Miracle-dz/UniFAR-FTUs huggingface dataset:
Abnormal liver tests in admitted patients with SARS-Cov-2 or other respiratory viruses- prognostic similarities and temporal disparities

Background and Aims: Abnormal liver tests are common in patients with severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) infection, but their association with short-term outcomes is controversial. We aimed to compare the pattern of abnormal liver tests in SARS-CoV-2 patients with those of patients infected with influenza or respiratory syncytial virus (RSV), two non-hepatotropic respiratory viruses, and their association with in-hospital mechanical ventilation or death. Methods: A retrospective cohort study of 1271 hospitalized patients (872 influenza, 218 RSV, and 181 SARS-Cov-2) in a tertiary medical center. We defined abnormal liver tests as GPT, GOT or GGT[≥]40IU/ML at any time-point during hospitalization. Results: Abnormal liver tests were mild-moderate in the majority of patients regardless of infection type but the majority of patients with influenza or RSV had a transaminases peak earlier during hospitalization compared to patients with SARS-Cov-2. Abnormal liver tests correlated with markers of severe disease across all types of infections, and were associated with mechanical ventilation or death, occurring mainly in patients with severe liver tests abnormalities (>200IU/L) (27.2%, 39.4% and 55.6% of patients with influenza, RSV or SARS-Cov-2). In multivariate analysis, controlling for age, gender, lymphopenia and CRP, liver tests abnormalities remained significantly associated with mechanical ventilation or death for influenza (OR= 3.047, 95% CI 1.518-6.117) and RSV (OR= 3.402, 95% CI 1.032- 11.220) but not for SARS-Cov-2 (OR= 0.995, 95% CI 0.198-4.989). These results were confirmed upon propensity score matching. Conclusions: Abnormal liver tests during hospitalization with different viral respiratory infections are common, may differ in their time-course and reflect disease severity. They are associated with worse outcomes, mainly in patients with severe liver test abnormalities, regardless of infection type.
Part I: Accuracy of Teledermatology in Inflammatory Dermatoses

Teledermatology is assuming a progressively greater role as a healthcare delivery method, especially now, during this pandemic time. It is important to know how accurate this tool is for different skin diseases. Most of the studies have focused on skin neoplasms or general dermatology. Studies based on a large number of inflammatory dermatoses have not yet been performed. Such knowledge can help dermatologists to decide whether endorsing this method or not. Our objective was to determine the accuracy of teledermatology in inflammatory dermatoses in a robust number of cases. A retrospective cohort study was conducted in São Paulo, Brazil, from July 2017–18, where a store-and-forward Teledermatology project was implemented under primary-care attention to triage surgical, more complex, or severe dermatoses. A total of 30,976 patients presenting 55,012 lesions took part in the project. Thirteen participating teledermatologists had three options to refer the patients: directly to biopsy, to the in-person dermatologist or back to the general physician with most probable diagnosis and management. In the group referred to the in-person dermatologist, we looked for the 20 most frequent International Classification of Diseases and Related Health Problems- 10th revision (ICD-10) of inflammatory dermatoses, which resulted in 739 patients and 739 lesions. As patients had been triaged by teledermatology previously, we were able to compare ICD-10 codes filled both by teledermatogists and by in-person dermatologists. The proportion of complete, partial, and no agreement rates between the in-person dermatologist's and the teledermatologist's diagnoses was used for accuracy. We also calculated Cohen's kappa, a statistical measure of inter-rater agreement, for complete agreement. The mean complete agreement rate for all twenty dermatoses was 78% (31–100%) and kappa = 0.743; partial agreement 8%; and no agreement 14%, presenting variability according to the disease. Our study showed that teledermatology for inflammatory dermatoses has a high accuracy. This result reassures that it can be a proper option for patient care.
EspcTM: Kinetic Transition Network Based on Trajectory Mapping in Effective Energy Rescaling Space

The transition network provides a key to reveal the thermodynamic and kinetic properties of biomolecular systems. In this paper, we introduce a new method, named effective energy rescaling space trajectory mapping (EspcTM), to detect metastable states and construct transition networks based on the simulation trajectories of the complex biomolecular system. It mapped simulation trajectories into an orthogonal function space, whose bases were rescaled by effective energy, and clustered the interrelation between these trajectories to locate metastable states. By using the EspcTM method, we identified the metastable states and elucidated interstate transition kinetics of a Brownian particle and a dodecapeptide. It was found that the scaling parameters of effective energy also provided a clue to the dominating factors in dynamics. We believe that the EspcTM method is a useful tool for the studies of dynamics of the complex system and may provide new insight into the understanding of thermodynamics and kinetics of biomolecular systems.
Fostering the Mediating Role of the Feeling of Belonging to an Organization Among Romanian Members of Generation Z

Abstract The addition of Generation Z/Centennials to the workplace landscape will bring about new challenges for the management of any organization. To tackle the changing work environment and workforce, we conducted a survey-based empirical exploratory study among students in economics from two universities located in the western part of Romania. Our study proposes an alternative view of the motivational potential, including the feeling of belonging to an organization in work settings. The aim was to explore the potential for the feeling of belonging to play the role of mediator between four distinct career attitudes and the turnover intention in the specific case of Romanian Generation Z members. Additionally, we investigated which variables are significant predictors for the feeling of belonging to an organization. The results indicate that is efficient to invest in creating belongingness for those Generation Z members inclined towards making moves between jobs and organizations (OMPA), for those who present the mental capacity to be mobile (BMA) and for those who can be adaptive in terms of performance and learning demands (SDA). For those Romanian Generation Z members who use their internal values to provide guidance and measure for success, including the feeling of belonging to an organization in work settings seems to be inefficient.
Supporting the evolution of applications deployed on edge-based infrastructures using multi-layer feature models

The proliferation of cyber-physical systems has encouraged the emergence of new technologies and paradigms to improve the performance of IoT-based applications. Edge Computing proposes using the nearby devices in the frontier/Edge of the access network for deploying application tasks. However, the functionality of cyberphysical systems, which is usually distributed in several devices and computers, imposes specific requirements on the infrastructure to run properly. The evolution of an application to meet new user requirements and the high diversity of hardware and software technologies in the edge can complicate the deployment of evolved applications. The aim of our approach is to apply Multi Layer Feature Models, which capture the variability of applications and the infrastructure, to support the deployment in edge-based environments of cyber-physical systems applications. This separation can support the evolution of application and infrastructure. Considering that IoT/Edge/Cloud infrastructures are usually shared by many applications, the SPL deployment process has to assure that there will be enough resources for all of them, informing developers about the alternatives of deployment. Prior to its deployment and leaning on the infrastructure feature models, the developer can calculate what is the configuration of minimal set of devices supporting application requirements of the evolved application. In addition, the developer can find which is the application configuration that can be hosted in the current evolved infrastructure.
Research on Recognition of Shoulder Joint Movement Imagination Based on BCI Technology

In the research of brain-computer interface (BCI) technology, it is difficult to recognize electroencephalogram (EEG) signals induced by different movements of a single joint. In response to this situation, this paper proposes the use of empirical mode decomposition (EMD) to obtain the intrinsic mode function (IMF), combining amplitude-frequency (AF) domain information in the IMF with the common spatial pattern (CSP) to propose the AF-CSP construction shoulder. The eigenvectors of the three types of joints imaginary EEG signals are classified and recognized by the twin support vector machine. The experimental results show that the accuracy rate of the feature vectors constructed by the AF-CSP method proposed in this paper is 89.7 percent recognized by the twin support vector machine, which proves the effectiveness of the method and can be further used in brain-computer interfaces.
The Role of Hypothermia in Large Hemispheric Infarction: A Systematic Review and Meta-Analysis

Background: Hypothermia is used in the treatment of large hemispheric infarction (LHI); however, its role in outcomes for LHI patients remains ambiguous. This systematic review and meta-analysis was conducted to evaluate the effect of hypothermia on the outcomes of LHI patients. Methods: We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, China Biological Medicine Database, and clinical trials registers before September 21, 2018, and then scanned the reference lists. Randomized controlled trials that compared hypothermia with normothermia in LHI patients were included. Primary outcomes that we reviewed were mortality and neurological outcome. Adverse events during treatment were defined as secondary outcomes. We performed a meta-analysis to calculate pooled risk ratios (RRs), standardized mean differences (SMDs), and 95% confidence intervals (CIs) using fixed-effect models. Results: Three randomized controlled trials involving 131 participants were included. No statistically significant association was revealed between hypothermia and mortality (RR, 1.12; 95% CI, 0.76–1.65). There was significant association between hypothermia and good neurological outcome as assessed by modified Rankin Scale score (mRS of 0–3) of survivors (RR, 2.09; 95% CI, 1.14–3.82), and with neurological outcome by mRS (SMD, −0.54; 95% CI, −1.07 to −0.01). However, significant associations were found between hypothermia and gastrointestinal bleeding, gastric retention, electrolyte derangement, and shivering. No significant differences were detected in the incidence of developing herniation in the rewarming process, pneumonia, cardiac arrhythmia, hemorrhagic transformation, hyperglycemia, hypotension, acute kidney injury, and venous thrombotic events in LHI patients who underwent hypothermia compared with those who had normothermia. Conclusions: This meta-analysis suggested that hypothermia was not associated with mortality in LHI patients. However, it was associated with the improvement of neurological outcome, but with a higher risk of adverse events during treatment. Future studies are needed to demonstrate the efficacy and safety of hypothermia for LHI. The protocol for this systematic review was obtained from PROSPERO (registration number: CRD42018111761).
Towards a model driven formal approach for merging data, access control and business processes

Information Systems (IS) are mostly built on three major concerns: data, security and business processes. Dealing with the correctness of these concerns makes the IS more efficient, which is of a great importance for organizations, given the impact their IS can have on their productivity. However, these concerns are often defined by different stakeholders leading to several inconsistencies between the resulting artifacts. This paper outlines our model driven approach to align and formally analyze in a decoupled way the Unified Modeling Language (UML) for data modeling, Role-based Access Control (RBAC) for security policies definition and the Business Process Model and Notation (BPMN) for process modeling. Several works addressed the integration of BPMN and UML or BPMN and Security, but none of them tried to make the bridge between the three concerns in a unified framework in order to formally establish their consistency. In this ongoing work we propose two kinds of formal analysis: the static analysis that deals with the structural properties of the three concerns, and the dynamic analysis, which is intended to apply the B method and underlying formal reasoning tools in order to animate processes and formally check their feasibility regarding data and security.
Elucidating the Surface Functionality of Biomimetic RGD Peptides Immobilized on Nano-P(3HB-co-4HB) for H9c2 Myoblast Cell Proliferation

Biomaterial scaffolds play crucial role to promote cell proliferation and foster the regeneration of new tissues. The progress in material science has paved the way for the generation of ingenious biomaterials. However, these biomaterials require further optimization to be effectively used in existing clinical treatments. It is crucial to develop biomaterials which mimics structure that can be actively involved in delivering signals to cells for the formation of the regenerated tissue. In this research we nanoengineered a functional scaffold to support the proliferation of myoblast cells. Poly(3-hydroxybutyrate-co-4-hydroxybutyrate) [P(3HB-co-4HB)] copolymer is chosen as scaffold material owing to its desirable mechanical and physical properties combined with good biocompatibility, thus eliciting appropriate host tissue responses. In this study P(3HB-co-4HB) copolymer was biosynthesized using Cupriavidus malaysiensis USMAA1020 transformant harboring additional PHA synthase gene, and the viability of a novel P(3HB-co-4HB) electrospun nanofiber scaffold, surface functionalized with RGD peptides, was explored. In order to immobilize RGD peptides molecules onto the P(3HB-co-4HB) nanofibers surface, an aminolysis reaction was performed. The nanoengineered scaffolds were characterized using SEM, organic elemental analysis (CHN analysis), FTIR, surface wettability and their in vitro degradation behavior was evaluated. The cell culture study using H9c2 myoblast cells was conducted to assess the in vitro cellular response of the engineered scaffold. Our results demonstrated that nano-P(3HB-co-4HB)-RGD scaffold possessed an average fiber diameter distribution between 200 and 300 nm, closely biomimicking, from a morphological point of view, the structural ECM components, thus acting as potential ECM analogs. This study indicates that the surface conjugation of biomimetic RGD peptide to the nano-P(3HB-co-4HB) fibers increased the surface wettability (15 ± 2°) and enhanced H9c2 myoblast cells attachment and proliferation. In summary, the study reveals that nano-P(3HB-co-4HB)-RGD scaffold can be considered a promising candidate to be further explored as cardiac construct for building cardiac construct.
Gene Regulatory Networks of Penicillium echinulatum 2HH and Penicillium oxalicum 114-2 Inferred by a Computational Biology Approach

Penicillium echinulatum 2HH and Penicillium oxalicum 114-2 are well-known cellulase fungal producers. However, few studies addressing global mechanisms for gene regulation of these two important organisms are available so far. A recent finding that the 2HH wild-type is closely related to P. oxalicum leads to a combined study of these two species. Firstly, we provide a global gene regulatory network for P. echinulatum 2HH and P. oxalicum 114-2, based on TF-TG orthology relationships, considering three related species with well-known regulatory interactions combined with TFBSs prediction. The network was then analyzed in terms of topology, identifying TFs as hubs, and modules. Based on this approach, we explore numerous identified modules, such as the expression of cellulolytic and xylanolytic systems, where XlnR plays a key role in positive regulation of the xylanolytic system. It also regulates positively the cellulolytic system by acting indirectly through the cellodextrin induction system. This remarkable finding suggests that the XlnR-dependent cellulolytic and xylanolytic regulatory systems are probably conserved in both P. echinulatum and P. oxalicum. Finally, we explore the functional congruency on the genes clustered in terms of communities, where the genes related to cellular nitrogen, compound metabolic process and macromolecule metabolic process were the most abundant. Therefore, our approach allows us to confer a degree of accuracy regarding the existence of each inferred interaction.
X-YOLO: A deep learning based toolset with multiple optimization strategies for contraband detection

Observing X-ray images manually is a common method for detecting contraband in packages. Long-term continuous observation is prone to visual fatigue, leading to problems of missed detection and false detection. Motivated by aiding operators in contraband detection in packages, we propose X-YOLO which is a deep learning based toolset with multiple optimization strategies for contraband detection to increase the detection precision. The path enhancement is designed to shorten the information path between the lower layer and the uppermost layer. We replace Leaky ReLU with Swish and Steps with SGDR to make training stable. Mixup, a dataset-independent method for data augmentation, is designed to increase the amount of training data for improving the generalization of model without expert knowledge. In order to solve the issue that Intersection over Union (IoU) can not deal with two non-overlapping objects, we apply Generalized Intersection over Union (GIoU) as bounding box losses. The experimental results show that X-YOLO achieves mAP up to 96.02% and recall up to 98.55%, surpassing Faster R-CNN, SSD, YOLOv1, YOLOv2, Tiny-YOLO, YOLOv3, YOLOv3-tiny, YOLOv3-spp and YOLOv3 with some of optimization strategies.
The Use of Scenarios in a Vision Seminar Process: The Case of Students Envisioning the Future of Study-Administration

In this paper we present a Vision Seminar Process (VSP) inspired by Future Workshops and core values from the Participatory Design tradition and the application of this process at Swedish university for the purpose of envisioning the future of study-administrative work and supporting technical systems for students. We present and discuss the use of scenarios in this process as well as an extension of the original VSP where the scenarios authored by participating students have been combined into one combined scenario by the authors of this paper. Possible implications and lessons learned from this experiment and potential uses for the resulting combined scenario are discussed before concluding with a brief discussion of the implications of the actual contents of the combined scenario.
Welfare parameters in dairy cows reared in tie-stall and open-stall farming systems: pilot study.

Animals can experience pain or distress as a result of widely accepted management practices. In dairy cattle, housing system can affect animal welfare. The assessment of animal welfare requires the use of multiple indicators in order to analyse the heterogeneity of the aspects involved. The aim of this study was to compare the welfare of dairy cows reared in a tie-stall (TS) and open-stall (OS) system by metabolic, immunological and stress related parameters. The study involved 80 pluriparous lactating cows belonging to eight dairy farms located in the area of Mugello (Florence, Italy) reared in TS and OS systems. Ten blood samples were collected at morning time to measure ala-nine-aminotransferase (ALT), aspartate-aminotransferase (AST), blood urea nitrogen (BUN), β-hydroxybutyrate (BHBA), creatinine (Creat), non-esterified fatty acids (NEFA), total proteins (TP), calcium (Ca), phosphorus (P), and potassium (K), serum lisozyme (SL), bactericidal activity (SBA), haptoglobin (Hp), oxygen free radicals (OFR), and hair cortisol levels. At the same time a body condition score (BCS) was recorded. Statistical analysis was performed by ANOVA. The experiment was carried out in accordance with European Commission regulations (Directive 2010/63/EC and Directive 98/58/EC). The results showed that the housing system affected various parameters such as ALT, BHBA, OFR, cortisol (P≤0.01) and AST, BUN (P≤0.05). Most of these parameters showed mean values within the range of reference without revealing any signs of suffering. An interesting outcome regarded the OFR levels, which was higher in the OS system (68.2±34.51 U.Carr. vs 36.1±21.39 U.Carr.), probably as a consequence of the high productive effort. In conclusion, it is possible to state that TS did not show a comparable overall situation with serious signs of welfare impairment.
Land management impacts on soil properties and initial soil erosion processes in olives and vegetable crops

Abstract This research aims to assess the impacts of soil use management on runoff, soil losses, and their main soil controls in vegetable cropland (CROP), tilled olives (OT), and grass-covered olive orchards (OGC) on Leptosol in Croatia. Soil analysis and rainfall simulation experiments were conducted to quantify runoff (Run), soil, and nutrient losses. Bulk density (BD) was significantly higher at OT plots, in addition to the CROP plots. Water-stable aggregates (WSA), mean weight diameter (MWD), and soil organic matter (OM) were significantly higher in OGC plots compared to the other land uses. Run and soil loss (SL) were significantly higher in CROP and OT plots compared to the OGC plots. The CROP plots showed soil management that can be considered as unsustainable with 52, 68- and 146-times higher losses of phosphorus (P loss), nitrogen (N loss), and carbon (C loss) compared to the OGC plots. The principal component analysis showed that MWD was associated with vegetation cover (VC), water-holding capacity (WHC), WSA, OM, total nitrogen (TN), time to ponding (TP), and time to runoff (TR). These variables were negatively related to P2O5, Run, SL, and P, N, and C loss. Results indicate the need for the adoption of conservation strategies in croplands and olive orchards.
Approaches to the Profiling Fake News Spreaders on Twitter Task in English and Spanish

This paper discusses the decisions made approaching PANs Proﬁling Fake News Spreaders on Twitter Task at CLEF 2020. We brieﬂy describe how we combined author tweets to create samples that do or do not represent a Fake News Spreader. We decided to handle both languages proposed for this task: Spanish and English; and the methodologies that we suggested were Linear Support Vector Machines (SVMs) and Gradient Boosting, respectively. Other approaches such as Long Short-Term Memory (LSTM) were taken into account in the process of ﬁnding a model with the best accuracy results and these were also reported in this paper. We made use of the cross-validation scenario to obtain accuracy results due to the reduced amount of data. We have managed to achieve average accuracy scores of 0.735 for the Spanish language identiﬁcation task and 0.685 for the English language identiﬁcation task.