Miracle-dz/UniFAR-FTUs huggingface dataset:
U NDERSTANDING M ENTAL R EPRESENTATIONS O F O BJECTS T HROUGH V ERBS A PPLIED T O T HEM

In order to interact with objects in our environment, we rely on an understanding of the actions that can be performed on them, and the extent to which they rely or have an effect on the properties of the object. This knowledge is called the object “affordance”. We propose an approach for creating an embedding of objects in an affordance space, in which each dimension corresponds to an aspect of meaning shared by many actions, using text corpora. This embedding makes it possible to predict which verbs will be applicable to a given object, as captured in human judgments of affordance, better than a variety of alternative approaches. Furthermore, we show that the dimensions learned are interpretable, and that they correspond to typical patterns of interaction with objects. Finally, we show that the dimensions can be used to predict a state-of-the-art mental representation of objects, derived purely from human judgements of object similarity.
3-Phase Bidirectional Buck-Boost Sinusoidal Input Current Three-Level SiC Y-Rectifier

Aiming for ever more compact and efficient Electric Vehicle (EV) battery chargers, in this paper a three-phase phasemodular buck-boost Three-Level Flying Capacitor Y-Rectifier (3L-FC-YR) is introduced. The unique circuit structure of the 3L-FC-YR requires time-varying flying capacitor voltages, making the safe and performant operation of such a converter system challenging. Accordingly, a special clamping modulation strategy is proposed which assures equal blocking voltage distribution among the power semiconductors. Further, control strategies and protection circuitry for system startup or failure-mode handling are discussed, such that all practical aspects of the 3L-FC-YR are covered. The concept is verified by means of closed-loop circuit simulations and the resulting waveforms are presented. Finally, a Pareto comparison considering the efficiency and power density limits of the 3L-FC-YR and the standard 2L-YR is conducted considering an extremely wide DC output voltage range of 200V to 920V according to the DC CCS HPC350 EV charging standard. The results indicate a significantly higher performance of the 3L approach and/or the feasibility of a CISPR 11 Class A compliant 3L-FC-YR prototype with a peak efficiency of 98.5% and power density of 19kW/dm (311W/in).
Feature Selection System for the Classification of Chronic Kidney Disease Based on Information Gain and Pearson Correlation

Recently, large amounts of data are widely accessible in information structures, and students have attracted great attention of academics to turn such data into useful knowledge. Researchers also need related data from vast records of patients using the feature selection method. The selection of features is the process of identifying the most important attributes and removing redundant and irrelevant attributes. The system implements obtaining information in the original data set without taking into account class labels to create the best functional subset using information gain and Pearson correlation. This system was tested on a chronic kidney disease dataset obtained from the UCI machine learning repository. The best data on chronic kidney disease with all the functions using data mining algorithms such as Naive Bayes, Multilayer Perceptron (MLP), J48, K Nearest Neighbor (KNN) to test the effectiveness of the system.
Perceptual Photo Enhancement with Generative Adversarial Networks

In spite of a rapid development in the quality of built-in mobile cameras, their some physical restrictions hinder them to achieve the satisfactory results of digital single lens reflex (DSLR) cameras. In this work we propose an end-to-end deep learning method to translate ordinary images by mobile cameras into DSLR-quality photos. The method is based on the framework of generative adversarial networks (GANs) with several improvements. First, we combined the U-Net with DenseNet and connected dense block (DB) in terms of U-Net. The Dense U-Net acts as the generator in our GAN model. Then, we improved the perceptual loss by using the VGG features and pixel-wise content, which could provide stronger supervision for contrast enhancement and texture recovery.
Effectiveness of bylaws in supporting sustainable crop intensification: A case of potato farming in Southwestern Uganda

1 Department of Extension and Innovation Studies, College of Agricultural and Environmental Sciences, Makerere University, P. O. Box 7062, Kampala Uganda. 2 Uganda Christian University, P. O. Box 4. Mukono, Uganda. 3 International Institute of Tropical Agriculture (IITA), Plot No 25 Mikocheni Light Industrial Area, Mwenge-Coca-Cola Road, Mikocheni B, Dar Es Salaam 34441, Tanzania. 4 Independent Consultant, P. O. Box 5689, Addis Ababa, Ethiopia.
Evaluation of the Outcome of Antiviral Therapy among Individuals Infected HIV-1 in Suqian District of Jiangsu Province, China

Background: To evaluate the condition of antiviral therapy (ART) for individuals infected HIV-1 in Suqian district of Jiangsu Province, China. Methods: Altogether, 561 HIV-positive patients who received antiviral therapy in Suqian district in 2019 were recruited. EDTA anticoagulated blood was collected and separated to obtain the plasma samples. Viral load (VL) were tested for evaluating the outcome of ART. Then samples with VL beyond 1000IU/mL were used to conduct the molecular test in order to master the characters of HIV-1 and the prevalence of resistance strains. Results: VL results showed that the virus in 91.1% of the patients who received continuous antiviral treatment for more than 6 months were effectively inhibited (VL ≤ 1000 IU / ml). Among the 50 patients who failed in the treatment, 46 HIV-1 pol gene sequences were obtained, and the positive rate was 92.0%. The most prevalent strain was CRF_ 07bc (32.6%), and new epidemic strains, such as 67_01B, 79_0107, 87_cpx, were popular in this district. Drug resistance test results showed that 56.5% of the patients failed in antiviral treatment due to drug resistance, mainly resistant to the national first-line antiviral drug 3TC. Drug-resistant strains were not found in 43.5% of the patients. Conclusion: ART achieved a satisfied result in Suqian district, but the main cause resulting in ART-failure was resistant, so it is very necessary to enhance the education of adherence prior to the initiation of ART.
NO reduction by activated carbons. VII: Some mechanistic aspects of uncatalyzed and catalyzed reaction

In this last paper of a series devoted to uncatalyzed and catalyzed reduction of NO by carbon, we discuss some mechanistic aspects of this reaction, which is thought to be a viable alternative to selective catalytic reduction by ammonia or hydrocarbons. We present a summary of the results of isothermal and temperature-programmed reduction studies on a metal-free activated carbon and carbon loaded with K, Ca, Fe, Cu, Cr, Co, and Ni catalysts. All the results obtained on catalyzed NO reduction are consistent with a simple oxidation-reduction (redox) mechanism involving the following kinetically significant steps : (1) chemisorption of NO on the catalyst surface ; (2) transfer of oxygen from the catalytically active sites to the carbon reactive sites ; and (3) desorption of oxygen from the carbon surface. A comparison with the proposed mechanisms for selective catalytic reduction is offered, as well as a mechanistic interpretation of the NO reduction enhancement in the presence of O 2 .
The SUCI-AKA Authentication Protocol for 5G Systems

Security is a fundamental requirement for all digital systems. In this paper we propose a new entity authentication protocol, which we call the SUCI-AKA protocol. In contrast to the existing 5G-AKA protocol, it will provide online mutual entity authentication. A central design criteria has been to provide a solution which minimizes the system impact and avoids hard breaks with existing schemes. The SUCI-AKA protocol is largely based on the new 5G scheme for subscriber privacy
IMPACT OF STRAIN-COUNTERSTRAIN ON TREATMENT OF ACUTE NONSPECIFIC LOW BACK PAIN: A SINGLE-BLIND RANDOMIZED CONTROLLED TRIAL

Purpose. The study was to assess the effectiveness of strain-counterstrain (SCS) techniques, after treatment and after a 6-week follow-up, on pain, range of motion (ROM), and disability in patients with acute nonspecific low back pain with mobility deficits. Methods. Overall, 84 patients diagnosed with nonspecific low back pain with mobility deficits were divided into 2 groups; 42 received SCS techniques (group A) and 42 (group B, control group) were advised to be active. The pressure pain threshold (PPT), lumbar flexion ROM, and Oswestry Disability Index (ODI) were used for assessment. All patients were assessed before treatment, after treatment, and after a 6-week follow-up. The treatment program was applied for 2 weeks, 2 sessions per week. Results. Statistical analysis revealed that there were significant increases in PPT on both sides of L5 and lumbar flexion ROM. In addition, a significant reduction in ODI scores was observed (p < 0.05) in the prevs. post-treatment evaluation, in the pre-treatment vs. post-6-week evaluation, and in the post-treatment vs. post-6-week evaluation with regard to both groups. As for between-group effects, multiple pairwise comparisons revealed significant increases in PPT on both sides of L5 and lumbar flexion ROM, in addition to a significant reduction in ODI scores (p < 0.05) in favour of group A as compared with group B after treatment and after the 6-week follow-up. Conclusions. SCS is preferable to be advised in the treatment of acute nonspecific low back pain with mobility deficits.
Patient feedback System using Sentimental Analysis

: Hospital attempt to collect feedback from patients to study their sentiment towards facilitates provided by the hospital to improve the hospital environment. In present scenario, grading technique is used for feedback. This grading technique does not reveal the true sentiment of patients, but the textual feedback provides a chance to the patients to highlight certain aspects. In this paper, a method has been proposed for sentimental analysis of patient ’ s feedback using machine learning algorithms such as Decision Tree, Logistic Regression, K-Nearest Neighbors, Multinomial Naïve Bayes Classifier, and Random Forest. A comparative analysis is also conducted between these machine learning techniques. To improve accuracy Ensembling Learning method are used. The experimental results suggest that Ensemble Classifier is more accurate than other methods .
Jannicke Baalsrud Hauge, Elizabeth Boyle, Igor Mayer, Rob Nadolski, Johann C. K. H. Riedel, Pablo Moreno-Ger, Francesco Bellotti, Theodore Lim, James Ritchie

The objective of this chapter is to provide an overview of the different methods that can be used to evaluate the learning outcomes of serious games. These include Randomised Control Trials (RCT), quasi-experimental designs, and surveys. Case studies of a selection of serious games developed for use in higher education are then presented along with evaluations of these games. The evaluations illustrate the different evaluation methods, along with an assessment of how well the evaluation method performed. Finally, the chapter discusses the lessons learned and compares the experiences with the evaluation methods and their transferability to other games. Study Design and Data Gathering Guide for Serious Games’ Evaluation Jannicke Baalsrud Hauge Bremer Institut für Produktion und Logistik (BIBA), Germany Elizabeth A Boyle University of the West of Scotland, UK Igor Mayer Technical University of Delft, The Netherlands Rob Nadolski Open University of The Netherlands, The Netherlands Johann C. K. H. Riedel Nottingham University, UK Pablo Moreno-Ger Universidad Complutense Madrid, Spain Francesco Bellotti Università degli Studi di Genova, Italy Theodore Lim Heriot-Watt University, UK James Ritchie Heriot-Watt University, UK DOI: 10.4018/978-1-4666-4773-2.ch018
Training Teachers for Diversity Awareness: Impact on School Attendance of Refugee Children

IZA DP No. 14557 JULY 2021 Training Teachers for Diversity Awareness: Impact on School Attendance of Refugee Children Despite efforts to integrate refugee children into host country education systems, their low school attachment remains a major policy challenge. Teachers play a key role in keeping students attached to school, yet classroom diversity poses difficulties for teachers who are not always adequately prepared to address the needs of minority students. Using administrative data and a regression discontinuity approach, we evaluate whether a teacher training program—designed to raise awareness of primary and secondary school teachers in Turkey—is effective in reducing absenteeism of refugee students. We find that the program almost halves the absenteeism gap between native and refugee students and its effect persists into the next academic year, albeit fading out in size. We argue that the most likely channel through which the effects of the program operate is a school-wide mentorship role acquired by trained teachers, which has broad impact on raising diversity awareness within schools. JEL Classification: I21, I28, J15
Paper presented at the 8th European Conference on Cognitive Ergonomics, ECCE-8,

A pilot activity analysis has been performed to study the relation between the cognitive behaviour of an expert aircraft pilot and the worksystem. The cognitive demand of the pilot’s task is related to the level of automation (or mode) of the supporting tools. The mode choice stems both from a personal "flying style" and worksystem constraints. One of the most relevant constraints is the air traffic control operator’s requests. A study on air traffic control operator stress shows that this demand actually comes from flow management and is propagated from the ground to the cockpit. Thus, our research, based on natural setting observations, confirms that operators, and designers, from both ground and cockpit sides, should better cooperate and consider that there is one and only one worksystem.
B AFFLE : T OWARDS R ESOLVING F EDERATED L EARN - ING ’ S D ILEMMA - T HWARTING B ACKDOOR AND I NFERENCE

Recently, federated learning (FL) has been subject to both security and privacy attacks posing a dilemmatic challenge on the underlying algorithmic designs: On the one hand, FL is shown to be vulnerable to backdoor attacks that stealthily manipulate the global model output using malicious model updates, and on the other hand, FL is shown vulnerable to inference attacks by a malicious aggregator inferring information about clients’ data from their model updates. Unfortunately, existing defenses against these attacks are insufficient and mitigating both attacks at the same time is highly challenging, because while defeating backdoor attacks requires the analysis of model updates, protection against inference attacks prohibits access to the model updates to avoid information leakage. In this work, we introduce BAFFLE, a novel in-depth defense for FL that tackles this challenge. To mitigate backdoor attacks, it applies a multilayered defense by using a Model Filtering layer to detect and reject malicious model updates and a Poison Elimination layer to eliminate any effect of a remaining undetected weak manipulation. To impede inference attacks, we build private BAFFLE that securely evaluates the BAFFLE algorithm under encryption using sophisticated secure computation techniques. We extensively evaluate BAFFLE against state-of-the-art backdoor attacks on several datasets and applications, including image classification, word prediction, and IoT intrusion detection. We show that BAFFLE can entirely remove backdoors with a negligible effect on accuracy and that private BAFFLE is practical.
A significant effect of the HUWE1 copy number on autistic spectrum disorder and the development of zebrafish

Haojuan Wu Sichuan University WCSUH: Sichuan University West China Second University Hospital Yan Liang Sichuan University West China Hospital Juan Li The First People's Hospital of Longquanyi District Chengdu Xueguang Zhang Sichuan University WCSUH: Sichuan University West China Second University Hospital Baoshan Xu Guangdong Provincial Stomatological Hospital Xiang Wang Sichuan University WCSUH: Sichuan University West China Second University Hospital Juan Cheng Sichuan University WCSUH: Sichuan University West China Second University Hospital Andras Dinnyes BioTalentum Ltd Jiang Xie Chengdu Third People's Hospital wenming Xu (  xuwenming@scu.edu.cn ) Sichuan University West China Second University Hospital https://orcid.org/0000-0002-3686-229X
HTML Document Content Comparison Algorithm

This paper describes still encountered problems of documents visual content comparison in contemporary computerized workplaces. There are many ways for creating HTML documents and plenty of invisible to user data that carries no information in terms of content. Such circumstances make the automation and visualization process of HTML document comparison rather complex. Introduced algorithm compares versions of HTML documents and displays changes in a result document. The comparison is carried out in such a way that all style and metadata of the document is preserved. Furthermore, the design phases and implementation aspects of the algorithm are investigated in order to share achieved results, to create an effectively working tool and draw guidelines for future work.
In uence of the treatment with the antineoplastic agents 5- uorouracil and Cisplatin on the severity of experimental periodontitis in rats

vivian novaes (  vcnnovaes@hotmail.com ) UNESP: Universidade Estadual Paulista Julio de Mesquita Filho https://orcid.org/0000-0003-0641-0046 Edilson Ervolino UNESP: Universidade Estadual Paulista Julio de Mesquita Filho Giovani Lopes Fernandes UNESP: Universidade Estadual Paulista Julio de Mesquita Filho Clara Possarle Cunha UNESP: Universidade Estadual Paulista Julio de Mesquita Filho Leticia Helena Theodoro UNESP: Universidade Estadual Paulista Julio de Mesquita Filho Valdir Gouveia Garcia UNESP: Universidade Estadual Paulista Julio de Mesquita Filho Juliano Milanezi de Almeida UNESP: Universidade Estadual Paulista Julio de Mesquita Filho
A Prototype Tool for Distinguishing Attacks and Technical Failures in Industrial Control Systems

Critical Infrastructures (CIs) are governed by Industrial Control Systems (ICSs). Modern ICSs do not operate in isolation anymore, but they are connected to the Internet. This transformation introduced numerous advantages, however, there are a few drawbacks as well. Integration with the Internet has left ICS exposed to potential cyber-attacks. Additionally, ICSs could also encounter technical failures during operation. Consequently, it is crucial to distinguish between attacks and technical failures to initiate an appropriate response. There is a deficiency of robust technology to assist operators in distinguishing attacks and technical failures in an ICS environment. However, a framework is proposed to construct Bayesian Network (BN) models that would help to distinguish between attacks and technical failures for different observable problems in our previous work. There are tools available to implement such BN models, but these tools are not appropriate to use in an ICS environment. In order to address this limitation, this paper develops and demonstrates a prototype tool for swift identification of the major cause (Intentional Attack/Accidental Technical Failure) in case of an abnormal behaviour in a component of ICS. The proposed tool enables BN models to automatically update prior probabilities based on the historical data and/or expert knowledge corresponding to the application. The developed tool can be further evaluated and used to distinguish between attacks and technical failures during operation in CIs where ICSs are employed.
Pricing American-Style Options under Jump-Diffusion Models by the Quadrature Method

In this paper, we extend the quadrature method of Andricopoulos, Widdicks, Duck, and Newton (2003) to price American options under jump-diffusion models in an efficient and accurate manner. We approximate American options by Bermudan options, which can be exercised on hundreds of dates, and implement a recursive process in a simple matrix form based on suggested static lattice points. In addition, to show the universality, we apply the proposed approach to the Gaussian jump model, the double-exponential jump model, and the lognormal jump-extended CEV model. To demonstrate the advantages of our method, we compare it in detail with other popular methods for pricing American options under jump-diffusion models. JEL classification: G12, C60
PII: S0969-8051(00)00212-2

The regional distribution in brain, distribution volumes, and pharmacological specificity of the PET 5-HT 2A receptor radiotracer [F]deuteroaltanserin were evaluated and compared to those of its non-deuterated derivative [ F]altanserin. Both radiotracers were administered to baboons by bolus plus constant infusion and PET images were acquired up to 8 h. The time-activity curves for both tracers stabilized between 4 and 6 h. The ratio of total and free parent to metabolites was not significantly different between radiotracers; nevertheless, total cortical R T (equilibrium ratio of specific to nondisplaceable brain uptake) was significantly higher (34–78%) for [F]deuteroaltanserin than for [ F]altanserin. In contrast, the binding potential (Bmax/K D) was similar between radiotracers. [ F]Deuteroaltanserin cortical activity was displaced by the 5-HT 2A receptor antagonist SR 46349B but was not altered by changes in endogenous 5-HT induced by fenfluramine. These findings suggest that [ F]deuteroaltanserin is essentially equivalent to [ F]altanserin for 5-HT2A receptor imaging in the baboon. © 2001 Elsevier Science Inc. All rights reserved.
Establishing Sustainable Cell Lines of a Coral,

Planula larvae of the scleractinian coral, Acropora tenuis, consist of elongated ectodermal cells and developing inner endodermal cells. To establish in vitro cell lines for future studies of cellular and developmental potential of coral cells, larvae were successfully dissociated into single cells by treating them with a tissue dissociation solution consisting of trypsin, EDTA, and collagenase. Brown-colored cells, translucent cells, and pale blue cells were the major components of dissociated larvae. Brown-colored cells began to proliferate transiently in the culture medium that was devised for the coral, while translucent cells and pale blue cells decreased in number about 1 week after cell dissociation. In addition, when a modular protease, plasmin, was added to the cell culture medium, brown-colored cells extended pseudopodia and assumed amorphous shapes. They then continued to proliferate in clumps for more than 6 months with a doubling time of approximately 4–5 days. From 3 weeks of cell culture onward, brown-colored cells often aggregated and exhibited morphogenesis-like behavior to form flat sheets, and blastula-like clusters or gastrula-like spheres. Single cells or cell-clusters of the cell lines were analyzed by RNA-seq. This analysis showed that genes expressed in these cells in vitro were A. tenuis genes. Furthermore, each cell line expressed a specific set of genes, suggesting that their properties include gastroderm, secretory cells, undifferentiated cells, neuronal cells, and epidermis. All cell properties were maintained stably throughout successive cell cultures. These results confirm the successful establishment of a coral in vitro cell line.