Miracle-dz/UniFAR-FTUs huggingface dataset:
Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris. L) are identified by QTL-based pooled sequencing

Background White mold (WM) is a major disease in common bean ( Phaseolus vulgaris L.), and its complex quantitative genetic control has limited the development of WM resistant cultivars. WM2.2 is one of the nine meta-QTL that has a major effect on WM tolerance. This QTL explains up to 35% of the phenotypic variation and was previously mapped to a large interval on Pv02. Our objective was to narrow the interval of this QTL using QTL-based bulk segregant analysis.Results The phenotypic and genotypic data from two RIL populations (R31 and Z0726-9), which possess different genetic backgrounds for white mold resistance, were used to select resistant and susceptible lines to generate subpopulations for bulk DNA sequencing, and reads were aligned against the sequence of the resistance parent. The QTL physical intervals for each RIL population were mapped by fixed SNPs in 10kb-2kb sliding windows. WM2.2 QTL was split into two regions WM2.2a (3.54-4.56 Mbp; euchromatic) and WM 2.2b (12.19 to 26.41 Mbp; heterochromatic) in populations R31 and Z0726-9, respectively. For each QTL interval, the possible functional contribution of significant non-synonymous and synonymous polymorphisms was investigated. Gene models encoding for pentatricopeptide repeat, gibberellin 2-oxidase, and heat-shock proteins are the likely candidate genes associated with WM2.2a resistance. A TIR-NBS-LRR class of disease resistance protein and a EF-TU receptor are potential candidate genes associated with WM2.2b resistance and most likely trigger a physiological resistance response to WM.Conclusion QTL-based pooled sequencing analysis revealed that the large genomic region associated with WM2.2 meta QTL consists of two major QTL each associated with a different WM resistance function. WM2.2a region is most likely associated with avoidance mechanisms while WM2.2b region triggers physiological resistance.
The design of a robotic hand with multiple actuators for children

This thesis details the development of a multi actuated hand designed for a five year old child. The thesis discusses the different methods of powering, controlling and manufacturing prosthetic devices; specifying the options chosen for this project. Following a feasibility study into advanced paediatric prosthetics (Redman et al., 2011), this research has aimed at improving the state of the art. It presents a modular device that has a powered opposable thumb and four individually powered fingers. A study into curling finger designs has produced a novel curling design that combines a natural closure trajectory with a mechanical advantage that is higher than other curling fingers. The final research represents a significant step in improving the functionality of prosthetic hands for children. Curling fingers and a driven opposable thumb are both abilities that have not been presented in devices aimed at children. The hand compares favourably to all commercially available paediatric prosthetic hands and advanced adult devices. The final point of this design that separates it from devices designed specifically for adults is that it can be easily scaled to produce versions for a range of age groups up to and including adults. This allows the research to start to address the issue of out-growing prosthesis. The device includes interchangeable modular parts that allow the hand to be "grown" with the child. These points are all aimed at increasing the acceptance of the child prosthesis. Acceptance of a device is the key to good prosthetic fitment. If the device is not fitted and then subsequently worn it renders any advancements inconsequential. To allow regular replacement of parts the modules have been designed to be low cost enough to be considered disposable. To achieve this, an evaluation of the feasibility of using rapid prototyping as a construction material for prosthetic devices has been completed, which concludes that the right printed material is suitable for this application. These features combine to deliver a device for children with a high level of dexterity that has only previously been seen on advanced adult devices. Thus, this thesis provided the basis for next generation rehabilitation devices for the next generation.
Digital sources: a case study of the analysis of the Recovery of Historical Memory in Spain on the social network Twitter

The incorporation of digital sources from online social media into historical research brings great opportunities, although it is not without technological challenges. The huge amount of information that can be obtained from these platforms obliges us to resort to the use of quantitative methodologies in which algorithms have special relevance, especially regarding network analysis and data mining. The Recovery of Historical Memory in Spain on the social network Twitter will be analysed in this article. An open-code tool called T-Hoarder was used; it is based on objectivity, transparency and knowledge-sharing. It has been in use since 2012.
Development strategy and process models for phased automation of design and digital manufacturing electronics

The strategy of quality of electronics insurance is represented as most important. To provide quality, the processes sequence is considered and modeled by Markov chain. The improvement is distinguished by simple database means of design for manufacturing for future step-by-step development. Phased automation of design and digital manufacturing electronics is supposed. The MatLab modelling results showed effectiveness increase. New tools and software should be more effective. The primary digital model is proposed to represent product in the processes sequence from several processes till the whole life circle.
Considering chain-to-chain competition on environmental and social concerns in a supply chain network design problem

ABSTRACT The supply chain network design problem has been widely studied as one of the most important issues in supply chain management. In recent years, competitive nature of markets caused researchers to attend the competition issue in their studies. In this research, a multi-objective mathematical model for dynamic and integrated network design of a competitive and sustainable supply chain is presented. In the proposed model, a chain-to-chain competition between two supply chains, who compete on environmental and social concerns, is considered. To solve this competitive model, a two-stage solution approach is introduced. A game theory approach is initially used to determine the equilibrium values for competitive decisions. Then, according to results of the competitive stage and respecting complexity of the proposed model, a Pareto-based multi-objective meta-heuristic algorithm is applied to solve the achieved network design problem. Finally, to evaluate the efficiency of the proposed model and presented solution approach, several generated numerical examples are graphically and statistically studied.
Highly Accelerated Multishot EPI through Synergistic Combination of Machine Learning and Joint Reconstruction

Purpose: To introduce a combined machine learning (ML) and physics-based image reconstruction framework that enables navigator-free, highly accelerated multishot echo planar imaging (msEPI), and demonstrate its application in high-resolution structural and diffusion imaging. Methods: Singleshot EPI is an efficient encoding technique, but does not lend itself well to high-resolution imaging due to severe distortion artifacts and blurring. While msEPI can mitigate these artifacts, high-quality msEPI has been elusive because of phase mismatch arising from shot-to-shot variations which preclude the combination of the multiple-shot data into a single image. We employ deep learning to obtain an interim image with minimal artifacts, which permits estimation of image phase variations due to shot-to-shot changes. These variations are then included in a Joint Virtual Coil Sensitivity Encoding (JVC-SENSE) reconstruction to utilize data from all shots and improve upon the ML solution. Results: Our combined ML + physics approach enabled Rinplane x MultiBand (MB) = 8x2-fold acceleration using 2 EPI-shots for multi-echo imaging, so that whole-brain T2 and T2* parameter maps could be derived from an 8.3 sec acquisition at 1x1x3mm3 resolution. This has also allowed high-resolution diffusion imaging with high geometric fidelity using 5-shots at Rinplane x MB = 9x2-fold acceleration. To make these possible, we extended the state-of-the-art MUSSELS reconstruction technique to Simultaneous MultiSlice (SMS) encoding and used it as an input to our ML network. Conclusion: Combination of ML and JVC-SENSE enabled navigator-free msEPI at higher accelerations than previously possible while using fewer shots, with reduced vulnerability to poor generalizability and poor acceptance of end-to-end ML approaches.
The contributions of human factors on human error in Malaysia aviation maintenance industries

Aviation maintenance is a multitasking activity in which individuals perform varied tasks under constant pressure to meet deadlines as well as challenging work conditions. These situational characteristics combined with human factors can lead to various types of human related errors. The primary objective of this research is to develop a structural relationship model that incorporates human factors, organizational factors, and their impact on human errors in aviation maintenance. Towards that end, a questionnaire was developed which was administered to Malaysian aviation maintenance professionals. Structural Equation Modelling (SEM) approach was used in this study utilizing AMOS software. Results showed that there were a significant relationship of human factors on human errors and were tested in the model. Human factors had a partial effect on organizational factors while organizational factors had a direct and positive impact on human errors. It was also revealed that organizational factors contributed to human errors when coupled with human factors construct. This study has contributed to the advancement of knowledge on human factors effecting safety and has provided guidelines for improving human factors performance relating to aviation maintenance activities and could be used as a reference for improving safety performance in the Malaysian aviation maintenance companies.
A Survey of FDD-Based Channel Estimation Schemes With Coordinated Multipoint

New enabling technologies that include millimeter wave (mmWave) communication, massive multiple-input-multiple-output (MIMO), and ultradense networks are set to transform the wireless communication systems. These emerging technologies contribute toward the evolution of fifth generation (5G) systems that promise greater connectivity, throughput, mobility, and reliability for communication networks. This article presents a comprehensive overview of techniques for channel estimation, particularly, frequency division duplex (FDD)-based estimation techniques for a communication network. An exhaustive literature survey of FDD-based estimation schemes is presented, with a comprehensive review of the coordinated multipoint (CoMP) strategies in 5G radio networks, and its reliance on acquisition of channel state information (CSI). Since accurate CSI promotes the adoption of channel precoding, and reliable signal detection in FDD-based 5G systems, therefore, channel estimation for CSI in conjunction with CoMP transmission is preferable. We also present future research directions for FDD-based channel estimation and CoMP in 5G.
Solving CCVRPTW using biased random key genetic algorithm (BRKGA) with multiple parent

This research addresses a Capacitated Vehicle Routing Problem with Time Windows (CCVRPTW) which is a Vehicle Routing Problem (VRP) with fleet capacity and delivery time constraints. In the research, a Biased Random Key Genetic Algorithm (BRKGA) is proposed to solve the problem. The standard BRKGA is improved by modifying the crossover process accommodating Multiple-Parent. The proposed BRKGA is coded using the Matlab programming language. A case of soft drink distribution is used to evaluate the performance of the algorithm. From the research, it can be concluded that (1) The proposed BRKGA is better than the heuristic method proposed by previous research for dealing with the same case; (2) the Multiple-Parent BRKGA can further improve the general BRKGA; (3) The Multiple-Parent BRKGA with third parent selected randomly from NON-ELITE group results in a better solution than that of selected randomly from the whole population.
PLING Adaptive Opportunity Checking of Web Service with Recommendation System

In the recent advancement of e-commerce, most of the populace in the world are using the World Wide Web for the retrieval of information and to perform various transactions through internet. This has led to the increase in the complexity of information retrieval and thereby creating hurdles on efficient and fast filtering of information. To overcome the above problem, and to help the online readers to handle huge volume of data, a new method of information filtering has to be created. In this paper we present a new hybrid filtering approach which is the combination of collaborative and content based filtering. Collaborative Filtering is the method of matching people who have similar interest, which is done by collecting desirous information from many users using Pearson Correlation Coefficient. Content Based Filtering uses Cosine S imilarity for analyzing the content of the user profile and the past browsing history maintained for each user. We present design of Adaptive Web Service Selection Framework that makes use of automated approach that systematically integrates all available training information such as past user, user similarity ratings as well content of user-paper rating, paper-user rating and user browsing history. The vital solution of our approach is simple relative frequency percentage bar to illustrate the combined approach which creates the most accurate web services recommendation to the individual user. The system is able to absorb the result of both filtering technique of information theories and it can be adopted for better and efficient recommendation. The results of this system reveals the fact that is able to dynamically offer recommended services based on end user’s interest. Keywords— Collaborative filtering; Cosine similarity; content based filtering; Pearson correlation coefficient; E-commerce.
Recommendation Algorithm Based on Restricted Boltzmann Machine and Item Type

Because of the sparsity of the ratings in the recommendation system, the calculation of the neighbors will be affected. The common method is to predict the missing ratings and calculate the neighbors with the prediction ratings. However, due to the deviation between prediction ratings and true ratings, it will also lead to the inaccuracy of nearest neighbors. In order to solve this problem, we use RBM to predict the missing ratings. Considering that the type or label of the item has certain influence on the rating, we introduce the type similarity of the item to modify the original neighbors. So that we get the neighbors which is closer to the target user. In this paper, the new model is applied to the MovieLens data set. The result shows that the results of the new model are better than collaborative filtering based on RBM and collaborative filtering based on SVD.
Phage-Display Selection of a Cell-Permeable Bicyclic Peptide as a Selective Ligand of the Human RNA Decapping Enzyme Dcp2

Dcp2 is an important enzyme that controls the stability of a subset of human cellular RNAs encoding functions such as transcription and immune responses. While >1800 Dcp2 substrates have been identified in human cells, compensatory gene expression changes secondary to genetic ablation of the DCP2 gene have complicated a complete mapping of its regulome. Cellpermeable, selective chemical ligands of Dcp2 could facilitate development of improved tools for elucidation of its function and cellular specificity. Here, we report the selection of a bicyclic peptide ligand of human Dcp2 from chemically cyclized phageencoded libraries, and evaluation of its affinity and selectivity for Dcp2 in vitro and in cells. Quantitative reverse transcription PCR (qRT-PCR) combined with a splinted ligation assay revealed that this stapled bicyclic peptide inhibits Dcp2 decapping activity toward specific RNA substrates inside human cells. We further demonstrate that CP21 increases formation of P-bodies, cellular liquid condensates enriched in intermediates of cellular RNA decay, in the same manner as deletion or mutation of Dcp2. Collectively, these results demonstrate development of a selective ligand of Dcp2 that modulates some of its functions inside cells. In the future, this molecule – and, more broadly, stapled peptide selection – may find utility in reverse chemical genetics to dissect the specificities of coexistent cellular RNA decay pathways.
Análise das manifestações patológicas em fachadas por meio de inspeção com VANT

A altura dos edifícios cria locais de difícil acesso que podem ter sua degradação mais acelerada pela falta de equipamentos hábeis para realização de inspeções prediais. Este artigo busca analisar os aspectos construtivos e as manifestações patológicas das fachadas industrializadas por meio de inspeções auxiliadas por Veículos Aéreos Não Tripulados (VANTs). A análise dos aspectos construtivos abrangeu visitas técnicas a edificação e observações realizadas no projeto arquitetônico da fachada industrializada. A análise das manifestações patológicas abrangeu a proposição e o teste de um método de inspeção para identificar as anomalias do revestimento externo. Com relação aos aspectos construtivos, observou-se que o projeto destas vedações exige níveis de detalhamento, tais como a paginação das fachadas, acompanhamento da produção e montagem dos painéis, assim como controle das juntas. Com relação ao método de inspeção testado, a técnica de obtenção das imagens por meio da estabilização do drone em pontos pré-determinados se mostrou mais eficiente que a técnica de frames em voos pré-definidos. Os resultados apontaram que a falta de detalhamento do projeto de fachada ocasionou falhas com relação à configuração dos orifícios de ventilação da câmara de ar e o aparecimento de manifestações patológicas prematuras. Por fim, conclui-se que os processos de inspeção com VANT podem contribuir para maior controle, precisão e periodicidade no monitoramento do comportamento das fachadas ao longo da sua vida útil, produzindo assim edifícios mais eficientes ambientalmente e resistentes à obsolescência.
Dynamic Optimization and Migration of Continuous Queries Over Data Streams

Continuous queries process real-time streaming data and output results in streams for a wide range of applications. Due to the fluctuating stream characteristics, a streaming database system needs to dynamically adapt query execution. This dissertation proposes novel solutions to continuous query adaptation in three core areas, namely dynamic query optimization, dynamic plan migration and partitioned query adaptation. Runtime query optimization needs to efficiently generate plans that satisfy both CPU and memory resource constraints. Existing work focus on minimizing intermediate query results, which decreases memory and CPU usages simultaneously. However, doing so cannot assure that both resource constraints are being satisfied, because memory and CPU can be either positively or negatively correlated. This part of the dissertation proposes efficient optimization strategies that utilize both types of correlations to search the entire query plan space in polynomial time when a typical exhaustive search would take at least exponential time. Extensive experimental evaluations have demonstrated the effectiveness of the proposed strategies. Dynamic plan migration is concerned with on-the-fly transition from
Left atrial mechanics in hypertrophic cardiomyopathy: discriminating hypertrophy and predicting fibrosis

BACKGROUND : Hypertrophic cardiomyopathy (HCM) and left ventricular hypertrophy (LVH) secondary to systemic hypertension (HTN) may be associated with left atrial (LA) functional abnormalities. We aimed to characterize LA mechanics in HCM and HTN and determine any correlation with the extent of fibrosis measured by cardiac magnetic resonance (CMR) in HCM patients. METHODS: Two-dimensional speckle tracking-derived longitudinal LA function was acquired from apical views in 60 HCM patients, 60 HTN patients, and 34 age-matched controls. HCM patients also underwent CMR, with measurement of late gadolinium enhancement (LGE) extension. Association with LA strain parameters was analyzed. RESULTS: The mean LV ejection fraction did not differ across groups. The E/e’ ratio was only preserved in the control group and significantly impaired in the HCM group. LA mechanics were significantly reduced in HCM, compared to the HTN group. LA strain rate in systole (LA-SRs) and late diastole (LA-SRa) were the best discriminators of HCM, with an area under the curve (AUC) of 0.8, followed by LA strain in systole (LA ɛsys) (AUC 0.76). LA-SRs and LA-SRa had high specificity (89% and 91%, respectively) and LA ɛsys had sensitivity of 80%. LA strain rate in early diastole (LA-SRe) was moderately correlated with the extension of LGE (r 2 0.42, p=0.027) CONCLUSIONS: LA-SRs and LA-SRa were the best discriminators for LVH secondary to HCM. LA-SRe was best correlated with the degree of fibrosis assessed by CMR. These findings suggest that LA mechanics can be potential predictors of disease severity in HCM.
Research on RMOLB Algorithms for Cloud Load Scheduling

An online load balancing resource scheduling algorithm (RMOLB) considering real-time and multi-dimensional resources is proposed. The algorithm is designed for real-time load balancing considering dynamic allocation of virtual machines in data centers. It is easy to operate and has good performance. The theoretical analysis proves that the algorithm has a competition ratio of 2-1/m, where m is the total number of physical machines. At the same time, through a large number of simulation analysis, it is found that RMOLB algorithm has certain advantages over other known algorithms in the key indicators of makespan (total completion time), capacity makespan (sum of capacity-completion time), imbalance degree and so on.
An effective approach for identifying defective critical fabrication path

Abstract Most defect signatures on wafers are caused by faulty tools. If these defects are not captured by in-line inspection tools or sampled during Defect Review-SEM, they are carried over multiple processing steps and discovered at the end of the fabrication procedure. Wafers with different defect signatures discovered at the end of the fabrication procedure are, most often, processed through same faulty tools. The fabrication paths of most defective wafers converge at some point to form a common sub-path before they disperse again. Usually, faulty tools in this common path cause most of the different defect signatures discovered at the end of the fabrication procedure. Process engineers would need to trace in reverse the fabrication paths to identify this common path to repair its tools. We introduce in this paper a defect diagnostic system called IDFP that can identify the common fabrication path that caused most of the defectivities on wafers discovered at the end of the fabrication procedure. We evaluated the quality of IDFP by experimentally comparing it with two systems. Results revealed marked improvement.