Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining intrinsic thalamic resting state networks using graph theory analysis: Implications for mTBI detection

A major challenge associated with understanding mild traumatic brain injury (mTBI) is the absence of biomarkers in standard clinical imaging modalities. Furthermore, the inhomogeneity of mTBI location and intensity, combined with latent symptoms further complicates identification and treatment. A growing body of evidence suggests that the thalamus may be injured or susceptible to change as the result of mTBI. A significant number of connections to and from cortical, subcortical, cerebellar and brain stem regions converge at the thalamus. Furthermore, the thalamus is also involved with information processing, integration and the regulation of specific behaviors. We use graph theory analysis to evaluate intrinsic functional networks of the left and right thalamus in mTBI subjects (N=15) and neurologically intact healthy controls (N=12). We also explore neural correlates of the thalamic network architecture with clinical assessments. Our results suggest the presence of distinct unilateral thalamic differences in mTBI subjects. We also observe correlations of the thalamic changes with clinical assessments. The findings from this study have implications for functional networks in the thalamus and its projections for application as a potential biomarker for mTBI detection.
Laparoscopic Gastrectomy with Enhanced Recovery After Surgery Protocol: Single-Center Experience

Background Surgery remains the mainstay of gastric cancer treatment. It is, however, associated with a relatively high risk of perioperative complications. The use of laparoscopy and the Enhanced Recovery After Surgery (ERAS) protocol allows clinicians to limit surgically induced trauma, thus improving recovery and reducing the number of complications. The aim of the study is to present clinical outcomes of patients with gastric cancer undergoing laparoscopic gastrectomy combined with the ERAS protocol. Material/Methods Fifty-three (21 female/32 male) patients who underwent elective laparoscopic total gastrectomy due to cancer were prospectively analyzed. Demographic and surgical parameters were assessed, as well as the compliance with ERAS protocol elements, length of hospital stay, number of complications, and readmissions. Results Mean operative time was 296.4±98.9 min, and mean blood loss was 293.3±213.8 mL. In 3 (5.7%) cases, conversion was required. Median length of hospital stay was 5 days. Compliance with ERAS protocol was 79.6±14.5%. Thirty (56.6%) patients tolerated an early oral diet well within 24 h postoperatively; in 48 (90.6%) patients, mobilization in the first 24 hours was successful. In 17 (32.1%) patients, postoperative complications occurred, with 7 of them (13.2%) being serious (Clavien-Dindo 3-5). The 30-day readmission rate was 9.4%. Conclusions The combination of laparoscopy and the ERAS protocol in patients with gastric cancer is feasible and allows achieving good clinical outcomes.
A multi-objective meta-model assisted memetic algorithm with non gradient-based local search

In this paper, we present an approach in which a local search mechanism is coupled to a multi-objective evolutionary algorithm. The local search mechanism is assisted by a meta-model based on support vector machines. Such a mechanism consists of two phases: the first one involves the use of an aggregating function which is defined by different weighted vectors. For the (scalar) optimization task involved, we adopt a non-gradient mathematical programming technique: the Hooke-Jeeves method. The second phase computes new solutions departing from those obtained in the first phase. The local search engine generates a set of solutions which are used in the evolutionary process of our algorithm. The preliminary results indicate that our proposed approach is quite promising.
Normal modes for predicting protein motions: A comprehensive database assessment and associated Web tool

We carry out an extensive statistical study of the applicability of normal modes to the prediction of mobile regions in proteins. In particular, we assess the degree to which the observed motions found in a comprehensive data set of 377 nonredundant motions can be modeled by a single normal‐mode vibration. We describe each motion in our data set by vectors connecting corresponding atoms in two crystallographically known conformations. We then measure the geometric overlap of these motion vectors with the displacement vectors of the lowest‐frequency mode, for one of the conformations. Our study suggests that the lowest mode contains useful information about the parts of a protein that move most (i.e., have the largest amplitudes) and about the direction of this movement. Based on our findings, we developed a Web tool for motion prediction (available from http://molmovdb.org/nma) and apply it here to four representative motions—from bacteriorhodopsin, calmodulin, insulin, and T7 RNA polymerase.
COMPILATION OF MEASURED NUTRIENT LOAD DATA FOR AGRICULTURAL LAND USES IN THE UNITED STATES 1

ABSTRACT: Measured field scale data are increasingly used to guide policy and management decisions based on comparative pollutant load information from various land management alternatives. The primary objective of this study was to compile measured annual nitrogen (N) and phosphorus (P) load data representing field scale transport from agricultural land uses. This effort expanded previous work that established an initial nutrient export coefficient dataset. Only measured annual N and P load data published in scientific peer‐reviewed studies were included in the present compilation. Additional criteria for inclusion were: spatial scale (field scale or farm scale, minimum 0.009 ha); land use (homogeneous, either cultivated agriculture or pasture/rangeland/hay); natural rainfall (not rainfall simulation); and temporal scale (minimum one year). Annual N and P load data were obtained from 40 publications, resulting in a 163‐record database with more than 1,100 watershed years of data. Basic descriptive statistics in relation to N and P loads were tabulated for tillage management, conservation practices, fertilizer application, soil texture, watershed size, and land use (crop type). The resulting Measured Annual Nutrient loads from A Circumlittoral Environments (MANAGE) database provides readily accessible, easily queried watershed characteristic and nutrient load data and establishes a platform suitable for input of additional project specific data.
Action recognition with skeletal volume and deep learning

The use of depth sensors in activity recognition is a technology that emerges in human computer interaction and motion recognition. In this study, an approach to identify single-person activities using deep learning on depth image sequences is presented. First, a 3D volumetric template is generated using skeletal information obtained from a depth video. The generated 3D volume is used for extracting features by taking images from different angles at different volumes. Actions are recognized by extracting deep features using AlexNet model [1] and Histogram of Oriented Gradients (HOG) features from these images. The proposed method has been tested with MSRAction3D [2] and UTHKinect-Action3D [2] datasets. The obtained results were comparable to similar studies in the literature.
Get more device drivers out of the kernel

Now that Linux has fast system calls, good (and getting better) threading, and cheap context switches, it’s possible to write device drivers that live in user space for whole new classes of devices. Of course, some device drivers (Xfree, in particular) have always run in user space, with a little bit of kernel support. With a little bit more kernel support (a way to set up and tear down DMA safely, and a generalised way to be informed of and control interrupts) almost any PCI bus-mastering device could have a user-mode device driver. I shall talk about the benefits and drawbacks of device drivers being in user space or kernel space, and show that performance concerns are not really an issue—in fact, on some platforms, our user-mode IDE driver out-performs the in-kernel one. I shall also present profiling and benchmark results that show where time is spent in in-kernel and user-space drivers, and describe the infrastructure I’ve added to the Linux kernel to allow portable, efficient userspace drivers to be written. ∗This work was funded by HP, National ICT Australia, the ARC, and the University of NSW through the Gelato programme (http://www.gelato.unsw. edu.au)
An Architectural Assessment of SPEC CPU Benchmark Relevance

SPEC compute intensive benchmarks are often used to evaluate processors in high-performance systems. However, such evaluations are valid only if these benchmarks are representative of more comprehensive real workloads. I present a comparative architectural analysis of SPEC CPU benchmarks and the more realistic SPEC Java Server benchmark. This analysis indicates the integer subset of CPU benchmarks are broadly representative of the branching and cache characteristics of server and business workloads. I also leverage the collected data to perform a statistical regression analysis, estimating an application’s performance as a linear function of its observed architectural characteristics. A linear model derived from simulated SPEC CPU data appears to fit the observed data quite well, with 94 percent of performance variance explained by four predictors that incorporate cache and queue usage. The linear model predicts server benchmark performance to within 2 percent of the observed value. Despite the regression model’s close fit to the observed data, its predictive ability is constrained by the trace collection facility. It is infeasible to use the performance of one trace suite to predict the performance of another trace suite if the underlying trace collection processes differ across suites.
Exosome Cofactors Connect Transcription Termination to RNA Processing by Guiding Terminated Transcripts to the Appropriate Exonuclease within the Nuclear Exosome*

The yeast Nrd1 interacts with the C-terminal domain (CTD) of RNA polymerase II (RNApII) through its CTD-interacting domain (CID) and also associates with the nuclear exosome, thereby acting as both a transcription termination and RNA processing factor. Previously, we found that the Nrd1 CID is required to recruit the nuclear exosome to the Nrd1 complex, but it was not clear which exosome subunits were contacted. Here, we show that two nuclear exosome cofactors, Mpp6 and Trf4, directly and competitively interact with the Nrd1 CID and differentially regulate the association of Nrd1 with two catalytic subunits of the exosome. Importantly, Mpp6 promotes the processing of Nrd1-terminated transcripts preferentially by Dis3, whereas Trf4 leads to Rrp6-dependent processing. This suggests that Mpp6 and Trf4 may play a role in choosing a particular RNA processing route for Nrd1-terminated transcripts within the exosome by guiding the transcripts to the appropriate exonuclease.
TROPE R HCRAESE R PAID I MULTIPLE OBJECT TRACKING USING FLOW LINEAR PROGRAMMING

Multi-object tracking can be achieved by detecting objects in individual frames and then linking detections across frames. Such an approach can be made very robust to the occasional detection failure: If an object is not detected in a frame but is in previous and following ones, a correct trajectory will nevertheless be produced. By contrast, a false-positive detection in a few frames will be ignored. However, when dealing with a multiple target problem, the linking step results in a difficult optimization problem in the space of all possible families of trajectories. This is usually dealt with by sampling or greedy search based on variants of Dynamic Programming, which can easily miss the global optimum. In this paper, we show that reformulating that step as a constrained flow optimization problem results in a convex problem that can be solved using standard Linear Programming techniques. In addition, this new approach is far simpler formally and algorithmically than existing techniques and lets us demonstrate excellent performance in two very different contexts.
Probabilistic online POMDP decision making for lane changes in fully automated driving

The Stadtpilot project aims at fully automated driving on Braunschweig's inner city ring road. The TU Braunschweig's research vehicle “Leonie” is one of the first vehicles having the ability of fully automated driving in real urban traffic scenarios. This paper shows our decision making approach for performing lane changes while driving fully automated in urban environments. We apply an online Partially Observable Markov Decision Process (POMDP) to accommodate inevitable sensor noise to be faced in urban traffic scenarios. In this paper we propose a two step algorithm to keep the complexity of the POMDP low enough for real-time decision making while driving. The presented approach has been integrated in our vehicle and was evaluated in real urban traffic.
Zn2+‐induced Ca2+ release via ryanodine receptors triggers calcineurin‐dependent redistribution of cortical neuronal Kv2.1 K+ channels

Increases in intracellular Zn2+ concentrations are an early, necessary signal for the modulation of Kv2.1 K+ channel localization and physiological function. Intracellular Zn2+‐mediated Kv2.1 channel modulation is dependent on calcineurin, a Ca2+‐activated phosphatase. We show that intracellular Zn2+ induces a significant increase in ryanodine receptor‐dependent cytosolic Ca2+ transients, which leads to a calcineurin‐dependent redistribution of Kv2.1 channels from pre‐existing membrane clusters to diffuse localization. As such, the link between Zn2+ and Ca2+ signalling in this Kv2.1 modulatory pathway is established. We observe that a sublethal ischaemic preconditioning insult also leads to Kv2.1 redistribution in a ryanodine receptor‐dependent fashion. We suggest that Zn2+ may be an early and ubiquitous signalling molecule mediating Ca2+ release from the cortical endoplasmic reticulum via ryanodine receptor activation.
Exploiting DBpedia for web search results clustering

We present a knowledge-rich approach to Web search result clustering which exploits the output of an open-domain entity linker, as well as the types and topical concepts encoded within a wide-coverage ontology. Our results indicate that, thanks to an accurate and compact semantification of the search result snippets, we are able to achieve a competitive performance on a benchmarking dataset for this task.
β-Secretase (BACE1) inhibition causes retinal pathology by vascular dysregulation and accumulation of age pigment

β‐Secretase (BACE1) is a major drug target for combating Alzheimer's disease (AD). Here we show that BACE1−/− mice develop significant retinal pathology including retinal thinning, apoptosis, reduced retinal vascular density and an increase in the age pigment, lipofuscin. BACE1 expression is highest in the neural retina while BACE2 was greatest in the retinal pigment epithelium (RPE)/choroid. Pigment epithelial‐derived factor, a known regulator of γ‐secretase, inhibits vascular endothelial growth factor (VEGF)‐induced in vitro and in vivo angiogenesis and this is abolished by BACE1 inhibition. Moreover, intravitreal administration of BACE1 inhibitor or BACE1 small interfering RNA (siRNA) increases choroidal neovascularization in mice. BACE1 induces ectodomain shedding of vascular endothelial growth factor receptor 1 (VEGFR1) which is a prerequisite for γ‐secretase release of a 100 kDa intracellular domain. The increase in lipofuscin following BACE1 inhibition and RNAI knockdown is associated with lysosomal perturbations. Taken together, our data show that BACE1 plays a critical role in retinal homeostasis and that the use of BACE inhibitors for AD should be viewed with extreme caution as they could lead to retinal pathology and exacerbate conditions such as age‐related macular degeneration.
Finite element modeling of compressive properties of three-dimensional woven composites under various strain rates

The compression properties of three-dimensional angle-interlock woven E-glass fabric/vinyl ester composite material along thickness direction under quasi-static (0.001 s−1) and high strain rates (800, 1600, and 2700 s−1) were investigated with finite element method and compared with those in experimental. The finite element method model was based on the three-dimensional woven composite microstructure. It was found that the compressive properties are sensitive to strain rate both in finite element method and experimental. The finite element method results showed good agreements with that of experimental in stress–strain curves and fracture morphologies. The obvious strain rate sensitivity of the compression properties and failure modes of three-dimensional angle interlock composites was both verified with the finite element method model and results in experimental. The compressive stiffness and maximum compressive stress increased with the strain rate while the failure strain showed an opposite trend. The failure mode is mainly in shear failure. The compressive failure mechanisms have been analyzed from the different components of the three-dimensional woven composites.
What Ion Flow along Ion Channels Can Tell us about Their Functional Activity

The functional activity of channel-forming peptides and proteins is most directly verified by monitoring the flow of physiologically relevant inorganic ions, such as Na+, K+ and Cl−, along the ion channels. Electrical current measurements across bilayer lipid membranes (BLMs) interposed between two aqueous solutions have been widely employed to this end and are still extensively used. However, a major drawback of BLMs is their fragility, high sensitivity toward vibrations and mechanical shocks, and low resistance to electric fields. To overcome this problem, metal-supported tethered BLMs (tBLMs) have been devised, where the BLM is anchored to the metal via a hydrophilic spacer that replaces and mimics the water phase on the metal side. However, only mercury-supported tBLMs can measure and regulate the flow of the above inorganic ions, thanks to mercury liquid state and high hydrogen overpotential. This review summarizes the main results achieved by BLMs incorporating voltage-gated channel-forming peptides, interpreting them on the basis of a kinetic mechanism of nucleation and growth. Hg-supported tBLMs are then described, and their potential for the investigation of voltage-gated and ohmic channels is illustrated by the use of different electrochemical techniques.
Computing motion using analog and binary resistive networks

The authors describe recent developments in the theory of early vision that led from the formulation of the motion problem as an ill-posed one to its solution by minimizing certain 'cost' functions. These cost or energy functions can be mapped onto simple analog and digital resistive networks. The optical flow is computed by injecting currents into resistive networks and recording the resulting stationary voltage distribution at each node. The authors believe that these networks, which they implemented in complementary metal-oxide-semiconductor (CMOS) very-large-scale integrated (VLSI) circuits, represent plausible candidates for biological vision systems. <<ETX>>
Decisions, Decisions … and Even More Decisions: Evaluation of a Digitized Mission Support System in the Land Warfare Domain

Digitized mission support systems are currently being introduced in the military arena. The projected benefits include quicker, better informed, more efficient decision making by the teams using them; however, these claims are often made without appropriate scientific testing. A live operational field trial of a land warfare digital mission support system was observed, and an integrated framework of Human Factors methods was used to evaluate performance with the mission support system. The findings indicated that, as a corollary of various flaws associated with the digital system, decision making was found to be more difficult, more drawn out, and more susceptible to error. Rather than augment the decision-making process, in some cases these flaws were seen to create further decision-making requirements for users. In closing, the implications of this study and the wider naturalistic decision making literature for the design of digitized mission support systems are discussed.
Proline and Glycinebetaine Confer Cadmium Tolerance on Tobacco Bright Yellow-2 Cells by Increasing Ascorbate-Glutathione Cycle Enzyme Activities

Cadmium (Cd) stress significantly decreased membrane integrity and impaired the ascorbate (ASC)-glutathione (GSH) cycle in tobacco Bright Yellow-2 cells. Exogenous application of proline and glycinebetaine (betaine) significantly restored the membrane integrity and increased the activities of ASC-GSH cycle enzymes under Cd stress without maintenance of the rich ASC or GSH pools. Moreover, proline offered more efficient protection against Cd stress than betaine.
Towards using neural networks to perform object-oriented function approximation

Many computational methods are based on the manipulation of entities with internal structure, such as objects, records, or data structures. Most conventional approaches based on neural networks have problems dealing with such structured entities. The algorithms presented in this paper represent a novel approach to neural-symbolic integration that allows for symbolic data in the form of objects to be translated to a scalar representation that can then be used by connectionist systems. We present the implementation of two translation algorithms that aid in performing object-oriented function approximation. We argue that objects provide an abstract representation of data that is well suited for the input and output of neural networks, as well as other statistical learning techniques. By examining the results of a simple sorting example, we illustrate the efficacy of these techniques.
Analysis of the frequent R1141X mutation in the ABCC6 gene in pseudoxanthoma elasticum.

PURPOSE To characterize the ABCC6 R1141X nonsense mutation, which is implicated in more than 25% of a cohort of patients from The Netherlands with pseudoxanthoma elasticum (PXE). METHODS A combination of single-strand conformational polymorphism (SSCP), PCR, sequencing, and Southern blot analysis was used to identify mutations in the ABCC6 gene in 62 patients. Haplotypes of 16 patients with the R1141X mutation were determined with eight polymorphic markers spanning the ABCC6 locus. The effect of the R1141X mutation on the expression of ABCC6 was studied in leukocytes and cultured dermal fibroblasts from affected skin in patients heterozygous or homozygous for the R1141X mutation. ABCC6 expression was analyzed by RT-PCR and immunocytochemistry with ABCC6-specific monoclonal antibodies. RESULTS The ABCC6 R1141X mutation was found on 19 alleles in 16 patients with PXE and occurred in heterozygous, homozygous, or compound heterozygous form. All R1141X alleles were associated with a common haplotype, covering at least three intragenic ABCC6 markers. None of the patients or healthy control subjects had a similar ABCC6 haplotype. Furthermore, the results showed that the expression of the normal allele in R1141X heterozygotes was predominant, whereas no detectable, or very low, ABCC6 mRNA levels were found in R1141X homozygotes. Immunocytochemical staining of cultured dermal fibroblasts with ABCC6-specific monoclonal antibodies showed no evidence of the presence of a truncated protein in patients with PXE who were homozygous for R1141X. CONCLUSIONS A specific founder effect for the R1141X mutation exists in Dutch patients with PXE. The R1141X mutation induces instability of the aberrant mRNA. Functional haploinsufficiency or loss of function of ABCC6 caused by mechanisms, such as nonsense-mediated decay (NMD), may be involved in the PXE phenotype.