Miracle-dz/UniFAR-FTUs huggingface dataset:
Double Clad Fiber Improves the Performance of a Single-Ended Optical Fiber Sensor

Single-ended, amplitude- or wavelength-modulated optical fiber sensors provide an attractive platform for minimally invasive chemical and biological sensing applications. However, in many cases, the sensor performance is limited by the collection efficiency of diffuse scattered and/or reflected light at the distal end of the waveguide, relative to background light generated within the waveguide. Using surface-enhanced Raman scattering (SERS) as an exemplary weak source of diffuse back-scattered light, we have evaluated the performance of single-ended sensing schemes based on hollow-core photonic crystal fiber (PCF) and double-clad fiber (DCF) compared with more conventional single-mode fibers (SMF-28 and S405). The SERS substrates were fabricated by oblique-angle deposition on the optical fiber end faces. In order to generate a comparable SERS substrate at the end face of the hollow-core PCF, a graded-index (GRIN) coupler was spliced onto the cleaved end face. Similar GRIN lens couplers were spliced onto the solid-core fibers for comparison with the PCF, as they are not expected to provide any advantage for coupling diffuse scattered light. The PCF offered no reduction in fiber background signal compared with either the single-mode fiber or the DCF with excitation through the inner core. In contrast, the DCF was found to provide up to 12-fold improvement in the signal-to-background ratio. These results indicate that DCF holds great promise as a single-ended optical fiber sensor platform.
Alternative Risk Assessment for Dangerous Chemicals in South Korea Regulation: Comparing Three Modeling Programs

Unlike other countries, the Korean chemical industry does not clearly distinguish between industrial sites and residential areas. The 2012 Gumi Hydrogen Fluoride Accident revealed that chemical accidents could cause damage to nearby residents. Accordingly, the Chemicals Control Act was enacted in 2015, which requested industrial sites using chemicals to perform a risk assessment for all chemical facilities and to distribute the results to the local residents and governments. Industrial businesses had the responsibility of warning the local residents. In this study, two programs (Areal Location of Hazardous Atmospheres (ALOHA), Process Hazard Analysis Software Tool (PHAST)) were compared with Korea Off-site Risk Assessment Supporting Tool (KORA), which is the current representative risk assessment program used in Korea Chemicals Control Act. The five chemical substances (nitric acid, hydrogen chloride, ammonia, sulfuric acid, and formaldehyde) most commonly involved in chemical accidents were selected. The range of influence of ERPG-2 (Emergency Response Planning Guideline) on chemical accidents was modeled and the results compared. ALOHA was found to be the most suitable program for the determination of toxicity for nitrate acid and ammonia, KORA for hydrogen chloride and sulfuric acid, and PHAST for formaldehyde. To maximize the safety of many local residents and to prepare for chemical accidents, risk assessments should be conducted using a variety of risk assessment programs, and the worst-case damage radius should be determined.
State of the Art on Social Network Analysis and its Applications on a Semantic Web

The increasingly popular web 2.0 sites provide the largest social network ever analyzed - users are now considered as plain web resources. Some researchers apply classical methods of social network analysis to such networks; others provide models to leverage the semantics of their representation. We present a state of the art of these two approaches and propose an architecture to merge and exploit the best features of each.
Synthesis and Characterization of Novel TMD: Rhenium Disulfide

Transition metal dichalcogenides (TMDs) are exciting new materials that have received much attention due to their semiconducting properties in the direct bandgap. Well-studied TMDs, such as molybdenum disulfide (MoS2) and tungsten diselenide (WSe2), exhibit a direct bandgap in the monolayer form, but an indirect bandgap in the bulk form. Rhenium disulfide (ReS2), on the other hand, is a new TMD that is unique in its ability to retain a direct bandgap independent of thickness. By using chemical vapor deposition (CVD), few-layer ReS2 is synthesized and characterized by optical methods such as Raman spectroscopy and photoluminescence. We also show characterization results for atomic force microscopy (AFM), x-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM), transmission electron microscope (TEM), and electrical transport to determine thickness, crystallinity, homogeneity, and electrical characteristics for use in future flexible electronics.
OLAPS: Online load-balancing in range-partitioned main memory database with approximate partition statistics

Modern database systems can achieve high throughput main-memory query execution by being aware of the dynamics of highly parallel hardware. In such systems, data is partitioned into smaller pieces to reach a better parallelism. Unfortunately, data skew is one of the main problems faced during parallel processing in a parallel main memory database. In some data-intensive applications, parallel range queries over a dynamic range partitioned system are important. Continuous insertions/deletions can lead to a very high degree of data skew and consequently a poor performance of parallel range queries. In this paper, we propose an approach for maintaining balanced loads over a set of nodes as in a system of communicating vessels, by migrating tuples between neighboring nodes. These frequent (or even continuous) data transfers inevitably involve dynamic changes in the partition statistics. To avoid the performance degradation typically associated with this dynamism, we provide a solution based on an approximate Partition Statistics Table. The basic idea behind this table is that both clients and nodes may have an imperfect knowledge about the effective load distribution. They can nevertheless locate any data with almost the same efficiency as using exact partition statistics. Furthermore, maintaining load distribution statistics do not require exchanging additional messages as opposed to the cost of efficient solutions from the state-of-art (which requires at least O(logn) messages). We show through intensive experiments that our proposal supports efficient range queries, while simultaneously guaranteeing storage balance even in the presence of numerous concurrent insertions/deletions generating a heavy skewed data distribution.
Dynamic Resource Allocation for Uplink MIMO NOMA VWN with Imperfect SIC

We investigate the uplink resource allocation problem for virtualized wireless networks (VWNs) supported by multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) and present a sensitivity analysis to imperfect successive interference cancellation (SIC) and various system parameters. The proposed algorithm for power and sub-carrier allocation is derived from the non- convex power minimization subject to rate and sub- carrier reservations, for which an optimal solution is NP-hard. To develop an efficient solution, the resource allocation is decomposed into separate power and sub-carrier allocation problems and an iterative algorithm based on successive convex approximation and complementary geometric programming is proposed. Simulation results demonstrate that compared to orthogonal multiple access, the proposed algorithm for MIMO NOMA can offer significant improvement in spectrum and power efficiency.
Emotional Reactions Prediction of News Posts

Nowadays, on-line news agents post news articles on social media platforms with the aim to attract more users. Different types of news trigger different emotions on users who may feel surprised or sad after reading some piece of news. In this paper, we are interested in predicting the amount of emotional reactions triggered on users after reading a news post. To address the problem, we propose a model that is trained on features extracted from users’ early commenting activity. Our results show that users’ early activity features are very important and that combining those features with terms can effectively predict the amount of emotional reactions triggered on users by a news post.
Revisiting Concurrency in High-Performance NoSQL Databases

We measure the performance of five popular databases and show that single-node performance does not scale while hosting data on high-performance storage systems (e.g., Flash-based SSDs). We then analyze each system, unveiling techniques each system uses to increase concurrent performance; our taxonomy places said approaches into six different categories (thread architecture, batching, granularity, partitioning, scheduling and low-level efficiency) and thus points towards possible remedies that can scale the system. Finally, we introduce Xyza, a modified version of MongoDB that uses a wide range of classic and novel techniques to improve performance under concurrent, write-heavy workloads. Empirical analysis reveals that Xyza is 2× to 3× faster than MongoDB and scales well (up to 32 processing cores).
Privacy-Preserving Linkage of Genomic and Clinical Data Sets

The capacity to link records associated with the same individual across data sets is a key challenge for data-driven research. The challenge is exacerbated by the potential inclusion of both genomic and clinical data in data sets that may span multiple legal jurisdictions, and by the need to enable re-identification in limited circumstances. Privacy-Preserving Record Linkage (PPRL) methods address these challenges. In 2016, the Interdisciplinary Committee of the International Rare Diseases Research Consortium (IRDiRC) launched a task team to explore approaches to PPRL. The task team is a collaboration with the Global Alliance for Genomics and Health (GA4GH) Regulatory and Ethics and Data Security Work Streams, and aims to prepare policy and technology standards to enable highly reliable linking of records associated with the same individual without disclosing their identity except under conditions in which the use of the data has led to information of importance to the individual's safety or health, and applicable law allows or requires the return of results. The PPRL Task Force has examined the ethico-legal requirements, constraints, and implications of PPRL, and has applied this knowledge to the exploration of technology methods and approaches to PPRL. This paper reports and justifies the findings and recommendations thus far.
Fine-grained evaluation of Quality Estimation for Machine translation based on a linguistically motivated Test Suite

We present an alternative method of evaluating Quality Estimation systems, which is based on a linguistically-motivated Test Suite. We create a test-set consisting of 14 linguistic error categories and we gather for each of them a set of samples with both correct and erroneous translations. Then, we measure the performance of 5 Quality Estimation systems by checking their ability to distinguish between the correct and the erroneous translations. The detailed results are much more informative about the ability of each system. The fact that different Quality Estimation systems perform differently at various phenomena confirms the usefulness of the Test Suite.
Three-Stage Distributed State Estimation for AC-DC Hybrid Distribution Network Under Mixed Measurement Environment

The ac–dc hybrid distribution network is a credible path for the future evolution of distribution network. State estimation is a paramount foundation for the safe and stable operation of the complex distribution network. The application of the centralized state estimation method in an ac–dc distribution network has some obstacles, such as low computational efficiency, large communication capacity, and privacy protection problem. Based on the three-stage state estimation theory, this paper established a three-stage state estimation model for the ac–dc hybrid distribution network integrating supervisory control and data acquisition system and phasor measurement unit. The proposed three-stage estimation model achieves linearization of the nonlinear state estimation for the ac–dc hybrid distribution network. That is, the first and third stages simply solve the linear state estimation problem, and the second stage is a one-step nonlinear transform. Moreover, the alternating direction method of multipliers (ADMM) is applied to solving the distributed problem. Thus, an accurate and efficient three-stage distributed state estimation method for the ac–dc hybrid distribution network is proposed. In this method, ac subsystems and dc subsystems execute state estimation tasks based on local information and eventually achieve the overall consistency of the system state estimation through the transfer iteration of the boundary information, respectively. The combination of bilinear theory and ADMM ensures the convergence of distributed state estimation while improving computational efficiency. The simulation results verified the advantage of the proposal over the existing methods in many aspects.
Mathematically Gifted Accelerated Students Participating in an Ability Group: A Qualitative Interview Study

Schools in Norway often emphasize heterogeneous groups in education. The postulated negative effects of homogeneous ability groups on motivation and academic self-concept have long been debated. This study uses semi-structured interviews to investigate how a group of 11 accelerated and ability-grouped high-ability students (gifted) in math have experienced school. All students were interviewed individually. This study explores categories connected to the students’ motivation for the subject, challenges in school, peer and teacher relationships, and academic self-concept. The aim of the study is to investigate whether the school system is able to provide an adequate learning environment for high-ability students, both in ordinary class and in ability groups. The findings show that although some of the needs of high-ability students in Norway are being met, there is much work to be done before an optimal learning environment is established for these students. For example, students do not receive sufficient challenges in math. Furthermore, teachers in the early years of school lack sufficient mathematical knowledge to challenge and support mathematically gifted students, students’ motivation for the subject is lower than expected, and boys’ self-concept seems to be higher than that of girls.
Satellite tracking of juvenile whale sharks in the Sulu and Bohol Seas, Philippines

The whale shark Rhincodon typus was uplisted to ‘Endangered’ in the 2016 IUCN Red List due to >50% population decline, largely caused by continued exploitation in the Indo-Pacific. Though the Philippines protected the whale shark in 1998, concerns remain due to continued take in regional waters. In light of this, understanding the movements of whale sharks in the Philippines, one of the most important hotspots for the species, is vital. We tagged 17 juvenile whale sharks with towed SPOT5 tags from three general areas in the Sulu and Bohol Seas: Panaon Island in Southern Leyte, northern Mindanao, and Tubbataha Reefs Natural Park (TRNP). The sharks all remained in Philippine waters for the duration of tracking (6–126 days, mean 64). Individuals travelled 86–2,580 km (mean 887 km) at a mean horizontal speed of 15.5 ± 13.0 SD km day−1. Whale sharks tagged in Panaon Island and Mindanao remained close to shore but still spent significant time off the shelf (>200 m). Sharks tagged at TRNP spent most of their time offshore in the Sulu Sea. Three of twelve whale sharks tagged in the Bohol Sea moved through to the Sulu Sea, whilst two others moved east through the Surigao Strait to the eastern coast of Leyte. One individual tagged at TRNP moved to northern Palawan, and subsequently to the eastern coast of Mindanao in the Pacific Ocean. Based on inferred relationships with temperature histograms, whale sharks performed most deep dives (>200 m) during the night, in contrast to results from whale sharks elsewhere. While all sharks stayed in national waters, our results highlight the high mobility of juvenile whale sharks and demonstrate their connectivity across the Sulu and Bohol Seas, highlighting the importance of the area for this endangered species.
Cryogenic Characteristics of Ge channel Junctionless Nanowire Transistors

We fabricated high performance Ge channel junctionless nanowire transistors (JNTs) and demonstrated their cryogenic characteristics from 90 to 270 K. The results show that the leakage current is more sensitive to temperature than drive current. The slope of threshold voltage shift with temperature is estimated to be 2.5 mV/K. Low field mobility decreases with reduced temperature and is found to be limited by both Coulomb scattering and neutral defects scattering.
Wikipedian: a social identity between work and contribution

Contributors to the Wikipedia "free encyclopedia" identify themselves and are identified as "Wikipedians". A Wikipedian does not leave his job when he becomes a Wikipedian. Nor does he become a Wikipedian in his workplace. The worker's identity and the Wikipedian identity coexist in the social identity of an individual. On which patterns does this coexistence between worker's identity and Wikipedian identity operate? Beyond the differences specific to the social identity of each contributor, we will try to show that singulars transactions all take place according to a finite number of patterns that it is possible to count. At this stage of our analysis, we are able to distinguish five identity patterns: employment, learning center, alternative development, continuity in upset, parallel arena. Our model aims to better understanding of why a contributor stay in Wikipedia and identifies himself as a contributor.
SHREC'18 track: Retrieval of gray patterns depicted on 3D models

This paper presents the results of the SHREC'18 track: Retrieval of gray patterns depicted on 3D models. The task proposed in the contest challenges the possibility of retrieving surfaces with the same texture pattern of a given query model. This task, which can be seen as a simplified version of many real world applications, requires a characterization of the surfaces based on local features, rather then considering the surface size and/or bending. All runs submitted to this track are based on feature vectors. The retrieval performances of the runs submitted for evaluation reveal that texture pattern retrieval is a challenging issue. Indeed, a good balance between the size of the pattern and the dimension of the region around a vertex used to locally analyze the color evolution is crucial for pattern description.
Using game technology to teach six elementary school children with autism to take a shower independently

ABSTRACT Objective: This paper contributes to research investigating the effectiveness of video game intervention in shower training of children with autism spectrum disorders. Previous studies have supported the use of video games in special education. Methods: We employed the Kinect sensor to gamify shower training. Specifically, a non-concurrent multiple baseline design was adopted to demonstrate the relation between game-based intervention and taking a shower independently. Six children in a special education class at a regular elementary school participated in the experiment. Results: Data showed that the percentage of correct task steps significantly increased among all six participants; motivation to engage in training was enhanced as well, thus improving task performance during the intervention and maintenance phases. Conclusions: Although the game is a promising and highly accepted training tool for school-use, it currently remains error-prone, and the requested demand exceeds the support that can be provided by special education teachers. A more technically robust system, combined with additional attractive games, will likely result in higher participant motivation and superior task performance.
Channel-Aware Secure Communication via Hybrid Wiretap Encoding and Secret Key Generation

Physical layer security is a promising technology for secure communication by using wiretap encoding or physical-layer secret key generation. Most of the existing research works study these two techniques separately, which however cannot fully utilize the radio resource. In this paper, we combine the two techniques by using a channel-aware threshold-based approach. Specifically, when the estimated channel gain is larger than the threshold, the wiretap encoding is adopted; otherwise, the secret key generation is performed. For given constraints on security and reliability, we respectively derive the effective secrecy rate of the two techniques and then obtain the secrecy throughput of the proposed scheme through simulations. Numerical results show that the proposed scheme can effectively combine the two techniques and enhance the average secrecy throughput.
Torulaspora delbrueckii produces high levels of C5 and C6 polyols during wine fermentations

&NA; Non‐Saccharomyces yeasts impact wine fermentations and can diversify the flavor profiles of wines. However, little information is available on the metabolic networks of most of these species. Here we show that unlike the main wine yeast Saccharomyces cerevisiae, Torulaspora delbrueckii and to a lesser extent Lachancea thermotolerans produce significant concentrations of C5 and C6 polyols under wine fermentation conditions. In particular, D‐arabitol, D‐sorbitol and D‐mannitol were produced at significant levels. Their release into the extracellular matrix started when that of glycerol ceased. The data also show that polyol production is influenced by initial sugar concentration, repressed by acetic acid and induced in ethanol supplemented media. Moreover, unlike glycerol and sorbitol, mannitol was partially re‐assimilated when populations started to decline. The findings suggest that polyol synthesis is a physiological adaptation to stressful conditions characteristic of alcoholic fermentation and that these polyols may serve a similar purpose as glycerol production in S. cerevisiae, including osmoadaptation and redox balancing.
Cryptanalysis and Security Enhancement of Three Authentication Schemes in Wireless Sensor Networks

Nowadays wireless sensor networks (WSNs) have drawn great attention from both industrial world and academic community. To facilitate real-time data access for external users from the sensor nodes directly, password-based authentication has become the prevalent authentication mechanism in the past decades. In this work, we investigate three foremost protocols in the area of password-based user authentication scheme for WSNs. Firstly, we analyze an efficient and anonymous protocol and demonstrate that though this protocol is equipped with a formal proof, it actually has several security loopholes been overlooked, such that it cannot resist against smart card loss attack and violate forward secrecy. Secondly, we scrutinize a lightweight protocol and point out that it cannot achieve the claimed security goal of forward secrecy, as well as suffering from user anonymity violation attack and offline password guessing attack. Thirdly, we find that an anonymous scheme fails to preserve two critical properties of forward secrecy and user friendliness. In addition, by adopting the “perfect forward secrecy (PFS)” principle, we provide several effective countermeasures to remedy the identified weaknesses. To test the necessity and effectiveness of our suggestions, we conduct a comparison of 10 representative schemes in terms of the underlying cryptographic primitives used for realizing forward secrecy.