bluuebunny/crossref_metadata_2025 huggingface dataset:
Giant Halo in 66Ca Within Relativistic Continuum Hartree–Bogoliubov Theory Combined with Lipkin–Nogami Method
Authors: Zhou Chang , Guo Peng , Jiang Xiaofei
Published: December 2024

The impact of the Lipkin–Nogami (LN) method on a giant halo is investigated within the relativistic continuum Hartree–Bogoliubov (RCHB) theory. The ground-state properties of Ca isotopes obtained from RCHB and RCHB+LN calculations are presented. The results show that the LN correction does not change the range of Ca isotopes with a giant halo. Taking 66Ca as an example, the neutron density distribution with LN correction is found to be slightly more diffused, which can be illustrated by the enlargement of the root mean square radius and the enhancement of the relative contribution in neutron 3s1/2 level.
Novel Antigenic Variant Infectious Bursal Disease Virus Outbreaks in Japan from 2014 to 2023 and Characterization of an Isolate from Chicken
Authors: Takahashi Mari , Oguro Shiori , Kato Atsushi , Ito Soma , Tsutsumi Nobuyuki
Published: December 2024

Novel antigenic variant strains of the infectious bursal disease virus (IBDV) classified into genogroup A2d have been found in the western part of Japan since 2017. Novel antigenic variant IBDVs now occur in higher frequencies in poultry houses and have been detected in the eastern part of Japan, indicating the spread of IBDVs despite the usual IBDV vaccination. We isolated a novel antigenic variant IBDV, designated as the B2977CE2C3 strain. The B2977CE2C3 strain had two genogroup A2d specific amino acids—lysine and isoleucine, at 221 and 252 aa—along with the other genogroup A2 common amino acids in the projection domains of the VP2 protein corresponding to the virus-neutralizing epitopes and viral pathogenicity. Experimental infection of the B2977CE2C3 strain did not produce any apparent clinical signs in the specific-pathogen-free chickens during the observation period (21 days), but atrophy of the bursa of Fabricius (BF) was apparent. The mean BF to the body weight ratio was 0.35 in negative control chickens at 21 days post-infection (pi) but 0.06 in the B2977CE2C3 infected group. An extremely high copy number of the IBDV genome (>108 copies/µL) was observed in the BF at 3 days pi, while a high copy number of the IBDV genome (>106 copies/µL) was observed in the thymus, spleen cecal tonsil, and bone marrow even though macroscopic lesions were not apparent in these organs.
Prospective Evaluation of the Prevalence and Laboratory Findings in Adult Cats with Low Thyroxine and Increased Thyrotropin Concentration
Authors: Lin Joanna , Schwens Christina , Bauer Natali , Hazuchova Katarina
Published: December 2024

Adult-onset spontaneous feline hypothyroidism (SH) is considered rare, but its prevalence is unknown. This study aimed to screen laboratory submissions for cats with laboratory suspected SH (LSSH) and to identify laboratory abnormalities associated with LSSH. Submissions to a commercial laboratory in Germany between January 2022 and April 2023 were prospectively screened for cats aged 3–12 years with low total thyroxine (TT4); in these cats, thyrotropin (TSH) was measured. Iatrogenic hypothyroidism was excluded by contacting submitting veterinarians. Creatinine, triglyceride and cholesterol concentration and red blood cell count (RBC) of cats with LSSH (low TT4, TSH > 0.53 ng/mL; i.e., [one sided TSH reference change value (76%) of TSH upper reference interval (RI)] + [TSH upper RI] = 0.53) were compared to euthyroid cats (TT4 within RI) and cats with suspected non-thyroidal illness (SNTIS) (low TT4, normal TSH (<0.3 ng/mL; upper RI)) by non-parametric tests. p < 0.05 was significant. In total, 31,572 submissions of cats were included, 25,169 (79.7%) were euthyroid, 3818 (12.1%) had SNTIS and 61 (0.2%) had LSSH. Cats with LSSH had higher creatinine (p = 0.002) and lower RBC count (p < 0.0001) than euthyroid cats as well as higher creatinine (p = 0.00035) than cats with SNTIS. Azotaemia (creatinine > 140 µmol/L) and anaemia (RBC < 7.2 × 1012/L) were present in 28/49 (57%) and 19/44 (43%) cats with LSSH, respectively. There was no difference between LSSH and SNTIS for the remaining parameters. In cats with low TT4, azotaemia and anaemia might indicate the presence of SH and reinforce the need for TSH testing. Hypercholesterolaemia and hypertriglyceridaemia are not indicators of SH.
Enhancement of Methane Detection in Tunable Diode Laser Absorption Spectroscopy Using Savitzky–Golay Filtering
Authors: Chen Shichao , Tian Xing , Mu Tong , Yuan Jun , Cao Xile , Cheng Gang
Published: December 2024

In order to enhance gas absorption efficiency and improve the detection sensitivity of methane, a gas absorption cell with an effective optical path length of 29.37 m was developed, employing tunable diode laser absorption spectroscopy (TDLAS) and a distributed feedback (DFB) laser with a center wavelength of 1.654 μm as the light source. However, despite these advancements, the detection accuracy was still limited by potential signal interference and noise. To address these challenges, the Savitzky–Golay (S-G) filtering technique was implemented to optimize the TDLAS detection signal. Experimental results indicated a significant enhancement in detection performance. For a methane concentration of 92 ppm, the application of the S-G filter improved the signal-to-noise ratio by a factor of 1.84, resulting in a final device detection accuracy of 0.53 ppm. This improvement demonstrates the effectiveness of the S-G filter in enhancing detection sensitivity, supporting high-precision methane monitoring for atmospheric analysis and various industrial applications.
Salicylic Acid-Induced Expression Profiles of LRR and LRR-RLK Candidate Genes Modulate Mungbean Yellow Mosaic India Virus Resistance in Blackgram and Its Two Wild Non-Progenitors
Authors: Shukla Mansi , Kaundal Priyanka , Purwar Shalini , Kumar Mukul , Maurya Chandragupt , Chirag  , Mishra Awdhesh Kumar , Baek Kwang-Hyun , Singh Chandra Mohan
Published: December 2024

Blackgram is an important short-duration grain legume, but its yield is highly affected by various stresses. Among biotic stresses, yellow mosaic disease (YMD) is known as a devastating disease that leads to 100% yield loss under severe conditions. The cultivated lines possess resistance, but exploring more diverse sources of resistance may be useful for pyramiding to improve the durability of said resistance. Some wild Vigna species have potentially demonstrated a high level of resistance. R-genes, including gene families of leucine-rich repeats (LRRs) and leucine-rich repeat receptor-like kinases (LRR-RLKs), are known for modulating the resistance in plants against various biotic stresses. The first comprehensive analysis of the LRR and LRR-RLK gene families in mungbean is reported in the present study. A total of forty-six candidate genes were identified and grouped into eight clades. Protein motif analysis showed that the “Pkinase domain” and “LRR domains” were conserved in most of the R-proteins. The expression of candidate genes viz. VrNBS_TNLRR-8, VrLRR_RLK-20, VrLRR_RLK-17, and VrLRR_RLK-19 demonstrated significantly up-regulated expression upon YMD infection in control and salicylic acid-primed (SA-primed) plants. The analysis provides insight into the diversity and robust candidate genes for functional studies modulating YMD resistance altered by salicylic acid.
Assessment of 3-Cyanobenzoic Acid as a Possible Herbicide Candidate: Effects on Maize Growth and Photosynthesis
Authors: Grizza Luiz Henryque Escher , Contesoto Isabela de Carvalho , Mendonça Ana Paula da Silva , Comar Amanda Castro , Boromelo Ana Paula , Ferro Ana Paula , Constantin Rodrigo Polimeni , dos Santos Wanderley Dantas , Marchiosi Rogério , Ferrarese-Filho Osvaldo
Published: December 2024

Chemical weed control is a significant agricultural concern, and reliance on a limited range of herbicide action modes has increased resistant weed species, many of which use C4 metabolism. As a result, the identification of novel herbicidal agents with low toxicity targeting C4 plants becomes imperative. An assessment was conducted on the impact of 3-cyanobenzoic acid on the growth and photosynthetic processes of maize (Zea mays), a representative C4 plant, cultivated hydroponically over 14 days. The results showed a significant reduction in plant growth and notable disruptions in gas exchange and chlorophyll a fluorescence due to the application of 3-cyanobenzoic acid, indicating compromised photosynthetic activity. Parameters such as the chlorophyll index, net assimilation (A), stomatal conductance (gs), intercellular CO2 concentration (Ci), maximum effective photochemical efficiency (Fv′/Fm′), photochemical quenching coefficient (qP), quantum yield of photosystem II photochemistry (ϕPSII), and electron transport rate through PSII (ETR) all decreased. The A/PAR curve revealed reductions in the maximum net assimilation rate (Amax) and apparent quantum yield (ϕ), alongside an increased light compensation point (LCP). Moreover, 3-cyanobenzoic acid significantly decreased the carboxylation rates of RuBisCo (Vcmax) and PEPCase (Vpmax), electron transport rate (J), and mesophilic conductance (gm). Overall, 3-cyanobenzoic acid induced substantial changes in plant growth, carboxylative processes, and photochemical activities. The treated plants also exhibited heightened susceptibility to intense light conditions, indicating a significant and potentially adverse impact on their physiological functions. These findings suggest that 3-cyanobenzoic acid or its analogs could be promising for future research targeting photosynthesis.
Proline and ROS: A Unified Mechanism in Plant Development and Stress Response?
Authors: Renzetti Marco , Funck Dietmar , Trovato Maurizio
Published: December 2024

The proteinogenic amino acid proline plays crucial roles in both plant development and stress responses, far exceeding its role in protein synthesis. However, the molecular mechanisms and the relative importance of these additional functions of proline remain under study. It is well documented that both stress responses and developmental processes are associated with proline accumulation. Under stress conditions, proline is believed to confer stress tolerance, while under physiological conditions, it assists in developmental processes, particularly during the reproductive phase. Due to proline’s properties as a compatible osmolyte and potential reactive oxygen species (ROS) scavenger, most of its beneficial effects have historically been attributed to the physicochemical consequences of its accumulation in plants. However, emerging evidence points to proline metabolism as the primary driver of these beneficial effects. Recent reports have shown that proline metabolism, in addition to supporting reproductive development, can modulate root meristem size by controlling ROS accumulation and distribution in the root meristem. The dynamic interplay between proline and ROS highlights a sophisticated regulatory network essential for plant resilience and survival. This fine-tuning mechanism, enabled by the pro-oxidant and antioxidant properties of compartmentalized proline metabolism, can modulate redox balance and ROS homeostasis, potentially explaining many of the multiple roles attributed to proline. This review uniquely integrates recent findings on the dual role of proline in both ROS scavenging and signaling, provides an updated overview of the most recent research published to date, and proposes a unified mechanism that could account for many of the multiple roles assigned to proline in plant development and stress defense. By focusing on the interplay between proline and ROS, we aim to provide a comprehensive understanding of this proposed mechanism and highlight the potential applications in improving crop resilience to environmental stress. Additionally, we address current gaps in understanding and suggest future research directions to further elucidate the complex roles of proline in plant biology.
Optimization of Breeding Tools in Quinoa (Chenopodium quinoa) and Identification of Suitable Breeding Material for NW Europe
Authors: Vleugels Tim , Van Waes Chris , De Keyser Ellen , Cnops Gerda
Published: December 2024

Quinoa (Chenopodium quinoa) cultivation has become increasingly popular in NW Europe but little is known about the performance of contract-free varieties in this region. In this study, we phenotyped 25 quinoa varieties on a single-plant basis in a field trial in Belgium. In addition, we optimized breeding tools such as NIRS (near-infrared reflectance spectroscopy) to estimate the seed crude protein content and a multiplex PCR set to identify true F1 progeny from pair crosses. We identified 14 varieties with sufficiently early maturity, 17 varieties with plant height below 150 cm, 21 large-seeded varieties, four varieties with a crude protein content exceeding 15%, and two low-saponin varieties. A variety of seed colors and plant morphological traits was observed. Seed yield was not correlated with maturity, plant height or saponin content, but was negatively correlated with seed crude protein content. NIRS could accurately predict seed crude protein content with a determination coefficient of 0.94. Our multiplex SSR set could correctly identify the paternity in 77% to 97% of progeny, depending on the pair cross. In conclusion, our study identified various contract-free varieties that may be suitable for cultivation in NW Europe. In addition, our study provides valuable phenotypic information and breeding tools that breeders can harness for breeding efforts in NW European quinoa.
Plant Growth-Promoting and Herbicidal Bacteria as Potential Bio-Based Solutions for Agriculture in Desertic Regions
Authors: Muñoz-Torres Patricio , Huanca-Mamani Wilson , Cárdenas-Ninasivincha Steffany , Aguilar Yola , Quezada Antonio , Bugueño Franco
Published: December 2024

The region of Arica and Parinacota hosts unexplored remote sites with unique characteristics suitable for developing novel agricultural bioproducts. Notable locations include Jurasi Hot Springs, Polloquere Hot Springs, and Amuyo Lagoons, featuring open pools fed by thermal mountain springs. These geothermal sites harbor bacteria with plant growth-promoting activities, particularly interesting to the strains J19, TP22, A20, and A3. These bacteria possess in vitro plant growth-promoting traits, the ability to produce hydrolytic enzymes, and the capacity to inhibit phytopathogenic fungi. Moreover, they can tolerate different concentrations of NaCl and boron, making them suitable for developing new agricultural bioproducts for arid environments. The bacterial strains A3 and A20 have a positive effect on the growth of the aerial part of tomato plants (increased stem length, fresh and dry weight), with a significant increment in proline concentration and chlorophyll A and B content under saline conditions. Meanwhile, the strains J19 and TP22 exhibit herbicidal activity against Cenchrus echinatus by reducing root elongation and germination of the weed. These strains possess plant growth-promoting traits and improve plant resistance to salinity stress. They are promising candidates for developing innovative bio-based agricultural products suited to arid and semi-arid regions.
A Comparative Evaluation of the Antioxidant Ability of Polygonum cuspidatum Extracts with That of Resveratrol Itself
Authors: Olszowy-Tomczyk Małgorzata , Wianowska Dorota
Published: December 2024

In this article, the resveratrol content and antioxidant activity of extracts obtained from Japanese knotweed (Polygonum cuspidatum Siebold & Zucc.) were evaluated. The extracts were prepared by pressurized liquid extraction (PLE), maceration, ultrasound-assisted solvent extraction (UASE), and sea sand disruption method (SSDM) using different extractants (methanol, methanol–water mixture, and water). The following methods were used to study antioxidant properties: ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), FRAP (ferric reducing antioxidant power), DPPH (2,2′-diphenyl-1-picrylhydrazyl), and CUPRAC (cupric ion reducing antioxidant capacity). It was proven that the resveratrol content depends not only on the extraction technique used but also on the solvent and extraction temperature. High resveratrol content was obtained by maceration and PLE using a mixture of methanol and water as the extraction solvent. Among the extracts tested, these were the ones showed the greatest antioxidant properties. However, it was confirmed that not only resveratrol but also other components of the extracts are responsible for the antioxidant properties. It was therefore shown that not only resveratrol, most commonly associated with Japanese knotweed, but also other ingredients affect the biological activity of this valuable-for-health plant.
Pathogenesis, Epidemiology, and Risk Factors of Malignant Tumors in Systemic Lupus Erythematosus
Authors: Blachut Dominika , Przywara-Chowaniec Brygida , Tomasik Andrzej
Published: December 2024

Systemic lupus erythematosus (SLE) is an autoimmune connective tissue disease with a complex pathogenesis, primarily affecting women. SLE is associated with the presence of autoantibodies, chronic inflammation, and multi-organ dysfunction. Increasing evidence suggests that SLE is linked to a higher risk of malignancies, compared to the general population, though the mechanism behind this phenomenon remains unclear. Malignant tumors are the fourth most common cause of death in SLE patients. SLE is associated with an elevated risk of hematological cancers, as well as cancers of the lungs, thyroid, liver, and bile ducts. The aim of this paper is to review the latest literature on the pathogenesis, epidemiology, and risk factors for malignancies in SLE patients. The mechanisms of oncogenesis in SLE are still not fully understood, and the pathophysiology includes such risk factors as chronic inflammation, immune disorders, therapies used, overlap syndromes of connective tissue diseases, viral infections, and traditional cancer risk factors. Evaluating these factors and understanding the process of oncogenesis are crucial for prevention. Systemic lupus erythematosus may be an independent risk factor for the development of malignancies. It is important to raise awareness among SLE patients about the increased risk of malignancies. Further research is needed to establish guidelines for prevention, including screening recommendations.
What Is Grazing Time? Insights from the Acoustic Signature of Goat Jaw Activity in Wooded Landscapes
Authors: Ungar Eugene David , Horn Reuven
Published: December 2024

Acoustic monitoring facilitates the detailed study of herbivore grazing by generating a timeline of sound bursts associated with jaw movements (JMs) that perform bite or chew actions. The unclassified stream of JM events was used here in an observational study to explore the notion of “grazing time”. Working with shepherded goat herds in a wooded landscape, a horn-based acoustic sensor with a vibration-type microphone was deployed on a volunteer animal along each of 12 foraging routes. The software-generated timeline of unclassified JMs contained a total of 334,582 events. After excluding rumination bouts, minutely JM rates showed a broad, non-normal distribution, with an overall mean of 61 JM min−1. The frequency distribution of inter-JM interval values scaled logarithmically, with a peak in the region of 0.43 s representing a baseline interval that generates the unconstrained, more-or-less regular, rhythm of jaw movement (≈140 JM min−1). This rhythm was punctuated by interruptions, for which duration scaled logarithmically, and which were primarily related to the search phase of the intake process. The empirical time accumulation curve shows the contribution of the inter-JM interval to the total foraging time and provides a penetrating profile of how the animal interacted with the foraging environment. The sum total of time along a foraging route spent at a near-potential JM rate was only ≈1 h, whereas sub-potential rates containing intervals as long as ≈30 s accounted for the bulk of the foraging route. The dimensionless behavioral grazing intensity was defined as the product of the number of ingestive JMs performed and the baseline interval, divided by the duration of the foraging route (excluding rumination). Values were mostly <0.5 for the foraging routes examined. This has implications for how animal presence should be translated to grazing pressure and for how long animals need to forage to meet their nutritional requirements.
FFL-IDS: A Fog-Enabled Federated Learning-Based Intrusion Detection System to Counter Jamming and Spoofing Attacks for the Industrial Internet of Things
Authors: Rehman Tayyab , Tariq Noshina , Khan Farrukh Aslam , Rehman Shafqat Ur
Published: December 2024

The Internet of Things (IoT) contains many devices that can compute and communicate, creating large networks. Industrial Internet of Things (IIoT) represents a developed application of IoT, connecting with embedded technologies in production in industrial operational settings to offer sophisticated automation and real-time decisions. Still, IIoT compels significant cybersecurity threats beyond jamming and spoofing, which could ruin the critical infrastructure. Developing a robust Intrusion Detection System (IDS) addresses the challenges and vulnerabilities present in these systems. Traditional IDS methods have achieved high detection accuracy but need improved scalability and privacy issues from large datasets. This paper proposes a Fog-enabled Federated Learning-based Intrusion Detection System (FFL-IDS) utilizing Convolutional Neural Network (CNN) that mitigates these limitations. This framework allows multiple parties in IIoT networks to train deep learning models with data privacy preserved and low-latency detection ensured using fog computing. The proposed FFL-IDS is validated on two datasets, namely the Edge-IIoTset, explicitly tailored to environments with IIoT, and CIC-IDS2017, comprising various network scenarios. On the Edge-IIoTset dataset, it achieved 93.4% accuracy, 91.6% recall, 88% precision, 87% F1 score, and 87% specificity for jamming and spoofing attacks. The system showed better robustness on the CIC-IDS2017 dataset, achieving 95.8% accuracy, 94.9% precision, 94% recall, 93% F1 score, and 93% specificity. These results establish the proposed framework as a scalable, privacy-preserving, high-performance solution for securing IIoT networks against sophisticated cyber threats across diverse environments.
Algorithmic Generation of Parameterized Geometric Models of the Aortic Valve and Left Ventricle
Authors: Pil Nikita , Kuchumov Alex G.
Published: December 2024

Simulating the cardiac valves is one of the most complex tasks in cardiovascular modeling. As fluid–structure interaction simulations are highly computationally demanding, machine-learning techniques can be considered a good alternative. Nevertheless, it is necessary to design many aortic valve geometries to generate a training set. A method for the design of a synthetic database of geometric models is presented in this study. We suggest using synthetic geometries that enable the development of several aortic valve and left ventricular models in a range of sizes and shapes. In particular, we developed 22 variations of left ventricular geometries, including one original model, seven models with varying wall thicknesses, seven models with varying heights, and seven models with varying shapes. To guarantee anatomical accuracy and physiologically acceptable fluid volumes, these models were verified using actual patient data. Numerical simulations of left ventricle contraction and aortic valve leaflet opening/closing were performed to evaluate the electro-physiological potential distribution in the left ventricle and wall shear stress distribution in aortic valve leaflets. The proposed synthetic database aims to increase the predictive power of machine-learning models in cardiovascular research and, eventually, improve patient outcomes after aortic valve surgery.
Research on Digital Terrain Construction Based on IMU and LiDAR Fusion Perception
Authors: Huang Chen , Wang Yiqi , Sun Xiaoqiang , Yang Shiyue
Published: December 2024

To address the shortcomings of light detection and ranging (LiDAR) sensors in extracting road surface elevation information in front of a vehicle, a scheme for digital terrain construction based on the fusion of an Inertial Measurement Unit (IMU) and LiDAR perception is proposed. First, two sets of sensor coordinate systems were configured, and the parameters of LiDAR and IMU were calibrated. Then, a terrain construction system based on the fusion perception of IMU and LiDAR was established, and improvements were made to the state estimation and mapping architecture. Terrain construction experiments were conducted in an academic setting. Finally, based on the output information from the terrain construction system, a moving average-like algorithm was designed to process point cloud data and extract the road surface elevation information at the vehicle’s trajectory position. By comparing the extraction effects of four different sliding window widths, the 4 cm width sliding window, which yielded the best results, was ultimately selected, making the extracted road surface elevation information more accurate and effective.
Instrumenting Parkrun: Usefulness and Validity of Inertial Sensors
Authors: Mason Rachel , Celik Yunus , Barry Gill , Godfrey Alan , Stuart Samuel
Published: December 2024

The analysis of running gait has conventionally taken place within an expensive and restricted laboratory space, with wearable technology offering a practical, cost-effective, and unobtrusive way to examine running gait in more natural environments. This pilot study presents a wearable inertial measurement unit (IMU) setup for the continuous analysis of running gait during an outdoor parkrun (i.e., 5 km). The study aimed to (1) provide analytical validation of running gait measures compared to time- and age-graded performance and (2) explore performance validation. Ten healthy adults (7 females, 3 males, mean age 37.2 ± 11.7 years) participated. The participants wore Axivity AX6 IMUs on the talus joint of each foot, recording tri-axial accelerometer and gyroscope data at 200 Hz. Temporal gait characteristics—gait cycle, ground contact time, swing time, and duty factor—were extracted using zero-crossing algorithms. The data were analyzed for correlations between the running performance, foot strike type, and fatigue-induced changes in temporal gait characteristics. Strong correlations were found between the performance time and both the gait cycle and ground contact time, with weak correlations for foot strike types. The analysis of asymmetry and fatigue highlighted modest changes in gait as fatigue increased, but no significant gender differences were found. This setup demonstrates potential for in-field gait analysis for running, providing insights for performance and injury prevention strategies.
Driving Intention Recognition of Electric Wheel Loader Based on Fuzzy Control
Authors: Chen Qihuai , Lin Yuanzheng , Xu Mingkai , Ren Haoling , Li Guanjie , Lin Tianliang
Published: December 2024

Energy conservation and emission reduction is a common concern in various industries. The construction process of electric wheel loaders has the advantages of being zero-emission and having a high energy efficiency, and has been widely recognized by the industry. The frequent shift in wheel loader working processes poses a serious challenge to the operator. Automatic shift is an effective way to improve the operator’s comfort and safety. The driving intention is an important input judgment condition to achieve efficient automatic shift. However, the current methods of vehicle driving intention recognition mainly focus on passenger cars. The working condition of the wheel loader is significantly different from that of the passenger car, with a high shifting frequency and severe load fluctuation. The driving intention recognition method of passenger cars is difficult to transplant directly. In this paper, aiming at the characteristics of wheel loader working conditions, a fuzzy recognition method based on fuzzy control is applied to driving intention recognition for electric wheel loaders. The throttle, throttle change rate and braking signals are used as inputs for recognizing the driving intention at the current moment of the whole machine. Five types of driving intentions, namely, rapid acceleration, normal acceleration, acceleration maintenance, deceleration and braking, are defined and recognized. In order to verify the effectiveness of the proposed method, simulation and experimental research are carried out. The results show that the proposed driving intention recognition method can effectively identify the driver’s intention and provide effective shift signal input for the wheel loader.
A Novel Real-Time Threshold Algorithm for Closed-Loop Epilepsy Detection and Stimulation System
Authors: Wang Liang-Hung , Zhang Zhen-Nan , Xie Chao-Xin , Jiang Hao , Yang Tao , Ran Qi-Peng , Fan Ming-Hui , Kuo I-Chun , Lee Zne-Jung , Chen Jian-Bo , Chen Tsung-Yi , Chen Shih-Lun , Abu Patricia Angela R.
Published: December 2024

Epilepsy, as a common brain disease, causes great pain and stress to patients around the world. At present, the main treatment methods are drug, surgical, and electrical stimulation therapies. Electrical stimulation has recently emerged as an alternative treatment for reducing symptomatic seizures. This study proposes a novel closed-loop epilepsy detection system and stimulation control chip. A time-domain detection algorithm based on amplitude, slope, line length, and signal energy characteristics is introduced. A new threshold calculation method is proposed; that is, the threshold is updated by means of the mean and standard deviation of four consecutive eigenvalues through parameter combination. Once a seizure is detected, the system begins to control the stimulation of a two-phase pulse current with an amplitude and frequency of 34 μA and 200 Hz, respectively. The system is physically designed on the basis of the UMC 55 nm process and verified by a field programmable gate array verification board. This research is conducted through innovative algorithms to reduce power consumption and the area of the circuit. It can maintain a high accuracy of more than 90% and perform seizure detection every 64 ms. It is expected to provide a new treatment for patients with epilepsy.
QuantumGS-Box—A Key-Dependent GA and QRNG-Based S-Box for High-Speed Cloud-Based Storage Encryption
Authors: Saini Anish , Tsokanos Athanasios , Kirner Raimund
Published: December 2024

Cloud computing has revolutionized the digital era by providing a more efficient, scalable, and cost-effective infrastructure. Secure systems that encrypt and protect data before it is transmitted over a network and stored in the cloud benefit the entire transmission process. Transmission data can be encrypted and protected with a secure dynamic substitution box (S-box). In this paper, we propose the QuantumGS-box, which is a dynamic S-box for high-speed cloud-based storage encryption generated by bit shuffling with a genetic algorithm and a quantum random number generator (QRNG). The proposed work generates the S-box optimized values in a dynamic way, and an experimental evaluation of the proposed S-box method has been conducted using several cryptographic criteria, including bit independence criteria, speed, non-linearity, differential and linear approximation probabilities, strict avalanche criteria and balanced output. The results demonstrate that the QuantumGS-box can enhance robustness, is resilient to differential and provide improved linear cryptoanalysis compared to other research works while assuring non-linearity. The characteristics of the proposed S-box are compared with other state of the art S-boxes to validate its performance. These characteristics indicate that the QuantumGS-box is a promising candidate for cloud-based storage encryption applications.
Optimizing Power Forecasting Models with Customized Features for Academic and Industrial Buildings
Authors: Cabezuelo David , Lopez-Ramirez Izar , Urkizu June , Goikoetxea Ander
Published: December 2024

Power consumption prediction is a crucial component in enhancing the efficiency and sustainability of building operations. This study investigates the impact of data collection frequency and model selection on the predictive accuracy of power consumption in two distinct building types: an Academic one with 15-min interval data and an Industrial one with hourly data. Various machine learning models, including Support Vector Machine (SVM) with Radial and Sigmoid kernels, Random Forest (RF), and Deep Neural Networks (DNNs), across different data splits and feature sets, were considered. Our analysis reveals that higher data collection frequency generally improves model performance, as indicated by lower RMSE, MAPE, and CV values, alongside higher R² scores. The inclusion of more historical power consumption features was also found to have a more significant impact on the accuracy of predictions than including climate condition features. Moreover, the SVM-Radial model consistently outperformed others, particularly in capturing complex, non-linear patterns in the data. However, the DNN model, while competent in some metrics, showed elevated MAPE values, suggesting potential overfitting issues. These findings suggest that careful consideration of data frequency, features, and model selection is essential for optimizing power prediction, contributing to more efficient power management strategies in building operations.
Probabilistic Causal Modeling of Barriers to Accessibility for Persons with Disabilities in Canada
Authors: Zakir Mouri , Wolbring Gregor , Yanushkevich Svetlana
Published: December 2024

This paper utilizes a methodological two-step process incorporating statistical and causal probabilistic modeling techniques to investigate factors affecting the accessibility experiences of persons with disabilities in Canada. We deploy a network-based approach using empirical data to perform a holistic assessment of the relations between various demographic features (e.g., age, gender and type of disability) and accessibility barriers. A statistical measurement method is applied that utilizes structural equation modeling supported by exploratory factor analysis. For causal probabilistic modeling, Bayesian networks are employed as a straightforward and compact way to interpret knowledge representation. This causal reasoning approach analyzes the nature and frequency of encountering barriers based on data to understand the risk factors contributing to pressing accessibility issues. Furthermore, to evaluate network performance and overcome any data limitations, synthetic data generation techniques are applied to create and validate artificial data built on real-world knowledge. The proposed framework strives to provide reasoning to understand the prevalence of physical, social, communication or technological barriers encountered by persons with disabilities in their daily lives. This study contributes to the identification of areas for prioritization in facilitating accessibility regulation and practices to realize an inclusive society.
Rebuilding Participatory Institutions in Brazil: The PPA Participativo Between Corporate Demands and Climate and Animal Rights
Authors: Delgado de Carvalho Priscila , Zanandrez Priscila , de Menezes Diego Matheus
Published: December 2024

In 2023, Brazil regained momentum in proposing innovative participatory institutions by launching a complex participatory experiment for budget planning within its “Multiannual Plan” (PPA). While this was not a scaled-up version of the local participatory budgeting plan that emerged decades earlier, its launch did reopen the debate on the possibilities of expanding political participation. The challenge was significant due to the intricate nature of budget planning and the complexity of the plan’s participatory design. This paper examines that experience by outlining the institutional design of the PPA Participativo and analyzing its results in terms of online participation. It also discusses the prominence of climate-related proposals, suggesting that the PPA Participativo serves as a relevant indicator of national concerns regarding climate-based issues. Building on previous experiences, the PPA Participativo is a strategy consisting of three layers: an online platform for digital participation, state-level meetings with civil society activists, and a high-level forum composed of members from national councils. This paper analyses some of the results from the online platform, which recorded 4 million visits from 1.5 million individual participants. These citizens were invited to submit proposals, vote for up to three proposals, and choose from a set of pre-designed government programs. The main concerns that emerged from this open-ended process included corporate demands, stemming from highly organized sectors, such as public health and education employees. However, animal rights also ranked among the most-voted proposals. The program of the Ministry of the Environment on climate change reached the top position in this segment, largely due to its strong campaigning strategy. This paper discusses these outcomes, drawing on evidence of both societal engagement and institutional activism to promote specific agendas.
Paving the Way for the Clean and Feasible Production of 2,5-Dimethylfuran
Authors: Russo Marco , Testa Maria Luisa
Published: December 2024

Biofuels have long been firmly established in the energy landscape in order to meet a considerable portion of the world’s energy demand and to contribute to the reduction in CO2 emissions [...]
Assessing the Influence of Business Intelligence and Analytics and Data-Driven Culture on Managerial Performance: Evidence from Romania
Authors: Hurbean Luminita , Militaru Florin , Munteanu Valentin Partenie , Danaiata Doina , Fotache Doina , Muntean Mihaela
Published: December 2024

Business intelligence and analytics (BI&A) have recently emerged as a strategic approach to managerial tasks, providing opportunities to improve work performance. Despite the growing interest in evaluating cases of BI&A adoption, to the best of our knowledge, few studies have addressed the influence of data-driven culture and the effects of BI&A adoption specifically on the work performance of managers. The aim of this study is to assess whether a data-driven culture predicts the adoption of BI&A in companies and its impact on decision-making effectiveness and managerial performance. This novel research model was tested with 180 managers from Romanian companies that work with BI&A tools. Based on PLS-SEM data analysis, our findings suggest that a data-oriented culture is a strong predictor of BI&A adoption and decision-making effectiveness. The results also confirm that BI&A utilization positively impacts decision-making effectiveness and individual work performance. The primary implication drawn from empirical evidence is that executives should prioritize the cultivation of a data-driven culture within their organizations, as this is essential for enhancing managerial performance through the adoption of business intelligence and analytics.
Assisting Hearing and Physically Impaired Students in Navigating Immersive Virtual Reality for Library Orientation
Authors: Ariya Pakinee , Yensathit Yakannut , Thongthip Phimphakan , Intawong Kannikar , Puritat Kitti
Published: December 2024

This study aims to design and develop a virtual reality platform (VR-ISLS) tailored to support hearing and physically impaired students at the university library for navigating and utilizing library services. By employing an immersive virtual environment, the platform replicates the physical setting of the university’s library to create a realistic experience that reduces anxiety and enhances familiarity. The platform integrates assistive technology functions, including sign language interpretation, customizable audio cues, vibration feedback, and various locomotion controls to meet the diverse needs of impaired students. The research methodology employs an iterative development process, incorporating feedback from library staff, disability support services, and students to ensure usability and accessibility. Evaluation of the platform using the System Usability Scale (SUS) and user feedback revealed a positive reception, with recommendations for further customization and enhanced assistive features to optimize the user experience. This study underscores the importance of inclusive design and continuous iteration in creating immersive virtual reality tools that provide significant benefits for persons with disabilities, enhancing both accessibility and learning experiences.
Application of Invasive Bacteria for the Delivery of Anti-Cancer Therapeutics
Authors: Akinsola Rasaq , Narayanan Kumaran
Published: December 2024

Bacterial vectors for biomolecule delivery to targeted organelles, facilitating temporary or continuous protein production, have emerged as a promising approach for treating acquired and inherited diseases. This method offers a selective cancer eradication and targeting strategy with minimal side effects. Bacterial vectors provide an alternative to viral gene delivery, given their capacity to deliver large genetic materials while inducing minimal immunogenicity and cytotoxicity. Bacteria such as Bifidobacterium, Salmonella, Clostridium, and Streptococcus have demonstrated potential for tumor-targeted biomolecule delivery or serve as oncolytic bacteria. These vectors have also been used to transfer and amplify genes encoding biomolecules such as pro-drug-converting enzymes, toxins, angiogenesis inhibitors, and cytokines. The microenvironment of necrotic tumors offers a unique opportunity for targeted therapy with the non-pathogenic anaerobic bacterium. For example, Clostridium sporogenes can germinate selectively in the necrotic regions upon injection as endospores, which helps to enhance the specificity of Clostridium sporogenes, resulting in tumor-specific colonization. Also, E. coli and Salmonella sp. can be capacitated with a hypoxic sensing promotor gene for specificity delivery into the core region of solid tumors. The uniqueness of the tumor microenvironment, including hypoxia, immunosuppression, metabolite deficiency or enrichment, and necrosis, selectively enables bacteria in the tumor. Combining traditional cancer therapy with bacterial therapy will significantly complement and cover the limitations of other treatments. This review provides an overview of the use of the bacteria vector in cancer therapy, discussing strategies to maximize delivery efficiency and address potential challenges. In this review, we discuss the potential of bacteria vectors as anti-cancer therapeutics while focusing on therapeutic delivery strategies. We highlight the complementary use of bacteria therapy with other cancer therapies and the mechanism of bacteria cancer immunotherapy with limitations and perspectives for future use.
Toxic Effects of Lead Exposure on Freshwater Climbing Perch, Anabas testudineus, and Bioremediation Using Ocimum sanctum Leaf Powder
Authors: Saha Nimai Chandra , Chatterjee Arnab , Banerjee Priyajit , Bhattacharya Ritwick , Sadhu Auroshree , Pastorino Paolo , Saha Shubhajit
Published: December 2024

The acute and chronic toxicity of lead to Anabas testudineus was determined in this study using static replacement bioassay testing. During the chronic toxicity studies, an experiment on the bioremediation of lead toxicity using Ocimum sanctum leaf powder was conducted. The 96 h LC50 values of lead for Anabas testudineus was 1.08 mg/L. Different biomarkers, such as the hepatosomatic index, gonadosomatic index, and fecundity, were significantly lower in fish subjected to 10% and 20% of the 96 h LC50 values of lead, compared to controls. The 45-day chronic exposure of fish to lead concentrations of 0.2 mg/L and above significantly lowered the number of total RBC, hemoglobin content, HCT (%), plasma protein, and cholesterol while decreasing the level of total WBC, plasma glucose, creatinine, serum AST and serum ALT. The leaf powder of Ocimum sanctum plays a significant role in ameliorating lead toxicity.
Density Functional Theory Insight in Photocatalytic Degradation of Dichlorvos Using Covalent Triazine Frameworks Modified by Various Oxygen-Containing Acid Groups
Authors: Yu Shouxi , Wang Zhongliao
Published: December 2024

Dichlorvos (2,2-dichlorovinyl dimethyl phosphate, DDVP) is a highly toxic organophosphorus insecticide, and its persistence in air, water, and soil poses potential threats to human health and ecosystems. Covalent triazine frameworks (CTFs), with their sufficient visible-light harvesting capacity, ameliorated charge separation, and exceptional redox ability, have emerged as promising candidates for the photocatalytic degradation of DDVP. Nevertheless, pure CTFs lack effective oxidative active sites, resulting in elevated reaction energy barriers during the photodegradation of DDVP. In this work, density functional theory (DFT) calculations were employed to investigate the impact of various oxygen-containing acid groups (-COOH, -HSO3, -H2PO3) on DDVP photodegradation performance. First, simulations of the structure and optical properties of modified CTFs reveal that oxygen-containing acid groups induce surface distortion and result in a redshift in the absorption edge. Subsequently, analysis of the density of states, frontier molecular orbitals, surface electrostatic potential, work function, and dipole moment demonstrates that oxygen-containing acid groups enhance CTF polarization, facilitate charge separation, and ameliorate their oxidative capability. Additionally, the free-energy diagram of DDVP degradation uncovers that oxygen-containing acid groups lower the energy barrier by elevating the adsorption and activation capability of DDVP. Notably, -H2PO3 presents optimal potential for the photodegradation of DDVP by unique electronic structure and activation capability. This work offers a valuable reference for the development of oxygen-containing acid CTF-based photocatalysts applied in degrading toxic organophosphate pesticides.
Long-Term Variation Characteristics and Health Risks of Atmospheric Hg in the Largest City in Northwestern China
Authors: Pang Yuqi , Xu Hongmei , Yang Mengyun , Zhang Bin , Liu Liyan , Chen Sulin , Xue Jing , Zhang Hui , Shen Zhenxing
Published: December 2024

In this study, gaseous element mercury (GEM) and gaseous oxidized mercury (GOM) in the atmosphere were continuously observed at a minute resolution from 1 April 2019 to 31 December 2020 in urban Xi’an, the largest central city in Northwestern China. The concentrations of GEM and GOM drastically fluctuated within the ranges of 0.022–297 ng/m3 and 0.092–381 pg/m3, showing average values of 5.78 ± 7.36 ng/m3 and 14.2 ± 20.8 pg/m3, respectively. GEM and GOM showed a decreasing trend of 0.121 ng/m3 and 0.472 pg/m3 per month, respectively, which we believe was mainly caused by anthropogenic sources, especially by a reduction in coal-fired emissions, rather than meteorological factors. The significant positive correlation between GEM and PM2.5, SO2, NO2, and CO, as well as Cr, As, and Pb in PM2.5 also proves that. GEM showed a higher concentration at nighttime than daytime, while an M-shaped diurnal trend was observed for GOM. The hazard quotient of GEM for both males and females decreased at a rate of 0.003 per month, and children aged 2–5 were more sensitive to non-carcinogenic health risks. The changing trends, controlling factors, and human health risks of Hg in the atmosphere are necessary and crucial to study for improving our understanding of the impacts of Hg in Northwestern China.