On rarely fuzzy e-continuous functions in the sense of Šostak’s

In this paper, we introduce the concepts of rarely fuzzy e-continuous functions in the sense of Šostak’s is introduced. Some interesting properties and characterizations of rarely fuzzy e-continuous and weakly fuzzy e-continuous are investigated. Also, fuzzy eT1/2-space, rarely fuzzy eT2-spaces and some applications to fuzzy compact spaces are established

Comparative Study of Ram Air Turbines based on Wind Tunnel Study for Specific Air Borne Energy Extraction

Ram Air Turbines (RAT) are used for emergency on-board power generation on aircraft and associated systems. Many studies on usage of RATs have shown promising results in terms of using RATs as a source of emergency on-board power generation. Many external podded systems on aircraft utilise RATs for self-sufficient adaptation. These pods generate their own power using RATs for their power requirements instead of depending on the mother aircraft power. Commercial cargo planes use RATs for generating emergency hydraulic power. A RAT was suggested to be used for emergency power, during failure of main alternator on a prototype aircraft. A specific requirement of the RAT was also to produce high drag for aerodynamic braking when deployed and concurrently generate electrical energy. Three models with different solidity were studied in wind tunnel at different wind speeds for suitability of this drag-energy combination. This paper presents the results of the study. Based on the results, a suitable RAT was selected for further analysis and ground trials

Improvement of Grazing Lands for Better Livestock Production--A Case Study from Chitradurga District in India

Chitradurga is a highly drought prone district in the central dry zone of Karnataka, India, with a normal rainfall of 530 mm per annum. Over 85 per cent of cultivable area is rainfed and the livestock plays a vital role in rural income generation in this district. Improper management and overgrazing have resulted in most of the grazing resources declining to a poor, degraded condition. Regeneration of pasture land was vital in the villages due to three reasons - a) people\u27s livelihood dependency on livestock was considerable b) small ruminants played a vital role for landless farmers and c) lack of adequate fodder was a prime factor for low livestock productivity. To improve the livelihood of livestock farmers, a few interventions were made under World Bank funded National Agricultural Innovation Project through consortium approach in 10 project villages. Frequent interactions were held with the local livestock farmers to discuss about the importance of increasing the fodder resources in the villages to improve the income and to sustain their livelihood. They realized the importance of fodder and came forward to take up cultivation of perennial fodders and also, for the revitalization of grazing lands, locally known as kavals. The primary survey in the villages indicated that about 90 to 96 per cent of the small ruminant holders are dependent on these common property grazing resources for the fodder needs. The High Level Panel of Experts on food security and nutrition, constituted by FAO, has emphasized the importance of extending appropriate technologies and inputs, providing the needed credit and ensuring assured and remunerative marketing opportunities to the smallholders (HLPE, 2013). Such measures are also essential for revitalizing the degraded grasslands in this region

Musical Training Influences Auditory Temporal Processing

Background: A link between musical expertise and auditory temporal processing abilities was examined. Material and methods: Trained musicians (n=13) and non-musicians (n=12) were tested on speech tasks (phonetic identification, speech recognition in noise) and non-speech tasks (temporal gap detection). Results: Results indicated musicians had shorter between-channel gap detection thresholds and sharper phonetic identification functions, suggesting that perceptual reorganization following musical training assists basic temporal auditory processes. Conclusions: In general, our results provide a conceptual advance in understanding how musical training influences speech processing, an ability which, when impaired, can affect speech and reading competency

Tinnitus and Qigong

Subjective tinnitus is the perception of sound despite the absence of an external stimulus. This challenging sensory event affects millions of people per year. There currently is no cure for tinnitus, but there have been many different options researched to help patients manage its effects, albeit with varying efficacy. In a viral internet video, the Beating the Heavenly Drum maneuver, found in the Eastern practice of Qigong, was said to eliminate the perception of tinnitus for the participants. In this current study, the Beating the Heavenly Drum maneuver was compared to a sham maneuver and evaluated for effectiveness in relieving tinnitus. To be included in this study, participants had experienced tinnitus for at least 6 months and were not currently receiving other tinnitus care. Exclusionary criteria included a diagnosis of Post-Traumatic Stress Disorder, Traumatic Brain Injury, any neurological condition, whiplash, neck injury, or severe anxiety or depression, as determined by the Hospital Anxiety and Depression Scale. Participants completed a tinnitus case history form, Tinnitus Functional Index (TFI), Tinnitus Handicap Index (THI), and Visual Analog Scale (VAS) ranking the annoyance of their tinnitus. Participants were assigned to groups in an alternating fashion, with odd identifiers in Group 1 and even identifiers in Group 2. In Group 2, participants received the experimental maneuver (Beating the Heavenly Drum) during the first session and the sham maneuver (circles rubbed at the base of the skull) during the second. In Group 1, participants received a sham maneuver during the first session and the experimental maneuver during the second session. Within 48 hours after each session, participants completed the TFI, THI, and rated the annoyance of their tinnitus on a scale of 0 to 10 (keeping the same parameters from the VAS) via phone call. Of the twelve participants, two reported that the experimental maneuver, Qigong, was effective for tinnitus relief; while five reported the sham condition relieved their tinnitus. The remaining five participants stated that neither maneuver altered their tinnitus sensation. Across all participants, there were no significant difference scores on the THI, and only one significant difference score on the TFI. While participants reported some change in their tinnitus with either maneuver, none of the questionnaire measures corroborated their subjective report. Additionally, the sham maneuver was perceived as more effective than the experimental maneuver. The Qigong maneuver was not effective for tinnitus relief in this study. It should be noted that a limitation to this study is the small sample size. While this Qigong maneuver did not relieve tinnitus, there are other Internet tinnitus “cures” that should be investigated for their effectiveness in tinnitus relief. With the rise of the Internet and more patients searching for “quick fixes” to tinnitus, it is vital that clinicians provide appropriate education and research to best help patients manage their tinnitus

Quantitative Imaging of Protein-Protein Interactions by Multiphoton Fluorescence Lifetime Imaging Microscopy using a Streak camera

Fluorescence Lifetime Imaging Microscopy (FLIM) using multiphoton excitation techniques is now finding an important place in quantitative imaging of protein-protein interactions and intracellular physiology. We review here the recent developments in multiphoton FLIM methods and also present a description of a novel multiphoton FLIM system using a streak camera that was developed in our laboratory. We provide an example of a typical application of the system in which we measure the fluorescence resonance energy transfer between a donor/acceptor pair of fluorescent proteins within a cellular specimen.Comment: Overview of FLIM techniques, StreakFLIM instrument, FRET application

Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial

Deep learning–based clinical imaging analysis underlies diagnostic artificial intelligence (AI) models, which can match or even exceed the performance of clinical experts, having the potential to revolutionize clinical practice. A wide variety of automated machine learning (autoML) platforms lower the technical barrier to entry to deep learning, extending AI capabilities to clinicians with limited technical expertise, and even autonomous foundation models such as multimodal large language models. Here, we provide a technical overview of autoML with descriptions of how autoML may be applied in education, research, and clinical practice. Each stage of the process of conducting an autoML project is outlined, with an emphasis on ethical and technical best practices. Specifically, data acquisition, data partitioning, model training, model validation, analysis, and model deployment are considered. The strengths and limitations of available code-free, code-minimal, and code-intensive autoML platforms are considered. AutoML has great potential to democratize AI in medicine, improving AI literacy by enabling “hands-on” education. AutoML may serve as a useful adjunct in research by facilitating rapid testing and benchmarking before significant computational resources are committed. AutoML may also be applied in clinical contexts, provided regulatory requirements are met. The abstraction by autoML of arduous aspects of AI engineering promotes prioritization of data set curation, supporting the transition from conventional model-driven approaches to data-centric development. To fulfill its potential, clinicians must be educated on how to apply these technologies ethically, rigorously, and effectively; this tutorial represents a comprehensive summary of relevant considerations

Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT

Protein-protein interactions (PPIs) are critical to normal cellular function and are related to many disease pathways. A range of protein functions are mediated and regulated by protein interactions through post-translational modifications (PTM). However, only 4% of PPIs are annotated with PTMs in biological knowledge databases such as IntAct, mainly performed through manual curation, which is neither time- nor cost-effective. Here we aim to facilitate annotation by extracting PPIs along with their pairwise PTM from the literature by using distantly supervised training data using deep learning to aid human curation. Method We use the IntAct PPI database to create a distant supervised dataset annotated with interacting protein pairs, their corresponding PTM type, and associated abstracts from the PubMed database. We train an ensemble of BioBERT models-dubbed PPI-BioBERT-x10-to improve confidence calibration. We extend the use of ensemble average confidence approach with confidence variation to counteract the effects of class imbalance to extract high confidence predictions. Results and conclusion The PPI-BioBERT-x10 model evaluated on the test set resulted in a modest F1-micro 41.3 (P =5 8.1, R = 32.1). However, by combining high confidence and low variation to identify high quality predictions, tuning the predictions for precision, we retained 19% of the test predictions with 100% precision. We evaluated PPI-BioBERT-x10 on 18 million PubMed abstracts and extracted 1.6 million (546507 unique PTM-PPI triplets) PTM-PPI predictions, and filter [Formula: see text] (4584 unique) high confidence predictions. Of the 5700, human evaluation on a small randomly sampled subset shows that the precision drops to 33.7% despite confidence calibration and highlights the challenges of generalisability beyond the test set even with confidence calibration. We circumvent the problem by only including predictions associated with multiple papers, improving the precision to 58.8%. In this work, we highlight the benefits and challenges of deep learning-based text mining in practice, and the need for increased emphasis on confidence calibration to facilitate human curation efforts.Aparna Elangovan, Yuan Li, Douglas E. V. Pires, Melissa J. Davis, and Karin Verspoo

Sorghum germplasm: diversity and utilization

Plant genetic resources can be defi ned as the “Genetic material of plants that is of value as a resource for the present and future generations of people” (IPGRI 1993). The importance of genetic resources was recognized at the inter-governmental platform under the umbrella of Food and Agricultural Organization (FAO) of the United Nations as “common heritage of mankind” that should be made available without restriction (FAO 1983). The genetic resources have evolved as a product of domestication, intensifi cation, diversifi cation and improvement through conscious and unconscious selection by countless generations of farmers, man-guided diversity in the form of landraces and improved cultivars that provide basic and strategic raw materials for crop improvement the world over in present and future generations