Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Structure and Metropolitan Mobility

The objective of this research to develop quantitative measures that capture various aspects of underlying network structure, using aggregate level travel data from fifty metropolitan areas across the U.S. The influence of these measures on system performance is then tested using statistical regression models. The results corroborate that the quantitative measures of network structure affect the system performance. The results from this analysis can be used to develop network design guidelines that can be used to address current transportation problems.
Dilemmas and Strategies for Reading Unfamiliar Words Among Children Learning English as a Foreign Language

Abstract The present study investigates common word reading dilemmas across 3 word types among children learning English as a foreign language (EFL). It also examines the effectiveness of a new word reading strategy, perceptual diacritics, for facilitating EFL children’s word reading dilemmas through an experimental design in which the experimental group received training in word reading facilitated by perceptual diacritics. We recruited 46 5th graders who spoke Chinese as their primary language from an urban district primary school. Results indicated that word type strongly influenced the word reading performance of the EFL children. After the intervention, the experimental group improved equivalently across the 3 word types, whereas the control group still struggled with the 2 higher level word types. The findings imply that EFL children have common difficulties with phonological recoding of words with less predictable orthographic patterns. With the help of the new strategy, EFL children may better decode these inconsistent patterns phonologically.
Elliptic Curve Scalar Point Multiplication Algorithm Using Radix-4 Booth’s Algorithm

The main back-bone operation in elliptic curve cryptosystems is scalar point multiplication. The most frequently used method implementing the scalar point multiplication, which is performed in the topmost level of GF multiplication and GF division, has been the double-and-add algorithm, which is being recently challenged by NAF (Non-Adjacent Format) algorithm. In this paper, we propose a more efficient and novel approach of a scalar multiplication method than the double-and-add by applying redundant recoding which originates from the radix-4 modified Booth’s algorithm. We call the novel algorithm quad-and-add. After deriving the algorithm, we created a new GF operation, named point quadruple, and verified with calculations of a real-world application to utilize it. Derived numerical expressions were verified using both C programs and HDL (Hardware Description Language). Proposed method of elliptic curve scalar point multiplication can be utilized in many elliptic curve security applications for handling efficient and fast calculations.
Pancreatic cancer: State‐of‐the‐art care

This review focuses on the pathogenesis, diagnosis, staging, and treatment of pancreatic cancer. Although much is needed to improve the still dismal outlook for patients with this disease, significant progress has been made in its surgical and oncologic management. Furthermore, our deepening understanding of the molecular genetics of pancreatic cancer lends hope for the possibility of earlier detection, which would result in substantial improvements in survival.
Is 5´-AMP-Activated Protein Kinase Both Jekyll and Hyde in Bladder Cancer?

The 5´-AMP-activated protein kinase (AMPK) is a key regulator of cellular metabolism and energy homeostasis in mammalian tissues. Metabolic adaptation is a critical step in ensuring cell survival during metabolic stress. Because of its critical role in the regulation of glucose homeostasis and carbohydrate, lipid, and protein metabolism, AMPK is involved in many human diseases, including cancers. Although AMPK signaling was originally characterized as a tumor-suppressive signaling pathway, several lines of evidence suggest that AMPK plays a much broader role and cannot simply be defined as either an oncogenic regulator or tumor suppressor. Notably, several recent studies demonstrated that the antitumorigenic effects of many indirect AMPK activators, such as metformin, do not depend on AMPK. Conversely, activation of AMPK induces the progression of cancers, emphasizing its oncogenic effect. Bladder cancer can be divided into two groups: non–muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). The molecular mechanisms underlying these two types of cancer are distinct: NMIBC is associated with activation of the Ras pathway, whereas MIBC is characterized by loss of major tumor suppressors. Importantly, both pathways are connected to the mammalian target of rapamycin (mTOR) pathway. In addition, our recent metabolomic findings suggest that β-oxidation of fatty acids is an important factor in the development of bladder cancer. Both mTOR and β-oxidation are tightly associated with the AMPK pathway. Here, I summarize and discuss the recent findings on the two distinct roles of AMPK in cancer, as well as the relationship between bladder cancer and AMPK.
Relationship Banking: What Do We Know?

This paper briefly reviews the contemporary literature on relationship banking. We start out with a discussion of the raison d'etre of banks in the context of the financial intermediation literature. From there we discuss how relationship banking fits into the core economic services provided by banks, and its costs and benefits. This leads to an examination of the interrelationship between the competitive environment and relationship banking as well as a discussion of the empirical evidence.
Additive kappa can be increased by combining adjacent categories

Weighted kappa is a measure that is commonly used for quantifying similarity between two ordinal variables with identical categories. Additive kappa is a special case of weighted kappa that allows the researcher to specify distances between adjacent categories. It is shown that additive kappa is a weighted average of the additive kappas of all collapsed tables of a specific size. It follows that, if the reliability of a categorical rating instrument is assessed with additive kappa, the reliability can be increased by combining categories.
Illumination and Contrast Balancing for Remote Sensing Images

Building a mathematical model of uneven illumination and contrast is difficult, even impossible. This paper presents a novel image balancing method for a satellite image. The method adjusts the mean and standard deviation of a neighborhood at each pixel and consists of three steps, namely, elimination of coarse light background, image balancing, and max-mean-min radiation correction. First, the light background is roughly eliminated in the frequency domain. Then, two balancing factors and linear transformation are used to adaptively adjust the local mean and standard deviation of each pixel. The balanced image is obtained by using a color preserving factor after max-mean-min radiation correction. Experimental results from visual and objective aspects based on images with varying unevenness of illumination and contrast indicate that the proposed method can eliminate uneven illumination and contrast more effectively than traditional image enhancement methods, and provide high quality images with better visual performance. In addition, the proposed method not only restores color information, but also retains image details.
Systematic Review and Meta-Analysis of Perioperative Intravenous Tranexamic Acid Use in Spinal Surgery

Background Tranexamic acid (TXA) is well-established as a versatile oral, intramuscular, and intravenous (IV) antifibrinolytic agent. However, the efficacy of IV TXA in reducing perioperative blood transfusion in spinal surgery is poorly documented. Methodology We conducted a meta-analysis of randomized controlled trials (RCTs) and quasi-randomized (qi-RCTs) trials that included patients for various spinal surgeries, such as adolescent scoliosis surgery administered with perioperative IV TXA according to Cochrane Collaboration guidelines using electronic PubMed, Cochrane Central Register of Controlled Trials, and Embase databases. Additional journal articles and conference proceedings were manually located by two independent researchers. Results Totally, nine studies were included, with a total sample size of 581 patients. Mean blood loss was decreased in patients treated with perioperative IV TXA by 128.28 ml intraoperatively (ranging from 33.84 to 222.73 ml), 98.49 ml postoperatively (ranging from 83.22 to 113.77 ml), and 389.21 ml combined (ranging from 177.83 to 600.60 ml). The mean volume of transfused packed cells were reduced by 134.55 ml (ranging 51.64 to 217.46) (95% CI; P = 0.0001). Overall, the number of patients treated with TXA who required blood transfusions was lower by 35% than that of patients treated with the comparator and who required blood transfusions (RR 0.65; 95% CI; 0.53 to 0.85; P<0.0001, I2 = 0%). A dose-independent beneficial effect of TXA was observed, and confirmed in subgroup and sensitivity analyses. A total of seven studies reported DVT data. The study containing only a single DVT case was not combined. Conclusions The blood loss was reduced in spinal surgery patients with perioperative IV TXA treatment. Also the percentage of spinal surgery patients who required blood transfusion was significantly decreased. Further evaluation is required to confirm our findings before TXA can be safely used in patients undergoing spine surgery.
Fifth‐generation lithospheric magnetic field model from CHAMP satellite measurements

Six years of low‐orbit CHAMP satellite magnetic measurements have provided an exceptionally high‐quality data resource for lithospheric magnetic field modeling and interpretation. Here we describe the fifth‐generation satellite‐only magnetic field model MF5. The model extends to spherical harmonic degree 100. As a result of careful data selection, extensive corrections, filtering, and line leveling, the model has low noise levels, even if evaluated at the Earth's surface. The model is particularly suited for inferring large‐scale structure and composition of the lithosphere. It is also meant to serve as the long‐wavelength part of continental‐ and global‐scale marine and aeromagnetic anomaly maps.
Salary 1st Career 1st Potential Romantic Partner

AND CONCRETE MINDSETS Of the many cues present in any situation, which will captivate one’s interest? Addressing this question is among behavioral science’s basic challenges, in that, as advertisers, political operatives, and other aspiring opinion-makers recognize, human action grows directly from what people attend to and how they interpret it. My collaborators and I are exploring the role of self-regulatory mindsets in determining how people interpret everyday events, opportunities, and situations (Freitas, Gollwitzer, & Trope, 2004). Building on related work (Freitas, Salovey, & Liberman, 2001), we have suggested that thinking about the abstract aims (versus underlying action procedures) of an activity will increase the accessibility of the general cognitive operation of considering activities’ abstract purposes (versus underlying processes), thus coloring how one construes newly encountered information. Balancing concerns about long-term, abstract aims with concerns about the immediate, concrete actions one must carry out in order to reach those aims constitutes a core essence of self-regulation. Accordingly, this hypothesized impact of an abstract or concrete mindset across different content domains may influence a broad range of thought and behavior. Construing Others’ Goals In one series of studies testing these ideas, subjects assigned to an “abstract mindset” manipulation thought about their own abstract, long-term goals, whereas subjects assigned to a “concrete mindset” manipulation thought about concrete, specific procedures by which they might meet their goals. Next, in an “unrelated” experiment, they indicated what kinds of goals they thought others should pursue. As shown in Figure 1, participants in an abstract mindset were more likely to suggest that others pursue important, long-term goals, even in the face of immediate difficulties. Participants in a concrete mindset, in contrast, were relatively more sensitive to the difficulty of the underlying tasks others needed to carry out.
Mean square stabilization of vector LTI systems over power constrained lossy channels

This paper studies the mean square stabilization problem of vector LTI systems over power constrained lossy channels. The communication channel is with packet dropouts, additive noises and input power constraints. To overcome the difficulty of optimally allocating channel resources among different sub-dynamics, schedulers are designed with time division multiplexing of channels. An adaptive TDMA (Time Division Multiple Access) scheduler is proposed first, which is shown to be able to achieve a larger stabilizability region than the conventional TDMA scheduler, and is optimal under some special cases. In particular, for two-dimensional systems, an optimal scheduler is designed, which provides the necessary and sufficient condition for mean square stabilization.
Cache-conscious Frequent Pattern Mining on a Modern Processor

In this paper, we examine the performance of frequent pattern mining algorithms on a modern processor. A detailed performance study reveals that even the best frequent pattern mining implementations, with highly efficient memory managers, still grossly under-utilize a modern processor. The primary performance bottlenecks are poor data locality and low instruction level parallelism (ILP). We propose a cache-conscious prefix tree to address this problem. The resulting tree improves spatial locality and also enhances the benefits from hardware cache line prefetching. Furthermore, the design of this data structure allows the use of a novel tiling strategy to improve temporal locality. The result is an overall speedup of up to 3.2 when compared with state-of-the-art implementations. We then show how these algorithms can be improved further by realizing a non-naive thread-based decomposition that targets simultaneously multi-threaded processors. A key aspect of this decomposition is to ensure cache re-use between threads that are co-scheduled at a fine granularity. This optimization affords an additional speedup of 50%, resulting in an overall speedup of up to 4.8. To the best of our knowledge, this effort is the first to target cache-conscious data mining.
Chromosomal Translocations in the Parasite Leishmania by a MRE11/RAD50-Independent Microhomology-Mediated End Joining Mechanism

The parasite Leishmania often relies on gene rearrangements to survive stressful environments. However, safeguarding a minimum level of genome integrity is important for cell survival. We hypothesized that maintenance of genomic integrity in Leishmania would imply a leading role of the MRE11 and RAD50 proteins considering their role in DNA repair, chromosomal organization and protection of chromosomes ends in other organisms. Attempts to generate RAD50 null mutants in a wild-type background failed and we provide evidence that this gene is essential. Remarkably, inactivation of RAD50 was possible in a MRE11 null mutant that we had previously generated, providing good evidence that RAD50 may be dispensable in the absence of MRE11. Inactivation of the MRE11 and RAD50 genes led to a decreased frequency of homologous recombination and analysis of the null mutants by whole genome sequencing revealed several chromosomal translocations. Sequencing of the junction between translocated chromosomes highlighted microhomology sequences at the level of breakpoint regions. Sequencing data also showed a decreased coverage at subtelomeric locations in many chromosomes in the MRE11-/-RAD50-/- parasites. This study demonstrates an MRE11-independent microhomology-mediated end-joining mechanism and a prominent role for MRE11 and RAD50 in the maintenance of genomic integrity. Moreover, we suggest the possible involvement of RAD50 in subtelomeric regions stability.
Endothelial Function and Chronic Exposure to Air Pollution in Normal Male Subjects

Exposure to urban air pollution, ultrafine particles or gases, is associated with acute cardiovascular mortality and morbidity. We investigated the effect of ambient air pollution on endothelial function in 40 healthy white male nonsmokers spontaneously breathing ambient air in Paris, France. Air pollutant levels (nitrogen, sulfur and carbon oxides, and particulate matter) were averaged during the 5 days preceding arterial measurements. Brachial artery endothelium-dependent flow-mediated dilatation and reactive hyperemia induced by hand ischemia and endothelium-independent glyceryl trinitrate dilatation were measured using a radiofrequency-based echo-tracking device at 2-week intervals. Flow-mediated dilatation was independently and negatively correlated with the average levels of sulfur dioxide (P<0.001) and nitrogen monoxide (P<0.01). Sulfur dioxide levels explained 19% of the variance of flow-mediated dilatation. An increase in gaseous pollutants, 2 weeks apart, was significantly associated with a decreased in flow-mediated dilatation. No association was found between air pollutants and glyceryl trinitrate–induced vasodilatation. Reactive hyperemia was significantly and positively correlated with particulate matter with aerodynamic diameters <10 &mgr;m and <2.5 &mgr;m (P<0.0001 and P<0.001, respectively) and nitrogen dioxide (P<0.01). An increase in particulate matter, 2 weeks apart, was significantly correlated with an increase in reactive hyperemia. Endothelial function was impaired by ordinary levels of pollution in healthy young males, in an urban area, and may be reduced by 50% between the least and the most polluted day. Gaseous pollutants affect large artery endothelial function, whereas particulate matter exaggerates the dilatory response of small arteries to ischemia.
Speaker Verification Based on Different Vector Quantization Techniques with Gaussian Mixture Models

The introduction of Gaussian Mixture Models (GMMs) in the field of speaker verification has led to very good results. This paper illustrates an evolution in state-of-the-art Speaker Verification by highlighting the contribution of recently established information theoretic based vector quantization technique. We explore the novel application of three different vector quantization algorithms, namely K-means, Linde-Buzo-Gray (LBG) and Information Theoretic Vector Quantization (ITVQ) for efficient speaker verification. The Expectation Maximization (EM) algorithm used by GMM requires a prohibitive amount of iterations to converge. In this paper, comparable alternatives to EM including K-means, LBG and ITVQ algorithm were tested. The GMM-ITVQ algorithm was found to be the most efficient alternative for the GMM-EM. It gives correct classification rates at a similar level to that of GMM-EM. Finally, representative performance benchmarks and system behaviour experiments on NIST SRE corpora are presented.
A Two-Stage Outdoor - Indoor Scene Classification Framework: Experimental Study for the Outdoor Stage

The state-of-the-art image classification methods require an intensive learning stage and a considerable amount of training images. Recently, with the introduction of these models (and in particular convolutional neural network (CNN)), it is believed that the best solution to achieve a system with high performance on scene classification is to learn deep scene features using CNN. While this can be true for large-scale image datasets (in the scale of one-million training images), the feasibility of reaching state-of-the-art performances in other complex datasets with a handful training examples remains unclear. Here, we argue that we can reach a highly accurate performance by presenting a simple model on the scene classification problem. This paper presents a hierarchical two-stage scene classification framework based on indoor versus outdoor notion. The suggested approach is a simple, yet a very efficient global image representation model for scene recognition. Though the term of indoor versus outdoor has been in the literature for quite a while, here we go further than that and propose a scene classifier model which classifies all the outdoor scene classes versus one undifferentiated indoor class. To achieve this, we tackle the problem of scene classification by using distributions of quantized filter responses to characterize the scenes. Later the classifier outputs either one of the several outdoor scene classes or a generic indoor scene class. We validate the proposed approach by feeding the algorithm with two benchmark datasets: 15-Scene category and SUN397. Successful experiments demonstrate the validity of the proposed approach. With the presented model, we reach an average accuracy of 97.84% and 55.1% in outdoor scenes and 93.09% and 92.4% in the indoor scene class on 15-Scene and SUN397 respectively.
Priority and relevance in belief revision

AGM model is the notable methodology in belief revision. But there are many AGM belief change operators when contract or revise a set of formulas by a formula. In order to obtain more useful belief change operator, researchers increase some interesting postulates to AGM postulates. On the one hand, Nebel give Prioritized belief change operator, a special AGM belief change operator, based on a relation over belief base/set. On the other hand, Parikh, Kourousias and Makinson formulated local belief change by the finest splitting over belief base/set. Naturally, whether there is a prioritized belief revision operator respects AGM postulates and relevance criterion or not? In the paper, we will answer the problem negatively by an example.
Delta Neutrophil Index as a Marker for Differential Diagnosis between Acute Graft Pyelonephritis and Acute Graft Rejection

Introduction The delta neutrophil index (DNI) is the fraction of circulating immature granulocytes, which reflect infectious and/or septic condition. Acute graft pyelonephritis (AGPN) versus acute graft rejection is a frequently encountered diagnostic and therapeutic dilemma in kidney transplant recipients, but little is known about the clinical usefulness of DNI value in the differentiation of the two conditions. Material & Methods A total of 90 episodes of AGPN or acute graft rejection were evaluated at the Kangdong Sacred Heart Hospital between 2008 and 2014. We performed retrospective analysis of demographic, clinical, and laboratory parameters data. Receiver operating curves (ROC) and multivariate logistic regression were conducted to ascertain the utility of DNI in discriminating between AGPN and acute graft rejection. Results AGPN group had significantly higher DNI values than acute graft rejection group (2.9% vs. 1.9%, P < 0.001). The area under the ROC curve for DNI value to discriminate between AGPN and acute graft rejection was 0.85 (95% confidence interval [CI]; 0.76–0.92, P < 0.001). A DNI value of 2.7% was selected as the cut-off value for AGPN, and kidney transplant recipients with a DNI value ≥ 2.7% were found to be at a higher risk of infection than those with a DNI < 2.7% (odd ratio [OR] 40.50; 95% CI 8.68–189.08; P < 0.001). In a multivariate logistic regression analysis, DNI was a significant independent factor for predicting AGPN after adjusting age, sex, log WBC count, log neutorphil count, log lymphocyte count, CRP concentration, and procalcitonin concentration (OR 4.32; 95% CI 1.81–10.34, P < 0.001). Conclusions This study showed that DNI was an effective marker to differentiate between AGPN and acute graft rejection. Thus, these finding suggest that DNI may be a useful marker in the management of these patients.