Miracle-dz/UniFAR-FTUs huggingface dataset:
Virtual-Grid Based Traffic Control Strategy With Multiple Intersections Collaboration

This paper proposes a dynamic cooperative traffic control framework for multiple intersections based on virtual grids to optimize the throughput and ensure fairness among all traffic flows. The traffic flows are divided by virtual grids; we call it virtual grid-based cooperative control of multiple-intersections (VGCC). The road segment between two intersections has been divided into two parts, which are defined as the reference region and the decision region. When the vehicle arrives at or goes away from any one part, it registers or deregisters itself to the road side unit. The traffic controller at intersection, called intersection control unit, collects the traffic information from all road segments and receives traffic messages from adjacent intersections. The proposed signal-scheduling algorithm considers not only the flows at the local intersection with higher passing rates but also the flows at downstream signalized intersections with higher passing rates. To ensure fairness, the algorithm gives chances to those phases who has a lower passing rate by using the ageing-counter matrix. According to the real-time traffic information, this paper makes signal timing for each phase of a signal cycle one by one. Moreover, a cooperative collision avoidance predictive control algorithm is proposed, which can assist vehicles to pass the next intersection without stopping, by predicting the time conflict. The results indicate that the VGCC algorithm significantly decreases the average number of vehicles on a road segment by 30.77%, reduces the average queuing length by 28.89%, decreases the average time spent on passing intersection by 26.93%, and reduces the average waiting time by 35.21% than the intersection of common road networks algorithm.
Influence of sevoflurane anesthesia with mechanical ventilation and fluid-therapy on distribution of subcutaneously administered robenacoxib in dogs

Robenacoxib is a novel nonsteroidal anti-inflammatory drug approved for dogs. The present study aimed to evaluate influences of sevoflurane anesthesia on the distribution of robenacoxib in dogs. Ten healthy beagle dogs (1 to 11 years old, 9.3 to 14.3 kg body weight, 6 males and 4 females) were subcutaneously administered robenacoxib (2 mg/kg) under conscious condition or sevoflurane anesthesia inhaled a 1.3-fold predetermined individual minimum alveolar concentration of sevoflurane at a 28-day interval. The dogs under sevoflurane anesthesia were also mechanically ventilated and received fluid-therapy. On each occasion, serum samples were collected from the dogs before and at 5, 15, 30, 60, 120, 180, and 240 min after the robenacoxib administration. Serum robenacoxib concentration was measured by a liquid chromatography-tandem mass spectrometry. Maximum serum concentration of robenacoxib (Cmax) was 2.2 µg/ml [range: 1.2–4.6] (median [range: minimum-maximum]) and time of Cmax (Tmax) was 90 min [range: 60–120] in the conscious dogs. In the sevoflurane-anesthetized dogs, the Cmax significantly declined (1.3 µg/ml [range: 0.8–1.4], P=0.008) and Tmax was delayed (120 min [range: 120–240], P=0.018) compared with those in the conscious dogs. The serum robenacoxib concentration at 240 min (C240) decreased to 0.5 µg/ml [range: 0.2–0.9] in the conscious dogs, while it remained higher in the sevoflurane-anesthetized dogs (1.0 µg/ml [range: 0.3–1.4], P=0.011). In conclusion, the anesthetic procedure with sevoflurane, mechanically ventilated, and received fluid-therapy might affect the pharmacokinetics of subcutaneously administered robenacoxib in dogs.
Brief Mindfulness Meditation Improves Attention in Novices: Evidence From ERPs and Moderation by Neuroticism

Past research has found that mindfulness meditation training improves executive attention. Event-related potentials (ERPs) have indicated that this effect could be driven by more efficient allocation of resources on demanding attentional tasks, such as the Flanker Task and the Attention Network Test (ANT). However, it is not clear whether these changes depend on long-term practice. In two studies, we sought to investigate the effects of a brief, 10-min meditation session on attention in novice meditators, compared to a control activity. We also tested moderation by individual differences in neuroticism and the possible underlying neural mechanisms driving these effects, using ERPs. In Study 1, participants randomly assigned to listen to a 10-min meditation tape had better accuracy on incongruent trials on a Flanker task, with no detriment in reaction times (RTs), indicating better allocation of resources. In Study 2, those assigned to listen to a meditation tape performed an ANT more quickly than control participants, with no detriment in performance. Neuroticism moderated both of these effects, and ERPs showed that those individuals lower in neuroticism who meditated for 10 min exhibited a larger N2 to incongruent trials compared to those who listened to a control tape; whereas those individuals higher in neuroticism did not. Together, our results support the hypothesis that even brief meditation improves allocation of attentional resources in some novices.
Modeling the Structure of Acute Sport-Related Concussion Symptoms: A Bifactor Approach

Abstract Objectives: Concussions cause diverse symptoms that are often measured through a single symptom severity score. Researchers have postulated distinct dimensions of concussion symptoms, raising the possibility that total scores may not accurately represent their multidimensional nature. This study examined to what degree concussion symptoms, assessed by the Sport Concussion Assessment Tool 3 (SCAT3), reflect a unidimensional versus multidimensional construct to inform how the SCAT3 should be scored and advance efforts to identify distinct phenotypes of concussion. Methods: Data were aggregated across two prospective studies of sport-related concussion, yielding 219 high school and college athletes in the acute (<48 hr) post-injury period. Item-level ratings on the SCAT3 checklist were analyzed through exploratory and confirmatory factor analyses. We specified higher-order and bifactor models and compared their fit, interpretability, and external correlates. Results: The best-fitting model was a five-factor bifactor model that included a general factor on which all items loaded and four specific factors reflecting emotional symptoms, torpor, sensory sensitivities, and headache symptoms. The bifactor model demonstrated better discriminant validity than the counterpart higher-order model, in which the factors were highly correlated (r=.55–.91). Conclusions: The SCAT3 contains items that appear unidimensional, suggesting that it is appropriate to quantify concussion symptoms with total scores. However, evidence of multidimensionality was revealed using bifactor modeling. Additional work is needed to clarify the nature of factors identified by this model, explicate their clinical and research utility, and determine to what degree the model applies to other stages of injury recovery and patient subgroups. (JINS, 2018, 24, 793–804)
Sex differences in murine cardiac pathophysiology with hyperoxia exposure

Hyperoxia (>90% oxygen) is commonly implemented in mechanically ventilated patients. Reports suggest that hyperoxia is directly associated with in‐hospital mortality in ventilated patients. Certain studies also show that mortality in women undergoing mechanical ventilation is significantly higher than that in men. Additionally, females are predisposed to certain cardiac electrophysiological risks, including QTc prolongation. In this study, we assessed the impact of hyperoxia in male and female mice (C57BL/6J) at age 8–10 weeks. On completion of either hyperoxia or normoxia exposures, physical, hemodynamic, biochemical, functional, electrophysiological, and molecular assessments were conducted. Hyperoxia‐exposed mice lost a significant amount of body mass, compared with normoxia controls, in both sexes. However, while both genders developed brady‐arrhythmia after hyperoxia exposure, female mice exhibited significantly reduced heart rates compared with males, with significantly elevated RR intervals. Additionally, 50% mortality was observed in females, whereas no mortality was reported in males. Furthermore, unlike in male mice, we observed no hypertrophy upon hyperoxia exposure in female mice. We reported that both hyperoxia‐treated male and female mice exhibit significant hyperdynamic left ventricular ejection fraction, which is marked by % ejection fraction > 70 compared with the normoxia controls. We also noted significant reductions in stroke volume and cardiac output in both mice with hyperoxia. Surface ECG also demonstrated that hyperoxia exposure significantly augments RR, PR, QRS, QTc, and JT intervals in both sexes. Molecular analysis of left ventricular tissue demonstrated dysregulation of potassium ion channels in hyperoxia‐treated males and females. In summary, we determined that sex differences are present with 72 hr hyperoxia exposure.
Mouse Authentication Without the Temporal Aspect – What Does a 2D-CNN Learn?

Mouse dynamics as behavioral biometrics are under investigation for their effectiveness in computer security systems. Previous state-of-the-art methods relied on heuristic feature engineering for the extraction of features. Our work addresses this issue by learning the features with a convolutional neural network (CNN), thereby eliminating the need for manual feature design. Contrary to time-series-based modeling approaches, we propose to use a two-dimensional CNN with images as inputs. While counterintuitive at first sight, it permits to profit from well-initialized lower-layer kernels obtained via transfer learning. We demonstrate our results on two public datasets, Balabit and TWOS, and compare against a 1D-CNN and a classical baseline relying on hand-crafted features, which are both outperformed. We show that a position-independent variant of the 2D-CNN loses little performance yet we learned that the trained classifier is very sensitive to simulated resolution shifts at test time. In a final step, we analyze and visualize the learned features on single test curves using layer-wise relevance propagation (LRP). This analysis reveals that the 2D-CNN uses curve information only sparsely, with a tendency to assign little relevance to straight segments and artifactual curve crossings.
Psychometric Properties and Factor Structures of Chinese Smartphone Addiction Inventory: Test of Two Models

There has been a growing concern of excessive smartphone use that interferes with people’s daily functioning, most notably among youngsters. The Smartphone Addiction Inventory (SPAI) was constructed to assess this type of information technology addiction. Although the SPAI was developed in a Taiwanese adolescent sample, this measure has not been validated on Chinese youngsters in other regions. Moreover, the initial evidence yielded a four-factor structure, but recent findings obtained an alternative five-factor structure. As no studies have systematically compared these two factor structures, which of the models fits the data better remained unknown. This study aimed to evaluate the empirical validity of both the four- and five-factor structures of the SPAI in a sample of university students from Mainland China (n = 463). Four psychometric properties of the SPAI were examined. First, the structural validity of both factor models was evaluated with confirmatory factor analysis. Satisfactory fit was found for both the five-factor model (RMSEA = 0.06, SRMR = 0.05, CFI = 0.99, TLI = 0.99) and the four-factor model (RMSEA = 0.07, SRMR = 0.06, CFI = 0.98, TLI = 0.98), but the five-factor model demonstrated an overall better model fit. Second, the five-factor model yielded good internal consistencies (all Cronbach α’s > 0.70). Third, concurrent validity of the SPAI was supported by its moderately strong correlations with four widely adopted criterion variables (i.e., loneliness, social anxiety, depression, and impulsivity). Lastly, the convergent validity of the SPAI was demonstrated by its strong, positive correlation with a popular, validated measure of Internet addiction. This study is the first to demonstrate the validity of the newly proposed five-factor model of the SPAI in a sample of Mainland Chinese youngsters.
High-Performance High-Order Stencil Computation on FPGAs Using OpenCL

In this paper we evaluate the performance of FPGAs for high-order stencil computation using High-Level Synthesis. We show that despite the higher computation intensity and on-chip memory requirement of such stencils compared to first-order ones, our design technique with combined spatial and temporal blocking remains effective. This allows us to reach similar, or even higher, compute performance compared to first-order stencils. We use an OpenCL-based design that, apart from parameterizing performance knobs, also parameterizes the stencil radius. Furthermore, we show that our performance model exhibits the same accuracy as first-order stencils in predicting the performance of high-order ones. On an Intel Arria 10 GX 1150 device, for 2D and 3D star-shaped stencils, we achieve over 700 and 270 GFLOP/s of compute performance, respectively, up to a stencil radius of four. These results outperform the state-of-the-art YASK framework on a modern Xeon for 2D and 3D stencils, and outperform a modern Xeon Phi for 2D stencils, while achieving competitive performance in 3D. Furthermore, our FPGA design achieves better power efficiency in almost all cases.
The lysine acetyltransferase GCN5 contributes to human papillomavirus oncoprotein E7‐induced cell proliferation via up‐regulating E2F1

General control nondepressible 5 (GCN5), the first identified transcription‐related lysine acetyltransferase (KAT), is an important catalytic component of a transcriptional regulatory SAGA (Spt‐Ada‐GCN5‐Acetyltransferase) and ATAC (ADA2A‐containing) complex. While GCN5 has been implicated in cancer development, its role in cervical cancer is not known. The human papillomavirus (HPV) oncoprotein E7 abrogates the G1 cell cycle checkpoint and induces genomic instability, which plays a central role in cervical carcinogenesis. In this study, we observed that GCN5 was up‐regulated in HPV E7‐expressing cells, knockdown of GCN5 inhibited cell cycle progression and DNA synthesis in HPV E7‐expressing cells. Notably, GCN5 knockdown reduced the steady‐state levels of transcription factor E2F1. Depletion of E2F1 caused G1 arrest while overexpression of E2F1 rescued the inhibitory effects of GCN5 knockdown on G1/S progression in HPV E7‐expressing cells. Results from chromatin immunoprecipitation (ChIP) assays demonstrated that GCN5 bound to the E2F1 promoter and increased the extent of histone acetylation within these regions. GCN5 also acetylated c‐Myc and increased its ability to bind to the E2F1 promoter. Knockdown of c‐Myc reduced the steady‐state levels of E2F1 and caused G1 arrest. These results revealed a novel mechanism of E7 function whereby elevated GCN5 acetylates histones and c‐Myc to regulate E2F1 expression and cell cycle progression.
Reactive Magnetic-Field-Inspired Navigation Method for Robots in Unknown Convex 3-D Environments

With a shift in current robotics application from known, well-defined environments toward unknown environments, the robot's ability to avoid unknown obstacles in real-time while relying on limited information about spatial constraints in its path becomes essential. Taking inspiration from the laws of electromagnetism, we present a novel navigation method, whereby the moving robot induces an artificial electric current onto the obstacle surface generating, in turn, a magnetic field guiding the robot along the obstacle's boundary without affecting its kinetic energy. Our method has several advantages over existing methods, which are as follows. 1) It guides point-like robots toward the goal without suffering from local minima in 3-D environments populated with convex obstacles. 2) It does not need any prior knowledge of obstacle positions and geometries. 3) It only requires environmental sensor information that is spatially and temporally local to generate motion commands iteratively. Our navigation method is tested in simulations and experiments, showing that a point-to-point navigation of point-like robots and the end effector of the Baxter's arm has been successfully achieved in a collision-free manner toward a goal position in a 3-D environment populated with unknown convex obstacles.
System Pharmacology-Based Strategy to Decode the Synergistic Mechanism of Zhi-zhu Wan for Functional Dyspepsia

Functional dyspepsia (FD) is a widely prevalent gastrointestinal disorder throughout the world, whereas the efficacy of current treatment in the Western countries is limited. As the symptom is equivalent to the traditional Chinese medicine (TCM) term “stuffiness and fullness,” FD can be treated with Zhi-zhu Wan (ZZW) which is a kind of Chinese patent medicine. However, the “multi-component” and “multi-target” feature of Chinese patent medicine makes it challenge to elucidate the potential therapeutic mechanisms of ZZW on FD. Presently, a novel system pharmacology model including pharmacokinetic parameters, pharmacological data, and component contribution score (CS) is constructed to decipher the potential therapeutic mechanism of ZZW on FD. Finally, 61 components with favorable pharmacokinetic profiles and biological activities were obtained through ADME (absorption, distribution, metabolism, and excretion) screening in silico. The related targets of these components are identified by component targeting process followed by GO analysis and pathway enrichment analysis. And systematic analysis found that through acting on the target related to inflammation, gastrointestinal peristalsis, and mental disorder, ZZW plays a synergistic and complementary effect on FD at the pathway level. Furthermore, the component CS showed that 29 components contributed 90.18% of the total CS values of ZZW for the FD treatment, which suggested that the effective therapeutic effects of ZZW for FD are derived from all active components, not a few components. This study proposes the system pharmacology method and discovers the potent combination therapeutic mechanisms of ZZW for FD. This strategy will provide a reference method for other TCM mechanism research.
In Vivo Biocompatibility of an Ionic Liquid-protected Silver Nanoparticle Solution as Root Canal Irrigant

Introduction: The aim of this study was to assess the biocompatibility of positively charged imidazolium-based ionic liquid-protected nanosilver solution (AgNPs) root canal irrigant. Methods and Materials: Eighteen male 4- to 5-month old Sprague-Dawley rats, weighing 200-300 gr were selected and randomly divided into 5 groups: Normal saline 0.9% (group 1), 5.25% NaOCl (group 2), 2.5% NaOCl (group 3), 2.0% chlorhexidine solution (group 4) and AgNPs at 5.7×10-8 M/L (group 5) were randomly injected in 5 sites of dorsal skin of each rat. Tissue inflammatory reaction were evaluated histopathologically after 2 h, 48 h and 14 days. Statistical analysis was done with SPSS version 21 and the Kruskal-Wallis H and Dunn tests were used to find statistically significant differences. The level of significance was set at 0.05. Result: All solutions irritated the highest tissue response after 48 h. Group 1 showed lower inflammatory response compared to groups 2 and 4 (P<0.05). Group 2 displayed higher inflammatory response in comparison with group 5 (P<0.05). Tissue reaction to group 5 was not more severe than the reaction to group 3 or 4. It also would irritate less inflammatory response compared to group 2 (P<0.05). Conclusion: Comparing with NaOCl and CHX, it is possible to label AgNPs as a tissue compatible agent.
Rectangular Waveguide Filters With Meandered Topology

In this paper, a new topology for rectangular waveguide bandpass and low-pass filters is presented. A simple, accurate, and robust design technique for these novel meandered waveguide filters is provided. The proposed filters employ a concatenation of ±90° $E$ -plane mitered bends (±90° EMBs) with different heights and lengths, whose dimensions are consecutively and independently calculated. Each ±90° EMB satisfies a local target reflection coefficient along the device so that they can be calculated separately. The novel structures allow drastically reduce the total length of the filters and embed bends if desired, or even to provide routing capabilities. Furthermore, the new meandered topology allows the introduction of transmission zeros above the passband of the low-pass filter, which can be controlled by the free parameters of the ±90° EMBs. A bandpass and a low-pass filter with meandered topology have been designed following the proposed novel technique. Measurements of the manufactured prototypes are also included to validate the novel topology and design technique, achieving excellent agreement with the simulation results.
Biotechnological approaches in glucosinolate production

Abstract Glucosinolates (GLSs) are sulfur‐rich, amino acid‐derived defense compounds characteristic of the Brassicales order. In the past, GLSs were mostly known as anti‐nutritional factors in fodder, biopesticides in agriculture, and flavors in condiments such as mustard. However, in recent times, GLSs have received increased attention as promoters of human health. This has spurred intensive research towards generating rich sources of health‐promoting GLSs. We provide a comprehensive overview of the biotechnological approaches applied to reach this goal. This includes optimization of GLS production and composition in native, GLS‐producing plants, including hairy root and cell cultures thereof, as well as synthetic biology approaches in heterologous hosts, such as tobacco and the microbial organisms Escherichia coli and Saccharomyces cerevisiae. The progress using these different approaches is discussed.
Coordinate Methods for Accelerating ℓ ∞ Regression and Faster Approximate Maximum Flow

In this paper we provide faster algorithms for approximately solving ℓ ∞ regression, a fundamental problem prevalent in both combinatorial and continuous optimization (for example, it was shown in [LS15a] that ℓ ∞ regression is equivalent to solving linear programming). In particular we provide an accelerated coordinate descent method which converges in k iterations at a O (cid:0) 1 k (cid:1) rate independent of the dimension of the problem, and whose iterations can be implemented cheaply for many structured matrices. Our algorithm can be viewed as an alternative approach to the recent breakthrough result of Sherman [She17] which achieves a similar running time improvement over classic algorithmic approaches, i.e. smoothing and gradient descent, which either converge at a O (cid:16) 1 √ k (cid:17) rate or have running times with a worse dependence on problem parameters. Our running times match those of [She17] across a broad range of parameters and in certain cases, improves upon it. We demonstrate the eﬃcacy of our result by providing faster algorithms for the well-studied maximum ﬂow problem. We show how to leverage our algorithm to achieve a runtime of ˜ O (cid:16) m + √ nsǫ (cid:17) to compute an ǫ -approximate maximum ﬂow, for an undirected graph with m edges, n vertices, and where s is the squared ℓ 2 norm of the congestion of any optimal ﬂow. As s = O ( m ) this yields a running time of ˜ O (cid:16) m + √ nmǫ (cid:17) , generically improving upon the previous best known runtime of ˜ O (cid:0) mǫ (cid:1) in [She17] whenever the graph is slightly dense. Moreover, we show how to