bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal decoding of neural dynamics occurs at mesoscale spatial and temporal resolutions
Authors: Samiei Toktam , Zou Zhuowen , Imani Mohsen , Nozari Erfan
Published: February 2024

Introduction

Understanding the neural code has been one of the central aims of neuroscience research for decades. Spikes are commonly referred to as the units of information transfer, but multi-unit activity (MUA) recordings are routinely analyzed in aggregate forms such as binned spike counts, peri-stimulus time histograms, firing rates, or population codes. Various forms of averaging also occur in the brain, from the spatial averaging of spikes within dendritic trees to their temporal averaging through synaptic dynamics. However, how these forms of averaging are related to each other or to the spatial and temporal units of information representation within the neural code has remained poorly understood.

Materials and methods

In this work we developed NeuroPixelHD, a symbolic hyperdimensional model of MUA, and used it to decode the spatial location and identity of static images shown to n = 9 mice in the Allen Institute Visual Coding—NeuroPixels dataset from large-scale MUA recordings. We parametrically varied the spatial and temporal resolutions of the MUA data provided to the model, and compared its resulting decoding accuracy.

Results

For almost all subjects, we found 125ms temporal resolution to maximize decoding accuracy for both the spatial location of Gabor patches (81 classes for patches presented over a 9×9 grid) as well as the identity of natural images (118 classes corresponding to 118 images) across the whole brain. This optimal temporal resolution nevertheless varied greatly between different regions, followed a sensory-associate hierarchy, and was significantly modulated by the central frequency of theta-band oscillations across different regions. Spatially, the optimal resolution was at either of two mesoscale levels for almost all mice: the area level, where the spiking activity of all neurons within each brain area are combined, and the population level, where neuronal spikes within each area are combined across fast spiking (putatively inhibitory) and regular spiking (putatively excitatory) neurons, respectively. We also observed an expected interplay between optimal spatial and temporal resolutions, whereby increasing the amount of averaging across one dimension (space or time) decreases the amount of averaging that is optimal across the other dimension, and vice versa.

Discussion

Our findings corroborate existing empirical practices of spatiotemporal binning and averaging in MUA data analysis, and provide a rigorous computational framework for optimizing the level of such aggregations. Our findings can also synthesize these empirical practices with existing knowledge of the various sources of biological averaging in the brain into a new theory of neural information processing in which the unit of information varies dynamically based on neuronal signal and noise correlations across space and time.
Transcranial magnetic stimulation therapy for central post-stroke pain: systematic review and meta-analysis
Authors: Gurdiel-Álvarez Francisco , Navarro-López Víctor , Varela-Rodríguez Sergio , Juárez-Vela Raúl , Cobos-Rincón Ana , Sánchez-González Juan Luis
Published: February 2024

Introduction

Although rare, central post-stroke pain remains one of the most refractory forms of neuropathic pain. It has been reported that repetitive transcranial magnetic stimulation (rTMS) may be effective in these cases of pain.

Aim

The aim of this study was to investigate the efficacy of rTMS in patients with central post-stroke pain (CPSP).

Methods

We included randomized controlled trials or Controlled Trials published until October 3rd, 2022, which studied the effect of rTMS compared to placebo in CPSP. We included studies of adult patients (>18 years) with a clinical diagnosis of stroke, in which the intervention consisted of the application of rTMS to treat CSP.

Results

Nine studies were included in the qualitative analysis; 6 studies (4 RCT and 2 non-RCT), with 180 participants, were included in the quantitative analysis. A significant reduction in CPSP was found in favor of rTMS compared with sham, with a large effect size (SMD: −1.45; 95% CI: −1.87; −1.03; p < 0.001; I2: 58%).

Conclusion

The findings of the present systematic review with meta-analysis suggest that there is low quality evidence for the effectiveness of rTMS in reducing CPSP.

Systematic review registration

Identifier (CRD42022365655).
COVID-19 reinfections in Mexico City: implications for public health
Authors: de Anda-Jáuregui Guillermo , Gómez-Romero Laura , Cañas Sofía , Campos-Romero Abraham , Alcántar-Fernández Jonathan , Cedro-Tanda Alberto
Published: February 2024

Background

Since its appearance, COVID-19 has immensely impacted our society. Public health measures, from the initial lockdowns to vaccination campaigns, have mitigated the crisis. However, SARS-CoV-2’s persistence and evolving variants continue to pose global threats, increasing the risk of reinfections. Despite vaccination progress, understanding reinfections remains crucial for informed public health responses.

Methods

We collected available data on clinical and genomic information for SARS-CoV-2 samples from patients treated in Mexico City from 2020 epidemiological week 10 to 2023 epidemiological week 06 encompassing the whole public health emergency’s period. To identify clinical data we utilized the SISVER (Respiratory Disease Epidemiological Surveillance System) database for SARS-CoV-2 patients who received medical attention in Mexico City. For genomic surveillance we analyzed genomic data previously uploaded to GISAID generated by Mexican institutions. We used these data sources to generate descriptors of case number, hospitalization, death and reinfection rates, and viral variant prevalence throughout the pandemic period.

Findings

The fraction of reinfected individuals in the COVID-19 infected population steadily increased as the pandemic progressed in Mexico City. Most reinfections occurred during the fifth wave (40%). This wave was characterized by the coexistence of multiple variants exceeding 80% prevalence; whereas all other waves showed a unique characteristic dominant variant (prevalence >95%). Shifts in symptom patient care type and severity were observed, 2.53% transitioned from hospitalized to ambulatory care type during reinfection and 0.597% showed the opposite behavior; also 7.23% showed a reduction in severity of symptoms and 6.05% displayed an increase in severity. Unvaccinated individuals accounted for the highest percentage of reinfections (41.6%), followed by vaccinated individuals (31.9%). Most reinfections occurred after the fourth wave, dominated by the Omicron variant; and after the vaccination campaign was already underway.

Interpretation

Our analysis suggests reduced infection severity in reinfections, evident through shifts in symptom severity and care patterns. Unvaccinated individuals accounted for most reinfections. While our study centers on Mexico City, its findings may hold implications for broader regions, contributing insights into reinfection dynamics.
Changes in self-reported health and wellbeing outcomes in 36,951 primary school children from 2014 to 2022 in Wales: an analysis using annual survey data
Authors: Einhorn Johanna , James Michaela , Kennedy Natasha , Marchant Emily , Brophy Sinead
Published: February 2024

Introduction

This study examines the changes in childhood self-reported health and wellbeing between 2014 and 2022.

Methods

An annual survey delivered by HAPPEN-Wales, in collaboration with 500 primary schools, captured self-reported data on physical health, dietary habits, mental health, and overall wellbeing for children aged 8–11 years.

Results

The findings reveal a decline in physical health between 2014 and 2022, as evidenced by reduced abilities in swimming and cycling. For example, 68% of children (95%CI: 67%–69%) reported being able to swim 25m in 2022, compared to 85% (95% CI: 83%–87%) in 2018. Additionally, unhealthy eating habits, such as decreased fruit and vegetable consumption and increased consumption of sugary snacks, have become more prevalent. Mental health issues, including emotional and behavioural difficulties, have also increased, with emotional difficulties affecting 13%–15% of children in 2017–2018 and now impacting 29% of children in 2021–2022. Moreover, indicators of wellbeing, autonomy, and competence have declined.

Discussion

Importantly, this trend of declining health and wellbeing predates the onset of the Covid-19 pandemic, suggesting that it is not solely attributed to the pandemic’s effects. The health of primary school children has been on a declining trajectory since 2018/2019 and has continued to decline through the COVID recovery period. The study suggests that these trends are unlikely to improve without targeted intervention and policy focus.
Isolation and characterization of saprophytic and pathogenic strains of Leptospira from water sources in the Midwestern United States
Authors: Hamond Camila , LeCount Karen , Anderson Tammy , Putz Ellie J. , Stuber Tod , Hicks Jessica , Camp Patrick , van der Linden Hans , Bayles Darrell O. , Schlater Linda K. , Nally Jarlath E.
Published: February 2024

The genus Leptospira is a diverse and unique group of bacteria comprising multiple saprophytic and pathogenic species, which survive and persist in suitable moist environments. Pathogenic species cause human and animal leptospirosis, a global and neglected zoonotic disease. Disease transmission occurs by exposure to contaminated water and moist soil environments or by contact with domestic animals and wildlife acting as reservoir hosts that shed Leptospira via urine. Here, we describe the unexpected diversity of saprophytic and pathogenic species of Leptospira isolated from water in the Midwestern United States. Samples were collected by volunteers in 11 counties in Iowa from water sources, including puddles, sewage, creeks, ponds, lakes, and rivers, during the summer of 2021. One hundred and five water samples were tested by culture for the presence of saprophytic and pathogenic species and by lipL32 qPCR specific for the detection of pathogens; 82 (78.1%) were culture positive and five (4.8%) were positive by lipL32 qPCR. Whole genome sequencing of isolates cultured from water samples identified 10 species of saprophytes, namely L. montravelensis, L. kemamanensis, L. bandrabouensis, L. bourretii, L. bouyouniensis, L. chreensis, L. ellinghausenii, L. terpstrae, L. yanagawae, and L. abararensis, as well as three novel saprophytic species. Whole genome sequencing also identified two novel pathogenic species. The remaining cultures comprised mixed populations of saprophytic species and six comprised a mixture of saprophytic and pathogenic species. One of these mixed cultures was enriched to select for a clonal isolate of pathogenic Leptospira, strain WS101.C1, which was classified as L. interrogans serogroup Djasiman serovar Djasiman. Cumulatively, 9.5% (10/105) of water samples were positive for pathogenic Leptospira. This study emphasizes the diversity of Leptospira present in water sources in the Midwestern United States and provides unique opportunities to explore the geographic diversity and evolution of this genus. The identification of known and novel pathogenic species circulating in local water sources highlights their potential usefulness as diagnostic antigens, as well as the role of water in the transmission of infection to human and animal populations. Integrating knowledge on human, animal, and environmental health is essential to control and predict risk for zoonoses.
Trichoderma Biocontrol Performances against Baby-Lettuce Fusarium Wilt Surveyed by Hyperspectral Imaging-Based Machine Learning and Infrared Thermography
Authors: Manganiello Gelsomina , Nicastro Nicola , Ortenzi Luciano , Pallottino Federico , Costa Corrado , Pane Catello
Published: February 2024

Fusarium oxysporum f. sp. lactucae is one of the most aggressive baby-lettuce soilborne pathogens. The application of Trichoderma spp. as biocontrol agents can minimize fungicide treatments and their effective targeted use can be enhanced by support of digital technologies. In this work, two Trichoderma harzianum strains achieved 40–50% inhibition of pathogen radial growth in vitro. Their effectiveness in vivo was surveyed by assessing disease incidence and severity and acquiring hyperspectral and thermal features of the canopies being treated. Infected plants showed a reduced light absorption in the green and near-red regions over time, reflecting the disease progression. In contrast, Trichoderma-treated plant reflectance signatures, even in the presence of the pathogen, converged towards the healthy control values. Seventeen vegetation indices were selected to follow disease progression. The thermographic data were informative in the middle–late stages of disease (15 days post-infection) when symptoms were already visible. A machine-learning model based on hyperspectral data enabled the early detection of the wilting starting from 6 days post-infection, and three different spectral regions sensitive to baby-lettuce wilting (470–490 nm, 740–750 nm, and 920–940 nm) were identified. The obtained results pioneer an effective AI-based decision support system (DSS) for crop monitoring and biocontrol-based management.
Enhancing SPARQL Query Generation for Knowledge Base Question Answering Systems by Learning to Correct Triplets
Authors: Qi Jiexing , Su Chang , Guo Zhixin , Wu Lyuwen , Shen Zanwei , Fu Luoyi , Wang Xinbing , Zhou Chenghu
Published: February 2024

Generating SPARQL queries from natural language questions is challenging in Knowledge Base Question Answering (KBQA) systems. The current state-of-the-art models heavily rely on fine-tuning pretrained models such as T5. However, these methods still encounter critical issues such as triple-flip errors (e.g., (subject, relation, object) is predicted as (object, relation, subject)). To address this limitation, we introduce TSET (Triplet Structure Enhanced T5), a model with a novel pretraining stage positioned between the initial T5 pretraining and the fine-tuning for the Text-to-SPARQL task. In this intermediary stage, we introduce a new objective called Triplet Structure Correction (TSC) to train the model on a SPARQL corpus derived from Wikidata. This objective aims to deepen the model’s understanding of the order of triplets. After this specialized pretraining, the model undergoes fine-tuning for SPARQL query generation, augmenting its query-generation capabilities. We also propose a method named “semantic transformation” to fortify the model’s grasp of SPARQL syntax and semantics without compromising the pre-trained weights of T5. Experimental results demonstrate that our proposed TSET outperforms existing methods on three well-established KBQA datasets: LC-QuAD 2.0, QALD-9 plus, and QALD-10, establishing a new state-of-the-art performance (95.0% F1 and 93.1% QM on LC-QuAD 2.0, 75.85% F1 and 61.76% QM on QALD-9 plus, 51.37% F1 and 40.05% QM on QALD-10).
Structural and Functional Insights into CRF Peptides and Their Receptors
Authors: Matsoukas Minos-Timotheos , Panagiotopoulos Vasilis , Karageorgos Vlasios , Chrousos George P. , Venihaki Maria , Liapakis George
Published: February 2024

Corticotropin-releasing factor or hormone (CRF or CRH) and the urocortins regulate a plethora of physiological functions and are involved in many pathophysiological processes. CRF and urocortins belong to the family of CRF peptides (CRF family), which includes sauvagine, urotensin, and many synthetic peptide and non-peptide CRF analogs. Several of the CRF analogs have shown considerable therapeutic potential in the treatment of various diseases. The CRF peptide family act by interacting with two types of plasma membrane proteins, type 1 (CRF1R) and type 2 (CRF2R), which belong to subfamily B1 of the family B G-protein-coupled receptors (GPCRs). This work describes the structure of CRF peptides and their receptors and the activation mechanism of the latter, which is compared with that of other GPCRs. It also discusses recent structural information that rationalizes the selective binding of various ligands to the two CRF receptor types and the activation of receptors by different agonists.
Deep Learning-Based Detection of Learning Disorders on a Large Scale Dataset of Eye Movement Records
Authors: El Hmimdi Alae Eddine , Kapoula Zoï , Sainte Fare Garnot Vivien
Published: February 2024

Early detection of dyslexia and learning disorders is vital for avoiding a learning disability, as well as supporting dyslexic students by tailoring academic programs to their needs. Several studies have investigated using supervised algorithms to screen dyslexia vs. control subjects; however, the data size and the conditions of data acquisition were their most significant limitation. In the current study, we leverage a large dataset, containing 4243 time series of eye movement records from children across Europe. These datasets were derived from various tests such as saccade, vergence, and reading tasks. Furthermore, our methods were evaluated with realistic test data, including real-life biases such as noise, eye tracking misalignment, and similar pathologies among non-scholar difficulty classes. In addition, we present a novel convolutional neural network architecture, adapted to our time series classification problem, that is intended to generalize on a small annotated dataset and to handle a high-resolution signal (1024 point). Our architecture achieved a precision of 80.20% and a recall of 75.1%, when trained on the vergence dataset, and a precision of 77.2% and a recall of 77.5% when trained on the saccade dataset. Finally, we performed a comparison using our ML approach, a second architecture developed for a similar problem, and two other methods that we investigated that use deep learning algorithms to predict dyslexia.
Finger Prosthesis Driven by DEA Pairs as Agonist–Antagonist Artificial Muscles
Authors: da Silva Alexandre B. S. , Mendes Gabriel E. P. , Bragato Eduardo S. , Novelli Guilherme L. , Monjardim Marina , Andrade Rafhael M.
Published: February 2024

Loss of an upper limb exerts a negative influence on an individual’s ability to perform their activities of daily living (ADLs), reducing quality of life and self-esteem. A prosthesis capable of performing basic ADLs functions has the capability of restoring independence and autonomy to amputees. However, current technologies present in robotic prostheses are based on rigid actuators with several drawbacks, such as high weight and low compliance. Recent advances in robotics have allowed for the development of flexible actuators and artificial muscles to overcome the limitations of rigid actuators. Dielectric elastomer actuators (DEAs) consist of a thin elastomer membrane arranged between two compliant electrodes capable of changing dimensions when stimulated with an electrical potential difference. In this work, we present the design and testing of a finger prosthesis driven by two DEAs arranged as agonist–antagonist pairs as artificial muscles. The soft actuators are designed as fiber-constrained dielectric elastomers (FCDE), enabling displacement in just one direction as natural muscles. The finger prosthesis was designed and modeled to show bend movement using just one pair of DEAs and was made of PLA in an FDM 3D printer to be lightweight. The experimental results show great agreement with the proposed model and indicate that the proposed finger prosthesis is promising in overcoming the limitations of the current rigid based actuators.
Lamellar Septa-like Structured Carbonate Apatite Scaffolds with Layer-by-Layer Fracture Behavior for Bone Regeneration
Authors: Taleb Alashkar Ahmad Nazir , Hayashi Koichiro , Ishikawa Kunio
Published: February 2024

Generally, ceramics are brittle, and porosity is inversely correlated with strength, which is one of the challenges of ceramic scaffolds. Here, we demonstrate that lamellar septum-like carbonate apatite scaffolds have the potential to overcome these challenges. They were fabricated by exploiting the cellular structure of the cuttlebone, removing the organic components from the cuttlebone, and performing hydrothermal treatment. Scanning electron microscopy revealed that the scaffolds had a cellular structure with walls between lamellar septa. The interwall and interseptal sizes were 80–180 and 300–500 μm, respectively. The size of the region enclosed by the walls and septa coincided with the macropore size detected by mercury intrusion porosimetry. Although the scaffold porosity was extremely high (93.2%), the scaffold could be handled without disintegration. The compressive stress–strain curve demonstrated that the scaffolds showed layer-by-layer fracture behavior, which seemed beneficial for avoiding catastrophic failure under impact. When the scaffolds were implanted into rabbit femurs, new bone and blood vessels formed within the scaffold cells at 4 weeks. At 12 weeks, the scaffolds were almost entirely replaced with new bone. Thus, the lamellar septum-like cellular-structured carbonate apatite is a promising scaffold for achieving early bone regeneration and compression resistance.
Performance Assessments of Plastering Mortars with Partial Replacement of Aggregates with Glass Waste
Authors: Vălean Maria , Manea Daniela Lucia , Aciu Claudiu , Popa Florin , Pleșa Luminița Monica , Jumate Elena , Furtos Gabriel
Published: February 2024

The rising concern for the environment and the need for a sustainable economic model has stimulated experimentation in the field of construction materials, notably in replacing certain components from cementitious materials with construction and demolition waste. The main objective of this study is to replace a significant proportion of natural aggregates with glass waste, in the composition of plastering mortars, and to observe the evolution of physical–mechanical characteristics in the fresh state: apparent density, consistency, and segregation tendency, and in the hardened state: apparent density, flexural strength, compression strength, and adhesion to the substrate, across time, at 3, 7, 14, and 28 days. SEM and EDX tests were also performed to observe the microscopical characteristics. The experimental program studied four types of plastering mortars: the reference mortar—CS IV, and three mortars in which aggregates have been replaced with glass waste in the following proportions, by mass: 15%, 30%, and 45%. Results obtained on fresh properties (apparent density and consistency) indicate a decrease in values as the percentage of glass increases, with the exception of the mortar with 30% aggregated glass replacement. The flexural strength and the compressive strength were improved by replacing 30% of the aggregates with glass waste and were not significantly impacted by a replacement of 15%. Mechanical properties decreased at a replacement level of 45%. All glass aggregate mortars had lower adhesion strength to the brick substrate than the reference mortar by up to 70%. SEM and EDX analyses showed the morphology of the studied mortars and the processes taking place to increase mechanical strength. Further research directions are proposed, including studying the glass particles, the occurrence of alkali–silica reactions, durability, and improvement of adhesion to the substrate, for progressing towards the most viable, locally sourced, waste-containing plastering mortar.
Non-Destructive Evaluation of Material Stiffness beneath Pile Foundations Tip Using Harmonic Wavelet Transform
Authors: Oh Hyun-Ju , Park Jung-Hoon , Park Hyung-Choon
Published: February 2024

Pile foundations are used to support superstructures and play an important role in the safety of these structures. The performance of pile foundations generally depends on the conditions of the pile itself and the material under the pile tip(i.e., bottom), especially for end-bearing piles installed in soft soil volumes. Therefore, to assess the performance of existing pile foundations, it is crucial not only to evaluate the structural integrity of the pile itself, but also to assess the ground conditions, such as subsoil stiffness beneath the pile foundation tip. Accessing the subsoil beneath the pile foundation tip is highly challenging in the field. Hence, there is a need for the development of non-destructive pile evaluation methods that allow the assessment of subsoil stiffness beneath the pile tip without direct access to the subsoil. Various non-destructive methods have been developed for pile performance assessment. However, these conventional non-destructive methods are primarily designed for assessing the structural integrity of the pile itself, and there are no existing non-destructive pile integrity testing methods applicable to evaluate the subsoil stiffness beneath the pile tip. In this study, a non-destructive method is developed to evaluate the subsurface soil stiffness beneath pile tip without direct access. The proposed method involves applying impact loading to the easily accessible pile head and measuring the elastic waves propagated within the pile foundation due to the impact loading. These wave signals are then recorded at the pile head. The measured time–history signals are decomposed using harmonic wavelet transform. This allows the obtainment of well-defined magnitude and phase information over time for various individual frequency components composing the wave. In this study, a method is proposed to assess the stiffness of the subsoil beneath the pile tip by simultaneously utilizing the magnitude and phase information of the measured signals obtained through harmonic wavelet transform. To facilitate this, a step-by-step data analysis procedure for evaluating the subsoil stiffness beneath the pile tip is introduced. To validate the proposed method, numerical simulations were conducted using ABAQUS. The experimental data obtained from the numerical simulations were processed using the proposed method to assess the subsoil stiffness beneath the pile. The determined subsoil stiffness was then compared with the exact soil stiffness used in the numerical simulation to evaluate the validity of the proposed method. Through this analysis, the proposed method demonstrated its effectiveness in assessing the subsoil stiffness beneath piles tip installed in weak soil volume.
Analysis of Influencing Factors on Solid Waste Generation of Public Buildings in Tropical Monsoon Climate Region
Authors: Meng Tingwei , Shan Xiaofang , Ren Zhigang , Deng Qinli
Published: February 2024

Environmental problems including the depletion of natural resources and energy have drawn a lot of attention from all sectors of society in the context of high-quality global development, and solid waste generated by the construction industry accounts for 36% of the total amount of municipal waste. The generation of large amounts of construction waste not only causes a waste of resources, but also causes great damage to the environment. Reducing the quantity of solid waste produced during a building’s new construction period can be greatly aided by construction site solid waste statistics and forecasts. Based on the statistical data of 61 public construction projects in Hainan Province, China, this study uses the Random Forest algorithm to rank the importance of possible factors affecting the amount of solid waste generated, and linearly fits the data to achieve the prediction of solid waste at construction sites. The findings indicate that building area, building height, concrete usage, steel usage and assembly rate are the main factors affecting solid waste in construction sites. In office buildings and exhibition buildings, an increase in ground area, building height, concrete usage, and steel usage increases the generation of each type of solid waste (inorganic non-metallic solid waste, metallic solid waste), with the exception of an increase in concrete usage, which results in a decrease in the generation of metallic solid waste. Furthermore, a higher assembly rate can substantially lower the production of all waste types. These results offer a theoretical foundation for the implementation of assembly construction to support the high-quality development of the construction industry, as well as partial design inspiration for the architectural design stage.
Epigallocatechin-3-gallate Synergistically Enhanced Arecoline-Induced Cytotoxicity by Redirecting Cycle Arrest to Apoptosis
Authors: Shih Li-Jane , Hsu Po-Chi , Chuu Chih-Pin , Shui Hao-Ai , Yeh Chien-Chih , Chen Yueh-Chung , Kao Yung-Hsi
Published: February 2024

Carcinogens, such as arecoline, play a crucial role in cancer progression and continuous gene mutations by generating reactive oxygen species (ROS). Antioxidants can reduce ROS levels and potentially prevent cancer progression but may paradoxically enhance the survival of cancer cells. This study investigated whether epigallocatechin-3-gallate (EGCG), an antioxidant from green tea, could resolve this paradox. Prostate cancer cells (PC-3 cell line) were cultured and treated with arecoline combined with NAC (N-acetylcysteine) or EGCG; the combined effects on intracellular ROS levels and cell viability were examined using the MTT and DCFDA assays, respectively. In addition, apoptosis, cell cycle, and protein expression were investigated using flow cytometry and western blot analysis. Our results showed that EGCG, similar to NAC (N-acetylcysteine), reduced the intracellular ROS levels, which were elevated by arecoline. Moreover, EGCG not only caused cell cycle arrest but also facilitated cell apoptosis in arecoline-treated cells in a synergistic manner. These were evidenced by elevated levels of cyclin B1 and p27, and increased fragmentation of procaspase-3, PARP, and DNA. Our findings highlight the potential use of EGCG for cancer prevention and therapy.
Post-Disaster Emergency Communications Enhanced by Drones and Non-Orthogonal Multiple Access: Three-Dimensional Deployment Optimization and Spectrum Allocation
Authors: Li Linyang , Zhu Lijun , Huang Fanghui , Wang Dawei , Li Xin , Wu Tong , He Yixin
Published: February 2024

Integrating the relaying drone and non-orthogonal multiple access (NOMA) technique into post-disaster emergency communications (PDEComs) is a promising way to accomplish efficient network recovery. Motivated by the above, by optimizing the drone three-dimensional (3D) deployment optimization and spectrum allocation, this paper investigates a quality of service (QoS)-driven sum rate maximization problem for drone-and-NOMA-enhanced PDEComs that aims to improve the data rate of cell edge users (CEUs). Due to the non-deterministic polynomial (NP)-hard characteristics, we first decouple the formulated problem. Next, we obtain the optimal 3D deployment with the aid of a long short-term memory (LSTM)-based recurrent neural network (RNN). Then, we transform the spectrum allocation problem into an optimal matching issue, based on which the Hungarian algorithm is employed to solve it. Finally, the simulation results show that the presented scheme has a significant performance improvement in the sum rate compared with the state-of-the-art works and benchmark scheme. For instance, by adopting the NOMA technique, the sum rate can be increased by 9.72% and the needs of CEUs can be satisfied by enabling the relaying drone. Additionally, the convergence, complexity, and performance gap caused by iterative optimization are discussed and analyzed.
Assessing the Quantitative Risk of Urban Hydrogen Refueling Station in Seoul, South Korea, Using SAFETI Model
Authors: Kwak Hyunjun , Kim Minji , Min Mimi , Park Byoungjik , Jung Seungho
Published: February 2024

Hydrogen refueling stations (HRS) operating at high pressures pose a higher risk of leakage than conventional gas stations. Therefore, in this study, a quantitative risk assessment (QRA) was conducted using DNV-GL SAFETI v.8.9. The impact of the shutoff valve was quantitatively assessed, and step-by-step mitigation was applied to propose the minimum installation requirements for the valve necessary to achieve broadly acceptable risk levels. The QRA includes sequence analysis (CA), individual risk (IR), and societal risk (SR), with accident scenarios consisting of catastrophic ruptures and three leak scenarios. The research results indicate that the application of a dual shutoff valve system resulted in an IR of 7.48 × 10−5, effectively controlling the risk below the as low as reasonably practicable (ALARP) criteria of the Health and Safety Executive (HSE). The SR was analyzed based on the ALARP criteria in the Netherlands, and the application of the dual shutoff valve system effectively controlled the risk below the ALARP criteria. Consequently, this study suggests that applying a dual shutoff valve system with a mitigation value exceeding 1.21 × 10−2 can successfully mitigate the risk of urban hydrogen refueling stations to broadly acceptable levels.
Design, Detection, and Countermeasure of Frequency Spectrum Attack and Its Impact on Long Short-Term Memory Load Forecasting and Microgrid Energy Management
Authors: Nazeri Amirhossein , Biroon Roghieh , Pisu Pierluigi , Schoenwald David
Published: February 2024

This paper introduces a frequency-domain false data injection attack called Frequency Spectrum Attack (FSA) and explores its effects on load forecasting and the energy management system (EMS) in a microgrid. The FSA analyzes time-series signals in the frequency domain to identify patterns in their frequency spectrum. It learns the distribution of dominant frequencies in a dataset of healthy signals. Subsequently, it manipulates the amplitudes of dominant frequencies within this healthy distribution, ensuring a stealthy attack against statistical analysis of the signal spectrum. We evaluated the performance of FSA on LSTM, a state-of-the-art network for load forecasting. The results show that FSA can triple the Mean Absolute Error (MAE) of predictions compared to the normal case and increase it by 70% compared to noise injection attacks. Furthermore, FSA indirectly enhances battery utilization in the EMS by 45%. We then proposed a detection method that combines statistical analysis and machine-learning-based classification techniques with features. The model effectively distinguishes FSA from healthy and noisy signals, achieving an accuracy of 98.7% and an F1-score of 98.1% on a load dataset, covering healthy, FSA, and noisy load data. Finally, a countermeasure was introduced based on the statistical analysis of the frequency spectrum of healthy signals to mitigate the impact of FSA. This countermeasure successfully reduces the MAE of the attacked model from 0.135 to 0.053, validating its effectiveness in mitigating FSA.
Fully Coupled Whole-Annulus Investigation of Combustor–Turbine Interaction with Reacting Flow
Authors: Wang Heyu , Luo Kai Hong
Published: February 2024

Micro-gas turbines are used for power generation and propulsion in unmanned aerial vehicles. Technological advancements to enhance their efficiency and fuel adaptability are continuously sought out. As part of a comprehensive study focused on understanding the fundamental performance and emission characteristics of a micro gas turbine model, with the aim of finding ways to enhance the operation of micro gas turbines, the current study uses a fully coupled whole-annulus simulation approach to systematically explore the combustor–turbine interaction without compromising the accuracy due to domain truncation. The numerical model is highly complex, spanning aerothermodynamics, fuel vaporization, combustion, and multi-species flow transport. Coupled with the realistic geometries of a representative micro-gas turbine, the proposed numerical model is highly accurate with the capability to capture the complex interaction between the flowfield and the aerothermodynamics and emission performances. The results show that unburnt gaseous Jet-A fuel is carried into the turbine domain through vortical flow structures originating from the combustion chamber. Notably, combustion processes persist within the turbine, leading to rapid Jet-A fuel concentration decay and linearly increasing soot concentration across the turbine domain. The relative circumferential positioning of the combustion chamber and turbine vane (i.e., clocking effects) profoundly influences micro-gas turbine aerothermodynamics and pollutant emissions. Leading-edge impingement hot-streak configurations enhance aerodynamic efficiency, while mid-passage hot-streak configurations mitigate aerothermal heat load and soot emissions. Clocking effects impact all parameters, indicating a complex interplay between the flowfield, aerothermal performance, and pollutant emissions. However, turbine vane heat load exhibits the most significant variations.
A Contactless Coupled Pendulum and Piezoelectric Wave Energy Harvester: Model and Experiment
Authors: Feng Wuwei , Chen Hongya , Zou Qingping , Wang Di , Luo Xiang , Cummins Cathal , Zhang Chuanqiang , Yang Shujie , Su Yuxiang
Published: February 2024

Wireless monitoring systems for the marine environment are important for rapidly growing subsea developments. The power supply of wireless sensor nodes within the monitoring systems, however, is a major challenge. This study proposes a novel piezoelectric wave energy converter (pWEC) device to power the wireless sensing nodes. Unlike previous studies, the proposed device utilizes contactless pWEC technology in which a spring pendulum provides a two-stage frequency amplification of 3.8 times for low-frequency wave environments. The pWEC device consists of a floating body, inner pendulum, spring pendulum, magnets and piezoelectric sheets. In order to harvest the energy from relatively low frequency ocean waves, the pWEC device is designed to have an enhanced energy-capturing frequency. The effects of internal pendulum mass, spring pendulum weight, pendulum length and spring stiffness on wave energy absorption are investigated using theoretical and numerical analysis combined with laboratory experiments. The slider that drives the motion of the piezoelectric sheet vibrates at up to 3.8 times the wave frequency. To test the piezoelectric generators in the laboratory environment, a mechanical structure is set up to simulate the motion of the external floating body and the internal wave energy converter under the action of waves. When the four piezoelectric plates are arranged horizontally, the average output power per plate is increased by 2.4 times, and a single piezoelectric plate can generate an average of 10 mW of power. The proposed piezoelectric wave energy converter device has the potential to provide long-term energy supply for small ocean monitoring platforms at remote locations with reasonable wave energy resources.
Large Eddy Simulation of Forced Convection around Wavy Cylinders with Different Axes
Authors: Kim Min-Ki , Chang Chin-Hyuk , Nam Seok-Hyun , Yoon Hyun-Sik
Published: February 2024

Four types of undulated cylinders with streamwise undulation, transverse undulation, in-phase undulation and antiphase undulation are employed to investigate the undulation-axis effect on the structure of heat transfer around wavy cylinders. The flows around these undulated cylinders are numerically simulated by large eddy simulation at Re = 3000. The force coefficients and Nusselt numbers of the cylinders with transverse undulation and in-phase undulation are significantly influenced by wavelength and wave amplitude. On the other hand, the cylinders with streamwise undulation and antiphase undulation show a very weak dependence of the force coefficients and Nusselt numbers on the combinations of wavelength and wave amplitude. It is noted that the cylinder with antiphase undulation, under certain wavy conditions, provides about the same Nusselt number as the smooth cylinder, even though the force coefficients are considerably decreased. The thermal characteristics, according to the combination of wavy geometric parameters, are supported by the surface distribution of the Nusselt numbers. In addition, the isothermal distribution, which depends on the wake flow, explains the variation in the Nusselt numbers. The present results suggest that a proper modification of geometry can improve both heat transfer and aerodynamic performances.
The Species at Risk Act (2002) and Transboundary Species Listings along the US–Canada Border
Authors: Raymond Sarah , Perkins Sarah E. , Garrard Greg
Published: February 2024

This paper is a collaborative interdisciplinary examination of the scientific, political, and cultural determinants of the conservation status of mammal species that occur in both Canada and the USA. We read Canada’s Species at Risk Act as a document of bio-cultural nationalism circumscribed by the weak federalism and Crown–Indigenous relations of the nation’s constitution. We also provide a numerical comparison of at-risk species listings either side of the US–Canada border and examples of provincial/state listings in comparison with those at a federal level. We find 17 mammal species listed as at-risk in Canada as distinct from the USA, and only 6 transboundary species that have comparable levels of protection in both countries, and we consider several explanations for this asymmetry. We evaluate the concept of ‘jurisdictional rarity’, in which species are endangered only because a geopolitical boundary isolates a small population. The paper begins and ends with reflections on interdisciplinary collaboration, and our findings highlight the importance of considering and explicitly acknowledging political influences on science and conservation-decision making, including in the context of at-risk-species protection.
Drought-Adapted Mediterranean Diet Plants: A Source of Bioactive Molecules Able to Give Nutrigenomic Effects per sè or to Obtain Functional Foods
Authors: La Scala Silvia , Naselli Flores , Quatrini Paola , Gallo Giuseppe , Caradonna Fabio
Published: February 2024

The Mediterranean diet features plant-based foods renowned for their health benefits derived from bioactive compounds. This review aims to provide an overview of the bioactive molecules present in some representative Mediterranean diet plants, examining their human nutrigenomic effects and health benefits as well as the environmental advantages and sustainability derived from their cultivation. Additionally, it explores the facilitation of producing fortified foods aided by soil and plant microbiota properties. Well-studied examples, such as extra virgin olive oil and citrus fruits, have demonstrated significant health advantages, including anti-cancer, anti-inflammatory, and neuroprotective effects. Other less renowned plants are presented in the scientific literature with their beneficial traits on human health highlighted. Prickly pear’s indicaxanthin exhibits antioxidant properties and potential anticancer traits, while capers kaempferol and quercetin support cardiovascular health and prevent cancer. Oregano and thyme, containing terpenoids like carvacrol and γ-terpinene, exhibit antimicrobial effects. Besides their nutrigenomic effects, these plants thrive in arid environments, offering benefits associated with their cultivation. Their microbiota, particularly Plant Growth Promoting (PGP) microorganisms, enhance plant growth and stress tolerance, offering biotechnological opportunities for sustainable agriculture. In conclusion, leveraging plant microbiota could revolutionize agricultural practices and increase sustainability as climate change threatens biodiversity. These edible plant species may have crucial importance, not only as healthy products but also for increasing the sustainability of agricultural systems.
Gynecological Cancers and Microbiota Dynamics: Insights into Pathogenesis and Therapy
Authors: Cocomazzi Giovanna , Del Pup Lino , Contu Viviana , Maggio Gabriele , Parmegiani Lodovico , Ciampaglia Walter , De Ruvo Daniele , Faioli Raffaele , Maglione Annamaria , Baldini Giorgio Maria , Baldini Domenico , Pazienza Valerio
Published: February 2024

In recent years, the relationship between the microbiota and various aspects of health has become a focal point of scientific investigation. Although the most studied microbiota concern the gastrointestinal tract, recently, the interest has also been extended to other body districts. Female genital tract dysbiosis and its possible impact on pathologies such as endometriosis, polycystic ovary syndrome (PCOS), pelvic inflammatory disease (PID), and gynecological cancers have been unveiled. The incursion of pathogenic microbes alters the ecological equilibrium of the vagina, triggering inflammation and compromising immune defense, potentially fostering an environment conducive to cancer development. The most common types of gynecological cancer include cervical, endometrial, and ovarian cancer, which occur in women of any age but especially in postmenopausal women. Several studies highlighted that a low presence of lactobacilli at the vaginal level, and consequently, in related areas (such as the endometrium and ovary), correlates with a higher risk of gynecological pathology and likely contributes to increased incidence and worse prognosis of gynecological cancers. The complex interplay between microbial communities and the development, progression, and treatment of gynecologic malignancies is a burgeoning field not yet fully understood. The intricate crosstalk between the gut microbiota and systemic inflammation introduces a new dimension to our understanding of gynecologic cancers. The objective of this review is to focus attention on the association between vaginal microbiota and gynecological malignancies and provide detailed knowledge for future diagnostic and therapeutic strategies.
Identification of Hit Compounds Using Artificial Intelligence for the Management of Allergic Diseases
Authors: Byun Junhyoung , Tai Junhu , Kim Byoungjae , Kim Jaehyeong , Jung Semyung , Lee Juhyun , Song Youn woo , Shin Jaemin , Kim Tae Hoon
Published: February 2024

This study aimed to identify and evaluate drug candidates targeting the kinase inhibitory region of suppressor of cytokine signaling (SOCS) 3 for the treatment of allergic rhinitis (AR). Utilizing an artificial intelligence (AI)-based new drug development platform, virtual screening was conducted to identify compounds inhibiting the SH2 domain binding of SOCS3. Luminescence assays assessed the ability of these compounds to restore JAK-2 activity diminished by SOCS3. Jurkat T and BEAS-2B cells were utilized to investigate changes in SOCS3 and STAT3 expression, along with STAT3 phosphorylation in response to the identified compounds. In an OVA-induced allergic rhinitis mouse model, we measured serum levels of total IgE and OVA-specific IgE, performed real-time PCR on nasal mucosa samples to quantify Th2 cytokines and IFN-γ expression, and conducted immunohistochemistry to analyze eosinophil levels. Screening identified 20 hit compounds with robust binding affinities. As the concentration of SOCS3 increased, a corresponding decrease in JAK2 activity was observed. Compounds 5 and 8 exhibited significant efficacy in restoring JAK2 activity without toxicity. Treatment with these compounds resulted in reduced SOCS3 expression and the reinstatement of STAT3 phosphorylation in Jurkat T and BEAS-2B cells. In the OVA-induced allergic rhinitis mouse model, compounds 5 and 8 effectively alleviated nasal symptoms and demonstrated lower levels of immune markers compared to the allergy group. This study underscores the promising nonclinical efficacy of compounds identified through the AI-based drug development platform. These findings introduce innovative strategies for the treatment of AR and highlight the potential therapeutic value of targeting SOCS3 in managing AR.