Miracle-dz/UniFAR-FTUs huggingface dataset:
A Field Experience Program for Teaching Children with Diverse Abilities Course in A Faculty of Education

This article discussed the gap between the Graduate Profile and the assessment of the Teaching Children With Diverse Abilities course held by the Faculty of Education in Tangerang, Indonesia. Therefore, the purpose of the paper was to explain the importance of a field experience program for the course as a solution to achieve the Graduate Profile. It is a qualitative research method. A case study was employed. The results were the field experience program could be implemented in this course because of (1) preparing the teacher students to teach special needs children; (2) building partnership with schools to be teaching practice places for the teacher students; (3) giving opportunities to teacher students to improve their teaching skills and develop their teaching affection, and (4) increasing the teacher students' feeling of competency. Moreover, the program did not only guide the teacher students to understand inclusive education, but also the holistic education from the Christian perspective. Therefore, the teacher students needed to have transcendental relationships before teaching the students with diverse abilities. The conclusion was the field experience program in the Teaching Children With Diverse Abilities fulfilled the graduate profile in the values of “Calling” and “Competence” through its achievement to Faculty of Education Program Learning Objectives, Competencies Learning Objectives, and assessments.
Optimizing the light source layout of the indoor visible light communication system

Aiming at the problem of uneven illuminance distribution in traditional indoor optical communication systems, this paper proposes a square + ellipse layout, using simulated annealing particle swarm algorithm to optimize the spacing of LED light sources, and optimize the uniformity of system illuminance and signal-to-noise ratio. The simulation results show that the optimized square + ellipse layout illumination ranges from 359.25 lx to 451.05 lx, and the mean square error reaches 12.66 lx. Signal noise ratio is between 18.54 dB and 20.75 dB, and the mean square error is 0.39 dB. Compared with the traditional square and elliptical layout, the illumination performance and communication performance are improved clearly, which provides a new reference scheme for indoor light source layout.
Seismic response of steel frames containing hierarchical friction- dissipating joints

Friction dissipating joints with slotted bolt holes have been used in concentrically braced frames (linear sliding) and more recently, in moment resisting frames (rotational sliding). Such joints have the ability to provide many cycles of ductile energy dissipation with little or no primary structural damage and permit the decoupling of the strength and stiffness of co nnected members. Suggestions are offered on the use of linear sliding joints in K-braced frames where they could lead to cheaper, stiffer structures with high levels of ductility. Rotating sliding bolted joints extend the benefits of damage-free energy dissipation to moment-resist ing frames. The decoupling of beam stiffness and end moment strength avoids over-sizing columns to deal with beam over-strength moments. The performance of a rotational slotted joint having a hierarchy of two distinct moment levels at which limited rotational slip can occur is di scussed. The basic characteristics of the joint are described and some observations made on the seismic response of some sample frames to seismic ground motion.
PREDICTION OF MATERIAL REMOVAL RATE USING REGRESSION ANALYSIS AND ARTIFICIAL NEURAL NETWORK OF ECDM PROCESS

The combination of two non conventional machining processes is known as Hybrid machining. It has become one of the most important machining techniques for glass and other brittle materials. In this paper, an attempt has been made to combine Electro Chemical machining(ECM) and Electrical Discharge Machining (EDM) to form a hybrid machining known as Electro Chemical Discharge Machining (ECDM). It can be applied for micro machining and micro finishing on the glass and its composites. The empirical models have been developed for grooving process of ECDM using Regression Analysis (RA) and the Artificial Neural Network (ANN) to predict the Material Removal Rate (MRR) . According to results, the prediction of ANN model for MRR is better as compared to the Regression model. The two models of ECDM process can be recommended to predict the MRR for grooving of ECDM for the given range of process parameters. The process parameters of the ECDM process are optimized. ANOVA is used to identify the significant affect of process parameters.
Reform Stress in the Public Sector? Linking Change Diversity to Turnover Intentions and Presenteeism Among Civil Servants Using a Matching Approach

Abstract This paper aims to examine the effect of having experienced diverse changes over a short period of time on the turnover intent and presenteeism behavior of public sector employees. Identifying such effect has been difficult since extant research often defined and studied organizational changes as single, isolated events. Consequently, they may have failed to capture how different changes interact with one another, and what cumulative impact diverse changes have on employees. We introduce nonparametric matching, using data from the Australian Public Service, allowing us to overcome the challenge of distinguishing between the effect of change diversity and that of preexisting problems. Results show both turnover intent and presenteeism increase in organizations with high change diversity. This suggests that employees perform emotion-focused (turnover intent) and problem-focused (presenteeism) coping when faced with high change diversity, and points at the need for sufficient recovery time in between changes.
Targeting Precision in Imperfect Targeted Advertising: Implications for the Regulation of Market Structure and Efficiency

With the rapid development of e-commerce and related information technologies, consumers’ individual information can be accurately collected and analyzed according to their previous purchase histories or browsing behaviors. Then the targeted advertising can be directly sent to the heterogeneous consumers in the segmented market by the firms. This study aims to explore the possible role of targeting precision on the market structure. This assay set up a game-theoretical model with duopolistic firms. Both firms compete in prices and imperfect targeted advertising. In this setup, the targeting precision is variable. The results indicate that each competitive firm’s equilibrium profit varies with the targeting accuracy of targeted advertising and shows a U-shape variation with precision. Moreover, both firms’ profits reveal monotonic properties, improving targeting precision while using distinct advertising strategies. Then, the model is extended into n different competitive firms to seek the possible market capacity. The results prove that the equilibrium free-entry numbers of firms also exhibit a U-shape variation as a function of targeting precision while sending the imperfect targeted advertising to the consumers. This conclusion implies that the firm conducting imperfect targeted advertising with a moderate targeting precision is beneficial for the most efficient free-entry of new rival competitive firms and shows the most effective efficiency for the whole market.
Exposing Android social applications: linking data leakage to privacy policies

ABSTRACT Social media applications (apps) use sensitive/private data in their nature. Android apps continue to share data with third parties and often transmit data unencrypted, leaking data directly and inadvertently. Internet Service Providers (ISPs) can legally collect and sell this leaked, sensitive user data. End users rely on privacy policies that have largely been absent, continue to lack detailed security methods, and have had inconsistencies with app actions. Overall, we lack a detailed understanding of the state of these privacy and security issues within sensitive settings such as social media apps. We aim to expose these apps, meticulously classifying and comparing unencrypted data transmitted with privacy policy disclosure, leveraging the Platform for Privacy Preferences (P3P) Specification. We develop an analysis framework and isolated testbed environments, leveraging open-source tools to enable accurate data collection through dynamic analysis. We then peer into privacy policy revisions, advertising/analytics libraries, and business relationships held by app companies. We report detailed inconsistencies between app behaviors and privacy disclosure. Most apps in our dataset transmitted the majority of their traffic unencrypted and several leaked personally identifiable information (PII)/sensitive data, while none detailed security methods or data transmission practices. Finalizing our study, we conduct brief follow-up experiments on several apps to note substantial changes in data transmission practices. We conclude that a failure to protect sensitive user data and a tendency for vague privacy policies continue to be prevalent, but over the last few years some apps have increased encryption use, thus beginning to combat some data leakage.
Uneven domestic tourism demand in times of pandemic

This study investigates the short-run impact of the COVID-19 pandemic on the number of domestic overnight stays at the regional level in the summer season 2020. Official data for 65 regions in four countries are used for the analysis (Austria, the Czech Republic, Germany and Switzerland). Dynamic panel data models are employed to estimate a tourism demand equation (real GDP and price fluctuations) augmented by average temperatures. Estimation results reveal that domestic overnight stays evolve unevenly in the first summer after the outbreak of the COVID-19 pandemic. The short-run effects show that the number of domestic overnight stays in densely populated regions decreases by 27% in July as well as in August 2020, in comparison with the same months in previous years, ceteris paribus. To the contrary, there is a surge of 27 and 10%, respectively, for sparsely populated areas in the same months. JEL: Z3, R11 and R12.
Kalman Filtering of Attitude Measurement with Magnetometer and Gyroscope

In the present research of integrated navigation based on magnetometer,it is firstly needed to determine the roll angle.Aiming at the problem,a Kalman filtering algorithm based on magnetometer and MEMS gyroscope was proposed in this paper.By applying angular rate of gyroscope and combing with the rolling angular of the earth magnetic component,the projectile attitude was obtained through Kalman filtering,which estimated three attitude angles simultaneously without any transcendental hypothesis.Error analysis showed that the proposed algorithm was appropriate and the error of attitude angle was relatively small and did not accumulate over time.
Artificial intelligence in interdisciplinary life science and drug discovery research

Artificial intelligence (AI) is lauded as an auspicious problem solver in many areas. However, the methodology is not always sufficiently understood. In fact, there often is an aura of mystery – and also concern – created around AI. For example, the expectation that machines would ‘think’ independently and reach autonomous decisions beyond human reasoning, which might also be threatening, depending on the situation, is not factual and falls into the realm of science fiction. In science, the popularity and promise of AI mostly originate from notable advances in a few fields, but are also influenced by business-driven hype and partly unrealistic expectations. In computer science, various disciplines are covered under the term AI [1]. Among these, deep learning (DL) using deep neural networks (DNN) – a sub-discipline of machine learning (ML) – has been responsible for recent progress in computer vision (image analysis) or natural language processing. These advances have greatly contributed to the popularity of AI in science. Robotics, another AI discipline, is a mainstay in industry and also plays an important role in laboratory automation. Furthermore, expert and recommender systems, which are also a part of AI, are beginning to be explored in the natural sciences. In the life sciences including medicinal chemistry and early-phase drug discovery, the focal points of this discussion, DL clearly dominates [2–5], and the term AI is for the most part synonymously used with DL. In medicine, a similar dominance of DL is observed across different therapeutic areas [6] such as radiology or oncology [7,8]. In clinical practice, medical image analysis represents a prime growth area for DL [7,9].
Larval habitats of Culicoides ornatus Taylor, 1913 (Diptera: Ceratopogonidae) within the mangroves of Darwin Harbour in the wet‐dry tropics of northern Australia

Larval habitats of the pest biting midge Culicoides ornatus were identified and characterised in a macrotidal mangrove creek system in Darwin Harbour in the wet‐dry tropics of northern Australia. Sampling was undertaken during the mid to late dry season using submersible emergence traps to indicate larval activity. Substantial emergence was found in two well separated and distinctly different habitats: open creekbanks covered in Avicennia marina (Grey Mangrove) pneumatophores in the upper reaches of small tidal creeks and broad relatively flat areas dominated by Sonneratia alba (Mangrove Apple) at the mouth of the creek system. Intervening areas along creeklines were lined by Camptostemon schultzii (Kapok Mangrove) and did not support emergence activity. Adults emerging from each habitat were conspecific, based on comparison of mitochondrial COI gene sequences and a range of morphological characters. Nine different haplotypes were identified from 26 adults, with four haplotypes common to both habitats. Neighbour‐joining analysis resolved all the haplotypes as a single highly supported clade with an average sequence difference of 1.6%. Features common to the two habitats included occurrence in sheltered mangrove‐lined estuaries; occurrence in soft, fine, silt mud; presence of mangrove pneumatophores; and an open vegetation structure providing partial shade. Dense vegetation appeared to be a limiting factor. The tidal creek habitat was similar to C. ornatus habitats previously described from the east coast of Australia, but neither the Sonneratia zone nor other habitats at such a low tidal elevation have been previously associated with C. ornatus. This is the first detailed account of the larval biology of this important mangrove breeding pest species. The identification of likely C. ornatus breeding sites in Darwin Harbour and other similar ria coastlines of northern Australia should be possible from aerial photographs using the habitat descriptions presented in this paper.
Network analysis: a cross-country comparison of peer attention among EU countries in response to China with the media data

ABSTRACT Peer attention is a significant feature in the horizontal cross-loading of EU countries when there are many uncertainties in the decision-making. Taking the case of the 28-EU countries’ interactive media attention during China’s second Belt and Road Initiative (BRI) forum in April 2019, this paper explores the two questions of who pays attention to whose action to the BRI, and what are the determinants of the peer attentions? The measurements from the network analysis identify the positions and roles of EU countries in the attention network. The gravity model further examines the determinants on different levels of peer attention flows. The findings suggest that the peer attention network the EU countries formulate is a core-periphery structure where big powers and forerunners construct the core and connect other big power and peripheral countries from the nearby to the far-reaching. Substantively, this paper contributes to the literature on the horizontal interaction of countries in response to China’s engagement. Methodologically, the network analysis is an innovative method to study how a country receives the influence imposed by a single country, by a cluster of countries and the peer attention network as a whole.
Creativity, Boredom Proneness and Well-Being in the Pandemic

Throughout the course of the pandemic, it has become clear that the strictures of social isolation and various levels of lockdown constraints have impacted people’s well-being. Here, our aim was to explore relations between trait dispositions associated with boredom proneness, self-regulation and well-being using data collected early in the pandemic. Specifically, we explored whether the tendency to engage in everyday creative pursuits (e.g., making your own greeting cards) would act as a prophylactic against poor well-being. Results showed that well-being was higher for those individuals who increased engagement with creative pursuits during the early stages of the pandemic. That is, people who engaged more in everyday creative activities also reported higher levels of self-esteem, optimism, and positive affect. In contrast, those who pursued fewer creative outlets had higher levels of depression and anxiety, were higher in boredom proneness, and reported experiencing more negative affect. As we emerge from the pandemic, these data provide a clue as to how people might plan to cope adaptively with the restrictive circumstances this extreme world event engendered. More generally, these data provide support for the notion that everyday creativity (and not necessarily creative expertise) has positive associations for well-being.
Status and Scenario of Genome Editing Device CRISPR-Cas9 in Crop Advancement

Plant breeding systems have a extensive antiquity and they had been employed meanwhile the commencement of subjugation of the initial agricultural crop plants. Subsequently, innumerable novel procedures have and are being advanced to added upsurge the profitable worth and harvest of plants. The newest crop enhancement method recognized as genome editing is a method which empowers accurate alteration of the crop genome via bashing out unwanted genes or permitting genes to advance novel occupation. Genome sequencing of many plants and advancement in genome editing methodologies has unlocked prospects to breed advantageous traits. Innovations in genome editing machineries for instance have created it feasible for biotechnologists to mark a specific gene of consideration more proficiently. The first-generation CRISPR/Cas9 genome editing entails modest conniving and cloning approaches, which can be accessible and applicable for various guide RNAs to edit various positions in the genome of targeted organism. It is more willingly recognized in the marketplace economically. The tradition of genome editing has verified to be reimbursements and theatres an encouraging part in upcoming crop development endeavors. So, in presented review article, it is intended to emphasize the advancement and usage of genome editing procedures, in regard, the CRISPR/Cas9 for crop improvement.
A 3D Printed Soft Robotic Gripper With a Variable Stiffness Enabled by a Novel Positive Pressure Layer Jamming Technology

In this research, a soft robotic gripper with a variable stiffness enabled by a novel positive pressure layer jamming technology was developed and fabricated in two materials using customized additive manufacturing. A novel positive layer jamming technology was developed for tuning stiffness of the gripper. Positive pressure layer jamming has a higher performance potential than conventional vacuum layer jamming since a higher pressure can be applied, approximately 1.6x higher in terms of payload capacity. Two different thermoplastics materials are printed together to form a relatively hard backbone and a relatively soft airtight actuation bellows. The implementation of positive layer jamming will be described, along with the additive manufacturing techniques used to produce the gripper and the test results of the final design. Experimental tests show that this soft gripper was able to vary its stiffness about 25x fold with the positive layer jamming. This work demonstrates that the positive pressure jamming offers a novel method for varying soft robot stiffness with higher payload capacity than the conventional vacuum based layer jamming technology.
Aerodynamic 3-Dimensional Optimal Design by NURBS of a Certain Stage Turbine Blades

The 3-dimensional profiled surface and the stacking line of turbomachinery blades are parameterized by NURBS,herewith getting the bend,the lean,the sweep and the twist deformation of the 3-dimensional profiled surface and the stacking line under control.This method provides the necessary design variables for the automatic optimizing design of blades.The 3-dimensional control module,herewith constructed,is then integrated into the optimizing viscous flow design platform with the help of iSIGHT based software;whence an optimizing algorithm is chosen for the 3-dimensional optimized trial design of blades of a certain stage,with the aim of making the stage efficiency as high as possible,without diminishing the volume of flow and simultaneously keeping the temperature of the moving blade's root as low as possible.Test results show that,after optimization,the properties of the blade profile has improved,while simultaneously meeting the restricting requirements of flow volume and temperature.Figs 23 and refs 5.
PowMail : want to fork? : do some work

We design and implement PowMail, a secure email framework that uses proof-of-work to prevent impersonation attacks. PowMail uses a novel authenticated data structure called a Po W-tree to enable email users to jointly certify the history of all users' public keys. An implementation is given in the Go programming language. We evaluate PowMail and demonstrate its feasibility for securing email communications today.
A Fast Weight Transfer Method for Real-Time Online Learning in RRAM-Based Neuromorphic System

In this work, a synaptic weight transfer method for a neuromorphic system based on resistive-switching random-access memory (RRAM) is proposed and validated. To implement the on-chip trainable neuromorphic system which utilizes large-scale hardware synapse units, a fast and reliable write scheme needs to be established. Based on the experimental results, it is confirmed that the gradual set and full reset operation is the most suitable operation scheme for fast programming due to the fundamental reliability characteristics of the resistive-switching memory cell. Also, the superiority of this programming method using the proposed RRAM compact model is demonstrated. In addition, a one weight/one synaptic device structure is newly adopted for realizing high-density synapse arrays by using a nonnegative weight constraint in supervised learning. Finally, the pattern recognition accuracies obtained at the software and hardware levels are compared.