Miracle-dz/UniFAR-FTUs huggingface dataset:
Advance of Clustered Regularly Interspaced Short Palindromic Repeats-Cas9 System and Its Application in Crop Improvement

Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 is the third generation of novel targeted genome editing technology after zinc finger nucleases (ZFNs) and transcription activator like effector nucleases (TALENs). It is also one of the most promising techniques for mutating and modifying genes. The CRISPR-Cas9 system has the advantages of simplicity, high efficiency, high specificity, and low production cost, thus greatly promoting the study of gene function. Meanwhile, it has attracted the attention of biologists. After the development and improvement in recent years, CRISPR-Cas9 system has become increasingly mature and has been widely used in crop improvement. Firstly, this review systematically summarizes the generation and advantages of CRISPR-Cas9 system. Secondly, three derivative technologies of the CRISPR-Cas9 system are introduced. Thirdly, this review focuses on the application of CRISPR-Cas9 system in gene knockout, gene knock-in, and gene regulation, as well as the improvement of yield, quality, and biological resistance of important crops such as rice, wheat, soybean, corn, and potato. Finally, this review proposes the potential challenges of CRISPR-Cas9 system, and discusses the future development of CRISPR-Cas9 system.
EZH2-Mediated H3K27me3 Targets Transcriptional Circuits of Neuronal Differentiation

The Polycomb Repressive Complex 2 (PRC2) plays important roles in the epigenetic regulation of cellular development and differentiation through H3K27me3-dependent transcriptional repression. Aberrant PRC2 activity has been associated with cancer and neurodevelopmental disorders, particularly with respect to the malfunction of sits catalytic subunit EZH2. Here, we investigated the role of the EZH2-mediated H3K27me3 apposition in neuronal differentiation. We made use of a transgenic mouse model harboring Ezh2 conditional KO alleles to derive embryonic stem cells and differentiate them into glutamatergic neurons. Time course transcriptomics and epigenomic analyses of H3K27me3 in absence of EZH2 revealed a significant dysregulation of molecular networks affecting the glutamatergic differentiation trajectory that resulted in: (i) the deregulation of transcriptional circuitries related to neuronal differentiation and synaptic plasticity, in particular LTD, as a direct effect of EZH2 loss and (ii) the appearance of a GABAergic gene expression signature during glutamatergic neuron differentiation. These results expand the knowledge about the molecular pathways targeted by Polycomb during glutamatergic neuron differentiation.
Enhancing Activity in the Right Temporoparietal Junction Modifies the Effect of a High CEO-to-Employee Pay Ratio on the Perceived Investment Potential in the Construction Industry

As an increasing number of governments require the disclosure of companies’ compensation information, compensation management is becoming an important part of internal management in the construction industry. Although the literature has shown that disclosing a high CEO-to-employee pay ratio will cause various effects on the decision-making of a company’s potential investors, there is little evidence on the neural basis of such effects. Given that previous neuroscience studies have shown that the right temporoparietal junction (TPJ) is associated with altruistic behaviors, this study used transcranial direct current stimulation (tDCS) to explore the role of the right TPJ in the effects of the CEO-to-employee pay ratio on potential investors’ perceived investment potential in the construction industry. The results show that enhancing activity in the right TPJ significantly reduced the perceived investment potential of female participants, especially those with no investment experience, when the company’s CEO-to-employee pay ratio is high compared to when the pay ratio is medium. This effect was not observed in male participants. The mechanisms underlying these effects of tDCS in the right TPJ on the perceived investment potential were also explored. The main contribution of this study lies in its pioneering exploration of the neural basis of investment decision-making regarding the CEO-to-employee pay ratio. Additionally, it reveals individual feature-based differences in the role of the TPJ in investment decision-making and its possible mechanisms.
Advances on Innate Immune Evasion by Avian Immunosuppressive Viruses

Innate immunity is not only the first line of host defense against pathogenic infection, but also the cornerstone of adaptive immune response. Upon pathogenic infection, pattern recognition receptors (PRRs) of host engage pathogen-associated molecular patterns (PAMPs) of pathogens, which initiates IFN production by activating interferon regulatory transcription factors (IRFs), nuclear factor-kappa B (NF-κB), and/or activating protein-1 (AP-1) signal transduction pathways in host cells. In order to replicate and survive, pathogens have evolved multiple strategies to evade host innate immune responses, including IFN-I signal transduction, autophagy, apoptosis, necrosis, inflammasome and/or metabolic pathways. Some avian viruses may not be highly pathogenic but they have evolved varied strategies to evade or suppress host immune response for survival, causing huge impacts on the poultry industry worldwide. In this review, we focus on the advances on innate immune evasion by several important avian immunosuppressive viruses (infectious bursal disease virus (IBDV), Marek’s disease virus (MDV), avian leukosis virus (ALV), etc.), especially their evasion of PRRs-mediated signal transduction pathways (IFN-I signal transduction pathway) and IFNAR-JAK-STAT signal pathways. A comprehensive understanding of the mechanism by which avian viruses evade or suppress host immune responses will be of help to the development of novel vaccines and therapeutic reagents for the prevention and control of infectious diseases in chickens.
Atypical Mycosis in Psittacine Birds: A Retrospective Study

A retrospective study was conducted on parrots submitted from necropsy to the Department of Veterinary Pathology, School of Biosciences and Veterinary, University of Camerino, Italy, from 2007 to 2018. From a total of 2,153 parrots examined at post-mortem, four cases were diagnosed with atypical mycosis and were considered for determination of the fungus species by PCR. A Fischer's lovebird (Agapornis fischeri), Peach-faced lovebirds (Agapornis roseicollis), and two Blue and Gold Macaws (Ara ararauna) from four different aviaries died after some days of lethargy and ruffled feathers. Records of gross necropsy and histopathological exams (H&E, PAS, and Grocott stain) were described and biomolecular analyses were carried out. No specific gross lesions were appreciated at necropsy, while histopathology evidenced a systemic mycosis in several organs, particularly in the lungs. In affected organs, broad and non-septate hyphae, suggestive of mycoses, were observed. Molecularly, Mucor racemosus (Fischer's lovebird) and M. circinelloides (Peach-faced lovebirds) were identified from formalin-fixed and paraffin-embedded (FFPE) lung and liver tissue. In addition, Alternaria alternata and Fusicladium spp. (respectively in male and female Blue and Gold macaws) were identified in FFPE tissue from several organs; whereas the role of Mucor spp. as true pathogens is well-demonstrated, and the behavior of A. alternata and Fusicladium spp. in macaws as opportunistic pathogens have been discussed. To our knowledge, this report is the first one reporting mucormycosis caused by M. racemosus and M. circinelloides in lovebirds, and A. alternata and Fusicladium spp. in macaws.
Activation and Regulation of NLRP3 by Sterile and Infectious Insults

Nod-Like Receptor (NLR) is the largest family of Pathogen Recognition Receptors (PRRs) that patrols the cytosolic environment. NLR engagement drives caspase-1 activation that cleaves pro-IL-1B which then gets secreted. Released IL-1B recruits immune cells to the site of infection/injury. Caspase-1 also cleaves Gasdermin-D (GSDM-D) that forms pores within the plasma membrane driving inflammatory cell death called pyroptosis. NLRP3 is the most extensively studied NLR. The NLRP3 gene is encoded by 9 exons, where exon 1 codes for pyrin domain, exon 3 codes for NACHT domain, and Leucine Rich Repeat (LRR) domain is coded by exon 4-9. Exon 2 codes for a highly disorganized loop that connects the rest of the protein to the pyrin domain and may be involved in NLRP3 regulation. The NLRP3 inflammasome is activated by many structurally divergent agonists of microbial, environmental, and host origin. Activated NLRP3 interacts with an adaptor protein, ASC, that bridges it to pro-Caspase-1 forming a multi-protein complex called inflammasome. Dysregulation of NLRP3 inflammasome activity is a hallmark of pathogenesis in several human diseases, indicating its highly significant clinical relevance. In this review, we summarize the existing knowledge about the mechanism of activation of NLRP3 and its regulation during activation by infectious and sterile triggers.
A dynamic threshold voltage MOSFET (DTMOS) for ultra-low voltage operation

To extend the lower bound of power supply to ultra-low voltages (0.6 V and below), we propose a dynamic-threshold voltage MOSFET (DTMOS) built on silicon-on-insulator (SOI). The threshold voltage of DTMOS drops as the gate voltage is raised, resulting in a much higher current drive than standard MOSFET at low power supply voltages. On the other hand, V/sub t/ is high at V/sub gs/=0, therefore the leakage current is low. We provide experimental results and 2-D device and mixed-mode simulations to analyze DTMOS and compare its performance with a standard MOSFET. These results verify excellent DC inverter characteristics down to V/sub dd/=0.2 V, and good ring oscillator performance down to 0.3 V for DTMOS. <<ETX>>
Modeling Semantic Relations from a Dependency-Based Graph: A Corpus-Based Network Analysis of Croatian Parliamentary Debates

The following paper examines the application of graph technologies to parliamentary data. Using the debates that took place in the Croatian Parliament between 2003 and 2017 as an example, it demonstrates how natural language processing (NLP) tools, graph databases, and network algorithms can be used to conduct corpus statistical, stylometric, and semantic analysis. Special attention will be paid to the structure of morpho-syntactically tagged corpora, which are embedded in a property graph database that enables the exploration of corpus-specific semantic relations. As will be shown, such a structure allows parliament-ary data to be empirically analyzed with regard to the communication, conceptualization, and framing of social identities, interactions, institutions, and cultural models.
Microsoft Word-64447191-file00.docx

250 Introduction 616 Discussion 1061 Abbreviations: CL, systemic clearance (after intravenous administration); CYP, Cytochrome-P450; IVIVE, in vitro to in vivo extrapolation; PD, pharmacodynamics; PK, pharmacokinetics; Vss, volume of distribution at steady state (after intravenous administration). This article has not been copyedited and formatted. The final version may differ from this version. DMD Fast Forward. Published on July 2, 2014 as DOI: 10.1124/dmd.114. 058099 at A PE T Jornals on M ay 2, 2022 dm d.aspurnals. org D ow nladed from
A Real-time Algorithm for Finger Detection in a Camera Based Finger-Friendly Interactive Board System

This paper proposes an approach to finger detection for a type of camera based interactive board. In this approach, finger finding is confined within a stripe that is the projection of the edge of the board on the image plane with respect to a camera instead of using global search. The region where a finger intersects with the stripe is first detected and segmented from the background. A region growing algorithm is then applied to the region to segment the whole finger. This approach can detect multi-targets and be implemented efficiently, processing 30 or more 640×120 images per second even in a cheap DSP.
The Impact of Migration on Vietnam Household Living Standards

This study is conducted to investigate the impact of migration on living standards of households with migrants in the context of Vietnam. Data were collected from the results of Vietnam Household Living Standards in the time series. Blinder–Oaxaca decomposition was employed to decompose the source of differences in income between households with migrants and households without migrants. The results show that households with migrants in the multiyear dataset had a higher income than nonmigrant households, and migration had different impacts on expenditure at different quantiles. By conducting quantile regression, migration had positive impacts on expenditures at the 10% and 50% quantile, but no impact at the 90% quantile. Based on the findings, some implications in policies for managers, such as appropriate policies for poor workers in order to improve their living standards, especially poor households in rural or mountainous areas, are proposed.
A robust optimized convolutional neural network model for human activity recognition using sensing devices

Human activity recognition has become an expansive field of interest in recent years, both in academic and industrial research. Human Activity recognition (HAR) is concerning the prediction of person's movement or action such as walking, standing, sitting, up and downstairs, etc. Convolutional neural network (CNN) is a key component with deep learning. The main objective of this study is to design and implement an activity recognition algorithm in the state of the art of deep learning systems which accomplish superlative performance to detect human activities. Accordingly, an extensive comparison has been developed between different deep learning algorithms such as classical (CNN) models and Recurrent Neural Network (RNN) models with respect to the major human activities. Furthermore, a robust (CNN) deep learning model has been built up and proposed in order to enhance the recognition precision of human activities. This proposed model uses raw data acquired from a set of inertial sensor and exploring numerous human achas been built up and proposedtivities; sitting, standing, jogging, walking, and etc. Experimental results show that the precision of the proposed deep structure has achieved 97.5% with respect to the NAdam optimizer which would be considered as the most effectively recognizer compared to other deep learning architectures.
The Biomechanical Effects of Variability in Femoral and Tibial Component Rotational Alignment in TKA using a Simulated Oxford Rig

ii Acknowledgments . iv Vita . vi List of Tables. viii List of Figures . ix Chapter 1: Introduction . 1 1.1 Focus of Thesis . 6 1.2 Significance of Research . 7 1.3 Overview of Thesis . 9 Chapter 2: Hip Kinematics Simulation Study . 10 2.
Effects of Persistent Drought and Re-watering on the Seedling Growth and Development of Switchgrass during Tillering Stage

The drought resistance of switchgrass seedling is a key factor limiting its growth in arid and semi-arid areas.Drought-resistance indicators and recovery growth after re-watering of switchgrass seedling were studied with split-unit design.Effects of persistent drought on the seedling growth and development of switchgrass differed from different varieties(lines). The Xiji 2(from Alamo) had better droughtresistance than others.The growth of switchgrass seedling was restrained with the increasing of drought stress.The top of seedling was firstly restrained when drought stress was less than 10 days and soil moisture content(SWC) was higher than 3.7%. The seedling was completely restrained with the loss of leaf water and chlorophyll content reduced sharply,whereas root/shoot ratio,MDA content,the SOD,CAT and POD activities of seedling were increased when drought stress for 12 days.The top of seedling was dry and the new sprout grew after re-watering.Switchgrass would be dying and could not be revived after rewatering if drought stress was more than 12 days(more than 14 days for Xiji 2). Therefore,Xiji 2 might be a suitable variety recommended for use in the lack of rain areas and should be re-watered timely to rescue seedling after more than 10 days of drought stress and SWC was under 3.7%.
Analyzing the Role of Copper in the Soot Oxidation Performance of Bamno3-Perovskite-Based Catalyst Obtained by Modified Sol-Gel Synthesis

9 A series of BaMn 0.7 Cu 0.3 O 3 solids were prepared by a modified sol-gel method in which 10 carbon black (VULCAN XC-72R), and different calcination temperatures (BMC3-CX, 11 where X indicates the calcination temperature) have been used. The fresh and used 12 catalysts were characterized by ICP-OES, XRD, XPS, FESEM, TEM, O 2 -TPD and H 2 - 13 TPR. The presence of a carbon black during sol-gel synthesis of BMC3 mixed oxide 14 allows diminishing the calcination temperature needed to achieve the perovskite 15 structure, but it hinders the formation of the BaMnO 3 polytype. The use of low 16 calcination temperatures during synthesis reduces the sintering effects, and the mixed 17 oxides present lower particle size, slightly higher BET surface areas and macropores 18 with lower diameter than BMC3. The distribution of copper in BMC3-CX catalysts 19 depends on the calcination temperature and copper insertion into the perovskite 20 structure is promoted as the calcination temperature increases. All BMC3-CX catalysts 21 are active for NO to NO 2 and NO x -assisted soot oxidation processes, but only BMC3-22 C600 and BMC3-C700 show higher catalytic activity than BMC3 reference catalyst. 23 BMC3-C600 presents the best performance as it features a high amount of surface 24 copper and oxygen vacancies that increase during reaction. The comparison between 25 the performance of the best catalysts of the BM-CX series (BM-C700) and of the BMC3-26 CX series (BMC3-C600) suggests that the unique advantage of using copper in the 27 modified sol-gel synthesis is an additional decrease of 100ºC in the calcination 28 temperature used for the synthesis, which is 700ºC for BM-CX and 600ºC for BMC3-CX.
Characterization and comparative study on chemically treated luffa fiber as reinforcement for polylactic acid bio-composites

Luffa reinforced polylactic acid (PLA) bio-composites were prepared and examined. The luffa surface was treated using three chemicals, i.e., sodium hydroxide, 3-aminopropyltriethoxysilane, and acetic anhydride, which enhanced luffa compatibility with PLA. Mechanical testing was done on the chemically modified luffa reinforced PLA bio-composites, i.e., tensile, flexural, hardness, and thermal. Infrared spectral functional group and morphological analyses were performed on each sample. The results showed increases in tensile and flexural strength of 7.1% and 6.9% for sodium hydroxide, 5.7% and 1.4% for silane, and 4.3% and 0.4% for acetylation, respectively, especially to the surface-treated samples at 15 wt. % fiber volume, and a decrease in water uptake (%). Fourier transform infrared spectroscopy confirmed that the chemical surface treatments were successful with the removal of lignin and hemicellulose structures, which cause the surface structure of the modified fiber to be rough. Smooth surfaces were observed through SEM images. Thermal stability was enhanced due to improved interfacial bonding between luffa and PLA, eliminating other constituents and impurities. Moreover, the morphological analysis showed improved bonding compatibility between the luffa and PLA matrix.
Dynamic quantile regression for trend analysis of streamflow time series

Water availability is an essential factor in maintaining the integrity of ecological processes and is a source of socio‐economic development. However, socio‐economic development increases the pressure on water resources. Thus, understanding the flow regime in a watershed is essential to correct water resource management. In this study, we propose using dynamic quantile regression (DQR) to analyse trends in streamflow time series. DQR is a subset of the general class of semi‐parametric quantile regression models, which is tailored for time series modelling. It allows for autoregressive dynamics and modelling of trending behaviour and seasonal fluctuations. With a single model, it is possible to estimate the impacts of predictor variables on any given quantile of the response distribution instead of simply evaluating such effects on the mean response, as is typically done in other statistical approaches. In other words, it is possible to gain knowledge on how predictors impact the magnitude of streamflow in wet (upper quantiles) and dry seasons (lower quantiles) separately. We used DQR to model a streamflow time series of 27 gauges, distributed in the Araguaia watershed in central Brazil. The results show that, except for a single gauge (Alto Araguaia), there are downward streamflow trends, thus non‐stationary behaviour. The model yielded excellent data fits (pseudo‐R2 above 0.80), and it was possible to obtain a confidence interval for each slope. In our analysis, the usefulness of DQR modelling for assessing trends in streamflow time series is shown and, consequently, for achieving efficient water resource management.
Robust optimisation approach for bidding strategy of renewable generation-based microgrid under demand side management

In the restructured electricity market, operator of grid-connected microgrid (MG) tries to supply local load at the lowest cost from alternative energy sources including upstream grid, gas-turbines as local dispatchable units and renewable energy sources (photovoltaic systems and wind-turbines) as well as charge/discharge of energy storage system. In order to purchase power from upstream grid, the bidding curve of MG should be prepared to bid to the market operator. Therefore, this study proposes a robust optimisation approach (ROA) for obtaining optimal bidding strategy of MG. Also, MG operator uses time-of-use rate of demand response program (DRP) to reduce procurement energy cost. For this purpose, ROA is used for uncertainty modelling of upstream grid prices in which the minimum and maximum limits of prices are considered for the uncertainty modelling. The lower and upper bounds of price are consecutively subdivided into sequentially nested subintervals which allow formulating robust mixed-integer linear programming problems. The bidding strategy curves of MG for each time considering DRP are obtained from sufficient data by solving these problems. To show the capability of proposed approach, two cases are studied.
The revival of commercial shipbuilding in the USA. Discussion. Author's closure

Twice in the 20th century the United States has been the dominant shipbuilding nation in the world and twice has the advantage been lost. Commercial shipbuilding is virtually non-existant in the USA today. This paper traces the developments since World War II and proposes a solution for a revival of the U.S. commercial shipbuilding industry. The paper describes a new ship design and construction method which along with the existing favorable labor conditions and U.S. technology should make it possible for some U.S. shipyards to compete in the international market.