Patching task-level robot controllers based on a local µ-calculus formula

We present a method for mending strategies for GR(1) specifications. Given the addition or removal of edges from the game graph describing a problem (essentially transition rules in a GR(1) specification), we apply a µ-calculus formula to a neighborhood of states to obtain a “local strategy” that navigates around the invalidated parts of an original synthesized strategy. Our method may thus avoid global resynthesis while recovering correctness with respect to the new specification. We illustrate the results both in simulation and on physical hardware for a planar robot surveillance task

Weed flora of aerobic rice and their effect on growth, yield and nutrient uptake by rice Oryza sativa in the coastal region of Karaikal of Puducherry, India

A field experiment was conducted at farm lands of Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal to know the weed floristic composition and their effect on growth, yield and nutrient uptake by aerobic rice (Oryza sativa). The results revealed that totally 29 species of weeds from 22 genera belonging to 17 families were noticed. Among them, four were grasses, six were sedges, and nineteen were broad leaved weeds. Of this 29 species, four were perennials, and the rest were annuals. During initial stages (30 DAS), sedges dominated (38.3%) whereas at later stages (60 DAS) broad leaved weeds dominated the aerobic rice fields (42.5%). Grasses were found to be comparatively less dominant at both the stages. Echinochloa colona Link. (28.1%) followed by E. cruss-galli (L.) Beauv. (6.1%) among the grasses; Cyperus difformis L. (19.8%) followed by C. iria L (9.9%) among the sedges and Ludwigia abyssinica (28.0%) among the broad leaved weeds, were the predominant weed species in aerobic rice cultivation. Weeds, when left unchecked, competed with rice for all resources like nutrients, space, light and soil moisture. The unweeded control recorded the maximum nutrient depletion by weeds (76.6, 6.4 and 106.8 Kg of N, P andK ha-1 ). Due to severe competition, weeds suppressed the growth of rice which resulted in lower growth and yield attributes leading to lower grain (333 kg ha-1 ) and straw yields (1903 kg ha-1 )

In vivo investigation of hyperpolarized [1,3-13C2]acetoacetate as a metabolic probe in normal brain and in glioma.

Dysregulation in NAD+/NADH levels is associated with increased cell division and elevated levels of reactive oxygen species in rapidly proliferating cancer cells. Conversion of the ketone body acetoacetate (AcAc) to β-hydroxybutyrate (β-HB) by the mitochondrial enzyme β-hydroxybutyrate dehydrogenase (BDH) depends upon NADH availability. The β-HB-to-AcAc ratio is therefore expected to reflect mitochondrial redox. Previous studies reported the potential of hyperpolarized 13C-AcAc to monitor mitochondrial redox in cells, perfused organs and in vivo. However, the ability of hyperpolarized 13C-AcAc to cross the blood brain barrier (BBB) and its potential to monitor brain metabolism remained unknown. Our goal was to assess the value of hyperpolarized [1,3-13C2]AcAc in healthy and tumor-bearing mice in vivo. Following hyperpolarized [1,3-13C2]AcAc injection, production of [1,3-13C2]β-HB was detected in normal and tumor-bearing mice. Significantly higher levels of [1-13C]AcAc and lower [1-13C]β-HB-to-[1-13C]AcAc ratios were observed in tumor-bearing mice. These results were consistent with decreased BDH activity in tumors and associated with increased total cellular NAD+/NADH. Our study confirmed that AcAc crosses the BBB and can be used for monitoring metabolism in the brain. It highlights the potential of AcAc for future clinical translation and its potential utility for monitoring metabolic changes associated with glioma, and other neurological disorders

Nesting Pattern Preferences of Stingless Bee, Trigona Iridipennis Smith (Hymenoptera: Apidae) in Jnanabharathi Campus, Karnataka, India

The patterning aspects of nests are receiving increased attention in nature, so we have studied it in human-dwelling environments involving repeated spatio-temporal mold of pattern. Different criteria such as nesting sites, orientations, nest characters, longevity and elevation of nests have been selected to check the level of preferences exhibited by an indigenous resident species of stingless bee, Trigona iridipennis Smith at the Jnanabharathi campus in the southern part of Bangalore (Karnataka). Nesting patterns gave a precise measurement of preference level exhibited by testing different paradigms. The deciduous, shrub type of vegetation helped for successful dominance in higher number of nests to thrive well, which in turn helped to look at the varying patterns of nests. Observations on different nests revealed: i. preference for the habitats made of walls, ii. north facing direction for nest opening, iii. different type of nests with oval-shaped opening and medium-sized exposure outside, iv. nests with more accumulation of mud, resin and wax deposits and v. bees preferring middle elevation range of 11-15 feet for nest-building purely depending on the safer strategies such as availability of flora, protection from predators for better and safe survival at the nesting sites

Support Vector Machine based Image Classification for Deaf and Mute People

A hand gesture recognition system provides a natural, innovative and modern way of nonverbal communication. It has a wide area of application in human computer interaction and sign language. The whole system consists of three components: hand detection, gesture recognition and human-computer interaction (HCI) based on recognition; in the existing technique, ANFIS(adaptive neuro-fuzzy interface system) to recognize gestures and makes it attainable to identify relatively complex gestures were used. But the complexity is high and performance is low. To achieve high accuracy and high performance with less complexity, a gray illumination technique is introduced in the proposed Hand gesture recognition. Here, live video is converted into frames and resize the frame, then apply gray illumination algorithm for color balancing in order to separate the skin separately. Then morphological feature extraction operation is carried out. After that support vector machine (SVM) train and testing process are carried out for gesture recognition. Finally, the character sound is played as audio output

In vivo detection of γ-glutamyl-transferase up-regulation in glioma using hyperpolarized γ-glutamyl-[1-13C]glycine.

Glutathione (GSH) is often upregulated in cancer, where it serves to mitigate oxidative stress. γ-glutamyl-transferase (GGT) is a key enzyme in GSH homeostasis, and compared to normal brain its expression is elevated in tumors, including in primary glioblastoma. GGT is therefore an attractive imaging target for detection of glioblastoma. The goal of our study was to assess the value of hyperpolarized (HP) γ-glutamyl-[1-13C]glycine for non-invasive imaging of glioblastoma. Nude rats bearing orthotopic U87 glioblastoma and healthy controls were investigated. Imaging was performed by injecting HP γ-glutamyl-[1-13C]glycine and acquiring dynamic 13C data on a preclinical 3T MR scanner. The signal-to-noise (SNR) ratios of γ-glutamyl-[1-13C]glycine and its product [1-13C]glycine were evaluated. Comparison of control and tumor-bearing rats showed no difference in γ-glutamyl-[1-13C]glycine SNR, pointing to similar delivery to tumor and normal brain. In contrast, [1-13C]glycine SNR was significantly higher in tumor-bearing rats compared to controls, and in tumor regions compared to normal-appearing brain. Importantly, higher [1-13C]glycine was associated with higher GGT expression and higher GSH levels in tumor tissue compared to normal brain. Collectively, this study demonstrates, to our knowledge for the first time, the feasibility of using HP γ-glutamyl-[1-13C]glycine to monitor GGT expression in the brain and thus to detect glioblastoma

Bio-Augmentation for Reducing the Traditional Panchagavya Production Time

Panchagavya, a traditional Indian biofertilizer made from five cow-derived products (dung, urine, milk, curd, and ghee), has long been used in Hindu rituals and Ayurveda. Recently, its role in organic agriculture has gained attention due to its benefits for plant growth, soil health, and pest control. Traditional preparation takes 45 days, limiting large-scale application. This study aimed to reduce fermentation time and improve product quality using an accelerated method. By introducing specific microbial cultures, the fermentation period was shortened by 18 days without compromising efficacy. Enhanced microbial activity maintained the bio-stimulant properties of the product. Additionally, bio-coagulants from Colocasia esculenta and Strychnos potatorum were incorporated to reduce turbidity and improve clarity by aggregating suspended particles. Microbial profiling of the optimized Panchagavya revealed beneficial strains like Pseudomonas, Bacillus, and Lactobacillus, along with unidentified lipolytic and proteolytic organisms, indicating areas for future research. The study concludes that accelerated fermentation combined with natural bio-coagulants improves production efficiency and quality, making Panchagavya more viable for commercial agriculture. This approach supports sustainable practices and could significantly scale up biofertilizer production

Select pyrimidinones inhibit the propagation of the malarial parasite, Plasmodium falciparum

Plasmodium falciparum, the Apicomplexan parasite that is responsible for the most lethal forms of human malaria, is exposed to radically different environments and stress factors during its complex lifecycle. In any organism, Hsp70 chaperones are typically associated with tolerance to stress. We therefore reasoned that inhibition of P. falciparum Hsp70 chaperones would adversely affect parasite homeostasis. To test this hypothesis, we measured whether pyrimidinone-amides, a new class of Hsp70 modulators, could inhibit the replication of the pathogenic P. falciparum stages in human red blood cells. Nine compounds with IC50 values from 30 nM to 1.6 μM were identified. Each compound also altered the ATPase activity of purified P. falciparum Hsp70 in single-turnover assays, although higher concentrations of agents were required than was necessary to inhibit P. falciparum replication. Varying effects of these compounds on Hsp70s from other organisms were also observed. Together, our data indicate that pyrimidinone-amides constitute a novel class of anti-malarial agents. © 2009 Elsevier Ltd. All rights reserved

Identification of Pulmonary Disease with Chest X-ray data using CNN Architecture

Pneumonia is an infectious and fatal sickness in breathing that is caused by germs, fungi, or a virus that infects the    human lung sacs with the load full of fluid or pus. The common method used to diagnose pneumonia are using chest x-rays and always needs a medical expert to assess the result of X-ray. This difficult technique of recognizing pneumonia results in a life loss due to improper diagnosis and treatment. This study intends to integrate deep learning methods to reduce the problem. Convolution Neural Network is optimized to perform the complicated task of detecting diseases like pneumonia from a group of chest X-ray images. This is model is based on supervised learning, the output of this system is dependent on the dataset’s quality. VGG16 Architecture which is a deep learning model is finely tuned using transfer learning to achieve higher accuracy. This model extracts attributes from chest X-ray dataset and categorize regardless if the man is affected with pneumonia or not. This model helps to reduce the sickness and describable challenges frequently faced with medical treatment