Miracle-dz/UniFAR-FTUs huggingface dataset:
Fritz, Hans and Ray, Nicola and Dyrba, Martin and Sorg, Christian and Teipel, Stefan and Grothe, Michel (2018)The corticotopic organization of the human basal forebrain as revealed by regionally selective functional connectivity

The cholinergic basal forebrain (CBF), comprising different groups of cortically projecting cholinergic neurons, plays a crucial role in higher cognitive processes and has been implicated in diverse neuropsychiatric disorders. A distinct corticotopic organization of CBF projections has been revealed in animal studies, but little is known about their organization in the human brain. We explored regional differences in functional connectivity (FC) profiles within the human CBF by applying a clustering approach to resting-state functional MRI (rsfMRI) data of healthy adult individuals of both sexes (N=85; 19-85y). We further examined effects of age on FC of the identified CBF clusters, and assessed the reproducibility of cluster-specific FC profiles in independent data from healthy older individuals (N=25; 6589y). Results showed that the human CBF is functionally organized into distinct anteriormedial and posterior-lateral subdivisions that largely follow anatomically defined boundaries of the medial septum/diagonal band and nucleus basalis Meynert (NBM), respectively, with a transitional zone in the anterior-medial NBM. The anterior-medial CBF subdivision was characterized by connectivity with the hippocampus and interconnected nodes of an extended medial cortical memory network, whereas the posterior-lateral subdivision was specifically connected to anterior insula and dorsal anterior cingulate components of a salience/attention network. FC of both CBF subdivisions declined with increasing age, but the overall topography of subregion-specific FC profiles was reproduced in independent rs-fMRI data of healthy older individuals acquired in a typical clinical setting. Rs-fMRI-based assessments of subregion-specific CBF function may complement established volumetric approaches for the in-vivo study of CBF involvement in neuropsychiatric disorders.
Austin Biomarkers & Diagnosis Kallistatin: A Novel Biomarker for Hypertension, Organ Injury and Cancer

Kallistatin has pleiotropic effects in vasodilation and inhibition of inflammation, angiogenesis, oxidative stress, fibrosis, and cancer progression. Kallistatin administration by gene or protein delivery is observed to offer protection against a large number of pathological conditions in animal models, such as hypertension, cardiovascular and organ damage, arthritis, sepsis, influenza virus infection, tumor growth and metastasis. However, injection of a neutralizing Kallistatin antibody into hypertensive rats aggravates cardiovascular and renal injury in association with increased inflammation, oxidative stress and tissue remodeling. Thus, animal studies show that kallistatin treatment exerts beneficial effects against hypertension, organ damage and cancer development. Moreover, serum kallistatin levels are markedly reduced in several animal models of hypertension and cardiac, cerebral and renal injury. Importantly, kallistatin levels in circulation, body fluids or tissues are significantly lower in patients with liver disease, septic syndrome, diabetic retinopathy, severe pneumonia, inflammatory bowel disease, and cancer of the colon and prostate. Furthermore, reduced plasma kallistatin levels are associated with adiposity and metabolic risk in apparently healthy African American youths. The focus of this review is to highlight circulating kallistatin as a potential new biomarker for human diseases.
Gul Guven, Reyhan and Guven, Kemal and Dawe, Adam and Worthington, John and Harvell, Christopher and Popple, Amy and Smith, Tim and Smith, Brette and de Pomerai, David I. (2006) Effects of radio-frequency fields on bacterial cell membranes and nematode

Membrane-related bioeffects have been reported in response to both radio-frequency (RF) and extremely low-frequency (ELF) electromagnetic fields (EMFs), particularly in neural cells. We have tested whether RF fields might cause inner membrane leakage in ML35 E. coli cells, which express -galactosidase (lacZ) constitutively, but lack the lacY permease required for substrate entry. The activity of lacZ (indicating substrate leakage through the inner cell membrane) was increased only slightly by RF exposure (1 GHz, 0.5 W) over 45 min. Since lacZ activity showed no further increase with a longer exposure time of 90 min, this suggests that membrane permeability per se is not significantly affected by RF fields, and that slight heating ( 0.1C) could account for this small difference. Temperature-sensitive (ts) mutants of the nematode, Caenorhabditis elegans, are wild-type at 15C but develop the mutant phenotype at 25C; an intermediate temperature of 21C results in a reproducible mixture of both phenotypes. For two ts mutants affecting transmembrane receptors (TRA-2 and GLP-1), RF exposure for 24 h during the thermocritical phase strongly shifts the phenotype mix at 21C towards the mutant end of the spectrum. For ts mutants affecting nuclear proteins, such phenotype shifts appear smaller (PHA-1) or non-significant (LIN-39), apparently confirming suggestions that RF power is dissipated mainly in the plasma membrane of cells. However, these phenotype shifts are no longer seen when microwave treatment is applied at 21C in a modified exposure apparatus that minimises the temperature difference between sham and exposed conditions. Like other biological effects attributed to microwaves in the C. elegans system, phenotype shifts in ts mutants appear to be an artefact caused by very slight heating.
High Prevalence of Methicillin Resistant in Pigs

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. High Prevalence of Methicillin Resistant in Pigs A.J. de Neeling, M.J.M. van den Broek, E.C. Spalburg, M.G. van Santen-Verheuvel, W.D.C. Dam-Deisz, H.C. Boshuizen, A.W. van de Giessen, E. van Duijkeren, X.W. Huijsdens
Designing a More Effective Way to Surface the Information Needs of People in Developing Communities

This paper is a reflection on the research design of an information and communication technology for development (ICT4D) research project using design science research (DSR) in the pragmatic tradition. The artefact created and evaluated during the study is the Community Shaping Solutions Framework (CSSF) in response to the problem that this study addresses: how should the information needs that are meaningful to women working as domestic workers, be effectively translated through the use of ICT in order to enhance their experience of the good life as defined by Sen's (1999) capability approach and to contribute to the success and social value of ICT4D projects.
M ONOCULAR C AMERA C ALIBRATION SING P ROJECTIVE I NVARIANTS

Camera calibration is a crucial step to improve the accuracy of the images captured by optical devices. In this paper, we take advantage of projective geometry properties to select frames with quality control points in the data acquisition stage and, further on, perform an accurate camera calibration. The proposed method consists of four steps. Firstly, we select acceptable frames based on the position of the control points, later on we use projective invariants properties to find the optimal control points to perform an initial camera calibration using the camera calibration algorithm implemented in OpenCV. Finally, we perform an iterative process of control point refinement, projective invariants properties check and recalibration; until the results of the calibrations converge to a minimum defined threshold.
with Adjustment for

Purpose: To examine predictors of quality of life gains for type 1 diabetes patients after taking part in a self management training programme (DAFNE). Method: Clinical and questionnaire data were collected from 437 patients with type 1 diabetes from 6 hospital centres at baseline before participation in the DAFNE programme and at 3 further time points (at 6, 12 and 18 month post-DAFNE training). The Diabetes-Specific Quality of Life Scale (DSQOLS) and the Problem Areas in Diabetes Scale (PAID) provided quality of life data, and the Hospital Anxiety and Depression Scale (HADS) provided data on psychological wellbeing. Glycated haemoglobin (HbA 1c ), weight and height, and blood pressure levels were recorded by health practitioners at patients’ clinic appointments. Age, gender, marital status, education level, years since diagnosis and smoking status were recorded at baseline. Linear mixed models were fitted to identify predictors of change in quality of life at 18 month follow up. Results: Those with high levels of diabetes-related distress experienced greatest improvement in DSQOLS quality of life scores (p=0.001). Those with poor glycaemic control (higher levels of HbA 1c ; p=0.03) and those with high levels of anxiety (p=0.001) experienced greatest reductions in diabetes-related distress. Conclusions: Those with higher baseline levels of anxiety, higher levels of diabetes-related distress and higher baseline levels of HbA 1c are most likely to benefit (in terms of quality of life gain) from participation in self-management programmes like DAFNE.
Analysis of Advanced Fuzzy Filters for Image Denoising

-Image denoising algorithms may be the oldest in image processing. A first pre-processing step in analyzing such datasets is denoising, that is, estimating the unknown signal of interest from the available noisy data. There are several different approaches to denoise images. To remove noise several techniques and image denoising filters are used. This paper shows a comparative study and analysis of image denoising techniques relying on fuzzy filters. First is the fuzzy impulse noise detection and reduction method (FIDRM) and second is noise adaptive fuzzy switching median filter for salt and pepper noise reduction (NAFSM). The comparative analysis shows that the NAFSM filter is better then the FIDRM filter in terms of execution time, peak signal to noise ratio (PSNR) and mean square error (MSE).
Re-analysis of microarray data reveals insights into altered transcriptional activity of TH17 and TReg signalling in psoriasis

: Identifying differential expression of genes in psoriatic and healthy skin by microarray data analysis is a key approach to understand the pathogenesis of psoriasis. Analysis of more than one dataset to identify genes commonly upregulated reduces the likelihood of false positives and narrows down the possible signature genes. Genes controlling the critical balance between T helper 17 and regulatory T cells are of special interest in psoriasis. Our objectives were to identify genes that are consistently upregulated in lesional skin from three published microarray datasets. We carried out a reanalysis of gene expression data extracted from three experiments on samples from psoriatic and nonlesional skin using the same stringency threshold and software and further compared the expression levels of 92 genes related to the T helper 17 and regulatory T cell signaling pathways. We found 73 probe sets representing 57 genes commonly upregulated in lesional skin from all datasets. These included 26 probe sets representing 20 genes that have no previous link to the etiopathogenesis of psoriasis. These genes may represent novel therapeutic targets and surely need more rigorous experimental testing to be validated. Our analysis also identified 12 of 92 genes known to be related to the T helper 17 and regulatory T cell signaling pathways, and these were found to be differentially expressed in the lesional skin samples.
Acceptor Substrate Discrimination in Phosphatidyl-myo-inositol Mannoside Synthesis

Long term survival of the pathogen Mycobacterium tuberculosis in humans is linked to the immunomodulatory potential of its complex cell wall glycolipids, which include the phosphatidylinositol mannoside (PIM) series as well as the related lipomannan and lipoarabinomannan glycoconjugates. PIM biosynthesis is initiated by a set of cytosolic α-mannosyltransferases, catalyzing glycosyl transfer from the activated saccharide donor GDP-α-d-mannopyranose to the acceptor phosphatidyl-myo-inositol (PI) in an ordered and regio-specific fashion. Herein, we report the crystal structure of mannosyltransferase Corynebacterium glutamicum PimB′ in complex with nucleotide to a resolution of 2.0 Å. PimB′ attaches mannosyl selectively to the 6-OH of the inositol moiety of PI. Two crystal forms and GDP- versus GDP-α-d-mannopyranose-bound complexes reveal flexibility of the nucleotide conformation as well as of the structural framework of the active site. Structural comparison, docking of the saccharide acceptor, and site-directed mutagenesis pin regio-selectivity to a conserved Asp residue in the N-terminal domain that forces presentation of the correct inositol hydroxyl to the saccharide donor.
Anatomical or Functional Evaluation as an Initial Test forStable Coronary Artery Disease: A Propensity Score Analysis

1Department of Cardiology, Daejeon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Daejeon, Korea; Departments of 2Cardiology, 3Biostatistics, 5Preventive Medicine, 6Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea. ; 4Institute of Health Services Research, Yonsei University, Seoul, Korea; 4Department of Hospital Management, Graduate School of Public Health, Yonsei University, Seoul, Korea.
Characterizing drag and velocity within model mangrove forests of ordered and random tree arrangement

Changes in velocity and drag force on model mangrove trees within 13 different simulated mangrove forest segments in a flume were investigated. The simulated forests were composed of 1/12 scale model Rhizophora mangrove trees placed at three densities: low (3.42 trees/m2), medium (6.34 trees/m2), and high (9.27 trees/m2). For the low tree density cases, one forest with ordered tree placement and six forests with random tree placement were studied. For the medium and high tree density cases, one ordered tree arrangement and two random tree arrangements were studied. Spatial arrangements of the forests were described using the mean distance to nearest neighbor (NN) for all trees in a particular forest. The forest arrangements were also described using the spatial aggregation index developed by Clark and Evans. [9] For forests of ordered tree arrangement, depth-averaged velocity was found to decrease from the leading edge to the trailing edge of the forest segment at each density, and the reduction in velocity moving through the forest was greater for denser forests. Vertical profiles of velocity show that a region of high velocity developed above the root zone when moving from the leading edge to the trailing edge of the forest. This effect was more pronounced in the forests with random tree arrangement and low mean NN distance. For all spatial arrangements, the drag force acting on an individual tree decreased from the leading edge to the trailing edge of the forest. Larger decreases in drag force occurred within denser forests. Mangrove tree drag coefficient values were found to be similar or slightly higher for trees within forests of random arrangement compared to trees within forests of ordered arrangement, but further study examining a greater amount of random tree arrangements is needed. This study describes changes in the vulnerability of a mangrove forest that could occur if mangrove trees were removed from the forest by natural or human causes. Thesis Supervisor: Heidi M. Nepf Title: Donald and Martha Harleman Professor of Civil and Environmental Engineering
the effects of subgrid variability of soil moisture on runoff generation in a land surface model. Journal of Geophysical

Different representations of runoff generation processes were implemented in the MOSES land 3 surface model which is used with mesoscale and global atmospheric models. The standard model 4 was compared with versions in which runoff generation was described by parameterizations based 5 on either the Probability Distributed Model (PDM) or modified forms of TOPMODEL, all of which 6 used probability functions to describe the subgrid distribution of soil moisture. The model results 7 were compared with observed streamflow in three catchments in southern France. After calibration, 8 the PDM- and TOPMODEL-based parameterizations performed substantially better than the 9 standard model. The TOPMODEL approach gave the best results through allowing a more 10 responsive subsurface flow that contributed to peak flows and also better captured the slower 11 changes during recessions. This approach was sensitive to uncertainty in the value of the 12 topographic index. The PDM-based model only changed the calculation of surface runoff and 13 retained the standard description of subsurface runoff, and this limited the possible improvement in 14 performance. In principle the values of the new parameters can be determined from observations, 15 but in practice calibration is likely to be required. However, for each new parameterization, a single 16 set of parameter values was found that performed well in all catchments. The simulated soil 17 moisture and surface heat fluxes during summer dry periods were affected by the choice of runoff 18 parameterization. 19 20 21 22 23 24
Extracting Expert's Goals by What-if Interpretable Modeling

Although reinforcement learning (RL) has tremendous success in many ﬁelds, applying RL to real-world settings such as healthcare is challenging when the reward is hard to specify and no exploration is allowed. In this work, we focus on recovering clinicians’ rewards in treating patients. We incorporate the what-if reasoning to explain the clinician’s treatments based on their potential future outcomes. We use generalized additive models (GAMs) - a class of accurate, interpretable models - to recover the reward. In both simulation and a real-world hospital dataset, we show our model outperforms baselines. Finally, our model’s explanations match several clinical guidelines when treating patients while we found the commonly-used linear model often contradicts them.
A novel reconstruction attack on foreign-trade official statistics, with a Brazilian case study

In this paper we describe, formalize, implement, and experimentally evaluate a novel transaction re-identification attack against official foreigntrade statistics releases in Brazil. The attack’s goal is to re-identify the importers of foreign-trade transactions (by revealing the identity of the company performing that transaction), which consequently violates those importers’ fiscal secrecy (by revealing sensitive information: the value and volume of traded goods). We provide a mathematical formalization of this fiscal secrecy problem using principles from the framework of quantitative information flow (QIF), then carefully identify the main sources of imprecision in the official data releases used as auxiliary information in the attack, and model transaction re-construction as a linear optimization problem solvable through integer linear programming (ILP). We show that this problem is NP-complete, and provide a methodology to identify tractable instances. We exemplify the feasibility of our attack by performing 2,003 transaction re-identifications that in total amount to more than $137M, and affect 348 Brazilian companies. Further, since similar statistics are produced by other statistical agencies, our attack is of broader concern.
Survey on the State-of-the-Art in Device-to-Device Communication: A Resource Allocation Perspective

Device to Device (D2D) communication takes advantage of the proximity between the communicating devices in order to achieve efficient resource utilization, improved throughput and energy efficiency, simultaneous serviceability and reduced latency. One of the main characteristics of D2D communication is reuse of the frequency resource in order to improve spectral efficiency of the system. Nevertheless, frequency reuse introduces significantly high interference levels thus necessitating efficient resource allocation algorithms that can enable simultaneous communication sessions through effective channel and/or power allocation. This survey paper presents a comprehensive investigation of the state-of-the-art resource allocation algorithms in D2D communication underlaying cellular networks. The surveyed algorithms are evaluated based on heterogeneous parameters which constitute the elementary features of a resource allocation algorithm in D2D paradigm. Additionally, in order to familiarize the readers with the basic design of the surveyed resource allocation algorithms, brief description of the mode of operation of each algorithm is presented. The surveyed algorithms are divided into four categories based on their technical doctrine i.e., conventional optimization based, Non-Orthogonal-Multiple-Access (NOMA) based, game theory based and machine learning based techniques. Towards the end, several open challenges are remarked as the future research directions in resource allocation for D2D communication.
Universal growth of social groups: empirical analysis and modeling

Social groups are fundamental elements of any social system. Their emergence and evolution are closely related to the structure and dynamics of a social system. Research on social groups was primarily focused on the growth and the structure of the interaction networks of social system members and how members’ group affiliation influences the evolution of these networks. The distribution of groups’ size and how members join groups has not been investigated in detail. Here we combine statistical physics and complex network theory tools to analyze the distribution of group sizes in three data sets, Meetup groups based in London and New York and Reddit. We show that all three distributions exhibit log-normal behavior that indicates universal growth patterns in these systems. We propose a theoretical model that combines social and random diffusion of members between groups to simulate the roles of social interactions and members’ interest in the growth of social groups. The simulation results show that our model reproduces growth patterns observed in empirical data. Moreover, our analysis shows that social interactions are more critical for the diffusion of members in online groups, such as Reddit, than in offline groups, such as Meetup. This work shows that social groups follow universal growth mechanisms that need to be considered in modeling the evolution of social systems.
An Exploration of Post-Editing Effectiveness in Text Summarization

Automatic summarization methods are efficient but can suffer from low quality. In comparison, manual summarization is expensive but produces higher quality. Can humans and AI collaborate to improve summarization performance? In similar text generation tasks (e.g., machine translation), human-AI collaboration in the form of “post-editing” AI-generated text reduces human workload and improves the quality of AI output. Therefore, we explored whether post-editing offers advantages in text summarization. Specifically, we conducted an experiment with 72 participants, comparing post-editing provided summaries with manual summarization for summary quality, human efficiency, and user experience on formal (XSum news) and informal (Reddit posts) text. This study sheds valuable insights on when post-editing is useful for text summarization: it helped in some cases (e.g., when participants lacked domain knowledge) but not in others (e.g., when provided summaries include inaccurate information). Participants’ different editing strategies and needs for assistance offer implications for future human-AI summarization systems.