Miracle-dz/UniFAR-FTUs huggingface dataset:
Retrieving Lost Stiffness of Planar Wire-Actuated Parallel Manipulators after Failure

In this paper, the effect of wire failure on the stiffness of planar wire-actuated parallel manipulators is investigated. Specifically, the stiffness matrix of the manipulator before and after failure is formulated and the effect of failure on the stiffness maps over the workspace of the manipulator is investigated. It is demonstrated that by changing the anchor position and mobile platform orientation, the lost stiffness due to failure of a wire or motor can be retrieved partially. Variation of the stiffness map area versus anchor position and/or mobile platform orientation of an example wire-actuated parallel manipulator are plotted. Through examination of these plots, optimum anchor position and mobile platform orientation can be identified to maximize the area of the stiffness map.
Applying the OMOP Common Data Model to Facilitate Benefit-Risk Assessments of Medicinal Products Using Real-World Data from Singapore and South Korea

Objectives The aim of this study was to characterize the benefits of converting Electronic Medical Records (EMRs) to a common data model (CDM) and to assess the potential of CDM-converted data to rapidly generate insights for benefit-risk assessments in post-market regulatory evaluation and decisions. Methods EMRs from January 2013 to December 2016 were mapped onto the Observational Medical Outcomes Partnership-CDM (OMOP-CDM) schema. Vocabulary mappings were applied to convert source data values into OMOP-CDM-endorsed terminologies. Existing analytic codes used in a prior OMOP-CDM drug utilization study were modified to conduct an illustrative analysis of oral anticoagulants used for atrial fibrillation in Singapore and South Korea, resembling a typical benefit-risk assessment. A novel visualization is proposed to represent the comparative effectiveness, safety and utilization of the drugs. Results Over 90% of records were mapped onto the OMOP-CDM. The CDM data structures and analytic code templates simplified the querying of data for the analysis. In total, 2,419 patients from Singapore and South Korea fulfilled the study criteria, the majority of whom were warfarin users. After 3 months of follow-up, differences in cumulative incidence of bleeding and thromboembolic events were observable via the proposed visualization, surfacing insights as to the agent of preference in a given clinical setting, which may meaningfully inform regulatory decision-making. Conclusions While the structure of the OMOP-CDM and its accessory tools facilitate real-world data analysis, extending them to fulfil regulatory analytic purposes in the post-market setting, such as benefit-risk assessments, may require layering on additional analytic tools and visualization techniques.
Deep Convolutional Gated Recurrent Unit Combined with Attention Mechanism to Classify Pre-Ictal from Interictal EEG with Minimized Number of Channels

The early prediction of epileptic seizures is important to provide appropriate treatment because it can notify clinicians in advance. Various EEG-based machine learning techniques have been used for automatic seizure classification based on subject-specific paradigms. However, because subject-specific models tend to perform poorly on new patient data, a generalized model with a cross-patient paradigm is necessary for building a robust seizure diagnosis system. In this study, we proposed a generalized model that combines one-dimensional convolutional layers (1D CNN), gated recurrent unit (GRU) layers, and attention mechanisms to classify preictal and interictal phases. When we trained this model with ten minutes of preictal data, the average accuracy over eight patients was 82.86%, with 80% sensitivity and 85.5% precision, outperforming other state-of-the-art models. In addition, we proposed a novel application of attention mechanisms for channel selection. The personalized model using three channels with the highest attention score from the generalized model performed better than when using the smallest attention score. Based on these results, we proposed a model for generalized seizure predictors and a seizure-monitoring system with a minimized number of EEG channels.
Explicit-to-Implicit Robot Imitation Learning by Exploring Visual Content Change

Demonstration understanding is the vital component for robot imitation learning. In this work, we investigate the visual change-based representation of the demonstration and build imitation learning pipelines in both explicit and implicit ways. Specifically, we first propose to represent the demonstration video via the visual change map and utilize it to generate explicit commands for robot execution. To pursue a more “humanlike” imitation learning pipeline, an implicit method is presented by extending the visual change-based representation from image level to feature level. Extensive experiments are conducted to evaluate the proposed methods and the results show that the proposed visual change-based approaches achieve the state-of-the-art imitation learning performance. Also, the results indicate the superiority of the implicit method over the explicit one for imitation learning. Supplementary video is available at https://vsislab.github. io/explicit2implicit/.
The Relationship between Osteoinduction and Vascularization: Comparing the Ectopic Bone Formation of Five Different Calcium Phosphate Biomaterials

Objective: The objective of this study is to compare the bone induction of five kinds of calcium phosphate (Ca-P) biomaterials implanted in mice and explore the vascularization and particle-size-related osteoinductive mechanism. Methods: The following five kinds of Ca-P biomaterials including hydroxyapatite (HA) and/or tricalcium phosphate (TCP) were implanted in the muscle of 30 BALB/c mice (n = 6): 20 nm HA (20HA), 60 nm HA (60HA), 12 µm HA (12HA), 100 nm TCP (100TCP) and 12 µm HA + 100 nm TCP (HATCP). Then, all animals were put on a treadmill to run 30 min at a 6 m/h speed each day. Five and ten weeks later, three mice of each group were killed, and the samples were harvested to assess the osteoinductive effects by hematoxylin eosin (HE), Masson’s trichrome and safranine–fast green stainings, and the immunohistochemistry of the angiogenesis and osteogenesis markers CD31 and type I collagen (ColI). Results: The numbers of blood vessels were 139 ± 29, 118 ± 25, 78 ± 15, 65 ± 14 in groups HATCP, 100TCP, 60HA and 20HA, respectively, which were significantly higher than that of group 12HA (12 ± 5) in week 5 (p < 0.05). The area percentages of new bone tissue were (7.33 ± 1.26)% and (8.49 ± 1.38)% in groups 100TCP and HATCP, respectively, which were significantly higher than those in groups 20HA (3.27 ± 0.38)% and 60HA (3.43 ± 0.27)% (p < 0.05); however, no bone tissue was found in group 12HA 10 weeks after transplantation. The expression of CD31 was positive in new blood vessels, and the expression of ColI was positive in new bone tissue. Conclusions: Nanoscale Ca-P biomaterials could induce osteogenesis in mice muscle, and the osteoinductive effects of TCP were about 124% higher than those of 20HA and 114% higher than those of 60HA. The particle size of the biomaterials affected angiogenesis and osteogenesis. There was a positive correlation between the number of blood vessels and the area percentage of new bone tissue; therefore, osteoinduction is closely related to vascularization. Our results provide an experimental basis for the synthesis of calcium–phosphorus matrix composites and for further exploration of the osteoinductive mechanism.
How to Increase News Literate Behaviors Via Interventions: Eight Guidelines by Early Adolescents

To develop guidelines for more effective news literacy interventions, we conducted focus groups with early adolescents (12-15 years old) on what these interventions should be like. Participants (N = 55) discussed that motivating early adolescents is a challenge, but did provide more insight into their preferences and needs. Future interventions should be easy to find and use, make news literate behaviors more accessible, should be interactive, and should tailor the content toward the target group. Developing interventions based on these guidelines could positively influence various predictors of news literate behaviors in early adolescents, and, in turn, lead to more news literate behaviors.
Experiments on vortex structures in AC electro-osmotic flow

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Valid points and looks: Reliability and validity go hand‐in‐hand when improving infant methods

In this commentary, we suggest that infancy researchers should carefully consider validity when taking steps to improve reliability. Zooming in to focus on looking-time methods, we argue that limitations in validity represent perhaps an even more fundamental issue than reliability. At the same time, focusing single-mindedly on reliability comes with two possible pitfalls: maximizing reliability at the expense of construct validity, and overvaluing parental report measures compared to direct measures of infant behaviour. Finally, we articulate several promising avenues for improving validity in infant research: experi-mental and modelling efforts to characterize the functional relationship between measures such as looking time and infant cognition, using multiple measures to establish convergent validity, and improving our understanding of how measures vary across a broader set of stimulus characteristics. do commendable work drawing attention to the importance of measurement reliability. In our commentary, we broaden the focus to include issues concerning validity. The goals of optimizing reliability and validity are intertwined — and may sometimes even conflict. While we focus on looking-time methods, many similar questions arise when considering other infant methodologies.
Exploring children’s participation in the framework of early childhood environmental education

ABSTRACT The paper explores the participation experiences that a nursery school gained through its involvement in an environmental education program that focused on the transformation of the school ground. The research took place in a nursery school in Greece, in which 15 preschool children aged 4 years old and their teacher were engaged in participatory action research. The research emphasizes the rights and abilities of young children as equal participants, solution seekers, problem solvers and initiators of action on authentic issues of their everyday environment. The research was based on a combination of action research and participatory planning methods. The findings of the research highlight the ability of young children to express their ideas and practice critical thinking, problem-solving and collaboration skills. When the teachers decided to withdraw their authority, the whole nursery school practiced democratic dialogue and action skills. New participation experiences took place for both children and adults.
Framing Service Quality : A Comprehensive Indicator for Measuring Service Quality in Public Administration : Case Study ofBürgerämter in Berlin

This paper introduces an indicator framework, which allows for a valid and reliable assessment of the service quality of customer-focused government services. While defining service quality is a difficult task, also operationalising and measuring such an elusive concept can never be done perfectly due to a number of problems. Given the ‘soft’ nature of service quality, most prior research has focused on survey-based methods, which while being essential have serious flaws owed to this method’s inherent lack of reliability. Following suggestions by prior research in the field, this paper develops an assessment framework combining a ‘soft’ indicator based on a SERVQUAL survey with a set of ‘hard’ variables adding the reliability, which previous approaches lack. The indicator was initially developed, tested and re-adjusted for measuring service quality in Berlin’s 40 Burgeramter. However, it can be adapted in a way that it is applicable to most customer-based government services. The ‘soft’ part of this indicator was developed on the lines of five dimensions, scoring services according to their tangibles, reliability, responsiveness, assurance and empathy. On the ‘hard’ dimension, we have picked a set of eleven variables, which unequivocally add/subtract from service quality, while having the advantage of being measured in a straightforward manner. While the operationalisation and weighting of these variables is open to academic and professional debate, we are confident to have followed a transparent and clearly comprehensible process. We acknowledge, however, that these variables will have to be adjusted when other services are being measured. All in all, the developed Service Quality Indicator for Customer-Based Public Services (SQI) should be regarded as a starting point for a comprehensive and easily constructible framework to assess service quality in the good governance arena. We hope that this indicator framework will be perfected to the point that it can contribute to a better overall measurement and therefore improvement of government services.
APER-DDQN: UAV Precise Airdrop Method Based on Deep Reinforcement Learning

Accuracy is the most critical factor that affects the effect of unmanned aerial vehicle (UAV) airdrop. The method to improve the accuracy of UAV airdrop based on traditional modeling has some limitations such as complex modeling, multiple model parameters and difficulty in considering all kinds of factors comprehensively when facing complex realistic environment. In order to solve the problem of UAV precision airdrop more conveniently, this paper introduces the deep reinforcement learning method and proposes an Adaptive Priority Experience Replay Deep Double Q-Network (APER-DDQN) algorithm based on Deep Double Q-Network (DDQN). This method introduces the priority experience replay mechanism based on DDQN, and adopts adaptive discount rate and learning rate to improve the decision-making performance and stability of the algorithm. Furthermore, this paper designs and builds a simulation experimental platform for algorithm training and testing. The experimental results show that our APER-DDQN has good performance and can more effectively solve the problem of UAV accurate airdrop while avoiding the complex modeling process. Firstly, in the training stage, compared with DDQN and Deep Q Network (DQN), APER-DDQN has faster convergence speed, higher reward and more stable performance. Then, in the test phase, compared with relying on human experience, our method shows higher average reward (average 3.01) and success rate (average 41%), and our method also has more advantages in performance compared with DDQN and DQN. Finally, extended experiments verify the generalization ability of APER-DDQN to different environments.
Molecular analysis for the OprD gene among Pseudomonas aueroginosa clinical isolates obtained from hospitals in Jordan.

INTRODUCTION Pseudomonas aeruginosa has increasingly been associated with the emergence of antibiotic resistance. Antibiotic resistance among P. aeruginosa isolates is an ambiguous and complicated mechanism utilizing several enzymes and structural proteins. This study was conducted to investigate the prevalence of mutations in the chromosomal OprD gene that show resistance to carbapenems among clinical isolates of P. aeruginosa. METHODOLOGY Sixty-three clinical isolates of P. aeruginosa resistant to meropenem were collected from public hospitals in Irbid city, north of Jordan. Analysis of antimicrobial susceptibility was carried out and their susceptibility was categorized. Molecular analysis of mutations in the OprD gene was performed using restriction fragment length polymorphism (RFLP) and DNA sequencing. RESULTS Molecular analysis of P. aeruginosa isolates showed 52% of the common molecular modifications among the collected isolates. These alterations could be associated and affect meropenem-susceptibility rather than imipenem. The most frequent molecular changes among the resistant isolates were the F170L substitution mutation. This was detected in 22 (35%) of the isolates with an unusual insertion sequence (IS) of 100 bp within the 590 bp DNA segment downstream of the restriction site. The divergent sequence of 10 amino acids 372(VDSSSSYAGL)383 was detected in 7 (11%) of the isolates. CONCLUSIONS A significant alteration in the OprD gene in P. aeruginosa clinical isolates was found. Alterations in the OprD gene could be linked to protein permeability of the outer membrane of P. aeruginosa associated with meropenem resistance. Further investigations with a larger number of bacterial isolates are needed to validate the proposed association.
PENGENALAN EKSPRESI WAJAH PENGGUNA ELEARNING MENGGUNAKAN ARTIFICIAL NEURAL NETWORK DENGAN FITUR EKSTRAKSI LOCAL BINARY PATTERN DAN GRAY LEVEL CO-OCCURRENCE MATRIX

Pembelajaran eLearning merupakan sistem pembelajaran berbasis elektronik yang terdiri dari berbagai domain teknologi pembelajaran seperti desain, pengembangan, pemanfaatan, pengelolaan, dan penilaian proses dan sumber belajar elektronik, interaksi pemelajar merupakan kelemahan yang harus diperhatikan dalam pembelajaran eLearning, salah satunya dengan pengenalan ekspresi wajah pengguna eLearning. Ekspresi wajah dapat dikenali berdasarkan perubahan fitur penting wajah sebagai parameter yaitu pada mata, alis, mulut dan dahi
The Role of Efflux Pumps in the Antibiotic Resistance of Campylobacter spp. Isolated From Domestic Animals and Poultry

Background: Recently, the rate of antibiotic resistance of Campylobacter has been reported to be increasing and the mechanism of this resistance has been reported to be related to the activity of efflux pumps. The purpose of this study was to isolate Campylobacter strains from domestic animals such as poultry and cows and evaluate the role of efflux pumps in antibiotic resistance property of them. Methods: A total of 300 fecal samples were collected from poultry and cows and subjected to isolation of Campylobacter by preT-KB method. The isolates were identified and confirmed by phenotypic and genotypic methods and their antibiotic susceptibility was evaluated using the disk diffusion method. Efflux pump activity in the isolates was assessed by EtBr-agar cartwheel method and the presence of efflux pump cmeABC was evaluated in all isolates. Finally, the correlation between efflux pump activity and antibiotic resistance was evaluated in the isolates using inhibition of efflux pump activity of Phe-Arg β-naphthylamide. Results: Of all samples, 10 (3.3%) Campylobacter strains were isolated. Seven (70%) and three (30%) strains were isolated from poultry and cows, respectively. Of all isolates, 9 belonged to Campylobacter jejuni and 1 belonged to Campylobacter coli. The isolates were resistant to three antibiotics, namely Ciprofloxacin, Ceftriaxone, and Cefotaxime. Efflux pump activity was observed in all isolates; however, cmeABC genes were not present in all of them. In addition, resistance to Erythromycin and Ciprofloxacin was associated with efflux pump activity. Conclusions: All Campylobacter isolates in the current study showed antibiotic resistance and the activity of efflux pumps could induce antibiotic resistance and decrease the antibacterial activity of many drug families in Campylobacter. In addition, the activity of efflux pumps can be considered a mechanism of antibiotic resistance and elimination of this activity might increase the effectiveness of antibiotics.
Sports Information Needs in Chinese Online Q&A Community: Topic Mining Based on BERT

The online Question and Answering (Q&A) community has grown globally, allowing users to ask, discuss, and answer questions based on shared interests. As a gathering place for people’s knowledge production, collaboration, and dissemination in the current Internet scene, the online Q&A community can intuitively reflect the public’s information needs and behavior. It also collects many sports-related data and becomes an effective vehicle for comprehending mass sports information needs and disseminating sports knowledge. However, sports-related studies on the online Q&A community have rarely been reported. This study took the sports information in Zhihu, the largest Q&A community in China, as the research object to explore the public needs for sports information in China. We introduced the BERT model through a self-compiled python program and collected 391,092 sports-topic answers in the online Q&A community of Zhihu. Then, we explored the topic content, evolution trend, and user attributes of these answers. We found that the overall trend of sports information needs in Zhihu can be divided into three cycles: the London 2012 Olympic period, the Rio 2016 Olympic period, and the Tokyo 2020 Olympic period in general. The diversified content of information needs included 40 second-level themes and eight first-level themes. Male and female users had similarities and differences in sports information needs. The male and female users had the same information needs for fitness-related information. However, men were more concerned with confrontational solid sports such as basketball and football; women were more likely to care about weight loss, shape effect, and self-protection while doing sports activities. In addition, compared with men, women preferred to emphasize their gender attributes when expressing their needs for sports information to obtain more practical knowledge. In conclusion, our finding reveals that the sports community formed by the current online Q&A community in China is still a male-dominated information field.
Exploratory Factor Analysis of Risk Intelligence Factors in Nigerian Small and Medium Enterprises

Exploratory factor analysis (EFA) is usually necessary to uncover the right items for inclusion in a research instrument. As a result, this research adapts and modifies an instrument on the risk intelligence construct within small and medium enterprises (SMEs) in Nigeria. The study uses Hawley’s risk theory of profit and employs the EFA to validate the instrument. Our study differs significantly from prior studies regarding SMEs' socio-economic, political, and cultural statuses, among other factors. More importantly, most past research focused on larger firms or used different dimensions. However, the current study uniquely integrates risk perception, risk-taking propensity, and insurance literacy within Nigerian SMEs to close the literature gap. The study adopts a cross-sectional research approach using quantitative data obtained through a structured survey from 370 SMEs across Nigeria's six geopolitical regions. The study tested the validity and reliability of the constructs used and refined the 27 items used. The EFA result finally reduced the items to 24; risk perception (6 items), risk-taking propensity (9 items) and insurance literacy (9 items).