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The impact of climate change on foreign direct investment (FDI) at the corporate level is insufficiently explored, despite extensive discussions on environmental protection. This research utilizes novel panel data (2009–2022) on Chinese A‐share listed firms, using a two‐way fixed‐effect estimator to probe whether and how a firm's exposure to climate change influences the inflow of FDI, while considering the moderating role of environmental, social, and governance (ESG). The results show: (i) firm‐level exposure to climate change harms inward FDI inflow; (ii) host country firms can mitigate the negative effect of exposure to climate change on inward FDI inflow by strengthening their ESG performance; (iii) exposure to climate change primarily impacts FDI inflow through environmental taxes and green investments; (iv) the detrimental effect of climate change risk on incoming FDI is more pronounced in the central and eastern region of China, and among non‐state‐owned firms. These findings provide insightful theoretical and practical implications for addressing SDG 13 (Climate Action) challenges and for attracting multinational investments in developing countries like China. [ABSTRACT FROM AUTHOR]

Welded components are highly vulnerable to fatigue failures due to stress concentrations and material imperfections. This study develops an analytical framework that predicts both high‐cycle (HCF) and low‐cycle (LCF) fatigue lives of welded joints using a structural strain parameter. By employing a linear hardening model, the method effectively translates structural stress into structural strain, providing a reliable metric for assessing fatigue life, especially in LCF conditions. Validated against experimental data from 62 longitudinal gusset joints, the approach proves both reliable and practical. This simplified method facilitates easier fatigue assessments, encouraging its wider use and potential standardization in engineering, thus improving the predictability of welded structures' performance. Highlights: An analytical framework is presented to assess the fatigue behavior of welded structures.The linear hardening law is introduced to capture the material hardening behavior.The analytical solutions for plane stress and plane strain conditions are provided.The method is applied to analyze 62 weldment fatigue data in both HCF and LCF regime. [ABSTRACT FROM AUTHOR]

Detecting small and densely packed objects in images remains a significant challenge in computer vision. Existing object detection methods often exhibit low accuracy and frequently miss detection when identifying dense small objects and require larger model parameters. This study introduces a novel detection framework designed to address these limitations by integrating advanced feature fusion and optimization techniques. Our approach focuses on enhancing both detection accuracy and parameter efficiency. The approach was evaluated on the open-source VisDrone2019 data set and compared with mainstream algorithms. Experimental results demonstrate a 70.2% reduction in network parameters and a 6.3% improvement in mAP@0.5 over the original YOLOv7 algorithm. These results demonstrate that the enhanced model surpasses existing algorithms in detecting small objects. [ABSTRACT FROM AUTHOR]

A recent study published in Integrative Zoology presents findings on the chromosome-level genome assembly of the tree sparrow. The researchers identified a burst of new genes with different structures but a similar testis-specific expression pattern in the tree sparrow. These new genes were found to be the result of segmental duplications (SDs), which are large and highly identical chromosomal segments. The study also suggests that the testis-specific expression pattern of these new genes supports the "out of testis" hypothesis, which proposes that new genes emerge and acquire new functions in the testis before being expressed in other tissues. This research provides valuable insights into the role of SDs in genome evolution and the adaptation of tree sparrows to different environments. [Extracted from the article]

In the dynamic and uncertain stock market, precise forecasting and decision-making are crucial for profitability. Traditional deep neural networks (DNN) often struggle with capturing long-term dependencies and multi-scale features in complex financial time series data. To address these challenges, we introduce CMR-DQN, an innovative framework that integrates discrete wavelet transform (DWT) for multi-scale data analysis, temporal convolutional network (TCN) for extracting deep temporal features, and a GRU–LSTM–Attention mechanism to enhance the model's focus and memory. Additionally, CMR-DQN employs the Rainbow DQN reinforcement learning strategy to learn optimal trading strategies in a simulated environment. CMR-DQN significantly improved the total return rate on six selected stocks, with increases ranging from 20.37% to 55.32%. It also demonstrated substantial improvements over the baseline model in terms of Sharpe ratio and maximum drawdown, indicating increased excess returns per unit of total risk and reduced investment risk. These results underscore the efficiency and effectiveness of CMR-DQN in handling multi-scale time series data and optimizing stock market decisions. [ABSTRACT FROM AUTHOR]

The mRNA-seq data analysis is a powerful technology for inferring information from biological systems of interest. Specifically, the sequenced RNA fragments are aligned with genomic reference sequences, and we count the number of sequence fragments corresponding to each gene for each condition. A gene is identified as differentially expressed (DE) if the difference in its count numbers between conditions is statistically significant. Several statistical analysis methods have been developed to detect DE genes based on RNA-seq data. However, the existing methods could suffer decreasing power to identify DE genes arising from overdispersion and limited sample size, where overdispersion refers to the empirical phenomenon that the variance of read counts is larger than the mean of read counts. We propose a new differential expression analysis procedure: heterogeneous overdispersion genes testing (DEHOGT) based on heterogeneous overdispersion modeling and a post-hoc inference procedure. DEHOGT integrates sample information from all conditions and provides a more flexible and adaptive overdispersion modeling for the RNA-seq read count. DEHOGT adopts a gene-wise estimation scheme to enhance the detection power of differentially expressed genes when the number of replicates is limited as long as the number of conditions is large. DEHOGT is tested on the synthetic RNA-seq read count data and outperforms two popular existing methods, DESeq2 and EdgeR, in detecting DE genes. We apply the proposed method to a test dataset using RNAseq data from microglial cells. DEHOGT tends to detect more differently expressed genes potentially related to microglial cells under different stress hormones treatments. [ABSTRACT FROM AUTHOR]

A versatile division of apicomplexan parasites and a dearth of conserved regulators have hindered the progress of apicomplexan cell cycle studies. While most apicomplexans divide in a multinuclear fashion, Toxoplasma gondii tachyzoites divide in the traditional binary mode. We previously identified five Toxoplasma CDK-related kinases (Crk). Here, we investigated TgCrk4 and its cyclin partner TgCyc4. We demonstrated that TgCrk4 regulates conventional G2 phase processes, such as repression of chromosome rereplication and centrosome reduplication, and acts upstream of the spindle assembly checkpoint. The spatial TgCyc4 dynamics supported the TgCrk4–TgCyc4 complex role in the coordination of chromosome and centrosome cycles. We also identified a dominant TgCrk4–TgCyc4 complex interactor, TgiRD1 protein, related to DNA replication licensing factor CDT1 but played no role in licensing DNA replication in the G1 phase. Our results showed that TgiRD1 also plays a role in controlling chromosome and centrosome reduplication. Global phosphoproteome analyses identified TgCrk4 substrates, including TgORC4, TgCdc20, TgGCP2, and TgPP2ACA. Importantly, the phylogenetic and structural studies suggest the Crk4–Cyc4 complex is limited to a minor group of the binary dividing apicomplexans. Synopsis: Apicomplexan parasite division can yield between two and thousands of progenies, and how this process is regulated remains a mystery. This study identifies a presumed missing G2 phase, and the complex TgCrk4-TgCyc4-TgiRD1 that regulates G2 phase, in Toxoplasma gondii. Expression of the CDK-related kinase TgCrk4, of the cyclin TgCyc4, and of the inhibitor of the DNA and centrosome reduplication TgiRD1 is essential for binary division of T. gondii tachyzoites. Removing TgCrk4 and TgiRD1 triggers the reduplication of chromosomes and centrosomes, revealing their role as guardians of the "once per cycle" duplication rule. Although distantly related to fungal and metazoan CDT1, TgiRD1 does not license DNA replication in G1 phase. Comparative genomic studies imply that expression of the Crk4-Cyc4 complex is restricted to apicomplexan parasites undergoing binary division. A previously unrecognized G2 phase in apicomplexan parasites undergoing binary division depends on a novel CDK-related kinase, an atypical cyclin, and a Cdt1-related inhibitor of re-duplication. [ABSTRACT FROM AUTHOR]

Background Plasmodium vivax presents a significant challenge for malaria elimination in the Greater Mekong Subregion. We evaluated the effectiveness of primaquine for reducing relapses of vivax malaria. Methods Patients with uncomplicated P vivax malaria from eastern Myanmar received chloroquine (25-mg base/kg given in 3 days) plus unsupervised PQ (0.25 mg/kg/d for 14 days) without screening for glucose-6-phosphate dehydrogenase deficiency and were followed for a year. Results A total of 556 patients were enrolled to receive the chloroquine/primaquine treatment from February 2012 to August 2013. During the follow-up, 38 recurrences were detected, presenting a cumulative recurrence rate of 9.1% (95% CI, 4.1%–14.1%). Genotyping at the pvmsp1 and pvmsp3α loci by amplicon deep sequencing and model prediction indicated that 13 of the 27 recurrences with genotyping data were likely due to relapses. Notably, all confirmed relapses occurred within the first 6 months. Conclusions The unsupervised standard dose of primaquine was highly effective as a radical cure for P vivax malaria in eastern Myanmar. The high presumed effectiveness might have benefited from the health messages delivered during the enrollment and follow-up activities. Six-month follow-ups in the Greater Mekong Subregion are sufficient for detecting most relapses. [ABSTRACT FROM AUTHOR]