” in the news. We have used an original mix of state-of-the-art algorithms, including those based on statistical distributions and two-layer neural networks, to detect the relevant topics in the news and characterize their linguistic context. We concluded that there is an excessive association between lower castes, victimization, and social unrest in the news that does not adequately cover the reports on other aspects of their life and personal identity, thus reinforcing conflict, while attenuating the vocality and agency of a large section of the population. From our conclusion, we propose a positive discrimination policy in the newsroom.

Sepsis occurs when the immune system has a severe reaction to an infection. It leads to extensive inflammation which can cause tissue damage, organ failure, and even death. Due to this, rapid diagnosis and treatment are necessary in order to ensure the patient's survival. However, it is extremely difficult to quickly diagnose sepsis, allowing sepsis to be the leading cause of preventable death worldwide. Thus, this study focuses on a technique that can be used to rapidly indicate that sepsis may be present. A model using machine learning was made in order to classify blood smears into "sepsis" and "not sepsis" using CNN learning methods. This rudimentary model is the foundation of an upcoming application that will use multi-label classification to accurately and quickly diagnose sepsis. [ABSTRACT FROM AUTHOR]

This study was carried out to evaluate the effectiveness of partial and full vaccination with ChAdOx1 nCoV-19 (COVISHIELD) to prevent the development of moderate or severe illness among COVID-positive cases. This prospective cohort study was conducted among Armed Forces personnel deployed in Northern India who were found COVID positive during the study period between January and June 2021. Information about the vaccination status, age and comorbidities was collected at the time of diagnosis. Classification of COVID cases as moderate or severe was performed as per criteria given by the Government of India. Individuals were considered partially vaccinated three weeks after one dose and fully vaccinated two weeks after the second dose. Risk ratio and vaccine effectiveness (VE) to prevent moderate or severe disease among COVID cases were calculated. A total of 2005 COVID-19 patients were included in our study. Partial vaccination and full vaccination with ChAdOx1 nCoV-19 offered 13% (95% credible interval (CI): −56.8%, 52.8%) and 66.6% (95% CI: 34.9%, 84.6%) protection against progression to moderate/severe illness among COVID-positive individuals. The risk of moderate-severe disease among COVID-positive cases occurring 4–11 weeks after the first dose was also lesser among those who had taken the second dose of vaccine than individuals who have been vaccinated with only one dose. Interval between the first and second doses of ChAdOx1 nCoV-19 vaccine should be reduced to 4–6 weeks, as partial vaccination offers lower protection against the development of moderate-severe illness after COVID infection. [ABSTRACT FROM AUTHOR]

The default scheduler of Apache Hadoop demonstrates operational inefficiencies when connecting external sources and processing transformation jobs. This paper has proposed a novel scheduler for enhancement of the performance of the Hadoop Yet Another Resource Negotiator (YARN) scheduler, called the Adaptive Node and Container Aware Scheduler (ANACRAC), that aligns cluster resources to the demands of the applications in the real world. The approach performs to leverage the user-provided configurations as a unique design to apportion nodes, or containers within the nodes, to application thresholds. Additionally, it provides the flexibility to the applications for selecting and choosing which node's resources they want to manage and adds limits to prevent threshold breaches by adding additional jobs as needed. Node or container awareness can be utilized individually or in combination to increase efficiency. On top of this, the resource availability within the node and containers can also be investigated.This paper also focuses on the elasticity of the containers and self-adaptiveness depending on the job type. The results proved that 15%-20% performance improvement was achieved compared with the node and container awareness feature of the ANACRAC. It has been validated that this ANACRAC scheduler demonstrates a 70%-90% performance improvement compared with the default Fair scheduler. Experimental results also demonstrated the success of the enhancement and a performance improvement in the range of 60% to 200% when applications were connected with external interfaces and high workloads. [ABSTRACT FROM AUTHOR]

The interrelations between fatigue, depression and health-related quality of life (HRQoL) in persons with multiple sclerosis (PwMS) are complex, and the directionality of the effects is unclear. To address this gap, the current study used a longitudinal design to assess direct and indirect effects of fatigue and depression on HRQoL in a one-year follow-up survey. A sample of 210 PwMS from the nationwide Swiss MS Registry was used. HRQoL was assessed using the European Quality of Life 5-Dimension 5-Level questionnaire. Path analysis on HRQoL, with fatigue and depression as predictors, was applied. Fatigue was measured by the Modified Fatigue Impact Scale (MFIS), including physical, cognitive and psychosocial subscales, and non-somatic depressive symptomatology was examined with the Beck Depression Inventory-Fast Screen (BDI-FS). Fatigue acted as a fully mediating variable (B = −0.718, SE = 0.253) between non-somatic depressive symptomatology and HRQoL. This indirect effect became apparent in the physical (B = −0.624, SE = 0.250), psychosocial (B = −0.538, SE = 0.256) and cognitive subscales (B = −0.485, SE = 0.192) of fatigue. In contrast, non-somatic depressive symptomatology did not act as a mediator. Our findings provide novel and clinically relevant longitudinal evidence showing that the debilitating effect of non-somatic aspects of depression on HRQoL was fully mediated and therefore explainable via fatigue.

Highly pure cellulosic polymers obtained from waste lignocellulose offer great potential for designing novel materials in the concept of biorefinery. In this work, alpha-cellulose and nanocrystalline cellulose were isolated from the date palm trunk mesh (DPTM) through a series of physicochemical treatments. Supercritical carbon dioxide treatment was used to remove soluble extractives, and concentrated alkali pretreatment was used to eliminate the lignin portion selectively to obtain alpha-cellulose in approximately 94% yield. Further treatments of this cellulose yielded nanocrystalline cellulose. The structure–property relationship studies were carried out by characterizing the obtained polymers by various standard methods and analytical techniques such as Fourier transform infrared spectroscopy-attenuated total reflection (FTIR-ATR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), energy dispersive X-ray diffraction (EDX-XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Almost 65% yield of pure cellulose was achieved, out of which 94% is the alpha-cellulose. This cellulose shows good thermal stability and crystallinity. The microscopic analysis of the nanocellulose showed a heterogeneous mix of irregular-shaped particles with a size range of 20–60 nm. The percentage crystallinity of alpha-cellulose and nanocellulose was found to be 68.9 and 71.8, respectively. Thus, this study shows that, this DPTM-based low-cost waste biomass can be a potential source to obtain cellulose and nano-cellulose.