A nodule on the forearm

Glomus tumors are benign tumors of the skin. Clinically, these tumors can present as solid, painful subcutaneous nodules, frequently seen on the hand (particularly subungual region). Glomangiomyomas are the least common histological type of glomus tumor. In the literature, there are only a few glomangiomyoma cases of the forearm location. We report a patient with a painful nodule, diagnosed as glomangiomyoma. Surgical excision was performed and no recurrence was observed after 5 years' follow-up

Tantalate-based Perovskite for Solar Energy Applications

To realize a sustainable society in the near future, the development of clean, renewable, cheap and sustainable resources and the remediation of environmental pollutions using solar energy as the driving force would be important. During the past few decades, plenty of efforts have been focused on this area to develop solar light active materials to meet the increased energy and environmental crisis. Owning to the unique perovskite-type structure, tantalate-based semiconductors with unable chemical composition show high activities toward the conversion of solar radiation into chemical energy. Moreover, various engineering strategies, including crystal structure engineering, electronic structure engineering, surface/interface engineering, co-catalyst engineering and so on, have been developed in order to modulate the charge separation and transfer efficiency, optical absorption, band gap position and photochemical and photophysical stability, which would open a realm of new possibilities for exploring novel materials for solar energy applications

Effect of electronic stimulation at Neiguan (PC 6) acupoint on gene expression of adenosine triphosphate-sensitive potassium channel and protein kinases in rats with myocardial ischemia

AbstractObjectiveTo investigate the effects of electronic stimulation at acupoints Neiguan (PC 6) and Lieque (LU 7) on the gene expression of the adenosine triphosphate (ATP)-Sensitive potassium channel (KATP: Kir6.1, Kir6.2, SUR2A, and SUR2B) and protein kinases (PKA, PKG, and PKCβ2) in myocardial cells of rats with myocardial ischemia (MI) induced by isoproterenol (ISO).MethodsRats were randomly divided into a control, model, Neiguan (PC 6), Lieque (LU 7), and non-acupoint groups. The MI model was established by injecting rats with ISO. Electro-acupuncture treatment was given to the acupuncture groups, once a day for 7 days. Gene expression was analyzed with real-time PCR.ResultsThe gene expression of KATP and protein kinases in the model group was higher than those in the control group (P < 0.05). After acupuncture treatment, the KATP and protein kinase expression levels were significantly lower in the Neiguan (PC 6) and Lieque (LU 7) groups compared with the model group (P < 0.05). The Neiguan (PC 6) group lowered these levels significantly more than that of the Lieque (LU 7) group (P < 0.05). No significant differences were observed between the model and non-acupoint groups (P > 0.05).ConclusionOur findings suggest that electronic needling of Neiguan (PC 6) can both reduce the gene expression of KATP and protein kinases in rats with ISO-induced MI

Flexible operation of large-scale coal-fired power plant integrated with solvent-based post-combustion CO2 capture based on neural network inverse control

Post-combustion carbon capture (PCC) with chemical absorption has strong interactions with coal-fired power plant (CFPP). It is necessary to investigate dynamic characteristics of the integrated CFPP-PCC system to gain knowledge for flexible operation. It has been demonstrated that the integrated system exhibits large time inertial and this will incur additional challenge for controller design. Conventional PID controller cannot effectively control CFPP-PCC process. To overcome these barriers, this paper presents an improved neural network inverse control (NNIC) which can quickly operate the integrated system and handle with large time constant. Neural network (NN) is used to approximate inverse dynamic relationships of integrated CFPP-PCC system. The NN inverse model uses setpoints as model inputs and gets predictions of manipulated variables. The predicted manipulated variables are then introduced as feed-forward signals. In order to eliminate steady-state bias and to operate the integrated CFPP-PCC under different working conditions, improvements have been achieved with the addition of PID compensator. The improved NNIC is evaluated in a large-scale supercritical CFPP-PCC plant which is implemented in gCCS toolkit. Case studies are carried out considering variations in power setpoint and capture level setpoint. Simulation results reveal that proposed NNIC can track setpoints quickly and exhibit satisfactory control performances

Оцінка впливу замісної гормоно-терапії гіпотиреозу на стан вагітності та виношування плоду

Гіпотиреоз – захворювання щитовидної залози, при якому знижується її продуктивність, тиреоїдних гормонів виробляється менше чим необхідно організму для нормальної життєдіяльності. За результатами популяційних досліджень, поширеність гіпотиреозу серед вагітних становить 2-3 %. Серед них близько двох третин мають субклінічний та 0,5 % − маніфестний гіпотиреоз. За даними багатьох дослідників, тільки 20-30% жінок з гіпотиреозом мають клінічні прояви гіпотиреозу, у інших, як правило, захворювання протікає без симптомів. Патологія ЩЗ негативно впливає на перебіг вагітності, розвиток плода й адаптацію новонародженого. Тиреоїдна дисфункція загрожує викиднями, передчасними пологами, відшаруванням плаценти, прееклампсією, післяпологовим тиреоїдитом у матері, а також зниженням інтелектуального потенціалу народжених дітей

Seasonal predictability of Kiremt rainfall in coupled general circulation models

The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June–September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985–2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.publishedVersio

Impact of ocean and sea ice initialisation on seasonal prediction skill in the Arctic

There is a growing demand for skillful prediction systems in the Arctic. Using the Norwegian Climate Prediction Model (NorCPM) that combines the fully-coupled Norwegian Earth System Model and the Ensemble Kalman filter, we present a system that performs both, weakly-coupled data assimilation (wCDA) when assimilating ocean hydrogaphy (by updating the ocean alone) and strongly-coupled data assimilation (sCDA) when assimilating sea ice concentration (SIC) (by jointly updating the sea ice and ocean). We assess the seasonal prediction skill of this version of NorCPM, the first climate prediction system using sCDA, by performing retrospective predictions (hindcasts) for the period 1985 to 2010. To better understand origins of the prediction skill of Arctic sea ice, we compare this version with a version that solely performs wCDA of ocean hydrography. The reanalysis that assimilates just ocean data, exhibits a skillful hydrography in the upper Arctic ocean, and features an improved sea ice state, such as improved summer SIC in the Barents Sea, or reduced biases in sea ice thickness. Skillful prediction of SIE up to 10-12 lead months are only found during winter in regions of a relatively deep ocean mixed layer outside the Arctic basin. Additional DA of SIC data notably further corrects the initial sea ice state, confirming the applicability of the results of Kimmritz et al. (2018) in a historical setting. The resulting prediction skill of SIE is widely enhanced compared to predictions initialised through wCDA of only ocean data. Particularly high skill is found for July-initialised autumn SIE predictions.publishedVersio

Better synoptic and subseasonal sea ice thickness predictions are urgently required: a lesson learned from the YOPP data validation

In the context of global warming, Arctic sea ice has declined substantially during the satellite era (Kwok 2018). The retreating and thinning of Arctic sea ice provide opportunities for human activities in the Arctic, such as tourism, fisheries, shipping, natural resource exploitation, and wildlife management; however, new risks emerge. To ensure the safety and emergency management of human activities in the Arctic, reliable Arctic sea ice prediction is essential