Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlation of Ischemia-Modified Albumin with SOFA and APACHE II Scores in Preoperative Patients with Colorectal Cancer

Purpose. Critical illnesses are assessed according to the sequential organ failure assessment (SOFA) and acute physiology and chronic health evaluation (APACHE) II. Circulating ischemia-modified albumin (IMA) is a biomarker generated under ischemic and oxidative conditions and may reflect disease severity in preoperative patients. This study investigated the correlations of IMA with SOFA and APACHE II scores in inpatients admitted for colorectal surgery. Methods. We examined 27 patients with advanced colorectal cancers (mean age 69 years, men/women = 15/12). Correlations between SOFA and APACHE II scores in addition to preoperative serum IMA and C-reactive protein (CRP) levels were analyzed. Results. The mean IMA level was 0.5 AU, and the median CRP level was 0.6 mg/dL. Median scores for SOFA and APACHE II were 2 and 12 points, respectively. Significant positive correlations between IMA and SOFA (r = 0.45, P < 0.05) and IMA and APACHE II (r = 0.45, P < 0.05) were identified which remained significant in confounder-adjusted analyses. In contrast, weak correlations were observed between CRP and the SOFA and APACHE II scores. Conclusions. The positive correlations between IMA and both SOFA and APACHE II scores suggest that serum IMA measurements reflect the severity of systemic failure in patients admitted for colorectal surgery in the preoperative phase.
Ultrafast polarization switching in thin-film ferroelectrics

We present an experimental approach to study the ultrafast polarization switching dynamics in thin-film ferroelectrics. A semiconductor photoconductive switch with femtosecond laser illumination is used as a “pulse generator” to produce jitter-free, sub-100 ps rise time step-function-like electrical pulses. Quantitative measurements yield a polarization switching time, ts, of ∼220 ps when measured with a 5 V, 68 ps rise time input electrical pulse. Modeling of the switching transients using the Merz–Ishibashi model and Merz–Shur model of switching kinetics yields a quantitative estimate of the characteristic switching time constant, t0, of ∼70–90 ps.
SM- Sens: Security middleware for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are exposed to numerous security threats that can affect the execution of applications. Securing WSNs is challenging due to their unique nature as an application and a network, and due to their limited capabilities. Therefore we introduce SM-Sens, a secure middleware that helps bridge the gap between high-level application requirements and WSN managing complexity. Our middleware uses defense mechanisms like asymmetric cryptography and authentication. The middleware defenses are efficient against a number of attacks either preventing from them or minimizing the damage they may cause to the network. We evaluate our middleware through extensive analysis, implementation, simulations and measurements. We argue that SM-Sens is viable and attractive to applications with security requirements.
An Ordered Inheritance Strategy for the Golgi Apparatus: Visualization of Mitotic Disassembly Reveals a Role for the Mitotic Spindle

During mitosis, the ribbon of the Golgi apparatus is transformed into dispersed tubulo-vesicular membranes, proposed to facilitate stochastic inheritance of this low copy number organelle at cytokinesis. Here, we have analyzed the mitotic disassembly of the Golgi apparatus in living cells and provide evidence that inheritance is accomplished through an ordered partitioning mechanism. Using a Sar1p dominant inhibitor of cargo exit from the endoplasmic reticulum (ER), we found that the disassembly of the Golgi observed during mitosis or microtubule disruption did not appear to involve retrograde transport of Golgi residents to the ER and subsequent reorganization of Golgi membrane fragments at ER exit sites, as has been suggested. Instead, direct visualization of a green fluorescent protein (GFP)-tagged Golgi resident through mitosis showed that the Golgi ribbon slowly reorganized into 1–3-μm fragments during G2/early prophase. A second stage of fragmentation occurred coincident with nuclear envelope breakdown and was accompanied by the bulk of mitotic Golgi redistribution. By metaphase, mitotic Golgi dynamics appeared to cease. Surprisingly, the disassembly of mitotic Golgi fragments was not a random event, but involved the reorganization of mitotic Golgi by microtubules, suggesting that analogous to chromosomes, the Golgi apparatus uses the mitotic spindle to ensure more accurate partitioning during cytokinesis.
Fibrobronchoscopic cryosurgery for secondary malignant tumors of the trachea and main bronchi

Patients with secondary malignant tracheal and main bronchial tumors may suffer severe symptoms as a result of major airway obstruction. Curative surgical resection is usually not suitable because of the presence of metastatic disease and poor performance status. In this study, the use of bronchoscopic cryosurgery to reopen the airway is analyzed.
Adolescent boys with obesity: The lived experiences

This study explored and described the lived experiences of adolescent boys who are obese. Participants were a purposive sample of nine boys between the ages of 13 and 18, six of them currently with obesity and with BMI levels at or above the 95th percentile for weight for height, and three with a history of obesity. Data were collected using in-depth phenomenological interviews, direct observations and field notes. Thematic coding was applied during the analysis process. Four themes emerged from the thematic analysis to characterise the adolescent boys’ experiences of being obese: living an empty life in a full body; vulnerable self-concept and low self-esteem; and being teased and humoured. They reported to cope with lived obesity by actively using motivation such as fear of death to lose weight and passively coping by wearing a mask. Obesity carries significant physical and psychological health risk to children in adolescence.
A deep wsrt 1.4 ghz radio survey of the spitzer space telescope flsv region

The First Look Survey (FLS) is the first scientific product to emerge from the Spitzer Space Telescope. A small region of this field (the verification strip) has been imaged very deeply, permitting the detection of cosmologically distant sources. We present Westerbork Synthesis Radio Telescope (WSRT) observations of this region, encompassing a ∼1 sq. deg field, centred on the verification strip (J2000 RA = 17:17:00.00, Dec = 59:45:00.000). The radio images reach a noise level of ∼8.5 µJy beam −1 - the deepest WSRT image made to date. We summarise here the first results from the project, and present the final mosaic image, together with a list of detected sources. The effect of source confusion on the position, size and flux density of the faintest sources in the source catalogue are also addressed. The results of a serendipitous search for H I emission in the field are also presented. Using a subset of the data, we clearly detect H I emission associated with four galaxies in the central region of the FLSv. These are identified with nearby, massive galaxies.
Effects of Age and Ability on Syllogistic Reasoning in Early Adolescence

To assess the influence of age and ability on linear syllogistic reasoning in early adolescence, 11 - and 13-year-old subjects of two levels of ability (bright and average) were presented with 64 three-term series problems (e.g., "If John is better than Bill, and Bill is better than Tom, then who is the best? "). Results showed that the effect of ability was quite dramatic even with verbal grade equivalent and Standard Progressive Matrices scores as covariates, whereas the effect of age was marginally significant and confounded with both. Comparison to Clark's 1969 adult sample showed that the pattern of errors was essentially similar for adolescents and adults, but more similar for the average than the bright subjects. Implications of the findings for Clark's theory and for a theory of intellectual precocity are discussed. A subject's success in correctly solving a problem depends on many factors: Some reflect momentary fluctuations in attention due to set and motivation; others reflect such long-term factors as the subject's intellectual ability, developmental level, and specific experiential history with the problem at hand. Our concern in this article is to investigate the effects of age and certain intellectual skills on the subject's syllogistic reasoning ability. In particular, we are concerned with the effects of subjects' reasoning skills at ages that correspond roughly to preformal and formal operational thought (Inhelder &
A Distributed Intrusion Detection Model Based on a Society of Intelligent Mobile Agents for Ad Hoc Network

The evolution of wireless network technologies and the recent advances in mobile computing hardware have made possible the introduction of various applications in mobile adhoc networks. Not only is the infrastructure of these networks inherently vulnerable but they have increased requirements regarding their security as well. As intrusion prevention mechanisms, such as encryption and authentication, are not sufficient regarding security, we need a second line of defence, Intrusion Detection. The focus of this paper is on distributed and intelligent intrusion detection. We propose a model for building a distributed and behavioural intrusion detection system by using a classification method.
Document representation based on semantic smoothed topic model

The goal of document representation is to capture certain feature of the document. Many existing document representation methods are based on bag-of-words and ignore semantic relevance between words in the document. There we proposed a semantic smoothed topic model to represent document. It takes semantic similarity into consideration for topic of document. We conducted two experiments utilizing this method for text classification and information retrieval task. The experimental results suggest that our method is useful for capturing the semantic of text to alleviating polysemy and synonyms problem and data sparseness problem.
Trajectories of binge drinking differentially mediate associations between adolescent violence exposure and subsequent adjustment in young adulthood.

Violence exposure in adolescence can disrupt ongoing adjustment, yet few studies have examined potential mechanisms that can explain these effects. Using data from the National Longitudinal Study of Adolescent to Adult Health, we examined associations among adolescent violence exposure and indicators of adjustment in young adulthood, and tested whether maladaptive trajectories of binge drinking could mediate these associations. Adolescents (N 3,342; Mage 16.09) reported on their violence exposure and binge drinking in an initial assessment (Wave 1). Adolescents were subsequently reassessed for binge drinking at 1 (Wave 2) and 6 years (Wave 3) post, and completed measures of adjustment (education, physical health, life satisfaction, depression, and delinquency) at 6 years post (Wave 3). Latent growth mixture modeling revealed 4 binge drinking trajectories: High Increasers (low baseline, large positive slope), Adolescence Elevated (high baseline, negative slope), Mid-Tier Stable (midlevel baseline, flat slope), and Slight Increasers (low baseline, small positive slope). Violence exposure was indirectly associated with (a) lower educational attainment and greater delinquency through an increased likelihood of being in the Adolescence Elevated binge drinking class, (b) lower life satisfaction through an increased likelihood of being in the High Increasers binge drinking class, and (c) worse physical heath through an increased likelihood of being in the Mid-Tier Stable binge drinking class. Violence-exposed adolescents may exhibit varying trajectories of binge drinking that carry differential risks for adverse outcomes, and disrupt adjustment during the transition to young adulthood. Implications for intervention and theory are discussed.
Critical view on the deeply bound K − pp system

We briefly review the situation around the claimed deeply bound ${K}^{\ensuremath{-}}$ states in different recent experiments and concentrate particularly on the state ${K}^{\ensuremath{-}}\mathit{pp}$ advocated by the FINUDA collaboration in nuclear ${K}^{\ensuremath{-}}$ absorption. We perform a theoretical simulation of the process and show that the peak in the $\ensuremath{\Lambda}p$ spectrum that was interpreted as a deep ${K}^{\ensuremath{-}}\mathit{pp}$ bound state corresponds mostly to the process ${K}^{\ensuremath{-}}pp\ensuremath{\rightarrow}\ensuremath{\Lambda}p$ followed by final-state interactions of the produced particles with the daughter nucleus.
Automatic Generation of Data Merging Program Codes

Data merging is an essential part of ETL (Extract-Transform-Load) processes to build a data warehouse system. To avoid rewheeling merging techniques, we propose a Data Merging Meta-model (DMM) and its transformation into executable program codes in the manner of model driven engineering. DMM allows defining relationships of different model entities and their merging types in conceptual level. Our formalized transformation described using ATL (ATLAS Transformation Language) enables automatic generation of PL/SQL packages to execute data merging in commercial ETL tools. With this approach data warehouse engineers can be relieved from the burden of repetitive complex script coding and the pain of maintaining consistency of design and implementation.
Machine learning techniques for age at death estimation from long bone lengths

Estimating age at death of cadavers is an important ability in various subfields of forensic science and bioarchaeology. It can allow investigators to pinpoint someone's identity, more accurately locate an event of interest in time and clarify other societal or legal issues concerning a given skeletal collection. There are two main categories of methods for estimating age at death: biochemical methods - which use various biological or chemical processes to obtain an estimation -, and mathematical methods - which employ the use of data mining tools such as regression in order to estimate age from various numerical features. In this paper, we propose two machine learning approaches for the age estimation problem and prove that they outperform existing mathematical approaches on a number of case studies derived from publicly available data used for this task. Moreover, our methods are more robust and easier to reuse on new data.
A categorical characterization of relative entropy on Polish spaces

We give a categorical treatment, in the spirit of Baez and Fritz, of relative entropy for probability distributions defined on Polish spaces. We define a category called PolStat suitable for reasoning about statistical inference on Polish spaces. We define relative entropy as a functor into Lawvere's category $[0,\infty]$ and we show convexity, lower semicontinuity and uniqueness.
Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks

In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections.
An improved constant-time approximation algorithm for maximum~matchings

This paper studies approximation algorithms for problems on degree-bounded graphs. Let n and d be the number of vertices and the degree bound, respectively. This paper presents an algorithm to approximate the size of some maximal independent set with additive error ε n whose running time is O(d2). Using this algorithm, it also shows that there are approximation algorithms for many other problems, e.g., the maximum matching problem, the minimum vertex cover problem, and the minimum set cover problem, that run exponentially faster than existing algorithms with respect to d and 1/ε. Its approximation algorithm for the maximum matching problem can be transformed to a testing algorithm for the property of having a perfect matching with two-sided error. On the contrary, it also shows that every one-sided error tester for the property requires at least Ω(n) queries.
Promoting inflammatory lymphangiogenesis by vascular endothelial growth factor-C (VEGF-C) aggravated intestinal inflammation in mice with experimental acute colitis

Angiogenesis and lymphangiogenesis are thought to play a role in the pathogenesis of inflammatory bowel diseases (IBD). However, it is not understood if inflammatory lymphangiogenesis is a pathological consequence or a productive attempt to resolve the inflammation. This study investigated the effect of lymphangiogenesis on intestinal inflammation by overexpressing a lymphangiogenesis factor, vascular endothelial growth factor-C (VEGF-C), in a mouse model of acute colitis. Forty eight-week-old female C57BL/6 mice were treated with recombinant adenovirus overexpressing VEGF-C or with recombinant VEGF-C156S protein. Acute colitis was then established by exposing the mice to 5% dextran sodium sulfate (DSS) for 7 days. Mice were evaluated for disease activity index (DAI), colonic inflammatory changes, colon edema, microvessel density, lymphatic vessel density (LVD), and VEGFR-3mRNA expression in colon tissue. When acute colitis was induced in mice overexpressing VEGF-C, there was a significant increase in colonic epithelial damage, inflammatory edema, microvessel density, and neutrophil infiltration compared to control mice. These mice also exhibited increased lymphatic vessel density (73.0±3.9 vs 38.2±1.9, P<0.001) and lymphatic vessel size (1974.6±104.3 vs 1639.0±91.5, P<0.001) compared to control mice. Additionally, the expression of VEGFR-3 mRNA was significantly upregulated in VEGF-C156S mice compared to DSS-treated mice after induction of colitis (42.0±1.4 vs 3.5±0.4, P<0.001). Stimulation of lymphangiogenesis by VEGF-C during acute colitis promoted inflammatory lymphangiogenesis in the colon and aggravated intestinal inflammation. Inflammatory lymphangiogenesis may have pleiotropic effects at different stages of IBD.
Using A Genetic Algorithm to Optimize the Fit of Cognitive Models

This paper analyzes the use of a genetic algorithm (GA) for auto-fitting a non-linear, multivariable model to data. The example model and task used to illustrate the effectiveness of a GA is the Tower of Nottingham task. Empirical data collected from adults completing the task were used to create an initial model. This model’s variables were adjusted with a GA to simulate the performance of a child completing the task. The optimized fit was better than the previous fit generated by hand. We note the steps required to duplicate the process with other models.
Fast and Provable Algorithms for Spectrally Sparse Signal Reconstruction via Low-Rank Hankel Matrix Completion

A spectrally sparse signal of order $r$ is a mixture of $r$ damped or undamped complex sinusoids. This paper investigates the problem of reconstructing spectrally sparse signals from a random subset of $n$ regular time domain samples, which can be reformulated as a low rank Hankel matrix completion problem. We introduce an iterative hard thresholding (IHT) algorithm and a fast iterative hard thresholding (FIHT) algorithm for efficient reconstruction of spectrally sparse signals via low rank Hankel matrix completion. Theoretical recovery guarantees have been established for FIHT, showing that $O(r^2\log^2(n))$ number of samples are sufficient for exact recovery with high probability. Empirical performance comparisons establish significant computational advantages for IHT and FIHT. In particular, numerical simulations on $3$D arrays demonstrate the capability of FIHT on handling large and high-dimensional real data.
Detecting Arabic Cloaking Web Pages Using Hybrid Techniques

Many challenges are emerging in the every day expanding Internet environment, whether for the Internet users or the Web sites owners. The Internet users need to retrieve the high quality relevant information which are relevant to their queries within a short period of time, in order to be a regular users who satisfied by search engine performance. While the Web site owners aim in most cases to increase the rank of their Web pages within SERP to attract more customers to their Web sites, and consequently gaining more visits, which in turn means more revenues. The top rank of the Web pages within SERPs, is very important to the e-commerce and commercial Web pages. The owners of Web sites can attract more visitors to their Web pages, and gain more revenue, through Pay Per Click when their pages appear in the top results of SERPs. This paper proposed new approach of Arabic Web spam detection, dedicated with the cloaking Web pages, using hybrid techniques of content and link analysis. The proposed detection system built the first Arabic cloaking dataset contains around 5,000 Arabic cloaked Web pages. The proposed system extracts all possible rules from HTML element to monitor the cloaking behaviors, and then used three classification algorithms (K-NN, Decision Tree, and Logistic Recognition) in the experimental tests. This novel system yielded a high accuracy results with an accuracy of 94.1606% in detecting cloaking behaviors in Arabic Web pages.
An Explorative Analysis of the Effects of Information and Communication Technologies and Inter-Organizational Relationships on Supply Chain Management Systems

This paper explores in a supply chain context the influences that inter- organizational relationships have on the use of information and communication technology (ICT). In particular it analyzes the system use of the emergent patterns of supply chain management (SCM) by considering the underlying supported business processes. The research model was created for the study of the ICT usage patterns and has been applied through a detailed qualitative study conducted on the leading software distributor in Italy. The obtained results lead us to the conclusion that ICT usage emerges from the interaction of parties with available technologies.
Off-Line Hand Written Thai Character Recognition using Ant-Miner Algorithm

— Much research into handwritten Thai character recognition have been proposed, such as comparing heads of characters, Fuzzy logic and structure trees, etc. This paper presents a system of handwritten Thai character recognition, which is based on the Ant-minor algorithm (data mining based on Ant colony optimization). Zoning is initially used to determine each character. Then three distinct features (also called attributes) of each character in each zone are extracted. The attributes are Head zone, End point, and Feature code. All attributes are used for construct the classification rules by an Ant-miner algorithm in order to classify 112 Thai characters. For this experiment, the Ant-miner algorithm is adapted, with a small change to increase the recognition rate. The result of this experiment is a 97% recognition rate of the training set (11200 characters) and 82.7% recognition rate of unseen data test (22400 characters).