Quantitative Evaluation of the Supply Chain Collaboration

Supply Chain Collaboration (SCC) is defined as a status of optimized overall utility of the supply chain under the precondition of satisfactions of each supply chain member. The achievement of SCC is relative to the cooperation mechanisms or contracts among members. To evaluate the degree of SCC in different contracts, a quantitative index of Collaboration Percent (CP) is defined, which can be used to evaluate the efficiency of the supply chain resources usage and direct the design and improvement of the contracts among supply chain members. The results of theoretic analysis and numerical experiments proved the validation of the quantitative evaluation index CP.published or submitted for publicationis peer reviewe

Formation of Oil-Particle-Aggregates: Numerical Model Formulation and Calibration

When oil spills occur in turbid waters, the oil droplets and mineral grains can combine to form oil-particle aggregates (OPAs). The formation of OPAs impacts the vertical transport of both the oil and the mineral grains; especially increasing deposition of oil to the seabed. Though the coastal oceans can be very turbid, to date, few numerical ocean models have accounted for aggregation processes that form OPAs. However, interactions between oil and mineral aggregates may be represented using techniques developed to account for sediment aggregation. As part of Consortium for Simulation of Oil Microbial Interactions in the Ocean (CSOMIO), we modified an existing, population dynamics-based sediment flocculation model to develop OPAMOD, a module that accounts for the formation of OPAs. A zero-dimensional model using OPAMOD is shown to be capable of reproducing the size distribution of aggregates from existing laboratory experimental results. Also using the zero-dimensional model, sensitivity tests were performed on two model parameters, the fractal dimension and collision efficiency. Results showed that fractal dimension played a role in the OPA size distribution by influencing the effective particle density, which modified the number concentration of flocs for a given mass concentration. However, the modeled particle characteristics and oil sequestration were relatively insensitive to collision efficiency. To explore OPA formation for an outer continental shelf site, two simulations were conducted using a one-dimensional (vertical) implementation of the model. One scenario had high sediment concentration near the seabed to mimic storm-induced resuspension. The other scenario represented river plume sediment delivery by having high sediment concentration in surface waters. Results showed that OPA formation was sensitive to the vertical distribution of suspended sediment, with the river plume scenario creating more OPA, and sequestering more oil within OPA than the storm resuspension scenario. OPAMOD was developed within the Coupled Ocean-Atmosphere-Wave-and-Sediment Transport (COAWST) modeling system, therefore the methods and parameterizations from this study are transferrable to a three-dimensional coupled oil-sediment-microbial model developed by CSOMIO within the COAWST framework

Comprehensive evaluation system for vegetation ecological quality: a case study of Sichuan ecological protection redline areas

Dynamic monitoring and evaluation of vegetation ecological quality (VEQ) is indispensable for ecological environment management and sustainable development. Single-indicator methods that have been widely used may cause biased results due to neglect of the variety of vegetation ecological elements. We developed the vegetation ecological quality index (VEQI) by coupling vegetation structure (vegetation cover) and function (carbon sequestration, water conservation, soil retention, and biodiversity maintenance) indicators. The changing characteristics of VEQ and the relative contribution of driving factors in the ecological protection redline areas in Sichuan Province (EPRA), China, from 2000 to 2021 were explored using VEQI, Sen’s slope, Mann-Kendall test, Hurst index, and residual analysis based on the XGBoost (Extreme gradient boosting regressor). The results showed that the VEQ in the EPRA has improved over the 22-year study period, but this trend may be unsustainable in the future. Temperature was the most influential climate factor. And human activities were the dominant factor with a relative contribution of 78.57% to VEQ changes. This study provides ideas for assessing ecological restoration in other regions, and can provide guidance for ecosystem management and conservation

Effects of ovarian stimulation protocols on outcomes of assisted reproductive technology in adenomyosis women: a retrospective cohort study

ObjectiveTo evaluate the effects of different ovarian stimulation protocols on in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) outcomes in infertile women with adenomyosis.MethodsWe carried out a retrospective cohort study among infertile women with adenomyosis receiving IVF/ICSI treatment, including 257 fresh embryo transfer (ET) cycles and 305 frozen embryo transfer (FET) cycles. In fresh ET cycles, ultra-long, long, short, and antagonist protocols were adopted. In FET cycles, patients received long-acting GnRH agonist (GnRHa) pretreatment or not. The primary outcome was clinical pregnancy rate (CPR), and the secondary outcomes included implantation rate (IR), miscarriage rate (MR), and live birth rate (LBR).ResultsIn fresh ET cycles, compared with ultra-long and long protocols, IR (49.7%, 52.1% versus 28.2%, P=0.001) and CPR (64.3%, 57.4% versus 35.6%, P=0.004) significantly decreased in the short protocol. Similarly, compared with ultra-long and long protocols, a decreased inclination of IR (49.7%, 52.1% versus 33.3%) and CPR (57.4%, 64.3% versus 38.2%) existed in the antagonist protocol, although no statistical significance was detected because of strict P adjustment of Bonferroni method (Padj=0.008). Compared with long protocol, LBR in short protocol decreased obviously (48.2% versus 20.3%, P<0.001). In FET cycles, no matter which origin of embryos, there were no statistical differences in IR, CPR, and LBR. For women ≥35 years receiving fresh ET, CPR was higher in ultra-long and long protocols (52.1%, 50.0% versus 20.0%, 27.5%, P=0.031) compared to antagonist and short protocols. For women ≥35 years receiving FET, compared with ultra-long and antagonist protocols, cycles with embryos originating from long and short protocols had higher proportions of long-acting GnRHa pretreatment (30.4%,30.00 versus 63.9%, 51.4%, P=0.009). IR (61.1%, 48.6% versus 32.6%, 25.0%, P=0.020) and CPR (58.3%, 48.6% versus 30.4%, 25.0%, P=0.024) in long and short protocols were higher than rates of ultra-long and antagonist protocols, but no statistical differences were supported because of strict Bonferroni method (Padj=0.008).ConclusionIn infertile women with adenomyosis, if a fresh embryo was planned for transfer, an ultra-long or long protocol might be beneficial. If antagonist and short protocols were used, whole embryos frozen followed by FET was recommended. In FET cycles, embryos derived from different protocols had no impact on pregnancy outcomes

Effects of duration of long-acting GnRH agonist downregulation on assisted reproductive technology outcomes in patients with adenomyosis: a retrospective cohort study

ObjectivesTo elucidate the relationship between long-acting GnRH agonist (GnRHa) downregulation and assisted reproductive technology (ART) outcomes and identify the optimal duration of downregulation in patients with adenomyosis.DesignRetrospective cohort study.ParticipantsThe study was designed to evaluate ART outcomes in adenomyosis patients with and without GnRHa downregulation between January 2016 and December 2020. A total of 374 patients with adenomyosis (621 cycles) were included with 281 cycles in downregulation group versus 340 cycles in non-downregulation group. After 1:1 propensity score matching (PSM), a sample size of 272 cycles in each group was matched. The matched downregulation group was further divided into 1-month (147 cycles), 2-months (72 cycles), and ≥3 months downregulation (53 cycles) subgroups. Stratification analysis was conducted on pregnancy outcomes in 239 fresh embryo transfer (ET) cycles and 305 frozen embryo transfer (FET) cycles.ResultsThe downregulation group had larger mean diameter of initial uterus and higher proportion of severer dysmenorrhea compared to non-downregulation group. The pregnancy-related parameters in GnRHa downregulation group were similar to those in non-downregulation group, except for higher late miscarriage rate (MR) (13.4% vs. 3.1%, P = 0.003). The subgroup comparisons in fresh ET cycles indicated that implantation rate (75.0% vs. 39.2%, P = 0.002), biochemical pregnancy rate (91.7% vs. 56.0%, P = 0.036) and clinical pregnancy rate (83.3% vs. 47.0%, P = 0.016) could be improved by prolonged GnRHa downregulation (≥3 months), whereas late MR was difficult to be reversed (30.0% vs. 3.2%, P = 0.017). In FET cycles, higher MR (53.6% vs. 29.9%, P = 0.029; 58.8% vs. 29.9%, P = 0.026) and lower live birth rate (18.8% vs. 34.1%, P = 0.023; 17.1% vs. 34.1%, P = 0.037) were observed in the 1-month and ≥3 months downregulation group, while no differences were found in the 2-months downregulation group compared to the non-downregulation group.ConclusionIn patients with severer adenomyosis, long-acting GnRHa downregulation might be correlated with improved ART outcomes. In fresh ET cycles, prolonged downregulation (≥3 months) might be beneficial to improve live birth rate, which needed to be verified by further study with larger sample. In FET cycles, the optimal duration of downregulation was not certain and still needed further exploration

Dial-insight: Fine-tuning Large Language Models with High-Quality Domain-Specific Data Preventing Capability Collapse

The efficacy of large language models (LLMs) is heavily dependent on the quality of the underlying data, particularly within specialized domains. A common challenge when fine-tuning LLMs for domain-specific applications is the potential degradation of the model's generalization capabilities. To address these issues, we propose a two-stage approach for the construction of production prompts designed to yield high-quality data. This method involves the generation of a diverse array of prompts that encompass a broad spectrum of tasks and exhibit a rich variety of expressions. Furthermore, we introduce a cost-effective, multi-dimensional quality assessment framework to ensure the integrity of the generated labeling data. Utilizing a dataset comprised of service provider and customer interactions from the real estate sector, we demonstrate a positive correlation between data quality and model performance. Notably, our findings indicate that the domain-specific proficiency of general LLMs can be enhanced through fine-tuning with data produced via our proposed method, without compromising their overall generalization abilities, even when exclusively domain-specific data is employed for fine-tuning