Miracle-dz/UniFAR-FTUs huggingface dataset:
Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid

Metagenomic next-generation sequencing (mNGS) for pan-pathogen detection has been successfully tested in proof-of-concept case studies in patients with acute illness of unknown etiology, but to date has been largely confined to research settings. Here we developed and validated an mNGS assay for diagnosis of infectious causes of meningitis and encephalitis from cerebrospinal fluid (CSF) in a licensed clinical laboratory. A clinical bioinformatics pipeline, SURPI+, was developed to rapidly analyze mNGS data, automatically report detected pathogens, and provide a graphical user interface for evaluating and interpreting results. We established quality metrics, threshold values, and limits of detection of between 0.16 – 313 genomic copies or colony forming units per milliliter for each representative organism type. Gross hemolysis and excess host nucleic acid reduced assay sensitivity; however, a spiked phage used as an internal control was a reliable indicator of sensitivity loss. Diagnostic test accuracy was evaluated by blinded mNGS testing of 95 patient samples, revealing 73% sensitivity and 99% specificity compared to original clinical test results, with 81% positive percent agreement and 99% negative percent agreement after discrepancy analysis. Subsequent mNGS challenge testing of 20 positive CSF samples prospectively collected from a cohort of pediatric patients hospitalized with meningitis, myelitis, and/or encephalitis showed 92% sensitivity and 96% specificity relative to conventional microbiological testing of CSF in identifying the causative pathogen. These results demonstrate the analytic performance of a laboratory-validated mNGS assay for pan-pathogen detection, to be used clinically for diagnosis of neurological infections from CSF.
Attention is required for knowledge-based sequential grouping of syllables into words

How the brain sequentially groups sensory events into temporal chunks and how this process is modulated by attention are fundamental questions in cognitive neuroscience. Sequential grouping includes bottom-up primitive grouping and top-down knowledge-based grouping. In speech perception, grouping acoustic features into syllables can rely on bottom-up acoustic continuity cues but grouping syllables into words critically relies on the listener’s lexical knowledge. This study investigates whether top-down attention is required to apply lexical knowledge to group syllables into words, by concurrently monitoring neural entrainment to syllables and words using electroencephalography (EEG). When attention is directed to a competing speech stream or cross-modally to a silent movie, neural entrainment to syllables is weakened but neural entrainment to words largely diminishes. These results strongly suggest that knowledge-based grouping of syllables into words requires top-down attention and is a bottleneck for the neural processing of unattended speech.
Studies Towards Broadening The Substrate Profile And Regulation Of Histone Deacetylase 1

STUDIES TOWARDS BROADENING THE SUBSTRATE PROFILE AND REGULATION OF HISTONE DEACETYLASE 1 by DHANUSHA ASHANTHI NALAWANSHA December 2016 Advisor: Dr. Mary Kay H. Pflum Major: Chemistry (Biochemistry) Degree: Doctor of Philosophy Aberrant expression of histone deacetylase 1 (HDAC1) is implicated in multiple diseases, including cancer. As a consequence, HDAC1 has emerged as an important therapeutic target for drug development. HDAC1 regulates key cellular processes, such as cell proliferation, apoptosis, and cell survival, by deacetylating both histone and nonhistone substrates. Due to the lack of simple tools to identify physiological substrates of HDAC1, the full spectrum of HDAC1 activities in the cell remains unclear. Here, we employed a substrate trapping strategy to discover cellular substrates of HDAC1. Using this approach, we identified mitosis-related protein Eg5 as a substrate. HDAC1 colocalizes with Eg5 during mitosis, suggesting a role for HDAC1 in the mitotic defects observed with HDAC inhibitor drugs. By extending our substrate trapping strategy to HEK293 cells, we identified lysine specific demethylase 1 (LSD1) as an HDAC1 substrate. Significantly, LSD1 is overexpressed in multiple cancers and has emerged as a potential anti-cancer drug target. LSD1 is typically found in association with another epigenetic enzyme, histone deacetylase1 (HDAC1). HDAC and LSD1 inhibitor compounds have been tested as
Eggshell Qualities as Indicative of Eggshell Strength for Layer Selection

The study aimed at investigating which of four traits is the most representative of eggshell strength (destructive eggshell thickness measurement, eggshell weight, egg specific gravity, ultrasonic measurement of eggshell thickness) and could be used for selection purposes. To date, investigations focused mostly on pairwise (eggshell strength vs. another eggshell feature) analyses, resulting in two-, maybe three-trait, models when eggshell traits are considered. Since the covariance estimates are also model dependent, we collected five eggshell traits within one analysis, which better reflects what occurs in nature. The eggs were collected from 4571 Rhode Island White and 2426 Rhode Island Red hens. A multiple-trait animal model and the REML method were employed to compute variance components for calculation of heritabilities and genetic correlations between the traits. On average, the highest correlations were found between the destructive measurement and the other quality traits. It is concluded, however, that the ultrasonic eggshell thickness measurement, also with high genetic correlations with the other traits and leaving an egg intact for further handling, can suit best, as an indirect criterion, the selection for eggshell strength.
The relationship between condition and form factors of the Adriatic fishes in the Zadar area

Abstract The relationship between the mean Fulton’s condition and form factors of 12 marine species (N=209 fish specimens) caught in the Zadar area (middle eastern Adriatic) was analysed. The lowest mean condition factor (K = 0.6329) referred to the elongated Trachinus draco, while the highest one (K = 1.7758) referred to the deep-bodied Scorpaena porcus. The correlation between the mean Fulton’s condition and form factors of these 12 populations was highly significant (K = 0.404 + 0.663 a3.0; r2 = 0.815; P < 0.01). Including more species in the calculation would give even more accurate results.
Detection of Void Defects in Ball Grid Array X-ray Image Using a New Blob Filter

Due to the advantages of small sizes, more I/O ports, etc., Ball Grid Array (BGA) has been used in the production of printed circuit board (PCB). However, BGA voids can degrade the performance of the board and cause failure. To automatically detect the voids in X-ray image, a novel blob filter that makes use of the local image gradient magnitude is proposed in this paper. The utilization of the local image gradient magnitude makes the proposed filter invariant to the image brightness, void shape, void position, and component interference. Furthermore, different sizes of box filters are employed to analyze the image in multi-scale, and as a result, the proposed blob filter is robust to void size. Experimental results show that the proposed method can obtain void detection accuracy up to 96.104% while keep low false ratio.
Hate Speech on Social Media: Netnographic Studies on Facebook Fanpages 2019 Change the President

: Social media is often a means to spread the utterance of hatred. Many cases of hate speech that we can see on social media. The purpose of this study is to see what forms of hate speech on social media are posted by Facebook fanpages 2019 Change President. The approach used in this study is descriptive-qualitative with the Netnography method. Netnography is a method used to see social or cultural phenomena that occur in cyber space. Phenomenon of hate speech by facebook fanpages 2019 Change the President to be analyzed by using four levels, namely media space, media documents, media objects and experience. The results of this study at the level of the media room, Facebook fanpages 2019 Change the President was used as a media that spread the utterance of hatred. at the level of media documents, content posted by facebook fanpages 2019 Change President in the form of writing, photos, memes, pictures and videos containing utterances of hate speech. At the level of the media object, one user with another user can interact through the comment column. However, the interaction that occurred in the comments column also indicated speeches of hatred. In the level of experience, this Facebook fanpages are used to invite or incite other users to also make an indication of the expression of hatred towards certain parties.
Morpho-molecular characterization of Peroneutypa (Diatrypaceae, Xylariales) with two novel species from Thailand

Three species of Peroneutypa were collected from dead wood in Thailand. Two new taxa P. diminutiasca and P. rubiformis are herein described, illustrated and compared with related taxa, based on the evidence from morphology and phylogenetic analyses. Details for the holomorphs of P. rubiformis and the third species P. scoparia are provided. Phylogenetic analyses of a combined ITS and TUB2 DNA sequence dataset support their placement in the genus Peroneutypa (Diatrypaceae, Xylariales). An updated key to Peroneutypa species is also provided.
Bayesian Nonparametric Clustering in SAS®

Traditional parametric models use a fixed and finite number of parameters which cannot be used in data mining and machine learning. This is because they may result in the over or under fitting of data due to the complexity of the models used in data mining and machine learning. The Bayesian nonparametric approach is an alternative to the traditional parametric approach. Probabilistic models are appropriate nonparametric models for data mining and machine learning since they are data-driven. One example of a Bayesian nonparametric model is the Dirichlet Process model. The Dirichlet Process model is one of the most popular BNP models. For clustering, the Dirichlet Process in the Gaussian Mixture Model (GMM) is used to find the best number of clusters within the data using the gmm action in the CAS procedure within SAS®. It is able to add new clusters and remove existing clusters during the clustering process, thus finding the best number of clusters adaptively. In the gmm action, the Dirichlet Process serves as the prior for the proportion of the Gaussian mixture. In this study, a real-world example will be used to demonstrate the use of Dirichlet Process Gaussian Mixture Model for nonparametric clustering in SAS® to analyze a large dataset.
Exposure to synthetic hydraulic fracturing waste influences the mucosal bacterial community structure of the brook trout (Salvelinus fontinalis) epidermis

Production of natural gas using unconventional technologies has risen as demand for alternative fuels has increased. Impacts on the environment from waste generated from these processes are largely unexplored. In particular, the outcomes of organismal exposure to hydraulic fracturing waste have not been rigorously evaluated. We evaluated the effects of exposure to surrogate hydraulic fracturing waste (HF waste) on mucosal bacterial community structure of the brook trout (Salvelinus fontinalis) epidermis. Brook trout are fish native to streams at risk to HF waste exposure. Here, fish were exposed to four treatments (control, 0.00%; low, 0.01%; medium, 0.10%; and high, 1.0% concentrations) of surrogate HF waste synthesized to mimic concentrations documented in the field. Epidermal mucus samples were collected and assessed 15 days post-exposure to determine if the associated bacterial community varied among treatments. We observed differences in epidermal mucosal bacterial community composition at multiple taxonomic scales among treatments. These community changes reflected compositional differences in taxa dominance and community similarity rather than losses or gains in taxonomic richness. The dominant bacterial genus that explained the greatest variation in community structure between exposed and unexposed fish was Flavobacterium. Two genera associated with salmonid diseases, Flavobacterium and Pseudomonas, were statistically more abundant in high treatments than controls. These results suggest that exposure to low levels of HF waste influences bacterial colonization and may lead to a disruption that favors bacterial populations associated with fish disease.
Security Characterization and Expression in Data Publishing Using Selection Algorithm

The expanding enthusiasm for gathering and distributing a lot of people information open for various purposes to research, showcase examination and practical measures have made significant security worries about people delicate data. Privacy-preservation data publishing has received lot of thoughtfulness, as it is always a problem of how to protect database of high dimension. We propose a structural importance aware approach to quantify the vulnerability/de-anonymizability of graph data to structure-based De-Anonymization (DA) attacks. We quantify both the seed-based and the seed-free Relative De-anonymizability (RD) of graph data for both perfect DA and partial DA under a general data model trust evaluation mechanisms among different entities in human society are fitted and the multi-granularity selection standard of trust levels based on Gaussian cloud transformation is constructed. They are non-sensitive data and sensitive data.
CFD Simulations of Gas Holdup in a Bubble Column at High Gas Temperature of a Helium-Water System

Bubble columns (BCs) are systems that contain two-phases; gas, and liquid, in which gaseous bubbles are dispersed through a liquid in a vertical column. They have a wide range of applications because of their many advantages. The hydrodynamics of the BCs have a significant effect on its scale up analysis. The most important parameter that can be used for describing the performance of the BCs is the gas holdup. In this paper, the overall gas holdup was predicted by developing computational fluid dynamics (CFD) simulations for a helium-water bubble column, where helium gas is injected at 90 o C through a liquid of water at 22 o C. The approaches used to model the bubble column by CFD is 2D plane. From the CFD simulations, it was found that the overall gas holdup increases by increasing the superficial gas velocity at any specific static liquid height. In addition, the overall gas holdup decreases by increasing the static liquid height at any given superficial gas velocity. All CFD simulation results of gas holdup were validated by experimental results of helium-water BCs from previous literature with good agreement, which demonstrates the applicability of the simulations for this kind of BC systems. The CFD results were validated for superficial gas velocities up to 0.15 m/s, and aspect ratios up to 4. From the comparison with the experimental results, it was found that in general, the profiles of gas holdup determined from CFD simulations, under-predicted the experimental data. Also, it was shown that the experimental effects of the static liquid height on gas holdup were correctly predicted by CFD simulations. Moreover, it was observed that the distribution of gas holdup along the cross-section of the column is unequal, where the gas holdup is higher at the center of the column and lower near the wall region.
Studies of mitochondrial genomics in Salmo trutta fario

Abstract Salmo trutta fario population is an important species for aquaculture and livestock industry. Moreover, these species were used for studies on the molecular markers. Mitochondrial genomic is also beneficial for phylogenetic studies in salmonid species. They applied maternal traits for mitogenome, whereas paternal traits related to nuclear genomics. It will be genetically highly divergent indicating that they may represent distinct and potentially locally adapted gene pools (Apostolidis et al., 2011). Evolutionary history has been studied on the Salmo taxa such as brown trout, Salmo salar, Salmo trutta populations (Kottelat & Freyhof, 2007; Simonovic et al., 2007).
Visual SLAM in Dynamic Environment using Semantic Segmentation

Simultaneous localization and mapping (SLAM) in dynamic environment forms a challenging problem which involves pose estimation, scene reconstruction and dynamic objects handling at the same time. Examples of practical application include autonomous cars driving through urban area with other vehicles and pedestrians in the scene or robots navigating through a building with people walking around. With the aid of semantic segmentation and object detection, we are able to identify moving objects in the scene while executing the SLAM task. In this project, we formulate the problem over the integration of semantic segmentation and monocular-based visual SLAM systems and investigate the capability on performance enhancement in dynamic environment.
Incremental analysis of vertebral centra can reconstruct the stable isotope chronology of teleost fishes

Isotope analysis has high potential for understanding fish ecology and food‐web structure in aquatic ecosystems. The utility of isotope analysis will be greatly improved if we can reconstruct the chronology of several isotopes at multiple growth stages of individual fish. However, no practical methods exist for reconstructing the chronology of light‐element isotopes (e.g. δ13C, δ15N, δ34S, and Δ14C) in teleost fishes. Here, we present and test a new analytical approach for reconstructing the isotopic ratios of light isotopes at multiple life‐stages in teleost fishes. We sampled an anadromous salmon species, masu salmon Oncorhynchus masou (n = 3), along with water from its natal stream and from the ocean. We subdivided the vertebral centra of the salmon equally into 10 sections and extracted bone collagen from each sample. We then measured the stable sulphur isotope ratios of each vertebral section and compared them with δ34S values of the river water and sea water. We also measured the 87Sr/86Sr ratios of otoliths as a reference indicator of salmon migration between fresh water and the ocean. In all samples, the bone section closest to the centre of the centrum had the lowest δ34S values, which were similar to those of fresh water. The δ34S values gradually increased from the centre to marginal sections, finally reaching constant values similar to those of seawater. The 87Sr/86Sr ratios of sagittal otolith sections had significant inter‐individual differences and were consistent with the patterns of variation of the δ34S values of the vertebral sections. Our results show that the vertebral centra of teleost fishes record isotopic information from juvenile to adult life stages. We suggest that our method can provide reproducible isotopic chronology, even in teleost fishes smaller than 50 cm. This method can be used in isoscape studies and in studies of the ecology of marine teleost fishes.
Observation on Health Quality of Teeth Before and After Root Canal Treatment Using DIP Algorithms

These days an exploration of dental infection is extremely useful in the clinical areas for programmed translation of illness inside less time and with more precise outcomes. Root canal treatment is a regularly clear system to mitigate dental torment and spare our teeth. There are numerous challenges in characterizing goal, for example, it is hard to translate ailments in light of the fact that there are exact moment varieties in X-rays, Poor image quality portrayal and division of every tooth in the radiographic image. The crude information got straightforwardly from X-rays obtaining gadget may yield a nearly poor image quality portrayal. On account of the part of a human (dental practitioner) understanding in light of his insight, experience and recognition which may vary from specialist to specialist, there are odds of the blunder in choosing the correct restorative treatment. Programming engineers alongside specialists have composed different institutionalized and logical instruments to limit the human blunder on account of the right treatment in light of visual perception. One of the points of this work is to Centre on the separated part (where the Root Canal Operation was done) of the tooth from computerized dental X-rays, finding the required data as highlights and helping the dental practitioner by utilizing the Digital Image Processing Algorithms.
Specification and verification in the field: Applying formal methods to BPF just-in-time compilers in the Linux kernel

This paper describes our experience applying formal meth-ods to a critical component in the Linux kernel,the just-in-time compilers (“JITs”) for the Berkeley Packet Filter (BPF) virtual machine. We verify these JITs using Jitterbug, the ﬁrst framework to provide a precise speciﬁcation of JIT correctness that is capable of ruling out real-world bugs, and an automated proof strategy that scales to practical implementations. Using Jitterbug, we have designed, implemented, and veriﬁed a new BPF JIT for 32-bit RISC-V, found and ﬁxed 16 previously unknown bugs in ﬁve other deployed JITs, and developed new JIT optimizations; all of these changes have been upstreamed to the Linux kernel. The results show that it is possible to build a veriﬁed component within a large, unveriﬁed system with careful design of speciﬁcation and proof strategy.
NaCl stress causes changes in photosynthetic pigments and accumulation of compatible solutes in Zea mays L.

The present study was conducted in order to evaluate the effects of NaCl on photosynthetic pigments and compatible solutes of Zea mays under salt stress. Seven NaCl regimes were used, 0mM, 25mM, 50mM, 75mM 100mM, 125mM and 150mM. Plants were analyzed on 15 th day after salt treatment. A factorial experiment in a completely randomized block design (CRBD) with seven treatments and three replications were applied. From the data attained, we understand that in accordance with the increase in salinity, photosynthetic pigment content reduced drastically, whereas compatible solutes like proline, glycine betaine and sugar enhanced marginally. The accumulation of compatible solutes makes the plant survive against salinity stress.
Production potential and chemical composition of elephant grass (Pennisetum purpureum Schum.) at different ages for energy purposes

The elephant grass has gained prominence as one of the main forage species used for biomass production. Therefore, the aim of this study was to identify elephant grass genotypes with high energy biomass production potential by evaluating morpho-agronomic and biomass quality. The following traits were evaluated in this study: dry matter yield (DMY), percentage of whole-plant dry matter (%DM), percentage of neutral detergent fiber (%NDF), percentage of acid detergent fiber (%ADF); percentage of cellulose (%CEL), percentage of lignin (%LIG), percentage of carbon (%C), percentage of nitrogen (%N), and carbon: nitrogen ratio (C: N). Five different production ages were evaluated, and significant differences were observed for the variable DMY. The harvests performed at 20 and 24 weeks of age, provided the best response for biomass energy production (DMY) from elephant grass, averaging 20.50 and 23.77 t.ha−1. The genotypes that most stood out during the evaluation period at the five production ages were King Grass, Mole de Volta Grande, and Mercker 86 - Mexico. Genotypes Mole de Volta Grande and King Grass are the most suitable for elephant grass breeding programs aimed at biomass energy production in the conditions of Campos dos Goytacazes - RJ, Brazil. Key words: Bioenergy, biomass quality, carbon: nitrogen ratios, Pennisetum purpureum Shum, yield.