Miracle-dz/UniFAR-FTUs huggingface dataset:
Short Term Exposure to Heat and Sediment Triggers Changes in Coral Gene Expression and Photo-Physiological Performance

Abstract Corals are known to exhibit a suite of mechanisms for survival under stressful conditions with the help of their endosymbiotic Symbiodiniaceae. However, exactly how the host animal responds to varying environmental conditions remains unclear. In this study, we tested two relevant environmental factors that are known to have deleterious effects on corals: heat and sediment. We examined among-genotype responses of Pocillopora acuta to these factors with RNA-Seq in concert with widely-used tools for assessing the physiological conditions of corals. Heat and sediment treatments were applied in a 2 × 2 crossed experimental design: (1) ~30°C without sediment (control, “C”), (2) ~30°C with sediment (sediment-only, “S”), (3) ~32°C without sediment (heat-only, “H”), (4) ~32°C with sediment (heat + sediment, “H+S”) over four consecutive days (3-h daily exposure) in ex situ aquarium conditions. A clear differentiation in gene expression patterns was observed in corals exposed to heat alone and to heat with sediment, relative to the control treatment. Few transcripts (~3) were found to be differentially expressed for corals exposed to sediment only. The greater impact of heat was supported by the photo-physiological measurements that showed significant effects on maximum quantum yield and average symbiont density among genotypes of P. acuta. The combined effect of heat and sediment caused a greater reduction in average symbiont density than the effect of sediment alone. Furthermore, “H+S” disrupted the ability of corals to maintain processes involving assembly and disassembly of cilium which suggest a synergistic effect between the two factors. We also found that host-specific genes which were expressed differentially may not be related to their interactions with algal symbionts. Rather, these genes are involved in a variety of biological functions including, but not limited to, cilium biogenesis and degradation, cilia motility, innate and adaptive immune responses, cell adhesion and bone mineralization, and processes involved in the cell cycle. These results reflect the complex response of the host alone. Overall, our findings indicate that acute heat stress in tandem with sediment can depress photo-physiological performance and trigger considerable changes in host gene expression.
Efficacy and Safety of Elbasvir/Grazoprevir in Hepatitis C Virus GT1- and GT4-Infected People Aged 65 Years or Older

Background: In elderly individuals aged ≥65 years with hepatitis C virus (HCV) infection, efficacious and safe HCV therapy is complicated by frequent comorbidities and concomitant medications. The aim of this analysis was to evaluate the efficacy and safety of elbasvir/grazoprevir (EBR/GZR) in people aged ≥65 years. Methods: This is an integrated retrospective analysis of EBR/GZR administered for 12 weeks in participants with HCV genotype 1 or 4 infection enrolled in 12 Phase 2/3 clinical trials. The primary end point was sustained virologic response 12 weeks after completing therapy (SVR12; HCV RNA below the lower limit of quantification). Results: Most participants aged ≥65 years were receiving ≥1 concomitant medication (322/339; 95.0%) and had ≥1 comorbidity (334/339; 99%). SVR12 rates were 95.3% (323/339) in participants aged ≥65 years and 95.4% (2,041/2,139) in those aged <65 years. Rates of adverse events, drug-related adverse events, serious adverse events, and discontinuations were similar in participants aged ≥65 years and those aged <65 years. In participants aged ≥65 years, median estimated glomerular filtration rate was similar at baseline and at the end of treatment. Conclusion: The efficacy and safety of EBR/GZR were similar in participants with HCV infection aged ≥65 years and those aged <65 years.
Geographic variation in thermal sensitivity of early life traits in a widespread reptile

Abstract Taxa with large geographic distributions generally encompass diverse macroclimatic conditions, potentially requiring local adaptation and/or phenotypic plasticity to match their phenotypes to differing environments. These eco‐evolutionary processes are of particular interest in organisms with traits that are directly affected by temperature, such as embryonic development in oviparous ectotherms. Here we examine the spatial distribution of fitness‐related early life phenotypes across the range of a widespread vertebrate, the painted turtle (Chrysemys picta). We quantified embryonic and hatchling traits from seven locations (in Idaho, Minnesota, Oregon, Illinois, Nebraska, Kansas, and New Mexico) after incubating eggs under constant conditions across a series of environmentally relevant temperatures. Thermal reaction norms for incubation duration and hatchling mass varied among locations under this common‐garden experiment, indicating genetic differentiation or pre‐ovulatory maternal effects. However, latitude, a commonly used proxy for geographic variation, was not a strong predictor of these geographic differences. Our findings suggest that this macroclimatic proxy may be an unreliable surrogate for microclimatic conditions experienced locally in nests. Instead, complex interactions between abiotic and biotic factors likely drive among‐population phenotypic variation in this system. Understanding spatial variation in key life‐history traits provides an important perspective on adaptation to contemporary and future climatic conditions.
The geometry of habitat fragmentation: Effects of species distribution patterns on extinction risk due to habitat conversion

Abstract Land‐use changes, which cause loss, degradation, and fragmentation of natural habitats, are important anthropogenic drivers of biodiversity change. However, there is an ongoing debate about how fragmentation per se affects biodiversity in a given amount of habitat. Here, we illustrate why it is important to distinguish two different aspects of fragmentation to resolve this debate: (a) geometric fragmentation effects, which exclusively arise from the spatial distributions of species and habitat fragments, and (b) demographic fragmentation effects due to reduced fragment sizes, and/or changes in fragment isolation, edge effects, or species interactions. While most empirical studies are primarily interested in quantifying demographic fragmentation effects, geometric effects are typically invoked as post hoc explanations of biodiversity responses to fragmentation per se. Here, we present an approach to quantify geometric fragmentation effects on species survival and extinction probabilities. We illustrate this approach using spatial simulations where we systematically varied the initial abundances and distribution patterns (i.e., random, aggregated, or regular) of species as well as habitat amount and fragmentation per se. As expected, we found no geometric fragmentation effects when species were randomly distributed. However, when species were aggregated, we found positive effects of fragmentation per se on survival probability for a large range of scenarios. For regular species distributions, we found weakly negative geometric effects. These findings are independent of the ecological mechanisms which generate nonrandom species distributions. Our study helps to reconcile seemingly contradictory results of previous fragmentation studies. Since intraspecific aggregation is a ubiquitous pattern in nature, our findings imply widespread positive geometric fragmentation effects. This expectation is supported by many studies that find positive effects of fragmentation per se on species occurrences and diversity after controlling for habitat amount. We outline how to disentangle geometric and demographic fragmentation effects, which is critical for predicting the response of biodiversity to landscape change.
Experimental test of birdcall detection by autonomous recorder units and by human observers using broadcast

Abstract Autonomous recording units are now routinely used to monitor birdsong, starting to supplement and potentially replace human listening methods. However, to date there has been very little systematic comparison of human and machine detection ability. We present an experiment based on broadcast calls of nocturnal New Zealand birds in an area of natural forest. The soundscape was monitored by both novice and experienced humans performing a call count, and autonomous recording units. We match records of when calls were broadcast with detections by both humans and machines, and construct a hierarchical generalized linear model of the binary variable of correct detection or not, with a set of covariates about the call (distance, sound direction, relative altitude, and line of sight) and about the listener (age, experience, and gender). The results show that machines and humans have similar listening ability. Humans are more homogeneous in their recording of sounds, and this was not affected by their individual experience or characteristics. Humans were affected by trial and location, in particular one of the stations located in a small but deep valley. Despite recorders being affected significantly more than people by distance, altitude, and line of sight, their overall detection probability was higher. The specific location of recorders seems to be the most important factor determining what they record, and we suggest that for best results more than one recorder (or at least, microphone) is needed at each station to ensure all bird sounds of interest are captured.
Gender Differences in Polychronicity

Polychronicity refers to a personal preference to engage in multitasking. In the current study, we investigated whether male and female participants differed in polychronicity. For this, 167 participants filled out an online questionnaire assessing polychronicity in a variety of ways, including the Multitasking Preference Inventory (MPI). Results showed that women were consistently more polychronic than men. We also found that women showed higher self-rated multitasking abilities, reported to spend more time multitasking, and considered multitasking to be more important in everyday life than men. We conclude that in our sample, which mainly consisted of University students in the United Kingdom, polychronicity shows a significant gender difference.
The behavioural inhibition system, behavioural activation system and experiential avoidance as explanatory variables of comorbid chronic pain and posttraumatic stress symptoms

ABSTRACT Background: The variables that underlie comorbid chronic pain and posttraumatic stress symptoms (PTSS) are not yet clearly established. Objective: The aim of the present study was to analyse the role of the behavioural inhibition system (BIS), behavioural approach system (BAS) and experiential avoidance (EA) in pain adjustment (i.e. pain intensity, daily functioning and pain-related impairment) in patients with chronic pain and PTSS. Methods: A battery of instruments was administered to 388 chronic pain patients. The sample was divided into those with PTSS (n = 194) and those without PTSS (n =194). Results: Significant differences were found between groups in the BIS, EA, impairment and daily functioning. No differences were found between groups in the BAS. Structural equation modelling showed that the BIS and EA were associated with worse adjustment in the 194 patients with both chronic pain and PTSS. The BAS was associated with a lower level of pain and greater daily functioning. Conclusion: The findings provide evidence that BIS and BAS activation and EA play a role in adjustment to chronic pain in patients with concurrent PTSS. These results may help guide the development of psychological treatments for patients with both conditions. HIGHLIGHTS • This is the first study to examine the role of the behavioural inhibition system, the behavioural activation system, experiential avoidance in comorbid chronic pain and posttraumatic stress symptoms. • Differences between patients with and without posttraumatic stress symptoms in behavioural inhibition system and experiential avoidance were found, thus providing a preliminary comprehensive framework for understanding the co-occurrence of both disorders. • The findings may help guide the development of psychological treatments for patients with both conditions.
On Challenges in Machine Learning Model Management

The training, maintenance, deployment, monitoring, organization and documentation of machine learning (ML) models – in short model management – is a critical task in virtually all production ML use cases. Wrong model management decisions can lead to poor performance of a ML system and can result in high maintenance cost. As both research on infrastructure as well as on algorithms is quickly evolving, there is a lack of understanding of challenges and best practices for ML model management. Therefore, this ﬁeld is receiving increased attention in recent years, both from the data management as well as from the ML community. In this paper, we discuss a selection of ML use cases, develop an overview over conceptual, engineering, and data-processing related challenges arising in the management of the corresponding ML models, and point out future research directions.
Amprolium exposure alters mice behavior and metabolism in vivo

Thiamine deficiency (TD) models have been developed, mainly using the thiamine analog pyrithiamine. Other analogs have not been used in rodents. We aimed to evaluate the effects and mechanisms of intraperitoneal (ip) amprolium‐induced TD in mice. We also evaluated the associated pathogenesis using antioxidant and anti‐inflammatory compounds (Trolox, dimethyl sulfoxide).
Alcohol Induces More Severe Fatty Liver Disease by Influencing Cholesterol Metabolism

Objectives. Fatty liver disease (FLD) is a major cause of morbidity and mortality worldwide. Dietary cholesterol and alcohol consumption are important risk factors for the progression of FLD, but whether and how alcohol induces more severe FLD with cholesterol ingestion remain unclear. Herein, we mainly used the Lieber-DeCarli diet to establish the FLD mouse model to investigate the synergistic effects of alcohol and cholesterol metabolism on liver damage. The indices of aspartate transaminase (AST), alanine transaminase (ALT), low-density lipoprotein cholesterol (LDL-c), and total cholesterol (TC) levels, inflammation foci, and pathogenesis by hematoxylin and eosin (H&E) and Oil Red O staining revealed that alcohol induces more severe liver damage by influencing cholesterol metabolism, which might be primarily related to the influence of cholesterol absorption, synthesis, and excretion on the liver or small intestine. Moreover, inhibition of absorption of intestinal cholesterol, but not of fat, sucrose, and alcohol, absorption into the body's metabolism by Ezetimibe, significantly improved FLD in rats fed with the high fat-cholesterol-sucrose and alcohol diet. These results showed that alcohol plays an important role in cholesterol metabolism in FLD.
Analysing graphene vibrations via molecular dynamics simulations and dimension reduction techniques

Graphene was first isolated in the lab in 2003 and this work was first published in 2004 by a research team at The University of Manchester. Since that date, graphene research has exploded due to its special properties. Phonons and molecular dynamic simulation provide valuable tools to study the molecular systems under different structure forms. They are helpful to study graphene ribbons and defects. On the other hand, many machine learning techniques were extensively used to analyse the enormous amounts of data resulted from the molecular simulations. As such, this thesis aimed to use one of the machine learning techniques to study phonons of graphene with single vacancy defect and graphene armchair nanoribbons. PCA can be used to transform the atomic velocities into orthogonal eigenvectors such that each eigenvector represents one of the phonon modes of graphene. This is helpful to visualize the atomic motion of a specific phonon mode. To provide orthogonal eigenvectors, PCA needs the data to be of gaussian distribution. The atomic velocities resulted from the molecular simulations follow gaussian distribution at the equilibrium state. Hence, the assumption of gaussian distribution needed by PCA is achieved. However, only some of the phonon modes can be calculated from the atomic velocities in their real space. Most of the phonon modes are calculated after transforming the atomic velocities to a reciprocal space (k space) using spatial Fourier transform. The k space atomic velocities are not following gaussian distribution. This thesis introduced a novel method to use PCA to isolate and visualize the phonon modes extracted from the k space velocities. To prove the feasibility of using PCA to isolate k space phonons, we conducted classical molecular simulations of graphene with different structures. The effect of single vacancy defect on graphene phonons was studied in comparison to the perfect graphene. In addition, the effect of the armchair ribbon width on graphene phonon modes was investigated. The results of the conducted molecular simulations were used with PCA to visualize some of the phonon modes of pristine graphene and armchair nanoribbons of graphene. We used PCA to present the evolution of the atomic motion of specific k space phonon modes of armchair ribbons: the first overtone of TA phonon mode and the highest overtone of TO phonon mode. The presented motions showed that the breathing like mode is a transition state between two opposite atomic motions of TA mode. In the method we introduced using PCA, we used the eigenvectors with the lowest eigenvalues to study the Fourier transformed atomic velocities. This method rotated the k space atomic velocities into the eigenvectors with the lowest eigenvalues which helped to isolate and visualize the k space phonon modes.
Anti‐leukemic and anti‐angiogenic effects of d‐Limonene on K562‐implanted C57BL/6 mice and the chick chorioallantoic membrane model

d‐Limonene, a monoterpene from citrus fruit has been found to have chemopreventive and chemotherapeutic activities in various types of cancers. In this study, we evaluated the in vivo effect of d‐Limonene on a K562‐induced model of chronic myeloid leukemia (CML) in C57BL/6 mice.
Studying and supporting activity awareness in collaborative learning groups: using a persuasive social actor

Collaborative learning is known as an effective learning method and various different kinds of technologies have been developed to support and facilitate collaborative learning. Many of these technologies are used to support the functional activities of a group of learners by enabling students to communicate, share documents and materials, track the work of the group, or distribute and allocate tasks. One factor that influences the success of collaborative groups is the awareness that members have of each others' activities i.e. activity awareness (Gutwin et al., 2004). Limited attention has been paid to promoting activity awareness in the collaborative learning literature. The work that does exist has focused on enhancing activity awareness by capturing and sharing details of the activity (e.g. Ganoe et al., 2003; Carroll et al., 2003). In contrast, there are no technologies that focus on the learners’ attitudes and behaviours with regard to activity awareness without considering the functional aspects of the group's work. This PhD hypothesises that persuasive technologies can offer a novel way of promoting activity awareness by changing learners’ attitudes and behaviours and persuading them to be more aware of fellow group members’ activities. This approach to enhancing activity awareness was investigated by using a persuasive social actor to change the attitudes and behaviours of learners who were working on collaborative learning projects over extended periods of time. Four studies were conducted: a pilot study to explore collaborative learning groups, an exploratory study to understand collaboration and activity awareness, a follow-up study to study activity awareness in depth, and a main study where a persuasive social actor for activity awareness in collaborative learning groups was developed and tested. All of these studies focused on a specific collaborative learning setting, in which small numbers of students (3 to 5) worked together in collaborative groups to complete real learning projects over approximately 6 weeks. This thesis makes four contributions to the fields of HCI and collaborative learning. The main contribution is a novel approach to enhance activity awareness in collaborative learning groups by changing learners’ attitudes and behaviours using a persuasive technology i.e. a persuasive social actor. The second contribution is a new method to evaluate activity awareness in collaborative learning groups. The third contribution is insight into how the Persuasive Systems Design (PSD) model (Oinas-kukkonen & Harjumaa, 2009) can be used in the design and evaluation of a persuasive social actor. The fourth contribution is an analysis of how students collaborate in long-term collaborative learning projects in naturalistic settings.
Ontology learning from the Arabic text of the Qur'an: concepts identification and hierarchical relationships extraction

Recent developments in ontology learning have highlighted the growing role ontologies play in linguistic and computational research areas such as language teaching and natural language processing. The ever-growing availability of annotations for the Qur’an text has made the acquisition of the ontological knowledge promising. However, the availability of resources and tools for Arabic ontology is not comparable with other languages. Manual ontology development is labour-intensive, time-consuming and it requires knowledge and skills of domain experts. This thesis aims to develop new methods for Ontology learning from the Arabic text of the Qur’an, including concepts identification and hierarchical relationships extraction. The thesis presents a methodology for reducing human intervention in building ontology from Classical Arabic Language of the Qur’an text. The set of concepts, which is a crucial step in ontology learning, was generated based on a set of patterns made of lexical and inflectional information. The concepts were identified based on adapted weighting schema that exploit a combination of knowledge to learn the relevance degree of a term. Statistical, domain-specific knowledge and internal information of Multi-Word Terms (MWTs) were combined to learn the relevance of generated terms. This methodology which represents the major contribution of the thesis was experimentally investigated using different terms generation methods. As a result, we provided the Arabic Qur’anic Terms (AQT) as a training resource for machine learning based term extraction. This thesis also introduces a new approach for hierarchical relations extraction from Arabic text of the Qur’an. A set of hierarchical relations occurring between identified concepts are extracted based on hybrid methods including head-modifier, set of markers for copula construct in Arabic text, referents. We also compared a number of ontology alignment methods for matching ontological bilingual Qur’anic resources. In addition, a multi-dimensional resource named Arabic Qur’anic Database (AQD) about the Qur’an is made for Arabic computational researchers, allowing regular expression query search over the included annotations. The search tool was successfully applied to find instances for a given complex rule made of different combined resources.