Structural Aspects and Prediction of Calmodulin-Binding Proteins

Calmodulin (CaM) is an important intracellular protein that binds Ca²⁺ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca²⁺ concentration through interactions with CaM.     

In Vivo Electrophysiology of Peptidergic Neurons in Deep Layers of the Lumbar Spinal Cord after Optogenetic Stimulation of Hypothalamic Paraventricular Oxytocin Neurons in Rats

The spinal ejaculation generator (SEG) is located in the central gray (lamina X) of the rat lumbar spinal cord and plays a pivotal role in the ejaculatory reflex. We recently reported that SEG neurons express the oxytocin receptor and are activated by oxytocin projections from the paraventricular nucleus of hypothalamus (PVH). However, it is unknown whether the SEG responds to oxytocin in vivo. In this study, we analyzed the characteristics of the brain–spinal cord neural circuit that controls male sexual function using a newly developed in vivo electrophysiological technique. Optogenetic stimulation of the PVH of rats expressing channel rhodopsin under the oxytocin receptor promoter increased the spontaneous firing of most lamina X SEG neurons. This is the first demonstration of the in vivo electrical response from the deeper (lamina X) neurons in the spinal cord. Furthermore, we succeeded in the in vivo whole-cell recordings of lamina X neurons. In vivo whole-cell recordings may reveal the features of lamina X SEG neurons, including differences in neurotransmitters and response to stimulation. Taken together, these results suggest that in vivo electrophysiological stimulation can elucidate the neurophysiological response of a variety of spinal neurons during male sexual behavior.     

一起发电机定子接地故障的分析与处理

文章介绍了海外某大型火力发电厂发生的一起发电机定子接地故障的分析和处理过程,对发电厂类似故障的处理和海外发电厂的运行和维护提供了参考。     

温度对核电站传热管阵列声透射特性的影响

为了研究温度分布对于管阵列结构中的声透射特性的影响，以核电站的实际工况为背景，构建了不同的温度场以及周期性变化的非均匀温度场，利用有限元方法进行数值模拟。结果表明：（1）温度分布会改变管阵列声透射频谱的“禁带”宽度以及中心频率位置。在同一介质中，温度变化对频率较高位置的影响大于频率较低的位置。（2）在同样为10℃的温度差下，当水的平均声速为1 653 m·s^-1、饱和水蒸气的平均声速为522.5 m·s^-1时，介质为水时的禁带宽度及中心频率位置变化较大，即声速大的介质的频谱对于温度的变化更敏感。（3）当温度差在10℃以内，在周期性变化的非均匀温度场和与均匀温度场中管阵列声透射特性在第一中心频率23 996.1 Hz之前，两频谱差别很小，在第一禁带之后会出现明显区别。该研究成果对完善核电站应用的声学检测提供了理论基础。     

Entropy analysis of unsteady MHD three-dimensional flow of Williamson nanofluid over a convectively heated stretching sheet

This article addresses an investigation of the entropy analysis of Williamson nanofluid flow in the presence of gyrotactic microorganisms by considering variable viscosity and thermal conductivity over a convectively heated bidirectionally stretchable surface. Heat and mass transfer phenomena have been incorporated by taking into account the thermal radiation, heat source or sink, viscous dissipation, Brownian motion, and thermophoretic effects. The representing equations are nonlinear coupled partial differential equations and these equations are shaped into a set of ordinary differential equations via a suitable similarity transformation. The arising set of ordinary differential equations was then worked out by adopting a well-known scheme, namely the shooting method along with the Runge-Kutta-Felberge integration technique. The effects of flow and heat transfer controlling parameters on the solution variables are depicted and analyzed through the graphical presentation. The survey finds that magnifying viscosity parameter, Weissenberg number representing the non-Newtonian Williamson parameter cause to retard the velocity field in both the directions and thermal conductivity parameter causes to reduce fluid temperature. The study also recognizes that enhancing magnetic parameters and thermal conductivity parameters slow down the heat transfer rate. The entropy production of the system is estimated through the Bejan number. It is noticeable that the Bejan number is eminently dependent on the heat generation parameter, thermal radiation parameter, viscosity parameter, thermal conductivity parameter, and Biot number. The skillful accomplishment of the present heat and mass transfer system is achieved through the exteriorized choice of the pertinent parameters.     

Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

Hydrogen production performance of a photovoltaic thermal system coupled with a proton exchange membrane electrolysis cell

As one of the cleanest energies, hydrogen has attracted much attention over the past decade. Hydrogen can be produced using water electrolysis in a Proton Exchange Membrane Electrolysis Cell (PEMEC). In the present study, the performance of the PEMEC, powered by the Photovoltaic-Thermal (PVT) system, is scrutinized. It is considered that the PVT system provides the required electrical power of the PEMEC and preheats the feedwater. A comprehensive numerical model of the coupled PVT-PEMEC system is developed. The model is used to investigate the effect of various operating parameters, including solar radiation intensity, inlet feedwater temperature, and feedwater mass flow rate, on the hydrogen production and operating voltage of the PEMEC at various Exchange Current Densities (ECDs). Furthermore, the effect of integration of Phase Change Material (PCM) and Thermoelectric Generator (TEG) on the hydrogen production of the system is evaluated. According to the obtained results, the PVT-TEG-PEMEC system outperforms other systems in hydrogen production. However, integration of the PVT-PEMEC system with PCM has a negligible effect on its hydrogen production.     

Impacts of slip and mass transpiration on Newtonian liquid flow over a porous stretching sheet

This article focuses on analytic solutions for Newtonian fluid flow with slip and mass transpiration on a porous stretching sheet using the differential transform method and Pade approximants of an exceptionally nonlinear differential equation. The impacts of different parameters including mass transpiration (suction/injection), Navier's slip, and Darcy number parameters on the velocity of the liquid and tangential stress are discussed. A comprehensive comparison of our results with the previous one in the literature is made, and the results showed good agreement. An investigation is conducted of a combination of magnetic liquids that are conceivably pertinent for wound medicines, skin repair, and astute coatings for natural gadgets. It is found that there is a decrease in the velocity profiles and the boundary layer thickness for the case of suction.     

Process knowledge-based random forest regression for model predictive control on a nonlinear production process with multiple working conditions

In process industry, predictive control approaches have been widely used for nonlinear production processes. Practically, the predictor in a predictive controller is extremely important since it provides future states for the optimization problem of controllers. The conventional predictive controller with precise mathematical predictors approximating the state space of physical systems is difficult and time-consuming for nonlinear production processes, and it performs poorly over a wide range of working conditions and with significant disturbances. To address the challenges, the trend of applying artificial intelligence emerges. However, the industrial process-specific knowledge is ignored in most cases. In this study, a predictive controller with a control process knowledge-based random forest (RF) model is proposed. Specifically, working data are clustered at first to handle diverse working conditions. Then, a process knowledge-based forest predictor, namely MIW-RF model with a redesigned cascading RF structure, is proposed to incorporate control process knowledge into modeling. Thus, future states of controlled variables could be more accurately acquired for the optimizer. A simplified version of the predictive model is also developed with quick model training and updating. The proposed predictive methods are finally introduced into the controller design. According to the empirical results, the proposed methods deliver a better control performance against benchmarks, including more accurate anticipated controlled-variable responses, better set-point tracking and disturbance rejection capability.     

Numerical investigation of a convective hybrid nanofluids around a rotating sheet

Hybrid nanofluids are formulated with various kinds of base fluids. They are designed to provide good heat transfer performance. They can achieve this by dispersing various kinds of nanoparticles in the base materials. This new technology of formulating hybrid nanofluids has a wide range of applications in various industries such as solar energy, medical equipment, and aerospace. Keeping these applications in view, this study provides an insight into the effects of convective heat transport on a Hybrid nanofluid, across a rotating sheet with a variable heat source. In this investigation, the governing boundary layer partial differential equations were modified into the ordinary differential equations, by using the proper similarity transformations. Later, they were solved numerically, with the support of the Lobatto IIIA technique in MATLAB. The influence of the Richardson number on flow parameters was studied, and it was discovered that increasing Ri increases the velocity while decreasing temperature and concentration profiles. The impact of various other flow parameters on the flow fields and also on the behavior of Nusselt number, coefficient skin friction, and Sherwood number were studied and represented graphically. The outcomes were found to be in excellent accord when compared with quoted studies.