Miracle-dz/UniFAR-FTUs huggingface dataset:
DBSTC: an effective method for discovering cluster features with different spatiotemporal densities

ABSTRACT Spatiotemporal clustering is one of the most advanced research topics in geospatial data mining. It has been challenging to discover cluster features with different spatiotemporal densities in geographic information data set. This paper presents an effective density-based spatiotemporal clustering algorithm (DBSTC). First, we propose a method to measure the degree of similarity of a core point to the geometric center of its spatiotemporal reachable neighborhood, which can effectively solve the isolated noise point misclassification problem that exists in the shared nearest neighbor methods. Second, we propose an ordered reachable time window distribution algorithm to calculate the reachable time window for each spatiotemporal point in the data set to solve the problem of different clusters with different temporal densities. The effectiveness and advantages of the DBSTC algorithm are demonstrated in several simulated data sets. In addition, practical applications to seismic data sets demonstrate the capability of the DBSTC algorithm to uncover clusters of foreshocks and aftershocks and help to improve the understanding of the underlying mechanisms of dynamic spatiotemporal processes in digital earth.
Cryosurgery for the treatment of cutaneous sporotrichosis in four pregnant women

Background Pregnant women with sporotrichosis should not receive systemic antifungal therapy except in severe cases when amphotericin B is recommended. Thermotherapy is the most reported treatment described in this group of patients. It entails weeks of daily self-application of heat to the lesions, requires that the patient faithfully apply it, and it could cause skin burns. Cryosurgery is a useful therapeutic tool for many cutaneous infectious diseases, safe for pregnant women, but not well evaluated for sporotrichosis treatment in this group. Methodology The authors conducted a retrospective study describing epidemiological, clinical, and therapeutic data related to four pregnant patients with sporotrichosis treated with cryosurgery. The authors reviewed the clinical records of four pregnant patients diagnosed with cutaneous sporotrichosis and treated with cryosurgery. The sessions were carried out monthly up to clinical cure. Molecular identification of the Sporothrix species was performed in two cases using T3B PCR fingerprinting assays. Principal findings All patients were in the second trimester of pregnancy and their age ranged from 18 to 34 years. With regard to clinical presentation, two patients had lymphocutaneous and two had the fixed form. S. brasiliensis was identified in two cases as the causative agent. Cryosurgery was well tolerated and the number of sessions ranged from 1 to 3. All the patients reached a complete clinical cure. Conclusions Cryosurgery was a safe, easy to perform and well tolerated method, and therefore it is suggested to be a suitable option for the treatment of cutaneous sporotrichosis in pregnant women.
InfraNodus: Generating Insight Using Text Network Analysis

In this paper we present a web-based open source tool and a method for generating insight from any text or discourse using text network analysis. The tool (InfraNodus) can be used by researchers and writers to organize and to better understand their notes, to measure the level of bias in discourse, and to identify the parts of the discourse where there is a potential for insight and new ideas. The method is based on text network analysis algorithm, which represents any text as a network and identifies the most influential words in a discourse based on the terms' co-occurrence. Graph community detection algorithm is then applied in order to identify the different topical clusters, which represent the main topics in the text as well as the relations between them. The community structure is used in conjunction with other measures to identify the level of bias or cognitive diversity of the discourse. Finally, the structural gaps in the graph can indicate the parts of the discourse where the connections are lacking, therefore highlighting the areas where there's a potential for new ideas. The tool can be used as stand-alone software by end users as well as implemented via an API into other tools. Another interesting application is in the field of recommendation systems: structural gaps could indicate potentially interesting non-trivial connections to any connected datasets.
Project PBerry: FPGA Acceleration for Remote Memory

Recent research efforts propose remote memory systems that pool memory from multiple hosts. These systems rely on the virtual memory subsystem to track application memory accesses and transparently offer remote memory to applications. We outline several limitations of this approach, such as page fault overheads and dirty data amplification. Instead, we argue for a fundamentally different approach: leverage the local host's cache coherence traffic to track application memory accesses at cache line granularity. Our approach uses emerging cache-coherent FPGAs to expose cache coherence events to the operating system. This approach not only accelerates remote memory systems by reducing dirty data amplification and by eliminating page faults, but also enables other use cases, such as live virtual machine migration, unified virtual memory, security and code analysis. All of these use cases open up many promising research directions.
Effect of Heat Treatment on Microstructure and Properties of Clad Plates 316L/Q370qE

Mechanical properties of Q370qE carbon steel can be improved by cladding it with 316L stainless steel. After rolling these materials together, microstructure, hardness, shear strength, and corrosion properties of the cladded metals were evaluated. Hardness and shear tests were performed according to appropriate standards to evaluate the bonds. The results show that the remarkable diffusion of Ni and Cr formed a hard transition zone. The width of this diffusion zone increases with increasing temperature. The shear strength of the clad interface reached a minimum of 385 MPa. In addition, the surfaces of samples were examined by neutral salt spray (NSS) tests and potentiodynamic polarization tests to examine corrosion behavior. The 316L side primarily exhibited pitting corrosion, while the Q370qE side was dominated by uniform corrosion.
Parallel edge-based sampling for static and dynamic graphs

Graph sampling is an important tool to obtain small and manageable subgraphs from large real-world graphs. Prior research has shown that Induced Edge Sampling (IES) outperforms other sampling methods in terms of the quality of subgraph obtained. Even though fast sampling is crucial for several workflows, there has been little work on parallel sampling algorithms in the past. In this paper, we present parIES - a framework for parallel Induced Edge Sampling on shared-memory parallel machines. parIES, equipped with optimized load balancing and synchronization avoiding strategies, can sample both static and streaming dynamic graphs, while achieving high scalability and parallel efficiency. We develop a lightweight concurrent hash table coupled with a space-efficient dynamic graph data structure to overcome the challenges and memory constraints of sampling streaming dynamic graphs. We evaluate parIES on a 16-core (32 threads) Intel server using 7 large synthetic and real-world networks. From a static graph, parIES can sample a subgraph with > 1.4B edges in < 2.5s and achieve upto 15.5X parallel speedup. For dynamic streaming graphs, parIES can process upto 86.7M edges per second achieving 15X parallel speedup.
Brain Inspired Dynamic System for the Quality of Service Control over the Long-Haul Nonlinear Fiber-Optic Link

Brain-inspired intelligence using the cognitive dynamic system (CDS) concept is proposed to control the quality-of-service (QoS) over a long-haul fiber-optic link that is nonlinear and with non-Gaussian channel noise. Digital techniques such as digital-back-propagation (DBP) assume that the fiber optic link parameters, such as loss, dispersion, and nonlinear coefficients, are known at the receiver. However, the proposed CDS does not need to know about the fiber optic link physical parameters, and it can improve the bit error rate (BER) or enhance the data rate based on information extracted from the fiber optic link. The information extraction (Bayesian statistical modeling) using intelligent perception processing on the received data, or using the previously extracted models in the model library, is carried out to estimate the transmitted data in the receiver. Then, the BER is sent to the executive through the main feedback channel and the executive produces actions on the physical system/signal to ensure that the BER is continuously under the forward-error-correction (FEC) threshold. Therefore, the proposed CDS is an intelligent and adaptive system that can mitigate disturbance in the fiber optic link (especially in an optical network) using prediction in the perceptor and/or doing proper actions in the executive based on BER and the internal reward. A simplified CDS was implemented for nonlinear fiber optic systems based on orthogonal frequency division multiplexing (OFDM) to show how the proposed CDS can bring noticeable improvement in the system’s performance. As a result, enhancement of the data rate by 12.5% and the Q-factor improvement of 2.74 dB were achieved in comparison to the conventional system (i.e., the system without smart brain).
Mitochondrial A3243G mutation causes mitochondrial encephalomyopathy in a Chinese patient

Rationale: Mitochondrial mutations are associated with a wide spectrum of clinical abnormalities. More than half of these mutations are distributed in the 22 mitochondrial tRNA genes, including tRNALeu(UUR). In particular, the A3243G mutation in the tRNALeu(UUR) gene causes mitochondrial encephalomyopathy. Patient concerns: A 12-year-old boy was admitted to Shaoxing People's Hospital because there is a reduction in the volume of speech, dysphonia, unable to write, recognize words, and unable to wear clothes, accompanied by unstable walking after treatment of unexplained fever and somnolence. Diagnoses: The proband underwent a thorough examination in our hospital and was diagnosed as mitochondrial encephalomyopathy. The proband carried the pathogenic heteroplasmic mutation A3243G mutation in mitochondrial 12S rRNA gene. Although his parents did not carry the mutation. Interventions: Intravenous acyclovir, ceftriaxone, and dexamethasone were used for the patient's antiviral, antimicrobial, and anti-inflammatory therapy, respectively. Intravenous mannitol was gradually tapered for reducing intracranial pressure with furosemide for inducing diuresis. Intravenous arginine could help to treat alkalosis and supple some essential amino acids. Oral oxiracetam capsules, vitamin B1, and coenzyme Q10 were used for providing nutrition and improving energy. His medications were 30 mg vitamin B1, 0.1 g vitamin C, and mecobalamin 750 &mgr;g daily after discharge from our hospital. Outcomes: The patient was able to walk and talk slowly with improved writing skills and no stroke-like episodes. The neurological examination was negative and muscle tension was identified as grade V. Lessons: Mitochondrial encephalomyopathy has different phenotypes, in addition to traditional examinations, it is important for clinicians to be familiar with genetic testing methodology as well as applications of these tests in clinic to get an accurate diagnosis.
Variable Influences of Water Availability and Rhizobacteria on the Growth of Schizachyrium scoparium (Little Bluestem) at Different Ages

There is significant interest in understanding the role of plant growth-promoting rhizobacteria (PGPR) in alleviating different types of plant stress. Schizachyrium scoparium (little bluestem) is a moderately drought tolerant, perennial bunchgrass native to North America. The goal of this experiment was to evaluate whether the addition of a bacterial root isolate in the Pseudomonas genus promoted the growth of S. scoparium with changes in water availability. Pseudomonas are common rhizobacteria and have been shown to improve plant growth. It was hypothesized that plants inoculated with the PGPR strain would have greater growth and health, and would be less affected by shifts in water availability. Pseudomonas strains were isolated from the roots of native S. scoparium plants. After germination, S. scoparium seedlings were subjected to four treatment groups: low water; high water; low water with PGPR; and high water with PGPR. The experiment was run three times with plants at different starting ages; 14-, 28-, and 70-day-old plants. The effects of the water and PGPR treatments were variable between the experimental trials. There were no significant effects of the water treatments on plant growth in Trial 1 (14-day-old plants) or Trial 2 (28-day-old plants), however, there was a significant negative effect of the high watering treatment on the shoot length and biomass in Trial 3. High water availability was significantly associated with greater plant health in Trial 1, but appeared to reduce plant health in Trials 2 and 3. The PGPR treatment appeared to promote root growth and biomass in Trial 2, and was associated with greater plant health in all three trials, especially when paired with the low water treatment. Results from a permutational MANOVA indicate that plant growth was significantly different between the trials due to differences in the starting age of the plants and the duration of the experiments. Thus, methodological choices, such as plant life history stage and experiment duration, may affect the response of plants to PGPR in the rhizosphere. This research provides an insight into the interactions between PGPR and water availability on the growth and health of native plants.
Analysis of Ephemeris Errors in Autonomous Celestial Navigation during Mars Approach Phase

A Celestial Navigation System (CNS) is a feasible and economical autonomous navigation system for deep-space probes. Ephemeris errors have a great influence on the performance of CNSs during the Mars approach phase, but there are few research studies on this problem. In this paper, the analysis shows that the ephemeris error of Mars is slowly-varying, while the ephemeris error of Phobos and Deimos is periodical. The influence of the ephemeris errors of Mars and its satellites is analysed in relation to both the Sun-centred frame and the Mars-centred frame. The simulations show that the position error of a probe relative to the Sun caused by the Mars ephemeris error is almost equal to the ephemeris error itself, that the velocity error is affected slightly, and that the position and velocity relative to Mars are hardly affected. The navigation result of a Mars probe is also greatly affected by the quantities and periodicities of the ephemeris errors of Phobos and Deimos, especially that of Deimos.
Molecular phylogeny of Old World monkeys (Cercopithecidae) as inferred from gamma-globin DNA sequences.

DNA sequence data of the nuclear-encoded gamma1-gamma2-globin duplication region were used to examine the phylogenetic relationships of 16 cercopithecid (Old World monkey) species representing 12 extant genera. Morphology- and molecular-based hypotheses of Old World monkey branching patterns are generally congruent, except for generic relationships within the subtribe Papionina. The cercopithecids divide into colobines (leaf-eating monkeys) and cercopithecines (cheek-pouched monkeys). The colobines examined by the DNA data divide into an Asian clade (Nasalis, proboscis monkeys; Trachypithecus, langurs) and an African clade (Colobus, colobus monkeys). The cercopithecines divide into tribes Cercopithecini (Erythrocebus, patas monkey; Chlorocebus, green monkeys; Cercopithecus, guenons) and Papionini. Papionins divide into subtribes Macacina (Macaca, macaques) and Papionina (Papio, hamadryas baboons; Mandrillus, drills and mandrills; Theropithecus, gelada baboons; Lophocebus, arboreal mangabeys; Cercocebus, terrestrial mangabeys). In a morphologically based classification, Mandrillus is a subgenus of Papio, whereas Lophocebus is a subgenus of Cercocebus. In contrast, the molecular evidence treats Mandrillus as a subgenus of Cercocebus, and treats both Theropithecus and Lophocebus as subgenera of Papio. Local molecular clock divergence time estimates were used as a yardstick in a "rank equals age" system to propose a reduction in taxonomic rank for most clades within Cercopithecidae.
Silicon Quantum Dot Light Emitting Diode at 620 nm

Here we report a quantum dot light emitting diode (QLED), in which a layer of colloidal silicon quantum dots (SiQDs) works as the optically active component, exhibiting a strong electroluminescence (EL) spectrum peaking at 620 nm. We could not see any fluctuation of the EL spectral peak, even in air, when the operation voltage varied in the range from 4 to 5 V because of the possible advantage of the inverted device structure. The pale-orange EL spectrum was as narrow as 95 nm. Interestingly, the EL spectrum was narrower than the corresponding photoluminescence (PL) spectrum. The EL emission was strong enough to be seen by the naked eye. The currently obtained brightness (∼4200 cd/m2), the 0.033% external quantum efficiency (EQE), and a turn-on voltage as low as 2.8 V show a sufficiently high performance when compared to other orange-light-emitting Si-QLEDs in the literature. We also observed a parasitic emission from the neighboring compositional layer (i.e., the zinc oxide layer), and its intensity increased with the driving voltage of the device.
Studying User Satisfaction with the MOOC Platform Interfaces Using the Example of Coursera and Open Education Platforms

The advantages of online courses over traditional education lie in the availability of individual training programs, but now the problem of involving and keeping students on the course is urgent for MOOC. Thus, despite the fact that test results on the reasons for unsuccessful completion of online courses by students are different, one of the identified factors was the interface design, while the problem of the influence of the interface on users is not adequately studied. In the present paper, a methodology for studying two different MOOC online platforms was developed, in order to identify factors that are more favorable for user convenience, as well as to identify the best design solutions. A comparative analysis of two MOOC platforms (Coursera and Open Education) made it possible to identify the best behavioral patterns and understand which details of the design of the online platform should be paid attention to and which should not. After carrying out a theoretical analysis and forming the methodology of work, as well as performing an experiment, recommendations were formulated for the development of the user interface of the Open Education platform.
Rapid Differentiation of Cryptic Species within Cryptococcus gattii by a Duplex PCR Assay

ABSTRACT Cryptococcus gattii consists of four cryptic species, VGI, VGII, VGIII, and VGIV. Herein, a duplex PCR assay using two primer pairs targeting the vacuolar membrane gene and the intergenic spacer region was developed. It successfully distinguished the cryptic species according to the distinct size of the amplicons.
Differences in Health News from Reliable and Unreliable Media

The spread of ‘fake’ health news is a big problem with even bigger consequences. In this study, we examine a collection of health-related news articles published by reliable and unreliable media outlets. Our analysis shows that there are structural, topical, and semantic patterns which are different in contents from reliable and unreliable media outlets. Using machine learning, we leverage these patterns and build classification models to identify the source (reliable or unreliable) of a health-related news article. Our model can predict the source of an article with an F-measure of 96%. We argue that the findings from this study will be useful for combating the health disinformation problem.
NIFify: Towards Better Quality Entity Linking Datasets

The Entity Linking (EL) task identifies entity mentions in a text corpus and associates them with a corresponding unambiguous entry in a Knowledge Base. The evaluation of EL systems relies on the comparison of their results against gold standards. A common format used to represent gold standard datasets is the NLP Interchange Format (NIF), which uses RDF as a data model. However, creating gold standard datasets for EL is a time-consuming and error-prone process. In this paper we propose a tool called NIFify to help manually generate, curate, visualize and validate EL annotations; the resulting tool is useful, for example, in the creation of gold standard datasets. NIFify also serves as a benchmark tool that enables the assessment of EL results. Using the validation features of NIFify, we further explore the quality of popular EL gold standards.
Learning Influence Probabilities and Modelling Influence Diffusion in Twitter

Influence diffusion has been widely studied in social networks for applications such as service promotion and marketing. There are two challenging issues here: (1) how we measure people’s influence on others; (2) how we predict whom would be influenced by a particular person and when people would be influenced. Existing works have not captured the temporal and structural characteristics of influence diffusion in Twitter. In this paper, we firstly develop a model to learn influence probabilities between users in Twitter from their action history; secondly, we introduce diffusion models that are used to predict how information is propagated in Twitter. Experiment results show that our proposed models outperform existing models in terms of the balanced precision and recall.
Application‐Specific Tone Mapping Via Genetic Programming

High dynamic range (HDR) imagery permits the manipulation of real‐world data distinct from the limitations of the traditional, low dynamic range (LDR), content. The process of retargeting HDR content to traditional LDR imagery via tone mapping operators (TMOs) is useful for visualizing HDR content on traditional displays, supporting backwards‐compatible HDR compression and, more recently, is being frequently used for input into a wide variety of computer vision applications. This work presents the automatic generation of TMOs for specific applications via the evolutionary computing method of genetic programming (GP). A straightforward, generic GP method that generates TMOs for a given fitness function and HDR content is presented. Its efficacy is demonstrated in the context of three applications: Visualization of HDR content on LDR displays, feature mapping and compression. For these applications, results show good performance for the generated TMOs when compared to traditional methods. Furthermore, they demonstrate that the method is generalizable and could be used across various applications that require TMOs but for which dedicated successful TMOs have not yet been discovered.