Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and Design of A Fully Soft Switched Two-Level DC-DC Boost Converter for Electric Vehicle Applications

In this paper, a fully soft switched two-level DC-DC Boost converter is proposed. The converter is used only one auxiliary cell to create the soft switching conditions for all semiconductor devices. The auxiliary cell contains one auxiliary switch, one resonant capacitor, one resonant inductor and one auxiliary diode. The auxiliary switch creates the soft switching conditions by control of resonant elements. Besides, the auxiliary cell is not located in the main power path and cannot decrease the converter efficiency. It has simple operation modes. Besides, the proposed softswitched converter is highly efficient while the control circuit is simple and remains PWM. Furthermore, the use of two-level structure in the proposed topology creates a converter with high gain. Based on the mentioned advantages, the proposed converter is a suitable candidate to use in electric vehicles. The theoretical waveforms, operation modes and simulation results are considered to show the good characteristics of the proposed converter.
Biological activity of Citrus paradisi peel

Citrus paradisi (Grapefruit) peel oil has medicinal properties which shows beneficial effects against plant pathogenic fungi Objective: The aim of this research was to investigate the antifungal potential of Citrus paradisi peel oil against different plant pathogenic fungal strains Methods: The essential oil of Grapefruit peel was provided in different concentrations 0.25 to 0.75ml per 100 ml of media to 3 different plant pathogenic fungal strains i.e, Fusarium oxysporum, Fusarium solani and Dreschlera tetramera and its effect on the growth of fungi was recorded Results: The studies provided the results compared with the controlled media, which showed the fungal growth was almost completely inhibited at 0.75ml concentration of oil, even the lower concentration was sufficient to retard the growth Conclusions: The study provided the blue print for fungicidal spray to cure serious diseases in plants, such as, rice blast, papaya fruit rot, seedling collar rot and wilt diseases.
Extreme Waves and Coastal Erosion Hazards, Communities Risk Perception and Social Vulnerability: Analysis of Two Villages in East Nusa Tenggara (NTT)

This study aims to examine risk perception and social vulnerability of two coastal communities in NTT namely Borokanda and Mautapaga. A quantitative method was applied to achieve the aim of this study. A primary dataset was collected through a structured questionnaire, which was responded to by a total of 110 households in these coastal communities. The differences between the coastal communities of Borokanda and Mautapaga, in social vulnerability and risk perception was analysed statistically using the Mann-Whitney U test. The results show that the coastal communities of Borokanda and Mautapaga have been identified to be significantly different in ethnicity, disaster experience, and disaster knowledge inherited from older generations. However, such indicators do not impact the differences between these coastal communities on social vulnerability and risk perception. A high score of social vulnerability index by the coastal communities of Borokanda and Mautapaga has been identified as the root cause of the low level of risk perception.
Autonomous Estimation of Patients’ Neuropsychological State Using Convolutional Neural Networks

The number of patients with neuropsychological problems is increasing rapidly in the world. Autonomous methods are replacing the traditional diagnosis methods in detection and classification of many mental and neurological problems. Machine learning algorithms and especially deep neural networks are able to diagnose various neurological and psychological complications automatically. In this paper, a machine learning based framework is used for autonomous estimation of patients’ neuropsychological state. The proposed framework can automatically diagnose neuropsychological state of the patients and present a personalized solution for their problems. A convolutional neural networks is used for automatic profiling of patients and to classify their mental state according to their EEG signals. The proposed framework can be used to help patients to have better life experience.
Intergroup interaction and attitudes to migrants

We report results from a randomized field experiment conducted in the Tigray region of Ethiopia, which tests the impact of interaction with migrants on host community members’ attitudes towards migrants. In three treatment groups, host community members were randomly paired with a migrant from a nearby refugee camp to play an incentivized guessing game. In the first of these treatments, the game was neutral in content, in the second it introduced subtle cues to economic matters, and in the third subtle cues to ethnic identity. In a fourth treatment, host community members were paired with other host community members to play the neutral game, and in the control condition host community members did not interact with anyone. The results show that, compared to the control group, interaction with a migrant significantly improved attitudes towards them. Subtle cues to economic matters or identity did not diminish this effect. However, we see similar effects on attitudes to migrants in the treatment group where hosts interacted with other hosts, which suggests that the effects are driven by human interaction in general, rather than by interacting specifically with a migrant. The effects of interaction are not much affected by the characteristics of the paired hosts and migrants, though host respondents in low skill occupations appear to respond more favourably to the treatments. Interestingly, however, we find no effects of the treatments on how migrants believe they are perceived by host community members.
Overcoming drug resistance in glioblastoma: new options in sight?

© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Overcoming drug resistance in glioblastoma: new options in sight?
ENVIRONMENTAL VULNERABILITY OF THE TROU DU NORD BASIN: A PRIORITY SUB-WATERSHED ANALYSIS VULNÉRABILITÉ ENVIRONNEMENTALE DU BASSIN DE TROU DU NORD: ANALYSE DES SOUS-BASSINS HYDROGRAPHIQUES PRIORITAIRES VULNERABILIDAD AMBIENTAL DE LA CUENCA DEL TROU DU NORD: ANÁLISIS DE SUB-CUENCAS PRIORITARIAS

The Trou Du Nord watershed has been ranked among the less vulnerable watersheds in Haiti by USAID according to five vulnerability indexes: Soil Erosion Potential, Population Vulnerability, Markets Vulnerability, Road Vulnerability and Irrigation Vulnerability. A similar ranking approach is downscaled here to characterize and rank sub-basins within the Trou Du Nord watershed, a basin where intensive industrial development is taking place at the Caracol Industrial Park (CIP) of northern Haiti. Our final objective is to establish a coherent reconnaissance-level approach for classifying sub-basin conditions, using a comprehensive set of indicators as proxies to the underlying ecological, hydrological, and geomorphic functions and processes that affect sub-watershed conditions. In other words, to establish how vulnerable those subwatersheds are to threats, especially to flooding. Prioritizing watersheds is based on ranking each of the sub-watersheds by their level of vulnerability and identifying which one has the most environmental concerns. We have identified population conglomerates, soil erosion, soil potential, and infrastructure replacement value as the key factors of vulnerability within the Trou Du Nord sub-watersheds and ranked them accordingly. Re-scaling a national level approach to a regional framework will account for regional risk factors linked to the CIP’s final objectives.
Resurvey reveals arrested population growth of the largest UK colony of European Storm-petrels Hydrobates pelagicus, Mousa, Shetland

The typical life history of long-lived seabirds makes their populations extra sensitive to decreases in adult survival. It is therefore important to uncover the extent, causes and consequences of any incident that involves massive die-offs of such species. Towards the end of a stormy winter, large numbers of dead Atlantic Puffins Fratercula arctica were beached in Vest-Agder and Rogaland counties, southwest Norway in February and March 2016. There were also reports of smaller numbers of birds found further north along the Norwegian coast, but it was not possible to assess the total extent of the wreck directly. The first birds stranded on 31 January, the day after the storm Gertrude (in Norway named Tor) caused the strongest winds ever recorded in Norway. Post-mortem examinations of 200 carcasses collected in the two counties over the following two months indicated that 59% of the birds were adults, whereas 9% were first-winter birds. Virological examination of three birds tested negative for Influenza A. All birds were emaciated and lacked significant fat deposits, and had presumably starved to death. Most birds, especially among adults, were in the last stage of primary moult, and had probably been flightless only a few weeks earlier. This may help explain why the different age groups were so disproportionately affected. The mean wing length of adults not in active moult indicated the birds originated mainly from colonies on the east coast of the UK. This conclusion was in accordance with the origins of eight ringed birds found dead in connection with the incident, seven of which were adults with a mean age of at least 21.6 years. It also fits well with results from recent tracking studies of birds with geolocators. The apparent survival of adult birds breeding on the Isle of May, southeast Scotland, was much lower between 2015 and 2016 than in most other years, which, unlike what has been possible for many other incidents, demonstrates that this wreck probably had a serious impact on the population level.
Efeitos da adubação com dejetos suínos, cama de aves e fosfato natural na recuperação de pastagens degradadas Effects of fertilization with pig manure, poultry litter and phosphate in the recovery of degraded

Resumo: O uso inadequado de areas exploradas pela atividade pecuaria tem sido uma das principais causas do declinio na fertilidade natural dos solos destas areas, o que leva a degradacao das pastagens. Uma alternativa que vem se destacando na busca da sustentabilidade na recuperacao dos solos degradados e a utilizacao de adubos orgânicos. O presente trabalho tem por objetivo expor pesquisas realizadas no Brasil com relacao ao uso de adubos orgânicos na recuperacao de pastagens degradadas. Tanto a utilizacao de adubacao orgânica como de fosfato natural tem se mostrado alternativas promissoras na recuperacao de pastagens degradadas em avaliacoes a curto prazo. Porem, verifica-se a necessidade de acompanhamentos a longo prazo do efeito do uso destas fontes, em especial aos adubos orgânicos, devido a dinâmica complexa destes adubos no solo e ao efeito que podem gerar no sistema. Palavras Chave: Recuperacao, Adubos Orgânicos, Pastagens Degradadas.
Wolf in sheep’s clothes: An uncommon case of pneumonic-type adenocarcinoma

Abstract We report a case of a patient who presented with clinical and radiological features of a non-resolving pneumonia. Special investigations and a poor response to antibiotic therapy excluded an infective aetiology. A diagnosis of invasive mucinous adenocarcinoma, previously termed bronchioloalveolar carcinoma, was made from lung biopsy. This case illustrates the challenges of establishing a timely diagnosis of an uncommon pneumonic-type of adenocarcinoma.
CPA Exam: Correlative Study of Preparation Activities and Exam Results

CPA exam candidate pass rates remain at 50-60% (AICPA 2019b). The purpose of this study was to determine whether there was an association between candidate preparation and exam results. This study investigated inspiration for becoming a CPA, work experience, education, study preparation and earning 150 credit-hours in relation to exam results. The scope was the State of Minnesota. The findings validated the flexibility in work experience and educational requirement guidelines from the AICPA and the State of Minnesota (AICPA 2020; MNBOA 2020). The findings showed 57% indicated CPA inspiration occurred during undergraduate studies while only 20.7% attributed it to faculty. A stronger relationship was found with exam results for those studying full-time while not working, using diverse study tools, and obtaining a higher level of education.
Reliability Analysis of Notched Plates under Anisotropic Damage Based on Uniaxial Loading Using Continuum Damage Mechanics Approach

Extensive recent researches have been underway to model the fracture mechanics degradation based on continuum damage mechanics (CDM) technique. CDM theory is a powerful tool for solving problems such as large plastic deformations that the fracture mechanics is unable to solve. This model is derived by means of the thermodynamics internal variable theory and based on the experimental results on material properties. In this paper, the reliability of rectangular plates containing a central circular hole under static tensile load using the CDM approach for ductile fracture has been studied. To investigate the initiation and evolution of damages, anisotropic damage expressed by second order damage tensor is used to derive constitutive equations. Then, these relationships together with material constants are implemented with subroutine in ABAQUS software. The reliability assessment has been investigated using first order reliability method (FORM) and second order reliability method (SORM). Based on the FORM and SORM, the limit state functions and random variables have been obtained according to the energy density release rate. The probability of failure of each plate with different hole sizes is estimated based on the anisotropic damage theory, and the results are compared with the isotropic damage model. Finally, the sensitivity analysis of the coefficient of variation is performed.
Eggplant Fruit (Solanum melongena L.) and Bio-Residues as a Source of Nutrients, Bioactive Compounds, and Food Colorants, Using Innovative Food Technologies

Consumers are very concerned with following a healthy diet, along with some precautions that may influence environmental impact. Solanum melongena L. is one of the most consumed vegetables due to its excellent nutritional value and antioxidant action. Associated with its high consumption, considerable amounts of agro-food wastes are produced. This work targets the valorization of this matrix, through the use of its bio-residues to study the obtention of coloring pigments, applying innovative technologies. Its nutritional value, chemical composition, and bioactive potential were evaluated, and the ultrasound-assisted extraction to obtain coloring pigments of high industrial interest was optimized. Considering the results, low contents of fat and carbohydrates and energy value were evident, as well as the presence of compounds of interest (free sugars, organic acids, unsaturated fatty acids, and phenolic acids). In addition, the antioxidant and antimicrobial potential was detected. Response surface methodology was performed to optimize the extraction of natural pigments, showing a concentration of 11.9 mg/g of anthocyanins/g of extract, applying optimal conditions of time, solvent, and solid/liquid ratio of 0.5 min, 68.2% (v/v) and 5 g/L, respectively. S. melongena proved to be a good source of bioactive compounds and natural pigments, which can generate great interest in the food industry.
DESIGN-THINKING: PRACTICE OF CUSTOMER EXPERIENCE RESEARCH

The purpose of our research is to find new tools for analysing hidden client needs (pains), regulating the sequence of reasoning when making decisions during the creation of innovative projects. We propose an approach of a creating a map of studying the customer experience of interaction with the product in which we can use Customer Jorney Map (CJM), method of triads and model PEDPL: Pre-Experience, Experience, Post-Experience, Lost-Experience). An important segment of model PEDPL is analysis “Lost Experience” when we can study new processes out-of-plane current business, an alternative to the use of a known product, expansion of functions, the reincarnation of the user experience in another plane, taking into account unrealized characteristics and interests of consumers (cultural characteristics, preferences, habits, traditions, etc.). This analysis can account for all patterns of the user experience in the product. This methodology puts in evidence new approaches to structuring information, which is important for immersing in user experience, understanding their problems and finding new solutions. Scientific novelty consists of proposed new tools for visualizing associative thinking, constructing a sequence of steps and methods for studying consumers, isolating the problem, developing an idea. The article presents a quest for the rector and the mayor, solving the problem: how easy and inexpensive to make a comfortable life of a short-sighted person in the city and University. In the preparation of the prototype used such methods of design thinking as the map of empathy, the method of the triad, CJM, PEDPL, SAP business origami. The results of the application can be in demand when developing a new Internet service or mobile application, or, for example, to develop a brand strategy, when it is important to explore the hidden needs of the client.
Diet Matters in Bladder Pain Syndrome and Interstitial Cystitis

Bladder Pain Syndrome/Interstitial Cystitis a medical condition that is challenging for both parties involved-the one suffering as well as for the one treating. One major part of the challenge is what the medical practitioner faces connected with the difficulty in detecting and diagnosing this condition. For the patient the challenge is about expressing their plight so that their problem is understood and then treated appropriately. Global figures say that takes approximately 10 years for a patient to get a diagnosis in place. There is also data to show that that patient usually go through evaluation by an average of 10 doctors before the problem gets identified and treated. Evidently, IC/BPS is a medical condition deserving better attention and understanding from all the stakeholders-the patient medical professionals and the family members.
Effects of Acrolein on Adrenal Glands

Aldosterone and cortisol, two major hormones secreted from adrenal glands, are vital to life by maintaining electrolyte, body fluid and energy homeostasis in human. Both of hormones are regulated precisely. Acrolein, the well-known cytotoxic agent released during the incomplete combustion. It abounds in the smoke of cigarette and in enclosed fires. Previous studies have demonstrated that smoking has the adverse effects on cardiovascular, nerve and other system. In particular, the pathogenic functions of tobacco inhalation in cardiovascular disorders as well as alters plasma electrolyte levels have been well documented. It is thus important to evaluate cellular/molecular mechanisms of smoking that change these responses. In a recent paper published in Steroids , we demonstrated that the major chemical in cigarette, acrolein, has the abilities to enhance aldosterone secretion and decrease corticosterone secretion. These effects may associate with the progression of cardiovascular and other diseases.
Deep neural networks in hydrology: the new generation of universal and efficient models

For around a decade, deep learning – the sub-field of machine learning that refers to artificial neural networks comprised of many computational layers – modifies the landscape of statistical model development in many research areas, such as image classification, machine translation, and speech recognition. Geoscientific disciplines in general and the field of hydrology in particular, also do not stand aside from this movement. Recently, the proliferation of modern deep learning-based techniques and methods has been actively gaining popularity for solving a wide range of hydrological problems: modeling and forecasting of river runoff, hydrological model parameters regionalization, assessment of available water resources, identification of the main drivers of the recent change in water balance components. This growing popularity of deep neural networks is primarily due to their high universality and efficiency. The presented qualities, together with the rapidly growing amount of accumulated environmental information, as well as increasing availability of computing facilities and resources, allow us to speak about deep neural networks as a new generation of mathematical models designed to, if not to replace existing solutions, but significantly enrich the field of geophysical processes modeling. This paper provides a brief overview of the current state of the field of development and application of deep neural networks in hydrology. Also in the following study, the qualitative long-term forecast regarding the development of deep learning technology for managing the corresponding hydrological modeling challenges is provided based on the use of “Gartner Hype Curve”, which in the general details describes a life cycle of modern technologies.
Design and Implementation of FlowGraph, a Distributed Framework for Temporal Pattern Recognition in Graph Data Structures

Graph data structures model relations between entities in many diverse application domains. Graph processing systems enable scalable distributed computations over large graphs, but are limited to static scenarios in which the structure of the graph does not change. However, virtually all applications are dynamic in nature, and this reflects to graphs that continuously evolve over time. Understanding the evolution of graphs is key to enable timely reactions when necessary. We address this problem by proposing a new model to express temporal patterns over graph data structures. The model seamlessly integrates computations over graphs to extract relevant values, and temporal operators that define patterns of interest in the evolution of the graph. We present the syntax and semantics of our model and discuss its concrete implementation in FlowGraph, a distributed framework for temporal pattern recognition in large scale graphs. We thoroughly evaluate the performance and scalability of FlowGraph with various workloads. FlowGraph presents a level of performance that is comparable to state-of-the-art graph processing tools when processing static graphs. In the presence of temporal patterns, it can further optimize processing by avoiding complex graph computations until strictly necessary for pattern evaluation.