Miracle-dz/UniFAR-FTUs huggingface dataset:
Scrub Typhus, a Disease with Increasing Threat in Guangdong, China

There has been a rapid increase in the number of scrub typhus cases in Guangdong Province, China. For this reason, an epidemiologic study was conducted to understand the characteristics of scrub typhus epidemics in Guangdong. From 2006 to 2013, the incidence of human cases increased from 0.4321 to 3.5917 per 100,000 with a bimodal peak in human cases typically occurring between May and November. To detect the prevalence of Orientia tsutsugamushi among suspected human cases and rodents, we performed ELISA tests of IgM/IgG and nested PCR tests on 59 whole blood samples from the suspected cases and 112 spleen samples from the rodents. Suspected cases tested positive for anti-O. tsutsugamushi IgM and IgG 66.1% (39/59) and 50.8% (30/59) of the time, respectively. Additionally, 20.3% (12/59) of blood samples and 13.4% (15/112) of spleen samples were positive for PCR. Phylogenetic analysis revealed that there were four definable clusters among the 27 nucleotide sequences of the 56-kDa antigen genes: 44.4% Karp (12/27), 25.9% Kato (7/27), 22.2% Gilliam (6/27) and 7.4% TA763 (2/27). We concluded many suspected cases may result in diagnostic errors; therefore, it is necessary to perform laboratory tests on suspected cases in hospitals. The high infection rate of O. tsutsugamushi among the limited rodents tested suggested that further rodent sampling throughout the province is necessary to further define high-risk areas. Furthermore, the multiple co-circulating genotypes of O. tsutsugamushi play a key role in the pervasiveness of scrub typhus in the Guangdong area.
Contributions of qualitative research to evidence-based practice in nursing.

AIM This article aims to identify the contributions of qualitative research to evidence-based practice in nursing. BACKGROUND Qualitative research dates back to the 1920s and 1930s, when anthropologists and sociologists used qualitative research methods to study human phenomena in naturalistic settings and from a holistic viewpoint. Afterwards, other subject matters, including nursing, adopted qualitative methods to answer their research questions. The restructuring of health care over the past decade has brought about increased accountability in nursing research. One method for increasing this accountability is evidence-based practice. METHOD The method used was a search in the Cumulative Index to Nursing and Allied Health Literature database from 1999-present. The search resulted in 61 citations for evidence-based practice in nursing research; however, only 5 citations focused on evidence-based practice and qualitative research. FINDINGS The authors' findings revealed six contributions of qualitative research to evidence-based practice: generation of hypotheses; development and validation of instruments; provision of context for evaluation; development of nursing interventions; development of new research questions; and application of Qualitative Outcome Analysis. CONCLUSION Qualitative research makes important contributions to the quality of evidence-based practice.
RORα Regulates Multiple Aspects of Dendrite Development in Cerebellar Purkinje Cells In Vivo

The establishment of cell-type-specific dendritic arbors is fundamental for proper neural circuit formation. Here, using temporal- and cell-specific knock-down, knock-out, and overexpression approaches, we show that multiple aspects of the dendritic organization of cerebellar Purkinje cells (PCs) are controlled by a single transcriptional factor, retinoic acid-related orphan receptor-alpha (RORα), a gene defective in staggerer mutant mice. As reported earlier, RORα was required for regression of primitive dendrites before postnatal day 4 (P4). RORα was also necessary for PCs to form a single Purkinje layer from P0 to P4. The knock-down of RORα from P4 impaired the elimination of perisomatic dendrites and maturation of single stem dendrites in PCs at P8. Filopodia and spines were also absent in these PCs. The knock-down of RORα from P8 impaired the formation and maintenance of terminal dendritic branches of PCs at P14. Finally, even after dendrite formation was completed at P21, RORα was required for PCs to maintain dendritic complexity and functional synapses, but their mature innervation pattern by single climbing fibers was unaffected. Interestingly, overexpression of RORα in PCs at various developmental stages did not facilitate dendrite development, but had specific detrimental effects on PCs. Because RORα deficiency during development is closely related to the severity of spinocerebellar ataxia type 1, delineating the specific roles of RORα in PCs in vivo at different time windows during development and throughout adulthood would facilitate our understanding of the pathogenesis of cerebellar disorders. SIGNIFICANCE STATEMENT The genetic programs by which each neuron subtype develops and maintains dendritic arbors have remained largely unclear. This is partly because dendrite development is modulated dynamically by neuronal activities and interactions with local environmental cues in vivo. In addition, dendrites are formed and maintained by the balance between their growth and regression; the effects caused by the disruption of transcription factors during the early developmental stages could be masked by dendritic growth or regression in the later stages. Here, using temporal- and cell-specific knock-down, knock-out, and overexpression approaches in vivo, we show that multiple aspects of the dendritic organization of cerebellar Purkinje cells are controlled by a single transcriptional factor, retinoic acid-related orphan receptor alpha.
Tell me more designing HRI to encourage more trust, disclosure, and companionship

Previous HRI research has established that trust, disclosure, and a sense of companionship lead to positive outcomes. In this study, we extend existing work by exploring behavioral approaches to increasing these three aspects of HRI. We increased the expressivity and vulnerability of a robot and measured the effects on trust, disclosure, and companionship during human-robot interaction. We engaged (N = 61) high school aged students in a 2 (vulnerability of robot: high vs. low) × 2 (expressivity of robot: high vs. low) between-subjects study where participants engaged in a short electronics learning activity with a robotic tutor. Our results show that students had more trust and feelings of companionship with a vulnerable robot, and reported disclosing more with an expressive robot. Additionally, we found that trust mediated the relationship between vulnerability and companionship. These findings suggest that vulnerability and expressivity may improve peoples' relationships with robots, but that they each have different effects.
RFI Mitigation in Microwave Radiometry Using Wavelets

The performance of microwave radiometers can be seriously degraded by the presence of radio-frequency interference (RFI). Spurious signals and harmonics from lower frequency bands, spread-spectrum signals overlapping the “protected” band of operation, or out-of-band emissions not properly rejected by the pre-detection filters due to the finite rejection modify the detected power and the estimated antenna temperature from which the geophysical parameters will be retrieved. In recent years, techniques to detect the presence of RFI have been developed. They include time- and/or frequency domain analyses, or statistical analysis of the received signal which, in the absence of RFI, must be a zero-mean Gaussian process. Current mitigation techniques are mostly based on blanking in the time and/or frequency domains where RFI has been detected. However, in some geographical areas, RFI is so persistent in time that is not possible to acquire RFI-free radiometric data. In other applications such as sea surface salinity retrieval, where the sensitivity of the brightness temperature to salinity is weak, small amounts of RFI are also very difficult to detect and mitigate. In this work a wavelet-based technique is proposed to mitigate RFI (cancel RFI as much as possible). The interfering signal is estimated by using the powerful denoising capabilities of the wavelet transform. The estimated RFI signal is then subtracted from the received signal and a “cleaned” noise signal is obtained, from which the power is estimated later. The algorithm performance as a function of the threshold type, and the threshold selection method, the decomposition level, the wavelet type and the interferenceto-noise ratio is presented. Computational requirements are evaluated in terms of quantization levels, number of operations, memory requirements (sequence length). Even though they are high for today’s technology, the algorithms presented can be applied to recorded data. The results show that even RFI much larger than the noise signal can be very effectively mitigated, well below the noise level.
Restoration ecology of Acacia pachyceras in the State of Kuwait

The purpose of this research was to evaluate the nodulation potential, seedling growth, and nutrition of Acacia gerrardii when inoculated with two commercial inoculum Rhizobiumleguminosarum ATCC and Bradyrhizobium sp. ATCC under greenhouse conditions. The characteristics of Kuwait soil with high gypsum and salt content and low clay and organic content makes the land deficient in plant available nutrients. Consequently, there is a need to improve soil fertility to protect and restore the only native plants Acacia gerrardii of Kuwait. In this present greenhouse study, Acacia gerrardii seedlings were inoculated with two commercial inoculum, and the nodulation capacity, nitrogen content, and growth performance of the seedlings were evaluated. The successful nodulation on Acacia gerrardii roots by Rhizobium leguminosarum ATCC and Bradyrhizobium sp. ATCC has occurred and confirmed that these two commercial inoculum have the ability to infect and establish nodulation with Acacia gerrardii. Our results also show improved seedling nutrition when inoculated with commercial inoculum. Further research is required to investigate the nitrogen fixation capacity of this commercial inoculum before using it in a large-scale inoculation program. However, our preliminary results suggest that these two commercial inoculum could be useful when used at optimum application rates of bacterial inoculum in inoculation programs to increase the growth and nutrition of Acacia gerrardii.
Afferent Deprivation Elicits a Transcriptional Response Associated with Neuronal Survival after a Critical Period in the Mouse Cochlear Nucleus

The mechanisms underlying enhanced plasticity of synaptic connections and susceptibilities to manipulations of afferent activity in developing sensory systems are not well understood. One example is the rapid and dramatic neuron death that occurs after removal of afferent input to the cochlear nucleus (CN) of young mammals and birds. The molecular basis of this critical period of neuronal vulnerability and the transition to survival independent of afferent input remains to be defined. Here we used microarray analyses, real-time reverse transcription PCR, and immunohistochemistry of the mouse CN to show that deafferentation results in strikingly different sets of regulated genes in vulnerable [postnatal day (P) 7] and invulnerable (P21) CN. An unexpectedly large set of immune-related genes was induced by afferent deprivation after the critical period, which corresponded with glial proliferation over the same time frame. Apoptotic gene expression was not highly regulated in the vulnerable CN after afferent deprivation but, surprisingly, did increase after deafferentation at P21, when all neurons ultimately survive. Pharmacological activity blockade in the eighth nerve mimicked afferent deprivation for only a subset of the afferent deprivation regulated genes, indicating the presence of an additional factor not dependent on action potential-mediated signaling that is also responsible for transcriptional changes. Overall, our results suggest that the cell death machinery during this critical period is mainly constitutive, whereas after the critical period neuronal survival could be actively promoted by both constitutive and induced gene expression.
Interactive Visualizations of Video Tours in Space and Time

Videos and movies are increasingly being created, shared and accessed from different platforms and devices, that are supporting georeferencing as a form to enrich their contextualization, demanding for new and more powerful ways to search, browse and view them. An effective access to video is very challenging due to the amount of items available and their inner complexity. Interactive visualization, in complement to video cataloguing, can help to handle this challenge, making information more accessible and useful. Moreover, it is worth doing this navigation ludic, and aesthetically interesting, while providing new ways to search and filter through their properties and their impact on the users. In previous work we focused on the temporal dimension in movies and videos in a way that is possible to explore and access them through time, genre and rating criteria, and inside their contents regarding image, movement, audio, subtitles and emotions. We are now extending our goal by considering the spatial dimension, through trajectories like the ones we find in city tours. We present the design of the main interactive visualizations for navigating georeferenced videos, allowing the user to 1) overview videos shot in a given geographic location in a given moment of time; 2) zoom in the trajectories of individual videos, e.g. by length, speed, age and content of the shootings; 3) access and watch each video content in a specific trajectory, e.g. through color, sound, spoken words, emotions and neighbor connections.
Regional InfoHubs by vehicles: balancing spatio-temporal coverage and network load

The growing ubiquity of on-board wireless communication devices in vehicles is steadily opening up new possibilities of vehicular networks. In this paper, we design a framework to utilize radio-equipped cars as regional information hubs, which periodically disseminate public regional information (e.g., advertisements, travel tips, emergency info, etc.) over a designated geographical area in a city. The cars driving in the designated area repeatedly broadcast the data messages, allowing other drivers and pedestrians to passively obtain the information with their on-board wireless devices and/or smartphones. Although the idea follows a natural extension of the current capability of vehicular networks, vehicle densities in urban areas are typically highly non-uniform both in time and space, making it difficult to robustly disseminate data messages with minimal network load. We tackle this issue by introducing a probabilistic framework to intelligently adapt message dissemination strategy. Analyzing location broadcast messages, which are periodically exchanged among vehicles for safety applications, our protocol predicts future locations of neighboring radio-equipped vehicles and dynamically adjusts probability of message transmissions at each moment to suppress redundant network traffic. Simulation results show that our protocol can reduce the total amount of redundant message transmissions by up to 78%, while maintaining the spatio-temporal coverage of message dissemination.
Improving Dynamic Scaling Performance of Cassandra

Load size for a service on the Internet changes remarkably every hour. Thus, it is expected for service system scales to change dynamically according to load size. KVS (key-value store) is a scalable DBMS (database management system) widely used in largescale Internet services. In this paper, we focus on Cassandra, a popular open-source KVS implementation, and discuss methods for improving dynamic scaling performance. First, we evaluate node joining time, which is the time to complete adding a node to a running KVS system, and show that its bottleneck process is disk I/O. Second, we analyze disk accesses in the nodes and indicate that some heavily accessed files cause a large number of disk accesses. Third, we propose two methods for improving elasticity, which means decreasing node adding and removing time, of Cassandra. One method reduces disk accesses significantly by keeping the heavily accessed file in the page cache. The other method optimizes I/O scheduler behavior. Lastly, we evaluate elasticity of our methods. Our experimental results demonstrate that the methods can improve the scaling-up and scaling-down performance of Cassandra. key words: KVS, key-value store, Cassandra, page cache
Electrocardiography system of twelve leads for the study of the spatial variability of ventricular repolarization intervals

This work describes the design and operation of a electrocardiograph capable of acquiring simultaneous recordings of 12-lead for the study of the spatial variability of ventricular repolarization intervals. The electrocardiography system consists of an acquisition module with a dedicated channel for each lead with a circuit for detection of lead failure. Each channel has a gain of 1000, a CMRR of 90 dB and a bandwidth of 0.05 Hz to 150 Hz. It uses a isolated power supply and high isolation amplifiers at the output system. An additional stage of programmable amplification is added for signals conditioning before being acquired by the computer. The communication between these systems is by the USB port using a commercial data acquisition system (ADS) model Ni-USB 6211 with a resolution of 16 bits. The system display the 12-lead with a interface developed in LabVIEW and the data can be stored in ¿. xls files¿ for later processing.
Assignment of Neisseria meningitidis Serogroups A, C, W135, and Y Anticapsular Total Immunoglobulin G (IgG), IgG1, and IgG2 Concentrations to Reference Sera

ABSTRACT Meningococcal serogroup-specific immunoglobulin G (IgG), IgG1, and IgG2 concentrations were assigned to three reference sera, CDC 1992, 89-SF, and 96/562, for meningococcal serogroups A, C, Y, and W135 via the method of cross standardization. The sum of the serogroup-specific IgG1 and IgG2 concentrations determined for the four meningococcal serogroups showed good agreement with the serogroup-specific IgG either determined here or as previously represented. Following the assignment of meningococcal serogroup-specific IgG1 and IgG2 concentration to these reference sera, a meningococcal serogroup-specific IgG1 and IgG2 enzyme-linked immunosorbent assay protocol was developed. The serogroup A and C specific subclass distribution of a panel of adult sera collected following vaccination with any combination of meningococcal serogroup C conjugate, bivalent, or tetravalent polysaccharide vaccines was determined. For the determination of serogroup W135 and Y specific subclass distribution, an adolescent panel 28 days following a single dose of either tetravalent polysaccharide or conjugate vaccine was used. The sum of the serogroup-specific IgG1 and IgG2 showed strong correlation with the serogroup-specific total IgG determined. The assignment here of IgG1 and IgG2 subclasses to these reference sera will allow more detailed evaluation of meningococcal conjugate and polysaccharide vaccines.
Anomaly Detection using Feature Selection and SVM Kernel Trick

Analysis of system security becomes a major task for researchers. Intrusion detection plays a vital role in the security domain in these days, Internet usage has been increased enormously and with this, the threat to system resources has also increased. Anomaly based intrusion changes its behaviour dynamically, to detect these types of intrusions need to adopt the novel approaches are required. Detection of intrusion is very important at the same time both accuracy and speed are imperative factors in the real environment. Analyzing intrusive behaviour of the network data is crucial because it contains huge amounts of data as well as the dimensions of the data are also a problem to researchers in detecting intrusive behaviour. In this paper rough set theory is used for the dimensional reduction and the feature selection. Once feature selection is done, Support Vector Machines (SVM) is used to classify the reduct data by using kernel trick. SVM works based on the structural risk minimization principle. It classifying the data in the faster manner with more accuracy to detect the intruder, here we achieved better results than existing techniques.
Exploiting formalin‐preserved fish specimens for resources of DNA barcoding

With the development of the DNA barcoding project, a large number of specimens are required to establish the library of reference barcode. Formalin‐fixed samples from museums provide a potential resource for it. However, recovery of DNA and amplification of the target gene from formalin‐fixed samples are challenging. In this study, a hot alkali pre‐treatment accompanied by the use of cetyltrimethylammonium bromide (CTAB) method was employed for DNA recovery from formalin‐preserved samples, with the purpose of pursuing the optimal condition for high quantity and quality of DNA and minimizing PCR inhibition. Meanwhile, a semi‐nested PCR‐based method was developed to enhance the efficacy of amplification. This advanced protocol was demonstrated to be reliable and effective. Even for 23‐year‐old samples, genomic DNA could be extracted, and COI gene was correctly sequenced.
Conceptual Modelling as the Core of the Information Systems Discipline - Perspectives and Epistemological Challenges

In this paper we argue that conceptual modeling is well suited to define a convincing profile for the information systems discipline. Different from empirical research, conceptual modeling should not only represent existing domains. To fully exploit the potential offered by information technology, conceptual models should also represent constructions of future reality. While such an approach is promising substantial benefits, it is accompanied by severe epistemological challenges. Rational discourses are about the only chance to deal with these challenges - although they do not offer a convincing solution. However, without facing this problem, the field of conceptual modeling is nothing more than a playground for inventing artifacts.
Exploring performance of clustering methods on document sentiment analysis

Clustering is a powerful unsupervised tool for sentiment analysis from text. However, the clustering results may be affected by any step of the clustering process, such as data pre-processing strategy, term weighting method in Vector Space Model and clustering algorithm. This paper presents the results of an experimental study of some common clustering techniques with respect to the task of sentiment analysis. Different from previous studies, in particular, we investigate the combination effects of these factors with a series of comprehensive experimental studies. The experimental results indicate that, first, the K-means-type clustering algorithms show clear advantages on balanced review datasets, while performing rather poorly on unbalanced datasets by considering clustering accuracy. Second, the comparatively newly designed weighting models are better than the traditional weighting models for sentiment clustering on both balanced and unbalanced datasets. Furthermore, adjective and adverb words extraction strategy can offer obvious improvements on clustering performance, while strategies of adopting stemming and stopword removal will bring negative influences on sentiment clustering. The experimental results would be valuable for both the study and usage of clustering methods in online review sentiment analysis.