The Role of Green Finance in Community Renewable Energy Projects of main Region and Taiwan

In order to achieve the goal of "non-nuclear homeland and realize the policy target that renewable energy accounts for 20% of power generation, the Taiwan government has actively promoted the integration of energy generation. Many small and medium-sized enterprises or start-up companies are faced with the challenge of financing their business expansion. This paper adopted document analysis method to seek more diversified financing channels compared with traditional ways of financing and lending from financial institutions, the combination of fintech and the power of the masses, such as crowdfunding, has become one of the emerging financial instruments for the development of green energy industry. Finally, the empirical result is compared main region about the community renewable energy projects and realized how to obtain renewable energy resources through new financing source. The study will be providing related reference to decision-making of country which plan to develop renewable energy projects.

Antibiotikaresistenz und Antibiotikaverbrauch in einer Region am Beispiel ambulant erworbener Harnwegsinfektionen

Zusammenfassung Hintergrund Angesichts zunehmender bakterieller Resistenzen wird eine sachgerechte, zurückhaltende Antibiotikatherapie (antibiotic stewardship) immer wichtiger, auch in der niedergelassenen Praxis. Für die Behandlung der unkomplizierten Harnwegsinfektionen liegt eine aktuelle S3-Leitlinie vor, die auch regelmäßige epidemiologische Untersuchungen zur Erregerempfindlichkeit orts- und zeitnah durchzuführen empfiehlt. Vor diesem Hintergrund wurden die Antibiotikaverordnungen der niedergelassenen Ärzte in Hessen untersucht und der Sensitivität der wichtigsten Erreger von Harnwegsinfektionen gegenübergestellt. Material und Methode Die Verordnungsdaten für Antibiotika (ATC J01) für den Bereich der Kassenärztlichen Vereinigung Hessen wurden von der Firma Insight Health GmbH & Co. KG, Waldems-Esch, die die Daten verwaltet, für die Jahre 2013 bis 2020 erhalten. Ein großes Labor, das zahlreiche niedergelassene Ärzte der Rhein-Main-Region versorgt, stellte bis 2016 nach CLSI und ab 2017 nach EUCAST getestete Sensibilitätsdaten aus mikrobiologischen Untersuchungen von Urinproben zur Abklärung ambulant erworbener Harnwegsinfektionen aus den Jahren 2011–2020 zur Verfügung. Ergebnisse Von 2013 bis 2020 nahmen die Antibiotika-Verordnungen insgesamt von 2 692 370 auf 1 708 134 ab (minus 37 %). Die Verordnungen an Cephalosporinen wurden um mehr als 40 % reduziert, die der Chinolone um 76 %. Unter den für Harnwegsinfektionen empfohlenen Antibiotika wurde am häufigsten Fosfomycin eingesetzt (2020: 130 476), gefolgt von Co-Trimoxazol (2020: 96 559), Nitrofurantoin (2020: 37 415), Trimethoprim (2020: 27 388), Pivmecillinam (20 984) und Nitroxolin (6818). Urologen hingegen verordneten am häufigsten Nitrofurantoin (2020: 9951) und Co-Trimoxazol (9772), gefolgt von Fosfomycin (7193), Trimethoprim (5050), Nitroxolin (3289) und Pivmecillinam (2722).Trotz des hohen Einsatzes von Fosfomycin in der ambulanten Medizin ist bei E. coli und Citrobacter spp. kein Sensibilitätsverlust erkennbar, bei Proteus mirabilis und S. aureus zeichnet sich ein geringer, bei Enterobacter cloacae ein deutlicher Wirkungsverlust ab. Die aus Urinproben zur Abklärung von komplizierten Harnwegsinfektionen detektierten E. coli-Stämme zeigen weiterhin eine exzellente Sensitivität für Fosfomycin, Nitrofurantoin, Nitroxolin und Mecillinam (> > 90 %), für Trimethoprim lag sie knapp unter 80 %. Diskussion und Schlussfolgerung Die Abnahme der Antibiotika-Verordnungen der Kassenärzte in Hessen zeigt, dass sich die Bedeutung einer zurückhaltenden Antibiotikatherapie auch in der ambulanten Praxis durchsetzt. Auf Co-Trimoxazol, das weiterhin sehr häufig eingesetzt wird, sollte wegen der erhöhten Nebenwirkungen der Sulfonamidkomponente bei gleicher Wirksamkeit von Trimethoprim zugunsten der Monotherapie mit Trimethoprim verzichtet werden. Die aus Urinproben zur Abklärung von komplizierten Harnwegsinfektionen detektierten E. coli-Stämme wiesen gegenüber Trimethoprim eine Sensitivität von knapp unter 80 % auf. Da bei unkomplizierten ambulant erworbenen Harnwegsinfektionen, die üblicherweise keine mikrobiologische Diagnostik erfordern, eine etwa 10 % bessere Sensitivitätsrate gefunden wurde, kann u. E. in Übertragung dieser Beobachtung im Rhein-Main-Gebiet und in Hessen auch Trimethoprim bei unkompliziertem Harnwegsinfektion weiterhin empirisch eingesetzt werden.

Conformity of the NASADEM_HGT and ALOS AW3D30 DEM with the Altitude from the Brazilian Geodetic Reference Stations: A Case Study from Brazilian Cerrado

The Brazilian Cerrado (tropical savanna) is the second largest biome in South America and the main region in the country for agricultural production. Altitude is crucial information for decision-makers and planners since it is directly related to temperature that conditions, for example, the climatic risk of rainfed crop plantations. This study analyzes the conformity of two freely available digital elevation models (DEMs), the NASADEM Merged Digital Elevation Model Global 1 arc second (NASADEM_HGT) version 1 and the Advanced Land Observing Satellite Global Digital Surface Model (ALOS AW3D30), version 3.1, with the altitudes provided by 1695 reference stations of the Brazilian Geodetic System. Both models were evaluated based on the parameters recommended in the Brazilian Cartographic Accuracy Standard for Digital Cartographic Products (PEC-PCD), which defines error tolerances according to eight different scales (from 1:1000 to 1:250,000) and classes A (most strict tolerance, for example, 0.17 m for 1:1000 scale), B, C, and D (least strict tolerance, for example, 50 m for 1:250,000 scale). Considering the class A, the NASADEM_HGT meets 1:250,000 and lower scales, while AW3D30 meets 1:100,000 and lower scales; for class B, NASADEM_HGT meets 1:100,000 scale and AW3D30 meets 1:50,000. AW3D30 presented lower values of root mean square error, standard deviation, and bias, indicating that it presents higher accuracy in relation to the NASADEM_HGT. Within eight of Cerrado’s municipalities with the highest grain production, the differences between average altitudes, measured by the Cohen’s effect size, were statistically insignificant. The results obtained by the PEC-PCD for the Cerrado biome indicate that both models can be employed in different DEM-dependent applications over this biome.

Palmitate reduces starvation-induced ER stress by inhibiting ER-phagy in hypothalamic cells

Palmitate is a saturated fatty acid that is well known to induce endoplasmic reticulum (ER) stress and autophagy. A high-fat diet increases the palmitate level in the hypothalamus, the main region of the brain regulating energy metabolism. Interestingly, hypothalamic palmitate level is also increased under starvation, urging the study to distinguish the effects of elevated hypothalamic palmitate level under different nutrient conditions. Herein, we show that ER-phagy (ER-targeted selective autophagy) is required for progress of ER stress and that palmitate decreases ER stress by inhibiting ER-phagy in hypothalamic cells under starvation. Palmitate inhibited starvation-induced ER-phagy by increasing the level of B-cell lymphoma 2 (Bcl-2) protein, which inhibits autophagy initiation. These findings suggest that, unlike the induction of ER stress under nutrient-rich conditions, palmitate protects hypothalamic cells from starvation-induced stress by inhibiting ER-phagy.

Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study

Purpose In 2-dimensional lateral cephalometric radiographs, patients with severe obstructive sleep apnea (OSA) exhibit a more crowded oropharynx in comparison with non-OSA. We tested the hypothesis that machine learning, an application of artificial intelligence (AI), could be used to detect patients with severe OSA based on 2-dimensional images. Methods A deep convolutional neural network was developed (n = 1258; 90%) and tested (n = 131; 10%) using data from 1389 (100%) lateral cephalometric radiographs obtained from individuals diagnosed with severe OSA (n = 867; apnea hypopnea index > 30 events/h sleep) or non-OSA (n = 522; apnea hypopnea index < 5 events/h sleep) at a single center for sleep disorders. Three kinds of data sets were prepared by changing the area of interest using a single image: the original image without any modification (full image), an image containing a facial profile, upper airway, and craniofacial soft/hard tissues (main region), and an image containing part of the occipital region (head only). A radiologist also performed a conventional manual cephalometric analysis of the full image for comparison. Results The sensitivity/specificity was 0.87/0.82 for full image, 0.88/0.75 for main region, 0.71/0.63 for head only, and 0.54/0.80 for the manual analysis. The area under the receiver-operating characteristic curve was the highest for main region 0.92, for full image 0.89, for head only 0.70, and for manual cephalometric analysis 0.75. Conclusions A deep convolutional neural network identified individuals with severe OSA with high accuracy. Future research on this concept using AI and images can be further encouraged when discussing triage of OSA.

The various accretion modes of AM Herculis: Clues from multi-wavelength observations in high accretion states

We report on XMM-Newton and NuSTAR X-ray observations of the prototypical polar, AM Herculis, supported by ground-based photometry and spectroscopy, all obtained in high accretion states. In 2005, AM Herculis was in its regular mode of accretion, showing a self-eclipse of the main accreting pole. X-ray emission during the self-eclipse was assigned to a second pole through its soft X-ray emission and not to scattering. In 2015, AM Herculis was in its reversed mode with strong soft blobby accretion at the far accretion region. The blobby acretion region was more luminous than the other, persistently accreting, therefore called main region. Hard X-rays from the main region did not show a self-eclipse indicating a pronounced migration of the accretion footpoint. Extended phases of soft X-ray extinction through absorption in interbinary matter were observed for the first time in AM Herculis. The spectral parameters of a large number of individual soft flares could be derived. Simultaneous NuSTAR observations in the reversed mode of accretion revealed clear evidence for Compton reflection of radiation from the main pole at the white dwarf surface. This picture is supported by the trace of the Fe resonance line at 6.4 keV through the whole orbit. Highly ionized oxygen lines observed with the Reflection Grating Spectrometer (RGS) were tentatively located at the bottom of the accretion column, although the implied densities are quite different from expectations. In the regular mode of accretion, the phase-dependent modulations in the ultraviolet (UV) are explained with projection effects of an accretion-heated spot at the prime pole. In the reversed mode projection effects cannot be recognized. The light curves reveal an extra source of UV radiation and extended UV absorbing dips. An Hα Doppler map obtained contemporaneously with the NuSTAR and XMM-Newton observations in 2015 lacks the typical narrow emission line from the donor star but reveals emission from an accretion curtain in all velocity quadrants, indicating widely dispersed matter in the magnetosphere.

0594 Can a Deep Convolutional Neural Network Extract Diagnostic Information on Obstructive Sleep Apnea from Images?

Introduction Lateral cephalometric radiography is a simple way to provide craniofacial soft/hard tissue profiles specific for patients with obstructive sleep apnea (OSA) and may thus offer diagnostic information on the disease. We hypothesized that a machine learning technology, a deep convolutional neural network (DCNN), could make it possible to detect OSA based solely on lateral cephalometric radiographs without the need for either large amounts of subjective/laboratory data or skilled analyses. Methods In this diagnostic study, a DCNN was developed (n=1,258) and tested (n=131) using data from 1,389 lateral cephalometric radiographs obtained from individuals diagnosed with severe OSA (n=867; apnea hypopnea index &gt;30/hour) or non-OSA (n=522; apnea hypopnea index &lt; 5) at a single center for sleep disorders from March, 2006 to February, 2017. Three kinds of data sets were prepared by changing the area of interest using a single image; original image without any modification (Full Image), image containing a facial profile, upper airway, craniofacial soft/hard tissues, and image containing part of the occipital region (upper left corner of the image; Head Only). A radiologist and an orthodontist also performed a manual cephalometric analysis of the Full Image for comparison. Observers were blinded to the patient groupings. Data analysis was performed from April, 2018 to August, 2019. When the predictive score obtained from the DCNN analysis exceeded the threshold (0.50), the patient was judged to have OSA. The primary outcome was diagnostic accuracy in terms of area under the receiver-operating characteristic curve. Results The sensitivity/specificity was 0.87/0.82 for Full Image, 0.88/0.75 for Main Region, 0.71/0.63 for Head Only, and 0.54/0.80 for the manual analysis. The area under the curve was the highest for Main Region (0.92): 0.89 for Full Image, 0.70 for Head Only, and 0.75 for the manual analysis. Conclusion A DCNN identified individuals with OSA with high accuracy. This is a useful approach that does not require any laborious analyses in a primary care setting or in remote areas where an initial specialized OSA diagnosis is not feasible. Support This study was supported in part by the Japan Society for the Promotion of Science (grant numbers 17K11793, 19K10236).

Sowing area, gross fees and sorghum yield in Russia and Samara region

Purpose. Analysis and assessment of sorghum sown areas, yields and gross collection in general for Russia and the Samara region. Research is based on methods of efficient production of sorghum and biological features of culture. Statistics were compiled and data on sorghum sowing areas in Russia as a whole were processed for the period 1990–2018. Results and scope of application. Data on sorghum areas and gross collection in Russia as a whole are given. Thus for the period 2015–2016, the area under sorghum was record-breaking and amounted to 224.2 and 228.7 thousand hectares, compared to 1990 when the area was 67.3 thousand hectares. The main region in Russia for the largest area of sorghum was – Saratov region, where it was sown according to the data for 2018 – 26.4 thousand hectares, or 37.1 % of the total share of sown area of sorghum. In the Samara region, the area under sorghum was within 4.0 thousand hectares and 5.5 % of the total share. In 2018, sorghum production amounted to 49 thousand tons. Sorghum yields in Russia in 2018 averaged 11 c/ha. In the Samara region it was – 18.3 c/ha. Scientific novelty lies in the field of sorghum seed production in the Samara region. Sugar and grain sorghum crops can be a reliable source of increased production of juicy and green feed. Those with high potential yield and grain quality differ in grain sorghum varieties – Premyera, Slavyanka, Ros’ and Kinel’skoye 63, created in Volga Research Institute for Breeding and Seed Breeding – Branch of Samara Science Center of Russian Academy of Sciences.