Miracle-dz/UniFAR-FTUs huggingface dataset:
EMNLP 2011 DIALECTS2011 Proceedings of the First Workshop on Algorithms and Resources for Modelling of Dialects and Language Varieties

Recent research on multilingual statistical machine translation (SMT) focuses on the usage of pivot languagesin order to overcome resource limitations for certain language pairs. This paper proposes a new method to translate a dialect language into a foreign language by integrating transliteration approaches based on Bayesian co-segmentation (BCS) models with pivot-based SMT approaches. The advantages of the proposed method with respect to standard SMT approaches are three fold: (1) it uses a standard language as the pivot language and acquires knowledge about the relation between dialects and the standard language automatically, (2) it reduces the translation task complexity by using monotone decoding techniques, (3) it reduces the number of features in the log-linear model that have to be estimated from bilingual data. Experimental results translating four Japanese dialects (Kumamoto, Kyoto, Okinawa, Osaka) into four Indo-European languages (English, German, Russian, Hindi) and two Asian languages (Chinese, Korean) revealed that the proposed method improves the translation quality of dialect translation tasks and outperforms standard pivot translation approaches concatenating SMT engines for the majority of the investigated language pairs.
Spectral Modeling of SNe Ia Near Maximum Light: Probing the Characteristics of Hydrodynamical Models

We have performed detailed non-local thermodynamic equilibrium (NLTE) spectral synthesis modeling of two types of one-dimensional hydrodynamical models: the very highly parameterized deflagration model W7, and two delayed-detonation models. We find that, overall, both models do about equally well at fitting well-observed SNe Ia near maximum light. However, the Si II λ6150 feature of W7 is systematically too fast, whereas for the delayed-detonation models it is also somewhat too fast but significantly better than that of W7. We find that a parameterized mixed model does the best job of reproducing the Si II λ6150 line near maximum light, and we study the differences in the models that lead to better fits to normal SNe Ia. We discuss what is required of a hydrodynamical model to fit the spectra of observed SNe Ia near maximum light.
Biophysical characterization of G protein ectodomain of group B human respiratory syncytial virus from E. coli

ABSTRACT Human respiratory syncytial virus (hRSV) is an important pathogen of acute respiratory tract infection. The G protein of hRSV is a transmembrane glycoprotein that is a neutralizing antigen and is thus a vaccine candidate. In this study, synthetic codon optimized ectodomain G protein [G(ΔTM)] of BA genotype of group B hRSV was cloned, expressed, and characterized using biophysical techniques. The molar absorption coefficient and mean residue ellipticity at 222 nm ([θ]222) of G (ΔTM) was found to be 7950 M−1 cm−1 and −19701.7 deg cm2 dmol-1 respectively. It was concluded that G(ΔTM) mainly consist of α-helix (74.9%) with some amount of β-sheet (4%). The protein was stable up to 85°C without any transition curve. However, heat-induced denaturation of G(ΔTM) resulted in total loss of β-sheet whereas not much change was observed in the α-helix part of the secondary structure. It was concluded that G(ΔTM) is an α-helical protein and it is highly stable at high temperature, but could be easily denatured using high concentrations of GdmCl/urea or acidic condition. This is the first investigation of cloning, expression, and characterization of G(ΔTM) of BA viruses from India. Structural characterization of G protein will assist in drug designing and vaccine development for hRSV.
A self-constructing type-2 fuzzy neural network for impulse noise removal in digital images

We propose a self-constructing type-2 fuzzy neural network for impulse noise removal in digital images. The architecture and corresponding parameters of the network are initialized by a SVD-based self-constructing rule generation algorithm, and the initialized parameters are optimized by a hybrid learning algorithm. The trained network can be employed to detect the noisy pixels in the images corrupted by impulse noise. After that, pixels identified as noisy are processed by a median filter whereas the other pixels are retained. Compared with the other approach, experimental results have shown that our approach possesses a better detection capability of impulse noise, resulting in the more effective filtering of impulse noise.
Identification of the Final Two Genes Functioning in Methanofuran Biosynthesis in Methanocaldococcus jannaschii

ABSTRACT All methanofuran structural variants contain a basic core structure of 4-[N-(γ-l-glutamyl)-p-(β-aminoethyl)phenoxymethyl]-(aminomethyl)furan (APMF-Glu) but have different side chains depending on the source organism. Recently, we identified four genes (MfnA, MfnB, MfnC, and MfnD) that are responsible for the biosynthesis of the methanofuran precursor γ-glutamyltyramine and 5-(aminomethyl)-3-furanmethanol-phosphate (F1-P) from tyrosine, glutamate, glyceraldehyde-3-P, and alanine in Methanocaldococcus jannaschii. How γ-glutamyltyramine and F1-P couple together to form the core structure of methanofuran was previously unknown. Here, we report the identification of two enzymes encoded by the genes mj0458 and mj0840 that catalyze the formation of F1-PP from ATP and F1-P and the condensation of F1-PP with γ-glutamyltyramine, respectively, to form APMF-Glu. We have annotated these enzymes as MfnE and MfnF, respectively, representing the fifth and sixth enzymes in the methanofuran biosynthetic pathway to be identified. Although MfnE was previously reported as an archaeal adenylate kinase, our present results show that MfnE is a promiscuous enzyme and that its possible physiological role is to produce F1-PP. Unlike other enzymes catalyzing coupling reactions involving pyrophosphate as the leaving group, MfnF exhibits a distinctive α/β two-layer sandwich structure. By comparing MfnF with thiamine synthase and dihydropteroate synthase, a substitution nucleophilic unimolecular (SN-1) reaction mechanism is proposed for MfnF. With the identification of MfnE and MfnF, the biosynthetic pathway for the methanofuran core structure APMF-Glu is complete. IMPORTANCE This work describes the identification of the final two enzymes responsible for catalyzing the biosynthesis of the core structure of methanofuran. The gene products of mj0458 and mj0840 catalyze the formation of F1-PP and the coupling of F1-PP with γ-glutamyltyramine, respectively, to form APMF-Glu. Although the chemistry of such a coupling reaction is widespread in biochemistry, we provide here the first evidence that such a mechanism is used in methanofuran biosynthesis. MfnF belongs to the hydantoinase A family (PF01968) and exhibits a unique α/β two-layer sandwich structure that is different from the enzymes catalyzing similar reactions. Our results show that MfnF catalyzes the formation of an ether bond during methanofuran biosynthesis. Therefore, this work further expands the functionality of this enzyme family.
Sugar-Sweetened Beverage Consumption and Risk of General and Abdominal Obesity in Iranian Adults: Tehran Lipid and Glucose Study

Background: General and abdominal obesity are major global health problems. This cross-sectional study was conducted to evaluate the association between consumption of sugar-sweetened beverages (SSBs) and body mass index and waist circumference status in 5852 Iranian adults within the framework of the Tehran Lipid and Glucose Study (TLGS). Methods: Intakes of SSBs including carbonated drinks and synthetic fruit juices were measured using a validated food frequency questionnaire. The association between body mass index, waist circumference and body adiposity index in each quartile category of SSB consumption were determined using the multivariable linear regression models. The odds ratio (OR) of general and abdominal obesity in each quartile of SSB consumption was also determined using the multivariable logistic regression models. Results: Mean dietary intake of SSBs was 48.9 g/d or 0.25 servings/d. After adjustment for all potential confounding variables, significant associations were observed between SSB consumption and BMI (β: 0.49, 95% CI: 0.13–0.86), and waist circumference (β: 1.28, 95% CI: 0.40–2.16) in the fourth quartile. There was no significant association between SSB consumption and body adiposity index. Participants who consumed > 57.1 g/d of SSBs had 22% higher risk of general obesity (OR: 1.22, 95% CI: 1.00–1.48) and 35% higher risk of abdominal obesity (OR: 1.35, 95% CI: 1.12–1.61), compared with those in the lowest quartile of SSB consumption. Conclusion: Higher intakes of SSBs were associated with the higher risk of general and abdominal obesity in adults suggesting that limiting the consumption of SSBs may be a practical approach to prevent and manage obesity.
Classi(cid:142) cation Trees With Bivariate Linear Discriminant Node Models

This article introduces a classi(cid:142)cation tree algorithm that can simultaneously reduce tree size, improve class prediction,and enhance data visualization.We accomplish this by (cid:142) tting a bivariate linear discriminant model to the data in each node. Standard algorithms can produce fairly large tree structures because they employ a very simple node model, wherein the entire partition associated with a node is assigned to one class. We reduce the size of our trees by letting the discriminant models share part of the data complexity. Being themselves classi(cid:142)ers, the discriminant models can also help to improve prediction accuracy. Finally, because the discriminant models use only two predictor variables at a time, their effects are easily visualized by means of two-dimensionalplots. Our algorithm does not simply (cid:142) t discriminantmodels to the terminal nodes of a pruned tree, as this does not reduce the size of the tree. Instead,discriminantmodelingis carried out in all phases of tree growth and the misclassi(cid:142)cation costs of the node models are explicitly used to prune the tree. Our algorithm is also distinct from the “linear combinationsplit” algorithms that partitionthe data spacewith arbitrarilyorientedhyperplanes.We use axis-orthogonalsplits to preservethe interpretabilityof the tree structures.An extensiveempirical study with real datasets shows that, in general, our algorithm has better predictionpower than many other tree or nontree algorithms.
Boosting-Based System Combination for Machine Translation

In this paper, we present a simple and effective method to address the issue of how to generate diversified translation systems from a single Statistical Machine Translation (SMT) engine for system combination. Our method is based on the framework of boosting. First, a sequence of weak translation systems is generated from a baseline system in an iterative manner. Then, a strong translation system is built from the ensemble of these weak translation systems. To adapt boosting to SMT system combination, several key components of the original boosting algorithms are redesigned in this work. We evaluate our method on Chinese-to-English Machine Translation (MT) tasks in three baseline systems, including a phrase-based system, a hierarchical phrase-based system and a syntax-based system. The experimental results on three NIST evaluation test sets show that our method leads to significant improvements in translation accuracy over the baseline systems.
An Indoor Context Aware Dynamic Positioning System for Personalized Shopping Assistance ( CAPSA )

Context aware, personalized service can give targeted and timely information in a seamless way for the users equipped with mobile devices. In this paper, we design and implement a personalized location based shopping assistance service intended to run over Wi-Fi connections between Access Points installed in shopping mall with the help of hand-held mobile devices. We propose a method that combines triangulation and fingerprinting to locate a handheld mobile device to provide a unique shopping assistant service that personalizes the attention provided to a customer based on individual needs. CAPSA (Context-Aware Personal Shopping Assistant) can be any small hand held, Wi-Fi enabled wireless communication device like a smartphone, a laptop or a PDA. CAPSA communicates to the centralized server’s customer and mall database and locates the customer inside the shopping mall. Based on this customer’s position, the shortest path for traversing inside the mall (to shop all the products in the shop list) is estimated and given back to the user with the route map to find all their shopping list items in an efficient way. We conduct experiments to discuss the error rates of customer’s location detection method in comparison with existing methods and it is shown that the proposed method is better than the existing methods in terms of shopping time, shopping distance and accuracy. Index Terms — Context aware computing, Wi-Fi, CAPSA, triangulation, fingerprinting, shortest path.
An Implementation of the Solaris Doors API for Linux

Linux is a freely available UNIX-like operating system for many varied hardware platforms. As of this writing, Linux is supported on the DEC Alpha, Intel x86, Sun SPARC and UltraSPARC, Motorola 68000 and PowerPC, Advanced RISC Machines ARM, and SGI MIPS processors. The list of supported hardware continues to grow at a rapid pace, mostly due to the strong programming support garnered by the open software development model and increased media and commercial support. Linux is used in a wide variety of applications, from the desktop to distributed-memory [8] and cluster-based [3, 4] supercomputing. The growing popularity of the Linux operating system, combined with the ability to freely publish source code modifications to the operating system, motivated its use in this project.
Towards tool support for analyzing legacy systems in technical domains

Software in technical domains contains extensive and complex computations in a highly-optimized and unstructured way. Such software systems developed and maintained over years are prone to become legacy code based on old technology and without accurate documentation. We have conducted several industrial projects to reengineer and re-document legacy systems in electrical engineering and steel making domains by means of self-provided techniques and tools. Based on this experience, we derived requirements for a toolkit to analyze legacy code in technical domains and developed a corresponding toolkit including feature location and static analysis on a multi-language level. We have applied our approach and toolkit for software systems implemented in the C++, Fortran, and PL/SQL programming languages and illustrate main benefits of our approach from these experiences.
Efficient Scalar Multiplication Algorithms Secure against Power Analysis Attacks for Koblitz Curve Cryptosystems

Recently, many power analysis attacks have been proposed. Since the attacks are powerful, it is very important to implement cryptosystems securely against the attacks. We propose countermeasures against power analysis attacks for elliptic curve cryptosystems based on Koblitz curves (KCs), which are a special class of elliptic curves. That is, we make our countermeasures be secure against SPA, DPA, and new DPA attacks, specially RPA, ZPA, using a random point at each execution of elliptic curve scalar multiplication. And since our countermeasures are designed to use the Frobenius map of KC, those are very fast. Also, we reduce the number of elliptic curve addition up to about 50% using pre-computed tables.
An exploratory study on reuse at google

Software reuse is a challenging and multifaceted topic. Significant research effort has been spent to address technical and organizational aspects. However, adoption of proposed practices and novel approaches often proceeds slowly. Additionally, little is known on how reuse is currently effected in practice and which solutions have proven useful. This paper aims to shed light on the matter by studying the current practice of reuse at Google. We conduct an exploratory study with a total of 49 participants of which 39 answered our online questionnaire and 10 participated in our 1h interviews. We assess reuse practices, success factors and challenges and collect ideas for improvement. We distill our findings to provide practitioners with examples of scalable reuse practices and detail on prerequisites required to implement/tailor a similar reuse approach. Furthermore, we point out open issues to support researchers and practitioners alike to align their efforts for developing solutions.
Melatonin Impact on In Vitro Development of Mouse Preantral Follicles and Oocyte Maturation

Introduction: In vitro environments expose developing oocytes to excess reactive oxygen species (ROS) which are not normally produced in vivo. Melatonin acts as an indirect antioxidant and is a powerful direct free radical scavenger and direct responses to melatonin in the gonads. This study aims to investigate the influence of different doses of melatonin on follicle development and oogenesis of in vitro cultured mouse ovarian follicles. Materials and Methods: Preantral follicles with diameters of 150–175 µm were mechanically isolated from 18–21 day-old NMRI mouse ovaries. Follicles were individually cultured in micro droplets of α-minimal essential medium (α-MEM) supplemented with 5% FBS, 100 mIU/ml rhFSH, 1% ITS, 100 IU/ml penicillin and 100 μg/ml streptomycin in conjunction with varying doses of melatonin (0, 1, 10, 100 nM and 100, 500 pM) for six days. On day six, in vitro ovulation was induced by the addition of hCG/rEGF to the culture medium and after 16 h the maturation state of the oocytes was assessed. Results: On day six of culture there was a significant (P<0.05) decrease in the number of surviving follicles in the groups that received 10, 100 nM and 500 pM melatonin compared to the other groups. After induction of in vitro ovulation, follicles in groups that received 1, 10, and 100 nM melatonin had higher ovulation rates (P<0.05) compared with the other groups. Oocyte maturation capacity was adversely influenced by five concentrations of melatonin and GV arrest was significantly higher compared to the control group (P< 0.01). Conclusions: Our data indicates that a dose of 100 pM melatonin has no toxic effects on follicular development and can be used to reduce oxidative stress in follicle culture systems.
A Novel Algorithm for Speeding up Keypoint Detection and Matching

This work proposes a novel keypoint detector called QSIF (Quality and Spatial based Invariant Feature Detector). The primary contributions include: (1) a multilevel box filter is used to build the image scales efficiently and precisely, (2) by examining pixels in quality and spatial space simultaneously, QSIF can directly locate the keypoints without scale space extrema detection in the entire image spatial space, (3) QSIF can precisely control the number of output keypoints while maintaining almost the same repeatability of keypoint detection. This characteristic is essential in many real-time application fields. Extensive experimental results with images under scale, rotation, viewpoint and illumination changes demonstrate that the proposed QSIF has a stable and satisfied repeatability, and it can greatly speed up the keypoint detect and matching.
A joint analysis to identify loci underlying variation in nematode resistance in three European sheep populations

Gastrointestinal nematode infections are one of the main health/economic issues in sheep industries, worldwide. Indicator traits for resistance such as faecal egg count (FEC) are commonly used in genomic studies; however, published results are inconsistent among breeds. Meta (or joint)-analysis is a tool for aggregating information from multiple independent studies. The aim of this study was to identify loci underlying variation in FEC, as an indicator of nematode resistance, in a joint analysis using data from three populations (Scottish Blackface, Sarda × Lacaune and Martinik Black-Belly × Romane), genotyped with the ovine 50k SNP chip. The trait analysed was the average animal effect for Strongyles and Nematodirus FEC data. Analyses were performed with regional heritability mapping (RHM), fitting polygenic effects with either the whole genomic relationship matrix or matrices excluding the chromosome being interrogated. Across-population genomic covariances were set to zero. After quality control, 4123 animals and 38 991 SNPs were available for the analysis. RHM identified genome-wide significant regions on OAR4, 12, 14, 19 and 20, with the latter being the most significant. The OAR20 region is close to the major histocompatibility complex, which has often been proposed as a functional candidate for nematode resistance. This region was significant only in the Sarda × Lacaune population. Several other regions, on OAR1, 3, 4, 5, 7, 12, 19, 20 and 24, were significant at the suggestive level.
Efficient, Verifiable Binary Sandboxing for a CISC Architecture

Executing untrusted code while preserving security requires enforcement of memory and control-flow safety policies: untrusted code must be prevented from modifying memory or executing code except as explicitly allowed. Software-based fault isolation (SFI) or “sandboxing” enforces those policies by rewriting the untrusted code at the level of individual instructions. However, the original sandboxing technique of Wahbe et al. is applicable only to RISC architectures, and other previous work is either insecure, or has been not described in enough detail to give confidence in its security properties. We present a novel technique that allows sandboxing to be easily applied to a CISC architecture like the IA-32. The technique can be verified to have been applied at load time, so that neither the rewriting tool nor the compiler needs to be trusted. We describe a prototype implementation which provides a robust security guarantee, is scalable to programs of any size, and has low runtime overheads. Further, we give a machine-checked proof that any program approved by the verification algorithm is guaranteed to respect the desired safety property.
SheetDiff: A Tool for Identifying Changes in Spreadsheets

Most spreadsheets, like other software, change over time. A frequently occurring scenario is the repeated reuse and adaptation of spreadsheets from one project to another. If several versions of one spreadsheet for grading/ budgeting/etc. have accumulated, it is often not obvious which one to choose for the next project. In situations like these, an understanding of how two versions of a spreadsheet differ is crucial to make an informed choice. Other scenarios are the reconciliation of two spreadsheets created by different users, generalizing different spreadsheets into a common template, or simply understanding and documenting the evolution of a spreadsheet over time. In this paper we present a method for identifying the changes between two spreadsheets with the explicit goal of presenting them to users in a concise form. We have implemented a prototype system, called SheetDiff, and tested the approach on several different spreadsheet pairs. As our evaluations will show, this system works reliably in practice. Moreover, we have compared SheetDiff to similar systems that are commercially available. An important difference is that while all these other tools distribute the change representation over two spreadsheets, our system displays all changes in the context of one spreadsheet, which results in a more compact representation.