Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Size-Distribution Environment on Breakage Parameters Using Closed-Cycle Grinding Tests

The so-called population balance model (PBM) is the most widely used approach to describe the grinding process. The analysis of the grinding data is carried out using—among others—the one-size fraction BII method. According to the BII method, the breakage parameters can be determined when a narrow particle size fraction is used as feed material to the mill. However, it is commonly accepted that these parameters are influenced by changing the particle size distribution in the mill. Thus, this study examines the breakage parameters through kinetic testing in different natural-size distribution environments generated by closed-cycle grinding tests that simulate industrial milling conditions. The differentiation of the milling environments was accomplished using various reference sieves in the closed-cycle tests. The experimentally determined breakage parameters were back-calculated and then used to simulate the closed-cycle tests using the MODSIMTM software. Additionally, the energy efficiency was evaluated based on the specific surface area of the grinding products and the energy consumption. The results of the kinetic tests showed that the breakage rate of the coarse particles increases as the aperture size of the reference sieve decreases, and consequently, the content of fines in the mill increases. The back-calculated breakage parameters can be reliably used to simulate closed-cycle circuits, thus helping control industrial milling operations.
Optimizing Orthognathic Surgery: Leveraging the Average Skull as a Dynamic Template for Surgical Simulation and Planning in 30 Patient Cases

Virtual planning has revolutionized orthognathic surgery (OGS), marking a significant advancement in the field. This study aims to showcase the practical application of our established 3D average skull template as a guiding framework for surgical planning, and to share valuable insights from our clinical experience. We enrolled 30 consecutive Taiwanese patients (18 females and 12 males) who underwent two-jaw orthognathic surgery with surgical simulation, utilizing the average skull template for planning. Results indicate the method’s applicability and precision. By adhering to the surgical plan, post-operative outcomes closely aligned with the average skull template, showing negligible deviations of less than 2 mm. Moreover, patients expressed high satisfaction with post-surgery facial changes, with the chin appearance receiving the highest satisfaction scores, while the lowest scores were attributed to nose appearance. Notably, the substantial change in lower jaw position post-mandibular setback surgery contributed to increased satisfaction with the chin position. In conclusion, this study does not seek to replace established surgical planning methods, but underscores that utilizing an average skull as a surgical design template provides a viable, accurate, and efficient option for OGS patients.
Fetch-limited wave growth in Nootka Sound

Ocean waves are generated at every coast line in the world. Wave generation and growth depends on wind. One hypothesis explored by this study is fetch-limited wave growth. Fetch is how far wind travels over a body of water, and the hypothesis states that the farther wind travels, the bigger waves will be. Big waves have potential for destruction, which has led many scientists to create models in an attempt to predict where, when and how big waves will be. The other goal of this study was to test the accuracy of a well-known wave predicting model used by coastal engineers. Data was gathered in a fjord called Nootka Sound using microSWIFT buoys to measure and analyze wave spectrum. The data was analyzed and fit to the Coastal Engineering Manual’s (CEM) model for wave growth. The results supported the hypothesis as larger fetch produced bigger waves. Comparing the observational data with the wave model suggested that the model was accurate for the wind conditions we were in, despite some disagreement.
A Biostimulant Based on Silicon Chelates Enhances Growth and Modulates Physiological Responses of In-Vitro-Derived Strawberry Plants to In Vivo Conditions

The purpose was to assess the effects of a biostimulant based on silicon chelates in terms of alleviation of the impact of in vivo conditions on strawberry (Fragaria × ananassa cv. ‘Solnechnaya polyanka’) in-vitro-derived plants. As a source of silicon chelates, a mechanocomposite (MC) obtained through mechanochemical processing of rice husks and green tea was used. Root treatment of plants with 0.3 g L−1 of MC dissolved in tap water was performed at 2 weeks after planting. Control plants were watered with tap water. The greatest shoot height, number of roots per plant, root length, number of stolons per plant, daughter ramets per stolon, relative water content, cuticle thickness, and root and shoot biomasses were achieved with the MC supplementation. The improved parameters were associated with a higher silicon content of roots and shoots of the MC-treated plants. Leaf concentrations of hydrogen peroxide and abscisic acid were reduced by the MC. This effect was accompanied by enhanced activity of superoxide dismutase and catalase. The phenolic profile showed upregulation of p-hydroxybenzoic acid, vanillic acid, gallic acid, syringic acid, and ellagic acid derivative 2, while kaempferol rutinoside and catechins were downregulated. Thus, silicon chelates improve growth and trigger the physiological processes that enhance free-radical-scavenging activity in strawberry plants in vivo.
Analysis and Optimization of a Novel Linear Permanent Magnet Vernier Motor with Spoke Structure

In this stage, linear motors are gradually replacing rotary motors for the actuators of linear servo systems due to their high accuracy as well as high response speed. Based on the principle of magnetic field modulation, the linear vernier motor achieves a role similar to that of a permanent magnet synchronous motor with variable poles, thus realizing the electromagnetic characteristics of large thrust at low speeds. In this paper, we propose a 6-slots, 10-poles spoke structure linear permanent magnet vernier motor (SLPMVM)with higher thrust density and higher air gap accuracy than the conventional vernier motor. Firstly, the basic structure and working principle of the motor are introduced, then the electromagnetic characteristics of the motor are analyzed and improved through parameter optimization, and finally the advantages of SLPMVM are analyzed by comparing with the traditional LPMVM.
Auditory Steady-State Responses in Schizophrenia: An Updated Meta-Analysis

This meta-analysis investigates auditory steady-state responses (ASSRs) as potential biomarkers of schizophrenia, focusing on previously unexplored clinical populations, frequencies, and variables. We examined 37 studies, encompassing a diverse cohort of 1788 patients with schizophrenia, including 208 patients with first-episode psychosis, 281 at-risk individuals, and 1603 healthy controls. The results indicate moderate reductions in 40 Hz ASSRs in schizophrenia patients, with significantly greater reductions in first-episode psychosis patients and minimal changes in at-risk individuals. These results call into question the expected progression of ASSR alterations across all stages of schizophrenia. The analysis also revealed the sensitivity of ASSR alterations at 40 Hz to various factors, including stimulus type, level of analysis, and attentional focus. In conclusion, our research highlights ASSRs, particularly at 40 Hz, as potential biomarkers of schizophrenia, revealing varied implications across different stages of the disorder. This study enriches our understanding of ASSRs in schizophrenia, highlighting their potential diagnostic and therapeutic relevance, particularly in the early stages of the disease.
Intelligent Control Applied to a Mobile Robot for Recognition and Collection of Plastic Bottles

This article presents the control of a mobile robot for the recognition and collection of plastic bottles applying artificial intelligence techniques. The robot was equipped with a mechanical arm with six degrees of freedom, on which two video cameras were mounted, so that the vertical movement of the arm allows changing the orientation of the cameras. In this way, it is possible to locate nearby and distant bottles, and not lose sight of them while the robot moves towards them. To recognize the bottles, a convolutional neural network was trained. To approach the bottles and collect them, a diffuse system was designed. The results show an accuracy of 95.3% in the recognition of the bottles and 87% in the approximation and collection process, with an average time of 43 seconds.
TrustSketch: Trustworthy Sketch-based Telemetry on Cloud Hosts

—Cloud providers deploy telemetry tools in software to perform end-host network analytics. Recent efforts show that sketches, a kind of approximate data structure, are a promising basis for software-based telemetry, as they provide high fidelity for many statistics with a low resource footprint. However, an attacker can compromise sketch-based telemetry results via software vulnerabilities. Consequently, they can nullify the use of telemetry; e.g., avoiding attack detection or inducing accounting discrepancies. In this paper, we formally define the requirements for trustworthy sketch-based telemetry and show that prior work cannot meet those due to the sketch’s probabilistic nature and performance requirements. We present the design and implementation T RUST S KETCH , a general framework for trustworthy sketch telemetry that can support a wide spectrum of sketching algorithms. We show that T RUST S KETCH is able to detect a wide range of attacks on sketch-based telemetry in a timely fashion while incurring only minimal overhead.
A push-broom compressive imaging system with situ calibration function for encoding mask

Compressive imaging（CI）can offer a versatile improvements for imaging systems, such as smaller compressed data volume and super-resolution. Among various methods to realize Compressive imaging, pushing encoding mask has attracted the most attention with its compatibility to the space remote sensing. However, complex pre- calibrations are usually needed for calibrating the encoding mask to achieve the measurement matrix for the image reconstruction. Herein, we design a pushing compressive imaging system which fixed with the function of situ calibration of the encoding mask. The pushing compressive imaging system was constructed, and the experimental results confirmed that the system had the ability for data compression and super-resolution. And above all, the system can avoid the complex pre-calibration, which makes the on-orbit calibration feasible. In the simulations, twice, three times and four times resolutions higher than the captured image’s resolution are performed respectively, which confirm that the method can improve the target image resolution based on the relative low resolution raw captured target images. Furthermore, by pushing the mask precisely which can be considered equivalent to the real pushing imaging, we have reconstructed the true super-resolution target image accurately based on the mask calibration and 6 captured pushing imaging frames.
JuliaCall: an R package for seamless integration between R and Julia

R is a widely used software and computing environment for statistics, which provides a variety of statistical techniques and packages (R Core Team, 2018). Many R packages provide interfaces to other computer languages to bring new functionalities to R or to accelerate computations, such as Rcpp (Eddelbuettel & François, 2011) and V8 (Ooms, 2019). The package JuliaCall provides an R interface to Julia, which is a computer language for high-performance scientific computing (Bezanson, Edelman, Karpinski, & Shah, 2017). JuliaCall embeds Julia in R, and provides functions to evaluate Julia commands, to call Julia functions, to transmit data objects between R and Julia, and so on. It also provides many utilities for user convenience. For example, JuliaCall gives detailed error messages for the embedded Julia. It also provides Julia package management functions such as installation and loading, and utility functions to get the documentation of Julia functions. JuliaCall can also be used in R Markdown document as the engine of Julia language, see Section 2.77 in Xie, Allaire, & Grolemund (2018).
Mechanism of Alternating Poly(lactic-co-glycolic acid) Formation by Polymerization of (S)- and (R)-3-Methyl Glycolide Using an Enantiopure Aluminum Complex

The mechanism(s) of alternating PLGA synthesis by ring-opening polymerization of (S)- and (R)-3-methyl glycolide promoted by enantiopure aluminum complexes have been rationalized by density functional theory (DFT) calculations. The high regioselectivity of the (S)-MeG polymerization is obtained by repetitive ring opening at the glycolyl site by the (R)-catalyst whereas a lower regioselectivity is predicted by the ROP of (R)-MeG. The behavior of the two monomers is rationalized by unveiling the active site fluxionality of the enantiopure catalyst, identifying the rate-limiting steps that encode a preference at the glycolyl site versus the lactyl site, and revealing selection of the opposite monomer enantioface. The microstructure of the PLGA copolymers is predicted by considering the influence of the configuration of the last inserted unit. The identification of the preferred mechanistic paths may allow for a targeted catalyst design to enhance control of the polymer microstructures.
Footprints of El Niño Southern Oscillation on Rainfall and NDVI-Based Vegetation Parameters in River Basin in Central India

AbstractAssessing the impacts of El Nino Southern Oscillation (ENSO) on hydrological cycle is critical for irrigation scheduling and water resources management. The ENSO-rainfall teleconnections in Venna River Basin in Maharashtra, India, and its impacts on vegetation have been identified in this study by using rainfall data, moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and geographic information system (GIS) techniques. Spatiotemporal analysis indicates correlation of rainfall with ENSO. Spatial variation in rainfall harmonizes with topography of the region, and a respective decrement and increment of 200–400 mm of rainfall at higher and lower elevations are seen to be associated with El Nino and La Nina events. This study also records the impacts of varying intensities of ENSO, causing inconsistencies in parameters, namely, premonsoon and postmonsoon vegetation growth, phenological parameters, and crop water requirements. The correlation of NDVI-pre.
Effect of Bioactive Glasses and Basic Fibroblast Growth Factor on Dental Pulp Cells

Ideal regeneration of hard tissue and dental pulp has been reported with the use of a combination of bioactive glass and basic fibroblast growth factor (bFGF). However, no previous study has investigated the molecular mechanisms underlying the processes induced by this combination in dental pulp cells. This study aimed to examine the cellular phenotype and transcriptional changes induced by the combination of bioactive glass solution (BG) and bFGF in dental pulp cells using phase-contrast microscopy, a cell counting kit-8 assay, alkaline phosphatase staining, and RNA sequence analysis. bFGF induced elongation of the cell process and increased the number of cells. Whereas BG did not increase ALP activity, it induced extracellular matrix-related genes in the dental pulp. In addition, the combination of BG and bFGF induces gliogenesis-related genes in the nervous system. This is to say, bFGF increased the viability of dental pulp cells, bioactive glass induced odontogenesis, and a dual stimulation with bioactive glass and bFGF induced the wound healing of the nerve system in the dental pulp. Taken together, bioactive glass and bFGF may be useful for the regeneration of the dentin-pulp complex.
Evaluation of Genetic Diversity in Quill Mites of the Genus Syringophiloidus Kethley, 1970 (Prostigmata: Syringophilidae) with Six New-to-Science Species

Simple Summary Morphology and barcode data were used to estimate the diversity and genetic variability of fourteen putative species of the genus Syringophiloidus Kethley, 1970. In most cases, both sources of information were consistent. The only exception was S. amazilia Skoracki, 2017, which according to our results is most likely a population of S. stawarczyki Skoracki, 2004, and probably should be treated as its junior synonym. The further findings of our study are six new-to-science species described herein. We indicate that both the host phylogeny and distribution can drive the evolution of quill mites. Our results increase the knowledge of quill mite diversity and provide some premises to formulate and further test evolutionary, ecological, and epidemiological inquiries. Abstract Quill mites (Acariformes: Syringophilidae) are poorly explored bird parasites. Syringophiloidus Kethley, 1970, is the most specious and widespread genus in this family. It is believed to contain mono-, steno- and poly-xenous parasites and thus seems to be an exemplary for studies on biodiversity and host associations. In this work, we applied the DNA barcode marker (mitochondrial cytochrome c oxidase subunit I gene fragment, COI) to analyze the species composition and host specificity of representatives of fifteen Syringophiloidus populations parasitizing fifteen bird species. The neighbor joining analyses distinguished thirteen monophyletic lineages, almost completely corresponding to seven previously known species recognized based on morphological features, and six new-to-science species. The only exception is S. amazilia Skoracki, 2017, which is most likely conspecific with Syringophiloidus stawarczyki Skoracki, 2004. The intraspecific distances of all species were not higher than 0.9%, whilst the interspecific diversity ranged from 5.9% to 19.2% and 6.3–22.4%, inferred as the distances p and K2P, respectively. Although all putative species (except S. amazilia) are highly supported, the relationships between them have not been fully resolved and only faintly indicate that both host phylogeny and distributions influence the phylogenetic structure of quill mite taxa.
Tools for agricultural drought detection in the frame of Drought Management Centre for Southeastern Europe – DMCSEE

Numerous specialized indices have been proposed to assess drought severity, but the precise quantification of drought is a difficult challenge. The purpose of this paper is to evaluate two indices: the well known Standardized Precipitation Index (SPI) and the Net Irrigation Requirements (NIR) derived by WinISAREG model. WinISAREG water balance model is tested in the frame of working activities of Drought Management Centre for Southeastern Europe (DMCSEE). The drought assessment for areas with different climatic characteristics in Slovenia is achieved using both indices for maize crop in the period from 1961 to 2010. A simple water balance was used for the comparison with the both indices. Results of the indices were compared with information about drought available in the agrometeorological reports of the Environmental Agency of the Republic of Slovenia for analysed time period. For the comparison among indices qualitative analysis for the vegetation season (April-September) was performed. For this reason 1-month and 6-month Standardized Precipitation Index were used. Soil type with low soil water holding capacity was chosen for the study. Seasonal NIR generally responds in a similar fashion to the 6-month Standardized Precipitation Index. With both indices extremely dry periods were validated by agrometeorological reports. There are some years with drought which are only confirmed by NIR and not confirmed by SPI6. SPI6 performs relatively well as indicator of long-term meteorological droughts caused by the lack of precipitation while NIR identifies also long-term agricultural droughts provoked by high evapotranspiration triggered by temperature stress. Study showed that at all locations NIR in the last ten years (2001-2010) increased on soils with low water holding capacity. NIR could be proposed as indicator for agricultural drought detection in the frame of DMCSEE.
Advanced Dual RNN Architecture for Electrical Motor Fault Classification

In recent years, there has been a remarkable increase in the usage of Deep Neural Networks (DNNs) for addressing and solving electrical field problems. This research primarily aims to present an advanced approach to classify different motor faults based on their time-series data by implementing a new Recurrent Neural Network (RNN) model that consists of mixed Long short-term memory (LSTM), Gated Recurrent Unit (GRU), and two Fully Connected (FC) layers. The main idea of this study centers on developing one comprehensive model capable of categorizing primary motor faults. The proposed model is supposed to classify 10 different classes, extracted from the Machinery Fault Database (MaFaulDa), which are normal (no-fault), vertical misalignment, horizontal misalignment, imbalance, overhang-ball, overhang-cage, overhang-outer race, underhang-ball, underhang-outer race, and underhang-cage. Classifying 10 different situations can be considered as a notable classification problem. Additionally, the learning period did not include any data augmentation, which reflects the model’s power in training over the available data. Significantly, the accuracy of the model is enhanced by setting precise values for hyperparameters, including network structure (number of layers and neurons), learning rate, regularization, optimizer type, number of epochs, and more. The obtained train-validation-test accuracies from the proposed model are 99.87%, 99.599%, and 99.48%, respectively. The accuracy of the model represents the highest accuracy among other publications. This advanced approach offers numerous advantages, including early-stage fault detection, improved robustness in industrial maintenance, and generating fast and intelligent alerts, thereby reducing the possible damage to electrical instruments.
Research on optical fiber SPR sensing characteristics of surface-enhanced fluorescence

An optical fiber-type fluorescence sensor based on surface-enhanced fluorescence (SEF) is proposed and analyzed through the finite element method. The field enhancement property of the designed multimode SPR fiber is utilized to improve the excitation rate of fluorescent molecules, which improves the sensitivity of fluorescence detection. Because the gold film is too close to fluorescent biomolecules, which can lead to fluorescence quenching, an optically transparent layer is added between the surface of the gold nanofilm and fluorescent biomolecules. And then analyze the layer's material and thickness parameters. When the gold film and PDMS thicknesses are 50 nm and 60 nm, the field enhancement factor (T) reaches the maximum value of 9.45. This fluorescence enhancement method provides a design possibility for improving the fluorescence detection sensitivity.