High Precision Positioning and Rotation Angle Estimation of a Flatbed Truck Based on BDS and Vision.

Centimeter-level localization and precise rotation angle estimation for flatbed trucks pose significant challenges in unmanned forklift automated loading scenarios. To address this issue, the study proposed a method for high-precision positioning and rotation angle estimation of flatbed trucks using the BeiDou Navigation Satellite System (BDS) and vision technology. First, an unmanned forklift equipped with a Time-of-Flight (ToF) camera and a dual-antenna mobile receiver for BDS positioning collected depth images and localization data near the front and rear endpoints of the flatbed. The Deep Dual-Resolution Network-23-slim (DDRNet-23-slim) model was used to segment the flatbed from the depth image and extract the straight lines at the edges of the flatbed using the Hough transform. The algorithm then computed the set of intersection points of the lines. A neighborhood feature vector was designed to identify the endpoint of a flatbed from a set of intersection points using feature screening. Finally, the relative coordinates of the endpoints were converted to a customized forklift navigation coordinate system by BDS positioning. A rotation angle estimation was then performed using the endpoints at the front and rear. Experiments showed that the endpoint positioning error was less than 3 cm, and the rotation angle estimation error was less than 0.3°, which verified the validity and reliability of the method.

A scoping review of utilization of the verbal fluency task in Chinese and Japanese clinical settings with near-infrared spectroscopy.

This review targets the application of the Verbal Fluency Task (VFT) in conjunction with functional near-infrared spectroscopy (fNIRS) for diagnosing psychiatric disorders, specifically in the contexts of China and Japan. These two countries are at the forefront of integrating fNIRS with VFT in clinical psychiatry, often employing this combination as a complementary tool alongside traditional psychiatric examinations. Our study aims to synthesize research findings on the hemodynamic responses elicited by VFT task in clinical settings of the two countries, analyzing variations in task design (phonological versus semantic), stimulus modality (auditory versus visual), and the impact of language typology. The focus on China and Japan is crucial, as it provides insights into the unique applications and adaptations of VFT in these linguistically and culturally distinct environments. By exploring these specific cases, our review underscores the importance of tailoring VFT to fit the linguistic and cultural context, thereby enhancing its validity and utility in cross-cultural psychiatric assessments.

Research on Performance Evaluation of Polymeric Surfactant Cleaning Gel-Breaking Fluid (GBF) and Its Enhanced Oil Recovery (EOR) Effect.

Clean fracturing fluid has the characteristics of being environmentally friendly and causing little damage to reservoirs. Meanwhile, its backflow gel-breaking fluids (GBFs) can be reutilized as an oil displacement agent. This paper systematically evaluates the feasibility and EOR mechanism of a GBF based on a polymer surfactant as an oil displacement system for reutilization. A rotating interfacial tensiometer and contact angle measuring instrument were used to evaluate the performance of reducing the oil-water interfacial tension (IFT) and to change the rock wettability, respectively. Additionally, a homogeneous apparatus was used to prepare emulsions to evaluate GBF's emulsifying properties. Finally, core flooding experiments were used to evaluate the EOR effect of GBFs, and the influence rules and main controlling effects of various properties on the EOR were clarified. As the concentration of GBFs increases, the IFT first decreases to the lowest of 0.37 mN/m at 0.20 wt% and then increases and the contact angle of the rock wall decreases from 129° and stabilizes at 42°. Meanwhile, the emulsion droplet size gradually decreases and stabilizes with increases in GBF concentration, and the smallest particle size occurs when the concentration is 0.12-0.15 wt%. The limited adsorption area of the oil-water interface and the long molecular chain are the main reasons that limit the continued IFT reduction and emulsion stability. The oil displacement experiment shows that the concentration of GBF solution to obtain the best EOR effect is 0.15 wt%. At this concentration, the IFT reduction and the emulsification performance are not optimal. This shows that the IFT reduction performance, reservoir wettability change performance, and emulsification performance jointly determine the EOR effect of GBFs. In contrast, the emulsifying performance of GBFs is the main controlling factor for the EOR. Finally, the optimal application concentration of GBFs is 0.15-0.20 wt%, and the optimal injection volume is 0.5 PV.

Facts in counterfactuals-cognitive representations of Chinese counterfactuals.

How do people represent counterfactuals? As languages differ in expressibility of counterfactuals-some languages employ explicit grammatical marking for counterfactuals while others do not-are some speakers' representations of counterfactuals less explicit? Prior studies examining this question with Chinese speakers-a language devoid of explicit counterfactual markings-found mixed results. Here we re-examined the issue by using a more sensitive test: people's sensitivity to detect anomalies in sentences. We asked Chinese speakers to rate the acceptability of sentences employing "ruguo (if)…jiu (then)" configuration-the typical but non-unique, non-explicit marking of counterfactuals. Critically, we varied the semantic adherence to real-world facts [factuality], with some sentences containing made-up conditions [-fact as in "If fish had legs, then…"] versus real facts [+ fact: "If dogs had legs, then…"]. If speakers represent counterfactuals clearly, they should give higher acceptability ratings to [- facts] than to [+ facts] sentences, because the ostensible point of counterfactuals is to express non-factual situations. That is, expressing a true fact under a syntactic counterfactual construction makes the sentence anomalous. Instead, we found that Chinese speakers gave the opposite ratings: factual "if…then" sentences were rated as more acceptable than non-factual ones. This suggests that Chinese speakers find the processing of counterfactuals to be more challenging than processing facts, and that their representation of counterfactuals may be less explicit. Overall, this research contributes to our understanding of the link between linguistic markings and cognitive representations.

Inhibition of LSD1 induces ferroptosis through the ATF4-xCT pathway and shows enhanced anti-tumor effects with ferroptosis inducers in NSCLC.

Lysine-specific demethylase 1 (LSD1) has been identified as an important epigenetic target, and recent advances in lung cancer therapy have highlighted the importance of targeting ferroptosis. However, the precise mechanisms by which LSD1 regulates ferroptosis remain elusive. In this study, we report that the inhibition of LSD1 induces ferroptosis by enhancing lipid peroxidation and reactive oxygen species (ROS) accumulation. Mechanistically, LSD1 inhibition downregulates the expression of activating transcription factor 4 (ATF4) through epigenetic modification of histone H3 lysine 9 dimethyl (H3K9me2), which sequentially inhibits the expression of the cystine-glutamate antiporter (xCT) and decreases glutathione (GSH) production. Furthermore, LSD1 inhibition transcriptionally upregulates the expression of transferrin receptor (TFRC) and acyl-CoA synthetase long chain family member 4 (ACSL4) by enhancing the binding of histone H3 lysine 4 dimethyl (H3K4me2) to their promoter sequences. Importantly, the combination of an LSD1 inhibitor and a ferroptosis inducer demonstrates an enhanced anti-tumor effect in a xenograft model of non-small cell lung cancer (NSCLC), surpassing the efficacy of either agent alone. These findings reveal new insights into the mechanisms by which LSD1 inhibition induces ferroptosis, offering potential guidance for the development of new strategies in the treatment of NSCLC.

Discovery of YS-363 as a highly potent, selective, and orally efficacious EGFR inhibitor.

The Epidermal Growth Factor Receptor (EGFR) tyrosine kinase inhibitors (TKIs) are the standard first-line therapy for EGFR-mutated NSCLC. However, long-term clinical treatment often leads to acquired drug resistance, making NSCLC refractory. Therefore, it is essential to design new EGFR inhibitors as potential drugs against NSCLC. This study reports on a novel quinazoline-based compound called YS-363 that acts as a new EGFR inhibitor. YS-363 demonstrated potent inhibition against both wild-type and L858R mutant forms of EGFR with IC50 values of 0.96 nM and 0.67 nM, respectively. Additionally, YS-363 had a reversible inhibitory effect on cellular EGFR signaling, had excellent inhibitory activity on cell proliferation and migration, and induced G0/G1 cell cycle arrest and apoptosis. In xenograft models dependent on EGFR signaling, oral administration of YS-363 substantially suppressed tumor growth by inhibiting this pathway. In summary, YS-363 is a promising selective reversible inhibitor with a novel quinazoline scaffold that can potentially develop more effective anti-lung cancer agents targeting EGFR in patients who have developed resistance to current therapies such as TKIs like gefitinib or erlotinib.

Fine-grained Lesion Classification Framework for Early Auxiliary Diagnosis.

The deep neural networks are envisaged for the early disease diagnosis from medical images. However, in the early stage of the disease, the medical images of patients and healthy people have only subtle visual differences. Distinguishing the medical images for early diagnosis belongs to the Fine-Grained Visual Classification (FGVC) task. Many recent works are based on a standard FGVC learning paradigm: locate the discriminative regions first and then classify by fusing the information of these regions. However, it is still not enough for medical images. Because the shape and size of the lesions are variable, and the relationship between lesions and the background is complex. In order to solve these problems, we propose a fine-grained lesion classification framework for early auxiliary diagnosis. We first locate and extract multiple lesions with different sizes and shapes from the original image and then fuse the feature of lesion and background based on attention mechanism. As shown by experiment results in two real-world clinical data sets, our model can locate accurately and perform better.

Research on renewable energy prediction technology: empirical analysis for Argentina and China.

Our world needs to develop clean energy to reach the target of carbon peak and carbon neutralization. As one of clean energy, wind energy should contribute to energy conservation and emission reduction. Wind power generation is an important field of wind energy application. However, the fluctuation and intermittency of wind can affect the safety of power system. Therefore, prediction of wind power accurately for wind power safety, dispatching, and power grid development is significant. This paper proposes a prediction model of wind power, and predicts the wind power of two wind farms. For the complex wind speed series, the variational modal decomposition (VMD) method is used to reduce its volatility before prediction. And this paper presents an improved method to improve the prediction efficiency when least square support vector machine (LSSVM) predicts stationary series. The prediction result shows that the proposed model improves the prediction of wind power effectively, provides an effective method for wind farm to predict the wind power, and makes contributions to reducing carbon emissions and environmental protection.

Preparation of liposome coated hollow copper sulfide nano-enzyme and their combined laser irradiation to against melanoma B16-F10 cells / 中国肿瘤生物治疗杂志

@#[摘 要] 目的：构建中空硫化铜纳米酶脂质复合载体CuS@LIP并探讨其联合激光照射杀伤黑色素瘤B6-F10细胞的效果与机制。方法：构建（2,3-二油酰基-丙基）-三甲胺-丙烷（氯盐）（DOTAP）阳离子脂质体包被硫化铜纳米载体CuS@LIP，研究不同质量浓度的CuS与CuS@LIP在1 064 nm激光照射下的光热性能和热稳定性，通过H2O2与3,3',5,5'-四甲基联苯胺（TMB）催化活性检测体系检测CuS@LIP的类过氧化物活性；用系列质量浓度梯度的CuS、CuS@LIP在有/无激光条件下分别处理B16-F10细胞，CCK-8法检测细胞的存活率，Calcein-AM/PI染色法、Annexin Ⅴ-FITC/PI染色法结合流式细胞仪分别检测20 μg/mL CuS或CuS@LIP在激光照射或非激光照射条件下对B16-F10细胞活力和凋亡的影响。结果：成功制备的CuS@LIP的平均粒径为（178.23±6.46）nm，平均Zeta电位为（20.47±0.93）mV；在激光照射下，80 μg/mL CuS@LIP最高温度可达65.4 ℃，比单纯CuS的63.4 ℃更高；经3个激光开关周期测试，CuS@LIP终点温度基本保持不变；此外，CuS@LIP与CuS具有相同的类过氧化物酶催化活性。低于20 μg/mL的CuS@LIP在体外对B16-F10细胞的增殖活性没有明显影响（P>0.05），但联合激光照射后细胞存活率明显降低（29.76±3.60）% vs （87.95±8.18）%，P<0.000 1，细胞凋亡率显著升高[（19.34±4.41）% vs （13.36±0.86）%，P<0.01]。结论：制备的CuS@LIP具有符合设计要求的理化性质、良好的光热性能和优异的类过氧化物酶催化活性，其与激光照射联合后显示出更优异的杀伤B16-F10细胞的效果。

The promising fNIRS: Uncovering the function of prefrontal working memory networks based on multi-cognitive tasks.

The diversity of cognitive task paradigms using functional near-infrared spectroscopy (fNIRS) and the lack of theoretical explanations for these functional imaging atlases have greatly hindered the application of fNIRS in psychiatry. The fNIRS brain imaging based on multiple cognitive tasks could generally reflect the working patterns and neurovascular coupling changes in the prefrontal working memory network. By alternating the stimulation patterns of resting and task states, six typical symptom-related functional brain imaging waveforms related to psychiatric disorders are identified and three joint networks of the prefrontal working memory, namely, the attentional working memory primary coordination network, the perceptual content working memory secondary network, and the emotional-behavioral working memory executive network, are initially represented. This is the first attempt to characterize the cognitive, emotional, and behavioral regulation of the prefrontal working memory network using fNIRS, which may promote the application of fNIRS in clinical settings.

An Advanced Chicken Face Detection Network Based on GAN and MAE.

Achieving high-accuracy chicken face detection is a significant breakthrough for smart poultry agriculture in large-scale farming and precision management. However, the current dataset of chicken faces based on accurate data is scarce, detection models possess low accuracy and slow speed, and the related detection algorithm is ineffective for small object detection. To tackle these problems, an object detection network based on GAN-MAE (generative adversarial network-masked autoencoders) data augmentation is proposed in this paper for detecting chickens of different ages. First, the images were generated using GAN and MAE to augment the dataset. Afterward, CSPDarknet53 was used as the backbone network to enhance the receptive field in the object detection network to detect different sizes of objects in the same image. The 128×128 feature map output was added to three feature map outputs of this paper, thus changing the feature map output of eightfold downsampling to fourfold downsampling, which provided smaller object features for subsequent feature fusion. Secondly, the feature fusion module was improved based on the idea of dense connection. Then the module achieved feature reuse so that the YOLO head classifier could combine features from different levels of feature layers to capture greater classification and detection results. Ultimately, the comparison experiments' outcomes showed that the mAP (mean average Precision) of the suggested method was up to 0.84, which was 29.2% higher than other networks', and the detection speed was the same, up to 37 frames per second. Better detection accuracy can be obtained while meeting the actual scenario detection requirements. Additionally, an end-to-end web system was designed to apply the algorithm to practical applications.

Gain or loss? The well-being of women in self-employment.

Using data from the Chinese Household Income Project survey, we find that self-employed women have lower levels of well-being compared with their male counterparts. When comparing individuals' well-being in self-employment and wage-employment, we discover that self-employed men have higher levels of health, the standard of living, satisfaction, and life satisfaction compared with wage-employed men, whereas self-employed women have lower levels of health and life satisfaction than their counterparts in wage-employment. Furthermore, if a given self-employed man or woman had been selected for wage employment, their well-being would not improve (controlling for individual characteristics that affect the likelihood to enter self-employment). Hence, self-employed women face a double challenge: lower well-being than both self-employed men and wage-employed women. The article discusses recommendations for future research and policy implications.

A High-Performance Day-Age Classification and Detection Model for Chick Based on Attention Encoder and Convolutional Neural Network.

Thanks to the boom of computer vision techniques and artificial intelligence algorithms, it is more available to achieve artificial rearing for animals in real production scenarios. Improving the accuracy of chicken day-age detection is one of the instances, which is of great importance for chicken rearing. To solve this problem, we proposed an attention encoder structure to extract chicken image features, trying to improve the detection accuracy. To cope with the imbalance of the dataset, various data enhancement schemes such as Cutout, CutMix, and MixUp were proposed to verify the effectiveness of the proposed attention encoder. This paper put the structure into various mainstream CNN networks for comparison and multiple ablation experiments. The final experimental results show that by applying the attention encoder structure, ResNet-50 can improve the accuracy of chicken age detection to 95.2%. Finally, this paper also designed a complete image acquisition system for chicken houses and a detection application configured for mobile devices.

MoS2/Ni3S2 Schottky heterojunction regulating local charge distribution for efficient urea oxidation and hydrogen evolution.

Electrocatalytic urea oxidation reaction (UOR) is a prospective method to substitute the slow oxygen evolution reaction (OER) and solve the problem of urea-rich water pollution due to the low thermodynamic voltage, but its complex six-electron oxidation process greatly impedes the overall efficiency of electrolysis. Here, density functional theory (DFT) calculations imply that the metallic Ni3S2 and semiconductive MoS2 could form Mott-Schottky catalyst because of the suitable band structure. Therefore, we synthesized MoS2/Ni3S2 electrocatalyst by a simple hydrothermal method, and studied its UOR and hydrogen evolution reaction (HER) performance. The formed MoS2/Ni3S2 Schottky heterojunction is only required 109  and 166 mV to obtain ±10 mA cm-2 for UOR and HER, respectively, showing great bifunctional catalytic activity. Moreover, the full urea electrolysis driven by MoS2/Ni3S2 delivers 10 and 100 mA cm-2 at a relatively low potential of 1.44 and 1.59 V. Comprehensive experiments and DFT calculations demonstrate that the MoS2/Ni3S2 Schottky heterojunction causes self-driven charge transfer at the interface and forms built-in electric field, which is not only benefit to reduce H* adsorption energy, but also helps to adjust the absorption and directional distribution of urea molecules, thereby promoting the activity of decomposition of water and urea. This research furnishes a tactic to devise more efficient catalysts for H2 generation and the treatment of urea-rich water pollution.

Unraveling the dynamics, heterogeneity, determinants of eco-efficiency in Beijing-Tianjin-Hebei urban agglomeration, China.

Eco-efficiency has been considered a valuable gauge for evaluating how efficient economic activities are in regard to resource inputs and eco-environmental pressures. Even though Ecosystem services (ESs) are inseparable from sustainable eco-environment, a paucity of literature has considered ESs in eco-efficiency research lines. Therefore, this study aims to construct a novel eco-efficiency evaluation framework by integrating ESs as natural capital input and measure it utilizing the Epsilon-based measure model for the county-level cities in Beijing-Tianjin-Hebei urban agglomeration (BTHUA) during the period 2005-2015. The spatial econometric technique is further performed to acquire quantitative evidence about whether ESs and other determinants impact eco-efficiency. The results revealed that eco-efficiency increased continuously in the whole BTHUA and BTHUA's optimized development functional areas, whereas eco-efficiency of BTHUA's sub-regions showed a significant temporal diversity. The average eco-efficiency values of cities in key development functional areas and restricted development functional areas showed the V-shaped trend (declining before 2010 and then rising). Interestingly, this study found that ESV economic loss may result in eco-efficiency decline for cities located in key development functional areas. From the spatial heterogeneity perspective, the city with high EE is mainly located in eastern BTHUA, whereas cities in the northern plateau areas, southwestern, and western BTHUA have relatively low EE. Furthermore, there existed a significant spatial autocorrelation and a spatial agglomeration heterogeneity, which suggests that the low-low correlation regions gradually being the most dominant spatial pattern. The results of spatial econometric model verified that water yield has the strongest positive effect on EE while soil erosion will lead to declining EE. This paper potentially provides new insights for future policy design of urban agglomeration sustainable deployment.

Synergistic Effect of TMSPi and FEC in Regulating the Electrode/Electrolyte Interfaces in Nickel-Rich Lithium Metal Batteries.

Nickel-rich LiNi0.8Co0.1Mn0.1O2 (NCM811) with respect to Li metal can enhance the energy density of lithium batteries effectively. However, the unstable Li deposition, together with the dissolution and migration of transition metal (TM) ions toward the anode deteriorate the cycle performance of NCM811||Li battery, especially when commercial carbonate electrolyte is used. Herein, tris(trimethylsilyl)phosphite (TMSPi) and fluoroethylene carbonate (FEC) are used to construct a dual-additive electrolyte, by which both electrodes can be protected. It is found that TMSPi can be preferentially adsorbed on the cathode surface through its strong coordination with Ni4+, playing the role as a HF scavenger and suppressing TM ions dissolution, as well as mitigating the structural degradation of the cathode effectively. When it comes to the lithium anode, the presence of TMSPi may lead to side reactions with Li metal, accompanied by fast dendrite growth. The introduction of FEC could facilitate the formation of stable electrode/electrolyte interfaces on both sides. Particularly, reduce the direct contact between TMSPi and Li anode, thus ameliorate the incompatibility issue. Consequently, the NCM811||Li cell with dual-additive demonstrates excellent capacity retention of 81.2% after 500 cycles at 1 C rate. As a sharp contrast, it only retains 13.9% in the one with blank electrolyte. The findings of this work provide a new insight into enhancing the cycle performance of NCM811||Li system via the synergistic effect between additives.

Nomogram for predicting transmural bowel infarction in patients with acute superior mesenteric venous thrombosis.

BACKGROUND: The prognosis of acute mesenteric ischemia (AMI) caused by superior mesenteric venous thrombosis (SMVT) remains undetermined and early detection of transmural bowel infarction (TBI) is crucial. The predisposition to develop TBI is of clinical concern, which can lead to fatal sepsis with hemodynamic instability and multi-organ failure. Early resection of necrotic bowel could improve the prognosis of AMI, however, accurate prediction of TBI remains a challenge for clinicians. When determining the eligibility for explorative laparotomy, the underlying risk factors for bowel infarction should be fully evaluated. AIM: To develop and externally validate a nomogram for prediction of TBI in patients with acute SMVT. METHODS: Consecutive data from 207 acute SMVT patients at the Wuhan Tongji Hospital and 89 patients at the Guangzhou Nanfang Hospital between July 2005 and December 2018 were included in this study. They were grouped as training and external validation cohort. The 207 cases (training cohort) from Tongji Hospital were divided into TBI and reversible intestinal ischemia groups based on the final therapeutic outcomes. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for TBI using the training data, and a nomogram was subsequently developed. The performance of the nomogram was evaluated with respect to discrimination, calibration, and clinical usefulness in the training and external validation cohort. RESULTS: Univariate and multivariate logistic regression analyses identified the following independent prognostic factors associated with TBI in the training cohort: The decreased bowel wall enhancement (OR = 6.37, P < 0.001), rebound tenderness (OR = 7.14, P < 0.001), serum lactate levels > 2 mmol/L (OR = 3.14, P = 0.009) and previous history of deep venous thrombosis (OR = 6.37, P < 0.001). Incorporating these four factors, the nomogram achieved good calibration in the training set [area under the receiver operator characteristic curve (AUC) 0.860; 95%CI: 0.771-0.925] and the external validation set (AUC 0.851; 95%CI: 0.796-0.897). The positive and negative predictive values (95%CIs) of the nomogram were calculated, resulting in positive predictive values of 54.55% (40.07%-68.29%) and 53.85% (43.66%-63.72%) and negative predictive values of 93.33% (82.14%-97.71%) and 92.24% (85.91%-95.86%) for the training and validation cohorts, respectively. Based on the nomogram, patients who had a Nomo-score of more than 90 were considered to have high risk for TBI. Decision curve analysis indicated that the nomogram was clinically useful. CONCLUSION: The nomogram achieved an optimal prediction of TBI in patients with AMI. Using the model, the risk for an individual patient inclined to TBI can be assessed, thus providing a rational therapeutic choice.

The 'double-edged effect' of progress in energy-biased technology on energy efficiency: A comparison between the manufacturing sector of China and Japan.

Based on data of the manufacturing sector of China and Japan from 2003 to 2016, this paper attempts to measure the progresses in energy-biased technology and energy efficiency by constructing a threshold panel regression model with variables including foreign direct investment (FDI) and energy consumption structure to explain energy efficiency using energy-biased technology as the key explaining variable. The estimation indicates significant differences in the energy efficiency of China's and Japan's manufacturing industries. In general, Japan's total energy efficiency is higher than China's. The industry with more intensive technology has higher energy efficiency which rises much faster. The paper finds that the energy efficiency of China's manufacturing sector shows an upward trend in general, while Japan's fluctuates more, showing two peaks and two troughs. Our empirical results show that there is a threshold value of progress in energy-biased technology; below this, progress in energy-biased technology will have a positive effect on energy efficiency and beyond it, the effect will be negative. Since this effect is not one-way, we define it as a 'double-edged effect'. It is estimated that the level of energy-biased technology progress of most manufacturing industries in China is below the threshold value, indicating that the technology progress in China's manufacturing sector has not been excessively biased towards energy consumption, and the impact on energy efficiency is still positive. The China-Japan comparison shows that the threshold value for Japan's manufacturing sector is significantly lower than that for China's, indicating a marginal effect on the 'double-edged effect': The threshold value will decrease when energy efficiency reaches a certain level. Therefore, it is necessary to offset these negative externalities from technological progress with other factors such as by increasing FDI and improving energy consumption structure.