Rainbow Medical (Israel)

Abstract. Land Surface Temperature (LST) is a critical parameter for urban climate analysis, photovoltaic (PV) planning, and environmental monitoring, yet its effective use is hindered by the coarse spatial resolution of thermal sensors like MODIS. This study introduces a two-stage hierarchical Convolutional Neural Network (CNN) framework that integrates multi-sensor satellite data (MODIS, ASTER, Sentinel-2) to generate fine-scale LST products and quantitatively assess scaling effects across heterogeneous landscapes. In the first stage, MODIS LST (1 km) was downscaled to 360 m, 270 m, and 90 m using Sentinel-2–derived scaling factors and validated against ASTER LST. In the second stage, ASTER LST (90 m) was downscaled to 60 m and 30 m and validated with Landsat-based LST. The framework employed spectral indices, topographic parameters, texture features, and sub-pixel land-cover fractions as scaling factors, capturing both spatial and spectral heterogeneity. Comparative evaluation against XGBoost and DisTrad revealed that CNN consistently achieved the highest determination coefficients (R2 = 0.69–0.87) and the lowest RMSE (1.94–2.34 K) and MAE (1.49–1.8 K) values, confirming its superior capacity to model complex nonlinear thermal relationships. Scaling-effect analysis demonstrated that while accuracy naturally decreases with finer resolutions, the CNN model exhibits strong scale stability and resilience to error propagation, outperforming traditional regression and machine-learning approaches. This hierarchical deep-learning design establishes a new paradigm for multi-sensor LST reconstruction, enabling accurate, scalable, and spatially coherent thermal mapping across diverse terrains. The proposed framework offers a generalizable solution for high-resolution thermal monitoring, PV site optimization, and climate-adaptive urban planning.

Bottom anti-reflection coatings (BARCs) are critical in advanced lithography for minimizing substrate reflections and improving pattern fidelity. In this study, we developed a self-polymerization resin system and focused on optimizing its optical properties through simulation guide, particularly the extinction coefficient (k value), to enhance light absorption and suppress standing wave effects during exposure. Moreover, tunable composition enables precise tailoring of BARC formulation to accommodate diverse film stacks and meet specific etch rate requirements. Simulation driven strategy and tunable formulation enabled precise control over film performance, leading to significantly reduced line-width roughness (LWR) and improved critical dimension uniformity. This approach provides a foundation for high performance BARCs capable of supporting the stringent requirement of next generation semiconductor manufacturing.

Endometriosis affects 1 in 10 women globally. We aimed to determine health provider involvement and preferred methods of obtaining an endometriosis diagnosis across international jurisdictions. A global cross‐sectional survey, distributed through formal and informal FIGO Reproductive Medicine, Endocrinology, and Infertility (REI) committee networks from September through October 2024. A total of 445 respondents from 76 countries began the survey, with 360 completions. Of the respondents, 63.9% were female, with most being gynecologists. Academics and/or researchers comprised 6.7%, with 39.2% involved in research in some capacity. Endometriosis was largely diagnosed by gynecologists (95.0%), with most respondents overall describing ultrasound as the most common method of diagnosis (77.8%). Of those surveyed, 93.6% stated clinicians in their country used non‐invasive imaging (predominantly ultrasound) to diagnose endometriosis before surgery. One third of respondents did not feel confident distinguishing between routine gynecological scans and specialist endometriosis imaging. Significant barriers for uptake of imaging diagnostics included access to training, cost, and geographical accessibility. Regarding adoption of non‐invasive imaging in clinical care, “game‐changing” effects were described, including improvements in surgical preoperative mapping, and patient‐centered care, with concerns that it could increase clinical workloads. Significantly, shifts in endometriosis diagnosis, from visualization of lesions at laparoscopy to non‐invasive imaging diagnostics, were observed internationally. Policies should aim to overcome barriers to uptake of imaging‐based diagnostics by supporting training initiatives, reducing associated costs, and improving geographical accessibility. Respondents predicted transformative changes in endometriosis care once non‐invasive endometriosis diagnostics are effectively adopted.

Mycoplasma pneumoniae (MP) is a common cause of community-acquired pneumonia in children and usually responds well to macrolide antibiotics. However, in recent years, the emergence of macrolide-resistant Mycoplasma pneumoniae (MRMP) is becoming a significant concern in some areas of the world, particularly in Asia, though it remains rare and not commonly reported in the United States.We report a case of a previously healthy early teenage boy presenting with persistent dry cough, chest tightness, sore throat, headache, fatigue, and fever. Despite completing a full course of azithromycin, his symptoms persisted, and radiographic findings showed no improvement. Repeat multiplex polymerase chain reaction(PCR) confirmed ongoing MP infection, and resistance genes were identified. The patient was subsequently treated with doxycycline, along with systemic corticosteroids and bronchodilators, which led to rapid clinical and radiologic improvement within 72 hours of doxycycline initiation.This case highlights the importance of considering MRMP in patients with confirmed MP infection who fail to respond to macrolide therapy, even in areas with low prevalence of mycoplasma infection. Despite the presence of atypical resistance genes in our case, the patient’s clinical course strongly supported the diagnosis of MRMP. It also underscores the potential role of adjunctive immunomodulator therapies, such as corticosteroids, alongside antibiotics in managing airway inflammation and bronchospasm associated with MP infection. Early diagnosis, appropriate antibiotics, and the use of immunomodulators are critical for achieving a fast recovery from the illness.

Sewing garments using robots has consistently posed a research challenge due to the inherent complexities in fabric manipulation. In this paper, we introduce an intelligent robotic automation system designed to address this issue. By employing a patented technique that temporarily stiffens garments, we eliminate the traditional necessity for fabric modeling. Our methodological approach is rooted in a meticulously designed three-stage pipeline: first, an accurate pose estimation of the cut fabric pieces; second, a procedure to temporarily join fabric pieces; and third, a closed-loop visual servoing technique for the sewing process. Demonstrating versatility across various fabric types, our approach has been successfully validated in practical settings, notably with cotton material at the Bluewater Defense production line and denim material at Levi’s research facility. The techniques described in this paper integrate robotic mechanisms with traditional sewing machines, devising a real-time sewing algorithm, and providing hands-on validation through a collaborative robot setup.

Chlorothalonil is a kind of high efficiency, low toxicity, and broad-spectrum fungicide pesticide, which is widely used in the prevention and control of plant fungal diseases. In this work, the solubility of chlorothalonil in 10 pure solvents and one binary solvent was determined by the gravimetric method at temperatures from 288.15 to 323.15 K. Ten experimental pure solvents were 1,4-dioxane, N,N-dimethylacetamide, acetone, cyclohexanone, acetonitrile, N,N-dimethylformamide, methyl isobutyl ketone, ethyl acetate, n-propyl acetate, and tetrahydrofuran. The selected binary solvent mixtures were N,N-dimethylacetamide and ethyl acetate in different proportions. The obtained data show that the solubility of chlorothalonil in the above solvents increases with the increase in temperature, and the solubility also increases with the increase in the N,N-dimethylacetamide ratio in the binary solvent. Furthermore, the experimental solubility data is well correlated by using the modified Apelblat model, Van’t Hoff model, modified Jouyban–Acree model, and Yaws model. The modified Apelblat model shows the best correlation with the solubility of chlorothalonil. In addition, the KAT-LSER model is used to investigate the influence of the solvent effect on the solubility, indicating that the solubility of chlorothalonil is negatively correlated with the polarity of the solvent.

Abstract In recent years, soil-borne diseases including pod rot have become increasingly rampant with climate change, causing serious yield and quality losses to peanut. Resistance breeding is considered an effective measure for pod rot management. Nine peanut cultivars with various degrees of resistance were used to study leaf/shell anatomical and shell biochemical features, main agronomic traits and leaf spot disease ratings in relation to pod rot score. All four anatomical features, viz., leaf palisade cell number, cell width, index and shell lignin staining area, were negatively correlated with peanut pod rot score at 0.01 levels. However, a robust association between shell lignin content and pod rot score was not established. Given the stable and strong correlation between these anatomical features and pod rot scores and high heritability estimates of these features, the pre-existing resistance may be identified even in the absence of disease. This study provided useful selection indicators for screening for resistance to pod rot in peanut. Association analysis of peanut pod rot resistance is being carried out at our laboratory using several natural populations phenotyped in multiple environments. Particular attention will be paid to the relationship between resistance and these indicators from a genetic perspective.