Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating 4D coronal heating events in magnetohydrodynamic simulations

Context. One candidate model for heating the solar corona is magnetic reconnection that embodies Ohmic dissipation of current sheets. When numerous small-scale magnetic reconnection events occur, then it is possible to heat the corona; if ever observed, these events would have been the speculated nanoflares. Aims. Because of the limitations of current instrumentation, nanoflares cannot be resolved. But their importance is evaluated via statistics by finding the power-law index of energy distribution. This method is however biased for technical and physical reasons. We aim to overcome limitations imposed by observations and statistical analysis. This way, we identify, and study these small-scale impulsive events. Methods. We employed a three-dimensional magnetohydrodynamic (3D MHD) simulation using the Bifrost code. We also employed a new technique to identify the evolution of 3D joule heating events in the corona. Then, we derived parameters describing the heating events in these locations, studied their geometrical properties and where they occurred with respect to the magnetic field. Results. We report on the identification of heating events. We obtain the distribution of duration, released energy, and volume. We also find weak power-law correlation between these parameters. In addition, we extract information about geometrical parameters of 2D slices of 3D events, and about the evolution of resolved joule heating compared to the total joule heating and magnetic energy in the corona. Furthermore, we identify relations between the location of heating events and the magnetic field. Conclusions. Even though the energy power index is less than 2, when classifying the energy release into three categories with respect to the energy release (pico-, nano-, and micro-events), we find that nano-events release 82% of the resolved energy. This percentage corresponds to an energy flux larger than that needed to heat the corona. Although no direct conclusions can be drawn, it seems that the most popular population among small-scale events is the one that contains nano-scale energetic events that are short lived with small spatial extend. Generally, the locations and size of heating events are affected by the magnitude of the magnetic field.
Knowledge Discovery from Database using an Integration of Clustering and Association Rule Mining

Clustering and Association are two important techniques of data mining. Association rule learning is a well researched method for discovering interesting relations between variables in large databases. It identifies and defines strong rules discovered in databases using different measures of interestingness. While, clustering is an unsupervised learning problem that group objects based upon distance or similarity. Each group formed is known as a cluster. In this paper we make use of a large database 'Kidney Dataset' containing 7 attributes and 154 instances to perform an integration of clustering and association rule mining to determine some essential and interesting rules formed in case of each cluster and can also demonstrate the results as the minimum support changes based on various parameters using WEKA (Waikato Environment for Knowledge Analysis), a Data Mining tool. The results of the experiment show that integration of clustering and Association Rule Mining give some essential and content-related rules.
Litter traits and palatability to detritivores: a case study across bio-geographical boundaries

The activity of the litter-feeding macrofauna affects litter decomposition rates at the local scale, and their preference for particular litter types is mediated by litter traits. Environmental changes such as invasion by exotic plants may change the characteristics of the litter at a local scale, with consequences to ecosystem processes. Here we evaluated the feeding preferences of four detritivores (terrestrial isopods) from two biogeographic regions (neotropical and palearctic), offering them native or non-native litter in cafeteria experiments. Our results show that isopods from different geographical regions exhibit essentially the same food preference, irrespective of whether or not they previously had encountered the litter tested. Combining the isopods' preference ranks with the principal component analysis of nine litter traits, we show that preference increases with increasing nitrogen and calcium contents and decreases with increasing toughness, C:N ratio and thickness, irrespective of the geographical origin of both litter and detritivores. We conclude that the palatability of a non-native litter to the native detritivore community can be predicted from their respective litter traits and thus, native detritivores will feed on a particular non-native litter type as likely as do detritivores in the native range of the plant. As the combination of traits that indicates palatability to the isopods also indicates litter decomposability, it could be possible to predict ecosystem responses in terms of litter decomposition rates upon changes in litter composition.
Identification of Psy1 genes alleles responsible for carotenoid accumulation in wheat grains

The aim of the research was to select and optimize marker systems for identification of Psy1 ge nes alleles, which are responsible for different levels of carotenoid pigments accumulation in wheat grains, as well as to screen varieties for the selection of valuable genotypes. 162 wheat samples were analyzed by the polymerase chain reaction method. Among them, varieties and lines with different allelic states of Psy-A1 and Psy-B1 genes were identified. The Psy-D1 gene did not show any polymorphism. As a result, samples with valuable alleles of Psy1 genes, which potentially contain increased carotenoids content in grains, were selected.
Teaching Model as a Living Document

Many new civil engineering faculty members have little to no formal training on teaching. New faculty are often welcomed to their respective institution, introduced to other faculty members, shown their office, and left to figure out how to teach on their own. Several institutions have recognized this deficiency, and have taken some type of action to develop the teaching ability of their faculty members. Teaching models are one of the tools that have been used by some organizations to develop the teaching ability of their faculty members. The Department of Civil and Mechanical Engineering at the United States Military Academy at West Point prepares their new faculty to teach by administering an in-depth six week training program. The training program, which is centered on the department’s teaching model, effectively prepares teachers to actively engage students in the learning and development process. The current teaching model was established in the late 1990s, and has remained unchanged for over 15 years. This paper provides an overview of the current teaching model and describes recent initiatives that led to several recommended changes, thus treating the teaching model as a living document to ensure it remains relevant.
An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization

Many application problems of practical interest can be posed as structured convex optimization models. In this paper, we study a new first-order primaldual algorithm. The method can be easily implementable, provided that the resolvent operators of the component objective functions are simple to evaluate. We show that the proposed method can be interpreted as a proximal point algorithm with a customized metric proximal parameter. Convergence property is established under the analytic contraction framework. Finally, we verify the efficiency of the algorithm by solving the stable principal component pursuit problem.
p 21 promotes error-free replication-coupled DNA double-strand break repair

p21 is a well-established regulator of cell cycle progression. The role of p21 in DNA repair, however, remains poorly characterized. Here, we describe a critical role of p21 in a replication-coupled DNA double-strand break (DSB) repair that is mechanistically distinct from its cell cycle checkpoint function. We demonstrate that p21-deficient cells exhibit elevated chromatid-type aberrations, including gaps and breaks, dicentrics and radial formations, following exposure to several DSBinducing agents. p21 / cells also exhibit an increased DNA damage-inducible DNA-PKCS S2056 phosphorylation, indicative of elevated nonhomologous DNA end joining. Concomitantly, p21 / cells are defective in replication-coupled homologous recombination (HR), exhibiting decreased sister chromatid exchanges and HRdependent repair as determined using a crosslinked GFP reporter assay. Importantly, we establish that the DSB hypersensitivity of p21 / cells is associated with increased cyclin-dependent kinase (CDK)-dependent BRCA2 S3291 phosphorylation and MRE11 nuclear foci formation and can be rescued by inhibition of CDK or MRE11 nuclease activity. Collectively, our results uncover a novel mechanism by which p21 regulates the fidelity of replication-coupled DSB repair and the maintenance of chromosome stability distinct from its role in the G1-S phase checkpoint.
Towards Understanding Practitioners ’ Knowledge and Experiences on the Software Architecture Viewpoints : A Survey

Architecture viewpoints promote separating software architectures into different viewpoints that each address the particular aspect of a software system. This paper discusses a survey conducted among 56 practitioners from 20 different countries who are involved in software development and aims at understanding their knowledge and experience about five important architectural viewpoints – i.e., logical, behaviour, concurrency, physical, and deployment. Some of the interesting survey results are as follows: (i) while the logical, behaviour, physical, and deployment viewpoints are widely used, the concurrency viewpoint is not so; (ii) the top-preferred structural unit for a logical component is the external interfaces and the least-preferred is the internal computation unit. (iii) the top-preferred simple connector type is the asynchronous events; (iv) the complex connectors (e.g., adaptor and arbitrator) are not as popular as simple connectors; (v) boxes and lines diagram and natural languages (e.g., English) are the top-preferred software modelling notations for each viewpoint considered, while architectural languages, and formal specification languages are never used by many; (vi) documenting design decisions and their communication is the main source of motivation for each viewpoint; (vii) the specifications of the interaction behaviours of components are highly desired by practitioners; (viii) mapping between different viewpoints cannot always be achieved due to the inadequate software modelling notations; and (ix) scalability, performance, and security are the top-considered quality properties for the behaviour viewpoint, while scalability and availability are the top-considered ones for the deployment viewpoint.
The Mediterranean Diet Protects Renal Function in Older Adults: A Prospective Cohort Study

Background: Chronic kidney disease entails a high disease burden that is progressively increasing due to population aging. However, evidence on the effect of the Mediterranean diet on renal function is limited, in particular among older adults in Mediterranean countries. Methods: Prospective cohort study with 975 community-dwelling adults aged ≥ 60 recruited during 2008–2010 in Spain and followed up to 2015. At baseline, food consumption was obtained using a validated dietary history. Two Mediterranean dietary patterns were used: (i) An a priori-defined pattern, the Mediterranean Diet Adherence Screener (MEDAS score: low adherence: 0–5 points; moderate: 6–8 points; high: 9–14 points); (ii) An a posteriori Mediterranean-like dietary pattern, based on 36 food groups, which was generated using factor analysis. Renal function decline was calculated as an estimated glomerular filtration rate (eGFR) decrease ≥1 mL/min/1.73 m2 per year of follow-up. Results: A total of 104 cases of renal function decline occurred. Compared with participants with a low MEDAS adherence, the multivariable-adjusted odds ratios (95% confident interval) for renal function decline risk were 0.63 (0.38–1.03) for moderate adherence, and 0.52 (0.29–0.95) for high adherence (p-trend: 0.015). Multivariable-adjusted odds ratios (95% confidence interval) for renal function decline risk according to increasing quartiles of the adherence to the a posteriori Mediterranean-like dietary pattern were 1.00, 0.67 (0.38–1.20), 0.65 (0.35–1.19), and 0.47 (0.23–0.96) (p-trend: 0.042). Conclusion: A higher adherence to a Mediterranean diet was associated with a lower risk of renal function decline in older adults, suggesting benefits to health of this dietary pattern in Mediterranean countries.
A Control Method for the Ultrasonic Spot Welding of Fiber-Reinforced Thermoplastic Laminates through the Weld-Power Time Derivative

It was found that the ultrasonic spot welding may serve as an efficient method to join relative large thin-walled parts made of fiber-reinforced thermoplastics. In this study, a new control method for the ultrasonic spot-welding process was investigated. It was found that, when welding fiber-reinforced thermoplastic laminates without energy directors, overheating and decomposition of the polymer at the weld spot occurred. The occurrence of the overheating took place at unpredictable times during welding. It was observed that the time trace of the consumed power curve by the welder follows a similar pattern as the time trace of the temperature in the weld spot center. Based on this observation, a control system was developed. The time derivative of the welder power was monitored in real time and, as soon as it exceeded a critical value, the ultrasonic vibration amplitude was actively adjusted through a microcontroller. The controlling of the ultrasonic welding process forced the temperature in the weld spot to remain in an adequate range throughout the welding duration for the polymer diffusion to occur. The results of the controlled welding process were evaluated by means of weld temperature measurements, computed tomography scans, and microscopic analysis of the weld spot fracture surfaces.
Smartphone-Based Evaluation of Postural Stability in Parkinson’s Disease Patients During Quiet Stance

Background: Postural instability is one of the most troublesome motor symptoms of Parkinson’s Disease (PD). It impairs patients’ quality of life and results in high risk of falls. The aim of this study is to provide a reliable tool for the automated assessment of postural instability. Methods: Data acquisition was performed on 42 PD patients and 7 young healthy subjects. They were asked to keep a quiet stance position for at least 30 s while wearing a waist-mounted smartphone. A total number of 414 features was extracted from both time and frequency domain, selected based on Pearson’s correlation, and fed to an optimized Support Vector Machine. Results: The implemented model was able to differentiate patients with mild postural instability from those with severe postural instability and from healthy controls, with 100% accuracy. Conclusion: This study demonstrated the feasibility of using inertial sensors embedded in commercial smartphones and proposed a simple protocol for accurate postural instability scoring. This tool can be used for early detection of PD motor signs, disease follow-up and fall prevention.
Privatization & FDI: Examining Growth in Vietnam's Provinces

Over the past three decades many developing countries have looked toward privatizing investment markets and relying more on Foreign Direct Investment (FDI) to supply needed capital investment for their emerging private sectors. In their pursuit of foreign capital, developing countries have enacted several changes in economic policy and regulation in hopes of transforming formerly rural and undeveloped countries into highly urbanized centers of global production. This is particularly true for a transitioning economy such as Vietnam, which has seen increasing privatization of industry and investment since the reforms of 1986 known as “Doi Moi. ” In this study I investigate the effect privatization of investment has had on industrial output per capita growth. My results indicate that FDI is both positive and statistically significant even after endogenous robustness checks. Further, I find convincing evidence that provinces with highly planned investment regimes have their growth significantly harmed by state investment and do not benefit from FDI, particularly if they are urbanizing. My results suggest that provinces with mixed and privatized investment regimes are best suited to increase growth and benefit from FDI.
Climate-change refugia: biodiversity in the slow lane

Climate-change adaptation focuses on conducting and translating research to minimize the dire impacts of anthropogenic climate change, including threats to biodiversity and human welfare. One adaptation strategy is to focus conservation on climate-change refugia (that is, areas relatively buffered from contemporary climate change over time that enable persistence of valued physical, ecological, and sociocultural resources). In this Special Issue, recent methodological and conceptual advances in refugia science will be highlighted. Advances in this emerging subdiscipline are improving scientific understanding and conservation in the face of climate change by considering scale and ecosystem dynamics, and looking beyond climate exposure to sensitivity and adaptive capacity. We propose considering refugia in the context of a multifaceted, long-term, network-based approach, as temporal and spatial gradients of ecological persistence that can act as “slow lanes” rather than areas of stasis. After years of discussion confined primarily to the scientific literature, researchers and resource managers are now working together to put refugia conservation into practice.
Hand-Dorsa Vein Recognition Based on Selective Deep Convolutional Feature

SUMMARY A pre-trained deep convolutional neural network (DCNN) is adopted as a feature extractor to extract the feature representation of vein images for hand-dorsa vein recognition. In speciﬁc, a novel selective deep convolutional feature is proposed to obtain more representative and discriminative feature representation. Extensive experiments on the lab-made database obtain the state-of-the-art recognition result, which demonstrates the e ﬀ ectiveness of the proposed model. key words: hand-dorsa vein recognition, pre-trained DCNN, selective deep convolutional feature
Analysis of Green Spaces by Utilizing Big Data to Support Smart Cities and Environment: A Case Study About the City Center of Shanghai

Green areas or parks are the best way to encourage people to take part in physical exercise. Traditional techniques of researching the attractiveness of green parks, such as surveys and questionnaires, are naturally time consuming and expensive, with less transferable outcomes and only site-specific findings. This research provides a factfinding study by means of location-based social network (LBSN) data to gather spatial and temporal patterns of green park visits in the city center of Shanghai, China. During the period from July 2014 to June 2017, we examined the spatiotemporal behavior of visitors in 71 green parks in Shanghai. We conducted an empirical investigation through kernel density estimation (KDE) and relative difference methods on the effects of green spaces on public behavior in Shanghai, and our main categories of findings are as follows: (i) check-in distribution of visitors in different green spaces, (ii) users’ transition based on the hours of a day, (iii) famous parks in the study area based upon the number of check-ins, and (iv) gender difference among green park visitors. Furthermore, the purpose of obtaining these outcomes can be utilized in urban planning of a smart city for green environment according to the preferences of visitors.
BSec-NFVO: A Blockchain-Based Security for Network Function Virtualization Orchestration

Network Function Virtualization (NFV) and Service Function Chaining (SFC) offer flexible end-to-end services that deploy virtual network functions in clouds of competing providers. Orchestration of virtual network functions occurs in a distributed and trustless environment that must tolerate byzantine failures and collusion attacks. This paper proposes BSec-NFVO, a blockchain-based system that secures orchestration operations in virtualized networks, ensuring auditability, non-repudiation and integrity. We propose an NFV-tailored blockchain and a transaction model. BSec-NFVO provides a modular architecture to secure orchestration in a simple and agile way. We develop a prototype of BSec-NFVO for the Open Platform for Network Function Virtualization (OPNFV) with an adaptation of the normal-case of a collusion-resistant consensus protocol. The results show BSec-NFVO incurs low overhead to the cloud orchestrator and presents stable performance as the number of consensus participants increases.
Methodological Issues in Studying Late Life Bereavement

The death of one’s spouse is considered one of the most distressing, yet also one of the most common, transitions that older Americans face. Although studies of spousal bereavement have flourished in recent years, researchers have not reached a consensus on important issues related to loss. Scholars continue to debate important policy-relevant questions, such as: Who suffers more, men or women? Why do men and women respond differently to spousal loss? How do characteristics of the spouse’s death affect the bereaved survivor’s adjustment? Is “absent” grief indicative of a healthy or pathological reaction to loss? Conclusive answers to these questions require well-designed rigorous studies that are free of sampling, measurement, and other methodological limitations that may lead to biased or inconclusive findings. This chapter reviews the methodological challenges that researchers must address in order to make sound contributions to the bereavement debate. I first review the strengths and weakness of commonly used data sources, including help-seeking, bereaved, and community samples. Second, I compare the attributes of cross-sectional versus prospective and longitudinal data sets as appropriate sources for studying bereavement. Third, I underscore the value of using a diverse range of outcomes in bereavement research. Fourth, I describe the purposes and potential contributions of both mediational and moderational analyses. Fifth, I describe the ways that developmental and age-related changes may affect adjustment to loss, and the implications of these patterns for researchers who rely on age-heterogeneous samples. Finally, I describe the
Chaos and Pattern Formation in Spatial Phytoplankton Dynamics

In this paper the dynamics of spatially extended infected phytoplankton with the Holling type II functional response and logistically growing susceptible phytoplankton system is studied. The proposed model is an extension of temporal model available [6], in spatiotemporal domain. The reaction diffusion system exhibits spatiotemporal chaos in phytoplankton dynamics. This is particularly important for the spatially extended systems that are studied in this paper as they display a wide spectrum of ecologically relevant behavior, including chaos. In this system stability of the system is studied with respect to disease contact rate and the growth fraction of infected phytoplankton indirectly rejoin the susceptible phytoplankton population. The results of numerical experiments in one dimension and two dimensions in space as well as time series in temporal models are presented using MATLAB simulation. Moreover, the stability of the corresponding temporal model is studied analytically. Finally, the comparison of the three types of numerical experimentations are discussed in conclusion.