Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Kalman Filtering and Recursive Maximum Likelihood Estimation Approaches to Fault Detection and Identification of Boeing 747 Sensors and Actuators

In this paper, a joint state and parameter estimation scheme is applied to address the problem of detection and identification of loss of effectiveness faults in both sensors or the actuators of a Boeing 747 longitudinal model. The Kalman filter and the recursive maximum likelihood schemes are used for the state and the parameter estimations, respectively. Compared to the other simultaneous state and parameter estimation methods, the proposed strategy maintains the linearity of the system and can also be applied to both sensor or actuator faults. In simulation studies conducted, our proposed approach is compared to the adaptive structure multiple-model scheme. In view of the computational resources considerations, the method proposed in this paper is more efficient than the adaptive structure multiple-model technique and also has the potential to detect and identify faults with lower severities as well as concurrent faults.
Rapid Identification of Multiple Gases

Rapid identification of low-leveled toxic and harmful gases is of a challenge in current environmental monitoring. In this paper, we combined convolutional neural networks and bidirectional long short-term memory neural network, and proposed a method for fast identifying gases existing in trace amount in the environment. The attention mechanism was introduced to extract the key features of the input, and the Bayesian optimization method was applied to optimize the hyper-parameters. In order to evaluate the proposed method, we ran experiments using the low-concentration gas sensing data employing several existing predictive methods and the proposed one, and eventually compared their performances with recall and F1-score metrics. The results demonstrate that the performance of the proposed method exceeds that of the other methods, and also gives better performance on classifying gas components, given the gas concentration is below 125 ppm and the response time is limited to 0.5s.
Standardizing Zebrafish Behavioral Paradigms Across Life Stages: An Effort Towards Translational Pharmacology

Zebrafish is a prominent vertebrate model, with many of its advantages related to its development, life cycle, and translational ability. While a great number of behavioral phenotypes and tasks to evaluate them are available, longitudinal studies across zebrafish life stages are scarce and made challenging because of the differences between protocols and endpoints assessed at each life stage. In this mini review, we highlight the relevance that longitudinal studies could have for neurobehavioral pharmacology using this model. We also present possible strategies to standardize behavior endpoints in domains related to human diseases throughout the life cycle, especially between larvae and adult fish. Furthermore, we discuss the remaining difficulties of these analyses and explore future advances needed to bridge this knowledge gap.
Adaptive Self-Guided Loop Filter for Video Coding

This paper describes an adaptive self-guided loop filter for video coding. The filter acts as a loop filter to reduce the artifacts caused by quantization. The proposed filter is applied on the reconstruction samples of a Transform Unit (TU). The unfiltered input block is regarded as a guidance for self-guided edge-preserving smooth filtering. The filtering strength for each sample inside the input block is decided according to the TU size, corresponding QP, and statistical information generated from a designed filtering window adaptively. The proposed filter could be performed as a prediction-loop-filter in which the filtered samples can be referenced by intra prediction. Alternatively, the proposed filter can be moved to the post-loop-filter stage that after the deblocking filter for a low decoding dependency. The proposed method has been implemented and tested according to the common test conditions in Versatile Video Coding (VVC) test model version 11.0 (VTM 11.0). The post-loop-filter version can achieve 0.46% and 0.41% BD-rate reduction in All Intra and Random-Access configurations respectively.
Models, Metaphors and the Hermeneutics of Designing

functions of models are not founded on their logical structures but on their metaphorical structures. Models are metaphors, and metaphors convey their meanings by way of a hermeneutical understanding. Therefore the assessment of the validity of a model of designing must be made by referencing hermeneutical criteria, such as the accuracy with which the model translates the design process as experienced in everyday designpractice and the degree to which the model conceals or discloses aspects of designing. Judged by these criteria, scientific models are disabling rather than enabling. They do not accurately translate what happens in the practice of designing, and they hide more than they reveal. By contrast, models based on herneneutical understanding are fully capable of giving felicitous translations of designing as they are directly experienced by designers.
An integrated framework to prevent unsafe proximity hazards in construction by optimizing spatio-temporal constraints

Hazardous proximity of construction resources, such as construction equipment, materials, and workers-on-foot has been identified as a distinct safety issue on construction jobsites. Spatial and temporal limits are practical constraints that coexist in movement of construction resources. Space and time conflicts could substantially hinder the productivity of ongoing activities as well as causing safety issues. Therefore, the spatial and temporal constraints and the state of construction resources need to be considered to prevent space-time conflicts and unsafe proximities. The state of a moving construction resource includes its position, moving direction/heading, speed, orientation, and other safety-related information. The area around each resource is divided into alert and warning areas which are quantified for them according to their corresponding spatial or proximity constraints. By integrating the states of resources, their warning/alert areas, and proximity constraints, as well as by visualizing them in time- integrated 2D space, a more precise understanding of potential hazardous situations can be achieved and therefore prevented. This paper presents a visual support tool aiming to reduce safety hazards in project planning stage by optimizing spatio-temporal proximities of resources. For this purpose, the developed method first optimizes potential movements of the resources by minimizing intersection of their warning areas and avoiding overlap of their alert areas. Thereafter, it visualizes the optimized locations of resources in time-integrated 2D space throughout the duration of their corresponding activities. In this way, the integrated visualization framework enables managers to make more judicious decisions and take corrective actions pertinent to safety hazards prevention. A numerical example with different scenarios and proximity measures is analyzed to test and validate the proposed framework.
Ethical work climate and firm performance.

This study aimed to investigate the relationship between Ethical Work Climate (EWC) and Firm Performance. The research conducted within Malaysian manufacturing companies. Since the unit of analysis was organization, 200 cases were selected randomly. The result of pilot test confirmed that all instruments are reliable to be used. Data was collected using a self-administered questionnaire. Managers as target respondent explained their perception via standardized questionnaires. Previous studies show that there is not enough documented research on such topics in Malaysia. So, it may open a new phase and develop the body of knowledge in this area. Based on the results, the study found a high correlation and significant relationship between EWC and Organizational Performance (OP) in Malaysian firms. It means the perception of managers regarding the ethical manners and ethical climate is positive.
Association of Serum Adipokines and Resting Energy Expenditure in Patients With Chronic Kidney Disease

Background and Aim Metabolic disorders are prevalent in patients with chronic kidney disease (CKD) and may lead to protein energy wasting (PEW). Adipokines improve connections between PEW and energy metabolism. We aimed to determine the relationship between adipokine levels and resting energy expenditure (REE) in patients with CKD. Methods A total of 208 patients in non-dialyzed CKD stages 3–5 were enrolled in this cross-sectional study. Serum adipokines (leptin, adiponectin, and interleukin 6 (IL-6) were measured using enzyme-linked immunosorbent assay. Patient's REE was measured using indirect calorimetry. Fat mass (FM) and lean tissue mass (LTM) were measured using multiple-frequency bioimpedance analysis. Spearman correlation analyses and multivariate linear regression models were used to assess the association between serum adipokines and REE. Results The mean age was 52.7 ± 14.6 years, and 26.9, 26.4, and 46.7% of our participants had CKD stages 3, 4, and 5, respectively. The median values of serum adiponectin, leptin, and IL-6 were 470.4 (range, 291.1–802.2), 238.1 (range, 187.9–418.4), and 4.0 (range, 2.4–9.5) pg/mL, respectively. The male participants had significantly lower FM% (P = 0.001) and lower leptin levels (P < 0.001) than the female participants. After adjusting for age, diabetes, high-sensitivity C-reactive protein, intact parathyroid hormone, LTM, and FM, multiple linear regression analysis revealed that serum leptin levels were significantly positively associated with REE in men rather than in women (P < 0.05). Serum adiponectin levels were inversely associated with REE in men, but this association disappeared while FM was additionally adjusted. Adiponectin levels in women were not correlated with REE (P > 0.05). IL-6 was not significantly associated with REE in either men or women. Conclusions A sex-specific relationship between serum adipokines (leptin and adiponectin) and REE was observed in patients with CKD stages 3–5, which was partly confounded by FM.
Inclusive Monetary Policy: How Tight Labor Markets Facilitate Broad-Based Employment Growth

This paper analyzes the heterogeneous effects of monetary policy on workers with differing levels of labor force attachment. Exploiting variation in labor market tightness across metropolitan areas, we show that the employment of populations with lower labor force attachment—Blacks, high school dropouts, and women—is more responsive to expansion-ary monetary policy in tighter labor markets. The effect builds up over time and is long lasting. We develop a New Keynesian model with heterogeneous workers that rationalizes these results. The model shows that expansionary monetary shocks lead to larger increases in the employment of less attached workers when the central bank follows an average inflation targeting rule and when the Phillips curve is flatter. These findings suggest that, by tight-ening labor markets, the Federal Reserve’s recent move from a strict to an average inflation targeting framework especially benefits workers with lower labor force attachment.
Control and data acquisition system to study dielectric breakdown in low-pressure DC plasma reactor with parallels electrodes

This work aimed to present the theory of dielectric breakdown of a glow discharge through the automation of gas injection (mass flow) systems with pressure control (pressure gauge) and voltage source with voltage control, in the reactor for the acquisition of rupture parameters for low-pressure glow discharges. Through the analysis of Paschen’s curves for the configuration with argon gases and atmospheric air, it was observed that the rupture potential for argon gas is lower than for atmospheric air, although the ionization potential of atmospheric air is lower about argon.
Noise Reduction Based on Dual Tree Complex Wavelet Transform-unfolding and Its Application in Fault Diagnosis

： The rolling element bearing works in a very complex environment. Early bearing fault features are relatively weak and easily to be overwhelmed by the large amount of noise. How to reduce the noise and extract the fault features accurately is a difficult problem. Novel noise reduction method is put forward based on dual tree complex wavelet transform (DTCWT) and maximum variance unfolding (MVU). The DTCWT is applied to rolling-bearing vibration signals to structure the high dimensional signal space. The MVU is used to extract the real signal subspace from high dimensional signal space and eliminate the noise interference of the noise subspace. The proposed method makes full advantage of the nonlinear feature extraction ability of the MVU algorithms and the perfect reconstruction and near shift invariance of the DTCWT. The simulation and the bearing engineering signal is carried out to inspect the noise reduction method, and the results demonstrate that DTCWT_MVU can effectively eliminate the noise component of the bearing signal and keep its characteristic waveform and improve signal to noise ratio (SNR) with the practical and generality.
Role of ZBTB38 Genotype and Expression in Growth and Response to Recombinant Human Growth Hormone Treatment

Abstract Context Single-nucleotide polymorphisms (SNPs) in ZBTB38 have been associated with idiopathic short stature (ISS) and adult height. Objective This study sought to (a) characterize the phenotype of ISS patients and their response to recombinant human growth hormone (rhGH) by ZBTB38 SNP genotype; (b) describe the relationship of ZBTB38 expression with normal growth; and (c) describe the in vitro effects of ZBTB38 knockdown on cell proliferation and MCM10 expression. Methods The genotype-phenotype relationship of rs6764769 and rs724016 were explored in 261 ISS patients and effects of genotype on response to rhGH were assessed in 93 patients treated with rhGH. The relationship between age and ZBTB38 expression was assessed in 87 normal children and young adults. Knockdown of ZBTB38 in SiHA cells was achieved with siRNAs and cell proliferation assessed with a WST-8 assay. Results We found that rs6764769 and rs724016 are in linkage disequilibrium. The rs724016 GG genotype was associated with lower birth length (P = 0.01) and a lower change in height SDS over the first year of treatment (P = 0.02). ZBTB38 expression was positively correlated with age (P < 0.001). siRNA-mediated knockdown of ZBTB38 resulted in increased cell proliferation at 72 and 96 hours posttransfection but did not alter expression of MCM10. Conclusions SNPs within ZBTB38 associated with ISS are linked to higher birth size within a cohort of ISS patients and a better response to rhGH therapy while ZBTB38 expression is positively related to age.
Current Trends in Software Engineering Research

Software engineering is dynamic disciplines that have continuous growth in research in identifying new methods, tools and methodologies that have cause vast improvement in software development and maintenance to be more reliable and efficient. Past research critics on cost reduction, quality and flexibility have endless try to design and develop many ways to improve these sectors are still causing impacts to the software industry [1]. The new trends in software engineering research topics resolves under the research field of Cloud Computing, Big Data, Android Computing, Network Security and Software Engineering Project Management. Nevertheless, there are more other research areas in software engineering that have been intense researched and implemented in the industries.
Exploring Prospective Research Areas in UI/UX through the Analysis of Patents

On UX/UI fields, understanding emerging technology is important for preoccupancy of a future market. Most of emerging field searching methods are qualitative methods. However, it is suitable for large companies to adduce its milestone, not for small enterprises. Thus, this study aims at purposing the improvement of utilizability for research field searching processes. We draw core patents with modified patent citation data, apply the Girvan-Newman clustering method based on bibliographic coupling patent relationship and then, draw emerging technology research UX/UI fields. Finally, the results were validated in comparison with a report on emerging research.
A self-supervised learning approach for astronomical images

MARTINAZZO, A. C. A self-supervised learning approach for astronomical images. 2021. Dissertação (Mestrado) Instituto de Matemática e Estat́ıstica, Universidade de São Paulo, São Paulo, 2021. Modern astronomical sky surveys are providing us with a flood of images with unusual characteristics, such as numerous channels, saturated signals, faint signals, uncertainties, and varying signal-to-noise ratios. The complexity and diversity of these images make them an adequate use case for deep convolutional neural networks. Moreover, they yield millions of detected objects whose classes are mostly unknown. Given this context, the main objective of this work is to investigate deep representation learning approaches for multichannel astronomical images, focusing on finding reasonable representations that do not require labeled data and that make use of some domain knowledge. A reasonable representation may be thought of as one that contains enough discriminative information, that can be later used for higher-level tasks such as object classification, outlier detection and clustering. We propose a self-supervised learning approach that makes use of astronomical properties (more specifically, magnitudes) of the objects in order to pretrain deep neural networks with unlabeled data. We choose the task of classifying galaxies, stars and quasars as a baseline for quantifying the quality of the learned representations, and empirically demonstrate that our approach yields results that are better than – or at least comparable to – a benchmark RGB model pretrained on ImageNet.
Towards a Taxonomy of Collective Emotions

This paper distinguishes collective emotions from other phenomena pertaining to the social and interactive nature of emotion and proposes a taxonomy of different types of collective emotion. First, it emphasizes the distinction between collective emotions as affective experiences and underpinning mechanisms. Second, it elaborates on other types of affective experience, namely the social sharing of emotion, group-based emotions, and joint emotions. Then, it proposes a working definition of collective emotion via a minimal threshold and four structural features. Finally, it develops a taxonomy of five types of collective emotion: emotional sharing, emotional contagion, emotional matching, emotional segregation, and emotional fusion.
Intellectual Capital dan Kinerja Keuangan pada UKM pada masa Pandemi Covid-19: Apakah terkait?

Penelitian ini bertujuan untuk menguji pengaruh dimensi modal intelektual terhadap kinerja keuangan UKM yang beroperasi di sektor industri kreatif pendukung pariwisata. Penelitian ini melakukan survey terhadap 670 pengrajin keris di Madura. Kuesioner terstruktur disebarkan kepada responden dengan teknik purposive sampling. Selanjutnya formulir survei kuesioner yang dikembalikan dianalisis dengan teknik SEM. Studi ini mengajukan enam hipotesis penelitian sebagai tujuan penelitian, selanjutnya data yang diperoleh dianalisis menggunakan pendekatan metode Structural Equation Modeling dengan bantuan Smart PLS. Hasil penelitian menunjukkan bahwa human capital, Structural capital, dan technological capital memberikan dampak terhadap kinerja keuangan UKM di masa Pandemi Covid-19. Kami tidak menemukan adanya dampak structural capital, social capital, dan spiritual capital pada studi kali ini. Penelitian ini hanya dilakukan pada UKM sektor kerajinan di Madura sehingga tidak dapat dilakukan generalisasi untuk UMKM keseluruhan. Penelitian ini berkontribusi terhadap pengembangan teori RBV tentang modal intelektual dan kinerja keuangan dalam perspektif UKM. Selain itu kontribusi praktis berupa saran kepada pelaku UKM untuk mengelola aset tak berwujud untuk menunjang kinerja organisasi utamanya Intellectual capital.
High-speed rail heading for innovation: the impact of HSR on intercity technology transfer

ABSTRACT This study examines the impact of China’s high-speed rail (HSR) network on regional innovation cooperation examining the impact on intercity patent rights transactions in 2016 between 81,510 city-pairs. It shows that (1) China’s intercity technology transfer network assumes a national-scale ‘diamond structure’; (2) China’s HSR network had a robust positive effect on intercity technology transfer; and (3) these impacts are direct and indirect operating through impacts on geographical proximity, industrial proximity, innovative proximity and technology complementarity. These findings broaden our understanding of the association between transport infrastructure and innovation networks in large emerging economies.
Risk factors for methicillin-resistant Staphylococcus aureus colonization and infection in patients with human immunodeficiency virus infection: A systematic review and meta-analysis

Objective To investigate the potential factors affecting methicillin-resistant Staphylococcus aureus (MRSA) colonization and infection in patients with human immunodeficiency virus (HIV) infection. Methods A systematic search of publications listed in electronic from inception up to August 2020 was conducted. A random-effects model was used to calculate odds ratio (OR) with 95% confidence interval (CI). Results A total of 31 studies reporting 1410 MRSA events in 17 427 patients with HIV infection were included. Previous hospitalization (OR 1.80; 95% CI 1.37, 2.36), previous antibiotic therapy (OR 2.69; 95% CI 2.09, 3.45), CD4+ count (OR 1.79; 95% CI 1.41, 2.28), Centers for Disease Control and Prevention classification of stage C (OR 2.66; 95% CI 1.80, 3.93), skin lesions (OR 2.02; 95% CI 1.15, 3.55), intravenous device use (OR 2.61; 95% CI 1.59, 4.29) and an MRSA colonization history (OR 6.30; 95% CI 2.50, 15.90) were significantly associated with an increased risk of MRSA colonization and infection. Antiretroviral therapy (OR 0.71; 95% CI 0.50, 0.99) and current antibiotic use (OR 0.13; 95% CI 0.05, 0.32) were significantly associated with a reduced risk of MRSA colonization and infection. Conclusion MRSA colonization and infection in HIV-infected patients is associated with a number of risk factors.
A scale development study for one of the 21st century skills: Collaboration at secondary schools

Collaboration skill has become one of the key skills in the 21st century both in education and work life. That is why educators need to learn about their students’ preferences and readiness in collaboration in the classroom. This study aims to develop a scale that lets secondary school students self-evaluate their collaboration skills. To follow this aim, a general survey methodology was used. A draft scale consisting of 33 items was developed through the relevant literature and was examined by experts. Then, the draft version was applied to a total of 402 secondary school students at a state secondary school in Aksaray City in Turkey in the 2019-2020 academic year. The data was subjected to first explanatory then confirmatory factor analysis. The explanatory factor analysis and first and second stage confirmatory factor analysis results indicate that the Scale for Self-Evaluation of Collaboration Skills (SSCS) with 29 items under three sub-dimensions -namely affective considerations, collaboration process, and roles and responsibilities- is a valid and reliable tool to examine collaboration skills of secondary school students.