Miracle-dz/UniFAR-FTUs huggingface dataset:
Crack identification through scan-tuning of vibration characteristics using piezoelectric materials

This research develops a frequency-based methodology with a scan vibration tuning process for crack identification in beam-type structures coupled with piezoelectric materials. Piezoelectric sensor and actuator patches are mounted on the surface of the host beam synchronously to generate feedback excitations for a tuning process by applying a feedback voltage output from the piezoelectric sensors. The feedback excitations can adjust the stiffness at local section of the beam covered by piezoelectric patches so as to tune its natural vibration mode shapes to amplify the natural frequency change due to the existence of the crack. Piezoelectric patches located at different positions of the beam are activated one by one to realize the scan-tuning process. The crack is identified since the natural frequency change is magnified by the piezoelectric sensor and actuator located at the crack position. Theoretical and finite element models of the scan-tuned beam structures coupled with piezoelectric materials are established. From simulation results, the crack existence and location can be effectively detected through the scan-tuning process with 25% natural frequency change due to a crack located at the middle of the beam. Further parameter studies are conducted to study the effects of the crack location and size on the detection sensitivity.
Blood coagulation monitoring under static and flow conditions with optical coherence tomography autocorrelation analysis

Detection of blood coagulation functions is essential for diagnosing blood diseases and treating vascular diseases. The viscoelasticity changes of the blood from a liquid to a clot can provide critical information for assessing blood coagulation. Here, we reported on noncontact monitoring of blood coagulation under static and flow conditions with optical coherence tomography (OCT) autocorrelation analysis. After OCT imaging, blood tissue dynamics were assessed by the OCT autocorrelation analysis during coagulation of the whole porcine blood. The properties of blood coagulation were quantitatively evaluated by three metrics, including the coagulation reaction time, the clot formation duration, and the maximum clot strength. The results show that the OCT autocorrelation method can quantify the coagulation properties under static and flow conditions and provides a unique opportunity for in situ coagulation detection and point-of-care testing.
A Novel Method for the Intelligent Recognition of Lattice Fringes in Coal HRTEM Images Based on Semantic Segmentation and Fuzzy Superpixels

High-resolution transmission electron microscopy (HRTEM) can directly obtain the lattice fringes and structure parameters of coal. Aiming at present problems in extracting lattice fringes in HRTEM images, such as unlocated fringe regions, single-threshold segmentation, unclassified fuzzy superpixels, and tedious fringe pruning, an intelligent recognition method based on semantic segmentation, deep neural networks, fuzzy superpixels, and other algorithms is proposed. For unlocated fringe regions, the fringe regions are automatically localized with semantic segmentation. The whole semantic segmentation network adopts DeepLab V3+ based on ResNet to reduce unnecessary operations brought by non-fringe regions. For single-threshold segmentation of the image, the image is chunked before anything else. The genetic-optimized watershed algorithm is applied to divide the fringe base maps and non-fringe ones in order to avoid the distortion caused by different lights and shades of the image. For the fuzzy superpixels between the fringes and non-fringes, a similarity category judgment method based on neighboring pixels is proposed to solve the problem of unclassified fuzzy superpixels and to enrich and perfect the information of the lattice fringe base map. Eventually, as for lattice fringe overlap caused by coals piling together, a similarity judgment method based on the fringes’ characteristics is proposed to remove the bur portion of the lattice fringes and improve the pruning rate. Combining the above theories, a visualization tool based on MATLAB App Designer is designed, and the above four steps can be completed by this app to accurately display the results of coal aromatic lattice fringe identification in HRTEM images. Comparison with the lattice fringes drawn by leading experts shows that the fringes interpreted by this method are reliable. This method facilitates the extraction of lattice fringes in HRTEM, which lays the foundation for the labeling of HRTEM images in a variety of deep learning algorithms and facilitates the direct observation of coal structures by researchers.
Lean practices and their effect on performance: a literature review

Abstract This paper introduces a literature review of 83 studies dealing with the degree of adoption of lean manufacturing practices around the world, and the links between those practices and organisation performance. The results of this study revealed that lean practices application still occurs in a fragmented way, disregarding the systemic linkage that is essential to lean manufacturing. Forty-one articles have suggested a positive effect of lean practices in at least one operational, financial and/or environmental performance metric. Nevertheless, five studies indicated that some lean practices had a negative effect on operational or financial performance. High demand variability, a perceived result of long-term lean manufacturing implementation, a country/company’s organisational culture and the difficulty of traditional costing production systems to measure and compare investments and economic gains from adopting lean manufacturing over time are some of the reasons to explain that negative effect of lean practice on performance.
Robust Detection and Modeling of the Major Temporal Arcade in Retinal Fundus Images

The Major Temporal Arcade (MTA) is a critical component of the retinal structure that facilitates clinical diagnosis and monitoring of various ocular pathologies. Although recent works have addressed the quantitative analysis of the MTA through parametric modeling, their efforts are strongly based on an assumption of symmetry in the MTA shape. This work presents a robust method for the detection and piecewise parametric modeling of the MTA in fundus images. The model consists of a piecewise parametric curve with the ability to consider both symmetric and asymmetric scenarios. In an initial stage, multiple models are built from random blood vessel points taken from the blood-vessel segmented retinal image, following a weighted-RANSAC strategy. To choose the final model, the algorithm extracts blood-vessel width and grayscale-intensity features and merges them to obtain a coarse MTA probability function, which is used to weight the percentage of inlier points for each model. This procedure promotes selecting a model based on points with high MTA probability. Experimental results in the public benchmark dataset Digital Retinal Images for Vessel Extraction (DRIVE), for which manual MTA delineations have been prepared, indicate that the proposed method outperforms existing approaches with a balanced Accuracy of 0.7067, Mean Distance to Closest Point of 7.40 pixels, and Hausdorff Distance of 27.96 pixels, while demonstrating competitive results in terms of execution time (9.93 s per image).
Intellectual Capital Performance Of State-Owned Enterprises In Indonesia

Tujuan penelitian ini untuk mengukur kinerja pengelolaan modal intelektual di Badan Usaha Milik Negara dengan menggunakan model Pulic dikenal dengan Value Added Intellectual Capital. Data yang digunakan adalah laporan keuangan BUMN tahun 2020. Hasil kajian menunjukkan 10 BUMN dengan kategori top performance dan 11 BUMN dengan kategori bad performance. Implikasi penilaian ini mendorong BUMN untuk terus membenah dalam memanfaatkan modal intelektual untuk menciptakan nilai agar mampu bertahan dan memiliki daya saing di Era Pengetahuan saat ini.The purpose of this study is to measure the performance of intellectual capital management in State-Owned Enterprises using the Pulic’s model known as Value Added Intellectual Capital. The data used is the financial statements of SOEs for 2020. The results of the study show 10 SOE’s in the top performance category and 11 SOE’s in the bad performance category. The implications of this assessment encourage SOE’s to continue to improve in utilizing intellectual capital to create value in order to be able to survive and have competitiveness in the current Knowledge Age.
Phased geometrical acoustics in a small cabin

While the assumptions of geometrical acoustics usually restrict the method to high frequencies and to the calculation of energetic quantities inside large enclosures, it is found that the complex acoustic pressure can be calculated in the low frequency region and for small enclosures. The particular method presented contains aspects of the image source, ray tracing and beam tracing methods. The center rays of many triangular beams are traced throughout an acoustic enclosure in order to find valid image sources. Boundary conditions, which may be complex, frequency-, and/or spatiallydependent, are imposed in post-processing, which is the main advantage of the method. Valid image sources are assumed to act as acoustic monopoles in free-space, and their sum approaches the steady-state pressure for a particular source/receiver pair. Comparisons with the Wave Based Method and the Finite Element Method will be presented.
It’s Just Not the Same: Virtual Teamwork in Public Libraries

Abstract The COVID-19 pandemic propelled organizations to adopt virtual work settings around the world, and libraries were no exception. This article presents findings of interviews with leaders from eight public library systems about their transition to virtual work settings during the COVID-19 pandemic. The findings include changes in librarians’ teams and work processes, their experiences with new technologies, service models, and working from home conditions.
Development of Computer Vision Algorithms for Multi-class Waste Segregation and Their Analysis

Classification of waste for recycling has been a focal point for scientists interested in the field of conservation of the environment. Recycling consists of numerous steps, of which one of the most crucial is the segregation of recyclables from all other waste. Due to a lack of safety standards in developing countries, waste collection is often done manually by domestic helpers, or "rag-pickers". Such a process risks individual and public health. The waste collection methods may ultimately cause waste to become non-recyclable due to cross-contamination. Literature shows that research in this direction focuses on a single class of waste detection. The proposed work investigates CNN, YOLO, and faster RCNN-based multi-class classification methods to detect different types of waste at the collecting point. The smart dustbin proposed employs these computer vision methods with a Raspberry Pi microcontroller and camera module. The experimental results for multi-class classification show that the CNN has 80% of accuracy with 60% of the loss. Whereas the YOLO algorithm shows an accuracy of 88% and a loss of 40%. But the best results were obtained from faster RCNN object detection with API, with an accuracy of 91% and a loss of 16%. There is already an existing method for making a smart dustbin, so the results are compared to show how computer vision can be used to make a smart dustbin. This shows how computer vision can be used to make a smart dustbin. Doi: 10.28991/ESJ-2022-06-03-015 Full Text: PDF
Analysis of Coxsackievirus B5 Infections in the Central Nervous System in Brazil: Insights into Molecular Epidemiology and Genetic Diversity

Coxsackievirus B5 (CVB5) is one of the most prevalent enteroviruses types in humans and causes annual epidemics worldwide. In the present study, we explored viral genetic diversity, molecular and epidemiological aspects of CVB5 obtained from cerebrospinal fluid and stool samples of patients with aseptic meningitis or acute flaccid paralysis, information that is still scarce in Brazil. From 2005 to 2018, 57 isolates of CVB5 were identified in the scope of the Brazilian Poliomyelitis Surveillance Program. Phylogenetic analyses of VP1 sequences revealed the circulation of two CVB5 genogroups, with genogroup B circulating until 2017, further replaced by genogroup A. Network analysis based on deduced amino acid sequences showed important substitutions in residues known to play critical roles in viral host tropism, cell entry, and viral antigenicity. Amino acid substitutions were investigated by the Protein Variation Effect Analyzer (PROVEAN) tool, which revealed two deleterious substitutions: T130N and T130A. To the best of our knowledge, this is the first report to use in silico approaches to determine the putative impact of amino acid substitutions on the CVB5 capsid structure. This work provides valuable information on CVB5 diversity associated with central nervous system (CNS) infections, highlighting the importance of evaluating the biological impact of certain amino acids substitutions associated with epidemiological and structural analyses.
Engineering Genders: A Spatial Analysis of Engineering, Gender, and Learning

phenomenon; it is contextualized and located within social practices, practices imbued with cultural meanings and histories but that are also dynamic and changing. Each one of these statements is a placeholder for a body of research that comes before it. I could pull out a single word and tell you why it is important to the study of learning: process, becoming, being, identity, practice, culture, change. However, without a context or theory behind each concept, they appear vapid; and yet, it is my hope that after reading this dissertation, the reader can come back to this paragraph and acknowledge that my primary focus for this dissertation is learning: learning from a situated perspective that that attends to both the change in individuals and practices. The context of my research is undergraduate engineering education. I began my empirical investigation examining how students studying engineering are produced through gendered discourse. Gender is a salient theme in my research because much of our social world is made meaningful through the construct of gender, and gender is made consequential in most social practices. By analyzing discourse, including the rituals and routines of engineering education, as well as the spatial representations of engineering practice, I wanted to uncover both the constraints and possibilities for transforming learning environments to be more gender equitable. Engineering education presented a ENGINEERING GENDERS CHAPTER 1 2 valuable context to study the gendered production of learning environments because it historically has been and continues to be a field disproportionately male despite sustained
Strategy for enhancing the active harvesting of piezoelectric energy

This article proposes new methods for enhancing the active harvest of piezoelectric energy using the synchronized switch harvesting on inductor (SSHI) technique. It was experimentally confirmed that the energy harvested by the original synchronized switch harvesting on inductor technique was decreased by the suppression of the vibration amplitude, and this critical problem was solved by developing new control strategies, namely, switch harvesting considering vibration suppression (SCVS) and adaptive SCVS (ASCVS). The SCVS technique was designed to intentionally skip some of the switching actions of the original synchronized switch harvesting on inductor technique, while the ASCVS technique enables more flexible variation of the number of skipped switching actions. The skipping of the switching actions facilitates the recovery of the vibration amplitude produced by the excitation force, and the developed strategies thus maintain the vibration amplitude at the highest possible level, resulting in increased energy harvest. The results of the experimental implementation of the proposed strategies showed that they enabled the harvesting of as much as 10.5 times the energy harvested by the original synchronized switch harvesting on inductor technique. The ASCVS technique particularly enables flexible enhancement of the harvested energy under various vibration conditions.
Static and Dynamic Biomaterial Engineering for Cell Modulation

In the biological microenvironment, cells are surrounded by an extracellular matrix (ECM), with which they dynamically interact during various biological processes. Specifically, the physical and chemical properties of the ECM work cooperatively to influence the behavior and fate of cells directly and indirectly, which invokes various physiological responses in the body. Hence, efficient strategies to modulate cellular responses for a specific purpose have become important for various scientific fields such as biology, pharmacy, and medicine. Among many approaches, the utilization of biomaterials has been studied the most because they can be meticulously engineered to mimic cellular modulatory behavior. For such careful engineering, studies on physical modulation (e.g., ECM topography, stiffness, and wettability) and chemical manipulation (e.g., composition and soluble and surface biosignals) have been actively conducted. At present, the scope of research is being shifted from static (considering only the initial environment and the effects of each element) to biomimetic dynamic (including the concepts of time and gradient) modulation in both physical and chemical manipulations. This review provides an overall perspective on how the static and dynamic biomaterials are actively engineered to modulate targeted cellular responses while highlighting the importance and advance from static modulation to biomimetic dynamic modulation for biomedical applications.
GABA and Fermented Curcuma longa L. Extract Enriched with GABA Ameliorate Obesity through Nox4-IRE1α Sulfonation-RIDD-SIRT1 Decay Axis in High-Fat Diet-Induced Obese Mice

Gamma-aminobutyric acid (GABA) is a natural amino acid with antioxidant activity and is often considered to have therapeutic potential against obesity. Obesity has long been linked to ROS and ER stress, but the effect of GABA on the ROS-associated ER stress axis has not been thoroughly explored. Thus, in this study, the effect of GABA and fermented Curcuma longa L. extract enriched with GABA (FCLL-GABA) on the ROS-related ER stress axis and inositol-requiring transmembrane kinase/endoribonuclease 1α (IRE1α) sulfonation were examined with the HFD model to determine the underlying anti-obesity mechanism. Here, GABA and FCLL-GABA supplementations significantly inhibited the weight gain in HFD fed mice. The GABA and FCLL-GABA supplementation lowered the expressions of adipogenic transcription factors such as PPAR-γ, C/EBPα, FAS, and SREBP-1c in white adipose tissue (WAT) and liver from HFD-fed mice. The enhanced hyper-nutrient dysmetabolism-based NADPH oxidase (Nox) 4 and the resultant IRE1α sulfonation-RIDD-SIRT1 decay under HFD conditions were controlled with GABA and FCLL-GABA. Notably, GABA and FCLL-GABA administration significantly increased AMPK and sirtuin 1 (SIRT1) levels in WAT of HFD-fed mice. These significant observations indicate that ER-localized Nox4-induced IRE1α sulfonation results in the decay of SIRT1 as a novel mechanism behind the positive implications of GABA on obesity. Moreover, the investigation lays a firm foundation for the development of FCLL-GABA as a functional ingredient.
High Precision 3D Printing for Micro to Nano Scale Biomedical and Electronic Devices

Three dimensional printing (3DP), or additive manufacturing, is an exponentially growing process in the fabrication of various technologies with applications in sectors such as electronics, biomedical, pharmaceutical and tissue engineering. Micro and nano scale printing is encouraging the innovation of the aforementioned sectors, due to the ability to control design, material and chemical properties at a highly precise level, which is advantageous in creating a high surface area to volume ratio and altering the overall products’ mechanical and physical properties. In this review, micro/-nano printing technology, mainly related to lithography, inkjet and electrohydrodynamic (EHD) printing and their biomedical and electronic applications will be discussed. The current limitations to micro/-nano printing methods will be examined, covering the difficulty in achieving controlled structures at the miniscule micro and nano scale required for specific applications.
An experimental study of the nonlinear dynamics of floating cranes

This paper gives a comparative overview of the operation capabilities of different crane vessel types. It demonstrates that the dynamic behaviour of moored floating cranes can be treated as being linear over a wide range of applications. Under certain conditions, however, the coupled system of floating structure and swinging load shows distinctly nonlinear phenomena and parametric oscillations can occur. In such cases a safe heavy lift operation cannot be guaranteed since the linear methods underestimate the occurring loads and motions. Nonlinear mooring line forces are a major cause of nonlinear crane vessel and load motions. Seakeeping tests have been carried out using a MAGNUS crane barge model at a scale of 1 : 25 in regular head seas. Time series show a coexistence of 2- and 3-periodic motions with significantly increased amplitudes compared to the 1-periodic linear mode. Surge and pitch motion of the floating body as well as the coupled motion of the swinging load are substantially influenced by the nonlinear restoring forces. High peaks in the mooring line forces occur due to increased surge amplitudes.
Using functional groups to predict the spatial distribution of large herbivores on the Palaeo‐Agulhas Plain, South Africa, during the Last Glacial Maximum

Throughout much of the Quaternary, lower sea levels in the southern Cape of South Africa exposed a different landscape to what we see today, the Palaeo‐Agulhas Plain (PAP). The PAP was dominated by large‐bodied and gregarious grazing species contrasting with the small‐bodied predominantly solitary species we find in the region today. The distribution of these herbivores would likely have been driven by similar drivers we see in contemporary herbivore ecology. Importantly, the occurrence of early humans and their associated technology would have also influenced the probability of herbivores occurring in an area. Here we create a predictive model for large herbivores using probability of occurrence of functional grouping in relation to environmental drivers and humans. We show how early humans influenced the distribution of large herbivores on the PAP alongside other environmental drivers. In the fynbos biome, probability of occurrence was highest for the medium‐sized social mixed feeders’ functional group in the thicket for small non‐social browsers, large browsers, and non‐ruminants and in grasslands for water‐dependent grazers. In our models, human influence affected functional groups to varying degrees but had the strongest effect on medium‐sized social mixed feeders.
The Roles of Romantic Beliefs and Imagined Interaction in Unrequited Love

The present study examined the roles of people's romantic beliefs and imagined interactions in unrequited love. Two hundred and twenty five Chinese college students participated in a survey study. More idealized romantic beliefs were associated with stronger unrequited love. Men's unrequited love was stronger than women's. Would-be lovers who had imagined interactions with beloved ones had stronger unrequited love in contrast to those who didn’t. Unrequited love and romantic beliefs were both positively related to the imagined interaction attributes of frequency and valence and the functions of compensation and relationship maintenance. Frequency of imagined interactions positively mediated the relationship between romantic beliefs and unrequited love.