Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Regulation of Metabolic Pathways in β-Cells Disrupted by Hyperglycemia*

In models of type 2 diabetes the expression of β-cell genes is altered, but these changes have not fully explained the impairment in β-cell function. We hypothesized that changes in β-cell phenotype and global alterations in both carbohydrate and lipid pathways are likely to contribute to secretory abnormalities. Therefore, expression of genes involved in carbohydrate and lipid metabolism were analyzed in islets 4 weeks after 85–95% partial pancreatectomy (Px) when β-cells have impaired glucose-induced insulin secretion and ATP synthesis. Px rats after 1 week developed mild to severe hyperglycemia that was stable for the next 3 weeks, whereas neither plasma triglyceride, non-esterified fatty acid, or islet triglyceride levels were altered. Expression of peroxisome proliferator-activated receptors (PPARs), with several target genes, were reciprocally regulated; PPARα was markedly reduced even at low level hyperglycemia, whereas PPARγ was progressively increased with increasing hyperglycemia. Uncoupling protein 2 (UCP-2) was increased as were other genes barely expressed in sham islets including lactate dehydrogenase-A (LDH-A), lactate (monocarboxylate) transporters, glucose-6-phosphatase, fructose-1,6-bisphosphatase, 12-lipoxygenase, and cyclooxygenase 2. On the other hand, the expression of β-cell-associated genes, insulin, and GLUT2 were decreased. Treating Px rats with phlorizin normalized hyperglycemia without effecting plasma fatty acids and reversed the changes in gene expression implicating the importance of hyperglycemiaper se in the loss of β-cell phenotype. In addition, parallel changes were observed in β-cell-enriched tissue dissected by laser capture microdissection from the central core of islets. In conclusion, chronic hyperglycemia leads to a critical loss of β-cell differentiation with altered expression of genes involved in multiple metabolic pathways diversionary to normal β-cell glucose metabolism. This global maladaptation in gene expression at the time of increased secretory demand may contribute to the β-cell dysfunction found in diabetes.
Content Caching Policy Based on GAN and Distributional Reinforcement Learning

To reduce content transmission power and network load pressure, content caching technology based on a large number of small base stations (SBSs) is considered to be an effective solution. However, due to the limited cache capacity and unknown content popularity, how to design an intelligent content caching policy has become a great challenge. In this paper, we propose a generative adversarial network (GAN) based on the distributional deep Q-Network (DDQN) algorithm, named QGAN, to learn the content caching policy. A content caching network that contains several cooperative SBSs is considered in the case of unknown content popularity, where each SBS fetches cached content from the adjacent SBS or cloud. Moreover, compared with three classical content caching policies and one reinforcement learning algorithm, the performance of the QGAN algorithm is verified. The simulation results show that the convergence rate is improved and the transmission cost is reduced with the proposed algorithm.
Adaptive Coordination of Damping Controllers for Enhanced Power System Stability

This paper introduces the concept of adaptive coordination of damping controllers for enhancing power system stability. The coordination uses phasor measurement units (PMUs) to adapt to different disturbances by selecting the switching status (on/off) of damping controllers that minimizes an energy-based dynamic performance measure. This dynamic performance measure, referred to as total action (TA), uses a physical interpretation of excited modes rather than fixed targeted modes as in the traditional damping control design. The coordination is formulated as a binary integer programming problem, which is solved by using the total action sensitivity (TAS). The concept of oscillation energy and the implementation of the adaptive coordination scheme is tested in the western North America power system (wNAPS). The results show that the proposed adaptive control scheme can improve oscillation damping for different short-circuit locations even in the presence of large communication delays.
Fetal Testosterone: Developmental Effects on Externalizing Behavior

Fetal testosterone (FT) exposure influences sexual differentiation and may promote wellestablished sex differences in externalizing (EXT) behavior. Although puberty may be a critical period for these effects, it is unknown how FT exposure influences EXT as a function of pubertal development. We used a longitudinal, multi-sample design to test the relationships between two proxy indices of FT exposure and EXT as a function of age and pubertal development (approximately ages 6, 9, 11, 14, and 16). Twin data were used to approximate FT exposure (TTFT) because testosterone is thought to cross the intrauterine membrane and cause variability in co-twin gonadal hormone exposure, with increasing exposure for males and participants with male co-twins. Increasing number of older siblings may also approximate increasing FT exposure (SI-FT), although existing research has yet to disentangle possible postnatal socialization effects from potential FT exposure using this variable. Given that biologically related siblings share a fetal and social environment while non-biologically related siblings simply share a social environment, we tested the independent effect of SI-FT on EXT using a sibling adoption design. Across four independent samples, SI-FT and TT-FT predicted externalizing for males alone. SI-FT predicted EXT over-and-above socialization influences and interacted with pubertal development in two independent samples, with elevated EXT for those in mid-late puberty that were exposed to increased FT. TT-FT predicted EXT differentially as a function of developmental period. Our data are consistent with the notion that exposure to FT promotes sexually differentiated, sexually selected behavior during reproductively relevant periods.
Environmental flows, river salinity and biodiversity conservation: managing trade-offs in the Murray-Darling basin

The Murray–Darling basin's river system suffers from over-allocation of water resources to consumptive use and salinity threats to water quality. This paper draws attention to the current state of knowledge and the need for further investigations into the biological effect of river salinity on aquatic biota and ecosystems, the threats of dryland salinity to terrestrial biodiversity, and managing environmental flows and salinity control to limit the trade-offs in water-resource security and river salinity. There is growing evidence that river salt concentrations lower than the normally adopted threshold have sublethal effects on species and ecosystems, over a longer time period. Further knowledge is required. There is no agreed process for incorporating terrestrial biodiversity values at risk into a strategic response for dryland-salinity management. This is a public policy issue to be addressed. Recent studies have quantified the trade-off in surface water flow and river salinity from refforestation and revegetation of upland catchments to control salinity. The potential losses or benefits to environmental values have not been quantified. Such improved knowledge is important to the Murray–Darling basin and relevant to other river basins and catchments in Australia.
Comparison of dentin penetration ability of different root canal sealers used with different obturation methods

This in vitro study aimed to investigate the tubular penetration depth of four different sealers used with two different obturation methods in the apical, middle, and coronal root canal dentin. Eighty‐four single‐rooted teeth were instrumented until the F4 ProTaper universal rotary file and filled with AH26, AH Plus (Dentsply, DeTrey, Konstanz, Germany), RealSeal (SybronEndo, Orange, CA), and MTA Fillapex (Angelus, Londrina, Brazil) using cold lateral condensation (CLC) and single‐cone (SC) obturation techniques. Thereafter, the roots were sectioned longitudinal and prepared for scanning electron microscope evaluation. The maximum and minimum sealers penetration depth into dentinal tubules at the apical, middle, and coronal regions and the average depth of sealer penetration were calculated. The data was statistically analyzed two‐way ANOVA and post hoc Tukey and Dunnett tests and independent samples t test using maximum mean values. There was no statistically difference between the obturation methods (p > .05). When the sealers are evaluated within themselves AH26 was affected by obturation methods significantly (p < .05). Also the results revealed a significant difference between root regions (p < .05). AH26 and RealSeal root canal sealers had the highest penetration values with CLC and SC obturation techniques, respectively. The obturation method did not affect the penetration amount of root canal sealers. RealSeal root canal sealer performed better penetration ability than the other sealers. Apical third of the root in all groups showed lowest penetration depth.
Weighted Averaged Behavior of Synchronization among Heterogeneous Agents in a Sampled-data Setting *

In this paper, we address the problem of synchronization among heterogeneous agents in a sampled-data setting. The key observation is that the sample-and-hold process introduces additional node-wise weights on the Laplacian matrix in the discrete-time domain. We then show that in the sampled-data setting, all of the agents’ states approach the state of the so-called weighted averaged dynamics, an auxiliary dynamics that represents the collective behavior of heterogeneous agents when they are synchronized. In addition, admissible ranges of the sampling period and the diffusive coupling gain are computed, with which the consensus among the agents is achieved in a practical sense.
The Moderation Influence of Power Distance on the Relationship Between Technological Factors and the Successful Implementation of Citizen Relationship Management in the Public Sector

The revolution of information and communication technology and the widespread use of it in all aspects of daily life, whether on a personal or institutional level, leads to the increase demand of citizens to get advanced and integrated electronic services. This has pushed many government institutions to implement Citizen Relationship Management systems to improve their performance and provide more sophisticated, efficient and effective services to citizens. However, previous studies have revealed the high rates of failure of such systems, and institutions have suffered significant financial losses. Studies on successful implementation of these systems in the public sector are rare, leaving us a nearly unexplored field of research. This study reinforced the body of knowledge on the successful implementation of Citizen Relationship Management by attempting to bridge the gap in previous studies and propose a comprehensive, unique and innovative theoretical model combining the technological context of Technological, Organizational, and Environmental (TOE) theory, and the power distance factor of Hofstede’s national cultural model as a moderator. This study aims to provide new insights into the factors that affect the successful implementation of Citizen Relationship management. The model was examined empirically through a quantitative study conducted on one of the Omani government institutions. The theoretical framework was verified using the structural equation modeling (SEM) approach using SmartPLS software. IT infrastructure and system quality found to be significant technological factors affecting the successful implementation of Citizen Relationship Management. Further, the power distance found to be significant moderator.
Design of smooth path based on the conversion between η3 spline and Bezier curve

Convex hull property is an important characteristic of designing control points of Bezier curves, which can be used for obstacle avoidance in path generating. η3-splines belong to a kind of 7th degree G3 polynomial curves that interpolate the boundary conditions of position, tangent, curvature and curvature derivative. In this research, the derivation of equivalence bijective transformation from simplified η3-splines to 7th degree Bezier curves is presented to take advantage of these two kinds of curves. Therefore, the manipulation of simplified η3-splines becomes more intuitive, and the design of Bezier curves to satisfy boundary conditions on the curvature and curvature derivative is computationally simpler. In addition, the transformation allows a clear geometric interpretation of the η parameter in terms of the control points. We propose the usage of this transformation as a basis for a path design procedure with an illustration of vehicle entering into roundabout.
New Insights into Crystallization of Heterophasic Isotactic Polypropylene by Fast Scanning Chip Calorimetry

The crystallization kinetics of metallocene-catalyzed heterophasic isotactic polypropylene composed of a matrix of isotactic polypropylene (iPP) and rubbery particles made of random ethylene–propylene copolymers (EPC), often denoted as heterophasic iPP copolymers, was analyzed as a function of the cooling rate and supercooling in nonisothermal and isothermal crystallization experiments, respectively. Fast scanning chip calorimetry (FSC) allowed assessing crystallization at processing-relevant conditions, and variation of the content (0–39 wt %) and composition (0–35 wt % propylene counits) of the EPC particles revealed qualitatively new insight about mechanisms of heterogeneous crystal nucleation. For neat iPP homopolymer, the characteristic bimodal temperature dependence of the crystallization rate due to predominance of heterogeneous and homogeneous crystal nucleation at high and low temperatures, respectively, is reconfirmed. At high temperatures, in heterophasic iPP, the here studied ethylene-(C2)-rich EPC particles accelerate crystallization of the iPP-matrix, with the acceleration or nucleation efficacy correlating with the EPC-particle content. The crystallization time reduces by more than half in presence of 39 wt % EPC particles. An additional nucleating effect of the EPC particles on iPP-matrix crystallization is detected after their crystallization, suggesting that liquid/rubbery particles are less effective than solid/semicrystalline particles in affecting crystallization of the surrounding iPP-matrix. At low temperature, homogeneous crystal nucleation in the iPP-matrix outpaces all heterogeneous nucleation effects, and the matrix-crystallization rate is independent of the sample composition. The obtained results lead to the conclusion that the crystallization kinetics of iPP can be affected significantly by the content and composition of EPC particles, even towards superfast crystallizing iPP grades.
Detecting Video Speed Manipulation

Manipulated videos are frequently an important part of misinformation campaigns. While much attention has recently focused on sophisticated threats such as deepfakes, the majority of videos used in misinformation campaigns have been created using relatively simple manipulations that can be produced by commonly available editing software. One important manipulation that has been used in previous misinformation attempts is altering the speed of a video. In the previous 18 months, widely circulated videos have had their speed manipulated to make Speaker of the House Nancy Pelosi appear disoriented, and to make reporter Jim Acosta appear to act aggressively toward a White House staffer. Currently, however, there are no approaches to accurately detect video speed manipulation that can be deployed at scale. In this paper, we propose new algorithms to detect video speed manipulation and to estimate the rate by which a video’s speed has been modified. To do this, we identify a new trace left by video speed manipulation and show how it can be extracted from a video. Our approaches to trace extraction, speed manipulation detection, and manipulation rate estimation are computationally efficient and can be run in a matter of milliseconds. We present experimental results that show that our proposed approach can detect manipulated videos with up to 99% accuracy.
NumbaSummarizer: A Python Library for Simplified Vectorization Reports

Python is a very popular programming language and has been adopted by many learning institutions as the first or only programming language taught to students. While its simple syntax and gentle learning curve makes it a very attractive option for new programmers, among its main drawbacks are that it obviates many key concepts of programming and computer architecture as well as rarely optimizing code to modern architectures.There are tools that provide optimizing capability for Python programmers. Numba is a JIT compiler for Python that among other things, optimizes Python and Numpy functions for better performance. Numba can exploit automatic parallelism and vectorization.In this paper we present NumbaSummarizer, a wrapper for Numba’s vectorization module that works as a vectorization reporting tool. Students can use it to identify functions that are exploiting SIMD instructions. The main purpose of this tool is to teach students about Parallel Computing, Vectorization, Data Dependence, and Loop Transformations.We evaluated the use of NumbaSummarizer with 64 students during a course on intermediate programming. Most students had little to no background in Computer Architecture nor Parallel Computing. When asked to expose parallelism in a set of 8 loops, 95% percent of the students were able to transform and optimize at least 6 of these loops. When testing conceptual understanding, they scored an average of 95% for parallel computing concepts, and 62% for dependence analysis.
Navigation Functions with non-Point Destinations and Moving Obstacles

This paper formally expands the application domain of robot motion planning methods that are based on navigation functions to the case of moving obstacles. It generalizes the navigation function methodology from static sphere world environments, to dynamic ones. Specifically, it allows the obstacles’ locations to be time-varying, albeit unknown, and accommodates the case where the navigation goal is not a single isolated point, but rather a spherical manifold. For such cases, the paper presents analytical bounds on the tuning parameters that guarantee the navigation function properties of the time-varying potential function, uniformly in time. Thus using the same choice of tuning parameters, the agent is ensured that at every instance in time, the artificial potential field that directs it to its destination is free of local minima. The parameter bounds naturally depend on the geometry of the agent workspace, and include conditions on how close the obstacles can approach each other, the fixed workspace boundary, and the destination sphere. The bounds presented here are conservative; their analytic determination serves mainly the purpose of theoretically guaranteeing completeness properties for the methodology in the time-varying obstacle case.
Further Non-local and Channel Attention Networks for Vehicle Re-identification

Vehicle re-identification remains challenging due to large intra-class difference and small inter-class variance. To address this problem, in AICity Vehicle Re-ID task 2020, we propose a two-branch adaptive attention network—Further Non-local and Channel attention (FNC) to improve feature representation and discrimination. Specifically, inspired by two-stream theory of visual cortex, based on Non-local and channel relation, a two-branch FNC network is constructed to capture multiple useful information. Second, an effective attention fusion method is proposed to sufficiently model the effects from spatial and channel attention. The experimental results show that our algorithm achieves 66.25%/Rank-1 and 53.54%/mAP in 2020 AIC-ity Challenge Vehicle Re-ID task without using extra data, annotation and other auxiliary information, which demonstrate the effectiveness of the proposed FNC network.
Nonlinear model reduction based on stochastic obsevability

The practical applicability of analytical model reduction methods is limited. In this paper, we show an optimality of Proper Orthogonal Decomposition (POD) based nonlinear model reduction. POD is a simulation-based model reduction method that has been widely applied to nonlinear large-scale systems, but there is no theoretical background in general. An observability-based analytical nonlinear model reduction is not well proposed. In this paper, after deriving a stochastic observability using a duality between optimal control and optimal estimation, we show that the observability-based and simulation-based methodologies with weights are equivalent when the input is only stochastic signal. We also show an example of nonlinear model reduction method using the deep autoencoder.
Optimal PID Parameters Tunning for a DC-DC Boost Converter: A Performance Comparative Using Grey Wolf Optimizer, Particle Swarm Optimization and Genetic Algorithms

The Grey Wolf Optimizer (GWO) algorithm is a metaheuristic optimization method based on the hunting made by wolves in nature. In this work, the GWO algorithm was proposed for tuning a Proportional-Integral-Derivative (PID) controller parameters for a DC-DC boost converter. DC-DC boost converters are electronic devices widely used for voltage regulation in renewable energies applications, these devices need a controller, commonly a PID controller which needs to be correctly tuned to reduce the error between the reference voltage and the system output voltage. Classical PID controller tuning methods require a mathematical formulation or an empirical system response analysis, bioinspired optimization algorithms are an alternative for system design. This paper presents a performance comparative analysis between the proposed GWO algorithm, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The simulation was carried out using MATLAB/Simulink environment, then the tuned PID controller performance was evaluated using the system response analysis to variable load conditions and Root Mean Squared Error (RMSE) between reference and output voltage. Results showed that the proposed GWO algorithm has a lower RMSE compared to PSO and GA, and therefore, it could be an effective method for optimal PID controllers for power converters applications.
(How) should information world maps be visually analyzed?

Information world mapping (IWM) is a participatory, arts‐based elicitation method for use in interviews about information behaviours or practices. The participant‐drawn maps that result from this technique are typically used as ancillary data sources to aid in analysis of interview transcripts; however it may be possible, and even useful, to analyze these maps as data independent of the interviews, using methods suited to image analysis. This brief paper and accompanying visual presenta‐ tion describe results of analyses of information world maps using four different and contrasting methods with accompanying examples, and issue recommendations regarding the use of qualitative content analysis, compositional analysis, conceptual analysis, and visual discourse analysis, for analysis of information world maps. These insights may be generalized to other objects (e.g., photos) created through arts‐based elicitation interviewing.