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The concept of “all cores are created equal” has been popular for several decades due to its simplicity and effectiveness in CPU (Central Processing Unit) design. The more cores the CPU has, the higher performance the host owns and the higher the power consumption. However, power-saving is also one of the key goals for servers in data centers and embedded devices (e.g., mobile phones). The big.LITTLE multicore architecture, which contains high-performance cores (namely big core) and power-saved cores (namely little core), has been developed by ARM (Advanced RISC Machine) and Intel to trade off performance and power efficiency. Facing the new heterogeneous computing architecture, the traditional lock algorithms, which are designed to run on homogeneous computing architecture, cannot work optimally as usual and drop into the performance issue for the difference between big core and little core. In our preliminary experiment, we observed that, in the big.LITTLE multicore architecture, all these lock algorithms exhibit sub-optimal performance. The FIFO-based (First In First Out) locks experience throughput degradation, while the performance of competition-based locks can be divided into two categories. One of them is big-core-friendly, so their tail latency increases significantly; the other is little-core-friendly. Not only does the tail latency increase, but the throughput is also degraded. Motivated by this observation, we propose a Core-Aware Lock for the big.LITTLE multicore architecture named CAL, which keeps each core having an equal opportunity to access the critical section in the program. The core idea of the CAL is to take the slowdown ratio as the matric to reorder lock requests of these big and little cores. By evaluating benchmarks and a real-world application named LevelDB, CAL is confirmed to achieve fairness goals in heterogeneous computing architecture without sacrificing the performance of the big core. Compared to several traditional lock algorithms, the CAL’s fairness has increased by up to 67%; and Its throughput is 26% higher than FIFO-based locks and 53% higher than competition-based locks, respectively. In addition, the tail latency of CAL is always kept at a low level.

Although NAND (Not And) flash-based Solid-State Drive (SSD) has recently demonstrated a significant performance advantage against hard disk, it still suffers from non-negligible performance under-utilization issues as the access conflict often occurs during servicing IO requests due to the share mechanism (e.g., several chips share one channel bus, several planes share one data register inside the die). Many research works have been devoted to minimizing access conflict by redesigning IO scheduling, cache replacement, and so on. These works have achieved reasonable results; however, the potential data similarity characterization is not utilized fully in prior works to alleviate access conflict. The basic idea is that, as data duplication is common in many workloads where data with the same content from different requests could be distributed to the address with minimized access conflict (i.e., the address does not share the same channel or chip), the logic address is mapped to more than one physical address. Therefore, the data can be read out from candidate pages when the channel or chip of its original address is busy. Motivated by this idea, we propose Data Similarity aware Flash Translation Layer (DS-FTL), which mainly includes a content-aware page allocation scheme and a multi-path read scheme. The DS-FTL enables maximization of the channel-level and chip-level parallelism and avoids the read stall induced by bus-shared mechanisms. We also conducted a series of experiments on SSDsim, with the subsequent results depicting the effectiveness of our scheme. Compared with the state-of-art, our scheme reduces read latency by 35.3% on average in our workloads.

Based on the analysis of air quality data in Yunnan Province from 2015 to 2020, combined with spatial interpolation analysis and geographic detector factor analysis, the spatial–temporal evolution characteristics of air quality in Yunnan Province have been studied, and the main driving factors, the mechanisms, and the impact of regional COVID-19 control measures affecting air quality have been discussed. The results show that the air quality in Yunnan Province was generally good (superior rate > 98%) from 2015 to 2020, that the Air Quality Index (AQI) value is better in the wet season than in the dry season, and that the concentration of major pollutants shows a decreasing trend. AQI values are spatially high in the east and low in the west. The relative humidity, precipitation, population density, building construction area, and civil vehicles have a greater degree of explanation for the spatial differentiation of AQI, whereas the synergistic influence (maximum value 0.92) of socio-economic factors and meteorological factors is significantly greater than that of a single factor (maximum value 0.80) by the geographic detector model. The control measures for COVID-19 in 2020 reduced the concentration of major pollutants in the atmosphere to a certain extent. Controlling regional air pollution in urban agglomerations in low-latitude plateau areas can improve their air quality by reducing human activities. However, the control of O3 concentration is more complex, and more restrictive factors need to be considered. The results will provide a scientific basis for the prevention and control of air pollution in plateau cities.

To improve the robotic assembly effects in unstructured environments, a reinforcement learning (RL) algorithm is introduced to realize a variable admittance control. In this article, the mechanisms of a peg-in-hole assembly task and admittance model are first analyzed to guide the control strategy and experimental parameters design. Then, the admittance parameter identification process is defined as the Markov decision process (MDP) problem and solved with the RL algorithm. Furthermore, a fuzzy reward system is established to evaluate the action–state value to solve the complex reward establishment problem, where the fuzzy reward includes a process reward and a failure punishment. Finally, four sets of experiments are carried out, including assembly experiments based on the position control, fuzzy control, and RL algorithm. The necessity of compliance control is demonstrated in the first experiment. The advantages of the proposed algorithms are validated by comparing them with different experimental results. Moreover, the generalization ability of the RL algorithm is tested in the last two experiments. The results indicate that the proposed RL algorithm effectively improves the robotic compliance assembly ability.

The Tarim River Basin (TRB) is one of the world’s largest cotton-producing areas, and its agricultural water use accounts for up to 95% of the total water consumption in the basin. Quantifying the future changes in the irrigation area carrying capacity under global warming is therefore essential in TRB. In this study, we analyzed the variation in the irrigation area in TRB over the last few decades, utilized the nonlinear autoregressive with an exogenous input neural network to simulate the future changes in the available water resources, and predicted the future irrigation area carrying capacity based on the water balance equation. The results showed that the present (1970–2020) irrigation area in TRB exhibited an increasing trend from 491 km2 in 1970s to 1382 km2 in 2020, as most of the natural vegetation was transformed into cropland. In the future (2022–2050), the available water resource will show an upward tendency while the irrigation area carrying capacity mainly ranges from 12×102–21×102 km2 and 17×102–30×102 km2 under scenarios SSP (shared socioeconomic pathway) 245 and SSP585, respectively. The simulated results will provide useful information for the allocation of water resources and the regional sustainable development of TRB.

In the synthetic aperture radar (SAR) imaging of ship-induced wakes, it is difficult to obtain the Doppler velocity of a Kelvin wake due to the lack of time-varying wake models and suitable radar equipment. The conventional Kelvin wake investigation based on the static Kelvin wake model failed to reflect time-varying characteristics, which are significant in the application of the Kelvin wake model. Therefore, a time-varying Kelvin wake model with consideration of geometric time-varying characteristics and the hydrodynamic equation is proposed in this paper, which reflects the wake’s time-varying change lacking in the conventional Kelvin wake investigation. The Doppler velocity measurement, measured by a specially designed radar, can be exploited to verify the time-varying model by the comparison of velocity fields. Ground-based multi-input multi-output (MIMO) millimeter wave radar imaging through the simultaneous switching of transceiver channels was used to obtain the Doppler velocity for the first time. Finally, promising results have been achieved, which are in good agreement with our proposed model in consideration of the experimental scene. The proposed time-varying model and radar equipment provide velocity measurements for the Kelvin wake observation, which contains huge application potential.

The utilization of chicken embryonic-derived pluripotent stem cell (PSC) lines is crucial in various fields, including growth and development, vaccine and protein production, and germplasm resource protection. However, the research foundation for chicken PSCs is relatively weak, and there are still challenges in establishing a stable and efficient PSC culture system. Therefore, this study aims to investigate the effects of the FGF2/ERK and WNT/β-catenin signaling pathways, as well as different feeder layers, on the derivation and maintenance of chicken embryonic-derived PSCs. The results of this study demonstrate that the use of STO cells as feeder layers, along with the addition of FGF2, IWR-1, and XAV-939 (FIX), allows for the efficient derivation of chicken PSC-like cells. Under the FIX culture conditions, chicken PSCs express key pluripotency genes, such as POUV, SOX2, and NANOG, as well as specific proteins SSEA-1, C-KIT, and SOX2, indicating their pluripotent nature. Additionally, the embryoid body experiment confirms that these PSC-like cells can differentiate into cells of three germ layers in vitro, highlighting their potential for multilineage differentiation. Furthermore, this study reveals that chicken Eyal–Giladi and Kochav stage X blastodermal cells express genes related to the primed state of PSCs, and the FIX culture system established in this research maintains the expression of these genes in vitro. These findings contribute significantly to the understanding and optimization of chicken PSC culture conditions and provide a foundation for further exploration of the biomedical research and biotechnological applications of chicken PSCs.

An external electric field is an effective tool to induce the polymorphic transformation of molecular crystals, which is important practically in the chemical, material, and energy storage industries. However, the understanding of this mechanism is poor at the molecular level. In this work, two types of order parameters (OPs) were constructed for the molecular crystal based on the intermolecular distance, bond orientation, and molecular orientation. Using the K-means clustering algorithm for the sampling of OPs based on the Euclidean distance and density weight, the polymorphic transformation of TNT was investigated using a finite temperature string (FTS) under external electric fields. The potential of mean force (PMF) was obtained, and the essence of the polymorphic transformation between o-TNT and m-TNT was revealed, which verified the effectiveness of the FTS method based on K-means clustering to OPs. The differences in PMFs between the o-TNT and transition state were decreased under external electric fields in comparison with those in no field. The fields parallel to the c-axis obviously affected the difference in PMF, and the relationship between the changes in PMFs and field strengths was found. Although the external electric field did not promote the convergence, the time of the polymorphic transformation was reduced under the external electric field in comparison to its absence. Moreover, under the external electric field, the polymorphic transformation from o-TNT to m-TNT occurred while that from m-TNT to o-TNT was prevented, which was explained by the dipole moment of molecule, relative permittivity, chemical potential difference, nucleation work and nucleation rate. This confirmed that the polymorphic transformation orientation of the molecular crystal could be controlled by the external electric field. This work provides an effective way to explore the polymorphic transformation of the molecular crystals at a molecular level, and it is useful to control the production process and improve the performance of energetic materials by using the external electric fields.

The delivery of biocompatible reagents into cancer cells can elicit an anticancer effect by taking advantage of the unique characteristics of the tumor microenvironment (TME). In this work, we report that nanoscale two-dimensional FeII- and CoII-based metal–organic frameworks (NMOFs) of porphyrin ligand meso-tetrakis (6-(hydroxymethyl) pyridin-3-yl) porphyrin (THPP) can catalyze the generation of hydroxyl radicals (•OH) and O2 in the presence of H2O2 that is overexpressed in the TME. Photodynamic therapy consumes the generated O2 to produce a singlet oxygen (1O2). Both •OH and 1O2 are reactive oxygen species (ROS) that inhibit cancer cell proliferation. The FeII- and CoII-based NMOFs were non-toxic in the dark but cytotoxic when irradiated with 660 nm light. This preliminary work points to the potential of porphyrin-based ligands of transition metals as anticancer drugs by synergizing different therapeutic modalities.