Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribution à l'étude de la convection naturelle tridimensionnelle en cavité différentiellement chauffée

Cette etude experimentale et numerique s'interesse aux ecoulements tridimensionnels de convection naturelle de l'air en cavite differentiellement chauffee pour une valeur du nombre de Rayleigh egale a 1,48. 109, soit en regime de transition avancee a la turbulence. La cavite a pour dimensions 1m x 1m x 0,32m. Elle est constituee de deux parois actives verticales a temperature uniforme et imposee, de deux parois horizontales isolantes et de deux parois laterales supposees adiabatiques. La resolution d'un probleme inverse permet la determination precise des conditions aux limites thermiques relatives aux parois horizontales, et des mesures par camera infrarouge fournissent une cartographie de temperature des parois laterales. Une caracterisation des champs thermiques par microthermocouples, et dynamiques (mesure des 3 composantes de la vitesse) par LDV, dans differents plans de la cavite est proposee ainsi que les champs couples vitesse-temperature dans le plan vertical median. Une comparaison de ces mesures aux resultats numeriques obtenus par DNS-3D par methode spectrale Chebyshev est restituee. L'influence de la profondeur de la cavite et de l'emissivite des differentes parois est examinee. Enfin, une simulation munie des conditions aux limites thermiques experimentales sur les 6 faces de la cavite permet notamment d'expliquer les mecanismes complexes d'alimentation des couches limites.
Decoupling of nutrient stoichiometry in Suaeda glauca (Bunge) senesced leaves under salt treatment

The stoichiometry of senesced leaves is pivotal in nutrient cycling and can be significantly influenced by soil salinization, a rising global issue threatening the functionality of ecosystems. However, the impacts of soil salinization on senesced leaf stoichiometry are not fully understood. In this study, we conducted a pot experiment with varying soil salt concentrations to examine their influence on the concentrations and stoichiometric ratios of nitrogen (N), phosphorus (P), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), and zinc (Zn) in the senesced leaves of Suaeda glauca (Bunge). Compared to the control group, salt treatments significantly enhanced Na concentration while diminishing the concentrations of K, Ca, Mg, Zn, N, and P. Interestingly, as salinity levels escalated, N concentration maintained stability, whereas P concentration exhibited an increasing trend. Moreover, K, Ca, and Mg significantly declined as salt levels rose. Salt treatments brought about significant changes in stoichiometric ratios, with the N:P, K:Na, N:Na, N:Mg, and Ca : Mg ratios dropping and the N:Ca and N:K ratios rising, illustrating the varying nutrient coupling cycles under different salt conditions. These findings shed light on the plasticity of stoichiometric traits in S. glauca senesced leaves in response to soil salinization shifts, which could potentially offer insights into nutrient cycling reactions to soil salinization.
The role of fungi in the diagnosis of colorectal cancer

ABSTRACT Colorectal cancer (CRC) is a prevalent tumour with high morbidity rates worldwide, and its incidence among younger populations is rising. Early diagnosis of CRC can help control the associated mortality. Fungi are common microorganisms in nature. Recent studies have shown that fungi may have a similar association with tumours as bacteria do. As an increasing number of tumour-associated fungi are discovered, this provides new ideas for the diagnosis and prognosis of tumours. The relationship between fungi and colorectal tumours has also been recently identified by scientists. Therefore, this paper describes the limitations and prospects of the application of fungi in diagnosing CRC and predicting CRC prognosis.
The Impact of Biomaterial Surface Properties on Engineering Neural Tissue for Spinal Cord Regeneration

Tissue engineering for spinal cord injury (SCI) remains a complex and challenging task. Biomaterial scaffolds have been suggested as a potential solution for supporting cell survival and differentiation at the injury site. However, different biomaterials display multiple properties that significantly impact neural tissue at a cellular level. Here, we evaluated the behavior of different cell lines seeded on chitosan (CHI), poly (ε-caprolactone) (PCL), and poly (L-lactic acid) (PLLA) scaffolds. We demonstrated that the surface properties of a material play a crucial role in cell morphology and differentiation. While the direct contact of a polymer with the cells did not cause cytotoxicity or inhibit the spread of neural progenitor cells derived from neurospheres (NPCdn), neonatal rat spinal cord cells (SCC) and NPCdn only attached and matured on PCL and PLLA surfaces. Scanning electron microscopy and computational analysis suggested that cells attached to the material’s surface emerged into distinct morphological populations. Flow cytometry revealed a higher differentiation of neural progenitor cells derived from human induced pluripotent stem cells (hiPSC-NPC) into glial cells on all biomaterials. Immunofluorescence assays demonstrated that PCL and PLLA guided neuronal differentiation and network development in SCC. Our data emphasize the importance of selecting appropriate biomaterials for tissue engineering in SCI treatment.
Clinical trials of antibody drugs in the treatments of atopic dermatitis

Atopic dermatitis (AD) is one of the most common, relapsing, chronic inflammatory skin disease, being regarded as a global health issue. Recent studies have shown that Th2 cell-mediated type 2 immunity plays a central role in AD. The type 2 inflammatory cytokines such as IL-4, IL-13, IL-22, IL-31, IL-17 and IL-5 mediate the pathogenesis of AD. A variety of antibody drugs targeting these cytokines have been developed to treat AD in clinics. Notably, several antibody drugs have exhibited high efficacy in treating atopic dermatitis in previous studies, demonstrating that they could be therapeutic methods for AD patients. Herein, we reviewed the clinical trials of antibody drugs in the treatment of AD, which provides a useful guideline for clinicians to treat patients with AD in clinics.
Collaborative Intelligence in AgriTech: Federated Learning CNN for Bean Leaf Disease Classification

This study introduces a convolutional neural network (CNN) technique based on federated learning to classify bean leaf diseases. The research allays data privacy by allowing users to train local models on their datasets without sharing raw data. Our method combines local models from four customers to produce a high-performing global model that can categorize bean leaf diseases into five groups. According to the findings, the local models for each customer performed well in terms of precision, recall, F1 score, and accuracy. The performance measures’ macro, weighted, and micro averages showed that the aggregated global model performed equally well across all customers. The global model’s weighted average precision, recall, F1-score, and accuracy were 92.61%, 89.72%, and 92.87%, respectively. This research demonstrates how the federated learning-based CNN technique can effectively use various data types from multiple clients while maintaining data privacy. The accuracy with which this method identified bean leaf illnesses demonstrates the potential of federated learning in the agricultural field and provides a viable strategy for further study and real-world applications.
Small blind-area, high-accuracy ultrasonic rangefinder using a broadband multi-frequency piezoelectric micromachined ultrasonic transducer array

This paper presents a broadband ultrasonic rangefinder, with merits of a small blind area and high accuracy, based on a multi-frequency piezoelectric micromachined ultrasonic transducer (MF-PMUT) array. The coupling bandwidth between six types of resonant cells with adjacent resonant frequencies was studied and optimized, and these cells were then integrated into an array to broaden the bandwidth of the device. The array device showed a wide −6 dB fractional bandwidth of 108% in silicon oil. A wide bandwidth can contribute to obtaining the maximum steady-state with less excitation and reducing its residual ring-down, resulting in a small blind area. Pulse-echo ranging experiments demonstrated that the blind area was effectively reduced to 5 mm due to the multi-frequency array. For short distance measurements (<250 mm), the error was well controlled within ±0.3 mm and the 3σ accuracy was 0.445 mm. Compared with earlier reported PMUTs designed for bandwidth enhancement, the proposed broadband MF-PMUT array is much simpler in design and fabrication, revealing it as a promising candidate for short-distance high-accuracy measurements.
DSHFNet: Dynamic Scale Hierarchical Fusion Network Based on Multiattention for Hyperspectral Image and LiDAR Data Classification

With the continuous improvement of satellite sensor performance, it is becoming easier to obtain different types of remote sensing (RS) data from multiple sensors, and the fusion of hyperspectral (HS) images and light detection and ranging (LiDAR) for land use/land cover (LULC) classification has become a research hotspot. However, the current mainstream methods still have defects in feature extraction and feature fusion. In the feature extraction stage, previous methods usually use a single-scale patch as input and a fixed convolution kernel for feature extraction, which makes it difficult to extract features in line with different land cover types at the same time and to obtain high-quality features. Although multiscale feature extraction can solve the one-sidedness problem of single-scale features, it also brings the challenge of high-dimensional multiscale features. In the feature fusion stage, the current fusion methods are relatively simple. Therefore, we propose a dynamic scale hierarchical fusion network (DSHFNet) for fusion classification of HS images and LiDAR data. By calculating the similarity in the scale space and judging the information at different scales through the threshold value, the appropriate scale features are dynamically selected, the small-scale features are integrated into the large-scale features, and the dimensionality of the features is reduced. This method solves the unreliability problem of single-scale features and the high-dimensional problem of multiscale features. In the feature fusion process, different attention modules are used for hierarchical fusion, spatial attention modules are used for shallow fusion and joint feature extraction, and modal attention modules are used for deep fusion of joint features and features from different sensors to achieve complete complementarity of features. Experimental evaluations on three real RS datasets demonstrate the superiority of the proposed method compared with existing methods. The source code can be downloaded at https://github.com/SYFYN0317/DSHFNet.
Q-Factor Optimization in Photonic Crystal Nanobeam Cavities Based on Elliptical Nanopillars for Refractive Index Sensing

Label free sensing applications based on refractive index (RI) require new encapsulated high Q-factor cavity designs, that can overcome the inaccuracies inherent in the fabrication process. The required fine tuning of the current RI sensors based on PhCNC makes them highly sensitive to disparities found in the fabrication. These imperfections can dramatically decrease the performance, in designs which possess strict features along the whole design parameters space [1]–[4]. To limit this behaviour, we propose elliptically shaped nanopillars in which the optimum zone of operation is extended. The schematics of the PhCNC and the fabricated device considered in this work are shown in Fig. 1(a) and (b), respectively. Fig. 1(a), depicts three different cross sections of the PhCNC immersed in different analyte refractive index $(n_{A})$ that can vary from 1 (refractive index that can be considered for gases) to 1.45 (SiO2). The vertical widths $(W_{y}(i))$ of the dielectric pillars are quadratically modulated $(W_{y}(i)= W_{y}(0)+i^{2}(W_{y}(i_{max})-W_{y}(0))/i_{max}{}^{2})$, from the center to both sides where $i$ increases from 0 to $i_{max}$ (see Fig. 1(a)-left). Fig. 1(c) shows the behavior of the Q-factor calculated by means of 3D-FDTD simulations [5], against different nanopillar widths $W_{x}$ in two extreme shape cases: rectangular and elliptical ones.
An Overview of Head and Neck Tumor Reirradiation: What Has Been Achieved So Far?

Simple Summary Head and neck cancers are highly prevalent worldwide. Despite the recent advances in cancer diagnosis and treatment, more than 50% of the cases relapse within 2 years after the initial treatment. Radiation therapy, a leading option in the head and neck tumor management, has increasing potential as a repeated treatment. This review outlined recent advances in radiotherapy as applied to recurrent head and neck cancers in terms of clinical outcomes. Abstract The recurrence rate of head and neck cancers (HNCs) after initial treatment may reach 70%, and poor prognosis is reported in most cases. Curative options for recurrent HNCs mainly depend on the treatment history and the recurrent tumor localization. Reirradiation for HNCs is effective and has been included in most guidelines. However, the option remains clinically challenging due to high incidence of severe toxicity, especially in cases of quick infield recurrence. Recent technical advances in radiation therapy (RT) provide the means for upgrade in reirradiation protocols. While the majority of hospitals stay focused on conventional and widely accessible modulated RTs, the particle therapy options emerge as tolerable and providing further treatment opportunities for recurrent HNCs. Still, the progress is impeded by high heterogeneity of the data and the lack of large-scale prospective studies. This review aimed to summarize the outcomes of reirradiation for HNCs in the clinical perspective.
Pigeon during the Breeding Cycle: Behaviors, Composition and Formation of Crop Milk, and Physiological Adaptation

Pigeon is an important economic poultry species in many countries. As an altricial bird, its growth and development are largely reliant on pigeon milk produced by the crop tissue in the first week. During the breeding cycle, pigeons undergo a series of behavioral changes. Pigeon milk is generally characterized by having high concentrations of proteins and lipids, and a complicated regulatory network is involved in the milk formation. Hormones, especially prolactin, could promote the proliferation of crop epidermal cells and nutrient accumulation. The expression of target genes associated with these important biological processes in the crop epidermis is affected by non-coding RNAs. Meanwhile, signaling pathways, such as target of rapamycin (TOR), Janus kinase/signal transducer and activator of transcription proteins (JAK/STAT), protein kinase B (Akt), etc., influence the production of crop milk by either enhancing protein synthesis in crop cells or inducing apoptosis of crop epidermal cells. In order to adapt to the different breeding periods, pigeons are physiologically changed in their intestinal morphology and function and liver metabolism. This paper reviews the behaviors and physiological adaptations of pigeon during the breeding cycle, the composition of pigeon crop milk, and the mechanism of its formation, which is important for a better understanding of the physiology of altricial birds and the development of artificial crop milk.
Circulating Soluble EPCR Levels Are Reduced in Patients with Ischemic Peripheral Artery Disease and Associated with Markers of Endothelial and Vascular Function

(1) Background: Endothelial dysfunction initiates cardiovascular pathologies, including peripheral artery disease (PAD). The pathophysiology of impaired new vessel formation in the presence of angiogenic stimuli, such as ischemia and inflammation, is unknown. We have recently shown in mice that reduced endothelial protein C receptor (EPCR) expression results in defective angiogenesis following experimental hindlimb ischemia. (2) Purpose: To determine soluble (s)EPCR levels in the plasma of patients with PAD and to compare them with the protein C activity and biomarkers of endothelial function, inflammation, and angiogenesis. (3) Methods and Results: Clinical tests of vascular function and immunoassays of plasma from patients with PAD stage II were compared to age- and sex-matched individuals with and without cardiovascular risk factors or PAD stage III/IV patients. sEPCR levels were significantly lower in PAD stage II patients compared to subjects with risk factors, but no PAD, and further decreased in PAD stage III/IV patients. Plasma protein C activity or levels of ADAM17, a mediator of EPCR shedding, did not differ. Significant associations between sEPCR and the ankle-brachial index (p = 0.0359), age (p = 0.0488), body mass index (p = 0.0110), and plasma sE-selectin levels (p = 0.0327) were observed. High-sensitive CRP levels and white blood cell counts were significantly elevated in PAD patients and associated with serum glucose levels, but not sEPCR. In contrast, plasma TNFα or IL1β levels did not differ. Circulating levels of VEGF were significantly elevated in PAD stage II patients (p = 0.0198), but not associated with molecular (sE-selectin) or functional (ankle-brachial index) markers of vascular health. (4) Conclusions: Our findings suggest that circulating sEPCR levels may be useful as biomarkers of endothelial dysfunction, including angiogenesis, in persons older than 35 years and that progressive loss of endothelial protein C receptors might be involved in the development and progression of PAD.
Autoimmune polyendocrine syndromes associated with autoimmune rheumatic diseases

Autoimmune polyendocrine syndromes (APSs), also called autoimmune polyglandular syndromes, are a group of autoimmune diseases characterized by the co-occurrence of dysfunctions of several (at least two) endocrine glands. They develop under the influence of environmental factors in genetically predisposed people. Autoimmune polyendocrine syndromes may accompany autoimmune rheumatic diseases and worsen their course – APS-2 and APS-3 are the most common. The APS-2 includes the coexistence of, e.g. Hashimoto’s disease, celiac disease and rheumatoid arthritis (RA). In APS-3, rheumatic diseases such as RA, systemic lupus erythematosus, and Sjögren’s syndrome may coexist with Hashimoto’s disease, type 1 diabetes and hypogonadism or other endocrinopathies. Undiagnosed endocrine diseases may be the reason for the intensification of metabolic disorders observed in the course of rheumatic diseases, cause the ineffectiveness of rheumatological treatment and also increase the frequency of bone fractures due to osteoporosis, cardiovascular complications and even miscarriages when coexistent, e.g. Hashimoto’s disease with hypothyroiditis, which increases the risk of pregnancy loss. It is important to be able to conduct an extensive interview, paying attention to the symptoms of possible endocrinopathy as well as the features of other autoimmune disorders in the physical examination (e.g. vitiligo or darkening of the skin in Addison’s disease). Depending on the history and physical examination, screening for various APSs is advised.
In Search of Apis mellifera pomonella in Kazakhstan

Apis mellifera pomonella is one of two subspecies that represent the eastern limits of honey bee (Apis mellifera) distribution, and it is important to understand its biogeography and evolution. Despite this, A. m. pomonella was not investigated after its discovery 20 years ago. In particular, it is not known if it was hybridized or not with exotic subspecies introduced by beekeepers. In this study, we analysed the variation in honey bee forewing shape in Kazakhstan. Bees were collected from apiaries, where the origin of the queens was not controlled by beekeepers; they formed a group called “local bees”, and apiaries where queens declared as either A. m. carnica or A. m. mellifera were obtained from queen breeders. The two later groups were called “exotic bees”. We showed that local bees are still distinct from exotic ones. However, some samples showed signs of introgression with exotic subspecies from lineage C. In terms of wing shape, the local bees were most similar to lineage O. We concluded that the local bees most likely represented A. m. pomonella. We provided wing images and identification data, which can help to identify A. m. pomonella and protect it in the future. It is interesting that the nearby honey bee population sourced from China, which is not separated by any clear barrier to gene flow, belonged to lineage M.
Influence of Split Ratio on Field Modulation Effect in Consequent-Pole Permanent Magnet Machine

This paper investigates the influence of split ratio on air-gap field modulation effect (AGFME) on consequent-pole permanent magnet (CPPM) machine. Because of the doubly sided opening slotting effect, the CPPM machine exhibits an abundant air-gap flux density working harmonics for torque production. To identify and quantify the torque contributions of the various air-gap field working harmonics, the Maxwell stress tensor method (MSTD) is employed to illustrate their contributed torque components and proportions. The simulated results show that the split ratio exhibits a great influence on AGFME on CPPM machine. Finally, a CPPM machine prototype is manufactured and tested to validate the finite element analysis.
The Association between Early Marriage Decisions and Poverty Incidents in Indonesia

Early marriage is one of the social problems prevalent in many emerging countries, including Indonesia. Early marriage is widely believed to impact future economic outcomes negatively and is also associated with higher poverty incidence. Previous research has shown that early marriage significantly affects an individual’s future welfare and makes them vulnerable to poverty (Dahl, 2010). Research on this issue is still limited in Indonesia, and we aim to pursue the impact of early marriage decisions on poverty, using divorce, dropout, and gender as control variables. We use panel logistic regression on Indonesia Family Life Survey (IFLS) data set. We classify early married individuals as someone who marry under 18 years old, while the poverty variable is measured using the national poverty line. The logistic regression shows that early marriage is significantly associated with lower wages and poverty. The marginal effect of the logistic regression shows that an individual who marries early has a higher probability of getting into poverty, as much as 13-15%. We also found that women are more vulnerable to poverty than male with the exact status of marriage and education level. This result implies that the early marriage problem needs further attention from the policymaker. Regulation of the age of marriage should be reinforced and supported by more stringent measures from local governments.