Miracle-dz/UniFAR-FTUs huggingface dataset:
Extreme drought pushes stream invertebrate communities over functional thresholds

Functional traits are increasingly being used to predict extinction risks and range shifts under long‐term climate change scenarios, but have rarely been used to study vulnerability to extreme climatic events, such as supraseasonal droughts. In streams, drought intensification can cross thresholds of habitat loss, where marginal changes in environmental conditions trigger disproportionate biotic responses. However, these thresholds have been studied only from a structural perspective, and the existence of functional nonlinearity remains unknown. We explored trends in invertebrate community functional traits along a gradient of drought intensity, simulated over 18 months, using mesocosms analogous to lowland headwater streams. We modelled the responses of 16 traits based on a priori predictions of trait filtering by drought, and also examined the responses of trait profile groups (TPGs) identified via hierarchical cluster analysis. As responses to drought intensification were both linear and nonlinear, generalized additive models (GAMs) were chosen to model response curves, with the slopes of fitted splines used to detect functional thresholds during drought. Drought triggered significant responses in 12 (75%) of the a priori‐selected traits. Behavioural traits describing movement (dispersal, locomotion) and diet were sensitive to moderate‐intensity drought, as channels fragmented into isolated pools. By comparison, morphological and physiological traits showed little response until surface water was lost, at which point we observed sudden shifts in body size, respiration mode and thermal tolerance. Responses varied widely among TPGs, ranging from population collapses of non‐aerial dispersers as channels fragmented to irruptions of small, eurythermic dietary generalists upon extreme dewatering. Our study demonstrates for the first time that relatively small changes in drought intensity can trigger disproportionately large functional shifts in stream communities, suggesting that traits‐based approaches could be particularly useful for diagnosing catastrophic ecological responses to global change.
Noisy Galvanic Vestibular Stimulation Sustainably Improves Posture in Bilateral Vestibulopathy

Patients with bilateral vestibulopathy (BV) suffer from persistent postural imbalance, leading to a marked decrease in quality of life and a higher risk of falls. However, so far, the effective treatments for BV are very limited. We examined whether long-term noisy galvanic vestibular stimulation (nGVS) keeps improving body balance after the cessation of the stimulus in BV patients. Thirteen BV patients received nGVS for 30 min with a lower intensity than the intensity at which they feel any cutaneous sensations, and their postural movement was monitored for 6 h after the stimuli. The same session was repeated at 14-day intervals. Stance tasks on two legs were performed with eyes closed. The velocity of the center of pressure (COP) movement, the area enclosed by the COP movement, and the root mean square of the displacement of the COP were measured. The power spectrum of the COP movement was assessed. Subjective improvement of body balance was graded as worsened (−2), slightly worsened (−1), unchanged (0), slightly improved (+1) and improved (+2) in comparison with that without nGVS. In each session, the velocity of the COP movement was significantly improved for 6 h after the stimulus had ceased (P < 0.01). Concomitantly, the mean frequency of the COP power spectrum was significantly reduced in the anterior-posterior axis (P < 0.05). Subjective symptoms of imbalance were improved during the post-stimulation effect (P < 0.05). nGVS leads to an improvement in body balance that lasts for several hours after the end of the stimulus in BV patients with a reduction in the high-frequency components of their postural movement. This trial was registered with the University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMINCTR: UMIN000028054).
High Genetic Risk Scores of ASIC2, MACROD2, CHRM3, and C2orf83 Genetic Variants Associated with Polycystic Ovary Syndrome Impair Insulin Sensitivity and Interact with Energy Intake in Korean Women

Background: We explored the genetic variants that were associated with polycystic ovary syndrome (PCOS) by genome-wide association study (GWAS) and evaluated the association of genetic risk scores (GRS) of the selected genetic variants with insulin resistance and the interaction of the GRS with nutrient intake to develop insulin resistance. Methods: The 6 genetic variants involved in brain and nervous system (acid sensing ion channel subunit 2 rs8071961, rs1988598, and rs16589, macro domain containing 2 rs7262810 CHRM3 rs1867265 and chromosome 2 open reading frame 83 rs11889798) were selected from a GWAS of the PCOS study. GRS of the 6 single nucleotide polymorphisms was calculated in 3,723 Korean women in the Ansan/Ansung cohort of KARE study. Results: Fasting serum insulin and C-reactive protein (CRP) levels, homeostasis model assessment of insulin resistance (HOMA-IR), and psychological stress levels were significantly higher in the high-GRS group than the low-GRS group. However, serum-free T4 levels were significantly lower in the high-GRS group. HOMA-IR and CRP were higher OR (1.129 and 1.382) in the high-GRS group than the low-GRS group after adjusted for covariates. There was a significant interaction between GRS and daily energy intake (p = 0.004). The OR (1.233) for HOMA-IR was higher in the high-GRS group than the low-GRS group only in the group with lower energy intakes based on estimated energy requirement. Conclusion: Women with high-GRS for PCOS had increased risk of insulin resistance and low energy intake did not protect against the elevation of insulin resistance in women with high GRS. Low energy intake might be protective against PCOS in carriers with low and medium GRS.
Early Intervention: Managing Adversity

This review proposes separate and distinct biological mechanisms for the effects of adversity, more commonly experienced in poverty, and socioeconomic status (SES) on child development. Adversity affects brain and cognitive development through the biological stress response, which confers risk for pathology. Critically, we argue that a different mechanism, enrichment, shapes differences in brain and cognitive development across the SES spectrum. Distinguishing between adversity and SES allows for precise, evidence-based policy recommendations. We offer recommendations designed to ensure equity in children’s experiences to help narrow the achievement gap and promote intergenerational mobility.
Authentication and Encryption for a Robotic Ad Hoc Network Using Identity-Based Cryptography

In some situations the communications of a place can be affected, totally lost, or not even exist. In these cases, the MANETs play an important role, allowing to establish a communications point using the different nodes of the network to reach the destination using decentralized communications. This paper proposes the implementation of a Robotic MANET, a decentralized network using robots together with IoT devices as its nodes, which allows to move the network nodes to the desired location remotely. For this, each robot has as a core a Raspberry Pi with the capabilities to perform audio and video streaming, remote control of robots, tracking of objects, and deployment of wireless networks. To protect the network, different security mechanisms are used that allow secure authentication on the network by different nodes and encryption of information transmitted between them. All communications are protected through Identity-Based Cryptography, specifically with an Identity-Based Signcryption scheme.
Baseline concentration of misfolded α‐synuclein aggregates in cerebrospinal fluid predicts risk of cognitive decline in Parkinson's disease

The prognostic significance of misfolded α‐synuclein (α‐Syn) aggregates in Parkinson's disease (PD) has not been well investigated. The aim of this study was to reveal the relationship between misfolded α‐Syn aggregate concentration in cerebrospinal fluid (CSF) and cognitive decline risk in PD.
Research on Output Characteristics of Magnetic Modulator Detection Winding

Mathematical model of magnetic modulator was established, characterized by the consistency with actual structure, which is two cores differential structure and excitation winding doubling as detection winding. Simulate and analyze the influence of excitation source (sine wave, triangle wave and square wave) and saturation depth of core on the output voltage of detection winding. The result shows that the output characteristic is optimal when employing square wave excitation source. Meanwhile, cores working in the over saturated state will lead to the oscillation of detection winding output waveform.
Automatic Generation of Textual Advertisement for Video Advertising

With the rapid growth of online videos, video advertising, as a main source of income for video streaming websites, has attracted increasing attention. It is challenging to insert advertisements at suitable positions while preserving comfortable watching experience of users. Existing methods usually insert advertisements at the fixed positions and neglect the variations of scenes, which can extremely reduce the attractiveness of videos due to intrusion to important visual elements. In this paper, we propose a method to automatically generate and embed appealing textual advertisements for online videos. First we estimate the visual significance of the main elements in the video frames via human face localization and saliency detection. Next we design an efficient algorithm to recognize the scene changes with the visual significance map, through which the system can find stable areas in distinct scenes for advertising. At last, a series of aesthetic designing principles are adopted to generate attractive advertisements which are in harmony with the style of video scenes. User studies show that our system can achieve the best user experience compared with the state-of-the-art methods as well as comparable results with commercial advertisements designed by professional designers.
Zijn opvoedingsvaardigheden te veranderen door middel van de ‘Incredible Years’ oudertraining?

Background: Previous research provides clear evidence for the importance of parenting practices as an early childhood risk factor for the development of conduct problems. This study examines the preventive effect of the Incredible Years (IY) parent training program in a population-based sample of families with pre-school children at risk for developing disruptive behaviour disorders (ODD and/ or CD). This parent management training is aimed at enhancing the parenting skills in order to reduce conduct problems in children. Method: A total of 144 children with a score at or above the 80 percentile on the aggression scale of the CBCL at age 4, was enrolled in this study. The participating families in the intervention group (n=72) and the families in the control group (n=72) were matched on six characteristics which have been proven to affect either the developmental course of the child's disruptive behavior or to be a moderator of treatment effect. Parent practices were measured pretreatment, post-treatment and 1 year after finishing IY, using the Parent Practices Interview and the Daily Discipline Interview. Results: Using a paired samples t-test, post-treatment improvements were found in appropriate discipline, praise and incentives and limit setting and reductions were found in harsh and inconsistent discipline, physical punishment and criticism. Results showed also significant differences between the intervention group and the control group 1 year after the intervention. There were still improvements in appropriate discipline and using praise and reductions in harsh and inconsistent discipline and giving commands. Conclusion: The Incredible Years parenting program significantly improved parenting practices. Improvements in positive parenting and reductions in negative parenting support the potential of the intervention to prevent later conduct problems in high risk children. __________________________________________________________________________________________
Coordinated exploration for labyrinthine environments with application to the Pursuit-Evasion problem

This paper introduces a multirobot cooperation approach to solve the "pursuit evasion'' problem for mobile robots that have omnidirectional vision sensors. The main characteristic of this approach is to implement a real cooperation between robots based on knowledge sharing and makes them work as a team. A complete algorithm for computing a motion strategy of robots is also presented. This algorithm is based on searching critical points in the environment. Finally, the deliberation protocol which distributes the exploration task among the team and takes the best possible outcome from the robots resources is presented.
Maximin Efficiencies under Treatment-Dependent Costs and Outcome Variances for Parallel, AA/BB, and AB/BA Designs

If there are no carryover effects, AB/BA crossover designs are more efficient than parallel (A/B) and extended parallel (AA/BB) group designs. This study extends these results in that (a) optimal instead of equal treatment allocation is examined, (b) allowance for treatment-dependent outcome variances is made, and (c) next to treatment effects, also treatment by period interaction effects are examined. Starting from a linear mixed model analysis, the optimal allocation requires knowledge on intraclass correlations in A and B, which typically is rather vague. To solve this, maximin versions of the designs are derived, which guarantee a power level across plausible ranges of the intraclass correlations at the lowest research costs. For the treatment effect, an extensive numerical evaluation shows that if the treatment costs of A and B are equal, or if the sum of the costs of one treatment and measurement per person is less than the remaining subject-specific costs (e.g., recruitment costs), the maximin crossover design is most efficient for ranges of intraclass correlations starting at 0.15 or higher. For other cost scenarios, the maximin parallel or extended parallel design can also become most efficient. For the treatment by period interaction, the maximin AA/BB design can be proven to be the most efficient. A simulation study supports these asymptotic results for small samples.
Inhibiting conjugation as a tool in the fight against antibiotic resistance

Antibiotic resistance, especially in gram‐negative bacteria, is spreading globally and rapidly. Development of new antibiotics lags behind; therefore, novel approaches to the problem of antibiotic resistance are sorely needed and this commentary highlights one relatively unexplored target for drug development: conjugation. Conjugation is a common mechanism of horizontal gene transfer in bacteria that is instrumental in the spread of antibiotic resistance among bacteria. Most resistance genes are found on mobile genetic elements and primarily spread by conjugation. Furthermore, conjugative elements can act as a reservoir to maintain antibiotic resistance in the bacterial population even in the absence of antibiotic selection. Thus, conjugation can spread antibiotic resistance quickly between bacteria of the microbiome and pathogens when selective pressure (antibiotics) is introduced. Potential drug targets include the plasmid‐encoded conjugation system and the host‐encoded proteins important for conjugation. Ideally, a conjugation inhibitor will be used alongside antibiotics to prevent the spread of resistance to or within pathogens while not acting as a growth inhibitor itself. Inhibiting conjugation will be an important addition to our arsenal of strategies to combat the antibiotic resistance crisis, allowing us to extend the usefulness of antibiotics.
Chicken Gut Microbiota: Importance and Detection Technology

Sustainable poultry meat and egg production is important to provide safe and quality protein sources in human nutrition worldwide. The gastrointestinal (GI) tract of chickens harbor a diverse and complex microbiota that plays a vital role in digestion and absorption of nutrients, immune system development and pathogen exclusion. However, the integrity, functionality, and health of the chicken gut depends on many factors including the environment, feed, and the GI microbiota. The symbiotic interactions between host and microbe is fundamental to poultry health and production. The diversity of the chicken GI microbiota is largely influenced by the age of the birds, location in the digestive tract and diet. Until recently, research on the poultry GI microbiota relied on conventional microbiological techniques that can only culture a small proportion of the complex community comprising the GI microbiota. 16S rRNA based next generation sequencing is a powerful tool to investigate the biological and ecological roles of the GI microbiota in chicken. Although several challenges remain in understanding the chicken GI microbiome, optimizing the taxonomic composition and biochemical functions of the GI microbiome is an attainable goal in the post-genomic era. This article reviews the current knowledge on the chicken GI function and factors that influence the diversity of gut microbiota. Further, this review compares past and current approaches that are used in chicken GI microbiota research. A better understanding of the chicken gut function and microbiology will provide us new opportunities for the improvement of poultry health and production.
The Exploration of E-personality in IT-enabled Value Co-creation

Facilitated by the Internet, people nowadays may express their “true self”, the real personal identityimportant aspects of self not often showed to others (Bargh, et al., 2002), when they participate the interactions online (Amichai-Hamburger et al., 2002). By expressing their true self with each other, people will be able to signal accurate information for their consumption choices (Brannon, 2016). However, the theory of true self has been challenged by several scholars. Marriott & Buchanan (2014) argued that the anonymity on the online social environment has been no longer useful to distinguish a person’s online and offline personality. Similarly, Dr. Emanuel and her colleagues (2014) found that people are willing to share more private information face-to-face than using the anonymous online platforms. Interestingly, Dr. Emanuel (2014)’s team suggested that the difference on the context of online spaces do have impacts on the amount and the type of information disclosed. In other words, people may behave variously in different online spaces. Value co-creation is a business strategy that could make customers actively participate in the production of an organization’s core value chain and thus build a closer relationship with customers to improve satisfaction and organizational commitment (Vega-Vazquez et al., 2013; Randall et al., 2011). Participants will express themselves differently due to different roles in the value developing process. To manage the interaction activities on the co-creation platform more efficiently, understanding true e-personality of each stakeholders would be important. However, the existing research on this topic is scarce. The main purpose of this study is thus to explore the attributes of e-personality on participants in the value collaboration process. A research framework on e-personality on value co-creation will be carefully developed. Researcher will use survey to test related hypotheses through quantitative analysis. It is expected that this research will help the readers understand the true self of different types of participants in IT-enabled value co-creation works. The collaboration platform provider will also be able to design a better system for next cooperation projects by gaining knowledge on its users.
Necesidad de Uso de Tecnologías para el Aprendizaje y el Conocimiento en Adolescentes - Need of Use of Knowledge and Learning Technologies in Adolescents

As a part of a greater study, this work proposes a conceptual model to understand how it is possible to foster the need of adolescents to support their educational process on knowledge and learning technologies (KLT), as a basic requirement for appropriation. Additionally, different interpretations of this phenomenon are explored amongst those responsible for the definition of technological and educational strategies, such as directors of educational units, and vendors of educational technologies. The use of a qualitative methodology is described, based on semi-structured in-depth interviews, followed by content analysis, particularly word counts and semantic networks to derive the proposed model. Finally, the results are discussed, and potential future research directions are posed. The outstanding contribution made by this work is related to the understanding of the target of appropriation itself, the adolescent, as a factor of greater importance over others established in existing adoption and appropriation models.
A Review on Learning Planning Action Models for Socio-Communicative HRI

For social robots to be brought more into widespread use in the fields of companionship, care taking and domestic help, they must be capable of demonstrating social intelligence. In order to be acceptable, they must exhibit socio-communicative skills. Classic approaches to program HRI from observed human-human interactions fails to capture the subtlety of multimodal interactions as well as the key structural differences between robots and humans. The former arises due to a difficulty in quantifying and coding multimodal behaviours, while the latter due to a difference of the degrees of liberty between a robot and a human. However, the notion of reverse engineering from multimodal HRI traces to learn the underlying behavioral blueprint of the robot given multimodal traces seems an option worth exploring. With this spirit, the entire HRI can be seen as a sequence of exchanges of speech acts between the robot and human, each act treated as an action, bearing in mind that the entire sequence is goal-driven. Thus, this entire interaction can be treated as a sequence of actions propelling the interaction from its initial to goal state, also known as a plan in the domain of AI planning. In the same domain, this action sequence that stems from plan execution can be represented as a trace. AI techniques, such as machine learning, can be used to learn behavioral models (also known as symbolic action models in AI), intended to be reusable for AI planning, from the aforementioned multimodal traces. This article reviews recent machine learning techniques for learning planning action models which can be applied to the field of HRI with the intent of rendering robots as socio-communicative.
What Makes Games Fun? Card Sort Reveals 34 Sources of Computer Game Enjoyment

Understanding what makes computer games fun not only helps with game design, it tells us how to design any interactive experience for enjoyment. Existing models of computer game enjoyment are either not comprehensive enough, not generated by empirical research, or both. To fill this literature gap, we conducted a card sort exploring participants’ experiences and mental models around what makes computer games enjoyable. A broad literature review identified 167 sources of enjoyment, which we printed on cards. Our research group did an open card sort to create 24 initial categories. Sixty participants then sorted the cards into the categories. After every ten participants, we revised cards and categories. Participants in the last two rounds of ten participants had inter-rater reliabilities of 0.9381 and 0.9367, as calculated with Randolph’s free-marginal multi-rater kappa. We present our final 34 categories as a new, more comprehensive model of the sources of computer game enjoyment.