bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of a Novel CD26-Targeted Chimeric Antigen Receptor T-Cell Therapy for CD26-Expressing T-Cell Malignancies
Authors: Kobayashi Eiji , Kamihara Yusuke , Arai Miho , Wada Akinori , Kikuchi Shohei , Hatano Ryo , Iwao Noriaki , Susukida Takeshi , Ozawa Tatsuhiko , Adachi Yuichi , Kishi Hiroyuki , Dang Nam H. , Yamada Taketo , Hayakawa Yoshihiro , Morimoto Chikao , Sato Tsutomu
Published: August 2023

Chimeric-antigen-receptor (CAR) T-cell therapy for CD19-expressing B-cell malignancies is already widely adopted in clinical practice. On the other hand, the development of CAR-T-cell therapy for T-cell malignancies is in its nascent stage. One of the potential targets is CD26, to which we have developed and evaluated the efficacy and safety of the humanized monoclonal antibody YS110. We generated second (CD28) and third (CD28/4-1BB) generation CD26-targeted CAR-T-cells (CD26-2G/3G) using YS110 as the single-chain variable fragment. When co-cultured with CD26-overexpressing target cells, CD26-2G/3G strongly expressed the activation marker CD69 and secreted IFNgamma. In vitro studies targeting the T-cell leukemia cell line HSB2 showed that CD26-2G/3G exhibited significant anti-leukemia effects with the secretion of granzymeB, TNFα, and IL-8, with 3G being superior to 2G. CD26-2G/3G was also highly effective against T-cell lymphoma cells derived from patients. In an in vivo mouse model in which a T-cell lymphoma cell line, KARPAS299, was transplanted subcutaneously, CD26-3G inhibited tumor growth, whereas 2G had no effect. Furthermore, in a systemic dissemination model in which HSB2 was administered intravenously, CD26-3G inhibited tumor growth more potently than 2G, resulting in greater survival benefit. The third-generation CD26-targeted CAR-T-cell therapy may be a promising treatment modality for T-cell malignancies.
The Role of Obesity in Breast Cancer Pathogenesis
Authors: Glassman Ira , Le Nghia , Asif Aamna , Goulding Anabel , Alcantara Cheldon Ann , Vu Annie , Chorbajian Abraham , Mirhosseini Mercedeh , Singh Manpreet , Venketaraman Vishwanath
Published: August 2023

Research has shown that obesity increases the risk for type 2 diabetes mellitus (Type 2 DM) by promoting insulin resistance, increases serum estrogen levels by the upregulation of aromatase, and promotes the release of reactive oxygen species (ROS) by macrophages. Increased circulating glucose has been shown to activate mammalian target of rapamycin (mTOR), a significant signaling pathway in breast cancer pathogenesis. Estrogen plays an instrumental role in estrogen-receptor-positive breast cancers. The role of ROS in breast cancer warrants continued investigation, in relation to both pathogenesis and treatment of breast cancer. We aim to review the role of obesity in breast cancer pathogenesis and novel therapies mediating obesity-associated breast cancer development. We explore the association between body mass index (BMI) and breast cancer incidence and the mechanisms by which oxidative stress modulates breast cancer pathogenesis. We discuss the role of glutathione, a ubiquitous antioxidant, in breast cancer therapy. Lastly, we review breast cancer therapies targeting mTOR signaling, leptin signaling, blood sugar reduction, and novel immunotherapy targets.
A Metal Organic Framework-Based Light Scattering ELISA for the Detection of Staphylococcal Enterotoxin B
Authors: Mao Kai , Tian Lili , Luo Yujie , Li Qian , Chen Xi , Zhan Lei , Li Yuanfang , Huang Chengzhi , Zhen Shujun
Published: August 2023

Enzyme-linked immunosorbent assay (ELISA) is one of the most commonly used method for the detection of staphylococcal enterotoxin B (SEB), the main protein toxin causing staphylococcal food poisoning. However, the traditional ELISA reaction needs to be stopped by sulfuric acid to obtain stable colorimetric signal, and it is easily influenced by a colored sample. In order to address this problem, a new ELISA method using zeolite imidazolate skeleton-8 metal-organic framework (ZIF-8 MOF) as a light scattering (LS) reporter for SEB detection was developed in this work. ZIF-8 MOF has the characteristics of high porosity, large specific surface area, clear pore structure, and adjustable size, which is one of the most representative MOFs constructed from Zn2+ and 2-methylimidazole (2-mIM). The 2-mIM ligand of ZIF-8 exhibited antioxidant activity and can strongly react with H2O2, which could destroy the structure of ZIF-8, resulting in the obvious decrease in LS intensity. We combined this specific reaction with the sandwich immune reaction to construct the LS ELISA method for the successful detection of SEB. This method is more reliable than commercial tests kits for the detection of colored samples, and it is simple, sensitive, and selective, and has great potential in the detection of other toxins by simply changing the corresponding recognition units.
Optical Dual Gas Sensor for Simultaneous Detection of Nitric Oxide and Oxygen
Authors: Mesin Rispandi , Chu Cheng-Shane
Published: August 2023

This work presents a new optical dual sensor based on PtTFPP-containing electrospun fibers and CsPbBr3 perovskite quantum dots (PQDs) for simultaneous detection of oxygen (O2) and nitric oxide (NO) gases, wherein PtTFPP-containing electrospun fibers for O2 sensing was based on electrospinning process fabricated by platinum(II) meso-tetrakis (pentafluorophenyl) porphyrin (PtTFPP) complex immobilized in cellulose acetate (CA) matrix. CsPbBr3 PQDs were used as NO-sensitive material and coated on the surface of PtTFPP-containing electrospun fibers. Both materials were excited by a UV LED with a central wavelength of 380 nm, and the fluorescence intensities of sensing materials were recorded and analyzed with a spectrometer. The experiment results show that the optical NO and O2 sensors have linear Stern–Volmer plots, and the sensitivities are around 2.7 and 10.7, respectively. The response and recovery times of the optical NO sensor are 71 and 109 s, respectively. For optical O2, response and recovery times are 60 and 65 s, respectively. The optical dual sensor with a new method based on fluorescent dye containing electrospun fibers and coated with CsPbBr3 PQDs has been successfully developed to detect NO and O2 gases simultaneously. The optical dual gas sensor provides great potential for practical applications with low cost and ease of fabrication.
Reliability of Agreement between Insulin, Clonidine, and Glucagon Stimulation Tests for the Diagnosis of Growth Hormone Deficiency in Children: A Retrospective Cohort Study
Authors: Al Balwi Rana , Al-Qahtani Mohammad , Alrowished Amani K. , Shash Hwazen A. , Alatrash Reem , Alhareth Alanoud , Aldossary Roba , Alahmari Maha , Hejazi Yara , Alammari Alia , AlShawaf Sarah , Al Balwi Rawan , AlKhater Suzan
Published: August 2023

Growth hormone (GH) deficiency (GHD) is a rare disorder. The diagnosis of GHD requires a combination of two provocative GH tests. This study aimed to find agreement between commonly used medications to determine which combined tests have high reliability of agreement. This retrospective cohort included 201 children who underwent GH provocation testing from January 2012 to December 2022. The insulin tolerance test (ITT) with the clonidine stimulation test (CST) or glucagon stimulation test (GST) with the CST were performed. We calculated Cohen’s kappa to determine the agreement between the test medications by considering the post-stimulation peak GH level with a cut-off value of 10 ng/mL as the primary outcome. A total of 151 patients underwent the two provocative tests and were included in the analysis. Of these patients, 119 underwent the ITT and CST and 54 (45.3%) were diagnosed with GHD. However, 32 patients underwent the GST and CST and 18 (56.2%) were diagnosed with GHD. The kappa value for ITT and CST was 0.258 (25.8%), indicating fair agreement between clonidine and insulin (p = 0.005). However, the kappa value for CST and GST was 0.178 (17.8%), representing slight agreement. The correlation coefficient revealed a very strong relationship between ITT and CST. Clonidine has fair agreement and a very strong correlation coefficient with ITT when used to diagnose GHD in children. Among the commonly used pharmacological tests for GH provocation in our unit, the CST was considered the best pharmacological test in terms of safety and reduced parental anxiety.
Health Promotion in Preschool Children
Authors: Şenol Yiğit , Şenol Fatma Betül
Published: August 2023

The key for individuals to live in health and well-being is the development of healthy living habits. In order for a healthy life habit to be formed, the relevant behaviors must be acquired in the preschool period. This study aimed to promote health knowledge among children attending preschool through health education. The study was designed using the qualitative case study design. The Personal Information Form and Health Hunter Children Follow Health Interview Form were used as data collection tools in the study. Health education activities were implemented in order to improve children’s knowledge about health. Activities consisted of physical activity, personal hygiene, injury prevention, sleeping habits, healthy nutrition, healthy life, and paramedic and treatment services categories. Activities were applied to children twice a week for eight weeks. As a result of the study, an improvement was observed in children’s knowledge about health. The answers given by the children before and after the Health Education Activities were collected in the categories of nutrition, safe life, illness status, well-being, hygiene, environmental health, and sports.
Solution-Processable Benzo[b]thieno[2,3-d]thiophene Derivatives as Organic Semiconductors for Organic Thin-Film Transistors
Authors: Kim Seongyun , Ryu Soomin , Ahn Jihae , Kim Dongkyu , Marrocchi Assunta , Kim Choongik , Seo SungYong
Published: August 2023

Two new benzo[b]thieno[2,3-d]thiophene (BTT) derivatives, 2-(benzo[b]thiophen-5-yl)benzo[b]thieno[2,3-d]thiophene (compound 2), and 2-(benzo[b]thieno[2,3-d]thiophene-2yl)dibenzo[b,d]thiophene (compound 3) have been synthesized and utilized as solution-processable small molecular organic semiconductors for organic field-effect transistors (OFETs). The physicochemical characteristics of the recently created substances were analyzed using thermogravimetric analysis (TGA), differential scanning calorimeter (DSC), and UV-vis spectroscopy. Subsequently, the above-mentioned substances were employed as semiconductor layers in bottom-gate/top-contact OFETs through solution shearing methods for device fabrication, and their electrical performances were meticulously evaluated. The outcoming OFET device displayed p-channel behavior, demonstrating hole mobility of up to 0.005cm2/Vs and a current on/off ratio higher than 106.
Construction of Amphiphilic Indocyanine–Green–Based Langmuir Film and Drop–Casting Film with Photoelectric Conversion Properties
Authors: Chen Jing , Li Na , Li Lin , Wang Chongling , Han Dongxue , Jiao Tifeng
Published: August 2023

Molecular self–assembly is the automatic formation of functional assemblies of different structural components through weak, reversible, non–covalent interactions on the basis of molecular recognition. Amphiphilic molecules have a natural advantage in self–assembly at the gas/liquid interface. In this work, two amphiphilic molecules with a special molecular structure, indocyanine green (ICG) and a derivative of indocyanine green (CCS), were combined with two dye molecules (tetraphenylporphyrin tetrasulfonic acid hydrate (TPPS) and nickel (II) phthalocyanine–tetrasulfonic acid tetrasodium salt (TsNiPc) for self–assembly through the Langmuir–Blodgett (LB) technique. The nanostructure and assembly behavior in ordered self–assembled films are effectively regulated by inducing dye molecules to form different types of aggregates (H– and J–aggregates). In addition, we prepared composite films containing the same functional components using the conventional drop–casting technique and performed a series of comparative experiments with LB films. The degree of hydrophilicity was found to be related to roughness, with LB composite films being flatter and denser, with the lowest roughness and the best hydrophobicity compared to drop–casting films. Notably, the LB films showed better optoelectronic properties under the same conditions, providing new clues for the application of optoelectronic functional ultrathin film devices.
Melting Thresholds of Materials Irradiated with a Wide Class of Pulsed Electron Beams
Authors: Markov Alexey
Published: August 2023

Based on the proposed criterion of the type of heating, a classification of the sources of pulsed electron beams was carried out, both to obtain a better understanding of the nature of the thermal processes occurring under irradiation and to predict their suitability for certain applications. The melting thresholds of materials were calculated over a wide ranges of accelerating voltages and pulse durations. On the basis of calculations, a refractoriness series was proposed for metals for surface–volume pulsed heating.
Sensitivity Analysis of Mathematical Models
Authors: Sysoev Anton
Published: August 2023

The construction of a mathematical model of a complicated system is often associated with the evaluation of inputs’ (arguments, factors) influence on the output (response), the identification of important relationships between the variables used, and reduction of the model by decreasing the number of its inputs. These tasks are related to the problems of Sensitivity Analysis of mathematical models. The author proposes an alternative approach based on applying Analysis of Finite Fluctuations that uses the Lagrange mean value theorem to estimate the contribution of changes to the variables of a function to the output change. The article investigates the presented approach on an example of a class of fully connected neural network models. As a result of Sensitivity Analysis, a set of sensitivity measures for each input is obtained. For their averaging, it is proposed to use a point-and-interval estimation algorithm using Tukey’s weighted average. The comparison of the described method with the computation of Sobol’s indices is given; the consistency of the proposed method is shown. The computational robustness of the procedure for finding sensitivity measures of inputs is investigated. Numerical experiments are carried out on the neuraldat data set of the NeuralNetTools library of the R data processing language and on data of the healthcare services provided in the Lipetsk region.
Analysis and 3D Imaging of Multidimensional Complex THz Fields and 3D Diagnostics Using 3D Visualization via Light Field
Authors: Gerasimov Michael , Yahya Adnan Haj , Nave Vadim Patrick , Dyunin Egor , Gerasimov Jacob , Friedman Aharon
Published: August 2023

We present a numerical platform for 3D imaging and general analysis of multidimensional complex THz fields. A special 3D visualization is obtained by converting electromagnetic (EM) radiation to a light field via the Wigner distribution function, which is known for discovering (revealing) hidden details. This allows for 3D diagnostics using the simple techniques of geometrical optics, which significantly facilitates the whole analysis. This simulation was applied to a complex field composed of complex beams emitted as ultra-narrow femtosecond pulses. A method was developed for the generation of phase–amplitude and spectral characteristics of complex multimode radiation in a free-electron laser (FEL) operating under various parameters. The tool was successful at diagnosing an early design of the transmission line (TL) of an innovative accelerator at the Schlesinger Family Center for Compact Accelerators, Radiation Sources, and Applications.
Study on Optical Positioning Using Experimental Visible Light Communication System
Authors: Vitsi Nikoleta , Stassinakis Argyris N. , Androutsos Nikolaos A. , Roumelas George D. , Varotsos George K. , Aidinis Konstantinos , Nistazakis Hector E.
Published: August 2023

Visible light positioning systems (VLP) have attracted significant commercial and research interest because of the many advantages they possess over other applications such as radio frequency (RF) positioning systems. In this work, an experimental configuration of an indoor VLP system based on the well-known Lambertian light emission, is investigated. The corresponding results are also presented, and show that the system retains high enough accuracy to be operational, even in cases of low transmitted power and high background noise.
A Survey of Post-Quantum Cryptography: Start of a New Race
Authors: Dam Duc-Thuan , Tran Thai-Ha , Hoang Van-Phuc , Pham Cong-Kha , Hoang Trong-Thuc
Published: August 2023

Information security is a fundamental and urgent issue in the digital transformation era. Cryptographic techniques and digital signatures have been applied to protect and authenticate relevant information. However, with the advent of quantum computers and quantum algorithms, classical cryptographic techniques have been in danger of collapsing because quantum computers can solve complex problems in polynomial time. Stemming from that risk, researchers worldwide have stepped up research on post-quantum algorithms to resist attack by quantum computers. In this review paper, we survey studies in recent years on post-quantum cryptography (PQC) and provide statistics on the number and content of publications, including a literature overview, detailed explanations of the most common methods so far, current implementation status, implementation comparisons, and discussion on future work. These studies focused on essential public cryptography techniques and digital signature schemes, and the US National Institute of Standards and Technology (NIST) launched a competition to select the best candidate for the expected standard. Recent studies have practically implemented the public key encryption/key encapsulation mechanism (PKE/KEM) and digital signature schemes on different hardware platforms and applied various optimization measures based on other criteria. Along with the increasing number of scientific publications, the recent trend of PQC research is increasingly evident and is the general trend in the cryptography industry. The movement opens up a promising avenue for researchers in public key cryptography and digital signatures, especially on algorithms selected by NIST.
Molecular Dynamics Simulation of the Interaction between Dislocations and Iron–Vanadium Precipitates in Alpha Iron: Effect of Chemical Composition
Authors: Yazdani Sepehr , Mesbah Mohsen , Vitry Veronique
Published: August 2023

In this study, molecular dynamics simulations were employed to study the interaction between dislocations with Fe-V precipitate with different vanadium concentrations. Increasing the vanadium concentration in the precipitate results in a strong interaction between the dislocations and the precipitate, and the dislocation line bows out more as a result of increasing the energy of the dislocation line, and the critical stress needed for depinning the dislocations increases. However, at a low vanadium concentration (1:3 atomic ratio) the dislocations cut through the precipitate without changing the speed. An increasing vanadium concentration not only affects the dislocation shape and movement speed, but also affects the configuration of the junction between the a/2[111] and a/2[100] dislocations, and the void formation after the cutting process. The formation of strong junctions and a high number of voids locks the a/2[111] dislocation motion, and increases the strength of the alloy. The results of the radial distribution function before and after the cutting process show that the structure of the precipitate changes from crystalline to amorphous, and the degree of amorphization decreases with an increasing vanadium concentration.
What Do Butterflies Tell Us about an Intermediate Disturbance in a Dry Tropical Forest Context?
Authors: Mercado-Gómez Yarlenis L. , Mercado-Gómez Jorge D. , Giraldo-Sánchez Carlos E.
Published: August 2023

Montes de María is the best-preserved tropical dry forest fragment in the Colombian Caribbean, making it an ideal location for studying the impacts of human disturbance on local ecosystems. In this study, we analyzed the community structure of diurnal butterflies in both forested and disturbed areas using 16 circular plots to identify relationships between alpha and beta diversity, and the geographic distance between disturbed areas and native forests, using a range of metrics, including range–abundance and rarefaction curves, nonlinear models, and the Bray–Curtis dissimilarity index. The results revealed three distinct species assemblages associated with forests, intermediate disturbed areas (IDAs), and disturbed areas (DAs). Nonlinear models show that IDAs are more diverse than forests and DAs. However, forests have more beta diversity in plots than IDAs and DAs. Indicator species for each butterfly assemblage were also identified. Thus, although new butterfly species assemblages emerge from a new human landscape, it is clear that species that only occur within dry forest fragments are lost when forest fragments disappear. Overall, these findings have important implications for conservation efforts and understanding how human disturbance affects biodiversity in tropical ecosystems.
Imaging of Temporal Bone Mass Lesions: A Pictorial Review
Authors: Shimanuki Marie N. , Nishiyama Takanori , Hosoya Makoto , Wakabayashi Takeshi , Ozawa Hiroyuki , Oishi Naoki
Published: August 2023

Tumoral lesions of the temporal bone include benign or malignant tumors and congenital or inflammatory lesions. Temporal bone lesions are difficult to approach. Therefore, making a preoperative diagnosis and considering whether the lesions require treatment are necessary; if they require treatment, then the type of treatment requires consideration. These tumors cannot be observed directly and must be diagnosed based on symptoms and imaging findings. However, the differentiation of temporal bone lesions is difficult because they are rare and large in variety. In this pictorial review, we divided temporal bone lesions by location such as along the facial nerve, along the internal jugular vein, around the endolymphatic sac, in the internal auditory canal/cerebellopontine angle, petrous apex, middle ear, and mastoid, focusing on the imaging findings of temporal bone lesions. Then, we created a diagnostic flowchart that suggested that the systematic separation of imaging findings is useful for differentiation. Although it is necessary to make comprehensive judgments based on the clinical symptoms, patient background, and imaging findings to diagnose temporal bone mass lesions, capturing imaging features can be a useful differentiation method.
Rapidly Progressive Metastatic Angiosarcoma of the Heart: A Case Report
Authors: An Soo Yeon , Shim Man-Shik
Published: August 2023

Cardiac angiosarcoma is a rare, malignant neoplasm affecting the heart. We present the clinical history of a 40-year-old patient diagnosed with metastatic angiosarcoma of the heart. The patient complained of shortness of breath, and a cardiac computed tomography scan revealed a mass in the right atrium and pericardial effusion. Transthoracic and transesophageal echocardiography provided detailed anatomical and functional information, and cardiac magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography/computed tomography were used to assess distant metastasis and characterize the mass in detail. Early differential diagnosis and comprehensive evaluation of a cardiac mass are vital for determining appropriate treatment strategies to improve patient outcomes. The pathological results from the endocardial biopsy confirmed the diagnosis of primary angiosarcoma. The patient underwent surgical resection of the right atrial mass but died within one month because of the locally advanced nature of the angiosarcoma and its rapid progression. The patient’s medical journey sheds light on the challenges associated with diagnosing and treating this rare condition, particularly the rapid progression of its cardiac manifestations.
Evaluating Headache and Facial Pain in a Headache Diagnostic Laboratory: Experiences from the Danish Headache Center
Authors: Schytz Henrik Winter , Hvedstrup Jeppe
Published: August 2023

Background: Diagnostic tests are not routinely used for the diagnosis of primary headaches. It is possible that laboratory tests could be developed and implemented at tertiary headache centers to be an integrated part of the diagnosis and management of headache patients, and laboratory tests that can be used on-site at headache centers could help in evaluating patients with secondary headache disorders. Methods: In this narrative review, we present some of the studies that have been made so far at the Headache Diagnostic Laboratory at the Danish Headache Center that aim to investigate and phenotype primary headaches and investigate secondary headaches as well as improve management. Results: Semi-structured interviews and deep phenotyping, quantitative sensory testing, and provocation studies have been shown to be valuable in categorizing primary and secondary headache subtypes, possible pathophysiology, and defining needs for further research. In patients suspected of increased intracranial pressure, transorbital ultrasound with measurement of the optic sheath diameter may be useful in monitoring patients. The management of headache patients needs to be critically evaluated to optimize treatment continuously. Conclusion: A Headache Diagnostic Laboratory is very useful and should be an integrated part of headache care and management at tertiary headache centers.
Hybrid Feature-Learning-Based PSO-PCA Feature Engineering Approach for Blood Cancer Classification
Authors: Atteia Ghada , Alnashwan Rana , Hassan Malak
Published: August 2023

Acute lymphoblastic leukemia (ALL) is a lethal blood cancer that is characterized by an abnormal increased number of immature lymphocytes in the blood or bone marrow. For effective treatment of ALL, early assessment of the disease is essential. Manual examination of stained blood smear images is current practice for initially screening ALL. This practice is time-consuming and error-prone. In order to effectively diagnose ALL, numerous deep-learning-based computer vision systems have been developed for detecting ALL in blood peripheral images (BPIs). Such systems extract a huge number of image features and use them to perform the classification task. The extracted features may contain irrelevant or redundant features that could reduce classification accuracy and increase the running time of the classifier. Feature selection is considered an effective tool to mitigate the curse of the dimensionality problem and alleviate its corresponding shortcomings. One of the most effective dimensionality-reduction tools is principal component analysis (PCA), which maps input features into an orthogonal space and extracts the features that convey the highest variability from the data. Other feature selection approaches utilize evolutionary computation (EC) to search the feature space and localize optimal features. To profit from both feature selection approaches in improving the classification performance of ALL, in this study, a new hybrid deep-learning-based feature engineering approach is proposed. The introduced approach integrates the powerful capability of PCA and particle swarm optimization (PSO) approaches in selecting informative features from BPI mages with the power of pre-trained CNNs of feature extraction. Image features are first extracted through the feature-transfer capability of the GoogleNet convolutional neural network (CNN). PCA is utilized to generate a feature set of the principal components that covers 95% of the variability in the data. In parallel, bio-inspired particle swarm optimization is used to search for the optimal image features. The PCA and PSO-derived feature sets are then integrated to develop a hybrid set of features that are then used to train a Bayesian-based optimized support vector machine (SVM) and subspace discriminant ensemble-learning (SDEL) classifiers. The obtained results show improved classification performance for the ML classifiers trained by the proposed hybrid feature set over the original PCA, PSO, and all extracted feature sets for ALL multi-class classification. The Bayesian-optimized SVM trained with the proposed hybrid PCA-PSO feature set achieves the highest classification accuracy of 97.4%. The classification performance of the proposed feature engineering approach competes with the state of the art.
Sliding Surface Designs for Visual Servo Control of Quadrotors
Authors: Yuksel Tolga
Published: August 2023

Autonomy is the main task of a quadrotor, and visual servoing assists with this task while providing fault tolerance under GPS failure. The main approach to visual servoing is image-based visual servoing, which uses image features directly without the need for pose estimation. The classical sliding surface design of sliding mode control is used by the linear controller law of image-based visual servoing, and focuses only on minimizing the error in the image features as convergence. In addition to providing convergence, performance characteristics such as visual-feature-convergence time, error, and motion characteristics should be taken into consideration while controlling a quadrotor under velocity limitations and disturbance. In this study, an image-based visual servoing system for quadrotors with five different sliding surface designs is proposed using analytical techniques and fuzzy logic. The proposed visual servo system was simulated, utilizing the moment characteristics of a preset shape to demonstrate the effectiveness of these designs. The stated parameters, convergence time, errors, motion characteristics, and length of the path, followed by the quadrotor, were compared for each of these design approaches, and a convergence time that was 46.77% shorter and path length that was 6.15% shorter were obtained by these designs. In addition to demonstrating the superiority of the designs, this study can be considered as a reflection of the realization, as well as the velocity constraints and disturbance resilience in the simulations.
Exact Solutions of Nonlinear Second-Order Autonomous Ordinary Differential Equations: Application to Mechanical Systems
Authors: Santana Murillo V. B.
Published: August 2023

Many physical processes can be described via nonlinear second-order ordinary differential equations and so, exact solutions to these equations are of interest as, aside from their accuracy, they may reveal beforehand key properties of the system’s response. This work presents a method for computing exact solutions of second-order nonlinear autonomous undamped ordinary differential equations. The solutions are divided into nine cases, each depending on the initial conditions and the system’s first integral. The exact solutions are constructed via a suitable parametrization of the unknown function into a class of functions capable of representing its behavior. The solution is shown to exist and be well-defined in all cases for a general nonlinear form of the differential equation. Practical properties of the solution, such as its period, time to reach an extreme value or long-term behavior, are obtained without the need of computing the solution in advance. Illustrative examples considering different types of nonlinearity present in classical physical systems are used to further validate the obtained exact solutions.
A Method of DDoS Attack Detection and Mitigation for the Comprehensive Coordinated Protection of SDN Controllers
Authors: Wang Jin , Wang Liping , Wang Ruiqing
Published: August 2023

Software defined networking (SDN) improves the flexibility and programmability of the network by separating the control plane and the data plane and effectively realizes the global control of the network infrastructure. However, the centralized structure design of SDN exposes the controller to potential threats. Attackers have used the active flow table delivery mode to launch distributed denial of service (DDoS) attacks on the SDN controller, resulting in the controller failure and seriously affecting the network performance. To overcome this problem, this paper proposes a defense framework called CC-Guard. The framework consists of four modules: attack detection triggering, switch migration, anomaly detection, and mitigation. Among them, the attack detection trigger module improves the system’s timely response to DDoS attacks. The switch migration module effectively unclogs the controller congestion problem and provides convenience for network flow transmission. The anomaly detection module uses a coarse-grained method for two-stage detection, which improves the detection accuracy. The mitigation module uses the idea of cross-domain cooperation of the controller to clear the abnormal flow in the blacklist. Experimental results show that our proposed CC-Guard has real-time DDoS attack defense capability and high detection accuracy, as well as efficient network resource utilization.
The Contribution of Digital Portfolios to Higher Education Students’ Autonomy and Digital Competence
Authors: Mogas Jordi , Cea Álvarez Ana , Pazos-Justo Carlos
Published: August 2023

Education is continuously evolving, even more with rapid technological advances and the needs and possibilities detected from the COVID-19 pandemic experience. In the current social context for higher education students, their need to have skills and competences related to autonomy, is increasingly acknowledged, and they must be capable of conducting better self-regulated learning. Digital competence is another elementary value to tackle with quality education: not only for online and hybrid modalities, also in face-to-face teaching and learning, the use of digital tools is proven to enrich the process and make learning more efficient. Among the resources explored in education, one of the most valuable are e-portfolios or reflexive digital portfolios. Thus, this study intends to give response to the following two questions in the context of students in higher education: is the experience of the use of a digital portfolio related to the promotion of autonomous competence? How is the use of digital portfolios related to digital competence? The sample is gathered within a European project; 355 students from six universities of five countries responded to a questionnaire. The main results confirm that students that have used e-portfolios appear more likely to be autonomous and also show remarkable differences in some items of their digital competence, compared with those that have not used e-portfolios. Not all responses point at significant differences, but at least for given aspects, we affirmatively conclude that e-portfolios may ease the learning process in terms of digital and autonomous competences.
Rethinking Learning Experience: How Generally Perceived Life Stress Influences Students’ Course Perceptions in Different Learning Environments
Authors: Gellisch Morris , Schäfer Thorsten , Yahya Imadeldin , Joswig Matthias , Cheng Xin , Morosan-Puopolo Gabriela , Brand-Saberi Beate
Published: August 2023

Previous research work has already demonstrated that both the form of teaching as well as different teaching methods directly influence students’ learning experience along with their psychobiological responses at the endocrine and autonomic level. Aiming to gain deeper insights into the constitution of the learning experience, this study examined the influence of external factors such as generally perceived life stress and self-efficacy on the immediate learning experience in different learning environments. Therefore, a randomized experimental field study was conducted in which both psychological constructs and physiological data (heart rate variability) were collected from healthy first-year medical students (n = 101) during the COVID-19 pandemic. In an effort to determine the consistency of the effects across various teaching formats, the same content of a practical histology course was carried out in a face-to-face setting as well as in passive and active online teaching. While self-efficacy was a strong predictor for positive course perceptions in all learning conditions (Pearson’s r = 0.41–0.58), generally perceived worries correlated with higher anxiety during passive online learning and face-to-face learning (Pearson’s r = 0.21–0.44), a finding supported by the negative correlation between the level of perceived life demands and enjoyment during the learning unit (Pearson’s r = −0.40–−0.43). Here, we additionally report initial evidence pointing towards the role of reduced general life stress as a resilience factor for the expression of physiological stress parameters in an academic context (small-sized effect; Pearson’s r = 0.18). The data gathered in this study illustrate the relevance of emerging emotional manifestations—either aversive; negative effect or positive; protective effect—for the immediate learning process and thus establish a connection between medical education and the importance of mental health and wellbeing—especially discussed against the background of current social and political challenges in increasingly complex societal structures.
Improved Traffic Small Object Detection via Cross-Layer Feature Fusion and Channel Attention
Authors: Chuai Qinliang , He Xiaowei , Li Yi
Published: August 2023

Small object detection has long been one of the most formidable challenges in computer vision due to the poor visual features and high noise of surroundings behind them. However, small targets in traffic scenes encompass a multitude of complex visual interfering factors, bearing crucial information such as traffic signs, traffic lights, and pedestrians. Given the inherent difficulties faced by generic models in addressing these issues, we conduct a comprehensive investigation on small target detection in this application scenario. In this work, we present a Cross-Layer Feature Fusion and Channel Attention algorithm based on a lightweight YOLOv5s design for traffic small target detection, named CFA-YOLO. To enhance the sensitivity of the model toward vital features, we embed the channel-guided Squeeze-and-Excitation (SE) block in the deep layer of the backbone. Moreover, the most excellent innovation of our work belongs to the effective cross-layer feature fusion method, which maintains robust feature fusion and information interaction capabilities; in addition, it simplifies redundant parameters compared with the baseline model. To align with the output features of the neck network, we adjusted the detection heads from three to two. Furthermore, we also applied the decoupled detection head for classification and bounding box regression tasks, respectively. This approach not only achieves real-time detection standards, but also improves the overall training results in parameter-friendly manner. The CFA-YOLO model significantly pays a lot of attention to the detail features of small targets, thereby it also has a great advantage in addressing the issue of poor performance in traffic small target detection results. Vast experiments have validated the efficiency and effectiveness of our proposed method in traffic small object detection. Compared with the latest lightweight detectors, such as YOLOv7-Tiny and YOLOv8s, our method consistently achieves superior performance both in terms of the model’s accuracy and complexity.
Handover Triggering Prediction with the Two-Step XGBOOST Ensemble Algorithm for Conditional Handover in Non-Terrestrial Networks
Authors: Kim Eunsu , Joe Inwhee
Published: August 2023

A Non-Terrestrial Network (NTN) is a network system that enables service for areas where terrestrial networks cannot cover. An NTN provides communication services using flying objects such as UAVs, HAPs, and satellites. In the case of satellites, they move in Earth’s orbit at a constant speed. Ground services from continuously moving satellites cause frequent handovers. In addition, frequent handovers may come as a load between User Equipment (UE) and the communication system, which leads to degradation of service quality. Unlike Terrestrial Networks (TN), communication services are provided to UEs at altitudes ranging from 20 km to 35,584 km, rather than from base stations close to the ground. Service at high altitudes is unreliable due to the measurement values that were previously used as quality indicators to operate terrestrial networks. Moreover, service at high altitudes demands long-distance communication, and propagation delay occurs from the long-distance communication. In the 3GPP Rel. 17 document, it is suggested that the above problems should be solved. This paper tries to solve the problem by proposing the two-step XGBOOST, a CART-based Gradient Boosting Model. Handover in TN uses measurement-based conditional handover (CHO), but the measured values in the NTN environment are not valid. Using this, the distance between the UE and the center of the cell and the elevation angle are used to construct a model that predicts the HO triggering time point. In order to overcome the propagation delay caused by communication at a high altitude, a model that predicts the distance and elevation angle between the UE and the center of the cell considering the propagation delay is proposed. The model is composed of two-step XGBOOST. The one-step model is a model in which the UE predicts the distance and elevation angle between cell centers after propagation delay at the time when satellite position information is transmitted to the UE. The two-step model predicts handover triggering occurrence based on the data predicted by the one-step result. As a result of the experiment, the model considering the propagation delay showed about 8% better performance on average than the model not considering the propagation delay, and the XGBOOST model achieved an average F1-score of 0.9891 in the propagation delay experiments.
Impact Mechanisms of Commutation Failure Caused by a Sending-End AC Fault and Its Recovery Speed on Transient Stability
Authors: Lin Yifeng , Hu Jiawei , Wang Tong , Wang Zengping
Published: August 2023

A sending-end AC fault may lead to commutation failure (CF) in a line-commutated converter high-voltage direct current (LCC-HVDC) system. In this paper, a theoretical analysis of the impact mechanisms of a CF and its recovery speed on the transient stability of a sending-end power system (TSSPS) is performed. Firstly, the models of the sending-end power system and DC power of CF are established; the ramp function is utilized to characterize the DC power recovery process. Secondly, the swing direction of the relative rotor angle caused by a sending-end AC fault is discussed, and the DC power flow method is employed to theoretically analyze the impacts of CF and its recovery speed on TSSPS. Next, the mathematic relations between parameters of the voltage-dependent current order limiter (VDCOL) and DC power recovery speed are further derived. It is concluded that the impacts of CF and its recovery speed on transient stability are related to the swing direction caused by a sending-end AC fault, the inertia of generators, and the location of the rectifier station. Finally, the theoretical analysis is validated by Kundur’s two-area system and IEEE 68-bus-based AC/DC asynchronous interconnection test power systems, respectively.
A Brief Review of the Latest Advancements of Massive Solar Thermal Collectors
Authors: Aquilanti Alessia , Peralta Ignacio , Koenders Eduardus A. B. , Di Nicola Giovanni
Published: August 2023

Technologies that can contribute to the reduction of greenhouse gases are mandatory, and those based on solar energy are good candidates to achieve this. In this sense, massive solar thermal collectors are suitable technologies for supplying the primary energy demand of buildings. To design these devices, it is necessary to fully understand the physics of the problem before proposing any new optimized solution. This review aims to briefly summarize significant aspects regarding the current state of development of these solar technologies. Attention is paid to works devoted to experimental studies to analyze the behavior of these systems, as well as numerical models to predict the physics of the problem. Furthermore, the future directions and prospects in the field of massive collectors are briefly described. The main novelty of this review is to provide a comprehensive overview that summarizes the works done so far in the field over the past 30 years, which allows the reader to delve deeper into the topic. According to the reviewed works, it can be concluded that these technologies can contribute to the reduction of greenhouse gases while at the same time being excellent examples of the integration of solar energy devices with buildings.
Research on an Error Compensation Method of SINS of a Mine Monorail Crane
Authors: Jiang Hai , Ji Xiaodong , Yang Yang , Du Jialu , Wu Miao
Published: August 2023

Underground coal mines belong to the GNSS-denied environment, and the Strapdown Inertial Navigation System (SINS) has a significant advantage in the precise positioning of equipment in this environment because of its operation without requiring interaction with external information and strong anti-interference capabilities. Nonetheless, the vibrations of the installation platform adversely affect the positioning accuracy of SINS. This article focuses on the monorail crane in coal mines as the subject of research, developing a dynamic model for the motion unit consisting of the “track + drive unit + driver’s cab”, while analyzing the relationship between track roughness conditions and the vibration excitation of this unit. Subsequently, utilizing the dynamic model, the study calculated the angular and linear vibration characteristics and formulated models to address coning error and sculling error specific to the SINS in this vibration condition. Lastly, by employing a multi-sample compensation algorithm, this article compensated for positioning errors in the SINS caused by track roughness-induced vibrations during uniform straight-line motion of the motion unit, thus achieving optimal positioning information for the monorail crane. The simulation results demonstrated that employing a four-sample compensation algorithm reduces the coning error in SINS positioning calculations by a minimum of 50% and decreases the sculling error by at least 31%, satisfying the positioning accuracy requirements for precise parking of the monorail crane during the transportation phase, while establishing the foundation for autonomous precise positioning and integrated navigation of underground track transport equipment in coal mines.