Miracle-dz/UniFAR-FTUs huggingface dataset:
Separating Partially-Polarized Diffuse and Specular Reflection Components under Unpolarized Light Sources

Separating diffuse and specular reflection components observed on an object surface is important for preprocessing of various computer vision techniques. Conventionally, diffuse-specular separation based on the polarimetric and color clues assumes that the diffuse/specular reflection components are unpolarized/partially polarized under unpolarized light sources. However, the diffuse reflection component is partially polarized in fact, because the diffuse reflectance is maximal when the polarization direction is parallel to the outgoing plane. Accordingly, we propose a method for separating partially-polarized diffuse and specular reflection components on the basis of the polarization reflection model and the dichromatic reflection model. In particular, our method enables us not only to achieve diffuse-specular separation but also to estimate the polarimetric properties of the object surface from a single color polarization image. We experimentally confirmed that our method performs better than the method assuming unpolarized diffuse reflection components.
Contribution of Sun-like faculae to the light-curve modulation of young active dwarfs

Aims. The time variability of the broadband solar irradiance depends not only on the intrinsic evolution and visibility modulation of sunspots but also on that of faculae that become brighter near the limb during the solar rotation. Sun-like faculae around spots could also play a significant role in modulating the broadband visible flux of active dwarfs. It is the aim of the present study to test this hypothesis. Methods. I analyzed high accuracy light-curves of two active dwarfs obtained with the MOST satellite during several stellar rotation periods. The observed time series were fitted using a model that takes into account not only starspot contributions but also the areas of faculae in active regions and their bolometric contrast. Results. A low value of the mean ratio of faculae to cool spot areas in active regions provides the best description of e Eri and K Ceti light curves. Conclusions. Although not conclusive, this result suggests that the ratio of faculae to cool spot areas decreases in stars somewhat more active than the Sun.
Sensitive Temperature Probes Detail Different Turbulence Processes in the Deep Mediterranean

In addition to large-scale water flows and eddies, small-scale turbulent mixing distributes heat, water masses, and suspended matter in the deep sea. In contrast to turbulent mixing near the sea surface, which is driven by wind and waves and redistributes solar heat input, large-scale mixing in the deep sea occurs near steep underwater topography such as ridges, seamounts, and continental slopes. For example, above the continental slope in the Western Mediterranean Sea, boundary flows, (sub-)mesoscale eddies, and internal waves dominate water motions. In this area, wintertime dense-water formation, breaking of internal waves, and geothermal heating are associated with turbulent mixing. As a result, vertical stable density stratification is very weak. Detailed observations of turbulent mixing in the deep sea are rare and demand high-resolution instrumentation. This paper provides an overview of various types of deep Mediterranean turbulence observed using high-resolution temperature sensors, including weak turbulence resulting from stable internal waves in late summer and autumn, strong turbulence caused by geothermal heating from below in winter, and moderate turbulence induced by stratified waters pressing down from above during dense-water formation in late winter and spring.
Detection Of Road Damage Using Faster Regional-Convolutional Neural Network Method

Road damage is a common occurrence daily. Even in developed nations, road damage is still a possibility. Rainwater, temperature and weather variations, air temperature, construction materials on the road, subgrade conditions on the road, poor compaction process above the subgrade, and vehicle weights that exceed the limit are all factors that cause damage. Potholes are the most common form of road damage. Damaged roads are a major annoyance for drivers, can lead to accidents, and can even result in on-the-spot deaths due to falls since drivers are unaware of the potholes. If road damage is not discovered or overcome, it can be dangerous, and the road will deteriorate. Many media, including images, can be used to detect road damage. This study uses the image by utilizing the Faster R-CNN method to detect road damage. It reveals that using the MobilenetV2 backbone achieved the optimal performance indicated by the mAP value of 79.7%.
ICRH power absorption measurements from analysis of RF sinusoidal low-frequency modulation experiments in TEXTOR

Modulation of the ICRH power amplitude has been performed sinusoidally in TEXTOR over a wide modulation frequency range in an (H)-D plasma. From an analysis of reproducible discharges in which the ICRH is modulated at a relatively high modulation frequency Omega /2 pi (50-300 Hz), we observe that only a fraction (about 50%) of the ICRH power is transferred to the plasma with a good energy confinement time. We also show that the analysis of a single modulated discharge already provides part of the information. The analysis is supported by a careful investigation of the non-stationary energy response obtained from the diamagnetic look and from the equilibrium measurement. The eigenfunction expansion of the transport equation for global energy in which each successive mode has a particular absorption coefficient and a decreasing confinement time indicates that about 50% of the ICRH power is coupled to the fundamental mode with the best confinement time. The remainder of the power goes to other modes with decreasing confinement times. Such a time-dependent analysis allows us therefore to distinguish between the fraction of the power absorbed by the core of the plasma (good confinement) and the fraction absorbed by the edge (bad confinement). The conclusions of this modulation analysis are qualitatively similar for high-field side (HFS) antennae with predominantly direct electron heating and for low-field side (LFS) antennae with predominantly minority-ion heating. In the second scenario, a detailed analysis has been provided to account for the anisotropic contribution to the energy of the minority ions.
Fuzzy Logic Control-Based Interleaved Boost Converter for Proton Exchange Membrane Fuel Cell System Applications

This paper presents the design and simulation of an interleaved boost converter using a 6-kW proton exchange membrane fuel cell (PEMFC). Fuel cells are a renewable energy source that produces clean and efficient power. However, due to changes in operating conditions, the resulting output voltage cannot be constant, so a converter is needed. This paper aims to describe the design and development of an interleaved boost converter (IBC) for a fuel cell application equipped with a fuzzy logic controller. The IBC design includes the selection of appropriate inductor and capacitor values as well as power semiconductor devices to reduce switching losses. Fuzzy controller design includes determining membership function and making fuzzy rules. The design simulation results show that the use of fuzzy logic control as a PWM controller in the interleaved boost converter can improve the dynamic characteristics of the output voltage transient response even though there is a disturbance in the converter input voltage (output of the fuel cell) because of disturbances or changes in operating conditions. The proposed two-phase IBC reduces the load voltage ripple to a very small extent. In addition, the ripple in the PEMFC load current is greatly reduced. This can help extend the life of the fuel cell.
Molecular Detection and Phylogenetic Analysis of Riemerella anatipestifer in Poultry and Wild Geese in Poland

Riemerella anatipestifer (RA) is one of the most relevant bacterial pathogens of commercial waterfowl from clinical and economic points of view. Our study aimed to evaluate the prevalence of RA infection in different types of commercial poultry in Poland and verify the potential role of wild geese as vectors of this pathogen. We tested a total of 126 poultry flocks, including geese (N = 20), ducks (N = 42), turkeys (N = 64) and 19 wild geese, including greater white-fronted geese (N = 9), greylag geese (N = 5) and Taiga bean geese (N = 5). Tracheal swabs were examined for RA using a PCR targeting a conserved region of the 16S rRNA gene. Selected PCR products were sequenced to perform the phylogenetic analysis. Among the commercial poultry, the highest RA prevalence was found in flocks of ducks (35.7%) and geese (30.0%), whereas the lowest one was found in turkeys (3.2%). Most tested wild geese (94.7%) were RA positive. The phylogenetic analysis showed relatively low genetic diversity of the sequences analyzed, which gathered in two clusters of the phylogenetic tree, and the minimum nucleotide identity was 98.6%. Our results would support the contention that RA isolates from commercial poultry circulate in wild bird populations but are not transmitted back to poultry.
On the approximate analytical solution to non-linear oscillation systems

This study describes an analytical method to study two well-known systems of nonlinear oscillators. One of these systems deals with the strongly nonlinear vibrations of an elastically restrained beam with a lumped mass. The other is a Duffing equation with constant coefficients. A new implementation of the Variational Approach (VA) is presented to obtain highly accurate analytical solutions to free vibration of conservative oscillators with inertia and static type cubic nonlinearities. In the end, numerical comparisons are conducted between the results obtained by the Variational Approach and numerical solution using Runge-Kutta's [RK] algorithm to illustrate the effectiveness and convenience of the proposed methods.
Similar tests and the standardized log likelihood ratio statistic

SUMMARY When testing an affine hypothesis in an exponential family the 'ideal' procedure is to calculate the exact similar test, or an approximation to this, based on the conditional distribution given the minimal sufficient statistic under the null hypothesis. By contrast to this there is a 'primitive' approach in which the marginal distribution of a test statistic is considered and any nuisance parameter appearing in the test statistic is replaced by an estimate. We show here that when using standardized likelihood ratio statistics the 'primitive' procedure is in fact an 'ideal' procedure to order O(n-3/2). As an example we consider inference for the mean of a log normal distribution in detail.
Fake News Detection Model on Social Media by Leveraging Sentiment Analysis of News Content and Emotion Analysis of Users’ Comments

Nowadays, social media has become the main source of news around the world. The spread of fake news on social networks has become a serious global issue, damaging many aspects, such as political, economic, and social aspects, and negatively affecting the lives of citizens. Fake news often carries negative sentiments, and the public’s response to it carries the emotions of surprise, fear, and disgust. In this article, we extracted features based on sentiment analysis of news articles and emotion analysis of users’ comments regarding this news. These features were fed, along with the content feature of the news, to the proposed bidirectional long short-term memory model to detect fake news. We used the standard Fakeddit dataset that contains news titles and comments posted regarding them to train and test the proposed model. The suggested model, using extracted features, provided a high detection accuracy of 96.77% of the Area under the ROC Curve measure, which is higher than what other state-of-the-art studies offer. The results prove that the features extracted based on sentiment analysis of news, which represents the publisher’s stance, and emotion analysis of comments, which represent the crowd’s stance, contribute to raising the efficiency of the detection model.
Epigenetic clocks derived from western samples differentially reflect Taiwanese health outcomes

Introduction: Several epigenetic clocks have been developed, with five measures of epigenetic age acceleration (EAA) especially receiving extensive investigations: HannumEAA, IEAA, PhenoEAA, GrimEAA, and DunedinPACE. These epigenetic clocks were mainly developed by individuals of European or Hispanic ancestry. It remains unclear whether they can reflect disease morbidity and physiological conditions in Asian populations. Methods: I here investigated five measures of EAA of 2,474 Taiwan Biobank participants with DNA methylation data. Using logistic regressions, I sequentially regressed various health outcomes on each of the five measures of EAA while adjusting for chronological age, sex, body mass index, the number of smoking pack-years, drinking status, regular exercise, educational attainment, and six cell-type proportions. Results: Except for IEAA, all measures of EAA reflected the obesity of Taiwanese (p < 4.0E-4). Diabetes was reflected by DunedinPACE (p = 5.4E-6) and GrimEAA (p = 5.8E-5). Moreover, DunedinPACE was associated with dyslipidemia, including hypertriglyceridemia (p = 1.1E-5), low high-density lipoprotein cholesterol (HDL-C) (p = 4.0E-5), and high triglyceride to HDL-C ratio (p = 1.6E-7). Discussion: This is one of the first studies to show that epigenetic clocks (developed by individuals of European or Hispanic ancestry) can reflect Taiwanese physiological conditions. DunedinPACE was associated with more Taiwanese health outcomes than the other four measures of EAA.
Impact time measurement by using the fiber optic sensor in the pendulum ball collision

In this paper physical quantities were measured using by the fiber optic sensor when a pendulum ball collides to the fixed ball on the wall. Both steel ball dimensions are 1 inch in diameter. The fiber optic Sagnac interferometer was used to detect the impact time. It is made a 1mm penetrated hole and optical fiber in the Sagnac loop passed through the hole. A ball was welded on the steel plate wall as a fixed ball. When the another ball collides to the fixed ball the fiber optic sensor detects the impact force in between them. Based on the experimental result impact time was measured about 0.14ms at the angle of 30 degree. This fiber optic sensor technique can be expanded to the moving bodies.
Research on large aperture telescope drive control technology

The direct drive motor of large aperture telescope, integrated with the telescope mechanic structure, has characteristics of high load torque and large moment of inertia. The control method of drive system should be specially designed for the heavy load. This article aims to list the key issues of engineering technology applied to large aperture telescope. Drive control architecture and method, as well as design requirements of segmented direct drive motor on large astronomic telescope, are discussed in this article.
Discriminative ‘Turn-on’ Detection of Al3+ and Ga3+ Ions as Well as Aspartic Acid by Two Fluorescent Chemosensors

In this work, two Schiff-base-based chemosensors L1 and L2 containing electron-rich quinoline and anthracene rings were designed. L1 is AIEE active in a MeOH-H2O solvent system while formed aggregates as confirmed by the DLS measurements and fluorescence lifetime studies. The chemosensor L1 was used for the sensitive, selective, and reversible ‘turn-on’ detection of Al3+ and Ga3+ ions as well as Aspartic Acid (Asp). Chemosensor L2, an isomer of L1, was able to selectively detect Ga3+ ion even in the presence of Al3+ ions and thus was able to discriminate between the two ions. The binding mode of chemosensors with analytes was substantiated through a combination of 1H NMR spectra, mass spectra, and DFT studies. The ‘turn-on’ nature of fluorescence sensing by the two chemosensors enabled the development of colorimetric detection, filter-paper-based test strips, and polystyrene film-based detection techniques.
Imbalanced Clustering With Theoretical Learning Bounds

Imbalanced clustering, where the number of samples varies in different clusters, has arisen from many real data mining applications. It has gained increasing attention. Nevertheless, due to its unsupervised nature, imbalanced clustering is more challenging than its supervised counterpart, i.e., imbalanced classification. Furthermore, existing imbalanced clustering methods are empirically designed and they often lack solid theoretical guarantees, e.g., the excess risk estimation. To solve these important but rarely studied problems, we first propose a novel <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="hou-ieq1-3242306.gif"/></alternatives></inline-formula>-Means algorithm for imbalanced clustering problem with Adaptive Cluster Weight (MACW), together with its excess clustering risk bound analysis. Inspired by this theoretical result, we further propose an improved algorithm called Imbalanced Clustering with Theoretical Learning Bounds (ICTLB). It refines the weights and encourages the optimal trade-off among per-cluster weights by optimizing the excess clustering risk bound. A theoretically-principled justification of ICTLB is provided for verification. Comprehensive experiments on many imbalanced datasets verify the effectiveness of ICTLB in solving cluster imbalanced problems.
Effect of Different Anticoagulant Agents on Immune-Related Genes in Leukocytes Isolated from the Whole-Blood of Holstein Cows

Anticoagulants, such as ethylenediaminetetraacetic acid (EDTA), sodium citrate (Na-citrate), or heparin are normally used in hematological clinical tests to prevent coagulation. Although anticoagulants are fundamental for the correct application of clinical tests, they produce adverse effects in different fields, such as those involving specific molecular techniques; for instance, quantitative real time polymerase chain reactions (qPCR) and gene expression evaluation. For this reason, the aim of this study was to evaluate the expression of 14 genes in leukocytes that were isolated from the blood of Holstein cows, and which were collected in Li-heparin, K-EDTA, or Na-citrate tubes; then, they were analyzed using qPCR. Only the SDHA gene showed a significant dependence (p ≤ 0.05) on the anticoagulant that was used with the lowest expression; this was observed in Na-Citrate after being compared with Li-heparin and K-EDTA (p < 0.05). Although a variation in transcript abundance with the three anticoagulants was observed in almost all the investigated genes, the relative abundance levels were not statistically significant. In conclusion, the qPCR results were not influenced by the presence of the anticoagulant; thus, we had the opportunity to choose the test tube that was used in the experiment without interfering effects impacting the gene expression levels caused by the anticoagulant.
Development and Validation of Semantic Differential Scale to Assess Teachers Belief Towards Socially Disadvantaged Students

This paper intended to record the process of developing and validating a Semantic Differential Scale to assess the teacher’s belief on socially disadvantaged students in the Indian context. Social Identity Theory (SIT) and Stereotype Content Model (SCM) has been adopted. Following the new method of developing SDS proposed by Ding et al. (2008), the process resulted in a 15-item scale with a three-factorial structure. The reliability and validity of the scale according to the new method were tested with SPSS 26 and Amos 26, with Cronbach’s alpha reliability coefficients greater than 0.962. With good indices on reliability and validity, the instrument is likely to be useful to both academicians and practitioners interested in assessing the addressed context.
Multimeric RGD-Based Strategies for Selective Drug Delivery to Tumor Tissues

RGD peptides have received a lot of attention over the two last decades, in particular to improve tumor therapy through the targeting of the αVβ3 integrin receptor. This review focuses on the molecular design of multimeric RGD compounds, as well as the design of suitable linkers for drug delivery. Many examples of RGD–drug conjugates have been developed, and we show the importance of RGD constructs to enhance binding affinity to tumor cells, as well as their drug uptake. Further, we also highlight the use of RGD peptides as theranostic systems, promising tools offering dual modality, such as tumor diagnosis and therapy. In conclusion, we address the challenging issues, as well as ongoing and future development, in comparison with large molecules, such as monoclonal antibodies.
Design of efficient storage and retrieval of medical records in blockchain based on InterPlanetary File System and modified bloom tree

In the healthcare sector, medical records contain sensitive information about patients, so guaranteeing the confidentiality and integrity of it is essential. To improve the security of it, blockchain technology is being utilized. The blockchain is a type of distributed ledger and it keeps data securely while also generating trust without the need of third party. It has data storage constraint and Merkle tree preserves data integrity but it is inefficient when searching transactions within it. Hence this paper describes InterPlanetary File System (IPFS) based storage and modified bloom tree data structure which is a hybridization of bloom filter and Merkle tree for efficient searching. To protect data privacy, initially it encrypts medical records using ciphertext policy‐attribute based encryption and then the data stored on IPFS returns a hash value. To diminish the false positive rate (FPR), the hash returned by IPFS is stored in two parts of the bloom filter. The first part stores the data by using “k” non‐cryptographic hash function and second part stores the transformed data with the same hash function. The bloom tree is created using Merkle proof for verification of medical record in blockchain. The experiments show that the proposed method reduces the FPR rate and searching complexity is O(log2).
Access Control for IoT: A Survey of Existing Research, Dynamic Policies and Future Directions

Internet of Things (IoT) provides a wide range of services in domestic and industrial environments. Access control plays a crucial role in granting access rights to users and devices when an IoT device is connected to a network. However, many challenges exist in designing and implementing an ideal access control solution for the IoT due to the characteristics of the IoT including but not limited to the variety of the IoT devices, the resource constraints on the IoT devices, and the heterogeneous nature of the IoT. This paper conducts a comprehensive survey on access control in the IoT, including access control requirements, authorization architecture, access control models, access control policies, access control research challenges, and future directions. It identifies and summarizes key access control requirements in the IoT. The paper further evaluates the existing access control models to fulfill the access control requirements. Access control decisions are governed by access control policies. The existing approaches on dynamic policies’ specification are reviewed. The challenges faced by the existing solutions for policies’ specification are highlighted. Finally, the paper presents the research challenges and future directions of access control in the IoT. Due to the variety of IoT applications, there is no one-size-fits-all solution for access control in the IoT. Despite the challenges encountered in designing and implementing the access control in the IoT, it is desired to have an access control solution to meet all the identified requirements to secure the IoT.