Market expansion, state intervention and wage differentials between economic sectors in urban China : a multilevel analysis

This work was supported by the National Natural Science Foundation of China (41501151, 41329001); the China Ministry of Education (11JJDZH006); the National Key Technology R&D Program (2012BAI32B07); and the Research Centre for Urban and Regional Development, Hong Kong Institute of Asia-Pacific Studies. This research is also supported by the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning.The rising earnings inequality in China has sparked a heated debate on the socioeconomic outcomes of market transformation. While a large body of literature has focussed on the temporal trend of wage inequality during the reform period, much less attention has been devoted to the structural causes of regional variations in sectoral wage differentials. Using a micro-data sample from the 2005 one percent population sample survey and multilevel methods, this article examines the geographic variability of wage differentials between economic sectors in urban China, with a particular focus on the combination effects of market expansion and state intervention. The results indicate that sectoral wage differentials vary substantially across regions, and that market expansion interacts with state intervention to reconfigure earnings outcomes. Specifically, prefectures located in the interior region tend to exhibit a large wage premium for the state sectors, while prefectures located in the coastal region tend to display a wage advantage of the foreign-invested sector. The wage gap between the state and non-state sectors is smaller in areas with diversified ownership; openness to foreign investment increases the relative wages of foreign-invested-sector employees; stringent government regulation of industries increases the wage gap between the state monopoly sector and the non-monopoly sector; and strong redistributive power increases the wage premium for the public service sector over other sectors. Our findings suggest the necessity to take into account contextually constituted and locally specific wage-setting mechanisms when studying China’s wage inequality.Publisher PDFPeer reviewe

Exploiting dynamic scheduling for VM-based code obfuscation

Code virtualization built upon virtual machine (VM) technologies is emerging as a viable method for implementing code obfuscation to protect programs against unauthorized analysis. State-of-the-art VM-based protection approaches use a fixed scheduling structure where the program follows a single, static execution path for the same input. Such approaches, however, are vulnerable to certain scenarios where the attacker can reuse knowledge extracted from previously seen software to crack applications using similar protection schemes. This paper presents DSVMP, a novel VM-based code obfuscation approach for software protection. DSVMP brings together two techniques to provide stronger code protection than prior VM-based schemes. Firstly, it uses a dynamic instruction scheduler to randomly direct the program to execute different paths without violating the correctness across different runs. By randomly choosing the program execution paths, the application exposes diverse behavior, making it much more difficult for an attacker to reuse the knowledge collected from previous runs or similar applications to perform attacks. Secondly, it employs multiple VMs to further obfuscate the relationship between VM bytecode and their interpreters, making code analysis even harder. We have implemented DSVMP in a prototype system and evaluated it using a set of widely used applications. Experimental results show that DSVMP provides stronger protection with comparable runtime overhead and code size when compared to two commercial VMbased code obfuscation tools

Personal, social, and ecological influences on loneliness and satisfaction among rural-to-urban migrants in Shanghai, China

Working PaperThis study examined personal, social, and ecological influences on loneliness and satisfaction among rural-urban migrants in Shanghai, China. Data used in this study were from the Shanghai Rural-to-Urban Migrant Worker Survey conducted by the Institute of Demographic Research, Fudan University, China. A host of demographic, socioeconomic, psychological, and ecological factors were identified as strong correlates of loneliness and satisfaction. In addition to upward social mobility manifested in socioeconomic achievement and improvement in living condition, living arrangement, psychosocial factors, and ecological contexts also exhibited important influences on mental well-being of rural-to-urban migrants in Shanghai. Friendly and helpful attitudes and equal treatment of the receiving urban community were associated with better mental health of these migrant workers. The effect of private or institutional discrimination was overwhelmingly negative on migrant mental well-being over and above other demographic, socioeconomic and psychological variables. Establishing neighborhood public facilities such as library and gym and taking measures to encourage family reunion of the migrants seem to be potentially fruitful ways to promote migrant mental well-being in China. But most essentially, policy makers should consider ways to reduce institutional inequalities disadvantaging rural-to-urban migrants and to help change the perennial image of rural-to-urban migrants as secondary citizens in cities

Group distance magic labeling of the Cartesian product of two directed cycles

Let $\overrightarrow{G}$ be a finite simple directed graph with $n$ vertices, and let $\Gamma$ be a finite abelian group of order $n$. A $\Gamma$-distance magic labeling is a bijection $\varphi:V(\overrightarrow{G})\longrightarrow \Gamma$ for which there exists $c\in\Gamma$ such that $\sum_{y\in N^+(x)}\varphi(y)-\sum_{y\in N^-(x)}\varphi(y) = c$ for any $x\in V(\overrightarrow{G})$, where $N^+(x)$ and $N^-(x)$ denote the set of the head and the tail of $x$, respectively. In this paper, we obtain a necessary and sufficient condition for that there exists a $\Gamma$-distance magic labeling for the Cartesian products of two directed cycles

Immune indicators as predictors of cancer-related fatigue: a risk prediction model in pan-cancer patients

BackgroundCancer‐related fatigue (CRF) is a prevalent and multifactorial symptom that significantly impairs the quality of life in cancer patients. This study aimed to identify immune and clinical factors associated with CRF in a pan-cancer cohort and to develop a predictive model for CRF to inform personalized clinical management.MethodsA retrospective analysis was conducted on clinical data from 146 cancer patients admitted to the Oncology Department of the First Affiliated Hospital of Tianjin University of Traditional Chinese Medicine. The variables collected included demographic information, disease‐related data, immunological parameters, and Brief Fatigue Inventory (BFI) scores. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for CRF. A predictive model was developed, and its performance was evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis.ResultsAnalysis results showed that multivariate logistic regression identified increasing age, increased absolute counts (AC) of CD4+CD38−T cells, and decreased AC of CD4+CD28−T cells as independent risk factors for CRF (P < 0.05). The predictive model demonstrated moderate performance, with an area under the ROC curve (AUC) of 0.725 in the training set and 0.581 in the validation set.ConclusionThese findings suggest that chronic inflammation, potentially associated with immunosenescence and immune remodeling, may contribute to the onset of CRF. Further research is needed to validate the model in large-scale, diverse patient populations and to develop targeted interventions to alleviate fatigue and improve the quality of life in cancer patients

Active anti-acetylcholinesterase component of secondary metabolites produced by the endophytic fungi of Huperzia serrata

Background: An endophytic fungus lives within a healthy plant during certain stages of, or throughout, its life cycle. Endophytic fungi do not always cause plant disease, and they include fungi that yield different effects, including mutual benefit, and neutral and pathogenic effects. Endophytic fungi promote plant growth, improve the host plant's resistance to biotic and abiotic stresses, and can produce the same or similar biologically active substances as the host. Thus, endophytic fungal products have important implications in drug development. Result: Among the numerous endophytic fungi, we identified two strains, L10Q37 and LQ2F02, that have anti-acetylcholinesterase activity, but the active compound was not huperzine A. The aim of this study was to investigate the anti-acetylcholinesterase activity of secondary metabolites isolated from the endophytic fungi of Huperzia serrata . Microbial cultivation and fermentation were used to obtain secondary metabolites. Active components were then extracted from the secondary metabolites, and their activities were tracked. Two compounds that were isolated from endophytic fungi of H. serrata were identified and had acetylcholine inhibitory activities. In conclusion, endophytic fungal strains were found in H. serrata that had the same anti-acetylcholinesterase activity. Conclusion: We isolated 4 compounds from the endophytic fungus L10Q37, among them S1 and S3 are new compounds. 6 compounds were isolated from LQ2F02, all 6 compounds are new compounds. After tested anti acetylcholinesterase activity, S5 has the best activity. Other compounds' anti acetylcholinesterase activity was not better compared with huperzine A

Integrating single-cell transcriptomics and whole-genome CRISPR CAS9 screen identifies a cell cluster associated with tumor dependency in triple-negative breast cancer

BackgroundTriple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype; however, clinically approved prognostic biomarkers and therapeutic options remain limited. This study aimed to investigate tumor dependency genes to identify novel therapeutic targets for TNBC.MethodsTumor dependency genes for TNBC were identified using the The Cancer Dependency Map (DEPMAP) database. The TCGA-BRCA dataset was utilized to analyze the expression, survival associations, and pathway enrichment of these genes. Single-cell datasets were employed to explore cellular trajectories and biological functions within tumor dependency gene-associated cell subpopulations. Genomic sequencing was used to investigate the somatic mutational landscape influencing the infiltration abundance of the tumor dependency-associated subpopulation. The METABRIC dataset assessed the impact of the tumor dependency-associated subpopulation on radiotherapy, chemotherapy, and combination therapy outcomes. Potential drugs were identified using the Connectivity Map (CMAP). Colony formation experiment and the CCK-8 experiment were performed to validate the biological function of gene.ResultsFour tumor dependency genes (TDGs) were identified. These genes were highly expressed in TNBC and associated with poor prognosis. Enrichment analysis revealed their significant involvement in cell cycle-related pathways. Single-cell analysis demonstrated that the tumor dependency-associated subpopulation (TDAS), defined by these four genes, resided at the differentiation terminus of epithelial/tumor cells and was linked to energy metabolism and cell proliferation pathways. Crucially, patients with high TDAS infiltration abundance were found to be unsuitable for surgery alone and should receive combined radiotherapy or chemotherapy. Potential therapeutic agents targeting the TDAS were screened. And in vitro experiments confirmed the cell proliferation role of candidate genes.ConclusionThis study identifies four potential TNBC biomarkers for assessing TDAS abundance, providing novel insights and strategies for personalized TNBC treatment

Exploiting Code Diversity to Enhance Code Virtualization Protection

Code virtualization built upon virtual machine (VM)technologies is emerging as a viable method for implementing code obfuscation to protect programs against unauthorized analysis. State-of-the-art VM-based protection approaches use a fixed set of virtual instructions and bytecode interpreters across programs. This, however, exposes a security vulnerability where an experienced attacker can use knowledge extracted from other programs to quickly uncover the mapping between virtual instructions and native code for applications protected under the same scheme. In this paper, we propose a novel VM-based code obfuscation system to address this problem. The core idea of our approach is to obfuscate the mapping between the opcodes of bytecode instructions and their semantics. We achieve this by partitioning each protected code region into multiple segments where the mapping of opcodes and their semantics is randomized in different ways in different segments. In this way, each bytecode instruction will be translated into different native code in different sections of the obfuscated code. This significantly increases the diversity of the program behavior. As a result, the knowledge of bytecode to native code mappings obtained from other programs will be less useful when targeting a new program. We evaluate our approach on a set of real-world applications and compare it against two state-of-the-art VM-based code obfuscation approaches. Experimental results show that our approach is effective, which provides stronger protection with comparable runtime overhead and code size