Miracle-dz/UniFAR-FTUs huggingface dataset:
On the structure of the self-sustaining cycle in separating and reattaching flows

The separating and reattaching flows and the wake of a finite rectangular plate are studied by means of direct numerical simulation data. The large amount of information provided by the numerical approach is exploited here to address the multi-scale features of the flow and to assess the self-sustaining mechanisms that form the basis of the main unsteadinesses of the flows. We first analyse the statistically dominant flow structures by means of three-dimensional spatial correlation functions. The developed flow is found to be statistically dominated by quasi-streamwise vortices and streamwise velocity streaks as a result of flow motions induced by hairpin-like structures. On the other hand, the reverse flow within the separated region is found to be characterized by spanwise vortices. We then study the spectral properties of the flow. Given the strongly inhomogeneous nature of the flow, the spectral analysis has been conducted along two selected streamtraces of the mean velocity field. This approach allows us to study the spectral evolution of the flow along its paths. Two well-separated characteristic scales are identified in the near-wall reverse flow and in the leading-edge shear layer. The first is recognized to represent trains of small-scale structures triggering the leading-edge shear layer, whereas the second is found to be related to a very large-scale phenomenon that embraces the entire flow field. A picture of the self-sustaining mechanisms of the flow is then derived. It is shown that very-large-scale fluctuations of the pressure field alternate between promoting and suppressing the reverse flow within the separation region. Driven by these large-scale dynamics, packages of small-scale motions trigger the leading-edge shear layers, which in turn created them, alternating in the top and bottom sides of the rectangular plate with a relatively long period of inversion, thus closing the self-sustaining cycle.
The Impact of Sleep Deprivation on Brain Networks in Response to Social Evaluation Tasks

Sleep loss may lead to negative bias during social interaction. In the current study, we conducted a revised social evaluation task experiment to investigate how sleep deprivation influences the self-referential and cognitive processes of social feedback. The experiment consisted of a first impression task and a social feedback task. Seventy-eight participants completed the first impression task and were divided into normal and poor sleep groups. The results of an independent samples t-test showed that participants who slept worse were less likely to socialize with others but did not evaluate others as less attractive. Afterward, 22 of the participants from the first impression task were recruited to complete the social feedback task during functional magnetic resonance imaging (fMRI) on the mornings following two different sleep conditions at night: one night of normal sleep and one night of sleep deprivation. The results of this within-subject design study showed that participants who experienced the latter condition showed increased activation within the default mode network (i.e. superior parietal lobule, precuneus, inferior parietal lobule, inferior temporal gyrus, and medial frontal gyrus) and anterior cingulate cortex (ACC) and stronger negative insula functional connectivity (FC) with the precuneus to negative feedback than positive feedback. The altered activation and behavioral pattern may indicate a negative bias for social cues. However, stronger negative coupling may indicate stronger cognitive control, which may protect against potential damage to self-concept. Our study suggested that sleep impairs most social functions, but may protect against impairment of important ones, such as self-concept.
Pattern-based stochastic simulation using restricted Boltzmann machine

For pattern-based simulation methods such as SIMPAT, filtersim, wavesim, ect, patterns are stored by scanning a training image with a sliding template. Dimensional reduction and pattern clustering are then preformed to generate a set of cluster prototypes. During simulation, the conditional data is matched to the best cluster by subsequent similarity measurements and a pattern is randomly sampled from that class. In this paper, a multiple-point, pattern-based, stochastic simulation algorithm using Restricted Boltzmann Machine (RBMSim) is proposed. In the learning phase of RBMSim, the clusters are learned by a contractive divergence learning algorithm which aggregates the two steps of dimensional reduction and pattern clustering. In simulation phase of RBMSim, the two steps of classification and sampling are also aggregated with an efficient Gibbs sampling algorithm. The contributions of this paper are: the learning and simulation are embedded within a mathematically well-defined probabilistic model which represents the entire configuration space; and the learning and simulation phases share the same Markov chain, Monte Carlo based sampling algorithm which explores the entire configuration space efficiently.
How Do Employability, Personality, and Talent Management Affect Lecturers' Organizational Citizenship Behavior

Private universities in Indonesia need to urgently enhance the lecturers' organizational citizenship behavior (OCB), especially in overcoming a transition period of learning patterns after the COVID-19 pandemic from online to offline. Therefore, this research explores employability, personality, and talent management affect OCB and proves job involvement mediates employability, personality, and talent management influences OCB. It was conducted through a survey using a Likert scale questionnaire with 230 participants of lecturers from Indonesian private universities. Path analysis supplemented by descriptive and correlational analysis was used as a data analysis technique. The results showed that employability, personality, talent management, and job involvement significantly affect OCB. In addition, job involvement mediates employability, personality, talent management influences OCB. Therefore, a new empirical model regarding employability, personality, and talent management affect OCB with job involvement mediation was developed. Accordingly, researchers and practitioners can utilize for the model in their future activities.
A Survey of mmWave-Based Human Sensing: Technology, Platforms and Applications

With the rapid development of the Internet of Things (IoT) and the rise of 5G communication networks and automatic driving, millimeter wave (mmWave) sensing is emerging and starts impacting our life and workspace. mmWave sensing can sense humans and objects in a contactless way, providing fine-grained sensing ability. In the past few years, many mmWave sensing techniques have been proposed and applied in various human sensing applications (e.g., human localization, gesture recognition, and vital monitoring). We discover the need of a comprehensive survey to summarize the technology, platforms and applications of mmWave-based human sensing. In this survey, we first present the mmWave hardware platforms and some key techniques of mmWave sensing. We then provide a comprehensive review of existing mmWave-based human sensing works. Specifically, we divide existing works into four categories according to the sensing granularity: human tracking and localization, motion recognition, biometric measurement and human imaging. Finally, we discuss the potential research challenges and present future directions in this area.
Haplotypes of the tRNAleu-COII mtDNA Region in Russian Apis mellifera Populations

Simple Summary One of the most discussed issues in beekeeping is the introduction and hybridization of the honey bee subspecies Apis mellifera mellifera (dark forest bee). In most of Russia, the dark forest bee is a native subspecies. However, due to hybridization with introduced subspecies, a small number of purebred populations of the dark forest bee remained. In this study, using the mitochondrial marker tRNAleu-COII, we established the maternal descent of honey bees from 19 regions of Russia. As a result, it was found that 198 of the studied colonies belong to the M evolutionary lineage and 71—to the C lineage. We have found two different population groups of the dark forest bee in Russia—one of them belongs to the haplogroup M17, the other to M4’. Haplogroup M4′ dominated in the European A. m. mellifera and A. m. iberiensis populations. Whereas haplogroup M17 was rare in European populations of the dark forest bee. Abstract Analysis of the mtDNA tRNAleu-COII locus is a widely used tool to establish belonging to a particular evolutionary lineage of Apis mellifera L. (lineages A, M, C, O, and Y). In Russia, most of the area was once inhabited by Apis mellifera mellifera from the M evolutionary lineage, but the introduction of bee subspecies from the southern regions of Russia (A. m. caucasica, A. m. carnica) and from abroad (A. m. carnica, A. m. ligustica) led to fragmentation of their native range. In this study, the results of assessing the haplotype number for the tRNAleu-COII locus of mtDNA in Russian Apis mellifera populations were presented. We analyzed 269 colonies from 19 regions of Russia. As a result, two evolutionary lineages were identified: the East European lineage C (26.4%) and the Northwestern European lineage M (73.6%). A total of 29 haplotypes were identified, 8 of them were already reported, and 21 were found to be novel. From the C lineage, haplotypes C1, C2, C2c, C2j, and C3 were predominant. All M lineage samples from Russia belong to the M17 and M4’ haplogroups but have only minor variations in the form of nucleotide substitutions. An analysis of publications devoted to the tRNAleu-COII locus haplotypes, as well as an analysis of the available tRNAleu-COII sequences in GenBank, showed that there is still a problem with the haplotype nomenclature.
Measurement and large-eddy simulation of single-sided natural ventilation in urban building groups

Natural ventilation is a highly respected and effective way to improve indoor air quality, and single-sided natural ventilation is easily formed in residential buildings. The site experiments were carried out, and the unsteady characteristics of the airflow were analyzed based on 3D wind speed series. With the experimental verification, large-eddy simulation was successfully applied to calculate the indoor–outdoor flow field of urban building groups. When the entrance boundary was constant, the flow field of the window varied all the time, and outflow was irregular. The natural ventilation efficiency was 42% with the incoming flow almost parallel to the window. The discrete wind speed inlet boundary is more suitable for the natural ventilation simulation of buildings in a real environment than the average wind speed boundary and the average wind speed superposition ±10% disturbance.
A physical map of traits of agronomic importance based on potato and tomato genome sequences

Potato, tomato, pepper, and eggplant are worldwide important crop and vegetable species of the Solanaceae family. Molecular linkage maps of these plants have been constructed and used to map qualitative and quantitative traits of agronomic importance. This research has been undertaken with the vision to identify the molecular basis of agronomic characters on the one hand, and on the other hand, to assist the selection of improved varieties in breeding programs by providing DNA-based markers that are diagnostic for specific agronomic characters. Since 2011, whole genome sequences of tomato and potato became available in public databases. They were used to combine the results of several hundred mapping and map-based cloning studies of phenotypic characters between 1988 and 2022 in physical maps of the twelve tomato and potato chromosomes. The traits evaluated were qualitative and quantitative resistance to pathogenic oomycetes, fungi, bacteria, viruses, nematodes, and insects. Furthermore, quantitative trait loci for yield and sugar content of tomato fruits and potato tubers and maturity or earliness were physically mapped. Cloned genes for pathogen resistance, a few genes underlying quantitative trait loci for yield, sugar content, and maturity, and several hundred candidate genes for these traits were included in the physical maps. The comparison between the physical chromosome maps revealed, in addition to known intrachromosomal inversions, several additional inversions and translocations between the otherwise highly collinear tomato and potato genomes. The integration of the positional information from independent mapping studies revealed the colocalization of qualitative and quantitative loci for resistance to different types of pathogens, called resistance hotspots, suggesting a similar molecular basis. Synteny between potato and tomato with respect to genomic positions of quantitative trait loci was frequently observed, indicating eventual similarity between the underlying genes.
Suboptimal Output Consensus for Time‐Delayed Singular Multi‐Agent Systems

The current paper investigates guaranteed‐cost output consensus analysis and design problems for high‐order linear time‐invariant singular multi‐agent systems with constant time delays, which can realize suboptimal output consensus control. Firstly, a new output consensus protocol with a suboptimal index and a single delay is proposed to realize the tradeoff design between output consensus regulation performances and control energy consumptions. Then, sufficient conditions for guaranteed‐cost output consensus and consensualization are derived in terms of linear matrix inequalities by a combined tool from the Lyapunov‐Krasovskii approach and the free‐weighting matrix technique, respectively, and the output consensus function is determined on the basis of the First Equivalent Form. Finally, a numerical example is performed to demonstrate the effectiveness and conservativeness of theoretical results.
Multi-Center Validation of Pain Assessment in Advanced Dementia (PAINAD) Scale in Malaysia

The detection of pain in persons with advanced dementia is challenging due to their inability to verbally articulate the pain they are experiencing. Pain Assessment in Advanced Dementia (PAINAD) is an observer-rated pain assessment tool developed based on non-verbal expressions of pain for persons with severe dementia. This study aimed to perform construct validation of PAINAD for pain assessment in persons with severe dementia in Malaysia. This was a prospective cross-sectional study conducted from 27 April 2022 to 28 October 2022 in eight public hospitals in Malaysia. The PAINAD scale was the index test, and the Discomfort Scale—Dementia of the Alzheimer Type (DS-DAT) and Nurse-Reported Pain Scale (NRPS) were the reference tests for construct and concurrent validity assessment. Pain assessment for the study subjects was performed by two raters concurrently at rest and during activity. The PAINAD score was determined by the first rater, whereas the DS-DAT and NRPS were assessed by the second rater, and they were blinded to each other’s findings to prevent bias. PAINAD showed good positive correlations ranging from 0.325 to 0.715 with DS-DAT and NRPS at rest and during activity, with a p-value of <0.05. It also demonstrated statistically significant differences when comparing pain scores at rest and during activity, pre- and post-intervention. In conclusion, the PAINAD scale is a reliable observer-rated pain assessment tool for persons with severe dementia in Malaysia. It is also sensitive to changes in the pain level during activity and at rest, pre- and post-intervention.
Factors Associated with Mathematics Results at G.C.E. (O/L) Examination

The General Certificate of Education (Ordinary Level) (G.C.E O/L) examination is the first most important public certificate examination in Sri Lanka. Most of the candidates „fail‟ the G.C. E (O/L) examination due to their failure in Mathematics, leaving them without any viable option for their future. Identification of factors related to the results of Mathematics is essential to rectify this problem. This paper presents some findings of a study carried out in 2008 to explore the factors related to the results of Mathematics of the G.C. E (O/L) examination. The necessary data were collected from a survey conducted in the Piliyandala Educational Zone. The components of the syllabus that are most weighted in the marking scheme and the components preferred by the students were identified. The external factors that are associated with Mathematics marks were also identified through analysis of variance and regression analysis. Findings are useful to those who design curricula as well as to the teachers and parents.
Search for ultralight scalar dark matter with NANOGrav pulsar timing arrays

An ultralight scalar field is a candidate for the dark matter. The ultralight scalar dark matter with mass around 10−23 eV induces oscillations of the pulse arrival time in the sensitive frequency range of the pulsar timing arrays. We search for the ultralight scalar dark matter using the North American Nanohertz Observatory for Gravitational Waves 11-year Data Set. We give the 95% confidence upper limit for the signal induced by the ultralight scalar dark matter. In comparison with the published Bayesian upper limits on the amplitude of the ultralight scalar dark matter obtained by Bayesian analysis using the Parkes Pulsar Timing Array 12-year data set (Porayko et al. 2018), we find three times stronger upper limit in the frequency range from 10−8.34 to 10−8.19 Hz which corresponds to the mass range from 9.45×10−24 to 1.34×10−23 eV. In terms of the energy density of the dark matter, we find that the energy density near the Earth is less than 7 GeV/cm3 in the range from 10−8.55 to 10−8.01 Hz (from 5.83×10−24 to 2.02×10−23 eV). The strongest upper limit on the energy density is given by 2 GeV/cm3 at a frequency 10−8.28 Hz (corresponding to a mass 1.09×10−23 eV). We find that the signal of the ultralight scalar dark matter is strongly covariant with the solar system ephemeris effect. Also, we reveal that the model of the solar system ephemeris effect prefers parameters which are contrary to the expectation that noise will be reduced on all pulsars.
Controller Synthesis of Aperiodic Sampled-Data Networked Control System With Application to Interleaved Flyback Module Integrated Converter

This paper investigates the stability analysis and controller design issues for aperiodic sampled-data networked control systems with time-varying delays. Three main results are obtained. Firstly, the discretized model with delay is constructed as an feedback interconnected system formed by a structural uncertainty operator and a linear time-invariant system. Secondly, an exponential decay rate is introduced as a performance index of the system through model transformation, an equivalent stability condition for the system is also obtained, further, the conclusion is extended to systems with arbitrary initial states. On this basis, the exponential stability conditions with minimal computational complexity are given under an integral quadratic constraint. Thirdly, an iterative algorithm for the solution of the controller is given to deal with the effects of non-linear coupling terms. Finally, two numerical examples and an application example of an interleaved flyback modular integrated converter are used to illustrate the effectiveness and computational simplicity of the stability criterion and the controller design algorithm of this paper.
Effective woody biomass estimation in poplar short-rotation coppices - Populus nigra × P. maximowiczii

Knowledge of the quantity of woody biomass of poplar short-rotation coppice (SRC) on agricultural land is a basic tool for management decisions like rotation length, volume production and the financial balance sheet of economic activities. The expansion of SRC requires a fast, reliable, easily applicable and cheap method for estimating the biomass yield, but existing methods are based on labour-demanding and lengthy measurements of all shoots per tree. The objective of this study was to verify a novel rapid biomass estimation method that uses averaged attributes of only a few largest shoots as a predictor variable for woody biomass in a poplar SRC, hybrid clone J-105 ( Populus nigra × P. maximowiczii ). Using data from 39 sample stumps with 187 shoots in total, we modelled shoot biomass as a function of an increasing number of shoots in interaction with different shoot parameters at two poplar SRC plantations. Results showed that the DBH of only three of the largest shoots per stump proved to be accurate estimators of the total shoot biomass of the individual stump. Comparison of biomass estimates at the stand level with a real amount of biomass indicated differences between 6-14%, depending on the site.
Generation of highly symmetric, cylindrically convergent shockwaves in water

We report on pulsed power driven, exploding copper wire array experiments conducted to generate cylindrical convergent shockwaves in water employing μs risetime currents >550 kA in amplitude and with stored energies of >15 kJ—a substantial increase over previous results. The experiments were carried out on the recently constructed Mega-Ampere-Compression-and-Hydrodynamics facility at Imperial College London in collaboration with colleagues of Technion, Israel. 10 mm diameter arrays consisting of 60 × 130 μm wires were utilized, and the current and voltage diagnostics of the load region suggested that ∼8 kJ of energy was deposited in the wires (and the load region close to the wires) during the experiments, resulting in the formation of dense, highly resistive plasmas that rapidly expanded driving the shockwaves in water. Laser-backlit framing images of the shockfront were obtained at radii <0.25 mm for the first time, and there was strong evidence that even at radii <0.1 mm this front remains stable, resu.
A Cognitive Semantics analysis of David Goggins’ idea of “transforming” mindset

The objective of the paper is an analysis of how David Goggins describes his life in his book Can’t Hurt Me. The analysis was conducted within the methodological framework of the Conceptual Metaphor Theory and Blending Theory. It has been established that the metaphors life is a journey and aspects of the self are individuals at war provide coherence to the story of his life, while conceptual blends are a mental tool used to reframe a situation and himself. As a result of implementing those blends in his thinking, David Goggins has developed a mindset that allowed him to transform from a broken teenager to “the strongest man alive”. This case study reveals how specific conceptual blends may impact not only cognition and language in general, as is argued in Cognitive Semantics, but also one’s emotional state, and consequently one’s physical performance.