Miracle-dz/UniFAR-FTUs huggingface dataset:
An Enhanced TSA-MLP Model for Identifying Credit Default Problems

Credit default has always been one of the critical factors in the development of personal credit business. By establishing a default identification model, default can be avoided effectively. There are some existing methods to identify credit default. However, these methods have some problems: Problem (1): It is different to deal the non-linear data, Problem (2): The local stagnation results in the high error rate, and Problem (3): The premature convergence leads to the low classification rate. In this paper, the sinhTSA-MLP default risk identification model is proposed to solve these problems. In this model, the proposed sinhTSA method can effectively avoid the problems of falling into local optimum and premature convergence. And the benchmark test results demonstrate sinhTSA is superior to other methods. According to the two experiments, the classification rate reaches 77.35% and 96.48%. Therefore, the sinhTSA-MLP default identification model has some particular advantages in identifying credit problems The feasibility of the sinhTSA-MLP default identification model has been proved through helping to manage credit default more consciously.
A Switching Control Strategy of Greenhouse Temperature-Humidity System based on Prediction Model

It's difficult to achieve the coordination control of multiple facilities which are driven by the on-off actuators in greenhouse, especially when more than one indoor environmental factor needs to be considered together. We proposed a switching control strategy based on prediction model, with the consideration of indoor air temperature and relative humidity. At first, the operation of greenhouse system was divided into several modes according to the on-off control characteristic of facilities. Then for each current mode, the operating modes which the greenhouse is likely to enter into at the next moment are listed in different conditions of indoor air temperature and humidity. When the two indoor environmental factors reach the upper or lower limits, we use the IARX models to predict them over a specified horizon for each optional mode respectively. The mode switch is achieved based on the prediction results. The simulation results show that the facilities can be controlled coordinately very well and the proposed control strategy is easy to implement. The control strategy is still applicative when there are more facilities or more indoor environmental factors needed to be taken into account.
Enabling Big Memory with Emerging Technologies

The demand for main memory capacity has been increasing for many years and will continue to do so. In the past, Dynamic Random Access Memory (DRAM) process scaling has enabled this increase in memory capacity. Along with continued DRAM scaling, the emergence of new technologies like 3D-stacking, buffered Dual Inline Memory Modules (DIMMs), and crosspoint nonvolatile memory promise to continue this trend in the years ahead. However, these technologies will bring with them their own gamut of problems. In this dissertation, I look at the problems facing these technologies from a current delivery perspective. 3D-stacking increases memory capacity available per package, but the increased current requirement means that more pins on the package have to be now dedicated to provide Vdd/Vss, hence increasing cost. At the system level, using buffered DIMMs to increase the number of DRAM ranks increases the peak current requirements of the system if all the DRAM chips in the system are Refreshed simultaneously. Crosspoint memories promise to greatly increase bit densities but have long read latencies because of sneak currents in the cross-bar. In this dissertation, I provide architectural solutions to each of these problems. We observe that smart data placement by the architecture and the Operating System (OS) is a vital ingredient in all of these solutions. We thereby mitigate major bottlenecks in these technologies, hence enabling higher memory densities. To my Wife, Parents, and the Wonderful People at the University of Utah.
Wideband Integrated Log-Periodic Antenna Array for 5G Q-Band Applications

A wideband integrated log-periodic antenna (LPA) based on multilayer printed circuit board for fifth-generation (5G) Q-band applications is presented in this letter. The LPA is fed by the broadband radial slot transition balun. The LPA has four dipoles which are separately placed on different thickness printed circuit board substrates. To enhance the gain and reduce the cross-polarization level, the symmetrical layout and differential feeding are adopted in the 4 × 4 LPA array design. The measured results show that the proposed 4 × 4 LPA array achieves the impedance bandwidth of 32.5% (32.5–45 GHz) and the peak gain of 15.5 dBi. Due to these advantages of low cost, wideband and easy for integration, the 4 × 4 LPA array will be a potential candidate scheme for 5G Q-band applications.
Behavior or culture? Investigating the use of cryptocurrencies for electronic commerce across the USA and China

Purpose This paper claims to identify the behavioral and cultural features that push to use, or not, cryptocurrencies for electronic commerce. Indeed, despite the use of cryptocurrencies for electronic commerce spreading worldwide at a fast and growing pace, there are supporters and detractors among their users. The analysis of what distinguish these two groups of users is fundamental for understanding their different intention to use cryptocurrencies for electronic commerce. Design/methodology/approach A survey has been administered to 2,532 cryptocurrencies’ users across the USA and China, collecting data on their behavioral predispositions and cultural features. Results were then analyzed through structured equation modeling. Findings Results showed that while attitude, subjective norms, perceived behavioral control and herding behavior have a positive impact on the intention to use cryptocurrencies for electronic commerce, financial literacy has no influence. Cultural dimensions amplified or reduced the discovered relationships and caused different effects: positive for the USA and negative for China when considering illegal attitude and perceived risk. Originality/value Theory of planned behavior, financial behavior and cultural factors can, all together, represent a useful framework for envisioning the behavior of users in adopting cryptocurrencies for electronic commerce purposes through a test of all its elements. To the best of the authors’ knowledge, this is the first study considering behavior and cultural variables on the intention to use cryptocurrencies for electronic commerce as well as being the largest carried out, in terms of sample, on the cryptocurrency topic.
Enhancing THz/mmWave Network Beam Alignment With Integrated Sensing and Communication

Future networks are envisioned to create digital twin representations of the physical world, motivated by the integrated sensing and communication (ISAC). To meet the needs, millimetre wave (mmWave) and terahertz (THz) signals shine with outstanding performance in high-speed transmission and high-accuracy perception, but requiring narrow beamwidth to compensate for high path-loss. It in turn causes severe beam misalignment that induces link failures, leaving reliable inter-cell handovers and intra-cell beam switches crucial challenges for THz/mmWave networks. Exploiting the Synchronization Signal Block (SSB) specified for beam management, we propose a system-level beam alignment scheme utilizing SSB-based sensing to assist beam switches. To fully utilize limited sensing resource, we provide a closed-form optimal SSB time-frequency pattern design that complies with current configuration. Results show that proposed scheme reduces up to 70% beam misalignment probability in highway and urban cases. Thus, guaranteeing the same beam alignment quality, sensing-aided networks can use narrower beams to enlarge network coverage. Also, the optimal resource allocation for SSB pattern design is stable against changing node density and mobility.
Emotional Context Shapes the Serial Position Curve

Emotional contexts affect memory processes. However, the impact of contextual priming as a function of the emotional valence on the recall of neutral information is not fully understood. The aim of the present study was to evaluate how a conditioning of emotional context during encoding may influence the subsequent memory of otherwise neutral materials in a well-established phenomenon as the serial position effect. Participants performed a free recall task for neutral words in three conditions: (i) word list alone; (ii) word list coupled with positive or neutral images; and (iii) word list coupled with negative or neutral images. Images were presented before each word stimulus. In three different experiments, the emotional context during the word list presentation was manipulated separately for primacy and recency clusters, and for the middle words (‘middlecy’). Emotional context affects free recall of neutral stimuli, changing the serial position curve effect across conditions. Namely, emotional images presented in the primacy and recency clusters worsen accuracy, whereas their occurrence in the ‘middlecy’ cluster reduces the oblivion. The present findings show that the typical pattern related to the serial position curve for neutral information can be shaped by the conditioning of emotional context. Findings have implications in medical-legal contexts in the case of the recollection of events with high emotional content.
Improved energy absorption capacity of closed-cell aluminium foams by electroplating

ABSTRACT In the present study, hybrid closed-cell foams consisting of two materials with different ductilities were manufactured to improve the energy absorption capacity. The mechanical characteristics, deformation modes and energy absorption capacities of the foams were investigated. Furthermore, the energy absorption mechanisms of the hybrid foams were analysed. The results demonstrated a significant synergistic effect between the foams and coating with different ductilities during deformation. Their combination increased the densification strain and improved the energy absorption capacity of the samples. Among the specimens investigated, the Al/Zn–Cu(A) foam showed the best densification strain (0.75) and presented superior energy absorption capacities (energy absorption capacity per unit volume (Uv) = 4.5 J cm–3; energy absorption capacity per unit mass (Um) = 8.4 J g–1). The intrinsic mechanism of energy absorption optimisation is a combination of the advantages of brittle and ductile deformation modes.
Investigation and prediction of hurricane eyewall replacement cycles

Flight-level aircraft data and microwave imagery are analyzed to investigate hurricane secondary eyewall formation and eyewall replacement cycles (ERCs). This work is motivated to provide forecasters with new guidance for predicting and better understanding the impacts of ERCs. A Bayesian probabilistic model that determines the likelihood of secondary eyewall formation and a subsequent ERC is developed. The model is based on environmental and geostationary satellite features. A climatology of secondary eyewall formation is developed; a 13% chance of secondary eyewall formation exists when a hurricane is located over water, and is also utilized by the model. The model has been installed at the National Hurricane Center and has skill in forecasting secondary eyewall formation out to 48 h. Aircraft reconnaissance data from 24 ERCs are examined to develop a climatology of flight-level structure and intensity changes associated with ERCs. Three phases are identified based on the behavior of the maximum intensity of the hurricane: intensification, weakening and reintensification. Despite a large oscillation of intensity, with a weakening of ~10 m s -1 occurring during most of the ERC, the net intensity change is near zero. However, a broadening of the wind field is observed, and the eye rarely contracts back to the radius prior to the ERC. The expanding storm size increases the storm’s integrated kinetic energy. Thermodynamic fluctuations are also documented during an ERC. Flight-level temperature, dewpoint, relative humidity, and θe are all found to increase within the inner-core over the course of an ERC, except for a decrease of mean relative humidity in the moat region. Near the end of an ERC, high values of inertial stability are associated with the relict inner eyewall circulation and create a “containment vessel” that confines the old-eye air mass. This is evident ii by the difference in θe values (> 10 K) between the old-eye air mass and the adjacent moat at the end of and following an ERC. The relict inner eyewall circulation is found to be an important feature that can impact the secondary circulation of the inner-core, the intensification of the outer eyewall, and the pressure-wind relationship of the storm.
Age-related variation in male youth athletes’ countermovement jump following plyometric training

Recent debate on the trainability of youths has focused on the existence of periods of accelerated adaptation to training. Accordingly, the purpose of this meta-analysis was to identify the age- and maturation-related pattern of adaptive responses to plyometric training in youth athletes. Thirty effect sizes were calculated from the data of 21 sources with studies qualifying based on the following criteria: (a) Healthy male athletes who were engaged in organised sport; (b) Groups of participants with a mean age between 10 and 18 years; (c) Plyometric-training intervention duration between 4 and 16 weeks. Standardised mean differences showed plyometric training to be moderately effective in increasing countermovement jump (CMJ) height (ES = 0.73 95% confidence interval: 0.47-0.99) across PRE-, MID-, and POST-peak height velocity groups. Adaptive responses were of greater magnitude between the mean ages of 10 and 12.99 years (PRE) (ES = 0.91 95% confidence interval: 0.47-1.36) and 16 and 18 years (POST) (ES = 1.02 [0.52-1.53]). The magnitude of adaptation to plyometric training between the mean ages of 13 and 15.99 years (MID) was lower (ES = 0.47 [0.16-0.77]), despite greater training exposure. Power performance as measured by CMJ may be mediated by biological maturation. Coaches could manipulate training volume and modality during periods of lowered response in order to maximise performance.
Linking JUICE and R: New developments in visualization ofunconstrained ordination analysis

JUICE program offers user friendly environment for editing, classification and analysis of vegetation data. R-project has almost unlimited possibilities of analysis and visualization of any type of data, yet its interface is not designed for user without an advanced experience. Therefore, we decided to use the benefits of these programs, using JUICE interface and R-project engine, for advanced visualization of results of unconstrained ordination analysis, such as Detrended Correspondence Analysis (DCA), Principal Components Analysis (PCA) and Non-metric Multidimensional Scaling (NMDS). In R-project, wide selection of analytical and visualization tools for multivariate ordination analysis is available in the package vegan, developed by Jari Oksanen and his colleagues. We used this package, extended its functionality for several new visualization methods and connected it with JUICE program. Beside traditional two dimensional ordination diagrams with projected environmental variables and vegetation groups, the combination of JUICE and R program offers more advanced methods such as three dimensional interactive ordination diagrams with convex hulls or spiderplots. The function such as manual update, online discussion forum, online manual and export of ordination results are also provided. We believe that this method, particularly the three dimensional visualization of ordination results, may bring new possibilities for interpretation of ordination results and their quick and effective visualization.
Analysis of a Repetitive Language Coding System: Comparisons between Fragile X Syndrome, Autism, and Down Syndrome

Expressive language sampling (ELS) is a frequently used tool for language analysis, as it can be used across widely ranging cognitive and language abilities. ELS can also evaluate pragmatic language, including excessive self-repetition, which is challenging to assess with traditional standardized assessments. This study explored how a well-established ELS protocol can assess three types of linguistic self-repetition in three neurodevelopmental disabilities: fragile X syndrome (FXS), autism spectrum disorder (ASD), and Down syndrome (DS). We examined its ability to differentiate between these disorders, the relationships between repetitive language and other participant characteristics, and initial construct validity. We found that the groups with FXS and ASD differed significantly on each of the three repetitive language measure, and that the group with DS differed from either ASD or FXS on two. Cognitive ability was significantly related to phrase repetition in the group with ASD. When the groups were combined, there was evidence of convergent and divergent validity. This study extends previous research on ELS and supports its use as a means to characterize pragmatic language. It also provides information about the relationships between repetitive language and other phenotypic characteristics.
Interactive effects of the low‐carbohydrate diet score and genetic risk score on Hypo‐HDL‐cholesterolemia among Korean adults: A cross‐sectional analysis from the Ansan and Ansung Study of the Korean Genome and Epidemiology Study

Abstract This cross‐sectional study investigated the interaction between the genetic risk score (GRS) and abnormal high‐density lipoprotein (HDL) cholesterol lipid levels, which are modified by low‐carbohydrate diets (LCDs) and their effects on the prevalence of hypo‐HDL‐cholesterolemia (hypo‐HDL‐C) in Korean adults. Baseline data were obtained from the Ansan and Ansung study of the Korean Genome and Epidemiology Study (KoGES), conducted from 2001 to 2002, that targeted 8,314 Korean adults aged 40–69 years, including old men (47.6%) and women (52.4%), and whole genomic single nucleotide polymorphism (SNP) genotyping was performed. We identified 18 SNPs significantly associated with hypo‐HDL‐C in the proximity of several genes, including LPL, APOA5, LIPC, and CETP, and calculated the GRS. The low‐carbohydrate diet score (LCDS) was calculated on the basis of energy intake information from food frequency questionnaires. Furthermore, we performed multivariable‐adjusted logistic modeling to examine the odds ratio (OR) for hypo‐HDL‐C across tertiles of LCDS and GRS, adjusted for several covariates. Among participants in the highest GRS tertile, those in the highest tertile of the LCDS had a significantly lower risk of hypo‐HDL‐C (OR: 0.759, 95% CI (confidence interval): 0.625–0.923) than those in the lowest tertile of the LCDS. In the joint effect model, the group with the lowest GRS and highest LCDS was found to have the lowest risk of hypo‐HDL‐C prevalence. This study suggests that individuals with a high genetic risk for low HDL concentrations may have a beneficial effect on a lower intake of carbohydrates.
Model Reference Adaptive Speed Observer Control of Permanent Magnet Synchronous Motor Based on Single Neuron PID

For the speed sensorless control of permanent magnet synchronous motor (PMSM), a design method based on model reference adaptive observer and single neuron PID speed loop was proposed. In this method, the model reference adaptive observer is used to identify the speed online, the Popov hyperstability is used to determine the reference adaptive law of the speed observer, the neural network module is used to control the q-axis current, and the LMS algorithm is selected to modify the weights of the neural network speed loop online. The simulation results show that the model reference adaptive speed observer control of PMSM based on single neuron PID is effective and robust.
MPPT Design Using PSO Technique for Photovoltaic System Control Comparing to Fuzzy Logic and P&O Controllers

The Maximum Power Point Tracker (MPPT) is the optimum operating point of a photovoltaic module. It plays a very important role to obtain the maximum power of a solar panel as it allows an optimal use of a photovoltaic system, regardless of irradiation and temperature variations. In this research, we present a novel technique to improve the control’s performances optimization of the system consisting of a photovoltaic panel, a buck converter and a load. Simulations of different parts of the system are developed under Matlab/Simulink, thus allowing a comparison between the performances of the three studied controllers: “Fuzzy TS”, “P&O” and “PSO”. The three algorithms of MPPT associated with these techniques are tested in different meteorological conditions. The obtained results, in different operating conditions, reveal a clear improvement of controlling performances of MPPT of a photovoltaic system when the PSO tracking technique is used.
Evaluating the Impact of Possible Dependencies on Architecture-Level Maintainability

Dependencies among software entities are the foundation for much of the research on software architecture analysis and architecture analysis tools. Dynamically typed languages, such as Python, JavaScript and Ruby, tolerate the lack of explicit type references, making certain dependencies indiscernible by a purely syntactic analysis of source code. We call these possible dependencies, in contrast with the explicit dependencies that are directly manifested in source code. We find that existing architecture analysis tools have not taken possible dependencies into consideration. An important question therefore is: to what extent will these missing possible dependencies impact architecture analysis? To answer this question, we conducted a study of 499 open-source Python projects, employing type inference techniques and type hint practices to discern possible dependencies. We investigated the consequences of possible dependencies in three software maintenance contexts, including capturing co-change relations recorded in revision history, measuring architectural maintainability, and detecting architecture anti-patterns that violate design principles and impact maintainability. Our study revealed that the impact of possible dependencies on architecture-level maintainability is substantial—higher than that of explicit dependencies. Our findings suggest that architecture analysis and tools should take into account, assess, and highlight the impacts of possible dependencies caused by dynamic typing.
Ecological Footprint at a Small Scale : Proposition of a Method and Model of Representation of Ecological Footprint for Industrial Activities

Ecological footprint, proposes a kind of “ecological balance” that assesses and compares biologically productive area supply and demand. If the success of this index at a national level is proven, we assume that, to help each organisation or person to apprehend its own contribution to ecological footprint, it can be helpful to develop methods of estimation of ecological footprint at organisational level. For a given sub national system two methods can be used to have an idea of its ecological footprint: (1) The national account based approach is based on the corrections of factors from the national averages of consumptions. , (2) The component-based approach is based on an inventory of the consumptions and wastes generated by the observed system, the calculation of standards or specific transfer coefficients. This method seemed to the authors more appropriate. However, it requires several methodological adaptations to the classical ecological footprint methods and it presents some limitations. In order to precise these adaptations requirements and limitations, we developed and experimented such a component-based approach on a real case. Our application field is a road work.