bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Mechanism of Sempervirine Inhibiting Glioblastoma Invasion Based on Network Pharmacology and Bioinformatics
Authors: Zhang Bingqiang , Wang Wenyi , Song Yu , Chen Huixian , Lin Xinxin , Chen Jingjing , Chen Ying , Huang Jinfang , Li Desen , Wu Shuisheng
Published: October 2024

Background: Invasion is an important characteristic of the malignancy of glioblastoma (GBM) and a significant prognostic factor. Sempervirine (SPV), a yohimbine-type alkaloid, has been proven to inhibit GBM cells proliferation in previous research and found to have a potential effect in anti-invasion, but its mechanism of anti-invasion is still unknown. Methods: To explore its pharmacodynamics in inhibiting GBM cell invasion in this study, we combined network pharmacology and bioinformatics to comprehensive exploratory analysis of SPV and verified the mechanism in vitro. Results: Firstly, targets of SPV and invasion-related genes were collected from public databases. Moreover, GBM samples were obtained to analyze differentially expressed genes (DEGs) from The Cancer Genome Atlas (TCGA). Then, the relevant targets of SPV inhibiting GBM invasion (SIGI) were obtained through the intersection of the three gene sets. Further, GO and KEGG analysis showed that the targets of SIGI were heavily enriched in the AKT signaling pathway. Subsequently, based on the method of machine learning, a clinical prognostic model of the relevant targets of SIGI was constructed using GBM samples from TCGA and the Gene Expression Omnibus (GEO). A four-genes model (DUSP6, BMP2, MMP2, and MMP13) was successfully constructed, and Vina Scores of MMP2 and MMP13 in molecular docking were higher, which may be the main targets of SIGI. Then, the effect of SIGI was confirmed via functional experiments on invasion, migration, and adhesion assay, and the effect involved changes in the expressions of p-AKT, MMP2 and MMP13. Finally, combined with AKT activator (SC79) and inhibitor (MK2206), we further confirmed that SPV inhibits GBM invasion through AKT phosphorylation. Conclusions: This study provides valuable and an expected point of view into the regulation of AKT phosphorylation and inhibition of GBM invasion by SPV.
Predicting the Release Mechanism of Amorphous Solid Dispersions: A Combination of Thermodynamic Modeling and In Silico Molecular Simulation
Authors: Walter Stefanie , Mileo Paulo G. M. , Afzal Mohammad Atif Faiz , Kyeremateng Samuel O. , Degenhardt Matthias , Browning Andrea R. , Shelley John C.
Published: October 2024

Background: During the dissolution of amorphous solid dispersion (ASD) formulations, the drug load (DL) often impacts the release mechanism and the occurrence of loss of release (LoR). The ASD/water interfacial gel layer and its specific phase behavior in connection with DL strongly dictate the release mechanism and LoR of ASDs, as reported in the literature. Thermodynamically driven liquid-liquid phase separation (LLPS) and/or drug crystallization at the interface are the key phase transformations that drive LoR. Methods: In this study, a combination of Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) thermodynamic modeling and in silico molecular simulation was applied to investigate the release mechanism and the occurrence LoR of an ASD formulation consisting of ritonavir as the active pharmaceutical ingredient (API) and the polymer, polyvinylpyrrolidone-co-vinyl acetate (PVPVA64). A thermodynamically modeled ternary phase diagram of ritonavir (PVPVA64) and water was applied to predict DL-dependent LLPS in the ASD/water interfacial gel layer. Microscopic Erosion Time Testing (METT) was used to experimentally validate the phase diagram predictions. Additionally, in silico molecular simulation was applied to provide further insights into the phase separation, the release mechanism, and aggregation behavior on a molecular level. Results: Thermodynamic modeling, molecular simulation, and experimental results were consistent and complementary, providing evidence that ASD/water interactions and phase separation are essential factors driving the dissolution behavior and LoR at 40 wt% DL of the investigated ritonavir/PVPVA64 ASD system, consistent with previous studies. Conclusions: This study provides insights into the potential of blending thermodynamic modeling, molecular simulation, and experimental research to comprehensively understand ASD formulations. Such a combined approach can be leveraged as a computational framework to gain insights into the ASD dissolution mechanism, thereby facilitating in silico screening, designing, and optimization of formulations with the benefit of significantly reducing the number of experimental tests.
Hybrid CNC–MXene Nanolubricant for Tribological Application: Characterization, Prediction, and Optimization of Thermophysical Properties Evaluation
Authors: Hisham Sakinah Muhamad , Sazali Norazlianie , Kadirgama Kumaran , Ramasamy Devarajan , Kamarulzaman Mohd Kamal , Samylingam Lingenthiran , Aslfattahi Navid , Kok Chee Kuang
Published: October 2024

In the present work, hybrid Cellulose Nanocrystal–MXene (CNC–MXene) nanolubricants were prepared via a two-step method and investigated as potential heat-transfer hybrid nanofluids for the first time. CNC–MXene nanolubricants were synthesized via a two-step method by varying the weight percentage of CNC–MXene nanoparticles (ranging from 0.01 to 0.05 wt%) and characterized using Fourier-Transform Infrared Spectroscopy and TGA (Thermogravimetric Analysis). Response surface methodology (RSM) was used in conjunction with the miscellaneous design model to identify prediction models for the thermophysical properties of the hybrid CNC–MXene nanolubricant. Minitab 18 statistical analysis software and Response Surface Methodology (RSM) based on Central Composite Design (CCD) were utilized to generate an empirical mathematical model investigating the effect of concentration and temperature. The analysis of variance (ANOVA) results indicated significant contributions from the type of nanolubricant (p < 0.001) and the quadratic effect of temperature (p < 0.001), highlighting non-linear interactions that affect viscosity and thermal conductivity. The findings showed that the predicted values closely matched the experimental results, with a percentage of absolute error below 9%, confirming the reliability of the optimization models. Additionally, the models could predict more than 85% of the nanolubricant output variations, indicating high model accuracy. The optimization analysis identified optimal conditions for maximizing both dynamic viscosity and thermal conductivity. The predicted optimal values (17.0685 for dynamic viscosity and 0.3317 for thermal conductivity) were achieved at 30 °C and a 0.01% concentration, with a composite desirability of 1. The findings of the percentage of absolute error (POAE) reveal that the model can precisely predict the optimum experimental parameters. This study contributes to the growing field of advanced nanolubricants by providing insights into the synergistic effects of CNC and MXene in enhancing thermophysical properties. The developed models and optimization techniques offer valuable tools for tailoring nanolubricant formulations to specific tribological applications, potentially leading to improved efficiency and durability in various industrial settings.
Optimization of Coreless PCB Coils Based on a Modified Taguchi Tuning Method for WPT of Pedelec
Authors: Chen Yu-Kai , Wang Cheng-An
Published: October 2024

The printed circuit board (PCB) winding coil offers advantages such as small size, high precision, high repeatability, and low cost, making it conducive to the miniaturization of electronic equipment and a popular choice in wireless power transmission systems. This paper aims to clarify the correlation between induction parameters and inductive capabilities using the orthogonal array of the modified Taguchi method for Pedelec applications. The conventional Taguchi method typically achieves only local optimization; however, this paper considers practical application conditions and combines experimental data to establish the initial values of the orthogonal array, thereby achieving global optimization. Additionally, the tuning process of the Taguchi method replaces physical experiments with simulations, enhancing optimization speed and reducing hardware implementation costs. The performance index for the proposed modified Taguchi tuning method is selected as a combination of the quality factor (Q) and coupling coefficient (k) to minimize AC resistance and improve system efficiency. To validate the proposed method, the designed coils were implemented and tested in a WPT system based on S–S compensation with a half-bridge topology. The experimental results demonstrate that the optimized PCB coil parameters derived from the proposed tuning method accurately validate the method’s effectiveness and accuracy. From the measured results with the proposed modified tuning method, the system efficiency is increased by 43.87% and the system transmitting power is increased by 28.51%.
Enhanced Hydrolysis of Carbonyl Sulfide in Coking Oven Gas Utilizing an Efficient Ca-Ba-γ-Al2O3 Catalyst
Authors: Li Kangrui , Wang Lemeng , Fu Dong , Zhang Pan
Published: October 2024

China possesses a substantial capacity for coke production, resulting in the annual generation of over 100 billion standard cubic meters of the by-product coke oven gas. The comprehensive utilization of this gas has emerged as a matter of significant concern within the coking industry. The removal of carbonyl sulfide (COS) from coke oven gas is crucial for enhancing gas quality, mitigating equipment corrosion, minimizing environmental pollution, elevating the quality of recovered products, and fostering the production of high-quality steel. A novel Ca-Ba-γ-Al2O3 catalyst has been devised, employing γ-Al2O3 as the catalyst matrix and integrating calcium hydroxide (Ca(OH)2) alongside barium hydroxide octahydrate (Ba(OH)2·8H2O) as the alkaline activating components. The impact of various factors, including reaction temperature, humidity, and the number of activating components loaded, on the hydrolysis efficiency of COS has been meticulously investigated. Furthermore, the catalytic reaction mechanism has been elucidated utilizing advanced characterization techniques such as X-ray diffraction (XRD) and Brunauer–Emmett–Teller (BET) analysis. The outcomes of this research reveal that, under optimal conditions of a reaction temperature of 55 °C and a humidity of 56%, the Ca-Ba-γ-Al2O3 catalyst achieves a remarkable COS hydrolysis efficiency of 95.22%.
Stable and Tunable Erbium Ring Laser by Rayleigh Backscattering Feedback and Saturable Absorber for Single-Mode Operation
Authors: Liao Chien-Yu , Kao Yu-Hsin , Chen Ying-Zhen , Cheng Kuan-Ming , Lin Chun-Yen , Wu Tsu-Hsin , Yang Teng-Yao , Yeh Chien-Hung
Published: October 2024

This work demonstrates a high-quality erbium-doped fiber (EDF) ring laser in the L-band gain range by combining the Rayleigh backscattering (RB) feedback signal and unpumped EDF induced saturable absorber (SA) filter. The optical filter effect induced by the RB feedback injection and EDF SA could generate single-longitudinal-mode (SLM) behavior and shrink the linewidth to sub-kHz. The output linewidth, power, and optical-signal-to-noise ratio (OSNR) of the fiber ring laser were also shown within the 42 nm wavelength bandwidth of 1565.0 to 1607.0 nm. Also, the instabilities of output power and central wavelength of each lasing lightwave were analyzed with a measurement time of 45 min.
Comparison and Optimization of Light Use Efficiency-Based Gross Primary Productivity Models in an Agroforestry Orchard
Authors: Cui Ningbo , He Ziling , Wang Mingjun , Zhang Wenjiang , Zhao Lu , Gong Daozhi , Li Jun , Jiang Shouzheng
Published: October 2024

The light-use efficiency-based gross primary productivity (LUE-GPP) model is widely utilized for simulating terrestrial ecosystem carbon exchanges owing to its perceived simplicity and reliability. Variations in cloud cover and aerosol concentrations can affect ecosystem LUE, thereby influencing the performance of the LUE-GPP model, particularly in humid regions. In this study, the performance of six big-leaf LUE-GPP models and one two-leaf LUE-GPP model were evaluated in a humid agroforestry ecosystem from 2018–2020. All big-leaf LUE-GPP models yielded GPP values consistent with that derived from the eddy covariance system (GPPEC), with R2 ranging from 0.66–0.73 and RMSE ranging from 1.81–3.04 g C m−2 d−1. Differences in model performance were attributed to the differences in the quantification of temperature (Ts) and moisture constraints (Ws) and their combination forms in the models. The Ts and Ws algorithms in the eddy covariance-light-use efficiency (EF-LUE) model well characterized the environmental constraints on LUE. Simulation accuracy under the common limitation of Ts and Ws (Ts × Ws) was higher than the maximum limitation of Ts or Ws (Min (Ts, Ws)), and the combination of the Ts algorithm in the Carnegie–Ames–Stanford Approach (CASA) and the Ws algorithm in the EF-LUE model was optimized in combination forms, thereby constraining LUE for GPP estimates (GPPBLO, R2 = 0.76). Various big-leaf LUE-GPP models overestimated or underestimated GPP on sunny or cloudy days, respectively, while the two-leaf LUE-GPP model, which considered the transmission of diffuse radiation and the difference in photosynthetic capacity of canopy leaves, performed well (R2 = 0.72, p < 0.01). Nevertheless, the underestimation/overestimation for shaded/sunlit leaves remained under different weather conditions. Then, the clearness index (Kt) was introduced to calculate the dynamic LUE in the big-leaf and two-leaf LUE-GPP models in the form of exponential or power functions, resulting in consistent performance even in different weather conditions and an overall higher simulation accuracy. This study confirmed the potential applicability of different LUE-GPP models and emphasized the importance of dynamic LUE on model performance.
Convolutional Neural Networks for Real Time Classification of Beehive Acoustic Patterns on Constrained Devices
Authors: Robles-Guerrero Antonio , Gómez-Jiménez Salvador , Saucedo-Anaya Tonatiuh , López-Betancur Daniela , Navarro-Solís David , Guerrero-Méndez Carlos
Published: October 2024

Recent research has demonstrated the effectiveness of convolutional neural networks (CNN) in assessing the health status of bee colonies by classifying acoustic patterns. However, developing a monitoring system using CNNs compared to conventional machine learning models can result in higher computation costs, greater energy demand, and longer inference times. This study examines the potential of CNN architectures in developing a monitoring system based on constrained hardware. The experimentation involved testing ten CNN architectures from the PyTorch and Torchvision libraries on single-board computers: an Nvidia Jetson Nano (NJN), a Raspberry Pi 5 (RPi5), and an Orange Pi 5 (OPi5). The CNN architectures were trained using four datasets containing spectrograms of acoustic samples of different durations (30, 10, 5, or 1 s) to analyze their impact on performance. The hyperparameter search was conducted using the Optuna framework, and the CNN models were validated using k-fold cross-validation. The inference time and power consumption were measured to compare the performance of the CNN models and the SBCs. The aim is to provide a basis for developing a monitoring system for precision applications in apiculture based on constrained devices and CNNs.
An Electrically Small Patch Antenna Sensor for Salt Concentration Measurement of NaCl Solution
Authors: Zhu Jinfeng , Chen Cheng , Sun Xiao , Ding Guowen , Wang Shenyun
Published: October 2024

In this paper, a complementary split-ring resonator (CSRR)-based patch antenna is proposed as a microwave sensor to measure the salt concentration of NaCl solution. The microwave sensor consists of an RF-4 substrate, where a small copper disc is attached on the top as the radiator, a larger copper disc integrated with two CSRRs is attached on the bottom side as the finite ground plane, and a coaxial feeding port is introduced at the ground plane center. During salt concentration sensing, only the top disc is immersed into NaCl solution. The results indicate that the proposed microwave sensor can measure salt concentrations ranging from 5‰ to 35‰ with a maximum sensitivity of 0.367 (kHz/(mg/L)). The proposed microwave sensor is low-cost, low-profile, electrically small, lightweight, and easy to fabricate, and it also can be applied to other solutions’ concentration sensing.
FaSS-MVS: Fast Multi-View Stereo with Surface-Aware Semi-Global Matching from UAV-Borne Monocular Imagery
Authors: Ruf Boitumelo , Weinmann Martin , Hinz Stefan
Published: October 2024

With FaSS-MVS, we present a fast, surface-aware semi-global optimization approach for multi-view stereo that allows for rapid depth and normal map estimation from monocular aerial video data captured by unmanned aerial vehicles (UAVs). The data estimated by FaSS-MVS, in turn, facilitate online 3D mapping, meaning that a 3D map of the scene is immediately and incrementally generated as the image data are acquired or being received. FaSS-MVS is composed of a hierarchical processing scheme in which depth and normal data, as well as corresponding confidence scores, are estimated in a coarse-to-fine manner, allowing efficient processing of large scene depths, such as those inherent in oblique images acquired by UAVs flying at low altitudes. The actual depth estimation uses a plane-sweep algorithm for dense multi-image matching to produce depth hypotheses from which the actual depth map is extracted by means of a surface-aware semi-global optimization, reducing the fronto-parallel bias of Semi-Global Matching (SGM). Given the estimated depth map, the pixel-wise surface normal information is then computed by reprojecting the depth map into a point cloud and computing the normal vectors within a confined local neighborhood. In a thorough quantitative and ablative study, we show that the accuracy of the 3D information computed by FaSS-MVS is close to that of state-of-the-art offline multi-view stereo approaches, with the error not even an order of magnitude higher than that of COLMAP. At the same time, however, the average runtime of FaSS-MVS for estimating a single depth and normal map is less than 14% of that of COLMAP, allowing us to perform online and incremental processing of full HD images at 1–2 Hz.
Criminalising Migration: The Vicious Cycle of Insecurity and Irregularity
Authors: Rosina Matilde
Published: October 2024

Recent years have witnessed growing emphasis on exceptional measures to address unauthorised arrivals. This article unpacks the relationship between migration policies, irregularity, and insecurity, by examining the consequences of a specific, yet often neglected, measure: the criminalisation of irregular migration (namely, the introduction of the “crime of irregular migration”). Investigating the cases of Italy and France, two of the countries with the most severe sanctions in Europe, it argues that criminalisation led to a two-fold feedback loop. On the one hand, by exceptionalising migration and constructing a continuum between migrants and criminals, criminalisation enhanced a sense of insecurity among the domestic public. On the other hand, by giving foreigners in irregular situations a criminal record, it increased their reliance on underground networks to stay and work in destination countries. Overall, this fostered demand for restrictive, yet counterproductive, policies, creating a vicious cycle of insecurity and irregularity.
Lego-like Bricks Manufacturing Using Recycled Polyethylene (PE) and Polyethylene Terephthalate (PET) Waste in Egypt
Authors: Ashraf Nada , El-Monayeri Ola D. , Hassan Hassan A.
Published: October 2024

Plastics are essential in modern civilization due to their affordability, simple manufacturing, and properties. However, plastics impact the environment as they decompose over a long period and degrade into microplastics. The construction sector has been exploring substituting conventional bricks with plastic bricks, as concrete and clay bricks consume natural resources and pollute the environment. The introduction of recycling plastic, and using plastic waste and sand mixtures to create Lego-like bricks has become a new trend. The bricks have superior properties to conventional bricks, such as a smoother surface, finer edges, easy application, crack-free, higher compression strength, almost zero water absorption, and reduced energy consumption. The study: compares the results of PE with sand and PET with sand samples to previous studies, confirms alignment, works as a control sample for PET and PE novel research, and validates the concept. Three plastic mixtures using two types of plastic waste (PE and PET) and sand were used. The plastic waste with sand was heated up to 200 °C. Plastic acts as a binder, while sand acts as a filler material. Optimized durability and cohesiveness were achieved at 30–40% plastic weight ratios. A mixture of PE and sand showed a maximum compressive strength of 38.65 MPa, while the PET and sand mixture showed 76.85 MPa, and the mix of PE and PET in equal proportions with sand resulted in 26.64 MPa. The plastic samples showed ductile behavior, with elongation between 20 and 30%, water absorption between 0 and 0.35%, and thermal conductivity from 0.8 to 1.05 W/(m/K). Carbon dioxide emissions are significantly reduced as compared to standard bricks. The CO2 per brick (kg) was 0.008 and 0.0085 in the PE; 0.0085 and 0.009 in the PET; and 0.0065 and 0.007 in the PE mixed with PET.
Hesitant Bipolar-Valued Intuitionistic Fuzzy Graphs for Identifying the Dominant Person in Social Media Groups
Authors: Alqahtani Mohammed , Keerthana R. , Venkatesh S. , Kaviyarasu M.
Published: October 2024

This work introduces the notion of a hesitant bipolar-valued intuitionistic fuzzy graph (HBVIFG), which reflects four different characterizations: membership with positive/negative aspects and non-membership with positive/negative aspects, incorporating multi-dimensional alternatives in all of its information. HBVIFG generalizes both HBVFG and BVHFG due to its diversified nature in observing four perspectives along with multiple attributes in a piece of information. Numerous studies, examples, and graphical representations emphasize the concept’s distinctiveness and importance. The following graph theory terms are defined: strong directed HBVIFG, full directed HBVIFG, directed spanning HBVIFSG, directed HBVIFSG, and partial directed hesitant bipolar-valued intuitionistic fuzzy subgraph (HBVIFSG). Examples of operations utilizing two HBVIFGs are Cartesian, direct, lexicographical, and strong products. A scenario is used to generate the mapping of relations, which includes homomorphism, isomorphism, weak isomorphism, and co-weak isomorphism. We describe a directed HBVIFG application that employs an algorithm to determine the most dominant person and self-persistent person in a social system and a comparative study is also provided. The proposed method provides a more detailed framework for assessing the most dominant and self-persistent individual in a social network across multi-level attributes along with positive and negative side membership and non-membership grades in each element of a network.
Notes on q-Gamma Operators and Their Extension to Classes of Generalized Distributions
Authors: Al-Omari Shrideh , Salameh Wael , Alhazmi Sharifah
Published: October 2024

This paper discusses definitions and properties of q-analogues of the gamma integral operator and its extension to classes of generalized distributions. It introduces q-convolution products, symmetric q-delta sequences and q-quotients of sequences, and establishes certain convolution theorems. The convolution theorems are utilized to accomplish q-equivalence classes of generalized distributions called q-Boehmians. Consequently, the q-gamma operators are therefore extended to the generalized spaces and performed to coincide with the classical integral operator. Further, the generalized q-gamma integral is shown to be linear, sequentially continuous and continuous with respect to some involved convergence equipped with the generalized spaces.
LSTM Gate Disclosure as an Embedded AI Methodology for Wearable Fall-Detection Sensors
Authors: Correia Sérgio D. , Roque Pedro M. , Matos-Carvalho João P.
Published: October 2024

In this paper, the concept of symmetry is used to design the efficient inference of a fall-detection algorithm for elderly people on embedded processors—that is, there is a symmetric relation between the model’s structure and the memory footprint on the embedded processor. Artificial intelligence (AI) and, more particularly, Long Short-Term Memory (LSTM) neural networks are commonly used in the detection of falls in the elderly population based on acceleration measures. Nevertheless, embedded systems that may be utilized on wearable or wireless sensor networks have a hurdle due to the customarily massive dimensions of those networks. Because of this, the algorithms’ most popular implementation relies on edge or cloud computing, which raises privacy concerns and presents challenges since a lot of data need to be sent via a communication channel. The current work proposes a memory occupancy model for LSTM-type networks to pave the way to more efficient embedded implementations. Also, it offers a sensitivity analysis of the network hyper-parameters through a grid search procedure to refine the LSTM topology network under scrutiny. Lastly, it proposes a new methodology that acts over the quantization granularity for the embedded AI implementation on wearable devices. The extensive simulation results demonstrate the effectiveness and feasibility of the proposed methodology. For the embedded implementation of the LSTM for the fall-detection problem on a wearable platform, one can see that an STM8L low-power processor could support a 40-hidden-cell LSTM network with an accuracy of 96.52%.
Observational Constraints and Cosmographic Analysis of f(T,TG) Gravity and Cosmology
Authors: Balhara Harshna , Singh Jainendra Kumar , Shaily  , Saridakis Emmanuel N.
Published: October 2024

We perform observational confrontation and cosmographic analysis of f(T,TG) gravity and cosmology. This higher-order torsional gravity is based on both the torsion scalar, as well as on the teleparallel equivalent of the Gauss–Bonnet combination, and gives rise to an effective dark-energy sector which depends on the extra torsion contributions. We employ observational data from the Hubble function and supernova Type Ia Pantheon datasets, applying a Markov chain Monte Carlo sampling technique, and we provide the iso-likelihood contours, as well as the best-fit values for the parameters of the power-law model, an ansatz which is expected to be a good approximation of most realistic deviations from general relativity. Additionally, we reconstruct the effective dark-energy equation-of-state parameter, which exhibits a quintessence-like behavior, while in the future the Universe enters into the phantom regime, before it tends asymptotically to the cosmological constant value. Furthermore, we perform a detailed cosmographic analysis, examining the deceleration, jerk, snap, and lerk parameters, showing that the transition to acceleration occurs in the redshift range 0.52≤ztr≤0.89, as well as the preference of the scenario for quintessence-like behavior. Finally, we apply the Om diagnostic analysis to cross-verify the behavior of the obtained model.
Real Ghosts of Complex Hadamard Products
Authors: Ballico Edoardo
Published: October 2024

For all integers n≥1 and k≥2, the Hadamard product v1★⋯★vk of k elements of Kn+1 (with K being the complex numbers or real numbers) is the element v∈Kn+1 which is the coordinate-wise product of v1,…,vk (introduced by Cueto, Morton, and Sturmfels for a model in Algebraic Statistics). This product induces a rational map h:Pn(K)k⤏Pn(K). When K=C, k=2 and Xi(C)⊂Pn(C), i=1,2 are irreducible, we prove four theorems for the case dimX2(C)=1, three of them with X2(C) as a line. We discuss the existence (non-existence) of a cancellation law for ★-products and use the symmetry group of the Hadamard product. In the second part, we work over R. Under mild assumptions, we prove that by knowing X1(R)★⋯★Xk(R), we know X1(C)★⋯★Xk(C). The opposite, i.e., taking and multiplying a set of complex entries that are invariant for the complex conjugation and then seeing what appears in the screen Pn(R), very often provides real ghosts, i.e., images that do not come from a point of X1(R)×⋯×Xk(R). We discuss a case in which we certify the existence of real ghosts as well as a few cases in which we certify the non-existence of these ghosts, and ask several open questions. We also provide a scenario in which ghosts are not a problem, where the Hadamard data are used to test whether the images cover the full screen.
Can Taxonomists Think? Reversing the AI Equation
Authors: Valdecasas Antonio G.
Published: October 2024

Confusion between the means and ends, specifically between technological achievements and their users, has been evident in taxonomy’s history since the end of the last century. Following a current of thought implicit in Anglo-Saxon culture, this trend aligns with the idea of inevitability. It is inevitable, so it is thought, that what a human organism can do, a machine will be able to do at some point in time. This will ultimately lead to dispensing with the human element for things they do not wish to do themselves. Despite certain misunderstandings about what has become known as the Turing Test, the general idea is to determine whether a machine can analyze data as meaningfully as a human does and make decisions based on that analysis. In the case of taxonomy, the initial aim of using machines was to efficiently replace a researcher for identification purposes. The situation later evolved to include the discovery of new entities in addition to identification. In this essay, I provide a brief overview of some milestones along this trajectory and its current state and discuss the influence of artificial intelligence (AI) in taxonomy.
Quad-Band Rectifier Circuit Design for IoT Applications
Authors: Bougas Ioannis D. , Papadopoulou Maria S. , Boursianis Achilles D. , Sotiroudis Sotirios , Zaharis Zaharias D. , Goudos Sotirios K.
Published: October 2024

In this work, a novel quad-band rectifier circuit is introduced for RF energy harvesting and Internet of Things (IoT) applications. The proposed rectifier operates in the Wi-Fi frequency band and can supply low-power sensors and systems used in IoT services. The circuit operates at 2.4, 3.5, 5, and 5.8 GHz. The proposed RF-to-DC rectifier is designed based on Delon theory and Greinacher topology on an RT/Duroid 5880 substrate. The results show that our proposed circuit can harvest RF energy from the environment, providing maximum power conversion efficiency (PCE) greater than 81% when the output load is 0.511 kΩ and the input power is 12 dBm. In this work, we provide a comprehensive design framework for an affordable RF-to-DC rectifier. Our circuit performs better than similar designs in the literature. This rectifier could be integrated into an IoT node to harvest RF energy, thereby proving a green energy source. The IoT node can operate at various frequencies.
A Cross-National Study on Sustainable Smart City Indicators and Their Influence on Life Expectancy—A Cluster Analysis of EU Countries
Authors: Chovancová Jana , Petruška Igor , Pata Ugur Korkut
Published: October 2024

As a consequence of climate change and its negative impacts on the environment and on human health, the topic of sustainability has become an integral part of urban policy. Smart city initiatives around the world are focusing on different aspects of sustainability in order to provide better living conditions for their residents. The aim of this study is to investigate the impact of selected smart city indicators on the average life expectancy as a variable for quality of life and well-being. Based on a Common Correlated Effects (CCE) model, Instrumental Variable Estimator with Common Factors (2SIV), and clustering regression model, EU countries were divided into three distinct clusters indicating common elements but also specificities of each group. The analysis confirmed the positive impact of GDP growth, renewable energy consumption, and the proportion of the population with a tertiary level of education on life expectancy. On the other hand, CO2 emissions and transport pollution have an adverse effect. The analysis provides valuable insights into the complex relationship between smart city variables and quality of life, and it may serve as a basis for informed and responsible decision-making by relevant urban stakeholders aimed at designing more sustainable, resilient, and healthier cities.
Applications of CRISPR/Cas as a Toolbox for Hepatitis B Virus Detection and Therapeutics
Authors: Kumar Anuj , Combe Emmanuel , Mougené Léa , Zoulim Fabien , Testoni Barbara
Published: October 2024

Hepatitis B virus (HBV) infection remains a significant global health challenge, leading to chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma (HCC). Covalently closed circular DNA (cccDNA) and integrated HBV DNA are pivotal in maintaining viral persistence. Recent advances in CRISPR/Cas technology offer innovative strategies to inhibit HBV by directly targeting both cccDNA and integrated HBV DNA or indirectly by degrading HBV RNAs or targeting host proteins. This review provides a comprehensive overview of the latest advancements in using CRISPR/Cas to inhibit HBV, with a special highlight on newer non-double-strand (non-DSB) break approaches. Beyond the canonical use of CRISPR/Cas for target inhibition, we discuss additional applications, including HBV diagnosis and developing models to understand cccDNA biology, highlighting the diverse use of this technology in the HBV field.
Interactions between Common Bean Viruses and Their Whitefly Vector
Authors: Ferreira Amanda L. , Ghanim Murad , Xu Yi , Pinheiro Patricia V.
Published: October 2024

Common bean (Phaseolus vulgaris L.) is a widely cultivated crop, representing an important protein source in the human diet in developing countries. The production of this crop faces serious challenges, such as virus diseases transmitted by the whitefly Bemisia tabaci. Although there is a lot of information about some of these viruses, most of what we know has been developed using model systems, such as tomato plants and tomato yellow leaf curl virus (TYLCV). There is still very little information on the most relevant common bean viruses, such as bean golden mosaic virus (BGMV), bean golden yellow mosaic virus (BGYMV), bean dwarf mosaic virus (BDMV), cowpea mild mottle virus (CPMMV), and bean yellow disorder virus (BnYDV). In this review, we discuss the available data in the most up-to-date literature and suggest future research avenues to contribute to the development of management tools for preventing or reducing the damage caused by viruses in this important crop.
Can Productive Aptitude and Age Affect Circulating Serotonin, Total Thyroid Hormones, and Cortisol Patterns in Cows?
Authors: Bruschetta Giuseppe , Bionda Arianna , Giunta Renato Paolo , Costa Giovanna Lucrezia , Fazio Esterina , Licata Patrizia , Bruno Fabio
Published: October 2024

Cattle productivity, whether in terms of meat yield or milk production, is intricately regulated by a multitude of factors. Among them, hormone concentrations play a significant role, reflecting the complex interplay between endocrine regulation and physiological processes that ultimately determine the efficiency and yield of production. High concentrations of 5-hydroxytriptamine (5-HT) are associated with a reduced metabolic load at the onset of lactation and a lower milk yield. Thyroid hormones (THs) and cortisol also affect several metabolic pathways, including carbohydrate, protein, and lipid metabolism. The aim of this study was to assess if milk or meat aptitudes and age influence circulating 5-HT, THs, and cortisol concentrations, investigating the possible interactions among these parameters. The research was performed on 46 healthy cows of three different breeds. Enzyme-linked immunosorbent assay (ELISA) methods were used to quantify circulating 5-HT and cortisol concentrations, and an immunochemiluminescent analyzer was used for THs. For parameters exhibiting non-normal distributions, an ANCOVA model using age, aptitude, and their interaction as fixed factors was applied. Significant lower T3 concentrations were recorded in dairy cows than in meat cows. Moreover, T4 significantly decreased with advancing age both in cows aimed at milk and meat production. Lastly, T4 was positively correlated with T3 and 5-HT in meat production-oriented cows.
A Study of Virtual Water Trade among G20 Countries from a Value-Added Trade Perspective
Authors: Deng Guangyao , Di Keyu
Published: October 2024

From a value-added trade perspective, this study utilizes the world input–output tables and the water footprint data of each industry in each country in the Eora database to explore the virtual water resources of 19 countries (the G20 countries excluding the European Union) in 2016. We calculated nine value chain decompositions and the pattern of virtual water flows and then explored the implied virtual water use due to the trade of intermediate goods and final goods, and we also analyzed the unequal trade of virtual water and added value among countries. The results indicate the following. Firstly, in most countries, the largest portion of virtual water is attributed to exports of intermediate inputs that are produced in the source country and fully utilized by the direct import countries, followed by the foreign value-added component of intermediate goods, while the smallest share of virtual water is returned to the country. Secondly, in value-added trade, excluding the rest of the world (ROW), China, France, Italy, Japan, Mexico, South Korea, South Africa, Saudi Arabia, and Germany are net importers in the virtual water trade between G20 countries, and the USA is the largest net exporter of virtual water. Thirdly, intermediate product trade is the dominant form of implied virtual water trade among countries, which leads to a net flow ratio of implied virtual water of about 80% to 90%. Lastly, the Virtual Water Inequality Index shows that thirteen country combinations, including Brazil and Argentina, exhibit significant inequality, and most countries are in a relatively equal state. In addition, the virtual water and added value of the relatively economically developed regions benefit more from the virtual water trade. Therefore, it is crucial for countries to reduce their consumption of virtual water when trading intermediate products to develop high-value-added and low-water-consumption industries and to choose appropriate virtual water trade targets.
Diffusion Mechanism of Variable-Rate Grouting in Water Prevention and Control of Coal Mine
Authors: Li Chong , Lu Cunjin , Xu Jinpeng , Zhang Kai , Liu Shiming , Zhao Hui
Published: October 2024

Regional grouting treatment is an effective technical means to prevent mine water disasters, and the grouting effect is affected by many factors. In actual grouting engineering, the single constant-rate grouting method is often transformed into a variable-parameter grouting process. However, research on grouting rates has been insufficient. This investigation focused on the issue of “the diffusion law of variable-rate grouting slurry in regional governance”. Methods such as theoretical analysis, numerical simulation, and field verification were used to evaluate the diffusion mechanism of variable-rate fracture grouting. The results indicated that the key parameters of variable-rate grouting, such as slurry diffusion distance and grouting pressure, were affected by the grouting rate. The decrease in the grouting rate reduced the migration speed of the slurry and the grouting pressure. The time for constant-velocity grouting and variable-velocity grouting to reach the same diffusion distance was 60 s and 108 s, respectively, which can be achieved with lower grouting pressure. When the grouting rate was 7.5 L/min and 30 L/min, the maximum grout diffusion distance was 2.81 m and 5.64 m, respectively, which required greater grouting pressure. The slurry diffusion rate decreased with the reduction in the grouting rate. Under the same diffusion distance conditions, variable-rate grouting took longer than constant high-rate grouting. In variable-rate grouting, the grouting pressure decreased stepwise with the grouting rate, with a final pressure drop of 77.4%. In grouting practice, the innovative use of the rate-reducing grouting method can greatly reduce the final grouting pressure under the premise of changing the slurry diffusion distance less, which can not only ensure the stability of surrounding rock but also reduce the cost of high-pressure grouting and the risk of grouting operation. The investigation results can provide scientific guidance for ground grouting renovation projects in deep coal mine water hazard areas.
DEFINITION AND ACCOUNTING OF INTERCURRENT TRANSPORT COSTS ARISING IN THE PROCESS OF SYNCHROMODAL DELIVERY IN THE SYSTEM OF MULTI-TRANSPORTATION
Authors:   Russian University of Transport (MIIT), Kurganova Nadegda Vladimirovna , Sazonov Aleksey Aleksandrovich ,   Sim-Auto LLC
Published: October 2024

The authors' research in terms of modeling the accounting of intercurrent transport costs arising in the process of synchromodal delivery in a multimodal transport system is an extremely important, relevant and relevant scientific issue in the development of modern logistics. The purpose of the work is to define the author's term, present a formula for assessing the effectiveness of intercurrent transport costs and conduct practical testing using the example of a production and commercial organization.
SOME PROBLEMS OF TRAFFIC MANAGEMENT IN SMALL AND MEDIUM-SIZED CITIES IN CHINA
Authors:   Don State Technical University, SHENG JINGXIANG
Published: October 2024

At present, China's urban traffic volume has increased, transportation development is relatively lagging behind, combined with pedestrians, bicycles and cars coexist in a mixed traffic state makes the traffic problem in small and medium-sized cities increasingly serious, small and medium-sized cities in the capital, infrastructure, traffic management, road users travel characteristics of large cities have great differences. For China's small and medium-sized cities traffic characteristics and traffic problems special characteristics of road infrastructure, traffic management, road users and other aspects of in-depth analysis, how to provide a basis for China's small and medium-sized cities traffic problem countermeasures.
DETERMINATION OF THE RATIONAL VARIANT DRIVER CANDIDATE TRAINING PROGRAM BASED ON THE FUZZY SET THEORY
Authors:   Belgorod state technological university, Kushchenko Liliya Evgen’evna , Eremin Sergey Vasilievich ,   State Duma of the Federal Assembly of the Russian Fed-eration, Koroleva Liliya Aleksandrovna ,   Belgorod state technological university, Savenkova Arina Yurievna ,   Belgorod state technological university
Published: October 2024

The article considers the issue of choosing the rational program for training driver candidates using the theory of fuzzy sets. Fuzzy logic methods are used to account for various uncertainties and fuzzy concepts, in this case, related to the driver training process. The article presents the basic principles of the theory of fuzzy sets and their application to the issue under study. The results obtained can be useful and informative in the development of effective and adaptive driver candidate training programs that take into account the individual characteristics of student.
FORECASTING CONDITIONS FOR EFFECTIVE OPERATION OF HYBRID VEHICLES
Authors:   Vologda State University, Rakov Vyacheslav Alexandrovich
Published: October 2024

The article provides a set of assessment methods that allow us to formulate criteria for the efficiency of hybrid cars. To predict the fuel efficiency of hybrid vehicles under given operating conditions, a theoretical calculation method is used, in which the hybrid engine is considered as a system in which energy from the gasoline engine is transmitted to the drive wheels through several energy chains. Taking into account the design features and the type of hybrid engine, energy trans-fer losses and fuel consumption are determined. As an example, the results of assessing the fuel consumption and CO2 emissions of cars with three types of hybrid engines when driving on the WLTC test cycle are presented. Based on the developed methods for assessing the operating efficiency and the method for predicting the fuel consumption of hybrid vehicles, the boundaries of their economically efficient operation were determined.
Aula invertida en el logro de competencias de las ciencias sociales
Authors: Farroñan Flores Lucero de los Milagros
Published: October 2024

El aula invertida es una estrategia pedagógica innovadora que se ha propuesto como una alternativa efectiva para mejorar el aprendizaje en diversas áreas académicas. Este estudio se centró en analizar la influencia de esta metodología en el logro de competencias en ciencias sociales en una institución educativa pública en Sayllapata, Cusco. La investigación empleó un enfoque cuantitativo, utilizando el método hipotético-deductivo y un diseño preexperimental con un solo grupo. La muestra consistió en 80 estudiantes del VII ciclo de educación básica regular, quienes participaron en el grupo experimental. Se aplicó un diseño preprueba-posprueba para evaluar los efectos del aula invertida, utilizando encuestas como instrumento de recolección de datos. Los resultados revelaron un valor p de 0,000 en la prueba de Wilcoxon, indicando una mejora significativa en las competencias evaluadas. Tras la implementación del aula invertida, el 81,25% de los estudiantes alcanzaron los niveles de logro esperado y destacado en competencias como interpretaciones históricas, gestión responsable del espacio y ambiente, y gestión de recursos económicos. Se concluye que el aula invertida tiene una influencia positiva y significativa en el logro de competencias en ciencias sociales en el contexto educativo público analizado.
Competencia digital en estudiantes universitarios: Una revisión sistemática
Authors: Sotelo-Núñez Ana Cecilia , Herrera Rojas Jessica Juliana , Herrera Rojas Mirela Zuceti , López-Regalado Oscar
Published: October 2024

Las competencias digitales son fundamentales en la formación académica debido a la creciente importancia de las tecnologías en los procesos de enseñanza y aprendizaje. Este estudio analiza competencias digitales en estudiantes universitarios de pregrado entre 2013 y 2023 mediante una revisión sistemática y bibliométrica. Se evaluaron 159 publicaciones de Scopus, Web of Science y PubMed, seleccionando 37 artículos. Los hallazgos muestran significativa colaboración internacional, con España y Ucrania como los países más representados, y destacan las revistas Education Sciences y Sustainability. Los resultados subrayan la importancia de las competencias digitales en el aprendizaje, la enseñanza, el currículo, el diseño instruccional, las políticas educativas y su impacto social y laboral.