Miracle-dz/UniFAR-FTUs huggingface dataset:
ALGORITHM AVERSION: SENSITIVITY TO INTERVENTIONS AND THE RELATIONSHIP WITH NUMERACY1

The main goal of this research was to investigate whether people exhibit algorithm aversion—a tendency to avoid using an imperfect algorithm even if it outperforms human judgments—in the case of estimating students’ percentile scores on a standardized math test. We also explored the relationships between numeracy and algorithm aversion and tested two interventions aimed at reducing algorithm aversion. In two studies, we asked participants to estimate the percentiles of 46 real 15-year-old Polish students on a standardized math test. Participants were offered the opportunity to compare their estimates with the forecasts of an algorithm—a statistical model that predicted real percentile scores based on fi ve explanatory variables (i.e., gender, repeating a class, the number of pages read before the exam, the frequency of playing online games, socioeconomic status). Across two studies, we demonstrated that even though the predictions of the statistical model were closer to students’ percentile scores, participants were less likely to rely on the statistical model predictions in 1 This research was funded by Wrocławskie Centrum Akademickie (FAST program BWU-22/2020/F2) and SWPS University. We want to thank Jakub Figol for his support in this project. * Michał Dzieżyk, SWPS University of Social Sciences and Humanities, Faculty of Psychology in Wroclaw, Center for Research on Improving Decision Making (CRIDM), www.cridm. edu.pl, Ostrowskiego 30b, 53238 Wroclaw, Poland ** Weronika Hetmańczuk, SWPS University of Social Sciences and Humanities, Faculty of Psychology in Wroclaw, Center for Research on Improving Decision Making (CRIDM), www.cridm. edu.pl, Ostrowskiego 30b, 53-238 Wroclaw, Poland *** Jakub Traczyk, corresponding author, SWPS University of Social Sciences and Humanities, Faculty of Psychology in Wroclaw, Center for Research on Improving Decision Making (CRIDM), www.cridm. edu.pl, Ostrowskiego 30b, 53-238 Wroclaw, Poland, e-mail: jtraczyk@swps.edu.pl DECYZJE nr 34 grudzień 2020
Assessment Perceptions and Practices in Academic Domain: The Design and Validation of an Assessment Identity Questionnaire (TAIQ) for EFL Teachers

The present research aimed to conceptualize the construct of Teacher Assessment Identity (TAI) by designing and validating a questionnaire in the Iranian EFL context. In so doing, a tentative scale with 96 items was piloted on 340 novice and experienced Iranian EFL teachers using Exploratory and Confirmatory Factor Analysis (EFA, CFA). The results of the analyses led to the removal of 33 items, leaving the questionnaire with 61 items on a five-point Likert scale. Moreover, the results revealed that the construct of TAI has 12 factors including assessment “knowledge”, “beliefs”, “attitudes”, “skills and confidence”, “practices”, “use assurance”, “feedback”, “rubric/criteria”, “consistency and consequence”, “grading/scoring”, “question-types”, and “roles”. Likewise, the convergent validity and reliability of the instrument to measure the construct of concern was statistically confirmed (p>.05). The findings have various implications for EFL teachers, teacher trainers, course designers, and language researchers by raising their awareness of assessment identity and its underlying components.
Mass Cytometry Identifies Expansion of T-bet+ B Cells and CD206+ Monocytes in Early Multiple Sclerosis

Multiple sclerosis (MS) is an immune-driven demyelinating disease of the central nervous system. Immune cell features are particularly promising as predictive biomarkers due to their central role in the pathogenesis but also as drug targets, even if nowadays, they have no impact in clinical practice. Recently, high-resolution approaches, such as mass cytometry (CyTOF), helped to better understand the diversity and functions of the immune system. In this study, we performed an exploratory analysis of blood immune response profiles in healthy controls and MS patients sampled at their first neurological relapse, using two large CyTOF panels including 62 markers exploring myeloid and lymphoid cells. An increased abundance of both a T-bet-expressing B cell subset and a CD206+ classical monocyte subset was detected in the blood of early MS patients. Moreover, T-bet-expressing B cells tended to be enriched in aggressive MS patients. This study provides new insights into understanding the pathophysiology of MS and the identification of immunological biomarkers. Further studies will be required to validate these results and to determine the exact role of the identified clusters in neuroinflammation.
Isolation and Thermal Characterization of Softwood-Derived Lignin with Thermal Flow Properties

A potential alternative biorefinery platform, in which high quality lignin is the main product of the process, is demonstrated. The polyethylene glycol (PEG)-modified softwood lignin (glycol lignin, GL) was isolated from Japanese cedar by acid-catalyzed PEG solvolysis, where liquid PEG with varying polymer chain length was used as the solvolysis reagent with a small amount of acid catalyst. The isolated glycol lignin had the weight-average molecular weight of 4000–7000 and exhibited a viscous thermal flow property, which is impossible for industrial softwood lignin without further processing steps. Thermal analyses, such as thermomechanical analysis (TMA) and capillary flow tester rheometer (CFT), proved to be sensitive techniques for determination of thermal flow behavior. The lignin yield and solid residue (mostly cellulosic residue), respectively, of 28%–31% and 36%–38% (dry wood basis) were obtained from PEG200 solvolysis with 0.5%–0.7% acid catalyst. The results indicated the effectiveness of the one.
Degradation kinetics of total phenolic compounds, capsaicinoids and antioxidant activity in red pepper during hot air and infrared drying process

Summary Degradation kinetics of total phenolic compounds, capsaicinoids and antioxidant activity in red pepper during both hot air drying and infrared drying were investigated, as well as the correlation between antioxidant compounds and antioxidant capacity was discussed in current study. The fractional conversion kinetic and first order kinetic models were proved to describe the changes of total phenolic compounds vs. drying time and moisture content, respectively. Degradation of capsaicinoids and antioxidant capacity vs. drying time and moisture content both followed fractional conversion kinetic model. Infrared drying accelerated the degradation rate of total phenolic compounds and capsaicinoids vs. drying time as compared with hot air drying at the same temperature; however, a contrary result was found that infrared drying decreased the degradation rate of both total phenolic compounds and capsaicinoids vs. moisture content. Total phenolic compounds exhibited a stronger relationship with antioxidant capacity of red pepper analysed by multiple linear regression analysis.
Shadows of change: Square-tailed Kites Lophoictinia isura nesting in the Bendigo area of Victoria

The Square-tailed Kite Lophoictinia isura is an uncommon Australian endemic raptor that has been infrequently recorded breeding in Victoria. We review the historic record of the species for the Bendigo area of north-central Victoria and show that it has increased markedly since about 2000. A survey for nests in remnant box-ironbark forest during the 2014–15 breeding season revealed ten concurrently-active nests and 34 old nests. Density was estimated to be 10.8 pairs per 1000 square kilometres overall and 25.8 pairs per 1000 square kilometres in forest blocks. Nine of ten nests fledged young, yielding a minimum of 1.6 and maximum of 1.8 fledglings per nest. These densities and success rates are as high as or higher than previously reported for the species, showing that the Bendigo forests provided outstanding habitat for the species at least in the study year. We suggest that optimal forest habitat for the species may be as much defined by the scarcity of predators of kite nestlings and adults, and of territorial competitors, as the abundance of food. Notes are provided on nests and kite behaviour. We briefly explore two hypotheses for the species’ increase, both of which involve or may involve changes to the abundance of aggressive or competing raptor species.
Thyroid Cancer Computer-Aided Diagnosis System using MRI-Based Multi-Input CNN Model

Achieving early detection and classification of thyroid nodules contributes to the prediction of cancer burdening and also steers appropriate clinical pathways of that medical condition. We propose a novel multimodal MRI-based computer-aided diagnosis (CAD) system that detects cancerous thyroid nodules using a deep-learning architecture. Particularly, our system is built with a multi-input convolutional neural network (CNN) to perform fusion of two MRI modalities: the diffusion weighted image (DWI) and apparent diffusion coefficient (ADC) map. The main contribution of our system is three-folded. Namely, (1) it is the first system to fuse thyroid DWI and ADC using CNN for classification purpose; (2) it enables independent convolutions process for each of DWI and ADC images, which can increase the likelihood of detecting deep texture patterns in thyroid nodules; and (3) it enables adding extra channels in each input with the possibility to integrate with additional MRI modalities and other imaging technologies. We compared our system to other fusion methods and also to other machine learning (ML) frameworks that use hand-crafted features. Our system achieved the highest performance among them with diagnostic accuracy of 0.88, precision of 0.82, and recall of 0.82.
Comparing International Communication of Corporate Social Responsibility by Chinese and Korean Firms on Social Media

Background: More and more multinational corporations (MNCs) based in East Asia are adopting international social media to communicate messages on corporate social responsibility (CSR), but little research has investigated their content qualitatively. Literature review: I reviewed the literature related to the convergence and divergence of corporate behaviors under the framework of the institutional theory. Comparative studies on web-based CSR communication (CSRC) were also addressed, and CSR development in China and Korea was described as the research context to develop hypotheses and research questions. Research questions: 1. How do Chinese and Korean CSRCs resemble each other in international social media? 2. What are the differences between Chinese and Korean CSRCs in international social media? Research methodology: I selected six Chinese companies and six Korean firms from the 2019 Forbes 2000 world's-largest-corporations ranking, and analyzed the content of their English-language Facebook accounts using “Leximancer,” a powerful textual analysis software package. Results: Results indicated that the CSR messages of Chinese and Korean firms resembled each other at a macrolevel but differed at a microlevel. In addition, the CSR messages of Chinese companies were more likely to reflect national strategic agendas, while Korean firms placed greater emphasis on short-term events and legal compliance. Conclusions: Chinese and Korean corporations have adopted an approach of “global topics, native framing” in their CSRCs to achieve a balance between internal and external legitimacy.
Multivariate Data Analysis Suggests The Link Between Brain Microstructure And Cognitive Impairment In Multiple Sclerosis

Multiple Sclerosis (MS) affects gray matter (GM), usually devoted to executive functions possibly susceptible of cognitive impairment. Potentially, diffusion Magnetic Resonance Imaging (dMRI) can highlight microstructural changes associated with the cognitive impairment. Aiming at shading lights on the joint variation between the cognitive assessment in MS and the dMRI derived GM microstructural alterations, we fitted a Partial Least Squares (PLS) regression to data collected on a cohort of 36 patients. Results showed that 45% variation of the data can be explained by an anti-correlation between anisotropy and restriction dMRI features, and diffusivity ones, together with relevant neuropsychological tests scores. Moreover, the data projected to the PLS derived latent space were distinguishable between cognitively impaired and preserved individuals, with a model significance p < 0.05.
Design of Robust Controller for 2-DOF Flexible Link Robot Manipulator

This paper proposes a practical and efficient control scheme for serial link flexible robot arm using the sliding mode control, reaching phase elimination and uncertainty disturbance estimation techniques to ensure robustness against any sort of uncertainty, disturbance or variation in parameter that may arise while in operation. The controllers for SMC, Reaching phase elimination and Uncertainty disturbance estimator are designed and implemented in MATLAB. The control algorithm performs as per the requirements and constraints placed on the system to drive the error in the states to zero with minimum expenditure of actuator dynamics and maintain the states once at the level. The system uses multiple techniques in conjunction with each other to guarantee optimal performance of the system for multiple scenarios. Further, the dynamic sliding and Uncertainty Disturbance Estimator techniques are being implemented for the 2-DOF flexible link robot arm for the first time
A 2.4–6 GHz Broadband GaN Power Amplifier for 802.11ax Application

This paper presents a 2.4–6 GHz highly integrated broadband GaN power amplifier (PA) with three stages for 2.4-/5-GHz dual-band 802.11ax application. A compact external output matching network is introduced to realize broadband output matching, while reducing the loss of the output matching network and saving the chip area. A novel topology of coupled resonators is exploited for the broadband inter-stage matching to cover the 802.11ax bands from 2.4 to 6 GHz. In the proposed topology, the coupling between the primary and secondary resonators is through a series inductor and a series capacitor. Compared with other conventional coupled resonators, the proposed topology produces an additional complex pole, further extending the bandwidth. The PA was designed and fabricated in Wolfspeed 0.25- $\mu \text{m}$ GaN-on-SiC technology. The implemented PA achieves a saturated output power (Psat) of 35.2–36.3 dBm with a maximum power added efficiency (PAE) of 38–53% from 2.4 to 6 GHz. When tested with an 80-MHz, 256-quadratic-amplitude modulation (QAM) 802.11ax signal, the PA delivers an average output power of 27.1 and 25.7–27.2 dBm with a PAE of 20.9% and 18.4–24.6% in the 2.4-GHz and 5-GHz wireless local area network (WLAN) bands, respectively, while meeting the specification of error vector magnitude (EVM) below −32 dB.
The Electrical Bias Influence on the Total Ionizing Dose Degradation of the MOST Parameters

power MOSFET are widely used in spacecraft equipment set. During the lifetime, which reaches 15 years or more for modern and promising spacecrafts, in space radiation environment the equipment is exposed to significant impacts of total ionizing dose (TID) effects, which leads to degradation of the parameters of the electronic components used, this may lead to the loss of the spacecraft and early termination of the space mission. In this case, the rate of TID-degradation of the parameters is largely depends on the electrical mode of the components during the irradiation.The article considers the influence of various electrical modes of the gate of a power n-channel MOSFET on the rate of TID-degradation of one of the most radiation-sensitive parameters – the threshold voltage [1], [2]. Investigations were carried out in the following electrical modes: constant gate-source voltage in the range from −20 V to +20 V; rectangular signals with different values of frequency, duty cycle, as well as with different values of the upper and lower voltage levels. During the irradiation process, the dependence of the drain current on the gate-to-source voltage was periodically monitored for each sample, the shift of which to the area of negative values of the gate-to-source voltage made it possible to evaluate the transistor TID-hardness in each of the considered modes.The results of investigations allow identifying the most critical electric mode n-channel MOSFET with ionizing radiation of outer space, as well as to assess the strength level of the transistor during irradiation in one of the studied conditions based on data on persistence, defined in the most critical mode [3].
Water Holding Capacity and Absorption Properties of Wood Chars

The application of biomass char as a kind of soil amendment has an important role in soil water holding capacity (WHC), which has a close relationship with its own surface area, total pore volume, and porosity structure. In this research, the WHC and absorption properties of the chars were investigated. Two kinds of wood (poplar and pine) were pyrolyzed at both 450 and 550 °C to produce the chars for the experiments. The Boehm titration was used to measure the concentration of the functional groups. The surface area was determined through the Brunauer–Emmett–Teller (BET) method, while the morphological characteristic of the chars was studied by scanning electron microscopy (SEM). Furthermore, the total pore volume, average pore diameter, and porosity structure of the chars were measured by a mercury porosimeter. On the basis of the pore size distribution of the chars, the definition of the Soil Science Society of America was used as the classification standard. The results showed that there was a signific.
Fluxionality in [ReH5(PPh3)2(pyridine)]

The new polyhydrides [ReH5(PPh3)2(L)] (1; L = 4-carbomethoxypyridine (a), pyridine (b), 4-picoline (c), 4-(dimethylamino)pyridine (d)), formed by reaction of L with [ReH7(PPh3)2], are rigid on the NMR time scale at low temperature. The low-temperature spectrum is assigned by ROESY NMR studies, and turnstile and pseudorotation fluxionality mechanisms are suggested to account for the two successive coalescence events in the VT NMR spectra.
Cu-Segnet: Corneal Ulcer Segmentation Network

Corneal ulcer is a common-occurring illness in cornea. It is a challenge to segment corneal ulcer in slit-lamp image due to the different sizes and shapes of point-flaky mixed corneal ulcer and flaky corneal ulcer. These differences introduce inconsistency and effect the prediction accuracy. To address this problem, we propose a corneal ulcer segmentation network (CU-SegNet) to segment corneal ulcer in fluorescein staining image. In CU-SegNet, the encoder-decoder structure is adopted as main framework, and two novel modules including multi-scale global pyramid feature aggregation (MGPA) module and multi-scale adaptive-aware deformation (MAD) module are proposed and embedded into the skip connection and the top of encoder path, respectively. MGPA helps high-level features supplement local high-resolution semantic information, while MAD can guide the network to focus on multi-scale deformation features and adaptively aggregate contextual information. The proposed network is evaluated on the public SUSTech-SYSU dataset. The Dice coefficient of the proposed method is 89.14%.
A Multi-Agent Approach for Personalized Hypertension Risk Prediction

Hypertension is a global health problem and a leading factor in severe and life-threatening cardiovascular diseases (CVD) and stroke. The onset is dependent on individual lifestyle choices, and no single root cause of the condition exists. Various machine learning solutions are proposed for the early diagnosis of hypertension and its prediction, but they are based on standard guidelines and do not provide personalized solutions. Current models mainly rely on batch learning methods and do not readily learn the new incoming data. There is also a lack of an intelligent technique for handling anomalies in data, which leads to unreliable prediction results. In this paper, an integrated multi-agent-based hypertension risk prediction system is proposed that detects and computes missing values in the time series and provides personalized hypertension risk predictions. The proposed solution incorporates Gaussian mixture models for enhancing the input data, and an Online Infinite Echo State Gaussian Process (OIESGP) is used to obtain real-time prediction distribution of blood pressure. The prediction system readily absorbs new incoming data, and the model is updated to learn any new patterns in the data. The hypertension risk score is estimated using the Framingham hypertension risk estimator, and a 4-year hypertension risk is computed. The prediction performance of the proposed model is evaluated on blood pressure data gathered from the Malaysian population using mean absolute error, mean square error, and root-mean-square errors. The experimental results indicate that the proposed prediction model exhibits greater prediction accuracy than existing state-of-the-art online prediction methods.
The Evolution of Domain-Specific Computing for Deep Learning

With the continued slowing of Moore? s law and Dennard scaling, it has become more imperative that hardware designers make the best use of domain-specific information to improve designs. Gone are the days when we could rely primarily on silicon process technology improvements to provide faster and more efficient computation. Instead, architectural improvements are necessary to provide improved performance, power reduction, and/or reduced cost. Nowhere is this more apparent than when looking at Deep Learning workloads. Cutting-edge techniques achieving state-of-the-art training accuracy demand ever-larger training data-sets and more-complex network topologies, which results in longer training times. At the same time, after training these networks, we expect them to be deployed widely. As a result, executing large networks efficiently becomes critical, whether that execution is done in a data center or in an embedded system. In this article, we look at trends in deep learning research that present new opportunities for domain-specific hardware architectures and explore how next-generation compilation tools might support them.
Iterative Pseudo-Soft-Reliability-Based Majority-Logic Decoding for NAND Flash Memory

This paper proposes a decoding algorithm for nonbinary low-density parity-check (NB-LDPC) codes, aiming to improve the error rate performance for NAND flash memory. Several NB-LDPC decoding methods for NAND flash memory have been studied. Some approaches rely on hard decisions, and these are relatively simple but do not have a good error rate performance. Others are based on soft decisions that require multiple reads for each flash memory cell, leading to significant memory throughput degradation. To improve the error rate performance without suffering performance degradation owing to multiple reads, an iterative pseudo-soft-reliability-based decoding algorithm is proposed. Using Galois field addition to calculate the Hamming distance at the initialization, the proposed algorithm not only improves the error rate performance but also reduces the average number of iterations compared with those of conventional hard-decision-based decoding algorithms.