Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling NICs with Unicorn

NICs are increasingly complex and diverse, offering a wide range of hardware functionality to aid network protocol processing. Harnessing the power of NIC hardware requires the ability to control and reason about a variety of different feature sets in the network stack. Towards this goal, we propose Unicorn, a language for describing modern NICs. Unicorn offers a simple set of abstractions for modeling both NIC functionality and the state of a protocol stack. To evaluate its expressivity and potential, we present a non-trivial model for the Intel i82599 10GbE NIC, and an algorithm that uses graph embedding to optimize the use of NIC hardware in the network stack.
Retention performances of green roofs worldwide at different time scales

Urbanization process is rapidly converting forested areas and grasslands to residential, commercial, or industrial spaces, triggering soil degradation and significantly increasing impervious surfaces. Consequently, man‐made environments experience significant decrease of infiltration and groundwater recharge, enhancing the problems related to the management and protection from increased stormwater runoff. Green roofs are structural measures able to mitigate these negative drawbacks due to anthropic transformation, retaining and detaining stormwater runoff, with the main advantage of reducing hydraulic loads on combined storm sewer systems. Hydrological performance of green roofs have been studied in different parts of the world under different climatic conditions, but a comprehensive study that provides global responses, even in an approximate way, is still missing. The aim of this work is to assess the convenience and the feasibility of installing green roofs in any target area of the world, providing a rough indication of geographic regions where green roof installation is possible with good hydrological performance, and feasible in rainfed conditions with low vegetation water stress. To do that, we explored in silico green roofs' hydrological performance worldwide, using climatological forcings from ERA‐Interim database as input for a simple conceptual hydrological model to estimate green roof outputs, in terms of evapotranspiration and runoff.
A Pilot Study of Glaucoma Visual Field Screening in Diabetes

Because people with diabetes may be at increased risk of glaucoma, we performed a pilot study using automated visual field testing for screening them. One hundred and seventy-six diabetic persons who had participated in the Wisconsin Epidemiologic Study of Diabetic Retinopathy were tested with the Armaly-Drance screening pattern on the Humphrey Visual Field Analyzer. Individuals with moderate diabetic retinopathy or worse tended to have lower sensitivity of the central visual field and missed more points than those with no or only mild retinopathy. People with a history of glaucoma had slightly less sensitivity and missed more points than controls. These preliminary findings suggest that although people with diabetes and glaucoma may more frequently have visual field defects than people with diabetes but no glaucoma, a larger study is needed. This pilot study shows that such a study would be feasible and should be designed to indicate the sensitivity, specificity, and cost-benefit ratio of a screening program so as to assess the utility of the screening visual field test for finding glaucoma amongst people with diabetes.
Neighborhood prefetching on multiprocessors using instruction history

A multiprocessor prefetch scheme is described in which a miss is followed by a prefetch of a group of lines, a neighborhood, surrounding the demand-fetched line. The neighborhood is based on the data address and the past behavior of the instruction that missed the cache. A neighborhood for an instruction is constructed by recording the offsets of addresses that subsequently miss. This neighborhood prefetching can exploit sequential access as can sequential prefetch and can to some extent exploit stride access, as can stride prefetch. Unlike stride and sequential prefetch it can support irregular access patterns. Neighborhood prefetching was compared to adaptive sequential prefetching using execution-driven simulation. Results show more useful prefetches and lower execution time for neighborhood prefetching for six of eight SPLASH-2 benchmarks. On eight SPLASH-2 benchmarks the average normalized execution, time is less than 0.9, for three benchmarks, less than 0.8.
Molecular Diversity in Bulgarian and Cypriot Barley Germplasm Collections – A Reference Point for Better Understanding, Exploitation and Improvement of Adaptiveness to Agro-Climatic Conditions

Barley is one of the major crops for Bulgaria and Cyprus. Knowledge of genetic diversity in barley germplasm helps to ensure that a broad genetic base of breeding materials is maintained not just for sustaining genetic improvement but also for reducing genetic vulnerability to pest, biotic and abiotic stresses. The changeable climatic conditions require precise selection of new cultivars and advanced breeding lines for high yield, tolerance to multiple stress factors and adaptation to different agro-climatic conditions. Responding to the demands for improvement of cereal crops in Bulgaria and Cyprus, a large scale characterization of native and newly introduced valuable germplasm was initiated by molecular markers. The objective of the present study is to compare and explore the genetic diversity in Bulgarian and Cypriot barley collections by SSR markers.
Rogers , M . F . , Shihab , H . A . , Ferlaino , M . , Gaunt

Sequencing data will become widely available in clinical practice within the near future. Uptake of sequence data is currently being stimulated within the UK through the government-funded 100,000 genomes project (Genomics England), with many similar initiatives being planned and supported internationally. The analysis of the large volumes of data derived from sequencing programmes poses a major challenge for data analysis. In this paper we outline progress we have made in the development of predictors for estimating the pathogenic impact of single nucleotide variants, indels and haploinsufficiency in the human genome. The accuracy of these methods is enhanced through the development of disease-specific predictors, trained on appropriate data, and used within a specific disease context. We outline current research on the development of disease-specific predictors, specifically in the context of cancer research.
Optimization Algorithms for Designing a Two-Section Dual-Band Transformer

In this paper, we focus on designing an impedance transformer with two sections and capable of achieving matching at two arbitrary frequencies. Specifically, the problem is formulated as minimizing the reflection coefficient by finding the optimal value of characteristic impedance and line length for the two section transmission line under the constraints of limited value for characteristic impedance. Using Convex Optimization and Steepest Descend Algorithm, we successfully find the optimal parameters for the transmission line. Simulation result shows that this algorithm can achieve reflection coefficient lower than 0.001 at the transmission frequency in GSM system while still guaranteeing a promising bandwidth of 70.6MHz.
Yeast Sequencing Reports Sequence Analysis of a 33.1 kb Fragment from the Left Arm of Saccharom yces cerevisiae Chromosome X, Including Putative “Proteins with Leucine Zippers, a Fungal Zn(II),-Cys, Binuclear Cluster Domain and a Putative a2-SCB-a2 Binding Site

In the framework of the European BIOTECH project for sequencing the Saccharomyces cerevisiae genome, we have determined the nucleotide sequence of the left part of the cosmid clone 232 and the cosmid clone 233 provided by F. Galibert (Rennes Cedex, France). We present here 33,099 base pairs of sequence derived from the left arm of chromosome X of strain S288C. This sequence reveals 17 open reading frames (ORFs) with more than 299 base pairs, including the published sequences for ARG3, LIGTRILIGI, ORF2, ACT3 and SCP160. Two other ORFs showed similarity with S. cerevisiae genes: one with the CAN1 gene coding for an arginine permease, and one with genes encoding the family of transcriptional activators containing a fungal Zn(II),-Cys, binuclear cluster domain like that found in Pprlp or Gal4p. Both putative proteins contain a leucine zipper motif, the Canlp homologue has 12 putative membrane-spanning domains and a putative a2-SCB-a2 binding site. In a diploid disruption mutant of ORF J0922 coding for the transcriptional activator homologue, no colonies appeared before 10 days after transformation and then grew slowly. In contrast, haploid disruption mutants showed a growth phenotype like wild-type cells. One ORF showed weak similarity to the rad4 gene product of Schizosaccharomyces pomhe and is essential for yeast growth. Five ORFs showed similarity to putative genes on the right arm of chromosome XI of 5’. cerevisiae. Two of them have similarity to each other and belong to a family of extracellular proteins that groups tnammalian SCPlTpx-1, insects Ag3lAg5, plants PR-1 and fungi Sc71Sc14. Three small ORFs are completely contained in the larger ORFs on the corresponding complementary strand and thus probably do not represent real genes. The DNA sequence has been deposited in the EMBL data library under Accession Number X83502.
The Brokerage Institution and the Development of Agricultural Markets: New Evidence from Ethiopia

Recognition that policies aimed at ‘getting prices right’ in less-developed countries have not been successful due to incomplete markets has spurred a new wave of reforms aimed instead at ‘getting markets and institutions right’. Previous studies of this policy shift have documented the potentially crucial role played by the brokerage institution in crop commercialization. However, few have investigated the factors that influence wholesalers’ decisions regarding their use of brokers. Results from a primary survey with traders show that brokerage services are particularly valuable for wholesalers who lack social capital and storage capacity, who are based in areas with low population density, and who trade at a distance, especially when roads are not asphalt. Buyers in drought-prone domains rely on brokers more for their long-distance purchases, while sellers in moisture-reliable domains employ brokers more for their long-distance sales. These results provide useful indications regarding where and how the recent formalization of brokerage functions through the Ethiopian Commodity Exchange (ECX) could be most beneficial for the functioning of Ethiopian agricultural markets.
Variable-component, energy-efficient technology for groundwater remediation

ABSTRACT A groundwater flow and mass transport model was used to evaluate energy-efficient alternatives for remediating a contaminated, unconfined aquifer. Alternatives were a two-well scheme featuring a downgradient extraction and upgradient injection well pumping at the same rate, and a two-well scheme augmented with passive (non-pumping) wells equipped with treatment (reactive) media. The augmented two-well scheme was the same as the plain two-well scheme, but for the addition of passive wells. The passive wells occupied a linear transect oriented perpendicular to the local hydraulic gradient and offset downgradient of the extraction well. Various combinations of passive well spacing and downgradient offset were evaluated in augmented schemes. The two-well scheme required a slightly higher pumping rate to contain and remove the contaminant plume; however, it removed the plume in less time than augmented schemes. In this case, “removed the plume” meant that simulated concentrations dropped below 1 mg/L at all model cells. Augmented schemes contained and removed the plume at a lower pumping rate, while removing less water and contaminant mass. Small differences in transect location and well spacing had substantial impact on the performance of augmented schemes. Overall, results of this study suggest that two-well and augmented schemes may be effective low-energy alternatives for remediating contaminated groundwater in some settings.
First-order phase transitions with more than one conserved charge: Consequences for neutron stars.

We consider how first-order phase transitions in systems having more than one conserved charge (multicomponent systems) differ from those in systems having only one. In general, the properties of the transition are quite different in the two cases. Perhaps most importantly the pressure varies continuously with the proportion of phases in equilibrium, and is not a constant in the mixed phase as in the example of the gas-liquid transition in familiar one-component systems. We identify the microphysics responsible for the difference. In the case that one of the conserved charges is the electric charge, a geometrical structure in the mixed phase is expected. As an example, possible consequences are developed for the structure of a neutron star in which the transition to quark matter in the core occurs. It is also pointed out that the general results pertain to relativistic nuclear collisions in the so-called stopping or baryon-rich domain where there are three conserved charges (baryon, electric, and strangeness), and impact the expected phase transition from confined hadronic matter to quark matter as regards signals that are supposedly driven by pressure. The physics discussed here is also relevant to the subnuclear gas-liquid transition that is under study in lower-energy nuclearmore » collisions. « less
Geometric Lévy Process Pricing Model

We consider models for stock prices which relates to random processes with independent homogeneous increments (Levy processes). These models are arbitrage free but correspond to the incomplete financial market. There are many different approaches for pricing of financial derivatives. We consider here mainly the approach which is based on minimal relative entropy. This method is related to an utility function of exponential type and the Esscher transformation of probabilistic measures.
Prevalence of Depressive Symptoms among University Students in Oman.

OBJECTIVES To study the prevalence of depressive symptoms and its association with gender, academic year, and college among university students in Oman. METHODS A cross-sectional study was conducted among Omani students attending the students' clinic of the Sultan Qaboos University (SQU). A systematic sampling of students, males and females, from different colleges, who visited the clinic during the study period, was carried out. The self-administered Patient Health Questionnaire (PHQ-9) was used to screen for propensity to depression. RESULTS A total of 481 students participated in the study (243 males and 238 females). Overall, 133 (27.7%) of the participants (66 males and 67 females) had depression of various grades based on the PHQ-9 diagnostic criteria using a cut point of more than 11. Depression score at the cut point of 11 was not statistically associated with gender, college and the academic year. CONCLUSION Tendency for depression might be a common health problem among college students in Oman attending primary health care facilities. Further research on socio-demographic characteristics and the effect of depression on the academic performance is needed.
Dirichlet-Derived Multiple Topic Scene Classification Model for High Spatial Resolution Remote Sensing Imagery

Due to the complex arrangements of the ground objects in high spatial resolution (HSR) imagery scenes, HSR imagery scene classification is a challenging task, which is aimed at bridging the semantic gap between the low-level features and the high-level semantic concepts. A combination of multiple complementary features for HSR imagery scene classification is considered a potential way to improve the performance. However, the different types of features have different characteristics, and how to fuse the different types of features is a classic problem. In this paper, a Dirichlet-derived multiple topic model (DMTM) is proposed to fuse heterogeneous features at a topic level for HSR imagery scene classification. An efficient algorithm based on a variational expectation-maximization framework is developed to infer the DMTM and estimate the parameters of the DMTM. The proposed DMTM scene classification method is able to incorporate different types of features with different characteristics, no matter whether these features are local or global, discrete or continuous. Meanwhile, the proposed DMTM can also reduce the dimension of the features representing the HSR images. In our experiments, three types of heterogeneous features, i.e., the local spectral feature, the local structural feature, and the global textural feature, were employed. The experimental results with three different HSR imagery data sets show that the three types of features are complementary. In addition, the proposed DMTM is able to reduce the dimension of the features representing the HSR images, to fuse the different types of features efficiently, and to improve the performance of the scene classification over that of other scene classification algorithms based on spatial pyramid matching, probabilistic latent semantic analysis, and latent Dirichlet allocation.
Cold-Induced Expression of Δ9-Desaturase in Carp by Transcriptional and Posttranslational Mechanisms

Poikilothermic animals respond to chronic cold by increasing phosphoglyceride unsaturation to restore the fluidity of cold-rigidified membranes. Despite the importance of this compensatory response, the enzymes involved have not been clearly identified, and the mechanisms that control their activity are unknown. In carp liver, cold induces an 8- to 10-fold increase in specific activity of the microsomal stearoyl coenzyme A desaturase. Cold-induced up-regulation of gene transcription resulted in a 10-fold increase in desaturase transcript amounts after 48 to 60 hours. However, this increase was preceded by the activation of latent desaturase, probably by a posttranslational mechanism. These two mechanisms may act sequentially to match desaturase expression to the demands imposed by a progressive decrease in temperature.
Sleep Deprivation Effects on Growth Factor Expression in Neonatal Rats : A Potential Role for BDNF in the Mediation of Delta Power

Ilana S. Hairston, Christelle Peyron, Daniel P. Denning, Norman F. Ruby, Judith Flores, Robert M. Sapolsky, H. Craig Heller, and Bruce F. O’Hara Department of Biological Sciences, Stanford University, Stanford, California 94305-5020; Centre National de la Recherche Scientifique Unité Mixte de Recherche 5167, Faculté de Médecine RTH Laënnec, 69 372 Lyon Cedex 08, France; and Department of Biology, University of Kentucky, Lexington, Kentucky 40506-0225
Rapid Feature Learning with Stacked Linear Denoisers

We investigate unsupervised pre-training of deep architectures as feature generators for "shallow" classifiers. Stacked Denoising Autoencoders (SdA), when used as feature pre-processing tools for SVM classification, can lead to significant improvements in accuracy - however, at the price of a substantial increase in computational cost. In this paper we create a simple algorithm which mimics the layer by layer training of SdAs. However, in contrast to SdAs, our algorithm requires no training through gradient descent as the parameters can be computed in closed-form. It can be implemented in less than 20 lines of MATLABTMand reduces the computation time from several hours to mere seconds. We show that our feature transformation reliably improves the results of SVM classification significantly on all our data sets - often outperforming SdAs and even deep neural networks in three out of four deep learning benchmarks.
Audio Concept Ranking for Video Event Detection on User-Generated Content

Video event detection on user-generated content (UGC) aims to find videos that show an observable event such as a wedding ceremony or birthday party rather than an object, such as a wedding dress, or an audio concept, such as music, speech or clapping. Different events are better described by different concepts. Therefore, proper audio concept classification enhances the search for acoustic cues in this challenge. However, audio concepts for training are typically chosen and annotated by humans and are not necessarily relevant to a specific event or the distinguishing factor for a particular event. A typical ad-hoc annotation process ignores the complex characteristics of UGC audio, such as concept ambiguities, overlap, and duration. This paper presents a methodology to rank audio concepts based on relevance to the events and contribution to the ability to discriminate. A ranking measure guides an automatic selection of concepts in order to improve audio concept classification with the goal to improve video event detection. The ranking aids to determine and select the most relevant concepts for each event, to discard meaningless concepts, and to combine ambiguous sounds to enhance a concept, thereby suggesting a focus for annotation and a better understanding of the UGC audio. Experiments show an improvement of the audio concepts mean classification accuracy per frame as well as a better-defined diagonal in the confusion matrix and a higher relevance score. In terms of accuracy, the selection of top 40 audio concepts using our methodology outperforms the highest-accuracy-based selection by a relative 17.56% and a frame-frequency-based selection by 5.74%. In terms of relevance to the events, the ranking-based selection provided the highest score. Index Terms: event detection, audio concept, user generated content, acoustic video processing.
Generation of frequency-doubled 55 fs pulses from an Erbium fiber laser system

We report on the frequency doubling of an Erbium-doped master-oscillator power-amplifier system. The fundamental 72 fs pulses at a wavelength of 1.56 μm are frequency doubled to 780 nm and compressed in a Gires-Tournois-interferometer mirror pair to a duration of 55 fs with an average power of 172 mW with an efficiency of 48%. To our knowledge these are the shortest pulses ever reported from a frequency-doubled fiber-laser system.
A Proposed Approach for Arabic Language Segmentation

This paper presents a research about natural language processing (NLP). Our area of interest is the process of Arabic text segmentation. Text segmentation is important step in any NLP. In this paper, we discuss several methods dealing mainly with cases of ambiguity of Arabic text segmentation. Several conclusions have been made. These conclusions lead to make a proposal of text segmentation. A vision based on connectors is developed.
A Lower-Bound for Answer Set Solver Computation

We build upon recent work by Lierler that denes an abstract framework for describing the algorithm underlying many of the existing answer set solvers (for answer set programs, based upon the Answer Set Seman- tics), considering in particular Smodels and SUP. We dene a particular class of programs, called AOH, and prove that the computation that the abstract solver performs actually represents a lower bound for deciding inconsis- tency of logic programs under the Answer Set Semantics. The main result is that for a given AOH program with n atoms, an algorithm that conforms to Lierler's abstract model needs ( n) steps before exiting with failure (no answer set exists). We argue that our result holds for every logic program that, like AOH programs, contains cyclic denitions and rules that can be seen as connecting the cycles.
Industrial Transformation, Heterogeneity in Price Stickiness, and the Great Moderation

Since the ’80s the volatility of output growth and in‡ation experienced by several industrialized countries has remarkably declined, what has been dubbed the "Great Moderation". Various explanations have been proposed and likely all play some role. This paper shows that when an industrial transformation reduces the weight of the manufacturing sector relative to the services sector, the presence of sectoral heterogeneity in price stickiness leads to a signi…cant decline in the volatility of in‡ation and output growth.