Miracle-dz/UniFAR-FTUs huggingface dataset:
Binary PSO and random forests algorithm for PROBE attacks detection in a network

During the past few years, huge amount of network attacks have increased the requirement of efficient network intrusion detection techniques. Different classification techniques for identifying various attacks have been proposed in the literature. In this paper we propose and implement a hybrid classifier based on binary particle swarm optimization (BPSO) and random forests (RF) algorithm for the classification of PROBE attacks in a network. PSO is an optimization method which has a strong global search capability and is used for fine-tuning of the features whereas RF, a highly accurate classifier, is used here for classification. We demonstrate the performance of our technique using KDD99Cup dataset. We also compare the performance of our proposed classifier with eight other well-known classifiers and the results show that the performance achieved by the proposed classifier is much better than the other approaches.
Through the development of a biomechatronic knee prosthesis for transfemoral amputees: Mechanical design and manufacture, human gait characterization, intelligent control strategies and tests

This paper presents the development of a biomechatronic knee prosthesis for transfemoral amputees. This kind of prostheses are considered ‘intelligent’ because they are able to automatically adapt their response at the knee axis, as a natural knee does. This behavior is achieved by characterizing the amputee's gait through the signals captured with instrumentation of a prosthesis, which provides feedback about its current state along the gait cycle and therefore responds with the corresponding control action. In this case, unlike other commercially available intelligent knee prostheses, gait cycle characterization is based on accelerometers signals processed by an events detection algorithm. Two intelligent control strategies are presented: a bio-inspired approach, that consists of using a central pattern generator to generate a knee angle reference to be followed by the prosthesis during walking, and an adaptive scheme, that applies a control action proportional to the knee angle according to an auto-adaptive parameter dependant on gait speed. The mechanical design of the prosthesis is also presented, showing the knee joint mechanism and part of the manufacturing process. Results obtained from walking tests with both able body and amputees are shown, demonstrating the positive performance of the prosthesis in several aspects. Future works aimed at a finished product are also stated.
Global Error Bounds for Convex Conic Problems

This paper aims at deriving and proving some Lipschitzian-type error bounds for convex conic problems in a simple way. First, it is shown that if the recession directions satisfy Slater's condition, then a global Lipschitzian-type error bound holds. Alternatively, if the feasible region is bounded, then the ordinary Slater condition guarantees a global Lipschitzian-type error bound. These can be considered as generalizations of previously known results for inequality systems, which also follow from general results by Bauschke and Borwein in [ SIAM Review, 38 (1996), pp. 367--426] and Bauschke, Borwein, and Li in a 1997 report. However, the proofs in the current paper are considerably simpler. Some of the results are generalized to the intersection of multiple shifted cones (with different shifts). Under Slater's condition alone, a global Lipschitzian-type error bound does not hold. It is shown, however, that such an error bound holds for a specific conic region. For linear systems we establish that the sharp constant involved in Hoffman's error bound is nothing but the condition number for linear programming as used by Vavasis and Ye in [ Math. Programming, 74 (1996), pp. 79--120].
Selection and Characterization of Pre-mRNA Splicing Enhancers: Identification of Novel SR Protein-Specific Enhancer Sequences

ABSTRACT Splicing enhancers are RNA sequences required for accurate splice site recognition and the control of alternative splicing. In this study, we used an in vitro selection procedure to identify and characterize novel RNA sequences capable of functioning as pre-mRNA splicing enhancers. Randomized 18-nucleotide RNA sequences were inserted downstream from a Drosophila doublesex pre-mRNA enhancer-dependent splicing substrate. Functional splicing enhancers were then selected by multiple rounds of in vitro splicing in nuclear extracts, reverse transcription, and selective PCR amplification of the spliced products. Characterization of the selected splicing enhancers revealed a highly heterogeneous population of sequences, but we identified six classes of recurring degenerate sequence motifs five to seven nucleotides in length including novel splicing enhancer sequence motifs. Analysis of selected splicing enhancer elements and other enhancers in S100 complementation assays led to the identification of individual enhancers capable of being activated by specific serine/arginine (SR)-rich splicing factors (SC35, 9G8, and SF2/ASF). In addition, a potent splicing enhancer sequence isolated in the selection specifically binds a 20-kDa SR protein. This enhancer sequence has a high level of sequence homology with a recently identified RNA-protein adduct that can be immunoprecipitated with an SRp20-specific antibody. We conclude that distinct classes of selected enhancers are activated by specific SR proteins, but there is considerable sequence degeneracy within each class. The results presented here, in conjunction with previous studies, reveal a remarkably broad spectrum of RNA sequences capable of binding specific SR proteins and/or functioning as SR-specific splicing enhancers.
Ground traffic signs recognition based on Zernike moments and SVM

In this paper, we propose an approach for recognizing ground traffic signs based on Zernike moments and support vector machine. Traditional traffic signs recognition was focus on the signs beside road, but there are relatively few researches on the ground traffic signs recognition. Ground traffic signs are important indication signs to indicate the carriageway. During the process of vehicle running, drivers need to judge which carriageway they are in, and select the right carriageway according to the itinerary planning. In order to recognize different traffic signs, we propose that using Zernike moments as the features of traffic signs, and SVM is used to classify the features. Real road scene images are used to evaluate the performance, and five classes of traffic signs are considered. Simulations show that our approach can recognize ground traffic signs effectively and practically.
Task Scheduling using Parallel Genetic Algorithm implemented with GRADE

In this paper, we present a task scheduling heuristic, based on a parallel genet ic algorithm (PGA). The algorithm schedules parallel programs, represented as directed acyclic graphs (DAGs), onto multi-processor systems with dy namic interconnection networks (DIN). It combines PGA with list scheduling approach and takes into account inter-processor communication cost, link contention in the DIN and changes of inter-processor connections. Parallel Genetic Algori thm is currently implemented on a cluster of workstations in GRADE environment.
No Coupling, No Decoupling, Only Mutual Inter-Dependence: Business Cycles in Emerging vs. Mature Economies

Even before the events of the past few years, economists and policy makers were musing about the apparent contradiction between globalization, as it is generally understood, and the seemingly different paths in overall economic activity taken by the emerging and more mature economies of the world. The present paper reconsiders whether it is, in fact, useful to think of correlations in business cycle movements as reflecting some form of coupling or decoupling and, instead, suggests that, even if business cycles may well have become more synchronous for a time, it is more useful to think of international business cycle co-movements as reflecting their mutual dependence that can be subjected to short-run interruptions or affected by a variety of other economic factors. I report evidence based on factor-augmented quantile regressions for a panel of annual data since 1980 from 9 regions of the world. A panel is used to estimate the common factors which are then applied to the quantile regression model to determine the sources of business cycle co-movements across countries and regions of the world.
Augmenter of liver regeneration: a flavin-dependent sulfhydryl oxidase with cytochrome c reductase activity.

Augmenter of liver regeneration (ALR; hepatopoietin) is a recently discovered enigmatic flavin-linked sulfhydryl oxidase. An N-terminal His-tagged construct of the short form of the human protein has been overexpressed in Escherichia coli. Several lines of evidence suggest that, contrary to a recent report, human ALR is a disulfide-bridged dimer (linked via C15-C124) with two free cysteine residues (C74 and 85) per monomer. The C15-124 disulfides are not critical for dimer formation and have insignificant impact on the dithiothreitol (DTT) oxidase activity of ALR. Although the crystal structure of rat ALR shows a proximal disulfide (C62-C65) poised to interact with the FAD prosthetic group [Wu, C. K. , Dailey, T. A. , Dailey, H. A. , Wang, B. C. , and Rose, J. P. (2003) Protein Sci. 12, 1109-1118], only flavin reduction is evident during redox titrations of the enzyme. ALR forms large amounts of neutral semiquinone during aerobic turnover with DTT. This semiquinone arises, in part, by comproportionation between flavin centers within the dimer. Surprisingly, cytochrome c is about a 100-fold better electron acceptor for ALR than oxygen when DTT is the reducing substrate. These data suggest that this poorly understood flavoenzyme may not function as a sulfhydryl oxidase within the mitochondrial intermembrane space but may communicate with the respiratory chain via the mediation of cytochrome c.
Predicting Reasoning from Memory

In an effort to assess the relations between reasoning and memory, in 8 experiments, the authors examined how well responses on an inductive reasoning task are predicted from responses on a recognition memory task for the same picture stimuli. Across several experimental manipulations, such as varying study time, presentation frequency, and the presence of stimuli from other categories, there was a high correlation between reasoning and memory responses (average r ϭ .87), and these manipulations showed similar effects on the 2 tasks. The results point to common mechanisms underlying inductive reasoning and recognition memory abilities. A mathematical model, GEN-EX (generalization from examples), derived from exemplar models of categorization, is presented, which predicts both reasoning and memory responses from pairwise similarities among the stimuli, allowing for additional influences of subtyping and deterministic responding. Inductive inference involves extending knowledge from known instances to novel instances and is a central component of human learning and reasoning. Such reasoning leads to conclusions that are probable rather than certain and is therefore thought to be critical to people's everyday encounters with an uncertain world. For example, after learning that lions, horses, and otters use dopamine as a neurotransmitter, one might make a reasonably confident (but by no means certain) inference that this property is shared by other mammals. Many believe that inductive reasoning is the most important component of human thought because " in-ductive inference is the only process. by which new knowledge comes into the world " (Fisher, 1951, p. 7). In 2 decades of research, a number of general principles that people follow when making inductive inferences has been identified (see Hayes, Heit, & Swendsen, 2010; Sloman & Lagnado, 2005, for reviews). The cognitive mechanisms underlying induction and the relation between these mechanisms and those underlying other cognitive phenomena such as categorization and memory , however, remain matters of intense debate (cf. Hayes & Heit, 2004). This article addresses two shortcomings in current process theories of induction. First, most current models of induction (e. have been framed to explain how novel properties are generalized from one or more categories of objects to other categories (as in the neurotransmitter example above). Although this kind of reasoning is important, it is also essential to explain how people generalize novel properties involving individual exemplars. Knowing the general characteristics of dogs does not necessarily help you to make an inference about whether a neighbor's dog will …
On the Impact of Garbage Collection on Flash-Based SSD Endurance

Garbage collection has a profound impact on the write amplification in flash-based SSDs, which in turn may significantly reduce its life span. The unequal wear of data blocks further contributes to this reduced life span. In this paper we study two performance measures: the SSD endurance which assesses the life span of an SSD and the PE fairness which is a measure for the degree of unequal wear. We demonstrate, using a mean field model and simulation, how these measures are affected by the garbage collection algorithm, spare factor, etc. Numerical results indicate that under uniform random writes there is no need to implement a wear leveling technique. For hot and cold data we see that design choices that lower the PE fairness may still result in a higher SSD endurance, which suggests that one should not emphasize too much on equaling the wear.
Evaluasi User Experiences Produk iDigital Museum dengan Menggunakan UEQ

Danau Bandung Purba, sebuah peristiwa geologis yang luar biasa, tidak akan menarik minat pengunjung untuk mengetahui dan memahami jika disampaikan dalam bentuk statis dan konvensional. Aplikasi Interaktif Bandung Purba merupakan suatu prototipe subsistem, bagian dari sistem iDigital Museum, yang bertujuan menyajikan fenomena geologis dalam bentuk yang lebih menarik, melibatkan interaksi dengan pemakai. Pemakai diberikan kesempatan menjelajah area Danau Bandung Purba dan mengenal artefak yang ada, dengan dipandu oleh sistem maupun memilih sendiri. Sistem diimplementasikan memakai aplikasi Unity 3D. Pengujian produk dilakukan dengan memakai User Experience Questionnaire, dengan hasil menunjukkan impresi positif kelompok attractiveness, perspiculty, efficiency, dependability, stimulation dan novelty
Effect of pioglitazone treatment on the adrenal androgen response to corticotrophin in obese patients with polycystic ovary syndrome.

BACKGROUND To investigate the effect of pioglitazone on adrenal steroidogenesis in polycystic ovary syndrome (PCOS), we studied 11 obese (two with BMI >25 kg/m(2); nine with BMI >27 kg/m(2)) PCOS women before and after 6 months of treatment at a dose of 45 mg/day. METHODS During the early follicular phase, ultrasonography and hormonal assays were performed. On separate days, all women underwent an oral glucose tolerance test (OGTT), a euglycaemic hyperinsulinaemic clamp and an adrenocorticotrophin hormone (ACTH) test. The same protocol was repeated after therapy. RESULTS Pioglitazone treatment significantly reduced the insulin response to OGTT and improved the insulin sensitivity indices (P < 0.01 and P = 0.03 respectively). A significant decrease was found in LH (P < 0.05) and androstenedione (P < 0.01) levels after therapy, whereas the other hormonal parameters improved but not significantly. Pioglitazone administration reduced the response of 17alpha-hydroxyprogesterone (17OHP) and androstenedione to ACTH (P < 0.01 and P < 0.02 respectively), most likely through an inhibition of cytochrome P450. The same treatment was able to rebalance the relative activity of 17,20-lyase, as documented by an increase in the androstenedione:17OHP ratio (P < 0.05) after ACTH stimulation. CONCLUSIONS Our data support the contention that insulin enhances ACTH-stimulated steroidogenesis, while inducing a relative impairment of 17,20-lyase activity. Whether the beneficial effects of pioglitazone on this imbalance could be related to the ameliorated glyco-insulinaemic metabolism or to a direct effect on the adrenal glands remains to be determined.
Pot à musique: tangible interaction with digital media

We describe the conceptualisation, design and prototype development of a tangible gesture-based interface for the control of a music player. The device takes the form of a pot, augmented with inertial sensing and model-based vibrotactile feedback, which it is envisioned will encourage a more playful form of interaction for a richer interactive experience with our increasingly dematerialised digital media.
Quantum Turing automata

A denotational semantics of quantum Turing machines having a quantum control is defined in the dagger compact closed category of finite dimensional Hilbert spaces. Using the Moore-Penrose generalized inverse, a new additive trace is introduced on the restriction of this category to isometries, which trace is carried over to directed quantum Turing machines as monoidal automata. The Joyal-Street-Verity Int construction is then used to extend this structure to a reversible bidirectional one.
Realistic Mouth-Synching for Speech-Driven Talking Face Using Articulatory Modelling

This paper presents an articulatory modelling approach to convert acoustic speech into realistic mouth animation. We directly model the movements of articulators, such as lips, tongue, and teeth, using a dynamic Bayesian network (DBN)-based audio-visual articulatory model (AVAM). A multiple-stream structure with a shared articulator layer is adopted in the model to synchronously associate the two building blocks of speech, i.e., audio and video. This model not only describes the synchronization between visual articulatory movements and audio speech, but also reflects the linguistic fact that different articulators evolve asynchronously. We also present a Baum-Welch DBN inversion (DBNI) algorithm to generate optimal facial parameters from audio given the trained AVAM under maximum likelihood (ML) criterion. Extensive objective and subjective evaluations on the JEWEL audio-visual dataset demonstrate that compared with phonemic HMM approaches, facial parameters estimated by our approach follow the true parameters more accurately, and the synthesized facial animation sequences are so lively that 38% of them are undistinguishable
Cotinine and Polycyclic Aromatic Hydrocarbons Levels in the Amniotic Fluid and Fetal Cord at Birth and in the Urine from Pregnant Smokers

Cigarette smoking during pregnancy has several impacts on fetal development, including teratogenic effects. The objective of this study was to assess whether the toxic substances (cotinine and polycyclic aromatic hydrocarbons) found in pregnant smokers are transmitted to their fetuses. The outcomes were analyzed measuring cotinine and 1-hydroxypyrene in the amniotic fluid and maternal urine, benzopyrene and cotinine in the umbilical cord blood. Through a controlled cross-sectional design, 125 pregnant women were selected and classified according to their smoking status: 37 current smokers, 25 passive smokers and 63 non-smokers (controls). We performed high-performance liquid chromatography to measure substances’ concentrations. A post-hoc Tukey’s test was used to analyze the differences between the groups. All variables were significantly different between controls and smokers. The mean ratios between the concentration of cotinine in smokers compared to controls were as follows: 5.9 [2.5–13.5], p<0.001 in the urine; 25 [11.9–52.9], p<0.001 in the amniotic fluid; and 2.6 [1.0–6.8], p = 0.044 in the umbilical cord blood. The mean ratios of 1-hydroxypyrene concentration between smokers and controls were 7.3 [1.6–29.6], p = 0.003 in the urine and 1.3 [1.0–1.7], p = 0.012 in the amniotic fluid, and of benzopyrene in umbilical cord blood was 2.9 [1.7–4.7], p<0.001. There were no significant differences between controls and passive smokers. When comparing the three groups together, there were statistical differences between all variables. Thus, the fetuses of pregnant smokers are exposed to toxic and carcinogens substances. To our knowledge, this is the first study to measure 1-hydroxypyrene in the amniotic fluid and benzopyrene in umbilical cord blood by high-performance liquid chromatography when considering pregnant women in relation to smoking exposure only.
Excitability Changes Related to GABAA Receptor Plasticity during Pregnancy

Alterations in GABAA receptor (GABAAR) expression and function, similar to those we described previously during pregnancy in the mouse dentate gyrus, may also occur in other brain regions. Here we show, using immunohistochemical techniques, a decreased δ subunit-containing GABAAR (δGABAAR) expression in the dentate gyrus, hippocampal CA1 region, thalamus, and striatum but not in the cerebral cortex. In the face of the highly elevated neurosteroid levels during pregnancy, which can act on δGABAARs, it may be beneficial to decrease the number of neurosteroid-sensitive receptors to maintain a steady-state level of neuronal excitability throughout pregnancy. Consistent with this hypothesis, the synaptic input/output (I/O) relationship in the dentate gyrus molecular layer in response to lateral perforant path stimulation was shifted to the left in hippocampal slices from pregnant compared with virgin mice. The addition of allopregnanolone, at levels comparable with those found during pregnancy (100 nm), shifted the I/O curves in pregnant mice back to virgin levels. There was a decreased threshold to induce epileptiform local field potentials in slices from pregnant mice compared with virgin, but allopregnanolone reverted the threshold for inducing epileptiform activity to virgin levels. According to these data, neuronal excitability is increased in pregnant mice in the absence of allopregnanolone attributable to brain region-specific downregulation of δGABAAR expression. In brain regions, such as the cortex, that do not exhibit alterations in δGABAAR expression, there were no changes in the I/O relationship during pregnancy. Similarly, no changes in network excitability were detected in pregnant Gabrd−/− mice that lack δGABAARs, suggesting that changes in neuronal excitability during pregnancy are attributable to alterations in the expression of these receptors. Our findings indicate that alterations in δGABAAR expression during pregnancy result in brain region-specific increases in neuronal excitability that are restored by the high levels of allopregnanolone under normal conditions but under pathological conditions may result in neurological and psychiatric disorders associated with pregnancy and postpartum.