Miracle-dz/UniFAR-FTUs huggingface dataset:
Can a Graph Have Distinct Regular Partitions?

The regularity lemma of Szemeredi gives a concise approximate description of a graph via a so called regular-partition of its vertex set. In this paper we address the following problem: can a graph have two "distinct" regular partitions? It turns out that (as observed by several researchers) for the standard notion of a regular partition, one can construct a graph that has very distinct regular partitions. On the other hand we show that for the stronger notion of a regular partition that has been recently studied, all such regular partitions of the same graph must be very "similar". En route, we also give a short argument for deriving a recent variant of the regularity lemma obtained independently by Rodl and Schacht ([11]) and Lovasz and Szegedy ([9],[10]), from a previously known variant of the regularity lemma due to Alon et al. [2]. The proof also provides a deterministic polynomial time algorithm for finding such partitions.
Identification of residues critical for Ras(17N) growth-inhibitory phenotype and for Ras interaction with guanine nucleotide exchange factors

The Ras(17N) dominant negative antagonizes endogenous Ras function by forming stable, inactive complexes with Ras guanine nucleotide exchange factors (GEFs; e.g., SOS1). We have used the growth-inhibitory phenotype of Ras(17N) to characterize two aspects of Ras interaction with GEFs. First, we used a nonprenylated version of Ras(17N), designated Ras(17N/186S), which no longer associates with the plasma membrane and lacks the growth-inhibitory phenotype, to address the importance of Ras subcellular location and posttranslational modification for its interaction with GEFs. We observed that addition of an N-terminal myristylation signal to Ras(17N/186S) restored the growth-inhibitory activity of nonprenylated Ras(17N). Thus, membrane association, rather than prenylation, is critical for Ras interaction with Ras GEFs. Second, we used a biological selection approach to identify Ras residues which are critical for Ras(17N) growth inhibition and hence for interaction with Ras GEFs. We identified mutations at residues 75, 76, and 78 that abolished the growth-inhibitory activity of Ras(17N). Since GEF interaction is dispensable for oncogenic but not normal Ras function, our demonstration that single-amino-acid substitutions at these three positions impaired the transforming activity of normal but not oncogenic Ras provides further support for the role of these residues in Ras-GEF interactions. Finally, Ras(WT) proteins with mutations at these residues were no longer activated by mammalian SOS1. Altogether, these results suggest that the Ras intracellular location and Ras residues 75 to 78 are critical for Ras-GEF interaction.
Lymphoma in cotton-top marmosets after inoculation with Epstein-Barr virus: tumor incidence, histologic spectrum antibody responses, demonstration of viral DNA, and characterization of viruses

6 of 20 cotton-top tamarins (Saguinus oedipus) inoculated with Epstein- Barr virus (EBV) developed diffuse malignant lymphoma resembling reticulum cell or immunoblastic sarcoma of man. Hyperplastic lymphoreticular lesions were induced in three additional animals; in two instances the hyperplastic lesions regressed. Inapparent infection with development of antibody occured in eight animals. In two animals there was no evidence of EBV infection. One animal died in the first week after inoculation of parasitic infection. 10 animals uninoculated or mock-inoculated developed neither lymphoproliferative disease nor antibody. The malignant lymphoma appeared to arise from a cell with an uncleaved vesicular nucleus found in the center of the germinal follicle. The prominent cytologic features of this cell were extensive formation or rough endoplasmic reticulum and elaboration of the cytoplasmic membrane with microvilli. Cell lines derived from these tumors did not have receptors for complement. IgFc, or sheep erythrocytes, and the cell lines adhered to glass and plastic. EB nuclear antigen was found in imprints of two lymph nodes, one with lymphoma and one with hyperplasia. EB virus DNA was detected directly in the tumors of three animals and in cell lines from two lymphomas. Typical herpes virus particles were found in supernatant fluids from cell lines obtained from lymph nodes with tumors and hyperplasia, as well as in lines derived from blood leukocytes of marmosets with inapparent infection. These virus preparations had the biologic property characteristic of EBV, namely, stimulation of cellular DNA synthesis and immortalization of human lymphocytes. The virus derived from two cell lines was neutralized by reference human sera with EBV antibody and not by antibody-negative human sera. The virus derived from the experimental lesions is thus indistinghishable from human EBV. The marmoset has enhanced susceptibility to oncogenesis by EB virus. Among identified factors which may play a role in the heightened tumorigenicity of EB virus in this species are the increased production of virus by transformed cells and the absence of membrane receptors for complement or IgFc on transformed cells.
The derivation of detector efficiencies in PET from single photon blank scans

We developed a means of calculating detector efficiencies from blank transmission scan measurements that use a single photon source. The method is based on a new measurement model that shows how the detector efficiencies contribute to the recorded measurement. Two different approaches to calculate efficiencies are given, where one is based on the maximum likelihood principle. By way of example, blanks acquired from an EXACT3D scanner are processed using these methods. The calculated sets of efficiencies from the two methods are shown to be similar to each other. The variation in the blank caused by detector efficiency is shown to match very well the measurement model when these estimated efficiencies are used. The first application of our approach has been to perform a daily detector check, removing the necessity for a phantom.
Evaluating the TLS Family of Protocols with Weakest Precondition Reasoning

In this paper we show how the Cryptographic Protocol Analysis Language Evaluation System (CPALES) was used in the analysis of the Transport Layer Security (TLS) protocol. CPALES was also used to reveal flaws in one of the security protocols developed by Kao and Chow. The TLS protocol is actually composed of a set of subprotocols. The difficulties of analyzing a protocol of this nature and the resulting improvements made to CPALES are discussed. We demonstrate the ability of the system to analyze TLS for insecurities arising from interactions among subprotocols.
EXTRACTION OF GRAPE SEED BY SUPERCRITICAL CARBON DIOXIDE

Supercritical fluid extraction of grape seed oil was performed to study the effect of various parameters such as pressure (80–120 bar), temperature (40-50°C) and modifier concentration (10-30%) on the yield and composition of oil. Experiments were performed based on experimental design in three levels. The maximum yield of the oil was obtained by adding 30% of methanol as a modifier. The fatty acid composition of grape seed oil was analyzed by GC-MS using by a standard estimation method. Unsaturated fatty acids constitute about 70% of the oil, in conformance with respective literature.
Sodium butyrate attenuates high-fat diet-induced steatohepatitis in mice by improving gut microbiota and gastrointestinal barrier.

AIM To investigate whether gut microbiota metabolite sodium butyrate (NaB) is an effective substance for attenuating non-alcoholic fatty liver disease (NAFLD) and the internal mechanisms. METHODS Male C57BL/6J mice were divided into three groups, normal control were fed standard chow and model group were fed a high-fat diet (HFD) for 16 wk, the intervention group were fed HFD for 16 wk and treated with NaB for 8 wk. Gut microbiota from each group were detected at baseline and at 16 wk, liver histology were evaluated and gastrointestinal barrier indicator such as zonula occluden-1 (ZO-1) were detected by immunohistochemistry and realtime-PCR, further serum or liver endotoxin were determined by ELISA and inflammation- or metabolism-associated genes were quantified by real-time PCR. RESULTS NaB corrected the HFD-induced gut microbiota imbalance in mice, while it considerably elevated the abundances of the beneficial bacteria Christensenellaceae, Blautia and Lactobacillus. These bacteria can produce butyric acid in what seems like a virtuous circle. And butyrate restored HFD induced intestinal mucosa damage, increased the expression of ZO-1 in small intestine, further decreased the levels of gut endotoxin in serum and liver compared with HF group. Endotoxin-associated genes such as TLR4 and Myd88, pro-inflammation genes such as MCP-1, TNF-α, IL-1, IL-2, IL-6 and IFN-γ in liver or epididymal fat were obviously downregulated after NaB intervention. Liver inflammation and fat accumulation were ameliorated, the levels of TG and cholesterol in liver were decreased after NaB intervention, NAS score was significantly decreased, metabolic indices such as FBG and HOMA-IR and liver function indicators ALT and AST were improved compared with HF group. CONCLUSION NaB may restore the dysbiosis of gut microbiota to attenuate steatohepatitis, which is suggested to be a potential gut microbiota modulator and therapeutic substance for NAFLD.
EyeNav: Gaze-Based Code Navigation

Navigating source code is at the core of software development, consuming a significant amount of time and effort. Navigation is typically done using the mouse, which in many cases may not be efficient and usable, as it causes context switching and interruptions. EyeNav brings eye tracking to code editors. It allows for a more natural source code navigation, controlled by the developer's gaze and keyboard shortcuts. It aims to improve usability and efficiency over the mouse on code navigation tasks. EyeNav provides a smoother user experience by letting developers keep their hands on the keyboard at all times. It is a production-ready Brackets.io plugin that allows anyone with an eye tracker to start using it immediately. Demo video: https://youtu.be/AkDyx2l-YGk Source code: https://github.com/sradevski/eyenav
Active learning by label uncertainty for acoustic emotion recognition

Speech data is in principle available in large amounts for the training of acoustic emotion recognisers. However, emotional labelling is usually not given and the distribution is heavily unbalanced, as most data is ‘rather neutral’ than truly ‘emotional’. In the ‘hay stack’ of speech data, Active Learning automatically identifies the ‘needles’, i.e., the more informative instances to reduce human labelling effort when building a classifier, e.g., for acoustic emotion recognition. The critical issue thus is the determination and quantification of informativeness. To this end, we suggest to exploit the reliability of the usual ambiguity of emotional labels, i.e., we propose a novel approach based on label uncertainty. By building a certainty model and predicting the candidate instances, informativeness is thus based on labeller agreement. In addition, we consider class sparseness. The results of extensive test runs under well standardised conditions show the method’s great potential in reducing labelling costs while boosting performance.
Identification of Quasi-ARX neurofuzzy model by using SVR-based approach with input selection

Quasi-ARX neurofuzzy (Q-ARX-NF) models have shown great approximation ability and usefulness in nonlinear system identification and control. However, the incorporated neurofuzzy networks suffer from the curse-of-dimensionality problem, which may result in high computational complexity and over-fitting. In this paper, support vector regressor (SVR) based identification approach is used to reduce computational complexity with the help of transforming the original problem into Lagrange space, which is only sensitive to the number of data samples. Furthermore, to improve the generalization capability, a parsimonious model structure is obtained by eliminating insignificant input variables for the incorporated neurofuzzy network, which is implemented by genetic algorithm (GA) based input selection method with a novel fitness evaluation function. Two numerical simulations are tested to show the effectiveness of the proposed method.
Unpacking the perceived opportunity to misbehave: The influence of spatio-temporal and social dimensions on consumer misbehavior

Purpose – This study aims to use opportunity as a theoretical lens to investigate how the spatio-temporal and social dimensions of the consumption environment create perceived opportunities for consumers to misbehave. Design/methodology/approach – Drawing on routine activity theory and social impact theory, the authors use two experiments to demonstrate that spatio-temporal and social dimensions can explain consumer theft in retail settings. Findings – Study 1 reveals mixed empirical support for the basic dimensions of routine activity theory, which posits that the opportunity to thieve is optimised when a motivated offender, suitable target and the absence of a capable formal guardian transpire in time and space. Extending the notion of guardianship, Study 2 tests social impact theory and shows that informal guardianship impacts the likelihood of theft under optimal routine activity conditions. Originality/value – The study findings highlight important implications for academicians and retail managers: rather than focusing on the uncontrollable characteristics of thieving offenders, more controllable spatio-temporal and social factors of the retail environment can be actively monitored and manipulated to reduce perceived opportunities for consumer misbehaviour.
Gradient-free decoding parameter optimization on automatic speech recognition

Finding the optimal decoding parameters in speech recognition is often done manually in a rather tedious manner, although automatic gradient-free optimization techniques have been shown to perform quite well for this task. While there have been recent scientific contributions in this field, no thorough comparison of possible methods, in terms of convergence speed and performance, has been undertaken. In this paper, we conduct a series of experiments with three decoding paradigms and four different optimization techniques found in recent literature, both on unconstrained and time-constrained decoder optimization. We offer our findings on the German Difficult Speech Corpus and on the LinkedTV test sets.
Celiac disease: 10-year experience in a Romanian tertiary center.

AIM To evaluate the experience of a single coeliac center over a 10-year-observational period. MATERIAL AND METHODS Between January 2003 and December 2013 a total of 195 consecutive patients admitted with celiac disease were tested by multiple duodenal biopsies, anti-tissue transglutaminase and anti-gliadin antibodies, and baseline demographic, clinical, biological and immunological parameters. RESULTS Patients were divided into two major groups according to the clinical features and number of signs and symptoms present upon admission: gastrointestinal (131, 67.17%) and non-gastrointestinal (64, 32.8%). Anti-tissue transglutaminase and anti-gliadin antibodies showed seropositivity in 109/158. Histological samples were available in 152 cases, according to Marsh-Oberhuber classification 11.18% being type 0, 17.76%, type I-II, and 71.05% type III. Correlations between anti-tissue transglutaminase antibody titers and Marsh-Oberhuber classification were found to be statistically significant. Body mass index was available in 96 cases. We found that severe atrophy was predominant in patients with a BMI<18 kg/m2. CONCLUSIONS Celiac disease has an increasing prevalence and can be diagnosed at any age. Histology samples were indicative of different stages of villous atrophy. The disease prevalence is significantly higher among women. There was no statistically significant correlation between Marsh classification and BMI values.
Investigation of data quality in a wireless sensing unit composed of off-the-shelf components

This paper presents the preliminary findings of a study on data and system identification results (derived from collected data) in a wireless sensing environment. The goal of this study is to understand how various hardware design choices and operational conditions affect the quality of the data and accuracy of the identified results; the focus of this paper is packet and data loss. A series of experimental investigations are carried out using a laboratory shaking table instrumented with off-the-shelf Micro-Electro-Mechanical Systems (MEMS) accelerometers. A wireless sensing unit is developed to interface with these wired analog accelerometers to enable wireless data transmission. To reduce the overall design variance and aid convenient application in civil infrastructure health monitoring, this wireless unit is built with off-the-shelf microcontroller and radio development boards. The anti-aliasing filter and analog-to-digital convectors (ADC) are the only customized components in the hardware. By varying critical hardware configurations, including using analog accelerometers of different commercial brands, taking various designs for the anti-aliasing filter, and adopting ADCs with different resolutions, shaking table tests are repeated, the collected data are processed, and the results are compared. Operational conditions such as sampling rate and wireless data transmitting range are also altered separately in the repeated testing. In all of the cases tested, data is also collected using a wire-based data acquisition system to serve as a performance baseline for evaluation of the wireless data transmission performance. Based on this study, the challenges in the hardware design of wireless sensing units and data processing are identified.
Highly Variable Microbiota Development in the Chicken Gastrointestinal Tract

Studies investigating the role that complex microbiotas associated with animals and humans play in health and wellbeing have been greatly facilitated by advances in DNA sequencing technology. Due to the still relatively high sequencing costs and the expense of establishing and running animal trials and collecting clinical samples, most of the studies reported in the literature are limited to a single trial and relatively small numbers of samples. Results from different laboratories, investigating similar trials and samples, have often produced quite different pictures of microbiota composition. This study investigated batch to batch variations in chicken cecal microbiota across three similar trials, represented by individually analysed samples from 207 birds. Very different microbiota profiles were found across the three flocks. The flocks also differed in the efficiency of nutrient use as indicated by feed conversion ratios. In addition, large variations in the microbiota of birds within a single trial were noted. It is postulated that the large variability in microbiota composition is due, at least in part, to the lack of colonisation of the chicks by maternally derived bacteria. The high hygiene levels maintained in modern commercial hatcheries, although effective in reducing the burden of specific diseases, may have the undesirable effect of causing highly variable bacterial colonization of the gut. Studies in humans and other animals have previously demonstrated large variations in microbiota composition when comparing individuals from different populations and from different environments but this study shows that even under carefully controlled conditions large variations in microbiota composition still occur.
Super-Resolution Reconstruction and Its Future Research Direction

During this decade, the enlargement in the extensive use of digital imaging technologies in consumer (e.g., digital video) and other markets (e.g. security and military) has brought with it a simultaneous demand for higher-resolution (HR) images. The demand for such images can be partially met by algorithmic advances in SuperResolution Reconstruction (SRR) technology in addition to hardware development. Not only do such HR images give the viewer a more pleasing picture but also offer additional details that are significant for subsequent analysis in many applications. SRR algorithm is considered to be one of the most promising techniques that can help overcome the limitations due to optics and sensor resolution. In general, the problem of super-resolution can be expressed as that of combining a set of aliased, noisy, lowresolution, blurry images to produce a higher resolution image or image sequence. The idea is to increase the information content in the final image by exploiting the additional spatio-temporal information that is available in each of the LR images. Consequently, the major advantage of the SRR algorithm is that it may cost less and the existing LR imaging systems can be still utilized. The SRR algorithm is proved to be useful in several practical cases where multiple frames of the same scene can be obtained, including medical imaging, satellite imaging, and video applications.
Solving Task Scheduling Problem for Distributed Sensor Network with Discrete Particle Swarm Optimization

From the computation point of view, task scheduling for distributed sensor network is an NP-hard combinatorial optimization problem. The Particle Swarm Optimization (PSO) has been proved to be a good optimization algorithm with outstanding global performance. However, PSO cannot be directly used in the combinatorial optimization problem mentioned above due to its continuity. In this paper, a heuristic discrete PSO (HDPSO) with a well-designed particle position code is proposed, in which effective fitness function based on approximate optimal waiting approach is adopted. Experiments show that the performance of the proposed algorithm is better than genetic algorithm.
ADME Evaluation in Drug Discovery, 7. Prediction of Oral Absorption by Correlation and Classification

A critically evaluated database of human intestinal absorption for 648 chemical compounds is reported in this study, among which 579 are believed to be transported by passive diffusion. The correlation analysis between the intestinal absorption and several important molecular properties demonstrated that no single molecular property could be used as a good discriminator to efficiently distinguish the poorly absorbed compounds from those that are well absorbed. The theoretical correlation models for a training set of 455 compounds were proposed by using the genetic function approximation technique. The best prediction model contains four molecular descriptors: topological polar surface area, the predicted distribution coefficient at pH = 6.5, the number of violations of the Lipinski's rule-of-five, and the square of the number of hydrogen-bond donors. The model was able to predict the fractional absorption with an r = 0.84 and a prediction error (absolute mean error) of 11.2% for the training set. Moreover, it achieves an r = 0.90 and a prediction error of 7.8% for a 98-compound test set. The recursive partitioning technique was applied to find the simple hierarchical rules to classify the compounds into poor (%FA < or = 30%) and good (%FA > 30%) intestinal absorption classes. The high quality of the classification model was validated by the satisfactory predictions on the training set (correctly identifying 95.9% of the compounds in the poor-absorption class and 96.1% of the compounds in the good-absorption class) and on the test set (correctly identifying 100% of the compounds in the poor-absorption class and 96.8% of the compounds in the good-absorption class). We expect that, in the future, the rules for the prediction of carrier-mediated transporting and first pass metabolism can be integrated into the current hierarchical rules, and the classification model may become more powerful in the prediction of intestinal absorption or even human bioavailability. The databases of human intestinal absorption reported here are available for download from the supporting Web site: http://modem.ucsd. edu/adme.