Reducing the risk of software cost estimation

Inaccurate cost estimation is a well-known problem in software development. The common cost estimation models are point estimates that are unable to quantify uncertainties. Furthermore, it is difficult to calibrate the uncertainties in cost estimation due to the lack of information. The purpose of this thesis is to prove that probability techniques could be synthesized into COCOMO (Constructive Cost Model) to quantify uncertainties. Another aim is to find out how to get more insight on reducing the risk of cost estimation. In this thesis, some historical data is presented to show the variance in factors of COCOMO. Monte Carlo simulation method is also introduced into COCOMO to quantify the uncertainties. Finally, a “What-if\u27 study is facilitated to find the potential factor changes to affect the result of simulation. The result of the study reveals that process maturity has more influence than productivity on reducing variance of estimation. It indicates that synthesizing Monte Carlo simulation and “What-if\u27 studies into COCOMO could produce insightful information to reduce the risk of software cost estimation

Understanding the Complexity of Inflammatory Bowel Disease from a Multi-Omics Perspective

Inflammatory bowel disease (IBD) has a wide range of risk factors including genetics, environment and gut microbiota. The pathology of the disease still remains unclear. This thesis is mainly based on the studies from 1000IBD cohort of University Medical Center Groningen, describing how genetics regulate gene expressions, protein levels, metabolites, gut microbiota and how these interactions are related to IBD. By using omics data integration approach, I revealed novel biological pathways potentially involved in the disease onset, which could provide new strategies in clinical practice

Finite element modeling of dynamic impact and cornering fatigue of cast aluminum and forged magnesium road wheels.

Numerical investigation of wheel dynamic impact and cornering fatigue performance is essential to shorten design time, enhance mechanical performance, and lower development cost. This dissertation focused on two objectives. First, finite element models of the dynamic impact test on a wheel and tire assembly were developed, which considered the material inhomogeneity of the wheel. The model complexity and resultant additional analysis time led to the development of a simplified approach for wheel impact testing without the tired. Comparison of the numerical predictions with the experimental measurements of wheel impact indicated that an approximate 20% reduction of the initial striker kinetic energy provides an effective method for simplifying the numerical modeling. Second, numerical prediction of wheel cornering fatigue testing was considered. Two numerical prediction methods were applied to simulate wheel cornering fatigue testing. The first method utilizes a static stress analysis with different bending directions applied to the hub. The second approach uses a dynamic stress analysis with the application of a rotating bending moment applied to the hub. The fatigue performance of the wheel was evaluated based upon the results from both the static and dynamic stress analyses. Using a Goodman linear fatigue failure criterion for multiaxial stresses, both the equivalent alternating and mean components of the combined stresses as well as the safety factors of wheel fatigue design were determined. The elements with low factors of fatigue safety were identified either by boundary constraints or by geometric stress concentration. Experimental testing results verified the numerical predictions. A design modification was applied to the forged magnesium wheel to improve its fatigue performance.* *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation).Dept. of Mechanical, Automotive, and Materials Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .S533. Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 4049. Thesis (Ph.D.)--University of Windsor (Canada), 2006

How does climate risk matter for corporate green innovation? Empirical evidence from heavy-polluting listed companies in China

Chinese heavy-polluting companies have been facing enormous challenges in responding to climate risk and energy transformation. This paper uses panel regression model and investigates the impact of climate risk on corporate green innovation in Chinese heavy-polluting listed companies from 2011 to 2020. The empirical results show that climate risk adversely affects green innovation in heavy-polluting companies, and this effect persists throughout a series of robustness and endogeneity tests. Climate risk may affect corporate green innovation through decreasing R&D investment, lowing resource allocation efficiency and increasing company risk. Climate risk has a greater negative impact on mid-western, state-owned and large-size heavy-polluting companies, but can be mitigated by the development of green finance, digital finance and marketization. These findings may help heavy-polluting companies fully utilize existing resources, policies, and channels for green innovation and mitigate climate risks

Cost-effectiveness analysis of serplulimab plus chemotherapy in the first-line treatment for PD-L1-positive esophageal squamous cell carcinoma in China

ObjectiveThe ASTRUM-007 trial (NCT03958890) demonstrated that serplulimab plus chemotherapy administered every 2-week significantly improved progression-free and overall survival in patients with previously untreated, programmed death-ligand 1 (PD-L1) positive advanced esophageal squamous-cell carcinoma (ESCC). This study was aimed to investigate the cost-effectiveness of serplulimab plus chemotherapy in the first-line treatment of PD-L1-positive advanced ESCC.MethodsA partitioned survival model with a 2-week cycle and a 10-year time horizon was constructed from the Chinese healthcare system perspective. The survival data, direct medical costs and utilities were derived from the ASTRUM-007 trial, YAOZHI database and published sources. Total costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) were calculated. Scenario, one-way and probabilistic sensitivity analyses were performed to assess the uncertainty around model parameters.ResultsCompared with chemotherapy, serplulimab plus chemotherapy provided additional 0.27 QALYs with an incremental cost of $33,460.86, which had an ICER of$124,483.07 per QALY. The subgroup analyses revealed that the ICERs of serplulimab plus chemotherapy were $134,637.42 and$105,589.71 in advanced ESCC patients with 1 ≤ CPS < 10 and CPS ≥ 10, respectively. The price of serplulimab, patient weight, utility values and discount rate were the most influential parameters on base-case results. At a willingness-to-pay threshold of three times per capita GDP ($40,587.59) in 2022, the probability of serplulimab plus chemotherapy being cost-effective was 0% compared with chemotherapy. When the price of serplulimab decreased by 70%, the probabilities of serplulimab plus chemotherapy being cost-effective were 81.42%, 67.74% and 96.75% in advanced ESCC patients with PD-L1-positive, PD-L1 1≤CPS<10 and CPS≥10, respectively.ConclusionSerplulimab plus chemotherapy in the first-line treatment for PD-L1-positive advanced ESCC might not be cost-effective in China