Miracle-dz/UniFAR-FTUs huggingface dataset:
Anytime Collaborative Brain-Computer Interfaces for Enhancing Group Decision-Making in Realistic Environments

In this paper we present and test collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of group decision-making in realistic situations. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves monotonically the longer the group decision can wait; (2) we apply our cBCIs to two realistic scenarios of military relevance (patrolling a dark corridor and manning an outpost at night where users need to identify any unidentified characters that appear) in which decisions are based on information conveyed through video feeds; and (3) our cBCIs exploit Event-Related Potentials (ERPs) elicited in brain activity by the appearance of potential threats but, uniquely, the appearance time is estimated automatically by the system (rather than being unrealistically provided to it). As a result of these elements, groups assisted by our cBCIs make both more accurate and faster decisions than when individual decisions are integrated in more traditional manners.
Mine Inventory and Compilation of Mine-Adit Chemistry Data

An inventory of inactive mines and mine-related sites in the Animas River watershed study area was compiled from published and unpublished State and Federal sources. Site locations were spatially verified using digital orthophoto quadrangles to ensure an accurate, geographically referenced inventory. The inventory provides, where available, descriptive information for mine-related sites, the estimated volume of mine-waste piles and mill-tailings deposits, and the discharge and pH of mine adits with flowing water. Water-quality and discharge data for 232 samples collected at 110 mine sites during low-flow conditions in 1995-99 have been compiled. In addition, time-series data are presented for water quality at seven adits sampled over the annual hydrologic cycle. These data provide site-specific information about potential sources of deposit-related acidity and trace elements that can be used to support an environmental evaluation of the effect of historical mining in the study area. Analysis of the spatial variation in water-quality data from mine adits at low flow shows considerable variability. Mine-adit water chemistry is controlled by the degree of hydrothermal alteration in the surrounding bedrock and the type and extent of base-metal sulfides in the mine workings. Time-series data collected from seven draining adits show that increases in discharge generally are not associated with spring runoff and that concentrations of many metals remain very nearly constant or show a slight increase during this seasonal event. Increases in discharge from a few mines during spring runoff may be controlled by surface water that infiltrates into the mine, forcing mine-pool water out at the adit. Mine-adit flow may represent a long-term source of metals that affect surface water quality.
Confident Information Coverage Hole Prediction and Repairing for Healthcare Big Data Collection in Large-Scale Hybrid Wireless Sensor Networks

In the Internet of Things (IoT) for smart healthcare applications, sensors collect a vast amount of healthcare data, while coverage significantly affects the Quality of Service (QoS). In wireless sensor networks (WSNs), the QoS as well as the network lifetime are dramatically degraded with the increment of coverage holes, especially in large-scale hybrid WSNs (LS-HWSNs) where big data are collected by thousands of sensors distributed in a wide monitored area. In a LS-HWSN, two crucial problems, i.e., covering the wide area without coverage holes and designing an energy-efficient manner for dispatching mobile sensors to repair coverage holes, need to be solved. We study the problems from the cutting point of confident information coverage hole repairing (CICHR). To this end, based on the confident information coverage (CIC) model, a CIC hole predicting (CICHP) algorithm, centralized energy-efficient repairing (CEER) algorithm, and distributed energy-efficient repairing (DEER) algorithm are developed. The CICHP algorithm can predict the prior information of CIC holes (CICHs) by using the period-by-period energy consumption information of sensor nodes. Based on the prior information of CICHs, two repairing algorithms: 1) CEER and 2) DEER can schedule mobile sensors to repair CICHs beforehand. Simulation results show that the proposed algorithms can significantly improve the QoS and extend the network lifetime of LS-HWSNs.
Dissecting the Contribution of Environmental Influences, Plant Phenology, and Disease Resistance to Improving Genomic Predictions for Fusarium Head Blight Resistance in Wheat

Environmental factors like temperature and humidity are presumed to greatly influence Fusarium head blight FHB infections in wheat. Anther retention AR, on the other hand, is a morphologically neutral trait that shares a common genetic basis with FHB resistance. In this study, our aims were to: (i) Evaluate two types of corrections of FHB severity scores, namely method-1 via linear regression on flowering time (FT), and method-2 via a best-subset multiple linear regression analysis comprising FT plus accumulated thermal time variables; and (ii) assess the performance of multi-trait genomic selection (MT.GS) models for FHB severity assisted by AR. The forward prediction scenarios where GS models were trained with data from the previous years revealed average prediction accuracies (PA) of 0.28, 0.33, and 0.36 for FHB severity scores that were uncorrected or corrected by method-1 and method-2, respectively. FHB severity scores free from the influences of both environment and phenology seemed to be the most efficient trait to be predicted across different seasons. Average PA increments up to 1.9-fold were furthermore obtained for the MT.GS models, evidencing the feasibility of using AR as an assisting trait to improve the genomic selection of FHB resistance breeding lines.
Diallel Analysis of Different Rice Genotypes under Water Deficiency Conditions and Assessing Genetic Diversity Using SSR Markers

A half diallel cross among seven diverse rice genotypes was carried out in 2019 growing season. Parents and their 21 F1 crosses were evaluated under normal (continuous flooding) and water deficit (irrigation every 12 days) conditions during 2020 growing season,to estimate general (GCA) and specific (SCA) combining ability effects as well as identifying type of gene action controlling the inheritance of the studied traits.Both GCA and SCA mean squares were highly significant for all the studied traits under normal and stress conditions. The non-additive gene action played an important role in the inheritance of all the studied traits, except leaf rolling under stress treatment. The parents Sakha 107, NERICA 9 and N22 were the best general combiners for grain yield/plant. The crosses Sakha 107×Giza 177, Sakha 107×Fuknishiki, NERICA 9×Giza 177, NERICA 9×Akihikari, N22 ×IET1444, N22×Fuknishiki and IET1444 × Giza 177 were identified as promising specific combiners for improving grain yield/plant and one or more of its components under both conditions. The genetic diversity among the seven parental genotypes was assessed using ten Simple Sequence Repeats (SSR) markers. A total of 33 alleles were detected ranging from 2 to 5 with an average of 3.3 alleles per locus. The PIC values ranged from 0.32 to 0.69, with an average of 0.51. Genetic distance ranged from 0.24 to 0.92 with an average of 0.63. High genetic diversity was detected among the tested genotypes at the molecular level, hence these genotypes could be exploited to improve water deficit tolerance in rice breeding program.
Short text classification based on bidirectional TCN and attention mechanism

The context-related semantic information of the text in the traditional short text classification algorithms are not fully captured, a text classification model based on bidirectional temporal convolutional network and attention mechanism (BTCA) was proposed. Multi-layer dilated convolution was used to increase the receptive field and better capture long distance dependent information. At the same time, attention mechanism was used to increase the attention to the local key feature in the text, and the bidirectional temporal convolution network was used to extract contextual multi-scale semantic information to enrich semantics, the problem of sparse short text features was solved to a certain extent, and text classification effect was improved. The public corpus of the THUCNews was used to conduct a comparative experiment. It is pointed out that effect of short text classification is improved by using BTCA model, with an accuracy rate of 91.47%, which is better than commonly used models.
Recent Advances in Design and Actuation of Continuum Robots for Medical Applications

Traditional rigid robot application in the medical field is limited due to the limited degrees of freedom caused by their material and structure. Inspired by trunk, tentacles, and snakes, continuum robot (CR) could traverse confined space, manipulate objects in complex environment, and conform to curvilinear paths in space. The continuum robot has broad prospect in surgery due to its high dexterity, which can reach circuitous areas of the body and perform precision surgery. Recently, many efforts have been done by researchers to improve the design and actuation methods of continuum robots. Several continuum robots have been applied in clinic surgical interventions and demonstrated superiorities to conventional rigid-link robots. In this paper, we provide an overview of the current development of continuum robots, including the design principles, actuation methods, application prospect, limitations, and challenge. And we also provide perspective for the future development. We hope that with the development of material science, Engineering ethics, and manufacture technology, new methods can be applied to manufacture continuum robots for specific surgical procedures.
ASSESSING STAKEHOLDERS’ CONFLICTS IN URBAN LOGISTICS NETWORKS THROUGH ANALYTIC HIERARCHY PROCESS

Logistical activities contribute about 10% to 30% of the total volume of traffic in urban areas (Agrebi et al., 2015). Such activities generate approximately 25% of CO2, 30% of NOx, 40% of noise due to city traffic (Lebeau et al., 2017). Evidence from many urban areas shows that urban logistics generates about 40% of the total logistics cost in the supply chain and causes 50% of the road accidents in the city centre (Lebeau et al., 2017).
The impact of ocean acidification on marine dissolved organic matter

In this thesis, I investigated the impact of ocean acidification on marine dissolved organic matter (DOM), one of the largest active carbon pools on earth and an important factor in the global carbon cycle. The first part evaluates the influence of elevated pCO2 levels on DOM based on experimental results from large-scale pelagic mesocosm experiments that allow for simulating future ocean conditions. The production and consumption of individual molecular compounds was monitored via ultrahigh-resolution Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). Whereas a clear succession could be observed for individual molecules being produced or consumed over time, no differences were detected in molecular DOM composition related to CO2 concentrations. The second part focuses on the diversity of DOM in terms of its chemical structure and fragmentation experiments using FT-ICR-MS indicated the presence of a large pool of compounds with common structural features in DOM among aquatic environments. Further evidence was observed for the fact that a high number of isomers exist for each molecular formula detected in DOM.
ENSINANDO A ENSINAR: DIRETRIZES E ESTRATÉGIAS PARA MELHORAR A FORMAÇÃO DE PROFESSORES NO ENSINO SUPERIOR

The debate on the quality of university teacher education is more than ever a relevant issue. It is a topic which frequently appears in specialized journals about Higher Education and is often examined in a scientific context. This article takes up some of these complicated issues and illustrates with examples taken from a study at the University of Bari.
The Conditions Around Engagement in Interventions Among Perpetrators of Domestic Violence: Literature Review

This article reviews the available literature on major theoretical explanations for understanding engagement by focusing on the stages and circumstances of male perpetrators’ involvement in domestic violence interventions. The review aims to improve the insights into theoretical accounts by conceptualising the perspectives of participants’ motivational influences in changing violent behaviour in domestic violence perpetrator programmes. This article applied a critical literature review to explore theoretical explanations of engagement in domestic violence perpetrator interventions. Various factors in relation to theoretical conceptualisations are identified since different conditions can impact on perpetrators’ engagement. This theoretical overview is helpful to recognise how these theories and models enable us to understand how key circumstances impact the effectiveness of their involvement in interventions. This article attempts to provide an integrated framework for understanding domestic abusers’ engagement process in intervention programs and suggests approaches that will increase engagement and subsequent behaviour change.
Atmospheric gas-phase composition over the Indian Ocean

Abstract. The Indian Ocean is coupled to atmospheric dynamics, transport and chemical composition via several unique mechanisms, such as the seasonally varying monsoon circulation. During the winter monsoon season, high pollution levels are regularly observed over the entire northern Indian Ocean, while during the summer monsoon, clean air dominates the atmospheric composition, leading to distinct chemical regimes. The changing atmospheric composition over the Indian Ocean can interact with oceanic biogeochemical cycles and impact marine ecosystems, resulting in potential climate feedbacks. Here, we review current progress in detecting and understanding atmospheric gas-phase composition over the Indian Ocean and its local and global impacts. The review takes into account results from recent Indian Ocean ship campaigns, satellite measurements, station data and information on continental and oceanic trace gas emissions. The distribution of all major pollutants and greenhouse gases shows pronounced differences between the landmass source regions and the Indian Ocean with strong gradients over the coastal areas. Surface pollution and ozone are highest during the winter monsoon over the Bay of Bengal and the Arabian Sea coastal waters due to air mass advection from the Indo-Gangetic Plain and continental outflow from Southeast Asia. We observe, however, that unusual types of wind patterns can lead to pronounced deviations of the typical trace gas distributions. For example, the ozone distribution maxima shift to different regions under different wind scenarios. The distribution of greenhouse gases over the Indian Ocean shows many similarities when compared to the pollution fields, but also some differences of the latitudinal and seasonal variations resulting from their long lifetimes and biogenic sources. Mixing ratios of greenhouse gases such as methane show positive trends over the Indian Ocean, but long-term changes of pollution and ozone, and in particular how they are driven by changing emissions and transport patterns, require further investigation in the future. Although we know that changing atmospheric composition and perturbations within the Indian Ocean affect each other, the impacts of atmospheric pollution on oceanic biogeochemistry and trace gas cycling is severely understudied. We highlight potential mechanisms, future research topics and observational requirements that need to be explored in order to fully understand interactions and feedbacks between the ocean and atmosphere in the Indian Ocean region.
Corporate characteristics and leverage: evidence from Gulf countries

PurposeThis study aims to investigate the impact of corporate characteristics on leverage in the Gulf Cooperation Council (GCC) non-financial listed firms.Design/methodology/approachA sample comprising a balanced panel for eight years from 2009–2016 for four Gulf countries is used. In total, 85 non-financial listed companies have been selected using a non-probability sampling technique. Corporate characteristics are represented by return on assets (ROA), return on equity, return on capital employed, market value-added, Tobin-Q, liquidity and firm size. The study used fixed and random effect models to estimate the results.FindingsThe findings of the study revealed that both ROA and FSIZE have a significant negative effect on leverage. However, market value-added, return on capital employed and Tobin-Q exhibited a statistically significant positive effect on leverage. Further, the results indicated that Qatar is better than kingdom of Saudi Arabia (KSA), Oman and the UAE. In addition, evidence noted that KSA is better than both UAE and Oman in terms of the overall impact of corporate characteristics on the leverage. However, this effect is not statistically significant.Practical implicationsThis study provides an open insight for managers, bankers, financial analysts in the GCC countries and some other developing economies by highlighting the relationship between corporate characteristics and leverage in an emerging market.Originality/valueThe current study provides an important insight into corporate characteristics and leverage. By so doing, it provides an attempt to identify the factors influencing corporate financing behavior taking into consideration different issues such as different proxies of firms’ profitability, market capitalization, market value added and liquidity, which provides original evidence from Gulf countries emerging markets. These countries are characterized by low tax rates and high liquidity. High liquidity may reduce the cost of borrowing and debt financing may not be a huge burden on firms’ profits. This makes the investigation of leverage and corporate characteristics, particularly, firms’ profitability and liquidity, very important. Therefore, the study tries to bridge an existing gap in the body of literature of capital structure and debt financing in Gulf countries emerging markets.
Synthesis of Grafted Polylactic Acid and Polyhydroxyalkanoate by a Green Reactive Extrusion Process

Grafted polylactic acid (PLA) and polyhydroxyalkanoate (PHA) were synthesized by a reactive extrusion method. The grafted bio-based polymers had either polar functional groups such as hydroxyl (-OH) and polyethylene glycol (PEG) or non-polar functional groups. It was found that grafted biopolymers had significantly reduced melt viscosity, making them more suitable for certain polymer processing such injection molding and fiber spinning. The grafted biopolymers had improved compatibility in blending with other polar polymers such as polyvinyl alcohol and exhibited improved fiber spinning processability in polymer blends. Grafted PHA had a low crystallization rate making continuous reactive extrusion impossible. It was found that a novel co-grafting method, i.e. grafting PHA in the presence of PLA, was effective to overcome the process challenge of PHA. The reactive groups introduced to PLA or PHA can be used for further side chain reactions. The free radical initiated grafting reaction was a green reaction method. It eliminated the use and recovery of organic solvents, the reaction rate was also significantly increased over solution grafting reaction, taking seconds to complete rather than hours.
Preparation, characterization and bioavailability of oral puerarin nanoparticles by emulsion solvent evaporation method

To improve the water solubility and dissolution rate, puerarin (PUE) was nanocrystallized by an emulsion solvent evaporation (ESE) method, followed by freeze-drying. The optimized conditions of the preparation process were obtained by a single-factor method. Under the optimum conditions, PUE nanoemulsion with mean particle size (MPS) of 185.2 ± 39.8 nm and polydispersity index value (PI) of 0.005 was prepared. PUE nanosuspension with an MPS of 67.9 nm (PI = 0.280) was obtained after removing the solvent by rotary evaporation. Puerarin nanoparticles (PUENs) with an MPS of 132.6 nm (PI = 0.173) and zeta potential of 23.60 ± 2.55 mV were successfully prepared via further freeze-drying. PUENs were characterized by SEM, TEM, FTIR, XRD, DSC, TGA, equilibrium solubility, dissolution rate, oral bioavailability, hemorheology, cytotoxicity and solvent residue analysis. These results showed PUENs had a smaller particle size than raw PUE, and were changed into an amorphous structure from the crystal structure of raw PUE. The solubility and dissolution rate of PUENs were significantly improved in simulated gastric fluid (SGF), simulated intestinal fluid (SIF) and deionized water compared with raw PUE. The oral bioavailability of PUENs was 2.83 times that of raw PUE. PUENs improved hemorheology and did not enhance the cytotoxicity toward normal cells. The residual amounts of ethyl acetate and ethanol were separately less than the ICH limit for class III solvents. According to the results above, PUENs show the potential application value of its oral absorption.
Mind Your Language Entrepreneur! Analysing Crowdfunding Success Through the Lens of Effectuation Theory

Crowdfunding has become an important source of funds for entrepreneurs. In this paper, we add a novel dimension to the literature examining how narrative styles affect the performance of such funding campaigns, by employing the lens of effectuation theory. Using data from a popular non-equity crowdfunding platform from 2009 to 2019 and examining the narratives of the campaigns through the lens of effectuation, we provide empirical evidence that entrepreneurial tendencies exhibited in crowdfunding campaigns’ narratives can affect the chances of success of such campaigns. More specifically, we show that narratives with higher effectual orientation exhibit higher chances of success in raising funds and this impact is more pronounced in commercial campaigns. We also show that campaigns having narratives with higher causal orientation tend to be more successful in raising the required funds, though the evidence is mixed.
Intensity of Gadgets Usage for Achieving Prime Social and Cognitive Health of Adolescents During the COVID-19 Pandemic

Before the COVID-19 pandemic, studies in 2018 and 2019 recommended limiting the use of gadgets by adolescents to 3-4 hours a day because prolonged use can interfere with learning and cognition related activities. The use of gadgets also needs to be limited so that adolescents are more productive in using their time, and have social interactions with their environment. The participants of this study were 1,277 vocational school students and teachers in three cities namely Salatiga, Belitung, and Manado. Data were collected through questionnaires, observations, and interviews. However, during the time COVID-19 pandemic, there was a change in the pattern and intensity of the use of gadgets by adolescents. This caused changes in the postulate boundaries of the use of gadgets that are considered normal. This change is caused by student and teacher learning activities. Among these is the use of learning facilities through various types of video conferencing. During the COVID-19 pandemic, adolescents become used to doing online learning for 3-4 hours a day. In addition, the use of gadgets for other activities such as playing games, browsing, and other activities continues. Thus, based on additional field findings and studies from other sources, this study found that the use of gadgets by adolescents for up to 8 hours a day during the COVID-19 pandemic is recommended.