Miracle-dz/UniFAR-FTUs huggingface dataset:
Roles of thermal advection in setting the Southern Ocean warming pattern

The Southern Ocean is the major region of global ocean heat gain. Most of the heat gain is concentrated in the region of the Antarctic Circumpolar Current (ACC), but SST within the ACC only exhibits a slight increase. Ocean circulation plays a fundamental role in setting the pattern of temperature response to global warming. In this study, a 1/4° Southern Ocean eddy‐permitting model configured based on the Regional Ocean Modeling System is used to study the role of ocean in setting the warming pattern, by examining the response of ocean temperature and heat budget terms to a uniform air–sea heat flux (Qnet) increase. As Qnet increases by a constant value, the SST increases, but with a smaller value within the ACC region. Consequently, more heat flux in the ACC region is induced from the atmosphere to the ocean through thermal adjustment. Heat budget analyses suggest that the surface warming induced by vertical diffusion is largely offset by the cooling effect of heat advection, especially within the ACC region; however, in the subsurface, the effect of vertical diffusion becomes slight, and heat advection dominates the temperature change and induces warming in the ACC region. These results highlight the importance of heat advection in setting the temperature response pattern to air–sea heat flux increase: by transporting more heat from the surface to the deep ocean, the SST increase within the ACC region becomes smaller, and this induces more heat flux from the atmosphere to the ocean and thus makes the ACC region become a major region of heat gain.
Primary Language Impairment and Developmental Dyslexia

Primary Language Impairment (PLI) and Developmental Dyslexia (DD) are developmental disorders which primarily affect language (and language-related abilities) from childhood onwards. Recent studies on DD have evidenced morphosyntactic weaknesses, in conjunction with a core phonological impairment. Therefore, compelling parallelism between children with DD and PLI is inferred. In the present paper, we will address the trivial issue of the relationship between the two disorders by discussing Italian data from a two-case study. In order to do so, we collected, transcribed and analyzed samples of spontaneous and elicited speech of two Italian speaking children. In addition, we proved their linguistic abilities by conducting standardized tests in order to evaluate the disruption of any linguistic level, with particular reference to phonology and morphosyntax. We intend to support the Comorbidity Model, which holds the view that PLI and DD are distinct but potentially comorbid developmental disorders.
USP7 Inhibition Suppresses Neuroblastoma Growth via Induction of p53-Mediated Apoptosis and EZH2 and N-Myc Downregulation

Neuroblastoma (NB) is a pediatric malignancy originating from neural crest cells of the sympathetic nervous system that accounts for 15% of all pediatric cancer deaths. Despite advances in treatment, high-risk NB remains difficult to cure, highlighting the need for novel therapeutic approaches. Ubiquitin-specific protease 7 (USP7) is a deubiquitinase that plays a critical role in tumor suppression and DNA repair, and USP7 overexpression has been associated with tumor aggressiveness in a variety of tumors, including NB. Therefore, USP7 is a potential therapeutic target for NB. The tumor suppressor p53 is a known target of USP7, and therefore reactivation of the p53 pathway may be an effective therapeutic strategy for NB treatment. We hypothesized that inhibition of USP7 would be effective against NB tumor growth. Using a novel USP7 inhibitor, Almac4, we have demonstrated significant antitumor activity, with significant decreases in both cell proliferation and cell viability in TP53 wild-type NB cell lines. USP7 inhibition in NB cells activated the p53 pathway via USP7 and MDM2 degradation, leading to reduced p53 ubiquitination and increased p53 expression in all sensitive NB cells. In addition, USP7 inhibition led to decreased N-myc protein levels in both MYCN-amplified and -nonamplified NB cell lines, but no correlation was observed between MYCN amplification and treatment response. USP7 inhibition induced apoptosis in all TP53 wild-type NB cell lines. USP7 inhibition also induced EZH2 ubiquitination and degradation. Lastly, the combination of USP7 and MDM2 inhibition showed enhanced efficacy. Our data suggests that USP7 inhibition may be a promising therapeutic strategy for children with high-risk and relapsed NB.
Polysaccharides Extracted from Agaricus blazei Murill as Applicable Drugs in Biomedicine

Agaricus blazei Murill (ABM) is a type of basidiomycete mushroom with various of nutrition including polysaccharides, ergosterol, sterols, minerals, vitamins, proteins and some phenolic compounds. As a kind of edible mushroom, ABM is also rich in a variety of potential pharmacological applications with administering the extraction contained in its fruiting body or mycelium. On the other hand, even if the ingredients and chemical structures of the ABM have been discovered deeply, the related drug extracted by the Agaricus blazei Murill is rare. This review aims at summarizing the immunoregulation benefits and anti-inflammation advantages of Agaricus blazei Murill polysaccharides (ABMP). With α-glucans and β-glucans as dominant bioactive polysaccharides, ABMP shows evidence in natural killer (NK) cells, macrophages with activating a comprehensive array of signal pathways and protecting creatures from inflammation. Whereas some of the biological mechanisms related to ABMP still remain controversy or conflicts. Furthermore, the experiments about the extractions of ABM may still have limitations in purifying, making some potential mechanisms or reactions unclear and have not been found. Therefore, more data about the ABMP, especially the clinical trials and the further purification of ABMP, is needed to be explored and analyzed.
AI-Driven Edge Computing for IoT: A Comprehensive Survey and Future Directions

The proliferation of Internet of Things (IoT) devices has ushered in an era of unprecedented data generation and processing demands. To meet these challenges, the convergence of Artificial Intelligence (AI) and Edge Computing has emerged as a promising solution. This paper presents a comprehensive survey of the state-of-the-art in AI-Driven Edge Computing for IoT, exploring key technologies, architectures, and applications. We begin by providing an overview of the fundamental concepts underpinning IoT and edge computing, highlighting the convergence of these technologies. As IoT continues to expand its reach across diverse domains, understanding the synergy between AI and edge computing is paramount for unlocking the full spectrum of possibilities, driving innovation, and ensuring a more connected and intelligent future
DDynamique des structures cohérentes en couche limite transitionnelle et turbulente étudiée par simulation des grandes échelles

La dynamique des structures coherentes en couche limite transitionnelle et turbulente est etudiee par simulation des grandes echelles. Une comparaison est effectuee dans la zone de croissance des instabilites entre notre code et un code pse non-lineaire. On montre que les resultats concordent et que les pse non-lineaires restent valides jusqu'a leur point d'arret. Trois type de transitions sont utilisees. La premiere et la seconde sont des transitions controlees faisant intervenir respectivement des resonances harmoniques et sous-harmonique. La troisieme reproduit le phenomene d'intermittence en modulant l'amplitude des perturbations incidentes. L'analyse statistique des correlations transverses de vitesse revelent que l'abscisse d'apparition des echelles transverses du systeme courants haute-basse vitesse se situe largement en amont de la turbulence developpee. Les visualisations montrent que cette echelle est liee a la largeur des tourbillons longitudinaux qui forment les structures en lambda transitionnelles. La topologie des structures turbulentes est retrouvee dans la zone de transition tardive, dans la zone de turbulence developpee et dans les fronts de propagation des spots. L'analyse de la dynamique de ces structures permet de mettre en evidence trois mecanismes d'interaction et deux vitesses de propagation caracteristiques de la turbulence (0. 9 u et 0. 6 u). La premiere est liee a l'interaction entre les zones externe et interne, elle est responsable de la propagation de la turbulence dans un milieu laminaire. La seconde est liee a la vitesse de propagation des tourbillons longitudinaux et a la regeneration de la turbulence.
Application of clinical and molecular profiling data to improve patient outcomes in psoriatic arthritis

Achieving a good outcome for a person with Psoriatic Arthritis (PsA) is made difficult by late diagnosis, heterogenous clinical disease expression and in many cases, failure to adequately suppress inflammatory disease features. Single-centre studies have certainly contributed to our understanding of disease pathogenesis, but to adequately address the major areas of unmet need, multi-partner, collaborative research programmes are now required. HIPPOCRATES is a 5-year, Innovative Medicines Initiative (IMI) programme which includes 17 European academic centres experienced in PsA research, 5 pharmaceutical industry partners, 3 small-/medium-sized industry partners and 2 patient-representative organizations. In this review, the ambitious programme of work to be undertaken by HIPPOCRATES is outlined and common approaches and challenges are identified. It is expected that, when completed, the results will ultimately allow for changes in the approaches to diagnosing, managing and treating PsA allowing for better short-term and long-term outcomes.
Motor imagery has a priming effect on motor execution in people with multiple sclerosis

Priming is a learning process that refers to behavioral changes caused by previous exposure to a similar stimulus. Motor imagery (MI), which involves the mental rehearsal of action representations in working memory without engaging in actual execution, could be a strategy for priming the motor system. This study investigates whether MI primes action execution in Multiple Sclerosis (MS). Here, 17 people with MS (PwMS) and 19 healthy subjects (HS), all right-handed and good imaginers, performed as accurately and quickly as possible, with a pencil, actual or mental pointing movements between targets of small (1.0 × 1.0 cm) or large (1.5 × 1.5 cm) size. In actual trials, they completed five pointing cycles between the left and right targets, whereas in mental trials, the first 4 cycles were imagined while the fifth was actually executed. The fifth cycle was introduced to assess the MI priming effect on actual execution. All conditions, presented randomly, were performed with both dominant (i.e., right) and non-dominant arms. Analysis of the duration of the first 4 cycles in both actual and mental trials confirmed previous findings, showing isochrony in HS with both arms and significantly faster mental than actual movements (anisochrony) in PwMS (p < 0.01) [time (s); HS right: actual: 4.23 ± 0.15, mental: 4.36 ± 0.16; left: actual: 4.32 ± 0.15, mental: 4.43 ± 0.18; PwMS right: actual: 5.85 ± 0.16, mental: 5.99 ± 0.21; left: actual: 6.68 ± 0.20, mental: 5.94 ± 0.23]; anisochrony in PwMS was present when the task was performed with the non-dominant arm. Of note, temporal analysis of the fifth actual cycle showed no differences between actual and mental trials for HS with both arms, whereas in PwMS the fifth actual cycle was significantly faster after the four actual cycles for the non-dominant arm (p < 0.05) [time (s); HS right: actual: 1.03 ± 0.04, mental: 1.03 ± 0.03; left: actual: 1.08 ± 0.04, mental: 1.05 ± 0.03; PwMS right: actual: 1.48 ± 0.04, mental: 1.48 ± 0.06; left: actual: 1.66 ± 0.05, mental: 1.48 ± 0.06]. These results seem to suggest that a few mental repetitions of an action might be sufficient to exert a priming effect on the actual execution of the same action in PwMS. This would indicate further investigation of the potential use of MI as a new motor-cognitive tool for MS neurorehabilitation.
A CIRCULARLY POLARIZED DUAL-AXIS WIDE-ANGLE RECTENNA EMPLOYING A DUAL-FEED ARRAY ANTENNA WITH INCLINED PATCHES

In this paper, a novel circularly polarized rectenna using a dual-feed array antenna with inclined patches is proposed to provide a dual-axis wide-angle reception capability. A new conical and pencil dual-beam circularly polarized array antenna integrating planar magic-Ts is designed and fabricated to overcome the polarization and main-beam misalignment between the transmitting and receiving antennas. To improve the rectenna’s output power, open stub matching networks are used to achieve the matching between the antenna and rectifying diodes. Two types of circularly polarized dual-axis rectennas which respectively allow the parallel and series connections of two diodes are experimentally evaluated and compared to confirm the wide-angle reception capabilities in the x-z and y-z planes.
A hybrid-model optimization algorithm based on the Gaussian process and particle swarm optimization for mixed-variable CNN hyperparameter automatic search

Convolutional neural networks (CNNs) have been developed quickly in many real-world fields. However, CNN’s performance depends heavily on its hyperparameters, while finding suitable hyperparameters for CNNs working in application fields is challenging for three reasons: (1) the problem of mixed-variable encoding for different types of hyperparameters in CNNs, (2) expensive computational costs in evaluating candidate hyperparameter configuration, and (3) the problem of ensuring convergence rates and model performance during hyperparameter search. To overcome these problems and challenges, a hybrid-model optimization algorithm is proposed in this paper to search suitable hyperparameter configurations automatically based on the Gaussian process and particle swarm optimization (GPPSO) algorithm. First, a new encoding method is designed to efficiently deal with the CNN hyperparameter mixed-variable problem. Second, a hybrid-surrogate-assisted model is proposed to reduce the high cost of evaluating candidate hyperparameter configurations. Third, a novel activation function is suggested to improve the model performance and ensure the convergence rate. Intensive experiments are performed on image-classification benchmark datasets to demonstrate the superior performance of GPPSO over state-of-the-art methods. Moreover, a case study on metal fracture diagnosis is carried out to evaluate the GPPSO algorithm performance in practical applications. Experimental results demonstrate the effectiveness and efficiency of GPPSO, achieving accuracy of 95.26% and 76.36% only through 0.04 and 1.70 GPU days on the CIFAR-10 and CIFAR-100 datasets, respectively.
A Bayesian Network Perspective on an Attributional Model of Reactions Toward People with HIV

Objective. Attributional theory has been widely studied to understand the overall perceptions regarding people suffering from negative events such as an HIV infection. The aim of the present study is to test the overall attribution model and its influence on the willingness to help, considering emotional reactions related to an HIV-infected individual. Method. We used a Bayesian network to analyze the association between attributions of causality (blame, responsibility, and control), willingness to help, and emotional reactions (anger and sympathy) toward an HIV-infected patient. Three hundred and fifty-eight individuals participated in the study. Results. Using the overall model, we found two different results: Anger contributed to the cognitive processes of attribution, and sympathy contributed to the behavioral willingness to help the patient.
A Dendrochronological Study of the Origin of Driftwood in Frobisher Bay, Baffin Island, N.W.T., Canada

Archaeological sites in Frobisher Bay, located far above the treeline, yielded large amounts of wooden remains. Questions were raised about the source of that wood. Forty driftwood samples were collected from the shores and analyzed by dendrochronological and wood-anatomical methods to determine their origins and ages. Four Picea logs are cross-dated via tree-ring chronologies from the Yukon River drainage in Alaska and two Pinus samples are cross-dated with a tree-ring chronology from the Yenisey River in Siberia. The Picea driftwood and some Larix driftwood were eroded naturally from river terraces, while most Pinus and Larix wood escaped logging and floating operations along Russian rivers. We propose that wood on the shores of Frobisher Bay drifted from the Arctic Ocean via Fram Strait, between Greenland and Svalbard, and around the southern tip of Greenland rather than through the Canadian Arctic Archipelago.
Emprint Microwave Thermoablation System: Bridging Thermal Ablation Efficacy between Human Patients and Porcine Models through Mathematical Correlation

To investigate the in vivo ablation characteristics of a microwave ablation antenna in the livers of humans with tumors, a retrospective analysis of the ablation zones was conducted after applying Emprint microwave ablation systems for treatment. Percutaneous microwave ablations performed between January 2022 and September 2022 were included in this study. Subsequently, immediate post-ablation echography images were subjected to retrospective evaluation to state the long ablated diameter, short ablated diameter, and volume. The calculated ablation lengths and volume indices were then compared between in vivo and ex vivo results obtained from laboratory experiments conducted on porcine liver. The ex vivo data showed a good correlation between energy delivered and both increasing ablated dimensions (both p < 0.001) and volume (p < 0.001). The in vivo data showed a good correlation for dimensions (p = 0.037 and p = 0.019) and a worse correlation for volume (p = 0.142). When comparing ex vivo and in vivo data for higher energies, the ablated volumes grew much more rapidly in ex vivo cases compared to in vivo ones. Finally, a set of correlations to scale ex vivo results with in vivo ones is presented. This phenomenon was likely due to the absence of perfusion, which acts as a cooling system.
Détection de communautés dans les grands graphes de terrain

Les grands graphes de terrain (encore appeles reseaux d'interactions ou reseaux complexes) permettent de modeliser de nombreux phenomenes dans diverses disciplines (sociologie, linguistique, epidemiologie, informatique, biologie, etc). Ces graphes possedent des proprietes structurelles non-triviales communes parmi lesquelles la presence de communautes (c'est a dire des ensemble de sommets fortement connectes entre eux et plus faiblement vers l'exterieur). Nous proposons dans cette these deux nouveaux algorithmes complementaires de detection de communautes dans les grands graphes de terrain. Le premier calcule une structure hie��rarchique de communautes (dendrogramme) a partir d'une distance. Cette distance, basee sur les marches aleatoires, mesure la similarite structurelle des sommets. Le second algorithme permet, a partir d'un dendrogramme (calcule par notre approche ou par toute autre approche), de determiner les partitions pertinentes des sommets en communautes a diverses echelles. Cet algorithme se base sur l'optimisation de fonctions de qualite. Nous proposons finalement une analyse comparative des principales approches de detection de communautes existantes. Cette analyse experimentale utilise un large jeu de graphes test reels et generes.
First Research on Bat Bacteria in Burkina Faso (West Africa)

The world is in turmoil with the emergence of various diseases in which bats play a key part. Indeed, bats are known to host bacteria that can create major public health problems. The investigation into bat bacteria was carried out from December 2020 to September 2021 at seven sites in Burkina Faso. Bat specimen collection occurred from 6 pm to 5 am with mist nets. On each bat captured, an oral and rectum swab was taken to search for bacterial species using standard bacterial culture methods. A total of 204 bats representing 11 species were captured. 183 bat specimens were infected by at least one bacterium with a prevalence of 89.7%. 54 species of bacteria divided into 30 genera were identified from the 183 specimens. Bacterial species richness was the highest in the bat Mops condylurus (A. Smith, 1833) followed by Epomo-phorus gambianus (Ogilby, 1835). Genus Escherichia was the most frequent of the bat species. Genus Pseudomonas alone is represented by six species. The most infected site was the rectum, from which we isolated 44 species of bacteria out of the 54 species. The most infected locality was Ouagadougou. Bacteria are highly pathogenic to humans and may be responsible for public health problems, such as Shigella sp. was identified and bacteria known to cause harm to bats such as Yersinia and Pasteurella were also isolated. From this study, decisions on the management of public health problems can be considered drown to avoid the emergence and re-emergence of certain zoonotic diseases.
B-Pose: Bayesian Deep Network for Camera 6-DoF Pose Estimation From RGB Images

Camera pose estimation has long relied on geometry-based approaches and sparse 2D-3D keypoint correspondences. With the advent of deep learning methods, the estimation of camera pose parameters, i.e., the six parameters that describe position and rotation denoted by 6 Degrees of Freedom (6-DoF), has decreased from tens of meters to a few centimeters in median error for indoor applications. For outdoor applications, errors can be quite large and highly dependent on the variations in occlusion, contrast, brightness, repetitive structures, or blur introduced by camera motion. To address these limitations, we introduce, B-Pose, a Bayesian Convolutional deep network capable of not only automatically estimating the camera's pose parameters from a single RGB image but also provides a measure of uncertainty in the parameter estimation. Reported experiments on outdoor and indoor datasets demonstrate that B-Pose outperforms SOTA techniques and generalizes better to unseen RGB images. A strong correlation is shown between the prediction error and the model's uncertainty, indicating that the prediction is almost always incorrect whenever the model's uncertainty is high.
Retinal Thickness in Myopes with OCT

Purpose: To investigate whether retinal thickness varies with refractive error. Also secondary to see if there is any difference in retinal thickness between the right and left eye. Methods: The inclusion criteria for the study was subjects without any pathologies, age between 18-45 and refractive error of maximum +0.75 SER and the myopia had no limit, as well as no astigmatism higher then -1.00D. Subjects, which fitted the inclusion criteria for the study, was shown to the OCT room were retinal thickness measurements were acquired first on the right and then left eye. To get the same reading area, the same setup was used and the fixation point was always centered for each patient. After all subjects had undergone the same method the results were analyzed using t-test and regression analysis. Results: The analysis showed a difference between emmetropic eyes and myopic eyes in the peripheral retinal thickness, having the myopes being significantly thinner. The inter myopic analysis showed no difference in retinal thickness in any of the points. This could however be due to the smaller sample size. The comparison between right and left eye showed a good symmetry between the two eyes both in the emmetropic and the myopic group. Conclusions: From this study we can conclude that the myopic group has a thinner peripheral retinal thickness than the emmetropic group. Central retinal thickness is not significantly different but could be due to the smaller sample size. There is no difference in retinal thickness between right and left eye.