Miracle-dz/UniFAR-FTUs huggingface dataset:
Frequency domain water table fluctuations reveal recharge in fractured aquifers depends on both intense and seasonal rainfall and unsaturated zone thickness

Groundwater recharge is difficult to estimate, especially in fractured aquifers, because of the spatial variability of the soil properties and because of the lack of data at basin scale. A relevant method, known as the WTF method, consists in inferring recharge directly from the water table fluctuations (WTF) observed in boreholes. However, the WTF method neglects the impact of lateral groundwater redistribution in the aquifer, i.e. assumes that all the WTF are attributable to recharge. In this study, we developed the WTF approach in the frequency domain to better consider groundwater lateral flow, which quickly 5 redistributes the inpulse of recharge and mitigates the link between WTF and recharge. First, we calibrated a 1D analytical groundwater model to estimate hydrodynamic parameters at each borehole. These parameters were defined from the WTF recorded for several years, independently of prescribed potential recharge. Second, calibrated models are reversed analytically in the frequency domain to estimate recharge fluctuations (RF) at weekly to monthly scales from the observed WTF. Models were tested on two twin sites with similar climate, fractured aquifer, and land use but different hydrogeologic settings: one 10 has been operated as a pumping site for the last 25 years (Ploemeur, France) while the second has not been perturbed by pumping (Guidel). Results confirm the important role of rainfall temporal distribution to generate recharge. While all rainfall contribute to recharge, the ratio of recharge to rainfall minus potential evapotranspiration is frequency dependent, varying between 20 − 30 % at periods < 10 days , 30 − 50 % at monthly scale, and reaching 75 % at seasonal time scales. We further show that the unsaturated zone thickness controls the intensity and timing of RF. Overall, this approach contributes to better 15 assess recharge and enable to improve the representation of groundwater systems within hydrological models. In spite of the heterogeneous nature of aquifers, parameters controlling WTF can be inferred from WTF time series.
Association between Intermediate-Density Lipoprotein Particles and the Progression of Carotid Atherosclerosis: A Community-Based Cohort Study

Aim: Experimental studies report that intermediate-density lipoprotein (IDL), the precursor of low-density lipoprotein, promotes atherosclerotic plaque formation. However, whether IDL is involved in the development of atherosclerosis in humans is still unclear. The aim of this community-based study is to examine the association between IDL particle (IDL-P) concentrations and the 5-year progression of carotid atherosclerosis. Methods: Baseline IDL-P concentrations were measured using nuclear magnetic resonance spectroscopy in 927 participants aged 45–74 years with no history of cardiovascular disease (CVD) at baseline. To estimate the association between baseline IDL-P concentrations and 5-year progression of carotid atherosclerosis, indicated by atherosclerotic plaque progression and changes in total plaque area (TPA), multivariable-adjusted regression was employed. Results: During the 5-year follow-up period, 45.8% of participants developed new plaques. Baseline IDL-P concentrations were significantly associated with the progression of carotid atherosclerosis. Participants in the highest quartile of IDL-P concentrations exhibited 1.36-fold (95% confidence interval [CI]: 1.09–1.68) increased progression of carotid plaque and 1.67-fold (95% CI: 1.04–2.69) higher TPA than those in the lowest quartile. These relationships were independent of baseline concentrations of low-density lipoprotein particles and very-low-density lipoprotein particles and their subclasses. Conclusions: Elevated IDL-P concentrations were independently associated with the progression of carotid atherosclerosis, suggesting that IDL-P is a novel risk factor for the development of atherosclerosis.
Limit theorems under the Maxwell-Woodroofe condition in Banach spaces

We prove that, for (adapted) stationary processes, the so-called Maxwell-Wood-roofe condition is sufficient for the law of the iterated logarithm and that it is optimal in some sense. We obtain a similar conclusion concerning the Marcinkiewicz-zygmund strong law of large numbers. Those results actually hold in the context of Banach valued stationary processes, including the case of $L^r$-valued random variables, with $1\le r<\infty$. In this setting we also prove the weak invariance principle, under a version of the Maxwell-Woodroofe condition, generalizing a result of Peligrad and Utev \cite{PU}. Our results extend to non-adapted processes as well, and, partly to stationary processes arising from dynamical systems. The proofs make use of a new maximal inequality and of approximation by martingales, for which some of our results are also new.
Extraordinary Hall effect in La0.7Ca0.3MnO3 and La0.7Ba0.3MnO3 thin films

The Hall effect of La0.7Ba0. 3MnO3 and La0.7Ca0. 3MnO3 thin films was measured in magnetic fields μ0H ⩽ 1 T and for temperatures 10 K ⩽ T ⩽ 340 K. In the ferromagnetic phase the slope of the Hall resistivity at zero magnetic induction rapidly increases with temperature until a maximum is reached at the Curie temperature TC. A detailed comparison of the Hall resistivity with the magnetization facilitates the separation of the ordinary and extraordinary Hall effect. The ordinary Hall constant RH shows a jump below TC. The extraordinary Hall constant RA scales with the zero-field resistivity. At low temperatures we find a quadratic dependence of RA on the resistivity crossing over to a linear dependence at higher temperatures. Whereas the quadratic scaling law in the ferromagnetic phase can be explained by a conventional side-jump mechanism, the linear dependence near TC and in the hopping regime is inconsistent with conventional skew scattering. The data are compared to a recent theory of the Hall effect in double-exchange ferromagnets.
Vehicles Detection and Tracking in Advanced & Automated Driving Systems: Limitations and Challenges

: Automated Driving Systems (ADS) and Advanced Driving Assistance Systems (ADAS) are widely investigated for developing safe and intelligent transportation systems. A common module in both systems is road objects monitoring, in which the semantic segmentation for road scene understanding has encountered lots of challenges. Due to the rapid evolution in technologies applied in vision-based systems in many fields, diverse techniques and algorithms have emerged to tackle such limitations, as invariant-illumination conditions, shadows, false positives, misdetections, weather conditions, real time processing and occlusions. A comparative study is conducted in this paper for vehicle detection and tracking methods applied on images and streams produced from monocular cameras and sensors in ADAS and ADS in terms of the aforementioned problems, the used dataset, along with the extracted features and the associated evaluation criteria. The study deduces the limitations of the current state-of-art techniques in such particular systems and highlights the main directions that can be ado ted for future research and investigations.
Performance Analysis of Fractional-Order Adaptive Filtering Algorithm and Its Improvement

Considering the $ \alpha$-stable input signals and noises, several robust fractional-order adaptive filtering algorithms have been proposed in recent years. However, the mean-square performance analysis of the FoAF algorithm has not been well studied in the literature. Toward that end, this letter provide a theoretical mean-square performance analysis of the FoAF algorithm, involving transient and steady-state behavior. Furthermore, an improved fractional-order adaptive filtering algorithm is derived by utilizing the M-estimate technique. Simulation experiments verify the results of the theoretical analysis and demonstrate the advantages of the proposed algorithm in heavy-tailed non-Gaussian environments.
Detecting Enclosed Board Channel of Data Acquisition System Using Probabilistic Neural Network with Null Matrix

The board channel is a connection between a data acquisition system and the sensors of a plant. A flawed channel will bring poor-quality data or faulty data that may cause an incorrect strategy. In this paper, a data-driven approach is proposed to detect the status of the enclosed board channel based on an error time series obtained from multiple excitation signals and internal register values. The critical faulty data, contrary to the known healthy data, are constructed by using a null matrix with maximum projection and are labelled as training examples together with healthy data. Finally, the status of the enclosed board channel is validated by a well-trained probabilistic neural network. The experimental results demonstrate the effectiveness of the proposed method.
The association of angiotensin-converting enzyme gene polymorphism with respiratory distress syndrome in premature neonates.

BACKGROUND There was a contradiction in the previous literature on whether the D/D genotype of angiotensinconverting enzyme (ACE) is a protective or risk factor for respiratory distress syndrome (RDS) in premature neonates. To solve this debate, we intended to examine the association between ACE gene polymorphism and RDS in premature neonates. METHODS We enrolled a total of 100 premature neonates with gestational age below 37 weeks. They were divided into 2 groups, the case group included 50 premature neonates diagnosed with RDS. While the control group included 50 premature neonates with no signs of RDS. We assessed ACE gene polymorphism using polymerase chain reaction. All neonates underwent chest x-ray, echocardiography, and routine laboratory investigations. RESULTS D/D and D/I genotypes were higher in the control group (48% and 50%) than in the case group (26% and 40%). Whereas, I/I genotype was lower in the control group (2%) than in the case group (34%) (p < 0.001). By counting D alleles among members of both groups, D-alleles were significantly higher in the control group (73%) than in the case group (46%) (p < 0.001). CONCLUSIONS In premature neonates, D/D and D/I genotypes and D-alleles are protective factors for RDS. Whereas, I/I genotype and I-alleles are associated with the incidence of RDS with complications.
A New Robust Variable Structure Controller With Nonlinear Integral-Type Sliding Surface for Uncertain More Affine Nonlinear Systems with Mismatched Uncertainties and Disturbance

In this note, a systematic general design of a new robust nonlinear variable structure controller based on state dependent nonlinear form is presented for the control of uncertain affine nonlinear systems with mismatched uncertainties and mismatched disturbance. After an affine uncertain nonlinear system is represented in the form of state dependent nonlinear system, a systematic design of a new robust nonlinear variable structure controller is presented. To be linear in the closed loop resultant dynamics, the nonlinear integral-type sliding surface is applied. A corresponding control input is proposed to satisfy the closed loop exponential stability and the existence condition of the sliding mode on the nonlinear integral-type sliding surface, which will be investigated in Theorem 1. Through a design example and simulation studies, the usefulness of the proposed controller is verified.
An effective context‐focused hierarchical mechanism for task‐oriented dialogue response generation

Task‐oriented dialogue system (TOD) is one kind of application of artificial intelligence (AI). The response generation module is a key component of TOD for replying to user's questions and concerns in sequential natural words. In the past few years, the works on response generation have attracted increasing research attention and have seen much progress. However, existing works ignore the fact that not each turn of dialogue history contributes to the dialogue response generation and give little consideration to the different weights of utterances in a dialogue history. In this article, we propose a hierarchical memory network mechanism with two steps to filter out unnecessary information of dialogue history. First, an utterance‐level memory network distributes various weights to each utterance (coarse‐grained). Second, a token‐level memory network assigns higher weights to keywords based on the former's output (fine‐grained). Furthermore, the output of the token‐level memory network will be employed to query the knowledge base (KB) to capture the dialogue‐related information. In the decoding stage, we take a gated‐mechanism to generate response word by word from dialogue history, vocabulary, or KB. Experiments show that the proposed model achieves superior results compared with state‐of‐the‐art models on several public datasets. Further analysis demonstrates the effectiveness of the proposed method and the robustness of the model in the case of an incomplete training set.
Extracellular Vesicles for Regenerative Medicine Applications

Tissue engineering and regenerative medicine (TERM) may be defined as a translational discipline focused on the development of novel techniques, devices, and materials to replace or repair injured or diseased tissue and organs. The main approaches typically use cells, scaffolds, and signaling molecules, either alone or in combination, to promote repair and regeneration. Although cells are required to create new functional tissue, the source of cells, either from an exogenous allogeneic or autologous source or through the recruitment of endogenous (autologous) cells, is technically challenging and risks the host rejection of new tissue. Regardless of the cell source, these approaches also require appropriate instruction for proliferation, differentiation, and in vivo spatial organization to create new functional tissue. Such instruction is supplied through the microenvironment where cells reside, environments which largely consist of the extracellular matrix (ECM). The specific components of the ECM, and broadly the extracellular space, responsible for promoting tissue regeneration and repair, are not fully understood, however extracellular vesicles (EVs) found in body fluids and solid phases of ECM have emerged as key mediators of tissue regeneration and repair. Additionally, these EVs might serve as potential cell-free tools in TERM to promote tissue repair and regeneration with minimal risk for host rejection and adverse sequelae. The past two decades have shown a substantial interest in understanding the therapeutic role of EVs and their applications in the context of TERM. Therefore, the purpose of this review is to highlight the fundamental characteristics of EVs, the current pre-clinical and clinical applications of EVs in TERM, and the future of EV-based strategies in TERM.
Feromagnetic "$\pi$"-junctions

We investigate Josephson coupling through a ferromagnetic thin film using Superconductor-Insulator-Ferromagnet-Superconductor planar junctions. Damped oscillations of the critical current are observed as a function of the ferromagnetic layer thickness. We show that they result from the exchange energy gained or lost by a quasiparticle Andreev-reflected at the ferromagnet-superconductor interface. The critical current cancels out at the transition from positive ("0") to negative ("$\pi$") coupling, in agreement with theoretical calculations.
From optimal to robust climate strategies: expanding integrated assessment model ensembles to manage economic, social, and environmental objectives

Cost-benefit integrated assessment models generate welfare-maximizing mitigation pathways under a set of assumptions to deal with deep uncertainty in future scenarios. These assumptions include socio-economic projections, the magnitude and dynamics of climate impacts on the economy, and physical climate response. As models explore the uncertainty space within the boundaries of their objective functions, they risk providing scenarios which are too narrow and not sufficiently robust. Here, we apply robust and multi-objective decision-making methods to extract relevant information from a large ensemble of optimal emissions-reduction pathways generated by a regionalized cost-benefit integrated assessment model under deterministic welfare optimization. We show that shifting the focus from optimal to robust solutions reduces the uncertainty in mitigation strategies and aligns them toward the Paris goals. Moreover, we analyze the trade-offs between climatic (temperature), social (inequality) and economic (welfare) objectives and illustrate four robust pathways under various decision-making criteria. We show that robust mitigation strategies can lead to regional emission-reduction strategies which are fair. Our results show how to extract more comprehensive climate strategies from available scenario ensembles and that the highest discrepancies at the local level policies are found in the developing and most-impacted regions.
CLIMATE CHANGE AND INHABITANTS’ PERCEPTION OF FLOOD RISK: PEÑÓN DE LOS BAÑOS, VENUSTIANO CARRANZA, MEXICO CITY, MEXICO

Climate change represents a long-term variability, namely decades of state of the climate, as identified by means of a statistical analysis containing a record of weather changes over time. These climate changes, which include temperature and precipitation mean values, may arise from natural processes within the same climate system or from anthropogenic events. Therefore, it is a mistake to attribute any temperature changes or variations to climate change without having some records or other comparable climate studies, as climate change entails a change in all climate features as determined by meteorological variables. Both in Mexico and worldwide, weather changes have occurred and have been attributed to climate change. However, in populations where floods are recurring, it is worth learning what population understands by climate change, if they find it to be a cause of floods, and why. To this end, a population was sampled (the town of Peñón de los Baños, in Mexico City), and semi-structured interviews on flood causes were used to ask people about the connection of floods with climate change. The importance of this research was not only to learn whether climate change is a cause of floods, as compared to the science behind what climate change is, but what the population is suggesting that should be done to solve the problem of floods, and to take local actions that contribute directly to control climate change.
Effect of Health Promoting Life Style Model on Self-Efficacy for Patient with Metabolic Syndrome

Background: Metabolic syndrome" MetS " is defined as a cluster of glucose intolerance, hypertension, dyslipidemia and central obesity with insulin resistance as the source of pathogenesis. MetS is considered as lifestyle disorder because poor dieting and lack of regular physical activity lead to insulin resistance or insulin resistance-linked obesity, a condition where the body’s cells are incapable of taking up glucose from the blood. Aim of the study:: This study aimed to evaluate the effect of implementing health promoting life style model on self-efficacy for patient with metabolic syndrome. Subjects and Methods: Research design: A quasi experimental design was used. Setting: This study was conducted at medical unit and diabetic out-patients clinics affiliated to Zagazig University Hospitals which is located at Sharquia Governorate, Egypt. Subjects: A purposive sample of 100 adult patients with type 2diabetes mellitus, 50 randomly allocated to each group study and control. Tools of data collection: Structured interview questionnaire, Self-rated abilities for health practices (Health self-efficacy measure) scale, and Health-Promoting Lifestyle Profile) questionnaire. Results: Most (92%) of the studied groups pre-test were having low self-efficacy (≤ 37.3), while majority (80%) of the studied groups post-test were having high self-efficacy (≥ 74.6). There was a positive highly significant correlation coefficient between total health-promoting lifestyle and self-efficacy among studied patients posttest ( r = 611 at p =.000). Also , there was a positive correlation coefficient between total self-efficacy and total knowledge among studied patients posttest ( r = 593 at p =.000 ). Conclusion : The implementation of Health Promoting Life Style Model for patients with MetS had a statistically significant positive effect on improving study group patients' knowledge, self-efficacy and health promoting behaviors versus to control group, which supported the proposed hypothesis. Recommendations: Further self-efficacy and health-promoting behavior training programs for MetS patients should be conducted.
Recent advances in nanoparticle-based drug delivery systems for rheumatoid arthritis treatment

Nanotechnology has increasingly emerged as a promising tool for exploring new approaches, from treating complex conditions to early detection of the onset of multiple disease states. Tailored designer nanoparticles can now more comprehensively interact with their cellular targets and various pathogens due to a similar size range and tunable surface properties. The basic goal of drug delivery is to employ pharmaceuticals only where they are needed, with as few adverse effects and off-target consequences as possible. Rheumatoid arthritis (RA) is a chronic inflammatory illness that leads to progressive loss of bone and cartilage, resulting in acute impairment, decreased life expectancy, and increased death rates. Recent advancements in treatment have significantly slowed the progression of the disease and improved the lives of many RA sufferers. Some patients, on the other hand, attain or maintain illness remission without needing to continue immunosuppressive therapy. Furthermore, a large percentage of patients do not respond to current treatments or acquire tolerance to them. As a result, novel medication options for RA therapy are still needed. Nanocarriers, unlike standard medications, are fabricated to transport drugs directly to the location of joint inflammation, evading systemic and negative effects. As a result, researchers are reconsidering medicines that were previously thought to be too hazardous for systemic delivery. This article gives an overview of contemporary nanotechnology-based tactics for treating rheumatoid arthritis, as well as how the nanotherapeutic regimen could be enhanced in the future.