Miracle-dz/UniFAR-FTUs huggingface dataset:
Multisensing Architecture for the Balance Losses During Gait via Physiologic Signals Recognition

In this paper, we propose an innovative multi-sensor architecture operating in the field of pre-impact fall detection (PIFD). The proposed architecture jointly analyzes cortical and muscular involvement when unexpected slippages occur during steady walking. The electrophysiological signals (EEG and EMG) are acquired through wearable and wireless acquisition devices interfaced with a central control unit. The control unit consists of a hybrid architecture that exploits both an STM32L4 microcontroller and a DSP-oriented Simulink model. The EMG computation block translates EMGs into binary signals, which are used to trigger the cortical analyses, to extract a score on the revealed muscular pattern and to distinguish “standard” muscular behaviors from anomalous ones (perturbation). A Simulink model evaluates the cortical responsiveness in five bands of interest and implements a logical-based network to detect near-falls or potential ones. The proposed architecture goal is to obtain a detection time conservatively below 550 ms, which represents a strict limit for the successful application of postural recovery strategies. The system has been tested on 6 healthy subjects and demonstrated to react in ${\sf 370.62} \pm {\sf 60.85}$ ms, while keeping competitive accuracy (96.21%).
Environmental Effects of Traffic Calming Devices on Residential Area using SUMO

Recently, the number of traffic accidents on trunk roads tends to decrease due to the performance improvement of passenger vehicles. In the commuter rush hour of morning and evening, vehicles via residential road increases without going along trunk roads. Therefore, there are many traffic accidents of pedestrians (or bicycles) and vehicles on residential roads. In order to safeguard residents against traffic accidents, traffic calming devices (TCD), such as chicane, speed hump, and school zone, etc. have been introduced. Investigating these effects repeatedly is not easy since many times and efforts are required, such as observed at the place actually. In this paper, the effects of TCDs in residential areas, such as noise, speed, and emission of a vehicle, using Simulation of Urban Mobility (SUMO) are examined. As a result, it is found that it is possible to reduce the speed of the vehicle by TCD, and the level of noise at the location behind TCD becomes higher than the level of noise at the location of TCD implemented.
Genetically Programmed Regioselective Immobilization of Enzymes in Biosilica Microparticles

Diatoms are single‐celled microalgae that produce a large variety of hierarchically porous, silica‐based microparticles as cell wall material. The presence of genetically encoded silica nanopatterns endows the biosilica with favorable properties for a wide range of applications including catalysis, chemical sensing, photonics, and drug delivery. Enhancing the performance of diatom biosilica requires i) a better understanding of the structure–property relationship in this material, and ii) methods that enable the manipulation of the biosilica structure and properties in a targeted manner. Here, genetic engineering of the diatom Thalassiosira pseudonana is employed to immobilize enzymes (glucose oxidase and horseradish peroxidase) into structurally distinct regions of the biosilica, which are termed valves and girdle bands. Remarkably, glucose oxidase in girdle bands exhibits >3‐fold higher catalytic activities compared to its location in valves. It is demonstrated through enzyme accessibility studies, protein engineering, and genetic engineering of biosilica morphology that the divergent enzyme activities are caused by the differences in the inherent silica nanopatterns of valves and girdle bands. This work highlights the importance of silica nanoscale architecture for the activity of immobilized enzymes and provides unprecedented tools for the biotechnological production of silica microparticles with tailored catalytic activities and anisotropic functionalities.
Short‐term interleukin‐1β increases the release of secreted APPα via MEK1/2‐dependent and JNK‐dependent α‐secretase cleavage in neuroglioma U251 cells

Several lines of neuroimmunological evidence correlate the development of the inflammatory responses of the brain with the formation of amyloid plaques associated with the pathogenesis of neurodegenerative disorders such as Alzheimer's disease. Within this context, we tested the ability of interleukin‐1β (IL‐1β) to regulate the processing of beta‐amyloid precursor protein (β‐APP) in neuroglioma U251 cells. Our findings have shown that short‐term treatment with IL‐1β (2 hr) resulted in a concentration‐dependent decrease in the amount of the cell‐associated form of β‐APP in U251 cells as compared to untreated cells, whereas a 2‐hr treatment with IL‐1β led to increased release of secreted APPα fragment (sAPPα) into the conditioned media of the cells. The fact that sAPPα is an α‐secretase cleavage metabolite of the cell‐associated form of β‐APP, and the observation that IL‐1β‐induced sAPPα release could be blocked by tissue inhibitors of metalloproteinases‐1 (α‐secretase inhibitors), suggested that α‐secretase might be involved in IL‐1β‐induced‐sAPPα release. Moreover, to determine whether an intracellular signaling pathway mediates the IL‐1β‐induced increase in sAPPα secretion, we used various specific signaling inhibitors and found that sAPPα release is significantly blocked by the mitogen‐activated protein kinase (MEK1/2) inhibitor PD98059 and the c‐Jun N‐terminal kinase inhibitor SP600125. These findings suggested that the mechanism of IL‐1β‐induced‐sAPPα release is dependent on MEK1/2‐ and JNK‐activated α‐secretase cleavage in neuroglioma U251 cells. © 2005 Wiley‐Liss, Inc.
VOLATILITY SPILLOVER BETWEEN STOCK AND FOREIGN EXCHANGE MARKET IN INDIA: USING SECTORAL INDICES

The present study aimed to contribute to the existing literature on volatility spillover between the stock and foreign exchange market in India using the diagonal BEKK-GARCH model. This study uses the daily data of BSE sector indices, namely BANKEX (Banking), IT (Information Technology), AUTO (Transport), CD (Consumer Durables), HCARE (Health care), POWER (Energy), and the everyday rupee exchange rate against US dollar. Using the closing prices for the period 1st January 2008 to 31st December 2018 the return series are calculated. The study found a bidirectional volatility spillover between the foreign exchange market and major stock market sectors in log run; even though they are very small in magnitude. The volatility spillover from stock market is found to have a negative impact on foreign exchange market and the volatility spillover from foreign exchange market is found to have a positive impact on the stock market. The changes in exchange market affects the stock market sectors largely based on whether they are import oriented or export oriented.
The influence of open innovation activities on non-financial performance in the cultural tourism content industry

ABSTRACT The sources of innovation in services, and especially in tourism services, are usually external to companies. To what extent do open innovation practices within cultural tourism content enterprises contribute to firm performance? Based on an online survey of employees of enterprises engaged in innovative cultural tourism in South Korea, our study examines the contributions of three open innovation activities (innovation capability, information search and external cooperation activity) on both internal and external non-financial performance. Additionally, the impact of internal performance on external performance is analysed. Findings contribute to understanding open innovation adoption and developing additional products containing creative content that can satisfy customers and generate revenue in the cultural tourism industry.
Server-specific add-on biometric security layer model 2 to enhance the usage of biometrics

With high paced growth in biometrics, and its easy availability to capture various biometric features, it is emerging as one of the most valuable technologies for multifactor authentication to verify a user’s identity, for data security. Organizations encourage their members to use biometrics, but they are hesitant to use due to perceived security risks. Because of its low usage rate, many medium and small segment organizations find it unfeasible to deploy robust biometric systems. We propose a “server-specific add-on biometric security layer model,” to enhance confidence in the usage of biometrics. We tested this model via a biometric mobile app, and the survey showed a favorable response of 80%. The innovative mobile app was tested for its usability and got a score of more than 71%. For test tool reliability, we examined the equal error rate (EER) of the app and got a reasonably low score of 6%. The results show a good potential of this framework to enhance users’ confidence-level in the usage of biometrics. Higher usage rates may make deployment of biometrics more cost-effective for many organizations to decrease their information security risk.
Building reputation through sustainable supplier selection: the case of an emerging economy

PurposeThe purpose of this research is to examine the drivers of sustainable supplier selection (SSS) and investigate the extent to which it is associated with a buyer's financial performance within an emerging economy context.Design/methodology/approachThe data were collected from 235 supply chain and procurement professionals in Thailand. The structural relationship was tested using partial least squares based structural equation modeling (PLS-SEM) and PROCESS tool.FindingsBased on the empirical findings, firms that pursue sustainability initiatives during supplier selection process enjoy better financial performance than their competitors. The analysis suggests six hypothetical paths explain SSS. Suppliers' human rights and safety focus are the most powerful determinants of SSS. Significantly, positive support was found for the SSS and buyers' financial performance relationship. Finally, there is a significant moderating effect of resource investment on sustainability efforts.Research limitations/implicationsData for the study were collected from a single industry, so the findings are indicative but not representative of all supply chains. Due to this limitation, the findings cannot be generalized across other countries and industries. This study is a starting point in understanding the role of SSS in creating a sustainable supply chain. Future research may develop a comprehensive understanding of the nature and magnitude of the impact of SSS on sustainable supply chains.Originality/valueThis paper contributes toward an understanding of the determinants of SSS and its consequences for sustainable supply chains.
Cloning and Characterization of a Ribonuclease, a Cysteine Proteinase, and an Aspartic Proteinase from Pitchers of the Carnivorous Plant Nepenthes ventricosa Blanco

Nepenthes ventricosa is a carnivorous plant with modified leaves, pitchers, that secrete hydrolases to digest trapped insects, thus obtaining supplemental nutrients. Using reverse transcriptase PCR (RT‐PCR), three cDNAs encoding one putative ribonuclease (NvRN1) and two putative proteinases (NvAP1, NvCP1) were cloned from N. ventricosa pitcher tissues. The deduced amino acid sequences of NvRN1, NvAP1, and NvCP1 are homologous to the S‐like RNase PD2 (Prunus dulcis), the aspartic proteinase NaAP3 (Nepenthes alata), and the cysteine proteinase CysP2 (Glycine max), respectively. NvRN1 and NvAP1 were expressed in pitcher tissues and male flowers. NvRN1 expression was also evident in female flowers. SDS‐PAGE activity gels showed that pitcher fluid samples contained at least six proteinases of differing molecular masses (124, 65, 61, 49, 36, and 33 kD) and a single 21‐kD RNase. Fluid samples from single pitchers showed no change in pattern of proteolytic activity over time, but samples from different pitchers exhibited differing activity patterns, indicating that separate pitchers may secrete proteinases of different molecular masses. Optimal proteinase activity at pH 3 and inhibition by treatment with pepstatin was consistent with previous studies showing that Nepenthes secrete aspartic proteinases. Proteinase activity was also inhibited by E‐64, indicating that cysteine proteinases could be present in pitcher fluid.
A Generalized VAMP-Based Channel Estimator for Uplink Quantized Massive MIMO Systems

In this study, we propose an improved channel estimator based on vector approximate message passing (VAMP) for quantized millimeter wave (mmWave) massive multiple-input and multiple-output (MIMO) systems. Using channel sparsity and the orthogonality of steering matrix, the proposed VAMP-on method designed for the on-grid scenario not only improves estimation performance but also has better convergence and inverse-free implementation. Furthermore, to achieve better estimation performance under the off-grid scenario, we provide a VAMP-off algorithm to update steering matrix and channel coefficients in an alternating fashion. Finally, simulation results are provided to demonstrate the advantages of the proposed approaches.
Identification of QTLs involved in cold tolerance during the germination and bud stages of rice (Oryza sativa L.) via a high-density genetic map

Low-temperature tolerance during the germination and bud stages is an important characteristic of direct-seeded rice (DSR). Recombinant inbred lines (RILs) derived from indica rice H335, which is highly tolerant to low temperature, and indica rice CHA-1, which is sensitive to low temperature, were used to identify quantitative trait loci (QTLs) associated with low-temperature tolerance during the germination and bud stages. a total of 11 QTLs were detected based on a high-density genetic map; among these, six QTLs explained 5.13–9.42% of the total phenotypic variation explained (PVE) during the germination stage, and five QTLs explained 4.17–6.42% of the total PVE during the bud stage. All QTLs were distributed on chromosome 9, and all favourable alleles originated from H335. The physical position of each QTL was determined, and 11 QTLs were combined into five genetic loci; three of these loci are involved during the germination stage (loci 1, 2, and 3), and three are involved during the bud stage (loci 3, 4, and 5). Loci 2, 4 and 5 were repeatedly detected in the wet season (WS) and dry season (DS). Notably, loci 3 was detected during both the germination and bud stages. These loci are good candidates for future studies of gene function and could serve as highly valuable genetic factors for improving cold tolerance during the germination and bud stages of rice.
Effects of Global Positioning System Collar Weight on Zebra Behavior and Location Error

Abstract Global Positioning System (GPS) collars are increasingly being used to study fine-scale patterns of animal behavior. Previous studies on GPS collars have tried to determine the causes of location error without attempting to investigate whether the accuracy of fixes provides a correspondingly accurate measure of the animal's natural behavior. When comparing 2 types of GPS collar, we found a significant effect of collar weight and fit on the rate of travel of plains zebra (Equus burchelli antiquorum) females in the Makgadikgadi, Botswana. Although both types of collar were well within accepted norms of collar weight, the slightly heavier collars (0.6% of total body mass [TBM]) reduced rate of travel by >50% when foraging compared with the collar that was 0.4% of TBM. Collar effect was activity specific, particularly interfering with grazing behavior; the effect was less noticeable when zebras crossed larger interpatch distances. We highlight that small differences in collar weight or fit can affect specific behaviors, limiting the extrapolation of fine-scaled GPS data. This has important implications for wildlife biologists, who hitherto have assumed that collars within accepted weight limits have little or no effect on animal movement parameters.
Clustering of designers based on building information modeling event logs

A network‐enabled event log mining approach is proposed for a deep understanding of the Building Information Modeling (BIM)‐based collaborative design work. It proposes a novel algorithm termed node2vec‐GMM combining a graph embedding algorithm named node2vec and a clustering method named Gaussian mixture model (GMM) to cluster designers within a network into several subgroups, and then makes cluster analysis. Its superiority lies in the efficient feature learning ability to preserve network structure and the powerful clustering ability to tackle uncertainty and visualize results, which can directly return the cluster embedding. As a case study, a directional network with 68 nodes (designers) and 436 ties (design task transmissions) is constructed based on retrieved data from 4GB real BIM event logs. The node2vec learns and projects the network feature representation into a 128‐dimensional vector, which is learned by GMM to discover three possible clusters owning 15, 26, and 27 closely linked designers. Analysis of each cluster is performed from node importance measurement and link prediction to identify information spreading and designers’ roles within clusters. Our new algorithm node2vec‐GMM is proven to better improve clustering quality than other state‐of‐the‐art methods by at least 6.0% Adjusted Rand Index and 13.4% Adjusted Mutual Information. Overall, the designer clustering process provides managers with data‐driven support in both monitoring the whole course of the BIM‐based design and making reliable decisions to increase collaboration opportunities.
Determination of Digital Citizenship Levels of University Students at Sakarya University Turkey

When digital transactions such as official transactions, banking transactions, communication, education, production, shopping are carried out in digital environment, the concept of digital citizenship has emerged. Digital citizenship; it is the person who has the ability to use information technologies appropriately and correctly in areas such as official transactions, social communication, education, and production. As technology improves, problems with its use increases exponentially. So technological behavior or technological citizenship it is clear that the behavior, values, ethical rules and awareness should be created. In this study in order to detection this awareness; it is aimed to determine the digital citizenship levels of university students. For this purpose, 253 students studied in various departments of the Hendek Vocational High School of Technical Sciences in Sakarya university. The research was carried out with the relational scanning model from the quantitative research method. “Digital Citizenship Scale for Youth” was developed by Kus, Gunes, Basarmak and Yakar (2017) the researcher as a data collection tool with permission. The scale has 49 items, the total variance of the scale was determined that the scale had 8-factor structure and was found to be 49,70%. Related dimensions are communication, jus and responsibility, critical thinking, participation, security, digital skills, ethics and commerce. In the analysis of the data, non-parametric tests were used in addition to the percentage, frequency and standard deviation values. As a result; students were revealed to be aware of digital citizenship’s sub-dimension.
3-D Mixed Far-Field and Near-Field Sources Localization With Cross Array

This correspondence proposes a localization method for mixed far-field (FF) and near-field (NF) sources based on cross arrays where two-dimensional (2-D) direction-of-arrival (DOA) and range estimation are considered. For 2-D DOA estimation, we first construct a range-free cumulant-based vector and employ the covariance matching criterion and Vandermonde decomposition theorem to retrieve DOA information. We then build a sparse model with respect to range parameter and solve an $\ell _1$-norm minimization problem to obtain range estimates. Our method enjoys the following advantages: 1) our method can locate mixed FF and NF sources; 2) the azimuth, elevation and range can be automatically paired; 3) array aperture loss can be avoided. Simulation results show the effectiveness of our method.
Aplikasi Cendawan Endofit terhadap Perkembangan Populasi Nematoda Radopholus similis pada Pisang Barangan

Radopholus similis is a major constraint to banana production in the world including Indonesia and growers have relied on nematicides to manage yield losses. The use of endophytic fungi is one method that may reduce the need for nematicides, however little is known on the effective application method of endophytic fungi to control R. similis . The aim of this research was to find out an effective application method of endophytic fungi to reduce R.similis population on banana. Fifteen isolates of endophytic fungi originated from banana corm and root collected from banana plantation in North Sumatera were applied to Barangan cultivar by sowing and deeping methods. The isolates was contained of 11 isolates of Fusarium sp. (2BSTMHMM, 3ASTMHP, 5ASP, 1ASU, 4BSP, 4BJP, 5BKJP, 4BSU, 1BJP, 2 BSP, and 4BKJP) and 4 isolates of Trichoderma sp. (2BSTMHP, 4BSTMHP, 2BSPH, and 2BSTMHH). All of these endophytic fungi were able to suppress the population of R. similis and they had potential to promote plant growth.
In-Situ Ellipsometric Study of the Optical Properties of LTL-Doped Thin Film Sensors for Copper(II) Ion Detection

Optical sensors fabricated in zeolite nanoparticle composite films rely on changes in their optical properties (refractive index, n, and thickness, d) to produce a measurable response in the presence of a target analyte. Here, ellipsometry is used to characterize the changes in optical properties of Linde Type L (LTL) zeolite thin films in the presence of Cu2+ ions in solution, with a view to improving the design of optical sensors that involve the change of n and/or d due to the adsorption of Cu2+ ions. The suitability of two different ellipsometry techniques (single wavelength and spectroscopic) for the evaluation of changes in n and d of both undoped and zeolite-doped films during exposure to water and Cu2+-containing solutions was investigated. The influence of pre-immersion thermal treatment conditions on sensor response was also studied. Due to the high temporal resolution, single wavelength ellipsometry facilitated the identification of a Cu2+ concentration response immediately after Cu2+ introduction, indicating that the single wavelength technique is suitable for dynamic studies of sensor–analyte interactions over short time scales. In comparison, spectroscopic ellipsometry produced a robust analysis of absolute changes in film n and d, as well as yielding insight into the net influence of competing and simultaneous changes in n and d inside the zeolite-doped films arising due to water adsorption and the ion exchange of potassium (K+) cations by copper (Cu2+).
Analysis of Pressure-Volume Curves of Leaves of Rosa hybrida cv. Sonia

By analysing the relationship between inverse water potential (ψ -1 ), and relative water content (RWC) measured on leaves of roses (Rosa hybrida cv. Sonia), grown soilless, it was found that a non-linear (NL) model was better suited than a linear model to reproduce values observed in the non-turgid region. To explain this apparent curvature, it is assumed that a reduction of the non-osmotic water fraction (A p ) takes place when ψ decreases. Osmotic potentials (ψ π ) measured on fresh and frozen leaf discs tend to support this hypothesis. A method for exploiting PV curves, which takes into account the variation of A p , is described