Job satisfaction and turnover decision of employees in the Internet sector in the US

This paper proposes that high value on the work-life balance, compensation, career opportunity and fitness of culture and management style would improve job satisfaction. A turnover risk prediction model based on the random forest is constructed to understand the turnover risk feature and identify risk. Using a sample of 17,724 online reviews of employees from Glassdoor, the positive effect of antecedents, the job satisfaction variable as a mediator, and the unemployment rate variable as a moderator is verified. Finally, job satisfaction is identified as the most important feature for predicting turnover based on the random forest algorithm

The Ethical Issues of Location-Based Services on Big Data and IoT

Both Internet of Things (IoT) and big data are hot topics in recent years. They indeed have brought about the change of business, promoted the progress of science and technology, and facilitated the lives of human beings. IoT creates the opportunity to connect every item to the Internet, and countless science and technology have supported the achievement of this goal. LBS is one of the indispensable technologies. It brings significant benefits to the business community, the individual, the society, and the national defense. However, at the same time, an individual’s personal information is disclosed and even attacked by ‘information thieves’. An inevitable reality is that the prerequisite of getting a location service is to expose your position first. Therefore, the privacy-related ethics issues are generated, and the danger is imminent, although there are corresponding protective measures

Multimodal Open-Vocabulary Video Classification via Pre-Trained Vision and Language Models

Utilizing vision and language models (VLMs) pre-trained on large-scale image-text pairs is becoming a promising paradigm for open-vocabulary visual recognition. In this work, we extend this paradigm by leveraging motion and audio that naturally exist in video. We present \textbf{MOV}, a simple yet effective method for \textbf{M}ultimodal \textbf{O}pen-\textbf{V}ocabulary video classification. In MOV, we directly use the vision encoder from pre-trained VLMs with minimal modifications to encode video, optical flow and audio spectrogram. We design a cross-modal fusion mechanism to aggregate complimentary multimodal information. Experiments on Kinetics-700 and VGGSound show that introducing flow or audio modality brings large performance gains over the pre-trained VLM and existing methods. Specifically, MOV greatly improves the accuracy on base classes, while generalizes better on novel classes. MOV achieves state-of-the-art results on UCF and HMDB zero-shot video classification benchmarks, significantly outperforming both traditional zero-shot methods and recent methods based on VLMs. Code and models will be released

Quantitative assessment of the associations between XRCC1 polymorphisms and bladder cancer risk

BACKGROUND: The XRCC1 polymorphisms have been implicated in bladder cancer risk, but individually published studies show inconsistent results. The aim of our study was to clarify the effects of XRCC1 variants on bladder cancer risk. METHODS: A systematic literature search up to September 13, 2012 was carried out in PubMed, EMBASE and Wanfang databases, and the references of retrieved articles were screened. Crude odds ratios with 95% confidence intervals were used to assess the associations between XRCC1 Arg194Trp and Arg399Gln polymorphisms and bladder cancer risk. Heterogeneity and publication bias were also evaluated. RESULTS: A total of 14 and 18 studies were eligible for meta-analyses of Arg194Trp and Arg399Gln, respectively. Regrouping was adopted in accordance with the most probable appropriate genetic models. No obvious heterogeneity between studies was found. For overall bladder cancer, the pooled odds ratios for Arg194Trp and Arg399Gln were 1.69 (95% confidence interval: 1.25 to 2.28; P = 0.001) and 1.10 (95% confidence interval: 1.03 to 1.19; P = 0.008), respectively. After excluding the studies that were not in Hardy–Weinberg equilibrium, the estimated pooled odds ratio still did not change at all. CONCLUSIONS: The meta-analysis results suggest that XRCC1 Arg194Trp and Arg399Gln polymorphisms may be associated with elevated bladder cancer risk

Understanding the Factors That Control theFormation and Morphology of Zn5(OH)8(NO3)2⋅2H2Othrough Hydrothermal Route

The influence of the choice of ethanol-water volume ratio, concentration of zinc salt, and ZnO buffer layer on the formation andmorphology of Zn5(OH)8(NO3)2⋅2H2O grown from the hydrothermal route was systematically discussed. Experimental resultssuggested that Zn5(OH)8(NO3)2⋅2H2O rectangle sheets and Zn5(OH)8(NO3)2⋅2H2O upright-standing plates were obtained bylimiting ethanol-water volume ratio. The concentration of zinc salt was crucial for getting phase-pure Zn5(OH)8(NO3)2⋅2H2O. Thepresence of ZnO buffer layer could lead to the that chemical composition of product grown on the substrate was totally differentfrom the product grown in the solution. Possible formation mechanism of Zn5(OH)8(NO3)2⋅2H2O was also studied. Ramanspectrum of Zn5(OH)8(NO3)2⋅2H2O displays a complex behavior with four modes, which can be assigned to the vibrationalmodes of Zn–H–O, Zn–O, H2O-nitrate, and nitrate. Porously ZnO rectangle sheets were obtained by thermal treatment ofZn5(OH)8(NO3)2⋅2H2O rectangle sheets

Pyrolysis gas as a carbon source for biogas production via anaerobic digestion

Carbon is an important resource for anaerobes to enhance biogas production. In this study, the possibility of using simulated pyrolysis gas (SPG) as a carbon source for biogas production was investigated. The effects of stirring speed (SS), gas holding time (GHT), and H2 addition on biomethanation of SPG were evaluated. The diversity and structure of microbial communities were also analyzed under an illumina MiSeq platform. Results indicated that at a GHT of 14 h and an SS at 400 rpm, SPG with up to 64.7% CH4could be bio-upgraded to biogas. Gas–liquid mass transfer is the limitation for SPG biomethanation. For the first time, it has been noticed that the addition of H2 can bioupgrade SPG to high quality biogas (with 91.1% CH4). Methanobacterium was considered as a key factor in all reactors. This study provides an idea and alternative way to convert lignocellulosic biomass and solid organic waste into energy (e.g., pyrolysis was used as a pretreatment to produce pyrolysis gas from biomass, and then, pyrolysis gas was bioupgraded to higher quality biogas via anaerobic digestion)

Facile preparation of high-performance Fe-doped Ce–Mn/TiO2 catalysts for the low-temperature selective catalytic reduction of NOx with NH3†

A Ce–Mn–Fe/TiO2 catalyst has been successfully prepared using a single impregnation method, and excellent low-temperature NH3-SCR activity was demonstrated in comparison with other typical SCR catalysts including Mn–Ce/TiO2 and metal-doped Mn–Ce/TiO2. The crystal structure, morphology, textural properties, valence state of the metals, acidity and redox properties of the novel catalyst were investigated comprehensively by X-ray diffraction (XRD), N2 adsorption and desorption analysis, X-ray photoelectron spectroscopy (XPS), NH3-temperature-programmed desorption (NH3-TPD), and H2-temperature-programmed reduction (H2-TPR). The Fe-doped Ce–Mn/TiO2 catalyst boosted the low-temperature NH3-SCR activity effectively under a broad temperature range (100–280 °C) with a superior NO conversion rate at low temperatures (100 °C, 96%; 120–160 °C, ∼100%). Fe doping caused this improvement by enlarging the catalyst pore volume, improving the redox properties, and increasing the amount of acidic sites. These properties enhanced the ability of the catalyst to adsorb NH3 and improved the low-temperature SCR performance, especially at temperatures lower than 150 °C. Moreover, redox cycles of Ce, Mn, and Ti (Mn4+ + Ce3+ ↔ Mn3+ + Ce4+, Mn4+ + Ti3+ ↔ Mn3+ + Ti4+) also played an important role in enhancing the low-temperature SCR efficiency by accelerating the electron transfer. The excellent NH3-SCR result is promising for developing environmentally-friendly and more effective industrial catalysts in the future

Photoluminescence mechanism and applications of Zn-doped carbon dots

Heteroatom-doped carbon dots (CDs) with excellent optical characteristics and negligible toxicity have emerged in many applications including bioimaging, biosensing, photocatalysis, and photothermal therapy. The metal-doping of CDs using various heteroatoms results in an enhancement of the photophysics but also imparts them with multifunctionality. However, unlike nonmetal doping, typical metal doping results in low fluorescence quantum yields (QYs), and an unclear photoluminescence mechanism. In this contribution, we detail results concerning zinc doped CDs (Zn-CDs) with QYs of up to 35%. The zinc ion charges serve as a surface passivating agent and prevent the aggregation of graphene p–p stacking, leading to an increase in the QY of the Zn-CDs. Structural and chemical investigations using spectroscopic and first principle simulations further revealed the effects of zinc doping on the CDs. The robust Zn-CDs were used for the ultra-trace detection of Hg2+ with a detection limit of 0.1 mM, and a quench mechanism was proposed. The unique optical properties of the Zn-CDs have promise for use in applications such as in vivo sensing and future phototherapy applications

Risk prediction models for incident type 2 diabetes in Chinese people with intermediate hyperglycemia : a systematic literature review and external validation study

Background People with intermediate hyperglycemia (IH), including impaired fasting glucose and/or impaired glucose tolerance, are at higher risk of developing type 2 diabetes (T2D) than those with normoglycemia. We aimed to evaluate the performance of published T2D risk prediction models in Chinese people with IH to inform them about the choice of primary diabetes prevention measures. Methods A systematic literature search was conducted to identify Asian-derived T2D risk prediction models, which were eligible if they were built on a prospective cohort of Asian adults without diabetes at baseline and utilized routinely-available variables to predict future risk of T2D. These Asian-derived and five prespecified non-Asian derived T2D risk prediction models were divided into BASIC (clinical variables only) and EXTENDED (plus laboratory variables) versions, with validation performed on them in three prospective Chinese IH cohorts: ACE (n = 3241), Luzhou (n = 1333), and TCLSIH (n = 1702). Model performance was assessed in terms of discrimination (C-statistic) and calibration (Hosmer-Lemeshow test). Results Forty-four Asian and five non-Asian studies comprising 21 BASIC and 46 EXTENDED T2D risk prediction models for validation were identified. The majority were at high (n = 43, 87.8%) or unclear (n = 3, 6.1%) risk of bias, while only three studies (6.1%) were scored at low risk of bias. BASIC models showed poor-to-moderate discrimination with C-statistics 0.52-0.60, 0.50-0.59, and 0.50-0.64 in the ACE, Luzhou, and TCLSIH cohorts respectively. EXTENDED models showed poor-to-acceptable discrimination with C-statistics 0.54-0.73, 0.52-0.67, and 0.59-0.78 respectively. Fifteen BASIC and 40 EXTENDED models showed poor calibration (P < 0.05), overpredicting or underestimating the observed diabetes risk. Most recalibrated models showed improved calibration but modestly-to-severely overestimated diabetes risk in the three cohorts. The NAVIGATOR model showed the best discrimination in the three cohorts but had poor calibration (P < 0.05). Conclusions In Chinese people with IH, previously published BASIC models to predict T2D did not exhibit good discrimination or calibration. Several EXTENDED models performed better, but a robust Chinese T2D risk prediction tool in people with IH remains a major unmet need.Peer reviewe