Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Response of Saccharomyces Hosts to Totiviridae L-A dsRNA Viruses Is Achieved through Intrinsically Balanced Action of Targeted Transcription Factors

Totiviridae L-A virus is a widespread yeast dsRNA virus. The persistence of the L-A virus alone appears to be symptomless, but the concomitant presence of a satellite M virus provides a killer trait for the host cell. The presence of L-A dsRNA is common in laboratory, industrial, and wild yeasts, but little is known about the impact of the L-A virus on the host’s gene expression. In this work, based on high-throughput RNA sequencing data analysis, the impact of the L-A virus on whole-genome expression in three different Saccharomyces paradoxus and S. cerevisiae host strains was analyzed. In the presence of the L-A virus, moderate alterations in gene expression were detected, with the least impact on respiration-deficient cells. Remarkably, the transcriptional adaptation of essential genes was limited to genes involved in ribosome biogenesis. Transcriptional responses to L-A maintenance were, nevertheless, similar to those induced upon stress or nutrient availability. Based on these data, we further dissected yeast transcriptional regulators that, in turn, modulate the cellular L-A dsRNA levels. Our findings point to totivirus-driven fine-tuning of the transcriptional landscape in yeasts and uncover signaling pathways employed by dsRNA viruses to establish the stable, yet allegedly profitless, viral infection of fungi.
Performance Management Analytics for the Automotive Industry: An Empirical Study

The automotive industry is permanently collecting data about the business that is then used to calculate high level Key Performance Indicators (KPI) that are organized on a Performance Management System (PMS) to help on the decision making process. However, these KPIs represent uniquely the past. The business, in order to be proactive "i.e." create the future, must predict how it will be. Using Data Mining, Machine Learning, Statistics and Artificial Intelligence tis project creates and compares predictive models to acquire future values for KPIs.
Exploring Bystanders’ Privacy Concerns with Smart Homes in Jordan

Smart homes continue to raise concerns about privacy and encroachment of businesses into intimate spaces. Prior research has focused on families and device owners in western contexts (Europe and North America), and has identified the importance of bystanders: individuals who are subjected to smart device use of others. Given the cultural and contextual aspects of accommodating bystanders, we identify a gap where bystanders in non-western societies have been insufficiently researched. To address this we conduct 20 interviews with domestic workers and household employers in Jordan, exploring privacy attitudes and practices. Our analysis uncovers a complex interplay between religious and social norms; legal and regulatory perspectives on privacy; and tensions between households and their domestic workers. We explore issues arising from smart homes coexisting as a residence and workplace, and highlight how workplace protections are ill-suited. We structure our findings to help inform public awareness, policy makers, manufacturers, and future research.
CLUSTERING-BASED DISCRIMINATIVE SPARSITY PRESERVING PROJECTIONS FOR UNSUPERVISED FACE RECOGNITION

Recently, dimension reduction algorithms are widely applied to high-dimensional data preprocessing, especially for face images. In this paper, a novel unsupervised dimension reduction algorithm, named clustering-based discriminative sparsity preserving projections (CDSPP), is proposed by integrating cluster analysis and sparse representation analysis into a joint framework. Unlike many existing approaches such as sparsity preserving projections (SPP), where the constructive weights are computed by the classical sparse representation (SR), CDSPP introduces some class discriminant information by using clustering ﬁrstly, and CDSPP uses margin maximization criterion (MMC) to apply the discriminative information in the learning model. The obtained projections will contain more discriminant information than classical sparse subspace learning methods SPP. Moreover, CDSPP is an unsupervised dimensionality reduction method, which improves the simplicity of model training. Experiments on AR and Yale-B image datasets demonstrate its eﬀectiveness.
Use of organic acids in water and its effect on productive performance in broiler chicks

In order to evaluate the productive performance, gut health, pH, digestive morphology, blood pH, jejunum resistance (JR) and skin pigmentation (SP) on the employment of an additional mixture of organic acids (OA) into the water, in broilers from 1 to 42 days of age, 1080 chickens were used, distributed in three treatments with nine repetitions of 40 birds. The treatments used: non-acidified drinking water (pH 8) control group (T1), acidification with an OA mixture (formic acid 31%, propionic acid 19 %, ammonium format 26% and ammonium propionate 6%) in a dose of 1.0 L/1000 L of water (T2) to obtain a pH of 4, and 0.3 L / 1000 L of water (T3) for a pH of 6. The results showed (p≤ 0.01) higher body weight, lower feed intake, and better feed efficiency for the birds from T3. There were no differences (p≥ 0.05) on the values of digestive pH, SP, and intestinal morphology; only showed effects (p≤ 0.01) in the width of villi and in the digestive area. Blood pH and JR showed effects (p≤0.01) among treatments. It is concluded that the acidification of the drinking water in broiler chickens, with the OA mixture at 0.3 L/1000 L is sufficient to obtain better performance.
Application of genetic algorithm to hydrocarbon resource estimation

Resource estimation is a process by which the economically recoverable hydrocarbons (HC) in place within a reservoir are calculated. The parameter that goes into resource estimation is variable and contains some aspect of risks. Resource can be defined as the total volume of hydrocarbon in place, which is further classified as reserve when proved commercially viable. Reserve estimation can be carried out deterministically while resource estimation is done probabilistically. In this paper we have utilized a probabilistic approach using genetic algorithm (GA) for resource estimation. GA is an adaptive heuristic approach which uses an analogy to the mechanism of Darwin’s theory of natural selection. This paper discusses the basic structure of GA and its operators that is, encoding, reproduction and termination, followed by the application of GA to a synthetic model for estimating the oil initially in place (OIIP) and recoverable resource, using triangular and lognormal probability distributions. Key words: Genetic algorithm, resource estimation, crossover, mutation.
Screening of Toxigenic Aspergillus flavus Strains and Aflatoxin Content from Agricultural Commodities in Indonesia

: Infection of toxigenic A. flavus in agricultural commodities may result in production of aflatoxin, a mycotoxin which is genotoxic carcinogenic for humans and animals. The aims of this study were to screen toxigenic A. flavus strains and to determine aflatoxin content of six agricultural commodities in Indonesia. A total of 50 A. flavus strains were obtained from Phytopathology Laboratory, SEAMEO BIOTROP. The strains were isolated from nutmeg, corn, cacao, white pepper, coffee bean, ground peanut and peanut-cropped soil. The toxigenicity of A. flavus were determined bfy growth simulation on aflatoxin-inducing medium (10% coconut agar medium) followed by observation of their fluorescence using 365 nm UV light. AFB and AFG toxin produced were quantified using HPLC. The results showed that 18% (9 strains) A. flavus were toxigenic, which derived from nutmeg (5 strains), ground peanut (2 strains), cacao (1 strain), and peanut-cropped soil (1 strain). Six toxigenic strains produced AFB1 exceeding the Indonesian-regulatory maximum level (15 ug/kg). A. flavus from peanut-cropped soil (BIO 3352) produced the highest AFB1 content (90.94 ug/kg), while the other from nutmeg (BIO 3345 and BIO 33212), ground peanut (BIO 3313 and BIO 3338), and cacao (BIO 33404) had AFB1 content of 89.53, 84.24, 70.26, 40.27, and 69.06 ug/kg respectively. The producing aflatoxin capability of these strains can be potentially hazard if contaminated in agricultural commodities.
PUS: A Fast and Highly Efficient Solver for Inclusion-based Pointer Analysis

A crucial performance bottleneck in most interprocedural static analyses is solving pointer analysis constraints. We present Pus, a highly efficient solver for inclusion-based pointer analysis. At the heart of Pus is a new constraint solving algorithm that signifi-cantly advances the state-of-the-art. Unlike the existing algorithms (i.e., wave and deep propagation) which construct a holistic constraint graph, at each stage Pus only considers partial constraints that causally affect the final fixed-point computation. In each iteration Pus extracts a small causality subgraph and it guarantees that only processing the causality subgraph is sufficient to reach the same global fixed point. Our extensive evaluation of Pus on a wide range of real-world large complex programs yields highly promising results. Pus is able to analyze millions of lines of code such as PostgreSQL in 10 minutes on a commodity laptop. On average, Pus is more than 7x faster in solving context-sensitive constraints, and more than 2x faster in solving context-insensitive constraints compared to the state of the art wave and deep propagation algorithms. Moreover, Pus has been used to find tens of previous unknown bugs in high-profile codebases including Linux, Redis, and Memcached.
EFFECTIVENESS OF SPATIAL TRAINING IN ELEMENTARY AND SECONDARY SCHOOL: EVERYONE LEARNS

Visuospatial processing is key to achieve optimal performance in academic activities, among others. In the field of spatial cognition, it has been found that practice with spatial tasks can reduce the gender gap in this type of reasoning. However, an increase in spatial scores does not always compensate the differences that exist between participants with greater and lesser spatial abilities. According to previous studies on individual differences and malleability in spatial cognition, comparable studies are needed in children and adolescents using the same evaluation and training method. In this work, the evolution profiles across three sessions of a mental rotation (MR) training of 39 students from Primary Education (study 1: 17 boys and 22 girls) and 21 from Secondary Education (study 2: 11 boys and 10 girls) were analyzed, as well as the degree of improvement obtained based on result was replicated for both genders. This research will serve as a starting point to promote and implement adaptive and personalized training, and thus be able to help those with less spatial skills. These types of interventions would become more effective and could maximize educational potential among the most disadvantaged groups. on the study of a) visual function in patients with visual anomalies (refractive and functional), b) visuospatial processes and strategies, and c) plasticity of spatial abilities through training programs. selective (a) development of intelligence and personality tests, and in (b) statistical methods for data structural
Multidimensional Study on Users’ Evaluation of the KRAKEN Personal Data Sharing Platform

: Background: Recent advances in the design of blockchain-based personal data sharing platforms bring the beneﬁt of empowering users with more control and privacy-preserving measures in sharing data products. However, so far very little is known about users’ intentions to adopt such platforms for providing or consuming data products. Objective: This study aims to investigate users’ main expectations, preferences, and concerns regarding the adoption of blockchain-based personal data sharing platforms in the health and education domains. Methods: Fifteen participants were involved in a multidimensional evaluation of a prototyped release of the KRAKEN blockchain-based data sharing platform and asked to assess it in the health or education pilot domains. Data collected during online group interviews with participants were analyzed by applying the micro interlocutor technique to provide a descriptive overview of participant responses. Results: Participants showed a marginal acceptance of the prototype usability, asking for some improvements of the user experience and for a more transparent presentation of the platform security and privacy preserving capabilities. Participants expressed interest in using the platform as data providers and consumers as well as setting privacy policies for sharing data products with third parties, including the possibility of revoking access to data. Conclusions: Blockchain-based data sharing platforms are more likely to engage target users when technical design is informed by a deeper knowledge of their needs, expectations, and relevant concerns.
Cognitive Radio Sensor Network With Green Power Beacon

In this paper, we propose a cognitive radio sensor network with green power beacon (PB) to solve spectrum and energy scarcity problems in the resource-limited wireless sensor networks. In the proposed model, a PB node harvests energy from ambient sources and transmits the harvested energy to cognitive sensor node (CSN) through in-band energy transmission. The CSN uses the received energy to transfer its data to the sink. Resource-constrained condition of sensor network motivates us to deploy random spectrum access scheme to control the interference between primary and secondary networks, and also self-interference inside the secondary network (i.e., between the CSN and the PB). This spectrum access scheme benefits from low hardware complexity and energy consumption. Using tools from queueing theory, we analyze the service rate of the CSN and primary network for both limited-battery as well as infinite-battery CSN. Then, by optimizing the spectrum access parameters of the PB and the CSN, service rate of the CSN is maximized, while the quality of service (QoS) constraint of primary network is satisfied. For each energy harvesting rate and QoS constraint, it is determined whether energy or spectrum or both are limiting the performance of the CSN. This result can be used to adopt proper solutions for improving the performance of the network.
Exploiting the Development of Robotic Hands A Survey and Comparison on Different Technologies

In this paper, some considerations about the state­ of-the-art and the current trends in the design and mechanisms of robotic hands are reported and discussed. Several robotic hands with multiple degrees-of-freedom have been developed over the last two decades, mainly through the use of traditional means of action (e.g., electric actuators). This paper surveys the related work accomplished by the scientific community so far, focusing on the problems engendered by these often con­ flicting requirements, and the work that has been done in this area. Although there are many robotic hands projects, only a few have been addressing alternative technologies such as the use of Shape Memory Alloy.
이용한 Extracting multiple sentiment expression areas using BERT+CRF

감성분석이란 텍스트에 들어있는 의견이나 감성, 평가, 태도 등의 주관적인 정보를 컴퓨터를 통해 분석하는 과 정이다[1]. 감성분석과 관련된 주요 연구는 주로 긍정, 부 정으로 이진 분류 모델을 중심으로 이루어지고 있다. 하 지만 감성분석을 효율적으로 사회분야에 응용하기 위해 서는 긍정과 부정의 이진분류를 넘어 다양한 감성을 분 석할 수 있는 다범주 감성분석 방법론이 필요하다. 이와 같은 문제점을 보완하기 위해 특정 텍스트 데이터를 다 양한 레이블로 분류하고자 하는 시도들이 있었다[2,3]. 그 중 [3]의 실험에서는 기쁨, 슬픔, 두려움, 수치, 죄책감, 분노, 혐오 등 일곱 가지 감성을 분류할 수 있는 딥러닝 모델을 개발하여 진행했다. 딥러닝 모델로는 다층 신경 망(MLNN), 합성곱 신경망(CNN), 순환 신경망의 한 종류 인 LSTM을 이용하여 실험을 진행하였다. 다른 문제점으 로는 긍정과 부정, 즉 이중 극성이 동존하는 문장은 감 성 분석에 혼동이 생기는 문제가 있다. 이를 해결하기 위해 단어의 감성 점수 예측을 통해 감성 단어 등장 순 서를 고려한 감성 분석 모델을 제안한 실험[4]도 있었다. 언어 모델인 ELECTRA를 한국어 대용량 말뭉치로 사전 학습하여 활용하고, 단어의 감성 점수 예측 계층을 설계 하여 감성 단어 등장 순서를 반영하는 감성 분석 모델로 실험을 진행하였다. 하나의 문장 내에는 여러 종류의 감성들이 여러 개 존 재할 수 있고 이와 같은 문제들은 정확한 감성분석을 하 는데 문제점이 될 수 있다. 문장 내 여러 개의 감성들로 인한 문제점을 해결하기 위해서 본 논문에서는 하나의 문장을 하나의 감성으로 분석하는 기존의 감성 분석과 다르게 하나의 문장에서 감성 표현을 가진 영역을 구분 하여 각각을 개별적인 감성으로 보고자 한다. 즉, 감성이 드러나는 부분을 파악하여 서술어 중심의 구 혹은 절 단 위로 감성 표현 영역을 추출하는 모델을 개발하고자 한 다. 특성 감성 표현 영역을 추출한 후 감성 분석을 진행 하면 감성 분석의 모호함도 줄여줄 수 있고 더 정확한 감성 분석을 진행할 수 있다. 또한 리뷰 기반의 추천 시 스템에서 세부적인 영역별로 감성분석을 하여 추천의 정 확성을 높이는데 많은 도움이 될 수 있다.
EPJ manuscript No will be inserted by the editor Phase diagram of the Mott Transition in the two band Hubbard model in in nite dimensions

The Mott metal insulator transition in the two band Hubbard model in in nite dimensions is studied by using the linearized dynamical mean eld theory recently developed by Bulla and Pottho The phase boundary of the metal insulator transition is obtained analytically as a function of the on site Coulomb interaction at the d orbital the charge transfer energy between the d and p orbitals and the hopping integrals between p d d d and p p orbitals The result is in good agreement with the numerical results obtained from the exact diagonalization method PACS Fd Lattice fermion models Hubbard model etc a Strongly correlated electron systems heavy fermions h Metal insulator transitions and other electronic transitions
Handbook of Biological Wastewater Treatment: Design and Optimisation of Activated Sludge Systems

The scope of this comprehensive new edition of Handbook of Biological Wastewater Treatment ranges from the design of the activated sludge system, final settlers, auxiliary units (sludge thickeners and digesters) to pre-treatment units such as primary settlers and UASB reactors. The core of the book deals with the optimized design of biological and chemical nutrient removal. The book presents the state-of-the-art theory concerning the various aspects of the activated sludge system and develops procedures for optimized cost-based design and operation. It offers a truly integrated cost-based design method that can be easily implemented in spreadsheets and adapted to the particular needs of the user. Handbook of Biological Wastewater Treatment: Second Edition incorporates valuable new material that improves the instructive qualities of the first edition. The book has a new structure that makes the material more readily understandable and the numerous additional examples clarify the text. On the website www.wastewaterhandbook. com three free excel design spreadsheets for different configurations (secondary treatment with and without primary settling and nitrogen removal) can be downloaded to get the reader started with their own design projects. New sections have been added throughout: • to explain the difference between true and apparent yield while the section on the F/M ratio, and especially the reasons not to use it, has been expanded; • to demonstrate the effect of the oxygen recycle to the anoxic zones on both the denitrification capacity and the concept of available nitrate is explained in more detail. • the latest developments on the causes and solution to sludge bulking and scum formation • to show the rapid developments of innovative nitrogen removal and sludge separation problems • the anaerobic pre-treatment section is completely rewritten based on the experiences obtained from an extensive review of large full-scale UASB based sewage treatment plants • a new section on industrial anaerobic wastewater treatment • three new appendices have been added. These deal with the calibration of the denitrification model, empirical design guidelines for final settler design (STORA/STOWA and ATV) and with the potential for development of denitrification in the final settler. • A new chapter on moving bed biofilm reactors Handbook of Biological Wastewater Treatment: Second Edition is written for post graduate students and engineers in consulting firms and environmental protection agencies. It is an invaluable resource for everybody working in the field of wastewater treatment. ISBN: 9781780400006 (Print) ISBN: 9781780400808 (eBook)
Design of Air Quality Analysis Monitoring Using LoRaMOTE Developing Module

: Recent researches on LoRa Technology which provide the low power and long range over 20km have been very attractive. LoRa Technology is one of the most developing technology in modern communication link. The overall LoRa network comprises of the gateways, network servers and end nodes. The LoRa network that can be used for either star or mesh topology. The gateways are called as base station or concentrators and end devices are also called as motes in LoRa. LoRaWAN is a protocol specification which is only top of LoRa technology. It uses unlicensed radio spectrum in ISM band. However, the feasibility of LoraWAN for smart city application need to be investigated. Now a day air pollution is a major problem in every cities. Air pollution is not only an environmental problem but also a social problem. This paper provides the analysis of LoRaMOTE and developing module for air quality monitoring. The old method of monitoring air quality is time consuming, low precision and costly. Therefore, there is a need for continuous monitoring of air quality parameters in real time. Air quality parameters are measured by different sensors such as pH, humidity, temperature, PM sensor. The device has been tested in the city and the measurement was compared with the output of the pollution control authority stations.
On the real-time calculation of the forward kinematics of suspended cable-driven parallel robots

This paper addresses the problem of the forward kinematics of cable-driven parallel robots (CDPR) having elastic or non elastic cables under the assumption that the cables are submitted to small changes in their lengths compared to an initial situation at which the pose is known, a situation that is typical of a real-time forward kinematics used for control purposes. We show that at the initial point it is necessary to have not only the pose but also the cable configuration, i.e. having the knowledge of which cables are under tension and that the result of the forward kinematics should be both the pose and the cable configuration after the change in cable lengths. We exhibit a first algorithm that allows one to determine all possible final poses and cable configurations. Then a second algorithm is proposed to determine all possible cable configurations also during the coiling process which is an important point as the CDPR state, including the cable tensions, may drastically change at this point. The last algorithm assumes a model of the coiling process and is able to determine the unique final pose and cable configuration. These algorithms provide safer real-time forward kinematics which will improve the CDPR control
Circularly polarised filtering monopole antenna based on miniaturised coupled filter

This Letter proposes a circularly polarised (CP) monopole antenna with filtering function, which is achieved by integrating a miniaturised coupled filter based on the bent-loop resonators. The circular-polarisation is obtained by using the falcate-shaped patch as the radiation part, and the existence of the coupled filter in the feeding line would not affect the CP radiation performances. Both numerical simulation and experimental demonstration are performed for the designed CP filtering antenna, and good agreements are obtained. The designed antenna with dimension of 70 × 75 mm2 exhibits good frequency selective performances for the return loss, gain and axial ratio at 2.45 GHz with measured impedance matching bandwidth (|S 11| < 10 dB) of 0.23 GHz. Such CP filtering antenna is a good candidate for the emerging application area, e.g. wearable biotelemetric devices.