Miracle-dz/UniFAR-FTUs huggingface dataset:
Essential waters: Young bull sharks in Fiji's largest riverine system

Abstract Coastal and estuarine systems provide critical shark habitats due to their relatively high productivity and shallow, protected waters. The young (neonates, young‐of‐the‐year, and juveniles) of many coastal shark species occupy a diverse range of habitats and areas where they experience environmental variability, including acute and seasonal shifts in local salinities and temperatures. Although the location and functioning of essential shark habitats has been a focus in recent shark research, there is a paucity of data from the South Pacific. In this study, we document the temporal and spatial distribution, age class composition, and environmental parameters of young bull sharks (Carcharhinus leucas) in the Rewa, Sigatoka, and Navua Rivers, Fiji's three largest riverine systems. One hundred and seventy‐two young bull sharks were captured in fisheries‐independent surveys from January 2016 to April 2018. The vast majority of the captures were neonates. Seasonality in patterns of occurrence of neonate individuals suggests a defined parturition period during summer. Environmental parameters between the Rewa and the Sigatoka River differed significantly, as did the recorded young bull sharks abundance. According to the surveys, young bull sharks occur in all three rivers with the Rewa River likely representing essential habitat for newly born bull sharks. These results enhance the understanding of bull shark ecology in Fiji and provide a scientific basis for the implementation of local conservation strategies that contribute to the protection of critical habitats.
Identification and Characterization of Stress Responsive Genes in Soybean and Sunflower

xxvi CHAPTER 1: LITERATURE REVIEW . 1 1.1 Soybean . 1 1.2. Sunflower . 2 1.3. Resistance (R) Genes . 3 1.4. Mitogen Activated Protein Kinase (MAPK) Genes . 3 1.5. Aphis glycines Matsumura . 5 1.5. 1 Life Cycle of A. glycines . 5 1.5. 2. Aphid Effectors . 7 1.5. 3. Aphis glycines Biotypes . 10 1.5. 4. Soybean Cultivars Exhibiting Antibiosis, Antixenosis, and Tolerance as a Resistance Response to Soybean Aphids . 11 1.5. 5. Rag Genes in Soybean Cultivars Provide Resistance to A. glycines . 12 1.5. 6. GWAS Studies on A. glycines Resistance in Soybean Expanding to a Number of QTLs . 17 1.5. 7. Rag Gene Pyramiding Provides Resistance to all A. glycines biotypes . 18 1.5. 8. Transcriptomic Studies on Soybean-A. Glycines Interaction: Jasmonic Acid (JA) and Abscisic Acid (ABA) Signaling Pathway Plays a Crucial Role in Plant Resistance . 18
Calibrating the sensing-coil radius by feed-down from a harmonic reference

A method for calibrating the radius of rotating, harmonic sensing coils is proposed that allows relaxing constraints on alignment and field errors of the reference quadrupole magnet. Radius calibration considering roll angle misalignment between the measurement bench, the magnet, and the motor-drive unit is studied first. We then study the calibration error when a harmonic field error of higher order is present in the calibration magnet. This also yields a calibration when a sextupole magnet is used, for example, when an insitu calibration [1] is required. The proposed calibration method has been validated by simulations with the CERN numerical field computation program ROXIE.
Nucleus Basalis Stimulation Stabilizes Attractor Networks and Enhances Task Representation in Prefrontal Cortex

The action of acetylcholine in the neocortex is critical for executive function. Cholinergic drugs can improve cognitive function in patient populations and normal adults. How endogenous cholinergic action affects neuronal activity in higher cortical areas is unknown. Here we tested the effects of electrical stimulation of the cortical source of acetylcholine in primates, the Nucleus Basalis of Meynert, on neural activity while monkeys performed working memory tasks. Stimulation delivered in an intermittent fashion improved behavioral performance and increased neuronal activity during the delay period of the task but not to the phasic responses of visual stimuli. Selectivity of neuronal responses broadened, rendering the bump of activity in an attractor network more stable, and filtering distracting stimuli more effectively. These neural results show that acetylcholine has effects on neural activity and selectivity in the prefrontal cortex opposing those of dopamine and fine tuning aggregate neural ensemble activity based on neuromodulatory tone.
Cryo-EM structure of Escherichia coli σ70 RNAP and promoter DNA complex revealed a role of σ non-conserved region during the open complex formation

First step of gene expression is transcribing the genetic information stored in DNA to RNA by the transcription machinery including RNA polymerase (RNAP). In Escherichia coli, a primary σ70 factor form the RNAP holoenzyme to express housekeeping genes. The σ70 contains a large insertion at between the conserved regions 1.2 and 2.1, the σ non-conserved region (σNCR), but its function remains to be elucidated. In this study, we determined the cryo-EM structures of the E. coli RNAP σ70 holoenzyme and its complex with promoter DNA (open complex, RPo) at 4.2 and 5.75 Å resolutions, respectively, to reveal native conformations of RNAP and DNA. The RPo structure presented here found an interaction between R157 residue in the σNCR and promoter DNA just upstream of the −10 element, which was not observed in a previously determined E. coli RNAP transcription initiation complex (RPo plus short RNA) structure by X-ray crystallography due to restraint of crystal packing effect. Disruption of the σNCR and DNA interaction by the amino acid substitution (R157E) influences the DNA opening around the transcription start site and therefore decreases the transcription activity of RNAP. We propose that the σNCR and DNA interaction is conserved in proteobacteria and RNAP in other bacteria replace its role with a transcription factor.
A Psychological Approach to Demand Forecasting: A Measure of Potential User in Bus Service

A recent trend in transport demand modeling with a focus on potential users emphasizes the understanding on the human decision-making process. Among various theories about the process, loyalty-based theory has the closest relationship with the concept of potential users. However, conventional loyalty frameworks are insufficient for demand modeling. To address the issue, the present study proposed a psychological demand model based on a loyalty framework considering both service-quality-related and non-service-quality-related factors. The proposed model is able to quantify potential users and to measure maximum values of bus patronage respect to different service scenarios. Based on the proposed model, an increase of 18.05% on the group of car drivers could be expected to be at the highest priority for pushing up bus patronage in term of improving service quality. In contrast, a little increase was found on the group of non-car drivers with only 3.81% even if an ideal service was provided.
Optimisation of a combined ARGO-FES system: adaptation of the knee mechanism to allow flexion of the knee during the swing phase

The knee mechanism of an Advanced Reciprocating Gait Orthosis is adapted to allow flexion of the knee during the swing phase. The new knee mechanism is electrically controlled and consists of a mini DC motor with gearbox, a cam and a follower. Preliminary tests with the system are positive, but they show that it should not be used without FES.
Consortium genome-wide meta-analysis for childhood dental caries traits

Prior studies suggest dental caries traits in children and adolescents are partially heritable, but there has been no large-scale consortium genome-wide association study (GWAS) to date. We therefore performed GWAS for caries in participants aged 2.5-18.0 years from 9 contributing centers. Phenotype definitions were created for the presence or absence of treated or untreated caries, stratified by primary and permanent dentition. All studies tested for association between caries and genotype dosage (imputed to Haplotype Reference Consortium or 1000 Genomes phase 1 version 3 panels) accounting for population stratification. Fixed–effects meta-analysis was performed weighted by inverse standard error. Analysis included up to 19,003 individuals (7,530 affected) for primary teeth and 13,353 individuals (5,875 affected) for permanent teeth. Evidence for association with caries status was observed at rs1594318-C for primary teeth (intronic within ALLC, Odds Ratio (OR) 0.85, Effect Allele Frequency (EAF) 0.60, p 4.13e-8) and rs7738851-A (intronic within NEDD9, OR 1.28, EAF 0.85, p 1.63e-8) for permanent teeth. Consortium-wide estimated heritability of caries was low (h2 of 1% [95% CI: 0%:7%] and 6% [95% CI 0%:13%] for primary and permanent dentitions, respectively) compared to corresponding within-study estimates (h2 of 28%, [95% CI: 9%:48%] and 17% [95% CI:2%:31%]) or previously published estimates. This study was designed to identify common genetic variants with modest effects which are consistent across different populations. We found few single variants associated with caries status under these assumptions. Phenotypic heterogeneity between cohorts and limited statistical power will have contributed; these findings could also reflect complexity not captured by our study design, such as genetic effects which are conditional on environmental exposure. Author summary Dental caries (tooth decay) is a common disease in children. Previous studies suggest genetic factors alter caries risk, but to date there is a gap of knowledge in identifying which specific genetic variants are responsible. We undertook analysis in a consortium including around 19,000 children and investigated whether any of 8 million common genetic variants were associated with risk of caries in primary (milk) or permanent teeth. If identified, these variants are used as ‘tags’ to highlight genes which may be involved in a disease. We identified variants in two loci associated with caries status; in the primary (rs1594318) and permanent dentition (rs7738851). The former is intronic in ALLC, a gene with poorly understood function. The latter is an intronic variant within NEDD9, a gene which has several known functions including a role in development of craniofacial structures. To gain a more comprehensive understanding of genetic effects which influence caries larger studies and a better understanding of environmental modifiers or interactions with genetic effects are required.
AM-FM separation using shunting neural networks

We describe an approach to estimating the amplitude-modulated (AM) and frequency-modulated (FM) components of a signal. Any signal can be written as the product of an AM component and an FM component. There have been several approaches to solving the AM-FM estimation problem described in the literature. Popular methods include the use of time-frequency analysis, the Hilbert transform, and the Teager energy operator. We focus on an approach based on FM-to-AM transduction that is motivated by auditory physiology. We show that the transduction approach can be realized as a bank of bandpass filters followed by envelope detectors and shunting neural networks, and the resulting dynamical system is capable of robust AM-FM estimation in noisy environments and over a broad range of filter bandwidths and locations. Our model is consistent with previous psychophysical experiments that indicate AM and FM components of acoustic signals may be transformed into a common neural code in the brain stem via FM-to-AM transduction. Applications of our model include signal recognition and multi-component decomposition.
Recent Advanced Statistical Background Modeling for Foreground Detection - A Systematic Survey

Background modeling is currently used to detect moving objects in video acquired from static cameras. Numerous statistical methods have been developed over the recent years. The aim of this paper is firstly to provide an extended and updated survey of the recent researches and patents which concern statistical background modeling and secondly to achieve a comparative evaluation. For this, we firstly classified the statistical methods in terms of category. Then, the original methods are reminded and discussed following the challenges met in video sequences. We classified their respective improvements in terms of strategies used. Furthermore, we discussed them in terms of the critical situations they claim to handle. Finally, we conclude with several promising directions for future research. The survey also discussed relevant patents.
SMNN: Batch Effect Correction for Single-cell RNA-seq data via Supervised Mutual Nearest Neighbor Detection

An ever-increasing deluge of single-cell RNA-sequencing (scRNA-seq) data has been generated, often involving different time points, laboratories or sequencing protocols. Batch effect correction has been recognized to be indispensable when integrating scRNA-seq data from multiple batches. A recent study proposed an effective correction method based on mutual nearest neighbors (MNN) across batches. However, the proposed MNN method is unsupervised in that it ignores cluster label information of single cells. Such cluster or cell type label information can further improve effectiveness of batch effect correction, particularly under realistic scenarios where true biological differences are not orthogonal to batch effect. Under this motivation, we propose SMNN which performs supervised mutual nearest neighbor detection for batch effect correction of scRNA-seq data. Our SMNN either takes cluster/cell-type label information as input, or, in the absence of such information, infers cell types by performing clustering of scRNA-seq data. It then detects mutual nearest neighbors within matched cell types and corrects batch effect accordingly. Our extensive evaluations in simulated and real datasets show that SMNN provides improved merging within the corresponding cell types across batches, leading to reduced differentiation across batches over MNN. Furthermore, SMNN retains more cell type-specific features after correction. Differentially expressed genes (DEGs) identified between cell types after SMNN correction are biologically more relevant, and the DEG true positive rates improve by up to 841%. SMNN is implemented in R, and freely available at https://yunliweb.its. unc.edu/SMNN/ and https://github.com/yycunc/SMNNcorrect. Author summary The presence of batch effects poses grand challenges to integrative analysis of scRNA-seq data from multiple resources. One powerful tool MNN corrects batch effect of scRNA-seq data based on mutual nearest neighbors across batches. However, this method makes a critical assumption that batch effect is orthogonal to true biological differences. This assumption in practice can easily be violated. When that happens, MNN suffers from biases introduced by wrongly matched pairs of cells. To overcome this shortcoming, here we present a new method, SMNN, which performs supervised mutual nearest neighbor detection for batch effect correction. We benchmark the performance of SMNN using both simulations and real data, and demonstrate that, compared to MNN, our SMNN can better mix cells of the same type/state across batches. More importantly, SMNN can more effectively retain biologically relevant features, and thereof provide improved cell type clustering and enhanced power for detecting differentially expressed genes (DEGs) between different cell types.
Natural genetic variation in C. elegans reveals genomic loci controlling metabolite levels

Metabolic homeostasis is sustained by complex biological networks responding to nutrient availability. Disruption of this equilibrium involving intricate interactions between genetic and environmental factors can lead to metabolic disorders, including obesity and type 2 diabetes. To identify the genetic factors controlling metabolism, we applied a quantitative genetic strategy using a Caenorhabditis elegans population consisting of 199 recombinant inbred lines (RILs) originally derived from crossing parental strains Bristol N2 and Hawaii CB4856. We focused on the genetic factors that control metabolite levels and measured fatty acid (FA) and amino acid (AA) composition in the 199 RILs using targeted metabolomics. For both FA and AA profiles, we observed large variation in metabolite levels with 32-82% heritability between the RILs. We performed metabolite-metabolite correlation analysis and detected strongly co-correlated metabolite clusters. To identify natural genetic variants responsible for the observed metabolite variations, we performed QTL mapping and detected 36 significant metabolite QTL (mQTL). We focused on the mQTL that displayed high significant linkage and heritability, including an mQTL for the FA C14:1 on chromosome I, and another mQTL for the FA C18:2 on chromosome IV. Using introgression lines (ILs) we were able to narrow down both mQTL to a 1.4 Mbp and a 3.6 Mbp region, respectively. Overall, this systems approach provides us with a powerful platform to study the genetic basis of C. elegans metabolism. It also allows us to investigate additional interventions, such as nutrients and stresses that maintain or disturb the regulatory network controlling metabolic homeostasis, and identify gene-by-environment interactions.
ADVANCEMENTS IN DIGITAL SIGNAL PROCESSING TECHNOLOGY ARE ENABLING ITS USE FOR INCREASINGLY WIDESPREAD APPLICATIONS . DEVELOPERS WILL BE CHALLENGED TO USE THIS PROCESSING POWER TO ITS UTMOST , WHILE CREATING NEW APPLICATIONS AND IMPROVING EXISTING ONES .

During the past decade digital signal processors (DSPs) have hit critical mass for high-volume applications (Figure 1). Today, the entire digital wireless industry operates with DSP-enabled handsets and base stations. The mass-storage industry depends on DSPs to produce hard-disk drives and digital versatile disc players. Ever-increasing numbers of digital subscriber line and cable modems, line cards, and other wired telecommunications equipments are based on DSPs. Digital still cameras, hearing aids, motor control , consumer audio gear such as Internet audio are just some of the many mass market applications in which DSPs are routinely found today. More specialized DSP applications include image processing, medical instrumentation, navigation, and guidance. With the growing importance of DSPs and their applications, it seems appropriate to look at the changes occurring in these devices and to hazard a few guesses about where DSP innovations will lead in the opening decades of the new century. The continued growth of DSP-enabled applications will depend on developments in several areas of technology: the underlying manufacturing processes, the DSP core and chip architectures, and the software for development and applications. An additional factor, and the most difficult one to anticipate, is innovation. In a few years, designers will be dealing with DSPs that integrate hundreds of millions of on-chip transistors and deliver performance measured in trillions of instructions per second. (See 1999 IEDM short course on system on a chip by author, available for sale at http://shop.ieee.org/store.) Determining how to use that processing power effectively will require imagination that goes beyond conventional engineering methodologies. Why have DSPs done so well in the last few years? The DSP phenomenon is part of the overall microprocessor success story, and it must be seen in that light. Like the high-end reduced instruction set computing (RISC) engines used in computers and the medium-range RISC microcontrollers in embedded systems, DSPs are becoming increasingly differentiated , designed to handle the processing tasks of specific types of applications. This trend will continue with all microprocessors in the years ahead, and it will be responsible for much of the future success of DSPs. Although DSPs are similar to RISC engines in some respects, they're fundamentally different in other ways. These differences date from the earliest microprocessor architectures, and they'll continue to influence the development of DSPs and their applications in the years ahead. Essentially, DSPs are designed for
Ifit1 regulates norovirus infection and enhances the interferon response in murine macrophage-like cells

Background Norovirus, also known as the winter vomiting bug, is the predominant cause of non-bacterial gastroenteritis worldwide. Disease control is predicated on a robust innate immune response during the early stages of infection. Double-stranded RNA intermediates generated during viral genome replication are recognised by host innate immune sensors in the cytoplasm, activating the strongly antiviral interferon gene programme. Ifit proteins, which are highly expressed during the interferon response, have been shown to directly inhibit viral protein synthesis as well as regulate innate immune signalling pathways. Ifit1 is well-characterised to inhibit viral translation by sequestration of eukaryotic initiation factors or by directly binding to the 5’ terminus of foreign RNA, particularly those with non-self cap structures. However, noroviruses have a viral protein, VPg, covalently linked to the 5’ end of the genomic RNA, which acts as a cap substitute to recruit the translation initiation machinery. Methods Ifit1 knockout RAW264.7 murine macrophage-like cells were generated using CRISPR-Cas9 gene editing. These cells were analysed for their ability to support murine norovirus infection, determined by virus yield, and respond to different immune stimuli, assayed by quantitative PCR. The effect of Ifit proteins on norovirus translation was also tested in vitro. Results Here, we show that VPg-dependent translation is completely refractory Ifit1-mediated translation inhibition in vitro and Ifit1 cannot bind the 5’ end of VPg-linked RNA. Nevertheless, knockout of Ifit1 promoted viral replication in murine norovirus infected cells. We then demonstrate that Ifit1 promoted interferon-beta expression following transfection of synthetic double-stranded RNA but had little effect on toll-like receptor 3 and 4 signalling. Conclusions Ifit1 is an antiviral factor during norovirus infection but cannot directly inhibit viral translation. Instead, Ifit1 stimulates the antiviral state following cytoplasmic RNA sensing, contributing to restriction of norovirus replication.
Phytochemical Constituency Profiling and Antimicrobial Activity Screening of Seaweeds Extracts Collected from the Bay of Bengal Sea Coasts

Seaweeds are able to produce a great variety of secondary metabolites that are characterized by a broad spectrum of biological activities. Two seaweeds species, namely Hypnea musciformis and Enteromorpha intestinalis were studied to evaluate the phytochemical constituency and antimicrobial activities. First of all, crude extracts of both sea weeds were prepared by two different extraction methods (soaking and water bath) using different solvents. Phytochemicals profiling results revealed the presence of bioactive compounds (flavonoids, alkaloids, tannin, saponin and phenols) in both seaweed extracts. Quantification results for ethanolic extracts of H. musciformis and E. intestinalis estimated 51 mg and 43 mg tannins in per gram of dried samples and flavonoids contents were found 67 mg and 57 mg/g mg QE/g respectively. Total phenolic contents were determined in terms of gallic acid equivalent (GAE). H. musciformis exhibited higher amount of phenolics (59 ± 0.0002 mg GAE/g) than E. intestinalis extracts (41 ± 0.0002 mg GAE/g). In antimicrobial activity test, ethanol extracts of H. musciformis and E. intestinalis were found 10 mm of inhibition diameter against all of the bacterial strains. Besides, methanol extracts of E. intestinalis were more susceptible to Staphylococcus aureus and Pseudomonas which was close to the inhibition diameter (>15 mm) of the mainstream antibiotic; Gentamicin. Moreover, Klebsiella sp. was found more susceptible to ethanol and methanol extracts of Hypnea musciformis as it showed inhibition zone greater than 15 mm. Both Seaweed extracts possessed higher amount of phytochemicals and showed promising antimicrobial activities when compared with the standards.