Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Edible Films Containing Procyanidin on the Preservation of Pork Meat during Chilled Storage

Procyanidins, which are natural antioxidants and antimicrobials found in grapes, enhance the quality and extend the shelf life of meat. We explored the effects of edible films incorporating procyanidins on pork loin stored for various times. Procyanidins (0, 0.1, and 0.3%, w/w) were incorporated into the edible films. We assessed meat color, pH, levels of volatile basic nitrogen (VBN) and 2-thiobarbituric acid-reactive substances (TBARS), and microbial populations for 14 d. The chromaticities and pH values of pork loin wrapped in film containing procyanidins (0.1% and 0.3%) generally increased (p<0.05) with storage time. VBN and TBARS levels, and total bacterial and Escherichia coli (E. coli) counts, significantly decreased (p<0.05) in the procyanidin groups. In particular, procyanidins strongly inhibited TBARS formation. Thus, our findings suggest that edible film impregnated with procyanidins inhibits lipid oxidation and microbial growth, thereby enhancing the quality and shelf life of pork meat.
Contrast sensitivity in mammographic softcopy reading

In mammographic softcopy reading, assessment of contrast resolution is mainly performed with phantoms, including detection tasks with a homogeneous image background. For tasks in visual perception a processing hierarchy is assumed, where detection tasks represent the base level. The results of investigations based on detection tasks might not allow predictions on the sensitivity for recognizing low-contrast patterns in a situation with complex images. We introduce the MCS method (Mammographic Contrast Sensitivity) for determining the contrast sensitivity function (CSF) in mammograms. Gabor patterns and digits are used as visual targets. The observers have to cope with an orientation discrimination task for the Gabor patterns and an identification task for the digits. The contrast thresholds are measured by a psychophysical staircase procedure at six spatial frequencies up to 16 cycles per degree. A study with eight observers was performed to show the applicability of the MCS method. The results of the observer study with several mammographic cases show that the approach is applicable independent of the chosen images. The results for Gabor pattern targets were different from those with digits, both in overall sensitivity and in the shape of the contrast sensitivity function. Sensitivity to pattern recognition is thus not reliably predicted from the Gabor CSF, and a more complex target like a digit or a character should be preferred. The measurement of a contrast sensitivity function does not take more than 4 minutes. The results can be used to appraise the effects of viewing conditions with an aim of drawing conclusions for mammographic softcopy reading.
Full-Search-Equivalent Pattern Matching with Incremental Dissimilarity Approximations

This paper proposes a novel method for fast pattern matching based on dissimilarity functions derived from the Lp norm, such as the Sum of Squared Differences (SSD) and the Sum of Absolute Differences (SAD). The proposed method is full-search equivalent, i.e. it yields the same results as the Full Search (FS) algorithm. In order to pursue computational savings the method deploys a succession of increasingly tighter lower bounds of the adopted Lp norm-based dissimilarity function. Such bounding functions allow for establishing a hierarchy of pruning conditions aimed at skipping rapidly those candidates that cannot satisfy the matching criterion. The paper includes an experimental comparison between the proposed method and other full-search equivalent approaches known in literature, which proves the remarkable computational efficiency of our proposal.
Identifying problematic classes in text classification

Real-world text classification tasks often suffer from poor class structure with many overlapping classes and blurred boundaries. Training data pooled from multiple sources tend to be inconsistent and contain erroneous labelling, leading to poor performance of standard text classifiers. The classification of health service products to specialized procurement classes is used to examine and quantify the extent of these problems. A novel method is presented to analyze the labelled data by selectively merging classes where there is not enough information for the classifier to distinguish them. Initial results show the method can identify the most problematic classes, which can be used either as a focus to improve the training data or to merge classes to increase confidence in the predicted results of the classifier.
The culturally co-opted brain: how literacy affects the human mind

The culturally co-opted brain: how literacy affects the human mind Falk Huettig, Régine Kolinsky and Thomas Lachmann Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands; Fonds de la Recherche Scientifique – FNRS, Brussels, Belgium; Unité de Recherche en Neurosciences Cognitives (UNESCOG), Center for Research in Cognition & Neurosciences (CRCN), Université Libre de Bruxelles (ULB), Brussels, Belgium; Center for Cognitive Science, Cognitive and Developmental Psychology Unit, University of Kaiserslautern, Kaiserslautern, Germany; Department of Experimental Psychology, University of Leuven, Leuven, Belgium
Parameter identification of transfer functions using MATLAB

This paper describes a procedure for identifying the transfer function parameters by using Matlab's System Identification Toolbox (SIT). The procedure is explained for obtaining numerical data using a digital oscilloscope in a format suitable for loading the data into Matlab and processing within the SIT. The measured data series connected RLC circuits were analyzed. Also, using the speed response of separately excited DC motor with and without smoothing coil was measured, and transfer functions were obtained.
The Formation of a Neural Fear Network in Posttraumatic Stress Disorder

Individuals differ strongly in their vulnerability to develop posttraumatic stress disorder (PTSD) in the aftermath of traumatic stress. This review on genetic risk factors in PTSD etiology employs the perspective of a psychobiological model, which proposes that intrusive memories, the core PTSD symptom, result from the formation of an associative neural fear network, which stores sensory-perceptual representations of traumatic memories. The current state of research on the genetics of PTSD, as well as common challenges, is presented in light of this framework. Because cumulative trauma exposure increases the fear memory strength, a standardized assessment of traumatic load and the investigation of Gene × Environment interactions are recommended. The investigation of genes involved in long-term memory formation, genome-wide association studies, pathway analyses, and the interplay of genetic and epigenetic factors could contribute to a deeper understanding of the molecular pathways involved in the formation and modification of the fear network.
Value estimation based computer-assisted data mining for surfing the Internet

Gathering of novel information from the WWW constitutes a real challenge for artificial intelligence (AI) methods. Large search engines do not offer a satisfactory solution, their indexing cycle is long and they may offer a huge amount of documents. An AI-based link-highlighting procedure designed to assist surfing is studied here. It makes use of (i) 'experts', i.e. pretrained classifiers, forming the long-term memory of the system, (ii) relative values of experts and value estimation of documents based on recent choices of the users. Value estimation adapts fast and forms the short-term memory of the system. All experiments show that surfing based filtering can efficiently highlight 10-20% of the documents in about 5 steps, or less.
Diagnosis of the Abnormality Extracted MRI Slice Images of a GUI Based Intelligent Diagnostic Imaging System

Diagnosis is the Key feature of an Intelligent Diagnostic Imaging System (IDIS). This paper describes the major diagnosis depending on the shape, texture, and area of the abnormality. Abnormality extraction is the vital step in a series of processes aimed at overall image understanding. Region based segmentation is used for abnormality extraction. This paper also describes author defined algorithms for threshold detection for abnormality extraction, which gives excellent result compared to the threshold detection using Otsu's method. Different algorithms are used for T1 and T2 MRI Images. This paper does the comparison of different segmentation techniques. MATLAB tools are used to do the segmentation.
GO-terms Semantic Similarity Measures

Four methods have been presented to determine the semantic similarity of two GO terms based on the annotation statistics of their common ancestor terms (Resnik [1], Jiang [2], Lin [3] and Schlicker [4]). Wang [5] proposed a new method to measure the similarity based on the graph structure of GO. Each of these methods has its own advantages and weaknesses. GOSemSim package [6] is developed to compute semantic similarity among GO terms, sets of GO terms, gene products, and gene clusters, providing both five methods mentioned above. I have developed another package, DOSE, for measuring semantic similarity among DO terms and gene products at disease perspective.
Error propagation in monocular navigation for Z∞ compared to eightpoint algorithm

Efficient visual pose estimation plays an important role for a variety of applications. To improve the quality, the measurements from different sensors can be fused. However, a reliable fusion requires the knowledge of the uncertainty of each estimate. In this work, we provide an error analysis for the Z∞ algorithm. Furthermore, we extend the existing first-order error propagation for the 8-point algorithm to allow for feature normalization, as proposed by Hartley or Mühlich, and the rotation matrix based decomposition. Both methods are efficient visual odometry techniques which allow high frame-rates and, thus, dynamic motions in unbounded workspaces. Finally, we provide experiments which validate the accuracy of the error propagation and which enable a brief comparison, showing that the Z∞ significantly outperforms the 8-point algorithm. We also discuss the influence of the number of features, the aperture angle, and the image resolution on the accuracy of the pose estimation.
A Characterization of GSAT ' sPerformance on a Class ofHard Structured

Randomized algorithms for solving hard satissability problems have been successfully applied to many application areas, but are still poorly understood. In this work, we show that, applied to SAT-encoded Hamil-ton circuit problems, GSAT with Random Walk (GWSAT) displays a very regular behaviour. In particular, the dependency of the success-rate on the maxSteps parameter for optimal walk probability can be charactarized by a simple algebraic function. We found an almost identical situation for GHC, a GSAT-variant adapted to the structure of the given problems class. Based on this observation, runtime estimates for given test-sets and parameter settings can be obtained. Furtheron this result shows that optimal speedup can be achieved for GWSAT (and GHC) when performing tries in parallel. The observed behaviour gives also rise to a novel interpretation of the search performed by GWSAT (and GHC) as an iterated blind probing in a much smaller, \virtual" searchspace the size of which is a measure for the search algorithms performance. We have evidence , that this concept can be also applied to other problem classes and local search algorithms.
A HOLOMORPHIC REPRESENTATION OF THE JACOBI ALGEBRA

A representation of the Jacobi algebra 𝔥1 ⋊ 𝔰𝔲(1, 1) by first-order differential operators with polynomial coefficients on the manifold is presented. The Hilbert space of holomorphic functions on which the holomorphic first-order differential operators with polynomials coefficients act is constructed.
Assessing healthcare Process Maturity: Challenges of using a Business Process Maturity Model

The quality of healthcare services is influenced by the maturity of healthcare processes used to develop it. A maturity model is an instrument to assess and continually improve organizational processes. In the last decade, a number of maturity models have been proposed with varied focus and depth for business processes. However, the number of studies that adapt these models to healthcare domain or propose healthcare-specific maturity models is very scarce. In this study, we share our experience and observations on assessing the healthcare processes of a hospital department in accordance to a well-known Business Process Maturity Model (BPMM) by Object Management Group (OMG). We also discuss challenges of assessing maturity of healthcare processes in accordance to a generic maturity model and outline opportunities for future work.
Staphylococcus aureus CcpA Affects Virulence Determinant Production and Antibiotic Resistance

ABSTRACT Carbon catabolite protein A (CcpA) is known to function as a major regulator of gene expression in different gram-positive organisms. Deletion of the ccpA homologue (saCOL1786) in Staphylococcus aureus was found to affect growth, glucose metabolization, and transcription of selected virulence determinants. In liquid culture, deletion of CcpA decreased the growth rate and yield; however, the effect was only transient during the exponential-growth phase as long as glucose was present in the medium. Depletion of glucose and production of lactate was delayed, while the level of excretion of acetate was less affected and was even higher in the mutant culture. On solid medium, in contrast, growth of the ΔccpA mutant resulted in smaller colonies containing a lower number of CFU per colony. Deletion of CcpA had an effect on the expression of important virulence factors of S. aureus by down-regulating RNAIII, the effector molecule of the agr locus, and altering the transcription patterns of hla, encoding α-hemolysin, and spa, encoding protein A. CcpA inactivation markedly reduced the oxacillin resistance levels in the highly methicillin-resistant S. aureus strain COLn and the teicoplanin resistance level in a glycopeptide-intermediate-resistant S. aureus strain. The presence of CcpA in the capsular polysaccharide serotype 5 (CP5)-producing strain Newman abolished capsule formation and decreased cap operon transcription in the presence of glucose. The staphylococcal CcpA thus not only is involved in the regulation of carbon metabolism but seems to function as a modulator of virulence gene expression as well.
Recurrence risk score based on the specific activity of CDK1 and CDK2 predicts response to neoadjuvant paclitaxel followed by 5-fluorouracil, epirubicin and cyclophosphamide in breast cancers.

BACKGROUND We established the cell cycle profiling (C2P) assay for specific activity (SA; activity/expression) of cyclin-dependent kinases (CDKs). C2P risk score (C2P-RS) based on CDK1 and CDK2 SAs was significantly associated with relapse in breast cancer (BC). This study was conducted to investigate the predictive value of C2P-RS for neoadjuvant chemotherapy (NAC). PATIENTS AND METHODS Among 124 eligible patients, 122 were treated with weekly paclitaxel followed by 5-fluorouracil, epirubicin and cyclophosphamide (P-FEC) and 2 were treated with paclitaxel monotherapy. C2P-RS was determined via C2P using frozen biopsy samples before NAC. RESULTS Negative estrogen receptor (ER), negative progesterone receptor (PR), positive human epidermal growth factor receptor 2 (HER2), high Ki-67 expression and intermediate + high C2P-RS were significantly associated with high pathological complete response (pCR) rates compared with positive ER (30% versus 9%), positive PR (25% versus 6%), negative HER2 (34% versus 11%), low Ki-67 expression (24% versus 7%) or low C2P-RS (24% versus 9%), respectively. The combination of C2P-RS and Ki-67 had a stronger impact on pCR than each parameter alone, and a multivariate analysis showed that the combination was an independent predictor of pCR (odds ratio 3.3, 95% confidence interval 1.1-9.5). CONCLUSIONS C2P-RS was significantly associated with pCR after P-FEC and may be a useful predictor for chemotherapy in BCs.
International Diversification in Bank Asset Portfolios

Through their transformation of assets, banks carry a considerably degree of non-diversifiable economic risks on their books. Given that banks are sensitive to costs of financial distress, we ask whether international extensions of credit may improve the diversification of such risks. Using a data set on the cross-border claims of banks located in four countries (France, Germany, the U.K., and the U.S.) to determine the degree of international diversification of bank asset portfolios, we find a substantial amount of home-country claims. We use the mean variance-portfolio model hedged for exchange-rate risk to determine the optimal degree of diversification. Relative to this benchmark, we find that banks in all countries except Germany are actually under-investing domestically. We investigate the determinants behind the difference between the optimal and actual observed portfolios through a regression of the deviation from benchmark on variables that capture country-specific risks and other potential barriers to cross-border lending. We find that less over-investment occurs between countries that are similar in legal system and language. However, conditional on over-investment, improvement in risk factors that proxy for sovereign and private sector risk, tends to increase the extent of over-investment. Hence, these variables capture risks, which are idiosyncratic relative to the benchmark portfolio, but affect banks’ actual portfolios.
Coping With Group Members Who Insult the In-Group

How do people cope with group members who insult the in-group? The 2016 U.S. Presidential election provided an opportunity to examine this question among group members experiencing unprecedented within-group strife. Participants read an essay written by an in-group or out-group member (Study 1, university affiliation; Study 2, U.S. political party affiliation, conducted at the height of the 2016 Presidential campaign), in which the author insulted his or her in-group. Participants reported the extent to which and reasons why they wanted to confront and avoid the target. Desire to rebuke the target, but not desire to protect oneself and the in-group, mediated the relationship between exposure to in-group (vs. out-group) deviance and confrontation. Desires to rebuke and protect jointly mediated the relationship with avoidance. Whereas people may differ on how they react to in-group deviance, they are primarily motivated by wanting to reprimand deviants, with implications for coping with intragroup conflict.
A Hadoop-based Multimedia Transcoding System for Processing Social Media in the PaaS Platform of SMCCSE

Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.
Heimdhal: a history-based policy engine for grids

The arising of grid platforms introduced inexpensive and highly available computing, storage and networking resources. Therefore, in a worldwide trend, institutions aggregate on virtual organizations, registering their resources to the grid and in return accessing a virtually limitless warehouse. This overabundance allowed the emergence of innovative application and business models, delivering the solution to several large-scale problems, as is the case of data processing, storage and sharing in CERN's Large Hadron Collider Project. In order to allow system administrators to assure resources are employed in a coordinated and secure way, policy mechanisms need to cope with such new models and the increased complexity in resource usage management. However, current grid platforms only provide simple primitives in their authorization modules. By restricting access control mechanisms to ACLs and role-based models, they disregard powerful usage semantics, such as those which are history-based (e.g. the Chinese-wall security policy). This absence obliges the development of ad hoc security managers for each deployed resource, introducing vulnerabilities in the security architecture. The use of advanced policies, and more specifically history-based policies, provides a natural method for expressing and enforcing several grid usage patterns, such as fair resource consumption. Additionally, some policy concepts not usually found in policy engines, such as periodic reevaluation, assure an effective policy enforcement. We present the Heimdhal system, a history-enabled policy engine which allows the definition, enforcement and accounting of history-based policies in grid platforms, and more specifically in Globus Toolkit 4.0. A practical evaluation using selected usage patterns corroborates the effectiveness of this kind of policies in grid computing environments, denoting encouraging performance results.
IDont: An Ontology Based Educational Modeling Framework for Instructional Design

It is inevitable to make use of technology to support 287 million adult illiterates of India spread across 22 Indian Languages and dialects. How to reduce the complexity during the creation and maintenance of adult literacy instructional design (goals, process, context, content and so on) while addressing large scale and variety? In this paper, we motivate the need for ontologies to address this inherent complexity in adult literacy problem. To this end, we present an ontology based educational modeling framework called IDont to capture different aspects of adult literacy instructional design. The core idea of this ontological framework is to systematize, separate and capture different aspects of adult literacy instructional design through several modular interrelated ontologies for context, goals, process, instructional material, role, evaluation and environment. Even though IDont is broadly applicable to all forms of educations in principle, we confine and present its application to adult literacy case study in this paper.