Miracle-dz/UniFAR-FTUs huggingface dataset:
Higher probability of compound flooding from precipitation and storm surge in Europe under anthropogenic climate change

More intense precipitation will increase the flood potential from concurring storm surges and precipitation in the future. In low-lying coastal areas, the co-occurrence of high sea level and precipitation resulting in large runoff may cause compound flooding (CF). When the two hazards interact, the resulting impact can be worse than when they occur individually. Both storm surges and heavy precipitation, as well as their interplay, are likely to change in response to global warming. Despite the CF relevance, a comprehensive hazard assessment beyond individual locations is missing, and no studies have examined CF in the future. Analyzing co-occurring high sea level and heavy precipitation in Europe, we show that the Mediterranean coasts are experiencing the highest CF probability in the present. However, future climate projections show emerging high CF probability along parts of the northern European coast. In several European regions, CF should be considered as a potential hazard aggravating the risk caused by mean sea level rise in the future.
Evaluating Socio-Ecological Interactions for the Management of Protected Urban Green Spaces

Protected urban green spaces (PUGS) are exposed to numerous disturbances and threats since they are immersed in highly dynamic socio-ecological systems. PUGS in highly urbanized cities require particular conservation strategies. Here, we propose an approach for PUGS management which integrates three components: i) scientific knowledge (monitoring/restoration), ii) community interaction with the environment, and iii) management decision. Our hypothesis asserts that the intersection of these components should produce a solid management program, provided that the obtained multidisciplinary knowledge meets the needs of information required by the community and decision makers. We tested this hypothesis for a small PUGS located within Mexico City at the National Autonomous University of Mexico campus that holds the Ecological Reserve of Pedregal de San Angel. Through a participatory approach we built a mental model to understand the perceptions of different campus actors (students, academics and administrators), and their social and ecological relationships with this PUGS. Our findings provide insight into the actors’ perceptions and concerns and suggest that the interactions among the three components, although important, are not self-generated and must be constructed. The findings also suggest that one of the management problems is the mismatch between scientific knowledge and conservation programs. It is paramount to include generated knowledge into management and monitoring programs. The complexity of the PUGS requires an active collaboration among actors and monitoring the development of management strategies using the three components while taking the conservation goals into account.
Motoric Mechanisms for the Emergence of Non-local Phonological Patterns

Non-local phonological patterns can be difficult to analyze in the context of speech production models. Some patterns – e.g., vowel harmonies, nasal harmonies – can be readily analyzed to arise from temporal extension of articulatory gestures (i.e., spreading); such patterns can be viewed as articulatorily local. However, there are other patterns – e.g., nasal consonant harmony, laryngeal feature harmony – which cannot be analyzed as spreading; instead these patterns appear to enforce agreement between features of similar segments without affecting intervening segments. Indeed, there are numerous typological differences between spreading harmonies and agreement harmonies, and this suggests that there is a mechanistic difference in the ways that spreading and agreement harmonies arise. This paper argues that in order to properly understand spreading and agreement patterns, the gestural framework of Articulatory Phonology must be enriched with respect to how targets of the vocal tract are controlled in planning and production. Specifically, it is proposed that production models should distinguish between excitatory and inhibitory articulatory gestures, and that gestures which are below a selection threshold can influence the state of the vocal tract, despite not being active. These ideas are motivated by several empirical phenomena, which include anticipatory posturing before production of a word form, and dissimilatory interactions in distractor-target response paradigms. Based on these ideas, a model is developed which provides two distinct mechanisms for the emergence of non-local phonological patterns.
Progressive Training for Motor Imagery Brain-Computer Interfaces Using Gamification and Virtual Reality Embodiment

This paper presents a gamified motor imagery brain-computer interface (MI-BCI) training in immersive virtual reality. The aim of the proposed training method is to increase engagement, attention, and motivation in co-adaptive event-driven MI-BCI training. This was achieved using gamification, progressive increase of the training pace, and virtual reality design reinforcing body ownership transfer (embodiment) into the avatar. From the 20 healthy participants performing 6 runs of 2-class MI-BCI training (left/right hand), 19 were trained for a basic level of MI-BCI operation, with average peak accuracy in the session = 75.84%. This confirms the proposed training method succeeded in improvement of the MI-BCI skills; moreover, participants were leaving the session in high positive affect. Although the performance was not directly correlated to the degree of embodiment, subjective magnitude of the body ownership transfer illusion correlated with the ability to modulate the sensorimotor rhythm.
Computational Modeling of Genetic Contributions to Excitability and Neural Coding in Layer V Pyramidal Cells: Applications to Schizophrenia Pathology

Pyramidal cells in layer V of the neocortex are one of the most widely studied neuron types in the mammalian brain. Due to their role as integrators of feedforward and cortical feedback inputs, they are well-positioned to contribute to the symptoms and pathology in mental disorders—such as schizophrenia—that are characterized by a mismatch between the internal perception and external inputs. In this modeling study, we analyze the input/output properties of layer V pyramidal cells and their sensitivity to modeled genetic variants in schizophrenia-associated genes. We show that the excitability of layer V pyramidal cells and the way they integrate inputs in space and time are altered by many types of variants in ion-channel and Ca2+ transporter-encoding genes that have been identified as risk genes by recent genome-wide association studies. We also show that the variability in the output patterns of spiking and Ca2+ transients in layer V pyramidal cells is altered by these model variants. Importantly, we show that many of the predicted effects are robust to noise and qualitatively similar across different computational models of layer V pyramidal cells. Our modeling framework reveals several aspects of single-neuron excitability that can be linked to known schizophrenia-related phenotypes and existing hypotheses on disease mechanisms. In particular, our models predict that single-cell steady-state firing rate is positively correlated with the coding capacity of the neuron and negatively correlated with the amplitude of a prepulse-mediated adaptation and sensitivity to coincidence of stimuli in the apical dendrite and the perisomatic region of a layer V pyramidal cell. These results help to uncover the voltage-gated ion-channel and Ca2+ transporter-associated genetic underpinnings of schizophrenia phenotypes and biomarkers.
The Experience of Nursing Home Care: A Strong Influence on Physical Therapist Students' Work Intentions

&NA; Purpose. The general population is aging rapidly, and the need for physical therapists to serve the geriatric community is significantly increasing. There is a growing concern that students have negative attitudes toward older adults and/or toward geriatric care settings. Negative attitudes may affect the professions' ability to meet the growing demand for qualified clinicians in geriatric settings. Previous research is limited and has centered on students' and professionals' attitudes and intentions toward geriatric employment, with a focus on factors such as personal, educational, or clinical experiences that positively or negatively influence attitudes and intentions. Yet, few studies have investigated these experiences from a qualitative perspective. This qualitative study was conducted to gain in‐depth understanding of physical therapist students' educational experiences in geriatric care settings. Subjects. Fifty physical therapist students enrolled at a large southern university participated in the study. Methods and Materials. Data were gathered through focus group interviews, one‐to‐one interviews, and journals in which students described their educational experiences with geriatric physical therapy. Analyses. Data were analyzed using the constant comparative method and interpretive strategies to create a thick description of students' experiences. Methodological rigor was established through the trustworthiness and authenticity criteria espoused by Lincoln and Guba (1985). Two major themes, “caring” and “uncaring,” were the essence of students' experiences and revealed their attitudes, beliefs, intentions, and behaviors regarding geriatric physical therapy. Findings. The most significant finding was that students' negative experiences in nursing homes greatly outweighed the positive experiences, which led to negative beliefs and attitudes toward working in nursing homes. This resulted in their intentions to seek employment in other settings. Furthermore, students felt powerless to change what they believed to be negative aspects of nursing home care. Although students had positive attitudes toward elderly clients, they failed to recognize their potential to be moral change agents in this setting. This reinforced their negative view toward employment in nursing homes. The findings of this study have serious implications for geriatric education and can inform physical therapy educators, practitioners, and researchers. Knowledge of students' experiences can assist in the development of educational interventions designed to motivate and attract physical therapists to work in nursing home settings.
Evaluation of Serum Vitamin D level in patients with inflammatory bowel disease in Duhok Governorate

Background: Vitamin D deficiency is a common problem in patients with inflammatory bowel diseases (IBDs). Objectives: The aim of the current study was to measure serum Vitamin D concentrations (25 (OH) D) in patients with IBD and examine its relation to the severity of disease. Materials and Methods: This was a prospective cross-sectional study of adult patients diagnosed with IBD including ulcerative colitis and Crohn's disease compared to sex-matched controls from an outpatient clinic in a public hospital in Iraq between February 2018 and May 2018. The Vitamin D deficiency levels were assessed as below 20 ng/ml as deficient, between 20 and 30 ng/ml as insufficient, and >30 ng/ml as sufficient level. Results: Serum Vitamin D levels were measured in 145 patients including 68 patients (median age: 30.5 ± 17.25) and 77 healthy controls (median age: 52.00 ± 12.25) ranged 18–63 years. Further, the median length of disease progression was 3.0 years. Serum Vitamin D levels were significantly lower in patients (IBD or separately) compared to healthy controls. However, such significant difference was not found between patients with respect to Vitamin D and disease severity. In addition, it was confirmed that disease severity is related to Vitamin D deficiency in IBD patients. Conclusions: The current study revealed that the patients with IBD have a significantly lower level of Vitamin D compared to healthy control group. In addition, the Vitamin D deficiency is related to disease severity.
Management of Delayed Skin Necrosis Following Hyaluronic Acid Filler Injection Using Pulsed Hyaluronidase

Facial fillers are minimally invasive aesthetic procedures performed for facial rejuvenation and contouring all over the world. Fillers even in the most experienced hands can lead to fatal complications such as vascular complications that need to be managed immediately with the help of hyaluronidase protocols mentioned in literature. In this case report, a patient was asymptomatic with no signs of vascular occlusion such as blanching or poor capillary refill for 48h. He came after more than 48h of the filler injection with complaints of pulsating pain in the right infraorbital and nasolabial area. We noticed necrosed microvesicles in the infraorbital artery territory with signs of impending skin necrosis extending from right infraorbital region up to the nasolabial fold (slightly medial to it). He was treated immediately with three pulsed doses of 500 units higher dilation of 10 ml each every hour (reconstitution carried out using 3mL normal saline). The skin color improved with decreased pain, and the next day (after 14 hours) we injected 500 units of hyaluronidase in higher dilution of 10mL as slight redness was still present. Skin redness, swelling, and pain disappeared the following day. Skin was completely healed and by 15 days we noticed slight post-inflammatory hyperpigmentation, which was easily managed with Q-switched laser and creams. We hereby report a case of delayed skin necrosis (>48h) following filler injections in the cheek area, in the infraorbital artery vascular territory, which was successfully managed with pulsed dose of hyaluronidase.
Anorexia Nervosa and Osteoporosis: Pathophysiology and Treatment

Anorexia nervosa (AN) affects 2.9 million people, many of whom experience bone loss and increased fracture risk. In this article, we review data on the underlying pathophysiology of AN-related osteoporosis and possible approaches to disease management. Available research suggests that low body weight and decreased gonadal function are the strongest predictors of bone loss and fractures in patients with AN. Additionally, other metabolic disturbances have been linked to bone loss, including growth hormone resistance, low leptin concentrations, and hypercortisolemia, but those correlations are less consistent and lack evidence of causality. In terms of treatment of AN-related bone disease, weight gain has the most robust impact on bone mineral density (BMD). Restoration of gonadal function seems to augment this effect and may independently improve BMD. Bisphosphonates, insulin-like growth factor 1 supplementation, and teriparatide may also be reasonable considerations, however need long-term efficacy and safety data.
Anti-inflammatory and Regulatory Effects of Huanglian Jiedu Decoction on Lipid Homeostasis and the TLR4/MyD88 Signaling Pathway in LPS-Induced Zebrafish

Huanglian Jiedu decoction (HLJDD) has been used in the clinical treatment of inflammatory conditions. To clarify the mechanism of its comprehensive anti-inflammatory activities, the correlation between lipid homeostasis and the TLR4/MyD88 signaling pathway in zebrafish was established in the present study. In the lipopolysaccharide (LPS)-induced inflammation in zebrafish model, RT-PCR assays of five inflammatory cytokines and six targeted proteins were measured. Lipidomics analysis was conducted to identify potential lipid markers. HLJDD displayed strong efficacies, with a 61% anti-inflammatory rate at a concentration of 50 μg/mL. The activation of TLR4/MyD88 played an essential role in the inflammatory process. All protein indexes in the HLJDD group exhibited a tendency to reverse back to normal levels. Moreover, 79 potential pathological lipid biomarkers were identified. Compared with the model group, 61 therapeutic lipid biomarkers were detected in HLJDD group. Most perturbations of lipids were ameliorated by HLJDD, mainly through the glycerophospholipid metabolic pathway. In the visual network study, the corresponding lipoproteins such as PLA2, SGMS, and SMDP were observed as important intermediates between lipid homeostasis and the TLR4/MyD88 signaling pathway.
Site-Directed Fluorescence Approaches for Dynamic Structural Biology of Membrane Peptides and Proteins

Membrane proteins mediate a number of cellular functions and are associated with several diseases and also play a crucial role in pathogenicity. Due to their importance in cellular structure and function, they are important drug targets for ~60% of drugs available in the market. Despite the technological advancement and recent successful outcomes in determining the high-resolution structural snapshot of membrane proteins, the mechanistic details underlining the complex functionalities of membrane proteins is least understood. This is largely due to lack of structural dynamics information pertaining to different functional states of membrane proteins in a membrane environment. Fluorescence spectroscopy is a widely used technique in the analysis of functionally-relevant structure and dynamics of membrane protein. This review is focused on various site-directed fluorescence (SDFL) approaches and their applications to explore structural information, conformational changes, hydration dynamics, and lipid-protein interactions of important classes of membrane proteins that include the pore-forming peptides/proteins, ion channels/transporters and G-protein coupled receptors.
Simultaneous decoding of velocity and speed during executed and observed tracking movements: an MEG study

: Brain signals carry rich information about voluntary upper-limb movements. Accessing this information to control an end-effector (upper-limb, robotic arm, cursor) has been a central topic in brain-computer interface (BCI) research. To date, non-invasive BCIs based on kinematics decoding have focused on extracting partial information (i.e, single or highly correlated kinematic parameters). In this work, we show that low-frequency magnetoencephalographic (MEG) signals simultaneously carry information about multiple kinematic parameters. Using linear models, we decoded cursor velocity and speed during executed and observed tracking movements with moderate (0.2 to 0.4) correlation coefﬁ-cients (CCs). Comparing the CCs between executed and observed tracking movements, revealed that the MEG signals carried more information (0.1 higher CCs) about velocity and speed during the executed tracking movements. The higher correlations were mainly explained by increased predictive activity in primary sensorimotor areas. We could, therefore, show that non-invasive BCIs have the potential to extract multiple kinematic signals from brain activity in sensorimotor areas.
Towards Semantic Models for Profiling and Behavior Change in eHealth Applications

Behavior change is a complex process in which people receive support in order to improve aspects of their behavior, for instance regarding their health or lifestyle. Although there exist several theoretical approaches to model behavior change, including abstractions that can be applied to different use-cases, these are not easily translated into reusable components that can be integrated into implementable systems for persuasion. This work discusses the need for an ontology-based approach to modelling interactions in eHealth systems, with the goal of achieving behavior change. This contribution includes an analysis of current modelling needs in behavior change, specially regarding: stages of change, motivation & ability factors, plans & actions, argumentation, and do-
A standard language for the description of datasets obtained in experimental studies

Despite the number of data increases rapidly this does not lead to a comparable increase in knowledge. This is particularly topical for the data received in scientific research as research efforts are expensive and publicly funded. The fundamental possibility of data reuse is provided by metadata but there are a set of standards that often not consistent. Thus, if two datasets described with different standards it is not easy to integrate them. This paper proposes a language for the description of datasets obtained in behavioral experiments. The language allows connecting datasets obtained by independent research groups. The language consists of two top-level concepts – for the experimental procedure and for the resulting dataset description – and ten lower-level concepts. Each of the concepts is described by mandatory and additional characteristics. The former is necessary for the data description, while the latter improves the understanding of the dataset and its suitability for reuse. The developed language was tested on the description (and further integration) of visual search task datasets obtained by different researchers.
Spatial filters for auditory evoked potentials transfer between different experimental conditions

: To interact with the brain in closed-loop applications despite low signal-to-noise ratios, brain-computer interfaces can make use of data-driven linear spatial ﬁltering approaches to improve the single-trial classiﬁcation performance. While the transfer of spatial ﬁlters between users and within multiple sessions of the same user under the same experimental paradigm is feasible to some extent, it is unclear, whether changing experimental conditions affects this transferability. To investigate this question with regards to spatial ﬁlters, we evoke event-related potentials by an auditory odd-ball paradigm under various stimulus onset asynchronies (SOAs). Using four similarity and distance measures, we analyze the between and within subject transferability of xDAWN ﬁlters. We found that the used measures reﬂect the differences of spatial ﬁlters between subjects. Within the same subject, the measures indicate similarity of the spatial ﬁlters for almost all SOA conditions. We conclude, that our proposed measures can be used to give indications under which circumstances spatial ﬁlters can be transferred.
Evaluating Automatic Artifact correction for Online Hypothesis Testing

: In BCI, artifact removal remains an acute challenge. Filtering must be efficient in removing artifacts while preserving relevant features, e.g. event-related potentials (ERP) like the mismatch negativity (MMN). MMN is a prediction error signal whose modulations reflect human perceptual inference and learning. Characterizing these subtle processes requires fitting non-linear models onto single-trial data. And disentangling between alternative models is challenging because of a low signal-to-noise ratio. We evaluated four methods for online artifact removal. We mimicked online data processing using real electroencephalography (EEG) data from an auditory oddball paradigm. We compared the four approaches with standard offline analysis, in their ability to reveal (i) the MMN, (ii) the MMN modulations by the manipulation of the predictability of a sound sequence and (iii) the most likely learning mechanism at play. Artifact Subspace Reconstruction (ASR) and Empirical Mode Decomposition (EMD) were the most successful. Interestingly, they even proved more sensitive than the offline analysis, likely because they avoid rejecting trials.