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BackgroundAlthough speech-language therapy (SLT) is proven to be beneficial to recovery of post-stroke aphasia, delivering sufficiently high amounts of dosage remains a problem in real-world clinical practice. Self-managed SLT was introduced to solve the problem. Previous research showed in a 10-week period, increased dosage frequency could lead to better performance, however, it is uncertain if dosage still affects performance over a longer period of practice time and whether gains can be seen following practice over several months.ObjectiveThis study aims to evaluate data from a health app (Constant Therapy) to investigate the relationship between dosage amount and improvements following a 30-week treatment period. Two cohorts of users were analyzed. One was comprised of patients with a consistent average weekly dosage amount and the other cohort was comprised of users whose practice had higher variability.MethodsWe conducted two analyses with two cohorts of post-stroke patients who used Constant Therapy. The first cohort contains 537 “consistent” users, while the second cohort contains 2,159. The 30-week practice period was split into three consecutive 10-week practice windows to calculate average dosage amount. In each 10-week practice period, patients were grouped by their average dosage into low (0–15 min/week), medium (15–40 min/week) and moderate dosage (greater than 40 min/week) groups. Linear mixed-effects models were employed to evaluate if dosage amount was a significant factor affecting performance. Pairwise comparison was also applied to evaluate the slope difference between groups.ResultsFor the consistent cohort, medium (β = .002, t17,700 = 7.64, P β = .003, t9,297 = 7.94, P β = .001, t = 1.76, P = .078).ConclusionsThis study showed a higher dosage amount is related to greater therapy outcomes in over 6 months of digital self-managed therapy. It also showed that regardless of the exact pattern of practice, self-managed SLT leads to significant and sustained performance gains.

Unobtrusive monitoring of distances between people indoors is a useful tool in the fight against pandemics. A natural resource to accomplish this are surveillance cameras. Unlike previous distance estimation methods, we use a single, overhead, fisheye camera with wide area coverage and propose two approaches. One method leverages a geometric model of the fisheye lens, whereas the other method uses a neural network to predict the 3D-world distance from people-locations in a fisheye image. To evaluate our algorithms, we collected a first-of-its-kind dataset using single fisheye camera, that comprises a wide range of distances between people (1-58 ft) and will be made publicly available. The algorithms achieve 1-2 ft distance error and over 95% accuracy in detecting social-distance violations.

Abstract: Allamanda cathartica L. belongs to the family Apocynaceae and is a traditionally valuable medicinal plant that has been commonly used in the traditional medicinal system and contributes to the native healthcare system in various parts of the world. This plant is renowned for its antibacterial and anticancer effects and its usage in the treatment of jaundice, diabetes, hypertension, and polio. All of the economically and medicinally essential plant parts of this species are used in the preparation of a potent cathartic. This review focused on and intended to highlight the most current knowledge about A. cathartica, including its important ethnomedicinal, modern medicinal, and phytochemical potential along with its green approaches. This plant has been extensively used in herbal medicine and has various important phytopharmacological properties. The modern green technological approaches of this plant enhance agricultural productivity when its various nanoparticles are applied in fields that perform antimicrobial, antipathogenic activities. Nanoparticles serve as carriers for the delivery of drugs and as disease targets in contemporary medicine. This plant has recently been involved in modern medicine as a threat to cancer, which is a significant accomplishment for modern medical science. Hence, A. cathartica is an important plant that can be useful to cure various ailments and could be useful in modern science with its green approaches. We must further investigate this plant's bioactivities to determine the mode of action.

Domain generalization aims to learn a model with good generalization ability, that is, the learned model should not only perform well on several seen domains but also on unseen domains with different data distributions. State-of-the-art domain generalization methods typically train a representation function followed by a classifier jointly to minimize both the classification risk and the domain discrepancy. However, when it comes to model selection, most of these methods rely on traditional validation routines that select models solely based on the lowest classification risk on the validation set. In this paper, we theoretically demonstrate a trade-off between minimizing classification risk and mitigating domain discrepancy, i.e., it is impossible to achieve the minimum of these two objectives simultaneously. Motivated by this theoretical result, we propose a novel model selection method suggesting that the validation process should account for both the classification risk and the domain discrepancy. We validate the effectiveness of the proposed method by numerical results on several domain generalization datasets., Comment: Accepted to ICASSP 2023

Domain generalization (DG) is a branch of transfer learning that aims to train the learning models on several seen domains and subsequently apply these pre-trained models to other unseen (unknown but related) domains. To deal with challenging settings in DG where both data and label of the unseen domain are not available at training time, the most common approach is to design the classifiers based on the domain-invariant representation features, i.e., the latent representations that are unchanged and transferable between domains. Contrary to popular belief, we show that designing classifiers based on invariant representation features alone is necessary but insufficient in DG. Our analysis indicates the necessity of imposing a constraint on the reconstruction loss induced by representation functions to preserve most of the relevant information about the label in the latent space. More importantly, we point out the trade-off between minimizing the reconstruction loss and achieving domain alignment in DG. Our theoretical results motivate a new DG framework that jointly optimizes the reconstruction loss and the domain discrepancy. Both theoretical and numerical results are provided to justify our approach., 13 pages, 2 tables

Person re-identification (PRID) from side-mounted rectilinear-lens cameras is a well-studied problem. On the other hand, PRID from overhead fisheye cameras is new and largely unstudied, primarily due to the lack of suitable image datasets. To fill this void, we introduce the "Fisheye Re-IDentification Dataset with Annotations" (FRIDA), with 240k+ bounding-box annotations of people, captured by 3 time-synchronized, ceiling-mounted fisheye cameras in a large indoor space. Due to a field-of-view overlap, PRID in this case differs from a typical PRID problem, which we discuss in depth. We also evaluate the performance of 10 state-of-the-art PRID algorithms on FRIDA. We show that for 6 CNN-based algorithms, training on FRIDA boosts the performance by up to 11.64% points in mAP compared to training on a common rectilinear-camera PRID dataset., 8 pages

Unsupervised contrastive learning (UCL) is a self-supervised learning technique that aims to learn a useful representation function by pulling positive samples close to each other while pushing negative samples far apart in the embedding space. To improve the performance of UCL, several works introduced hard-negative unsupervised contrastive learning (H-UCL) that aims to select the "hard" negative samples in contrast to a random sampling strategy used in UCL. In another approach, under the assumption that the label information is available, supervised contrastive learning (SCL) has developed recently by extending the UCL to a fully-supervised setting. In this paper, motivated by the effectiveness of hard-negative sampling strategies in H-UCL and the usefulness of label information in SCL, we propose a contrastive learning framework called hard-negative supervised contrastive learning (H-SCL). Our numerical results demonstrate the effectiveness of H-SCL over both SCL and H-UCL on several image datasets. In addition, we theoretically prove that, under certain conditions, the objective function of H-SCL can be bounded by the objective function of H-UCL but not by the objective function of UCL. Thus, minimizing the H-UCL loss can act as a proxy to minimize the H-SCL loss while minimizing UCL loss cannot. As we numerically showed that H-SCL outperforms other contrastive learning methods, our theoretical result (bounding H-SCL loss by H-UCL loss) helps to explain why H-UCL outperforms UCL in practice.

In this paper, we propose a novel domain generalization (DG) framework based on a new upper bound to the risk on the unseen domain. Particularly, our framework proposes to jointly minimize both the covariate-shift as well as the concept-shift between the seen domains for a better performance on the unseen domain. While the proposed approach can be implemented via an arbitrary combination of covariate-alignment and concept-alignment modules, in this work we use well-established approaches for distributional alignment namely, Maximum Mean Discrepancy (MMD) and covariance Alignment (CORAL), and use an Invariant Risk Minimization (IRM)-based approach for concept alignment. Our numerical results show that the proposed methods perform as well as or better than the state-of-the-art for domain generalization on several data sets., Comment: 8 pages, 2 figures, and 1 table. This paper is accepted at 32nd IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2022)

The rhizosphere is a dynamic region influenced by complex interactions between plants and microbes that are closely linked to the metabolically active hotspots of the roots below the soil and participate in below-ground interactions. We must consider the roles of the rhizosphere to improve above-ground productivity and hence regulate the environment. Initially, the soil was measured to be stable only based on nutrient abundance, but the healthy soil is now seen with large microbial communities after rhizosphere evolution. In this regard, numerous strategies for manipulating the rhizosphere for better ecological functioning need to be developed. Based on current ecological evidence, we propose a new sketch in which future comparative research through sustainable agriculture and an environment is required to uncover the underlying mechanisms. Plant roots manage below-ground diversity by releasing exudates into the rhizosphere, due to their microbial growth capability. The microbes are attracted to the exudates, and in the rhizosphere, they developed communities. Roots play an important role in the microbial community establishment, having a major and primary energy channel in the ecosystem of the rhizosphere. Via the roots channel, the energy release then transfers to the microbial channel, eventually converted into microbial biomolecules, which are then returned to the above-ground in the form of volatile compounds and productivity. This review discusses the different energy channels in the rhizosphere that facilitate the development of the microbial community and the transfer of energy in a sequence in the form of productivity from above-ground to below-ground to above-ground. Importantly, such awareness may result in strategies for improving plant health and development in the context of future agricultural demand.

Conventional agriculture plays a substantial role in meeting the food demands of a growing human population, which has led to an increased reliance on chemical fertilizers and pesticides. Chemical fertilizers are industrially manipulated substances and composed of known amount of nitrogen, phosphorus and potassium. In appropriate and misuse use of chemical fertilizers causes air and ground water pollution by eutrophication of water bodies and causing health problem in human. Therefore, the aim of this chapter is to emphasize the importance and use of plant growth promoting bacteria (PGPB) as a gateway to sustainable agriculture that could ensure plant productivity and quality agricultural practices in an environment friendly manner. In this respect, efforts have been made to products of nutrient rich high-quality food in feasible way to ensure bio-safety. The innovative aspect of farm production attracts the need of biological based organic fertilizers, an exclusive alternative to agro-chemicals. Organic farming is one of such strategies that not only ensures food safety but also adds to the biodiversity of soil. The eco-friendly approaches trigger a wide range of application of PGPB that leads to improved plant growth, soil health, nutrient uptake and plant tolerance to abiotic and biotic stress. PGPB is an essential component of organic farming and play crucial role in maintaining long term soil fertility and sustainability and would be a viable alternative for farmers to increase productivity per unit area in organic farming for an era of prosperity and clean environment.

The genus Ceropegia L. is a highly diversified genus of the family Apocynaceae whose most of the species are facing threats. The species Ceropegia wallichii Wight is categorized under Data Deficient (DD) which is found between 2500 to 2900 m altitudes since till date according to available literature while this article first time mentioned its elevation in 1735 m altitude. Hence, in this scenario, its new elevation should be changed from 1700 to 2900 m. Owing to its poor abundance of sheets in Indian herbaria, this species also needs to be protected.

There are many medicinal plants that have various medicinal properties in their different parts. The medicinal plants are major backbone of pharmaceutical industries. In this article we compare the antioxidants properties from various plants parts (root, stem, leaf, flower and bark) of the most important medicinal plant, Justicia adhatoda L. Various plant parts showed the good amount of antioxidant properties. These results enhance the medicinal properties of this plant due to the presence of good amount of antioxidants; among all the plant parts leaves and flowers showed maximum natural antioxidants, hence the study could be saying that this plant has good efficacy of antioxidants.

Growing concern about climatic influence on plants reproductive biology leads to a recent surge. Climate affects directly floral morphology of plants on this basis current study summarizes climatic effects on floral or reproductive biology of Solanum nigrum L. Effect of summer, rainy and winter seasons were recorded on floral morphology, pollens viability & germination, pollen tube growth, fruit-set percentage during investigations which were subjected to one factorial analysis of variance (ANOVA) and least significant differences at p < 0.05. Climatic conditions affect floral morphology and produce polymorphism in specific conditions. In rainy and winter seasons, polymorphism was recorded in petals, stamens and pistil which is a first record of climatic influence on polymorphism. Rainy season reported for their maximum flowers numbers which promote a huge fruit-set percentage in open pollination as compared with self and cross pollination. This study confirms the effect of various climates on different floral parts which produce polymorphism along with growth, germination, length, etc. Scanning Electron Microscopy (SEM) study indicated the climatic variations on microscopic observations.

There are many medicinal plants that have various medicinal properties in their different parts. The medicinal plants are major backbone of pharmaceutical industries. In this article we compare the antioxidants properties from various plants parts (root, stem, leaf, flower and bark) of the most important medicinal plant, Justicia adhatoda L. Various plant parts showed the good amount of antioxidant properties. These results enhance the medicinal properties of this plant due to the presence of good amount of antioxidants; among all the plant parts leaves and flowers showed maximum natural antioxidants, hence the study could be saying that this plant has good efficacy of antioxidants.

Secondary metabolites have potential benefits to human being. They are used in the food, agricultural and pharmaceutical industries. The secondary metabolite of furanocoumarins from different plant sources is essential in various skin-related ailments. Biologically, these chemicals are isolated from different plants in the Apiaceae, Fabaceae, Rutaceae and Moraceae families. Ammi majus L. is one of the most common plants in the family of Apiaceae with a large quantity of derivatives. The furanocoumarin derivatives defend the plant by fighting external enemies by Systemic Acquired Resistance (SAR). Via suppressing or retarding microbial growth in infected parts, these derivatives, along with SAR, help to alleviate inflammation in the human body. Latest evidence of these compounds has been established in the treatment of cancer, but the mechanism that needs to be elaborated is not yet understood. Recent studies have shown that furanocoumarin derivatives bind to DNA base pairs and block DNA replication. This may be a potential pathway that helps to regulate the growth of cancerous cells. This article reflects on the pharmaceutical data of furanocoumarins and their different mechanisms in these cases.

When journalists cover a news story, they can cover the story from multiple angles or perspectives. A news article written about COVID-19 for example, might focus on personal preventative actions such as mask-wearing, while another might focus on COVID-19's impact on the economy. These perspectives are called "frames," which when used may influence public perception and opinion of the issue. We introduce a Web-based system for analyzing and classifying frames in text documents. Our goal is to make effective tools for automatic frame discovery and labeling based on topic modeling and deep learning widely accessible to researchers from a diverse array of disciplines. To this end, we provide both state-of-the-art pre-trained frame classification models on various issues as well as a user-friendly pipeline for training novel classification models on user-provided corpora. Researchers can submit their documents and obtain frames of the documents. The degree of user involvement is flexible: they can run models that have been pre-trained on select issues; submit labeled documents and train a new model for frame classification; or submit unlabeled documents and obtain potential frames of the documents. The code making up our system is also open-sourced and well-documented, making the system transparent and expandable. The system is available on-line at http://www.openframing.org and via our GitHub page https://github.com/davidatbu/openFraming ., 8 pages, 8 figures, EMNLP 2020 demonstration papers

Indigenous agricultural practices adopted by locals largely depend on traditional knowledge, common in agricultural system to preserve ecosystem, biodiversity, and useful in maintaining sustainable food and human health. Farmers possess a vast pool of indigenous knowledge in livestock management which reduces external input dependency by utilizing various renewable farm resources as agricultural practices. These practices address the rural development and nature conservation; contribute to maintaining ecosystem of particular area which leads to sustainable use of biodiversity conservation. This knowledge is not systematically recorded; therefore, it is not easily accessible to agricultural researchers; hence, these are valuable practices that provide farmer-to-farmer training or local technology transfer. Different governmental as well as non-governmental policies are designed to maintain biodiversity; hence, indigenous agriculture is one of the most important practices followed for biodiversity conservation. To change the people’s mind towards indigenous agriculture through spiritual education is one of the most important factors which could be focused on important ethics; hence, it can preserve both indigenous knowledge and biodiversity for achieving sustainable development.

In view of the overall health impact of NIDDM, inventers understand the necessity of improving glycemic control in adults with type 2 diabetes. BGR-34 provides an effective treatment option for adults with type 2 diabetes who have been inadequately controlled on lifestyle with or without other oral hypoglycemic agents (OHGAs) such as metformin, sulfonylurea, or a glitazones. BGR-34 is an appropriate option to consider for addition to a managed care drug formulary. Treatment with BGR-34 produced clinically relevant and statistically significant reductions in all three key measures of glucose control studied —FPG, PPBG and HbA1c— when compared with placebo. BGR-34, showed the promising result with respect to glycemic parameters in NIDDM patient with a significant reduction in fasting blood sugar by 34.3%, postprandial blood sugar 35.5% & glycosylated haemoglobin by 20.31% as compared to placebo group showing a reduction by 13.2%, 10.9% & 10.87% respectively. The trial has also been registered to CTRI, India. This study has been registered in the clinical trial registry-India., Graphical abstract BGR 34, has been investigated to contain a number of active biomolecule molecules including the compound ‘berberine’ (source; Berberis aristata), a natural dipeptidyl peptidase IV (DPP-4) inhibitor, that act by increasing endogenous GLP-1 and GIP concentrations.Image 1

Chemical analysis of hexane and ethyl acetate soluble fractions obtained from the rhizobacteria Pseudomonas jessenii strain R62 and Pseudomonas synxantha strain R81 was carried out using gas chromatography-mass spectrometry and their nematicidal activity was evaluated against root-knot nematode, Meloidogyne incognita second stage juveniles (J2). Results showed that the hexane extract of both strains, together with mixed ethyl acetate extract, were found to have better nematicidal activity than their individual ethyl acetate fractions above 100 ppm. Some of the chemical compounds of these bioactive fractions were identified using gas chromatography-mass spectroscopy (GC–MS) analysis. A total of sixteen and six similar compounds were detected in hexane and ethyl acetate fractions, respectively from both bacteria. The major compounds, namely hexadecenoic acid and hexadecanoic acid may be responsible for the nematicidal activity.

Arbuscular mycorrhizal fungi are important for controlling soil-borne diseases and could be important for managements of root-knot disease. Effective co-inoculation of mycorrhiza (Rhizophagus irregularis) and root-knot nematode (Meloidogyne incognita) on plant growth, physiological and biochemical changes during root-knot nematode infection into tomato (Lycopersicon esculentum cv. PT-3) plants were studied. Experiments were conducted under controlled conditions and carried up to one month after nematode inoculation. Rhizophagus irregularis treated plants significantly enhanced plant growth and reduced nematode induced parameters. They also exhibited potent activity of phenolics and defensive enzymes i.e. peroxidase (PO), polyphenyloxidase (PPO) and superoxide dismutase (SOD) while a significant reduction was recorded in malondialdehyde (MDA) and hydrogen peroxide (H2O2) content. Both physiological and biochemical parameters were significantly improved in response to Rhizophagus irregularis. These finding indicates the importance of Rhizophagus irregularis as a potential biocontrol tool for the management of root-knot disease.

Arbuscular mycorrhiza (AM), plant growth promoting rhizobacteria (PGPRs) and root-knot nematode survive in the rhizosphere and perform the same niche. AM and PGPRs play positive role in roots while nematode oppose it. Nematode damages the root system, which reduces the nutrient uptake specially phosphorus (P) while AM help to uptake. PGPRs are another symbiotic micro-organism helpful to mycorrhizal survival and colonization. AM and PGPRs can defeat the soil borne diseases like root-knot disease which lead to increasing mycorrhizal colonization and nutrient uptake. On this basis current work emphasizes the effects on mycorrhizal colonization and P uptake in presence of PGPRs along with root-knot nematode infection in tomato plants.

Arbuscular mycorrhizal fungi (AMF) and plant growth promoting rhizobacteria (PGPR) have potential to control soil-borne diseases including plant-parasitic nematodes. First, the effects of dual inoculation of mycorrhiza (Rhizophagus irregularis) and two stains of pseudomonads (Pseudomonas jessenii strain R62 and Pseudomonas synxantha strain R81) on tomato (Solanum lycopersicum cv. PT-3) growth were tested. Further, the physiological and biochemical changes caused by these beneficial organisms during infection by the root-knot nematode Meloidogyne incognita were studied. The experiment was conducted under glass house conditions and carried out up to one month after nematode inoculation. Plants treated with dual or individual inoculation of AMF and PGPR showed significantly enhanced plant growth and reduced nematode infection. In addition, they exhibited potent activity of phenolics (28 %) and defensive enzymes i.e. peroxidase (PO; 1.26 fold), polyphenyloxidase (PPO; 1.35 fold) and superoxide dismutase (SOD; 1.09 fold) while a significant reduction in malondialdehyde (MDA; 1.63 fold) and hydrogen peroxide (H2O2; 1.30 fold) content was recorded when compared to the nematode-infected plants. These findings indicate the feasibility of AMF and PGPR individually or in combinations as potential biocontrol agents for the management of root-knot nematodes.

In present study, a total of 104 bacteria and 96 actinomycetes were isolated from rhizosphere plant root of finger millet (E leusine coracana ) from Almora district of Uttarakhand, India. Isolates were characterized using microscopic and morphological methods followed by their biochemical test. Based on functional tests, four most promising isolates were identified using 23S rDNA primers as Streptomyces labedae (SB-9), Streptomyces flavofuscus (SA-11), and 16S rDNA primers as Pseudomonas poae (KA-5), and Pseudomonas fluorescens (KB-7). Influence of Glomus intraradices (G.I.) singly and along with actinomycetes and Pseudomonas spp. were evaluated under irrigated and water deficit conditions. Out of eight treatments studied in this study, a higher significant increase in plant height with S. labedae SB-9 + G.I and P. poae KA-5 + G.I were recorded. In well watered and water deficient conditions, maximum shoot dry matter content was recorded in P. Poae + P. flurosence + G.I and S. labedae + S. flavofuscus + G.I inoculated plants in comparison to their respective control. Under in vitro condition, P. poae KA-5 produced higher amount of indole acetic acid (IAA) among the selected isolates. Anti-oxidant enzyme, superoxide dismutase (SOD) and accumulation of free proline content in leaves were maximum in P. Poae + G.I inoculated plants under water deficit condition. In the presence of Streptomyces and Pseudomonas spp. a better mycorrhizal infection was observed in treated plant roots. This investigation support mutual symbiosis of Streptomyces and Pseudomonas strains with G. intraracides which had synergic effect on finger millet cv. Korchara plant under irrigated as well as under water stress condition. Keywords: Glomus intraradices , Streptomyces , Pseudomonas , anti oxidants, plant growth promotion, IAA production

Root-knot disease poses a worldwide problem to agriculture; hence, several environmentally hazardous chemical nematicides are being used to control it. Rhizobacteria could be one of the important biocontrol agents which can replace these chemicals. This study focused on the effect of bacterial cell-free culture filtrate against Root-knot nematodes. Experiment was conducted to observe the effect of different dilutions of cell-free culture filtrate on Meloidogyne incognita under laboratory and in greenhouse conditions. In laboratory, toxicity effect of filtrate was recorded on second stage juveniles (J2), 100% mortality was recorded in all treatment above the 75% concentration. In greenhouse, all the growth and nematode induced parameters were significantly differed after culture filtrate treatment to the tomato plants. The finding indicates the capability of fluorescent Pseudomonad's culture filtrate as a powerful biocontrol tool for the management of Root-knot nematodes.

The largest continent, Asia, which harbored some of the world's oldest civilizations, constitutes one-third of the earths land area. The physiography of central Asia is dominated by the mightiest ranges: the Himalayas, Hindukush, Kunlun, and Tien Shan. The distribution and abundance of rodents in Asia indicate a broad pattern which, in a way, corresponds to the terrain physiography and bioclimate of the region. Periodic as well as sporadic outbreaks in the rodent populations enhance their numbers menacingly. Such outbreaks can be caused either by failure of monsoon, by favorable reproductive conditions after a fairly long spell of climates, or can be associated with flowering of bamboo in forests. Quantified information on actual damage caused by rodents to agricultural crops in China is not available; however, 10% loss in field crops is reported. Rodent damage to grasslands and fodder crops is very severe, especially in the arid tracts.

The availability of anticoagulant rodenticides, particularly that of the second generation, has generated ample hope that, by their use, rodent populations can be reduced below the threshold level, thereby substantially reducing the losses incurred by these pests. The acute toxicant, zinc phosphide, still remains the most used and popular rodenticide in most parts of the world. In a control operation, zinc phosphide baits are recommended for distribution in the fields on three consecutive days. When poison baits are exposed to the rodent populations, some of them consume a lethal quantity and succumb, whereas those which ingest only a sublethal dose of poison survive the poisoning. The bait shyness and poison aversion phenomena, due to ingestion of various poisons, persist for varying durations in different species and with different rodenticides. Even after acquiring considerable knowledge about phenomena of bait shyness and poison aversion, we know very little about how to overcome them with a view to enhance success of control operations.

Manufacturing of protein/enzymes by biotechnological methods may contribute to develop new protein/enzyme preparations useful in various sectors of industry. Microbial enzymes released in growing medium and difficult to isolate. In this study, a rapid method has been developed for isolating extracellular proteins from cultured nutrient broth. After removing the bacterial cells from cultured broth through 0.4mm filter paper and dissolved proteins recovered by precipitation with 5% trichloroacetic acid (TCA). Sodium dodecyl sulfate - polyacrylamide gel electrophoresis (SDS-PAGE) analysis of the isolated crude enzymes from bacterial cell free culture filtrate showed the presence of different bands in the electrophoretic field.

Privacy-preserving data release mechanisms aim to simultaneously minimize information-leakage with respect to sensitive data and distortion with respect to useful data. Dependencies between sensitive and useful data results in a privacy-utility tradeoff that has strong connections to generalized rate-distortion problems. In this work, we study how the optimal privacy-utility tradeoff region is affected by constraints on the data that is directly available as input to the release mechanism. In particular, we consider the availability of only sensitive data, only useful data, and both (full data). We show that a general hierarchy holds: the tradeoff region given only the sensitive data is no larger than the region given only the useful data, which in turn is clearly no larger than the region given both sensitive and useful data. In addition, we determine conditions under which the tradeoff region given only the useful data coincides with that given full data. These are based on the common information between the sensitive and useful data. We establish these results for general families of privacy and utility measures that satisfy certain natural properties required of any reasonable measure of privacy or utility. We also uncover a new, subtler aspect of the data processing inequality for general non-symmetric privacy measures and discuss its operational relevance and implications. Finally, we derive exact closed-analytic-form expressions for the privacy-utility tradeoffs for symmetrically dependent sensitive and useful data under mutual information and Hamming distortion as the respective privacy and utility measures., 20 pages, 3 figures, under submission

Lycopersicon esculentum is a widely grown vegetable crops throughout the world and it is highly affected by root-knot nematode (Meloidogyne spp.); globally more than 27% yield losses in tomato is due to their infections. As the inoculums level increases, the absorption, translocation and photosynthesis rate decreases in the host plants; it means damage caused by nematodes is directly proportional to the number of second-stage juveniles (J2) which are penetrating and establishing in the host roots. In this aspect, the present study focused on the effect of different inoculums on the tomato plants. The study reports that with increased intensity of root-knot nematode infection, the plant growth and biomass were highly reduced. Key words: Tomato, root-knot nematode, inoculum, growth, infection.

Root-knot disease caused by Meloidogyne spp. poses a worldwide threat to agriculture as well as environment due to excess use of chemical nematicides for its management. Recently, arbuscular mycorrhizal fungi (AMF) have achieved importance as biocontrol agent for the managements of root-knot disease. In this aspect, the present study was focused on the effect of AMF (Glomus intraradices) against root-knot disease of tomato (Lycopersicon esculentum) caused by Meloidogyne incognita. Observations of G. intraradices against M. incognita were taken at 10, 20 and 30 days after M. incognita second stage juveniles (J2) inoculation on tomato roots, which were pre-colonized by G. intraradices. A significant effect was observed on plant growth (length and biomass) and nematode induced (root galls, egg masses, egg and adult females) parameters in nematode inoculated G. intraradices colonized plants as compared to non-colonized plants at all the three harvesting periods. The finding of present study indicates the potential of G. intraradices as a potential biocontrol tool for the management of root-knot disease and can be used in the place of environmentally hazardous chemical nematicides. Key words: Arbuscular mycorrhiza, root-knot disease, nematicides, biocontrol, management.

Fruit is a ripened ovary it may either fleshy or nut and divided into cultivated as well as wild categories Wild fruits are worldwide distributed and mostly found in the part of earth where anthropogenic activities are no or negligible The use of Himalayan plant species for food and medicine has been known for a long time Uttarakhand is one of these places which is suitable for wild edible fruiting plants because of their difficult geography and climatic conditions and awesome taste of fruits which are attracted by their people as a rich source of their nutrition Wild edible plants are very important for the well being of rural populations in the region not only as sources of supplemental food nutritionally balanced diets medicines fodder and fuel but also for their income generating potential Large numbers of wild fruits along with their edible values also used in medicine and many other wild fruits viz Rubus ellipticus Fragaria times ananassa Prunus persica Myrica esculentaetc have high nutritive quality and used by the local peoples for the different edible products Such wild plants might be explore for their nutritional and medicinal properties and need to conserve for biodiversity maintenance

Rice is one of the widely consumed staple foods among the world's human population. Its production is adversely affected by high temperature and is more pronounced at flowering stage. Elucidating elevated temperature stress-related proteins as well as associated mechanisms is inevitable for improving heat tolerance in rice. In the present study, a proteomic analysis of heat-sensitive rice genotype, IET 21405 was conducted. Two-dimensional electrophoresis (2-DE) and MALDI-TOF/MS-based proteomics approaches revealed a total of 73 protein spots in rice leaf. The protein profiles clearly indicated variations in protein expression between the control and heat treated rice genotypes. Functional assessment of 73 expressed proteins revealed several mechanisms thought to be involved in high temperature including their putative role in metabolism, energy, protein synthesis, protein transport/storage, etc. Besides these, some proteins are expected to involve in photosynthesis, tricarboxylic acid (TCA) cycle, glycolysis and other proteins for energy production. The proteins identified in the present study provide a strong basis to elucidate gene function of these proteins and to explain further the molecular mechanisms underlying the adaptation of rice to high temperature stress.

Soil is an excellent niche for the growth of microorganisms which includes plant growth-promoting rhizobacteria (PGPRs). PGPRs have great potential for plant growth promotion as they control pest and disease and have been considered important in sustainable agriculture. PGPRs induce and/or synthesize various growth-promoting and biocontrolling chemicals which are useful for sustainable agriculture and environment. These chemicals are phytohormones, antibiotics, enzymes, etc., which react with the soil and provide better health to the plants. PGPRs directly or indirectly circulate their products to soil for better soil health which further enhance the soil immunity followed by influencing plant growth, productivity, and yield. Soil immune system works strongly by the activities of soil microbes which are considered as a heart of soil. These soil microbes are responsible for increasing soil fertility and productivity which are considered important for sustainable agriculture.

The basic function of soil microorganisms is the decomposition and transformation of organic materials, which are derived from the plant residues. Thus, soil microbial communities play a critical role in ecosystem processes. Soil microbial activities, populations and communities are governed by environmental variables and agricultural system. The conventional agriculture has an important role in improving food productivity. The earthworms have been modifying soil characteristics for millennia wherever they are found world-wide, it has only been recently that soil scientists described vermic horizons and even vermisols, where earthworm influence on soils reaches dramatic proportions. The earthworm body, both internally and externally, is the site of metabolic processes, at this level, microbial activity is enhanced. The increase of soil porosity in organic system indicated the decrease in soil bulk density which promotes the soil microbial activity.

The article Mycorrhizal colonization and phosphorus uptake in presence of PGPRs along with nematode infection, written by Ishwar Prakash Sharma and A. K. Sharma, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 20 September 2018 with open access.

We develop necessary and sufficient conditions and a novel provably consistent and efficient algorithm for discovering topics (latent factors) from observations (documents) that are realized from a probabilistic mixture of shared latent factors that have certain properties. Our focus is on the class of topic models in which each shared latent factor contains a novel word that is unique to that factor, a property that has come to be known as separability. Our algorithm is based on the key insight that the novel words correspond to the extreme points of the convex hull formed by the row-vectors of a suitably normalized word co-occurrence matrix. We leverage this geometric insight to establish polynomial computation and sample complexity bounds based on a few isotropic random projections of the rows of the normalized word co-occurrence matrix. Our proposed random-projections-based algorithm is naturally amenable to an efficient distributed implementation and is attractive for modern web-scale distributed data mining applications., Typo corrected; Revised argument in Lemma 3 and 4

Small Mammalian Diversity on the Abu Hill