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Applying Novel Techniques from Physical and Biological Sciences to Life Detection

Space(Science & Technology) 2023年第1期3卷 325-338页

作者： Tony Z.Jia Chaitanya Giri Andrea Aldaba Ilknur Bahcivan Nipun Chandrasiri Ilankuzhali Elavarasan kashish gupta Sakshi P.Khandare Christos Liaconis Arpita Saha Orlando J.Solórzano Paola Ines Tiranti Aivaras Vilutis Graham E.Lau Earth-Life Science Institute Tokyo Institute of Technology2-12-1-IE-1 OokayamaMeguro-kuTokyo 152-8550Japan Blue Marble Space Institute of Science 6001st AveFloor 1SeattleWA 98104USA Research and Information System for Developing Countries(RIS) Core IV-BFourth FloorIndia Habitat CentreLodhi RoadNew Delhi 110003India Department of Physical and Natural Sciences School of Liberal EducationFLAME UniversityLavalePune 412115MaharashtraIndia School of Physical Sciences and Nanotechnology Yachay Tech University100119 UrcuquíEcuador

One of the primary goals of the space exploration community is to unambiguously detect past or present life outside of *** such,a number of so-called life detection technologies,instruments,and approaches have been applied as part of past,current,and future space *** astrobiology is a truly interdisciplinary field within the realm of space exploration with major contributions from physical and biological sciences(among others),recently there has been development of a number of relevant techniques from scientific fields that have yet to be fully applied to extraterrestrial life *** a culmination of the 2021 Blue Marble Space Institute of Science(BMSIS)Young Scientist Program(YSP),we present a number of techniques drawn from various fields(including,but not limited to,chemistry,materials science,biology,nanotechnology,medical science,astrophysics,and more)that either have been or have the potential to be applied to life detection *** techniques broadly fall under three categories:instrumentation for in situ measurements of biosignatures within the solar system,calculations or observational techniques for remote measurements of exoplanet biosignatures,and *** hope that this primer serves to inspire the field to consider applying more potential technologies from adjacent fields into any of these three categories of life detection.

关键词： signature applying outside

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Insights from a Brief Study of Renal Calculi: Recent Diagnostic and Treatment Approaches

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生物组学研究杂志(英文) 2024年第1期07卷 8-19页

作者： Kumar Aashish Goyal Rajat Garg Kajal gupta Sumeet Wilson kashish Chopra Hitesh MM College of Pharmacy Maharishi Markandeshwar (Deemed to be University) Mullana-Ambala Haryana India Lal Chand Mal College of Education Jhansa Kurukshetra Haryana India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India

Background: Renal calculi, commonly known as kidney stones, is a prevalent urological condition that affects a substantial portion of the population worldwide. The formation of kidney stones is a complex process influenced by various factors, including diet, fluid intake, genetics, and metabolic abnormalities. The pathogenesis of renal calculi involves a complex interplay of multiple factors, including supersaturation of urine with stone-forming constituents, urinary supersaturation, crystallization, and ***: This review aims to provide an overview of the present understanding of renal calculi, their pathophysiology, diagnostic approaches, and available treatment ***: This review discusses the different types of kidney stones, such as calcium oxalate, calcium phosphate, uric acid, and struvite stones, and explores their formation mechanisms and associated risk factors. The management of renal calculi relies on stone characteristics, patient symptoms, stone size, and location. Furthermore, counseling and education regarding lifestyle modifications and risk factor management are essential for long-term ***: Accurate diagnosis and appropriate management based on stone characteristics and patient symptoms are essential for successful outcomes. Preventive strategies to reduce stone recurrence are vital for long-term management and patient well-being. However, further research is needed to refine diagnostic techniques, improve treatment options, and enhance the understanding of the underlying pathophysiology of renal calculi.

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Transfer Learning Model to Indicate Heart Health Status Using Phonocardiogram

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Computers, Materials & Continua 2021年第12期69卷 4151-4168页

作者： Vinay Arora Karun Verma Rohan Singh Leekha Kyungroul Lee Chang Choi Takshi gupta kashish Bhatia Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatialaPunjabIndia Associate Application ITConcentrixGurugramHaryanaIndia School of Computer Software Daegu Catholic UniversityGyeongsanKorea Department of Computer Engineering Gachon UniversitySeongnam13120Korea Information Security Engineering Soonchunhyang UniversityKorea Department of Computer Engineering University College of EngineeringPunjabi UniversityPatialaPunjabIndia

The early diagnosis of pre-existing coronary disorders helps to control complications such as pulmonary hypertension,irregular cardiac functioning,and heart ***-based learning of heart sound is an efficient technology which can help minimize the workload of manual auscultation by automatically identifying irregular cardiac ***(PCG)and electrocardiogram(ECG)waveforms provide the much-needed information for the diagnosis of these *** this work,the researchers have converted the heart sound signal into its corresponding repeating pattern-based *** 2016 and PASCAL 2011 have been taken as the benchmark datasets to perform *** existing models,***,Xception,Visual Geometry Group(VGG16),ResNet,DenseNet,and InceptionV3 of Transfer Learning have been used for classifying the heart sound signals as normal and *** PhysioNet 2016,DenseNet has outperformed its peer models with an accuracy of 89.04 percent,whereas for PASCAL 2011,VGG has outperformed its peer approaches with an accuracy of 92.96 percent.

关键词： PCG signals transfer learning repeating pattern-based spectrogram biomedical signals internet of things(IoT)

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