Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Fermented Rapeseed Meal, Inoculated with Selected Protease-Assisting Screened B. subtilis YY-4 and L. plantarum 6026, Showed High Availability and Strong Antioxidant and Immunomodulation Potential Capacity

A study was conducted to investigate the yield of small peptides from rapeseed meal (RSM) by solid-state fermentation (SSF) with acid-protease-assisting B. subtilis YY-4 and L. plantarum CICC6026 (FRSMP). This study explored the availability, antioxidant capacity and immunomodulation activity. The objective of this study was to develop a novel functional food ingredient to contribute to health improvement. The results showed that the concentrations of soluble peptides and free amino acids significantly increased after fermentation (p < 0.001), and the concentration of small molecular peptides (molecular weight < 1 KDa) significantly increased (p < 0.001). The dense surface microstructure of the RSM after fermentation was changed to be loose and porous. The FRSMP exhibited high availability and high antioxidant activity, and it displayed high immunomodulation activity. The novel fermentation was effective for improving the nutritional and biological properties, which provided a feasible method of enhancing the added value.
Lessons for Robotics From the Control Architecture of the Octopus

Biological and artificial agents are faced with many of the same computational and mechanical problems, thus strategies evolved in the biological realm can serve as inspiration for robotic development. The octopus in particular represents an attractive model for biologically-inspired robotic design, as has been recognized for the emerging field of soft robotics. Conventional global planning-based approaches to controlling the large number of degrees of freedom in an octopus arm would be computationally intractable. Instead, the octopus appears to exploit a distributed control architecture that enables effective and computationally efficient arm control. Here we will describe the neuroanatomical organization of the octopus peripheral nervous system and discuss how this distributed neural network is specialized for effectively mediating decisions made by the central brain and the continuous actuation of limbs possessing an extremely large number of degrees of freedom. We propose top-down and bottom-up control strategies that we hypothesize the octopus employs in the control of its soft body. We suggest that these strategies can serve as useful elements in the design and development of soft-bodied robotics.
Brain Tumor Segmentation and Classification in MRI using Clustering and Kernel-Based SVM

Brain tumor and other nervous systems cancer are one of the leading causes of death for many patients. Magnetic resonance imaging (MRI) is the most important medical imaging modality for diagnosing brain tumors and other disorders in the brain. Manual evaluation of several MRI images by radiologists or experts for diagnosing brain tumors especially at early stages is a challenging task. Hence, this paper proposes an automated framework for the segmentation and classification of brain tumors using K-means clustering and kernel-based support vector machine (K-SVM). The major steps of the proposed framework consist of preprocessing, segmentation, feature extraction with selection, and classification. In the preprocessing step, the regions of interest (ROI) are extracted using skull stripping and a median filter. In the next step, the tumor is segmented using an optimized K-means algorithm. Further, discrete wavelet transform (DWT)-based texture features are used for feature extraction, and significant features are selected by principal component analysis (PCA). Finally, the kernel-based support vector machine (K-SVM) is used for the classification of brain tumor types into benign and malignant, with a dataset using 160 MRI images, consisting of 20 normal and 140 abnormal. Experimental findings demonstrated the efficacy of the proposed framework with 98.75% accuracy, 95.43% precision, and 97.65% recall. The simulation findings emphasize the importance of the proposed system as compared to state-of-the-art techniques in terms of coherence parameters and performance.
Co-Administration of Lactulose Crystals with Amoxicillin Followed by Prolonged Lactulose Treatment Promotes Recovery of the Human Gut Microbiome In Vitro

The validated SHIME model was used to assess the effect of repeated administration of two different lactulose dosages (5 g/d and 10 g/d) on the human gut microbiome during and following amoxicillin–clavulanic acid treatment. First, antibiotic treatment strongly decreased Bifidobacteriaceae levels from 54.4% to 0.6% and from 23.8% to 2.3% in the simulated proximal and distal colon, respectively, coinciding with a marked reduction in butyrate concentrations. Treatment with lactulose enhanced acetate and lactate levels during antibiotic treatment, likely through lactulose fermentation by Lachnospiraceae and Lactobacillaceae. One week after cessation of antibiotic treatment, Bifidobacteriaceae levels re-increased to 20.4% and 7.6% in the proximal and distal colon of the 5 g lactulose/d co-administered unit, as compared with 1.0% and 2.2% in the antibiotic-treated unit, and were even further stimulated upon extension of lactulose administration. Marked butyrogenic effects were observed upon prolonged lactulose supplementation, suggesting the establishment of cross-feeding interactions between Bifidobacteriaceae and butyrate producers. Furthermore, a limited Enterobacteriaceae outgrowth following antibiotic treatment was observed upon dosing with 10 g lactulose/d, indicating inhibition of pathogenic colonization by lactulose following antibiotic therapy. Overall, lactulose seems to be an interesting candidate for limiting the detrimental effects of amoxicillin–clavulanic acid on the human gut microbiome, though further studies are warranted to confirm these findings.
Application of Multi-Electrode Resistivity Method on Semi-Diagenesis Rocks in Freezing Area and Its’ Implications

Recently, with the development of geophysical exploration technology, geophysical engineering instruments and methods have also improved. The multi-electrode resistivity method is widely used in engineering exploration. In this paper, multi-electrode resistivity tests were carried out in a seasonal frozen soil area in Heilongjiang Province, to provide an optimized multi-electrode resistivity method under the conditions of frozen soil. Combined with shear wave velocity tests and standard penetration tests, multi-electrode resistivity tests were used to comprehensively analyze and evaluate the physical and mechanical properties of Tertiary semi-diagenesis rocks. The results show that the high resistivity due to the frozen surface layer acting as a shield can be eliminated by technical means. It is feasible to test the resistivity through the frozen surface layer. The multi-electrode resistivity method can visually reflect the interface between saturated sand and semi-diagenetic rocks. Dividing the interface between saturated sand and semi-diagenetic rocks is advantageous as the morphology of the resistivity curve has a significant curvature change. There is a strong correlation between the resistance and shear wave velocity of a strata in which the Pearson correlation coefficient is as high as 0.99. The multi-electrode resistivity method test used in combination with the shear wave velocity test and the standard penetration test could give the bearing capacity and frictional resistance of semi-diagenetic rocks, which saves a lot of time and material costs in engineering exploration.
A Bivariate Beta from Gamma Ratios for Determining a Potential Variance Change Point: Inspired from a Process Control Scenario

Within statistical process control (SPC), normality is often assumed as the underlying probabilistic generator where the process variance is assumed equal for all rational subgroups. The parameters of the underlying process are usually assumed to be known—if this is not the case, some challenges arise in the estimation of unknown parameters in the SPC environment especially in the case of few observations. This paper proposes a bivariate beta type distribution to guide the user in the detection of a permanent upward or downward step shift in the process’ variance that does not directly rely on parameter estimates, and as such presents itself as an attractive and intuitive approach for not only potentially identifying the magnitude of the shift, but also the position in time where this shift is most likely to occur. Certain statistical properties of this distribution are derived and simulation illustrates the theoretical results. In particular, some insights are gained by comparing the newly proposed model’s performance with an existing approach. A multivariate extension is described, and useful relationships between the derived model and other bivariate beta distributions are also included.
Ensemble Based Feature Selection Technique For Flow Based Intrusion Detection System

The use of the internet has been drastically increasing in the last decades; hence, network security has become a big issue. To resolve these issues Intrusion detection system (IDS) plays a very important role. IDS detects malicious activity in the network by inspecting all network traffic and sending an alert message or signal to the administrator. So that the person can take the most reliable action to stop or block an attack, by using a higher number of features, we can easily develop an IDS, but it will take more computational time. Hence, it is necessary to choose a relevant set of features from the dataset, which will give us high accuracy and low computational time. In the proposed system CICIDS-2017 dataset is used, and for feature selection, the arithmetic operation is performed on Gain ratio, and Pearson’s correlation. Based on the arithmetic operation result, the top 30 features are selected out of 78 features, and these reduced sets of features are fed to the machine learning classifier random forest, and results are calculated. The result shows that a reduced set of features provides better accuracy, 99.8302%, than the total 78 features.
Multi-Photonen Verschrankung

An apparatus useful for continuous pan coating of edible cores which includes a coating drum arranged for rotation around an inclined axis and having an inlet opening at the upper axial end of the coating drum for reception of the edible cores, and a discharge opening at the lower axial end of the drum, so that the force of gravity urges the cores through the drum. The apparatus also includes a means for continuously driving the drum, means for providing coating material to the cores at a controllable rate, and means for delivering drying gas, such as air, to the cores also at a controllable rate while the cores are in the drum. The present invention has at least one after-treatment drum likewise arranged for rotation around an inclined axis and having an inlet opening at the upper axial end of the after-treatment drum and a discharge opening at the lower axial end, as well as a means for continuously driving the cores from the coating drum to the first after-treatment drum. In a preferred embodiment, the apparatus also includes a second after-treatment drum similar to the first after-treatment drum.
Enhancer-LSTMAtt: A Bi-LSTM and Attention-Based Deep Learning Method for Enhancer Recognition

Enhancers are short DNA segments that play a key role in biological processes, such as accelerating transcription of target genes. Since the enhancer resides anywhere in a genome sequence, it is difficult to precisely identify enhancers. We presented a bi-directional long-short term memory (Bi-LSTM) and attention-based deep learning method (Enhancer-LSTMAtt) for enhancer recognition. Enhancer-LSTMAtt is an end-to-end deep learning model that consists mainly of deep residual neural network, Bi-LSTM, and feed-forward attention. We extensively compared the Enhancer-LSTMAtt with 19 state-of-the-art methods by 5-fold cross validation, 10-fold cross validation and independent test. Enhancer-LSTMAtt achieved competitive performances, especially in the independent test. We realized Enhancer-LSTMAtt into a user-friendly web application. Enhancer-LSTMAtt is applicable not only to recognizing enhancers, but also to distinguishing strong enhancer from weak enhancers. Enhancer-LSTMAtt is believed to become a promising tool for identifying enhancers.
Gold Nanoparticles Prepared with Cyclodextrin Applied to Rapid Vertical Flow Technology for the Detection of Brucellosis

Currently, brucellosis seriously threatens the health of humans and animals and hinders the development of animal husbandry. However, the diagnostic methods for brucellosis have some disadvantages, such as low sensitivity, long detection time, professional operation, and high cost. This study aims to establish a convenient, fast, effective, and inexpensive detection method for brucellosis. Gold nanoparticles with β-cyclodextrin as a reducing agent were prepared and optimized, applied to rapid vertical flow technology (RVFT), and used to establish a kit for the detection of brucellosis. In this study, gold nanoparticles prepared from β-cyclodextrin were applied to RVFT for the first time, and on this basis, silver staining amplification technology was introduced, which further improved the sensitivity and reduced the detection limit of this method. Standard Brucella-Positive Serum (containing Brucella antibody at 4000 IU/mL) could be detected in this system even for a dilution factor of 1 × 10−3. The detection limit was 4 IU/mL. RVFT is simple to operate, has a short reaction time, and is 5–6 min visible to the naked eye, without any equipment.
Deformation Monitoring Using Remotely Sensed Radar Interferometric Data

The paper focuses on the capabilities of SAR (Synthetic Aperture Radar) interferometry for the monitoring of deformations of the Earth surface. The paper begins with a concise description of different interferometric procedures, like the coherence-based techniques and the amplitude-based techniques. A brief discussion of some important aspects, like the flexibility of the interferometric techniques and their capability to support a fully quantitative monitoring of deformations is included. The conditions to achieve high quality standards with SAR interferometry are described. In particular, the techniques based on single image pairs and those based on multiple SAR images are compared. The last part of the paper illustrates the preliminary results obtained over the city of Barcelona (Spain) using a stack of 20 ERS SAR images and a coherence based technique.
Creativity and Smartphone Use: Three Correlational Studies

Abstract Various books and popular media outlets claim that mindless smartphone use can impair creativity, yet few studies have tested this idea. We conducted a survey and three correlational studies focused on divergent thinking, the mindful ability to generate creative responses to open-ended problems. Most of the 48,000 participants surveyed thought that smartphone use reduced creativity. This view was consistent with the negative correlations we found between divergent thinking and both screen time and problematic smartphone use ( to −.35) in an exploratory sample of 62 university students. However, in two pre-registered replications with larger and more diverse samples (N = 294 and 16,932), we found at most tiny correlations between measures of divergent thinking or creative achievement and several types of smartphone use ( to .09). Thus, the link between smartphone use and creativity may be weaker or more nuanced than is commonly believed.
Programming E-Books: Culture, English, and Scratch for Schoolchildren of Rural Taiwan

There were few papers for interdisciplinary integration of Scratch programming, English learning, and local cultures as far as the digital animated E-book creation of elementary schools was concerned. This article proposes an interdisciplinary innovative teaching mode, with college students as teachers, Scratch programming and English learning as tools, and a local legend The Wind Chasers of Siraya as material for schoolchildren in a remote area of Taiwan. Schoolchildren were divided into four groups, and each group was responsible for a part, and finally these four parts were integrated into a complete animated English picture book with images, sound, music, and games. The purpose is to enhance the acquisition and learning of information technology and English application among schoolchildren in the remote area. Participants were evaluated in accordance with their learning motivation, self-efficacy, and learning effect. The self-efficacy scale was designed from three dimensions of the self-efficacy theory presented by Bandura and the syllabus of five functions in Scratch. The teaching effects were investigated with paired sample $t$ test. The results of these assessments revealed that schoolchildren’s learning motivation has been elevated, with a significant improvement of self-efficacy and overall learning achievement. In addition, the post-test revealed that Scratch programming and English learning from the culture-based illustration book had significant correlation, which suggested that the overall program successfully integrated these two subjects.
Assessment of Neoadjuvant Treatment Response Using Automated Breast Ultrasound in Breast Cancer

Breast imaging techniques are used to assess the tumor response to neoadjuvant treatment (NAT), which is increasingly one of the preferred therapeutic options and increases the rate of breast conservation for breast cancer. Herein, we report a case in which a woman was diagnosed with invasive ductal carcinoma in the left breast and received NAT before surgery. Automated breast ultrasound (AB US) was regularly performed before and during the NAT to evaluate the tumor response to NAT by measuring diameter changes and volume reductions of the tumor. Images showed that the tumor size was significantly reduced and disappeared after 7 cycles of NAT, except for macrocalcification. Postoperative histopathological examination confirmed that there were no residual tumor cells. We found that AB US overcame the limitations of handheld US, such as operator dependence, poor reproducibility and limited field of view, and can be an alternative modality to assess the tumor response of NAT in the absence of magnetic resonance imaging (MRI) instruments.
Comparison of contact interface factors for surface electromyography control wearable device

Surface electromyography is commonly used as control signals for wearable devices. Compared to physical sensors, bioelectric signal are more sensitive to pressure and placement of interface. Discussion of these factors includes not only ergonomic issues but also control issues. Variations of the two factors in setup could lead to variability in output values. In this article, we mainly discussed the influence of the two factors, including contact pressure and placement, to estimate the elbow joint angles based on surface electromyography. To our knowledge, there has been no research about this problem. We first measured the surface electromyography signal with elbow flexion and extension motion, then estimated the angles of motion through the pattern recognition method, and finally assessed the distribution of contact pressure and the accuracy of regression. Our results indicated that the accuracy of angle recognition depends on the consistency of pressure distribution over the contact surface. The contact surface can be placed in the anterior of the upper arm at lower contact pressures. When high contact pressure is required, the placement of the strap should cover the muscle belly. The main contribution of this study is that our results can be used to guide the human–machine interface design of wearable devices.
Exploration of Artificial Landscapes - Based on Random Graphs

The mapping of RNA{molecules to secondary structures is a good example to study principles of evolutionary optimization. Instead of using a prediction algorithm which takes into account thermodynamic parameters, we apply random graph theory to perform the mapping. Thereby we focus on statistical properties. The most prominent feature of preimages (neutral networks) is the existence of a threshold value for density and connectiv-ity properties. The neutral networks percolate sequence space and allow for optimization by using point and pair mutations.
Zn–Mn-Doped Mesoporous Bioactive Glass Nanoparticle-Loaded Zein Coatings for Bioactive and Antibacterial Orthopedic Implants

In recent years, natural polymers have replaced synthetic polymers for antibacterial orthopedic applications owing to their excellent biocompatibility and biodegradability. Zein is a biopolymer found in corn. The lacking mechanical stability of zein is overcome by incorporating bioceramics, e.g., mesoporous bioactive glass nanoparticles (MBGNs). In the present study, pure zein and zein/Zn–Mn MBGN composite coatings were deposited via electrophoretic deposition (EPD) on 316L stainless steel (SS). Zn and Mn were co-doped in MBGNs in order to make use of their antibacterial and osteogenic potential, respectively. A Taguchi design of experiment (DoE) study was established to evaluate the effect of various working parameters on the morphology of the coatings. It was observed that coatings deposited at 20 V for 5 min with 4 g/L concentration (conc.) of Zn–Mn MBGNs showed the highest deposition yield. Uniform coatings with highly dispersed MBGNs were obtained adopting these optimized parameters. Scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) were employed to investigate the morphology and elemental composition of zein/Zn–Mn MBGN composite coatings. Surface properties, i.e., coating roughness and wettability analysis, concluded that composite coatings were appropriate for cell attachment and proliferation. For adhesion strength, various techniques, including a tape test, bend test, pencil hardness test, and tensile test, were performed. Wear and corrosion analysis highlighted the mechanical and chemical stability of the coatings. The colony forming unit (CFU) test showed that the zein/Zn–Mn MBGN composite coating was highly effective against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) due to the presence of Zn. The formation of a hydroxyapatite (HA)-like structure upon immersion in the simulated body fluid (SBF) validated the in vitro bioactivity of the coating. Moreover, a WST-8 assay depicted that the MG-63 cells proliferate on the composite coating. It was concluded that the zein/Zn–Mn MBGN coating synthesized in this work can be used for bioactive and antibacterial orthopedic applications.
Assisted Reproductive Technique and Abnormal Cord Insertion: A Systematic Review and Meta-Analysis

Abnormal cord insertion (ACI) is associated with adverse obstetric outcomes; however, the relationship between ACI and assisted reproductive technology (ART) has not been examined in a meta-analysis. This study examines the association between ACI and ART, and delivery outcomes of women with ACI. A systematic review was conducted, and 16 studies (1990–2021) met the inclusion criteria. In the unadjusted pooled analysis (n = 10), ART was correlated with a higher rate of velamentous cord insertion (VCI) (odds ratio (OR) 2.14, 95% confidence interval (CI) 1.64–2.79), marginal cord insertion (n = 6; OR 1.58, 95%CI 1.26–1.99), and vasa previa (n = 1; OR 10.96, 95%CI 2.94–40.89). Nevertheless, the VCI rate was similar among the different ART types (blastocyst versus cleavage-stage transfer and frozen versus fresh embryo transfer). Regarding the cesarean delivery (CD) rate, women with VCI were more likely to have elective (n = 3; OR 1.13, 95%CI 1.04–1.22) and emergent CD (n = 5; OR 1.93, 95%CI 1.82–2.03). In conclusion, ART may be correlated with an increased prevalence of ACI. However, most studies could not exclude confounding factors; thus, further studies are warranted to characterize ART as a risk factor for ACI. In women with ACI, elective and emergent CD rates are high.