Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on flexural and shear performance of ultra‐high performance concrete prefabricated pi‐beams

Ultra‐high performance concrete (UHPC) prefabricated beams are competitive in accelerated bridge construction. However, their broader application has been hindered by limited large‐scale tests and inaccurate design methods. To fill this gap, the authors conducted an experimental investigation on the shear and flexural performance of UHPC pi‐beams using two full‐scale specimens. One specimen was a precast UHPC beam, while the other was a composite beam with a normal concrete slab on the UHPC beam. The primary focus was on crack propagation, ultimate capacities, and failure modes. To complement the experimental findings, the extended finite element method (XFEM) was developed as a numerical approach. Nevertheless, relying solely on XFEM to understand real structural behavior is prone to misinterpretations. Moreover, the shear and flexural capacities were evaluated using existing codes and compared with the experimental results. The comparisons revealed that the predictions of shear capacities were at least 15% lower than the experimental values, whereas the flexural capacities showed acceptable agreement. To address this, the authors introduced the limit equilibrium method, leading to a more accurate prediction of shear capacity for UHPC beams with a deviation of <2%.
Propulsion and Control of Microrobot using a Multiple Wireless Power Transfer Coil

Microrobot can be used for a various kind of applications. To maximize the utilization of microrobot, the mobility as well as providing electrical energy is necessary. Therefore, by using a time-varying magnetic field, which is accompanies on wireless power transfer system, the magnetic force and torque is applied to the magnetic material have been researched. In this paper, a multiple wireless power transfer coil based microrobot control is analyzed. The transmitting coil is selectively activated to generate the impulsive magnetic force and torque on a magnetic material based microrobot. The 3D FEM electromagnetic simulation was conducted to validate this idea and the results showed that the magnetic force and torque can be varied according to the incident magnetic field direction by using a multiple transmitting coil.
Complex assessment of parameters of central hemodynamics and microcirculation in children of 6-7 years old

The paper presents the results of a comprehensive assessment of central hemodynamic and microcirculation indices in the skin of upper and lower limbs in 6–7-year-old children. 14 girls and 7 boys were examined using laser Doppler flowmetry methods (the LASMA-PF device, allowing simultaneous recording by four sensors) and the analysis of heart rate variability ("Varicard"). The parameters characterizing microcirculation in the limbs were determined and the signs of the appearing functional asymmetry of the upper limbs, as well as the differences in the mechanisms of modulation of cutaneous blood flow in boys and girls were revealed. The estimation of heart rate variability reveals the signs of girls' inclination to sympathotony and boys' inclination to vagotony at the given age. It was marked that central regulation mechanisms have the greater contribution to cardiac rhythm formation in girls. The data obtained testify to the fact that age-related changes at different levels of the cardiovascular system and regulation mechanisms occur somewhat earlier in girls than in boys.
Frequency Domain-Based Features for Hyperspectral Image Classification

Frequency spectrum has been proven to have the potential in hyperspectral image classification and ground object recognition. The characteristics of the frequency spectrum, such as dc component, descent rate, and spectrum oscillation, are different from each other; thus, based on the discrepancy in the frequency spectrum, 14 frequency spectrum features, including frequency spectrum integration area, spectral centroid (<inline-formula> <tex-math notation="LaTeX">$C_{k}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$C_{k-\textrm {log}}$ </tex-math></inline-formula>), spectral rolloff (<inline-formula> <tex-math notation="LaTeX">$C_{t}$ </tex-math></inline-formula>), spectral flux, spectral gradient of peaks, and valley, number of crosspoint, and first three peaks and valleys position, are proposed. To evaluate the performance of the proposed features, two commonly used hyperspectral images were taken as experimental data sets. Then, we employed three frequently used classification methods to perform the experiment based on spectral-only and frequency-spectral features. The results show that the proposed features can distinctly prompt the classification accuracies by combining the original spectral features.
Serratia marcescens Outbreak at a Correctional Facility: Environmental Sampling, Laboratory Analyses and Genomic Characterization to Assess Sources and Persistence

Serratia marcescens is an environmental bacterium and clinical pathogen that can cause an array of infections. We describe an environmental sampling and comparative genomics approach used to investigate a multi-year outbreak of S. marcescens at a correctional facility. Whole genome sequencing analysis revealed a predominant cluster of clonally related S. marcescens from nine patient cases and items associated with illicit drug use. Closely related strains found among items associated with case-patient cells and diluted Cell Block 64 (CB64), a quaternary ammonium disinfectant, and Break Out (BO), a multipurpose cleaner, highlighted their role as environmental reservoirs for S. marcescens in this outbreak. Comparative genomic analysis suggested outbreak strains were both persistent (identical strains found over long periods and in multiple locations of the correctional facility) and diverse (strains clustered with multiple global samples from NCBI database). No correlation was found between antimicrobial resistance (AMR) genes of outbreak strains; NCBI strains have more AMR genes. Principal component analysis (PCA) of virulence factors associated with persistence and infectivity indicated variation based on phylogroups, including the predominant cluster; identifiable variations among environmental versus clinical strains were not observed. Identification of multiple distinct genetic groups highlights the importance of putting epidemiological genomic studies in a proper genetic context.
A Three-Year Analysis of Toxic Benzene Levels and Associated Impact in Ploieşti City, Romania

This study examines the levels of benzene and the potential health impact during three years of continuous monitoring (2019–2021), including the COVID-lockdown period from 2020 in a city that is an important Romanian center for petroleum refining and associated product manufacturing. The dataset contains benzene, toluene, NOx, PM10 concentrations, and meteorological factors monitored by six automatic stations from the national network of which four are in the city and two outside. Special attention was given to the benzene dynamics to establish patterns related to the health impact and leukemia. An assessment of the exposure was performed using EPA’s ExpoFIRST v. 2.0 for computing the inhalation Average Daily Dose (ADD) and Lifetime Average Daily Dose (LADD). The health impact was estimated based on several indicators such as lifetime cancer risk (LCR), Hazard Quotient (HQ), Disability-Adjusted Life Years (DALY), and Environmental burden of disease (EBD). Overall, the annual average of all stations was almost similar between years i.e., 3.46 in 2019, 3.41 in 2020, and 3.63 µg/m3 in 2021, respectively. The average of all stations during the lockdown period was 2.67 µg/m3, which was lower than the multiannual average of the 2019–2021 period, i.e., 3.5 µg/m3. Significant correlations were present between benzene and other pollutants such as NOx (r = 0.57), PM10 fraction (r = 0.70), and toluene (r = 0.69), and benzene and temperature (r = −0.46), humidity (r = 0.28), and wind speed (r = −0.34). Regarding the ADD, in all scenarios, the most affected age categories are small children, despite a lower outdoor exposure time. From birth to <70 years, the ADD varied depending on the exposure scenario resulting in 3.27 × 10−4, 5.6 × 10−4, and 4.04 × 104 mg/kg-day, and 3.95 × 10−4, 10.6 × 10−4, and 6.76 × 10−4 mg/kg-day for the LADD, respectively. The Integrated Lifetime Cancer Risk (ILTCR) values were 14.1 × 10−5 in winter, 9.04 × 10−5 in spring, 8.74 × 10−5 in summer, and 10.6 × 10−4 in autumn. The ILTCR annual averages were 1.08 × 10−4 (2019), 1.07 × 10−4 (2020), 1.04 × 10−4 (2021), and 1.06 × 10−4 for the entire period. The resulting ILTCR values point out very risky conditions, with the annual averages reaching the definite cancer risk category. The corresponding burden based on the DALY’s loss due to leukemia in Ploieşti was estimated at 0.291 (2 μg/m3 benzene), 0.509 (3.5 μg/m3 benzene), 0.582 (4 μg/m3 benzene), and 0.873 DALYs per 100,000 inhabitants (6 μg/m3 benzene), respectively. The current study provides useful insights for a better understanding of the exposure levels to benzene and associated health impact in Ploieşti despite the limitations determined by the data hiatus and incomplete or missing information regarding the health impact.
Molecular Investigation of Mitochondrial RNA19 Role in the Pathogenesis of MELAS Disease

In mammalian mitochondria, the processing of primary RNA transcripts involves a coordinated series of cleavage and modification events, leading to the formation of processing intermediates and mature mt-RNAs. RNA19 is an unusually stable unprocessed precursor, physiologically polyadenylated, which includes the 16S mt-rRNA, the mt-tRNALeuUUR and the mt-ND1 mRNA. These peculiarities, together with the alteration of its steady-state levels in cellular models with defects in mitochondrial function, make RNA19 a potentially important molecule for the physiological regulation of mitochondrial molecular processes as well as for the pathogenesis of mitochondrial diseases. In this work, we quantitatively and qualitatively examined RNA19 in MELAS trans-mitochondrial cybrids carrying the mtDNA 3243A>G transition and displaying a profound mitochondrial translation defect. Through a combination of isokinetic sucrose gradient and RT-qPCR experiments, we found that RNA19 accumulated and co-sedimented with the mitoribosomal large subunit (mt-LSU) in mutant cells. Intriguingly, exogenous expression of the isolated LARS2 C-terminal domain (Cterm), which was shown to rescue defective translation in MELAS cybrids, decreased the levels of mt-LSU-associated RNA19 by relegating it to the pool of free unbound RNAs. Overall, the data reported here support a regulatory role for RNA19 in mitochondrial physiopathological processes, designating this RNA precursor as a possible molecular target in view of therapeutic strategy development.
Omega-3 Fatty Acids, Cognition, and Brain Volume in Older Adults

The elderly population is growing at increased rates and is expected to double in size by 2050 in the United States and worldwide. The consumption of healthy foods and enriched diets have been associated with improved cognition and brain health. The key nutrients common to many healthy foods and diets are the omega-3 polyunsaturated fatty acids (omega-3 FAs), such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). We explored whether omega-3 FA levels are associated with brain volume and cognition. Forty healthy, cognitively normal, Seventh-day Adventist older adults (mean age 76.3 years at MRI scan, 22 females) completed neurocognitive testing, a blood draw, and structural neuroimaging from 2016 to 2018. EPA and an overall omega-3 index were associated with individual measures of delayed recall (RAVLT-DR) and processing speed (Stroop Color) as well as entorhinal cortex thickness. EPA, DHA, and the omega-3 index were significantly correlated with the total white matter volume. The entorhinal cortex, frontal pole, and total white matter were associated with higher scores on delayed memory recall. This exploratory study found that among healthy, cognitively older adults, increased levels of omega-3 FAs are associated with better memory, processing speed, and structural brain measures.
Genome-Wide Analysis of SPL/miR156 Module and Its Expression Analysis in Vegetative and Reproductive Organs of Oil Palm (Elaeis guineensis)

The SPL (SQUAMOSA-promoter binding protein-like) gene family is one of the largest plant transcription factors and is known to be involved in the regulation of plant growth, development, and stress responses. The genome-wide analysis of SPL gene members in a diverse range of crops has been elucidated. However, none of the genome-wide studies on the SPL gene family have been carried out for oil palm, an important oil-yielding plant. In this research, a total of 24 EgSPL genes were identified via a genome-wide approach. Phylogenetic analysis revealed that most of the EgSPLs are closely related to the Arabidopsis and rice SPL gene members. EgSPL genes were mapped onto the only nine chromosomes of the oil palm genome. Motif analysis revealed conservation of the SBP domain and the occurrence of 1–10 motifs in EgSPL gene members. Gene duplication analysis demonstrated the tandem duplication of SPL members in the oil palm genome. Heatmap analysis indicated the significant expression of SPL genes in shoot and flower organs of oil palm plants. Among the identified EgSPL genes, a total 14 EgSPLs were shown to be targets of miR156. Real-time PCR analysis of 14 SPL genes showed that most of the EgSPL genes were more highly expressed in female and male inflorescences of oil palm plants than in vegetative tissues. Altogether, the present study revealed the significant role of EgSPL genes in inflorescence development.
Intercity networks and urban performance: a geographical text mining approach

Compared to the burgeoning literature discussing the importance of agglomeration externalities for development, limited attention has been given to network externalities. This is largely due to limited data availability. We propose a general measure to proxy city network externalities based on toponym co-occurrences that indicate the relatedness between cities. This paper extracts intercity relationships based on the co-occurrence of Chinese place names on 2.5 billion webpages. We calculate and map absolute and relative network positions, which we use to explain urban labour productivity. We found that a stronger embeddedness in networks of cities is signi ﬁ cantly and positively associated with urban productivity. Smaller cities bene ﬁ t comparatively more from being well embedded in city networks, suggesting that these relations can compensate for a lack of agglomeration externalities. We also compare the importance for urban performance of city network externalities vis-à-vis agglomeration externalities. City network externalities turn out to be more important in explaining urban performance than agglomeration externalities. This calls for new theorizing on a relational approach to urban and regional development. Rather than stimulating further concentration of urbanization, our ﬁ ndings suggest that fostering relationships between cities is a viable alternative urban development strategy. We conclude with suggestions for a research agenda that delves deeper into city network externalities.
Effect of Lactobacillaceae Probiotics on Colonic Microbiota and Metabolite Production in Cystic Fibrosis: A Comparative In Vitro Study

Cystic Fibrosis-related gut dysbiosis (CFRGD) has become a recognised complication in children with this condition, and current evidence remains insufficient to guide the selection of probiotic strains for supplementation treatments. The aim of this study was to characterise the effect of three probiotic strains on CFRGD by means of a dynamic in vitro simulation of the colonic fermentation (SHIME®). The configuration of the system included three bioreactors colonised with the faecal inoculum of a child with cystic fibrosis. For 20 days, each bioreactor was supplied daily with either Lacticaseibacillus rhamnosus GG (ATCC 53103 TM), Limosilactobacillus reuteri (DSM 17938) or Lactiplantibacillus plantarum (DSM 22266). The baseline microbiota was characterised by a high abundance of Prevotella, Faecalibacterium and Acidaminococcus genera. After 20 days of supplementation, L. rhamnosus and L. plantarum reduced Prevotella significantly, and the three strains led to increased Faecalibacterium and Bifidobacterium and decreased Acidaminococcus, with some of these changes being maintained 10 days after ceasing supplementation. The metabolic activity remained unaltered in terms of short-chain fatty acids, but branched-chain fatty acids showed a significant decrease, especially with L. plantarum. Additionally, ammonia decreased at 20 days of supplementation, and lactate continuously increased with the three strains. The effects on colonic microbiota of L. rhamnosus, L. reuteri or L. plantarum were established, including increased beneficial bacteria, such as Faecalibacterium, and beneficial metabolites such as lactate; and on the other hand, a reduction in pathogenic genera, including Prevotella or Acidaminococcus and branched-chain fatty acids, overall supported their use as probiotics in the context of CFRGD.
Prediction models for the emergence of mycotoxins in grain

The Swedish Meteorological and Hydrological Institute calculates an increase in temperature in Sweden by 4-6°C before the year 2100, with the possibility of increased incidence of mycological and mycotoxical material in grain intended for feed and food production. Four models for predicting emergence of mycotoxins in grain were developed using a regression analysis function in the statistical software Weka 3.6 along with data from SVA, SMHI, Lantmannen and the Swedish Museum of Natural History.
Predictive Ability of Perfusion Index for Determining the Success of Adductor Canal Nerve Block for Postoperative Analgesia in Patients Undergoing Unilateral Total Knee Arthroplasty

Background: The perfusion index (PI) is an objective method used to determine a successful nerve block. This study aimed to investigate the prognostic ability of the PI for a successful adductor canal nerve block (ACB) and suggest the optimal PI cut-off value for predicting a block. Methods: This study was a prospective observational study and enrolled a total of 39 patients. The patients were dichotomized into successful and inappropriate ACB groups according to the results of the sensation tests. The PI value, Pleth variability index (PVi) value, and heart rate were recorded one minute before the block, at the time of the block, and one to 30 min after the block at one-minute intervals. Delta (dPI), which was defined as the difference in PI value from the baseline (the value one minute before the block), was the primary outcome. The area under the receiver operating characteristic curve (AUROC) was calculated to determine the dPI prognostic accuracy and optimal cut-off value. Results: Successful ACB was achieved in 33 patients, while ACB was inappropriate in six patients. The dPI showed significant differences between the two groups under the time interval measured (p = 0.001). The dPI at 5 and 20 min showed good prognostic ability for a successful block, with optimal cut-off values of 0.33 (AUROC: 0.725, 95% CI 0.499–0.951) and 0.64 (AUROC: 0.813, 95% CI 0.599–1.000), respectively. Conclusions: The dPI is an effective predictor of successful ACB. The suggested dPI cut-off values at 5 and 20 min were below 0.33 and 0.64, respectively.
PENERAPAN TEKNOLOGI PENGOLAHAN LIMBAH MINYAK GORENG BEKAS MENJADI SABUN CUCI PIRING UNTUK PENGENDALIAN PENCEMARAN DAN PEMBERDAYAAN MASYARAKAT

Desa Sekaran memiliki Pertumbuhan penduduk, perkembangan industry, restoran dan usaha kuliner pesat karena terdapat universitas yang setiap tahunnya mengalami peningkatan mahasiswa. Hal ini memberikan banyak dampak positif bagi masyarakat, namun di sisi lain juga menimbulkan dampak yang kurang menguntungkan dari sisi lingkungan. Salah satu dampak negatif dari keberadaan usaha kuliner di wilayah Gunungpati adalah volume limbah minyak goreng tinggi. Ini terjadi karena kebanyakan masyarakat, dalam ha1 ini adalah para pedagang membuang limbah minyak goreng begitu saja. limbah minyak goreng tersebut apabila tidak dikelola dengan baik akan menimbulkan masalah bagi lingkungan, yaitu menjadikan lingkungan kotor dan dapat menemari air serta tanah. Untuk mengatasi masalah itu, perlu adanya inovasi dalam pengelolaan limbah minyak goreng dengan melibatkan masyarakat luas sehingga limbah minyak goreng dapat dimanfaatkan menjadi produk yang bernilai ekonomis. Salah satu potensi limbah minyak goreng adalah kandungan asam lemak dari minyak nabati yang tinggi sehingga dapat dimanfaatkan menjadi sabun cuci piring yang ramah lingkungan. Oleh karena itu, untuk mengatasi masalah volume limbah minyak goreng yang tinggi, dilakukan kegiatan pengabdian masyarakat yang bertujuan untuk meningkatkan nilai tambah bagi limbah minyak goreng dengan jalan mengolah limbah minyak goreng menjadi sabun cuci piring. Pelatihan ketrampilan mengenai pengolahan limbah minyak goreng menjadi sabun cuci piring ramah lingkungan telah dilaksanakan bagi masyarakat di desa Sekaran wilayah Gunungpati. Pengabdian masyarakat ini memberikan manfaat: 1) Masyarakat mengetahui dampak negative minyak goreng bekas terhadap kesehatan dan lingkungan, 2) Masyarakat mengetahui dan terampil mengaplikasikan teknologi tepat guna pengolahan minyak jelantah menjadi sabun cuci piring, 3) Masyarakat mengetahui potensi ekonomis limbah minyak goreng bekas, 4) Mendorong pemberdayaan masyarakat melalui penerapan teknologi tepat guna.
Revolutionizing Rice Disease Diagnosis: A Fusionof Convolutional Neural Networks and Support Vector Machines

This study uses a CNN architecture to provide a deep learning strategy for the detection and categorization of eight common rice illnesses. Three layers of convolution, three maximum pooling layers, including two fully linked layers make up the proposed model. The photos of numerous rice diseases were gathered from various sources and included in the dataset for this study. A 2,830 picture-labeled dataset with an 80/20 split between both the testing and training sets is used to train the model. The model that was trained is then assessed using Fl-score metrics for precision, recall, and recall. The evaluation’s findings are shown in a graph where each disease class’s effectiveness is gauged by the percentage of assistance given to each class. According to the experimental findings, the model that was suggested achieves a precision of 81.23%, so it’s comparable to the most recent models. The accuracy of each class is greater than 77%, demonstrating the model’s ability to distinguish between various rice illnesses. showing that the model is capable of recognizing the majority of the instances for each disease class, the accuracy of the recall of every category is also over 55%. Each class’s F1 score is higher than 67%, indicating a decent overall performance for the model. In conclusion, the suggested model has a good level of accuracy, recall, and Fl-score for accurately classifying various rice illnesses. The detection and treatment of rice diseases may benefit from the findings of this research, which will help rice production continue to grow sustainably. It is possible to do additional research to enhance the performance of the model by expanding the dataset and utilizing transfer learning strategies.