Miracle-dz/UniFAR-FTUs huggingface dataset:
Large-Scale Neuronal Network Dysfunction in Diabetic Retinopathy

Diabetic retinopathy (DR) patients are at an increased risk of cognitive decline and dementia. There is accumulating evidence that specific functional and structural architecture changes in the brain are related to cognitive impairment in DR patients. However, little is known regarding whether the functional architecture of resting-state networks (RSNs) changes in DR patients. The purpose of this study was to investigate the intranetwork functional connectivity (FC) and functional network connectivity (FNC) of RSN changes in DR patients using independent component analysis (ICA). Thirty-four DR patients (18 men and 16 women; mean age, 53.53 ± 8.67 years) and 38 nondiabetic healthy controls (HCs) (15 men and 23 women; mean age, 48.63 ± 11.83 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the nine RSNs. Then, two-sample t-tests were conducted to investigate different intranetwork FCs within nine RSNs between the two groups. The FNC toolbox was used to assess interactions among RSNs. Pearson correlation analysis was conducted to explore the relationship between intranetwork FCs and clinical variables in the DR group. A receiver operating characteristic (ROC) curve was conducted to assess the ability of the intranetwork FCs of RSNs in discriminating between the two groups. Compared to the HC group, DR patients showed significant decreased intranetwork FCs within the basal ganglia network (BGN), visual network (VN), ventral default mode network (vDMN), right executive control network (rECN), salience network (SN), left executive control network (lECN), auditory network (AN), and dorsal default mode network (dDMN). In addition, FNC analysis showed increased VN-BGN, VN-vDMN, VN-dDMN, vDMN-lECN, SN-BGN, lECN-dDMN, and AN-BGN FNCs in the DR group, relative to the HC group. Furthermore, altered intranetwork FCs of RSNs were significantly correlated with the glycosylated hemoglobin (HbA1c) level in DR patients. A ROC curve showed that these specific intranetwork FCs of RSNs discriminated between the two groups with a high degree of sensitivity and specificity. Our study highlighted that DR patients had widespread deficits in both low-level perceptual and higher-order cognitive networks. Our results offer important insights into the neural mechanisms of visual loss and cognitive decline in DR patients.
Silicon Detector Technologies for Future Particle Collider Experiments

Future collider experiments are typically motivated by the search for new particles and precision measurements of physical observables. The goal is to find deviations from existing theories. In practice, this requires advances towards higher luminosities at higher collision energies, finally resulting in a more difficult experimental environment. At the same time, more precise measurements are required. One such collider is the high luminosity upgrade of the LHC (HL-LHC), that is planned to start operation in 2026. Compared to LHC, the number of simultaneous collisions (pile-up) will increase by roughly a factor four and the radiation exposure of the detectors will be an order of magnitude larger than for LHC. Another proposed collider is the Compact Linear Collider (CLIC) that would provide electronpositron collisions at a centre-of-mass energy of up to 3TeV. As the collision partners are fundamental particles, the initial state and energy are well known. This allows for precision measurements of Higgs and Top quark observables, including a wide variety of measurements that are particularly sensitive to physics beyond the standard model. Here, the detector is required to deliver an unprecedented precision on the measurement of jet energy, impact parameter and particle momentum. For both colliders and their associated experiments, silicon detectors play an essential role in meeting the detection requirements. For CLIC, the desired momentum resolution together with the flavour tagging performance will require a vertex detector with a spatial resolution of around 3 μm and a time resolution better than 5 ns, all at a material budget of only 0.2%X0 per layer. This can be achieved by using thin silicon pixel sensors of around 50μm thickness. The design of the CLIC calorimeter is driven by the need of an unprecedented jet energy resolution. To achieve this, CLIC will employ a highly granular sampling calorimeter optimised for Particle Flow techniques. Silicon pad sensors will be used as active material in the electromagnetic calorimeter due to their compactness, operational stability, excellent signal-to-noise ratio and good segmentation properties. More recently, the CMS collaboration has decided to adopt a similar concept in the upgrade of their endcap calorimeters for the HL-LHC phase, a project commonly called HGCAL. Here, the reasoning to use silicon as active calorimeter material is however broader. It is additionally driven by the need for radiation hardness and precise time stamping for pile-up mitigation. In this work, the role of silicon detectors in the CLIC vertex detector as well as the calorimeters for
Isolation and genomic analysis of 11-aminoundecanoic acid-degrading bacterium Pseudomonas sp. JG-B from nylon 11 enrichment culture

Nylon 11 is a polymer synthesized from 11-aminoundecanoic acid, and widely used in commercial manufacturing. In this study, we describe the isolation of the first organism capable of metabolizing 11-aminoundecanoic acid from nylon 11 enrichment culture. The strain shows rapid growth on 11-aminoundecanoic acid as a sole source of carbon, nitrogen, and energy. Furthermore, the genome sequence of strain JG-B was deciphered and shown to belong to genus Pseudomonas. Many genes encoding putative extracellular hydrolases, as well as homologues of nylon 6 hydrolases (NylB and NylA) were identified, suggesting the metabolic versatility and possibility that this organism could also depolymerase nylon 11 polymers.
Dosimetric verifi cation of the dose distribution in pulsed dose rate brachytherapy

Background Pulsed dose rate (PDR) brachytherapy is clinically used as an irradiation technique. It combines the physical advantages of high-dose-rate (HDR) technology (isodose optimization, planning fl exibility and radiation safety) with the radiobiological advantages of low-dose-rate (LDR) brachytherapy [1,2]. The single radioactive stepping source moves through all the implanted catheters during each pulse. The source is enclosed in a capsule 2.5mm long with a diameter of 1.1mm [3]. The resulting isodoses can be optimized by modulating the dwell time of the source as a function of its trajectory within the implanted volume.
Quasi-static and Dynamic Properties of Technical Fibers

Introduction Natural and synthetic fi bers are used in many products including fabric, insulation, and composite materials. Often, the mechanical properties of the fi bers dictate the performance and longevity of the products in which they are used. Generally, it is not suffi cient to assume that a fi ber will have the same strength as a larger specimen of the same material. This is especially true for metals, because strength depends directly on grain size, and grain size depends on geometric constraints. So for its size, a thin metal wire will generally be stronger than a large specimen of the same material, because the wire has smaller grains. Some polymers also manifest size-dependent strengthening mechanisms [1]. Therefore, the ability to measure the mechanical properties of fi bers is essential for their successful incorporation into products. This article describes experimental method and results for three prototypical fi bers: a basalt glass fi ber, a fi ne tungsten wire, and polypropylene.
Modifying copulas for improved dependence modelling

The problem is that most traditional methods for dealing with complex dependency structures assume a parametric or Gaussian distribution and linear correlation structure, but these assumptions are often violated in practical applications [3, 8]. Furthermore, the two main approaches to handling outliers or missing data are to either remove them, or replace them with some other appropriate value, but there are instances, such as in risk-management, where these anomalous observations are of key importance and cannot be eliminated. In these cases, appropriate methods are needed to model tail dependencies.
Using the Convolution Neural Network Attempts to Match Japanese Women’s Kimono and Obi

Currently, the decline in kimono usage in Japan is serious. This has become an important problem for the kimono industry and kimono culture. The reason behind this lack of usage is that Japanese clothing has many strict rules attached to it. One of those difficult rules is that kimonos have status, and one must consider the proper kimono to wear depending on the place and type of event. At the same time, the obi (sash) also has status, and the status of the kimono and obi must match. The matching of the kimono and obi is called “obiawase” in Japanese, and it is not just a matter of the person wearing the kimono selecting a pair that she likes. Instead, the first place you wear a kimono determines its status, and the obi must match that status and kimono. In other words, the color, material, meaning behind the pattern must be matched with obi. Kimono patterns may evoke the seasons or a celebratory event. All this must be considered. The kimono was originally everyday wear, and people were taught these things in their households, but with today’s increasingly nuclear families, that person who could teach these things isn’t nearby, adding to the lack of use of kimonos. Because of this, there has been interest in using CNN (Convolution Neural Network) from the digital fashion industry. We are attempting to use machine learning to tackle the difficult task of matching an obi to a kimono, using the CNN machines drawing the most attention today.
The Effect of Entrepreneurial Activity on 2011-2015 National Economic Growth: An Econometric Analysis of Global Entrepreneurship Monitor Data

Although it is generally agreed that entrepreneurship acts as a key determinant for economic growth, there has been a historical lack of empirical-based work on this topic. The creation of the Global Entrepreneurship Monitor (GEM), an organization that internationally collects data on entrepreneurship, provided researchers a standardized way to compare entrepreneurial activity across countries. Past literature that utilized this data offered promising insights on the effect of entrepreneurship on economic growth. However, most, if not all, of these papers were conducted only a few years after the advent of the GEM in 1999, limiting the amount of data that could be studied. Now that around two decades have passed, enough countries have participated in the GEM for multiple years to allow for an extensive time-series based analysis. With the latest GEM data, this paper investigates whether Total Entrepreneurial Activity (TEA) and its variants-opportunity, necessity, and high potential TEA-affect Gross Domestic Product (GDP) growth for a sample of 54 countries. Alternative growth-influencing variables are controlled for with the inclusion of the Growth Competitiveness Index (GCI). Out of the four types of TEA, only high potential TEA is found to have a statistically significant effect on economic growth. This finding is consistent with past literature that conducted empirical work on the GEM data and suggests that firms with high potential for growth impact the economy through job creation, increased innovation, and firm dynamics.
SHARPER UPPER BOUNDS FOR THE ORDER OF APPEARANCE IN THE FIBONACCI SEQUENCE

Let Fn be the nth Fibonacci number. The order of appearance z(n) of a natural number n is defined as the smallest natural number k such that n divides Fk. In 1975, J. Sallé proved that z(n) ≤ 2n, for all positive integers n. In this paper, we shall provide sharper upper bounds for z(n) which are substantially smaller than 2n for some values of n. Moreover, we shall prove that lim inf n→∞ z(n) n = 0.
Eyes, Screen, and Hands: Investigating Spatial Manipulation in Peripersonal Space

Advances in virtual and augmented reality (VR/AR) technology is re-shaping our way of interacting with the virtual world. However, current VR/AR methodologies still fall short of being the default in how humans approach and interact with their virtual surroundings. Our work draws from ecological psychology and action-speciﬁc perception to re-think spatial interactions for object manipulation in the context of peripersonal space, space immediately surrounding the body. In this paper, we focus on the relative spatial conﬁguration of the user’s visual ﬁeld (eyes), the location of visual feedback (screen)
Risk factors for milk off-flavours in dairy herds from Prince Edward Island, Canada

A sudden increase in the incidence of milk off-flavours in bulk tank milk from Prince Edward Island (Canada) dairy farms in the late 1990s prompted an investigation of potential herd-level risk factors. A prospective case-control study was conducted from 2000 to 2002. Data on herd management were obtained by questionnaire and field investigation from all the 62 identified off-flavour positive farms (cases) and 62 loosely matched (for data-collection convenience) off-flavour negative farms (controls). Forty-three of the 62 cases (69%) of milk off-flavours identified during the study period were classified as ‘‘transmitted’’ (feed) off-flavours, and 9 (15%), 6 (10%), and 4 (6%) as ‘‘rancid’’, ‘‘oxidized’’ and ‘‘malty’’ off-flavours, respectively. Given this evidence and the relatively low incidence of other flavour defects in milk, only transmitted-flavour cases were considered in the analyses of risk factors. Poor air quality in the lactating cows’ barn (OR = 40.8), using baled silage as the main forage (OR = 10.6), as well as feeding roughage before milking (OR = 253.3) or as a free choice (OR = 3.2) all were significantly (P < 0.05) associated with the incidence of transmitted flavours in bulk-tank milk. Clipping the hair on the cows’ udder (OR = 0.07) and changing the bedding material more than once a day (OR = 0.12) were protective. The finding about feeding baled www.elsevier. com/locate/prevetmed Preventive Veterinary Medicine 64 (2004) 133–145 Abbreviations: PEI, Prince Edward Island; OR, odds ratio; BIC, Bayesian information criterion; PAF, population attributable fraction. * Corresponding author. Tel. : +1 902 566 0609; fax: +1 902 566 0823. E-mail address: amounchili@upei.ca (A. Mounchili). 0167-5877/$ – see front matter # 2004 Published by Elsevier B.V. doi:10.1016/j.prevetmed. 2004.05. 008 silage before milking has raised hypotheses about silage composition (in particular the off-flavour compounds or their precursors) and also about the process of silage making itself. # 2004 Published by Elsevier B.V.
The Implementation of Performance-Related Pay in Collaboration with Employers: The Cases of Two Russian Vocational Schools

Vocational schools are involved in partnerships with employers to generate extra resources and in the implementation of high-stake accountability reforms in Russia. We examine school capacity in the top-down implementation of performance-related pay (PRP) in Russia. We consider two cases of collaboration between schools and local employers that are either highly or loosely integrated with different companies. We elaborate the understanding of the resource and productivity dimensions of school capacity embedded within the broader context of schools’ formal and informal ties. The findings indicate tensions that emerge in the implementation of a system of rewards with regard to the within schools’ trust and the trust developed with their partners and funders, educational goals, work arrangements, and the distribution of school finances generated in partnerships. These issues can be negotiated with local industrial partners at multiple levels.
ORGANIC SOLAR CELL WITH SPDA: AG NANOWIRE NETWORK

Bu calismada, organik gunes pilleri icin yuksek saydamlik ve dusuk dirence sahip olmasi beklenen Sulfonatli poli (difenilamin): Ag nanotel ag saydam iletken elektrot hazirlanmistir. Sulfonatli poli (difenilamin): Ag nanotel ag saydam iletken elektrotun yuzey direnci 10 Ωcm -2 ve optik gecirgenligi % 88’dir. Elektrot organik gunes hucresinde kullanildiginda gunes hucresinin verimi % 2,7 elde edilmistir. Hazirlanan Sulfonatli poli (difenilamin): Ag nanowire ag elektrotu, gelecek vaat eden bir elektrot olarak organik elektronik cihazlarda kullanim icin Indiyum kalay oksit malzemeye alternatiftir ve esnek elektronik uygulamalarda da kullanilabilir.
Update Delivery Mechanisms for Prospective Information Needs: A Reproducibility Study

Real-time summarization systems monitor continuous streams of documents with the goal of delivering relevant, novel, and timely updates to users. These updates can either be sent to users' mobile devices as push notifications or be silently deposited in an inbox to be consumed - the important difference is whether the user is interrupted by the delivery. Previously, a two-year study examining user attention under these different mechanisms revealed interesting findings about users' information consumption behavior, but the conclusions were marred by a few methodological shortcomings. We present a reproducibility study that follows the same design as the original evaluation, but corrects its flaws. We find that most conclusions from the original study are confirmed, although there are some surprising differences as well. Overall, the magnitude of the observed effects are not as strong as in the original study.
NDT_A_216389 81..86

Department of Psychiatry, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Objective: The risk of coronary heart disease (CHD) in patients with major depressive disorder (MDD) is higher than that in the general population. However, the mechanisms underlying the increased CHD risk in patients with MDD remain unclear. Inflammation plays an important role in the pathogenesis of MDD and CHD. Therefore, we explored the relationship between inflammatory biomarkers and CHD risk in patients with MDD. Methods: We included 454 patients with acute MDD and 458 controls that matched the sample in age and gender. A readily available complete blood count was used to reflect inflammation, and the risk of CHD was assessed using the Framingham risk score. Results: The results showed that patients with MDD showed low-grade inflammation with an elevated platelet (p<0.001) and monocyte count (p<0.001), high platelet/lymphocyte (p=0.003) and monocyte/lymphocyte ratios (p<0.001), and a raised systemic immuneinflammation index (p=0.002). In addition, monocyte count was the only factor significantly associated with CHD risk in patients with MDD (B=7.521, 95% CI: 3.409–11.633, t=3.594, p<0.001). Conclusion: Collectively, the results of this study support the hypothesis that MDD is systemic inflammation, and suggest that monocyte count predicts the risk of CHD in patients with MDD.
Challenges and Cultural Attributes Influencing the Implementation of the Learner Centered Approach

Many developing countries have been implementing the learner centered approach to improve learning and poor performance of students. The approach enables the system of education to achieve quality education. This article discusses the characteristics of the learner centered approach in an educational provision. Execution of the foregoing learning paradigm encounters various challenges. The observation indicates challenges that have been affecting teachers, students and in general the system of education. It explains teachers’ misconceptions and students’ resistances against the preceding educational approach. In addition, the article describes the influence of cultural attributes on this style of teaching and learning. It ends by presenting suggestions for improving the implementation of the learner centered approach as well as the educational provision.
Hybrid Machine Learning Algorithms for Predicting Academic Performance

The large volume of data and its complexity in educational institutions require the sakes from informative technologies. In order to facilitate this task, many researchers have focused on using machine learning to extract knowledge from the education database to support students and instructors in getting better performance. In prediction models, the challenging task is to choose the effective techniques which could produce satisfying predictive accuracy. Hence, in this work, we introduced a hybrid approach of principal component analysis (PCA) as conjunction with four machines learning (ML) algorithms: random forest (RF), C5.0 of decision tree (DT), and naive Bayes (NB) of Bayes network and support vector machine (SVM), to improve the performances of classification by solving the misclassification problem. Three datasets were used to confirm the robustness of the proposed models. Through the given datasets, we evaluated the classification accuracy and root mean square error (RSME) as evaluation metrics of the proposed models. In this classification problem, 10-fold cross-validation was proposed to evaluate the predictive performance. The proposed hybrid models produced very prediction results which shown itself as the optimal prediction and classification algorithms.
Provenance Histogram Explorer

We present Provenance Histogram Explorer, a web based visualization solution for exploring and analyzing provenance histograms generated by UNICORN, an advanced persistent threat (APT) detector. While UNICORN is effective in detecting malicious activities by analyzing provenance log by processing it into efficient yet expressive provenance histograms, it also poses a challenge to security researchers who wish to understand and study the said malicious activities, because UNICORN does not represent the generated histogram in an intuitive and human-friendly way. We tackle this problem by designing and implementing a visualization solution that takes in UNICORN’s histogram representations, and displays the histogram in an approachable manner, that facilitates the analysis if malicious activities as reflected in the histograms by researchers, by making it easier to identify anomalies, to study the trend in the program activities, and to understand the histogram in general.
Study of genetic variability in Thottea Sp. using randomly amplified polymorphic DNA (RAPD) & Unweighted Pair Group Method with Mean Arithmetic (UPGMA)

Received on: 08.06. 2011 Revised on: 27.06. 2011 Accepted on: 27.07. 2011 Genetic variability is one of the most important aspects to find out variation in the nucleotides, genes among the species. Thottea is well-defined genus of Sub shrubs or rarely shrubs which mostly occurring in tropical and warm temperate forests of southern-eastern Asian countries, which has totally around 25 species and it, is characterize only eight species in India. This shrub is commonly called as ‘Alpam’ or ‘Apama’. Here we summarize the studies on RAPD outcome that all the eight different species of Thottea genus illustrate higher levels of genetic variation along with polymorphism among these species. Cluster analysis based on Unweighted Pair Group Method with Mean Arithmetic (UPGMA) it reveals three clusters comprising T. abrahami, T. dinghoui, T. ponmudiana and T. barberi the first cluster and T. siliquosa and T. sivarajanii in the second cluster and T. ducharteri and T. idukkiana in the last cluster. Final observation results the T. ducharteri and T. idukkiana are similar ones and are separated from each other by small difference.