Miracle-dz/UniFAR-FTUs huggingface dataset:
Kaldi-Web: An Installation-Free, On-Device Speech Recognition System

Speech provides an intuitive interface to communicate with machines. Today, developers willing to implement such an interface must either rely on third-party proprietary software or become experts in speech recognition. Conversely, researchers in speech recognition wishing to demonstrate their results need to be familiar with technologies that are not relevant to their research (e.g., graphical user interface libraries). In this demo, we introduce Kaldi-web: an open-source, cross-platform tool which bridges this gap by providing a user interface built around the online decoder of the Kaldi toolkit. Additionally, because we compile Kaldi to Web Assembly, speech recognition is performed directly in web browsers. This addresses privacy issues as no data is transmitted to the network for speech recognition.
Inhibitory Impact of Nitrite on the Anaerobic Ammonium Oxidizing (Anammox) Bacteria: Inhibition Mechanisms and Strategies to Improve the Reliability of the Anammox Process as a N-Removal Technology

16 CHAPTER 1.INTRODUCTION 19 Nitrogen pollution 19 1.1. Regulations 21 1.2. Current biotechnologies for nitrogen removal 23 1.3. Conventional nitrification-denitrification processes 25 1.3. 1. Nitrification 25 1.3. 1.1. Denitrification 27 1.3. 1.2. N removal technologies based on nitrification-denitrification 28 1.3. 1.3. Anaerobic ammonium oxidation 33 1.4. Morphology and metabolism: 35 1.4. 1. Application and technologies based on Anammox process 38 1.4. 2. Biofilm based systems 41 1.4. 2.1. Suspended growth: 43 1.4. 2.2. Hybrid growth systems: 44 1.4. 2.3. Inhibition of the anammox process and consequences 45 1.4. 3. Acronym list 47 1.5. CHAPTER 2.OBJECTIVES 48 Aim 48 2.1. Specific Objectives 48 2.1.1. CHAPTER 3.INHIBITION OF ANAEROBIC AMMONIUM OXIDIZING (ANAMMOX) ENRICHMENT CULTURES BY SUBSTRATES, METABOLITES AND COMMON WASTEWATER CONSTITUENTS 50 7 Abstract 50 3.
Estimating expected shortfall using a quantile function model

Distribution of financial returns defined by the existing GARCH models usually focus on the overall features such as the location, scale, skewness and kurtosis of the distribution. When using such GARCH models for expected shortfall (ES) estimation, it is difficult to consider specific information about the tails (such as the shape of the tails of the distribution), resulting in possible bias in ES estimation. We propose a quantile function threshold GARCH model to overcome some of the limitations of existing models. The model allows us to use the information including the skewness and tail shape of the distribution and the structure changes in the volatility of financial returns to obtain ES estimates. Our results show that the proposed model outperforms the benchmark models, confirming that tail shape of the distribution also plays an important role in ES estimation.
Adapting to Local Context and Managing Relationships: A Case Study of a Multinational SDP Partnership in Bahrain

Abstract This paper considers the managerial process of a sport-for-development event in a geographic area that has rarely been investigated from a Sport for Development and Peace (SDP) academic perspective. Specifically, an examination of the relationships between multinational SDP organizations and a local SDP entity in managing and implementing an event in Bahrain is explored. Reflecting on the broader contextual aspects of the case, participant observation over 4 days and interviews with those involved from all organizations are used to reflect upon and build an understanding of how SDP management and relationships are localized in this regional setting. Initial findings indicate potential for further cooperation and expertise sharing between international organizations, with a particular need for understanding roles and partnership structures as well as being cognizant of local contexts and needs. Significantly, donor-recipient tensions are identified, and the positive impact of partnership-strengthening workshops are considered.
A Comparison Between Weakly-Compressible Smoothed Particle Hydrodynamics (WCSPH) and Moving Particle Semi-Implicit (MPS) Methods for 3D Dam-Break Flows

Lagrangian particle-based methods have opened new perspectives for the investigation of complex problems with large free-surface deformation. Some well-known particle-based methods adopted to solve non-linear hydrodynamics problems are the smoothed parti- cle hydrodynamics (SPH) and the moving particle semi-implicit (MPS). Both methods model the continuum by a system of Lagrangian particles (points), but adopting distinct approaches for the numerical operators, pressure calculation, and boundary conditions. Despite the ability of the particle-based methods in modeling highly nonlinear hydrodynamics, some shortcomings, such as unstable pressure computation and high computational cost remain. In order to assess the performance of these two methods, the weakly-compressible SPH (WCSPH) parallel solver, DualSPHysics, and an in-house incompressible MPS solver are adopted in this work. Two test cases consisting of three-dimensional (3D) dam-break problems are simulated, and wave heights, pressures and forces are compared with the available experimental data. The influence of the artificial viscosity on the accuracy of WCSPH is investigated. Computational times of both solvers are also compared. Finally, the relative benefits of the methods for solving free-surface problems are discussed, therefore providing directions of their applicability.
Screening of Diabetic Retinopathy and its stages using Deep Neural Networks on Retinal optical Images

Vision loss is also caused by Diabetic Retinopathy, being a consequence of Diabetes from which a vast portion of the world’s population is suffering. To automate the diagnosis of Diabetic Retinopathy we have presented two-stage Detection and grading system using Deep Neural Networks. For our analysis, we have made use of the publicly available dataset. On performing hyper-parametric variations in the architecture, we have been able to reach an accuracy of 97.46% to classify if it is a Diabetic Retinal Image or not. We have obtained an accuracy of 73% for classifying the different stages of Diabetic Retinopathy.
Impacts of The Invasive Seaweed Asparagopsis armata Exudate on Rockpool Invertebrates

The marine red algae Asparagopsis armata is an invasive species which competitive advantage arises from the production and release of large amounts of toxic compounds to the surrounding invaded area, reducing the abundance of native species. The main objective of this study was to evaluate the effects of this invasive seaweed on marine invertebrates by exposing the common prawn Palaemon elegans and the marine snail Gibbula umbilicalis to the exudate of this macroalgae. The seaweed was collected and placed in tanks, for 12 hours, in the dark in a 1:10 ratio. Afterwards the media containing its secondary metabolites was collected for further testing. Lethal and sublethal effects of A. armata were investigated. Biochemical biomarkers responses associated with energy metabolism (lactate dehydrogenase, LDH; electron transport system activity, ETS; content in lipids, proteins and carbohydrates) were analysed. The biomarker responses showed invertebrates’ physiological status impairment after exposure to low concentrations of this algae exudate. Highest concentrations of exudate significantly increased lipid content in both organisms. In the shrimp, protein content, ETS, and LDH were also significantly increased. On the contrary, these parameters were significantly decreased in G. umbilicalis. A behavioural impairment was also observed in G. umbilicalis exposed to A. armata exudate, with reduction in feeding consumption. These results represent an important step in the research of natural toxic exudates released to the environment and prospective effects of this seaweed in invaded communities under increasing global change scenarios.
Entrepreneurship or Paid Employment: The Post-School Job Preference of Undergraduates in Nigerian Public Universities

Post-graduation employment has been of great concern to students, teachers, and parents. This is because of the stiff competition in the contemporary labour market. The job preference of students informs their post-graduation expectations and interests. This study, therefore, assessed the post-school job preference of undergraduates in Nigerian public universities using the survey approach of quantitative design. The population was the six south-west states of Nigeria having 17 public universities in the zone, and comprising of 12,890 male and 13,966 female final year undergraduates of the universities. Using the simple random sampling technique, three public universities were selected. Furthermore, 1,500 final year undergraduates were selected using the criterion purposive sampling technique. The Undergraduates’ Job Preference Scale (UNJOP-S), a 20-item questionnaire, was designed and administered. Descriptive and inferential statistics were used to answer the research question and hypothesis respectively. The study found that paid employment was the most preferred job of undergraduates. It equally showed a significant relationship between entrepreneurship education and measures of undergraduates’ job preference. Consequently, entrepreneurial content should be incorporated in every discipline to shape the undergraduates’ job preference towards entrepreneurial endeavours after graduation, as this will change their orientation for entrepreneurial activities and facilitate the school-to-work transition.
Trait-based Measure of Dehumanization: Adaptation for the Portuguese population

Although dehumanization (i.e., the denial of full humanness to others; Haslam, 2006) has been a frequent subject in social psychology, a set of traits designed to evaluate this phenomenon has not been validated to the Portuguese population. The main purpose of this study was to translate, culturally adapt and validate a set of dehumanization traits proposed by Haslam and colleagues (Haslam & Bain, 2007; Haslam, Bain, Douge, Lee & Bastian, 2005), which measure both the denial of uniquely human and human nature traits. A sample of 597 individuals (Mage = 40.83; SD = 11.50) were asked to rate a set of 52 traits on how much they perceived each as a characteristic of human nature and human uniqueness, as well as its desirability. T-tests were conducted to distinguish between low and high rated traits in each dimension, and to construct clusters of traits that differ in each dimension. We successfully provide a measure containing positive traits in both senses of humanness dimensions; however, we were only able to validate a human uniqueness measure with negative valence. Implications of this measure for future research on dehumanization processes are discussed.
Pre-Service Teachers’ Perceptions of Blended Learning on Mathematics Learning Based on Gender

The research aims to analyze pre-service teachers’ perceptions about the application of the blended learning model in mathematics learning. The total research subjects were 254 pre-service teachers from 12 different universities in Indonesia. Furthermore, this research method is a survey with a qualitative approach where data are analyzed using the Rasch Model (WinSteps). The instrument of this study was a questionnaire consisting of 20 statements and divided into four indicators. Based on the wright maps table on WinSteps, women pre-service teachers prefer the blended learning model in learning mathematics than men pre-service teachers. Meanwhile, when viewed in terms of grade, fourth year pre-service teachers like the application of the blended learning model the most. In addition, it is also known that the most disliked thing in understanding mathematics by using blended learning is the difficulty to access assignments online and it requires internet quotas.
Variability in Reaction to Root and Crown Rot Caused by Rhizoctonia Solani Among Table Beet Cultivars, Breeding Lines, and Plant Introductions in Controlled Environment Conditions

Table beet (Beta vulgaris ssp. vulgaris) is adversely affected by the soilborne fungus, Rhizoctonia solani, which greatly decreases root quality. There are no reports of breeding efforts designed to improve resistance to this fungus in table beet. A collection of table beet PIs, cultivars, and publicly available inbreds were characterized for their response to inoculation with R. solani in three replicated greenhouse experiments conducted between 2017 and 2019. An isolate of AG 2-2 IIIB was used to inoculate 8-week old plants, and both susceptible and resistant sugar beet genotypes were used for comparison. Plants were evaluated for internal and external disease characteristics 3 and 5 weeks postinoculation. Compared with uninoculated controls, PI accessions ranged from 2% to 44% infection, whereas cultivars and inbred lines ranged from 16% to 53% and 22% to 52%, respectively. No commercial cultivar outperformed the resistant sugar beet genotype; however, several PI accessions exhibited lower mean diseased tissue percentages than the resistant sugar beet. This suggests that resistance to R. solani may exist in table beet germplasm. PI accessions exhibited greater resistance on average than did cultivars. Inbred lines exhibited the least amount of variation. Ordinal regression allowed for prediction of infection response, which may be helpful in future selection efforts. ‘Badger Flame’, Ames 22164, PI 502294, PI 169015, ‘Long Season’, ‘Red Cloud’, and ‘Albina Vereduna’ were some of the most resistant accessions in our screens. The findings from this study can be used to inform decisions for breeding for host plant resistance in table beet.
Reflections and Results from the Intersections: Teaching and Learning the Praxis of Intersectionality in the Psychology Classroom

This article bridges multiple ways of knowing to explore the experience of an undergraduate psychology class focused on intersectionality. Drawing on feminist pedagogy, intersectionality, and critical consciousness literatures, we, the instructor and students together work to understand the experiences of the course and to offer our lessons learned. We present a detailed structure of the course, Experiences of Intersectionality, results of a qualitative analysis of students’ written course reflections, and instructor reflections. Three themes were extracted from the data: Vulnerability and Privilege, “Small Slaps in the Face,” and Empathy and Action. The discussion of the findings includes reflections from the course instructor and applications to praxis, particularly for educators.
Process matters: from car owner experiences to automotive design proposals

Collecting and analysing user experiences, communicating discovered patterns, translating information into design proposals and materialising designed features is central to design driven research. This process immerses design teams into all aspects of users’ experiences, helping them empathise with and scrutinise every detail until designers own the experiences and produce design proposals addressing end users’ needs in unique ways leading to disruptive innovation. Design practice’s strength is crystallising solutions into visualised and interactive proposals, presenting in-depth details of the look, feel and emotions they stimulate, and assisting decision making in product, service and business innovations. Existing research focusses on early stage collection of lived user experiences and final visualisation of the design proposal, yet seems to miss detailed discussion of the core bridging of user experiences and precise design proposals. We describe optimising a process supporting designers continuously switching between gathering user experiences and industry/market contexts when generating automotive design proposals.
Near-Field Propagation Analysis for Vivaldi Antenna Design: Insight into the propagation process for optimizing the directivity, integrity of signal transmission, and efficiency

Refined optimization of complex curve–linear-shaped radiators, such as traveling-wave Vivaldi antennas, can be achieved by considering simulated near fields to interpret in detail the structural influences of a design. The relationships between the space and time distributions of electromagnetic (EM) energy clusters and the geometric features are revealed with appropriate use of impulse response analysis combined with the multiple signal classification (MUSIC) algorithm. This article reports a deeper approach when applied to the adjustment of the geometric features of a traveling-wave antenna based on an analysis of near-field propagation features.
A Multi-Objective Train Operational Plan Optimization Approach for Adding Additional Trains on a High-Speed Railway Corridor in Peak Periods

Passenger demand for railway transportation rapidly increases in peak periods, and the transport capacity for existing trains is not sufficient. Railway companies usually adopt the strategy of adding additional trains in peak periods to meet the higher passenger demand. Designing a good operational plan for additional trains becomes a challenge for operators, though. A new optimization approach for designing an operational plan for additional trains is proposed in this paper. The number of trains, the operational plan, the stop plan, and the timetable for each train can be considered simultaneously in the new optimization approach, which will make it easier to design an operational plan for additional trains. A multi-objective nonlinear model with three objectives of minimizing total running distance, dwelling time, and unsatisfied passengers is proposed. Big-M is introduced to transform the nonlinear model into a linear model. The solver CPLEX is used to solve the transformed linear model and obtain the optimal operational plan. Small-scale numerical experiments are implemented to show the effectiveness of the optimization approach. The large-scale case of the Beijing‒Shanghai railway corridor is studied to demonstrate that the optimization approach can be applied to real-word and large-scale situations.
Operational Performance and Degradation of PV Systems Consisting of Six Technologies in Three Climates

In Indonesia, the solar photovoltaic (PV) market is rapidly growing. However, studies on the outdoor performance of PV systems in this tropical rainforest country is lacking. In this work, we compare the performance of PV systems in Indonesia with PV systems in Australia (arid, desert, hot) and Italy (temperate, dry summer, hot summer). Monitoring data from 2008 to 2019, ranging from two to nine years, from fifteen PV systems of six technologies were analyzed. The performance of the PV systems was presented using their performance ratio (PR) and performance loss rate (PLR). PR was calculated using IEC standard 61724, and PLR was calculated using seasonal and trend decomposition, applying locally weighted scatterplot smoothing (STL decomposition) and the year-on-year approach from NREL/RdTools. The results showed that the CIGS (copper indium gallium selenide) system had the highest average PR value of 0.88 ± 0.04. The lowest average PR was found in the a-Si (amorphous silicon) PV systems (0.78 ± 0.05). The p-Si (polycrystalline silicon) systems in the Cfb (temperate, no dry season, warm summer) climate of Italy had a higher average PR of 0.84 than those operated in climates BWh (arid, desert, hot) of Australia and Af (tropical, rainforest) of Indonesia, with the same value of 0.81. The p-Si systems showed the lowest PLR, with a value of −0.6%/year. The fastest degradation was experienced by a-Si modules at −1.58%/year. The methodological differences in the calculation of PLR using both tested approaches resulted in a significant difference in the degradation value, which demands standardization of the term and calculation methodology.
Occurrence of visible losses and relationship with corn silage management in dairy farms in the State of Paraná

The aim of this study was to relate the occurrence of visible losses in silage (effluent, spoiled top-layer and during feedout) with silage-making practices, physical and chemical characteristics of silage, and milk composition in Brazilian dairy herds. One-hundred and eight silos from 95 farms, in the State of Parana, were visited for data collection. Data were analyzed by Fisher's Exact and Pearson Correlation Test. Effluent loss was higher in silages with the lowest dry matter content. Using unwalled clamp (drive-over piles) silos, neglecting a protection over the plastic film, and unloading silage with a bucket increased the occurrence of top spoilage. Feedout losses were higher in farms where: the crop was harvested with self-propelled machines; the particle size was larger, and the silage density was lower. There was no relationship between visible losses and silage composition or milk composition, except for milk fat content that, unexpectedly, there was a positive correlation with spoiled silage in the top-layer. Silage losses are reduced by adopting good practices during silage production and feedout.
Development of the kit for diagnostics of COVID-19 by real time RT-PCR

Late in December 2019, an outbreak of an unknown coronavirus, later identified as SARS-CoV2, emerged in the city of Wuhan, China. It causes a dangerous respiratory coronavirus disease in humans — COVID-19. Objective. To detect cases of the disease and prevent its spread across the Russian Federation it is necessary to create an effective diagnostic test system. Material and methods. Based on the analysis of the alignment of the SARS-CoV-2 nucleotide sequences, primers and a probe for RT-PCR were selected, and the analysis conditions were optimized. Results. The diagnostic system was developed and registered in the shortest possible time in real-time RT-PCR format for detecting SARS-CoV-2 coronavirus RNA in smears from the nasopharynx and oropharynx, sputum and feces. The high specificity of the system was verified on a representative set of viruses and microorganisms, the analytical sensitivity was 1x103 copies / ml in smears from the mucous membrane of the nasopharynx and oropharynx and sputum, 5x104 copies / ml in fecal samples. Diagnostic sensitivity and specificity established during clinical trials on samples from patients with confirmed COVID-19 infection, from patients with a different etiology of a disease and clinically healthy people were to 100% (range 94.2-100% with a confidence level of 95%).
Dictionary of disease ontologies (DODO): a graph database to facilitate access and interaction with disease and phenotype ontologies

The formal, hierarchical classification of diseases and phenotypes in ontologies facilitates the connection to various biomedical databases (drugs, drug targets, genetic variant, literature information.). Connecting these resources is complicated by the use of heterogeneous disease definitions, and differences in granularity and structure. Despite ongoing efforts on integration, two challenges remain: (1) no resource provides a complete mapping across the multitude of disease ontologies and (2) there is no software available to comprehensively explore and interact with disease ontologies. In this paper, the DODO (Dictionary of Disease Ontology) database and R package are presented. DODO aims to deal with these two challenges by constructing a meta-database incorporating information of different publicly available disease ontologies. Thanks to the graph implementation, DODO allows the identification of indirect cross-references by allowing some relationships to be transitive. The R package provides several functions to build and interact with disease networks or convert identifiers between ontologies. They specifically aim to facilitate the integration of information from life science databases without the need to harmonize these upfront. The workflow for local adaptation and extension of the DODO database and a docker image with a DODO database instance are available.