Miracle-dz/UniFAR-FTUs huggingface dataset:
Image reconstruction algorithms for electrical capacitance tomography

Electrical capacitance tomography (ECT) is used to image cross-sections of industrial processes containing dielectric material. This technique has been under development for more than a decade. The task of image reconstruction for ECT is to determine the permittivity distribution and hence material distribution over the cross-section from capacitance measurements. There are three principal difficulties with image reconstruction for ECT: (1) the relationship between the permittivity distribution and capacitance is non-linear and the electric field is distorted by the material present, the so-called 'soft-field' effect; (2) the number of independent measurements is limited, leading to an under-determined problem and (3) the inverse problem is ill posed and ill conditioned, making the solution sensitive to measurement errors and noise. Regularization methods are needed to treat this ill-posedness. This paper reviews existing image reconstruction algorithms for ECT, including linear back-projection, singular value decomposition, Tikhonov regularization, Newton–Raphson, iterative Tikhonov, the steepest descent method, Landweber iteration, the conjugate gradient method, algebraic reconstruction techniques, simultaneous iterative reconstruction techniques and model-based reconstruction. Some of these algorithms are examined by simulation and experiment for typical permittivity distributions. Future developments in image reconstruction for ECT are discussed.
Electrical and structural properties of poly-SiGe film formed by pulsed-laser annealing

Electrical and structural properties of polycrystalline silicon germanium (poly-SiGe) films fabricated by pulsed-laser annealing were investigated. Observation of laser-induced melt-regrowth of SiGe films using transient conductance measurement revealed that the melt depth and the crystallization velocity increased as Ge concentration increased. The increase of the crystallization velocity resulted in increase of the average size of crystalline grains from 66 to 120 nm at the laser energy density of 360 mJ/cm2 with increasing Ge concentration from 0 to 60%. The crystalline volume ratio obtained by reflectivity spectra in the ultraviolet region also increased from 0.83 to 1.0. Numerical analysis revealed that the density of electrically active defects decreased from 3.5×1018 to 1.1×1018 cm−3 as Ge concentration increased from 0 to 80%. The density of defect states of Si0.8Ge0. 2 films were reduced from 3.5×1018 to 1.9×1018 cm−3 by 13.56-MHz hydrogen plasma treatment at 250 °C, 30 W, and 130 Pa for 30 s. How.
A Socially-Aware Dependent Tasks Offloading Strategy in Mobile Edge Computing

With the advent of 5G, Mobile Edge Computing (MEC), a promising computing paradigm sits closer to users than cloud computing, is being broadly used in various Internet of Things (IoT) applications, and achieve high-quality user experience. Task offloading, as a critical research issue in MEC, is playing an important role in optimizing computational resources and management. However, many tasks are executed dependent on the computational results of other tasks. Moreover, in the case of offloading tasks with other devices, it is often required to consider the success rate of offloading, since not all users are willing to lend their mobile devices to others for task execution. To address this challenge, by taking social relationships between users into account, this paper intends to combine computational resources of local devices and edge clouds and provide more flexible offloading and execution solutions, for achieving the efficient offloading of dependent tasks with the joint consideration of network latency and energy consumption. This paper develops a dependent task offloading strategy based on Bipartite Graph Matching. Extensive simulations are conducted for validating the effectiveness of our proposed strategy. Experimental results demonstrate that our proposed strategy can significantly minimize the overhead compared with other baseline strategies. In particular, the overhead is reduced 8.2%, compared with the strategy which consider the Device-to-Device (D2D) offloading only.
Application of Convolutional Neural Networks Using Action Potential Shape for In-Silico Proarrhythmic Risk Assessment

This study proposes a convolutional neural network (CNN) model using action potential (AP) shapes as input for proarrhythmic risk assessment, considering the hypothesis that machine-learning features automatically extracted from AP shapes contain more meaningful information than do manually extracted indicators. We used 28 drugs listed in the comprehensive in vitro proarrhythmia assay (CiPA), consisting of eight high-risk, eleven intermediate-risk, and nine low-risk torsadogenic drugs. We performed drug simulations to generate AP shapes using experimental drug data, obtaining 2000 AP shapes per drug. The proposed CNN model was trained to classify the TdP risk into three levels, high-, intermediate-, and low-risk, based on in silico AP shapes generated using 12 drugs. We then evaluated the performance of the proposed model for 16 drugs. The classification accuracy of the proposed CNN model was excellent for high- and low-risk drugs, with AUCs of 0.914 and 0.951, respectively. The model performance for intermediate-risk drugs was good, at 0.814. Our proposed model can accurately assess the TdP risks of drugs from in silico AP shapes, reflecting the pharmacokinetics of ionic currents. We need to secure more drugs for future studies to improve the TdP-risk-assessment robustness.
An Immunoinformatics Approach to Design Novel and Potent Multi-Epitope-Based Vaccine to Target Lumpy Skin Disease

The lumpy skin disease (LSD) virus of the Poxviridae family is a serious threat that mostly affects cattle and causes significant economic loss. LSD has the potential to spread widely and its rapidly across borders. Despite the availability of information, there is still no competitive vaccine available for LSD. Therefore, the current study was conducted to develop an epitope-based LSD vaccine that is efficient, secure, and biocompatible and stimulates both innate and adaptive immune responses using immunoinformatics techniques. Initially, putative virion core proteins were manipulated; B-cell and T-cell epitopes have been predicted and connected with the help of adjuvants and linkers. Numerous bioinformatics methods, including antigenicity testing, transmembrane topology screening, allergenicity assessment, conservancy analysis, and toxicity evaluation, were employed to find superior epitopes. Based on promising vaccine candidates and immunogenic potential, the vaccine design was selected. Strong interactions between TLR4 and TLR9 and the anticipated vaccine design were revealed by molecular docking. Finally, based on the high docking score, computer simulations were performed in order to assess the stability, efficacy, and compactness of the constructed vaccine. The simulation outcomes showed that the polypeptide vaccine design was remarkably stable, with high expression, stability, immunogenic qualities, and considerable solubility. Additionally, computer-based research shows that the constructed vaccine provides adequate population coverage, making it a promising candidate for use in the design of vaccines against other viruses within the Poxviridae family and potentially other virus families as well. These outcomes suggest that the epitope-based vaccine developed in this study will be a significant candidate against LSD to control and prevent LSDV-related disorders if further investigated experimentally.
Efficient Clustering of Software Vulnerabilities using Self Organizing Map (SOM)

The common vulnerabilities and exposures (CVE) database was created with a mission to “identify, define, and catalog publicly disclosed cybersecurity vulnerabilities”. This rich body of information can be used to enable rapid and efficient response to secure and defend cyber operations and protect critical cyber infrastructure. The main goal of this paper is to develop a visual analytic tool to enable deep analysis of CVEs using unsupervised clustering techniques. We enhance our analysis by first mapping CVEs to hierarchical-classes in Common Weakness Enumeration (CWE) using information in the National Vulnerability Database (NVD). Both the mapping and the numerical representation of CVEs are enabled by V2W-BERT, which uses natural language processing of the extensive information in NVD to generate a large tabular database of 137,226 CVE entries from 1999 to 2020, where each CVE is represented by a vector of 768 numerical features. The vectorized data is processed by Self-Organizing Maps (SOM), which is an unsupervised machine learning technique for dimensionality reduction, visual representation and clustering. Using a Torus map of 6417 units, we achieve 10-fold data compression of 140k CVEs using SOM. The trained map is further clustered using standard K-means clustering into 138 clusters of CVEs. We conducted a brief investigation of the rich mapping of CVEs to best-matching-units to K-means clusters, as well as CVEs to CWEs. For example, this novel mapping provided insight into the role of CWE-59 and CWE-264 in several CVEs that is otherwise hard to explore in the original data. We conclude that our this novel approach will not only enable deep analysis of the complex relationships between CVEs and CWEs, but also a mechanism to quickly respond to and design mitigation actions for rapidly evolving vulnerabilities that have not been mapped to existing CWEs.
Two-dimensional Submicron Focusing of Hard X-rays by Two Elliptical Mirrors Fabricated by Plasma Chemical Vaporization Machining and Elastic Emission Machining

To realize submicron focusing of hard X-rays, elliptical mirrors were manufactured using the new fabrication methods of elastic emission machining and plasma chemical vaporization machining. Line focused X-ray beam profiles of each mirror was evaluated at the 1-km-long beamline of SPring-8, and this showed nearly diffraction-limited performances were achieved. A Kirkpatrick–Baez mirror unit equipping an automatic optical alignment system, in which the fabricated mirrors were used, was designed, constructed and confirmed to enable 200×200 nm2 focusing of 15 keV X-ray.
Time dependent degradation of photovoltaic modules by ultraviolet light

For high efficiency silicone encapsulated solar modules for concentrator photovoltaic systems or space applications, the question of performance degradation due to long term exposure to ultraviolet (UV) light is addressed. The transparent silicones DC93-500 and Elastosil S690 and S695 were subjected to a time and wavelength resolved UV test with a total accumulated dose of 10 000 equivalent sun hours. Based on a model for the kinetics of photodegradation, it is shown that the measured decrease in transmittance translates into a universal logarithmic time dependence for the module short circuit current. The UV related performance impact over 15years under the AM0 spectrum in space and the terrestrial AM1.5 spectrum with 500× concentration is quantified.For high efficiency silicone encapsulated solar modules for concentrator photovoltaic systems or space applications, the question of performance degradation due to long term exposure to ultraviolet (UV) light is addressed. The transparent silicones DC93-500 and Elastosil S690 and S695 were subjected to a time and wavelength resolved UV test with a total accumulated dose of 10 000 equivalent sun hours. Based on a model for the kinetics of photodegradation, it is shown that the measured decrease in transmittance translates into a universal logarithmic time dependence for the module short circuit current. The UV related performance impact over 15years under the AM0 spectrum in space and the terrestrial AM1.5 spectrum with 500× concentration is quantified.
A highly integrated terahertz imaging detector with conical extended hemispherical lens antennas

In order to realize the integrated terahertz imaging detector, the on-chip Schottky barrier diodes and lens antennas are studied in this paper. Schottky barrier diode with cut-off frequency of 800 GHz was manufactured by polysilicon gate separation technology in SMIC 180 nm process. A conic extension is used for optimizing the spherical aberration of lenses. The principle is explained by ray-tracing theory, and its model is simulated, optimized and fabricated by nylon. The integrated detector is composed of a lens antenna and a Schottky barrier diodes. The assembled detector is tested at 220GHz, whose response rate of the test result is 130 V/W and the noise equivalent power is 400 pW / ✓ Hz. Using the detector designed in this paper to do the liquid level imaging experiment in the opaque ceramic bottle, the liquid level image is clearly visible, which shows the application potential of terahertz imaging in the field of nondestructive testing.
Local government spending efficiency and fiscal decentralization: evidence from Italian municipalities

ABSTRACT This article investigates the association between fiscal decentralization and municipality efficiency by conducting an empirical analysis focused on the Italian context. We conduct a cost-efficiency analysis based on a stochastic frontier approach with municipality and time fixed effects modelling the decentralization effect with a continuous variable, taxation autonomy, which allows for accounting for the degree and evolution of fiscal decentralization over time. The empirical analysis provides convincing evidence that fiscal decentralization is positively associated with municipalities’ efficiency. The positive effect is confirmed when additional controls are included into the model and persists to robustness checks. This evidence lends support for policies aimed at making more closely aligned expenditure and revenue decision-making.
An Approach toward Artificial Intelligence Alzheimer’s Disease Diagnosis Using Brain Signals

Background: Electroencephalography (EEG) signal analysis is a rapid, low-cost, and practical method for diagnosing the early stages of dementia, including mild cognitive impairment (MCI) and Alzheimer’s disease (AD). The extraction of appropriate biomarkers to assess a subject’s cognitive impairment has attracted a lot of attention in recent years. The aberrant progression of AD leads to cortical detachment. Due to the interaction of several brain areas, these disconnections may show up as abnormalities in functional connectivity and complicated behaviors. Methods: This work suggests a novel method for differentiating between AD, MCI, and HC in two-class and three-class classifications based on EEG signals. To solve the class imbalance, we employ EEG data augmentation techniques, such as repeating minority classes using variational autoencoders (VAEs), as well as traditional noise-addition methods and hybrid approaches. The power spectrum density (PSD) and temporal data employed in this study’s feature extraction from EEG signals were combined, and a support vector machine (SVM) classifier was used to distinguish between three categories of problems. Results: Insufficient data and unbalanced datasets are two common problems in AD datasets. This study has shown that it is possible to generate comparable data using noise addition and VAE, train the model using these data, and, to some extent, overcome the aforementioned issues with an increase in classification accuracy of 2 to 7%. Conclusion: In this work, using EEG data, we were able to successfully detect three classes: AD, MCI, and HC. In comparison to the pre-augmentation stage, the accuracy gained in the classification of the three classes increased by 3% when the VAE model added additional data. As a result, it is clear how useful EEG data augmentation methods are for classes with smaller sample numbers.
High Transmittance Band-Pass Plasmonic Filter Using Metal-Insulator-Metal Waveguide with Double Split Circular Ring Resonator

In this paper, a band-pass plasmonic filter based on Metal-Insulator-Metal (MIM) waveguides and its modified structures are designed and investigated theoretically and numerically. The filter consists of two circular ring resonator and its modified structures which has narrow gaps in the middle of resonant rings. To study their performance in different structures, propagation modes of surface plasmon polaritons (SPPs) are investigated. In outer gapped model, we found that the transmission in different resonant modes can be effectively tuned by varying the gap width, and the transmission peak wavelength is nonlinear with the gap width. The results are obtained by high-order symplectic FDTD (SFDTD) algorithm which is non-dissipative and has low dispersion error. The structure with double gaps in both external and internal rings have potential applications in plasmonic integrated circuits, because of its characteristic of a single narrow band-pass with high transmittance. The introduced structures may provide a novel method for the design of devices in highly integrated optical circuits.
Average Daily Gain in Lambs Weaned at 60 Days of Age Is Correlated with Rumen and Rectum Microbiota

Colonization of gastrointestinal microbiota in mammals during early life is vital to host health. The objective of this study was to investigate whether lambs with high and low ADG have a different rumen and rectum microbial community. Thus, we investigated potential relationships between rumen and rectum microbiota and average daily gain (ADG) in weaned lambs. Sixteen lambs with similar body weights (7.63 ± 1.18 kg) were selected at 30 days of age. At 60 days of age, lambs were weaned, and ADG was calculated from 60 to 90 days. Then, two groups were generated: higher ADG (HG, 134.17 ± 13.48 g/day) and lower ADG (LG, 47.50 ± 19.51 g/day). Microbiota was evaluated at 30, 60, and 90 days of age. The final live weight and ADG at 90 days of age was higher (p < 0.05) in the HG group compared to the LG group. The maturity of bacterial and fungal communities was increased (p < 0.05) in the HG group for the 30 days vs. 90 days comparison and 60 days vs. 90 days comparison. Linear discriminant analysis effect size (LEfSe) analysis revealed a total of 18 bacterial biomarkers that are ADG-specific in the rumen and 35 bacterial biomarkers in the rectum. Meanwhile, 15 fungal biomarkers were found in the rumen and 8 biomarkers were found in the rectum. Our findings indicated that ADG is related to the rumen and rectum microbiota in lambs.
Evaluation of Beta-Defensin 1 and Mannose-Binding Lectin 2 Polymorphisms in Children with Dental Caries Compared to Caries-Free Controls: A Systematic Review and Meta-Analysis

Background and objective: Some variants in defensin beta 1 (DEFB1) and mannose-binding lectin 2 (MBL2) genes can be associated with oral diseases. Herein, we designed a systematic review and meta-analysis to evaluate the association of DEFB1 (rs11362, rs1799946, and rs1800972) and MBL2 (rs7096206 and rs1800450) polymorphisms with the susceptibility to dental caries (DC) in children. Materials and methods: A systematic literature search was conducted in the PubMed/Medline, Web of Science, Scopus, and Cochrane Library databases until 3 December 2022, without any restrictions. The odds ratio (OR), along with a 95% confidence interval (CI) of the effect sizes, are reported. Analyses including a subgroup analysis, a sensitivity analysis, and funnel plot analyses were conducted. Results: A total of 416 records were identified among the databases, and nine articles were entered into the meta-analysis. A significant relationship was found between the T allele of DEFB1 rs11362 polymorphism and DC susceptibility, and the T allele was related to an elevated risk of DC in children (OR = 1.225; 95%CI: 1.022, 1.469; p = 0.028; I2 = 0%). No other polymorphisms were associated with DC. All articles were of moderate quality. Egger’s test in homozygous and dominant models demonstrated a significant publication bias for the association of DEFB1 rs1799946 polymorphism with DC risk. Conclusions: The results demonstrated that the T allele of DEFB1 rs11362 polymorphism had an elevated risk for DC in children. However, there were only few studies that evaluated this association.
Lactobacillus rhamnosus GG Promotes Recovery of the Colon Barrier in Septic Mice through Accelerating ISCs Regeneration

Disruption of the intestinal barrier is both the cause and result of sepsis. The proliferation and differentiation of intestinal stem cells (ISCs) promote the regenerative nature of intestinal epithelial cells, repairing the injured intestinal mucosal barrier; however, it is uncertain whether the recovery effects mediated by the ISCs are related to the gut microbiota. This research found that the survival rate of septic mice was improved with a Lactobacillus rhamnosus GG (LGG) treatment. Furthermore, an increased proliferation and decreased apoptosis in colon epithelial cells were observed in the LGG-treated septic mice. In vitro, we found that a LGG supernatant was effective in maintaining the colonoid morphology and proliferation under the damage of TNF-α. Both in the mice colon and the colonoid, the LGG-induced barrier repair process was accompanied by an increased expression of Lgr5+ and lysozyme+ cells. This may be attributed to the upregulation of the IL-17, retinol metabolism, NF-kappa B and the MAPK signaling pathways, among which, Tnfaip3 and Nfkbia could be used as two potential biomarkers for LGG in intestinal inflammation therapy. In conclusion, our finding suggests that LGG protects a sepsis-injured intestinal barrier by promoting ISCs regeneration, highlighting the protective mechanism of oral probiotic consumption in sepsis.
Nonlinear optical crystal-line writing in glass by yttrium aluminum garnet laser irradiation

Crystal lines with second-order optical nonlinearity have been successfully fabricated at the surface of 10Sm2O3.35Bi2O3. 55B2O3 glass by continuous irradiation of Nd:YAG laser. The laser-induced crystalline phase was confirmed to be Bi0.7Sm0. 3BO3 by x-ray diffraction measurements, and second-harmonic generation (SHG) from the phase was clearly observed. An array structure of crystal lines was fabricated by laser writing under automatic computer control, and Maker fringe patterns of SHG were observed, indicating that the direction of polarization in the structure with a crystal line array was parallel to the sample surface. In addition, we measured polarization optical microphotographs, and found uniform phase retardation for a whole length of crystal lines. It is strongly suggested from these results that crystal lines by laser irradiation are formed in single-domain crystalline phase (single crystal) with second-order nonlinearity.