Miracle-dz/UniFAR-FTUs huggingface dataset:
An Online Assimilation Method to Improve the Numerical Forecast of Sea Fog Using Microwave Radiometer‐Retrieved Cloud Water Path

Numerical forecast of the sea fog is sensitive to the initial moist stratification within the marine atmospheric boundary layer (MABL). This study develops an online assimilation method to improve the MABL thermal and moist structures in sea fog ensemble forecasts based on the Weather Research and Forecasting model and Grid‐point Statistical Interpolation/EnKF system. It uses the satellite‐retrieved cloud water path (CWP) as the indicator of sea fog and low‐level stratus to determine the best ensemble members at each grid point. The relative humidity and cloud water profiles are extracted from the best members to generate a series of pseudo‐observations, which are assimilated to update all the members by EnKF method. The new method significantly improves the ensemble forecast of five widespread advection fog events over the Yellow Sea, which can be attributed to the decrease of both missed and spurious fog areas. The case study shows that assimilating the information of both humidity and cloud water outperforms assimilating either of them, while the impact of directly assimilating CWP observation is insignificant. The analysis increments of cloud water, thermal and moist structures in MABL together contribute to the correction of forecasted sea fog. The generation of pseudo‐observations can use the dynamic compatibility of the model to alleviate the impact of erroneous data in the observation, leading to the low sensitivity of the new method to CWP retrieval error.
Geography is not destiny: A quantitative test of Diamond's axis of orientation hypothesis

Jared Diamond suggested that the unique East-West orientation of Eurasia facilitated the spread of cultural innovations and gave it substantial political, technological and military advantages over other continental regions. This controversial hypothesis assumes that innovations can spread more easily across similar habitats, and that environments tend to be more homogeneous at similar latitudes. The resulting prediction is that Eurasia is home to environmentally homogenous corridors that enable fast cultural transmission. Despite indirect evidence supporting Diamond's influential hypothesis, quantitative tests of its underlying assumptions are currently lacking. Here we address this critical gap by leveraging ecological, cultural and linguistic datasets at a global scale. Our analyses show that although societies that share similar ecologies are more likely to share cultural traits, the Eurasian continent is not significantly more ecologically homogeneous than other continental regions. Our findings highlight the perils of single factor explanations and remind us that even the most compelling ideas must be thoroughly tested to gain a solid understanding of the complex history of our species.
Dietary intervention for tertiary prevention in head and neck squamous cell carcinoma survivors: clinical and translational results of a randomized phase II trial

Background There is a strong need for preventive approaches to reduce the incidence of recurrence, second cancers, and late toxicities in head and neck squamous cell carcinoma (HNSCC) survivors. We conducted a randomized controlled trial (RCT) to assess a dietary intervention as a non-expensive and non-toxic method of tertiary prevention in HNSCC survivors. Methods Eligible participants were disease-free patients with HNSCC in follow-up after curative treatments. Subjects were randomized 1:1 to receive a highly monitored dietary intervention plus the Word Cancer Research Fund/American Institute for Cancer Research recommendations for cancer prevention (intervention arm) or standard-of-care recommendations (control arm). The planned sample size for the event-free survival evaluation (primary endpoint) was not reached, and the protocol was amended in order to investigate the clinical (nutritional and quality-of-life questionnaires) and translational study [plasma-circulating food-related microRNAs (miRNAs)] as main endpoints, the results of which are reported herein. Results One hundred patients were screened, 94 were randomized, and 89 were eligible for intention-to-treat analysis. Median event-free survival was not reached in both arms. After 18 months, nutritional questionnaires showed a significant increase in Recommended Food Score (p = 0.04) in the intervention arm vs. control arm. The frequency of patients with and without a clinically meaningful deterioration or improvement of the C30 global health status in the two study arms was similar. Food-derived circulating miRNAs were identified in plasma samples at baseline, with a significant difference among countries. Conclusion This RCT represented the first proof-of-principle study, indicating the feasibility of a clinical study based on nutritional and lifestyle interventions in HNSCC survivors. Subjects receiving specific counseling increased the consumption of the recommended foods, but no relevant changes in quality of life were recorded between the two study arms. Food-derived plasma miRNA might be considered promising circulating dietary biomarkers.
Nonlinear effects and applications of AlN: A comprehensive physical formulation approach

Piezoelectric materials have nonlinear effects that can be used in 5G and IoT technologies. However, since most nonlinear problems in this area do not have analytic solutions, FEM simulations are an essential design tool. In this study, we have developed a stress-charge formulation for non-linear piezoelectric materials compatible with commonly used simulation tools in industry and research. FEM simulation results for AlN with three nonlinear phenomena are presented: variation of effective electrical permittivity, shift of the effective elasticity constants, and enhancement of electromechanical coupling factor. These simulations were conducted with the same material parameters, having great agreement with recent and important experimental results. The simulations allow us to deduce the values of the components of the high-order tensors for the first time as qr_331 = qr_333 = −1600 and g_333 = −80N/V m. The maximum percent errors obtained for the simulations of theeffective electrical permittivity and effective elasticity constants were 0.1% and 1.77%, respectively.
Community involvement in rural and regional schooling and student retention

Student retention in school until the successful completion of Year 12 is an acknowledged challenge in many parts of Australia, particularly rural and regional areas (e.g., Alloway & Dalley-Trim, 2009). This is concerning, given the compelling evidence that the completion of school to Year 12 has long term positive economic and social consequences for the individual students and their communities (OECD, 2013). The research reported here focuses on community involvement in rural and regional schooling and student retention. The qualitative data were collected as part of a three-year ARC Linkage study of issues associated with completion of school education to Year 12 in rural, regional and disadvantaged parts of Tasmania. In-depth interviews (≥ 45 minutes) were conducted with 11 rural and regional community leaders across Tasmania. A descriptive account of the 20 themes covered by the interviewees in relation to school retention was reported in Watson et al. (2015). This paper reports on two other aspects of the research: the type of involvement of the organisation that the interviewees represented and the motivation for the involvement that took place. A two-dimensional framework (Sanders, 2001) was used to classify the 108 activities in which the 11 participants reported being involved. One dimension documented the type of organisation that the participant represented: local/national government, consultancies/boards, and non-profit groups. The second dimension focused on the type of activity in which participants were involved: student-centred, family-centred, school-centred, and community-centred. The range of specific activities was broad, as was the range of reasons that motivated the involvement. Apart from Gregoric’s (2013) work in South Australia, this study reports the only other known data about community involvement with schools in Australia reported by the community members themselves. The outcomes of the research provide benchmarks for other studies in similar Australian or international rural and regional communities where student retention is an issue.
Vestigial Tail Associated to Spinal Lipomas: Report of Seven Cases

Objective: Vestigial tail is a rare form of cutaneous stigmata often related to occult spinal dysraphism. We present 7 cases of vestigial tail associated to tethered cord and spinal lipomas in the Pediatric Neurosurgery Service of the Hospital Civil de Guadalajara. Methods: In this retrospective study from 2017-2022 we reviewed the spinal dysraphism data base of the Hospital de Guadalajara and included the cases of vestigial tails. Results: 7 patients, 5 female and 2 males with vestigial tails were included. Six different morphologies of tails are described so as their location and relationship to occult spinal dysraphism. All the patients received surgical treatment. Complete resection of the cutaneous stigmata and cord detethering were performed in four cases related to fatty filum terminale and the remaining three of the patients required radical resection of associated complex conus medullaris lipomas. All the surgical procedures were performed with microsurgical techniques and neurophysiological monitoring. Conclusions: The different classifications include two main forms of tails, true tail and false tail. Most true tails represent only a cosmetic issue, while the false ones are often in close relationship with spinal dysraphism. Considering the risk of underlying malformations associated with false human tails, the preoperative assessment should include a thorough neurological examination, and a spine magnetic resonance imaging. We present the association of several forms of spinal lipomas related to vestigial tails. Keywords: Vestigial tail, Tethered cord, Spinal lipoma, Pseudo tail, Occult spinal dysraphism.
Prevalence and antibiotic resistance of mastitis pathogens isolated from dairy herds transitioning to organic management

Changes in udder health and antibiotic resistance of mastitis pathogens isolated from dairies upon conversion from conventional to organic management over a 3-year period was studied. Coagulase-negative staphylococci (CNS) were the most prevalent mastitis pathogens isolated. CNS were significantly less resistant to β-lactam antibiotics when isolated from milk after the herd transitioned to organic management. Cessation of the use of antimicrobial therapies in dairies in combination with organic management could lead to a reduction in the antimicrobial resistance of mastitis pathogens.
What Does the Yield Curve Tell Us About GDP Growth?

A lot, including a few things you may not expect. Previous studies find that the term spread forecasts GDP but these regressions are unconstrained and do not model regressor endogeneity. We build a dynamic model for GDP growth and yields that completely characterizes expectations of GDP. The model does not permit arbitrage. Contrary to previous findings, we predict that the short rate has more predictive power than any term spread. We confirm this finding by forecasting GDP out-of-sample. The model also recommends the use of lagged GDP and the longest maturity yield to measure slope. Greater efficiency enables the yield-curve model to produce superior out-of-sample GDP forecasts than unconstrained OLS regressions at all horizons.
Handbook of Ecological Restoration: The ecological context: a landscape perspective

INTRODUCTION Restoration ecology has developed from, and has been practised primarily on, a site-based approach. The restoration of a well-defined area such as a minesite, wetland or a degraded ecosystem of some description is generally attempted. However, it is clear that relatively large areas of the earth are in need of some form of restoration, following degradation through overuse or inappropriate management, which has impaired the functioning or altered the structure of the landscape as a whole (MacMahon, 1998). Thus, there is a need to expand the scope of restoration ecology to embrace broader scales and tackle landscape-scale problems. While this is increasingly recognised, the science of landscape-scale restoration is still in a formative phase (Bell et al ., 1997). In this chapter I present a summary of landscape structure and function, discuss the impacts of human modification of landscapes, and present a series of options for developing guidelines for landscape restoration. Some of the material in this chapter is modified from work presented elsewhere (Hobbs, 1995, 1999; Hobbs & Harris, 2001; Hobbs & Lambeck, in press). LANDSCAPES: STRUCTURE AND FUNCTION A landscape is defined as an area of land, at the scale of hectares to square kilometres, which consists of a collection of different, but interacting patches (also called landscape elements). Patchiness focuses on the spatial matrix of ecological processes, and emphasises the fluxes of materials and organisms within and between parts of the landscape.
DeepMerge: Deep-Learning-Based Region-Merging for Image Segmentation

Image segmentation aims to partition an image according to the objects in the scene and is a fundamental step in analysing very high spatial-resolution (VHR) remote sensing imagery. Current methods struggle to effectively consider land objects with diverse shapes and sizes. Additionally, the determination of segmentation scale parameters frequently adheres to a static and empirical doctrine, posing limitations on the segmentation of large-scale remote sensing images and yielding algorithms with limited interpretability. To address the above challenges, we propose a deep-learning-based region merging method dubbed DeepMerge to handle the segmentation of complete objects in large VHR images by integrating deep learning and region adjacency graph (RAG). This is the first method to use deep learning to learn the similarity and merge similar adjacent super-pixels in RAG. We propose a modified binary tree sampling method to generate shift-scale data, serving as inputs for transformer-based deep learning networks, a shift-scale attention with 3-Dimension relative position embedding to learn features across scales, and an embedding to fuse learned features with hand-crafted features. DeepMerge can achieve high segmentation accuracy in a supervised manner from large-scale remotely sensed images and provides an interpretable optimal scale parameter, which is validated using a remote sensing image of 0.55 m resolution covering an area of 5,660 km^2. The experimental results show that DeepMerge achieves the highest F value (0.9550) and the lowest total error TE (0.0895), correctly segmenting objects of different sizes and outperforming all competing segmentation methods.
Streamlining search methods to update evidence and gap maps: A case study using intergenerational interventions

Abstract Background Evidence and Gap Maps (EGMs) should be regularly updated. Running update searches to find new studies for EGMs can be a time‐consuming process. Search Summary Tables (SSTs) can help streamline searches by identifying which resources were most lucrative for identifying relevant articles, and which were redundant. The aim of this study was to use an SST to streamline search methods for an EGM of studies about intergenerational activities. Methods To produce the EGM, 15 databases were searched. 8638 records were screened and 500 studies were included in the final EGM. Using an SST, we determined which databases and search methods were the most efficient in terms of sensitivity and specificity for finding the included studies. We also investigated whether any database performed particularly well for returning particular study types. For the best performing databases we analysed the search terms used to streamline the strategies. Results No single database returned all of the studies included in the EGM. Out of 500 studies PsycINFO returned 40% (n = 202), CINAHL 39% (n = 194), Ageline 25% (n = 174), MEDLINE 23% (n = 117), ERIC 20% (n = 100) and Embase 19% (n = 98). HMIC database and Conference Proceedings Citation Index‐Science via Web of Science returned no studies that were included in the EGM. ProQuest Dissertations & Theses (PQDT) returned the highest number of unique studies (n = 42), followed by ERIC (n = 33) and Ageline (n = 29). Ageline returned the most randomised controlled trials (42%) followed by CINAHL (34%), MEDLINE (29%) and CENTRAL (29%). CINAHL, Ageline, MEDLINE and PsycINFO performed the best for locating systematic reviews. (62%, 46% and 42% respectively). CINAHL, PsycINFO and Ageline performed best for qualitative studies (41%, 40% and 34%). The Journal of Intergenerational Relationships returned more included studies than any other journal (16%). No combinations of search terms were found to be better in terms of balancing specificity and sensitivity than the original search strategies. However, strategies could be reduced considerably in terms of length without losing key, unique studies. Conclusion Using SSTs we have developed a method for streamlining update searches for an EGM about intergenerational activities. For future updates we recommend that MEDLINE, PsycINFO, ERIC, Ageline, CINAHL and PQDT are searched. These searches should be supplemented by hand‐searching the Journal of Intergenerational Relationships and carrying out backwards citation chasing on new systematic reviews. Using SSTs to analyse database efficiency could be a useful method to help streamline search updates for other EGMs.
Prospective Study of Canaloplasty and Trabeculotomy Performed by Trainees

Purpose To evaluate outcomes of new adopters of the OMNI® Surgical System (Sight Sciences, Inc.) by prospectively evaluating intermediate-term outcomes of patients operated by trainees. Patients and Methods This was a prospective study of surgeries performed by trainees on patients with open angle glaucoma undergoing simultaneous cataract surgery and ab interno canaloplasty and trabeculotomy using the OMNI Surgical System. Pre-operative intraocular pressure (IOP) and number of glaucoma medications were recorded. Only patients with a minimum of 6-month follow up were included. Baseline IOP was used to separate subjects into two groups: Group 1 (IOP ≥18 mmHg) and Group 2 (IOP <18 mmHg). Mean decrease in IOP and medications was calculated and compared with paired t-tests for the overall sample as well as the subgroups. Success was defined as those with a ≥20% reduction from pre-operative IOP or with an IOP ≤18 mmHg and ≥6 mmHg and on the same or fewer number of medications while not requiring additional surgery. Adverse events were also recorded. Results Forty-two eyes of 31 patients were included. Mean pre-operative IOP was 17.2 ± 4.8 mmHg and mean number of medications was 2.4 ± 1.2. The primary endpoint was reached in 83.3% of patients at 12 months. IOP was reduced by 22.3% to 13.4 ± 2.4 (p<0.001). Mean number of medications decreased to 1.7 ± 1.6 (p<0.001). Group 1 mean IOP decreased 35.4% from 22.2 ± 4.6 mmHg to 14.3 ± 2.8 mmHg (p<0.001). Group 2 mean number of medications decreased from 2.3 ± 1.1 to 1.6 ± 1.5 (p<0.001). Conclusion When operated on by the novice MIGS surgeon, the OMNI device provides effective IOP and glaucoma medication reduction with minimal adverse events. Efficacy and safety of the device in the hands of trainees was comparable to experienced glaucoma surgeons suggesting its ease of adoption.
Artificial Intelligence-Enhanced Neurocritical Care for Traumatic Brain Injury : Past, Present and Future.

In neurointensive care units (NICU), particularly in cases involving traumatic brain injury (TBI), swift and accurate decision-making is critical because of rapidly changing patient conditions and the risk of secondary brain injury. The use of artificial intelligence (AI) in NICU can enhance clinical decision support and provide valuable assistance in these complex scenarios. This article aims to provide a comprehensive review of the current status and future prospects of AI utilization in the NICU, along with the challenges that must be overcome to realize this. Presently, the primary application of AI in NICU is outcome prediction through the analysis of pre-admission and high-resolution data during admission. Recent applications include augmented neuromonitoring via signal quality control and real-time event prediction. In addition, AI can integrate data gathered from various measures and support minimally invasive neuromonitoring to increase patient safety. However, despite the recent surge in AI adoption within the NICU, the majority of AI applications have been limited to simple classification tasks, thus leaving the true potential of AI largely untapped. Emerging AI technologies, such as generalist medical AI and digital twins, harbor immense potential for enhancing advanced neurocritical care through broader AI applications. If challenges such as acquiring high-quality data and ethical issues are overcome, these new AI technologies can be clinically utilized in the actual NICU environment. Emphasizing the need for continuous research and development to maximize the potential of AI in the NICU, we anticipate that this will further enhance the efficiency and accuracy of TBI treatment within the NICU.
Association of endometriosis with Sjögren's syndrome: Genetic insights (Review)

Patients with a history of endometriosis have an increased risk of developing various autoimmune diseases such as rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus, multiple sclerosis and celiac disease. There is a potential association between endometriosis and an increased susceptibility for Sjögren's syndrome (SS). SS is a common chronic, inflammatory, systemic, autoimmune, multifactorial disease of complex pathology, with genetic, epigenetic and environmental factors contributing to the development of this condition. It occurs in 0.5-1% of the population, is characterized by the presence of ocular dryness, lymphocytic infiltrations and contributes to neurological, gastrointestinal, vascular and dermatological manifestations. Endometriosis is an inflammatory, estrogen-dependent, multifactorial, heterogeneous gynecological disease, affecting ≤10% of reproductive-age women. It is characterized by the occurrence of endometrial tissue outside the uterine cavity, mainly in the pelvic cavity, and is associated with pelvic pain, dysmenorrhea, deep dyspareunia and either subfertility or infertility. It is still unclear whether SS appears as a secondary response to endometriosis, or it is developed due to any potential shared mechanisms of these conditions. The aim of the present review was to explore further the biological basis only of the co-occurrence of these disorders but not their association at clinical basis, focusing on the analysis of the partially shared genetic background between endometriosis and SS, and the clarification of the possible similarities in the underlying pathogenetic mechanisms and the relevant molecular pathways.