Miracle-dz/UniFAR-FTUs huggingface dataset:
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The rocky intertidal zone is one of the most difficult environments for organisms to survive in due to its harsh biotic and abiotic conditions. As such, it is also one of the best indicators of climate change and an important barrier to beach erosion. This study looked at the rocky intertidal zone of the Puerto Cabuyal-Punta San Clemente Marine Reserve in the Manabí province of Ecuador, with a focus on observing and identifying the organisms found in the area. Data was collected along 30 m transects at varying elevations along the shore using quadrants of two sizes: 50x50 cm for sessile organisms and algae and 1x1 m for macroinvertebrates. That data was then compared with other studies along coastal Ecuador where it was determined that Puerto Cabuyal does hold a similar level of species richness and diversity as well as similar species. A total of 56 species were identified from the following phyla: Mollusca (20 species), Arthopoda (12), Ochrophyta (6), Echinodermata (5), Rhodophyta (5), Chlorophyta (2), Chordata (2), Cnidaria (2), and Platyhelminthes (2). The low transects, measured at the level closest to the water, were shown to have the highest species richness. The data collected in this study can be used in the future to understand changes in the diversity of the intertidal zone of this marine reserve and for comparisons along coastal Ecuador.
Unveiling Profound Seasonal and Spatial Dynamics of Greenhouse Gases (CO2, CH4, N2O) in the Northern Benguela Upwelling System Unnamed Article

The northern Benguela Upwelling System (nBUS) represents one of the ocean’s largest and most biologically productive marine ecosystems, crucial for the cycling of greenhouse gases (GHG). Despite its signiﬁcance, there is a scarcity of direct evidence on the seasonal variability of GHG production and emissions in the nBUS and its major driving factors. Through multi-year observations, we examined the spatio-temporal dynamics in the nBUS to understand their inﬂuence on GHG dynamics. Our ﬁndings revealed coastal GHG hotspots with seasonal gradients, primarily inﬂuenced by upwelling. The nBUS consistently acted as a perennial source of GHG to the atmosphere, with peak CO 2 , CH 4 , and N 2 O sea-air ﬂuxes during austral winter (increases of 97%, 47%, and 87% compared to austral summer, respectively). Winter CO 2 -equivalent (CO 2 -e) emissions accounted for 70 – 73% of GHG emissions, followed by N 2 O (23 – 24%) and CH 4 (2 – 6%). In summer, these percentages shifted considerably, with CO 2 contributing 23 – 30%, N 2 O 38 – 51%, and CH 4 17 – 38%. We argue for the necessity of including non-CO 2 GHG when assessing the impacts of coastal ecosystems on climate dynamics. Our results oﬀer detailed insights into the primary drivers of spatial and seasonal variability in GHG dynamics within coastal upwelling waters. This study constitutes the ﬁrst comprehensive simultaneously evaluation of all three GHG within the region. It serves as a foundational framework for subsequent model studies aimed at reﬁning the sea-air ﬂux variability, particularly in anticipation of projected ocean warming and the expanding oxygen minimum zones.
Comparison of Model Predictions and Laboratory Observations of Transgene Frequencies in Continuously-Breeding Mosquito Populations

The persistence of transgenes in the environment is a consideration in risk assessments of transgenic organisms. Combining mathematical models that predict the frequency of transgenes and experimental demonstrations can validate the model predictions, or can detect significant biological deviations that were neither apparent nor included as model parameters. In order to assess the correlation between predictions and observations, models were constructed to estimate the frequency of a transgene causing male sexual sterility in simulated populations of a malaria mosquito Anopheles gambiae that were seeded with transgenic females at various proportions. Concurrently, overlapping-generation laboratory populations similar to those being modeled were initialized with various starting transgene proportions, and the subsequent proportions of transgenic individuals in populations were determined weekly until the transgene disappeared. The specific transgene being tested contained a homing endonuclease gene expressed in testes, I-PpoI, that cleaves the ribosomal DNA and results in complete male sexual sterility with no effect on female fertility. The transgene was observed to disappear more rapidly than the model predicted in all cases. The period before ovipositions that contained no transgenic progeny ranged from as little as three weeks after cage initiation to as long as 11 weeks.
Do Translation Professionals Need to Tolerate Ambiguity to be Successful ? A Study of the Links between Tolerance of Ambiguity , Emotional Intelligence and Job Satisfaction

Hubscher-Davidson, Severine (2018). Do Translation Professionals Need to Tolerate Ambiguity to be Successful? A Study of the Links between Tolerance of Ambiguity, Emotional Intelligence and Job Satisfaction. In: Lacruz, Isabel and Jääskeläinen, Riitta eds. Innovation and Expansion in Translation Process Research. American Translators Association Scholarly Monograph Series (XVIII). Amsterdam/Philadelphia: John Benjamins, pp. 77–103.
Do Translation Professionals Need to Tolerate Ambiguity to be Successful? A Study of the Links between Tolerance of Ambiguity, Emotional Intelligence and Job Satisfaction

Hubscher-Davidson, Severine (2018). Do Translation Professionals Need to Tolerate Ambiguity to be Successful? A Study of the Links between Tolerance of Ambiguity, Emotional Intelligence and Job Satisfaction. In: Lacruz, Isabel and Jääskeläinen, Riitta eds. Innovation and Expansion in Translation Process Research. American Translators Association Scholarly Monograph Series (XVIII). Amsterdam/Philadelphia: John Benjamins, pp. 77–103.
A joint source and channel coding scheme base on simple protograph structured codes

A scheme of joint source and channel coding (JSCC) with double Low Density Parity Check (LDPC) structure has been proposed recently, which results in a popular and promising research topic for further improving JSCC design at physical layer. However, it becomes an important problem how to enhance the error performance and reduce the complexity of the whole system. Therefore, we propose a state-of-the-art JSCC scheme, denoted as P-JSCC, based on simple protograph structured codes considering the performance and hardware advantages of such LDPC-like codes. The simulation results with different lengths of source sequence show that the Bit Error Ratio (BER) performance of the proposed scheme is better than that of the previous JSCC scheme base on regular LDPC codes, denoted as traditional [1], in the turbo cliff region. Furthermore, it is found that the performance of the proposed JSCC scheme becomes worse as p1, the probability of binary bit with value one in source sequence, increases. Eventually, we enlarge the degree of check nodes in source code while keep the channel code invariable, and the simulation results illustrate that a significant improvement is achieved on error floor region.
BT-Nurse: computer generation of natural language shift summaries from complex heterogeneous medical data

The BT-Nurse system uses data-to-text technology to automatically generate a natural language nursing shift summary in a neonatal intensive care unit (NICU). The summary is solely based on data held in an electronic patient record system, no additional data-entry is required. BT-Nurse was tested for two months in the Royal Infirmary of Edinburgh NICU. Nurses were asked to rate the understandability, accuracy, and helpfulness of the computer-generated summaries; they were also asked for free-text comments about the summaries. The nurses found the majority of the summaries to be understandable, accurate, and helpful (p<0.001 for all measures). However, nurses also pointed out many deficiencies, especially with regard to extra content they wanted to see in the computer-generated summaries. In conclusion, natural language NICU shift summaries can be automatically generated from an electronic patient record, but our proof-of-concept software needs considerable additional development work before it can be deployed.
Effects of Acupuncture on Menopausal Hot Flashes and Sleep Quality in Women With Natural Menopause: A Single Arm Clinical Trial

Abstract Objectives: Hot flush (HF) is a common menopausal symptom and can cause dysfunction in different aspects of living. Due to the concerns about hormonal treatment, non-medical methods, including acupuncture, are suggested for managing HFs. This study aimed to assess the effect of acupuncture on HF episodes and sleep quality in menopausal women. Materials and Methods: This single-arm clinical trial was performed on 26 menopausal women who were referred to the gynecologic clinic of a tertiary hospital in Mashhad, Iran between December 2018 and December 2019. The menopausal state was documented based on hormonal tests. Participants underwent acupuncture 3 times a week (7 acupuncture points based on traditional Korean medicine) for 4 weeks. The duration of each session was 20 min. Pittsburgh Sleep Quality Index (PSQI) was filled for each participant at baseline, at the end of the intervention, and after 6 and 12 weeks of follow-up. Results: The mean age of participants was 51.96 ± 3.53. Moderate and low knowledge about menopause were reported in 50% and 34.6% of the participants, respectively. Reduced spousal interest was reported by 15.4% of the participants. Acupuncture significantly improved HFs, sleep disorders and sleep quality, and sleep latency subscales of PSQI ( P <0.05). Conclusions: Acupuncture could reduce HFs and improve sleep quality in menopausal women. The effects of acupuncture with medical interventions should be evaluated in future studies.
Non-adherence in difficult asthma: time to take it seriously

Recent studies have demonstrated a high prevalence of non-adherence with anti-inflammatory medication in patients referred for specialist assessment with difficult-to-control asthma. As well as poor asthma outcome and increased healthcare cost, failure to detect non-adherence makes identification of true treatment-resistant/refractory asthma challenging. This is because guideline definitions of refractory asthma are all predicated on failure to respond to high-dose anti-inflammatory therapy but do not state how adherence with this therapy should be assessed. With the advent of novel expensive biological therapies, the systematic identification of non-adherence becomes more essential to avoid targeting therapies at an inappropriate patient group. Novel biomarkers of steroid exposure, in combination with more traditional surrogate measures such as prescription filling assessment, may allow more objective assessments of non-adherence to be developed in the future. When identified, non-adherence can potentially be targeted and improved, but the key challenge is to empower patients to make informed choices about medicines rather than decisions influenced by misplaced beliefs about benefit and harm. There is an urgent need for the systematic development of individualised interventions which allow non-adherence to be effectively managed. Thus, non-adherence must become a priority in the clinical assessment of difficult-to-control asthma because addressing non-adherence is likely to deliver greater benefits in this group than any novel treatment. It is essential that future research examines strategies and interventions to address non-adherence in subjects with difficult-to-control asthma.
Towards an Improvement of Bug Severity Classification

Predicting the severity of bugs has been found in past research to improve triaging and the bug resolution process. For this reason, many classification/prediction approaches emerged over the years to provide an automated reasoning over severity classes. In this paper, we use text mining together with bi-grams and feature selection to improve the classification of bugs in severe/non-severe classes. We adopt the Naïve Bayes (NB) classifier considering Mozilla and Eclipse datasets commonly used in related works. Overall, the results show that the application of bi-grams can improve slightly the performance of the classifier, but feature selection can be more effective to determine the most informative terms and bi-grams. The results are in any case project-dependent, as in some cases the addition of bi-grams may worsen the performance.
Playing nice: a multi-methodological study on the effects of social conformity on memory

Conformity is an important aspect of social behavior. Two main motives have been identified: people may adapt their behavior to “play nice” despite knowing better (normative conformity) or they may accept the others' opinion as a valid source of information (informative conformity). Neuroimaging studies can help to distinguish between these two possibilities. Here, we present a functional magnetic resonance imaging (fMRI) study on memory conformity in a real group situation. We investigated the effects of group pressure on activity in hippocampus and anterior cingulate cortex (ACC) which likely support informative and normative memory conformity, respectively. Furthermore, we related the single nucleotide polymorphism (SNP) rs4680 [called Catechol-O-methyltransferase (COMT) Val158Met] on the gene coding for COMT to both behavior and fMRI activation. Homozygous Met-allele carriers (Val−) behaved more conformist than carriers of at least one Val-allele (Val+). In the neuroimaging data, we compared trials in which subjects were confronted with a majority of incorrect group responses to trials in which they were confronted with a majority of correct group responses. We found increased hippocampal activity when the majority of the group was correct, possibly indicating retrieval processes. Moreover, we observed enhanced activity in the ACC when the majority of the group was incorrect, suggesting that conformity was mostly normative. Most interestingly, this latter effect was more pronounced for Val− as compared to Val+ participants. This offers a speculative explanation for the higher behavioral levels of social conformity in Val− allele carriers, because their subjectively perceived conflict in the presence of an incorrect group majority may have been higher. Overall, this study demonstrates how the mechanisms leading to complex social behavior such as conformity can be studied by combining genetic analyses and fMRI in social neuroscience paradigms.
Knowledge sharing in information system development teams: examining the impact of shared mental model from a social capital theory perspective

Shared mental model (SMM), a concept from psychology, is defined as a common thinking style developed when individuals perform similar tasks in a cohesive manner. In this article, we investigate the relationship between the three dimensions of social capital and SMM. We also examine whether SMM mediates the impact of social capital on knowledge sharing (KS) behaviour in information system development (ISD) teams. Social capital is defined as the resource of social relationships owned by individuals. It is useful for explaining human behaviour in social networks. The data collected represent 492 ISD professionals in 118 teams from 18 middle-sized enterprises. The results of this study indicate that social capital theory is useful for explaining the antecedents of SMM, and SMM is positively related to KS and team performance. This research also emphasises the importance of developing SMM in a team.
Integrated weed management in cotton under irrigated condition of middle Gujarat

A field experiment was conducted for two consecutive Kharif seasons of 2014 and 2015 at research farm of AICRP-Weed Management, AAU, Anand to study the integrated weed management in cotton under irrigated condition. Pre-emergence application of pendimethalin 1000 g/ha fb hand weeding twice at 20 and 50 DAS, and pyrithiobac-sodium + quizalofop-p-ethyl (62.5 + 50 g/ha) as PoE fb directed spray of glyphosate 2000 g/ha at 60 DAS recorded significantly lower weed dry biomass as well as higher seed cotton yield and benefit cost ratio as compared to rest of the treatments. The weed control efficiency of these treatments proved to be 90 and 86% during 2014 and 2015, respectively.
Gonadotrophin pulsatility in girls with the Turner syndrome: modulation by exogenous sex steroids

The endocrine manisfestation of puberty, nocturnal pulsatile secretion of gonadotrophins precedes the physical manifestations by 2 years. Whether gonadal steroids and inhibin have a role to play in the regulation of pulsatile gonadotrophin release is unclear. The agonadal model, girls with Turner's syndrome (TS), has been used to determine the role of the hypothalamic pulse generator in the ontogeny of gonadotrophin secretion in man. We evaluated the ontogeny of gonadotrophin secretion in TS girls with respect to amplitude and frequency and compared these results to those obtained in a group of normal girls. The effects of treatment with ethinyloestradiol (EE2) or oxandrolone (OX) on parameters of gonadotrophin secretion were also evaluated.
Imitation learning of globally stable non-linear point-to-point robot motions using nonlinear programming

This paper presents a methodology for learning arbitrary discrete motions from a set of demonstrations. We model a motion as a nonlinear autonomous (i.e. time-invariant) dynamical system, and define the sufficient conditions to make such a system globally asymptotically stable at the target. The convergence of all trajectories is ensured starting from any point in the operational space. We propose a learning method, called Stable Estimator of Dynamical Systems (SEDS), that estimates parameters of a Gaussian Mixture Model via an optimization problem under non-linear constraints. Being time-invariant and globally stable, the system is able to handle both temporal and spatial perturbations, while performing the motion as close to the demonstrations as possible. The method is evaluated through a set of robotic experiments.
A Psychologically-Motivated Model of Opinion Change with Applications to American Politics

Agent-based models are versatile tools for studying how societal opinion change, including political polarization and cultural diffusion, emerges from individual behavior. This study expands agents' psychological realism using empirically-motivated rules governing interpersonal influence, commitment to previous beliefs, and conformity in social contexts. Computational experiments establish that these extensions produce three novel results: (a) sustained strong diversity of opinions within the population, (b) opinion subcultures, and (c) pluralistic ignorance. These phenomena arise from a combination of agents' intolerance, susceptibility and conformity, with extremist agents and social networks playing important roles. The distribution and dynamics of simulated opinions reproduce two empirical datasets on Americans' political opinions.
An Enhanced Grey Wolf Optimization Based Feature Selection Wrapped Kernel Extreme Learning Machine for Medical Diagnosis

In this study, a new predictive framework is proposed by integrating an improved grey wolf optimization (IGWO) and kernel extreme learning machine (KELM), termed as IGWO-KELM, for medical diagnosis. The proposed IGWO feature selection approach is used for the purpose of finding the optimal feature subset for medical data. In the proposed approach, genetic algorithm (GA) was firstly adopted to generate the diversified initial positions, and then grey wolf optimization (GWO) was used to update the current positions of population in the discrete searching space, thus getting the optimal feature subset for the better classification purpose based on KELM. The proposed approach is compared against the original GA and GWO on the two common disease diagnosis problems in terms of a set of performance metrics, including classification accuracy, sensitivity, specificity, precision, G-mean, F-measure, and the size of selected features. The simulation results have proven the superiority of the proposed method over the other two competitive counterparts.
Non-classical Riemann solvers with nucleation

We introduce a new non-classical Riemann solver for scalar conservation laws with concave–convex flux-function. This solver is based on both a kinetic relation, which determines the propagation speed of (under-compressive) non-classical shock waves, and a nucleation criterion, which makes a choice between a classical Riemann solution and a non-classical one. We establish the existence of (non-classical entropy) solutions of the Cauchy problem and discuss several examples of wave interactions. We also show the existence of a class of solutions, called splitting–merging solutions, which are made of two large shocks and small bounded-variation perturbations. The nucleation solvers, as we call them, are applied to (and actually motivated by) the theory of thin-film flows; they help explain numerical results observed for such flows.
Chemoprevention of intestinal tumorigenesis by nabumetone: induction of apoptosis and Bcl-2 downregulation

Treatment of MIN mice with the nonsteroidal anti-inflammatory drug, nabumetone, resulted in a dose-dependent suppression of intestinal tumorigenesis. In both the uninvolved MIN mouse colonic epithelium and HT-29 colon cancer cells, nabumetone downregulated the anti-apoptotic protein, Bcl-2, with concomitant induction of apoptosis, suggesting a potential mechanism for colon cancer chemoprevention. © 2001 Cancer Research Campaign
The role of JAGGED in shaping lateral organs

Position-dependent regulation of growth is important for shaping organs in multicellular organisms. We have characterized the role of JAGGED, a gene that encodes a protein with a single C2H2 zinc-finger domain, in controlling the morphogenesis of lateral organs in Arabidopsis thaliana. Loss of JAGGED function causes organs to have serrated margins. In leaves, the blade region is most severely affected. In sepals, petals and stamens, the strongest defects are seen in the distal regions. By monitoring cell-cycle activity in developing petals with the expression of HISTONE 4, we show that JAGGED suppresses the premature differentiation of tissues, which is necessary for the formation of the distal region. The localization of defects overlaps with the expression domain of JAGGED, which is restricted to the growing regions of lateral organs. JAGGED expression is notably absent from the cryptic bract, the remnant of a leaf-like organ that subtends the flower in many species but does not normally develop in wild-type Arabidopsis. If misexpressed, JAGGED can induce the formation of bracts, suggesting that the exclusion of JAGGED from the cryptic bract is a cause of bractless flowers in Arabidopsis.