Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Photometric Stereo-Based 3 Dimensional Object Reconstruction for Welding Application

Photometric stereo works on recovering the shape and reflectance properties of an object using multiple images taken in variable lighting conditions. In this study, a system has been implemented to construct a height field from 12 images of an object. The algorithm which is able to calibrate the lighting direction, find the normals and color albedo at each pixel have been optimized to compute the surface which best fit the normals. This algorithm was also implemented to the welding product to reconstruct the shape of welding bead.
Application of simulated annealing to solve multi-objectives for aggregate production planning

Aggregate production planning (APP) is one of the most significant and complicated problems in production planning and aim to set overall production levels for each product category to meet fluctuating or uncertain demand in future. and to set decision concerning hiring, firing, overtime, subcontract, carrying inventory level. In this paper, we present a simulated annealing (SA) for multi-objective linear programming to solve APP. SA is considered to be a good tool for imprecise optimization problems. The proposed model minimizes total production and workforce costs. In this study, the proposed SA is compared with particle swarm optimization (PSO). The results show that the proposed SA is effective in reducing total production costs and requires minimal time.
WGCNA-Based DNA Methylation Profiling Analysis on Allopurinol-Induced Severe Cutaneous Adverse Reactions: A DNA Methylation Signature for Predisposing Drug Hypersensitivity

Background: The role of aberrant DNA methylation in allopurinol-induced severe cutaneous adverse reactions (SCARs) is incompletely understood. To fill the gap, we analyze the DNA methylation profiling in allopurinol-induced Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) patients and identify the DNA methylation signature for predisposing allopurinol hypersensitivity. Methods: Genome-scale methylation analysis was conducted using the Illumina® HumanMethylation450 BeadChip. Weighted Gene Co-Expression Network Analysis (WGCNA) was utilized to analyze the data. Results: A total of 21,497 annotated promoter regions were analyzed. Ten modules were identified between allopurinol hypersensitivity and tolerance, with turquoise and yellow modules being the most significant correlation. ATG13, EPM2AIP1, and SRSF11 were the top three hub genes in the turquoise module. MIR412, MIR369, and MIR409 were the top three hub genes in the yellow module. Gene Ontology (GO) analysis revealed that the turquoise module was related to the metabolic process in intracellular organelles and the binding of various compounds, proteins, or nucleotides. The yellow module, however, was related to stimulus sensory perception in cytoskeletal elements and the activity of the receptor or transducer. Conclusion: DNA methylation plays a vital role in allopurinol-induced SCARs. DNA methylation profiling of SJS/TEN is significantly related to autophagy and microRNAs (miRNAs).
STRUCTURAL EQUATION MODELING IN DETERMINING FACTORS THAT INFLUENCE USER SATISFACTION OF KRS ONLINE IPB

Nowadays, Information and Communication Technology (ICT) cannot be separated in our lives, it becomes a basic necessity to us whether in daily life and even in organization or institution. Bogor Agricultural University (IPB) as one of the top five universities in Indonesia, uses one of ICT’s form which is Infomation System (IS) Services for their organizational activities. One of the IS Services in IPB is KRS Online IPB. KRS Online IPB is a website that facilitates academic study plan registration for students and it is a very important website for students in IPB. In order to maintain the good quality and the satisfaction of KRS Online, Structural Equation Model is used to analyze the factors that influence satisfaction and the relationship between indicators and construct based on EGOVSAT model. The result shows that utility and flexibility are the factors that influence user satisfaction of KRS Online IPB significantly. Keywords: Information System Services, Structural Equation Modeling, User Satisfaction.
Leak Localization in Looped Pipe Networks Based on a Factorized Transient Wave Model: Theoretical Framework

Urban water distribution systems are often made of loops to increase redundancy and improve reliability. The inherent feature of multipath wave propagation in looped networks has been the main obstacle to directly derive a factorized wave propagation model with decoupled leak location and size, which is essential for developing a robust and efficient leak localization method. To address this problem, this article proposes an efficient algorithm to estimate the transient hydraulic pressure and discharge at all nodes of a looped network using boundary measurements. Given these hydraulic properties, a factorized wave propagation model is formulated by applying conservation laws to a tree‐shaped control volume of the looped network. Based on this factorized model, a fast and efficient one‐dimensional search of the leak location along all pipes of a looped network is realized by the matched‐field processing technique. Numerical experiments demonstrate that an unknown leak anywhere in a five‐loop network with 13 pipes can be accurately and efficiently localized by the proposed method.
Laterally Movable Gate Field Effect Transistor (LMGFET) for microsensor and microactuator applications

A laterally movable gate field effect transistor (LMGFET) is designed and fabricated in our laboratory. Unlike previous moving gate FETs, the motion of the gate is lateral or parallel to the substrate plane rather than perpendicular to the substrate. The device provides direct coupling of mechanical motion to electronics in a MEM system. The coupling is linear as the current in a LMGFET is a linear function of gate position and hence motion. The device fabrication process developed here is compatible with standard, CMOS IC fabrication technology and the LIGA process for high-aspect ratio structures. A comb drive with a simple serpentine spring structure is used to drive the moving gate and to study its electrical response. The paper describes the fabrication process and analyzes performance of this novel device structure. The fabricated LMGFET is a sensitive tool to measure distance in the nanometer scale.
Multiple linear correlation and prediction of lifetime performance on the basis of first lactation fertility and production traits in Karan Fries cattle

Higher productions along with superior fertility are the functions of greater staying ability of dairy cattle in the herd. Present investigation was undertaken to evaluate lifetime traits and their prediction on the basis of first lactation traits in Karan Fries cows maintained at National Dairy Research Institute. Data of 5878 lactation records of 1988 adult cows pertaining to the period of 1978 to 2012 were collected for analysis. The phenotypic and genetic correlations of first lactation with lifetime traits were estimated and lifetime performance was predicted using backward elimination multiple linear regression models. Cumulative milk yield (CMY) analysis indicated that the Karan Fries cows achieved around 85% of their lifetime production by 4th lactation. Phenotypic and genetic correlations of lifetime production traits were positive with first lactation production traits, whereas the association was negative with first lactation fertility traits. The coefficient of variation and Mallow's Cp estimates of better fit models were lower and ranged between 12 to 18% and 2.51 to 6.00, respectively. Results indicated that the first lactation traits used for the prediction, best explained the variation in traits such as Lifetime yield upto two lactations (51.00%) and breeding efficiency (51.43%), on the basis of coefficient of determination (R 2 ) estimates. Regression models for predicting lifetime yield upto three lactations, milk yield per day of productive life and lifetime daughter pregnancy rate had moderate coefficient of determination estimates.
Identifying Suitable Location for Surface Rainwater Harvesting Using GIS and Analytical Hierarchy Process

Abstract Rainwater harvesting is old but auspicious technology of sustainable water resource management. In general, the immediate barriers for installing rainwater harvesting techniques is a universal problem which includes the availability of suitable place, initial cost, lack of desired, sound technology etc. The present paper mainly focuses on finding suitable locations for surface rainwater harvesting structures, validation and characterization of these areas using GIS and AHP methods. For validation and characterization of the location google earth and associated thematic layers have been used. The identification of appropriate locations for RWH structures for the Asansol Urban Area in Paschim Burdwan district of West Bengal has been made by utilizing eight different thematic layers in GIS environment. Different GIS layers such as surface elevation, land-use/land-cover, drainage, depression, geology, slope, rainfall and lineament have been used for identifying the suitable location. The result of the study depicts that most of the identified locations as high (10.62%) and very high (4.12%) are suitable for constructing any kind of natural or manmade RWH structure. The present method is comparatively cost effective and time saving which may be convenient for sustainable water resource management planning across the water scarce area in the world.
Mn(II) Sorption on Stream Sediments Sampled in Manganese Mining Area: Dynamics and Mechanisms

The stream sediments that have been impacted by manganese (Mn) containing wastewater for decades contain not only abundant microorganisms but also organic/inorganic substances. To achieve effective treatment of manganese (Mn)-containing effluent and recovery of Mn from water/sediments, the Mn(II) sorption behaviors and mechanism on sediments of a stream in Mn mining areas were studied. In addition, the study analyzed the effects of various factors (initial concentration, solution pH, sediment dose, contact time, and coexisting cations) on the Mn sorption efficiency of Daxin sediments, and explored the contribution of microbial activity in the sediment sorption of Mn(II). The results showed that the sorption process of Mn(II) on the sediments was consistent with the Elovich and Freundlich models, and the removal of heavy metals was maximum at 40 °C (62.47–98.93%), pH = 8 (77.51%), initial concentration of 1 mmol·L−1 (95.37%) and sediment dosing of 12 g·L−1 (98.93%). The addition of 50 mM NaN3 inhibited the microbial activity in the Daxin sediment, reducing the sorption and removal rates of Mn(II) by 0.605 mg·g−1 and 8.92%, respectively. After sorption, the proportion of the Fe–Mn oxidation(iron–manganese) state in Daxin sediments decreased from 54% to 43%, while the proportion of the exchangeable state increased by 10.80%. Microorganisms in the sediment had a positive effect on inhibiting heavy metal migration and reducing the bioavailability of contaminants in the soil. Through this study, we hope to further understand the sorption and desorption mechanism of manganese by stream sediments in manganese ore areas, so as to provide a guide on the management and recovery of Mn from stream sediments in manganese mining areas.
Advances in Nucleic Acid Amplification-Based Microfluidic Devices for Clinical Microbial Detection

Accurate and timely detection of infectious pathogens is urgently needed for disease treatment and control of possible outbreaks worldwide. Conventional methods for pathogen detection are usually time-consuming and labor-intensive. Novel strategies for the identification of pathogenic nucleic acids are necessary for practical application. The advent of microfluidic technology and microfluidic devices has offered advanced and miniaturized tools to rapidly screen microorganisms, improving many drawbacks of conventional nucleic acid amplification-based methods. In this review, we summarize advances in the microfluidic approach to detect pathogens based on nucleic acid amplification. We survey microfluidic platforms performing two major types of nucleic acid amplification strategies, namely, polymerase chain reaction (PCR) and isothermal nucleic acid amplification. We also provide an overview of nucleic acid amplification-based platforms including studies and commercialized products for SARS-CoV-2 detection. Technologically, we focus on the design of the microfluidic devices, the selected methods for sample preparation, nucleic acid amplification techniques, and endpoint analysis. We also compare features such as analysis time, sensitivity, and specificity of different platforms. The first section of the review discusses methods used in microfluidic devices for upstream clinical sample preparation. The second section covers the design, operation, and applications of PCR-based microfluidic devices. The third section reviews two common types of isothermal nucleic acid amplification methods (loop-mediated isothermal amplification and recombinase polymerase amplification) performed in microfluidic systems. The fourth section introduces microfluidic applications for nucleic acid amplification-based detection of SARS-CoV-2. Finally, the review concludes with the importance of full integration and quantitative analysis for clinical microbial identification.
Application of Big Data Analysis Techniques in Sports Training and Physical Fitness Analysis

With the development of sports and information technology, people use mathematical tools and computer technology to study sports data and mine the intrinsic value of sports data. Statistical methods are the most widely used to achieve this goal. The research purpose of sports effect evaluation research is to understand the impact of sports on physical fitness through mining and analysis of sports data and to provide theoretical guidance for the public to participate in fitness activities scientifically and effectively. At present, in the study of combining individual performance test data, the research on the standardization of physical fitness monitoring data for sports training is relatively scarce. Therefore, based on the background of big data, this paper integrates the existing data standardization work and designs a plan for the standardization of physical fitness monitoring data for sports training. Combined with machine learning, data preprocessing is performed to obtain the data required by the machine model. The comprehensive physical fitness rating model and the recommendation model are established to realize the development of physical fitness monitoring service applications. In the experiment, compared with the three classical methods, the results show that the classification accuracy of this paper is 4% higher than that of other algorithms, which can more intuitively reflect the characteristic samples of sports training. In this paper, the data mining and analysis technology based on feature indicators in the mining and application of sports data has great application value for human fitness guidance and has certain research value and market application prospects.
How Modularity Theory explains the main components of Digital Business Ecosystems

Technological disruption and social transformation have gone hand-in-hand in recent decades and caused radical changes in the viability of business strategies. This continuous change, happening with unprecedented speed, forces organizations to consider being part of new collaborative value creation networks, such as digital business ecosystems (DBEs). Although scholars have analyzed DBEs from different perspectives since its emergence over a decade ago, DBE research lacks its own theories. Through a single case study, the purpose of this study is to identify the main components and its relationships of the DBE of the Spanish instant mobile payment solution Bizum, under the Modularity Theory developed by Baldwin (2020a). The findings show that technology shapes the ecosystem and helps to create superior digital value as an instrument to solve technical or strategic bottlenecks. The main contribution of this study is that this theory can be considered as a first step for a DBE-specific theorisation.
An Improved Structural-Based Ontology Matching Approach Using Similarity Spreading

Increasing number of ontologies demand the interoperability between them in order to gain accurate information. the ontology heterogeneity also makes the interoperability process even more difficult. These scenarios let the development of effective and efficient ontology matching. The existing ontology matching systems are mainly focusing with subject derivatives of the concern domain. Since ontologies are represented as data model in structured format, In this paper, a new modified model of similarity spreading for ontology mapping is proposed. In this approach the mapping mainly involves with node clustering based on edge affinity and then the graph matching is achieved by applying coefficient similarity propagation. This process is carried out by iterative manner and at the end the similarity score is calculated for iteration. This model is evaluated in terms of precision, recall and f-measure parameters and found that it outperforms well than its similar kind of systems.
FPGA accelerated model predictive control for autonomous driving

Purpose – The purpose of this paper is to reduce the dif ﬁ culty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic research. Design/methodology/approach – In this paper, the MPC algorithm is written into FPGA by combining hardware with software. Experiments have veri ﬁ ed this method. Findings – This paper implements a ZYNQ-based design method, which could signi ﬁ cantly reduce the dif ﬁ culty of development. The comparison with the CPU solution results proves that FPGA has a signi ﬁ cant acceleration effect on the solution of MPC through the method. Research limitations implications – Due to the limitation of practical conditions, this paper cannot carry out a hardware-in-the-loop experiment for the time being, instead of an open-loop experiment. Originality value – This paper proposes a new design method to deploy the MPC algorithm to the FPGA, reducing the development dif ﬁ culty of the algorithm implementation on FPGA. It greatly facilitates researchers in the ﬁ eld of autonomous driving to carry out FPGA algorithm hardware acceleration research.
SMYD3 Promotes Cell Cycle Progression by Inducing Cyclin D3 Transcription and Stabilizing the Cyclin D1 Protein in Medulloblastoma

Simple Summary Medulloblastoma is the most common malignant pediatric brain tumor and is classified into four molecular subgroups: Wnt, Shh, Group 3, and Group 4. Of these subgroups, patients with Myc+ Group 3 MB have the worst prognosis. Using an RNAi functional genomic screen, we identified the lysine methyltransferase SMYD3 as a crucial epigenetic regulator responsible for promoting Group 3 MB cell growth. We demonstrated that SMYD3 drives MB cell cycle progression by inducing cyclin D3 transcription and preventing cyclin D1 ubiquitination. Using in vitro and ex vivo studies, we showed that SMYD3 suppression by shRNA and BCI-121 significantly impaired proliferation, resulting in the downregulation of cyclin D3, cyclin D1, and pRBSer795. Moreover, we are the first to show that SMYD3 methylates the cyclin D1 protein, indicating that the SMYD3 stabilizes cyclin D1 through post-translational modification. Collectively, our studies position SMYD3 as a promising treatment option for Group 3 Myc+ MB patients. Abstract Medulloblastoma (MB) is the most common malignant pediatric brain tumor. Maximum safe resection, postoperative craniospinal irradiation, and chemotherapy are the standard of care for MB patients. MB is classified into four subgroups: Shh, Wnt, Group 3, and Group 4. Of these subgroups, patients with Myc+ Group 3 MB have the worst prognosis, necessitating alternative therapies. There is increasing interest in targeting epigenetic modifiers for treating pediatric cancers, including MB. Using an RNAi functional genomic screen, we identified the lysine methyltransferase SMYD3, as a crucial epigenetic regulator that drives the growth of Group 3 Myc+ MB cells. We demonstrated that SMYD3 directly binds to the cyclin D3 promoter to activate its transcription. Further, SMYD3 depletion significantly reduced MB cell proliferation and led to the downregulation of cyclin D3, cyclin D1, pRBSer795, with concomitant upregulations in RB in vitro. Similar results were obtained following pharmacological inhibition of SMYD3 using BCI-121 ex vivo. SMYD3 knockdown also promoted cyclin D1 ubiquitination, indicating that SMYD3 plays a vital role in stabilizing the cyclin D1 protein. Collectively, our studies demonstrate that SMYD3 drives cell cycle progression in Group 3 Myc+ MB cells and that targeting SMYD3 has the potential to improve clinical outcomes for high-risk patients.
Development of Religious Education to Spread the Culture of Dialogue within Saudi Universities: Ethnographic Case Study

This project investigates how the culture of dialogue among university students might be improved by developing the university textbook of their course in religious education. Dialogue in Saudi Arabia has in the last decade become more important as an issue and the regime is seeking to improve the culture of the people through dialogue. This study seeks to contribute to this plan. From the huge number of university courses in Saudi Arabia, this study has chosen one as a case study with its textbook. The first step in doing so is to understand the present culture of dialogue within Saudi society by adopting the methodology of an ethnographic instrumental case study. To this end, teachers and students within the university were contacted as well as others outside who are interested in dialogue. At the same time, various documents relating to the culture of dialogue in Saudi Arabia were analysed, in order to discover the teachers’ and students’ behaviours vis-a-vis dialogue and the meaning behind these behaviours by classroom observations of male and female classes.
Buffer-Aware User Selection and Resource Allocation for an Opportunistic Cognitive Radio Network: A Cross-Layer Approach

In this paper, we focus on a cross-layer resource allocation problem for an opportunistic cognitive radio network, where secondary users (SUs) share a primary network’s licensed spectrum only when the primary network is sensed to be idle. We consider cooperative spectrum sensing, where SUs participate in sensing only when a benefit from resource allocation is guaranteed. Number of SUs for cooperative spectrum sensing is an important parameter as it defines both sensing and resource allocation performance. The fusion centre captures interaction between physical layer spectrum sensing, channel condition, and higher layer data buffer while selecting SUs for cooperative sensing. We consider heterogeneous data types at SUs’ data buffers during SU selection to make our system model more general. We form a mixed integer non-linear optimization problem, from which we select SUs’ set for sensing and resource allocation, appropriate sensing thresholds, and corresponding resource allocation parameters. Due to it’s combinatorial nature, the optimization problem is non-trivial. We devise an optimal algorithm to solve the optimization problem. Moreover, we also propose a computationally efficient and near-optimal greedy algorithm with suitable performance bounds. We also show advantage of our proposed optimal algorithms compared to other traditional methods through extensive simulations.