Miracle-dz/UniFAR-FTUs huggingface dataset:
A statistical model for brain networks inferred from large-scale electrophysiological signals

Network science has been extensively developed to characterize the structural properties of complex systems, including brain networks inferred from neuroimaging data. As a result of the inference process, networks estimated from experimentally obtained biological data represent one instance of a larger number of realizations with similar intrinsic topology. A modelling approach is therefore needed to support statistical inference on the bottom-up local connectivity mechanisms influencing the formation of the estimated brain networks. Here, we adopted a statistical model based on exponential random graph models (ERGMs) to reproduce brain networks, or connectomes, estimated by spectral coherence between high-density electroencephalographic (EEG) signals. ERGMs are made up by different local graph metrics, whereas the parameters weight the respective contribution in explaining the observed network. We validated this approach in a dataset of N = 108 healthy subjects during eyes-open (EO) and eyes-closed (EC) resting-state conditions. Results showed that the tendency to form triangles and stars, reflecting clustering and node centrality, better explained the global properties of the EEG connectomes than other combinations of graph metrics. In particular, the synthetic networks generated by this model configuration replicated the characteristic differences found in real brain networks, with EO eliciting significantly higher segregation in the alpha frequency band (8–13 Hz) than EC. Furthermore, the fitted ERGM parameter values provided complementary information showing that clustering connections are significantly more represented from EC to EO in the alpha range, but also in the beta band (14–29 Hz), which is known to play a crucial role in cortical processing of visual input and externally oriented attention. Taken together, these findings support the current view of the functional segregation and integration of the brain in terms of modules and hubs, and provide a statistical approach to extract new information on the (re)organizational mechanisms in healthy and diseased brains.
Alcohol-dysregulated microRNAs in hepatitis B virus-related hepatocellular carcinoma

Alcohol consumption and chronic hepatitis B virus (HBV) infection are two well-established risk factors for Hepatocellular carcinoma (HCC); however, there remains a limited understanding of the molecular pathway behind the pathogenesis and progression behind HCC, and how alcohol promotes carcinogenesis in the context of HBV+ HCC. Using next-generation sequencing data from 130 HCC patients and 50 normal liver tissues, we identified a panel of microRNAs that are significantly dysregulated by alcohol consumption in HBV+ patients. In particular, two microRNAs, miR-944 and miR-223-3p, showed remarkable correlation with clinical indication and genomic alterations. We confirmed the dysregulation of these two microRNAs in liver cell lines treated by alcohol and acetaldehyde, and showed that manipulation of miR-223-3p and miR-944 expression induces significant changes in cellular proliferation, sensitivity to doxorubicin, and the expression of both direct-binding and downstream mRNA targets. Together, the results of this study suggest that alcohol consumption in HBV+ HCCs regulates microRNAs that likely play previously uncharacterized roles in the alcohol-associated carcinogenesis of HCC, and future studies of these microRNAs may be valuable for furthering the understanding and treatment of alcohol and HBV-associated HCC.
Insulin resistance among obese middle-aged is associated with decreased cerebrovascular reactivity

Objective: To evaluate differences in cerebrovascular reactivity (CVR) to mild hypercapnia in obese/overweight individuals with and without insulin resistance (IR) compared to comparable lean controls. Methods: A total of 60 cognitively normal participants (20 lean controls and 24 obese/overweight individuals with and 16 without IR) were evaluated using a high spatial resolution arterial spin labeling MRI technique at rest and during mild hypercapnia. We analyzed group differences in CVR in cerebral cortex and ascertained the relationships between CVR, IR, and body mass index (BMI). Results: Obese/overweight participants with and without IR had significantly lower CVR to hypercapnia than lean controls after controlling for age, sex, and the presence of hypertension (F2,53 = 5.578, p = 0.006 = 0.174). In the obese/overweight participants with IR, there was a significant correlation between higher CVR and a measure of insulin sensitivity, even after accounting for BMI (rp = 0.575, p = 0.004). In contrast, there was no relationship between CVR and BMI when controlling for IR. No such relationships existed for the other 2 groups. Conclusions: IR is associated with impaired CVR; the relationship appears to be driven by the degree of IR and not by obesity. These rarely reported results suggest that early forms of cerebrovascular dysfunction exist among obese middle-aged individuals with significant IR but without type 2 diabetes mellitus. These functional vascular abnormalities may help explain the associations among IR, diabetes, and dementia, and suggest that interventions aiming to improve IR or CVR may help prevent cognitive decline later in life.
Properties of polyurethane nanocomposite filaments for conductive textile applications

Composite filaments of thermoplastic polyurethane (TPU) and single-walled carbon nanotubes (SWCNTs) have been fabricated via extrusion process and their properties were studied using various characterization techniques. Twin-screw extruder has been used for making the composite filaments and the processing parameters like temperature, screw speed, and pressure were optimized. Thermal, morphological, mechanical, and electrical properties were studied by varying the weight percentage of SWCNTs. Raman shift of SWCNTs is observed for the CNTs dispersed in TPU matrix. Thermal analysis shows that there is an increase in the degradation and melting temperature of the TPU/SWCNTs blends. With the addition of SWCNTs as small filler loadings of 1 wt%, the tensile strength of the blended materials increased from 13 MPa to 21.6 MPa. The electrical conductivity of the composite filaments starts with the addition of 0.01% of SWCNTs. The highest value of electrical conductivity (3.7 × 10−7 S cm−1) obtained with 2 wt% of SWCNTs. This melt extrusion process method could open up for the preparation of new high-performance nanotube composite materials.
IMPACTS OF SECOND HOME DEVELOPMENT ON HOUSING PRICES IN THE SOUTHERN APPALACHIAN HIGHLANDS

This study estimates the value of socioeconomic, spatial and environmental attributes on housing prices of both urban and rural communities in the primary and second home areas of the Southern Appalachian Highlands, using the hedonic property price model. Distance and environmental attributes are valued more heavily in the rural communities of the second home area than in the urban communities of the primary home area. The effect of second homes on housing prices is mainly evident in the rural communities. Second home development impacts a home's value by US$2,378, or 4.2% of $56,245, the average value of a rural home.
Bond Graph Model of Cerebral Circulation: Toward Clinically Feasible Systemic Blood Flow Simulations

We propose a detailed CellML model of the human cerebral circulation that runs faster than real time on a desktop computer and is designed for use in clinical settings when the speed of response is important. A lumped parameter mathematical model, which is based on a one-dimensional formulation of the flow of an incompressible fluid in distensible vessels, is constructed using a bond graph formulation to ensure mass conservation and energy conservation. The model includes arterial vessels with geometric and anatomical data based on the ADAN circulation model. The peripheral beds are represented by lumped parameter compartments. We compare the hemodynamics predicted by the bond graph formulation of the cerebral circulation with that given by a classical one-dimensional Navier-Stokes model working on top of the whole-body ADAN model. Outputs from the bond graph model, including the pressure and flow signatures and blood volumes, are compared with physiological data.
Improved Insulin Secretion by Autologous Islet Transplantation, Compared to Oral Antidiabetic Agents, after Distal Pancreatectomy

In this study, the effects of autologous islet transplantation (ITx) were compared to those of oral antidiabetic drugs (OAD) after distal pancreatectomy (NCT01922492). We enrolled nondiabetic patients who underwent distal pancreatectomy for benign tumors. In the ITx group, islets were isolated from the normal part of the resected pancreas and implanted via the portal vein. Patients who did not receive ITx were regularly monitored and were enrolled in the OAD group if diabetes mellitus developed. The OAD group was treated with metformin with or without vildagliptin. Metabolic parameters were monitored for 12 months postoperatively. Nine patients in the ITx group and 10 in the OAD group were included in the analysis. After 12 months, hemoglobin A1c significantly increased by 5% of the baseline in each group. Area under the curve for blood glucose (AUCglucose) of the 75-g oral glucose tolerance test increased similarly in the immediate postoperative period in both groups but significantly reduced only in the ITx group thereafter. Insulinogenic index (INSindex) significantly decreased from 25.6 ± 18.9 to 4.7 ± 3.7 in the OAD group, while no significant change was observed in the ITx group (from 15.0 ± 4.5 to 11.0 ± 8.2). In the multiple regression analysis, ITx was an independent factor for changes in AUCglucose and INSindex. In addition, changes in INSindex in the ITx group after postoperative 6 months were associated with the efficacy of islet isolation, amount of grafts, and peak serum HMGB1 and VEGF levels after ITx. ITx was superior to OAD in maintaining insulin secretory capacity and glucose tolerance after distal pancreatectomy.
Collaborative exploratory search for information filtering and large‐scale information triage

Modern information seekers face dynamic streams of large‐scale heterogeneous data that are both intimidating and overwhelming. They need a strategy to filter this barrage of massive data sets, and to find all of the information responding to their information needs, despite the pressures imposed by schedules and budgets. In this applied research, we present an exploratory search strategy that allows professional information seekers to efficiently and effectively triage all of the data. We demonstrate that exploratory search is particularly useful for information filtering and large‐scale information triage, regardless of the language of the data, and regardless of the particular industry, whether finance, medical, business, government, information technology, news, or legal. Our strategy reduces a dauntingly large volume of information into a manageable, high‐precision data set, suitable for focused reading. This strategy is interdisciplinary, integrating concepts from information filtering, information triage, and exploratory search. Key aspects include advanced search software, interdisciplinary paired search, asynchronous collaborative search, attention to linguistic phenomena, and aggregated search results in the form of a search matrix or search grid. We present the positive results of a task‐oriented evaluation in a real‐world setting, discuss these results from a qualitative perspective, and share future research areas.
Marginal accuracy of computer-aided design- and computer-aided manufacturing-fabricated full-arch zirconia restoration

Objective This study evaluated marginal accuracy of full-arch zirconia restoration fabricated from two digital computer-aided design and computer-aided manufacturing (CAD-CAM) systems (Trios-3 and CS3500) in comparison to conventional cast metal restoration. Materials and methods A stainless steel model comprising two canine and two molar abutments was used as a master model for full-arch reconstruction. The canine and molar abutments were machined in a cylindrical shape with 5° taper and chamfer margin. The CAD-CAM systems based on the digital approach were used to construct the full-arch zirconia restoration. The conventional cast metal restoration was fabricated according to a conventional lost-wax technique using nickel–chromium alloys. Ten restorations were fabricated from each system. The marginal accuracy of each restoration was determined at four locations for each abutment. An analysis of variance (ANOVA) and Tukey’s honest significant difference (HSD) multiple comparisons were used to determine statistically significant difference at 95% confidence interval. Results The mean values of marginal accuracy of restorations fabricated from conventional casting, Trios-3, and CS3500 were 48.59±4.16 μm, 53.50±5.66 μm, and 56.47±5.52 μm, respectively. ANOVA indicated significant difference in marginal fit of restorations among various systems. The marginal discrepancy of zirconia restoration fabricated from the CS3500 system demonstrated significantly larger gap than that fabricated from the 3Shape system (p<0.05). Tukey’s HSD multiple comparisons indicated that the zirconia restoration fabricated from either CS3500 or Trios-3 demonstrated a significantly larger marginal gap than the conventional cast metal restoration (p<0.05). Conclusion Full-arch zirconia restoration fabricated from the Trios-3 illustrated better marginal fits than that from the CS3500, although, both were slightly less accurate than the conventional cast restoration. However, the marginal discrepancies of restoration produced by both CAD-CAM systems were within the clinically acceptable range and satisfactorily precise to be suggested for construction full-arch zirconia restoration.
Graph-Based Cooperative Localization Using Symmetric Measurement Equations

Safety is one of the critical challenges for a semi or fully automated driving assistance systems. One of the key parameters for a safe automated driving assistance system is precise localization of the self and surrounding vehicles. Our previous work demonstrated the use of Symmetric Measurement Equations (SME) in a Factor Graph framework and exploited the use of sensor located outside the vehicle. In this paper we present a new approach which not only performs above mentioned cooperative vehicle infrastructure localization but also uses Dedicated Short Range Communication (DSRC). This work goes further in the direction of a complete V2X solution not only involving the infrastructure sensor but also the neighbouring vehicles. DSRC has been increasingly incorporated in all the the modern vehicles. Better state estimation is achieved by formulating the range information from DSRC as a new DSRC Range Factor in the Factor Graph. Simulations indicate better performance over the previously proposed approach of only using SME in the Factor Graph, thereby progressing a step further towards safe automated driving assistance systems.
Identification of a Novel Gene for Diabetic Traits in Rats, Mice, and Humans

The genetic basis of type 2 diabetes remains incompletely defined despite the use of multiple genetic strategies. Multiparental populations such as heterogeneous stocks (HS) facilitate gene discovery by allowing fine mapping to only a few megabases, significantly decreasing the number of potential candidate genes compared to traditional mapping strategies. In the present work, we employed expression and sequence analysis in HS rats (Rattus norvegicus) to identify Tpcn2 as a likely causal gene underlying a 3.1-Mb locus for glucose and insulin levels. Global gene expression analysis on liver identified Tpcn2 as the only gene in the region that is differentially expressed between HS rats with glucose intolerance and those with normal glucose regulation. Tpcn2 also maps as a cis-regulating expression QTL and is negatively correlated with fasting glucose levels. We used founder sequence to identify variants within this region and assessed association between 18 variants and diabetic traits by conducting a mixed-model analysis, accounting for the complex family structure of the HS. We found that two variants were significantly associated with fasting glucose levels, including a nonsynonymous coding variant within Tpcn2. Studies in Tpcn2 knockout mice demonstrated a significant decrease in fasting glucose levels and insulin response to a glucose challenge relative to those in wild-type mice. Finally, we identified variants within Tpcn2 that are associated with fasting insulin in humans. These studies indicate that Tpcn2 is a likely causal gene that may play a role in human diabetes and demonstrate the utility of multiparental populations for positionally cloning genes within complex loci.
Path Sampling: A Fast and Provable Method for Estimating 4-Vertex Subgraph Counts

Counting the frequency of small subgraphs is a fundamental technique in network analysis across various domains, most notably in bioinformatics and social networks. The special case of triangle counting has received much attention. Getting results for 4-vertex patterns is highly challenging, and there are few practical results known that can scale to massive sizes. Indeed, even a highly tuned enumeration code takes more than a day on a graph with millions of edges. Most previous work that runs for truly massive graphs employ clusters and massive parallelization. We provide a sampling algorithm that provably and accurately approximates the frequencies of all 4-vertex pattern subgraphs. Our algorithm is based on a novel technique of 3-path sampling and a special pruning scheme to decrease the variance in estimates. We provide theoretical proofs for the accuracy of our algorithm, and give formal bounds for the error and confidence of our estimates. We perform a detailed empirical study and show that our algorithm provides estimates within 1% relative error for all subpatterns (over a large class of test graphs), while being orders of magnitude faster than enumeration and other sampling based algorithms. Our algorithm takes less than a minute (on a single commodity machine) to process an Orkut social network with 300 million edges.
Correlation of Radiation Dose Estimates by DIC with the METREPOL Hematological Classes of Disease Severity

The degree of severity of hematologic acute radiation syndrome (HARS) may vary across the range of radiation doses, such that dose alone may be a less reliable predictor of clinical course. We sought to elucidate the relationship between absorbed dose and risk of clinically relevant HARS in humans. We used the database SEARCH (System for Evaluation and Archiving of Radiation Accidents based on Case Histories), which contains the histories of radiation accident victims. From 153 cases we extracted data on dose estimates using the dicentric assay to measure individual biological dosimetry. The data were analyzed according to the corresponding hematological response categories of clinical significance (H1–4). These categories are derived from the medical treatment protocols for radiation accident victims (METREPOL) and represent the clinical outcome of HARS based on severity categories ranging from 1–4. In addition, the category H0 represents a post-exposure hematological response that is within the normal range for nonexposed individuals. Age at exposure, gender and ethnicity were considered as potential confounders in unconditional cumulative logistic regression analysis. In most cases, victims were Caucasian (82.4%) and male (92.8%), who originated from either the Chernobyl (69.3%) or Goiânia (10.5%) accident, and nearly 60% were aged 20–40 years at time of exposure. All individuals were whole-body exposed (mean 3.8 Gy, stdev ±3.1), and single exposures were predominantly reported (79%). Seventy percent of victims in category H0 were exposed to ≤1 Gy, with rapidly decreasing proportions of H0 seen at doses up to 5 Gy. There were few HARS H4 cases reported at exposed dose of 1–2 Gy, while 82% of H4 cases received doses of >5 Gy. HARS H1–3 cases varied among dose ranges from 1–5 Gy. In summary, single whole-body radiation doses <1 Gy and >5 Gy corresponded in general with H0 and H3–4, respectively, and this was consistent with medical expectations. This underlines the usefulness of dose estimates for HARS prediction. However, whole-body doses between 1–5 Gy poorly corresponded to HARS H1–3. The dose range of 1–5 Gy was of limited value for medical decision-making regarding, e.g., hospitalization for H2–3, but not H1 and treatment decisions that differ between H1–3. Also, there were some H0 cases at high doses and H2–4 cases at low doses, thereby challenging an individual recommendation based solely on dose.
Improved synchronization scheme for indoor visible-light differential on-off keying

In this paper, as binary modulation schemes, the differential on-off keying (DOOK) system, which can achieve anti-background noise capability and high data transmission efficiency, is considered. In order to solve the synchronization slip, a visible-light framed DOOK system embedding {-1,+1}-synchronization signal pattern is proposed. Moreover, theoretical formulas of detection and false alarm probability are derived. The detection probability taking into account false rate is evaluated under the visible-light channel with scintillation and background noise. Consequently, in the evaluation of detection probability taking into account false alarm rate, the proposed system is better than the conventional system.
High-Resolution VLA Imaging of the Supernova Remnant W28 at 328 and 1415 MHz

We present new VLA images at 328 and 1415 MHz of the supernova remnant (SNR) W28. The image at 1415 MHz, produced after the combination of 50 separate VLA pointings and the addition of single-dish data, has an angular resolution of 88″ × 48″, with an rms noise of 5 mJy beam-1. At 328 MHz, the image has an angular resolution of 97″ × 52″ and an rms noise of 14 mJy beam-1. From these observations we reestimated the characteristic parameters of W28: angular diameter 48′, flux densities S1415 MHz = 246 Jy and S328 MHz = 425 Jy, Σ1 GHz∼1.8 × 10-20 W m-2Hz-1 sr-1, and α = -0.35 (S ∝ να). The radio spectrum has local variations which correlate with total intensity features. The brighter radio filaments have a spectral index systematically flatter than the rest. The comparison of the radio emission with images in other spectral ranges reveal several excellent correlations. We conclude that (1) the encounter of the SNR shock with a molecular cloud to the east of W28 produced enhanced synchrotron and thermal X-ray emission, compression and distortion in the radio shell, Hα filaments, and the excitation of many OH (1720 MHz) masers exactly located in the interface between the shock front and the eastern molecular cloud; and (2) the interaction of the shock front moving toward us with molecular gas located in front of it has been responsible for the formation of the bright radio filaments seen in projection in the northern half of W28 and the excitation of more OH masers. Also, excellent radio/Hα correspondence is observed toward the northwest of the SNR. The total energy in relativistic particles is estimated in 2 × 1047 ergs.