Green supply chain finance strategies with market competition and financial constraints.

In the context of sustainable development, market competition is intensifying, and financial constraints have emerged as a significant hindrance to green project investment. Green Supply Chain Finance (GSCF), characterized by long-term collaboration, has emerged as a crucial financial approach to mitigate corporate financial limitations and channel capital flows into environmentally friendly industries. We propose a two-echelon supply chain with one supplier and two competing retailers over a single period and investigate ordering, sales, and financing decisions simultaneously under competition. Retailers constrained by financial considerations may secure GSCF or traditional bank financing (BF) loans. This study investigates the influence of competition on pricing and sales strategies during the selling season. The results demonstrate that retailers select between clearance and responsive selling strategies based on the level of market competition. During the ordering season, retailers share the product market equally when interest rates are uniform, and the supplier formulates a supply chain contract while considering the financing interest rate. In the presence of differential interest rates, retailers may not always opt for the GSCF, even when they offer an interest rate advantage, due to the comprehensive impacts of operational and financial strategies. Remarkably, competitive retailers do not choose the GSCF when their initial green investment capital surpasses a certain threshold.

Intelligent assessment of atrial fibrillation gradation based on sinus rhythm electrocardiogram and baseline information.

BACKGROUND: Atrial fibrillation (AF) is a progressive arrhythmia that significantly affects a patient's quality of life. The 4S-AF scheme is clinically recommended for AF management; however, the evaluation process is complex and time-consuming. This renders its promotion in primary medical institutions challenging. This retrospective study aimed to simplify the evaluation process and present an objective assessment model for AF gradation. METHODS: In total, 189 12-lead electrocardiogram (ECG) recordings from 64 patients were included in this study. The data were annotated into two groups (mild and severe) according to the 4S-AF scheme. Using a preprocessed ECG during the sinus rhythm (SR), we obtained a synthesized vectorcardiogram (VCG). Subsequently, various features were calculated from both signals, and age, sex, and medical history were included as baseline characteristics. Different machine learning models, including support vector machines, random forests (RF), and logistic regression, were finally tested with a combination of feature selection techniques. RESULTS: The proposed method demonstrated excellent performance in the classification of AF gradation. With an optimized feature set of VCG and baseline features, the RF model achieved accuracy, sensitivity, and specificity of 83.02 %, 80.56 %, and 88.24 %, respectively, under the inter-patient paradigm. CONCLUSION: Our results demonstrate the value of physiological signals in AF gradation evaluation, and VCG signals were effective in identifying mild and severe AF. Considering its low computational complexity and high assessment performance, the proposed model is expected to serve as a useful prognostic tool for clinical AF management.

Patient Biochemistry and Treatment Need in Chronic Hepatitis B Virus Infection Across Three Continents: Retrospective Cross-Sectional Cohort Studies.

INTRODUCTION: Chronic hepatitis B virus (HBV) infection is associated with significant global morbidity and mortality. Low treatment rates are observed in patients living with HBV; the reasons for this are unclear. This study sought to describe patients' demographic, clinical and biochemical characteristics across three continents and their associated treatment need. METHODS: This retrospective cross-sectional post hoc analysis of real-world data used four large electronic databases from the United States, United Kingdom and China (specifically Hong Kong and Fuzhou). Patients were identified by first evidence of chronic HBV infection in a given year (their index date) and characterized. An algorithm was designed and applied, wherein patients were categorized as treated, untreated but indicated for treatment and untreated and not indicated for treatment based on treatment status and demographic, clinical, biochemical and virological characteristics (age; evidence of fibrosis/cirrhosis; alanine aminotransferase [ALT] levels, HCV/HIV coinfection and HBV virology markers). RESULTS: In total, 12,614 US patients, 503 UK patients, 34,135 patients from Hong Kong and 21,614 from Fuzhou were included. Adults (99.4%) and males (59.0%) predominated. Overall, 34.5% of patients were treated at index (range 15.9-49.6%), with nucleos(t)ide analogue monotherapy most commonly prescribed. The proportion of untreated-but-indicated patients ranged from 12.9% in Hong Kong to 18.2% in the UK; almost two-thirds of these patients (range 61.3-66.7%) had evidence of fibrosis/cirrhosis. A quarter (25.3%) of untreated-but-indicated patients were aged ≥ 65 years. CONCLUSION: This large real-world dataset demonstrates that chronic hepatitis B infection remains a global health concern; despite the availability of effective suppressive therapy, a considerable proportion of predominantly adult patients apparently indicated for treatment are currently untreated, including many patients with fibrosis/cirrhosis. Causes of disparity in treatment status warrant further investigation.

The first high resolution PAH record of industrialization over the past 200 years in Liaodong Bay, northeastern China.

Polycyclic aromatic hydrocarbons (PAHs) are excellent tracers for fossil fuel combustion, natural fires and petroleum contamination, and have been widely used for reconstructing past wildfires and industrial activities at a variety of time scales. Here, for the first time, we obtain a high resolution (annual to decadal scale) record of PAHs from two parallel marine sediment cores from the Liaodong Bay, Northeastern China to reconstruct the industrial activities, spanning the past ∼ 200 years from 1815 to 2014. Our data indicate that PAH variations can be divided into four episodes: I) low (probably near background) PAHs from natural fires and domestic wood combustion during the pre-industrial period from 1815 to 1890; II) slightly increased (but with large fluctuations) PAH concentrations derived from intermittent warfare during the World War (1891-1945) and increased industrial activities after 1946 (1946-1965); III) a period of stagnation and, in some cases, reduction in PAHs during the "Cultural Revolution" (1966 to 1979); and IV) a rapid and persistent rise in PAHs post 1979 linked to fast economic development, with PAH concentrations doubled from 1979 to 2014. Changes in PAH distributions demonstrate major shifts in the dominant types of fuels over time from vegetation/wood, to coal and wood, followed by coal and petroleum (including vehicle emissions) over the past 200 years. We find that PAH records also show similar trend to domestic economy and the estimated regional Anthropocene CO2 emissions from industrial activities, suggesting sedimentary PAH fluxes could be used as an indirect and qualitative proxy to track the trend for regional anthropogenic CO2 emissions.

Sustainable supply chain partner selection and order allocation: A hybrid fuzzy PL-TODIM based MCGDM approach.

Sustainability, as a trend of social development and the embodiment of corporate social responsibility, has begun to receive more attention. To achieve this goal, sustainable supplier selection (SSS) and order allocation (OA) are seen as the crucial activities in corporate management. In the process of SSS, the psychological behavior of decision-makers (DMs) could play a critical role in the evaluation results. Therefore, introducing it into the decision-making process may lead to decision in line with the actual situation. In the uncertain multi-criteria group decision-making (MCGDM) problem described by probability linguistic term sets (PLTS), the DMs can evaluate the criteria of each supplier based on his own preference and hesitation, which is useful to avoid the loss of information. For this reason, this study develops a novel multi-criteria group decision-making combined with fuzzy multi-objective optimization (MCGDM-FMOO) model for SSS/OA problems by considering the triple bottom line (TBL) in which includes economic, environmental and social factors. The proposed method includes four stages. (1) the best-worst method (BWM) and entropy weight method are utilized to assign the weights of criteria to obtain the comprehensive weight. According to the output weights, the an acronym for interactive and multi-criteria decision-making in Portugese (TODIM) approach is applied to rank the suppliers under PLTS environment; (2) a FMOO model that can effectively deal with uncertainties and dynamic nature of parameter is formulated for allocating optimal order quantities; (3) two novel approaches are utilized to solve the FMOO model in order to obtain the richer Pareto frontier; and (4) the final OA solution is achieved by technique for order preference by similarity to ideal solution (TOPSIS) method. Finally, the validity and practicability of proposed MCGDM-FMOO model are verified by an example and comparative analysis with other classical MCGDM methods.

Strategic interaction of original equipment manufacturers between outsourcing and purchasing in a quality-differentiated market.

Economic globalization has swept the whole world. To focus on their main business, enterprises that are referred to as original equipment manufacturers (OEMs) outsource non-core production activities to contract manufacturers (CMs). By constructing a two-level supply chain consisting of two competing OEMs and one upstream CM, the strategic interaction of the OEMs between outsourcing and purchasing is studied. Specifically, the CM can offer custom- and predefined modes of original equipment manufacturing (namely, CO mode and PO mode, respectively). The former mode enables OEMs to determine product quality, while the latter only allows them to purchase from several quality configurations. The results show that, first, since the CO mode allows the adopter to lead the product design, whether to choose this mode depends on the required R&D cost. Interestingly, however, a lower R&D cost does not necessarily result in the adoption of the CO mode if the product quality difference is small under the PO mode. Second, the optimal purchasing strategy of an OEM is indifferent to the outsourcing mode (CO and PO) of its rival but significantly affected by the quality cost. However, compared to the PO mode, choosing the CO mode would cause the competitor to suffer more profit losses. Third, differing from the prior literature, this paper finds that when the downstream OEM can make quality decisions, although this may lead to profit loss of the contract manufacturer in some channels, it could benefit the CM overall.

Vulnerability assessment and management planning for the ecological environment in urban wetlands.

As a special ecosystem in cities, urban wetland parks have important environmental regulation and social service functions. This paper proposes a new methodology of urban wetland planning and management based on the vulnerability of the ecological environment. The Jixi National Wetland Park (JNWP) was taken as the research area to analyze the ecological, geological and environmental factors that affect urban wetlands. A remote sensing image, digital elevation model, and environmental quality interpolation processing were used to generate the factor layer, and a comprehensive evaluation index system was established. The fuzzy Delphi analytic hierarchy process (FDAHP) method was used to calculate the comprehensive weight of each evaluation factor. A model to evaluate the ecological environment vulnerability of the JNWP was established. Then, an improved k-means clustering algorithm was used to classify the ecological environment of the study area. The ecological environment vulnerability of the wetland was evaluated. The results showed that the vulnerability of the ecological environment in the study area could be divided into five levels, including very low, low, medium, high and very high vulnerability areas. According to the vulnerability level and the results of k-means++ cluster analysis, the JNWP is divided into five areas. The wetland buffer zone is the main factor that determines the distribution of ecological environment vulnerability in urban wetlands. However, cultivated land development and ecological environmental restoration are the main factors that determine the evolution of ecological environment vulnerability in urban wetlands. The FDAHP and geographic information systems (GIS), combined with cluster analysis, are effective methods to evaluate the vulnerability of the ecological environment of urban wetlands, which provides a scientific and accurate methodology for the management and sustainable development of urban wetlands.

Comparison of apparent diffusion coefficient and T2 relaxation time variation patterns in assessment of age and disc level related intervertebral disc changes.

PURPOSE: To compare the variation patterns of ADC and T2 values in different age and intervertebral disc (IVD) levels, thus to identify their sensitivities in assessing age and disc level related IVDs changes. MATERIALS AND METHODS: The T2 and ADC values were recorded from 345 IVDs of 69 volunteers. Kendall's correlation analysis was used to identify the relationship between age and T2/ADC mean values respectively. The one-way analysis of variance (ANOVA) with post hoc analysis was then applied to test the differences of T2 and ADC values among different IVD levels and age groups, followed by linear regression analysis between age (<45 and >45 years) and T2/ADC mean values. This study was approved by the Ethics Committee of the Chinese Academy of Medical Sciences and the Peking Union Medical College Hospital. RESULTS: Significant negative correlation was observed between age and T2/ADC mean values. The T2 and ADC values showed significant differences among IVD levels and among age groups except for T2 values in age group 1 (25-34 years) and group 2 (35-44 years), and for ADC values at L1-2 level. Both T2 and ADC values showed significant differences between young (age<45 years) and elderly group (age>45 years) at each IVD level. A linear relationship was observed between age and T2/ADC mean values in the elderly group as well as in the young group for the ADC mean values, while no such tendency was identified in the young group for the T2 mean values. CONCLUSIONS: ADC values may be a more sensitive parameter than T2 in assessing age and disc level related intervertebral disc changes.

Economical, green synthesis of fluorescent carbon nanoparticles and their use as probes for sensitive and selective detection of mercury(II) ions.

The present article reports on a simple, economical, and green preparative strategy toward water-soluble, fluorescent carbon nanoparticles (CPs) with a quantum yield of approximately 6.9% by hydrothermal process using low cost wastes of pomelo peel as a carbon source for the first time. We further explore the use of such CPs as probes for a fluorescent Hg(2+) detection application, which is based on Hg(2+)-induced fluorescence quenching of CPs. This sensing system exhibits excellent sensitivity and selectivity toward Hg(2+), and a detection limit as low as 0.23 nM is achieved. The practical use of this system for Hg(2+) determination in lake water samples is also demonstrated successfully.

Hydrothermal treatment of grass: a low-cost, green route to nitrogen-doped, carbon-rich, photoluminescent polymer nanodots as an effective fluorescent sensing platform for label-free detection of Cu(II) ions.

Increasing reaction temperature produces photoluminescent polymer nanodots (PPNDs) with decreased particle size and increased quantum yield. Such PPNDs are used as an effective fluorescent sensing platform for label-free sensitive and selective detection of Cu(II) ions with a detection limit as low as 1 nM. This method is successfully applied to determine Cu(2+) in real water samples.