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Climate change has a considerable influence on agricultural output, raising farmers’ production risk. Nevertheless, the risk can be mitigated by selecting stable genotypes. In countries such as India, where significant proportions of farmers are smallholders or operate on marginal land, the minimization of risk is of paramount importance. Existing methods of stability measures often result in low-yielding varieties. Consequently, there is a need to develop more effective stability strategy to solve this problem without reducing yield. In light of the preceding, the Rank Based Stability Index (RSI) has been proposed for choosing genotypes based on the rank of interaction residuals to mitigate the influence of climatic changes without compromising yield. Through statistical analyses, the RSI approach demonstrates its ability to discern stable genotypes resilient to environmental fluctuations. By evaluating genotype performance across multiple environments and seasons, RSI identifies cultivars with consistent yield performance, thus offering a valuable tool for enhancing crop resilience and ensuring food security. The effectiveness of the proposed RSI approach for selecting stable genotypes from groundnut (Arachis hypogaea L.) data has been notably demonstrated in comparison to other methods. RSI emerges as a promising methodology for genotype selection in groundnut, offering a robust framework for mitigating the influence of climatic changes on crop yields.

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ABSTRACTThe main purpose of this work is to design a robust adaptive backstepping (RABS) control strategy for a pediatric exoskeleton system during passive-assist gait rehabilitation. The nonlinear dynamics of the exoskeleton system have ill-effects of uncertain parameters and external interferences. In this work, the designed robust control strategy is applied on the exoskeleton to assist children of 08–12 years, 25–40 kg weight, and 115–125 cm height. The dynamic model of the coupled human-exoskeleton system is established using the Euler–Lagrange principle. An appropriate Lyapunov function is selected to prove the uniform boundedness of the control signals. The “explosion of terms” is avoided by establishing a virtual control law without the dynamical system parameters. A Microsoft Kinect-LabVIEW experiment is carried out to estimate the desired gait trajectory. The robustness of the proposed control is validated by varying the limb segment masses and inducing the periodic external disturbances. The proposed control strategy is compared with the decentralized modified simple adaptive-PD (DMSA-PD) control strategy. From simulation results and performance improvement index, it is observed that RABS control outperforms the contrast control (DMSA-PD) to track the desired gait during passive-assist rehabilitation under the effect of model uncertainties and external disturbances.

Summary: The current abundance of immunotherapy clinical trials presents an opportunity to learn about the underlying mechanisms and pharmacodynamic effects of novel drugs on the human immune system. Here, we present a protocol to study how these immune responses impact clinical outcomes using large-scale high-throughput immune profiling of clinical cohorts. We describe the Human Immune Profiling Pipeline, which comprises an end-to-end solution from flow cytometry results to computational approaches and unsupervised patient clustering based on lymphocyte landscape.For complete details on the use and execution of this protocol, please refer to Lyudovyk et al. (2022).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Initial evaluations of the System of Rice Intensification in India and elsewhere focused mainly on its impacts on yield and income, and usually covered just one or two seasons. Researchers at the ICAR-Indian Institute of Rice Research have conducted a more comprehensive evaluation of SRI methods over six years (six wet and six dry seasons), comparing them with three alternatives: modified, partially mechanized SRI (MSRI) to reduce labor requirements; direct-seeded rice (DSR) as an alternative method for growing rice; and conventional transplanting of rice with flooding of fields (CTF). Grain yield with SRI methods was found to be about 50% higher than with CTF (6.35 t ha−1 vs. 4.27 t ha−1), while the MSRI yield was essentially the same (6.34 t ha−1), 16% more than with DSR (5.45 t ha−1). Water productivity with SRI methods was 5.32–6.85 kg ha-mm−1, followed by 4.14–5.72 kg ha-mm−1 for MSRI, 5.06–5.11 kg ha-mm−1 for DSR, and 3.52–4.56 kg ha-mm−1 for CTF. In comparison with CTF, SRI methods significantly enhanced soil microbial populations over time: bacteria by 12%, fungi by 8%, and actinomycetes by 20%. Biological activity in the rhizosphere was also higher as indicated by 8.5% greater dehydrogenase and 16% more FDA enzymes in soil under SRI management. Similarly, an indicator of soil organic matter, glucosidase activity, was 78% higher compared to CTF. SRI enhanced the relative abundance of beneficial microbial-feeding nematodes by 7.5% compared to CTF, while that of plant-pathogenic nematodes was 7.5% lower under SRI. Relative to conventional methods, SRI management reduced GHG emissions by 21%, while DSR reduced them by 23%, and MSRI by 13%, compared to standard rice-growing practice. Economic analysis showed both gross and net economic returns to be higher with SRI than with the other management systems evaluated. While the six-year study documented many advantages of SRI crop management, it also showed that MSRI is a promising adaptation that provides similar benefits but with lower labor requirements.

Carrot (Daucus carota L.) is a highly consumed vegetable rich in carotenoids, known for their potent antioxidant, anti-inflammatory, and immune-protecting properties. While genetic and molecular studies have largely focused on wild and Western carrot cultivars (cvs), little is known about the evolutionary interactions between closely related Eastern and Western cvs. In this study, we conducted comparative transcriptome profiling of root tissues from Eastern (UHSBC-23-1) and Western (UHSBC-100) carrot cv. to better understand differentially expressed genes (DEGs) associated with storage root development and vascular cambium (VC) tissue patterning. Through reference-guided TopHat mapping, we achieved an average mapping rate of 73.87% and identified a total of 3544 DEGs (p < 0.05). Functional annotation and gene ontology classification revealed 97 functional categories, including 33 biological processes, 19 cellular components, 45 metabolic processes, and 26 KEGG pathways. Notably, Eastern cv. exhibited enrichment in cell wall, plant-pathogen interaction, and signal transduction terms, while Western cv. showed dominance in photosynthesis, metabolic process, and carbon metabolism terms. Moreover, constructed gene regulatory network (GRN) for both cvs. obtained orthologs with 1222 VC-responsive genes of Arabidopsis thaliana. In Western cv, GRN revealed VC-responsive gene clusters primarily associated with photosynthetic processes and carbon metabolism. In contrast, Eastern cv. exhibited a higher number of stress-responsive genes, and transcription factors (e.g., MYB15, WRKY46, AP2/ERF TF connected via signaling pathways with NAC036) were identified as master regulators of xylem vessel differentiation and secondary cell wall thickening. By elucidating the comparative transcriptome profiles of Eastern and Western cvs. for the first time, our study provides valuable insights into the differentially expressed genes involved in root development and VC tissue patterning. The identification of key regulatory genes and their roles in these processes represents a significant advancement in our understanding of the evolutionary relations and molecular mechanisms underlying secondary growth of carrot and regulation by vascular cambium.

Pearl millet (Pennisetum glaucum L.), an important source of iron (Fe) and zinc (Zn) for millions of families in dryland tropics, helps in eradicating micronutrient malnutrition. The crop is rich in Fe and Zn, therefore, identification of the key genes operating the mineral pathways is an important step to accelerate the development of biofortified cultivars. In a first-of-its-kind experiment, leaf and root samples of a pearl millet inbred ICMB 1505 were exposed to combinations of Fe and Zn stress conditions using the hydroponics method, and a whole-genome transcriptome assay was carried out to characterize the differentially expressed genes (DEGs) and pathways. A total of 37,093 DEGs under different combinations of stress conditions were identified, of which, 7,023 and 9,996 DEGs were reported in the leaf and root stress treatments, respectively. Among the 10,194 unique DEGs, 8,605 were annotated to cellular, biological, and molecular functions and 458 DEGs were assigned to 39 pathways. The results revealed the expression of major genes related to the mugineic acid pathway, phytohormones, chlorophyll biosynthesis, photosynthesis, and carbohydrate metabolism during Fe and Zn stress. The cross-talks between the Fe and Zn provided information on their dual and opposite regulation of key uptake and transporter genes under Fe and Zn deficiency. SNP haplotypes in rice, maize, sorghum, and foxtail millet as well as in Arabidopsis using pearl millet Fe and Zn responsive genes could be used for designing the markers in staple crops. Our results will assist in developing Fe and Zn-efficient pearl millet varieties in biofortification breeding programs and precision delivery mechanisms to ameliorate malnutrition in South Asia and Sub-Saharan Africa.

Background: crub typhus is caused by Orientia tsutsugamushi (rickettsial disease) commonly transmitted by the bite of larval chiggers of trombiculid mites. It has been one of the important causes of febrile illness, especially in south India. The clinical diagnosis is difficult owing to the non-specific presentation. We in the current study tried to evaluate the serodiagnosis of scrub typhus with the Weil Felix test and IgM ELISA. Methods: This study was conducted in the Department of Microbiology, Prathima Institute of Medical Sciences, Naganoor, Karimnagar. All the sera samples were subjected to the Weil Felix test using Proteus OX2, OX19, OX-K strain agglutination test, and subsequently, Scrub typhus IgM ELISA test. Results: All the samples were subjected to the Weil Felix test n=4(6.06%) were positive for scrub typhus (OXK antigen) n=11(16.67%) were positive for the spotted group of fever (OX2 antigen) and n=10 (15.15%) were positive of typhus group (OX19 antigen). N=5 sera samples were positive for more than one type of antigens. All the n=66 serum samples were subjected to IgM ELISA for scrub typhus. Out of n=66, only two serum samples (3.03%) were positive by IgM ELISA. Conclusion: Scrub typhus is emerging as an important public health issue. It is one of the important causes of acute febrile illness. Although it is difficult to distinguish scrub typhus based on the clinical symptoms alone a simple test such as Weil Felix was found to be promising in the diagnosis of scrub typhus. ELISA IgM test may be performed additionally in laboratories with adequate facilities. Hence for clinicians, any case with a fever of unknown origin should arouse suspicion of scrub typhus.

Ginger (Zingiber officinale Rosc.) is a commercial crop grown for its aromatic rhizomes which is used both as a spice and medicine. Being a root crop and owing to its physical structure, ginger rhizomes contain heavy soil load which makes washing as an important and prime post-harvest operation. Manual washing of ginger is a laborious and time consuming process. An experiment was conducted at the ICAR-Indian Agricultural Research Institute, New Delhi during 2020 with an objective to develop a continuous rotary drum type battery operated ginger washer and to evaluate its performance.The machine consists of the frame, feeding and discharge chutes, rotary drum with internal flights, pressure pump and nozzle assembly, battery and a drive unit. The developed washer was evaluated at different feed rate and residence time to appraise the washing efficiency, microbial washing efficiency, bruise index and colour of washed ginger. Increase in feed rate significantly reduced the washing and microbial efficiencies but increased mechanical damage. Washing and microbial efficiencies increased with increase in residence time.Significant difference in the colour was found between washed and unwashed ginger.The best set of conditions under which the washer could be operated was 150 kg/h and 25 sec, at which the machine was found to have mechanical washing efficiency of 92.48%, microbial washing efficiency of 93.18% and 4.54% bruise index. Besides eliminating drudgery of washing operation, the developed washer was found to save time, water and operating cost as compared to manual washing.

Over the last decade, lower limb exoskeletons have seen significant development, with a particular focus on improving the interaction between the subject and the exoskeleton. This has been achieved by implementing advanced control strategies that enable the safe and efficient use of the exoskeleton. In this work, the control strategies for lower limb exoskeletons are divided into upper-level control (supervisory and high-level control) and lower-level control (the servo layer). Before discussing these control strategies, a brief introduction to lower limb exoskeletons and their control schemes is provided. The control hierarchy for lower limb exoskeletons is then systematically reviewed along with an overview of the techniques used. A Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement is used to highlight the systematic process of identifying relevant articles with inclusion and exclusion criteria. The details of supervisory control, high-level control, and servo control strategies are presented by citing relevant state-of-the-art studies, particularly from the past five years. The targeted lower limb joint, training mode, and development stage for different control strategies are highlighted in a tabulated form to articulate the overall hierarchy level. Finally, the potential opportunities and limitations of subject-cooperative control are discussed. Overall, this work aims to provide an in-depth understanding of the control strategies used in lower limb exoskeletons, focusing on subject cooperation. This knowledge can be used to improve the safety and efficacy of lower limb exoskeletons, ultimately benefiting individuals with mobility impairments.

Global climate change is anticipated to have a profound impact on drought occurrences, leading to detrimental consequences for the environment, socioeconomic relations, and ecosystem services. In order to evaluate the extent of drought impact, a comprehensive study was conducted in the Hyderabad–Karnataka region, India. Precipitation data from 31 stations spanning a 50-year period (1967–2017) were analyzed using the standardized precipitation index (SPI) based on gamma distribution. The findings reveal that approximately 15% of the assessed years of experienced drought conditions, with a range of influence between 41% and 76% under SPI_3, and between 43% and 72% under SPI_6. Examining the timescale magnitude frequency provided insights into variations in the severity of drought events across different locations and timescales. Notably, the Ballari (−8.77), Chitapur (−8.22), and Aland (−7.40) regions exhibited the most significant magnitudes of drought events for SPI_3 with a 5-year return period. The heightened risk of recurrent droughts in the study area emphasizes the necessity of integrating SPI in decision-making processes, as such integration can markedly contribute to the development of reliable and sustainable long-term water management strategies at regional and national levels.

Organic agriculture (OA) is a continuously growing global concept that emphasizes the use of sustainable and environmentally-friendly practices. By adopting OA, it is possible to improve ecosystems services, increase biodiversity, decrease environmental pollution, reduce carbon footprints and mitigate greenhouse gas emissions, generating food that is free from harmful residues of agrochemicals, thereby enhancing food safety and security. This study provides a comprehensive review of the latest insights on the global utilization of land resources in OA, focusing particularly on some EU countries that experienced a notable and rapid progress in organic farming during the past two decades. With negligible 1.6% (75 Mha) of global cropland is currently dedicated to OA, there is ample opportunity to expand the adoption of OA and realize its multi-beneficial potential for farmers (by premium prices), and consumers (by healthier and nutritious food). The importance of OA has been recognized by the most recent EU agro-environmental policies and green strategies, with an ambitious goal to have at least 25% of agroecosystems under organic management by 2030. Despite numerous financial supports and a multifold increase in OA land area, many member states are unlikely to achieve this goal, including Croatia, which currently has a share of only 8% (~109,000 ha) of lands in OA. Furthermore, converting conventional land to organic farming has not always led to an increase in value-added final OA products. EU policies related to OA have been focused on the area of land cultivated organically, rather than overall production performance, and financial subsidies have been essential to achieve this policy. Therefore, some of critical obstacles and challenges for OA under rising pressures due to global climate change, public health and geopolitical crises need to be managed by specifically designed policies and regulations, which would contribute to more sustainable OA, i.e., food safety and security.

Rice (Oryza sativa L.) is an important source of nutrition for the world’s burgeoning population that often faces yield loss due to infestation by the brown planthopper (BPH, Nilaparvata lugens (Stål)). The development of rice cultivars with BPH resistance is one of the crucial precedences in rice breeding programs. Recent progress in high-throughput SNP-based genotyping technology has made it possible to develop markers linked to the BPH more quickly than ever before. With this view, a genome-wide association study was undertaken for deriving marker-trait associations with BPH damage scores and SNPs from genotyping-by-sequencing data of 391 multi-parent advanced generation inter-cross (MAGIC) lines. A total of 23 significant SNPs involved in stress resistance pathways were selected from a general linear model along with 31 SNPs reported from a FarmCPU model in previous studies. Of these 54 SNPs, 20 were selected in such a way to cover 13 stress-related genes. Kompetitive allele-specific PCR (KASP) assays were designed for the 20 selected SNPs and were subsequently used in validating the genotypes that were identified, six SNPs, viz, snpOS00912, snpOS00915, snpOS00922, snpOS00923, snpOS00927, and snpOS00929 as efficient in distinguishing the genotypes into BPH-resistant and susceptible clusters. Bph17 and Bph32 genes that are highly effective against the biotype 4 of the BPH have been validated by gene specific SNPs with favorable alleles in M201, M272, M344, RathuHeenati, and RathuHeenati accession. These identified genotypes could be useful as donors for transferring BPH resistance into popular varieties with marker-assisted selection using these diagnostic SNPs. The resistant lines and the significant SNPs unearthed from our study can be useful in developing BPH-resistant varieties after validating them in biparental populations with the potential usefulness of SNPs as causal markers.

Abstract Corticosteroids, anti-CD20 agents, immunotherapies, and cytotoxic chemotherapy are commonly used in the treatment of patients with cancer. It is unclear how these agents affect patients with cancer who are infected with SARS-CoV-2. We retrospectively investigated associations between SARS-CoV-2-associated respiratory failure or death with receipt of the aforementioned medications and with pre-COVID-19 neutropenia. The study included all cancer patients diagnosed with SARS-CoV-2 at Memorial Sloan Kettering Cancer Center until June 2, 2020 (N = 820). We controlled for cancer-related characteristics known to predispose to worse COVID-19 as well as level of respiratory support during corticosteroid administration. Corticosteroid administration was associated with worse outcomes prior to use of supplemental oxygen; no statistically significant difference was observed in sicker cohorts. In patients with metastatic thoracic cancer, 9 of 25 (36%) and 10 of 31 (32%) had respiratory failure or death among those who did and did not receive immunotherapy, respectively. Seven of 23 (30%) and 52 of 187 (28%) patients with hematologic cancer had respiratory failure or death among those who did and did not receive anti-CD20 therapy, respectively. Chemotherapy itself was not associated with worse outcomes, but pre-COVID-19 neutropenia was associated with worse COVID-19 course. Relative prevalence of chemotherapy-associated neutropenia in previous studies may account for different conclusions regarding the risks of chemotherapy in patients with COVID-19. In the absence of prospective studies and evidence-based guidelines, our data may aid providers looking to assess the risks and benefits of these agents in caring for cancer patients in the COVID-19 era.

The System of Rice Intensification (SRI) developed in Madagascar has spread to many parts of the world, including India. This study assessing insect pest prevalence on rice grown with SRI vs. conventional methods at multiple locations in India was prompted by reports that SRI-managed rice plants are healthier and more resistant to pest and disease damage. Field experiments were conducted under the All-India Coordinated Rice Improvement Project over a 5-year period. The split-plot design assessed both cultivation methods and different cultivars, hybrids and improved varieties. Across the eight locations, SRI methods of cultivation showed a lower incidence of stem borer, planthoppers, and gall midge compared to conventional methods. Whorl maggots and thrips, on the other hand, were observed to be higher. Grain yield was significantly higher with SRI management across all locations. Higher ash, cellulose, hemicellulose, as well as silica content in rice plants under SRI management could explain at least in part the SRI plants’ resistance to pest damage. Analysis of guild composition revealed that in SRI plots, there were more natural enemies (insect predators and parasitoids) present and fewer crop pests (phytophages). A meta-analysis that considered other published research on this subject revealed a lower incidence of dead hearts, white ear-heads, and leaf folders, along with higher grain yield, in SRI plots.

Abstract To improve grain yield under direct seeded and aerobic conditions, weed competitive ability of a rice genotype is a key desirable trait. Hence, understanding and dissecting weed competitive associated traits at both morphological and molecular level is important in developing weed competitive varieties. In the present investigation, the QTLs associated with weed competitive traits were identified in BC1F2:3 population derived from weed competitive accession of O. glaberrima (IRGC105187) and O. sativa cultivar IR64. The mapping population consisting of 144 segregating lines were phenotyped for 33 weed competitive associated traits under direct seeded condition. Genetic analysis of weed competitive traits carried out in BC1F2:3 population showed significant variation for the weed competitive traits and predominance of additive gene action. The population was genotyped with 81 genome wide SSR markers and a linkage map covering 1423 cM was constructed. Composite interval mapping analysis identified 72 QTLs linked to 33 weed competitive traits which were spread on the 11 chromosomes. Among 72 QTLs, 59 were found to be major QTLs (> 10% PVE). Of the 59 major QTLs, 38 had favourable allele contributed from the O. glaberrima parent. We also observed nine QTL hotspots for weed competitive traits (qWCA2a, qWCA2b, qWCA2c, qWCA3, qWCA5, qWCA7, qWCA8, qWCA9, and qWCA10) wherein several QTLs co-localised. Our study demonstrates O. glaberrima species as potential source for improvement for weed competitive traits in rice and identified QTLs hotspots associated with weed competitive traits.

Objectives. This is a diagnostic test research study to evaluate the various existing methods of thyroid examination and their comparison with the novel modified Rose method. It also aims to measure inter-examiner variation in clinical findings based on the level of education and training, as compared to ultrasonography. Methodology. This cross-sectional study was conducted at a tertiary care hospital with eighty-three patients presenting to surgery OPD with neck swelling. Each patient was examined by one trained Junior Resident and a Surgery Consultant with all the four methods and with ultrasonography. Data was analysed by Stata-14, agreement between the two categorical variables was assessed by Kappa. In case of continuous variable agreement was assessed by Intra class correlation and Bland-Altman plot. Results. Modified Rose method by the consultant has the highest sensitivity (98%) and diagnostic odds (210) as compared to others but its specificity ranges from 46.7- 91.1% to diagnose retro-sternal extension of a goiter. It has 93.98% agreement for identification of nodules. It has a high specificity (Consultant -100%, Resident – 95.5%) with relatively lower sensitivity (Consultant -94%, Resident – 86.8%) to diagnose solitary thyroid nodule (STN) but the sensitivity and specificity for diagnosing a multinodular goitre (MNG) was high. However, the highest sensitivity to diagnose STN was highest with Crile’s method, but specificity was low. Lahey’s method was a better clinical method to palpate lymph nodes compared to the other three. Conclusion. Examination in modified Rose’s position is a better method of clinical examination of thyroid especially in patients with occult substernal extension. Lahey’s method is a better method to examine cervical lymph nodes.

Pneumatic artificial muscles (PAMs) are soft and flexible linear pneumatic actuators which produce human muscle like actuation. Due to these properties, the muscle actuators have an adaptable compliance for various robotic platforms as well as medical applications. While a variety of possible actuation schemes are present, there is still a need for the development of a soft actuator that is very light-weight, compact, and flexible with high power-to-weight ratio. To achieve this, the development of the PAM actuators has become an interesting topic for many researchers. In this review, the development of the different kinds of PAM available to date are presented along with manufacturing process and the operating principle. The various force models for artificial muscle presented in the literature are broadly reviewed with the constraints. Furthermore, the applications of PAM are included and classified based on the fields of biorobotics, medicine, and industry, along with advanced medical instrumentation. Finally, the needful improvements in terms of the dynamics of the muscle are discussed for the precise control of the PAMs as per the requirements for the applications. This review will be helpful for researchers working in the field of robotics and for designers to develop new type of artificial muscle depending on the applications.

The demonstrations on improved rice production technology were organized in the Wanaparthy, Nagarkurnool, Yadadri Bhuvanagiri, and Rangareddy districts of Telangana state of India. These demonstrations were organized under the Scheduled Caste Sub Plan of the Indian Institute of Rice Research during the wet season of 2021. The biofortified varieties assume great significance to achieve nutrition security. Hence, the zinc biofortified rice variety, DRR Dhan 48 was demonstrated on the 142 farmer fields and the economic impact of these demonstrations was assessed with the ‘difference in difference’ approach. The results revealed that the production of rice under demonstration plots was more profitable with a higher benefit-to-cost ratio (B:C; 1.9) compared to that of the control plots (1.4). The independent two-sample t-test revealed that the productivity at the control plots was not statistically different from that of the demonstrations plots (p = 0.112) before the project was implemented, however, with the intervention in the form of the demonstration of improved rice production technology, the productivity differed significantly (p = 0.000) for the control and the demonstration plots for the intervention year. The results of the difference in differences estimator revealed that there was a positive impact of demonstrations on the yield of the beneficiaries. The mean productivity of demonstration plots and control plots were 5.52 t/ha and 4.5 t/ha, respectively. The farmers had an additional yield advantage of 22.6% over the control plots. The results indicated that the adoption of an improved package of practices would enable harnessing higher productivity levels and bridging the yield gaps in similar agroecosystems. Also, the results suggest the practical significance of the popularization of biofortified rice varieties for food and nutritional security.

Via national lockdowns, the COVID-19 pandemic disrupted the production and distribution of foodstuffs worldwide, including rice (Oryza sativa L.) production, affecting the prices in India’s agroecosystems and markets. The present study was performed to assess the impact of the COVID-19 national lockdown on rice prices in India, and to develop statistical machine learning models to forecast price changes under similar crisis scenarios. To estimate the rice prices under COVID-19, the general time series models, such as the autoregressive integrated moving average (ARIMA) model, the artificial neural network (ANN) model, and the extreme learning machine (ELM) model, were applied. The results obtained using the ARIMA intervention model revealed that during the COVID-19 lockdown in India, rice prices increased by INR 0.92/kg. In addition, the ELM intervention model was faster, with less computation time, and provided better results vs other models because it detects the nonlinear pattern in time series data, along with the intervention variable, which was considered an exogenous variable. The use of forecasting models can be a useful tool in supporting decision makers, especially under unpredictable crises. The study results are of great importance for the national agri-food sector, as they can bolster authorities and policymakers in planning and designing more sustainable interventions in the food market during (inter)national crisis situations.

Integrated management of rice–maize systems is an emerging challenge in southern India due to improper rice residues and tillage management in maize crops. Conservation agriculture (CA) practices such as a reduced tillage and maintaining stubble mulch may hold the potential to increase yields, reduce crop establishment costs and increase farm incomes. A five-year trial was performed to study the effect of different CA and establishment methods in rice on system productivity, profitability, and soil carbon status in a rice–maize system. In the rainy season, the trial consisted of two main treatments: (i) normal manual transplanting and (ii) direct-wet seeding, and three sub-main treatments at different sowing dates with fifteen day intervals. In addition, in the winter season, two tillage treatments (conventional and minimum tillage) were imposed over the rainy season treatments. Both rice and maize were grown under irrigated conditions. The results showed that sowing times at 15 day intervals did not impact the yield significantly. Transplanted rice obtained a significantly higher grain yield during the first four years, but in the last year, the yield was similar in both of the establishment methods. In the winter season, conventional tilled maize recorded a higher cob yield than under the minimum tilled treatment, except for the last year, where both the tillage treatment effects were the same. System productivity of CA-based minimum tilled rice–maize was inferior during the first three years but was superior to the conventionally tilled method in the fourth and fifth year. Pooled analysis revealed that the conventionally tilled rice–maize system resulted in a similar system productivity as that of the CA during the study period. The cost–benefit analysis revealed that transplanted rice and conventionally tilled maize fetched higher net returns of INR 111,074 and INR 101,658/ha, respectively, over the direct-wet seeded rice and CA. In addition, the 15 July rice sown followed by the maize system led to an increase in irrigation water productivity by 15.7%, and the total water (irrigation + rainfall) productivity by 27.1% in the maize crop compared with the 30 July sown system. The CA-based rice–maize system resulted in a significantly higher very labile (0.194%) and labile (0.196%) carbon concentration at a 0–5 cm depth of soil compared to those under the conventional system. Thus, CA can be recommended for southern India and similar agro-ecological tropic and sub-tropic conditions. This system can be followed with appropriate location-specific modification in South-Asian countries, where crop yields and soil health are declining as a result of continuous cereal–cereal crop rotation.

Polished rice is one of the commonly consumed staple foods across the world. However, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising recombinant inbred lines (RILs) for grain Zn and single plant yield, 190 RILs developed from PR116 and Ranbir Basmati were evaluated in two environments (E1 and E2). A subset of 44 contrasting RILs for grain Zn was screened in another two environments (E3 and E4). Phenotypic data was collected for 10 traits, viz., days to 50% flowering, plant height, panicle length, number of tillers, single plant yield (SPY), test weight, Fe and Zn in brown (IBR, ZBR), and polished rice (IPR, ZPR). Stepwise regression analysis of trait data in 190 RILs and a subset of 44 RILs revealed the interdependence of ZPR, ZBR, IPR, and IBR and the negative association of grain Zn with single plant yield. Based on the additive main effect and multiplicative interaction (AMMI) and genotype and genotype × environment interaction (GGE) analyses of the subset of 44 RILs across four environments (E1–E4), six promising RILs were identified for ZPR with >28 ppm. Mapping of 190 RILs with 102 simple sequence repeats (SSRs) resulted in 13 QTLs for best linear unbiased estimates (BLUEs) of traits including advantage over check (AOC). Using genotype-based sequencing (GBS), the subset of 44 RILs was mapped with 1035 single-nucleotide polymorphisms (SNPs) and 21 QTLs were identified. More than 100 epistatic interactions were observed. A major QTL qZPR.1.1 (PV 37.84%) and another QTL qZPR.11.1 (PV 15.47%) were identified for grain Zn in polished rice. A common major QTL (qZBR.2.1 and qZPR.2.1) was also identified on chromosome 2 for grain Zn content across SSR and SNP maps. Two potential candidate genes related to transporters were identified based on network analyses in the genomic regions of QTL < 3 Mb. The RILs identified for grain Zn and SPY were nominated for national evaluation as under rice biofortification, and two QTLs identified based on BLUEs could be used in the rice biofortification breeding programs.

The design of an accurate control scheme for a lower limb exoskeleton system has few challenges due to the uncertain dynamics and the unintended subject’s reflexes during gait rehabilitation. In this work, a robust linear quadratic regulator- (LQR-) based neural-fuzzy (NF) control scheme is proposed to address the effect of payload uncertainties and external disturbances during passive-assist gait training. Initially, the Euler-Lagrange principle-based nonlinear dynamic relations are established for the coupled system. The input-output feedback linearization approach is used to transform the nonlinear relations into a linearized state-space form. The architecture of the adaptive neuro-fuzzy inference system (ANFIS) and used membership function are briefly explained. While varying mass parameters up to 20%, three robust neural-fuzzy datasets are formulated offline with the joint error vector and LQR control input. Thereafter, to deal with external interferences, an error dynamics with a disturbance estimator is presented using an online adaptation of the firing strength matrix. The Lyapunov theory is carried out to ensure the asymptotic stability of the coupled human-exoskeleton system in view of the proposed controller. The gait tracking results for the proposed control scheme (RLQR-NF) are presented and compared with the exponential reaching law-based sliding mode (ERL-SM) controller. Furthermore, to investigate the robustness of the proposed control over LQR control, a comparative performance analysis is presented for two cases of parametric uncertainties and external disturbances. The first case considers the 20% raise in mass values with a trigonometric form of disturbances, and the second case includes the effect of the 30% increment in mass values with a random form of disturbances. The simulation runs have shown the promising gait tracking aspects of the designed controller for passive-assist gait training.

Background. Informal (unqualified) health care providers are an important source of medical care for persons with presumptive TB (PPTB) in India. A project (titled RIPEND) was implemented to engage informal providers for the identification of PPTBs and TB patients in 4 districts of Telangana State, India, during October 2018-December 2019 project period. Engagement involved sensitizing the informal providers about TB, providing them financial incentives to identify PPTBs, and linking these PPTBs to diagnostic and treatment services provided by the Government of India’s National TB Elimination Programme. Objectives. To describe (a) the characteristics of the informal providers, along with their self-reported practices on TB diagnosis, treatment, and challenges encountered by the RIPEND project staff in engaging them in the project and (b) the outputs and outcomes of this engagement. Methods. We used a combination of one-on-one interviews with informal providers, group interviews with RIPEND project staff, and secondary analysis of data available within the project’s recording and reporting systems. Results. A total of 555 informal providers were actively engaged under the project. The majority (87%) had a nonmedicine-related graduate degree and had been providing medical care for more than 10 years. Most (95%) were aware that a cough for 2 weeks or more is a symptom of pulmonary TB and that such patients should be referred for sputum-smear microscopy at a government health facility. Challenges in engaging the informal providers included motivating them to participate in the study, suboptimal mobile usage for referral services, and delays in providing financial incentives to them for referring PPTBs. During the project period (October 2018-December 2019), 8342 PPTBs were identified of which 1003 TB patients were detected and linked to TB treatment services. Conclusion. This project showed that engaging informal providers is feasible and that a large number of PPTB and TB patients can be identified through this effort. The Government of India should consider engaging informal providers for the early diagnosis of TB to reduce the missing TB cases in the country.

An inadequate supply of amino acids leads to accumulation of uncharged tRNAs, which can bind and activate GCN2 kinase to reduce translation. Here, we show that glutamine-specific tRNAs selectively become uncharged when extracellular amino acid availability is compromised. In contrast, all other tRNAs retain charging of their cognate amino acids in a manner that is dependent upon intact lysosomal function. In addition to GCN2 activation and reduced total translation, the reduced charging of tRNAGln in amino-acid-deprived cells also leads to specific depletion of proteins containing polyglutamine tracts including core-binding factor α1, mediator subunit 12, transcriptional coactivator CBP and TATA-box binding protein. Treating amino-acid-deprived cells with exogenous glutamine or glutaminase inhibitors restores tRNAGln charging and the levels of polyglutamine-containing proteins. Together, these results demonstrate that the activation of GCN2 and the translation of polyglutamine-encoding transcripts serve as key sensors of glutamine availability in mammalian cells.

Salinization of soils and freshwater resources by natural processes and/or human activities has become an increasing issue that affects environmental services and socioeconomic relations. In addition, salinization jeopardizes agroecosystems, inducing salt stress in most cultivated plants (nutrient deficiency, pH and oxidative stress, biomass reduction), and directly affects the quality and quantity of food production. Depending on the type of salt/stress (alkaline or pH-neutral), specific approaches and solutions should be applied to ameliorate the situation on-site. Various agro-hydrotechnical (soil and water conservation, reduced tillage, mulching, rainwater harvesting, irrigation and drainage, control of seawater intrusion), biological (agroforestry, multi-cropping, cultivation of salt-resistant species, bacterial inoculation, promotion of mycorrhiza, grafting with salt-resistant rootstocks), chemical (application of organic and mineral amendments, phytohormones), bio-ecological (breeding, desalination, application of nano-based products, seed biopriming), and/or institutional solutions (salinity monitoring, integrated national and regional strategies) are very effective against salinity/salt stress and numerous other constraints. Advances in computer science (artificial intelligence, machine learning) provide rapid predictions of salinization processes from the field to the global scale, under numerous scenarios, including climate change. Thus, these results represent a comprehensive outcome and tool for a multidisciplinary approach to protect and control salinization, minimizing damages caused by salt stress.

Polished rice is widely consumed staple food across the globe, however, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising genotypes for grain Zn, a total of 40 genotypes consisting 20 rice landraces, and 20 released high yielding rice varieties were evaluated in three environments (wet seasons 2014, 2015 and 2016) for nine traits including days to 50% flowering (DFF), plant height (PH), panicle length (PL), total number of tillers (TNT), single plant yield (SPY), Fe and Zn in brown (IBR, ZBR) and polished rice (IPR, ZPR). Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype × Environment Interaction (GGE) analyses identified genotypes G22 (Edavankudi Pokkali), G17 (Taraori Basmati), G27 (Chittimuthyalu) and G26 (Kalanamak) stable for ZPR and G8 (Savitri) stable for SPY across three environments. Significant negative correlation between yield and grain Zn was reaffirmed. Regression analysis indicated the contribution of traits toward ZPR and SPY and also desirable level of grain Zn in brown rice. A total of 39,137 polymorphic single nucleotide polymorphisms (SNPs) were obtained through double digest restriction site associated DNA (dd-RAD) sequencing of 40 genotypes. Association analyses with nine phenotypic traits revealed 188 stable SNPs with six traits across three environments. ZPR was associated with SNPs located in three putative candidate genes (LOC_Os03g47980, LOC_Os07g47950 and LOC_Os07g48050) on chromosomes 3 and 7. The genomic region of chromosome 7 co localized with reported genomic regions (rMQTL7.1) and OsNAS3 candidate gene. SPY was found to be associated with 12 stable SNPs located in 11 putative candidate genes on chromosome 1, 6, and 12. Characterization of rice landraces and varieties in terms of stability for their grain Zn and yield identified promising donors and recipients along with genomic regions in the present study to be deployed rice Zn biofortification breeding program.

Abstract: Ibrutinib has previously been shown to inhibit Bruton's tyrosine kinase (BTK) and interleukin-2–inducible T-cell kinase (ITK), which mediate B-cell and T-cell receptor signaling, respectively. BTK inhibition with ibrutinib has demonstrated impressive clinical responses in a variety of B-cell malignancies. Whether ibrutinib inhibition of ITK can lead to clinical response in T-cell malignancies is unknown. We hypothesized that ibrutinib-mediated ITK inhibition in T-cell lymphoma would result in decreased signaling through the T-cell receptor pathway and promote antitumor immune response by driving selective cytotoxic Th1 CD4 effector T-cell differentiation. This pilot clinical trial evaluated 2 dose levels of ibrutinib: 560 and 840 mg orally daily. Fourteen patients with relapsed, refractory peripheral T-cell lymphoma and cutaneous T-cell lymphoma were enrolled. Both dose levels were safe and well tolerated, and no dose-limiting toxicities were observed. One patient achieved a partial response (overall response rate, 8% [1/13]). ITK occupancy studies demonstrated a mean occupancy of 50% (range, 15%-80%). Higher ITK occupancy of more than 50% correlated with higher serum levels of tumor necrosis factor-α and interferon-γ and favored a Th1 phenotype. Our data suggest that ibrutinib inhibition of ITK has limited clinical activity in T-cell lymphoma. This study is registered at www.clinicaltrials.gov as #NCT02309580.

A robust forecast of rice yields is of great importance for medium-to-long-term planning and decision-making in cereal production, from regional to national level. Incorporation of spatially correlated adjacent effects in forecasting models in general, results in accurate forecast. The Space Time Autoregressive Moving Average (STARMA) is the most popular class of model in linear spatiotemporal time series modelling. However, STARMA cannot process nonlinear spatiotemporal relationships in datasets. Alternately, Time Delay Neural Network (TDNN) is a most popular machine learning algorithm to model the nonlinear pattern in data. To overcome these limitations, two-stage STARMA approach was developed to predict rice yield in some of the most intensive national rice agroecosystems in India. The Mean Absolute Percentage Errors value of proposed STARMA-II approach is lower compared to Autoregressive Moving Average (ARIMA) and STARMA model in all examined districts, while the Diebold-Mariano test confirmed that STARMA-II model is significantly different from classical approaches. The proposed STARMA-II approach is promising alternative to classical linear and nonlinear spatiotemporal time series models for estimating mixed linear and nonlinear patterns and can be advanced tool for mid-to-long-term sustainable planning and management of crop yields and patterns in agroecosystems, i.e., food supply and demand from local to regional levels.

The Asian rice gall midge (Orseolia oryzae (Wood-Mason)) is a major insect pest in rice cultivation. Therefore, development of a reliable system for the timely prediction of this insect would be a valuable tool in pest management. In this study, occurring between the period from 2013–2018: (i) gall midge populations were recorded using a light trap with an incandescent bulb, and (ii) climatological parameters (air temperature, air relative humidity, rainfall and insulations) were measured at four intensive rice cropping agroecosystems that are endemic for gall midge incidence in India. In addition, weekly cumulative trapped gall midge populations and weekly averages of climatological data were subjected to count time series (Integer-valued Generalized Autoregressive Conditional Heteroscedastic—INGARCH) and machine learning (Artificial Neural Network—ANN, and Support Vector Regression—SVR) models. The empirical results revealed that the ANN with exogenous variable (ANNX) model outperformed INGRACH with exogenous variable (INGRCHX) and SVR with exogenous variable (SVRX) models in the prediction of gall midge populations in both training and testing data sets. Moreover, the Diebold–Mariano (DM) test confirmed the significant superiority of the ANNX model over INGARCHX and SVRX models in modeling and predicting rice gall midge populations. Utilizing the presented efficient early warning system based on a robust statistical model to predict the build-up of gall midge population could greatly contribute to the design and implementation of both proactive and more sustainable site-specific pest management strategies to avoid significant rice yield losses.

This study’s objective was to assess the impact of the COVID-19 pandemic on tomato supply and prices in Gudimalkapur market in Hyderabad, India. The lockdown imposed by the government of India from 25 March 2020 to 30 June 2020 particularly affected the supply chain of perishable agricultural products, including tomatoes as one of the major vegetable crops in the study area. The classical time series models such as autoregressive integrated moving average (ARIMA) intervention models and artificial intelligence (AI)-based time-series models namely support vector regression (SVR) intervention and artificial neural network (ANN) intervention models were used to predict tomato supplies and prices in the studied market. The modelling results show that the pandemic had a negative impact on supply and a positive impact on tomato prices. Moreover, the ANN intervention model outperformed the other models in both the training and test data sets. The superior performance of the ANN intervention model could be due to its ability to account for the nonlinear and complex nature of the data with exogenous intervention variable.

An effort has been made to get precise forecast of rice yield through ARIMAX and proposed hybrid models using weather variables. In this article, two hybrid approaches like ARIMAX-ANN and ARIMAX-SVM have been proposed. Firstly, ARIMAX model was fitted for the considered time series data. Rice yield along with weather variables of Aligarh district of Uttar Pradesh have been considered to evaluate the forecasting performance of the proposed hybrid models. The residuals obtained from the fitted model which exhibit nonlinear pattern were fitted employing ANN and SVM. Using the fitted yield values through the hybrid approaches via ANN and SVM, MAPE under ARIMAX (0,1,1)-ANN and ARIMAX (0,1,1)-SVM are estimated to be 0.37 and 1.11, respectively, as compared to 12.18 under ARIMAX (0,1,1) model. Based on the results obtained, we infer that although performance of proposed ARIMAXSVM and ARIMAX-ANN models are close to each other but much superior to the conventional ARIMAX model for the considered data set. Performance of hybrid ARIMAX model is found to be quite encouraging. Yield has also been forecasted up to 2020 on the basis of forecasted rainfall using ARIMAX (0,1,1) model.

Long term forecasting of crop production is required to establish long term vision, say by 2025, to meet growing demand of population at that point of time. Existing univariate linear time series ARIMA approach is valid for short term forecast only. In this paper, a technique for long term yield forecast has been proposed. Initially, we have tried to improve short term forecast of yield by using hybrid ARIMA through ANN approach. The forecast values of yield through hybrid approach was considered as baseline data for long term forecast of yield. Time series data on rice yield was considered for Aligarh district of Uttar Pradesh for the study. Through ARIMA (2,1,0), we got short term forecast of yield by 2020 and the residuals obtained by 2013 were used to model and forecast through ANN approach. For the residuals, 05:04s:1l (05 time delay and 04 hidden nodes) model was identified as suitable one as it has minimum values of mean absolute percentage error (MAPE) for training and testing sets. Using 05:04s:1l model, residuals were forecasted by 2020, forecast values of yield obtained through ARIMA (2,1,0) were corrected by forecasted residuals and eventually get forecast of yield through hybrid approach. The estimated MAPE for ARIMA (2,1,0) and hybrid approach were 17.677% and 4.65%, respectively. Significant reduction in MAPE through hybrid approach indicates it’s much better performance as compared to ARIMA alone. Using hybrid approach, we got forecast of yield by 2020 and considering this forecasted yield as baseline data, we got forecast by 2025 through the proposed approach.

Introduction: The aim of management of Allergic Fungal Rhinosinusitis (AFRS) is to control the disease process and the local immune response of the nasal mucosa. This is achieved by a two pronged approach – surgical clearance of all sinuses by Functional Endoscopic Sinus Surgery (FESS) followed by suppression of local immune response using steroids. Recently delivery of topical steroid by way of douching has been introduced. The effect of budesonide in management of postoperative AFRS patients is yet to be studied. Aim: To evaluate the role of budesonide nasal douching in postoperative management of AFRS. Materials and Methods: A total of 60 postoperative AFRS patients were randomly divided into two groups. Both groups received routine post Functional Endoscopic Sinus Surgery (FESS) medication as per the institute protocol. One group of patients received budesonide douching in addition to the routine care. Both groups were evaluated endoscopically at one, two and six weeks post op. Pre and postoperative quality of life change, patient complains, need for revision surgery and endoscopic Kupferberg scoring were used to compare the two postoperative groups. Results: The average preoperative Sino-Nasal Outcome Test 22 (SNOT-22) score was 50.2. It was reduced to an average of 29.6 in patients who used the standard postoperative regimen and to 19.8 postoperatively in patients who had budesonide added to their douching solutions. The average Kupferberg score was 1.2 for patients who did receive budesonide as compared to 1.9 for patients who did not receive budesonide douching. Conclusion: Budesonide douching can offer a safe and effective tool in managing local inflammatory response in AFRS. It leads to a significantly better quality of life and has an effective response on nasal mucosa – leading to lesser mucosal oedema and lesser incidence of polypoidal changes postoperatively.

Introduction: Tibial diaphyseal fractures are the commonest long bone fractures in adults, most commonly managed by intramedullary interlocking nailing. However, several metaanalysis show that locking plate osteosynthesis is equally effective in managing tibial diaphyseal fractures and are associated with less number of complications. Aim: To compare the results of fixation of tibial fractures following plating and nailing in terms of union, patient satisfaction and complications. Materials and Methods: A hospital based non randomized clinical trial was performed from September 2013 to August 2016 where closed or open diaphyseal or metaphyseo- diaphyseal fractures of the tibia (closed or open Gustilo Anderson type 1 through 3B) were included. Simple sequential allocation was used for allotting the patients to two groups, one for interlocking nailing and other for plating. The patients were followed up for clinical, radiographic and functional results. Results: Forty patients with 41 involved limbs completed follow up for one year. The duration of surgery and average blood loss during surgery was 75.45±3.03 minutes and 165.00±5.31 ml respectively in case of nailing and 85.05±2.54 minutes and184.29±5.33 ml respectively in case of plating and their difference was statistically significant. In our study union was achieved in less than 20 weeks in 29 (70.8%) of the patients and 25-30 weeks in nine (22%) cases. The average time of union in our study was 19.55±0.69 weeks in case of interlocking nailing and 20.38±1.39 weeks in case of plating and there was no statistically significant difference between the two. However, there is statistically significant difference in the functional score in between the two groups in terms of Lower Extremity Functional Score (LEFS). Delayed union in one case of nailing and two cases of plating, valgus malunion in one case of nailing and joint stiffness in two cases each of nailing and plating were the major complications observed. Conclusion: There was no difference between the two modalities in terms of fracture union. Complications were lesser but more serious in case of plating. Patient satisfaction was more with plating.