Miracle-dz/UniFAR-FTUs huggingface dataset:
Baby food production chain: Pesticide residues in fresh apples and products

During 3 years of a monitoring programme, 522 samples of fresh apples, six brands of fruit purées and various types of fruit baby food prepared from these materials were analysed. Each sample was examined for the presence of 86 GC amenable pesticide residues. The reporting limits of the procedure employed for sample analyses were in the range 0.003–0.01 mg kg−1. Pesticide residues were detected in 59.5% of the samples of fresh apples. However, maximum residue levels (European Union MRLs) were exceeded only in 1.4% of samples. The levels of residues in ‘positive’ fruit purées were substantially lower, overall with residues detected in 33% of samples. Fruit baby food represented the commodity with the lowest incidence of residues being detected in only 16% of samples. The 0.01 mg kg−1 MRL was exceeded in 9% of these products. Multiple residues were found in 25% of fresh apples and in 10% of fruit purées. None of fruit baby food samples contained more than a single residue. Organophosphorus insecticides and fungicides representing phtalimides, sulphamides and dicarboximides were the most frequently found residues. To obtain more knowledge on the fate of residues during fruit baby food production, processing experiments employing apples with incurred residues (fenitrothion, phosalone and tolylfluanid) were conducted. Washing of apples did not significantly reduce the content of pesticides. Steam boiling followed by removal of peels/stems was identified as the most efficient steps in terms of residues decrease (phosalone) or complete elimination (fenitrothion and tolylfluanid).
Approximating the crossing number of graphs embeddable in any orientable surface

The crossing number of a graph is the least number of pairwise edge crossings in a drawing of the graph in the plane. We provide an O(n log n) time constant factor approximation algorithm for the crossing number of a graph of bounded maximum degree which is "densely enough" embeddable in an arbitrary fixed orientable surface. Our approach combines some known tools with a powerful new lower bound on the crossing number of an embedded graph. This result extends previous results that gave such approximations in particular cases of projective, toroidal or apex graphs; it is a qualitative improvement over previously published algorithms that constructed low-crossing-number drawings of embeddable graphs without giving any approximation guarantees. No constant factor approximation algorithms for the crossing number problem over comparably rich classes of graphs are known to date.
Retrovirus-mediated enzymatic correction of Tay-Sachs defect in transduced and non-transduced cells.

Tay-Sachs disease is a severe neurodegenerative disorder due to mutations in the HEXA gene coding for the alpha-chain of the alpha-beta heterodimeric lysosomal enzyme beta-hexosaminidase A (HexA). Because no treatment is available for this disease, we have investigated the possibility of enzymatic correction of HexA-deficient cells by HEXA gene transfer. Human HEXA cDNA was subcloned into a retroviral plasmid generating to G.HEXA vector. The best Psi-CRIP producer clone of G.HEXA retroviral particles was isolated, and murine HexA-deficient fibroblasts derived from hexa -/- mice were transduced with the G.HEXA vector. Transduced cells overexpressed the alpha-chain, resulting in the synthesis of interspecific HexA (human alpha-chain/murine beta-chain) and in a total correction of HexA deficiency. The alpha-chain was secreted in the culture medium and taken up by HexA-deficient cells via mannose-6-phosphate receptor binding, allowing for the restoration of intracellular HexA activity in non-transduced cells.
Keyword based search over semantic data in polynomial time

In pursuing the development of Yanii, a novel keyword based search system on graph structures, in this paper we present the computational complexity study of the approach, highlighting a comparative study with actual PTIME state-of-the-art solutions. The comparative study focuses on a theoretical analysis of different frameworks to define complexity ranges, which they correspond to, in the polynomial time class. We characterize such systems in terms of general measures, which give a general description of the behavior of these frameworks according to different aspects that are more general and informative than mere benchmark tests on a few test cases. We show that Yanii holds better performance than others, confirming itself as a promising approach deserving further practical investigation and improvement.
Automatic Music Video Generation Based on Emotion-Oriented Pseudo Song Prediction and Matching

The main difficulty in automatic music video (MV) generation lies in how to match two different media (i.e., video and music). This paper proposes a novel content-based MV generation system based on emotion-oriented pseudo song prediction and matching. We use a multi-task deep neural network (MDNN) to jointly learn the relationship among music, video, and emotion from an emotion-annotated MV corpus. Given a queried video, the MDNN is applied to predict the acoustic (music) features from the visual (video) features, i.e., the pseudo song corresponding to the video. Then, the pseudo acoustic (music) features are matched with the acoustic (music) features of each music track in the music collection according to a pseudo-song-based deep similarity matching (PDSM) metric given by another deep neural network (DNN) trained on the acoustic and pseudo acoustic features of the positive (official), less-positive (artificial), and negative (artificial) MV examples. The results of objective and subjective experiments demonstrate that the proposed pseudo-song-based framework performs well and can generate appealing MVs with better viewing and listening experiences.
Evaluation of an Online Group Intervention to Improve Test-Taking Self-Efficacy and Reduce Licensure Test Anxiety

ABSTRACT We evaluated whether a synchronous online group intervention, using the Association for Social Work Boards Group Review Practice Test© items, increased students’ LMSW licensure test-taking confidence and decreased their test anxiety. A non-equivalent comparison group study was used to measure change in 59 graduate students’ confidence in test-taking and test anxiety. Almost 45% of students reported test anxiety in the clinical range at pretest. Using a repeated measures GLM, we found that students in the intervention group experienced a significant increase in confidence from pretest posttest. For overall anxiety, impairment anxiety, and worry anxiety, students in the intervention group experienced less anxiety over time, and students in the comparison group experienced more anxiety over time. Implications for programs are discussed.
Experience using the PLANET Method for Designing Inter-Organisational Relationships

The PLANET method for designing partnerships and alliances gives recommendations for the structure and management of relationships from a marketing/ competitor analysis of the potential partnering organisations. The method extends Williamson’s transaction cost theory with specific techniques for market analysis and realtionship selection with guidelines on management and implications fro IT strategy. The method is described and experience of applying the method and presenting it in tutorial format are discussed.
Contributions to a History of Prices in Norway: Monthly Price Indices, 1777-1920

This study reports the outcome of an effort to collect market price data for Norway with a view to constructing monthly price indices from the year 1777 to 1920. The material covers data on commodity prices from agriculture, shery, dairying, manufacturing and mining. Indices of the wholesale and producer price index families are constructed, using the repeat sales method for constructing the underlying price series. Separate indices for commodity exports and imports are also presented. The new wholesale price index, as well as the export and import price indices, are linked to existing price indices after 1920 and brought forward to the end of 1940. The price indices shed new light on two great wartime inflationary episodes in Norway: 1807-1817 and 1913-1920. In spite of a 61-fold increase in the price level in the first period and a 4-fold increase in the second, it is found that, after inflation had been brought under control, prices reverted to a level consistent with the purchasing power parity principle.
Succinct Inputs, Lindstr om Quantifiers, and a General Complexity Theoretic Operator Concept

We address the question of the power of several logics with Lindstr¨om quantiﬁers over ﬁnite ordered structures. We will see that in the ﬁrst-order case this nicely ﬁts into the framework of Bar-rington, Immerman, and Straubing’s examination of constant depth circuit classes. In the second-order case we get a strong relationship to succinct encodings of languages via circuits. Some of these logics can be characterized as closures of succinct encodings under appropriate reducibilities, others by certain hierarchies of circuit classes. We will see that in a special case second-order Lindstr¨om quantiﬁers can equivalently be expressed in ﬁrst-order logic, while in the general case this equivalence seems unlikely.
Genome-Wide Association Study of Schizophrenia in Japanese Population

Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p<0.01 and 473 SNPs of p<0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology.
Concept of a Rule-based Configurator for Auto-WEKA Using OpenML

Despite a large amount of research devoted to improving meta-learning techniques, providing and using background knowledge for this task remains a challenge. In this paper we propose a mechanism for automatic recommendation of suitable machine learning algorithms and their parameters. We used OpenML database and use rule-based configurator to improve Auto-WEKA tool. This paper discusses the concept of our approach and the prototype tool based on the HEARTDROID rule engine being developed.
Cascaded Subgroups Discovery with an Application to Regression

Subgroup discovery is a task from the area of Knowledge Discovery in Databases (KDD) that aims at finding interesting subgroups of a population. One problem with subgroup discovery algorithms is that many of them return a very high number of subgroups, including many redundant ones. In this paper, we present an approach to iteratively build up a set of subgroups for a numerical target attribute. The result is a additive representation of the patterns in the dataset, which can also be used as a regression model. The iterative scheme presented is similar to Transformation-Based Regression (TBR), an algorithm from the area of rule-based regression. While this is work in progress, first experiments show that the resulting sets of subgroups have a predictive accuracy that is similar to that of models generated by TBR, while the models are much more compact and arguably easier to interpret.
Turkish Radiology Dictation System

We have designed a Turkish dictation system for Radiology applications. Turkish is an agglutinative language with free word order. These characteristics of the language result in the vocabulary explosion and the complexity of the N-gram language models in speech recognition. In order to alleviate this problem, we propose a task-specific, radiology, dictation system. Using words as recognition units, we achieve 87.06 % recognition performance with a small vocabulary size in a speaker independent system. The most common reason of errors during the recognition is due to the pronunciation variations across speakers, and also due to the inaccurate modeling. In this paper, to overcome these problems, we proposed a pronunciation modeling technique in which variation is modeled at the lexicon level. The pronunciation variants are selected by learning the common mistakes of our speech recognition system. As a proof of the concept, firstly we apply this method to the isolated recognition of small vocabulary radiological words. Our preliminary results show that, 24.74 % error rate reduction can be achieved for isolated word recognition. This idea can also be generalized to continuous speech recognition problem with a moderate vocabulary size.
Parameters Identification of Nonlinear DC Motor Model Using Compound Evolution Algorithms

Abstrac—The genetic algorithms (GA) with global optimization character and the simplex method are combined and used into the application of the parameter identification. The nonlinear dynamic model of an actual DC motor including the nonlinear friction torque is established. By means of the compound evolution algorithms proposed, the detail procedure of the all parameters identification in the DC motor with actual system’s input-output data are given. The effectiveness of identification is verified by the comparison between actual system values and model’s in the different situations including the motor running in the dead zone, saturated zone and linear zone, respectively.
Growth of horizontally aligned dense carbon nanotubes from trench sidewalls

Horizontally aligned, dense carbon nanotubes (HADCNTs) in the form of CNT cantilevers/bridges were grown from selected trench sidewalls in silicon substrate by chemical vapor deposition (CVD). The as-grown CNT cantilevers/bridges are packed with multiwalled carbon nanotubes (MWCNTs) with a linear density of about 10 CNTs µm − 1. The excellent horizontal alignment of these CNTs is mainly ascribed to the van der Waals interactions within the dense CNT bundles. What is more, the Raman intensity ratio IG/ID shows a gradual increase from the CNT roots to tips, indicating a defect gradient along CNTs generated during their growth. These results will inspire further efforts to explore the fundamentals and applications of HADCNTs.
Mining Feature-Opinion in Online Customer Reviews for Opinion Summarization

Online customer reviews is considered as a significant informative resource which is useful for both potential customers and product manufacturers. In web pages, the reviews are written in natural language and are unstructured-free-texts scheme. The task of manually scanning through large amounts of review one by one is computational burden and is not practically implemented with respect to businesses and customer perspectives. Therefore it is more efficient to automatically process the various reviews and provide the necessary information in a suitable form. The high-level problem of opinion summarization addresses how to determine the sentiment, attitude or opinion that an author expressed in natural language text with respect to a certain feature. In this paper, we dedicate our work to the main subtask of opinion summarization. The task of product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the performance of opinion orientation identification. It is important to properly identify the semantic relationships between product features and opinions. We proposed an approach for mining product feature and opinion based on the consideration of syntactic information and semantic information. By applying dependency relations and ontological knowledge with probabilistic based model, the result of our experiments shows that our approach is more flexible and effective.
Average-case hardness of RIP certification

The restricted isometry property (RIP) for design matrices gives guarantees for optimal recovery in sparse linear models. It is of high interest in compressed sensing and statistical learning. This property is particularly important for computationally efficient recovery methods. As a consequence, even though it is in general NP-hard to check that RIP holds, there have been substantial efforts to find tractable proxies for it. These would allow the construction of RIP matrices and the polynomial-time verification of RIP given an arbitrary matrix. We consider the framework of average-case certifiers, that never wrongly declare that a matrix is RIP, while being often correct for random instances. While there are such functions which are tractable in a suboptimal parameter regime, we show that this is a computationally hard task in any better regime. Our results are based on a new, weaker assumption on the problem of detecting dense subgraphs.
Conditional Inactivation of Androgen Receptor Gene in the Nervous System: Effects on Male Behavioral and Neuroendocrine Responses

Testosterone (T) profoundly influences central sexual differentiation and functions. In the brain, T signals either directly through androgen receptor (AR) or indirectly through estrogen receptor (ER) following aromatization into E2 (17-β-estradiol). As T, through AR, also controls peripheral male sexual differentiation, the relative contribution of central AR in T-mediated regulation of behavioral and neuroendocrine responses still remains unclear. To address this question, we generated, by using Cre-loxP technology, mice selectively lacking AR expression in the nervous system. The mutant male urogenital tract was normally developed, and mice were able to produce offspring. Nonetheless, sexual motivation and performance as well as aggressive behaviors were affected. Only a low percentage of males displayed a complete sexual behavior and offensive attacks. The latency to show masculine behaviors was increased and copulation length prolonged. Erectile activity during mating was also altered. These alterations occurred despite increased levels of T and its metabolites, and an unaffected number of ERα-immunoreactive cells. Olfactory preference and neuronal activation, mapped by Fos immunoreactivity, following exposure to estrus female-soiled bedding were also normal. At comparable T levels, greater differences in masculine behaviors were observed between gonadectomized control and mutant males. AR invalidation in the nervous system also disrupted the somatotropic axis since mutant males exhibited growth retardation and decreased serum levels of insulin-like growth factor I. Our findings show that central AR is required in T-induced regulation of male-typical behaviors and gonadotrope and somatotropic axes. This genetic model offers a unique opportunity in the understanding of AR's role in cerebral functions of T.
China's Pure Exporter Subsidies

One third of Chinese exporters sell more than ninety percent of their production abroad. We argue that this distinctive pattern is attributable to a wide range of subsidies that provide incentives to these “pure exporters. ” We propose a heterogeneous-firm model in which firms exporting all their output receive an ad-valorem sales subsidy. Using microdata on manufacturing firms matched with custom transactions for the years 2000-2006, we measure sizable differences in productivity and paid taxes between pure exporters and domestic firms and between pure and regular exporters, in line with the predictions of our model. Embedding a pure-exporter subsidy in a two-country general equilibrium environment, we show that this instrument is worse from a welfare standpoint than a standard export subsidy, partly because it increases protection of the domestic market. A counterfactual analysis suggests that eliminating these subsidies would result in a welfare gain for China comparable to halving its trade costs.
Mean normalization of power function based cepstral coefficients for robust speech recognition in noisy environment

This paper presents the effect of mean normalization to various types of cepstral coefficients for robust speech recognition in noisy environments. Although the cepstral mean normalization (CMN) technique was originally designed to compensate channel distortion, it has also been proved that the CMN also improves recognition accuracy in additive noisy environment. However, no one has yet considered the interaction of CMN with spectral mapping functions required for extracting cepstral features. This paper investigates the impact of CMN to the speech recognition system depending on the types of spectral mapping function by mathematically analyzing the amount of spectral distortion between clean and noisy conditions. The analytic result is also confirmed by comparing the type of recognition error patterns in automatic speech recognition experiment with Aurora 2 database. Experimental results show that the performance improvement by adopting CMN becomes significant if the logarithmic function is replaced with the appropriate setting of fractional power mapping function. Especially, the deletion errors are dramatically reduced.
The Hekaton Memory-Optimized OLTP Engine

Hekaton is a new OLTP engine optimized for memory resident data and fully integrated into SQL Server; a database can contain both regular disk-based tables and in-memory tables. In-memory (a.k.a.Hekaton) tables are fully durable and accessed using standard T-SQL. A query can reference both Hekaton tables and regular tables and a transaction can update data in both types of tables. T-SQL stored procedures that reference only Hekaton tables are compiled into machine code for further performance improvements. To allow for high concurrency the engine uses latch-free data structures and optimistic, multiversion concurrency control. This paper gives an overview of the design of the Hekaton engine and reports some initial results.
Pathogenesis of Renal Failure in Multiple Myeloma: Any Role of Contrast Media?

The spectrum of kidney disease-associated monoclonal immunoglobulin and plasma cell malignancies is remarkably broad and encompasses nearly all nephropathologic entities. Multiple myeloma with kidney impairment at presentation is a medical emergency since the recovery of kidney function is associated with survival benefits. In most cases, kidney impairment may be the first clinical manifestation of malignant plasma cell dyscrasias like multiple myeloma and light chain amyloidosis. Multiple myeloma per se cannot be considered a main risk factor for developing acute kidney injury following intravascular administration of iodinated contrast media. The risk is increased by comorbidities such as chronic kidney disease, diabetes, hypercalcemia, dehydration, and use of nephrotoxic drugs. Before the administration of contrast media, the current recommended laboratory tests for assessing kidney function are serum creatinine measurement and the estimation of glomerular filtration rate by using the CKD-EPI equation. The assessment of Bence Jones proteinuria is unnecessary for evaluating the risk of kidney failure in patients with multiple myeloma, since this test cannot be considered a surrogate biomarker of kidney function.