Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of Site Effects and Q Factor Using a Reference Event

A method to determine site effects and the Q factor using a reference event is described. Spectral ratios between pairs of earthquakes and a reference one were written as logarithmic summations in order to obtain individual solutions for the numerators and denominators. Given the seismic moment and corner frequency for one of the events following the ω 2 model, a source model was assumed to constrain the amplitude of the solution. The validity and limitations of this technique were tested on synthetically generated data. We analyzed the variances of the results depending on the different number of stations used, the amount of noise present in the records, and the change in the seismic moment, corner frequency, and source model of the reference event. Aftershocks of the 2000 Tottori, Japan, earthquake were used to estimate the site effects and Q factor in that region. Two strong motion networks, K-NET and KiK-net, recorded the aftershocks. The latter network contained both surface and borehole receivers at every station. Data were inverted first using only surface records and then using the borehole records from KiK-net stations in order to study amplitude differences. Our results suggest that the study area presents a low Q value and that there is also amplification at borehole sites. Manuscript received 18 January 2002.
The Significance of Maximal Squat Strength for Neuromuscular Knee Control in Elite Handball Players: A Cross-Sectional Study

Both weak muscle strength and impaired neuromuscular control has previous been suggested as risk factors for future traumatic knee injury. However, data on the relationship between these two factors are scarce. Thus, the aim of this study was to investigate the relationship and influence of the one repetition maximum (1RM) barbell squat strength on dynamic knee valgus in elite female and male handball players. In this cross-sectional study 22 elite handball players (7 females) were included. A unilateral drop jump (VDJ) test was used for the assessment of frontal plane dynamic knee valgus. Players also performed a one repetition maximum (1RM) barbell squat test, expressed relative to bodyweight (r1RM), to assess maximal strength, which were dichotomized to analyze ‘weak’ versus ‘strong’ players according to median. Correlations were noted between r1RM in squat and knee valgus angle for both the non-dominant (r = −0.54; p = 0.009) and dominant leg (r = −0.46, p = 0.03). The odds of knee valgus were eight times higher, for the dominant leg, in the weak group compared to the strong group (p = 0.03) and 27 times higher, for the non-dominant leg (p = 0.002). The outcome of the present study suggests that maximum squat strength plays an important role when it comes to neuromuscular control of the knee, and that weak handball players are at higher risk of knee valgus compared to strong players during jumping activity.
Design of Adaptive Periodic Event-Triggered Mechanism-Based EID with MRC Based on PSO Algorithm for T-S Fuzzy Systems

This article discusses issues with disturbance rejection and periodic signal tracking in a specific type of time-varying delay nonlinear systems. The proposed approach, known as the modified repetitive controller (MRC) scheme, utilizes an equivalent-input-disturbance (EID) estimator to enhance the system’s performance. It effectively improves the system’s ability to reject both aperiodic and periodic unknown disturbances, while also achieving accurate tracking of periodic reference signals. A T-S fuzzy model has been used to roughly represent the system nonlinearity. Additionally, a fuzzy state observer based on an adaptive periodic event-triggered mechanism (APETM-FSO) has been used to decrease data transfer, energy use, and communication resource utilization. The APETM is able to identify the occurrence of an event by surpassing a predetermined threshold with the error signal, thanks to the designed adaptive event triggering condition. Transmission of the current data only takes place when the event happens, while data can remain unchanged using a zero-order hold if the event does not occur. In addition to, controller parameters are tuned using a particle swarm optimization (PSO) approach. Hence, T-S fuzzy model-based EID, MRC, FSO-APETM, and PSO construct the overall system. In order to ensure the asymptotic stability of the entire system in the presence of unknown disturbances, the article establishes sufficient conditions using the Lyapunov–Krasovskii functional stability theory and linear matrix inequalities (LMIs). These conditions are derived to guarantee the desired stability properties of the system. To demonstrate the effectiveness and feasibility of the proposed scheme, simulation results with comparative study are presented. The proposed controller has achieved better tracking performance with less tracking error with maximum value of 0.05. In addition, the suggested APETM has minimum triggering times which is 34 as comparison with PETM which is 40 times, and hence, APETM is more effective than PETM in reducing data transmission frequency and using less communication resources overall.
The effects of indication of local geographical origin on food perceptions

This research examines the impact of a local origin label on perceptions and purchase intent regarding food products. It also reveals the psychological mechanism specific to local origin to explain these effects. Two experiments, conducted on a total of 632 consumers, show that cheese (Study 1) and apples (Study 2) are perceived as healthier, better tasting, and more respectful of the environment and the work of farmers when they are presented as local foods (as opposed to national or from another “region”). Purchase intention is also higher when products are labeled as locally sourced. Study 2 shows that these effects can be explained by construal level theory. Local produce is perceived as spatially and psychologically closer by the consumer, who can thus picture more specifically how it was grown and prepared, and this in turn positively influences perceptions and purchase intent. These effects are measured on products that are not typical of the territory. They persist regardless of the degree of local identity of the person evaluating the product.
Dietary Barriers Appear to Influence the Effects of a Dyadic Web-Based Lifestyle Intervention on Caloric Intake and Adiposity: A Mediation Analysis of the DUET Trial

Mechanisms that explain behavior change within web-based lifestyle interventions are not well-studied. This secondary analysis explores whether the effects of the DUET web-based lifestyle intervention on diet, physical activity, and/or adiposity are mediated through changes in self-efficacy, social support, and perceived barriers (key constructs of social cognitive theory). Data on mediators, diet quality, caloric intake, moderate-to-vigorous physical activity (MVPA), weight, and waist circumference (WC) were analyzed from 112 cancer survivors and their partners enrolled in the DUET intervention. Mediation analyses were performed using Mplus to execute regression analyses and determine associations. Mediation analyses supported an effect of the intervention on caloric intake (−3.52, 95% CI [−8.08 to −0.84]), weight (−1.60, CI [−3.84 to −0.47]), and WC (−0.83, CI [−1.77 to −0.18]), interpreting these negative associations as intervention induced reductions in dietary barriers. Higher social support was significantly and positively associated with, but not a mediator for, improvements in self-reported and accelerometry-measured MVPA (b = 0.69, CI [0.19, 1.24]) and (b = 0.55, CI [0.15, 1.00]), respectively. Self-efficacy did not appear to mediate the intervention’s effects. Findings suggest that the effects of the DUET intervention on diet and adiposity stem from reducing perceived barriers to a healthful, low-calorie diet.
Multimodal Learning Analytics: An Overview of the Data Collection Methodology

Since, multimodal learning analytics has shared a common interdisciplinary approach with learning analytics utilizing technologies like low-cost sensors and wearable devices, artificial intelligence (AI), and machine learning (ML) to provide real-time feedback to students and instructors. MMLA focuses on research within intermediary spaces— between research and classroom application, bridging private and public learning contexts by tracking students’ interactions with social media and connected devices, and exploring context-aware and adaptive technologies. However, there is a dearth of evidence demonstrating the successful application of multimodal learning findings in classroom settings on a larger scale. The encroachment on students’ privacy due to the intrusive nature of multimodal data collection methods, often involving sensors and recording technologies, remains a substantial concern that necessitates attention. This study systematically reviews multimodal learning analytics, examining aspects such as data collection rationale, data scope, study contexts, ethical considerations, commercial interests, and downstream data uses. Findings emphasize the need for greater ethical scrutiny, reevaluation of data collection rationale, and comprehensive privacy protections.
TEMPORAL PATTERN OF NATICID PREDATION ON GLYCYMERIS YESSOENSIS (SOWERBY) DURING THE LATE CENOZOIC IN JAPAN

Abstract No temporal trend in the intensity of drilling by naticids on Glycymeris yessoensis can be recognized during the late Cenozoic. Drilling sites shifted from the umbo to the center of the valve during the late Cenozoic. This shift might reflect the change of predators from Glossaulax in the Miocene to Cryptonatica or Euspira in the Pleistocene. Borehole sites in the middle Pleistocene were more stereotyped than in the early Pleistocene population despite the same predators. Edge drilling, which is a faster drilling method, first appeared in the population showing high drilling intensities in the early Pleistocene. Because a prediction of the hypothesis of escalation is that changes in predators' behavior developed through time, these changes in drilling location may be the results of escalation. In contrast with the stereotypic trend of borehole sites, correlation coefficients of predator-prey size decreased from the early to the middle Pleistocene.
The design of multi-value sand nourishments

Relative sea level rise and climate change, but also the migration of the growing world population to the coast, continuously increase the pressure on the coastal system. In combination with the increased awareness for sustainability, the interests in the coastal zone become integrated and complex. Integrated Coastal ZoneManagement (ICZM) becomes increasingly important to satisfy the diverse societal needs in the coastal zone. Along sandy shorelines multi-value sand nourishments are therefore potentially valuable and feasible solutions. An example of amulti-value sand nourishment is the Sand Engine in theNetherlands. This innovative 21.5Mm3 mega nourishment was developed in line with the Building with Nature (BwN) design philosophy. To create value with multi-value sand nourishments for other endangered coastal zones in the world, a design methodology for multi-value sand nourishments is necessary. In this research a design methodology is developed that integrates the socioeconomic environment in order to design sand nourishments for the societal needs and determine their feasibility. To create optimal values for society with sand nourishments, the physical and the socioeconomic environments are integrated in the design cycle. The physical environments of sandy shorelines provide functions, and the desired values depend on the socioeconomic environment. To create an overview of the potential values of sandy shorelines, functions categories are defined: culture, economy, food resources, infrastructure, nature, safety, tourism & recreation and water resources. Sand nourishments aim to increase the functionality of sandy shorelines for one (or more) of these categories. In the developed methodology, the physical and the socioeconomic environment are integrated in the design cycle by quantifying the sandy shoreline function categories with indicators. In this way the functionality of the physical environment is translated to potential values for the socioeconomic environment and the societal needs are translated to benchmarked indicators for the physical environment. An application to Gold Coast’s Palm Beach in Australia illustrated that the developed methodology supports the design of multi-value sand nourishments. The most potential solutions for Palm Beach are assessed based on their feasibility in terms of finance and stakeholder commitment. At strategic level, the most potential was allocated to the solution to increase the sand buffer. At conceptual level, the concentrated nourishment was considered to be supported the most by the government and the businesses. An increased surf quality for experienced surfing, and therefore increased value for tourism & recreation of Palm Beach and the Gold Coast can be created with this solution.
Preliminary Study on Effects of Glacial Retreat on the Dominant Glacial Snow Bacteria in Laohugou Glacier No. 12

One impact of climate change is the rapid shrinking of glaciers, resulting in microorganisms deposited into glacial snow or ice being exposed to new environments such as glacier foreland. A pyrosequencing analysis based on the bacterial 16S rRNA gene showed that bacterial diversity was the highest in proglacial soil, followed by that of glacial snow in ablation zone, then by that of glacial snow in the accumulation area, finally by that of glacial snow in glacier terminus, with the combination of Chao1, ACE, Shannon and Simpson analysis. Eighteen phyla were detected from the 7 samples, but mainly composed of Proteobacteria, Actinobacteria and Bacteroidetes. Flavobacterium, Massilia, Pedobacter, Polaromonas were more abundant in glacial snow samples than in glacial soil sample. Massilia was rarely reported in other environments, implying the necessity for its conservation under scenarios of glacier and snowpack loss induced by climate change.
Harnessing Attenuation-Related Mutations of Viral Genomes: Development of a Serological Assay to Differentiate between Capripoxvirus-Infected and -Vaccinated Animals

Sheeppox, goatpox, and lumpy skin disease caused by the sheeppox virus (SPPV), goatpox virus (GTPV), and lumpy skin disease virus (LSDV), respectively, are diseases that affect millions of ruminants and many low-income households in endemic countries, leading to great economic losses for the ruminant industry. The three viruses are members of the Capripoxvirus genus of the Poxviridae family. Live attenuated vaccines remain the only efficient means for controlling capripox diseases. However, serological tools have not been available to differentiate infected from vaccinated animals (DIVA), though crucial for proper disease surveillance, control, and eradication efforts. We analysed the sequences of variola virus B22R homologue gene for SPPV, GTPV, and LSDV and observed significant differences between field and vaccine strains in all three capripoxvirus species, resulting in the truncation and absence of the B22R protein in major vaccines within each of the viral species. We selected and expressed a protein fragment present in wildtype viruses but absent in selected vaccine strains of all three species, taking advantage of these alterations in the B22R gene. An indirect ELISA (iELISA) developed using this protein fragment was evaluated on well-characterized sera from vaccinated, naturally and experimentally infected, and negative cattle and sheep. The developed wildtype-specific capripox DIVA iELISA showed >99% sensitivity and specificity for serum collected from animals infected with the wildtype virus. To the best of our knowledge, this is the first wildtype-specific, DIVA-capable iELISA for poxvirus diseases exploiting changes in nucleotide sequence alterations in vaccine strains.
Genetic dissection of early endosomal recycling highlights a TORC1-independent role for Rag GTPases

unknown. We discovered that yeast has a recycling route from endosomes to the cell surface that functions effi-ciently after inactivation of the sec7-1 allele of Sec7, which controls transit through the Golgi. A genetic screen based on an engineered synthetic reporter that exclusively follows this pathway revealed that recycling was subject to metabolic control through the Rag GTPases Gtr1 and Gtr2, which work downstream of the exchange factor Vam6. Gtr1 and Gtr2 control the recycling pathway independently of TORC1 regulation through the Gtr1 interactor Ltv1. We further show that the early-endosome recycling route and its control though the Vam6>Gtr1/Gtr2>Ltv1 pathway plays a physiological role in regulating the abundance of amino acid transporters at the cell surface.
High-Performance STT-MRAM-Based Computing-in-Memory Scheme Utilizing Data Read Feature

With the development of Artificial Intelligence (AI) and Binary neural networks (BNN), the computing efficiency of the computing system is expected to be much better, however, enormous amounts of data processing have caused an intolerable ‘memory wall’ and ‘power wall’ challenge for traditional Von Neumann architectures. Therefore, more advanced Computing-in-memory (CiM) architectures are proposed. The emerging non-volatile memory Spin Transfer Torque Magnetic Random Access Memory (STT-MRAM), with its fast access speed, near-zero leakage power consumption and high density is one of the most competitive carriers for CiM architectures.Due to the inherent read-write asymmetry of STT-MRAM, the read overhead is multiples smaller than the exaggerated write overhead. To better exploit the potential of MRAM, we focus on implementing an CiM based on the reading process.This work introduces the principle of CiM and proposes four basic logic operations (XNOR, XOR, AND and OR) based on STT-MRAM. Furthermore, a delay-based XNOR-popcount (XNOR-PC) operation for BNN based on XNOR operation is proposed. Incorporating the reading characteristics of STT-MRAM and slight modifications to the peripheral circuitry, these operations achieve significant optimisation in terms of performance and energy consumption. Simulation results show the proposed scheme can reduce the latency of XOR, AND, and OR operations at least by 99.3%, 82.2% and 80.2% compared with the existing design. The proposed XNOR-PC operation achieves at least a 59.4% reduction in power consumption and has a high degree of reliability. Also, Monte Carlo simulations prove the feasibility and robustness of the schemes.
Leaders’ induced justice perceptions as mediator of the relation between participative leadership behaviors and team learning

Introduction In today’s complex and changing business environment organizations need to learn and adapt to emerging circumstances. Teams can be a preferred vehicle to facilitate solving challenges that require diverse perspectives and expertise, collaboration, and knowledge sharing among members. To support team learning, organizations need to understand and promote an appropriate environment that facilitates learning within teams. By drawing on Fairness Theory and Social Exchange Theory, this study explores the role of leader-induced justice perceptions as a mediator in the relationship of participative leadership and team learning. Methods Using a split-half team survey methodology with a sample of 211 teams, the study analyzes the role of team justice climate as a mediation mechanism in the relationship between participative leadership behaviors and team learning. Results Results from structural equation modeling analyses suggest that, at a team level, participative leadership behaviors have both a direct association with team learning and are partially mediated by the team’s justice climate. Discussion This study contributes to existing literature by offering evidence that the perceptions of justice instilled by leaders play a role mediating participatory leadership and team learning. Moreover, the study supports the idea that leader induced justice perceptions can be considered as an aggregated construct at the team level. From a practical standpoint, the findings imply that team leaders can contribute to create an environment conducive to team learning by treating team members with fairness.
Computer Modelling of Pipe Straightening Process on a Six-Roller Cross-Roll Machine

The role of computer modelling in the research of physical and industrial objects has significantly increased, as well as the quality of programs for modelling processes. Finite element modelling is successfully used to study metal forming processes, which allows to study phenomena and improve technology. In this paper, with the use of Abaqus CAE software for finite element analysis, a solid-state model of a sixroller cross roll machine for straightening of rolled pipes was built. The spread of such machines is constrained by the difficulties of setting up the process of straightening of pipe end sections at the entrance and exit from the edge rolls, where buckling defects occur. Minimization of residual pipe curvature is also important. In order to predict the stress-strain state and force modes of tube dressing, finite element modelling was carried out, which revealed the character of influence of design and technological parameters of the dressing process in profiled rolls with symmetrical profiling of pairs of edge rolls. According to the results of computer modelling, the crossed rolls overlapping conditions were established, which allow to reduce the residual curvature of the pipe three times.
Intelligent vehicle localization and navigation based on intersection fingerprint roadmap (IRM) in underground parking lots

The localization and navigation of underground parking lots presents a ‘last mile’ problem for intelligent vehicles. To address the issues of poor localization and navigation efficiency caused by the lack of global navigation satellite system signals in this scenario, this study presents a low-cost and computationally efficient real-time localization and navigation algorithm. The algorithm begins by constructing a node fingerprint based on the characteristics of underground parking lot intersections and proposes an intersection fingerprint roadmap (IRM). To address the problem of difficult initial position computation during navigation, a node-level localization method based on scene matching and pose calculation is proposed and then combined with the IRM. Finally, the IRM is used to search for routes on the scene plan and perform path smoothing to obtain a globally feasible driving route. The algorithm proposed in this study can achieve fast vehicle localization and real-time navigation with low computational power, and the proposed localization method can be applied not only to underground parking lots but also to other outdoor scenes. The method is evaluated on datasets collected from different environments, and the experimental results show that the algorithm has an average localization error of approximately 20 cm and provides faster navigation speed and smoother navigation in comparison with other algorithms.