Miracle-dz/UniFAR-FTUs huggingface dataset:
A Genotype-Independent Real-Time PCR Assay for Quantiﬁcation of Hepatitis B Virus DNA (cid:1)

Accurate quantiﬁcation of hepatitis B virus (HBV) DNA levels is important for monitoring patients with chronic HBV infection and for assessing their responses to antiviral therapy. This study aimed to develop a real-time PCR assay that is sensitive and can accurately quantify a wide range of HBV DNA levels across the known HBV genotypes. An “in-house” real-time PCR assay using primers and a TaqMan probe in a highly conserved region of the HBV surface gene was designed. The assay was standardized against a WHO standard and validated against plasmids of HBV genotypes A through H. The linear quantiﬁcation range was approx-imately 5 (cid:1) 10 0 to 2.0 (cid:1) 10 9 IU/ml. Results of samples from patients infected with HBV genotypes A through H tested using our real-time “in-house” PCR assay showed an excellent correlation with those of the Cobas Amplicor HBV Monitor ( R 2 (cid:2) 0.9435) and the Cobas TaqMan HBV ( R 2 (cid:2) 0.9873) tests. We have established a real-time PCR assay that is genotype independent and can accurately quantify a wide range of HBV DNA levels. Further studies of additional samples are ongoing to validate the genotype independence of our assay. The availability of PCR assays in a 50- (cid:3) l reaction mixture containing 25 (cid:3) l TaqMan Universal PCR master mix (Applied Biosystems) with 0.2 (cid:3) M primers, 0.1 (cid:3) M probes, and 10 (cid:3) l extracted DNA. An initial 2-min incubation at 50 ° C to activate uracil- N- glycosylase and to destroy potential amplicon carryover was followed by a 10-min incubation at 95 ° C, which activates the thermostable DNA polymerase and denatures the uracil- N- glycosylase. Subsequently, 50 cycles of 95 ° C for 15 s and 60 ° C for 1 min were performed with an iCycler iQ multicolor real-time PCR detection each primer, and 5 (cid:3) l of DNA extract. Thermal cycling was performed using the following conditions: an initial incubation at 95°C for 10 min and then 45 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 60 s. The ampliﬁed region corre- sponded to a 681-bp region of the S gene (nucleotide [nt] 1564 to 2244; genotype A, serotype adw2). The PCR products were cloned into a pGEM-T-Easy vector (Promega, Madison, WI). The recombinant plasmids were puriﬁed, and the concentration of HBV DNA was determined using a spectrophotometer. Serial dilutions of the WHO standard, with concentrations ranging from 20 to 2.0 (cid:6) 10 6 IU/ml, were tested with the real-time PCR assay to obtain a standard curve. Subsequently, serial dilutions of HBV S gene plasmid DNA from a genotype A sample with concentrations ranging from 2.0 (cid:6) 10 2 to 2.0 (cid:6) 10 5 IU/ml were calibrated against the WHO standard. Finally, serial dilutions of the WHO standard and S gene plasmids of HBV genotypes A through H with concentrations ranging from 2.0 (cid:6) 10 2 to 2.0 (cid:6) 10 7 IU/ml were tested in parallel with the real-time PCR assay to compare the ampliﬁcation efﬁciencies across these genotypes.
One-Class Classiﬁcation Using (cid:96) p -Norm Multiple Kernel Fisher Null-Space

—The paper addresses the one-class classiﬁcation (OCC) problem and advocates a one-class multiple kernel learning (MKL) approach for this purpose. To this aim, based on the Fisher null-space one-class classiﬁcation principle, we present a multiple kernel learning algorithm where an (cid:96) p -norm constraint ( p ≥ 1 ) on kernel weights is considered. We cast the proposed one-class MKL task as a min-max saddle point Lagrangian optimisation problem and propose an efﬁcient method to solve it. An extension of the proposed one-class MKL approach is also considered where several related one-class MKL tasks are learned concurrently by constraining them to share common kernel weights. An extensive assessment of the proposed method on a range of data sets from different application domains conﬁrms its merits against the baseline and several other algorithms.
4 - Champs de Markov cachés et estimation conditionnelle itérative

This work deals with the parameter estimation problem in hidden Markov fields . The principal goal is the comparison of methods deriving from a recent general procedure of estimation in the case ofhidden data, Iterative Conditional Estimation (ICE), with some existing algorithms. The paper starts with the recall of the importance of the hidden Markov fields estimation problem in unsupervised image segmentation. Then we compare ICE methods with sonie existing algorithms at different levels : principle, generality of models, difficulty of its implementation. The Stochastic Gradient of L. Younes and the Gibbsian EM of B . Chalmond are compared with ICE methods in some detail . The principle of ICE, different from principles of all existing methods, allows the conception of algorithms applicable in a quite general framework. Furthermore, the EM formulae can be obtained by ICE and, in this sense, it can be seen as particular ICE case .
Boundary Conditions for 3D Fluid-Structure Interaction Simulations of Compliant Vessels

The goal of this study was to investigate different outlet boundary conditions for a straight compliant tube, by the means of fluid-structure interaction simulations. In addition to investigating boundary conditions it was desirable to see how different parameters, like time step, grid refinement and CFL-number would influence the results. Simulations were run with different time steps and grids. Changing these parameters had only minor influence on the results of the simulations, except for very small time steps, when the simulations would not converge. Four different boundary conditions were tested at the outlet: A reflection free boundary, an imposed reflection factor of 0.9, a two-element Windkessel model and a three-element Windkessel model. The reflection free model gave almost no reflections, while the simulation with a reflection factor of 0.9 gave the imposed amount of reflections at the outlet. For the reflection free case, comparing the results with simpler, analytical solutions gave poor accuracy, because the assumption of Poiseuille flow was invalid. Changing the velocity profile at the inlet from uniform to parabolic improved the accuracy. The two-element Windkessel model was not able to model a reflection free outlet. Reflections would occur even when the parameters were chosen to give a theoretically reflection free outlet. This was improved by using the three-element Windkessel model. When choosing parameters that would theoretically give zero reflections, the amount of reflections was very low.
Indoor Navigation Control System for Visually Impaired People

— Blindness affects the perception of the surrounding environmental conditions. The primary requirement of any visual aid for mobility is obstacle detection. This work proposes an indoor navigation system for the visually impaired people. The system presented in this study is a robust, independent and portable aid to assist the user to navigate with auditory guidance. Computer-based algorithms developed in C sharp for the Microsoft Xbox Kinect 360 sensor allows to build a device for the navigational purpose. Kinect sensor streams both colour and depth data from the surrounding environment in real-time, which is then processed to provide the user with directional feedback using the wireless earphones. The effectiveness of the system was tested in experiments conducted with six blindfolded volunteers who successfully navigated across various indoor locations. Moreover, the user could also follow a specific individual through the output generated from the processed images.
International Journal of Agriculture and Environmental Research

This paper analysed the impact of irrigation project on agro pastoral household income in Fentalle district. It analysed factors determining agro-pastoralist participation in irrigation. The study result depends on cross-sectional data collected from a sample of 144 households of which 72 irrigators and 72 non-irrigators using a combination of multistage disproportionately stratified, and random sampling. It used descriptive statistics, test statistics and logistic regression to assess the factors that affect participation in irrigation, performed propensity score matching, and treatment effect analysis. The Result revealed that access to irrigation has intense impact on improving household income. It was observed that among the variables in logistic regression age, sex, ln income, input use and participation in cooperative organization have affected positively, while, farm experience, distance to the district market, and tropical livestock unit, affected participation in irrigation negatively and significantly. Further, the study substantiated that irrigation in the study area has significantly improved the income level. It shall be great and rewarding if policy makers, designers, implementers, and any funding agencies with similar interest further capitalise and scale up the project to achieve the development plan and objective.
Predictive gene signatures

Cancers exhibit abnormal molecular signatures associated with disease initiation and progression. Molecular signatures could improve cancer screening, detection, drug development and selection of appropriate drug therapies for individual patients. Typically only very small amounts of tissue are available from patients for analysis and biopsy samples exhibit broad heterogeneity that cannot be captured using a single marker. This report details application of an in-house custom designed GenomeLab System multiplex gene expression assay, the hCellMarkerPlex, to assess predictive gene signatures of normal, adenomatous polyp and carcinoma colon tissue using archived tissue bank material. The hCellMarkerPlex incorporates twenty-one gene markers: epithelial (EZR, KRT18, NOX1, SLC9A2), proliferation (PCNA, CCND1, MS4A12), differentiation (B4GANLT2, CDX1, CDX2), apoptotic (CASP3, NOX1, NTN1), fibroblast (FSP1, COL1A1), structural (ACTG2, CNN1, DES), gene transcription (HDAC1), stem cell (LGR5), endothelial (VWF) and mucin production (MUC2). Gene signatures distinguished normal, adenomatous polyp and carcinoma. Individual gene targets significantly contributing to molecular tissue types, classifier genes, were further characterised using real-time PCR, in-situ hybridisation and immunohistochemistry revealing aberrant epithelial expression of MS4A12, LGR5 and prior to development of carcinoma. Identified gene signatures identify aberrant epithelial expression of genes prior to cancer development using in-house custom designed gene expression multiplex assays. approach may be used to assist objective classification staging, progression and therapeutic responses using biopsy
Illustrated Technical Paper - A Pub/Sub SDN-Integrated Framework for IoT Trafﬁc Orchestration

This " ILLUSTRATED TECHNICAL PAPER " presents the slides describing the contents of the paper "A Pub/Sub SDN-Integrated Framework for IoT Trafﬁc Orchestration". The talk was presented at the 3rd International Conference on Future Networks and Distributed Systems - ICFNDS 2019 , 1 - 2 July 2019 at Paris, France. The "illustrated technical paper format" is intended to complement, enrich and subsidize the technical paper content and contains slides, complementary text and additional and/or focused bibliographic references.
Development and characterization of a panel of anti-idiotype antibodies to 1C10 that cross-neutralize HIV-1 subtype B viruses

The V3 loop of the human immunodeficiency virus type 1 (HIV-1) envelope protein (Env) is one of the conserved immunogenic regions targeted by neutralizing antibodies (nAb). Two different binding modes of anti-V3 abs have been reported in studies using two V3 mimotopes: the ladle-type and cradle-type. We previously isolated a ladle-type nAb, 1C10, that potently and broadly neutralized clade B viruses. Despite its potent neutralization activity, 1C10 possesses no unique features in its amino acid sequence. We hypothesized that the neutralization potency of 1C10 is derived from its antigen-binding characteristics, which are not a consequence of the two previously reported binding modes of anti-V3 nAbs. To analyze epitope-paratope interactions between 1C10 and the V3 loop, we produced five anti-idiotypic antibodies (anti-Id abs) from mice immunized with 1C10 nAb. The idiotopes of the anti-Id Abs on the 1C10 heavy chain were estimated by alanine scanning, germline reversion mutagenesis, and a 1C10 sibling clone. Next-generation sequencing combined with homology modeling revealed contact between R315 at the tip of the V3 loop and 1C10 by D53 of CDRH2 and Phe/Asp of CDRH3. These amino acids were enriched in the anti-Id-ab-reactive B cell receptors encoded by the IGHV3-30 gene. We also found that 20% of HIV-infected individuals had abs specific to the anti-Id abs, as well as both of the V3 mimotopes, that did not respond to the linear V3 peptide. Our findings showed that the anti-Id abs induced by 1C10 recognized a key amino acid formation essential for steric interactions between the ladle-type nAb and the V3 loop. We also revealed the coexistence of anti-V3 ab reactivity to V3 loop mimotopes and to the anti-Id abs in HIV-positive individuals.
Gaussian approach versus Dolph-Chebyshev synthesis of pencil beams for linear antenna arrays

A very simple and fast method for the synthesis of pencil beams with linear antenna arrays of equally spaced elements is presented. The proposed procedure starts selecting the desired pencil beam as a Gaussian function. This is very convenient for two reasons: first, the continuous line-source distribution that exactly produces the desired pencil beam (i.e. the Fourier transform of it) is in turn a Gaussian function and is immediately calculated. Second, a suitable weighted sampling of this distribution gives the excitations of the array elements in closed form. Two numerical examples reveal the good performances of the proposed approach, also in comparison with the classical method by Dolph-Chebyshev. It is shown that the synthesised array factors well approximate the desired pencil beams in real time, in particular ensuring a very good behaviour in the side lobe regions. Furthermore, the ‘dynamic range ratio’ of the excitations, defined as the ratio between the maximum and the minimum amplitude of the excitations, is very low and close to unity when the array length is sufficiently small.
Temporal sampling and network analysis reveal rapid population turnover and dynamic migration pattern in overwintering regions of a cosmopolitan pest

Genetic makeup of insect pest is informative for source-sink dynamics, spreading of insecticide resistant genes, and effective management. However, collecting samples from field populations without considering temporal resolution and calculating parameters related to historical gene flow may not capture contemporary genetic pattern and metapopulation dynamics of highly dispersive pests. Plutella xylostella (L.), the most widely distributed Lepidopteran pest that developed resistance to almost all current insecticides, migrates heterogeneously across space and time. To investigate its real-time genetic pattern and dynamics, we executed four samplings over two consecutive years across Southern China and Southeast Asia, and constructed population network based on contemporary gene flow. Across 48 populations, genetic structure analysis identified two differentiated insect swarms, of which the one with higher genetic variation was replaced by the other over time. We further inferred gene flow by estimation of kinship relationship and constructed migration network in each sampling time. Interestingly, we found mean migration distance at around 1,000 km. Such distance might have contributed to the formation of step-stone migration and migration circuit over large geographical scale. Probing network clustering across sampling times, we found a dynamic P. xylostella metapopulation with more active migration in spring than in winter, and identified a consistent pattern that some regions are sources (e.g., Yunnan in China, Myanmar and Vietnam) while several others are sinks (e.g., Guangdong and Fujian in China) over 2 years. Rapid turnover of insect swarms and highly dynamic metapopulation highlight the importance of temporal sampling and network analysis in investigation of source-sink relationships and thus effective pest management of P. xylostella, and other highly dispersive insect pests.
Perceived teacher autonomy support for adolescents’ reading achievement: The mediation roles of control-value appraisals and emotions

Analyzing students’ internal cognitive-motivational appraisals and achievement emotions is of pivotal importance for educational outcomes and student individual wellbeing, yet little is shown about their associations with teacher autonomy support. This study investigates the relationship between perceived teacher autonomy support and reading achievement by addressing mediating influences of control and value-related constructs, i.e., reading self-efficacy, meaning in life, and reading enjoyment. Multiple mediation modeling was adopted to test the proposed model with carrying out a total of 12,058 students from 361 schools in China in the Programme for International Student Assessment (PISA) 2018 reading database. The results elucidated that student-perceived teacher autonomy support is significantly positively related to adolescents’ reading outcomes by fostering internal control and value appraisals and academic enjoyment. These current findings confirm the positive correlation between teacher autonomy support and adolescents’ motivational and emotional factors, providing significant practical implications for educators to adopt various teaching strategies to enhance adolescents’ self-efficacy, intrinsic values, and positive emotions.
SemNet: Learning semantic attributes for human activity recognition with deep belief networks

Human Activity Recognition (HAR) is a prominent application in mobile computing and Internet of Things (IoT) that aims to detect human activities based on multimodal sensor signals generated as a result of diverse body movements. Human physical activities are typically composed of simple actions (such as “arm up”, “arm down”, “arm curl”, etc.), referred to as semantic features. Such abstract semantic features, in contrast to high-level activities (“walking”, “sitting”, etc.) and low-level signals (raw sensor readings), can be developed manually to assist activity recognition. Although effective, this manual approach relies heavily on human domain expertise and is not scalable. In this paper, we address this limitation by proposing a machine learning method, SemNet, based on deep belief networks. SemNet automatically constructs semantic features representative of the axial bodily movements. Experimental results show that SemNet outperforms baseline approaches and is capable of learning features that highly correlate with manually defined semantic attributes. Furthermore, our experiments using a different model, namely deep convolutional LSTM, on household activities illustrate the broader applicability of semantic attribute interpretation to diverse deep neural network approaches. These empirical results not only demonstrate that such a deep learning technique is semantically meaningful and superior to its handcrafted counterpart, but also provides a better understanding of the deep learning methods that are used for Human Activity Recognition.
Sandwich teaching improved students' critical thinking, self-learning ability, and course experience in the Community Nursing Course: A quasi-experimental study

The youngest generation of students prefers a more active learning style. Sandwich teaching may suit their learning style by alternating between active individual learning and passive collective learning. Sandwich teaching has been rarely applied to the Community Nursing Course for nursing students, and its teaching effects on this course remain unclear. This study applied Sandwich teaching to the Community Nursing Course for Chinese nursing undergraduates and investigated its effects on students' critical thinking, self-learning ability, course experience, and academic performance. This is a quasi-experimental study with 72 Chinese nursing undergraduates. Students receiving traditional teaching were enrolled in the control group (n = 36), and those who received Sandwich teaching were recruited into the experimental group (n = 36). Both groups received the 12-week, 90-min Community Nursing Course. Our main outcome variable, including students' critical thinking, self-learning ability, and course experience, was assessed by specific questionnaire. The paired t-tests were applied to compare the differences of the same group in the pre-test and the post-test, and the independent-sample t-tests were used to compare the differences between the two groups. We observed that nursing students' critical thinking ability and self-learning ability were significantly improved after receiving Sandwich teaching. Students' course experience of Sandwich teaching was significantly better than that of traditional teaching. The final exam score in the experimental group was not significantly higher than that in the control group. These results suggest that Sandwich teaching in Community Nursing Course improved Chinese nursing undergraduates' critical thinking, self-learning ability, and course experience, but failed in improving academic performance.
A review of non-destructive methods for the detection tiny defects within organic insulating materials

In recent years, solid organic materials such as silicone rubber and epoxy resin have been widely used in electrical equipment due to their excellent insulation properties. However, as a result of manufacturing and design flaws as well as aging issues during operation, the insulating materials in the linked state no longer fit tightly and tiny structural defects (defect size less than 10 mm) develop, such as debonding at the composite interface, pores or cracks within the insulating material, etc. Tiny defects are prone to partial discharges and breakdowns, compromising the safety of high-voltage power equipment, particularly when subjected to strong electric fields. Therefore, it is necessary to carry out non-destructive testing (NDT) for such tiny defects. Such defects are small in size, easily buried in the material, and even some are wrapped in metal, which in turn requires very high detection accuracy, but traditional methods are difficult to achieve, so NDT technologies for tiny defects within insulating materials have become a research hotspot in the field of electric power in recent years. This paper firstly introduces the sources of tiny defects in solid organic insulating materials for electrical equipment. Secondly, the harm caused by structural defects is elaborated. Finally, emerging NDT methods and their advantages and limitations in defect detection are described in detail. The review aims to provide the reader with a comprehensive overview of most of the NDT techniques used in the detection of tiny defects within solid organic insulating materials for electrical equipment and their most salient features.