Miracle-dz/UniFAR-FTUs huggingface dataset:
Grazing increases evapotranspiration without the cost of lowering soil water storages in arid ecosystems

Grazing is the predominant land use practice in arid environments; however, there are relatively few studies of grazing effects on ecosystem functioning. We assessed the impact of grazing on soil moisture, evapotranspiration (ET), canopy conductance (Gc), and root water uptake in the Patagonian steppe. Studies were done in 3 sites along a gradient of grazing intensity. High grazing intensity increased the soil water storage by 24% and decreased the amount of water extracted from deep layers compared to the low grazing intensity. Grazing affected ET and its partitioning into transpiration (T) and evaporation. High shrub cover and Gc increased ET and T or ET partitioning in the heavily grazed site. Annual ET increased from 78% to 92% of the annual precipitation from the lowest to the highest grazing intensity, respectively. Total T was 21% higher in the highest intensity site compared to the lowest intensity site. Changes in Gc suggest that grazing modified the canopy architecture, and thus the response of vegetation to environmental factors. At the beginning of the growing season when moisture was high, Gc exhibited the highest value in the heavily grazed site, but a strong regulation of water losses was observed under drier conditions. This study emphasizes the need to assess simultaneously multiple factors for understanding regulatory mechanisms of grazing effects on hydrological processes. From a sustainable management point of view, we suggest that increasing the number of water sources, and thus spreading the sheep in a paddock, can enhance the stocking rate while maintaining soil water storage.
Temporomandibular Disorders Treatments and Its Effects on Headaches

Objective: temporomandibular Disorders (TMD) are the most common causes of chronic orofacial pain and, along with primary headaches, are considered Chronic Overlapping Pain Conditions (COPCs). The aim of this study is to evaluate TMD treatment effects in individuals with comorbid headaches. Methods: a systematic review was conducted over a search in the database up to October 2020. Selected studies were randomized clinical trials with individuals diagnosed with TMD and comorbid headaches compared to a control group after treatments for TMD. All included studies were evaluated for their methodological quality through the Cochrane Collaboration tool for assessing the risk of bias. Results: seven studies fulfilled the inclusion criteria and were applied in the review, with a total of 432 participants. Four studies were included in a meta-analysis. There was no significative mean difference in the frequency of headache after TMD treatment, nor for a reduction in pain, after TMD intervention for less than 12 weeks. Although for an individual with a TMD intervention period higher than 12 weeks, there was a significant reduction in pain. Conclusion: there is moderate evidence that painful TMD therapies for 12 weeks or higher reduce headache intensity in individuals with painful TMD and headaches. Simultaneous management of TMD and headache must be prioritized for more effective results on both conditions.
Multiphase Constant On-Time Control With Phase Overlapping–Part II: Stability Analysis

Processor core voltage regulators (VRs) widely use pulse distributor-based multiphase current-mode constant on-time (COT) control to improve light-load performance, achieve fast transient response, and simplify phase interleaving. Part I of this article presented a small-signal model of this control for the whole duty cycle range. Part II of this article finds that the total current loop of an $N$-phase COT-controlled VR becomes unstable for duty cycle $D>1/N$ without a sufficient external ramp. Also, the minimum ramp (or critical ramp) required to preserve stability varies with the number of overlapping phases. Hence, this article derives the critical ramp in each phase overlapping region using the model from Part I. The unstable closed-loop poles of the total current loop in phase-overlapping regions cause this issue. Hence, we first identified the characteristic equation that introduces these poles. Then, we rearranged it to formulate a theoretical loop gain and derived a stability condition using the discrete-time Nyquist criterion. Finally, we evaluated this condition to determine the exact critical ramp expressions up to four overlapping phases and an analytical approximation for the same beyond four overlapping phases. The critical stability limits are verified using SIMPLIS simulations and experimental results from a six-phase COT-controlled buck platform.
Humoral Immune Responses after an Omicron-Adapted Booster BNT162b2 Vaccination in Patients with Lymphoid Malignancies

To accommodate waning COVID-19 vaccine immunity to emerging SARS-CoV-2 variants, variant-adapted mRNA vaccines have been introduced. Here, we examine serological responses to the BA.1 and BA.4-5 Omicron variant-adapted BNT162b2 COVID-19 vaccines in people with lymphoid malignancies. We included 233 patients with lymphoid malignancies (chronic lymphocytic B-cell leukemia: 73 (31.3%), lymphoma: 89 (38.2%), multiple myeloma/amyloidosis: 71 (30.5%)), who received an Omicron-adapted mRNA-based COVID-19 vaccine. IgG and neutralizing antibodies specific for the receptor-binding domain (RBD) of SARS-CoV-2 were measured using ELISA-based methods. Differences in antibody concentrations and neutralizing capacity and associations with risk factors were assessed using mixed-effects models. Over the period of vaccination with an Omicron-adapted COVID-19 vaccine, the predicted mean concentration of anti-RBD IgG increased by 0.09 log10 AU/mL/month (95% CI: 0.07; 0.11) in patients with lymphoid malignancies across diagnoses. The predicted mean neutralizing capacity increased by 0.9 percent points/month (95% CI: 0.2; 1.6). We found no associations between the increase in antibody concentration or neutralizing capacity and the variant included in the adapted vaccine. In conclusion, a discrete increase in antibody concentrations and neutralizing capacity was found over the course of Omicron-adapted vaccination in patients with lymphoid malignancies regardless of the adapted vaccine variant, indicating a beneficial effect of Omicron-adapted booster vaccination in this population.
Artificial Intelligence as Catalyst for the Tourism Sector: A Literature Review

The analysis of Artificial Intelligence techniques and models used in the tourism sector provides insightful information for the management and innovation of this industry. In this paper, we conduct a comprehensive review of the different techniques and models, in regards to Artificial Intelligence when applied to the tourism industry. Specifically, we present a categorization of Artificial Intelligence applications used in different areas of tourism. The results allow to recognize valid studies and useful tools for the activation and growth of the tourism sector, an industry that represents a significant increase in the Gross Domestic Product of various economies and supports the development of life conditions for their inhabitants. Artificial Intelligence applications generate more personalized travel experiences, improve the efficiency of tourism services and strengthen the tourism competitiveness of the destination.
Control Concept for a Molten Salt Receiver in Star Design

A promising approach to reduce the system costs of molten salt solar receivers is to enable the irradiation of the absorber tubes on both sides. The star design is an innovative receiver design, pursuing this approach. The unconventional design leads to new challenges in controlling the system. This paper presents a control concept for a molten salt receiver system in star design. The control parameters are optimized in a defined test cycle by minimizing a cost function. The control concept is tested in realistic cloud passage scenarios based on real weather data. During these tests, the control system showed no sign of unstable behavior, but to perform sufficiently in every scenario further research and development like integrating Model Predictive Controls (MPCs) need to be done. The presented concept is a starting point to do so.
Assessment of Pierce's disease susceptibility in
 Vitis vinifera
 cultivars with different pedigrees

E. Deyett, J. Pouzoulet, J.-I. Yang, V. E. Ashworth, C. Castro, M. C. Roper and P. E. Rolshausen* Department of Botany and Plant Sciences, University of California Riverside, 900 University Ave, Riverside, CA 92521, USA; Unit e Mixte de Recherche, 1287 Ecophysiologie et G enomique Fonctionnelle de la Vigne (EGFV), INRA, Institut des Sciences de la Vigne et du Vin, 33883 Villenave d’Ornon, France; Department of Plant Pathology and Microbiology, National Taiwan University, Taipei 106, Taiwan; and Department of Microbiology and Plant Pathology, University of California Riverside, 900 University Ave, Riverside, CA 92521, USA
Using eye-tracking to assess sourcing during multiple document reading: A critical analysis

During the last 15 years, there have been some efforts to extend the use of eye-tracking to researching reading in complex contexts, such as the reading of multiple documents. The research community involved in this extension has been interested in higher-order comprehension processes occurring in complex reading contexts, such as sourcing, defined as the processes of attending to, representing, evaluating, and using available or accessible information about the sources of textual content. In this article, we argue that extending eye-tracking research to investigate more complex reading contexts has been made without critically reflecting on its reliability and validity in those contexts. Specifically, because eye-tracking captures automatic as well as conscious processes, it is currently an open question how reliably and consistently eye-tracking captures the strategic sourcing processes that take place during multiple document reading, in particular compared to subjective methods that mainly target conscious processes, such as interviews. We compared sourcing indicators based on eye-tracking measures to sourcing indicated by a post-reading interview. Results suggested that current eye-tracking indices of sourcing are not universally valid and reliable measures, and that simpler methods, such as interviews, may be more suited to assess strategic sourcing during multiple document reading.
Enhancing Forecasting Accuracy Through Artificial Intelligence-Driven Complexity-Conscious Prediction Modeling

: Traditional linear and simpler models often fail to capture the complex, multifaceted nature of real-world data, leading to inaccurate predictions. This research addresses this challenge by exploring the potential of complexity-conscious prediction, which seeks to incorporate the inherent intricacy within the data. The paper aims to demonstrate the significance of acknowledging and incorporating data complexity in forecasting models, especially in domains where accurate predictions are crucial for informed decision-making and can have a profound impact. By employing statistical methods to measure intricate patterns and by developing advanced deep learning models, such as Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), this research endeavors to achieve more accurate and reliable forecasts. Both LSTM and GAN models demonstrated remarkable capability in handling complex time series data, with MAPE values below 3.5%, indicating high accuracy. The GAN model, in particular, showed exceptional performance with a MAPE of less than 2% across all tested stocks, underscoring its advanced predictive capabilities. The findings suggest that deep learning models, especially GANs, substantially improve accuracy over traditional linear forecasting methods. This supports the thesis that integrating data complexity into predictive models through advanced deep learning techniques can significantly enhance forecast precision, thus providing a notable advantage in fields where accurate forecasting is crucial.
“Understanding the World”

A central mandate of the teacher librarian (TL) is the development of information literatestudents who can locate and use information responsibly and ethically as learners and citizens(Australian Library and Information Association, 2016; International Federation of LibraryAssociations and Institutions, 2021). Therefore, it is vital that TLs are supported in theirendeavours to deliver high quality information literacy instruction, which reflects thechanging nature of information and the information landscape.
In Vino Veritas: does origin truly matter ?

This paper applies hedonic analysis for an identification of the values which consumers place on attributes of origin as they are listed on the labels of bottles of wine. In particular, region and country of origin are examined with respect to the consumers' degree of product identification. Generalised least squares regressions are employed to infer the implicit valuation of information about wine attributes from explicit market prices in the British off-licence sector. The analysis allows for differential effects between attributes. Where these effects are found to have a significant impact on price, consumers are viewed as regarding attribute bundles as imperfect substitutes. The study identifies these cases where identical grape varieties originate from different countries and regions within those countries. Results suggest that grape varieties are highly important in the choice of Italian and Australian wines, whereas regional origins constitute the most important choice criterion in the case of French wines. The relationship between origin and quality is further explored as marketing implications for retailers are investigated. While considering interactions between the attributes, it is shown what potential gains or losses retailers may have to face as they intend a stock-transfer of wines from different origins.
Experimental Demonstration of Millimeter-Wave Self-Bending Over-Obstacle Focused Beam Using Single Phase-Modulated 3-D Printed Dielectric Plate Structure

In this letter, we demonstrated a self-bending beam with over-obstacle focusing characteristics by using a single phase-modulated dielectric plate at 28 GHz. Unlike conventional near-field focusing, this self-bending over-obstacle focusing offers a promising solution to enhance the efficiency and reliability of wireless power transfer systems, particularly in scenarios where obstacles are present between the transmitter and receiver. The phase profile of proposed phase-modulated plate structure is a phase combination form of a radial phase plate and a Fourier lens. Benefiting from low-cost 3-D printing technology, a prototype of the proposed phase-modulated plate is fabricated. Based on full wave simulation and near-field measurement experiments, we analyzed this unique self-bending focusing behavior at 28 GHz in detail. The experiment results indicate that even if the obstacle of a metal plate is placed in front of the phase-modulated plate, the focus behind the obstacle can still be well observed.
Evaluation of atopic dermatitis severity using artificial intelligence

Atopic dermatitis is a prevalent and persistent chronic inflammatory skin disorder that poses significant challenges when it comes to accurately assessing its severity. The aim of this study was to evaluate deep learning models for automated atopic dermatitis severity scoring using a dataset of Aceh ethnicity individuals in Indonesia. The dataset of clinical images was collected from 250 patients at Dr. Zainoel Abidin Hospital, Banda Aceh, Indonesia and labeled by dermatologists as mild, moderate, severe, or none. Five pretrained convolutional neural networks (CNN) architectures were evaluated: ResNet50, VGGNet19, MobileNetV3, MnasNet, and EfficientNetB0. The evaluation metrics, including accuracy, precision, sensitivity, specificity, and F1-score, were employed to assess the models. Among the models, ResNet50 emerged as the most proficient, demonstrating an accuracy of 89.8%, precision of 90.00%, sensitivity of 89.80%, specificity of 96.60%, and an F1-score of 89.85%. These results highlight the potential of incorporating advanced, data-driven models into the field of dermatology. These models can serve as invaluable tools to assist dermatologists in making early and precise assessments of atopic dermatitis severity and therefore improve patient care and outcomes.
Translation domain segmentation model based on improved cosine similarity for crowd motion segmentation

Abstract. With the continuous growth of the global population, large-scale public gatherings have become more common, and crowd management at these gatherings has become an urgent problem for public safety management. Crowd motion analysis and early warning based on crowd motion segmentation in video surveillance systems has become an important research topic in computer vision. A translation domain segmentation (TDS) model based on improved cosine similarity (ICS) is proposed to segment moving crowds with different crowding levels and complex motion modes. The method reconstructs the objective function of the basic TDS model by ICS to simultaneously measure the difference between both magnitude and direction of two vectors; thus, undersegmentation due to the magnitude difference can be avoided. By switching between “localization” and “globalization” modes of the objective function, the algorithm can be applied to segment crowds with different densities and motion states. Moreover, by simultaneously introducing local motion magnitude and local frame difference magnitude thresholds, nonforeground regions can be excluded from the initial regions during region evolution. Experimental results show that the proposed method achieves superior performance and higher accuracy compared to existing flow field-based methods when applied to complex scenes containing moving crowds.
Arcopilus aureus: a valuable endophytic associate of hazelnut

Endophytic fungi are increasingly being considered for their ecological role and effects on plant protection and nutrition. Their contribution in improving fitness can be particularly relevant in the case of semi-extensive tree crops, such as hazelnut. In this manuscript, the occurrence and properties of the species Arcopilus aureus are reviewed, following its finding as a component of the endophytic microbiome of hazelnut in the distant geographic and climatic contexts of Poland and Italy, representing an indication of its widespread association with this plant and a possible role in protection against biotic adversities.
The Large Maf Transcription Factor Traffic Jam Regulates Collective Cell Migration During Drosophila Oogenesis

Collective cell migration is a fundamental process throughout development. The migrating border cell cluster (BCC) in the Drosophila ovary is a good in-vivo model system to study this process. My work focuses on the function of the large Maf transcription factor, Traffic Jam (Tj), in regulating BCC migration. Tj has a dual function in both promoting and inhibiting BCC migration, as reduction or increase of tj expression leads to migration delays. I found a genetic interaction between Tj and three factors known to promote BCC migration: an inhibitor of the JAK/Stat pathway, Socs36E, the transcription factor Slow border cells (Slbo), and the adhesion molecule DEcadherin (DEcad). At high expression level, Tj enhances the expression of Socs36E, which subsequently inhibits JAK/Stat and causes reduction of Slbo. High Tj expression also inhibits DEcad upregulation in the BCC. Activation of Slbo, which is induced by JAK/Stat, leads to a natural downregulation of Tj. This low expression level of Tj maintains Slbo expression in the BCC, which allows for DEcad upregulation. My work has shown that Tj is an important component of this regulatory network, which allows for proper BCC migration.
Modeling of the Subthreshold Swing in Cryogenic MOSFET With the Combination of Gaussian Band Tail and Gaussian Interface State

To quantitatively describe the inflection and the recently observed protrusion phenomenon in the subthreshold region at cryogenic temperature, this study presents a novel model featuring a Gaussian-distributed band tail, combining the Gaussian interface state positioned away from the energy band. The Gaussian band tail can capture the inflection phenomenon of low-temperature subthreshold swing (SS), and the introduction of the interface state in the forbidden band enables accurate modeling of the SS protrusion. The proposed model can favorably describe <inline-formula> <tex-math notation="LaTeX">${I}_{\text {DS}}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${V}_{\text {GS}}$ </tex-math></inline-formula>, SS–<inline-formula> <tex-math notation="LaTeX">${I}_{\text {DS}}$ </tex-math></inline-formula>, and SS–<inline-formula> <tex-math notation="LaTeX">${T}$ </tex-math></inline-formula> spanning from 10 to 300 K of the commercial 0.35-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> bulk n/p- MOSFET and 14-nm n-FinFET technology, potentially enabling a unified method of capturing the SS of a MOSFET at the cryogenic temperature.
Robotic-Assisted Knee Arthroplasty: Insights and Implications From Current Literature

Robotic-assisted knee arthroplasty has emerged as a promising development, aiming to enhance surgical precision and patient outcomes. This literature review examines the clinical efficacy, cost implications, environmental impact, and potential of telesurgery in robotic-assisted total knee arthroplasty (RATKA) and robotic-assisted unicompartmental knee arthroplasty (RAUKA) relative to conventional techniques. A thorough literature search was conducted across medical databases. Clinical and radiological outcomes of RATKA and RAUKA were extracted and analyzed. Direct costs, operating time, surgeon learning curve, environmental implications, and the futuristic concept of telesurgery were also considered. Subjective patient assessments such as WOMAC, Oxford Knee Score, and SF-36, alongside objective measures like HSS score and KSS, were commonly used. Radiological parameters like hip-knee-ankle (HKA) and femorotibial angle provided insights into post-operative alignment. Evidence indicated sporadic high-level design studies, often with limited samples. Cost remains a major constraint with robotic systems, though high-volume cases might offset expenses. Environmental assessments revealed robotic surgeries generate a higher carbon footprint. Telesurgery, an evolving field, could transcend geographical boundaries but is not without challenges, including high costs, latency issues, and cyber threats. While robotic-assisted surgeries may hold promise in the future, substantial barriers, including acquisition costs, potential surgeon deskilling, and environmental concerns, need addressing. Greater robot utilization may drive costs down with more competitors entering the market. Continued research, especially multi-center RCTs, is pivotal to solidifying the role of robotic systems in knee arthroplasty.
First record of the Neolicaphrium recens Frenguelli, 1921 (Mammalia, Litopterna) in the Pleistocene of Santiago del Estero Province, Argentina

The first record of the Neolicaphrium recens Frenguelli (Mammalia, Litopterna) from Pleistocene deposits of the Rio Dulce, Rio Hondo Department, Santiago del Estero Province, Argentina, is reported. The morphology and morphometry observed in the specimen MPAT073 is coincident with the diagnostic characteristics of that species. This finding represents the northernmost and westernmost record of the species, and thus extends its geographical distribution. Although the fossil was found in the recent sands of the Rio Dulce, geological data suggest that its original source is a still unnamed Pleistocene stratigraphic unit.