Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation of ferromagnetic (In,Mn)As with a high Curie temperature of 90 K

The authors found high Curie temperatures of up to 90K in annealed (In,Mn)As epilayers grown by molecular beam epitaxy using a relatively high V/III beam flux ratio. Magnetization data suggest that increasing the As beam flux results in an increase in the effective Mn content, and the carrier transport data indicate an increase in the hole concentration from a 1019to1020cm−3 range with low-temperature annealing after growth. The highest Curie temperature was obtained in lattice matched (In,Mn)As∕Al(As,Sb) samples. Both Hall effect and magneto-optical polar Kerr rotation measurements confirm that the high Curie temperature is due to hole-mediated ferromagnetism.
Folate–Methionine Cycle Disruptions in ASD Patients and Possible Interventions: A Systematic Review

Autism Spectrum Disorder (ASD) has become a major public health concern due to its rapidly rising incidence over the past few years. Disturbances in folate or methionine metabolism have been identified in many individuals with ASD, suggesting that the folate–methionine cycle may play an essential role in the pathogenesis of autism. Thus, changes in metabolite concentrations associated with this cycle could be used as potential biomarkers and therapeutic targets for ASD. The aim of this systematic review is to elucidate the perturbations of this cycle and the possible interventions that may be proposed in this context. Several studies have shown that high levels of homocysteine and low levels of vitamins B12 and folate are associated with ASD. These changes in serum metabolites are influenced by poor diet. In fact, children with ASD tend to eat selectively, which could compromise the quality of their diet and result in nutrient deficiencies. Moreover, these disturbances may also be caused by genetic predispositions such as polymorphisms of the MTHFR gene. Few studies have demonstrated the beneficial effects of the use of nutritional supplements in treating ASD children. Therefore, larger, well-structured studies are recommended to examine the impact of vitamin B12 and folate supplementation on homocysteine levels.
Gyro-Landau fluid equations for trapped and passing particles

A new system of gyro-Landau fluid (GLF) equations for tokamak plasmas is presented. The new equations include both trapped particles, which can average the Landau resonance, and passing particles which do have a Landau resonance. The trap GLF (TGLF) model is unrestricted in trapped fraction or perpendicular wave number of the electrostatic perturbation. The linearly unstable eigenmodes of the TGLF equations include low-frequency trapped ion modes all the way up to high-frequency electron temperature gradient driftwaves. Extensive benchmarking of the linear TGLF eigenmodes with a large database of gyrokinetic linear stability calculations verifies that the TGLF model is accurate over the full range of plasma parameters tested.
Analyzing the influence of withering degree on the dynamic changes in non-volatile metabolites and sensory quality of Longjing green tea by non-targeted metabolomics

Withering is an important processing stage in green tea, which contributes to the tea flavor quality. The aim of this work was to comprehensively investigate the changes of chemical features and flavor attributes in Longjing green teas produced with five different withering degrees (moisture content of 75.05, 72.53, 70.07, 68.00, and 64.78%, w.b.). Combined with human sensory evaluation, electronic tongue and chromatic differences analysis, an assessment of the relationship between the withering degree and the sensory quality of Longjing tea was obtained. By using a non-targeted metabolomics approach, 69 significantly differential metabolites were screened. As the withering degree increased, most free amino acids and catechin dimers were increased, largely attributed to the hydrolysis of proteins and catechin oxidative polymerization, respectively. The contents of organic acids as well as phenolic acids and derivatives were reduced. Interestingly, flavone C-glycosides decreased overall while flavonol O-glycosides increased. The correlation analysis revealed that metabolites such as theasinensin F, theasinensin B, theaflavin, theaflavin-3,3′-gallate, theaflavin-3′-gallate, malic acid, succinic acid, quinic acid, theanine glucoside and galloylglucose had a greater influence on the taste and color of tea infusion (|r| > 0.6, p < 0.05). Overall, an appropriate withering degree at a moisture content of around 70% is more favorable to enhance the Longjing tea quality. These results may enhance the understanding of green tea flavor chemistry associated with withering and provide a theoretical basis for green tea processing.
Multistatic human micro-Doppler classification of armed/unarmed personnel

Classification of different human activities using multistatic micro-Doppler data and features is considered in this study, focusing on the distinction between unarmed and potentially armed personnel. A database of real radar data with more than 550 recordings from 7 different human subjects has been collected in a series of experiments in the field with a multistatic radar system. Four key features were extracted from the micro-Doppler signature after a short time Fourier transform analysis. The resulting feature vectors were then used as individual, pairs, triplets and all together before inputting to different types of classifiers based on the discriminant analysis method. The performance of different classifiers and different feature combinations is discussed aiming at identifying the most appropriate features for the unarmed against armed personnel classification, as well as the benefit of combining multistatic data rather than using monostatic data only.
Using nonessential singularities of the second kind in two-dimensional filter design

It is shown that nonessential singularities of the second kind are not necessarily obstacles to the design of well-behaved (practical bounded-input/bounded-output (BIBO) stable) two-dimensional (2-D) discrete recursive filter transfer functions. For some widely utilized classes of filters, such as fan filters, it is shown that the existence of a nonessential singularity of the second kind on the unit bidisc is in fact required and, further, such filters, although BIBO unstable, can be designed to be practical-BIBO stable and well-behaved in practical applications. >
Improvement of a Real-Time Reverse Transcription–Polymerase Chain Reaction Assay for the Sensitive Detection of the F Gene of Avian Orthoavulavirus-1 (AOAV-1)

Simple Summary Avian orthoavulavirus-1 (AOAV-1) can cause Newcastle disease in poultry, and thus lead to massive economic losses worldwide. Compared to the original assay, the adapted real-time reverse-transcription PCR presented here proved to be more sensitive for detecting currently circulating AOAV-1 strains, in particular the pigeon-type strains (pigeon paramyxovirus-1). This highlights the importance of constant monitoring of existing methods. Abstract Avian orthoavulavirus-1 (AOAV-1) is the causative agent of Newcastle disease in poultry. This highly infectious disease causes large economic losses annually and worldwide. AOAV-1 does not only infect poultry, but it has a very broad host range and has been detected in over 230 bird species to date. A distinct group of viral strains within AOAV-1 are pigeon-adapted strains, also named pigeon paramyxovirus-1 (PPMV-1). AOAV-1 is transmitted through the feces of infected birds and secretions from the nasal and oral cavities and eyes. It is worth mentioning that wild birds can transmit the virus to captive birds, especially feral pigeons to poultry. Therefore, early and sensitive detection of this virus—including the monitoring of pigeons—is of utmost importance. A variety of molecular methods for the detection of AOAV-1 already exist, but the detection of the F gene cleavage site of currently circulating PPMV-1 strains has not proven to be particularly sensitive or suitable. As presented here, by modifying the primers and probe of an already established real-time reverse-transcription PCR, the sensitivity could be increased, allowing for a more reliable detection of the AOAV-1 F gene cleavage site. Furthermore, it becomes clear how important it is to constantly monitor and, if necessary, adapt existing diagnostic procedures.
The Incidence of Retrograde Peri-Implantitis in a Single University Dental Hospital Training Center: A Retrospective Analysis

Background and objective: Retrograde peri-implantitis (RPI) is a periapical radiolucent lesion developed around the implant apex. This study aimed to investigate the Incidence of RPI in a single university dental hospital training center. Materials and Methods: All records of patients who received single Implants between 2016–2020 were screened. For cases that met inclusion criteria, clinical and radiographic data were analyzed. Results: A total of 215 were included and categorized as follows, Category A: implants were placed next to endodontically treated teeth (n = 58, 27%); category B, implants placed at the sites with previous endodontic involvement within 6 months of tooth extraction (n = 25, 11.6%); Category AB: implants placed at sites that fulfill the criteria of groups A and B (n = 18, 8.4%); and Category C: Implants that were placed next to vital teeth and at a site with no previous endodontic treatment or a site that was allowed to heal for more than six (n = 114, 53%). Categories A, B and AB served as the endodontically involved (EI) group, while category C served as non- endodontically involved (NEI) group. Only two sites (0.9%) were confirmed as RPI, both from group A (3.4%). Comparing all groups studied showed no statistically significant difference in RPI incidence. Conclusions: The incidence of RPI is low; however, endodontically treated teeth with periapical lesions (PALs) next to an implant site could contribute to RPI.
Reduced surface leakage current and trapping effects in AlGaN/GaN high electron mobility transistors on silicon with SiN/Al2O3 passivation

The surface leakage currents and the surface trapping effects of the AlGaN/GaN high electron mobility transistors (HEMTs) on silicon with different passivation schemes, namely, a 120 nm plasma enhanced chemical vapor deposited SiN, a 10 nm atomic layer deposited (ALD) Al2O3 and a bilayer of SiN/Al2O3 (120/10 nm) have been investigated. After SiN passivation, the surface leakage current of the GaN HEMT was found to increase by about six orders; while it only increased by three orders after the insertion of Al2O3 between SiN and AlGaN/GaN. The surface conduction mechanism is believed to be the two-dimensional variable range hopping for all the samples. The leakage current in the etched GaN buffer layer with SiN/Al2O3 bilayer passivation was also much smaller than that with only SiN passivation. The pulse measurement shows that the bilayer of SiN/Al2O3 passivation scheme can effectively reduce the surface states and suppress the trapping effects.
Mesoscale Convective Systems and Their Synoptic-Scale Environment in Finland

AbstractThe environments within which high-latitude intense and nonintense mesoscale convective systems (iMCSs and niMCSs) and smaller thunderstorm clusters (sub-MCSs) develop were studied using proximity soundings. MCS statistics covering 8 years were created by analyzing composite radar imagery. One-third of all systems were intense in Finland and the frequency of MCSs was highest in July. On average, MCSs had a duration of 10.8 h and traveled toward the northeast. Many of the linear MCSs had a southwest–northeast line orientation. Interestingly, a few MCSs were observed to travel toward the west, which is a geographically specific feature of the MCS characteristics. The midlevel lapse rate failed to distinguish the environments of the different event types from each other. However, in MCSs, CAPE and the low-level mixing ratio were higher, the deep-layer-mean wind was stronger, and the lifting condensation level (LCL) was lower than in sub-MCSs. CAPE, low-level mixing ratio, and LCL height were the best.
Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture

Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process‐guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.
Social Support in a Cancer Patient-Informal Caregiver Dyad: A Scoping Review

Simple Summary In addition to studies on the quality of life, hope, self-efficacy, and unsatisfied needs, research on social support is a priority in the search for ways to cope with cancer, which affects a patient and their relatives. Coping with cancer, therefore, also applies to caregivers. Hence, psychosocial interventions that reduce the level of stress and, above all, improve the ability to cope with difficult situations are more effective when conducted in dyads. A scoping review of studies on the impact of social support in a dyadic patient-informal caregiver relationship during cancer treatment in the period 2012–2022 was conducted. Thirteen articles met the inclusion criteria and qualified for the analysis. Abstract Social support that includes promoting healthy behaviours throughout the oncology pathway, from diagnosis to treatment to survival, can leverage existing support networks and improve the health of patients and family members in supportive roles. This scoping review aimed to identify and summarise the impact of social support on the patient-informal caregiver relationship during cancer treatment. Inclusion criteria were related to a high focus on dyadic cancer patient-informal caregiver relationships, considering a population of adult cancer patients in active hospitalisation on an oncology ward, and published between 2012 and 2022 to get a portrait of the literature that might influence the current practice. A systematic search using the “Population, Concept, and Context” framework was performed in PubMed, Web of Science, SCOPUS, EBSCO Medline, and CINAHL: 13 articles from the 16,425 pre-qualified articles published between 2012 and 2022. The narrative synthesis of the included studies highlighted that social support, encompassing its different forms within the context of dyads, is frequently associated with an enhanced quality of life, hope, and resilience of both patients and informal caregivers. However, it is important to recognize that the support interventions provided to patients, particularly caregivers, were frequently not thoroughly evaluated or explained, and the sample sizes of the included studies were often limited. Therefore, this review clarified the social and clinical potential of social support for the patient-informal caregiver relationship, paving the way for future robust studies that require to be powered and designed on specific outcomes to allow informing the practice on specific recommendations.
Simulation of free surface effects on turbulence with a Reynolds stress model

The main features of the highly anisotropic turbulence in the region of vanishing shear near the free surface of two-dimensional channel flow have been calculated using a Reynolds-stress transport model with surfaceeffect terms in the pressure-strain-rate correlation. The form of these terms is identical for solid and free surfaces. For a free surface, however, the surface-proximity function is an order of magnitude greater than the function for a rigid surface.
A New Method Based on Encoding Data Probability Density and Convolutional Neural Network for Rotating Machinery Fault Diagnosis

In order to apply the advantages of image recognition for fault diagnosis using convolutional neural network (CNN), it is necessary to convert one-dimensional (1D) signal data into two-dimensional (2D) images. Traditional signal-based conversion methods face the challenges of complex feature extraction process, high dependence on expert knowledge and poor feature repeatability, which hinder timely and accurate fault diagnosis. Therefore, this paper proposes a fault diagnosis method for rotating machinery in virtue of Data Probability Density-Gram Angle Field-Convolutional Neural Network (DPD-GAF-CNN). DPD-GAF first computes the DPD of a 1D time series through parameter-free statistics, and then encodes the DPD into a 2D feature image that directly reflects the mean and standard deviation of the probability distribution. Besides the simplified transformation process, no artificially designed features are required like the original GAF to encode in the process of fault diagnosis. After that, the CNN based on LeNet-5 transformation is used to achieve high-precision fault classification. The proposed fault diagnosis method is verified and compared with other existing intelligent methods using the experimental data generated by the planetary gearbox test bench with various faulty conditions and the bearing data set of Case Western Reserve University. The results show that the presented method can effectively improve the accuracy and stability of fault diagnosis with the classification accuracy of several fault datasets up to 99.9%.
Visualizing the perturbation of partial integrability

In this paper we explain how the perturbation of partial integrability can be visualized by the restriction of the Poincaré map to an invariant two-dimensional subset of its full domain. The most appropriate surface is a normally hyperbolic invariant manifold built up by stack construction over the most prominent hyperbolic fixed point of the reduced Poincaré map for the partially integrable case. As an example, we present the numerical results for the motion of an electron in a perturbed magnetic dipole field.
Diagnostic Modeling of the Indian Monsoon Onset. Part I: Model Description and Validation

Abstract A new type of diagnostic model is developed and applied to the study of the onset of the Indian summer monsoon. The purpose of the model is to aid in the analysis of interactions between the physical processes that affect the monsoon onset. The model is one-dimensional and consists of a single atmospheric column coupled to an ocean mixed layer. The atmospheric component of the model includes representations of all the physical processes typically included in general circulation models, except that the fields of vertical motion and horizontal advection are specified at each time step from observational data rather than predicted. With these time-dependent observational inputs, the model is then integrated numerically to produce consistent profiles of atmospheric temperature and humidity, together with energy budget components and other diagnostic quantities. The atmospheric model is based on the thermodynamic energy equation and a conservation equation for water. Parameterizations of the effects o.
Threshold peaks and structures in elastic and vibrationally inelastic electron impact cross sections for CS2

Elastic, vibrationally inelastic and superelastic cross sections were measured for electron impact on CS2 at 135°, with emphasis on the threshold region. The elastic cross section rises dramatically at low energies. The cross sections for the excitation of all three fundamental vibrations (010), (100) and (001) have very strong threshold peaks, more than ten times higher than those observed for CO2. The elastic and the (010) and (100) inelastic cross sections have deep narrow structures at energies up to about 0.3 eV. The structures are weak for the (001) vibration. Substantial excitation of overtone vibrations is observed even near threshold. The threshold structures appear to be caused primarily by the 2 Πu valence state of CS2−. Various broad resonant peaks are observed in the cross sections in the 1–12 eV range.
The Hepatoprotective Effect of Two Date Palm Fruit Cultivars’ Extracts: Green Optimization of the Extraction Process

Date palm fruit (Phoenix dactylifera: Arecaceae) is rich in essential nutrients and possesses several pharmacological and medicinal activities. The current study aimed to optimize a water bath-assisted extraction method for two cultivars of date palm fruits, Anbara (An) and Reziz (Rz), and investigated the protective effect of the optimized date palm fruit extract against CCl4-induced liver toxicity in relation to oxidative stress, inflammation, apoptosis, and DNA integrity. The optimization process of two date palm fruit cultivars was applied, using response surface methodology through adjusting three “factors”; time, temperature, and rotation, to allow maximum contents of total phenolic (TPC), total flavonoid (TFC), reducing power (FRAP) and scavenging activity (ABTS) of the extract “responses”. Extraction factors’ application significantly enhanced TPC, TFC, FRAP, and ABTS responses by 1.30, 1.23, 3.03, and 2.06-fold, respectively in An and 2.18, 1.71, 1.11, and 2.62-fold, respectively in Rz, in relation to the convectional water extraction. Furthermore, co-administered CCl4 with An or Rz optimized extracts enhanced body weight gain, amended hepatic architecture, and diminished collagen fiber accumulation. Furthermore, An or Rz extracts reduced liver enzymes, hydroxyproline, alpha-fetoprotein (AFP), MDA, inflammatory cytokine (TNF-α, NF-κB) levels, and DNA fragmentation, while increasing deteriorated adiponectin (ADP) and antioxidant enzyme (GSH, GPX, NO, and IFN-γ) levels, relative to CCl4-administered animals. The protective effects of An or Rz-optimized extracts were also evidenced by suppressing hepatic fibrosis and improving liver function and structure via modulating oxidative stress, inflammation, and apoptosis, in CCl4-induced hepatic damage. Hence, the optimized extraction process for the two date palm fruits resulted in extracts which are rich in phenolic and flavonoid contents and with an elevated antioxidant power. The presence of these rich extracts could help to explain their proven hepatoprotective activity against CCl4-induced liver toxicity.