Miracle-dz/UniFAR-FTUs huggingface dataset:
Pan-sharpening of remote sensing images based on gradient projection and cross fusion

ABSTRACT Pan-sharpening is the fusion of panchromatic (PAN) image and multispectral (MS) image through certain rules to generate high-resolution multispectral (HRMS) image with vivid spatial details and uniform spectral distribution. It has become an important technology in remote sensing image processing. Recently, convolutional neural networks based on deep learning have achieved remarkable results in the field of pan-sharpening. Guided by this method, this paper proposes a pan-sharpening network PSAM-NET for remote sensing images based on depth expansion combined with Cross-Attention Fusion. It consists of gradient projection and the main image fusion module. The gradient projection mainly generates the fusion module by stacking low-resolution multispectral images and panchromatic images alternately, and two deep prior regularized optimization problem formulas are respectively solved by the gradient projection algorithm. The other principal image fusion module realizes double branch fusion, which is mainly composed of cross attention fusion and channel attention fusion, to produce an excellent fusion effect. The simulation and real data experiments were performed on the standard datasets WV2, GF-2, and QB. The qualitative analysis and quantitative comparison with the classical pan-sharpening method proved that the spatial information of the image obtained by this method is complete. The spectral distribution is uniform, and the evaluation index also has some advantages.
Approximate Arithmetic Circuit Design for Error Resilient Applications

When the application context is ready to accept different levels of exactness in solutions and is supported by human perception quality, then the term ‘Approximate Computing’ tossed before one decade will become the first priority . Even though computer hardware and software are working to generate exact results, approximate results are preferred whenever an error is in predefined bound and adaptive. It will reduce power demand and critical path delay and improve other circuit metrics. When it comes to traditional arithmetic circuits, those generating correct results with limitations on performance are rapidly getting replaced by approximate arithmetic circuits which are the need of the hour, and so on about their design.
Using Decision Trees as an Expert System for Clinical Decision Support for COVID-19

COVID-19 has impacted billions of people and health care systems globally. However, there is currently no publicly available chatbot for patients and care providers to determine the potential severity of a COVID-19 infection or the possible biological system responses and comorbidities that can contribute to the development of severe cases of COVID-19. This preliminary investigation assesses this lack of a COVID-19 case-by-case chatbot into consideration when building a decision tree with binary classification that was stratified by age and body system, viral infection, comorbidities, and any manifestations. After reviewing the relevant literature, a decision tree was constructed using a suite of tools to build a stratified framework for a chatbot application and interaction with users. A total of 212 nodes were established that were stratified from lung to heart conditions along body systems, medical conditions, comorbidities, and relevant manifestations described in the literature. This resulted in a possible 63,360 scenarios, offering a method toward understanding the data needed to validate the decision tree and highlighting the complicated nature of severe cases of COVID-19. The decision tree confirms that stratification of the viral infection with the body system while incorporating comorbidities and manifestations strengthens the framework. Despite limitations of a viable clinical decision tree for COVID-19 cases, this prototype application provides insight into the type of data required for effective decision support.
Reducing thermal conductivity of thermoelectric materials by using a narrow wire geometry

The dependence of the thermal conductivity of narrow wires made from bismuth and covalently bonded materials on wire diameter was numerically calculated by considering contributions of mean free paths of carriers and phonons. The results suggest that a reduction in the thermal conductivity should be observable in a bismuth wire having a diameter of less than 1 μm sample. A reduction of nearly 20% in the temperature range of 150–300 K is expected due to the use of a narrow wire geometry. Such a geometry reduces the mobility and the thermal conductivity of the carriers, which is the dominant component, while the thermal conductivity due to phonons was dramatically reduced by using narrow wires at temperatures under 50 K due to the longer mean free path phonons. The thermal conductivity of materials with covalent bonding such as silicon was also estimated, and it is expected that the thermal conductivity of a silicon wire could be reduced due to the mean free path of phonons being longer than that of the car.
The relationship of low-density lipoprotein cholesterol and all-cause or cardiovascular mortality in patients with type 2 diabetes: a retrospective study

Background The optimal levels of low-density lipoprotein cholesterol (LDL-C) in patients with type 2 diabetes (T2D) are not currently clear. In this study, we determined the relationship between various mean LDL-C and all-cause or cardiovascular mortality risks in patients with T2D, stratifying by albumin level, age, sex, and antilipid medication use. We also evaluated the association of LDL-C standard deviation (LDL-C-SD) and all-cause and cardiovascular mortality by type of antilipid medication use. Methods A total of 46,675 T2D patients with a prescription for antidiabetic agents >6 months from outpatient visits (2003–2018) were linked to Taiwan’s National Death Registry to identify all-cause and cardiovascular mortality. The Poisson assumption was used to estimate mortality rates, and the Cox proportional hazard regression model was used to assess the relative hazards of respective mortality in relation to mean LDL-C in patient cohorts by albumin level, age, sex, and antilipid use adjusting for medications, comorbidities, and laboratory results. We also determined the overall, and anti-lipid-specific mortality rates and relative hazards of all-cause and cardiovascular mortality associated with LDL-C-SD using the Poisson assumption and Cox proportional hazard regression model, respectively. Results All-cause and cardiovascular mortality rates were the lowest in T2D patients with a mean LDL-C > 90-103.59 mg/dL in the normal albumin group (≥ 3.5 g/dL). Compared to T2D patients with a mean LDL-C > 90–103.59 mg/dL, those with a mean LDL-C ≤ 77 mg/dL had an elevated risk of all-cause mortality in both the normal and lower albumin groups. T2D patients with a mean LDL-C ≤ 90 and > 103.59–119 mg/dL had relatively higher risk of cardiovascular mortality in the normal albumin group, but in the lower albumin group (<3.5 g/dL), any level of mean LDL-C ≤ 119 mg/dL was not significantly associated with cardiovascular mortality. Increased risks of all-cause and cardiovascular mortality were observed in patients with a mean LDL-C ≤ 77 mg/dL in both sexes and in all age groups except in those aged <50 years, a lower mean LDL-C was not associated with cardiovascular mortality. Similarly, patients with an LDL-C-SD <10th and > 90th percentiles were associated with significant risks of all-cause and cardiovascular mortality. In statin users, but not fibrate users, lower and higher levels of mean LDL-C and LDL-C-SD were both associated with elevated risks of all-cause and cardiovascular mortality. Conclusions The optimal level of LDL-C was found to be >90–103.59 mg/dL in T2D patients. Lower and higher levels of mean LDL-C and LDL-C-SD were associated with all-cause and cardiovascular mortality, revealing U-shaped associations. Further studies are necessary to validate the relationship between optimal LDL-C levels and all-cause and cardiovascular mortality in patients with diabetes.
Search for 17 μm H2 Pure Rotational Emission from Circumstellar Disks

We report the negative detection of the S(1) pure rotational line emission of molecular hydrogen at 17.035 μm for four young stars, HD 163296, MWC 863, CQ Tau, and LkCa 15, for which Infrared Space Observatory (ISO) observations detected the S(1) emission, with the Cooled Mid-Infrared Camera and Spectrometer (COMICS) on the 8.2 m Subaru Telescope. We did not detect the line emission toward the central star nor within 15′′ of the central star along the slit for any of the present targets. Upper limits of the present observations are much smaller than previous line flux estimates based on ISO Short Wavelength Spectrometer ( SWS) observations, irrespective of the intrinsic line width. The present results indicate that the emission detected by the ISO SWS is not concentrated within the disk. Our detection limit of the H2 S(1) emission corresponds to upper limits of the disk masses of (0.72-3.8) × 10-4 M☉ within a radius of ~30-45 AU for the optically thin emission from the gas of 150 K. The upper limits of the disk masses are significantly lower than those of the warm molecular hydrogen mass predicted by the model (Chiang & Goldreich 1997), suggesting that the optically thick emission from dust dominates in the radiation from the disks in the mid-infrared wavelength. We point out that detectability of the H2 emission in young stars depends on the evolution of the disks, particularly in the sedimentation and growth of dust grains in the disk.
Nitrous oxide emissions from rice paddy: Impacts of rice straw and water management

Typically, organic amendment additions like rice straw (RS) are used in agriculture to improve soil quality. The application of RS may influence the production of methane and nitrous oxide (N2O), which may increase the amount of accessible nutrients and organic matter (OM). When compared to farmers' practices of continuous flooding irrigation (CFI), water management (WM) techniques like alternative wetness and dryness irrigation (AWDI) in paddy rice cultivation boost water use efficiency and may result in lower greenhouse gas (GHGs) emissions. A randomized complete block design (RCBD) was employed to evaluate the impacts of WM (CFI and AWDI), RS (15.0 and 30.0 ton ha−1), and their interaction (RS*WM) on the N2O emission and rice yield in a rice paddy calcareous soil. In comparison to control, a single application of RS at 15.0 and 30.0 ton ha−1 significantly reduced N2O emissions by 16.20% and 31.40% (p < 0.01). AWDI regime increased N2O emissions by 67.0% in comparison to the CFI regime (p < 0.01). According to two tailed Pearson correlation, the correlations between AWDI and N2O emissions in the days following rice planting were significantly positive at 0.01 levels. In AWDI regime, adding RS significantly reduced N2O emissions by 18.68% and 31.55% in 15.0 and 30.0 ton ha−1 added RS, respectively, compared to solo WM treatments (p < 0.01). Both RS rates resulted in a considerable increase in biomass and rice grain while AWDI had no significant effect on them. Our study shows that AWDI saved 18.50% water in comparison with CFI regime.
Bianchi Type-I String Cosmological Model with Bulk Viscosity and Time-Dependent Λ term

Einstein field equations with the cosmological constant is considered in the presence of bulk viscosity in a Bianchi type-I universe. Solutions of the field equations are obtained by assuming the following conditions: the bulk viscosity is proportional to the expansion scalar ξ ∝ θ; the expansion scalar is proportional to shear scalar θ ∝ σ; and Λ is proportional to the Hubble parameter Λ ∝ H. The corresponding interpretations of the cosmological solutions are also discussed.
Acute pain management after thoracoscopic lung resection: a systematic review and explorative meta-analysis

Abstract OBJECTIVES Pain after thoracoscopic surgery may increase the incidence of postoperative complications and impair recovery. Guidelines lack consensus regarding postoperative analgesia. We performed a systematic review and meta-analysis to determine the mean pain scores of different analgesic techniques (thoracic epidural analgesia, continuous or single-shot unilateral regional analgesia and only systemic analgesia) after thoracoscopic anatomical lung resection. METHODS Medline, Embase and Cochrane databases were searched until 1 October 2022. Patients undergoing at least >70% anatomical resections through thoracoscopy reporting postoperative pain scores were included. Due to a high inter-study variability an explorative meta-analysis next to an analytic meta-analysis was performed. The quality of evidence has been evaluated using the Grading of Recommendations Assessment, Development and Evaluation system. RESULTS A total of 51 studies comprising 5573 patients were included. Mean 24, 48 and 72 h pain scores with 95% confidence interval on a 0–10 scale were calculated. Length of hospital stay, postoperative nausea and vomiting, additional opioids and the use of rescue analgesia were analysed as secondary outcomes. A common-effect size was estimated with an extreme high heterogeneity for which pooling of the studies was not appropriate. An exploratory meta-analysis demonstrated acceptable mean pain scores of Numeric Rating Scale <4 for all analgesic techniques. CONCLUSIONS This extensive literature review and attempt to pool mean pain scores for meta-analysis demonstrates that unilateral regional analgesia is gaining popularity over thoracic epidural analgesia in thoracoscopic anatomical lung resection, despite great heterogeneity and limitations of current studies precluding such recommendations. PROSPERO REGISTRATION ID number 205311
Magnetoelectric MEMS Magnetic Field Sensor Based on a Laminated Heterostructure of Bidomain Lithium Niobate and Metglas

Non-contact mapping of magnetic fields produced by the human heart muscle requires the application of arrays of miniature and highly sensitive magnetic field sensors. In this article, we describe a MEMS technology of laminated magnetoelectric heterostructures comprising a thin piezoelectric lithium niobate single crystal and a film of magnetostrictive metglas. In the former, a ferroelectric bidomain structure is created using a technique developed by the authors. A cantilever is formed by microblasting inside the lithium niobate crystal. Metglas layers are deposited by magnetron sputtering. The quality of the metglas layers was assessed by XPS depth profiling and TEM. Detailed measurements of the magnetoelectric effect in the quasistatic and dynamic modes were performed. The magnetoelectric coefficient |α32| reaches a value of 492 V/(cm·Oe) at bending resonance. The quality factor of the structure was Q = 520. The average phase amounted to 93.4° ± 2.7° for the magnetic field amplitude ranging from 12 to 100 pT. An AC magnetic field detection limit of 12 pT at a resonance frequency of 3065 Hz was achieved which exceeds by a factor of 5 the best value for magnetoelectric MEMS lead-free composites reported in the literature. The noise level of the magnetoelectric signal was 0.47 µV/Hz1/2. Ways to improve the sensitivity of the developed sensors to the magnetic field for biomedical applications are indicated.
Effects of Particle Geometry for PLGA-Based Nanoparticles: Preparation and In Vitro/In Vivo Evaluation

The physicochemical properties (size, shape, zeta potential, porosity, elasticity, etc.) of nanocarriers influence their biological behavior directly, which may result in alterations of the therapeutic outcome. Understanding the effect of shape on the cellular interaction and biodistribution of intravenously injected particles could have fundamental importance for the rational design of drug delivery systems. In the present study, spherical, rod and elliptical disk-shaped PLGA nanoparticles were developed for examining systematically their behavior in vitro and in vivo. An important finding is that the release of the encapsulated human serum albumin (HSA) was significantly higher in spherical particles compared to rod and elliptical disks, indicating that the shape can make a difference. Safety studies showed that the toxicity of PLGA nanoparticles is not shape dependent in the studied concentration range. This study has pioneering findings on comparing spherical, rod and elliptical disk-shaped PLGA nanoparticles in terms of particle size, particle size distribution, colloidal stability, morphology, drug encapsulation, drug release, safety of nanoparticles, cellular uptake and biodistribution. Nude mice bearing non-small cell lung cancer were treated with 3 differently shaped nanoparticles, and the accumulation of nanoparticles in tumor tissue and other organs was not statistically different (p > 0.05). It was found that PLGA nanoparticles with 1.00, 4.0 ± 0.5, 7.5 ± 0.5 aspect ratios did not differ on total tumor accumulation in non-small cell lung cancer.
Molecular Docking and the Pharmacokinetic Properties of the Anti-Viral Compounds Towards SARS-CoV- An In-silico Approach

The main aim of this study is to determine the bioactive compounds which have drug-like properties and has the potential to combat the spike-glycoprotein of SARS-CoV-2. The 6LXT protein of covid-19 was chosen from the protein data bank as a target protein. The compounds which are potentially capable to bind with the target were picked from the PubChem database and docked using the tool Autodock 4.2. Molecular docking of the molecules was done with the best conformations of the ligands and grid size was selected according to the hit compounds' interaction with the target protein. The ligand binding sites with the target molecules were predicted using MetaPocket 2.0. The docking Score of 50 compounds wascarried out and also toxicity studies were carried out. The compounds selected were calculated to identify the best conformations having drug-likeness properties. The top 10 compounds were chosen for the structure-activity relationship based on their binding interactions with the protein and ligand. The ligands then underwent the pharmacokinetic analysis followed by Lipinski's and all the results were finalized and categorized. ManzamineA, Imatinib, and basotinib were elected as the peak compounds with the binding energy -9.01kcal/mol, -8.71kcal/mol, and -8.01kcal/mol.
An Examination of Barriers to Accessing Mental Health Care, and Their Association with Depression, Stress, Suicidal Ideation, and Wellness in a Bangladeshi University Student Sample

Background: The mental health burden is high and rising among Bangladeshi university students. Understanding barriers to mental healthcare and how barriers impact mental health outcomes may inform the development of targeted interventions to decrease barriers and improve access to care. Aims: This study identifies barriers to mental healthcare and their association with mental health outcomes in a Bangladeshi university student sample. Methods: We conducted a cross-sectional survey (n = 350) on stigma-related, attitudinal, and instrumental barriers to accessing mental healthcare among Bangladeshi university students. We examined the association between stigma and non-stigma (i.e., attitudinal and instrumental) barriers with four mental health outcomes: suicidal ideation, depression, high perceived stress, and wellness. Results: Attitudinal barriers were the most reported barriers. Stigma-related barriers were significant for individuals who had experienced suicidal ideation (aOR = 2.97, p = 0.001), not for individuals with depression. Non-stigma-related barriers were significant for individuals who had experienced depression (aOR = 2.80, p = 0.011). Conclusions: The current work advances our understanding of how to improve access to mental healthcare among university students in Bangladesh. Stigma-related barriers were particularly salient for individuals who experienced suicidal ideation. Further study is needed on how stigma may impact access to care distinctly for different mental health problems among Bangladeshi university students.
Protocooperative Effect of Sphaerodes mycoparasitica Biocontrol and Crop Genotypes on FHB Mycotoxin Reduction in Bread and Durum Wheat Grains Intended for Human and Animal Consumption

The occurrence of Fusarium Head Blight (FHB) mycotoxins in wheat grains is a major threat to global food safety and security. Humans and animals are continuously being exposed to Fusarium mycotoxins such as deoxynivalenol (DON) and its acetylated derivatives 3ADON and 15ADON through the ingestion of contaminated food or grain-based diet. In this study, a host-specific mycoparasite biocontrol agent (BCA), Sphaerodes mycoparasitica, significantly reduced FHB mycotoxin occurrence in harvested wheat grains from Fusarium graminearum 3ADON chemotype infected plants in greenhouse. Four genotypes of wheat, two common wheat and two durum wheat cultivars with varying FHB resistance levels were used in this study. Principal Coordinate Analysis (PCoA) using Illumina ITS sequences depicted beta diversity changes in Fusarium species indicating that both plant cultivar and BCA treatments influenced the Fusarium species structure and mycotoxin occurrence in grains. Fusarium graminearum complex (cluster A), F. avenaceum and F. acuminatum (cluster B), and F. proliferatum (cluster C) variants were associated with different FHB mycotoxins based on LC-MS/MS analyses. The predominant FHB mycotoxins measured were DON and its acetylated derivatives 3ADON and 15ADON. The BCA reduced the occurrence of DON in grains of all four cultivars (common wheat: 1000–30,000 µg·kg−1.; durum wheat: 600–1000 µg·kg−1) to levels below the Limit of Quantification (LOQ) of 16 µg·kg−1. A relatively higher concentration of DON was detected in the two common wheat genotypes when compared to the durum wheat genotype; however, the percentage reduction in the wheat genotypes was greater, reaching up to 99% with some S. mycoparasitica treatments. Similarly, a higher reduction in DON was measured in susceptible genotypes than in resistant genotypes. This study’s findings underscore the potential of a Fusarium-specific S. mycoparasitica BCA as a safe and promising alternative that can be used in conjunction with other management practices to minimize FHB mycotoxins in cereal grain, food and feed intended for human and animal consumption.
Beam shape control system by machine learning on the NISSIN BeyEX medium current ion implanter

In the ion implantation process for semiconductor device fabrication, beam shape is one of the most important physical quantities affecting device characteristics. However, controlling the beam shape requires accurate monitoring of the beam shape and complex adjustment of multiple beam tuning parameters according to the ion implantation conditions, which is difficult to automate by rule-based programming. In this study, we developed and evaluated an automatic parameter tuning system that uses machine learning to infer and output optimal parameters based on the current beam condition and equipment condition as train data. The system sets the target beam size for arbitrary beam conditions (ion species, energy, and beam current) in advance, and performs beam setup within the range of the target beam size. The system obtained a coefficient of determination of more than 90% for train data with the target beam size in vertical and horizontal directions.