Miracle-dz/UniFAR-FTUs huggingface dataset:
COVID-19 Sounds: A Large-Scale Audio Dataset for Digital Respiratory Screening

Audio signals are widely recognised as powerful indicators of overall health status, and there has been increasing interest in leveraging sound for affordable COVID-19 screening through machine learning. However, there has also been scepticism regarding the initial efforts, due to perhaps the lack of reproducibility, large datasets and transparency which unfortunately is often an issue with machine learning for health. To facilitate the advancement and openness of audio-based machine learning for respiratory health, we release a dataset consisting of 53,449 audio samples (over 552 hours in total) crowd-sourced from 36,116 participants through our COVID-19 Sounds app 1 . Given its scale, this dataset is comprehensive in terms of demographics and spectrum of health conditions. It also provides participants’ self-reported COVID-19 testing status with 2,106 samples tested positive. To the best of our knowledge, COVID-19 Sounds is the largest multi-modal dataset of COVID-19 respiratory sounds: it consists of three modalities including breathing, cough, and voice recordings. Additionally, in this paper, we report on several benchmarks for two principal research tasks: respiratory symptoms prediction and COVID-19 prediction. For these tasks we demonstrate performance with a ROC-AUC of over 0 . 7 , conﬁrming both the promise of machine learning approaches based on these types of datasets as well as the usability of our data for such tasks. We describe a realistic experimental setting that hopes to pave the way to a fair performance evaluation of future models. In addition, we reﬂect on how the released dataset can help to scale some existing studies and enable new research
Optimization of Diclofenac Sodium Orodispersible Tablets with Natural Disintegrants using Response Surface Methodology

Traditionally experimental methods in the pharmaceutical formulation development involve significant amount of time and efforts to get an optimized dosage form. It is very much desirable as per industrial perspective to obtain suitable, optimized and stable formulation with minimum amount of time and effort. The purpose of this study was to study the synergic effect of natural disintegrants and central composite design in optimization of diclofenac sodium orodispersible tablets. In this study, central composite design was applied to study the effect of natural disintegrant as independent variables i.e. seed mucilage of Plantago ovata, and seed mucilage of Ocimum basilicum. Diclofenac sodium orodispersible tablets were prepared by direct compression method on Cadmech single punch machine using flat 8-mm punches and characterized for the dependent variables like disintegration time and cumulative percent drug released after 25 minutes. Optimization study by multiple regression analysis revealed that, 6% of Plantago ovata and 5% Ocimum basilicum was found to be optimum which has disintegrated in 36 secs and cumulative percent drug released was 99.2% at 25 minutes. A checkpoint formulation was prepared to prove the validity of the evolved mathematical model. These findings suggest that synergic effect of natural disintegrants of Plantago ovata and Ocimum basilicum employed with systematic experimental design approach have greater influence in optimization of diclofenac sodium orodispersible tablets. It is likely that this formulation technology can be exploited for commercial production of dispersible tablets.
An Overview of the Berkeley Mobile Offshore Base Dynamic Positioning Project

The Mobile Offshore Base (MOB) is a large, self-propelled, floating, pre-positioned ocean structure formed of three to five modules and reaching up to 1,500 meters in length. It must accommodate the landing and take-off of C -17 conventional aircraft, host 3000 troops, carry 10 million gallons of fuel and provide 3 million square feet of internal configurable storage. The alignment of the modules is maintained through the use of slew-able thrusters and/or connectors. The University of California at Berkeley’s involvement with the ONR Mobile Offshore Base project resulted in a three-year effort meant to provide insight into the design and architecture of coordinated DP systems (systems involving the DP of a structure or vessel relative to another floating ocean structure or vessel), a simulation environment in which different MOB concepts could be tested and evaluated, and an experimental scaled platform (1:150) on which the coordinated DP control algorithms were implemented and evaluated.
Student Perceptions of Branding Benefits of a New Collegiate Stadium

Student Perception of Branding Benefits of a New Collegiate Stadium In recent years, a wide range of universities have undertaken expensive stadium construction or renovation projects (“2015 by the Numbers,” 2015; “College Hoops Research,” 2017). Current renovation projects include an ongoing $307-million renovation of Arizona State’s football stadium, and an upcoming $72-million renovation of the University of Dayton’s basketball arena (Garbe, 2017; Ryman, 2017). The high costs often lead to questions about the benefits of the facilities, especially when funding comes from outside the sport organization or athletic department. Proponents of large stadium projects often tout their economic impact, yet researchers have argued that argument is insufficient to justify the cost or public contribution in professional stadiums (Coates & Humphreys, 2008; Harger, Humphreys, & Ross, 2016). Maxcy and Larson (2015) also found this to be true with the impact of collegiate stadiums. As the direct economic impact of a stadium does not appear to justify the construction cost, researchers and organizations alike have offered alternative justifications for stadium projects.
Current-induced superconducting anisotropy of Sr2RuO4

In the unconventional superconductor Sr2RuO4, unusual first-order superconducting transition has been observed in the low-temperature and high-field region, accompanied by a four-fold anisotropy of the in-plane upper critical magnetic field Hc2. The origin of such unusual Hc2 behavior should be closely linked to the debated superconducting symmetry of this oxide. Here, toward clarification of the unusual Hc2 behavior, we performed the resistivity measurements capable of switching in-plane current directions as well as precisely controlling the field directions. Our results reveal that resistive Hc2 under the in-plane current exhibits an additional twofold anisotropy. By systematically analyzing Hc2 data taken under various current directions, we succeeded in separating the two-fold Hc2 component into the one originating from applied current and the other originating from certain imperfection in the sample. The former component, attributable to vortex flow effect, is weakened at low temperatures where Hc2 is substantially suppressed. The latter component is enhanced in the first order transition region, possibly reflecting a change in the nature of the superconducting state under high magnetic field.
Learning to learn for innovation and sustainable development

Since the 1960s, the attention paid by policy makers and scientists to the negative environmental and social effects of economic development has grown steadily. However, although some progress has been made in a number of areas, unsustainable trends in the patterns of our systems of production and consumption have not changed to any significant degree. This research is based on the observation that innovation to improve sustainable development requires learning at societal, organizational and individual levels. Business practices influence the development of systems of production and consumption, and in order to move towards sustainable development there is a need for innovation in the way businesses learn and innovate. The research focuses on innovation processes and uses case studies of four innovation projects in the paper and board producing industry in The Netherlands. Three main aspects of innovation projects are identified: the development of innovation processes, the development of inter-organizational learning systems, and the development of capabilities that enable the innovation processes and the management of learning systems. On the basis of these aspects, a conceptual model is built that demonstrates the dynamics of inter-organizational learning for innovation. The conclusions drawn, with respect to learning for innovation and sustainable development, cover the fields of team diversity, learning from the past, joint decision-making, guidance by experienced senior managers, and dealing with the complexity of social issues and the dynamics of innovation projects.
INTEGRATING INTELLIGENCE IN HYDROPONIC FARMS

Agriculture plays a major role on improving the economy of the country. Modern farming technique like Hydroponics is in rise which is soilless farming culture and the plants were grown with the help of nutrient solutions. The Hydroponic system can be controlled by applying machine learning algorithms like Deep Neural Networks. Internet of Things (IoT) allows Machine to Machine communication and controlling the hydroponic system autonomously and intelligently. This work proposes to develop an intelligent IoT based hydroponic system by employing Deep Neural Networks. The system so developed is intelligent enough in providing the appropriate control over the sprinkler and water flow for the hydroponic environment based on the multiple input parameters gathered from sensors like pH, temperature, humidity and water flow.
Three-phase SVA inverter

This paper presents an inverter topology based on series-voltage-action (SVA) used to generate additional levels. This inverter will be called as SVA Inverter. The SVA Inverter presents some advantages over the traditional inverters, such as output voltage higher than the dc-link voltage and lower distortion in output voltage. The complete analysis presented in this paper includes the inverter model and its operation and PWM strategy. A general comparison with conventional inverter is also presented. Simulated and experimental results corroborate the theoretical study.
Market Segmentation of Tuxedo Customers

This research project was designed to segment the tuxedo customer market and develop customer profiles. Data were collected by a questionnaire mailed to 266 tuxedo customers. Respondents (n = 90) were segmented as purchasers and renters as well as light and heavy tuxedo users. These customer segments were compared according to their information search patterns, clothing involvement, product characteristics, clothing behaviors, and consumer demographics. Customer profiles were developed, along with applicable marketing implication. This study contributes to research in male consumer behavior.
High Power Density Silicon Combustion Systems for Micro Gas Turbine Engines

As part of an effort to develop a microscale gas turbine engine for power generation and micropropulsion applications, this paper presents the design, fabrication, experimental testing, and modeling of the combustion system. Two radial inflow combustor designs were examined; a single-zone arrangement and a primary and dilution-zone configuration. Both combustors were micromachined from silicon using deep reactive ion etching (DRIE) and aligned fusion wafer handing. Hydrogen-air and hydrocarbon-air combustion were stabilized in both devices, each with chamber volumes of 191 mm 3 . Exit gas temperatures as high as 1800 K and power densities in excess of 1100 MW/m 3 were achieved. For the same equivalence ratio and overall efficiency, the dual-zone combustor reached power densities nearly double that of the single-zone design. Because diagnostics in microscale devices are often highly intrusive, numerical simulations were used to gain insight into the fluid and combustion physics. Unlike large-scale combustors, the performance of the microcombustors was found to be mole severely limited by heat transfer and chemical kinetics constraints. Important design trades are identified and recommendations for microcombustor design are presented.
THE NONDESTRUCTIVE TESTING OF CONCRETE: AN UPDATE

Abstract In the last time a lot of new developments in the field of nondestructive testing (NDT) methods justified to prepare a study on the state of these methods, carried out by the author by order of the German Research Foundation (DFG). The author presents a general classification of these methods in a graphical form [1]. Since the 1960s the author himself has been actively involved in research, teaching, practical applications and expertise in this held, so that final conclusions on the advantages and limitations of all these methods, which are always also influenced by the author's own experience, represent a “balanced“ view on this topic [2]. The assessment of the concrete strength in-situ nondestructively is a very controversial subject. The results obtained by NDT methods in many companies by the author are compared with the destructively obtained ones by these building companies. The good agreement of both categories of results is a further support for the use of NDT and for a quantitative appro.
Effect of planting system and seedling number on growth and rice yield rice Inpari-IR-Nutri Zinc

Rice Inpari-IR-Nutri Zinc is a biofortified product with a high zinc content compared to other types of rice. This study aimed to obtain the best planting system and the number of seeds in increasing the growth and yield of Inpari IR Nutri Zinc. This study used a Divided Plot Design which was repeated four times. There was a total of 32 treatment combinations. The planting system (S) is placed as the main plot consisting of S1 (4: 1 Legowo Planting System) and S2 (Tile Planting System), while the number of seeds (J) as sub-plots consists of J1 (1 seed), J2 (3) seeds), J3 (3 seeds) and J4 (7 seeds). The planting system and the number of seeds had a significant effect on the variables of plant height, total tiller number, number of productive tillers, the weight of 1,000 seeds, panicle length, and rice production of Inpari IR Nutri Zinc. The use of seeds of 1 and 3 plants produced 4.74 and 4.60 tons/ha. The legowo 4: 1 planting system had 4.88
Channel noise modeling of deep submicron MOSFETs

This brief presents a new channel noise model using the channel length modulation (CLM) effect to calculate the channel noise of deep submicron MOSFETs. Based on the new channel noise model, the simulated noise spectral densities of the devices fabricated in a 0.18 /spl mu/m CMOS process as a function of channel length and bias condition are compared to the channel noise directly extracted from RF noise measurements. In addition, the hot electron effect and the noise contributed from the velocity saturation region are discussed.
New current feed back control method for solar energy inverter using digital signal processor

A solar energy inverter for photovoltaic power systems connected to electric utility lines has been developed. It is a power conditioner with a high-frequency transformer link for residential use at a power level of 3 kW. This paper describes a new synchronous current feedback control method using a digital signal processor (DSP). An adaptive finite impulse response filter is introduced into the control scheme. This paper also suggests a new method for detecting power outages. It gives frequent changes to the frequency of the inverter output voltage using a distortion of the inverter output current.
SHEAR STRENGTH OF PRESTRESSED CONCRETE BEAMS WITH FRP TENDON

本研究において, 非線形有限要素解析による数値実験により連続繊維補強プレストレストコンクリートはりのせん断耐力評価式を構築した. 本評価式は, 既に著者が提案した連続繊維補強コンクリートはりのせん断耐力評価式を, プレストレスカの影響を考慮し拡張したものである. 最終的に, 本評価式の妥当性が既往の実験結果と比較することにより示された.
Message Passing Based Calculation of MI and MMSE Matrix for Massive MIMO Systems With Finite-Alphabet Inputs

Under finite-alphabet inputs, the mutual information (MI) and minimum mean-square error (MMSE) matrix have no closed-form solutions, and numerical integrations, e.g., Monte Carlo simulation, endure prohibitive computational burden for massive multiple-input multiple-output (MIMO) systems. In this letter, we propose a new method based on the approximate message passing (AMP) algorithm for estimating the MI and MMSE matrix. By the new method, the computational complexity is reduced from <inline-formula> <tex-math notation="LaTeX">${\mathcal{ O}}(N_{\mathrm{ sa}}N_{r}N_{t}M^{2N_{t}})$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">${\mathcal{ O}}({N_{r}N_{t}})$ </tex-math></inline-formula> for a <inline-formula> <tex-math notation="LaTeX">$N_{r}\times N_{t}$ </tex-math></inline-formula> MIMO system, where <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> is the cardinality of the input and <inline-formula> <tex-math notation="LaTeX">$N_{\mathrm{ sa}}$ </tex-math></inline-formula> is the number of samples. Simulation results also demonstrate the effectiveness and high-performance of the proposed new method.
Seven Previously Unrecorded Fungal Species Isolated from Freshwater Ecosystems in Korea

Various freshwater ecosystems, such as streams, lakes and rivers, provide a dynamic habitat for fungi. In this study, we isolated several fungal strains from freshwater sediment and plant litter. The strains were identified using molecular phylogenetic analyses of rDNA and beta tubulin (TUB) sequences. Morphological characteristics of the fungi were also investigated using microscopy and culture characteristics of the fungi grown on several media. We identified seven species previously unrecorded in Korea, Nothophoma spiraeae, Westerdykella aquatica, W. aurantiaca, W. dispersa, Chrysosporium sanyaense, C.pseudomerdarium and Taeniolella phialosperma.
A Bayesian learning of probabilistic relations between perceptual attributes and technical characteristics of car dashboards to construct a perceptual evaluation model

Starting from a primary perceptual evaluation of a set of car dashboards, we propose to build a Bayesian network (BN) between perceptual attributes and design attributes. Two types of learning processes may be considered: supervised BN when the prediction on a targeted attribute must be optimised and unsupervised BN otherwise. These two types of BNs are considered along three design simulation scenarios: the direct scenario which consists of the prediction of a design change impact on customer perceptions, the inverse scenario for fixing design characteristics so as to result in an expected customer perception, and a more realistic combined scenario.
Frequency-Insensitive Rotor Position Estimation Method for Three-Stage Synchronous Machine Based on Indirect High-Frequency Signal Injection

A frequency-insensitive rotor position estimation method for the three-stage synchronous machine (TSM) in the starting procedure is proposed in this article, where the high-frequency signals (HFSs) are injected into the main exciter (ME), and response signals for the rotor position estimation are extracted from the main generator (MG). Due to the specific structure, the frequency of the response HFSs is distorted by the intermediate links of the ME and rotating rectifier, the frequency-response characteristics of the response signals with information of rotor position are analyzed, and the frequency-insensitive demodulation method for the rotor position estimation based on the second-order generalized integrator (SOGI) is given. Finally, the simulation and experiment results are implemented to verify the effectiveness and feasibility of the proposed frequency-insensitive rotor position estimation method for TSM.
A simple parallel architecture for discrete wavelet transform

In this paper, we present a simple parallel architecture for Discrete Wavelet Transform (DWT). Efficient computation of the pyramid algorithm for the computing of the discrete wavelet transform is possible due to the similarity between computation results of each octave. By using similarity, we separated the filter into 2 parts, an even filter and an odd filter. 1 octave and other octave computation are performed in the even and odd filters at the same time. The proposed architecture has following features. (1) Critical path is 1 multiplier and 1 adder; (2) the number of required registers is 1+J*([L/sub h//2]-1)+1+J*([L/sub 1//2]-1)+J, where J is the number of octaves, L/sub h/ is length of the highpass filter and L/sub 1/ is length of the lowpass filter.
ISOLATION, PURIFICATION AND CHARACTERIZATION OF ACTIVE COMPOUND FROM ANDROGRAPHIS PANICULATA L. AND TESTING ITS ANTI - VENOM AND CYTOTOXIC ACTIVITY BY IN - VITRO AND IN - VIVO STUDIES

Snake bite is a serious problem in tropical and subtropical countries like India with 5 mil lion human fatalities annually. The present study aimed on the shade grown Andrographis p aniculata L under organic condition. 6 month old plants were collected at dawn; shade dried and extracted with methanol, followed by fractionation to isolate the activ e compound and characterization of the active compound was done using FT - IR study which was found to be identified as andrographolide. Furthermore, in vivo and in vitro studies confirm the anti - venom property of the plant and the cytotoxic levels determin ed by the use of cell lines has its major start tow ards the cellular level study. These studies and investigations confirms the presence of cobra venom inhibiting factor whose bite pose a huge threat to the life of people. Commercializing the drug again st envenomation would prove successful in rural areas and the areas where the health centre is out of reach. Under economic circumstances, this study has the advantage of being very niggardly charged for the anti - venom preparation unlike the present day anti - venom that involves in rearing a horse and collecting the horse plasma that possess the raised anti - bodies which by further purification process would result in ASVS. Thus prepared ASVS holds the main disadvantage of bringing cross reactions like anaphyl axis and many more of the same sort. So, the plant as a drug would prove more effective, with high degree of safety and cost effective.
Every Book You Take: Evaluating Compliance Behavior In An Information Commons

There has been a heated debate related to the effects of business background on ethical behavior. According to some authors, students majoring in business courses – such as accounting, economics, and management – would be more likely to free ride or defect from coalitions in collective action situations, given the emphasis of such courses on individualistic values. Other authors have challenged that view, presenting empirical evidence that questions the link between business education and opportunistic behavior. The present paper revisits this debate, by studying the impact of business education on rule compliance in a specific type of information commons (libraries). Employing a novel dataset related to more than 700,000 library transactions during a 10-year period (2006-2015), I correlate business background with users’ compliance behavior, while controlling for their time-invariant characteristics. I find no evidence of a significant effect of business education on rule compliance in this specific setting. In fact, some of the estimates here reported suggest a negative correlation between business background and compliance behavior. These results have important implications for ethical theories in economics, suggesting that compliance behavior is context-dependent.