Miracle-dz/UniFAR-FTUs huggingface dataset:
A Kind of Parallel Evolutionary Algorithms and Its Application in E-Business

Parallel Genetic Algorithms (PGAs) were used to simultaneously optimize the structure and weights for feedforward neural networks. Aiming at its large-scale application in common distributed network system, a concentrative coarse-grained model for parallel evolutionary neural networks is designed and realized in a laboratorial distributed computation environment, and the initial results of experiments indicate that the parallel model can quicken the searching process and improve the evolutionary efficiency. For the parallel characteristics, this method can analyze massive information during the process of e-business. Several application scopes of this method in e-business are discussed also in this paper .
Croatia WHAT KIND OF MO(VE)MENT IS FRIDAYS FOR FUTURE? MOTIVATION, SUCCESS PERCEPTION AND CLIMATE ACTION FRAMING IN FRIDAYS FOR FUTURE

2022. ABSTRACT Fridays for Future climate protests, which began as individual actions, soon morphed into a powerful global youth movement, with millions participating in Global Climate Strikes in 2019. In this study, we conducted 19 semi-structured interviews with the organizers and participants of the Fridays for Future Croatia movement and we aimed to examine the main characteristics of these protests in the context of new social movements theory and contemporary movements research, as well as in the specific national context. Challenging the suitability of the new social movements theory to adequately explain the Fridays for Future movement, we found many connections with contemporary social movements: participants are a new generation of first-time activists; social media use is crucial and qualitatively different; the organisational structure is completely loosened; and the issues encompass environmental protection and political economy, urging the transformation of both individual and social identities and socio-economic
Relationships of Learning Environment, School Type and Secondary School Students' Academic Achievement Marakwet East Sub-County, Kenya

: This study was developed purposely to investigate the relationships between learning environment, secondary school type and students' academic achievement in secondary schools located in Marakwet East Sub-County, Kenya. The study aimed at providing answers to the research questions; what is the relationship between learning environment and students' academic achievements? What learning environment exists in Marakwet East Sub-County? What is the level of academic achievement of public secondary schools in the Sub-County? Are there relationships between school learning environment, school type and secondary school students’ academic achievements? The study adopted the theory of socio-cultural theory of Lev Vygotsky (1978) that beliefs that parents, caregivers, students' peers and the peoples' cultural heritage are responsible for all human development. It also assumes that most human learning take place in processes or steps and requires being a social venture. This takes learning as a social matter. Educationists Piaget and Boyle (1994) believed that learners are constructors of their own purposeful reality, knowledge, and understanding of many varied things and experiences and therefore reflecting on their own experiences. The research adopted mixed embedded methods of research that combined use of quantitative and qualitative designs. The study targeted 18 secondary schools, 18 directors of studies, and 140 teachers across the area. The study used stratified and simple random sampling techniques. Data collection was done using; questionnaires, in-depth interview guide, document analysis, checklist and observation. These instrument results were subjected to content validity in order to remove ambiguities. Two secondary schools were piloted. Test-re-test as used to obtain reliability of the instruments' results. The researcher analyzed qualitative data thematically and presented using in-depth explanations, narratives and verbatim. The study findings showed that secondary schools for boys had better teaching and learning environments while mixed day schools had unsupportive physical learning environments. This indicated that boys' only schools did better that either girls or mixed schools. The study concluded that learning environment and school type affected students' academic achievement. The study recommended for adequate funding to support physical development, resources mobilization, equipment, social and other learning environment resources. The study implores education stakeholders to pull resources for enhanced secondary school students' academic achievements. academic achievements marks or that are earned by after for Certificate of Secondary Examinations (KCSE). Continuous tests or examinations are widely used to students’ academically. How it should be is a of discussion without end. conducted a study that investigated the relationships between physical environment and academic achievement in public secondary schools in Nairobi City County, Kenya. Does the settings where learning occurs matter?
STATUS AND PROGRESS OF FOIL AND TARGET FABRICATION ACTIVITIES FOR THE PRODUCTION OF 99 MO FROM LEU

Argonne National Laboratory has produced most of the hot-rolled uranium foils used in experiments to produce 99 Mo from LEU-foil targets. We are working with the Indonesian BATAN and several other members of the IAEA coordinated research project (CRP) on “Small-Scale Indigenous Production of 99 Mo Using LEU Targets or Neutron Activation” to develop their own capability to roll foils. This paper details the foil fabrication and other activities at Argonne, in particular, (1) characterization of direct-cast foils supplied by KAERI as an alternative to Argonne’s hot rolled foils and (2) a high-level, preliminary study of the requirements (equipment and footprint,) related to producing rolled foil and targets for industrial-scale production of 99 Mo using the Argonne annular LEU-foil target. Preliminary findings do not eliminate the feasibility of using the direct-cast foils for demonstration purposes.
Hardware Support for Irregular Control Flow in Vector Processor

As data parallel processors grow in popularity, so too does their desired range of applications. If this growth is too continue, data parallel processors must be able to support regular as well as irregular data parallelism. In light of this fact, this paper presents an implementation of a vector processor that can handle data parallel applications that exhibit irregular control ﬂow. In particular, I start with a single threaded pending vector fragment buffer(PVFB) design which I then extend to a multithreaded PVFB design. Through an extensive design space exploration of various microarchitectural alternatives, I evaluate the efﬁciency and performance of my system. My results indicate that a multithreaded PVFB design with 8 threads and 64 µThreads per thread maximizes performance while minimizing the area overhead.
Synthesis of Surfactant-Modified Activated Carbon (SMAC) Above Critical Micelle Concentration as Cr(VI) Ion Adsorbent

The synthesis of surfactant-modified activated carbon (SMAC) has been widely studied. However, no research has been conducted to study SMAC concentrations higher than the critical micellar concentration. Therefore, in this study, SMAC was synthesized using anionic and cationic surfactants above CMC (Critical Micelle Concentration) and compared with SMAC below CMC and coconut husk-based activated carbon. This study aimed to determine the surface profile of SMAC and the characteristics and mechanism of metal ion adsorption by SMAC. The selected metal ions were Cr(VI) cations and NH4+ cations as a reference. SMAC was prepared by modifying coconut shell-based activated carbon with anionic surfactant SLS (Sodium Lauryl Sulfate) and cationic surfactant HDTMA-Br (Hexadecyl Trimethyl Ammonium Bromide). Modification of SMAC was performed by three different methods: (a) activated carbon was added gradually with SLS followed by HDTMA-Br, (b) activated carbon was added with HDTMA-Br followed by SLS, (c) activated carbon was mixed with SLS and HDTMA-Br simultaneously. All synthesized SMAC were characterized using FTIR, GSA (Gas Sorption Analyzer), and zeta potential. The FTIR analysis results showed that the synthesized SMAC comprised S=O and (CH3)3N+ groups derived from surfactants. GSA analysis revealed that SMAC has a surface area of 36.790 m2/g, and it was more stable than activated carbon according to the zeta potential result. In this study, the efficiency of SLS and HDTMA-Br in synthesizing SMAC was 99.98% and 95.85%, respectively. SMAC synthesis using method c resulted in Cr(VI) adsorption efficiency of 93.50% and NH4+ adsorption efficiency of 87.37%. In comparison, SMAC below CMC has adsorption capacities of 93.41% for Cr(VI) and 85.05% for NH4+, respectively, whereas Cr(VI) adsorption efficiency by coconut shell-based activated carbon was 99.98%.
Influence of agricultural cultivation methods on the physicochemical and colour parameters of Florina apples during storage in conventional refrigerated rooms

Dobrevska, G. Ivanova P. & Dallev, M. (2022). Influence of agricultural cultivation methods on the physicochemi cal and colour parameters of Florina apples during storage in conventional refrigerated rooms. Bulg. J. Agric. Sci., 28(3), 534–540 The scientific experiment was conducted at the Department of Food Technology at IFPQ-Plovdiv with the aim of assessing the impact of three-month refrigerated (1-4°C) storage on the physicochemical and colour properties of biologically and con ventionally cultivated Florina apples. The assessment is made on the basis of dry substance content, %; antioxidant activity measured in µmolTE/100 g; total polyphenols content in mg GAE/100g and colour properties – brightness and intensity of the red/green and yellow hues – as measured by the CieLab system.
Binge Eating Disorder and Major Depressive Disorder: Potential Overlaps in Mechanisms and Treatment

Many patients with Binge Eating Disorder (BED) also suffer from Major Depressive Disorder (MDD). This paper discusses potential relationships and overlaps between binge eating disorders and depression. It is interesting to find that patients with these two kinds of disorders share distorted thoughts, maladaptive behaviors, poor connections with other people, and the inability to effectively regulate their emotions. Because of the multiple overlaps between BED and MDD, and the variety of studies that demonstrate the effectiveness of Cognitive Behavioral Therapy and Interpersonal Psychotherapy in their treatment, the implication of this article is that treating these two disorders together might lead to a better treatment outcome. It is really crucial to understand the underlying associations and overlapping comorbidities between BED and MDD during treatment.
A Multimodal Strategy for Singing Language Identification

Identification of the language of performance of songs is important for applications such as personalized recommendations, discovery, and search. In this paper, we present an automated multimodal approach to identify the singing language of songs that scales to millions of songs. The proposed model uses a variety of song-level features, including a consumption embedding derived from sessions listening data from a music streaming service, segment-level vocals embedding computed from the vocal track of a song, and generic timbral features. Our experimental results show that our approach outperforms benchmark models in the signing-language identification task, and demonstrates the benefit of the multimodal approach through an ablation study. In addition, we present a data augmentation technique to increase the robustness of the model to missing data modalities.
AIRSAR Wish List

– AIRSAR has served as a test-bed for both imaging radar techniques and radar technologies for over a decade. In fact, t h e polarimetric, cross-track interferometric, and along-track interferometric radar techniques were all developed using AIRSAR. In this paper, w e discuss the improvements and upgrades we would like to pursue if we had the necessary funding and workforce.
Successfulness of the Bakri Intrauterine Balloon For Uterotonic-Unresponsive Postpartum Haemorrhage Treatment: Systematic Review and Meta-Analysis.

The main purpose of this meta-analysis was to quantify the successfulness of Bakri balloon in managing postpartum haemorrhage (PPH) unresponsive to uterotonics. We performed a literature search using the MEDLINE (accessed via PubMed) database from inception to October 2019, for clinical trials and observational studies. Meta-analysis was performed applicating the random-effects model. Primary outcome was the successfulness of the Bakri balloon in stopping PPH unresponsive to uterotonics. Twenty-eight publications (n=1868 applications of Bakri balloon) matched the inclusion criteria for the meta-analysis. Ten studies referred the incidence of Bakri balloon applications with a 0.335% (1004/299124; 95% CI, 0.2–0.4%) rate. Success rate of the haemostatic balloon in stopping PPH without requiring other procedures was 82% (1597/1868; 95% CI, 78– 86%), while further procedures were needed for 271 patients (13,83%; 95% CI, 11–21%). Bakri balloon plus additional procedures were effective in the control of the PPH in the 95% of all cases (1645/1868; 95% CI, 93–98%). Hysterectomy was performed in the 5% (78/1597; 95% CI, 2–6%) of all women who needed a Bakri balloon. Bakri balloon represents a successful therapeutic option for blocking PPH when unresponsive to uterotonics.
The Role of Human Resource Policies on Work Life Balance Among Information Technology Sector of Women Professionals

Work life balance is the relationship between, how much time and effort someone spends to work and how much time and effort spend to other elements of their life, such as family, children, friends etc., HR policies are the organization’s continuing guidelines for managing its employees. As in this study, it mainly focuses on what are all roles played by the human resource department on balancing work and life in the Information Technology sector of women professionals. For this research, descriptive research was done with a sample of 200 women professionals from selected IT companies in Chennai using simple random sampling technique. The questionnaire was created using the independent variable of HR policies on work life balance and mediator of continuance commitment with a dependent variable of work life balance. The statistical tools used in this study are CFA, Discriminant validity and Composite reliability with the assistance of SPSS and AMOS software. The research found that, all the item used in the study are reflect a good measure of the variables.
A Model with Endogenous Programme Participation

This paper provides new estimates of the impact of the French tax credit on the employment outcomes of women. We model simultaneously the employment probability and the determinants of programme eligibility. We improve on earlier studies in this ﬁeld that, using a single evaluation equation framework, predicted ex-ante programme eligibility. Within this framework, we also allow for hours responses. The data for the analysis are drawn from the French labour force surveys of years 1999 to 2002. We ﬁnd no signiﬁcant impact of the tax credit on either employment or hours of French women.
Augmented Reality Mobile Tool for Engineering Education

This paper falls under evidence-based practice analyzing the effectiveness and usefulness of Augmented Reality (AR) in engineering education practices via a mobile device and includes the design and implementation rationale of the AR-based mobile tool and its assessment through a survey. Researchers have claimed that traditional education needs to be supplemented with innovative tools and suggested that AR-based education enhanced learning. AR can be particularly helpful in learning about the structures of complex models. The use of complex physical equipment/replicas poses a challenge in teaching due to their cost, limited quantity, accessibility, and safety issues. Therefore, AR app-based learning using easily accessible smartphones in the digital world today can be a better choice for smart and effective learning. Moreover, it will have more significance with increasing online studies in the current pandemic scenario. In this paper, an AR mobile tool prototype developed for engineering education is discussed. The app includes limited opensource 3D models, interaction abilities, teaching content, and quiz feature and was evaluated with a survey. This paper will introduce the project, present an overview, design framework, implementation process, testing, and survey results. The survey results show that the app is effective and useful in learning.
Evaluating Biomedical Event Extraction on a generative language model using TANL

Every year more than 1 million biomedical papers are published on the database PubMed [1]. Those scientific papers contain information regarding medical and biomedical research, for instance about protein interactions and the usage of drugs for specific diseases. A main goal in natural language processing of biomedical text is to extract the most useful information and provide it for everyone in a useful format. This, for example, can be done by structuring the information and generating a graph out of it. Previous works used text-to-graph translation models for this task [2]. But those models had two major drawbacks. The first problem is that they are not scalable to large corpora. The information density of biomedical text can be much higher than in any other text and that caused issues in building the graph. The second major drawback is that the used framework is based on discriminative models. Those models do not produce output text rather than just output labels. This implies that the output-graph is limited by the given labels. One solution to those two problems is to use a generative model that produces output text in a natural language. Those models are scalable for large corpora with high information density and predict output strings for given input text [3]. [4] presented a Framework called Translation between Augmented Natural Languages (TANL) to solve many structured prediction tasks. This framework generates sentences for solving tasks like relation extraction, named entity recognition, event extraction and many more. They used a text-to-text transfer transformer (T5) model as basis for their framework to make it applicable and scalable for many tasks. They also used a natural language description with special annotations as output to keep the results as close to the natural English language as possible. The graph can be build by adapting the language description for the event extraction task and post process the output string from the model. The model has shown good performance on previous event extraction tasks. That’s why this framework seems well suited for using it for information extraction on biomedical text [4].
Leveraging Auxiliary Data for Semi-Supervised Learning

State-of-the-art semi-supervised learning algorithms leverage both labeled data, which is often scarce, and unlabeled data, which is often abundant, to learn a given task. However, little attention has been paid to semi-supervised learning with auxiliary data , labeled datasets from other tasks. In this paper, we explore strategies for designing, building, and evaluating semi-supervised learning algorithms that leverage auxiliary data. This work is part of the TAGLETS project, which is available as an open-source system at github.com/BatsResearch/taglets
Impact of study partner status and group membership on commitment device effectiveness among college students

Procrastination is a major problem among college students and solutions are urgently needed. This experiment explores the effectiveness of a soft commitment device, a contract taken up voluntarily by a person in order to accomplish their goals, as one possible solution for procrastination. If the commitment is broken, there are psychological consequences (e.g., disapproval or disappointment). We hypothesized that status as defined by educational level and group membership based on music taste of a person’s study partner would affect how well they fulfilled their commitment. To test this hypothesis, we conducted an online experiment wherein 134 participants were randomly assigned study partners of different status (high-status or low-status) and group membership (in-group or out-group). To quantify the effectiveness of the commitment device, we asked them how much time they would commit to studying, had them share the goal with their study partner, and then measured whether they accomplished this goal. We found that status and group membership did not significantly affect the likelihood of college students achieving their committed goals, which may be attributed to how status and group membership were manipulated. We also found a trending but non-significant increase in a participant’s committed study time when their study partner was of low-status. Overall, this experiment shows the potential of soft commitment devices that take advantage of social relationships to reduce procrastination in college students.
Current state and usage limitations of vegetation indices in precision agriculture

Bojinov, B. , Ivanov, B. & Vasileva, S. (2022). Current state and usage limitations of vegetation indices in precision agriculture. Bulg. J. Agric. Sci., 28 (3), 387–394 The current state of development and interpretation of vegetation indices makes them relatively difficult for practical use in farming. In this review, we briefly describe the key bottlenecks, together with discussing possible solutions to overcom ing some of them. Based on our own experience with developing working precision agriculture solutions for field crops we propose an integrated approach to working towards building systems that can prove easily understandable outputs with low management requirements for the farmers that plan to use them.
AB-tree: Index for Concurrent Random Sampling and Updates

There has been an increasing demand for real-time data analytics. Approximate Query Processing (AQP) is a popular option for that because it can use random sampling to trade some accuracy for lower query latency. However, the state-of-the-art AQP system either relies on scan-based sampling algorithms to draw samples, which can still incur a non-trivial cost of table scan, or creates samples of the database in a preprocessing step, which are hard to update. The alternative is to use the aggregate B-tree indexes to support both random sampling and updates in database with logarithmic time. However, to the best of our knowledge, it is unknown how to design an aggregate B-tree to support highly concurrent random sampling and updates, due to the difficulty of maintaining the aggregate weights correctly and efficiently with concurrency. In this work, we identify the key challenges to achieve high concurrency and present AB-tree, an index for highly concurrent random sampling and update operations. We also conduct extensive experiments to show its efficiency and efficacy in a variety of workloads.