Miracle-dz/UniFAR-FTUs huggingface dataset:
Partial Predictability in Avoidance Acquisition and Expression of Wistar-Kyoto and Sprague-Dawley Rats: Implications for Anxiety Vulnerability in Uncertain Situations

Individual differences or vulnerabilities must exist which bias some individuals toward psychopathology while others remain resilient in the face of trauma. Recent work has studied the effects of uncertainty on individuals expressing behavioral inhibition (BI). The current study extended this work with uncertainty to Wistar Kyoto (WKY) rats which are a behaviorally inhibited inbred strain that models learning vulnerabilities for anxiety disorders and posttraumatic stress disorder (PTSD). WKY rats exhibit superior avoidance performance in a signaled bar press avoidance task in which a tone conditioned stimulus (CS) signals a foot shock unconditional stimulus (US) when compared with non-inhibited Sprague-Dawley (SD) rats. In addition, WKY rats express enhanced eyeblink conditioning. Recent work with behaviorally inhibited humans has indicated that this enhanced eyeblink conditioning is more evident in conditions that insert CS- or US-alone trials into CS-US paired training, resulting in uncertain and suboptimal learning conditions. The current study examined the effects of partial predictability training, in which the CS signaled the US only one-half of the time, on the acquisition and expression of avoidance. Standard training with a fixed 60-s CS which predicted shock on 100% of trials was compared with training in which the CS predicted shock on 50% of trials (partial predictability) using a pseudorandom schedule. As expected, WKY rats acquired avoidance responses faster and to a greater degree than SD rats. Partial predictability of the US essentially reduced SD rats to escape responding. Partial predictability also reduced avoidance in WKY rats; however, adjusting avoidance rates for the number of potential pairings of the CS and US early in training suggested a similar degree of avoidance expression late in the last session of training. Enhanced active avoidance expression, even in uncertain learning conditions, can be interpreted as behaviorally inhibited WKY rats responding to the expectancy of the shock by avoiding, whereas non-inhibited SD rats were responding to the presence of the shock by escaping. Future work should explore how WKY and SD rats as well as behaviorally inhibited humans acquire and extinguish avoidance responses in uncertain learning situations.
Creating a guide for reflective practice: applying Dewey’s reflective thinking to document faculty scholarly engagement

ABSTRACT This article introduces the creation of a guide for reflective practice to document faculty scholarly engagement. As the editor for a journal designed to showcase scholarship of application and integration, I recognized the need for a guide to help faculty structure reflective practice and document their practical and scientific contributions. John Dewey's seminal framework on reflective thinking was used as a conceptual scaffolding to create the guide. There is a discussion of the challenges in interpreting Dewey’s work in creating the guide, and I explain choices made that deviate from Dewey’s original work on reflective thinking. I recommend expanding the guide to a method that education researchers or scholar-practitioners could use to systematically inquire about problems of practice.
Repurposing Drugs, Ongoing Vaccine, and New Therapeutic Development Initiatives Against COVID-19

As the COVID-19 is still growing throughout the globe, a thorough investigation into the specific immunopathology of SARS-CoV-2, its interaction with the host immune system and pathogen evasion mechanism may provide a clear picture of how the pathogen can breach the host immune defenses in elderly patients and patients with comorbid conditions. Such studies will also reveal the underlying mechanism of how children and young patients can withstand the disease better. The study of the immune defense mechanisms and the prolonged immune memory from patients population with convalescent plasma may help in designing a suitable vaccine candidate not only for the current outbreak but also for similar outbreaks in the future. The vital drug candidates, which are being tested as potential vaccines or therapeutics against COVID-19, include live attenuated vaccine, inactivated or killed vaccine, subunit vaccine, antibodies, interferon treatment, repurposing existing drugs, and nucleic acid-based vaccines. Several organizations around the world have fast-tracked the development of a COVID-19 vaccine, and some drugs already went to phase III of clinical trials. Hence, here, we have tried to take a quick glimpse of the development stages of vaccines or therapeutic approaches to treat this deadly disease.
Performance Comparison of Yolo-Lite and YoloV3 Using Raspberry Pi and MotionEyeOS

This paper proposes system comparison on identifying and processing of human image based on YOLOLITE and YOLOV3 algorithms. Computer Vision (CV) is a field of computer science where the focus is on learning how computers can be trained to identify and process image data as humans do. There are many open source CV frameworks have been proposed such as OpenCV. This paper shows a comparison between YOLO-LITE and YOLOV3 algorithms and analyzes their performance. We have implemented both algorithms in several test cases in the real time domain and carried out in the same test environment. The result shows that the Raspberry Pi camera worked at 15 fps on YOLO-LITE and 1 fps on YOLOV3. This indicates that YOLO-LITE has an average performance of 1 second faster while YOLOV3 has an average accuracy of 30% better.
Bilateral Humanoid Teleoperation System Using Whole-Body Exoskeleton Cockpit TABLIS

We describe a system design approach for the bilateral teleoperation of a humanoid robot. We have focused on bipedal stability and 2D/3D locomotion space problems. Our proposed system has two robot hardware and two control software. The master side hardware is newly developed seat-type whole-body exoskeleton cockpit called “TABLIS,” and the master side software reproduces a remote 2D/3D ground surface and overcomes the space limitation of locomotion, such as the use of treadmills. The slave side software prevents the humanoid from falling down in cases where an operator provides an inaccurate input. We used humanoid robot “JAXON” as a slave side hardware. We have achieved a bilateral quasi-3D step traversing and demonstrated the validity of our system design.
Analytical study of floating effects on load sharing characteristics of planetary gearbox for off-road vehicle

Uneven load sharing of a planetary gear set is the main cause of preventing the miniaturization and weight reduction of a planetary gearbox. Non-torque loads and carrier pinhole position errors are the main factors that worsen the load-sharing characteristics. However, their effects are seldom analyzed at a system level especially for an off-road vehicle. To make up this gap, some simulation models are proposed to investigate the effects of floating members on the load-sharing characteristics and the strength of a planetary gear set with non-torque load and carrier pinhole position error. When the error is not considered, the mesh load factor converges to unity irrespective of the type and number of floating members and the safety factors for pitting and bending are increased slightly. When the carrier pinhole position error is considered, the mesh load factor dramatically worsens. Although it is improved using the floating members, it does not converge to unity. However, the bending safety factor of the planet gear with the error is increased by 26%. This indicates that the design modification for the original planetary gearbox is needed to satisfy the safety factor requirement, but the problem is solved using only floating members.
Assessment of Finite Element Simulation Methodologies for the Use of Paschen’s Law in the Prediction of Partial Discharge Risk in Electrical Windings

The prediction of partial discharge (PD) occurrence in electrical motors at the design phase is key to the development of future devices. As a result, there is a growing interest for predictive numerical tools to help assess partial discharge risk. Currently, most efforts rely on Paschen’s law as a criterion for partial discharge occurrence between two neighboring wires. Its use requires field lines data obtained with finite element electrostatic simulations. In this paper, we explore the extent to which these finite element simulations can be simplified without losing accuracy regarding subsequent partial discharge risk assessment using Paschen’s law. First, we examine whether partial discharge risk predictions between two turns are influenced by the presence of other turns nearby. Our results suggest that the partial discharge is mostly a local phenomenon hardly affected by the surroundings. Performing simulations for an isolated pair of conductors may thus be sufficient to determine the maximum allowable constraints between two turns, at least for large wires. Also, we show that neglecting field line curvature in the calculation does not alter predictions, vindicating the straight line assumption which has been adopted in the literature for the sake of simplicity.
Protecting Private Attributes in App Based Mobile User Profiling

The Analytics companies enable successful targeted advertising via user profiles, derived from the mobile apps installed by specific users, and hence have become an integral part of the mobile advertising industry. This threatens the users’ privacy, when profiling is based on apps representing sensitive information, e.g., gambling problems indicated by a game app. In this work, we propose an app-based profile obfuscation mechanism, ProfileGuard, with the objective of eliminating the dominance of private interest categories (i.e. the prevailing private interest categories present in a user profile). We demonstrate, based on wide-range experimental evaluation of Android apps in a nine month test campaign, that the proposed obfuscation mechanism based on similarity with user’s existing apps (ensuring that selected obfuscating apps belong to non-private categories) can achieve a good trade-off between efforts required by the obfuscating system and the resulting privacy protection. We also show how the bespoke (customised to profile obfuscation) and bespoke++ (resource-aware) strategies can deliver significant improvements in the level of obfuscation and (particularly bespoke++) in the use of mobile resources, making the latter a good candidate strategy in resource-constrained scenarios e.g., for fixed data use mobile plans. We also implement a POC ProfileGuard app to demonstrate the feasibility of an automated obfuscation mechanism. Furthermore, we provide insights to Google AdMob profiling rules, such as showing how individual apps map to user’s interests within their profile in a deterministic way and that AdMob requires a certain level of activity to build a stable user profile.
Plasmon-enhanced organic and perovskite solar cells with metal nanoparticles

Abstract Solution-processing thin-film solar techniques, such as organic solar cells (OSCs) and perovskite solar cells (PeSCs), hold great promise as cost-effective renewable energy sources with feasible large-scale manufacturing. However, these devices are suffering from the incomplete photon absorption and thereby cannot unlock the full potential of device efficiency despite their rapid development in recent decades. Incorporation of plasmonic metal nanoparticles (NPs) into the thin active layers has been considered as a breakthrough strategy to solve this inherent limit and represent an imperative milestone toward the highly efficient OSCs and PeSCs, arising from the significantly enhanced light absorption and electrical characteristics in fundamental. Herein, the recent advances in fabrication and incorporation strategies of plasmonic NPs are reviewed. The in-depth efficiency and stability enhancement mechanisms are investigated and highlighted. Meanwhile, potential strategies and perspectives for their further development of NP-based solution-processing OSCs and PeSCs are presented.
Simultaneous and Proportional Estimation of Multijoint Kinematics From EMG Signals for Myocontrol of Robotic Hands

As the primary effector of human, hand is dexterous, important, and biomechanically complex. How to control the robotic hand as human intends in the human-centered robotic systems is a hot topic to guarantee natural interaction between users and robots. In this article, we investigate the simultaneous and proportional estimation of human's movement intent from surface electromyography (EMG) signals. A sparse pseudo-input Gaussian process regression method is proposed to map the EMG features and the hand kinematics. The kinematics of five primary degrees of freedom (DoFs) are estimated from EMG recorded during functional grasping tasks. From the experiments on eight able-bodied subjects, ipsi-lateral and contra-lateral training strategies represent similar estimation accuracy (CC = 0.89 and 0.88, respectively) and no significant difference (p = 0.8) between them. The online estimation with contra-lateral strategy shows higher average estimation accuracy (CC = 0.91). In addition, the estimation of the intended kinematics can be decoded in real time with negligible response delays. It is suggested to apply the proposed method to multi-DoF decoding for natural, intuitive, and accurate myocontrol of robotic hands.
The effect of safflower meal substitution in a lysine fortified corn-soybean meal diet on performance, egg quality, and yolk fat profile of laying hens

SUMMARY Two experiments were conducted to study the performance, egg quality, and yolk fat profile of laying hens fed rations containing de-hulled-extruded safflower meal (SFM) in partial or total substitution of de-hulled soybean meal (SBM). In Experiment 1, a balanced diet containing SFM with crystalline L- lysine (SFD) was formulated to meet or slightly exceed the Hy-line W-98 commercial management guide. A corn-SBM (control) also was formulated without supplemental lysine. These 2 diets contained 0.80 and 0.93% lysine, respectively. A third SFM containing diet (SFDL) was mixed in which L- lysine was further added to match the lysine level of the control diet (0.93%). All diets were isocaloric and isonitrogenous. In Experiment 2, a corn-SBM diet (control) and diets with SFM substituted for 20, 40, 60, 80, and 100% of the soybean protein in the control diet were prepared. The 3 treatment diets in trial 1 were replicated in a completely randomized design among 20 individually caged hens and fed for 168 d. In trial 2, the 6 treatment diets were similarly replicated among 12 individually caged hens and fed for 140 d. Production parameters such as egg production, egg mass, feed conversion, and hen weight were not affected by any of the dietary treatments in either experiment. Similarly, all SFM containing diets had no effect on egg weight, specific gravity, Haugh unit score, or shell thickness throughout the experimental periods of both trials. Dietary SFM at a substitution rate higher than 40% SBM resulted in an increase (P
Stability of Entomopathogenic Fungi Beauveria bassiana and Metarhizium anisopliae on Beetle-attracting Tubers and Cowpea Foliage in Brazil

Conidia of two entomogenous fungi, Beauveria bassiana (Balsamo) and Metarhizium anisopliae (Metschnikoff) Sorokin, were applied to chrysomelid beetle-attracting tubers, Ceratosanthes hilariana Cogniaux, cowpea foliage, and cover slips and held outdoors under three exposure conditions of sunlight, or in the laboratory at 27 and 4°C, to determine the stability of conidia for potential use as microbial control agents of chrysomelid pests of grain legumes in Brazil. Under each exposure condition of sunlight (i.e., full, partial, or no protection from sunlight) conidia of B. bassiana survived best on the cucurbitaceous tubers, but the persistence of M. anisopliae conidia was more variable. In all cases for both fungi, exposure of conidia to full sunlight on all substrates was most detrimental to conidial stability; the half-life was generally 1–2 days and conidia were inviable within 1 week of exposure to sunlight. In contrast, conidia protected from sunlight survived much longer, in some cases remaining highly viable for ≥3 weeks. Results indicate that B. bassiana conidia retain high stability on beetle-attracting tubers if protected from sunlight. Use of fungal-treated tubers as a bait for control of chrysomelid beetles in cowpea-growing regions of Brazil or other countries is of potential importance.
The proteostatic effects of traffic-derived air pollution on Alzheimer's disease risk

Alzheimer's disease (AD) is an age-related neurodegenerative disease and the leading cause of dementia in the elderly. Recent decades have been marked by considerable advances in our understanding of genetic and environmental risk factors and also of the AD mechanism(s) of action. Nonetheless, there is still no cure and the myriad ways AD affects the brain is overwhelmingly complex. Such complexity is manifest in part by the fact that genetic background interacts with the environment, including traffic-derived particulate air pollution, to greatly exacerbate AD risk. Determining the mechanisms by which particulate air pollution acts as an AD risk factor has the potential to reveal yet unknown aspects of AD pathology. This review carefully peels back the layers of complexity to discern whether a unifying disease model, one with proteostasis imbalance at its core, holds up to scrutiny in light of the recent literature. While the data are compelling, it is now time for carefully designed studies to definitively determine whether particulate air pollution acts with ageing, genetic background and other sources of proteotoxic stress to disrupt the delicate proteostasis balance.
The Arabidopsis AS2 Gene Encoding a Predicted Leucine-zipper Protein Is Required for the Leaf Polarity Formation

The asymmetric leaves2as2) is a classical Arabidopsis thaliana (L.) Heynh. mutant that shows leaf lobes and leaflet_like structures from the petioles of leaves. Genetic and molecular analyses have demonstrated that theAS2[WTBZfunction is required for repression of meristem_related homeobox genes in leaves. In this study, we describe phenotypic characterizations of newas2alleles that are in the Landsberg erecta (Ler) genetic background. In addition to theas2phenotypes reported previously, the newas2mutants have some leaves with petiole growth underneath the leaf blade, showing a lotus_leaf structure. More severe rosettes leaves of theas2mutants form a filament_like structure, reflecting a loss of the adaxial_abaxial polarity in leaves. Amongas2mutants analyzed in different genetic backgrounds, only those that are in the Ler genetic background resulted in a high frequency of the lotus_leaf structure. We have isolated the[STBX]AS2gene by map_based gene cloning. The predictedAS2protein contains a leucine_zipper motif, and its N_terminus shares high levels of sequence similarity to those of a group of predicted proteins with no known biological functions. AS2transcripts were detected in leaves, flowers and fruits, but absent in stems, consistent with the mutant phenotypes.
NB-IoT Network Planning for Advanced Metering Infrastructure in Surabaya, Sidoarjo, and Gresik

Narrow Band Internet of Things (NB-IoT) technology is one of the Low Power Wide Area (LPWA) technologies with low cost, low power consumption, and wide range connectivity. NB-IoT is supported by cellular networks or Long-Term Evolution (LTE) with 3GPP Release 13 standard, making NB-IoT becomes an appropriate technology for the development and needs of the Internet of Things (IoT). Connectivity is needed to guarantee the service connection, in which one of the technologies is Narrow Band Internet of Things (NB-IoT). As an example of the NB-IoT rollout in urban areas, the study conducted the network design and analysis for AMI (Advanced Metering Infrastructure) in cities of Surabaya, Sidoarjo, and Gresik. The study result indicates that both coverage and capacity of the gateway requirements for Internet of Things (IoT) network planning using NB-IoT are 20 sites for the Surabaya area, 7 sites for the Sidoarjo area, and 5 sites for the Gresik area. Based on the simulations undertaken, the average acceptable signal levels are −57.9dBm for Surabaya, 59.62 dBm for Sidoarjo, and −58.71dBm for Gresik. And for Received Signal Strength Indicator (RSSI) value or sensitivity at the receiver for the three regions, the above standard sensitivity value for NB-IoT is −141dBm, while the minimum sensitivity value for the Surabaya, Sidoarjo and Gresik areas are −100dBm, −104dBm, and −105dBm. The study results also show different network planning parameters although it was planned in the same urban area and using the same capacity per cell approach model. It is possible to happen because of different environmental conditions, different number of users and different coverage areas in each urban city.
Competitive advantage of rare behaviours induces adaptive diversity rather than social conformity in skill learning

Recent studies have emphasized the role of social learning and cultural transmission in promoting conformity and uniformity in animal groups, but little attention has been given to the role of negative frequency-dependent learning in impeding conformity and promoting diversity instead. Here, we show experimentally that under competitive conditions that are common in nature, social foragers (although capable of social learning) are likely to develop diversity in foraging specialization rather than uniformity. Naive house sparrows that were introduced into groups of foraging specialists did not conform to the behaviour of the specialists, but rather learned to use the alternative food-related cues, thus forming groups of complementary specialists. We further show that individuals in such groups may forage more effectively in diverse environments. Our results suggest that when the benefit from socially acquired skills diminishes through competition in a negative frequency-dependent manner, animal societies will become behaviourally diverse rather than uniform.
3D Localization for Light-Field Microscopy via Convolutional Sparse Coding on Epipolar Images

Light-field microscopy (LFM) is a type of all-optical imaging system that is able to capture 4D geometric information of light rays and can reconstruct a 3D model from a single snapshot. In this paper, we propose a new 3D localization approach to effectively detect 3D positions of neuronal cells from a single light-field image with high accuracy and outstanding robustness to light scattering. This is achieved by constructing a depth-aware dictionary and by combining it with convolutional sparse coding. Specifically, our approach includes 3 key parts: light-field calibration, depth-aware dictionary construction, and localization based on convolutional sparse coding (CSC). In the first part, an observed raw light-field image is calibrated and then decoded into a two-plane parameterized 4D format which leads to the epi-polar plane image (EPI). The second part involves simulating a set of light-fields using a wave-optics forward model for a ball-shaped volume that is located at different depths. Then, a depth-aware dictionary is constructed where each element is a synthetic EPI associated to a specific depth. Finally, by taking full advantage of the sparsity prior and shift-invariance property of EPI, 3D localization is achieved via convolutional sparse coding on an observed EPI with respect to the depth-aware EPI dictionary. We evaluate our approach on both non-scattering specimen (fluorescent beads suspended in agarose gel) and scattering media (brain tissues of genetically encoded mice). Extensive experiments demonstrate that our approach can reliably detect the 3D positions of granular targets with small Root Mean Square Error (RMSE), high robustness to optical aberration and light scattering in mammalian brain tissues.