Energy Modeling of IoT Mobile Terminals on WiFi Environmental Impacts †

With the popularity of various IoT mobile terminals such as mobile phones and sensors, the energy problems of IoT mobile terminals have attracted increasingly more attention. In this paper, we explore the impacts of some important factors of WiFi environments on the energy consumption of mobile phones, which are typical IoT end devices. The factors involve the WiFi signal strength under good signal conditions, the type and the amount of protocol packets that are initiated by WiFi APs (Access Points) to maintain basic network communication with the phones. Controlled experiments are conducted to quantitatively study the phone energy impacts by the above WiFi environmental factors. To describe such impacts, we construct a time-based signal strength-aware energy model and packet type/amount-aware energy models. The models constructed in the paper corroborate the following user experience on phone energy consumption: (1) a phone’s energy is drawn faster under higher WiFi signal strengths than under lower ones even in normal signal conditions; (2) phones consume energy faster in a public WiFi network than in a private one even in the basic phone state. The energy modeling methods proposed in the paper enable ordinary developers to analyze phone energy draw conveniently by utilizing inexpensive power meters as measurement tools. The modeling methods are general and are able to be used for phones of any type and any platform.

MEMe: A Mutually Enhanced Modeling Method for Efficient and Effective Human Pose Estimation

In this paper, a mutually enhanced modeling method (MEMe) is presented for human pose estimation, which focuses on enhancing lightweight model performance, but with low complexity. To obtain higher accuracy, a traditional model scale is largely expanded with heavy deployment difficulties. However, for a more lightweight model, there is a large performance gap compared to the former; thus, an urgent need for a way to fill it. Therefore, we propose a MEMe to reconstruct a lightweight baseline model, EffBase transferred intuitively from EfficientDet, into the efficient and effective pose (EEffPose) net, which contains three mutually enhanced modules: the Enhanced EffNet (EEffNet) backbone, the total fusion neck (TFNeck), and the final attention head (FAHead). Extensive experiments on COCO and MPII benchmarks show that our MEMe-based models reach state-of-the-art performances, with limited parameters. Specifically, in the same conditions, our EEffPose-P0 with 256 × 192 can use only 8.98 M parameters to achieve 75.4 AP on the COCO val set, which outperforms HRNet-W48, but with only 14% of its parameters.

[Establishment and Validation of Animal Models of Peripheral Diabetic Neuropathies]

Objective To analyze the common animals,modeling methods,modeling indicators,and applicable indicators of animal models of type 2 diabetic peripheral neuropathies(DPN)by literature review.Methods Literature on animal experiments concerning type 2 DPN were searched in databases including CNKI,PubMed,and Wanfang Database.The relevant indicators and data were statistically analyzed.Results SD rats were commonly used as the modeling animals of type 2 DPN,and the commonly used method was experimental induction,during which a combination of low-dose streptozotocin(STZ)and high-energy intake was applied.Indicators of successful modeling of type 2 diabetes mellitus included:fasting blood glucose>11.1 mmol/L or random blood glucose> 13.8 mmol/L and insulin resistance;indicators of successful DPN modeling included:decreased nerve conduction velocity,abnormal thermal and mechanical pain,abnormal morphology of sciatic nerve,and decreased subepidermal nerve fibers.Conclusions Type 2 DPN animal modeling usually uses SD male rats,which are fed with high-sugar and high-fat diet(containing 10% lard and 20% sucrose)or high-fat diet(containing 45%-60% Lard)combined with a single intraperitoneal injection of low-dose STZ(25-35 mg/kg),which is featured by high modeling rate,low mortality,and strong operability.With the success of modeling can be judged by the behaviors,pathomorphology,and neuroelectricity of the animals.These findings may inform further studies on the mechanisms of early-stage type 2 DPN and its interventions.

[Methods for establishing animal model of bronchopulmonary dysplasia and their evaluation]

With the development of treatment, the survival rate of premature infants has significantly increased, especially extremely premature infants and very low birth weight infants. This has led to an increase in incidence of bronchopulmonary dysplasia (BPD) year by year. BPD has been one of the most common respiratory system diseases in premature infants, especially the small premature infants. Arrested alveolar development is an important cause of BPD. Therefore, the mechanism of arrested alveolar development and the intervention measures for promoting alveolar development are the focuses of research on BPD. Selecting the appropriate animal model of BPD is the key to obtaining meaningful results in the basic research on BPD. Based on above, several common methods for establishing an animal model of BPD and the corresponding changes in pathophysiology are summarized and evaluated in order to provide a reference for selecting the appropriate animal model in studies on the pathogenesis, pathophysiology, and prevention and control strategies of BPD.

Estimation of greenhouse gas emissions from Iran's gas flaring by using satellite data and combustion equations

In addition to the waste of resources and economic losses, environmental damage by gas flaring is widespread and significant. Since flaring the associated gas gives no added value in exchange for its pollution and greenhouse gas (GHG) emissions, it could be identified as a top priority for mitigation. Iran is the third gas flaring country after Russia and Iraq among those facing this issue, and is responsible for 12.1% of the world's gas flaring. While the necessity of developing a method for the precise estimation of flaring GHG emissions is clear, especially for evaluating the result of countries' efforts to meet their nationally determined contribution target, there are huge uncertainties and discrepancies in the values of emission factors among various data sources due to the lack of actual measurements of the volume and diversity of the composition of flare gas. This study aimed to fill the gap in providing authentic data on Iran's gas flaring GHG and air pollutant emissions by developing a model based on satellite data on flare volumes, gas compositions, and combustion equations. Our results revealed that based on 2021 data on flaring volume, Iranian gas flares are emitting approximately 50 million metric tons of CO₂ equivalent to the atmosphere annually, which could be reduced to 43 by only enhancing the flares' efficiency. It accounted for 5.5%-6% of the total GHG emissions of the country. Integr Environ Assess Manag 2023;19:735-748. © 2022 SETAC.

Giant Piezoelectric Coefficient of Polyvinylidene Fluoride with Rationally Engineered Ultrafine Domains Achieved by Rapid Freezing Processing

Domains play an essential role in determining the piezoelectric properties of polymers. The conventional method for achieving ultrafine piezoelectric domain structures for polymers is multiphase polymerization, which is not the primary choice for industrial-scale applications because of its complex synthesis and weak mechanical properties. In this study, it is demonstrated for the first time that a nanoscale domain design can be achieved in a commercially available polyvinylidene fluoride (PVDF) homopolymer through a simple fabrication method involving cyclic compression and rapid freezing. The domain-engineered PVDF exhibits largely enhanced piezoelectric output with a record-breaking piezoelectric coefficient (d33) of 191.4 picocoulombs per Newton (8.9 times higher than that of PVDF without engineered domain structure) and electromechanical coupling factor (k33) of 77.1%. Moreover, nanoscale domain-induced ferroelectric and dielectric evolutions are revealed. A smaller domain is found to be beneficial for domain switching. An in-depth understanding of the interplay between the domain structure and piezoelectric properties reveals a simple, low-cost method for fabricating high-performance polymeric piezoelectric.

An Improved Model of Single-Event Transients Based on Effective Space Charge for Metal-Oxide-Semiconductor Field-Effect Transistor

In this paper, a single-event transient model based on the effective space charge for MOSFETs is proposed. The physical process of deposited and moving charges is analyzed in detail. The influence of deposited charges on the electric field in the depletion region is investigated. The electric field decreases in a short time period due to the neutralization of the space charge. After that, the electric field increases first and then decreases when the deposited charge is moved out. The movement of the deposited charge in the body mainly occurs through ambipolar diffusion because of its high-density electrons and holes. The derivation of the variation in electric field in the depletion region is modeled in the physical process according to the analysis. In combination with the ambipolar diffusion model of excessive charge in the body, a physics-based model is built to describe the current pulse in the drain terminal. The proposed model takes into account the influence of multiple factors, like linear-energy transfer (LET), drain bias, and the doping concentration of the well. The model results are validated with the simulation results from TCAD. Through calculation, the root-mean-square error (RMSE) between the simulation and model is less than 3.7 × 10-4, which means that the model matches well with the TCAD results. Moreover, a CMOS inverter is simulated using TCAD and SPICE to validate the applicability of the proposed model in a circuit-level simulation. The proposed model captures the variation in net voltage in the inverter. The simulation result obviously shows the current plateau effect, while the relative error of the pulse width is 23.5%, much better than that in the classic model. In comparison with the classic model, the proposed model provides an RMSE of 7.59 × 10-5 for the output current curve and an RMSE of 0.158 for the output voltage curve, which are significantly better than those of the classic model. In the meantime, the proposed model does not produce extra simulation time compared with the classic double exponential model. So, the model has potential for application to flow estimation of the soft error rate (SER) at the circuit level to improve the accuracy of the results.

[Methods for establishing animal model of bronchopulmonary dysplasia and their evaluation]

With the development of treatment, the survival rate of premature infants has significantly increased, especially extremely premature infants and very low birth weight infants. This has led to an increase in incidence of bronchopulmonary dysplasia (BPD) year by year. BPD has been one of the most common respiratory system diseases in premature infants, especially the small premature infants. Arrested alveolar development is an important cause of BPD. Therefore, the mechanism of arrested alveolar development and the intervention measures for promoting alveolar development are the focuses of research on BPD. Selecting the appropriate animal model of BPD is the key to obtaining meaningful results in the basic research on BPD. Based on above, several common methods for establishing an animal model of BPD and the corresponding changes in pathophysiology are summarized and evaluated in order to provide a reference for selecting the appropriate animal model in studies on the pathogenesis, pathophysiology, and prevention and control strategies of BPD.