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Halide perovskite materials have broad prospects for applications in various fields such as solar cells, LED devices, photodetectors, fluorescence labeling, bioimaging, and photocatalysis due to their bandgap characteristics. This study compiled experimental data from the published literature and utilized the excellent predictive capabilities, low overfitting risk, and strong robustness of ensemble learning models to analyze the bandgaps of halide perovskite compounds. The results demonstrate the effectiveness of ensemble learning decision tree models, especially the gradient boosting decision tree model, with a root mean square error of 0.090 eV, a mean absolute error of 0.053 eV, and a determination coefficient of 93.11%. Research on data related to ratios calculated through element molar quantity normalization indicates significant influences of ions at the X and B positions on the bandgap. Additionally, doping with iodine atoms can effectively reduce the intrinsic bandgap, while hybridization of the s and p orbitals of tin atoms can also decrease the bandgap. The accuracy of the model is validated by predicting the bandgap of the photovoltaic material MASn1−xPbxI3. In conclusion, this study emphasizes the positive impact of machine learning on material development, especially in predicting the bandgaps of halide perovskite compounds, where ensemble learning methods demonstrate significant advantages. [ABSTRACT FROM AUTHOR]

Urban Agglomeration (UA) is regarded as an emerging complex urban system in China. The development of UA demands a reasonable scale structure, which can be investigated by Zipf's law. However, few studies have been conducted to quantify the optimal scale of UA and how its development deviates from the optimal scale. With the continuous urban expansion, the problem of UAs' scale structure has received increasing attention. In this study, we propose a method based on Zipf's law for estimating the theoretical optimal scale of UAs in China and assessing the deviation rate from their optimal scales. Twelve typical UAs in China are selected, and their development is assessed via urban impervious surface data from 2000 to 2018. The results show that the average deviation rate of the investigated UAs decreased from 3.40% in 2000 to 2.32% in 2018, demonstrating that these UAs are on a positive evolution trajectory. Furthermore, according to the development stage, we make recommendations on "large cities vs. medium/small-sized cities and promoting vs. restraining" to each UA based on its size. The conceptual and analytical knowledge, as well as the results from this study, are expected to offer valuable insights and new references for regulating and managing UAs' development in China. [ABSTRACT FROM AUTHOR]

The purpose of this study is to verify whether the transportation infrastructure investment carried out by the Asian Infrastructure Investment Bank (AIIB) has promoted the economic development of its recipient countries. Since the establishment of the AIIB, its investments in infrastructure development, aimed at promoting economic growth in Asian developing countries, have garnered considerable attention. This study selects India, the largest recipient country of the AIIB, as the research object and chooses the Gujarat Road Project as the research case, since it is a completed infrastructure construction investment project in the transportation field. This paper provides an overview of the project's operation and summarizes key factors in the project's implementation. In the data analysis section, the per capita GDP is selected as the explained variable to measure economic development, and the LASSO regression method is used to select several variables that affect economic development. Moreover, the random forest model is used to obtain the causal relationship between road construction and the per capita GDP from 2001 to 2022. The results indicate that road construction in India has a significant positive effect on per capita GDP growth, the Gujarat Road Project supported by the AIIB also has a positive effect on per capita GDP growth, and this effect is stronger than that at the national level. The main contribution of this work is the validation of the investment strategy of the AIIB and the quantification of the economic contribution of AIIB investment projects to the local area. [ABSTRACT FROM AUTHOR]

D2D communication is a promising technology for enhancing spectral efficiency (SE) in cellular networks, and full-duplex (FD) has the potential to double SE. Due to D2D's short-distance communication and low transmittance power, it is natural to integrate FD into D2D, creating FD-D2D to underlay a cellular network to further improve SE. However, the residual self-interference (RSI) resulting from FD-D2D and interference arising from spectrum sharing between D2D users (DUs) and cellular users (CUs) can restrict D2D link performance. Therefore, we propose an FD-D2D underlying cellular system in which DUs jointly share uplink and downlink spectral resources with CUs. Moreover, we present two algorithms to enhance the performance experience of DUs while improving the system's SE. For the first algorithm, we tackle an optimization problem aimed at maximizing the sum rate of FD-DUs in the system while adhering to transmittance power constraints. This problem is formulated as a mixed-integer nonlinear programming problem (MINLP), known for its mathematical complexity and NP-hard nature. In order to address this MINLP, our first algorithm decomposes it into two subproblems: power control and spectral resource allocation. The power control aspect is treated as a nonlinear problem, which we solve through one-dimensional searching. Meanwhile, spectral resource allocation is achieved using the Kuhn–Munkres algorithm, determining the pairing of CUs and DUs sharing the same spectrum. As for the second algorithm, our objective is to enhance the individual performance of FD-DUs by maximizing the minimum rate among them, ensuring more uniform rate performance across all FD-DUs. In order to solve this optimization problem, we propose a novel spectral resource allocation algorithm based on bisection searching and the Kuhn–Munkres algorithm, whereas the power control aspect remains the same as in the first algorithm. The numerical results demonstrate that our proposed algorithm effectively enhances the performance of DUs in an FD-D2D underlying cellular network when compared to the sum rate maximization design. [ABSTRACT FROM AUTHOR]

In this paper, a micro‐bare‐tube heat exchanger structure with the tube bundle diameter varying gradually in the range of 1.0–0.4 mm is proposed. The airside friction and heat transfer performance correlations for this structure are given. This paper applies CFD simulation to develop and verify the correlation of the diameter gradually varied micro‐bare‐tube heat exchangers' performance. Compared with the traditional same diameter micro‐bare‐tube heat exchanger, the new structure not only reduces the pressure drop, but also improves the thermal hydraulic performance. The friction coefficient f is decreased by 8.59%, the pressure drop is reduced by 43.14%, the heat transfer coefficient j is increased by 12.07% compared to the constant diameter micro‐bare‐tube heat exchanger. At the same time, it reduces the void volume by 47.32% and the tube bundle manufacturing material by 28.57%. The proposed airside performance prediction equation can make the error of more than 70% source data within 10%, and the error of more than 90% source data within 20%. It is suggested to apply this empirical equation to 7–29 rows. [ABSTRACT FROM AUTHOR]

The problem of accurately measuring the motion parameters of low radar cross-section (RCS) maneuvering targets has long been a hurdle in the radar technology landscape. Small targets, due to their elusive characteristics, are particularly difficult to detect with conventional radar systems. In this paper, we investigate the capabilities of dechirp-receiving stepped-frequency radar, a modern system using a linear frequency modulation signal for downconversion. This permits the radar to function at reduced sampling rates while maintaining the transmission of large-bandwidth signals and achieving synthetic imaging. Our primary contribution is introducing the stepped dechirp generalized Radon–Fourier transform (stepped DGRFT) algorithm. This novel approach allows the radar system to perform coherent accumulation, enhancing the accuracy of motion parameter estimates for low-RCS maneuvering targets. Results from our simulations and measured data analysis validate the effectiveness of our proposed algorithm, demonstrating its superiority over other methods. [ABSTRACT FROM AUTHOR]

Introduction: Parasagittal meningiomas (PM) are very common intracranial lesion but their occurrence in young adult is very rare. Most giant PM are characterized with the invasion of the superior sagittal sinus and form very huge collaterals which makes surgical resection very difficult. The origin of meningioma is still a matter of debate which make our case much more puzzling. We therefore reviewed detailed literature on the etiologies of meningioma as well. Case presentation: We present a case of 24-years old young lady with history of seizures, blurred vision, intermittent tremors and occasional dropping of objects on the right arm. She had dizziness, headaches, tinnitus and paresthesia on the right side with loss of smell. She had a transient amaurosis fugax once before presenting to us. MRI done revealed a huge tumor compression on the left fronto-parietal gyrus and invading the superior sagittal sinus (SSS). The goal of surgery in this young lady was to preserve the SSS completely, stop frequent seizures and also preserve eloquent areas since the lesion was lying directly on the focal motor area. With a good preoperative evaluation and careful resection of the tumor, we achieved total resection without any further neurologic complications. Conclusion: We believe the etiology of meningioma in our patients started at childhood and progress to this giant status. We therefore suggest that neurosurgeon's screen children early to detect meningiomas before they advance into giant stages. Two years follow-up after surgery showed no tumor recurrence. Keywords: Parasagittal meningiomas (PM), Superior sagittal sinus (SSS), Seizures, Young female, Angiography

Bi2Te3‐based alloys have great market demand in miniaturized thermoelectric (TE) devices for solid‐state refrigeration and power generation. However, their poor mechanical properties increase the fabrication cost and decrease the service durability. Here, this work reports on strengthened mechanical robustness in Bi2Te3‐based alloys due to thermodynamic Gibbs adsorption and kinetic Zener pinning at grain boundaries enabled by MgB2 decomposition. These effects result in much‐refined grain size and twofold enhancement of the compressive strength and Vickers hardness in (Bi0.5Sb1.5Te3)0.97(MgB2)0.03 compared with that of traditional powder‐metallurgy‐derived Bi0.5Sb1.5Te3. High mechanical properties enable excellent cutting machinability in the MgB2‐added samples, showing no missing corners or cracks. Moreover, adding MgB2 facilitates the simultaneous optimization of electron and phonon transport for enhancing the TE figure of merit (ZT). By further optimizing the Bi/Sb ratio, the sample (Bi0.4Sb1.6Te3)0.97(MgB2)0.03 shows a maximum ZT of ≈1.3 at 350 K and an average ZT of 1.1 within 300–473 K. As a consequence, robust TE devices with an energy conversion efficiency of 4.2% at a temperature difference of 215 K are fabricated. This work paves a new way for enhancing the machinability and durability of TE materials, which is especially promising for miniature devices. [ABSTRACT FROM AUTHOR]

GeTe and (Bi,Sb)2Te3 are two representative thermoelectric (TE) materials showing maximum performance at middle and low temperature, respectively. In order to achieve higher performance over the whole temperature range, their segmented one‐leg TE modules are designed and fabricated by one‐step spark plasma sintering (SPS). To search for contact and connect layers, the diffusion behavior of Fe, Ni, Cu, and Ti metal layers in GeTe is studied systematically. The results show that Ti with a similar linear expansivity (10.80 × 10−6 K−1) to GeTe, has low contact resistance (3 µΩ cm2) and thin diffusion layer (0.4 µm), and thus is an effective metallization layer for GeTe. The geometric structure of the GeTe/(Bi,Sb)2Te3 segmented one‐leg TE module and the ratio of GeTe to (Bi,Sb)2Te3 are determined by finite element simulation method. When the GeTe height ratio is 0.66, its theoretical maximum conversion efficiency (ηmax) can reach 15.9% without considering the thermal radiation and thermal/electrical contact resistance. The fabricated GeTe/(Bi,Sb)2Te3 segmented one‐leg TE module showed a ηmax up to 9.5% with a power density ≈ 7.45 mW mm−2, which are relatively high but lower than theoretical predictions, indicating that developing segmented TE modules is an effective approach to enhance TE conversion efficiency. [ABSTRACT FROM AUTHOR]

Due to the characteristics of global coverage, on-demand access, and large capacity, the low earth orbit (LEO) satellite communication (SatCom) has become one promising technology to support the Internet-of-Things (IoT). However, due to the scarcity of satellite spectrum and the high cost of designing satellites, it is difficult to launch a dedicated satellite for IoT communications. To facilitate IoT communications over LEO SatCom, in this paper, we propose the cognitive LEO satellite system, where the IoT users act as the secondary user to access the legacy LEO satellites and cognitively use the spectrum of the legacy LEO users. Due to the flexibility of code division multiple access (CDMA) in multiple access and the wide use of CDMA in LEO SatCom, we apply CDMA to support cognitive satellite IoT communications. For the cognitive LEO satellite system, we are interested in the achievable rate analysis and resource allocation. Specifically, considering the randomness of spreading codes, we use the random matrix theory to analyze the asymptotic signal-to-interference-plus-noise ratios (SINRs) and accordingly obtain the achievable rates for both legacy and IoT systems. The power of the legacy and IoT transmissions at the receiver are jointly allocated to maximize the sum rate of the IoT transmission subject to the legacy satellite system performance requirement and the maximum received power constraints. We prove that the sum rate of the IoT users is quasi-concave over the satellite terminal receive power, based on which the optimal receive powers for these two systems are derived. Finally, the resource allocation scheme proposed in this paper has been verified by extensive simulations. [ABSTRACT FROM AUTHOR]

The prostate tumor suppressor NKX3.1 augments response to DNA damage and enhances survival after DNA damage. Within minutes of DNA damage, NKX3.1 undergoes phosphorylation at tyrosine 222, which is required for a functional interaction with ataxia telangiectasia mutated (ATM) kinase. NKX3.1 binds to the N-terminal region of ATM, accelerates ATM activation, and hastens the formation of γhistone2AX. NKX3.1 enhances DNA-dependent ATM kinase activation by both the MRN complex and H2O2 in a DNA-damage-independent manner. ATM, bound to the NKX3.1 homeodomain, phosphorylates NKX3.1, leading to ubiquitination and degradation. Thus, NKX3.1 and ATM have a functional interaction leading to ATM activation and then NKX3.1 degradation in a tightly regulated DNA damage response specific to prostate epithelial cells. These findings demonstrate a mechanism for the tumor-suppressor properties of NKX3.1, demonstrate how NKX3.1 may enhance DNA integrity in prostate stem cells and may help to explain how cells differ in their sensitivity to DNA damage.

A traffic crash is becoming one of the major factors that leads to unexpected death in the world. Short window traffic crash prediction in the near future is becoming more pragmatic with the advancements in the fields of artificial intelligence and traffic sensor technology. Short window traffic prediction can monitor traffic in real time, identify unsafe traffic dynamics, and implement suitable interventions for traffic conflicts. Crash prediction being an important component of intelligent traffic systems, it plays a crucial role in the development of proactive road safety management systems. Some near future crash prediction models were put forward in recent years; further improvements need to be implemented for actual applications. This paper utilizes traffic accident data from the study Freeway in China to build a time series-based count data model for daily crash prediction. Lane traffic flow, weather information, vehicle speed, and truck to car ratio were extracted from the deployment of non-intrusive detection systems with support of the Bridge Management Administration study and were input into the model as independent variables. Different types of prediction models in machine learning and time series forecasting methods such as boosting, ARIMA, time-series count data model, etc. are compared within the paper. Results show that integrating time series with a count data model can capture traffic accident features and account for the temporal structure for variable serial correlation. A prediction error of 0.7 was achieved according to Root Mean Squared Deviation. [ABSTRACT FROM AUTHOR]

Realizing high average thermoelectric figure of merit (ZTave) and power factor (PFave) has been the utmost task in thermoelectrics. Here the new strategy to independently improve constituent factors in ZT is reported, giving exceptionally high ZTave and PFave in n‐type PbSe. The nonstoichiometric, alloyed composition and resulting defect structures in new Pb1+xSe0.8Te0.2 (x = 0–0.125) system is key to this achievement. First, incorporating excess Pb unusually increases carrier mobility (µH) and concentration (nH) simultaneously in contrast to the general physics rule, thereby raising electrical conductivity (σ). Second, modifying charge scattering mechanism by the authors' synthesis process boosts a magnitude of Seebeck coefficient (S) above theoretical expectations. Detouring the innate inverse proportionality between nH and µH; and σ and S enables independent control over them and change the typical trend of PF to temperature, giving remarkably high PFave ≈20 µW cm−1 K−2 from 300 to 823 K. The dual incorporation of Te and excess Pb generates unusual antisite Pb at the anionic site and displaced Pb from the ideal position, consequently suppressing lattice thermal conductivity. The best composition exhibits a ZTave of ≈1.2 from 400 to 823 K, one of the highest reported for all n‐type PbQ (Q = chalcogens) materials. [ABSTRACT FROM AUTHOR]

Isobaric specific heat capacity (Cp) is an important parameter not only in physics but also for most materials. Its accurate measurement is particularly critical for performance evaluation of thermoelectric materials, but the experiments by differential scanning calorimetry (DSC) often lead to large uncertainties in the measurements, especially at elevated temperatures. In this study, we propose a simple method to determine Cp by measuring the sound velocity (υ) based on lattice vibration and expansion theory. The relative standard error of the υ is smaller than 1%, showing good accuracy and repeatability. The calculated Cp at elevated temperature (>300 K) increases slightly with increasing temperature due to the lattice expansion, which is more reasonable than the Dulong–Petit value. [ABSTRACT FROM AUTHOR]

This paper proposes a system of 6G Internet of Things (IoT) based on downlink non-orthogonal multiple access (NOMA) technology, where the base station (BS) allows signals of the same frequency to serve users at different distances. In particular, we study a cooperative MIMO-NOMA system based on downlink simultaneous wireless information and power transfer (SWIPT) assistance. To improve the overall performance, we employ machine learning to optimize user-pairing and radio resource allocation. At the end of the paper, the simulation results are obtained, which fully prove that the MIMO-NOMA system constructed in this paper is correct in theory and can be realized in practice. [ABSTRACT FROM AUTHOR]

In order to promote the economic development of China's provinces and provide references for the provinces to make effective economic decisions, it is urgent to investigate the trend of province-level economic development. In this study, DMSP/OLS data and NPP/VIIRS data were used to predict economic development. Based on the GDP data of China's provinces from 1992 to 2016 and the nighttime light remote sensing (NTL) data of corresponding years, we forecast GDP via the linear model (LR model), ARIMA model, ARIMAX model, and SARIMA model. Models were verified against the GDP records from 2017 to 2019. The experimental results showed that the involvement of NTL as exogenous variables led to improved GDP prediction. [ABSTRACT FROM AUTHOR]