bluuebunny/crossref_metadata_2025_split huggingface dataset:
IoT Terminal Architecture Model
Authors: Zhao Xianping , Mao Yuxing , Liu Siyang , Zhou Lidan , Li Jian , Wang Hongyu 
Published: September 2023

Abstract
The physical Information mapping relationship and function in the sense and control domain is described using entities such as gateway, sense, and control device in the existing IoT reference architecture. However, due to the lack of research on the IoT terminal architecture, there have been difficulties in the research and application of IoT terminal technologies. Starting from the trend analysis of application development of IoT systems, this article proposes an IoT terminal architecture reference model IoT TARM that integrates gateway and sense and control device functions. It analyses the architecture and functional characteristic enhancement acting on the IoT systems due to the IoT TARM. It summarizes the low-power, reconfigurable, lightweight, and platform characteristics of IoT TARM and expounds on the relationship between IoT TARM and the existing IoT architecture.
Capacity Allocation Optimization of Wind-Solar-Hydrogen-Storage Coupled Power Generation System Based on a Double-layer Model
Authors: Ni Yunli , Du Banghua , Deng Jian , Xu Lamei , Xie Changjun 
Published: September 2023

Abstract
Grid-integrated wind-solar and hydrogen storage coupling power generation systems face problems such as high costs of investment, construction, operation, and maintenance. After the conformity of renewable energy, the system’s dependability decreases, and the comprehensive power fluctuation influences the power grid greatly. To solve the above problems, this paper proposes a two-tier model. With the system economy, reliability, and wind-solar comprehensive power fluctuation suppression as optimization objectives, the capacity distribution of the hydrogen storage devices can be optimized. Based on a practical microgrid example, the inner and outer layers adopt Sparrow Search Algorithm (SSA) and Multi-objective Optimization Particle Swarm Optimization Algorithm (MOPSO), respectively, to solve the established model. The optimization results are compared according to three scenarios. The results demonstrate that this model can enhance the operational reliability of the system while considering the overall economy of the system and effectively suppressing the fluctuation of solar and wind power.
An Optimal Configuration Model for Supercapacitor Capacity to Suppress Wind Power Fluctuations
Authors: Zhou Zhuomin , Liang Jian , Yu Aiqin , Liu Haotian , Qin Zhengbin , Sheng Yanchao , Guo Wei 
Published: September 2023

Abstract
This paper presents an optimization configuration scheme for energy storage capacity by taking into account the operational characteristics of supercapacitors. The scheme utilizes Empirical Mode Decomposition (EMD) to address power fluctuations during the integration of wind power into the grid. To begin with, the wind power data undergoes EMD to decompose it into different-order intrinsic mode functions. These functions are then reconstructed as low-frequency components and high-frequency components. The low-frequency components are directly connected to the grid, while the high-frequency components are employed for power smoothing through energy storage. Subsequently, the impact of various wind power grid limits on the directly connected power is compared to identify the optimal value. A model is established to configure the capacity of supercapacitors, aiming to mitigate wind power fluctuations. The model considers an objective function that minimizes the sum of energy storage investment and operational maintenance costs, along with the compensation cost associated with wind power fluctuation opportunities. Finally, the proposed model’s effectiveness and economic feasibility are validated through case studies. This ensures that the model’s efficacy in reducing power fluctuations and its viability from a financial standpoint are thoroughly examined.
Count the charging load forecast of the battery remaining life and ownership
Authors: Li Chenghao 
Published: September 2023

Abstract
In order to solve the accuracy of EV charging load prediction, the residual life reduction and the exact value of EV ownership caused by battery aging are taken into consideration. The charging load curve of the EV is simulated based on the Monte Carlo simulation method. Finally, based on the actual data of a certain region, the charging load of electric vehicles within a day is obtained. The case analysis shows that the proposed charging load prediction model of electric vehicles has high accuracy, which also shows that the large-scale grid connection of electric vehicles will bring new challenges to the power system. This method provides data support for the subsequent formulation of electric vehicle charging strategy and load side peak shifting and valley filling.
Load-Side Inertia Estimation Method Based on Comprehensive Statistics
Authors: Chen Xinyu , Wang Chenqi , Yu Chenyang , Wang Xin , Xu Jianing , Li Weidong 
Published: September 2023

Abstract
The development of modern power systems is accompanied by the problem of inertia deficit, and there is an urgent need to evaluate the system inertia level. Especially, the accurate estimation of load-side inertia level is extremely important. Based on comprehensive statistics, a load-side inertia estimation method is proposed. Starting from the inertia analysis of load-side base elements, the expressions for load-side inertia estimation under various operation modes are given based on the inertia modeling of basic load units; the uniform correction formula for load-side inertia estimation is given considering the hidden effect of behind-the-meter power supply on inertia estimation. The simulation analysis is carried out based on the IEEE9 bus standard system, and the results show that the proposed load-side inertia estimation method does not exceed 5%.
Research on Inertia Lifting of New Power System Based on VSG Double Sagging Optimization Control
Authors: Wang Mingdong , Yang Aodi , Li Hongji 
Published: September 2023

Abstract
With the development of new energy sources, the power grid inertia declines rapidly, which makes the frequency adjustment ability and the power system stability poor. The virtual synchronous generator (VSG) uses a control algorithm to simulate the synchronous generator, which improves the frequency stability of the grid, but the dynamic adjustment performance would likely be degraded. Moreover, the optimal values of the pivotal parameters such as virtual inertia and damping are difficult to determine. Therefore, a VSG optimization strategy of double sagging control and neural network prediction is proposed which can effectively enhance the voltage and frequency safety of the system. Simulating the characteristic equation of the generator, the small signal analysis model of VSG is built, and the initial value of J and D is completed. An artificial neural network is accomplished, and the weight is adjusted to change the J and D of VSG by analyzing and learning the power grid operation. The expected parameter value can be gained after many times of learning and the adaptive control of VSG is realized.
Hybrid Twin Simulation Technology for Training and Testing of New Generation Substation Secondary System
Authors: Mu Li , Ren Yubao , Jin Wei , Zhang Xinyi , He Xiaoyu , Wang Jing 
Published: September 2023

Abstract
In this paper, a hybrid twin scheme for power substations is proposed for secondary system simulation, which can be used to support operator training and equipment testing. The proposed scheme is composed of a hardware-in-the-loop (HIL) based twin substation and a digital twin substation which can reflect the real operating status for both primary and secondary systems of a real substation. Based on the proposed scheme, the modeling method and system architecture are studied in the paper. According to the proposed hybrid twin substation, equipment testing and operator training can be conducted for new-generation secondary systems with fewer costs and security risks.
The Method of Household Adjustable Electricity Prediction Based on Maximum Mean Discrepancy
Authors: Liu Bin , Tan Zhukui , Zhang Junwei , Xu Yutao , Feng Qihui , Chen Zhiwei 
Published: September 2023

Abstract
As electricity market reforms continue and households consume more electricity, Household Electricity Response (HER) becomes an essential part of Demand Response (DR). The ability of households to adjust their electricity demand is a critical factor in evaluating the demand-side response capacity of the power systems. Therefore, a prediction method of household adjustable electricity (HAE) based on cross-domain generalization is proposed to solve the problem. In our method, the convolutional neural networks (CNNs) model with Maximum Mean Discrepancy (MMD) loss term is constructed to realize the goal, which improves the accuracy and generalization of HAE prediction in different regions and provides technical support for DR.
Computational modeling of the variation of the transmembrane potential of the endothelial cells of the blood-brain-barrier subject to an external electric field
Authors: Sehati Mahboobe , Rafii-Tabar Hashem , Sasanpour Pezhman 
Published: September 2023

Abstract
The electromechanical properties of the membrane of endothelial cells forming the blood–brain barrier play a vital role in the function of this barrier. The mechanical effect exerted by external electric fields on the membrane could change its electrical properties. In this study the effect of extremely low frequency (ELF) external electric fields on the electrical activity of these cells has been studied by considering the mechanical effect of these fields on the capacitance of the membrane. The effect of time-dependent capacitance of the membrane is incorporated in the current components of the parallel conductance model for the electrical activity of the cells. The results show that the application of ELF electric fields induces hyperpolarization, having an indirect effect on the release of nitric oxide from the endothelial cell and the polymerization of actin filaments. Accordingly, this could play an important role in the permeability of the barrier. Our finding can have possible consequences in the field of drug delivery into the central nervous system.
An all-passive Si3N4 optical row decoder circuit for addressable optical RAM memories
Authors: Simos S , Moschos T , Fotiadis K , Chatzitheocharis D , Alexoudi T , Vagionas C , Sacchetto D , Zervas M , Pleros N 
Published: September 2023

Abstract
In this work we experimentally demonstrate a Si
3
N
4
photonic integrated circuit which offers row decoding and RAM addressing functionalities. The passive integrated structure comprises a MRR-based wavelength filtering bank scheme in a 2 × 4 configuration, which reveals a suppression ratio in the range of 12–25 dB. The performance of the optical circuit has been evaluated in a system-level testbed, where successful addressing in one RAM row has been achieved. Error-free operation has been accomplished for all cases under study, with the whole row decoder system’s performance to offer a total power penalty of 2.5 dB.
EHD2 regulates plasma membrane integrity and downstream insulin receptor signaling events
Authors: Neuhaus Mathis , Fryklund Claes , Taylor Holly , Borreguero-Muñoz Andrea , Kopietz Franziska , Ardalani Hamidreza , Rogova Oksana , Stirrat Laura , Bremner Shaun K. , Spégel Peter , Bryant Nia J. , Gould Gwyn W. , Stenkula Karin G. 
Published: September 2023

Adipocyte dysfunction is a crucial driver of insulin resistance and type 2 diabetes. We identified EH domain-containing protein 2 (EHD2) as one of the most highly upregulated genes at the early stage of adipose-tissue expansion. EHD2 is a dynamin-related ATPase influencing several cellular processes, including membrane recycling, caveolae dynamics, and lipid metabolism. Here, we investigated the role of EHD2 in adipocyte insulin signaling and glucose transport. Using C57BL6/N EHD2 knockout mice under short-term high-fat diet conditions and 3T3-L1 adipocytes we demonstrate that EHD2 deficiency is associated with deterioration of insulin signal transduction and impaired insulin-stimulated GLUT4 translocation. Furthermore, we show that lack of EHD2 is linked with altered plasma membrane lipid and protein composition, reduced insulin receptor expression, and diminished insulin-dependent SNARE protein complex formation. In conclusion, these data highlight the importance of EHD2 for the integrity of the plasma membrane milieu, insulin receptor stability, and downstream insulin receptor signaling events, involved in glucose uptake and ultimately underscore its role in insulin resistance and obesity.
What makes the diverse flight of birds possible? Phylogenetic comparative analysis of avian alula morphology
Authors: Tatani Masanori , Yamasaki Takeshi , Tanaka Hiroto , Nakata Toshiyuki , Chiba Satoshi 
Published: September 2023

Abstract
Studies on the evolution of avian flight have failed to clarify why wing shape is weakly correlated with flight styles and phylogenetically constrained. Birds seem to have achieved their diverse flight styles owing to changes in the shapes of localized parts of the wing, despite a highly conserved wing outline. The alula, which stems from the first digit of the wing, is a part of the wing that might have enabled various flight styles to develop. To test this hypothesis, we measured alula length and width using museum specimens of 187 species from 21 orders of birds and used a phylogenetic comparative method to investigate the relationship between alula morphology and flight style, body mass, habitat and migratory distance. We found that: (1) phylogenetic signals were weak for the alula width and aspect ratio but moderate for length; (2) alula morphology exhibited an allometric relationship with body mass; and (3) fewer flapping birds had large alulae. Alula morphology might have evolved in response to changes in body mass and flight styles. Variations in the shape of localized wing parts, such as the alula, which modifies airflow around a wing, might be key to the evolution of the diverse flight styles of birds.
Optimal control of a hybrid microgrid for hydrogen-based heat supply using deep reinforcement learning
Authors: Heckmann Robin 
Published: September 2023

Abstract
Green hydrogen is considered one of the key technologies of the energy transition, as it can be used to store surpluses from renewable energies in times of high solar radiation or wind speed for use in dark lulls. This paper examines the decarbonization potential of hydrogen for the heating industry. Worldwide, 99% of hydrogen is produced from fossil fuels, because hydrogen derived from renewable energy sources remains prohibitively expensive compared with its conventional counterpart. However, due to the expansion of renewable energy sources and the current energy crisis of conventional energy sources, hydrogen from renewable energy sources is becoming more and more economical. To optimize the efficiency of green hydrogen production and make it more price-competitive, the author simulates a hydrogen production plant consisting of a photovoltaic plant, a power grid, hydrogen storage, an electrolyser, a natural gas purchase option, a district heating plant and households. Using the deep deterministic policy gradient algorithm from deep reinforcement learning, the plant is designed to optimize itself by simulating different production scenarios and deriving strategies. The connected district heating plant is used to map how hydrogen can be optimally used for heat supply. A demonstrable outcome of this paper is that the utilization of deep deterministic policy gradient, over the course of a full year, can result in a competitive production of hydrogen derived from renewable or stored energy sources for the heating industry as a natural gas substitute.
An update on absolute and relative indications for dialysis treatment modalities
Authors: Lambie Mark , Davies Simon 
Published: September 2023

ABSTRACT

Background
Choosing a dialysis modality is an important decision for people to make as their kidney failure progresses. In doing so, their options should be informed by any absolute or relative indications that may favour one modality over another.

Methods
In creating this update, we reviewed literature using a framework that considered first, high-level outcomes (survival and modality transition) from large registry data and cohort studies when considering optimal patient pathways; second, factors at a dialysis provider level that might affect relative indications; and third, specific patient-level factors. Both main types of dialysis modality, peritoneal (PD) and haemodialysis (HD), and their subtypes were considered.

Results
For most people starting dialysis, survival is independent of modality, including those with diabetes. Better survival is seen in those with less comorbidity starting with PD or home HD, reflecting continued improvements over recent decades that have been greater than improvements seen for centre HD. There are provider-level differences in the perceived relative indications for home dialysis that appear to reflect variability in experience, prejudice, enthusiasm, and support for patients and carers. Absolute contraindications are uncommon and, in most cases, where modality prejudice exists, e.g. obesity, Adult Polycystic Kidney Disease, and social factors, this is not supported by reported outcomes.

Conclusion
Absolute contraindications to a particular dialysis modality are rare. Relative indications for or against particular modalities should be considered but are rarely more important than patient preferences.
Partnering with patients and caregivers to enrich research and care in kidney disease: values and strategies
Authors: Cazzolli Rosanna , Sluiter Amanda , Guha Chandana , Huuskes Brooke , Wong Germaine , Craig Jonathan C , Jaure Allison , Scholes-Robertson Nicole 
Published: September 2023

ABSTRACT
Patient and caregiver involvement broadens the scope of new knowledge generated from research and can enhance the relevance, quality and impact of research on clinical practice and health outcomes. Incorporating the perspectives of people with lived experience of chronic kidney disease (CKD) affords new insights into the design of interventions, study methodology, data analysis and implementation and has value for patients, healthcare professionals and researchers alike. However, patient involvement in CKD research has been limited and data on which to inform best practice is scarce. A number of frameworks have been developed for involving patients and caregivers in research in CKD and in health research more broadly. These frameworks provide an overall conceptual structure to guide the planning and implementation of research partnerships and describe values that are essential and strategies considered best practice when working with diverse stakeholder groups. This article aims to provide a summary of the strategies most widely used to support multistakeholder partnerships, the different ways patients and caregivers can be involved in research and the methods used to amalgamate diverse and at times conflicting points of view.
Shared decision making: a personal view from two kidney doctors and a patient
Authors: Hole Barnaby , Scanlon Miranda , Tomson Charlie 
Published: September 2023

ABSTRACT
Shared decision making (SDM) combines the clinician's expertise in the treatment of disease with the patient's expertise in their lived experience and what is important to them. All decisions made in the care of patients with kidney disease can potentially be explored through SDM. Adoption of SDM in routine kidney care faces numerous institutional and practical barriers. Patients with chronic disease who have become accustomed to paternalistic care may need support to engage in SDM—even though most patients actively want more involvement in decisions about their care. Nephrologists often underestimate the risks and overestimate the benefits of investigations and treatments and often default to recommending burdensome treatments rather than discussing prognosis openly. Guideline bodies continue to issue recommendations written for healthcare professionals without providing patient decision aids. To mitigate health inequalities, care needs to be taken to provide SDM to all patients, not just the highly health-literate patients least likely to need additional support in decision making. Kidney doctors spend much of their time in the consulting room, and it is unjustifiable that so little attention is paid to the teaching, audit and maintenance of consultation skills. Writing letters to the patient to summarise the consultation rather than sending them a copy of a letter between health professionals sets the tone for a consultation in which the patient is an active partner. Adoption of SDM will require nephrologists to relinquish long-established paternalistic models of care and restructure care around the values and preferences of patients.
Plant physiological indicators for optimizing conservation outcomes
Authors: Schönbeck Leonie , Arteaga Marc , Mirza Humera , Coleman Mitchell , Mitchell Denise , Huang Xinyi , Ortiz Haile , Santiago Louis S 
Published: September 2023

AbstractPlant species of concern often occupy narrow habitat ranges, making climate change an outsized potential threat to their conservation and restoration. Understanding the physiological status of a species during stress has the potential to elucidate current risk and provide an outlook on population maintenance. However, the physiological status of a plant can be difficult to interpret without a reference point, such as the capacity to tolerate stress before loss of function, or mortality. We address the application of plant physiology to conservation biology by distinguishing between two physiological approaches that together determine plant status in relation to environmental conditions and evaluate the capacity to avoid stress-induced loss of function. Plant physiological status indices, such as instantaneous rates of photosynthetic gas exchange, describe the level of physiological activity in the plant and are indicative of physiological health. When such measurements are combined with a reference point that reflects the maximum value or environmental limits of a parameter, such as the temperature at which photosynthesis begins to decline due to high temperature stress, we can better diagnose the proximity to potentially damaging thresholds. Here, we review a collection of useful plant status and reference point measurements related to photosynthesis, water relations and mineral nutrition, which can contribute to plant conservation physiology. We propose that these measurements can serve as important additional information to more commonly used phenological and morphological parameters, as the proposed parameters will reveal early warning signals before they are visible. We discuss their implications in the context of changing temperature, water and nutrient supply.