イオン液体を用いたナトリウム二次電池用リン化物負極材料に関する研究

京都大学0048新制・課程博士博士(エネルギー科学)甲第22795号エネ博第409号新制||エネ||78(附属図書館)京都大学大学院エネルギー科学研究科エネルギー基礎科学専攻(主査)教授 萩原 理加, 教授 佐川 尚, 教授 野平 俊之学位規則第4条第1項該当Doctor of Energy ScienceKyoto UniversityDFA

Opinion-Mining on Marglish and Devanagari Comments of YouTube Cookery Channels Using Parametric and Non-Parametric Learning Models

YouTube is a boon, and through it people can educate, entertain, and express themselves about various topics. YouTube India currently has millions of active users. As there are millions of active users it can be understood that the data present on the YouTube will be large. With India being a very diverse country, many people are multilingual. People express their opinions in a code-mix form. Code-mix form is the mixing of two or more languages. It has become a necessity to perform Sentiment Analysis on the code-mix languages as there is not much research on Indian code-mix language data. In this paper, Sentiment Analysis (SA) is carried out on the Marglish (Marathi + English) as well as Devanagari Marathi comments which are extracted from the YouTube API from top Marathi channels. Several machine-learning models are applied on the dataset along with 3 different vectorizing techniques. Multilayer Perceptron (MLP) with Count vectorizer provides the best accuracy of 62.68% on the Marglish dataset and Bernoulli Naïve Bayes along with the Count vectorizer, which gives accuracy of 60.60% on the Devanagari dataset. Multilayer Perceptron and Bernoulli Naïve Bayes are considered to be the best performing algorithms. 10-fold cross-validation and statistical testing was also carried out on the dataset to confirm the results

Disruptive Technologies in Smart Farming: An Expanded View with Sentiment Analysis

Smart Farming (SF) is an emerging technology in the current agricultural landscape. The aim of Smart Farming is to provide tools for various agricultural and farming operations to improve yield by reducing cost, waste, and required manpower. SF is a data-driven approach that can mitigate losses that occur due to extreme weather conditions and calamities. The influx of data from various sensors, and the introduction of information communication technologies (ICTs) in the field of farming has accelerated the implementation of disruptive technologies (DTs) such as machine learning and big data. Application of these predictive and innovative tools in agriculture is crucial for handling unprecedented conditions such as climate change and the increasing global population. In this study, we review the recent advancements in the field of Smart Farming, which include novel use cases and projects around the globe. An overview of the challenges associated with the adoption of such technologies in their respective regions is also provided. A brief analysis of the general sentiment towards Smart Farming technologies is also performed by manually annotating YouTube comments and making use of the pattern library. Preliminary findings of our study indicate that, though there are several barriers to the implementation of SF tools, further research and innovation can alleviate such risks and ensure sustainability of the food supply. The exploratory sentiment analysis also suggests that most digital users are not well-informed about such technologies

COVID-19 Diagnosis from Cough Acoustics using ConvNets and Data Augmentation

With the periodic rise and fall of COVID-19 and countries being inflicted by its waves, an efficient, economic, and effortless diagnosis procedure for the virus has been the utmost need of the hour. COVID-19 positive individuals may even be asymptomatic making the diagnosis difficult, but amongst the infected subjects, the asymptomatic ones need not be entirely free of symptoms caused by the virus. They might not show any observable symptoms like the symptomatic subjects, but they may differ from uninfected ones in the way they cough. These differences in the coughing sounds are minute and indiscernible to the human ear, however, these can be captured using machine learning-based statistical models. In this paper, we present a deep learning approach to analyze the acoustic dataset provided in Track 1 of the DiCOVA 2021 Challenge containing cough sound recordings belonging to both COVID-19 positive and negative examples. To perform the classification on the sound recordings as belonging to a COVID-19 positive or negative examples, we propose a ConvNet model. Our model achieved an AUC score percentage of 72.23 on the blind test set provided by the same for an unbiased evaluation of the models. The ConvNet model incorporated with Data Augmentation further increased the AUC-ROC percentage from 72.23 to 87.07. It also outperformed the DiCOVA 2021 Challenge's baseline model by 23% thus, claiming the top position on the DiCOVA 2021 Challenge leaderboard. This paper proposes the use of Mel frequency cepstral coefficients as the feature input for the proposed model.Comment: DiCOVA, top 1st, This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Assessment of Anti-aging Efficacy of the Master Antioxidant Glutathione

A chief tripeptide antioxidant Glutathione (GSH) is present inside each body cell which may have a profound effect in the control of aging. The anti-aging potency of GSH and its role towards the progression of certain age-related disease is still unclear. Glutathione based articles were searched on PubMEd database since the very first study of glutathione related to its discovery in 1923 to its present status till 2016. The data was made more informative and precise by searching glutathione relevant reports on google. Those articles were selected which were indicating the association of glutathione with the progression of age-related diseases, pre-clinical and clinical studies and age-longevity effect. It was analyzed that the increased oxidative stress (elevated GSSG/GSH ratio) is responsible for the incidence of age-related diseases and different organs failure. The glutathione redox ratio (GSSG/GSH) was found to be more pro-oxidizing with aging which plays a chief role for the generation of reactive oxygen species (ROS) and subsequently damages the macromolecular structures affecting the normal body mechanisms and functions. The clinical data has recommended that glutathione is a potent therapeutic agent for the control of age-related diseases and experimental analysis has confirmed its prominent effect in age-longevity

Bronchiectasis in India:results from the European Multicentre Bronchiectasis Audit and Research Collaboration (EMBARC) and Respiratory Research Network of India Registry

BACKGROUND: Bronchiectasis is a common but neglected chronic lung disease. Most epidemiological data are limited to cohorts from Europe and the USA, with few data from low-income and middle-income countries. We therefore aimed to describe the characteristics, severity of disease, microbiology, and treatment of patients with bronchiectasis in India. METHODS: The Indian bronchiectasis registry is a multicentre, prospective, observational cohort study. Adult patients ( 6518 years) with CT-confirmed bronchiectasis were enrolled from 31 centres across India. Patients with bronchiectasis due to cystic fibrosis or traction bronchiectasis associated with another respiratory disorder were excluded. Data were collected at baseline (recruitment) with follow-up visits taking place once per year. Comprehensive clinical data were collected through the European Multicentre Bronchiectasis Audit and Research Collaboration registry platform. Underlying aetiology of bronchiectasis, as well as treatment and risk factors for bronchiectasis were analysed in the Indian bronchiectasis registry. Comparisons of demographics were made with published European and US registries, and quality of care was benchmarked against the 2017 European Respiratory Society guidelines. FINDINGS: From June 1, 2015, to Sept 1, 2017, 2195 patients were enrolled. Marked differences were observed between India, Europe, and the USA. Patients in India were younger (median age 56 years [IQR 41-66] vs the European and US registries; p<0\ub70001]) and more likely to be men (1249 [56\ub79%] of 2195). Previous tuberculosis (780 [35\ub75%] of 2195) was the most frequent underlying cause of bronchiectasis and Pseudomonas aeruginosa was the most common organism in sputum culture (301 [13\ub77%]) in India. Risk factors for exacerbations included being of the male sex (adjusted incidence rate ratio 1\ub717, 95% CI 1\ub703-1\ub732; p=0\ub7015), P aeruginosa infection (1\ub729, 1\ub710-1\ub750; p=0\ub7001), a history of pulmonary tuberculosis (1\ub720, 1\ub707-1\ub734; p=0\ub7002), modified Medical Research Council Dyspnoea score (1\ub732, 1\ub725-1\ub739; p<0\ub70001), daily sputum production (1\ub716, 1\ub703-1\ub730; p=0\ub7013), and radiological severity of disease (1\ub703, 1\ub701-1\ub704; p<0\ub70001). Low adherence to guideline-recommended care was observed; only 388 patients were tested for allergic bronchopulmonary aspergillosis and 82 patients had been tested for immunoglobulins. INTERPRETATION: Patients with bronchiectasis in India have more severe disease and have distinct characteristics from those reported in other countries. This study provides a benchmark to improve quality of care for patients with bronchiectasis in India. FUNDING: EU/European Federation of Pharmaceutical Industries and Associations Innovative Medicines Initiative inhaled Antibiotics in Bronchiectasis and Cystic Fibrosis Consortium, European Respiratory Society, and the British Lung Foundation

Expulsion of Fluoride and Arsenate from Water Solution by Mg/Fe Layered Double Hydroxide

In this work an attempt was made to remove fluoride and arsenate from the aqueous solution by using calcined Mg/ Fe layered double hydroxide. Calcined Mg/Fe Layered double hydroxide (Mg/Fe-CLDH) was used as an adsorbent for expulsion of fluoride and arsenate from the water solution in this study. In this Mg/Fe layered double hydroxide was prepared by using co-precipitation method by using Magnesium Nitrate (Mg(NO3)2.6H2O) and Ferric Nitrate (Fe(NO3)3.9H2O). After this sample was washed by the centrifuge method and then sample was freeze dried to get the nanopowders. This nanopowers was calcined at about 400oC after this Fluoride stock solution was prepared by dissolving NaF into deionized water then Mg/Fe LDH nanopowder was used as the adsorbent, by applying LDH nanopowder to the stock solution samples were taken out from the solution at different time interval and then this samples were analysed by UV Visible Spectrometer with the help of the ethanol and methyl orange. Arsenate stock solution was prepared by dissolving Na2HAsO4.7H2O into deionized water water then Mg/Fe LDH nanopowder was used as the adsorbent, by applying LDH nanopowder to the stock solution samples were taken out from the solution at different time interval and then this samples were analysed by Atomic Adsorption Spectroscopy with the help of Sodium borohydride (NaBH4), Aluminium chloride (AlCl3), Ascorbic acid, Sodium hydroxide (NaOH), Potassium Iodide (KI). In this work adsorbent behaviour of calcined LDH with time dependency was analysed. For this, respectively. The adsorbents were characterized by XRD, FT-IR, FESEM, UV Visible Spectrometer, Atomic Adsorption Spectroscopy and the analysis results demonstrated by the adsorption mechanism

High-Performance Sodium Secondary Batteries Using Synergistic Effect of Amorphous SiP₂/C Anode and Ionic Liquid Electrolyte

A silicon diphosphide-carbon composite (SiP₂/C) was investigated as a negative electrode material for sodium secondary batteries with the Na[FSA]–[C₃C₁pyrr][FSA] (FSA⁻ = bis(fluorosulfonyl)amide anion and C₃C₁pyrr⁺ = N-methyl-N-propylpyrrolidinium cation) ionic liquid electrolyte. Two amorphous silicon diphosphide materials, SiP₂/C (80:20) and SiP₂/C (70:30) (80:20 and 70:30 refer to the SiP₂:C weight ratio), were prepared by a facile two-step high energy ball-milling process. SiP₂/C (80:20) and SiP₂/C (70:30) delivered high discharge capacities of 883 and 791 mAh g⁻¹, respectively, at 100 mA g⁻¹ in the first cycle at 90 °C, with the latter showing better cyclability. Comparison of the performance of SiP₂/C (70:30) in the ionic liquid and organic electrolytes at 25 °C indicated the advantage of the ionic liquid electrolyte in terms of higher discharge capacity and improved cyclability. Electrochemical impedance spectroscopy revealed that the interfacial resistance decreased with cycling in the ionic liquid electrolyte at 25 °C but significantly increased at 90 °C. Ex situ X-ray diffraction revealed that the product remains amorphous even after charging and discharging in SiP₂/C (70:30). This study demonstrated the importance of ionic liquids and phosphide based materials as high performance enablers for sodium secondary batteries