Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatiotemporal Associative Classification for Satellite Image Time Series

Mining spatiotemporal data is a challenging task since time and space bring two complex variables to the mining analysis. Traditional classiﬁers consider the individual data instances alone disregarding the time and spatial correlations. This leads to a lessening of the analysis potential of the traditional mining to an analysis solely of a given time or space. In this paper, we propose a Spatiotemporal Associative Classiﬁer, called SAC, able to catch time and spatial correlations in the classiﬁcation task. To perform spatiotemporal classiﬁcation SAC employs, as the learning model, Thematic Spatiotemporal Association Rules (TSAR). TSAR are association rules that track the relations of time and space and the evolution of the thematic attributes values. We employed SAC and TSAR to mine Satellite Image Time Series (SITS) in order to predict sun ﬂares events. However, a TSAR has a difﬁcult understanding, not treated previously in the literature. In this sense, this paper also employs the proposed clas-siﬁer to improve its understanding by the domain specialist. The results presented high accuracies and are promising according to the domain specialists.
The Symptom Trajectory of Attention-Deficit Hyperactivity Disorder in Korean School-Age Children

Objective We aimed to investigate symptom trajectory of attention-deficit hyperactivity disorder (ADHD) in Korean school-age children. Methods Four hundred fifty six elementary school children were enrolled when they were in 1st grade and assessed once per year until 4th grade. Symptom severity was assessed by parents using the Korean version of the ADHD rating scale (K-ARS). High-risk was defined as a K-ARS score >18; 377, 325, and 284 children participated in the subsequent assessments. Symptom trajectory was analyzed using a mixed-model approach consistent with the longitudinal nature of the present study including missing data. Results K-ARS scores demonstrated significant main effects of time (F=35.33; p<0.001), sex (F=20.77; p<0.001), and first-year high-risk group (F=240.90; p<0.001). It also demonstrated a significant time×first-year high-risk group interaction effect (F=38.14; p<0.001), but not a time×sex interaction effect. Conclusion K-ARS scores demonstrated a tendency to decline with aging. Individuals in the high-risk group demonstrated earlier declining tendency than those in the non-high risk group. Although total K-ARS scores differed significantly between the sexes at all assessments, the declining pattern between both sexes did not differ significantly. Further studies including larger sample sizes, diagnostic interviews, and complete data sets are needed to confirm findings of the present study.
Fast winding numbers for soups and clouds

Inside-outside determination is a basic building block for higher-level geometry processing operations. Generalized winding numbers provide a robust answer for triangle meshes, regardless of defects such as self-intersections, holes or degeneracies. In this paper, we further generalize the winding number to point clouds. Previous methods for evaluating the winding number are slow for completely disconnected surfaces, such as triangle soups or-in the extreme case- point clouds. We propose a tree-based algorithm to reduce the asymptotic complexity of generalized winding number computation, while closely approximating the exact value. Armed with a fast evaluation, we demonstrate the winding number in a variety of new applications: voxelization, signing distances, generating 3D printer paths, defect-tolerant mesh booleans and point set surfaces.
Engineering the Bone-Implant Interface

The world of osseointegration has moved forward as a courtesy of the recent technological revolutionwhich has presented itself in many forms, one of which is the introduction of new implant geometries and surfaceswhich is changing the surgical protocols, making everything easier, faster, andmore predictable. In fact, new implant macrotopographies have been introduced aiming to allow clinicians to obtain better and more predictable primary stability, therefore using dental implants as a solution to more challenging cases (such as areas of poor bone quality and/or in fresh postextraction sockets), with the possibility of anticipating nonconventional loading scenarios of the prosthetic superstructure, with the aim to provide positive patients outcome based on obtaining predictable shortand long-term results. Immediate placement of dental implants in fresh extraction sockets is usually highly appreciated protocol by patients, as it can provide satisfactory restorations at fraction of trauma, time, and cost. Similarly, the possibility of speeding up fitting the prosthetic superstructure is appreciated by patients, because it reduces treatment time and the related costs; in addition, it allows patients to avoid the discomfort and embarrassment of having to use provisional removable dentures during the healing period, with functional and aesthetic benefits. In order to accelerate the bone healing processes, new implant microand nanotopographies have been introduced in the market. In fact, new surface treatments allow us to obtain microand nano-rough implant surfaces, characterized by a controlled microand nanotopography, able to geometrically stimulate and accelerate the bone healing processes: this can effectively enhance osseointegration, reducing healing times. These are important applications, in dentistry, of the tissue engineering concepts. In the present thematic special issue, we have gathered several well conducted scientific and clinical papers that examine and describe the above concepts. This thematic special issue features a series of clinical studies on the effects of new implant macrotopographies on the implant stability, survival, and success in the short and long term. Moreover, we have collected a series of scientific articles (in vitro studies on cell cultures, in vivo animal histologic/histomorphometric studies, in vivohumanhistologic/histomorphometric studies, and clinical studies) on the effects of new macro-, micro, and nanotopographies on osseointegration. Finally, we are delighted that this issue includes the first human histologic article in the dental literature, reporting on the 5-year results with an innovative strategy for enhancing aesthetics in implant treatment in the anterior maxilla utilising the root membrane/socket shield technique. Only high quality research and clinical papers have been selected and published in the present thematic special issue. We really hope you will enjoy the reading and find it very interesting.
Every drop counts: unleashing the prospective locations for water harvesting using geospatial analytics

Water is at the heart of 'Sustainable Development Goals (SDGs)' set by United Nations - with an objective to balance the three dimensions of sustainable development: Environment, Social and Economic - and is indirectly associated with the success of all the other Goals. But, with changing climatic patterns, untimely rains, prolonged dry spells, depleting ground water and drought making every drop of water extremely precious, the need of the hour is to gauge and work towards the major aspects of water harvesting - 'Catchment'. Water Harvesting must be a key element of any strategy to bring an end to India's perennial swings between drought and flood and to meet the following SDGs for sustained development. This study presents a structured and meticulous approach, wielding 'Geospatial Analytics' to identify the prospective locations for Water Harvesting in arid and semi-arid parts of the country for sustainable development. This paper is structured as follows. Section 1 describes the background and motivation for this idea. Section 2 details out the objective. In section 3 we present the 'Literature Survey' on the work that has already been carried out in this field. While section 4 discerns our area of study, Section 5 provides process flow starting from Data gathering, Data extraction, Data pre-processing, Model selection and Multi Criteria Decision Making (Model Application). In Section 6, we present and validate our experimental results achieved using the proposed methodology. Section 7 concludes our study followed by Section 8 on Recommendations for future enhancements and next steps.
Kernel-Supported Cost-Effective Audit Logging for Causality Tracking

The Linux Audit system is widely used as a causality tracking system in real-world deployments for problem diagnosis and forensic analysis. However, it has poor performance. We perform a comprehensive analysis on the Linux Audit system and find that it suffers from high runtime and storage overheads due to the large volume of redundant events. To address these shortcomings, we propose an in-kernel cache-based online log-reduction system to enable high-performance audit logging. It features a multi-layer caching scheme distributed in various kernel data structures, and uses the caches to detect and suppress redundant events. Our technique is designed to reduce the runtime overhead caused by transferring, processing, and writing logs, as well as the space overhead caused by storing them on disk. Compared to existing log reduction techniques that first generate the huge raw logs before reduction, our technique avoids generating redundant events at the first place. Our experimental results of the prototype KCAL (Kernel-supported Cost-effective Audit Logging) on one-month real-world workloads show that KCAL can reduce the runtime overhead from 40+% to 15-%, and reduce space consumption by 90% on average. KCAL achieves such a large reduction with 4% CPU consumption on average, whereas a state-of-the-art user space log-reduction technique has to occupy a processor with 95+% CPU consumption all the time.
Optimization with Clause Problems

We introduce a new input class called clause problems, that can be used to study local constraint structures, which occur in inputs translated from general NP-hard problems to the D-Wave native topology. We describe a small family of clause problems that are contrived to create signicant challenges for two classical competition solvers, simulated annealing (SA) and the Hamze–de Frietas–Selby solver (HFS). We identify key properties of these inputs that lead to poor performance by the classical solvers, and consider whether these properties might naturally arise in problems from real-world applications. Optimization with Clause Problems
Neural Cryptography for Secret Key Exchange and Encryption with AES

Cryptography is the art of mangling information into apparent unintelligibility in a manner allowing a secret method of unmangling. The basic service provided by cryptography is the ability to send information between participants in a way that prevents others from reading it. In order to protect the content against an opponent, sender encrypts her message using a fast symmetric encryption algorithm. But now receiver needs to know sender's key for reading her message, one can achieve this by using a key-exchange protocol. Diffie Hellman key exchange protocol was introduced for key exchange protocol. But Diffie Hellman is prune to man in middle attack so neural cryptography is used for key exchange. Secret keys are generated by synchronization of Three Parity machines which is running on both sites. Generated key is used for AES encryption.
SEM/TEM Investigation of Aluminide Coating Co-Doped with Pt and Hf Deposited on Inconel 625

The effect of simultaneous introduction of Hf and Pt into aluminide coating deposited on Inconel 625 alloy was investigated using scanning and transmission electron microscopy (SEM/TEM) methods. The coating consisted of two layers: the additive and the interdiffusion. The additive layer and part of the interdiffusion layer consist of the β-NiAl type phase. The middle part of the interdiffusion layer comprised an interpenetrating finger-like structure formed by the β-NiAl and TCP—σ type phases with numerous fine Cr precipitates in the former and occasional larger precipitates of NbC carbides interspersed in between them. The σ type phase inclusions are situated at the border between the substrate and the interdiffusion layer. The experiment showed that platinum fully dissolves in the β-NiAl-type matrix, while most of the introduced hafnium accumulates in HfO2 dioxide precipitates located close to the additive/interdifusion interface.
Formulation and Characterization of Potential Antifungal Oleogel with Essential Oil of Thyme

The aim of this research was to formulate oleogel with thyme essential oil with potential antimicrobial activity, design optimal formulation, and evaluate the influence of ingredients on texture parameters of preparation. Central composite design was applied to statistical optimization of colloidal silica and paraffin oil mixture for the modeling of oleogel delivery system. The influence of designed formulations on response variables (texture parameters), firmness, cohesiveness, consistency, and index of viscosity, was evaluated. Quality of essential oil of thyme was assessed by determinate concentration of thymol and carvacrol using gas chromatography with flame ionization detection (GC-FID). Microbiological tests have shown that oleogel with thyme essential oil affects Candida albicans microorganism when thyme essential oil's concentration is 0,05% in oleogel mixture.
Current transport mechanisms in plasma-enhanced atomic layer deposited AlN thin films

Here, we report on the current transport mechanisms in AlN thin films deposited at a low temperature (i.e., 200 °C) on p-type Si substrates by plasma-enhanced atomic layer deposition. Structural characterization of the deposited AlN was carried out using grazing-incidence X-ray diffraction, revealing polycrystalline films with a wurtzite (hexagonal) structure. Al/AlN/ p-Si metal-insulator-semiconductor (MIS) capacitor structures were fabricated and investigated under negative bias by performing current-voltage measurements. As a function of the applied electric field, different types of current transport mechanisms were observed; i.e., ohmic conduction (15.2–21.5 MV/m), Schottky emission (23.6–39.5 MV/m), Frenkel-Poole emission (63.8–211.8 MV/m), trap-assisted tunneling (226–280 MV/m), and Fowler-Nordheim tunneling (290–447 MV/m). Electrical properties of the insulating AlN layer and the fabricated Al/AlN/p-Si MIS capacitor structure such as dielectric constant, flat-band voltage, effective charge density, and threshold voltage were also determined from the capacitance-voltage measurements.
Intervention to Promote PhysicianWell-being , Job Satisfaction , and Professionalism A Randomized Clinical Trial

RESULTS Empowerment and engagement at work increased by 5.3 points in the intervention arm vs a 0.5-point decline in the control arm by 3 months after the study (P = .04), an improvement sustained at 12 months (+5.5 vs +1.3 points; P = .03). Rates of high depersonalization at 3 months had decreased by 15.5% in the intervention arm vs a 0.8% increase in the control arm (P = .004). This difference was also sustained at 12 months (9.6% vs 1.5% decrease; P = .02). No statistically significant differences in stress, symptoms of depression, overall quality of life, or job satisfaction were seen. In additional comparisons including the nontrial physician cohort, the proportion of participants strongly agreeing that their work was meaningful increased 6.3% in the study intervention arm but decreased 6.3% in the study control arm and 13.4% in the nonstudy cohort (P = .04). Rates of depersonalization, emotional exhaustion, and overall burnout decreased substantially in the trial intervention arm, decreased slightly in the trial control arm, and increased in the nontrial cohort (P = .03, .007, and .002 for each outcome, respectively).
Segmentation of medical images by feature tracing in a self-dual morphological scale-space

The multiscale approach derives a segmentation from the evolution of appropriate signal-descriptive features in scale-space. Features that are stable for a wide range of scales are assumed to belong to visually sensible regions. To compensate the well-known drawbacks of linear scale- spaces, the shape-preserving properties of morphological scale-space filtering are utilized. The limiting duality of morphological filters is overcome by a selfdual morphological approach considering both light and dark structures in either the opening or the closing branch of the scale-space. Reconstructive opening/closing-filters enable the scale=analysis of 2D signals, since they are causal with respect to regional maxima/minima. This allows to identify important regions in scale=space via their extrema. Each extremum is assigned a region by a gradient watershed of the corresponding scale. Due to morphological filtering, the scale behavior of the regions is representable by a tree structure describing the spatial inter- and intra-scale relations among regions. The significance of a watershed region is automatically derived from its scale behavior by considering various attributes describing scale-dependent, morphological, and statistical properties of the region. The most significant regions from the segmentation of the image. The algorithm was verified for various medical image domains, such as cytological micrographs, bone x-rays, and cranial NMR slices.
A General and Efficient Querying Method for Learning to Hash

As an effective solution to the approximate nearest neighbors (ANN) search problem, learning to hash (L2H) is able to learn similarity-preserving hash functions tailored for a given dataset. However, existing L2H research mainly focuses on improving query performance by learning good hash functions, while Hamming ranking (HR) is used as the default querying method. We show by analysis and experiments that Hamming distance, the similarity indicator used in HR, is too coarse-grained and thus limits the performance of query processing. We propose a new fine-grained similarity indicator, quantization distance (QD), which provides more information about the similarity between a query and the items in a bucket. We then develop two efficient querying methods based on QD, which achieve significantly better query performance than HR. Our methods are general and can work with various L2H algorithms. Our experiments demonstrate that a simple and elegant querying method can produce performance gain equivalent to advanced and complicated learning algorithms.
Transcriptome Analysis Reveals Dynamic Gene Expression Profiles in Porcine Alveolar Macrophages in Response to the Chinese Highly Pathogenic Porcine Reproductive and Respiratory Syndrome Virus

Porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most economically important swine pathogens and causes reproductive failure in sows and respiratory disease in growing pigs. PRRSV mainly infects porcine alveolar macrophages (PAMs), leading to the subversion of innate and adaptive immunity of pigs. The transcriptome analysis of gene expression profiles in PRRSV-infected PAMs is essential for understanding the pathogenesis of PRRSV. Here we performed next-generation RNA sequencing and a comprehensive bioinformatics analysis to characterize the dynamic transcriptome landscapes in PAMs following PRRSV infection. Totally 38222 annotated mRNAs, 12987 annotated long noncoding RNAs (lncRNAs), and 17624 novel lncRNAs in PRRSV-infected PAMs were identified through a transcripts computational identification pipeline. The differentially expressed mRNAs and lncRNAs during PRRSV infection were characterized. Several differentially expressed transcripts were validated using qRT-PCR. Analyses on dynamic overrepresented GO terms and KEGG pathways in PRRSV-infected PAMs at different time points were performed. Meanwhile the genes involved in IFN-related signaling pathways, proinflammatory cytokines and chemokines, phagocytosis, and antigen presentation and processing were significantly downregulated, indicating the aberrant function of PAMs during PRRSV infection. Moreover, the differentially and highly expressed lncRNA XR_297549. 1 was predicted to both cis-regulate and trans-regulate its neighboring gene, prostaglandin-endoperoxide synthase 2 (PTGS2), indicating its role in inflammatory response. Our findings reveal the transcriptome profiles and differentially expressed mRNAs and lncRNAs in PRRSV-infected PAMs in vitro, providing valuable information for further exploration of PRRSV pathogenesis.
MultiCloud: Interactive Word Cloud Visualization for Multiple Texts

Word Clouds have gained an impressive momentum for summarizing text documents in the last years. They visually communicate in a clear and descriptive way the most frequent words of a text. However, there are only very few word cloud visualizations that support a contrastive analysis of multiple documents. The available approaches provide comparable overviews of the documents, but have shortcomings regarding the layout, readability, and use of white space. To tackle these challenges, we propose MultiCloud, an approach to visualize multiple documents within a single word cloud in a comprehensible and visually appealing way. MultiCloud comprises several parameters and visual representations that enable users to alter the word cloud visualization in different aspects. Users can set parameters to optimize the usage of available space to get a visual representation that provides an easy visual association of words with the different documents. We evaluated MultiCloud with visualization researchers and a group of domain experts comprising ﬁve humanities scholars.
Frontal and Heat Content Variability in the Indian Sector of Southern Ocean during Austral Summer 2004

Two meridional CTD and XBT sections were covered along 45°E and 57°30’E to investigate the morphology of main fronts in the southwest Indian Ocean as a part of Indian pilot expedition to the Southern Ocean on board ORV Sagar Kanya. The frontal systems distinguish the different regimes of cold Antarctic waters from the warmer and saltier waters of the subtropical regime. Along 57°30’E, the signature of the Subtropical Front (STF) was a rapid decrease in surface temperature from 17°C to 10.6°C between 43°50’S and 45°40’S and it was identified as a broad frontal region with a southward shift compared to that at 45°E. The Subantarctic Front (SAF) and Polar Front (PF) were also located with remarkable features noted in the literature. PF was identified between 48° and 52°S along 45°E, where the surface temperature reduced from 5.5 to 2.7°C and where the northern limit of sub-surface temperature minimum layer (<2°C) is extended. This study reveals a southward shift of the oceanic fronts (STF and SAF) from west to east, with a maximum southward displacement of ~4° latitude for STF. The thermocline region was absent south of PF. An enhancement in the mixed layer thickness from 42° to 52°S occurred in association with the strengthening of the wind forcing. The presents of major watermasses like Subtropical Surface Water, Subantarctic Surface Water, Mode Water, Antarctic Intermediate Water, Circumpolar Deep Water and Antarctic Bottom Water were identified along the 45°E meridional section. Upper-ocean heat-content computation revealed a remarkable drop of 989 ×10 J/m (~42°S) and 1405 × 10 J/m (~44°S) along 45° and 57°30’E, respectively. This sudden drop in heat content in turn affects the meridional heat transfer which is crucial for the studies related to global climatic variability.