Miracle-dz/UniFAR-FTUs huggingface dataset:
Organosolv Lignin-Based Wood Adhesive. Influence of the Lignin Extraction Conditions on the Adhesive Performance

Ethanol organosolv alfa grass lignins were extracted in the presence of sulfuric acid or Lewis acids (Sc(OTf)3, FeCl3) as catalysts and subjected to a comprehensive structural characterization by solid state 13C NMR, GPC, MALDI-TOF, and ASAP-MS/MS. The impact of the severity of the treatment and of the nature of the acid catalyst on the recovered lignin structure was investigated. The lignins isolated at high severity were highly recondensed and partly composed of regular structures composed of furan-like rings. The alfa (Stipa tenacissima L.) organosolv lignins were used for the preparation of formaldehyde-free adhesives which were characterized by TMA and used for the preparation of particleboard without any addition of synthetic resin. It has been demonstrated for the first time that: (1) the addition of 10% to 30% of organosolv alfa lignin in a tannin-based adhesive improved the adhesive performance; and (2) the conditions of the lignin extraction strongly impact the lignin-based adhesive performances. The highly recondensed lignin extracted with sulfuric acid as a catalyst allowed the production of resins with improved performances. Formulations composed of 50% glyoxalated alfa lignin and 50% of Aleppo Pine tannins yielded good internal bond strength results for the panels (IB = 0.45 MPa) and satisfied relevant international standard specifications for interior-grade panels.
Document Routing as Statistical Classification

In this paper, we compare learning techniques based on statistical classification to traAitional methods of relevance feedback for the document routing problem. We consider three classification techniques which have decision rules that are derived via explicit error minimization: linear discriminaat analysis, logistic regression, and neural networks. We demonstrate that the classifiers perform 10-15% better than relevance feedback via Rocchio expansion for the TREC-2 and TREC-3 routing tasks.
Supervised and Semi-Supervised Multi-View Canonical Correlation Analysis Ensemble for Heterogeneous Domain Adaptation in Remote Sensing Image Classification

In this paper, we present the supervised multi-view canonical correlation analysis ensemble (SMVCCAE) and its semi-supervised version (SSMVCCAE), which are novel techniques designed to address heterogeneous domain adaptation problems, i.e., situations in which the data to be processed and recognized are collected from different heterogeneous domains. Specifically, the multi-view canonical correlation analysis scheme is utilized to extract multiple correlation subspaces that are useful for joint representations for data association across domains. This scheme makes homogeneous domain adaption algorithms suitable for heterogeneous domain adaptation problems. Additionally, inspired by fusion methods such as Ensemble Learning (EL), this work proposes a weighted voting scheme based on canonical correlation coefficients to combine classification results in multiple correlation subspaces. Finally, the semi-supervised MVCCAE extends the original procedure by incorporating multiple speed-up spectral regression kernel discriminant analysis (SRKDA). To validate the performances of the proposed supervised procedure, a single-view canonical analysis (SVCCA) with the same base classifier (Random Forests) is used. Similarly, to evaluate the performance of the semi-supervised approach, a comparison is made with other techniques such as Logistic label propagation (LLP) and the Laplacian support vector machine (LapSVM). All of the approaches are tested on two real hyperspectral images, which are considered the target domain, with a classifier trained from synthetic low-dimensional multispectral images, which are considered the original source domain. The experimental results confirm that multi-view canonical correlation can overcome the limitations of SVCCA. Both of the proposed procedures outperform the ones used in the comparison with respect to not only the classification accuracy but also the computational efficiency. Moreover, this research shows that canonical correlation weighted voting (CCWV) is a valid option with respect to other ensemble schemes and that because of their ability to balance diversity and accuracy, canonical views extracted using partially joint random view generation are more effective than those obtained by exploiting disjoint random view generation.
Semisoft Generalized Total Variation Minimization for Image Reconstruction in Computed Tomography

The generalized <inline-formula> <tex-math notation="LaTeX">$l_{1}$ </tex-math></inline-formula> greedy algorithm was recently proposed and shown to outperform the standard reweighted <inline-formula> <tex-math notation="LaTeX">$l_{1}$ </tex-math></inline-formula>-minimization and <inline-formula> <tex-math notation="LaTeX">$l_{1}$ </tex-math></inline-formula>-greedy algorithms for image reconstruction in computed tomography (CT). Herein, this algorithm is extended as a semisoft generalized <inline-formula> <tex-math notation="LaTeX">$l_{1}$ </tex-math></inline-formula> greedy algorithm by adapting the wavelet technique of semisoft thresholding. The extended algorithm can also be applied to image reconstruction by incorporating it into the BCPCS framework, resulting in a semisoft generalized total variation minimization (SSGTV) algorithm for CT. Numerical tests indicate that the proposed SSGTV algorithm improves the image reconstruction for CT.
Game of Registrars: An Empirical Analysis of Post-Expiration Domain Name Takeovers

Every day, hundreds of thousands of Internet domain names are abandoned by their owners and become available for re-registration. Yet, there appears to be enough residual value and demand from domain speculators to give rise to a highly competitive ecosystem of drop-catch services that race to be the first to re-register potentially desirable domain names in the very instant the old registration is deleted. To pre-empt the competitive (and uncertain) race to re-registration, some registrars sell their own customers’ expired domains pre-release, that is, even before the names are returned to general availability. These practices are not without controversy, and can have serious security consequences. In this paper, we present an empirical analysis of these two kinds of postexpiration domain ownership changes.We find that 10 % of all com domains are re-registered on the same day as their old registration is deleted. In the case of org, over 50 % of re-registrations on the deletion day occur during only 30 s. Furthermore, drop-catch services control over 75 % of accredited domain registrars and cause more than 80 % of domain creation attempts, but represent at most 9.5 % of successful domain creations. These findings highlight a significant demand for expired domains, and hint at highly competitive re-registrations. Our work sheds light on various questionable practices in an opaque ecosystem. The implications go beyond the annoyance of websites turned into “Internet graffiti” [26], as domain ownership changes have the potential to circumvent established security mechanisms.
Leading Associations

Leaders make vital contributions to the survival and success of civic associations, but they vary widely in levels of commitment to those groups. Why are some leaders more committed than others? We draw from scholarship on civic participation, volunteering, social movements, and team management to develop an original explanation. Although theory suggests individual and organizational factors may explain differences, most prior empirical studies examine only individual-level hypotheses. We use data collected from 1,616 Sierra Club volunteer leaders and the 368 chapters and groups they led to conduct multilevel analyses of the determinants of behavioral commitment among leaders. At the individual level, we find that leaders with more applicable skills, available time, and aligned motivations are more committed to the organization. At the organizational level, we find that leaders whose organizations are more complex, and who are on teams that operate more interdependently, share work more equally, and devote smaller shares of time to meetings, are more committed. These findings have implications for scholars of leadership and commitment and for organizations seeking more committed leaders.
Incorporating variability in user behavior into systems based evaluation

Click logs present a wealth of evidence about how users interact with a search system. This evidence has been used for many things: learning rankings, personalizing, evaluating effectiveness, and more. But it is almost always distilled into point estimates of feature or parameter values, ignoring what may be the most salient feature of users---their variability. No two users interact with a system in exactly the same way, and even a single user may interact with results for the same query differently depending on information need, mood, time of day, and a host of other factors. We present a Bayesian approach to using logs to compute posterior distributions for probabilistic models of user interactions. Since they are distributions rather than point estimates, they naturally capture variability in the population. We show how to cluster posterior distributions to discover patterns of user interactions in logs, and discuss how to use the clusters to evaluate search engines according to a user model. Because the approach is Bayesian, our methods can be applied to very large logs (such as those possessed by Web search engines) as well as very small (such as those found in almost any other setting).
Identification of a Site in Sar1 Involved in the Interaction with the Cytoplasmic Tail of Glycolipid Glycosyltransferases*

Glycolipid glycosyltransferases (GGT) are transported from the endoplasmic reticulum (ER) to the Golgi, their site of residence, via COPII vesicles. An interaction of a (R/K)X(R/K) motif at their cytoplasmic tail (CT) with Sar1 is critical for the selective concentration in the transport vesicles. In this work using computational docking, we identify three putative binding pockets in Sar1 (sites A, B, and C) involved in the interaction with the (R/K)X(R/K) motif. Sar1 mutants with alanine replacement of amino acids in site A were tested in vitro and in cells. In vitro, mutant versions showed a reduced ability to bind immobilized peptides with the CT sequence of GalT2. In cells, Sar1 mutants (Sar1D198A) specifically affect the exiting of GGT from the ER, resulting in an ER/Golgi concentration ratio favoring the ER. Neither the typical Golgi localization of GM130 nor the exiting and transport of the G protein of the vesicular stomatitis virus were affected. The protein kinase inhibitor H89 produced accumulation of Sec23, Sar1, and GalT2 at the ER exit sites; Sar1D189A also accumulated at these sites, but in this case GalT2 remained disperse along ER membranes. The results indicate that amino acids in site A of Sar1 are involved in the interaction with the CT of GGT for concentration at ER exiting sites.
Novel BRCA1 and BRCA2 pathogenic mutations in Slovene hereditary breast and ovarian cancer families

The estimated proportion of hereditary breast and ovarian cancers among all breast and ovarian cancer cases is 5–10%. According to the literature, inherited mutations in the BRCA1 and BRCA2 tumour-suppressor genes, account for the majority of hereditary breast and ovarian cancer cases. The aim of this report is to present novel mutations that have not yet been described in the literature and pathogenic BRCA1 and BRCA2 mutations which have been detected in HBOC families for the first time in the last three years. In the period between January 2009 and December 2011, 559 individuals from 379 families affected with breast and/or ovarian cancer were screened for mutations in the BRCA1 and BRCA2 genes. Three novel mutations were detected: one in BRCA1 - c.1193C>A (p.Ser398*) and two in BRCA2 - c.5101C>T (p.Gln1701*) and c. 5433_5436delGGAA (p.Glu1811Aspfs*3). These novel mutations are located in the exons 11 of BRCA1 or BRCA2 and encode truncated proteins. Two of them are nonsense while one is a frameshift mutation. Also, 11 previously known pathogenic mutations were detected for the first time in the HBOC families studied here (three in BRCA1 and eight in BRCA2). All, except one cause premature formation of stop codons leading to truncation of the respective BRCA1 or BRCA2 proteins.
Sonification of EEG signals

ii iii To my mother iv v Acknowledgements I wish to thank my supervisors Sergi and Sebastian for their generous assistance and for giving me the opportunity to pursue my interests in scientific research. I'm also grateful to Mathieu Bosi from the MTG, for the basic tips for Pure Data. An infinite gratitude goes to all my family, for encouraging me despite the many miles that kept us separated for so long. This thesis as all the other goals that I achieved in my life, I owe to them and it is also the result of their support. I wish all of you a lot of love. A big thanks goes to Gianmaria Troiano. Thanks for the passions that we share, for the long nights of study and for the laughs. vi vii Abstract This master project aims to study sonification techniques for the explicit display of Electroencephalography signals (EEG). In particular, this research focus on studying the correlation between EEG signal characteristics and the information perceived trough sounds. A system for real-time presentation of sound synthesis based on EEG measures was developed and experiments on sound perception and recognition were carried on. The primary goal of the study was to understand what sonification strategies led to a better display and subjective recognition of EEG signal dynamics. While the specific goals of the study were firstly to investigate the application of different sound mappings to display different EEG signal features, next to develop a sonification system that allowed auditory display of real-time and off-line EEG data and finally to assess the success of different EEG sonification techniques in providing the subjective experience of alpha band instantaneous coherence. Therefore, different sonification scenarios were created and submitted to subjects participating to experiments, during which their subjective assessments were acquired in real-time by a physical inputs (midi controller). Then data were analyzed by means of correlation analysis in order to evaluate how subjects react to the induced auditory stimuli: the goal of the analysis was to find out how EEG features (coherence level) could be perceived among different sonification strategies. The correlation analysis has shown that the Hybrid sonification obtained the better results. It has achieved an average correlation of r=0.7441 with p<0.005 and a maximum average value of r=0.8995.
Bluetongue Virus VP6 Acts Early in the Replication Cycle and Can Form the Basis of Chimeric Virus Formation

ABSTRACT A minor core protein, VP6, of bluetongue virus (BTV) possesses nucleoside triphosphatase, RNA binding, and helicase activities. Although the enzymatic functions of VP6 have been documented in vitro using purified protein, its definitive role in BTV replication remains unclear. In this study, using a recently developed T7 transcript-based reverse genetics system for BTV, we examined the importance of VP6 in virus replication. We show that VP6 is active early in replication, consistent with a role as part of the transcriptase or packaging complex, and that its action can be provided in trans by a newly developed complementary cell line. Furthermore, the genomic segment encoding VP6 was mutated to reveal the cis-acting sequences required for replication or packaging, which subsequently enabled the construction of a chimeric BTV expressing enhanced green fluorescent protein. These data confirm that one of the 10 genome segments of BTV can be replaced with a chimeric RNA containing the essential packaging and replication signals of BTV and the coding sequence of a foreign gene.
An Examination of Cross-Cultural Similarities and Differences from Social Media Data with respect to Language Use

We present a methodology for analyzing cross-cultural similarities and differences using language as a medium, love as domain, social media as a data source and 'Terms' and 'Topics' as cultural features. We discuss the techniques necessary for the creation of the social data corpus from which emotion terms have been extracted using NLP techniques. Topics of love discussion were then extracted from the corpus by means of Latent Dirichlet Allocation (LDA). Finally, on the basis of these features, a cross-cultural comparison was carried out. For the purpose of cross-cultural analysis, the experimental focus was on comparing data from a culture from the East (India) with a culture from the West (United States of America). Similarities and differences between these cultures have been analyzed with respect to the usage of emotions, their intensities and the topics used during love discussion in social media.
Induction of CD8 T Cells against a Novel Epitope in TB10.4: Correlation with Mycobacterial Virulence and the Presence of a Functional Region of Difference-11

Although infection with Mycobacterium tuberculosis (M.tb) induces a robust CD8 T cell response, the role of CD8 T cells in the defense against M.tb, and the mechanisms behind the induction of CD8 T cells, is still not clear. TB10.4 is a recently described Ag that is expressed by both bacillus Calmette-Guérin (BCG) and M.tb. In the present study, we describe a novel CD8 T cell epitope in TB10.4, TB10.43-11. We show that TB10.43-11-specific CD8 T cells are induced at the onset of infection and are present throughout the infection in high numbers. TB10.43-11 CD8 T cells were recruited to the site of infection and expressed CD44, TNF-α, and IFN-γ. In addition, TB10.43-11 CD8 T cells showed an up-regulation of FasL and LAMP-1/2 (CD107A/B), which correlated with a strong in vivo cytolytic activity. The induction of TB10.43-11-specific CD8 T cells was less pronounced following infection with BCG compared to infection with M.tb. By using a rBCG expressing the genetic region of difference-1 (RD1), we show that the presence of a functional RD1 region increases the induction of TB10.43-11-specific CD8 T cells as well as the bacterial virulence. Finally, as an M.tb variant lacking the genetic region RD1 also induced a significant amount of TB10.43-11-specific CD8 T cells, and exhibited increased virulence compared with BCG, our data suggest that virulence in itself is also involved in generating a robust CD8 T cell response against mycobacterial epitopes, such as TB10.43-11.
Extending Prolog with Constraint Arithmetic on Real Intervals

Prolog can be extended by a system of constraints on closed intervals to perform declarative relational arithmetic. Imposing constraints on an interval can narrow its range and propagate the narrowing to other intervals related to it by constraint equations or inequalities. Relational interval arithmetic can be used to contain oating point errors and, when combined with Prolog backtracking, to obtain numeric solutions to linear and non-linear rational constraint satisfaction problems over the reals (e.g. n-degree polynomial equations). This technique di ers from other constraint logic programming (CLP) systems like CLP(<) or Prolog-III in that it does not do any symbolic processing.
Relationship of body fat distribution by waist circumference, dual-energy X-ray absorptiometry and ultrasonography to insulin resistance by homeostasis model assessment and lipid profile in obese and non-obese postmenopausal women

Objective. To correlate body fat distribution evaluated by waist circumference, dual-energy X-ray absorptiometry and ultrasonography to insulin resistance and lipid profile in obese and non-obese postmenopausal women. Methods. We studied 40 obese and 47 non-obese postmenopausal women, assessing obesity by measuring waist circumference and fat tissue using dual-energy X-ray absorptiometry and ultrasonography, and examining their correlation with metabolic parameters: insulin resistance as determined by the homeostasis model assessment technique (HOMA-IR) and lipid profile including triglycerides (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), very-low-density lipoprotein, lipoprotein(a) (Lp(a)) and apoplipoprotein A-I (Apo A-I). Results. There was no difference in lipid profile between the two groups. Insulin resistance was the metabolic disturbance of highest prevalence in the obese group, evaluated by HOMA-IR (obese: 3.38 ± 2.2; non-obese: 1.20 ± 0.7; p < 0.001). Obesity was not a confounding factor in linear regression analyses among HOMA-IR, HDL-C, TG, Lp(a), Apo A-I and the methods used to measure body fat distribution. Waist circumference was the method that best explained HOMA-IR (R2 = 34.9%, p < 0.001) and TG concentration (R2 = 10.9%, p = 0.002). HDL-C presented a positive association with subcutaneous fat evaluated by ultrasonography (R2 = 12.5%, p < 0.001). Obesity was a confounding factor in multiple regression analyses between TC and LDL-C, when related to abdominal fat evaluated by ultrasonography, and resulted in a positive association among the obese and a negative association among the non-obese women. The sensibility of this method was related to the quantity of fat in the visceral region. Conclusions. Waist circumference showed the highest association with insulin resistance. Fat distribution evaluated by dual-energy X-ray absorptiometry and ultrasound was also associated with insulin resistance, but with lower intensity. The relationship of visceral fat distribution evaluated by ultrasound to TC cholesterol and LDL-C showed opposed results between obese and non-obese menopausal women.
A fast analytical technique for estimating the bounds of on-chip clock wire inductance

Accurate integrity assessment of on-chip clock lines is difficult without any a priori knowledge about their inductance at an early stage in the clock design process. This paper introduces an efficient approach to estimate the bounds of on-chip clock wire inductance at the very beginning of the design stages. With this information, more accurate waveforms along the clock distribution networks can be obtained thus greatly reducing the overall length of design cycles.
Particle Swarm Optimization based Algorithm for Economic Load Dispatch

Particle Swarm Optimization (PSO) has emerged as a useful tool for engineering optimization. However, most of the PSO algorithms are aimed at unconstrained problems. For the constrained problems, the approach introduced is just the traditional combination of primitive PSO and the penalty function. It was investigated that the simple penalty function strategy cannot be integrated well with PSO algorithms because it does not utilize the historical memory information, which is an essential of PSO. In view of this problem, a new constraints handling strategy suitable for the optimization mechanism of PSO is proposed. In addition, local search procedure is hybridized with PSO to intensify its search ability in local regions, and a hybrid PSO (HPSO) algorithm for constrained optimization is put forward. Economic load dispatch problem is used to demonstrate its efficiency. Experimental results show that the proposed HPSO algorithm is both effective and efficient.