Miracle-dz/UniFAR-FTUs huggingface dataset:
Benefits of Zataria multiflora Boiss in Experimental Model of Mouse Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a chronic condition of the intestine with unknown etiology involving multiple immune, genetic and environmental factors. We were interested to examine the effect of total extract from Zataria multiflora Boiss, a folk medicinal plant on prevention and treatment of experimental IBD. Z. multiflora was administered (400, 600, 900 p.p.m.) through drinking water to IBD mice induced by intrarectal administration of acetic acid. Prednisolone was used as the standard drug for comparison. Biochemical, macroscopic and microscopic examinations of colon were performed. Biochemical evaluation of inflamed colon was done using assay of myeloperoxidase (MPO) activity and thiobarbituric acid reactive substances (TBARS) concentration as indicators of free radical activity and cell lipid peroxidation. The activity of MPO and lipid peroxidation products (TBARS) increased in acetic acid-treated groups while recovered by pretreatment of animals with Z. multiflora (400–900 p.p.m.) and prednisolone. Z. multiflora (600 and 900 p.p.m.) and prednisolone-treated groups showed significantly lower score values of macroscopic and microscopic characters when compared with the acetic acid-treated group. The beneficial effect of Z. multiflora (900 p.p.m.) was comparable with that of prednisolone. The antioxidant, antimicrobial and anti-inflammatory potentials of Z. multiflora might be the mechanisms by which this herbal extract protects animals against experimentally induced IBD. Proper clinical investigation should be carried out to confirm the activity in human.
Function of PrPC (1-OPRD) in biological activities of gastric cancer cell lines

Approximately 10–15% of the human prion disease is inherited and one of the important genetic mutations occurs in the octapeptide repeat region of prion protein gene. One of the variants, one octapeptide repeat deletion (1‐OPRD), existed in several gastric cancer cell lines and its mutation frequency was higher in gastric cancer cases. However, the biological functions of it remain unknown. Wild‐type and mutation forms of PrPC were cloned and transfected into gastric cancer cells. Cell apoptosis, adhesion, invasion, multidrug resistance (MDR) and proliferation were, respectively, investigated. Different expressed genes were screened by gene array and proved by PT‐PCR. Further, luciferase report assay was used to explore the transcriptional activation of target genes. Forced overexpression PrPC (1‐OPRD) could promote the gastric cancer cells SGC7901 growth through facilitating G1‐ to S‐phase transition in the cell cycle. PrPC (1‐OPRD) could also inhibit apoptosis, and promote adhesion, invasion and MDR in SGC7901. However, it exhibited no significant difference between wild‐type PrPC (1‐OPRD) and PrPC on apoptosis, invasion or MDR effects. Further experiments indicated that PrPC (1‐OPRD) could trigger the transactivation of cyclinD3 besides cyclinD1 to promote cell transition and proliferation. Overexpression of PrPC (1‐OPRD) might promote the proliferation of gastric cancer cells at least partially through transcriptional activation of cyclinD3 to accelerate the G1‐/S‐phase transition. The promoting proliferation effect of PrPC (1‐OPRD) was more than that of wild‐type PrPC. However, they showed no difference on apoptosis, adhesion, invasion or MDR effects of gastric cancer cells.
A uniformly convergent adaptive particle filter

Particle filters are Monte-Carlo methods that aim to approximate the optimal filter of a partially observed Markov chain. In this paper, we study the case where the transition kernel of the Markov chain depends on unknown parameters: we construct a particle filter for the simultaneous estimation of the parameter and the partially observed Markov chain (adaptive estimation) and we prove the convergence of this filter to the correct optimal filter, as time and the number of particles go to infinity. The filter presented here generalizes Del Moral’s Monte-Carlo particle filter, presented in [5].
Mitochondrial and nuclear gene expression for cytochrome oxidase subunits are disproportionately regulated by functional activity in neurons

Mitochondrial respiratory complexes such as cytochrome oxidase (CO) contain both mitochondrial- and nuclear-encoded subunits. To determine whether mitochondrial and nuclear gene expression are regulated proportionately in neurons, we analyzed CO subunit mRNA and mitochondrial DNA (mtDNA) levels by in situ hybridization and grain counting in the visual system of normal and monocular TTX-treated monkeys. We compared the regulation of these molecules with the regulation of CO activity and CO protein, analyzed by histochemistry and immunohistochemistry, respectively. In normal animals, CO activity was in general related more closely to mtDNA and CO subunit I (COI) (mitochondrial-encoded) mRNA levels than to COIV or COVIII (nuclear- encoded) mRNA levels. For example, puffs (also known as blobs) of high CO activity in striate cortex were enriched in mtDNA and COI mRNA, but not COIV or COVIII mRNA. In 3–7 d TTX-treated animals, proportionate decreases in CO activity and CO protein were observed in specific visual centers; these changes were accompanied by disproportionate decreases in COI, COIV, and COVIII mRNA levels. After 7 d of TTX, COI mRNA fell by 49 +/- 3% (mean +/- SEM) in LGN neurons, while COIV and COVIII mRNAs fell by only 18 +/- 3% and 29 +/- 3%, respectively. In comparison, CO activity decreased by 23 +/- 2%, and mtDNA by 26 +/- 4%. Qualitative observations in striate cortex also indicated that COI mRNA changed more than COIV mRNA, COVIII mRNA, mtDNA, or CO activity. Our results suggest that the local distribution of CO within neurons, and acute regulatory changes in CO activity occurring over periods of days are controlled mainly by regulation of the mitochondrial genes that encode the catalytic subunits of the enzyme.
Iterated Hard Shrinkage for Minimization Problems with Sparsity Constraints

A new iterative algorithm for the solution of minimization problems in infinite-dimensional Hilbert spaces which involve sparsity constraints in form of $\ell^{p}$-penalties is proposed. In contrast to the well-known algorithm considered by Daubechies, Defrise, and De Mol, it uses hard instead of soft shrinkage. It is shown that the hard shrinkage algorithm is a special case of the generalized conditional gradient method. Convergence properties of the generalized conditional gradient method with quadratic discrepancy term are analyzed. This leads to strong convergence of the iterates with convergence rates $\mathcal{O}(n^{-1/2})$ and $\mathcal{O}(\lambda^n)$ for $p=1$ and $1 < p \leq 2$, respectively. Numerical experiments on image deblurring, backwards heat conduction, and inverse integration are given.
Fast and robust template matching algorithm in noisy image

In the majority of robot applications, including human-computer interaction, template matching is used to find a specific area in a given image or a frame of video stream. Flexible and robust template matching algorithm necessitates feature extraction, for example gradient calculation. This requires complex calculation which causes bad response time of the system. An alternative solution is the use of index table, which stores coordinates that have the same grey level. However, due to the mechanism of the matching algorithm, it is necessary to have several disadvantages in the algorithm. But these restrictions are less important, and there is an idea that copes with these limitations. This paper proposes fast and robust template matching algorithm that uses grey level index table and image rank technique. This algorithm can find specific area under the given template query image with 30% Gaussian noise.
Addendum to 'Generalized Fractional-Octave Smoothing of Audio and Acoustic Responses'

A methodology is introduced for smoothing the complex transfer function of measured responses using well-established or arbitrary fractional-octave profiles, based on a novel time-frequency mapping framework. A corresponding impulse response, also derived analytically, has reduced complexity but conforms to perceptual principles. The relationship be tween complex smoothing and traditional power spectral smoothing is also discussed.
Application of adaptive UKF in initial alignment of MINS/GPS integrated navigation system

In order to overcome the shortcomings of standard unscented Kalman filter (UKF), which are obviously influenced by the error of initial value and the model error of system, adaptive UKF which is based on the adaptive principle is applied in initial alignment of the MINS/GPS integrated navigation system. Coarse alignment cannot be done by micro inertial measurement unit (MIMU) itself because of its low precision, the method of using magnetometer to assist it with coarse alignment is presented. Simulation results show that the adaptive UKF can overcome the influences of initial values error and inaccurate system model, and improve the convergence speed and alignment accuracy effectively.
THE VALIDATION OF A FUZZY EXPERT SYSTEM FOR UMBILICAL CORD ACID-BASE ANALYSIS

Objective assessment of the neonatal outcome of labour is important, but it is a difficult and challenging problem. It is an invaluable source of information which can be used to provide feedback to clinicians, to audit a unit’s overall performance, and can guide subsequent neonatal care. Current methods are inadequate as they fail to distinguish damage that occurred during labour from damage that occurred before or after labour. Analysis of the chemical acid-base status of blood taken from the umbilical cord of an infant immediately after delivery provides information on any damage suffered by the infant due to lack of oxygen during labour. However, this process is complex and error prone, and requires expertise which is not always available on labour wards. Previous work had resulted in the development of a crisp expert system for the interpretation of umbilical acid-base status. However, this domain is characterised by uncertainty in both the basic data and the knowledge required for its interpretation. Fuzzy logic provides a technique for representing both these forms of uncertainty in a single framework. Experimental work to establish the imprecision in acid-base parameters, in conjunction with fresh knowledge elicitation sessions, allowed the creation of an expert system to validate and interpret acid-base data using fuzzy logic. The performance of the system was evaluated in a rigorous validation study. This demonstrated excellent agreement with the experts for the numeric outputs, and agreement on a par with the experts for the linguistic outputs. One output of the fuzzy expert system is a novel single dimensional measure that accurately represents the severity of acid-base results. jong@cis.plym. ac.uk, julian@cis.plym. ac.uk, e.ifeachor@plymouth.ac.uk
Evaluation of dynamic scheduling methods in simulations of storm-time ion acceleration

In this paper we investigate the applicability of classic dynamic loop scheduling methods on a numerical simulation code that calculates the trajectories of charged particles in the earth's magnetosphere. The numerical application under consideration investigates the influence of sub storm-induced electric fields that cause magneto spheric disturbances, responsible for severe hazards in human activities and technology infrastructures in the near-earth space environment. The computational time to simulate the motion of each particle is dependent on the inital conditions applied and may greatly vary between different particles. This fact leads to great load imbalances in parallel execution scenarios and thus to degraded overall performance. For this reason we apply dynamic scheduling techniques to load-balance the tasks in homogeneous, heterogeneous and loaded distributed-memory parallel platforms and select the most appropriate among the available strategies.
Face verification put to test: A hill-climbing attack based on the uphill-simplex algorithm

The vulnerabilities of a PCA-based face verification system against a hill-climbing attack using the uphill-simplex algorithm are studied. Experiments are carried out on the face subcorpus of the publicly available BioSecure DB, where the attack has shown a remarkable performance proving the lack of robustness of the tested system to this type of threat. Furthermore, the proposed attacking scheme is not only able to bypass the security of the recognition system, but it is also capable of reconstructing the users face image, with the privacy concerns that this entails. As a possible countermeasure to minimize the effect of the attack, score quantization is applied. This protection method is able to reduce both the success rate and the efficiency of the attack, however it does not completely succeed in preventing a possible intruder from accessing the system. The study also highlights the high adaptation capabilities of the proposed attack which had already been used to break a signature-based verification system.
Supervised Blockmodelling

Collective classification models attempt to improve classification performance by taking into account the class labels of related instances. However, they tend not to learn patterns of interactions between classes and/or make the assumption that instances of the same class link to each other (assortativity assumption). Blockmodels provide a solution to these issues, being capable of modelling assortative and disassortative interactions, and learning the pattern of interactions in the form of a summary network. The Supervised Blockmodel provides good classification performance using link structure alone, whilst simultaneously providing an interpretable summary of network interactions to allow a better understanding of the data. This work explores three variants of supervised blockmodels of varying complexity and tests them on four structurally different real world networks.
Indexed Induction and Coinduction, Fibrationally

This paper extends the fibrational approach to induction and coinduction pioneered by Hermida and Jacobs, and developed by the current authors, in two key directions. First, we present a sound coinduction rule for any data type arising as the final coalgebra of a functor, thus relaxing Hermida and Jacobs' restriction to polynomial data types. For this we introduce the notion of a quotient category with equality (QCE), which both abstracts the standard notion of a fibration of relations constructed from a given fibration, and plays a role in the theory of coinduction dual to that of a comprehension category with unit (CCU) in the theory of induction. Second, we show that indexed inductive and coinductive types also admit sound induction and coinduction rules. Indexed data types often arise as initial algebras and final coalgebras of functors on slice categories, so our key technical results give sufficent conditions under which we can construct, from a CCU (QCE) U : e → B, a fibration with base B/I that models indexing by I and is also a CCU (QCE).
Multisource DOA estimation based on time-frequency sparsity and joint inter-sensor data ratio with single acoustic vector sensor

By exploring the time-frequency (TF) sparsity property of the speech, the inter-sensor data ratios (ISDRs) of single acoustic vector sensor (AVS) have been derived and investigated. Under noiseless condition, ISDRs have favorable properties, such as being independent of frequency, DOA related with single valuedness, and no constraints on near or far field conditions. With these observations, we further investigated the behavior of ISDRs under noisy conditions and proposed a so-called ISDR-DOA estimation algorithm, where high local SNR data extraction and bivariate kernel density estimation techniques have been adopted to cluster the ISDRs representing the DOA information. Compared with the traditional DOA estimation methods with a small microphone array, the proposed algorithm has the merits of smaller size, no spatial aliasing and less computational cost. Simulation studies show that the proposed method with a single AVS can estimate up to seven sources simultaneously with high accuracy when the SNR is larger than 15dB. In addition, the DOA estimation results based on recorded data further validates the proposed algorithm.
HLA: a standards effort as architectural style

In this position paper we introduce a case study, the DOD “High Level Architecture for Simulations (HLA),” and briefly discuss our efforts to apply WRIGHT, an architectural description language, to the HLA. Our work on HLA has focused on understanding the HLA as an architectural style, concentrating on the Interface Specitication (lFSpec) description of the “Runtime Infrastructure (RTI)” as the central architectural design issue. Specifically, we have used WRIGHT, a formal architectural description language, to characterize the RTI and analyze a number of its properties. By providing an analysis of the properties of the RTI as described by the IFSpec, we can help the standards committee to determine whether the IFSpec ensuresthe properties that they want and to discoverinconsistencies or other weaknesses of the specification.
Heritability and intelligence.

HERITABILITY AND INTELLIGENCE One need only think of one's fellow men and women to realize that individual intellectual makeups vary in numerous ways. Psychology's most longstanding indicator of individual differences in intellectual functioning is the intelligence quotient (IQ). Although IQ was originally invented to differentiate children into groups of those whose level of intellectual functioning corresponds to that of peers of similar age and those whose level of mental functioning does not, it has since evolved into the most frequently used indicator of individual differences (or variability) in intellectual functioning. The point of this chapter, however, is not to analyze individual differences in IQ per se, but, rather, the sources of these differences. In other words, what forces make people similar (or dissimilar) in IQ? The sources of variability in IQ have been the subject of a field known as the psychology of individual differences. This subfield is one of the oldest in psychology, and, like any mature field, it has witnessed successive theoretical transformations. In this case, different theories have been employed to explain the etiology of the traits in which people differ (e.g., Kimble, 1993). The landmark of research on the etiology of individual differences in IQ is the concept of heritability, a statistic describing the proportion of phenotypic (observed) differences among individuals in a population that can be attributed to genetic differences between them. It has been said that there are very few subfields in psychology as controversial and yet sterile as that of heritability-based studies of IQ (Danzinger, 1997). The debates concerning these studies are remarkable in number and pervasiveness.
Performance Analysis of User Selected Subband Channel Quality Indicator Feedback Scheme of LTE

Frequency-domain scheduling and rate adaptation have helped next generation orthogonal frequency division multiple access (OFDMA) based wireless cellular systems such as Long Term Evolution (LTE) achieve significantly higher spectral efficiencies. To overcome the severe uplink feedback bandwidth constraints, LTE uses several techniques to reduce the feedback required by a frequency-domain scheduler about the channel state information of all subcarriers of all users. In this paper, we analyze the throughput achieved by the User Selected Subband feedback scheme of LTE. In it, a user feeds back only the indices of the best $M$ subbands and a single 4-bit estimate of the average rate achievable over all selected $M$ subbands. In addition, we compare the performance with the subband-level feedback scheme of LTE, and highlight the role of the scheduler by comparing the performances of the unfair greedy scheduler and the proportional fair (PF) scheduler. Our analysis sheds several insights into the working of the feedback reduction techniques used in LTE.
Comparing Classifiers for ( a special case of ) Transition-Based Parsing

Transition-based parsing has proven to be very competitive. Part of the reason for this is that with respect to machine learning the parsing reduces to multi-class classification. This allows the use of very powerful machine learning algorithms such as Support Vector Machines. If we can find an even better classifier we would expect better parsing results. We will therefore try out different classifiers in order to find the one that does best on a classification problem from transition-based parsing.
Fast Optical Monte Carlo Simulation With Surface-Based Geometries Using Chroma

We propose an alternative approach to Monte Carlo simulation of optical photons based on a detector geometry defined by triangulated surfaces rather than constructive solid geometry. This technique allows for highly optimized track propagation techniques using bounding volume hierarchies, and is also amenable to parallelization with a graphics processing unit (GPU). We describe a working implementation of this idea, called Chroma. Chroma provides a very fast realtime ray-tracer as well as a full optical Monte Carlo of a detector that can be nearly 50 times faster than GEANT4, propagating more than 1 million photons per second. We show some example uses of Chroma, including visualization of PMT properties in 3D and realtime Monte Carlo PDF generation for maximum likelihood based reconstruction.
Guided Debugging Practices of Game Based Programming for Novice Programmers

—The objective of this study is to use game based programming to facilitate the teaching of debugging for novice programmers. The programing errors which novice programmers frequently committed were involved in the game programs. Worksheets were designed to guide students how to apply debugging strategies to find these errors and correct them. The debugging practices include the programming concepts of variable assignments, boolean statements, if statements and loop statements. Forty-one senior high school students participated in this experiment for six weeks including pre-and post-achievement test. The data including programming achievement test, debugging self-efficacy and questionnaire results were collected and examined. Though students' debugging self-efficacy wasn't significantly enhanced after the experiment, the paired-samples T test results show that this model of debugging practices was effective in improving students' programming concepts. Furthermore, students showed positive attitudes to this learning model and programming learning in the future.
1.1 to 1.9GHz CMOS VCO for tuner application with resistively tuned variable inductor

A VCO is fabricated in 0. 35µm CMOS technology for tuner application as a proof of concept for a novel method of resistively tuning the inductance of an LC VCO. By employing a transformer as inductor, L is varied by changing the secondary coil current using active resistors. This eliminates the need for using multiple inductors to cover the frequency spectrum of 1.1 to 1.9GHz, resulting in large savings in area. Power consumption is comparable to other known transformer based, magnetic tuning inductance methods due to its single powered VCO core implementation. It draws about 6.8mA from a 3V supply. The achievable tuning range of 1.06 to 1.88GHz (56%) and phase noise of −116.1dBc/Hz is adequate for tuner application.