Miracle-dz/UniFAR-FTUs huggingface dataset:
A Recent Survey on Control for Synchronization and Passivity of Complex Networks

Over the past few years, dynamical behaviors of complex networks (CNs) and complex networks with multi-weights (CNMWs) have attracted considerable attention on account of their successfully applying in many distinct fields. This paper attempts to introduce some recent progress in the dynamical behaviors (including synchronization and passivity) for CNs and CNMWs under various control approaches. Firstly, we focus on synchronization, passivity, and their extensions for CNs and CNMWs. Secondly, some control methods, such as adaptive control, pinning control, and impulsive control, used in CNs and CNMWs are also discussed, where some of the existing results along these topics are presented in a tutorial-like fashion. Thirdly, we introduce several applications of synchronization in CNs and CNMWs, especially complex human networks and urban public traffic networks. These existing results are summarized and some interesting future investigations are also highlighted in end.
Targeted mutagenesis of StISAC stabilizes the production of anthocyanins in potato cell culture

Abstract To increase the production of decorated anthocyanins in potato cell cultures, we knocked out a novel potato gene, named Inducer Silencing of Anthocyanins in Cell culture (StISAC), using CRISPR‐Cas9 editing. Our results provided evidence that mutant cell lines doubled the accumulation level of anthocyanins biosynthesized. Moreover, the production of these important pigments was stabilized over time. Our study overcame important challenges in the efficient biotechnological production of these valuable pigments and reported the function of a novel anthocyanin biosynthesis repressor gene.
Substantive Bias and Variation in the Acquisition of /n/~/l/ Alternation

Phonological biases suppose that language learners are predisposed toward certain sound patterns. A widely studied phonological bias is substantive bias, a bias that favors phonetically natural or motivated patterns. Experimental results for substantive bias have been mixed. Against this background, this study explores the possible factors influencing the effect of substantive bias, and the focus is on the input variability. An artificial language learning study on /n/~/l/ alternation by native speakers of Hong Kong Cantonese was conducted. There were two categorical learning conditions and two variable learning conditions. In the categorical learning conditions, all the initial /n/ changed to /l/ either in phonetically motivated or unmotivated contexts. In the variable learning conditions, the dominant percentage of initial /n/ changed to /l/ in phonetically motivated or unmotivated context. Substantive bias arose only in variable learning conditions, which suggests that the substantive bias effect is not global, but it is activated under certain circumstances. This study found that the shape and distribution of input could influence the effect of substantive bias.
SEAN 2.0: Formalizing and Generating Social Situations for Robot Navigation

We present SEAN 2.0, an open-source system designed to advance social navigation via the training and benchmarking of navigation policies in varied social contexts. A key limitation of current social navigation research is that policies are often trained and evaluated considering only a few social contexts, which are fragmented across prior work. Inspired by work in psychology, we describe navigation context based on social situations, which encompass the robot task and environmental factors, and propose logic-based classifiers for five common examples. SEAN 2.0 allows a robot to experience these social situations via different methods for specifying and generating pedestrian motion, including a novel Behavior Graph method. Our experiments show that when data collected using the Behavior Graph method is used to learn a robot navigation policy, that policy outperforms others trained using alternative methods for pedestrian control. Also, social situations were found to be useful for understanding performance across social contexts. Other components of SEAN 2.0 include vision and depth sensors, several physical environments, different means of specifying robot tasks, and a range of evaluation metrics for social robot navigation. User feedback for SEAN 2.0 indicated that the system was “easier to navigate and more user friendly” than SEAN 1.0.
Knowledge, attitude and practices related to the use of personal protective equipment among welders in small-scale metal workshops in Nansana Municipality, Wakiso District, Uganda

ABSTRACT Background Despite the risks involved in welding, there is limited evidence of the knowledge, attitude and practices related to the use of personal protective equipment (PPE) among welders in small-scale metal workshops. We assessed the level of knowledge, attitude and practices (KAP) related to PPE use among welders in small-scale workshops in Nansana Municipality, Wakiso district, Uganda. Methods A cross-sectional study was conducted among 329 welders. A structured questionnaire was used to collect data on welder knowledge and attitude while an observation checklist was used to establish utilization of PPE. Ten key informant interviews were conducted to further understand welders’ knowledge, attitude and PPE-related practices. A ‘modified Poisson’ regression analysis was done to establish the independent factors associated with PPE KAP. NVivo 12 was used for the management of qualitative data. A thematic content approach guided qualitative data analysis. Results About 61.4% (202/329) of the respondents had a high level of knowledge, 68.7% (226/329) had a negative attitude, and only 37.1% (122/329) exhibited good PPE-related practices. Knowledge of PPE use was associated with the type of training (aPR = 1.52, CI = 1.29–1.80). Attitude toward PPE use was associated with the level of education (aPR = 2.31, CI = 1.28–4.14), duration of work experience (aPR = 2.37, CI = 1.01–5.55), (aPR = 2.79, CI = 1.13–6.89), and level of knowledge (aPR = 1.73, CI = 1.13–2.65). PPE-related practices were associated with the type of training (aPR = 2.91, CI = 2.14–3.96) and attitude (aPR = 1.45, CI = 1.08–1.93). Conclusion While the welders’ level of knowledge of PPE was found to be high, the majority exhibited a negative attitude and poor PPE-related practices. A high level of knowledge was associated with a positive attitude. In turn, a positive attitude was associated with good PPE practices. Welders need to be sensitized on the health risks that may arise from the non-use of PPE.
STATISTICAL MECHANICS AND COMBINATORICS OF SOME DISCRETE LATTICE MODELS

OF THE DISSERTATION Statistical Mechanics and Combinatorics of Some Discrete Lattice Models by Arvind Ayyer Dissertation Director: Professor Joel L. Lebowitz Many problems in statistical physics involve enumeration of certain objects. In this thesis, we apply ideas from combinatorics and statistical physics to understand three different lattice models. I We investigate the structure of the nonequilibrium stationary state (NESS) of a system of first and second class particles on L sites of a one-dimensional lattice in contact with first class particle reservoirs at the boundary sites and second class particles constrained to lie the system. The internal dynamics are described by the usual totally asymmetric exclusion process (TASEP) with second class particles. We show in a conceptually simple way how pinned and unpinned (fat) shocks determine the general structure of the phase diagram. We also point out some unexpected features in the microscopic structure of the NESS both for finite L and in the limit L → ∞. In the latter case the local distribution of second class particles is given by an equilibrium pressure ensemble with a pair potential between neighboring particles which grows logarithmically with distance.
Development of Adaptive Line Tracking Breakpoint Detection Algorithm for Room Sensing using LiDAR Sensor

—This research focuses on the use of Light Detection and Ranging (LiDAR) sensors for robot localization. One of the most essential algorithms in LiDAR localization is the breakpoint detector algorithm which is used to determine the corner of the room. The previously developed breakpoint detection methods have weaknesses, such as the Adaptive Breakpoint Detector (ABD), could generate dynamic threshold values. The ABD results, on the other hand, still require Line Extraction to obtain the corner breakpoint. Line Extraction method, e.g. Iterative End Point Fit (IEPF), is used to categorize data, resulting in the generation of a line pattern as an interpretation of a wall. The computational method for obtaining the corner breakpoint becomes longer as the line is extracted. To address this issue, our algorithm proposes a new threshold area in the form of an ellipse with the threshold value parameter obtained from previously identified room size and sensor characteristics. As a result the corner breakpoint detection becomes more adaptive. The goal of this research is to create an Adaptive Line Tracking Breakpoint Detector (ALTBD) approach that will reduce the computing time required to detect corner breakpoints. Furthermore, the Line Extraction method required for corner breakpoint detection is modified in the ALTBD. To distinguish between the edge of the wall and the corner of the room, the boundary value is increased. The ALTBD method was tested in a simulation arena comprised of multiple rooms and halls. According to the results, the ALTBD computation time is faster in detecting corner breakpoints than the ABD IEPF method, also the accuracy for determining the position of the robot was improved.
Factors affecting true and functional productive lifespan in Italian Holstein-Friesian cows

Abstract The identification of factors affecting longevity in dairy cows is of great importance to improve their length of productive life. Cows can be replaced for poor milk production (i.e. true productive lifespan, TPL) or other reasons than production (functional productive lifespan, FPL). The objective of the present study was to investigate the influence of milk yield, fat and protein contents, insemination status (INS), somatic cell count (SCC) and β-hydroxybutyrate (BHB) concentration in milk on TPL and FPL. Data included 70,748 Italian Holstein-Friesian cows that calved for the first time between 2014 and 2018. Proportional hazards models assuming a piecewise Weibull distribution of the baseline hazard function, with or without adjustment for milk production, were used to compute relative risks of culling associated with FPL and TPL, respectively. Our study revealed that milk yield, protein and fat contents, INS, SCC and concentration of BHB in milk exhibited significant relationships with TPL and FPL. In particular, the huge difference in risk ratios between high- and low-producing cows confirms the central role of milk production in culling decision-making. In addition, farmers appear more prone to cull cows with several events of high SCC and BHB concentration in milk. HIGHLIGHTS Milk yield, fat and protein contents, insemination status, somatic cell count and ketosis affect productive lifespan in Italian Holstein cows. These factors, therefore, contribute significantly to culling decisions. The identified risk factors of culling can be exploited to improve the current management practices in Italian Holstein Friesian herds and cows’ longevity.
Seawater Hydration Modulates IL-6 and Apelin Production during Triathlon Events: A Crossover Randomized Study

A triathlon is an endurance event in which athletes need an efficient hydration strategy since hydration is restricted at different stages. However, it seems that seawater intake can be a suitable hydration alternative for this type of endurance event. Therefore, the aim of this study was to evaluate the efficacy of seawater hydration during a triathlon on cytokine production. Fifteen trained male triathletes (age = 38.8 ± 5.62 years old; BMI = 22.58 ± 2.51 kg/m2) randomly performed three triathlons, one of them consuming seawater (Totum SPORT, Laboratories Quinton International, S.L., Valencia, Spain), the other one consuming tap water ad libitum, and the last a physiologic saline solution as placebo. The triathlon consisted of an 800 m swim, a 90 km bike ride, and a 10 km run. Blood samples were taken at rest and after training, where markers of inflammation, hemoglobin, and hematocrit concentration were assessed. While the seawater was not ergogenic, it significantly increased the release of IL-6 and apelin post-exercise. However, no differences were found between the fractalkine, IL-15, EPO, osteonectin, myostatin, oncostatin, irisin, FSTL1, osteocrin, BDNF, and FGF-21 values over those of the placebo group. The present study demonstrates that hydration with seawater stimulates myokine production, which could lead to improved performance recovery after exercise.
On the Dynamic Consistency of the Split Step Method for Classifying the Asymptotic Behaviour of Globally Stable Differential Equations perturbed by State--independent Stochastic terms

In this paper we classify the pathwise asymptotic behaviour of the discretisation of a general autonomous scalar differential equation which has a unique and globally stable equilibrium. The underlying continuous equation is subjected to a stochastic perturbation whose intensity is state--independent. In the main result, it is shown that when the split--step--method is applied to the resulting stochastic differential equation, and the stochastic intensity is decreasing, the solutions of the discretised equation inherit the asymptotic behaviour of the continuous equation, regardless of whether the continuous equation has stable, bounded but unstable, or unbounded solutions, provided the step size is chosen sufficiently small.
Mechanism Understanding for Size Regulation of Silver Nanowires Mediated by Halogen Ions

The controllable preparation of silver nanowires (AgNWs) with a high aspect ratio is key for enabling their applications on a large scale. Herein, the aspect ratio regulation of AgNWs mediated by halogen ion composition in ethylene glycol system was systematically investigated and the size evolution mechanism is elaborately understood. The co-addition of Br− and Cl− results in AgNWs with the highest aspect ratio of 1031. The surface physicochemical analysis of AgNWs and the density functional theory calculations indicate that the co-addition of Br− and Cl− contributes to the much-enhanced preferential growth of the Ag(111) crystal plane. At the same time, when Cl− and Br− coexist in the solution, the growth of the Ag(100) crystal plane on the AgNWs was restrained compared with that in the single Cl− system. Resultantly, the enhanced growth of Ag(111) and the inhibited growth of Ag(100) contribute to the formation of AgNWs with a higher aspect ratio in the Cl–Br mixed solution. The results can provide new insights for understanding the morphology and size evolution during the AgNWs preparation in ethylene glycol system.
Counting strongly-connected, sparsely edged directed graphs

A sharp asymptotic formula for the number of strongly connected digraphs on $n$ labelled vertices with $m$ arcs, under a condition $m-n\to\infty$, $m=O(n)$, is obtained; this solves a problem posed by Wright back in $1977$. Our formula is a counterpart of a classic asymptotic formula, due to Bender, Canfield and McKay, for the total number of connected undirected graphs on $n$ vertices with $m$ edges. A key ingredient of their proof was a recurrence equation for the connected graphs count due to Wright. No analogue of Wright's recurrence seems to exist for digraphs. In a previous paper with Nick Wormald we rederived the BCM formula via counting two-connected graphs among the graphs of minimum degree $2$, at least. In this paper, using a similar embedding for directed graphs, we find an asymptotic formula, which includes an explicit error term, for the fraction of strongly-connected digraphs with parameters $m$ and $n$ among all such digraphs with positive in/out-degrees.
THE RELATIONSHIP BETWEEN LOWER LIMB STIFFNESS AND RUNNING ECONOMY IN CHILD SOCCER PLAYERS

ABSTRACT Introduction Lower limb stiffness has been shown to be associated with running economy (RE) in adults, but this relationship in children remains unclear. Objectives The purpose of this study was to investigate the relationship between lower limb stiffness, RE, and repeated-sprint ability in child soccer players. Methods Twenty-eight male child soccer players (mean age 11.8 ± 0.9 years) participated in the study. RE was determined by measuring the steady-state oxygen uptake (ml/min/kg) at submaximal running speeds of 8 and 9 km/h. Vertical and leg stiffness were calculated from the flight and contact time data obtained during two submaximal running tests. Additionally, vertical stiffness was measured during the maximal and submaximal hopping tests. All participants performed the repeated sprint test consisting of 10 × 20-m all-out sprints interspersed with 20-s active recovery. Results During both submaximal running tests, vertical (r= –0.505 to –0.472) and leg stiffness (r= –0.484 to –0.459) were significantly correlated with RE (p< 0.05). Maximal (r= –0.450) and submaximal hopping stiffness (r= –0.404) were significantly correlated with RE at 8 km/h (p< 0.05). Maximal hopping stiffness was significantly correlated with the best sprint time (r= –0.439) and mean sprint time (r= –0.496) (p< 0.05). Vertical (r= –0.592 to –0.433) and leg stiffness (r= –0.612 to –0.429) at 8 and 9 km/h and submaximal hopping stiffness (r= –0.394) were significantly correlated with the fatigue index (p< 0.05). Conclusions Current findings indicate that the lower limb stiffness may be an important determinant of both RE and repeated-sprint ability in child soccer players. Level of Evidence II; Diagnostic Studies - Investigating a Diagnostic Test.
Multi-Field Inflation from String Theory

We construct a multi-field inflationary model consisting of multiple K\"ahler moduli derived from type IIB string compactification in the large volume limit. The model consists of both heavy and light fields, with the former being frozen during the inflationary period and the latter acting as the inflaton(s). We study the evolution of all the fields during and after inflation until the preheating era when all the fields oscillate around their vacuum expectation values. Our numerical analysis shows that the curvature perturbations have an almost scale invariant power spectrum with $n_s \simeq 0.96$.
Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition and Genetic Algorithm-Optimized Wavelet Threshold Denoising

Fault diagnosis of rolling bearings can be a serious challenge, as rolling bearings often work under complex conditions and their vibration signals are typically nonlinear and nonstationary. This paper proposes a novel approach to diagnosing faults of rolling bearings based on variational mode decomposition (VMD) and genetic algorithm-optimized wavelet threshold denoising. First, VMD was used to decompose the vibration signals of faulty rolling bearings into a series of band-limited intrinsic mode functions (BLIMFs). During the decomposition, the parameters of VMD were selected by Kullback–Leibler (K–L) divergence. Then, the effective BLIMFs were determined by the analysis of their correlation coefficients and variance contributions. Finally, genetic algorithm-optimized wavelet threshold denoising was proposed to optimize the selection of important parameters, and the optimized threshold function used not only ensures the continuity of the threshold function but also avoids the fixed deviation of the soft threshold. The validity and superiority of the proposed approach were verified by theoretical calculations, numerical simulations and application studies. The results indicate that the proposed approach is promising in fault diagnosis of rotary machinery.
Probiotic Ameliorating Effects of Altered GABA/Glutamate Signaling in a Rodent Model of Autism

Autism spectrum disorders (ASDs) comprise a heterogeneous group of pathological conditions, mainly of genetic origin, characterized by stereotyped behavior, such as marked impairment in verbal and nonverbal communication, social skills, and cognition. Excitatory/inhibitory (E/I) imbalances have been recorded as an etiological mechanism of ASD. Furthermore, GABA, the main inhibitory neurotransmitter in adult life, is known to be much lower in both patients and rodent models of ASD. We propose correcting GABA signaling as a therapeutic strategy for ASD. In this study, 40 young male western Albino rats, 3–4 weeks in age, weighing about 60–70 g, were used. The animals were randomly assigned into six experimental groups, each including eight rats. Group I served as the control group and was orally administered phosphate-buffered saline. Groups II and III served as rodent models of ASD and were orally administered a neurotoxic dose of propionic acid (PPA). The rats in the three therapeutic groups (IV, V, and IV) received the same doses of PPA, followed by 0.2 g/kg body weight of pure Bifidobacterium infantis, a probiotic mixture of ProtexinR, and pure Lactobacillus bulgaricus, respectively, for 3 weeks. Selected variables related to oxidative stress, glutamate excitotoxicity, and gut bacteria were measured in the six groups. Both pure and mixed Lactobacillus and Bifidobacterium were effective in ameliorating glutamate excitotoxicity as an autistic feature developed in the PPA-induced rodent model. Their therapeutic effects mostly involved the correction of oxidative stress, restoration of depleted GABA, and up-regulation of GABA receptor gene expression. Pure Bifidobacterium was the most effective, followed by the mixture of probiotics and finally lactobacillus. In conclusion, Bifidobacteria and lactobacilli can be used independently or in combination as psychobiotics to ameliorate oxidative stress and glutamate excitotoxicity as two confirmed etiological mechanisms through the gut–brain axis.