Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional Variations in Diets in Japan

Japan is a diverse country. From the wide open spaces of the northern island of Hokkaido, to the crowded metropolises of the Kanto plains, to the fishing villages in the southern island of Kyushu, Japan presents a rich tapestry of often quite distinct and different life-styles and traditions. These differences are reflected in differing food consumption patterns across many parts of the country. Japanese food consumption has been a popular topic of research, particularly by analysts in those countries hoping to capture a larger share of Japan’s increasingly open agricultural markets. However, variations in food consumption between different parts of Japan have been overlooked in the past, at least by Western researchers. The purpose of this paper is to contribute to the understanding of Japanese food consumption by investigating regional variations in per person food consumption. This will help show whether regional differences in food consumption still exist. The data set is taken from Kokumin Eiyo Chosa [National Nutrition Survey], published by the Ministry of Health and Welfare, which utilises information from approximately 6,000 households annually. The study period runs from 1974 to 1992. The results of the analysis suggest that per person consumption of beef, pork, poultry, processed meats, fish, beer and vegetables is tending to converge and that consumption patterns are in general less variable across regions than they were in the past.
Translanguaging in a French-medium CLIL course: An action research on a novice teacher’s course preparation

While translanguaging has been regarded as an appropriate approach to addressing the challenges that teachers and learners experience in content and language integrated learning (CLIL) classrooms, few studies have discussed translanguaging practices in the preparation of content for third language integrated learning courses. This study aims to explore teachers’ translanguaging practices when preparing CLIL courses through the medium of languages other than English (LOTEs) in a Chinese tertiary education institution. To address the research objective, we collected data including one novice CLIL teacher’s course planning and design documents, teaching materials and other reference materials, along with reflective reports written by the teacher. Through a frequency analysis and a thematic analysis of the data, this research not only documented the dynamic flow of translanguaging practices during CLIL course preparation, but also identified multiple functions served by different languages in the CLIL context. These findings have the potential to inform LOTE teachers involved in CLIL classrooms about different translanguaging pedagogies, and enrich the theoretical framework of translanguaging. FUNDING INFORMATION. This paper was supported by Program for Innovative Research Team of Shanghai University of Finance and Economics (IRTSHUFE) under Grant [2020110925] and by [the Fundamental Research Funds for the Central Universities, SUFE] under Grant [2020110892].
The Radiocarbon Approach to Neanderthals in a Carnivore Den Site: a Well-Defined Chronology for Teixoneres Cave (Moià, Barcelona, Spain)

Abstract During the Middle Paleolithic period, carnivores and hominids periodically occupied the same areas at different times and each predator generated significant palimpsests, rendering difficult their archaeological interpretation. Teixoneres Cave, a carnivore den site, located in the northeastern part of the Iberian Peninsula, demonstrates that it is possible to overcome these problems by using a careful strategy in selecting samples for radiocarbon dating, in order to produce an accurate chronology of the site in question and certainly attest the human occupation.
A new candidate epitope-based vaccine against PspA PhtD of Streptococcus pneumoniae: a computational experimental approach

Introduction Pneumococcus is an important respiratory pathogen that is associated with high rates of death in newborn children and the elderly. Given the disadvantages of current polysaccharide-based vaccines, the most promising alternative for developing improved vaccines may be to use protein antigens with different roles in pneumococcus virulence. PspA and PhtD, highly immunogenic surface proteins expressed by almost all pneumococcal strains, are capable of eliciting protective immunity against lethal infections. Methods In this study using immunoinformatics approaches, we constructed one fusion construct (called PAD) by fusing the immunodominant regions of PspA from families 1 & 2 (PA) to the immunodominant regions of PhtD (PD). The objective of this project was to test the immunogenicity of the fusion protein PAD and to compare its protective activity against S. pneumoniae infection with PA or PD alone and a combination of PA and PD. The prediction of physicochemical properties, antigenicity, allergenicity, toxicity, and 3D-structure of the constructs, as well as molecular docking with HLA receptor and immune simulation were performed using computational tools. Finally, mice were immunized and the serum levels of antibodies/cytokines and functionality of antibodies in vitro were evaluated after immunization. The mice survival rates and decrease of bacterial loads in the blood/spleen were examined following the challenge. Results The computational analyses indicated the proposed constructs could be antigenic, non-allergenic, non-toxic, soluble and able to elicit robust immune responses. The results of actual animal experiments revealed the candidate vaccines could induce the mice to produce high levels of antibodies and cytokines. The complement-mediated bactericidal activity of antibodies was confirmed and the antibodies provided favorable survival in immunized mice after bacterial challenge. In general, the experimental results verified the immunoinformatics studies. Conclusion For the first time this report presents novel peptide-based vaccine candidates consisting of immunodominant regions of PspA and PhtD antigens. The obtained findings confirmed that the fusion formulation could be relatively more efficient than the individual and combination formulations. The results propose that the fusion protein alone could be used as a serotype-independent pneumococcal vaccine or as an effective partner protein for a conjugate polysaccharide vaccine.
Analytical Procedure for Estimation of the Assimilation Cell Phase CO2 Mass Transfer Coefficient of Crop Leaf from Experimental Measurements of the Net Photosynthetic Rate

Analytical solutions for the CO2 concentration profile CA (z, t) and CO2 mass transfer coefficient kL within the assimilation cell phase of the crop leaf in the net photosynthesis process were obtained by the concept of “rate of process” in the engineering science.To solve the CO2 mass transfer problem of the crop leaf in net photosynthesis, CO2-H2O equilibrium at the assimilation-aerenchyma tissue interface within the crop leaf, Henry's Law, was introduced and the net photosynthetic reaction was approximated by a pseudo-1st order irreversible form.Simultaneously, in order to estimate quantitatively kL and the over-all gas phase CO2 mass transfer coefficient kG from the practical observed results of the net photosynthetic rate RA, the graphical method and its procedure were proposed, using the results of RA for “rice” presented by Yabuki (1992). The summary is as follows:1) CO2 mass transfer of a crop leaf in the photosynthesis process is a gas absorption-reaction. It is also a diffusion phenomenon in a gas-liquid binary system and the mechanism of CO2 absorption may be represented schematically by a “two-film penetration diffusion model”. 2) Analytical solutions and the graphical method are available for evaluation of kL and kG from RA observed in the field. These basic analytical procedures for gas absorption engineering are useful to obtain the correlation of the net photosynthesis reaction rate constant k1 with RA and CO2 mass transfer coefficients.3) k1 is a primary characteristic parameter to evaluate the net photosynthetic ability of the crop. The over-all assimilation cell phase CO2 mass transfer coefficients, KL, kL, and kG depend on k1. Therefore, to estimate a valid RA or an appropriate net photosynthetic ability of the crop leaf, CO2 mass transfer coefficients correlated with k1 must be used.
A remote sensing image classification method based on residual network and attention mechanism

In the process of remote sensing image classification, remote sensing image itself has the characteristics of complex spatial relationship and diverse information in the image. This paper puts forward a remote sensing image classification method based on the residual network ResNet50, adding channel attention and spatial attention mechanism, replace the full connection layer. The experimental results prove its feasibility, and when the remote sensing image data does not meet the independent and identical distribution, it can still get better classification effect when it is input into the improved ResNet50, so as to further process the remote sensing image.
COASTAL TOURIST RESORTS: HISTORY, DEVELOPMENT AND MODELS

This paper begins with a brief review of the historical development of coastal tourist destinations and the links between their characteristic design and structure, their markets and the means of access for visitors. It notes that early resorts were often developed by the transportation companies bringing visitors to them with a very distinctive purpose-focused morphology that still exists in many older resorts because it is still highly efficient today. It then discusses some of the models which have been created to explain these patterns of development and location, focusing particularly upon the Tourism Area Life Cycle model, the most cited of these frameworks in the literature. This model suggests that the pattern of development of most resorts goes through a series of stages from exploration to stagnation followed by a series of possible outcomes. The final stage depends upon management interventions being put into practice in earlier stages. If such interventions are not made by the appropriate agencies it is argued that a resort will fall into decline and experience great difficulty in rejuvenating itself and regaining its original or a new market. The paper concludes with a review of some of the applications and suggested modifications of the Tourism Area Life Cycle model, followed by some thoughts on potential future areas of research into resort development.
ERGPNet: lesion segmentation network for COVID-19 chest X-ray images based on embedded residual convolution and global perception

The Segmentation of infected areas from COVID-19 chest X-ray (CXR) images is of great significance for the diagnosis and treatment of patients. However, accurately and effectively segmenting infected areas of CXR images is still challenging due to the inherent ambiguity of CXR images and the cross-scale variations in infected regions. To address these issues, this article proposes a ERGPNet based on embedded residuals and global perception, to segment lesion regions in COVID-19 CXR images. First, aiming at the inherent fuzziness of CXR images, an embedded residual convolution structure is proposed to enhance the ability of internal feature extraction. Second, a global information perception module is constructed to guide the network in generating long-distance information flow, alleviating the interferences of cross-scale variations on the algorithm’s discrimination ability. Finally, the network’s sensitivity to target regions is improved, and the interference of noise information is suppressed through the utilization of parallel spatial and serial channel attention modules. The interactions between each module fully establish the mapping relationship between feature representation and information decision-making and improve the accuracy of lesion segmentation. Extensive experiments on three datasets of COVID-19 CXR images, and the results demonstrate that the proposed method outperforms other state-of-the-art segmentation methods of CXR images.
The evolution of resistance to synergistic multi‐drug combinations is more complex than evolving resistance to each individual drug component

Multidrug antibiotic resistance is an urgent public health concern. Multiple strategies have been suggested to alleviate this problem, including the use of antibiotic combinations and cyclic therapies. We examine how adaptation to (1) combinations of drugs affects resistance to individual drugs, and to (2) individual drugs alters responses to drug combinations. To evaluate this, we evolved multiple strains of drug resistant Staphylococcus epidermidis in the lab. We show that evolving resistance to four highly synergistic combinations does not result in cross‐resistance to all of their components. Likewise, prior resistance to one antibiotic in a combination does not guarantee survival when exposed to the combination. We also identify four 3‐step and four 2‐step treatments that inhibit bacterial growth and confer collateral sensitivity with each step, impeding the development of multidrug resistance. This study highlights the importance of considering higher‐order drug combinations in sequential therapies and how antibiotic interactions can influence the evolutionary trajectory of bacterial populations.
Bed-Shear Stress in Turbulent Wave-Current Boundary Layers

An approach for calculating turbulent flows in a wave-current boundary layer over a slowly varying bed is presented. Waves are periodic in time with several harmonics. In this paper, we adopt a time invariant eddy viscosity model, in which the eddy viscosity is linearly proportional to the distance from the bed. The boundary-layer flow field is solved analytically in terms of Fourier components. The approach allows fast computations and can be easily included in a phase resolving wave propagation model. As a part of the results, bottom shear stress and the spatial variation of the boundary layer thickness are also obtained. Present results compare well with experimental data and can explain the asymmetries in the bottom shear stress under sawtooth shaped waves.
Role of Vagus Nerve Stimulation in Refractory and Super Refractory Status Epilepticus: A Pediatric Case Series

Background: Status epilepticus is a life-threatening condition that is defined as refractory (RSE) when the seizure activity continues despite treatment with benzodiazepine and a second appropriate treatment. Super refractory status epilepticus (SRSE) is an RSE that persists or recurs for ≥24 h. Few papers have reported the outcomes of pediatric patients affected by RSE and SRSE and treated with neuromodulation therapies. Vagus nerve stimulation (VNS) is an approved treatment for drug-resistant epilepsy. We present our findings of pediatric patients treated with VNS for RSE/SRSE. Methods: We present a case series of seven consecutive pediatric patients treated with VNS for SRSE since 2012 by a single surgeon in Monza and Padua. A rapid titration was started soon after implantation. We considered electroclinical data before and after VNS implantation and at the last follow-up. Results: We achieved the resolution of SRSE in five out of seven patients in a mean time of two weeks. At the last follow-up, these patients had a significant reduction of seizure burden without any relapse of SE. Discussion and Conclusions: Based on our limited findings, we discuss the potential role of VNS therapy in similar but distinct clinical contexts. For patients with drug-resistant epilepsy and RSE/SRSE, prompt VNS consideration is suggested, offering rapid responses and potentially reducing pharmacological load. Meanwhile, in NORSE/FIRES, we suggest early neuromodulation during the acute phase if standard treatments prove ineffective or not tolerated. This approach may leverage VNS’s potential anti-inflammatory effects and neuromodulation, enhancing patient-specific treatments. Expanding case studies and prolonged follow-ups are recommended to strengthen these clinical insights.
Bionic Underwater Vehicle: A Data-Driven Disturbance Rejection Control Framework

Disturbances caused by unknown dynamics and environmental factors render the automatic control of underwater vehicles extremely challenging. These effects are complex, time varying, and difficult to model accurately, leading to possible instability in the control process. This article focuses on the disturbance rejection problem of an underactuated bionic underwater vehicle (BUV). A novel control approach that combines the robustness of a model predictive controller with the modeling capabilities of a learning-based observer is proposed. More specifically, a practical Gaussian process (GP)-based disturbance observer is designed for online disturbance estimation. The interactive prediction results are integrated into a model predictive controller to obtain a refined dynamics model. The control framework optimally solves for the optimal control output to achieve control at the dynamics level. The proposed approach realizes disturbance rejection control while ensuring real-time application, constraint satisfaction, and recursive feasibility under complicated disturbances. The feasibility and efficiency of the proposed approach are verified through simulations and real-world experiments.
Joint measurement of electron density, temperature, and emission spectrum of Nd:YAG laser-produced tin plasma

We present the results of joint measurements of electron density (ne), temperature (Te), and emission spectra of an Nd:YAG-driven tin plasma. Collective Thomson scattering provides space- and time-resolved ne and Te data during drive laser irradiation, and extreme ultraviolet (EUV) emission spectra, which is space-resolved in the target normal, are measured using a flat-field grazing incidence spectrometer (GIS). As the distance from the target increased, the emission intensity quickly decreases, and the peaks of the spectra gradually shift to longer wavelengths. This can be explained by the rapid decrease in ne, and thus, self-absorption, with an increase in distance. We obtain the EUV spectra by calculating the transfer of photons along the line-of-sight of the GIS, using theoretical emissivity and opacity, and applying the measured spatial distribution of ne and Te. The results quantitatively demonstrate that the self-absorption effect is significant; the emission from the core regions is mostly reabsorbed by the surrounding plasma. The calculated spectra are compared with the measured spectra. While good agreement is achieved in the spectral region of 13.3 and 15.3 nm, considerable differences are found in the 12.5–13 and 15.5–17.5 nm region. The results demonstrate the significance of this joint measurement for further validation of the atomic process model considering self-absorption effect, which is critical for the future high-density, solid laser-driven EUV source.
Race and sex differences in the association between lifespan glycemic status and midlife cognitive function: the Bogalusa heart study

Introduction Glycemic markers throughout life are associated with increased risk of midlife cognitive decline, yet it is unclear whether these associations differ by race and sex. Methods This study used cross-sectional analysis of prospectively maintained cohort. 1,295 participants in the Bogalusa Heart Study, a biracial epidemiological cohort located in a micropolitan area core setting, provided fasting plasma insulin (FPI) and glucose (FPG) biannually from 1973 to 2016. Memory, executive function (EF), attention, working memory (WM), and global cognition (GC), collected 2013–2016. Glycemic markers (i.e., FPG, FPI, and HOMA-IR) averaged within lifespan epochs (≤ 20 years, childhood/adolescence (C/A); 21–40 years, early adulthood (EA); and 40–58 years, midlife). Linear regression models were analyzed for each epoch and separate models were analyzed with sex and race, education as a covariate. Results Sample was 59% women, 34% African American (AA). Among women, higher C/A FPG was associated with poorer memory and poorer GC. Higher EA FPG was associated with poorer WM. Among men, higher EA HOMA-IR was associated with worse attention. Higher C/A HOMA-IR and FPI were associated with better memory, as was higher EA FPI. Among AA, higher C/A FPG was associated with worse attention, EF, and GC. Higher EA HOMA-IR was associated with worse attention. Higher midlife FPI and C/A HOMA-IR were associated with worse WM and EF among White Americans (WAs). Discussion Markers indicative of hyperglycemia at different epochs were associated with worse midlife cognition in women, AAs, and WAs; but not in men. Differences in the relationship between lifespan glycemic exposures and midlife cognition could reflect broader health disparities.
Classification of COVID-19 and lung opacity using vision transformer on chest x-ray images

There are several recent works which had proposed an automatic computer-aided diagnosis (CAD) deep learning (DL) model to diagnose coronavirus disease 2019 (COVID-19) using chest x-ray images (CXR) to propose a high-accuracy CAD method to detect COVID-19 automatically. In this study, seven different models including Convolutional Neural Network (CNN) models such as VGG-16 and vision transformer (ViT) models, are proposed. The different proposed models are trained with a three-class balanced dataset consisting of 3,000 CXR images consisting of 1,000 CXR images for each class of COVID-19, Normal, and Lung-Opacity. A publicly available dataset to train and test the models is used from Kaggle-COVID-19-Radiography-Dataset. From the experiments, the accuracy of the VGG16 model is 93.44% and ViT’s is 92.33%. Besides, the binary classification between two classes of COVID-19 and Normal CXR with a limited number of just 100 images for each class, using a transfer learning technique, with a validation accuracy of 97.5% is proposed.
Designing Legged Wheels for Stair Climbing

Mobile robotics has been used in recent years to provide various types of services in fields such as agriculture, surveillance, rehabilitation, space exploration, and logistics, among others. In many cases, mobile robots need to overcome complex obstacles where traditional wheels are not the best solution, and many researchers have proposed legged wheel hybrid designs. This paper presents a comprehensive study on the effect of the geometry of legged wheels on the performance of mobile robots in climbing stairs. The method used to develop this research is dynamic simulation, in which the parameters that affect the kinematics and dynamics of the robot are included. Subsequently, the results of how the robot manages to perform the test, the torque of the motors, and the contact force of the wheels are analyzed. The main hypothesis of this research is that the opening of the legs of the wheels is a geometric parameter that determines whether the structure will be able to climb the stairs. After 63 simulations, the proportional relationship between the diagonal of the stands and the opening of the wheel legs ranges between 1.11 and 1.53. This parameter showed a strong correlation with the torque of the motors and significant differences in terms of the simulations that succeeded in climbing the stairs and those that did not. These results were used to state a design method for flat, robotic structures using legged wheels. This method was validated by an additional simulation that was performed for a four-legged wheel. It can be concluded that the contribution of this work is a series of steps with which to design these mechanical structures to climb the stairs based on the proposed indicator.