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Access to information and effective delivery can be improved by using multimedia as a tool for advisory services. Various factors contribute to the development of an effective multimedia-based agro-advisory model. Stakeholders’ perception plays a major role to design and validate it properly. To measure stakeholders’ perception towards multimedia-based agro-advsiory (Pusa Samachar), a multi-dimensional perception scale was developed using Polychoric Principal Component Analysis (PCA). The data pertaining to this study were collected from 150 farmers using Google forms in 2021 and from 225 farmers in 2022. These farmers were sampled using stratified two-stage sampling from five districts each from Uttar Pradesh, Haryana and Punjab states. The majority of the farmers (68.6%) reported watching full weekly episode of agro-advisory telecasted as Pusa Samachar. Notably, farmers of Uttar Pradesh (54.67%) and Haryana (60.0%) showed affirmative perception; while Punjab (50.83%) had neutral perception towards Pusa Samachar model. Analysis of average perception score of farmers revealed that technical factor ranked I followed by linguistic factor (II), content and design factor (III) and timeliness factor (IV). Audio-visual quality, graphics, time duration of content, language, accent, and style of presentation with quality content could be considered as prime parameters for developing multimedia-based content. Location-specific, farmers’ centric language-based, and farmer participatory multimedia-based content should be created for better information availability and acceptance among farming community.

The livelihood of Indian farmers is primarily shaped by agriculture and its allied components. The degree of intricacy and contributions of each agricultural activity, although, vary with different social-ecological systems. Migration is considered an approach to livelihood adaptation; however, the migrants face challenges in new social-ecological settings due to their limited access to resources. This research aimed to develop a predictive model for sustainable agricultural employment options in Rajasthan and Uttar Pradesh (UP). In this study, states were selected purposively, while respondent farmers were chosen using a stratified multistage sampling design. A total of 480 resident and migrant farmers were selected to collect data. The machine learning algorithm, based on classification and regression tree (CART) analysis, was applied that could help to identify factors and prospects for migrant farmers in the agricultural sector. Results indicated that milk yield, operational land holding, and rabi crop yield were significant predictors. Further, milk yield, rabi crop yield, and kharif crop yield were observed to be the essential factors contributing to profitable ventures. The recommendations provided by Krishi Vigyan Kendra’s professionals led to the identification of key income-generating activities, such as livestock management, vegetable production, and organic farming. These prospects are tailored to the location-specific context where migrant farmers reside. Overall, this research shed light on viable employment opportunities, ultimately contributing to the well-being of migrant workers in northern India, in addition to the policy interventions focused on capacity building and providing an enabling environment to the migrants.

Farm women are often forced to work in extremely hazardous conditions due to their limited access to improved agricultural technologies. This circumstance makes agricultural work physically demanding, requiring significant physiological effort and the maintenance of good posture. It is also very exhausting, time-consuming, and stressful. The study was designed to evaluate and quantify the drudgery involved in the rice-wheat production system for rural women. Three replications of a 10-min work cycle without a break were used to assess the physiological and postural demands of various farm tasks on the female workers. Observations were recorded on farm women workers who were in normal health, without any major illness, and regularly involved in farm operations. In the attempt to obtain and analyze the prioritized drudgery experiences in crop production activities through drudgery assessment and reduction, various ergonomically sound farm tools and implements were provided for crop cultivation and intercultural operations. Data indicating musculoskeletal disorders were analyzed by ergonomics assessment of postural and biomechanical assessments using the Human Physical Drudgery Index (HPDI), resulting in the maximum drudgery reflecting very high risk in transplanting (48.4%), followed by threshing (47.2%), load carrying (46.00%), and harvesting (45.14%). For physiological ergonomics quantifications, the most drudgery-prone activities in the rice-wheat production system, i.e., transplanting, harvesting, threshing & post-harvest, and load carrying, were evaluated, and it was found that drudgery is caused by different activities with reflects working energy expenditure rate ranging from ~7.00 to 12.00 (kJ/min) and total cardiac cost of work (TCCW) ~ 331.00 to 524.00. Multivariate regression analysis was employed to drive relationships between energy expenditure rate (dependent variable) and other independent variables, such as age, body mass index (BMI), mid-upper arm circumference (MUAC), calf circumference (CC), skinfold measurements, body density (D), % body fat, fat mass, and fat-free mass (kg). It was found that energy expenditure rate during various crop production practices is positively correlated with independent variables (R = 0.721, R2 = 0.520, Adjusted R2 = 0.518, Standard Error of Estimate = 0.0324, Durbin-Watson = 1.531). It was found that with higher physiological parameters, the corresponding energy expenditure is maximized relating to the drudgery in respective agricultural activities. The present study addressed the magnitude of drudgery for women farmers in the rice-wheat production system and its mitigation strategy.

Angluin's L$^*$ algorithm learns the minimal deterministic finite automaton (DFA) of a regular language using membership and equivalence queries. Its probabilistic approximatively correct (PAC) version substitutes an equivalence query by numerous random membership queries to get a high level confidence to the answer. Thus it can be applied to any kind of device and may be viewed as an algorithm for synthesizing an automaton abstracting the behavior of the device based on observations. Here we are interested on how Angluin's PAC learning algorithm behaves for devices which are obtained from a DFA by introducing some noise. More precisely we study whether Angluin's algorithm reduces the noise and produces a DFA closer to the original one than the noisy device. We propose several ways to introduce the noise: (1) the noisy device inverts the classification of words w.r.t. the DFA with a small probability, (2) the noisy device modifies with a small probability the letters of the word before asking its classification w.r.t. the DFA, (3) the noisy device combines the classification of a word w.r.t. the DFA and its classification w.r.t. a counter automaton, and (4) the noisy DFA is obtained by a random process from two DFA such that the language of the first one is included in the second one. Then when a word is accepted (resp. rejected) by the first (resp. second) one, it is also accepted (resp. rejected) and in the remaining cases, it is accepted with probability 0.5. Our main experimental contributions consist in showing that: (1) Angluin's algorithm behaves well whenever the noisy device is produced by a random process, (2) but poorly with a structured noise, and, that (3) is able to eliminate pathological behaviours specified in a regular way. Theoretically, we show that randomness almost surely yields systems with non-recursively enumerable languages.

A study was undertaken to analyse farmers’ access to various agricultural extension service sources, their preferences and to delineate underlying determinants for their access. The study used NSSO 77th survey dataset of 14,782 households of IGP states (Bihar, Haryana, Punjab, Uttar Pradesh, West Bengal). Farmers’ preferences varied, with private agencies—particularly input dealers—emerging as the top choice, followed by traditional mass media channels and the public extension system. Utility of Cooperative model, and farmer-based organizations have not yet been fully explored for information needs. The inputs (seeds, fertilizers, plant protection) were the most sought-after information. However, in an era of changing needs, farmers should strive to acquire additional information on aspects such as marketing, climate change, and post-harvest functions. The type of information sought by the farmers, influences their preferred sources of extension services. Irrespective of the source, the degree of access diminishes with the decreasing landholding. Among the five IGP states, Haryana emerged as the champion of information access for farmers, while Bihar lagged. Multivariate probit analysis reported that the likelihood of access to agricultural information sources was positively influenced by age, gender, education, size of operational landholding, irrigated area, and sale of produce at MSP. The study suggests making the extension services for small and socio-economically marginalized farmers more inclusive. Inclusiveness of extension services is essential for sustainability because it ensures that all farmers, regardless of their landholding, gender, age, caste, etc., have access to knowledge and resources they need to adopt improved agricultural practices and thus, secure prosperous livelihoods.

Abstract Activation-induced cytidine deaminase (AID) is the key mediator of antibody diversification in activated B-cells by the process of somatic hypermutation (SHM) and class switch recombination (CSR). Targeting AID to the Ig genes requires transcription (initiation and elongation), enhancers, and its interaction with numerous factors. Furthermore, the HIRA chaperon complex, a regulator of chromatin architecture, is indispensable for SHM. The HIRA chaperon complex consists of UBN1, ASF1a, HIRA, and CABIN1 that deposit H3.3 onto the DNA, the SHM hallmark. We explored whether UBN1 interacts with AID using computational and in-vitro experiments. Interestingly, our in-silico studies, such as molecular docking and molecular dynamics simulation results, predict that AID interacts with UBN1. Subsequently, co-immunoprecipitation and pull-down experiments established interactions between UBN1 and AID inside B-cells. Additionally, a double immunofluorescence assay confirmed that AID and UBN1 were co-localized in the human and chicken B-cell lines. Moreover, proximity ligation assay studies validated that AID interacts with UBN1. Ours is the first report on the interaction of genome mutator enzyme AID with UBN1. Nevertheless, the fate of interaction between UBN1 and AID is yet to be explored in the context of SHM or CSR.

Background: Morphology and morphometry of lengths of bones with respect of the height of the person vary from country to country and from place to place. Objective: objective was to study relationship between the percutaneous length of fibula & height of that individual in adult bengalee population. Methods: In a cross sectional descriptive study, 400 (200male & 200 female) adult bengalee person were studied and the percutaneous length of fibula & their height were measured and analysed. Results: Positive correlation was found between the height of the person and the length of both right and left fibula separately both in case of male and female subjects. Also correlation between the right and left fibula was statistically significant both in male and female subjects. Conclusion: In the present study the results showed that length of fibula is important for estimating height in respect of specific racial, geographical and gender specific population group (here adult Bengalee population). Separate and independent linear regression equation derived for the specific population group & it demonstrates that the length of fibula (long bone) can be used to estimate the stature of adult Bengalee population in Burdwan District.

The migration patterns of farmers, rural women, and youth within agricultural households have a significant impact on rural communities and the agricultural sector. To gain a deeper understanding of research trends in migration behavior, a study was conducted using comprehensive bibliometric analysis and text mining. René Descartes’ Discourse framework was employed to analyze 504 research articles retrieved from the Dimension.ai database followed by further analysis with Microsoft Excel, R software and VOS viewer. The study revealed a growing interest of various stakeholders in this field, with an increasing number of publications focusing on various aspects from 1934 to 2023. In terms of the publication’s performance analysis, the study identified human society and the second Sustainable Development Goal (SDG) as the most significant research areas. These areas aim to address hunger and improve food security for migrants. Regarding migration studies, three influential journals—Sustainability, World Development, and Journal of Rural Studies—were identified, with the most influential author being J. Vernon Henderson from the United Kingdom. Citation analysis was conducted to determine the highest number of citations for the influential author (J. V. Hernderon), journal (World Development), organization (World Bank), and country (United States) based on scientific attribution. Additionally, a co-word analysis was performed to research article’s abstracts to map into key thematic clusters that include climate change, food insecurity, and the COVID-19 crisis. The study visualized the social network of authors, organizations, and countries involved in co-authorship analysis within the research field. Furthermore, a journal co-citation analysis was undertaken to reveal the intellectual structure of migration studies in the agricultural context. Text mining of the research documents uncovered both anticipated and unanticipated effects of migration on households. Consequently, these findings provide valuable insights into future research directions and evidence-based policy framing which will contribute to shielding agricultural households from unforeseen consequences of migration, benefiting researchers, policymakers, and practitioners in this arena.

Introduction: Good communication skills (CSs) are not only the crux of a good doctor–patient relationship but also the foundation over which any human relationship is based. The aim of this study was to assess the impact of training on CS in Phase I MBBS students in a Government Medical College in West Bengal, India. Materials and Methods: One hundred and eighty-four Phase I medical students were trained on how to communicate properly with their peers, seniors, teachers, college authorities, department staff, patient relatives, and other health professionals. Each participant underwent a set of three assessments (presession, postsession, and late postsession) for both knowledge and skills in CS. After postsession assessment, feedback by the faculties and peers was provided and reflections were obtained from the participants. A prevalidated questionnaire and Gap-Kalamazoo CS Assessment Form (with some modification) were used for knowledge and skill's assessment, respectively. At the end of the module, feedback was collected from the participants. Data were tabulated and results were compared and interpreted. Results: Mean score and standard deviation for knowledge assessment were 5.29 ± 1.35, 9 ± 1.20 and 8.55 ± 0.97 in T1, T2, and T3 and for skills' score were 17.78 ± 4.89, 26.32 ± 5.04 and 30.77 ± 3.66 in SA1, SA2, and SA3, respectively. Most participants showed improvement in T2 with mean improvement score (T2–T1) of 79.57 ± 47.25 and mean retention score (T3–T1) of 71.9 ± 47.84. About 52% of participants showed deterioration in T3 with late deterioration score (T3–T2) of − 4.06 ± 11.42. 33% showed no change in knowledge, i.e., they retained their improvements, whereas 15% showed further improvement. Fifty-two percent of participants showed skills' improvement by scores of 7–12, 43% showed retention by 13–18, and late deterioration was shown by 82%, their scores dropped by 0–6. Conclusion: The training module was successfully implemented, and participants appreciated this type of participant centric assessment-based teaching learning module. They learned about the effective ways of communication in a fun manner and were determined to apply all that they have learned.

Summary: Background: The utility of early metabolic response assessment to guide selection of the systemic component of definitive chemoradiotherapy (dCRT) for oesophageal cancer is uncertain. Methods: In this multi-centre, randomised, open-label, phase II substudy of the radiotherapy dose-escalation SCOPE2 trial we evaluated the role of 18F-Fluorodeoxyglucose positron emission tomography (PET) at day 14 of cycle 1 of three-weekly induction cis/cap (cisplatin (60 mg/m2)/capecitabine (625 mg/m2 days 1–21)) in patients with oesophageal squamous cell carcinoma (OSCC) or adenocarcinoma (OAC). Non-responders, who had a less than 35% reduction in maximum standardised uptake value (SUVmax) from pre-treatment baseline, were randomly assigned to continue cis/cap or switch to car/pac (carboplatin AUC 5/paclitaxel 175 mg/m2) for a further induction cycle, then concurrently with radiotherapy over 25 fractions. Responders continued cis/cap for the duration of treatment. All patients (including responders) were randomised to standard (50Gy) or high (60Gy) dose radiation as part of the main study. Primary endpoint for the substudy was treatment failure-free survival (TFFS) at week 24. The trial was registered with International Standard Randomized Controlled Trial Number 97125464 and ClinicalTrials.gov NCT02741856. Findings: This substudy was closed on 1st August 2021 by the Independent Data Monitoring Committee on the grounds of futility and possible harm. To this point from 22nd November 2016, 103 patients from 16 UK centres had participated in the PET-CT substudy; 63 (61.2%; 52/83 OSCC, 11/20 OAC) of whom were non-responders. Of these, 31 were randomised to car/pac and 32 to remain on cis/cap. All patients were followed up until at least 24 weeks, at which point in OSCC both TFFS (25/27 (92.6%) vs 17/25 (68%); p = 0.028) and overall survival (42.5 vs. 20.4 months, adjusted HR 0.36; p = 0.018) favoured cis/cap over car/pac. There was a trend towards worse survival in OSCC + OAC cis/cap responders (33.6 months; 95%CI 23.1-nr) vs. non-responders (42.5 (95%CI 27.0-nr) months; HR = 1.43; 95%CI 0.67–3.08; p = 0.35). Interpretation: In OSCC, early metabolic response assessment is not prognostic for TFFS or overall survival and should not be used to personalise systemic therapy in patients receiving dCRT. Funding: Cancer Research UK.

Abstract Background Anal cancer is a rare cancer with rising incidence. Despite the relatively good outcomes conferred by state-of-the-art chemoradiotherapy, further improving disease control and reducing toxicity has proven challenging. Developing and validating prognostic models using routinely collected data may provide new insights for treatment development and selection. However, due to the rarity of the cancer, it can be difficult to obtain sufficient data, especially from single centres, to develop and validate robust models. Moreover, multi-centre model development is hampered by ethical barriers and data protection regulations that often limit accessibility to patient data. Distributed (or federated) learning allows models to be developed using data from multiple centres without any individual-level patient data leaving the originating centre, therefore preserving patient data privacy. This work builds on the proof-of-concept three-centre atomCAT1 study and describes the protocol for the multi-centre atomCAT2 study, which aims to develop and validate robust prognostic models for three clinically important outcomes in anal cancer following chemoradiotherapy. Methods This is a retrospective multi-centre cohort study, investigating overall survival, locoregional control and freedom from distant metastasis after primary chemoradiotherapy for anal squamous cell carcinoma. Patient data will be extracted and organised at each participating radiotherapy centre (n = 18). Candidate prognostic factors have been identified through literature review and expert opinion. Summary statistics will be calculated and exchanged between centres prior to modelling. The primary analysis will involve developing and validating Cox proportional hazards models across centres for each outcome through distributed learning. Outcomes at specific timepoints of interest and factor effect estimates will be reported, allowing for outcome prediction for future patients. Discussion The atomCAT2 study will analyse one of the largest available cross-institutional cohorts of patients with anal cancer treated with chemoradiotherapy. The analysis aims to provide information on current international clinical practice outcomes and may aid the personalisation and design of future anal cancer clinical trials through contributing to a better understanding of patient risk stratification.

Summary: Background: Effective surveillance strategies are required for patients diagnosed with oesophageal squamous cell carcinoma (OSCC) or adenocarcinoma (OAC) for whom chemoradiotherapy (CRT) is used as a potentially-curative, organ-sparing, alternative to surgery. In this study, we evaluated the safety, acceptability and tolerability of a non-endoscopic immunocytological device (the Cytosponge™) to assess treatment response following CRT. Methods: This multicentre, single-arm feasibility trial took place in 10 tertiary cancer centres in the UK. Patients aged at least 16 years diagnosed with OSCC or OAC, and who were within 4-16 weeks of completing definitive or neo-adjuvant CRT, were included. Participants were required to have a Mellow-Pinkas dysphagia score of 0-2 and be able to swallow tablets. All patients underwent a single Cytosponge™ assessment in addition to standard of care (which included post-treatment endoscopic evaluation with biopsy for patients undergoing definitive CRT; surgery for those who received neo-adjuvant CRT). The primary outcome was the proportion of consented, evaluable patients who successfully underwent Cytosponge™ assessment. Secondary and tertiary outcomes included safety, study consent rate, acceptance rate, the suitability of obtained samples for biomarker analysis, and the comparative efficacy of Cytosponge™ to standard histology (endoscopy and biopsy or post-resection specimen) in assessing for residual disease. The trial is registered with ClinicalTrials.gov, NCT03529669. Findings: Between 18th April 2018 and 16th January 2020, 41 (42.7%; 95% confidence interval (CI) 32.7-53.2) of 96 potentially eligible patients consented to participate. Thirty-nine (95.1%, 95% CI 83.5-99.4) successfully carried out the Cytosponge™ procedure. Of these, 37 (95%) would be prepared to repeat the procedure. There were only two grade 1 adverse events attributed to use of the Cytosponge™. Thirty-five (90%) of the completed Cytosponge™ samples were suitable for biomarker analysis; 29 (83%) of these were concordant with endoscopic biopsies, three (9%) had findings suggestive of residual cancer on Cytosponge™ not found on endoscopic biopsies, and three (9%) had residual cancer on endoscopic biopsies not detected by Cytosponge™. Interpretation: Use of the CytospongeTM is safe, tolerable, and acceptable for the assessment of treatment response following CRT in OAC and OSCC. Further evaluation of Cytosponge™ in this setting is warranted. Funding: Cancer Research UK, National Institute for Health Research, Medical Research Council.

Calcium ions are used as important signals during various physiological processes. In malaria parasites, Plasmodium spp., calcium dependent protein kinases (CDPKs) have acquired the unique ability to sense and transduce calcium signals at various critical steps during the lifecycle, either through phosphorylation of downstream substrates or mediating formation of high molecular weight protein complexes. Calcium signaling cascades establish important crosstalk events with signaling pathways mediated by other secondary messengers such as cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP). CDPKs play critical roles at various important physiological steps during parasite development in vertebrates and mosquitoes. They are also important for transmission of the parasite between the two hosts. Combined with the fact that CDPKs are not present in humans, they continue to be pursued as important targets for development of anti-malarial drugs.

BabA of Helicobacter pylori is the ABO blood group antigen-binding adhesin. Despite considerable diversity in the BabA sequence, it shows an extraordinary adaptation in attachment to mucosal layers. In the current study, multiple replica molecular dynamics simulations were conducted in a neutral aqueous solution to elucidate the conformational landscape of isoforms of BabA bound to Lewis b (Leb) hexasaccharide. In addition, we also investigated the underlying molecular mechanism of the BabA-glycan complexation using the MM/GBSA scheme. The conformational dynamics of Leb in the free and protein-bound states were also studied. The carbohydrate-binding site across the four isoforms was examined, and the conformational variability of several vital loops was observed. The cysteine–cysteine loops and the two diversity loops (DL1 and DL2) were identified to play an essential role in recognizing the glycan molecule. The flexible crown region of BabA was stabilized after association with Leb. The outward movement of the DL2 loop vanished upon ligand binding for the Spanish specialist strain (S381). Our study revealed that the S831 strain shows a stronger affinity to Leb than other strains due to an increased favorable intermolecular electrostatic contribution. Furthermore, we showed that the α1-2-linked fucose contributed most to the binding by forming several hydrogen bonds with key amino acids. Finally, we studied the effect of the acidic environment on the BabA-glycan complexation via constant pH MD simulations, which showed a reduction in the binding free energy in the acidic environment. Overall, our study provides a detailed understanding of the molecular mechanism of Leb recognition by four isoforms of H. pylori that may help the development of therapeutics targeted at inhibiting H. pylori adherence to the gastric mucosa.

A significant portion of total horticultural production is lost each year due to post-harvest losses. These losses vary significantly in different segments of the supply chain and these variations are primarily due to various farmlevel factors. Present study was carried out during 2019–20 to isolate the predictors of post-harvest losses in potatoes (Solanum tuberosum L.) in the purposively selected Khandoli block of Agra district, Uttar Pradesh. The total sample size was 160 included 120 farmers; 10 wholesalers; 15 retailers and 15 institutional stakeholders. The study used ordered logistic regression analysis and found that the knowledge level of the producers, training received, variety, timely labour availability, quantity harvested, and storage duration influenced the amount of losses in potatoes. The major constraints identified in the potato value chain were small operational size, absence of storage facilities, inadequate insurance coverage and poor market intelligence. The study suggested focusing more on capacity building, breeding & disseminating improved varieties; creating local-level storage infrastructure; ensuring financial risk coverage and price policy support; creating strong marketing intelligence network and farmer mobilization into farmers groups for effective post-harvest management.

Massive multiple-input multiple-output (M-MIMO) is one of the key ingredients in the upcoming 5G technology. The benefits associated with M-MIMO rely largely on the accuracy of channel state information (CSI) available at the base station (BS). The existing literature mostly employs pilot-aided schemes which require additional pilots for improving their CSI accuracy; additionally, pilot contamination degrades their performance to a large extent. In this paper, we design a Space-Alternating Generalized Expectation-Maximization (SAGE) based semi-blind estimator for pilot contaminated multi-user (MU) M-MIMO systems. It utilizes both pilot and a few data symbols for CSI estimation through two stages, namely initialization and iterative SAGE (ISAGE). We obtain an initial channel estimate with the help of a pilot-aided linear minimum mean squared error (LMMSE) estimator in the initialization stage. The acquired initial estimate from the former stage is then iteratively updated by SAGE algorithm with the joint usage of pilot and a few data symbols in ISAGE stage. The inclusion of data information in ISAGE stages' estimation process aids in simultaneous improvement of CSI accuracy and spectral efficiency (SE) of a M-MIMO system; which is unlikely for a pilot based estimation scheme. Through simulations, we show that our estimator obtains a considerable improvement over the existing pilot-aided schemes in terms of mean squared error (MSE), bit error rate (BER), SE, and energy efficiency (EE) at a nominal increase in complexity. Besides, on average, it achieves convergence in almost two iterations. We also derive modified Cramer-Rao lower bound (MCRLB) to validate the estimation efficacy of our estimator. We evaluate a closed-form expression for lower bound on UL achievable rate of MU M-MIMO systems under both perfect and imperfect CSI scenario. We also discuss the trade-off between SE and EE.

With the growth of wireless network technology-based devices, identifying the communication behaviour of wireless connectivity enabled devices, e.g. Internet of Things (IoT) devices, is one of the vital aspects, in managing and securing IoT networks. Initially, devices use frames to connect to the access point on the local area network and then, use packets of typical communication protocols through the access point to communicate over the Internet. Toward this goal, network packet and IEEE 802.11 media access control (MAC) frame analysis may assist in managing IoT networks efficiently, and allow investigation of inclusive behaviour of IoT devices. This paper presents network traffic traces data of D-Link IoT devices from packet and frame levels. Data collection experiment has been conducted in the Network Systems and Signal Processing (NSSP) laboratory at Universiti Brunei Darussalam (UBD). All the required devices, such as IoT devices, workstation, smartphone, laptop, USB Ethernet adapter, and USB WiFi adapter, have been configured accordingly, to capture and store network traffic traces of the 14 IoT devices in the laboratory. These IoT devices were from the same manufacture (D-Link) with different types, such as camera, home-hub, door-window sensor, and smart-plug.

Age of Information has been emerged as an interesting metric in real-time wireless networks that captures the freshness of information in the underlying applications. This topic is motivated by the problem in which the users of a network care about timely information defined as the age of the most recent status update a user has received. In the proposed work, we have studied this concept in the context of an industrial wireless sensor-actuator network for cyber-physical production systems. Such a network with ever-changing dynamics requires continuous updates of the system states and ongoing tasks by exchanging the time-critical, event-driven, and/or time-driven information to maintain the stability of the system, failing which may lead to shut down of the plant and other fatal consequences. Different real-time transmission scheduling algorithms manage how the channel resources are allocated each time depending on the packet arrivals to minimize the age of the information. However, unlike other real-time networks like broadcasting and sensor networks, etc. in cyber-physical systems, cyber and physical devices have different requirements to improve their quality of performance. Balancing between the performance criteria of both cyber and physical units seems to be a great challenge. In this work, the minimization of staleness of the real-time updates by minimizing the age of information and their effect on network performance have been studied extensively for this purpose. Two greedy scheduling policies have been proposed: one for the total age minimization and another one for stale age and jitter minimization. Their performances and complexities are compared with other existing scheduling algorithms. Moreover, the optimality of each of our proposed algorithms are proved analytically and claims are validated via simulation results too. Eventually, these results come to a conclusion that minimum age does not always guarantee the maximum freshness of information and satisfactory system performance at the same time.

Recently, a highly contagious novel coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has emerged, posing a global threat to public health. Identifying a potential target and developing vaccines or antiviral drugs is an urgent demand in the absence of approved therapeutic agents. The 5′-capping mechanism of eukaryotic mRNA and some viruses such as coronaviruses (CoVs) are essential for maintaining the RNA stability and protein translation in the virus. SARS-CoV-2 encodes S-adenosyl-L-methionine (SAM) dependent methyltransferase (MTase) enzyme characterized by nsp16 (2′-O-MTase) for generating the capped structure. The present study highlights the binding mechanism of nsp16 and nsp10 to identify the role of nsp10 in MTase activity. Furthermore, we investigated the conformational dynamics and energetics behind the binding of SAM to nsp16 and nsp16/nsp10 heterodimer by employing molecular dynamics simulations in conjunction with the Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) method. We observed from our simulations that the presence of nsp10 increases the favorable van der Waals and electrostatic interactions between SAM and nsp16. Thus, nsp10 acts as a stimulator for the strong binding of SAM to nsp16. The hydrophobic interactions were predominately identified for the nsp16-nsp10 interactions. Also, the stable hydrogen bonds between Ala83 (nsp16) and Tyr96 (nsp10), and between Gln87 (nsp16) and Leu45 (nsp10) play a vital role in the dimerization of nsp16 and nsp10. Besides, Computational Alanine Scanning (CAS) mutagenesis was performed, which revealed hotspot mutants, namely I40A, V104A, and R86A for the dimer association. Hence, the dimer interface of nsp16/nsp10 could also be a potential target in retarding the 2′-O-MTase activity in SARS-CoV-2. Overall, our study provides a comprehensive understanding of the dynamic and thermodynamic process of binding nsp16 and nsp10 that will contribute to the novel design of peptide inhibitors based on nsp16.

Hill agriculture is different from agriculture at plains, in respect to land type, altitude and climate, in addition to lack of infrastructure and fragmented land holding. Due to lack of employment opportunities hill farmers are leaving agriculture and migrating to plains. Lack of industries and marketing infrastructure has made it more difficult for farmers to excel in farm business. Farmers Producer Company (FPC) has emerged as a new agri-business model and is working in hilly areas it too. With an intention to find out the effectiveness of hill based FPC for enhancing livelihood wellbeing and empowering women farmers in hills the present study was conducted by selecting an women farmer based Organization, Mahila Umang Producer Company (MUPC) of a group of hill rural women. An ex-post facto research design was used. Difference in difference research design was used to calculate the actual impact of FPC. To measure the livelihood wellbeing an index were prepared by following the standard protocol. The study was conducted in Almora district of Uttarakhand from 37 randomly selected members of MUPC and 20 nonmember respondents from the same locale. The MUPC was found effective in enhancing income and empowering hill women. Joining the FPC has improved the hill women’s livelihood in terms of economic, human, and political dimensions.

Janus droplets were prepared by vortex mixing of three non-mixable liquids, i.e., olive oil, silicone oil and water, in the presence of gold nanoparticles (AuNPs) in the aqueous phase and magnetite nanoparticles (MNPs) in the olive oil. The resulting Pickering emulsions were stabilized by a red-colored AuNP layer at the olive oil/water interface and MNPs at the oil/oil interface. The core–shell droplets can be stimulated by an external magnetic field. Surprisingly, an inner rotation of the silicon droplet is observed when MNPs are fixed at the inner silicon droplet interface. This is the first example of a controlled movement of the inner parts of complex double emulsions by magnetic manipulation via interfacially confined magnetic nanoparticles.

We devise a machine learning technique to solve the general problem of inferring network links that have time delays using only time series data of the network nodal states. This task has applications in many fields, e.g., from applied physics, data science, and engineering to neuroscience and biology. Our approach is to first train a type of machine learning system known as reservoir computing to mimic the dynamics of the unknown network. We then use the trained parameters of the reservoir system output layer to deduce an estimate of the unknown network structure. Our technique, by its nature, is noninvasive but is motivated by the widely used invasive network inference method, whereby the responses to active perturbations applied to the network are observed and employed to infer network links (e.g., knocking down genes to infer gene regulatory networks). We test this technique on experimental and simulated data from delay-coupled optoelectronic oscillator networks, with both identical and heterogeneous delays along the links. We show that the technique often yields very good results, particularly if the system does not exhibit synchrony. We also find that the presence of dynamical noise can strikingly enhance the accuracy and ability of our technique, especially in networks that exhibit synchrony.

Background and Aims: Knowledge of physiological calcification in brain parenchyma is essential to avoid misinterpretation during radiological evaluation. The calcifications are commonly seen in pineal gland, falx cerebri, tentorium cerebelli and choroid plexus. Objective: To determine the incidence of physiological intracranial calcification and its relationship to age and sex in eastern Indian population. Materials and Method: A cross sectional descriptive study of CT scan brain was performed in age group between 20-80 yrs in eastern India. The study was conducted on 64 Slice MDCT PHILIPS Brilliance. Bulk of our patients was of road traffic accidents and routine CT scan study revealed these physiological calcifications and did not possess any morphological abnormality.Results: 852 patients of which 503 male and 349 female were studied and overall 1429 separate calcified areas were identified due to co-existent calcifications in most of the patients. The incidence of calcification was in pineal gland (62%), choroid plexus (53%), dura mater (26%), basal ganglia (2.8%), dentate nucleus (1.4%) and Habenular nuclei (6%). Incidence is more in male than in female. Conclusion: Physiological calcifications in some of the intracranial structures are not a very uncommon finding and it should not be confused with a pathological one.

Farmers Producer Company (FPC) has emerged as a new business model for the rural area. Like agriculture and horticulture, it is working in poultry sector too. With an intuition to find out the impact of poultry based Farmer Producer Company on upliftment of rural people, the present study was conducted by selecting Madhya Pradesh Women Poultry Producer Company Pvt. Limited (MPWPCL) founded by a team of poor rural women. An Ex-Post Facto research design was used. Difference in difference technique was utilized to estimate the actual impact of FPCs. To measure the effectiveness of MPWPCL and its impact, two indices, viz. effectiveness index and livelihood wellbeing index were prepared. Study was conducted in Orchha district of Madhya Pradesh from 37 randomly selected poultry growers' members and 15 nonmember respondents from the same locale. The MPWPCL was found highly effective with overall effectiveness score of 71.88. Joining the FPC has improved the poor rural women's human, social and political dimensions of livelihood empowerment in addition to a significant economic gain.

Surgical simulators and injury-prediction human models require a combination of representative tissue geometry and accurate tissue material properties to predict realistic tool–tissue interaction forces and injury mechanisms, respectively. While biological tissues have been individually characterized, the transition regions between tissues have received limited research attention, potentially resulting in inaccuracies within simulations. In this work, an approach to characterize the transition regions in transversely isotropic (TI) soft tissues using functionally graded material (FGM) modeling is presented. The effect of nonlinearities and multi-regime nature of the TI model on the functional grading process is discussed. The proposed approach has been implemented to characterize the transition regions in the leaflet (LL), chordae tendinae (CT) and the papillary muscle (PM) of porcine tricuspid valve (TV) and mitral valve (MV). The FGM model is informed using high resolution morphological measurements of the collagen fiber orientation and tissue composition in the transition regions, and deformation characteristics predicted by the FGM model are numerically validated to experimental data using X-ray diffraction imaging. The results indicate feasibility of using the FGM approach in modeling soft-tissue transitions and has implications in improving physical representation of tissue deformation throughout the body using a scalable version of the proposed approach.

We report on a new type of chimera state that attracts almost all initial conditions and exhibits power-law switching behavior in networks of coupled oscillators. Such switching chimeras consist of two symmetric configurations, which we refer to as subchimeras, in which one cluster is synchronized and the other is incoherent. Despite each subchimera being linearly stable, switching chimeras are extremely sensitive to noise: Arbitrarily small noise triggers and sustains persistent switching between the two symmetric subchimeras. The average switching frequency scales as a power law with the noise intensity, which is in contrast with the exponential scaling observed in typical stochastic transitions. Rigorous numerical analysis reveals that the power-law switching behavior originates from intermingled basins of attraction associated with the two subchimeras, which, in turn, are induced by chaos and symmetry in the system. The theoretical results are supported by experiments on coupled optoelectronic oscillators, which demonstrate the generality and robustness of switching chimeras.

Mammalian heart valves are soft tissue assemblies with multi-scale material properties. This is because they are constructs comprising both muscle and non-contractile extracellular matrix proteins (such as collagens and proteoglycans) and transition regions where one form of tissue structure becomes another, significantly different form. The leaflets of the mitral and tricuspid valves are connected to chordae tendinae which, in turn, bind through papillary muscles to the cardiac wall of the ventricle. The transition regions between these tissue subsets are complex and diffuse. Their material composition and mechanical properties have not been previously described with both micro and nanoscopic data recorded simultaneously, as reported here. Annotating the mechanical characteristics of these tissue transitions will be of great value in developing novel implants, improving the state of the surgical simulators and advancing robot-assisted surgery. We present here developments in multi-scale methodology that produce data that can relate mechanical properties to molecular structure using scanning X-ray diffraction. We correlate these data to corresponding tissue level (macro and microscopic) stress and strain, with particular emphasis on the transition regions and present analyses to indicate points of possible failure in these tissues.

There is a growing optimism that the farmers' organizations can act as a potential driving force for enhancing farmers' income. India has witnessed a positive growth of producer organizations in terms of types of organization, numbers and members. The Producer Company is a special case of producer organization that is registered under Section IXA of the Companies Act, 1956. A need was felt at that time to have an independent farmers’ organization which enables incorporation of producers into such an institution like the companies which will be controlled by them, having welfare and business outlook at a time while not compromising the sustainability issues. That creates the milieu for the genesis of Farmers’ Producer Company (FPC) in India. The FPCs are fundamentally farmer-owned and farmer-governed micro-enterprises which can be considered as hybrids between cooperative societies and private companies. The way of participation, membership and organization is similar to that of a cooperative, while the incorporation into corporate law allows greater flexibility and professionalism in their business actions. Till date 1048 FPCs are registered in India. In this article attempt has been made to review the issues of FPC, current status and future prospects. Forecasting the growth of FPC has been done up to the year 2020 utilizing Grey Model. Emphasis has been given to critically analyse the status, prospects and potentials with future outlook of 2020 concluding with strategies and policy needs.

The never-ending quest to improve the security of digital information combined with recent improvements in hardware technology has caused the field of random number generation to undergo a fundamental shift from relying solely on pseudo-random algorithms to employing optical entropy sources. Despite these significant advances on the hardware side, commonly used statistical measures and evaluation practices remain ill-suited to understand or quantify the optical entropy that underlies physical random number generation. We review the state of the art in the evaluation of optical random number generation and recommend a new paradigm: quantifying entropy generation and understanding the physical limits of the optical sources of randomness. In order to do this, we advocate for the separation of the physical entropy source from deterministic post-processing in the evaluation of random number generators and for the explicit consideration of the impact of the measurement and digitization process on the rate of entropy production. We present the Cohen-Procaccia estimate of the entropy rate h(𝜖,τ) as one way to do this. In order to provide an illustration of our recommendations, we apply the Cohen-Procaccia estimate as well as the entropy estimates from the new NIST draft standards for physical random number generators to evaluate and compare three common optical entropy sources: single photon time-of-arrival detection, chaotic lasers, and amplified spontaneous emission.

In this paper, we address the issue of maximizing the lifetime of a static wireless ad-hoc network wherein the nodes are battery powered and have limited energy. In such scenarios, routing the traffic along shortest paths will lead to over-use of some nodes leading to premature network partition and an eventual end of communication. Network Coding is a promising technique that has been used, of late, by researchers for throughput improvement. We propose an algorithm that exploits network coding to route a set of unicast traffic demands, the objective being network lifetime maximization. The routing algorithm uses a link metric that takes care of the communication power consumption, the residual energy at the nodes and also the potential coding opportunities available at the node. Simulation results show that this algorithm enhances the network lifetime compared to the existing algorithms that do not employ network coding.

The Drop when seen (DWS) technique, an online network coding strategy is capable of making a broadcast transmission over erasure channels more robust. This throughput optimal strategy reduces the expected sender queue length. One major issue with the DWS technique is the high computational complexity. In this paper, we present a randomized version of the DWS technique (rDWS), where the unique strength of the DWS, which is the sender’s ability to drop a packet even before its decoding at receivers, is not compromised. Computational complexity of the algorithms is reduced with rDWS, but the encoding is not throughput optimal here. So, we perform a throughput efficiency analysis of it. Exact probabilistic analysis of innovativeness of a coefficient is found to be difficult. Hence, we carry out two individual analyses, maximum entropy analysis, average understanding analysis, and obtain a lower bound on the innovativeness probability of a coefficient. Based on these findings, innovativeness probability of a coded combination is analyzed. We evaluate the performance of our proposed scheme in terms of dropping and decoding statistics through simulation. Our analysis, supported by plots, reveals some interesting facts about innovativeness and shows that rDWS technique achieves near-optimal performance for a finite field of sufficient size.