Miracle-dz/UniFAR-FTUs huggingface dataset:
Diverse Embedding Neural Network Language Models

We propose Diverse Embedding Neural Network (DENN), a novel architecture for language models (LMs). A DENNLM projects the input word history vector onto multiple diverse low-dimensional sub-spaces instead of a single higher-dimensional sub-space as in conventional feed-forward neural network LMs. We encourage these sub-spaces to be diverse during network training through an augmented loss function. Our language modeling experiments on the Penn Treebank data set show the performance benefit of using a DENNLM.
Dual-polarized patch antenna for wireless communication

The design of a dual-polarized patch antenna for Ku-band is presented in this paper. The cornerchopped square patch with bent slots is adopted in this design. The antenna has a compact structure and the total size is 15 × 15mm2. The result shows that the impedance bandwidth (VSWR ≤ 2) of the proposed antenna is 7.72% (from 11.8GHz – 12.75GHz). The antenna has achieved a stable radiation performance with gain greater than 4.25dBi across the whole operating frequency (11–14GHz). Details of the proposed antenna design and results are presented and discussed. The patch shows a high matching level in Ku-band and isolation elements that make it a suitable radiating element for base station in the wireless communication.
A COMPARISON OF SERUM LEVELS OF 25-HYDROXY VITAMIN D IN PREGNANT WOMEN AT RISK FOR GESTATIONAL DIABETES MELLITUS AND WOMEN WITHOUT RISK FACTORS

Background: During pregnancy, Low serum 25-hydroxyvitamin-D [25(OH)D] concentration is even more critical. This deficiency leads to higher incidences of preeclampsia, gestational diabetes, preterm birth, bacterial vaginosis, and also affects the health of the infants. The aim of this study was to evaluate the relationships between serum levels of 25-hydroxyvitamin D (25[OH]D) and gestational diabetes mellitus (GDM) and differences in high-risk pregnant women and women without risk factors for GDM. Methods: This cross sectional study including 155 pregnant women, who are still in the first trimester of pregnancy (less than 12 weeks gestation), were randomized to two groups of high and low risk for GDM. For these people, once at the gestational age less than 12 times a week and once at for 24 to 28 weeks of pregnancy, tests of FBS / BS / HbA1C / 25OHD / insulin / Ca / Albumin was requested. Besides, the OGTT test was performed with 75 g glucose at 24 and 28 weeks of pregnancy to diagnose GDM. Results: Serum levels of 25(OH)D in the second trimester of pregnancy ng / ml (24.1 ± 39.5) was significantly lower than that of the first trimester ng / ml (25.9 ± 45.6) (p <0.001). But serum 25(OH)D levels in the first and second trimester of pregnancy was significantly different in women at high risk for GDM than women who had no risk factors (p =0.584 and p =0.99). Serum levels of 25(OH)D has an inverse and significant relationship with HbA1C at the beginning of pregnancy (p=0.007). In addition, a significant and inverse relationship was shown between serum levels of 25(OH)D in the second trimester with insulin (p=0.047) and blood sugar 2 hours after ingestion of 75 g glucose (p=0.045) at 24-28 weeks of gestation. Conclusion: Regarding to the relationship between serum levels of 25(OH)D and blood sugar and insulin at the second trimester of pregnancy, it is recommended for pregnant women to take vitamin D supplementation.
Structural and biochemical analysis of the UvrA-binding module of the bacterial transcription-repair coupling factor Mfd

Diese Dissertation wurde selbständig, ohne unerlaubte Hilfe erarbeitet. Structural basis for transcription coupled repair: the N-terminus of Mfd resembles UvrB with degenerate ATPase motifs. Journal of Molecular Biology 355(4): 675-683. "[One] topic we touched on was mutation . We totally missed the possible role of … [DNA] repair although … I later came to realise that DNA is so precious that probably many distinct repair mechanisms would exist. Nowadays, one could hardly discuss mutation without considering repair. " Francis Crick in "The double helix: a personal view" (Crick, 1974). 1.1 DNA repair DNA, the carrier of genetic information, is constantly threatened by a variety of damaging agents. Sources of DNA damage can be either exogenous (like chemicals or radiation) or endogenous (reactive metabolites like oxygen radicals or replication errors). They affect either the nucleobases or the backbone of the DNA helix (Lodish et al., 2000; Hoeijmakers, 2001). Examples for common DNA lesions are listed in table 1.1. DNA damage types Examples Caused by Base modifications Oxidation: 8-oxoguanine Alkylation: 7-methylguanine Deamination of cytosine to uracil Oxygen radicals Alkylating reagents Spontaneous deamination Mismatches G/T or A/C pairs Replication errors Breaks in the backbone Single strand breaks (SSBs) Double strand breaks (DSBs) Ionizing radiation or chemicals Bulky photoadducts Cyclobutane-pyrimidine dimers (CPDs), 6-4-Photoproducts UV radiation Cross-links Intrastrand cross-links Interstrand cross-links Cross-linking agents (bifunctional alkyklating agents) If left unrepaired, these DNA lesions can lead to mutations – which may in higher organisms result in cancer – or cell death. DNA damaging agents are often used as chemotherapeutics in cancer therapy in order to inhibit DNA replication and therefore stop cell division. In particular, DNA cross-linking agents, e.g cis-diammine dichloroplatinum(II) (cisplatin) or mitomycin C, are applied Cells have evolved multiple repair mechanisms, which use different enzymes and deal with different kinds of lesions (see table 1. humans, several inherited disorders were found to be associated with defects in DNA Introduction 2 damage repair genes (see chapters 1.1.1.2. and 1.1.2.5.). Many of these syndromes are characterized by premature ageing and cancer predispositions (Hoeijmakers, 2001). Repair mechanism Repair systems Applied to Direct damage reversal Photoreactivation Oxidative demethylation Ligation of SSBs Photoproducts (CPDs) Alkylated bases SSBs Damage removal (Excision repair) Nucleotide excision repair (NER)-Global genome repair (GGR)-Transcription coupled repair (TCR) Base excision repair (BER) Mismatch repair (MMR) Bulky, helix-distorting lesions like photoproducts, cisplatin-adducts, or cross-links Modified bases Single-base mispairs Double strand break (DSB) repair Homologous recombination (HR) Non-homologous end-joining …
Panoramic horizon recognition

This paper describes a method in which SIFT features on and around the horizon are used for image classification (matching or recognition). Ordinarily, transformational geometry relating two images is recovered from a set of point correspondances – but correspondance formation may be improved and accelerated using geometric constraints. The proposed solution to this chicken/egg problem is to first search for an approximate geometric relationship between images using only the scale, orientation and position of SIFT features; if found, the recovered transformational geometry is used to filter feature matching. Generous feature position tolerance simplifies the search to 1 dimension in unwarped panoramic images.
Transient anomalous diffusion of tracer particles in soft matter

This paper is motivated by experiments in which time series of tracer particles in viscoelastic liquids are recorded using advanced microscopy. The experiments seek to infer either viscoelastic properties of the sample [Mason and Weitz, Phys. Rev. Lett. 74, 1250–1253 (1995)] or diffusive properties of the specific tracer particle in the host medium [Suh et al., Adv. Drug Delivery Rev. 57, 63–78 (2005); Matsui et al., Proc. Natl. Acad. Sci. U.S.A. 103, 18131–18136 (2006); Lai et al., Proc. Natl. Acad. Sci. U.S.A. 104, 1482–1487 (2007); Fricks et al., SIAM J. Appl. Math. 69, 1277–1308 (2009)]. Our focus is the latter. Experimentalists often fit data to transient anomalous diffusion: a sub-diffusive power law scaling (tν, with 0<ν<1) of mean-squared displacement (MSD) over a finite time interval, with longtime viscous scaling (t1). The time scales of sub-diffusion and exponents ν are observed to vary with particle size, particle surface chemistry, and viscoelastic properties of the host material. Until now, .
Functional Promoter Polymorphisms Govern Differential Expression of HMG-CoA Reductase Gene in Mouse Models of Essential Hypertension

3-Hydroxy-3-methylglutaryl-coenzyme A [HMG-CoA] reductase gene (Hmgcr) is a susceptibility gene for essential hypertension. Sequencing of the Hmgcr locus in genetically hypertensive BPH (blood pressure high), genetically hypotensive BPL (blood pressure low) and genetically normotensive BPN (blood pressure normal) mice yielded a number of single nucleotide polymorphisms (SNPs). BPH/BPL/BPN Hmgcr promoter-luciferase reporter constructs were generated and transfected into liver HepG2, ovarian CHO, kidney HEK-293 and neuronal N2A cells for functional characterization of the promoter SNPs. The BPH-Hmgcr promoter showed significantly less activity than the BPL-Hmgcr promoter under basal as well as nicotine/cholesterol-treated conditions. This finding was consistent with lower endogenous Hmgcr expression in liver and lower plasma cholesterol in BPH mice. Transfection experiments using 5′-promoter deletion constructs (strategically made to assess the functional significance of each promoter SNP) and computational analysis predicted lower binding affinities of transcription factors c-Fos, n-Myc and Max with the BPH-promoter as compared to the BPL-promoter. Corroboratively, the BPH promoter-luciferase reporter construct co-transfected with expression plasmids of these transcription factors displayed less pronounced augmentation of luciferase activity than the BPL construct, particularly at lower amounts of transcription factor plasmids. Electrophoretic mobility shift assays also showed diminished interactions of the BPH promoter with HepG2 nuclear proteins. Taken together, this study provides mechanistic basis for the differential Hmgcr expression in these mouse models of human essential hypertension and have implications for better understanding the role of this gene in regulation of blood pressure.
Using Internet Activity Profiling for Insider-threat Detection

The insider-threat problem continues to be a major risk to both public and private sectors, where those people who have privileged knowledge and access choose to abuse this in some way to cause harm towards their organisation. To combat against this, organisations are beginning to invest heavily in deterrence monitoring tools to observe employeesâ activity, such as computer access, Internet browsing, and email communications. Whilst such tools may provide some way towards detecting attacks afterwards, what may be more useful is preventative monitoring, where user characteristics and behaviours inform about the possibility of an attack before it happens. Psychological research advocates that the behaviour and preference of a person can be explained to a great extent by psychological constructs called personality traits, which could then possibly indicate the likelihood of an individual being a potential insider threat. By considering how browsing content relates to psychological constructs (such as OCEAN), and how an individualâs browsing behaviour deviates over time, potential insider-threats could be uncovered before significant damage is caused. The main contribution in this paper is to explore how Internet browsing activity could be used to predict the individualâs psychological characteristics in order to detect potential insider-threats. Our results demonstrate that predictive assessment can be made between the content available on a website, and the associated personality traits, which could greatly improve the prospects of preventing insider attacks.
Physical Layer Impact upon Packet Errors

We postulate a future for optical networks where data is more susceptible to errors than has been the case to date. This paper builds upon a previous study that highlighted content-dependent error in Gigabit Ethernet. In this paper we explain our previous non-uniformity results in terms of interactions between the coding scheme and observed physical layer characteristics. We also present a tool that is able to detect such non-uniform error characteristics in test and deployed networks.
Discovery of a relation between black hole mass and soft X-ray time lags in active galactic nuclei

We carried out a systematic analysis of time lags between X-ray energy bands in a large sample (32 sources) of unabsorbed, radio quiet active galactic nuclei (AGN), observed by XMM-Newton. The analysis of X-ray lags (up to the highest/shortest frequencies/time-scales), is performed in the Fourier-frequency domain, between energy bands where the soft excess (soft band) and the primary power law (hard band) dominate the emission. We report a total of 15 out of 32 sources displaying a high-frequency soft lag in their light curves. All 15 are at a significance level exceeding 97 per cent and 11 are at a level exceeding 99 per cent. Of these soft lags, seven have not been previously reported in the literature, thus this work significantly increases the number of known sources with a soft/negative lag. The characteristic time-scales of the soft/negative lag are relatively short (with typical frequencies and amplitudes of ν ∼ 0.07-4 × 10−3 Hz and τ ∼ 10-600 s, respectively), and show a highly significant (≳4σ) correlation with the black hole mass. The measured correlations indicate that soft lags are systematically shifted to lower frequencies and higher absolute amplitudes as the mass of the source increases. To first approximation, all the sources in the sample are consistent with having similar mass-scaled lag properties. These results strongly suggest the existence of a mass-scaling law for the soft/negative lag, that holds for AGN spanning a large range of masses (about 2.5 orders of magnitude), thus supporting the idea that soft lags originate in the innermost regions of AGN and are powerful tools for testing their physics and geometry.
Environmental ultrasound in laboratories and animal houses: a possible cause for concern in the welfare and use of laboratory animals

Many laboratory animals are known to be sensitive to sounds (ultrasounds) beyond the nominal upper limit (20 kHz) of the human hearing range. Sources of sound in laboratories and animal houses were examined to determine the extent of ambient ultrasound. Of 39 sources monitored, 24 were found to emit ultrasonic sounds. Many of these (e.g. cage washers and hoses) also produced sound in the audible range. Running taps, squeaky chairs and rotating glass stoppers created particularly high sound pressure levels and contained frequencies to over 100 kHz. The oscilloscopes and visual display units investigated provided particular cause for concern as they emitted sounds that were entirely ultrasonic and therefore were apparently silent. Ambient ultrasound therefore appears to be common in laboratories and animal houses. It is suggested that its effect on laboratory animals should be investigated and guidelines on acceptable levels be formulated.
Spectrum-based BIST in complex SOCs

Presents a spectral built-in-self-test (BIST) for a system-on-a-chip (SOC) environment. Test vectors are generated using the spectral properties of the embedded cores. Because some embedded cores may not have direct connections to the embedded TPG, it would be necessary to test them via other cores. As a result, testing such (cascaded) cores requires considerations on the spectral characteristics of the predecessor and successor cores. Matching spectral characteristics between the outputs of the predecessor core and dominant inputs of the successor core allows the successor core to be more testable. Experimental results for the spectral BIST showed that significantly more faults can be detected using spectral patterns than by conventional weighted random BIST technique.
Structure‐based identification of catalytic residues

The identification of catalytic residues is an essential step in functional characterization of enzymes. We present a purely structural approach to this problem, which is motivated by the difficulty of evolution‐based methods to annotate structural genomics targets that have few or no homologs in the databases. Our approach combines a state‐of‐the‐art support vector machine (SVM) classifier with novel structural features that augment structural clues by spatial averaging and Z scoring. Special attention is paid to the class imbalance problem that stems from the overwhelming number of non‐catalytic residues in enzymes compared to catalytic residues. This problem is tackled by: (1) optimizing the classifier to maximize a performance criterion that considers both Type I and Type II errors in the classification of catalytic and non‐catalytic residues; (2) under‐sampling non‐catalytic residues before SVM training; and (3) during SVM training, penalizing errors in learning catalytic residues more than errors in learning non‐catalytic residues. Tested on four enzyme datasets, one specifically designed by us to mimic the structural genomics scenario and three previously evaluated datasets, our structure‐based classifier is never inferior to similar structure‐based classifiers and comparable to classifiers that use both structural and evolutionary features. In addition to the evaluation of the performance of catalytic residue identification, we also present detailed case studies on three proteins. This analysis suggests that many false positive predictions may correspond to binding sites and other functional residues. A web server that implements the method, our own‐designed database, and the source code of the programs are publicly available at http://www.cs. bgu.ac. il/∼meshi/functionPrediction. Proteins 2011; © 2011 Wiley‐Liss, Inc.
An Approach for Configuring Ontology-based Application Context Model

Because the notion of context affects the intelligent behavior of the humans, it is generally agreed that context-awareness should be simulated in computing systems to strengthen their capability to communicate, to behavior and to process information. Context-aware infrastructure is required to be capable of configuring appropriate context model and managing it. In this paper, we propose a conceptual context modeling approach using ontology which mainly focuses on how to configure application context model through expanding the infrastructure's context model for intelligent services in pervasive computing environment
Robustness of a Class of Non-ordinary Petri Nets

Robustness analysis provides an alternative way to analyze a perturbed system to quickly respond to resource failures. Nonordinary Petri nets have weighted arcs and have the advantage to compactly model operations requiring multiple parts or resources. In this paper, we consider a class of non-ordinary flexible assembly/disassembly Petri net (NFADPN) models and study its robustness properties. Due to the routing flexibility in NFADPN, there may exist different ways to accomplish the tasks. To take advantage of the alternative routes without enforcing liveness for the whole system, we generalize the concept of persistent production proposed to NFADPN. We propose a condition for persistent production. We extend robustness analysis to NFADPN by exploiting its structure. We identify several patterns of resource failures and characterize the conditions to maintain operation in the presence of resource failures. Keywords—Petri net, robustness, failure
Performance of texture descriptors in classification of medical images with outsiders in database

During the years image classification gained important significance in practice, especially in the fields of digital radiology, remote sensing, image retrieval, etc. Typical algorithm for image classification contains descriptor extraction phase, learning phase and testing phase. Testing phase calculates accuracy of the classifier based on predetermined set of labelled images. This paper analyse performance of texture descriptors combined with SVMs, in the case when test dataset contains images not belonging to any predetermined class. A robustness of texture descriptors on outsiders is analysed, to see if descriptor is able to separate outsiders in specific class. Medical dataset containing various radiology images is used for testing. It was shown that it is possible to separate images not belonging to any class with cost of decreased performance by few percent.
Visualizing cyber attacks using IP matrix

An Internet cyber threat monitoring system detects cyber threats using network sensors deployed at particular points on the Internet, statistically analyzes the time of attack, source of attack, and type of attack, and then visualizes the result of this analysis. Existing systems, however, simply visualize country-by-country statistics of attacks or hourly changes of attacks. Using these systems, it is difficult to understand the source of attack, the diffusion of the attack, or the relation between the target and the source of the attack. This paper described a method for visualizing cyber threats by using 2-dimensional matrix representation of IP addresses. The advantages of this method are that: (1) the logical distance of IP addresses is represented intuitively; (2) Internet address space is visualized economically; (3) macroscopic information (Internet level) and microscopic information (local level) are visualized simultaneously. By using this visualization framework, propagation of the Welchia worm and the Sasser.D worm are visualized.
Melatonin‐induced increased activity of the respiratory chain complexes I and IV can prevent mitochondrial damage induced by ruthenium red in vivo

Melatonin displays antioxidant and free radical scavenger properties. Due to its ability with which it enters cells, these protective effects are manifested in all subcellular compartments. Recent studies suggest a role for melatonin in mitochondrial metabolism. To study the effects of melatonin on this organelle we used ruthenium red to induce mitochondrial damage and oxidative stress. The results show that melatonin (10 mg/kg i.p.) can increase the activity of the mitochondrial respiratory complexes I and IV after its administration in vivo in a time‐dependent manner; these changes correlate well with the half‐life of the indole in plasma. Melatonin administration also prevented the decrease in the activity of complexes I and IV due to ruthenium red (60 μg/kg i.p.) administration. At this dose, ruthenium red did not induce lipid peroxidation but it significantly reduced the activity of the antioxidative enzyme glutathione peroxidase, an effect also counteracted by melatonin. These results suggest that melatonin modulates mitochondrial respiratory activity, an effect that may account for some of the protective properties of the indoleamine. The mitochondria‐modulating role of melatonin may be of physiological significance since it seems that the indoleamine is concentrated into normal mitochondria. The data also support a pharmacological use of melatonin in drug‐induced mitochondrial damage in vivo.