Miracle-dz/UniFAR-FTUs huggingface dataset:
Graph Analysis of Functional Brain Networks in Patients with Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is one of the most common neurological disorders worldwide. Posttraumatic complaints are frequently reported, interfering with outcome. However, a consistent neural substrate has not yet been found. We used graph analysis to further unravel the complex interactions between functional brain networks, complaints, anxiety and depression in the sub-acute stage after mTBI. This study included 54 patients with uncomplicated mTBI and 20 matched healthy controls. Posttraumatic complaints, anxiety and depression were measured at two weeks post-injury. Patients were selected based on presence (n = 34) or absence (n = 20) of complaints. Resting-state fMRI scans were made approximately four weeks post-injury. High order independent component analysis resulted in 89 neural components that were included in subsequent graph analyses. No differences in graph measures were found between patients with mTBI and healthy controls. Regarding the two patient subgroups, degree, strength, local efficiency and eigenvector centrality of the bilateral posterior cingulate/precuneus and bilateral parahippocampal gyrus were higher, and eigenvector centrality of the frontal pole/ bilateral middle & superior frontal gyrus was lower in patients with complaints compared to patients without complaints. In patients with mTBI, higher degree, strength and eigenvector centrality of default mode network components were related to higher depression scores, and higher degree and eigenvector centrality of executive network components were related to lower depression scores. In patients without complaints, one extra module was found compared to patients with complaints and healthy controls, consisting of the cingulate areas. In conclusion, this research extends the knowledge of functional network connectivity after mTBI. Specifically, our results suggest that an imbalance in the function of the default mode- and executive network plays a central role in the interaction between emotion regulation and the persistence of posttraumatic complaints.
Rapid weight loss in the context of Ramadan observance: recommendations for judokas

Judo is a weight-classified combat sport, and many athletes seek to compete at the lightest possible weight category to gain an advantage from competing against shorter/smaller, and supposedly weaker opponents. To achieve a desired weight, most judokas opt for rapid weight loss techniques. Short-duration maximal efforts are not greatly affected by “making weight”, but prolonged and/or repeated exercise is significantly impaired. Negative effects on mood, ratings of perceived exertion, and cognitive function are also reported. Moreover, rapid weight loss reduces maximal cardiac output and glycogen stores, and impairs thermo-regulation. Limited empirical data suggest that Ramadan reduces judokas’ performance, and this is likely to be exacerbated by attempts at rapid weight loss. Weight reduction during Ramadan tends to be counterproductive, and judokas who aim for a lower weight category are advised to attempt any desired reduction of body mass during the weeks leading up to Ramadan, rather than during the holy month.
Hot and Spicy: Ups and Downs on the Price Floor and Ceiling at Japanese Supermarkets

This paper develops a model of dynamic pricing with menu cost for a monopolistic retail store. By examining the prices of two brands of curry paste, the model shows that frequent price changes appear to be the optimal price policy. The key reason behind this strategy is that customers differ in their willingness to pay, depending on whether they purchase the product for immediate consumption or to add to their inventory at home. The empirical results strongly support the model’s predictions that: (1) stores tend to lower prices when (a) the share of customers still holding inventory is low, and when (b) the expected number of customers is high; and (2) demand is negatively dependent on the duration of the lower price and positively dependent on the duration of the higher, regular price. Unlike in models that posit a negative dependence of current demand on past prices, the findings support the theory that inventory accumulation (when the price is low) and decumulation (when the price is high) drive short-run fluctuations in demand.
A Note on Dominating Fractional Factorial Two-Level Designs With Clear Two-Factor Interactions

This note builds on results from Wu, Mee, and Tang's article (henceforth WMT) on admissible fractional factorial two-level designs, specifically concentrating on the “dominating designs” that were introduced but not further pursued in WMT. WMT's work has been used for increasing the efficiency of the author's graph-based algorithm for creation of minimum aberration designs that keep a requirement set of two-factor interactions clear: That algorithm originally searched aberration-sorted complete catalogs of nonisomorphic resolution IV designs; according to WMT's proposal, it suffices to search the dominating designs. For implementing this reduction of search space, aberration-sorted catalogs of dominating resolution IV regular fractional factorial two-level designs with up to 128 runs were created; this was achieved with the help of a recent subgraph isomorphism algorithm by Solnon that proved to be particularly efficient for this search task. The online supplementary materials provide the code used for identifying the dominating designs and ASCII files with the design generators for all resolution IV and higher dominating designs in 64 and 128 runs.
Constructing Realistic Engrams: Poststimulus Activity of Hippocampus and Dorsal Striatum Predicts Subsequent Episodic Memory

Encoding of real-life episodic memory commonly involves integration of information as the episode unfolds. Offline processing immediately following event offset is expected to play a role in encoding the episode into memory. In this study, we examined whether distinct human brain activity time-locked to the offset of short narrative audiovisual episodes could predict subsequent memory for the gist of the episodes. We found that a set of brain regions, most prominently the bilateral hippocampus and the bilateral caudate nucleus, exhibit memory-predictive activity time-locked to the stimulus offset. We propose that offline activity in these regions reflects registration to memory of integrated episodes.
XCpp : Preprocessing without Some Common Pitfalls

Preprocessing (e.g., cpp) is a simple technique to handle program variants by including/excluding variant feature code to/from a base program. When variant features grow in number, they affect the base code and each other in many places, and feature interactions lead to hidden dependencies among many code segments. Code becomes heavily instrumented with preprocessing directives, difficult to understand, test, maintain and reuse. In the paper, we describe XCpp, a system that to certain extent alleviates some of these problems, by extending preprocessing mechanisms, and providing a query-based visual environment for analysis of feature interaction patterns. XCpp is a subset of XVCL generative technique and tools [27]. We use a sizable study to illustrate problems that such extended preprocessing can and cannot solve. XCpp concepts can enhance any preprocessing system known to us, such as cpp or m4, providing similar benefits, and added values as a variation mechanism in reuse via Product Line approach. We compare XCpp with compositional and annotative approaches proposed in research.
A Unified Learning Framework of Skip-Grams and Global Vectors

Log-bilinear language models such as SkipGram and GloVe have been proven to capture high quality syntactic and semantic relationships between words in a vector space. We revisit the relationship between SkipGram and GloVe models from a machine learning viewpoint, and show that these two methods are easily merged into a unified form. Then, by using the unified form, we extract the factors of the configurations that they use differently. We also empirically investigate which factor is responsible for the performance difference often observed in widely examined word similarity and analogy tasks.
Modulation of myostatin expression during modified muscle use

Previous findings have provided strong evidence that myostatin functions as a negative regulator of muscle mass during development and growth. In the present study, we test the hypothesis that myostatin may serve a similar function in fully differentiated muscle experiencing modified loading. Our findings show that myostatin expression can be modulated in fully differentiated, non‐pathological skeletal muscle in a manner that is inversely related to changes in muscle mass. Atrophy of rat hind limb muscles induced by 10 days of unloading resulted in a 16% decrease in plantaris mass, a 110% increase in myostatin mRNA, and a 37% increase in myostatin protein. Immunohisto‐chemical observations showed a detectable increase in myostatin concentration at myotendinous junctions during muscle unloading. The concentration of myostatin mRNA and protein returned to values not significantly different from ambulatory controls after 4 days of reloading, during which time plantaris mass also returned to control values. However, the results also show that periods of 30 min of daily muscle loading during the unloading period were sufficient to prevent significant losses of muscle mass caused by unloading, although myostatin mRNA still showed a 55% increase in concentration. Thus, significant increases in myostatin expression are not sufficient for muscle mass loss, although muscle mass loss during unloading is accompanied by increases in myostatin. —Wehling, M. , Cai, B. , Tidball, J. G. Modulation of myostatin expression during modified muscle use. FASEB J. 14, 103–110(2000)
Search for mixing-induced CP violation using partial reconstruction of ¯ B 0 → D (cid:1)þ X l − ¯ ν l and kaon tagging

(Received We describe in detail a previously published measurement of CP violation in B 0 - ¯ B 0 oscillations, based on an integrated luminosity of 425 . 7 fb − 1 collected by the BABAR experiment at the PEPII collider. We apply a novel technique to a sample of about 6 million ¯ B 0 → D (cid:1)þ l − ¯ ν l decays selected with partial reconstruction of the D (cid:1)þ meson. The charged lepton identifies the flavor of one B meson at its decay time, the flavor of the other B is determined by kaon tagging. We determine a CP violating asymmetry A CP ¼ ð N ð B 0 B 0 Þ − N ð ¯ B 0 ¯ B 0 ÞÞ = ð N ð B 0 B 0 Þ þ N ð ¯ B 0 ¯ B 0 ÞÞ ¼ ð 0 . 06 (cid:3) 0 . 17 þ 0 . 38 − 0 . 32 Þ % corresponding to Δ CP ¼ 1 − j q=p j ¼ ð 0 . 29 (cid:3) 0 . 84 þ 1 . 88 − 1 . 61 Þ × 10 − 3 . This measurement is consistent and competitive with those obtained at the B factories with dilepton events.
Dysregulation of the miR-34a-SIRT1 axis inhibits breast cancer stemness

Enforced expression of miR-34a eliminates cancer stem cells in some malignant tumors. Sirtuin-1 (SIRT1) is a direct target of miR-34a. Here we found low levels of miR-34a and high levels of SIRT1 in CD44+/CD24− breast cancer stem cells (BCSCs). MiR-34a overexpression and knockdown of SIRT1 decreased proportion of BSCSs and mammosphere formation. Expression of CSC markers, ALDH1, BMI1 and Nanog was decreased. In nude mice xenografts, stable expression of miR-34a and silencing of SIRT1 reduced tumor burden. Taken together, our results demonstrated that miR-34a inhibits proliferative potential of BCSCs in vitro and in vivo, at least partially by downregulating SIRT1. The miR-34a-SIRT1 axis may play role in self-renewal of BCSCs.
Are Multilayer Perceptrons Adequate for Pattern Recognition and Verification?

Discusses the ability of multilayer perceptrons (MLPs) to model the probability distribution of data in typical pattern recognition and verification problems. It is proven that multilayer perceptrons with sigmoidal units and a number of hidden units less or equal than the number of inputs are unable to model patterns distributed in typical clusters, since these networks draw open separation surfaces in the pattern space. When using more hidden units than inputs, the separation surfaces can be closed but, unfortunately it is proven that determining whether or not a MLP draws closed separation surfaces in the pattern space is NP-hard. The major conclusion of the paper is somewhat opposite to what is believed and reported in many application papers: MLPs are definitely not adequate for applications of pattern recognition requiring a reliable rejection and, especially, they are not adequate for pattern verification tasks.
The Economic Determinants of Interest Rate Option Smiles

We address three questions relating to the interest rate options market: What is the shape of the smile? What are the economic determinants of the shape of the smile? Do these determinants have predictive power for the future shape of the smile and vice versa? We investigate these issues using daily bid and ask prices of euro ([euro]) interest rate caps/floors. We find a clear smile pattern in interest rate options. The shape of the smile varies over time and is affected in a dynamic manner by yield curve variables and the future uncertainty in the interest rate markets; it also has information about future aggregate default risk. Our findings are useful for the pricing, hedging and risk management of these derivatives.
The Use of Finite Difference/Element Approaches for Solving the Time-Fractional Subdiffusion Equation

In this paper, two finite difference/element approaches for the time-fractional subdiffusion equation with Dirichlet boundary conditions are developed, in which the time direction is approximated by the fractional linear multistep method and the space direction is approximated by the finite element method. The two methods are unconditionally stable and convergent of order $O(\tau^q+h^{r+1})$ in the $L^2$ norm, where $q=2-\beta$ or 2 when the analytical solution to the subdiffusion equation is sufficiently smooth, $\beta\,(0<\beta<1)$ is the order of the fractional derivative, $\tau$ and $h$ are the step sizes in time and space, respectively, and $r$ is the degree of the polynomial space. The corresponding schemes for the subdiffusion equation with Neumann boundary conditions are presented as well, where the stability and convergence are shown. Numerical examples are provided to verify the theoretical analysis. Comparisons between the algorithms derived in this paper and the existing algorithms are given, .
Investigating the Use and Acceptance of Technologies by Professors in a Higher Education Institution

This article analyses the use and acceptance of technologies by professors in the teaching and learning context in a higher education institution. In the empirical study, a questionnaire based on the technology acceptance model was applied. The results indicated that the most used technologies are Moodle, Facebook and YouTube and it was concluded that in general, those technologies are well accepted. Few statistically significant differences between respondents' gender, scientific areas or ages were found, revealing that the use of those technologies is already widespread in the studied institution. Results also showed that perceived usefulness and perceived ease of use are two important determinants of Moodle acceptance, and that the majority of respondents did not know the MOOC concept. This article is valuable for researchers in the area and for professors that want to implement the use technologies in the teaching and learning context.
Enabling ITS real world experimentation in NITOS future Internet facility

Inter-Vehicle Communication is expected to be widely adopted during the next years by the car industry, enabling Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication targeting at safer commuting. Therefore, the research community have been working towards providing a robust communication solution that will interoperate with existing network infrastructure and will provide an effective way of communicating using location information. One of the proposed solutions is the GeoNetworking protocol, standardized by ETSI, using location based addresses and an IPv6 adaptation sublayer for communicating with the Internet. Several implementations of the protocol exist currently, however most of them are integrated in simulation environments, thus ignoring several factors induced when experimenting under real conditions. In this paper we present our own implementation of an ETSI compliant GeoNetworking protocol and its integration in the NITOS Future Internet facility that enables open and remote access to experimenters on a 24/7 basis. This is the first real implementation in an open wireless testbed, which offers to the research community high diversity in the configuration parameters of their ITS experiments. We further explain our extensions that enable real world testing of our protocol implementation and we finally evaluate our solution in a real large scale wireless setup.
T-cell phenotype in protocol renal biopsy from transplant recipients treated with belatacept-mediated co-stimulatory blockade.

BACKGROUND Belatacept is thought to disrupt the interaction between CD80/86 and CD28, thus preventing T-cell activation by blocking the co-stimulatory second signal. However, the consequences on the T-cell profile in human renal transplant cases have not been determined. METHODS In this study, we analysed intra-graft levels of the mRNAs for Treg (FOXP3), cytotoxic CD8 T cells (Granzyme B), Th1 (INFγ, Tbet), Th2 (GATA3) and Th17 (RORγt and IL-17) in protocol biopsies obtained 12 months after renal transplantation in recipients treated with Belatacept or calcineurin inhibitor (CNI). RESULTS Only the intra-graft abundance of FOXP3 mRNA was significantly lower (P < 0.001) in the Belatacept group than the CNI group. Conclusions. These results are in agreement with in vitro data suggesting that CD28 is a major co-stimulatory signal of both Tregs development and peripheral homeostasis but contrast with clinical trials showing a better 1-year graft function and a lower incidence of chronic allograft nephropathy in patients receiving Belatacept than patients treated with CNI. They suggest that immune benefits induced by Belatacept are not mediated by Treg expansion and that FOXP3 is not by itself a prognostic marker of long-term graft function in a non-inflammatory context. These results have to be, however, considered as preliminary since the size of our study population is limited.
Statistical part-based models: theory and applications in image similarity, object detection and region labeling

The automatic analysis and indexing of visual content in unconstrained domain are important and challenging problems for a variety of multimedia applications. Much of the prior research work deals with the problems by modeling images and videos as feature vectors, such as global histogram or block-based representation. Despite substantial research efforts on analysis and indexing algorithms based on this representation, their performance remains unsatisfactory. This dissertation attempts to explore the problem from a different perspective through a part-based representation, where images and videos are represented as a collection of parts with their appearance and relational features. Such representation is partly motivated by the human vision research showing that the human vision system adopts similar mechanism to perceive images. Although part-based representation has been investigated for decades, most of the prior work has been focused on ad hoc or deterministic approaches, which require manual designs of the models and often have poor performance for real-world images or videos due to their inability to model uncertainty and noise. The main focus of this thesis instead is on incorporating statistical modeling and machine learning techniques into the paradigm of part-based modeling so as to alleviate the burden of human manual design, achieve the robustness to content variation and noise, and maximize the performance by learning from examples. We focus on the following three fundamental problems for visual content indexing and analysis: measuring the similarity of images, detecting objects and learning object models, and assigning semantic labels to the regions in images. We focus on a general graph-based representation for images and objects, called Attributed Relational Graph (ARG). We explore new statistical algorithms based upon this representation. Our main contributions include the following: First, we introduce a new principled similarity measure for ARGs that is able to learn the similarity from training data. We establish a theoretical framework for the similarity calculation and learning. And we have applied the developed method to detection of near-duplicate images. Second, we extend the ARG model and traditional Random Graph to a new model called Random Attributed Relational Graph (Random ARG) to represent an object model. We show how to achieve object detection through constructing Markov Random Fields, mapping parameters and performing approximations using advanced inference and learning algorithms. Third, we explore a higher-order relational model and efficient inference algorithms for the region labeling problem, using video scene text detection as a test case.
Fabrication of embedded microvalve on PMMA microfluidic devices through surface functionalization

The integration of a PDMS membrane within orthogonally placed PMMA microfluidic channels enables the pneumatic actuation of valves within bonded PMMA-PDMS-PMMA multilayer devices. Here, surface junctionalization of PMMA substrates via acid catalyzed hydrolysis and air plasma corona treatment were investigated as possible techniques to permanently bond PMMA microfluidic channels to PDMS surfaces. FTIR and water contact angle analysis of functionalized PMMA substrates showed that air plasma corona treatment was most effective in inducing PMMA hydrophilicity. Subsequent fluidic tests showed that air plasma modified and bonded PMMA multilayer devices could withstand fluid pressure at an operational flow rate of 9 muL/min. The pneumatic actuation of the embedded PDMS membrane was observed through optical microscopy and an electrical resistance based technique. PDMS membrane actuation occurred at pneumatic pressures of as low as 10 kPa and complete valving occurred at 14 kPa for ~100 pm times 100 pm channel cross-sections.