Miracle-dz/UniFAR-FTUs huggingface dataset:
Phases of Hyperconnectivity and Hypoconnectivity in the Default Mode and Salience Networks Track with Amyloid and Tau in Clinically Normal Individuals

Alzheimer's disease (AD) is characterized by two hallmark molecular pathologies: amyloid aβ1–42 and Tau neurofibrillary tangles. To date, studies of functional connectivity MRI (fcMRI) in individuals with preclinical AD have relied on associations with in vivo measures of amyloid pathology. With the recent advent of in vivo Tau-PET tracers it is now possible to extend investigations on fcMRI in a sample of cognitively normal elderly humans to regional measures of Tau. We modeled fcMRI measures across four major cortical association networks [default-mode network (DMN), salience network (SAL), dorsal attention network, and frontoparietal control network] as a function of global cortical amyloid [Pittsburgh Compound B (PiB)-PET] and regional Tau (AV1451-PET) in entorhinal, inferior temporal (IT), and inferior parietal cortex. Results showed that the interaction term between PiB and IT AV1451 was significantly associated with connectivity in the DMN and salience. The interaction revealed that amyloid-positive (aβ+) individuals show increased connectivity in the DMN and salience when neocortical Tau levels are low, whereas aβ+ individuals demonstrate decreased connectivity in these networks as a function of elevated Tau-PET signal. This pattern suggests a hyperconnectivity phase followed by a hypoconnectivity phase in the course of preclinical AD. SIGNIFICANCE STATEMENT This article offers a first look at the relationship between Tau-PET imaging with F18-AV1451 and functional connectivity MRI (fcMRI) in the context of amyloid-PET imaging. The results suggest a nonlinear relationship between fcMRI and both Tau-PET and amyloid-PET imaging. The pattern supports recent conjecture that the AD fcMRI trajectory is characterized by periods of both hyperconnectivity and hypoconnectivity. Furthermore, this nonlinear pattern can account for the sometimes conflicting reports of associations between amyloid and fcMRI in individuals with preclinical Alzheimer's disease.
Fusing Multi-techniques Based on LDA-CCA and Their Application in Palmprint Identification System

In this paper, we investigate an efficient palmprint texture modeling method that incorporates a robust analysis based on fusing multiple information. In fact, a single descriptor alone may not achieve a high accuracy in palmprint biometric system. Hence, we propose the fusion of various information features extracted by the different descriptors, such as the fractal and the Multi-fractal techniques which produce a robustness to face the numerous challenging and variation of palmprint in unconstrained environments. To increase the performance of palmprint biometric systems, information fusion is proposed as a key phase in multi-characteristic systems. The obtained information can be combined at different levels, i.e., at the feature level, the score level or the decision level. Nevertheless, the feature level fusion is considered more effective than both the matching score and the classifier decision levels, thanks to a feature vector set which contains more and richer information about the input palmprint image. In order to improve the discriminating texture information, our proposed method extracts the fractal dimension features from the preprocessed palmprint images and fuses them with the Multi-fractal dimension features using the Canonical Correlation Analysis (CCA) incorporating the Linear Discriminant Analysis (LDA) in order to reduce the feature dimensionality for each feature set. To demonstrate the feasibility and effectiveness of our proposed method, we performed the experimental results on two benchmark datasets. These results outperform other well-known state of the art methods and produce promising recognition rates by achieving 96.02% for PolyU-Palmprint database and 97.00% for CASIA-Palmprint database.
Population structure of the invasive forest pathogen Hymenoscyphus pseudoalbidus

Understanding the genetic diversity and structure of invasive pathogens in source and in introduced areas is crucial to the revelation of hidden biological features of an organism, to the reconstruction of the course of invasions and to the establishment of effective control measures. Hymenoscyphus pseudoalbidus (anamorph: Chalara fraxinea) is an invasive and highly destructive fungal pathogen found on common ash Fraxinus excelsior in Europe and is native to East Asia. To gain insights into its dispersal mechanisms and history of invasion, we used microsatellite markers and characterized the genetic structure and diversity of H. pseudoalbidus populations at three spatial levels: (i) between Europe and Japan, (ii) in Europe and (iii) at the epidemic's front in Switzerland. Phylogenetic and network analysis demonstrated that individuals from both regions are conspecific. However, populations from Japan harboured a higher genetic diversity and were genetically differentiated from European ones. No evident population structure was found among the 1208 European strains using Bayesian and multivariate clustering analysis. Only the distribution of genetic diversity in space, pairwise population differentiation (GST) and the spatial analysis of principal components revealed a faint geographical pattern around Europe. A significant allele deficiency in most European populations pointed to a recent genetic bottleneck, whereas no pattern of isolation by distance was found. Our data suggest that H. pseudoalbidus was introduced just once by at least two individuals. The potential source region of H. pseudoalbidus is vast, and further investigations are required for a more accurate localization of the source population.
A speciation solver based on the semismooth Newton method : application to cement paste modeling

The mineral assemblage of a cement paste may vary considerably with its environment. In addition, the water content of a cement paste is relatively low and the ionic strength of the interstitial solution is often high. These conditions are extreme conditions with respect to the common assumptions made in speciation problem. Furthermore the common trial and errors algorithm to nd the phase assemblage does not provide any guarantee of convergence. We propose a speciation solver based on a semismooth Newton method adapted to the thermodynamic modeling of cement paste. The strong theoretical properties associated with these methods oer practical advantages. Results of numerical experiments indicates that the algorithm is reliable, robust, and ecient. 1
Technical Analysis in Foreign Exchange - The Workhorse Gains Further Ground

This work extends earlier survey studies on the use of technical analysis by considering flow analysis as a third form of information production. Moreover the survey covers FX dealers and also the rising fund managers. Technical analysis has gained importance over time and is now the most equally spread kind of analysis. It has by far the greatest importance in FX dealing and is second in fund management. Charts are used for shorter-term forecasting horizons while flows dominate at the shortest-term and fundamentals at longer horizons. Preferred users of each kind of analysis exhibit different views about market frictions.
The interactive effects of child maltreatment and the FK506 binding protein 5 gene (FKBP5) on dissociative symptoms in adolescence

Abstract The FK506 binding protein 5 gene (FKBP5) has been associated with susceptibility to pathogenic effects of childhood trauma including dissociative symptoms. This study examines the impact of maltreatment on dissociative tendencies in adolescence as moderated by the FKBP5 gene. Dissociative symptoms and variation within FKBP5 were assessed in a high-risk, low socioeconomic status community sample of 279 maltreated and 171 nonmaltreated adolescents. Following the assignment of haplotypes across four single nucleotide polymorphisms (rs3800373, rs9296158, rs1360780, and rs9470080), individuals with one or more copies of the CATT haplotype (N = 230) were grouped together and compared to individuals with zero copies of this haplotype (N = 185). Analyses of covariance were conducted to test hypotheses regarding the effects of developmental timing and the chronicity of maltreatment and the CATT haplotype. We found a significant interactive effect of timing/chronicity of maltreatment and the CATT haplotype on dissociative symptoms. Among adolescents who had no copies of the CATT haplotype, dissociative symptoms were higher for chronically maltreated adolescents who had an infancy onset compared to those who were not maltreated or whose maltreatment experience was either relatively less chronic or not started in infancy. The groups did not differ significantly among subjects who carry one or more copies of the CATT haplotype.
Treatment of autonomic dysfunction in Parkinson disease and other synucleinopathies

Dysfunction of the autonomic nervous system afflicts most patients with Parkinson disease and other synucleinopathies such as dementia with Lewy bodies, multiple system atrophy, and pure autonomic failure, reducing quality of life and increasing mortality. For example, gastrointestinal dysfunction can lead to impaired drug pharmacodynamics causing a worsening in motor symptoms, and neurogenic orthostatic hypotension can cause syncope, falls, and fractures. When recognized, autonomic problems can be treated, sometimes successfully. Discontinuation of potentially causative/aggravating drugs, patient education, and nonpharmacological approaches are useful and should be tried first. Pathophysiology‐based pharmacological treatments that have shown efficacy in controlled trials of patients with synucleinopathies have been approved in many countries and are key to an effective management. Here, we review the treatment of autonomic dysfunction in patients with Parkinson disease and other synucleinopathies, summarize the nonpharmacological and current pharmacological therapeutic strategies including recently approved drugs, and provide practical advice and management algorithms for clinicians, with focus on neurogenic orthostatic hypotension, supine hypertension, dysphagia, sialorrhea, gastroparesis, constipation, neurogenic overactive bladder, underactive bladder, and sexual dysfunction. © 2018 International Parkinson and Movement Disorder Society
Magnetoelastic anisotropy distribution in glass-coated microwires

Amorphous microwires, obtained by the glass-coated melt-spinning method having diameters in the range of micrometers, can exhibit perfectly square (single and large Barkhausen jump) or quasi-anhysteretic hysteresis loops, depending on the easy magnetization direction determined by the intrinsic magnetoelastic anisotropy. The thermoelastic internal stressed frozen-in during the fabrication that model the domain structure are here calculated by considering the classical theory of elasticity. A complex stress distribution is obtained having magnitude of 10^3 MPa. Circular stresses turn out to be predominant, which arises from the composite nature of the microwire (metallic nucleus and insulating glass coating having different mechanical and thermal properties).
A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic Data

Gated Recurrent Unit (GRU) is a recently-developed variation of the long short-term memory (LSTM) unit, both of which are variants of recurrent neural network (RNN). Through empirical evidence, both models have been proven to be effective in a wide variety of machine learning tasks such as natural language processing, speech recognition, and text classification. Conventionally, like most neural networks, both of the aforementioned RNN variants employ the Softmax function as its final output layer for its prediction, and the cross-entropy function for computing its loss. In this paper, we present an amendment to this norm by introducing linear support vector machine (SVM) as the replacement for Softmax in the final output layer of a GRU model. Furthermore, the cross-entropy function shall be replaced with a margin-based function. While there have been similar studies, this proposal is primarily intended for binary classification on intrusion detection using the 2013 network traffic data from the honeypot systems of Kyoto University. Results show that the GRU-SVM model performs relatively higher than the conventional GRU-Softmax model. The proposed model reached a training accuracy of ≈81.54% and a testing accuracy of ≈84.15%, while the latter was able to reach a training accuracy of ≈63.07% and a testing accuracy of ≈70.75%. In addition, the juxtaposition of these two final output layers indicate that the SVM would outperform Softmax in prediction time - a theoretical implication which was supported by the actual training and testing time in the study.
Prevalence and Risk Factors for Xerosis in the Elderly: A Cross-Sectional Epidemiological Study in Primary Care

Background: Limited information is available concerning the prevalence and risk factors of xerosis in the elderly. Objective: To establish the prevalence of xerosis and associated factors in elderly patients. Methods: A national, multicenter, observational, cross-sectional study in patients aged 65 or older was performed. The data collected by general practitioners were demographics and medical history, including history of atopic disease. Xerosis was evaluated using the Overall Dry Skin score. Results: 756 patients were included. The prevalence of xerosis was 55.6%. Xerosis was significantly associated with older age (OR: 1.48, 95% CI: 1.16–1.89), female sex (OR: 1.80, 95 CI%: 1.29–2.53), treatments that can potentially cause xerosis (OR: 2.21, 95 CI%: 1.54–3.17), itching during sweating (OR: 7.11, 95% CI: 3.90–12.95), a history of dry skin (OR: 2.89, 95% CI: 1.65–5.08) and a history of atopic dermatitis (OR: 3.60, 95% CI: 1.99–6.52). Conclusion: Xerosis is highly prevalent in the elderly. A history of atopy, especially atopic dermatitis, is associated with an increased risk of xerosis in the elderly.
Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations

Decades of psychological research have been aimed at modeling how people learn features and categories. The empirical validation of these theories is often based on artificial stimuli with simple representations. Recently, deep neural networks have reached or surpassed human accuracy on tasks such as identifying objects in natural images. These networks learn representations of real-world stimuli that can potentially be leveraged to capture psychological representations. We find that state-of-the-art object classification networks provide surprisingly accurate predictions of human similarity judgments for natural images, but they fail to capture some of the structure represented by people. We show that a simple transformation that corrects these discrepancies can be obtained through convex optimization. We use the resulting representations to predict the difficulty of learning novel categories of natural images. Our results extend the scope of psychological experiments and computational modeling by enabling tractable use of large natural stimulus sets.
Changes in lifestyle upon diagnosis of cancer or other chronic illnesses: A Turkish Oncology Group study

Cancer, like other chronic illnesses, changes the patients’ way of living significantly. Although some may think, for instance, that religiousness would increase with the diagnosis of cancer, no previous studies have been performed in the Turkish society to confirm this. We, as the Turkish Oncology Group, conducted a survey in seven different oncology centres, representing a large majority of Turkey, to investigate how patients’ lifestyles changed following a cancer diagnosis; we used dialysis patients as a chronic illness control group. The study findings showed how changes in spiritual practices are completely in line with what is observed in other chronic illnesses. These findings may help to address cancer patients’ needs and facilitate resource allocation accordingly.
Naturally Occurring Culturable Aerobic Gut Flora of Adult Phlebotomus papatasi, Vector of Leishmania major in the Old World

Background Cutaneous leishmaniasis is a neglected, vector-borne parasitic disease and is responsible for persistent, often disfiguring lesions and other associated complications. Leishmania, causing zoonotic cutaneous leishmaniasis (ZCL) in the Old World are mainly transmitted by the predominant sand fly vector, Phlebotomus papatasi. To date, there is no efficient control measure or vaccine available for this widespread insect-borne infectious disease. Methodology/Principal Findings A survey was carried out to study the abundance of different natural gut flora in P. papatasi, with the long-term goal of generating a paratransgenic sand fly that can potentially block the development of Leishmania in the sand fly gut, thereby preventing transmission of leishmania in endemic disease foci. Sand flies, in particular, P. papatasi were captured from different habitats of various parts of the world. Gut microbes were cultured and identified using 16S ribosomal DNA analysis and a phylogenetic tree was constructed. We found variation in the species and abundance of gut flora in flies collected from different habitats. However, a few Gram-positive, nonpathogenic bacteria including Bacillus flexus and B. pumilus were common in most of the sites examined. Conclusion/Significance Our results indicate that there is a wide range of variation of aerobic gut flora inhabiting sand fly guts, which possibly reflect the ecological condition of the habitat where the fly breeds. Also, some species of bacteria (B. pumilus, and B. flexus) were found from most of the habitats. Important from an applied perspective of dissemination, our results support a link between oviposition induction and adult gut flora.
Long-term leucine supplementation does not increase muscle mass or strength in healthy elderly men.

BACKGROUND It has been reported that the blunted muscle protein synthetic response to food intake in the elderly can be normalized by increasing the leucine content of a meal. OBJECTIVE The objective was to assess the effect of 3 mo of leucine supplementation on muscle mass and strength in healthy elderly men. DESIGN Thirty healthy elderly men with a mean (+/-SEM) age of 71 +/- 4 y and body mass index (BMI; in kg/m(2)) of 26.1 +/- 0.5 were randomly assigned to either a placebo-supplemented (n = 15) or leucine-supplemented (n = 15) group. Leucine or placebo (2.5 g) was administered with each main meal during a 3-mo intervention period. Whole-body insulin sensitivity, muscle strength (one-repetition maximum), muscle mass (measured by computed tomography and dual-energy X-ray absorptiometry), myosin heavy chain isoform distribution, and plasma amino acid and lipid profiles were assessed before, during, and/or after the intervention period. RESULTS No changes in skeletal muscle mass or strength were observed over time in either the leucine- or placebo-supplemented group. No improvements in indexes of whole-body insulin sensitivity (oral glucose insulin sensitivity index and the homeostasis model assessment of insulin resistance), blood glycated hemoglobin content, or the plasma lipid profile were observed. CONCLUSION Long-term leucine supplementation (7.5 g/d) does not augment skeletal muscle mass or strength and does not improve glycemic control or the blood lipid profile in healthy elderly men. This trial was registered at clinicaltrials.gov as NCT00807508.
Effect of the vibration on friction and wear behavior between the carbon strip and copper contact wire pair

This article reports an experimental study on the friction and wear behavior of carbon strip sliding against copper contact wire under strong electric current utilizing a high-speed block-on-ring tester. The dynamic mechanism of electric arc generation was investigated. Scanning electron microscopy was used to observe morphology of worn surfaces of the carbon strips. The results show that arc discharge has a certain correlation with low-frequency vibration of the carbon strip. The arc discharge frequency and the average single arc discharge energy initially decrease and then tend to stable with increasing normal load at different speeds. The wear rate increases first and then decreases and has the minimum when the load is equal to 100 N especially. Moreover, the wear rate steadily increases with increase in arc discharge energy and is almost directly proportional to arc discharge energy. Arc erosion was a dominant wear mechanism occurred in carbon strip sliding against copper contact wire at a low load, accompanying with adhesive wear and material transferring. However, mechanical wear was a main wear mechanism at a high load. Severe arc erosion weakened the conductivity of the carbon strip.
Structured Embedding via Pairwise Relations and Long-Range Interactions in Knowledge Base

We consider the problem of embedding entities and relations of knowledge bases into low-dimensional continuous vector spaces (distributed representations). Unlike most existing approaches, which are primarily efficient for modelling pairwise relations between entities, we attempt to explicitly model both pairwise relations and long-range interactions between entities, by interpreting them as linear operators on the low-dimensional embeddings of the entities. Therefore, in this paper we introduces Path-Ranking to capture the long-range interactions of knowledge graph and at the same time preserve the pairwise relations of knowledge graph; we call it 'structured embedding via pairwise relation and long-range interactions' (referred to as SePLi). Comparing with the-state-of-the-art models, SePLi achieves better performances of embeddings.
Novel Mutations in the PKD1 and PKD2 Genes of Chinese Patients with Autosomal Dominant Polycystic Kidney Disease

Background/Aims: Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder with mutations in PKD1 or PKD2. This study aimed to identify novel PKD1 and PKD2 mutations in Chinese patients with ADPKD. Methods: Mutational analyses of both PKD genes were performed in 120 Chinese families with inherited ADPKD using long-range PCR and targeted next-generation sequencing approaches. Sanger sequencing was performed to check the positive mutations, while multiplex ligation-dependent probe amplification was adopted to examine those without mutations for the presence of large deletions. Results: A total of 93 mutations in PKD1 and PKD2 were identified in 98 Chinese families with ADPKD inheritance and the detection rate was 81.7% (98/120). The mutation rates of PKD1 and PKD2 were 91.4% (85/93) and 8.6% (85/93), respectively. Among the 93 mutations, 59.1% (55/93) were reported for the first time. A total of 65 mutations (26 nonsense, 33 frameshift, 2 large deletion, and 4 typical splicing mutations) were identified as definite pathogenic mutations. The remaining 28 mutations (21 missense, 3 in-frame deletion, and 4 atypical splicing mutations) were determined as probable pathogenic mutations. In addition, 9 de novo mutations were found by pedigree analysis. Correlation analysis between genotype and phenotype revealed that patients with PKD1 mutations or truncating mutations exhibited the most severe clinical outcome. Conclusion: The newly identified sites for known mutations will facilitate the early diagnosis and prediction of prognosis in patients with ADPKD, and provide fundamental genetic information for clinical intervention to prevent the inheritance of this disease in affected families.