Miracle-dz/UniFAR-FTUs huggingface dataset:
Descriptive Capability of Datasets as Proxy of Sea Water Temperature in Coastal Systems: An Evaluation from the Aegean Sea

Scientific and technological progresses have introduced diverse data sources for seawater temperature over broad temporal and spatial ranges. Here, we investigated the performance of satellite and model-based seawater temperature data for different temporal composites and depths. We applied an in-situ temperature time-series obtained in a coastal bottom in the Aegean Sea over three years, as the reference. Both datasets showed largely significant relationships based on cross-correlation analyses and presented descriptive properties of the in-situ conditions at corresponding depths. Based on the results of analyses, the modeling datasets presented more reliable results and representations of in-situ conditions than the datasets obtained from satellite for the coastal region. However, the datasets obtained from the satellite also provided reliable data for all time frames investigated, particularly in the mixed surface layer. Monthly datasets were more effective in providing descriptive values in long term studies. This is the first detailed study to explore the descriptive capacities of modeling for water temperature in coastal environments. According to the results, the selection of a dataset as a proxy for seawater temperature requires careful consideration. The present study provides an extensive baseline for evaluating the suitability of the application of specific datasets as proxies in coastal ecosystems.
Fabrication and simulations of high-aspect-ratio nanopores for polymer-based resistive pulse sensors

Microfluidic devices are a class of Micro Electromechanical Systems (MEMS) intended for fluids manipulation, mostly liquids, in the order of microliters and below. The global market of micro and nanofluidic devices has experienced continuous growth over the past few years [1]. In 2020, this market was valued at over USD 4.6 billion in conservative terms, and it is predicted to keep a growth rate of somewhat between 13 and 23% in the next half-decade [2]–[3]. Microdevices are characterized by having at least one dimension in the micrometre range, as well as nanodevices, have it in the nanometer scale. The main applications to micro and nanofluidic devices are drug delivery, pharmaceutical and biotechnology research, clinical and point-of-care (POC) diagnostics [2]. Companies working in this field experienced a surge in demand with the rise of the COVID-19 pandemic. For the rapid testing against SARS-CoV-2, testing devices became necessary for screening populations afar from testing centers and health care facilities [4]–[5]. The development of micro-and nano detectors for new viruses is challenging even with all the background acquired from working with other viruses [6]–[7]. One long-standing detection approach was established in 1953 by W. Coulter for counting cells, a method which is known as Resistive Pulse Sensor (RPS) or Coulter counter [8]. In short, an RPS refers to two chambers filled with electrolyte solution and connected by a single orifice. The target delivered in one chamber shall flow through the orifice to the other chamber led by electrochemical forces. The translocation of the targets causes partial and non-permanent obstruction of the orifice. By monitoring the electric current during this assay, it induces the formation of a pulse-like shape representing a pulse of resistance. In the following decades, this method was adapted to the submicrometric scale with advances in micro-and nanofabrication techniques [9]–[10]. The fabrication of such micro detectors is often based on photolithography, but some emergent and alternative techniques are becoming more common [6, 11–12]. Focused ion beam (FIB) is one of these unconventional approaches that allow for patterning high aspect ratio structures into a mixture of materials [13]–[14]. A challenge to pattern composite materials (e.g., sandwich-like membranes), which might be based on polymers and metals, raises from the different physical properties of materials [15]. The sensitivity and applicability of RPS are directly dependant on the shape and quality of the final structure. For instance, wall smoothness is one of the parameters that should be considered when choosing a fabrication approach. In this work, we will present an advanced nanofabrication design based on focused ion beam technology to drill a nanopore into a polymer-metal-polymer membrane. The intricate structure to be presented in this work was chosen to avoid fabrication artifacts described previously [16]. Numerical simulations will be also provided for comparison with a trivial cylindrical design.
Mitigating Congestion with Explicit Cache Placement Notification for Adaptive Video Streaming over ICN

SUMMARY Recently, information centric network (ICN) has attracted attention because cached content delivery from router’s cache storage improves quality of service (QoS) by reducing redundant tra ﬃ c. Then, adaptive video streaming is applied to ICN to improve client’s quality of experience (QoE). However, in the previous approaches for the cache control, the router implicitly caches the content requested by a user for the other users who may request the same content subsequently. As a result, these approaches are not able to use the cache e ﬀ ectively to improve client’s QoE because the cached contents are not always requested by the other users. In addition, since the previous cache control does not consider network congestion state, the adaptive bitrate (ABR) algorithm works incorrectly and causes congestion, and then QoE degrades due to unnecessary congestion. In this paper, we propose an explicit cache placement notiﬁcation for congestion-aware adaptive video streaming over ICN (CASwECPN) to mitigate congestion. CASwECPN encourages explicit feedback according to the congestion detection in the router on the communication path. While congestion is detected, the router caches the requested content to its cache storage and explicitly notiﬁes the client that the requested content is cached (explicit cache placement and notiﬁcation) to mitigate congestion quickly. Then the client retrieve the explicitly cached content in the router detecting congestion according to the general procedures of ICN. The simulation experiments show that CASwECPN improves both QoS and client’s QoE in adaptive video streaming that adjusts the bitrate adaptively every video segment download. As a result, CASwECPN e ﬀ ectively uses router’s cache storage as compared to the conventional cache control policies.
On the Learning Dynamics of Semi-Supervised Training for ASR

The use of semi-supervised training (SST) has become an increasingly popular way of increasing the performance of ASR acoustic models without the need for further transcribed speech data. However, the performance of the technique can be very sensitive to the quality of the initial ASR system. This paper undertakes a comprehensive study of the improvements gained with respect to variation in the initial systems, the quantity of untranscribed data used, and the learning schedules. We postu-late that the reason SST can be effective even when the initial model is poor is because it enables utterance-level information to be propagated to the frame level, and hence hypothesise that the quality of the language model plays a much larger role than the quality of the acoustic model. In experiments on Tagalog data from the IARPA MATERIAL programme, we ﬁnd that indeed this is the case, and show that with an appropriately chosen recipe it is possible to achieve over 50% relative WER reduc-tions from SST, even when the WER of the initial system is more than 80%.
The Construction Industry as the Subject of Implementing Corporate Social Responsibility (the Case of Poland)

Companies of the construction sector face a significant impact on the environment and people: consume massive amounts of natural resources, emit pollutants, and generate large amounts of waste, are a place of danger and accidents at work. It is well established that implementation of CSR principles can lead to several economic, social, and environmental benefits. This is shown by numerous studies carried out in various countries among companies from different sectors of the economy. The aim of the article is to identify the most determining activity motives, barriers, and effects of implementing CSR principles by enterprises of the Polish construction sector and to determine the differences in this aspect between large, medium, and small-size enterprises. A questionnaire survey covered 177 enterprises. Factor like size, a place of origin, type of capital (domestic, foreign), annual turnover and time in the market were also considered. The documents of enterprises, reports, statistical data, and internal regulations of companies were also examined. The research results show large variations in terms of motives, barriers and expected benefits out of the implementation of CSR principles in various types of construction enterprises. There are different ways of implementing CSR principles and incorporating this area into organizational structures of the companies. A special role is assigned to large enterprises that show the greatest commitment in this scope. They become sources of good practices for other types of enterprises.
A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning

Detecting anomalies on graph data has two types of methods. One is pattern mining that discovers strange structures globally such as quasi-cliques, bipartite cores, or dense blocks in the graph’s adjacency matrix. The other is feature learning that mainly uses graph neural networks (GNNs) to aggregate information from local neighborhood into node representations. However, there is a lack of study that utilizes both the global and local information for graph anomaly detection. In this article, we propose a synergistic approach that leverages pattern mining to inform the GNN algorithms on how to aggregate local information through connections to capture the global patterns. Specifically, it uses a GNN encoder to perform feature aggregation, and the pattern mining algorithms supervise the GNN training process through a novel loss function. We provide theoretical analysis on the effectiveness of the loss function, as well as empirical analysis on the proposed approach across a variety of GNN algorithms and pattern mining methods. Experiments on real-world data show that the synergistic approach performs significantly better than existing graph anomaly detection methods.
Features of Currents on the Black Sea Northwestern Shelf Based on the Numerical Simulation Results

Purpose. The work is aimed at studying the features of currents on the Black Sea northwestern shelf based of the reanalysis results, and at analyzing the reasons of these features. Methods and Results. To analyze the currents on the northwestern shelf, applied were the results of physical reanalysis of the Black Sea fields performed by the authors earlier, namely, the arrays of hydrodynamic fields on a regular grid with the 21-year duration (1992–2012). Surface currents on the northwestern shelf of the Black Sea are directed mainly to the southwest. Throughout the whole year (except for the summer months when the wind effect weakens), an intensive compensatory current directed to the south is formed along the western coast. The waters near the western coast are highly horizontally stratified that is caused by fresh water inflowing with the river runoffs. In winter seasons, the stratification is most pronounced, whereas in summer, the horizontal density gradient decreases. The horizontal density stratification leads to the following: starting from the depth ~ 20 m, the pressure gradient changes its sign and the along-coastal jet countercurrent directed to the north, occurs. Conclusions. The performed studies have shown that the water circulation on the Black Sea northwestern shelf is determined mainly by the following factors: the wind-induced water flows across the shelf boundary and strong horizontal water stratification near the western coast resulted from the river runoffs. As the currents on the sea surface are directed mainly to the southwest, the compensatory current directed to the south is formed near the western coast. Due to the strong horizontal stratification resulted from the river runoffs, a countercurrent directed to the north is formed in the subsurface layer near the western coast. In case the seawater flows to the shelf are extremely high, the countercurrent may be absent.
Own health, spousal health and transitions in loneliness among middle-aged and older adults in China

Abstract This study examines the effects of own and spousal health on transitions in loneliness over time among married middle-aged and older adults in China, and explores the possible gender differences in these effects using data from the three waves of the China Health and Retirement Longitudinal Study (2011–2015). The sample includes 6,422 men and 6,391 women who were married and aged 45 and older at the baseline survey. Middle-aged and older adults with poorer physical and emotional health statuses are more likely to transition into and less likely to transition out of loneliness in a two-year period. Spouse's emotional health also affects both types of transition in loneliness and spouse's functional limitation affects transition into loneliness through spouse's emotional health. In addition, for married men, their own functional limitation is significantly associated with their transitions into and out of loneliness. For married women, their spouse's functional limitation is significantly associated with their transition into loneliness and this is mainly through its association with spouse's emotional health. Also, for married women, their spouse's emotional health is significantly associated with their transition out of loneliness. Social interventions to reduce feelings of loneliness need to take a couple approach and consider both spouses’ health problems and how they may affect their daily activities and their interactions with each other and with others.
Gated Convolutional Neural Networks with Sentence-Related Selection for Distantly Supervised Relation Extraction

SUMMARY Relation extraction is one of the key basic tasks in natural language processing in which distant supervision is widely used for obtaining large-scale labeled data without expensive labor cost. However, the automatically generated data contains massive noise because of the wrong labeling problem in distant supervision. To address this problem, the existing research work mainly focuses on removing sentence-level noise with various sentence selection strategies, which however could be incompetent for disposing word-level noise. In this paper, we propose a novel neural framework considering both intra-sentence and inter-sentence relevance to deal with word-level and sentence-level noise from distant supervision, which is denoted as Sentence-Related Gated Piecewise Convolutional Neural Networks (SR-GPCNN). Speciﬁcally, 1) a gate mechanism with multi-head self-attention is adopted to reduce word-level noise inside sentences; 2) a soft-label strategy is utilized to alleviate wrong-labeling propagation problem; and 3) a sentence-related selection model is designed to ﬁlter sentence-level noise further. The extensive experimental results on NYT dataset demonstrate that our approach ﬁlters word-level and sentence-level noise e ﬀ ectively, thus signiﬁcantly outperforms all the baseline models in terms of both AUC and top-n precision metrics.
Morphophysiological and phytochemical changes of Mentha piperita using calcium, potassium, iron and manganese nano-fertilizers

This study was conducted to investigate the effects of foliar application of iron, potassium, calcium and manganese nano-chelates on morphological, physiological and biochemical traits of Mentha piperita (Peppermint) in a completely randomized design weight, total leaf chlorophyll, leaf protein, peroxidase activity, phenol content, leaf iron, potassium, calcium, manganese content and essential oil percentage Nano Ch (Fe 6 + K 6 + Ca 6 + Mn 6 ) had the highest amount in the second experiment.
A Causal U-Net Based Neural Beamforming Network for Real-Time Multi-Channel Speech Enhancement

People are meeting through video conferencing more often. While single channel speech enhancement techniques are useful for the individual participants, the speech quality will be sig-niﬁcantly degraded in large meeting rooms where the far-ﬁeld and reverberate conditions are introduced. Approaches based on microphone array signal processing are proposed to explore the inter-channel correlation among the individual microphone channels. In this work, a new causal U-net based multiple-in-multiple-out structure is proposed for real-time multi-channel speech enhancement. The proposed method incorporates the traditional beamforming structure with the multi-channel causal U-net by explicitly adding a beamforming operation at the end of the neural beamformer. The proposed method has entered the INTERSPEECH Far-ﬁeld Multi-Channel Speech Enhancement Challenge for Video Conferencing. With 1.97M model parameters and 0.25 real-time factor on Intel Core i7 (2.6GHz) CPU, the proposed method has outperforms the baseline system of this challenge on PESQ, Si-SNR and STOI metrics.
Modeling the Evolution of Trap States with Thermal Post-deposition Treatments in Sol-gel Indium Zinc Oxide TFTs

Metal oxides have been investigated for use in displays and wearable electronics, owing to their high mobility in the amorphous state. In solution-processed oxide thin-film transistors, post-deposition thermal processing significantly change the film’s transport properties, and is essential for high-performance devices. The mobility, bias stability and trapping-detrapping related hysteresis are improved with higher processing temperatures, which is generally attributed to decreased localized states which act as electron traps. Here we develop a model to validate that post-deposition processing indeed changes the density and properties of the localized states. We obtain good agreement between this model and the experimental data measured from sol-gel indium zinc oxide TFTs. When the processing temperature increases from 300 to 500 0C, the model indicates that the trap state density in the bulk semiconductor and at the interface decrease by a factor of 5 and a factor of 3, respectively. Furthermore, the localized states become shallower, and the band mobility increases at higher processing temperatures.
Respon Peserta Didik Terhadap Augmented Reality Arloopa Sebagai Multimedia Pembelajaran Matematika

Memasuki abad ke-21, semua peserta didik dituntut untuk memiliki kemampuan berpikir kritis dan keterampilan menggunakan teknologi untuk menilai dan mengevaluasi permasalahan. Institusi pendidikan dituntut untuk dapat menemukan model pembelajaran yang tepat guna memenuhi kebutuhan tersebut, termasuk pada masa pandemi Covid-19 saat ini. Salah satu inovasi pembelajaran yang dapat dikembangkan adalah pembelajaran berbasis teknologi Augmented Reality (AR). Penelitian ini bertujuan untuk mengetahui respon siswa terkait penggunaan ARLOOPA dalam pembelajaran Matematika. Pada beberapa penelitian AR dianggap efektif dalam meningkatkan hasil belajar peserta didik. Penelitian ini merupakan penelitian deskriptif tentang tingkat kepuasan peserta didik dalam proses pembelajaran menggunakan teknologi AR berbasis Discovery Learning. Respon peserta didik dikumpulkan menggunakan USE questionnaire dengan skala linkert, kemudian dianalisis menggunakan teknik persentase nilai. Pada K1 diperoleh bahwa semua aspek mencapai taraf persentase lebih dari . Sedangkan pada K2, diperoleh tingkat persentase pencapaian aspek usefulness, ease of learning dan satisfaction di atas .
Coping strategies as a causal mediator of the effect of loss-related memory characteristics and negative loss-related appraisals on symptoms of PGD, PTSD and depression

Abstract Background Psychological models of posttraumatic stress disorder (PTSD) and prolonged grief disorder (PGD) make predictions about the role of unhelpful coping strategies in maintaining difficulties by blocking self-correction of negative appraisals and memory integration following stressful life events like bereavement. However, few studies have tested these predictions directly. Method We used counterfactually based causal mediation to assess whether unhelpful coping strategies mediated the relationship between (1) loss-related memory characteristics and/or (2) negative grief-related appraisals and symptoms of PGD, PTSD and depression using a three-wave longitudinal sample (N = 275). Appraisals and memory characteristics were measured at time point 1, unhelpful coping strategies at T2, and symptom variables at T3. Additionally, multiple mediation analyses within a structural equation modelling (SEM) framework assessed which types of coping strategies differentially mediated symptoms of PGD, PTSD and depression. Results Coping strategies mediated the relationship between negative appraisals and memory characteristics and symptoms of PGD, PTSD and depression after adjusting for demographics and loss characteristics. Sensitivity analyses suggested that these results were most robust for PGD, followed by PTSD and then depression. Multiple mediation analyses suggested that all four subscales (avoidance, proximity seeking, loss rumination and injustice rumination) individually mediated the effect of memory characteristics and appraisals on PGD. Conclusions These results suggest that core predictions of the cognitive model for PTSD and the cognitive behavioural model of PGD are useful in predicting symptoms of post-loss mental health problems in the first 12–18 months after loss. Targeting unhelpful coping strategies is likely to reduce symptoms of PGD, PTSD and depression.
PLA2G6 gene mutation and infantile neuroaxonal degeneration; report of three cases from Iran

Objective(s): Infantile neuroaxonal degeneration (INAD) is a rare subgroup of neurodegeneration with brain iron accumulation (NBIA) disorders. This progressive disorder may develop during the early years of life. Affected individuals mostly manifest developmental delay and/or psychomotor regression as well as other neurological deficits. In the present study, we discussed 3 INAD patients diagnosed before the age of 10 by using Whole-Exome Sequencing (WES). Materials and Methods: We evaluated 3 pediatric patients with clinical phenotypes of INAD who underwent WES. Sanger sequencing was performed for co-segregation analysis of the variants in the families. An in-silico study was conducted for identification of the molecular function of the identified genetic variants in the PLA2G6 gene. Results: We detected three novel genetic variants in the PLA2G6 gene including a homozygous missense (NM_003560.2; c.1949T>C; p.Phe650Ser), a splicing (NM_001349864; c.1266-1G>A) and a frameshift variant (NM_003560.4; c.1547_1548dupCG; p.Gly517ArgfsTer29). Since the variants were not previously reported in literature or population databases, we performed in-silico studies for these variants and demonstrated their potential pathogenicity. Conclusion: The current study reports novel genetic variants in the PLA2G6 gene in the Iranian population, emphasizing the importance of high-throughput genetic testing in rare diseases.