Miracle-dz/UniFAR-FTUs huggingface dataset:
An analysis of frequent ways of making undiscoverable Web Service descriptions

The ever increasing number of publicly available Web Services makes standardcompliant service registries one of the essential tools to service-oriented application developers. Previous works have shown that the descriptiveness of published service descriptions is important from the point of view of the algorithms that support service discovery using this kind of registries as well as human developers, who have the final word on which discovered service is more appropriate. This paper presents a catalog of frequent bad practices in the creation of Web Service descriptions that attempt against their chances of being discovered, along with novel practical solutions to them.Additionally, the paper presents empirical evaluations that corroborated the benefits of the proposed solutions. These anti-patterns will help service publishers avoid common discoverability problems and improve existing service descriptions.
A Robust Approach for Securing Audio Classification Against Adversarial Attacks

Adversarial audio attacks can be considered as a small perturbation unperceptive to human ears that is intentionally added to an audio signal and causes a machine learning model to make mistakes. This poses a security concern about the safety of machine learning models since the adversarial attacks can fool such models toward the wrong predictions. In this paper we first review some strong adversarial attacks that may affect both audio signals and their 2D representations and evaluate the resiliency of deep learning models and support vector machines (SVM) trained on 2D audio representations such as short time Fourier transform, discrete wavelet transform (DWT) and cross recurrent plot against several state-of-the-art adversarial attacks. Next, we propose a novel approach based on pre-processed DWT representation of audio signals and SVM to secure audio systems against adversarial attacks. The proposed architecture has several preprocessing modules for generating and enhancing spectrograms including dimension reduction and smoothing. We extract features from small patches of the spectrograms using the speeded up robust feature (SURF) algorithm which are further used to transform into cluster distance distribution using the K-Means++ algorithm. Finally, SURF-generated vectors are encoded by this codebook and the resulting codewords are used for training a SVM. All these steps yield to a novel approach for audio classification that provides a good tradeoff between accuracy and resilience. Experimental results on three environmental sound datasets show the competitive performance of the proposed approach compared to the deep neural networks both in terms of accuracy and robustness against strong adversarial attacks.
Macrophage-Driven Biomaterial Degradation Depends on Scaffold Microarchitecture

In situ tissue engineering is a technology in which non-cellular biomaterial scaffolds are implanted in order to induce local regeneration of replaced or damaged tissues. Degradable synthetic electrospun scaffolds are a versatile and promising class of biomaterials for various in situ tissue engineering applications, such as cardiovascular replacements. Functional in situ tissue regeneration depends on the balance between endogenous neo-tissue formation and scaffold degradation. Both these processes are driven by macrophages. Upon invasion into a scaffold, macrophages secrete reactive oxygen species (ROS) and hydrolytic enzymes, contributing to oxidative and enzymatic biomaterial degradation, respectively. This study aims to elucidate the effect of scaffold microarchitecture, i.e., μm-range fiber diameter and fiber alignment, on early macrophage-driven scaffold degradation. Electrospun poly-ε-caprolactone-bisurea (PCL-BU) scaffolds with either 2 or 6 μm (Ø) isotropic or anisotropic fibers were seeded with THP-1 derived human macrophages and cultured in vitro for 4 or 8 days. Our results revealed that macroph age-induced oxidative degradation in particular was dependent on scaffold microarchitecture, with the highest level of ROS-induced lipid peroxidation, NADPH oxidase gene expression and degradation in the 6 μm Ø anisotropic group. Whereas, biochemically polarized macrophages demonstrated a phenotype-specific degradative potential, the observed differences in macrophage degradative potential instigated by the scaffold microarchitecture could not be attributed to either distinct M1 or M2 polarization. This suggests that the scaffold microarchitecture uniquely affects macrophage-driven degradation. These findings emphasize the importance of considering the scaffold microarchitecture in the design of scaffolds for in situ tissue engineering applications and the tailoring of degradation kinetics thereof.
A Blahut-Arimoto Type Algorithm for Computing Classical-Quantum Channel Capacity

Based on Arimoto’s work in 1978 [1], we propose an iterative algorithm for computing the capacity of a discrete memoryless classical-quantum channel with a finite input alphabet and a finite dimensional output, which we call the Blahut-Arimoto algorithm for classical-quantum channel, and an input cost constraint is considered. We show that to reach ε accuracy, the iteration complexity of the algorithm is up bounded by $\frac{{\log n\log \varepsilon }}{\varepsilon }$ where n is the size of the input alphabet. In particular, when the output state ${\{ {\rho _x}\} _{x \in \mathcal{X}}}$ is linearly independent in complex matrix space, the algorithm has a geometric convergence. We also show that the algorithm reaches an ε accurate solution with a complexity of $O\left( {\frac{{{m^3}\log n\log \varepsilon }}{\varepsilon }} \right)$, and $O\left( {{m^3}\log \varepsilon {{\log }_{(1 - \delta )}}\frac{\varepsilon }{{D\left( {{p^{\ast}}\left\| {{p^{{N_0}}}} \right.} \right)}}} \right)$ in the special case, where m is the output dimension and $D\left( {{p^{\ast}}\left\| {{p^{{N_0}}}} \right.} \right)$ is the relative entropy of two distributions and δ is a positive number.
Carrier Transport and Gain Mechanisms in $\beta$ –Ga2O3-Based Metal–Semiconductor–Metal Solar-Blind Schottky Photodetectors

In this paper, carrier transport and gain mechanisms are exploited in the <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub>-based metal–semiconductor–metal photodetectors with Au back-to-back Schottky contacts. The resultant devices exhibit a low dark current of <10 pA at 10 V, a sustaining bias over 500 V without electric breakdown, a self-powered sensitivity with a UVC-to-visible rejection ratio over <inline-formula> <tex-math notation="LaTeX">$10^{{3}}$ </tex-math></inline-formula>, and a photo-to-dark current ratio of 50 at 473 K, indicative of its strong operation capability at high temperature and in harsh environments. Temperature-dependent current–voltage features reveal that the dark reverse leakage is dominated by the thermionic field emission at low electric field and Poole–Frenkel emission from a deep trap level of 0.42 eV under the conduction band at high field, respectively. These negatively charged traps positioned below the Fermi level in the vicinity of Schottky interface capture photogenerated holes and reduce the barrier height upon illumination. The temperature- and bias-dependent photoresponse features are identified in physics that the photoconductive gain as well as slow response speed is originated from the change of barrier height due to trap repopulation.
Genomic Identification of Low-Density Granulocytes and Analysis of Their Role in the Pathogenesis of Systemic Lupus Erythematosus

Key Points A module of genes defining LDGs in lupus has been identified. LDG gene enrichment correlates with corticosteroid use, anti-dsDNA, and low complement. LDGs were not detected in lupus-affected tissues. Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by the presence of low-density granulocytes (LDGs) with a heightened capacity for spontaneous NETosis, but the contribution of LDGs to SLE pathogenesis remains unclear. To characterize LDGs in human SLE, gene expression profiles derived from isolated LDGs were characterized by weighted gene coexpression network analysis, and a 92-gene module was identified. The LDG gene signature was enriched in genes related to neutrophil degranulation and cell cycle regulation. This signature was assessed in gene expression datasets from two large-scale SLE clinical trials to study associations between LDG enrichment, SLE manifestations, and treatment regimens. LDG enrichment in the blood was associated with corticosteroid treatment as well as anti-dsDNA, low serum complement, renal manifestations, and vasculitis, but the latter two of these associations were dependent on concomitant corticosteroid treatment. In addition, LDG enrichment was associated with enrichment of gene signatures induced by type I IFN and TNF irrespective of corticosteroid treatment. Notably, LDG enrichment was not found in numerous tissues affected by SLE. Comparison with relevant reference datasets indicated that LDG enrichment is likely reflective of increased granulopoiesis in the bone marrow and not peripheral neutrophil activation. The results have uncovered important determinants of the appearance of LDGs in SLE and have emphasized the likely role of LDGs in specific aspects of lupus pathogenesis.
Complimentary Methods for Multivariate Genome-Wide Association Study Identify New Susceptibility Genes for Blood Cell Traits

Genome-wide association studies (GWAS) have found hundreds of novel loci associated with full blood count (FBC) phenotypes. However, most of these studies were performed in a single phenotype framework without putting into consideration the clinical relatedness among traits. In this work, in addition to the standard univariate GWAS, we also use two different multivariate methods to perform the first multiple traits GWAS of FBC traits in ∼7000 individuals from the Ugandan General Population Cohort (GPC). We started by performing the standard univariate GWAS approach. We then performed our first multivariate method, in this approach, we tested for marker associations with 15 FBC traits simultaneously in a multivariate mixed model implemented in GEMMA while accounting for the relatedness of individuals and pedigree structures, as well as population substructure. In this analysis, we provide a framework for the combination of multiple phenotypes in multivariate GWAS analysis and show evidence of multi-collinearity whenever the correlation between traits exceeds the correlation coefficient threshold of r2 >=0.75. This approach identifies two known and one novel loci. In the second multivariate method, we applied principal component analysis (PCA) to the same 15 correlated FBC traits. We then tested for marker associations with each PC in univariate linear mixed models implemented in GEMMA. We show that the FBC composite phenotype as assessed by each PC expresses information that is not completely encapsulated by the individual FBC traits, as this approach identifies three known and five novel loci that were not identified using both the standard univariate and multivariate GWAS methods. Across both multivariate methods, we identified six novel loci. As a proof of concept, both multivariate methods also identified known loci, HBB and ITFG3. The two multivariate methods show that multivariate genotype-phenotype methods increase power and identify novel genotype-phenotype associations not found with the standard univariate GWAS in the same dataset.
D-dimer value in the diagnosis of pulmonary embolism-may it exclude only?

Background Pulmonary embolism (PE) is the third most common cause of death for cardiovascular diseases in Europe. Quick PE diagnosis is therefore crucial for prognosis improvement. It is critical to have suitable screening tests both to exclude PE as well to select patient with highest likelihood of PE occurrence. Currently D-dimer test is accepted as important tool useful to exclude PE in low risk patients. Our goal was to assess the D-dimer test positive prognostic value. Methods A retrospective study based on medical record analysis of consecutively admitted patients to 9 wards of The University Clinical Center in Katowice who were hospitalized during four consecutive years was performed. Three hundred and seventy patients met the inclusion criteria for the study, which involved the D-dimer tests and computed tomographic pulmonary angiography (CTPA) performed during hospitalization. Assessed patients were divided into two groups: PE confirmed and PE excluded by CTPA. Results We have found that patients with D-dimer levels higher than 2,152 ng/mL had significantly increased risk of PE [area under curve (AUC) of 0.69; 95% CI, 0.64-0.75; P<0.05]. Positive predictive value (PPV) reached the level of 53%, whereas negative predictive value (NPV) reached 82%. We also found that patients with the history of neoplasm and at >65 years of age had D-dimer cut-off point moved to the level of 2,652 ng/mL (AUC of 0.67; 95% CI, 0.52-0.81; P<0.05). Conclusions Whereas the NPV of the D-dimer test is generally accepted our results suggest that, in selected cases, an increased plasmatic D-dimer levels may have PPV in PE diagnosis. Patients with the history of neoplasm have higher cut-off D-dimer points above which we should consider increased PE likelihood. CTPA should be considered even for patients with low probability of PE when D-dimer values exceed four times the normal level.
A qualitative study on the oral health of humanitarian migrants in Canada.

OBJECTIVES There is limited evidence to guide oral health policy and services for the 25,000 refugees and asylum seekers who arrive in Canada yearly. The purpose of this study was to explore and understand the pre-migration use of dental services, oral health knowledge, and the effects of oral disease among newly arrived humanitarian migrants in order to inform policy and practice for the population. METHODS Using focused ethnography and the public health model of the dental care process, we conducted face-to-face interviews (50-60 minutes) with a purposive sample of humanitarian migrants who had indicated the need for dental care. We observed mobile dental clinics that provided care to underserved communities in Montreal. Data were analyzed using a thematic and contextual approach that combined inductive and deductive frameworks. RESULTS Participants included 25 humanitarian migrants from four global geographical regions. Five major thematic categories were explored: problem-based dental consultation, self-assessed oral health status, causes of oral diseases, personal oral hygiene, and good oral health for wellbeing. In their countries of origin, participants consulted a dentist when oral symptoms persisted. They cited excessive sugar consumption and inadequate oral hygiene as causes of oral diseases, and reported significant oral diseases impacts that limited their daily functions and wellbeing once in Canada. CONCLUSIONS Humanitarian migrants were knowledgeable about causes of oral disease and the importance of good oral health, yet poor oral health continued to affect their lives in Canada in important ways.
LADN: Local Adversarial Disentangling Network for Facial Makeup and De-Makeup

We propose a local adversarial disentangling network (LADN) for facial makeup and de-makeup. Central to our method are multiple and overlapping local adversarial discriminators in a content-style disentangling network for achieving local detail transfer between facial images, with the use of asymmetric loss functions for dramatic makeup styles with high-frequency details. Existing techniques do not demonstrate or fail to transfer high-frequency details in a global adversarial setting, or train a single local discriminator only to ensure image structure consistency and thus work only for relatively simple styles. Unlike others, our proposed local adversarial discriminators can distinguish whether the generated local image details are consistent with the corresponding regions in the given reference image in cross-image style transfer in an unsupervised setting. Incorporating these technical contributions, we achieve not only state-of-the-art results on conventional styles but also novel results involving complex and dramatic styles with high-frequency details covering large areas across multiple facial features. A carefully designed dataset of unpaired before and after makeup images is released at https://georgegu1997.github. io/LADN-project-page.
GCNet: Non-Local Networks Meet Squeeze-Excitation Networks and Beyond

The Non-Local Network (NLNet) presents a pioneering approach for capturing long-range dependencies, via aggregating query-specific global context to each query position. However, through a rigorous empirical analysis, we have found that the global contexts modeled by non-local network are almost the same for different query positions within an image. In this paper, we take advantage of this finding to create a simplified network based on a query-independent formulation, which maintains the accuracy of NLNet but with significantly less computation. We further observe that this simplified design shares similar structure with Squeeze-Excitation Network (SENet). Hence we unify them into a three-step general framework for global context modeling. Within the general framework, we design a better instantiation, called the global context (GC) block, which is lightweight and can effectively model the global context. The lightweight property allows us to apply it for multiple layers in a backbone network to construct a global context network (GCNet), which generally outperforms both simplified NLNet and SENet on major benchmarks for various recognition tasks.
Genome-Wide Analyses Reveal Footprints of Divergent Selection and Drought Adaptive Traits in Synthetic-Derived Wheats

Crop-wild introgressions have long been exploited without knowing the favorable recombination points. Synthetic hexaploid wheats are one of the most exploited genetic resources for bread wheat improvement. However, despite some QTL with major effects, much less is known about genome-wide patterns of introgressions and their effects on phenotypes. We used two genome-wide association approaches: SNP-GWAS and haplotype-GWAS to identify SNPs and haplotypes associated with productivity under water-limited conditions in a synthetic-derived wheat (SYN-DER) population. Haplotype-GWAS further enriched and identified 20 more genomic regions associated with drought adaptability that did not overlap with SNP-GWAS. Since GWAS is biased to the phenotypes in the study and may fail to detect important genetic diversity during breeding, we used five complementary analytical approaches (t-test, Tajima’s D, nucleotide diversity (π), Fst, and EigenGWAS) to identify divergent selections in SYN-DER compared to modern bread wheat. These approaches consistently pinpointed 89 ‘selective sweeps’, out of which 30 selection loci were identified on D-genome. These key selections co-localized with important functional genes of adaptive traits such as TaElf3-D1 (1D) for earliness per se (Eps), TaCKX-D1 (3D), TaGS1a (6D) and TaGS-D1 (7D) for grain size, weight and morphology, TaCwi-D1 (5D) influencing drought tolerance, and Vrn-D3 (7D) for vernalization. Furthermore, 55 SNPs and 23 haplotypes of agronomic and physiological importance such as grain yield, relative water content and thousand grain weight in SYN-DER, were among the top 5% of divergent selections contributed by synthetic hexaploid wheats. These divergent selections associated with improved agronomic performance carry new alleles that have been introduced to wheat. Our results demonstrated that GWAS and selection sweep analyses are powerful approaches for investigating favorable introgressions under strong selection pressure and the use of crop-wild hybridization to assist the improvement of wheat yield and productivity under moisture limiting environments.
The Role of Attachment Trauma and Disintegrative Pathogenic Processes in the Traumatic-Dissociative Dimension

Epidemiological, clinical, and neurobiological studies of the last 30 years suggest that traumatic attachments during the early years of life are associated to specific psychopathological vulnerabilities based on dissociative pathogenic processes. It has been observed that the dissociative pathogenic processes caused by these traumatic attachments either may contribute to the genesis of well-defined mental disorders (e.g., dissociative disorders) or may variably occur in many other diagnostic categories, complicating their clinical pictures and worsening their prognosis. For this reason, we proposed to define the dimension of psychopathological outcomes linked to traumatic attachments and dissociative pathogenic processes as the “traumatic-dissociative” dimension (TDD). The clinical complexity of the TDD requires specific training to enable mental health professionals to recognize the signs of traumatic developments and to implement specific treatment strategies. The present article aims to review some crucial points about the clinical meaning and treatment strategies of the TDD, the dissociative pathogenic processes characterizing the TDD, as well as of the role of attachment trauma in the TDD. We also focused on the clinical and theoretical evidence suggesting that dissociation and dis-integration may be considered two different processes but highly correlated. The usefulness of clinical reasoning in terms of psychopathological dimensions, instead of distinct diagnostic categories, as well as several therapeutic implications of these issues was finally discussed.
Mental Rotation Test Performance in Brazilian and German Adolescents: The Role of Sex, Processing Speed, and Physical Activity in Two Different Cultures

It was the main goal of this study to investigate performance on the mental rotation test (MRT) in Brazilian and German adolescents. Mental rotation is the ability to mentally transform a three-dimensional stimulus in mind and relates to science education. 60 German and 60 Brazilian adolescents (76 males and 44 females, 11–17 years) completed the Mental Rotation Test, a physical activity and media use questionnaire and a Number Connection Test. The result showed no difference between Brazilian and German adolescents in the cognitive processing speed measurement. German adolescents are more active and show a less media use compared to the Brazilian adolescents. Furthermore, German adolescents demonstrate a better MRT performance than Brazilian ones, as well as boys show a better performance than girls do. A multiple regression analysis indicated that the MRT performance could be predicted by nationality, sex, and cognitive processing speed. Since cognitive processing speed did not differ between Brazilian and German adolescents, the worse MRT performance of the Brazilian adolescents could be explained by different educational systems. Further studies have to follow which investigate the reasons for the different nations in more detail.
Long‐term outcomes after endoscopic dacryocystorhinostomy without mucosal flap preservation

A growing body of evidence demonstrates that endonasal endoscopic dacryocystorhinostomy (eDCR) techniques provide comparable results to conventional external techniques. The purpose of this study was to evaluate long‐term outcomes after powered endoscopic DCR without preservation of mucosal flaps for the management of acquired nasolacrimal duct obstruction performed by a single surgical team.