Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Place Categorization With Deep Domain Generalization

Traditional place categorization approaches in robot vision assume that training and test images have similar visual appearance. Therefore, any seasonal, illumination, and environmental changes typically lead to severe degradation in performance. To cope with this problem, recent works have been proposed to adopt domain adaptation techniques. While effective, these methods assume that some prior information about the scenario where the robot will operate is available at training time. Unfortunately, in many cases, this assumption does not hold, as we often do not know where a robot will be deployed. To overcome this issue, in this paper, we present an approach that aims at learning classification models able to generalize to unseen scenarios. Specifically, we propose a novel deep learning framework for domain generalization. Our method develops from the intuition that, given a set of different classification models associated to known domains (e.g., corresponding to multiple environments, robots), the best model for a new sample in the novel domain can be computed directly at test time by optimally combining the known models. To implement our idea, we exploit recent advances in deep domain adaptation and design a convolutional neural network architecture with novel layers performing a weighted version of batch normalization. Our experiments, conducted on three common datasets for robot place categorization, confirm the validity of our contribution.
Reduced Antifungal Susceptibility of Vulvovaginal Candida Species at Normal Vaginal pH Levels: Clinical Implications

Objective The aims of the study were to assess for differences in antifungal in vitro potency at pH 7 and pH 4 and to discuss any potential clinical implications of that difference. Materials and Methods A retrospective analysis of 217 first positive yeast cultures from 217 patients. Yeast isolates underwent antifungal susceptibility testing, with minimum inhibitory concentrations (MICs) (microgram per milliliter) measured at pH 7 and pH 4 for fluconazole, itraconazole, miconazole, clotrimazole, terconazole, and nystatin. Only the first isolates collected from each patient were included in the analysis. Results Yeast first isolates included 173 Candida albicans, 15 Candida glabrata, and 29 isolates from 8 other species. Geometric mean (GM) MIC values for all antifungals were significantly higher when tested at pH 4 (p < .001 for all comparisons). For C. albicans, the largest GM MIC differences were observed for terconazole (0.17 pH 7 vs 6.17 pH 4) and clotrimazole (0.04 vs 0.24). For terconazole, 97.7% of the isolates had a MIC of 1 or less at pH 7 but 83.2% had a MIC of 4 or higher at pH 4. For C. glabrata, terconazole (GM MIC = 0.26 pH 7 vs >64 pH 4), clotrimazole (0.13 vs 6.96), miconazole (0.06 vs 0.76), and fluconazole (3.17 vs 26.6) were most affected. All C. glabrata isolates had a MIC of 1 or less for terconazole at pH 7 and one had a MIC of 8 at pH 4, whereas all the rest were highly resistant (MIC > 64). Conclusions Antifungals have reduced in vitro potency when tested at lower pH. Candida glabrata is more affected than C. albicans. The impact may be greatest for the antifungal terconazole and against C. glabrata isolates.
Effect of Micronutrients Supplement on Nutrient Utilization and Growth Performance in Pre-ruminant Calves

The present study was undertaken to assess the effect of micronutrients supplement (MS) on the nutrient utilization and growth performance in pre-ruminant calves. The sixteen day old crossbred calves (body weight 24.50 ± 0.56 kg) were randomly allocated into two dietary treatments; control (C) and treatment (T) groups. Diets were same for both groups and in addition to diet micronutrients supplement was given to individual calf of treatment group. The supplementation of MS in the diet of crossbred calves did not affect the intake and digestibility coefficients of CP, EE, NDF and ADF. Over all body weight changes and feed conversion efficiency did not differ significantly between groups but average daily gain (g) was significantly (P<0.05) higher in T group as compare to control (C) group. Thus it was concluded that supplementation of micro-nutrients in pre-ruminant calves showed significant improvement in average daily gain while the intake, feed efficiency and digestibility of nutrients were comparable between the groups.
License plate detection in complex scenes based on fusion of Gaussian filtering and Bayesian network

In this paper, the problem of automatic license plate recognition is addressed. We focus on detecting the location of the license plate, which is one of the most challenging parts of such systems. Due to the strength of edges within the plate region, most existing methods start by edge detection. However, relying only on edge detection is subject to failure in complex backgrounds and bad-illuminated images. To soften these conditions, we propose to fuse two strong tools, i.e. Gaussian filter and Bayesian network after preprocessing and edge detection, to achieve acceptable detection rate. Our experimental results confirm the effectiveness of the proposed method in detecting the license plate in low/high illumination conditions and complex backgrounds.
Synthesis, characterization, and thermal degradation of novel poly(2‐(5‐bromo benzofuran‐2‐yl)‐2‐oxoethyl methacrylate)

A novel methacrylate monomer containing benzofuran side group, 2-(5-bromo benzofuran-2-yl)-2-oxoethyl methacrylate (BOEMA), was synthesized from esterification reaction of 2-bromo-1-(5-bromo benzofuran-2-yl) ethanone with sodium methacrylate at 85°C in the presence of 1,4-dioxane solvent. After characterization with Fourier transform infrared spectrophotometer, nuclear magnetic resonance (1H-NMR and 13C-NMR), its homopolymerization was carried out by free radical polymerization at 60°C in the presence of benzoyl peroxide initiator and 1,4-dioxane solvent. The glass transition temperature (Tg) of the synthesized novel polymer, poly(2-(5-bromo benzofuran-2-yl)-2-oxoethyl methacrylate) [poly(BOEMA)], was determined to be 137°C with differential scanning calorimetry technique. Thermal degradation kinetics of poly(BOEMA) was investigated by thermogravimetric analysis method at different heating rates with 5°C/min intervals between measurements. From dynamic measurements, the analysis of each process mechanism of Coats–Redfern and Van Krevelen methods showed that the most probable model for the decomposition process of poly(BOEMA) homopolymer agrees with the random nucleation, F1 mechanism. The apparent decomposition activation energies of poly(BOEMA) by Kissinger's and Flynn–Wall–Ozawa methods in the studied conversion range were 188.47 and 180.13 kJ/mol, respectively. POLYM. ENG. SCI., 2012. © 2011 Society of Plastics Engineers
TTNWW to the rescue: no need to know how to handle tools and resources

"But I don’t know how to work with [name of tool or resource]" is something one often hears when researchers in Human and Social Sciences (HSS) are confronted with language technology, be it written or spoken, tools or resources. The TTNWW project shows that these researchers do not need to be experts in language or speech technology, or to know all kinds of details about the tools involved. In principle they only need to make clear what they want to achieve. In this paper we describe a series of tools that are already available as a webservice. Details are not presented - interested readers are referred to the papers mentioned in the References and to the TTNWW website.
AUV antagonistic tactics study for naval battle based on dynamic game

According to the cooperative antagonism game problem of multi autonomous underwater vehicles(AUVs), multi AUVs cooperative attack dynamic countermeasures are researched. A multi-combat steps dynamic target assignment optimization model is built based on the game theory for multi-strategy autonomous underwater vehicles cooperative attack. Particle swarm optimization (PSO) algorithm is applied to solve the Nash equilibrium point for obtaining optimal antagonistic tactics. It is confirmed that the feasibility and validity of the proposed model and method.
iBrownout: An Integrated Approach for Managing Energy and Brownout in Container-Based Clouds

Energy consumption of Cloud data centers has been a major concern of many researchers, and one of the reasons for huge energy consumption of Clouds lies in the inefficient utilization of computing resources. Besides energy consumption, another challenge of data centers is the unexpected loads, which leads to the overloads and performance degradation. Compared with VM consolidation and Dynamic Voltage Frequency Scaling that cannot function well when the whole data center is overloaded, brownout has shown to be a promising technique to handle both overloads and energy consumption through dynamically deactivating application optional components, which are also identified as containers/microservices. In this work, we propose an integrated approach to manage energy consumption and brownout in container-based cloud data centers. We also evaluate our proposed scheduling policies with real traces in a prototype system. The results show that our approach reduces about 40, 20, and 10 percent energy than the approach without power-saving techniques, brownout-overbooking approach and auto-scaling approach, respectively, while ensuring Quality of Service.
THERMAL CHARACTERISTICS, MECHANICAL PROPERTIES AND BIODEGRADABILITY OF POLYCARBONATES/POLY(LACTIC ACID ) (PPC/PLA) BLENDS

Polycarbonates/poly(lactic acid) (PPC/PLA) blends were prepared by solution cast method. The thermal characteristics were studied by means of differential scanning calorimetry (DSC) and thermogravimetry (TG). Mechanical properties of the blends were investigated by tensile mechanical test. Biodegradability for PPC/PLA blends was investigated in detail by soil suspension cultivation and scanning electron microscopy (SEM). Experimental results indicated that increasing PPC content led to decrease in tensile strength and modulus, and yet significantly increase the rate of biodegradation of the blends. But at some blend ratios, the rate of weight-loss of PPC/ PLA blends (20/80, or 40/60) was faster than that of pure PPC. PPC/ PLA blends possess a good combination of mechanical properties and biodegradation rate.
Zero-cost labelling with web feeds for weblog data extraction

Data extraction from web pages often involves either human intervention for training a wrapper or a reduced level of granularity in the information acquired. Even though the study of social media has drawn the attention of researchers, weblogs remain a part of the web that cannot be harvested efficiently. In this paper, we propose a fully automated approach in generating a wrapper for weblogs, which exploits web feeds for cheap labelling of weblog properties. Instead of performing a pairwise comparison between posts, the model matches the values of the web feeds against their corresponding HTML elements retrieved from multiple weblog posts. It adopts a probabilistic approach for deriving a set of rules and automating the process of wrapper generation. Our evaluation shows that our approach is robust, accurate and efficient in handling different types of weblogs.
Formal Linked Data Visualization Model

Recently, the amount of semantic data available in the Web has increased dramatically. The potential of this vast amount of data is enormous but in most cases it is difficult for users to explore and use this data, especially for those without experience with Semantic Web technologies. Applying information visualization techniques to the Semantic Web helps users to easily explore large amounts of data and interact with them. In this article we devise a formal Linked Data Visualization Model (LDVM), which allows to dynamically connect data with visualizations. We report about our implementation of the LDVM comprising a library of generic visualizations that enable both users and data analysts to get an overview on, visualize and explore the Data Web and perform detailed analyzes on Linked Data.
Evidence Supporting Serology-based Pathway for Diagnosing Celiac Disease in Asymptomatic Children From High-risk Groups

Objective: The European Society for Pediatric Gastroenterology Hepatology and Nutrition (ESPGHAN) guidelines for diagnosing celiac disease (CD) in children were modified in 2012. They recommend that in symptomatic children with anti-tissue transglutaminase antibody (anti-tTG) titer of >10 times upper limit of normal (>10× ULN) and who have positive anti-endomysial antibody and HLA-DQ2/DQ8 haplotype, the diagnosis of CD can be based on serology. The aim of this study is to establish whether serology-based pathway of the ESPGHAN guidelines could also be reliably applied to asymptomatic children from high-risk groups. Methods: From March 2007 to February 2017, prospective data on anti-tTG titer, age, sex, and reason for screening were collected at diagnostic endoscopy on all asymptomatic children being diagnosed as having CD. The relationship between modified Marsh-Oberhuber classification histological grading and contemporaneous anti-tTG titers was analyzed. Results: A total of 157 asymptomatic children were diagnosed as having CD. Eighty-four of 157 (53.5%) had antitTG >10× ULN (normal <10 IU/mL) and 75 of 84 were from high-risk groups. All 75 had definitive histological evidence (Marsh-Oberhuber 3a-3c) of small bowel enteropathy. Fifty-three of 84 children had anti-tTG >200 IU/mL and total villous atrophy was present in 29 of 53 (55%). Main reasons for serological screening were: type-1 diabetes mellitus (n = 36) and first-degree relatives with CD (n = 24). Mean age at diagnosis was 8.8 years. Serology-based diagnosis is cost-beneficial by around £1275 per child in the United Kingdom. Conclusions: All 75 asymptomatic children from high-risk groups with anti-tTG >10× ULN had histology-proven CD. This study provides further evidence that the guidelines for diagnosing CD by the serology-based pathway should be extended to these children.
Gene Flow Between Domestic and Sylvan Populations of Aedes aegypti (Diptera: Culicidae) in North Cameroon

Abstract Polymorphisms at eight microsatellite loci and a fragment of the mitochondrial DNA (mtDNA)-ND4 gene were surveyed in Aedes aegypti (L.) (Diptera: Culicidae) populations collected from six localities in North Cameroon, with emphasis on comparing domestic versus sylvan populations. The microsatellites revealed significant genetic differentiation among sylvan populations, with mean FST = 0.066. Domestic collections were genetically homogeneous (mean FST = 0.012). No pattern of isolation by distance was detected, and one of highest levels of genetic differentiation was estimated between populations sampled a few kilometers apart, each in a distinctly different ecological environment (FST = 0.076). Analyses of mtDNA-ND4 polymorphisms and divergence between the two neighboring populations revealed increased genetic diversity within the domestic population, with molecular signatures suggesting recent demographic expansion, whereas a single haplotype was observed in the sylvan sample. These data suggest reduced gene flow between sylvan and domestic Ae. aegypti populations in North Cameroon, reminiscent of the situation for Ae. aegypti in Kenya in East Africa.
STN area detection using K-NN classifiers for MER recordings in Parkinson patients during neurostimulator implant surgery

Deep Brain Stimulation (DBS) applies electric pulses into the subthalamic nucleus (STN) improving tremor and other symptoms associated to Parkinson’s disease. Accurate STN detection for proper location and implant of the stimulating electrodes is a complex task and surgeons are not always certain about final location. Signals from the STN acquired during DBS surgery are obtained with microelectrodes, having specific characteristics differing from other brain areas. Using supervised learning, a trained model based on previous microelectrode recordings (MER) can be obtained, being able to successfully classify the STN area for new MER signals. The K Nearest Neighbours (K-NN) algorithm has been successfully applied to STN detection. However, the use of the fuzzy form of the K-NN algorithm (KNN-F) has not been reported. This work compares the STN detection algorithm of K-NN and KNN-F. Real MER recordings from eight patients where previously classified by neurophysiologists, defining 15 features. Sensitivity and specificity for the classifiers are obtained, Wilcoxon signed rank non-parametric test is used as statistical hypothesis validation. We conclude that the performance of KNN-F classifier is higher than K-NN with p<0.01 in STN specificity.
Phylogenetic surveys on the newt genus Tylototriton sensu lato (Salamandridae, Caudata) reveal cryptic diversity and novel diversification promoted by historical climatic shifts

Global climatic transitions and Tibetan Plateau uplifts are hypothesized to have profoundly impacted biodiversity in southeastern Asia. To further test the hypotheses related to the impacts of these incidents, we investigated the diversification patterns of the newt genus Tylototriton sensu lato, distributed across the mountain ranges of southeastern Asia. Gene-tree and species-tree analyses of two mitochondrial genes and two nuclear genes revealed five major clades in the genus, and suggested several cryptic species. Dating estimates suggested that the genus originated in the early-to-middle Miocene. Under different species delimitating scenarios, diversification analyses with birth-death likelihood tests indicated that the genus held a higher diversification rate in the late Miocene-to-Pliocene era than that in the Pleistocene. Ancestral area reconstructions indicated that the genus originated from the northern Indochina Peninsula. Accordingly, we hypothesized that the Miocene Climatic Transition triggered the diversification of the genus, and the reinforcement of East Asian monsoons associated with the stepwise uplifts of the Tibetan Plateau promoted the radiation of the genus in southeastern Asia during the Miocene-to-Pliocene period. Quaternary glacial cycles likely had limited effects on speciation events in the genus, but mainly had contributions on their intraspecific differentiations.
Characterisation of triple junction geometry in polycrystals by automated digital image processing

The dihedral angle distribution is a useful parameter in the quantification of polycrystalline microstructures. However, this microstructural parameter has not received much attention because the methodologies associated with the accurate measurements of dihedral angles are generally tedious and time consuming. In this paper an automated methodology, based on image processing and analysis, is developed to evaluate dihedral angles in microstructures in a two-dimensional plane section of polycrystals. It is shown that the technique is extremely fast and accurate and therefore can be applied to obtain a significantly large statistical sample of dihedral angles. The application of this method is demonstrated by evaluating triple junction geometry of polycrystalline 316L austenitic stainless steel.
A Joint MMSE Scheme for Multiuser AF Relaying Systems Under Power Constraints

This letter studies a minimum mean square error (MMSE) relay strategy for multiuser amplify-and-forward relaying system consisting of <inline-formula><tex-math notation="LaTeX">$M$</tex-math></inline-formula> source–destination pairs between <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula> relays with only a single antenna per node. We design jointly and explicitly optimal diagonal relay amplifying and destination decoder matrices under relay transmit power constraints. By adopting the derived optimal relay amplifying matrix, the MMSE cost function (CF) behavior is analytically and numerically investigated. In addition, it is analytically and numerically shown that the MMSE CF values are always less than <inline-formula> <tex-math notation="LaTeX">$M$</tex-math></inline-formula>, regardless of <inline-formula><tex-math notation="LaTeX"> $N$</tex-math></inline-formula> if <inline-formula><tex-math notation="LaTeX">$M \gtrless N$</tex-math></inline-formula> . And an efficient iterative algorithm with a small number of iterations is proposed to solve the jointly desired optimization problem. Finally, simulation results show that the proposed scheme outperforms the existing ones.
Analysis of genetic relatedness among Indian cattle (Bos indicus) using genotyping-by-sequencing markers.

Genetic relatedness of 24 animals belonging to seven Indian cattle breeds was studied using high throughput genotyping-by-sequencing (GBS) markers. GBS produced 93.6 million reads with an average of about 3.9 million reads per animal. A total of 107 488 SNPs were identified in these individuals. When only one SNP per read was considered, a total of 60 261 SNPs representing independent reads were identified with an average SNP-to-SNP distance of 45 kb across the bovine reference genome. About 24% of the GBS-SNP markers were more than 100 kb apart. Of these, 58 322 SNPs mapped to autosomes, 1645 to the X chromosome and 28 to the Y chromosome. The average SNP-to-SNP distance on the X chromosome was 91.3 kb, whereas on the Y chromosome it was 1546.4 kb. The minor allele frequency within the Indian cattle varied from 0.103 (Ongole) to 0.177 (Siri), whereas Holstein cattle had the lowest value of 0.089. This is the first application of GBS in cattle of South Asia. The baseline information generated in this study might prompt implementation of GBS in breeding of cattle belonging to this region.
Home localization system for misplaced objects

Smart Home systems have been an important area of CE research in recent years. People sometimes forget where they left certain things, such as glasses, wallets, keys, etc. in their home. It is often troublesome to find them. This study proposes an RFID solution to localize the easily-lost objects based on 3 nearest reference points. The current highest accuracy rate of 87.5% encourages enhancement of the technique and implementation of the complete system.
The Fracture Process Simulation and Fracture Strength of Gear Tooth in Mining Machine

The initiation and expansion of the root crack of gears is investigated according to the fracture mechanics principles. The root stress and root stress intensity factor with the crack initiating position and expansion direction are studied and computed by the finite element method. By means of the fracture process simulation the variation of the root stress intensity factor with the crack propagation trajectory and the fracture process are analyzed, and the method of the calculation of the tooth fracture strength and the significance of the fracture process are explained.
Microblog Analysis as a Programme of Work

Inspired by a European project, PHEME, that requires the close analysis of Twitter-based conversations in order to look at the spread of rumors via social media, this paper has two objectives. The first of these is to take the analysis of microblogs back to first principles and lay out what microblog analysis should look like as a foundational programme of work. The other is to describe how this is of fundamental relevance to Human-Computer Interaction's interest in grasping the constitution of people's interactions with technology within the social order. Our critical finding is that, despite some surface similarities, Twitter-based conversations are a wholly distinct social phenomenon requiring an independent analysis that treats them as unique phenomena in their own right, rather than as another species of conversation that can be handled within the framework of existing Conversation Analysis. This motivates the argument that Microblog Analysis be established as a foundationally independent programme, examining the organizational characteristics of microblogging from the ground up. We articulate how aspects of this approach have already begun to shape our design activities within the PHEME project.