Explore the vast range of titles available.

BackgroundThere is currently no consensus on the impact of class imbalance methods on the performance of clinical prediction models. We aimed to empirically investigate the impact of random oversampling and random undersampling, two commonly used class imbalance methods, on the internal and external validation performance of prediction models developed using observational health data.MethodsWe developed and externally validated prediction models for various outcomes of interest within a target population of people with pharmaceutically treated depression across four large observational health databases. We used three different classifiers (lasso logistic regression, random forest, XGBoost) and varied the target imbalance ratio. We evaluated the impact on model performance in terms of discrimination and calibration. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC) and calibration was assessed using calibration plots.ResultsWe developed and externally validated a total of 1,566 prediction models. On internal and external validation, random oversampling and random undersampling generally did not result in higher AUROCs. Moreover, we found overestimated risks, although this miscalibration could largely be corrected by recalibrating the models towards the imbalance ratios in the original dataset.ConclusionsOverall, we found that random oversampling or random undersampling generally does not improve the internal and external validation performance of prediction models developed in large observational health databases. Based on our findings, we do not recommend applying random oversampling or random undersampling when developing prediction models in large observational health databases.

The COVID-19 pandemic may have exacerbated mental health conditions by introducing and/or modifying stressors, particularly in university populations. We examined longitudinal patterns, time-varying predictors, and contemporaneous correlates of moderate-severe psychological distress (MS-PD) among college students. During 2020–2021, participants completed self-administered questionnaires quarterly (T1 = 562, T2 = 334, T3 = 221, and T4 = 169). MS-PD reflected Kessler-6 scores ≥ 8. At T1 (baseline), most participants were cisgender women [96% vs. 4% transgender/gender non-conforming (TGNC)]. MS-PD prevalence was over 50% at all timepoints. MS-PD predictors included low self-rated health and perceptions of local pandemic control, verbal/physical violence experience, food insecurity, cohabitation dynamics, geographic location, and loneliness. Unique MS-PD correlates encompassed drug use and TGNC identity. Trajectories comprised Persistently (40%), Highly (24% MS-PD twice/thrice), Minimally (15% MS-PD once), and Never (21%) Distressed. Persistently Distressed students had low social support and self-rated health; high food insecurity, drug use, physical/verbal violence experience, need-based financial aid, and TGNC representation; and fluctuating self-rated health amid increasing COVID-19 symptomatology. In this sample, MS-PD prevalence was high, persistent, and associated with financial, behavioral, structural, experiential, and intra- and inter-personal factors. Given its complexity, improving and preserving college students’ mental health necessitates comprehensive, multi-component activities to change adjustable stressors while attenuating the adverse effects of immutable influences.

It is well known that the racial composition of a neighborhood influences who chooses to live there. Less established is whether the political party mix of the neighborhood influences neighborhood choice. In this paper, we study racial and political neighborhood sorting, their interaction, and how they are changing over time. Our methodology involves the estimation of a conditional logit model with data on hundreds of thousands of homebuyers whose race and political affiliation are known. The neighborhood choices of homeowners categorized by race and party are explained by a typology that defines neighborhoods by their dominance of a particular party and race/ethnicity. We find that both Democrats and Republicans prefer living in a neighborhood that matches their race and political party, but both show an increased willingness to live in a non-matched neighborhood over the past decade. Our results are encouraging, suggesting that both political and racial/ethnicity neighborhood segregation may subside in the future.

The complete removal of cancerous tissue is a central aim of surgical oncology, but is difficult to achieve in certain cases, especially when the removal of surrounding normal tissues must be minimized. Therefore, when post-operative pathology identifies residual tumor at the surgical margins, re-excision surgeries are often necessary. An intraoperative approach for tumor-margin assessment, insensitive to nonspecific sources of molecular probe accumulation and contrast, is presented employing kinetic-modeling analysis of dual-probe staining using surface-enhanced Raman scattering nanoparticles (SERS NPs). Human glioma (U251) and epidermoid (A431) tumors were implanted subcutaneously in six athymic mice. Fresh resected tissues were stained with an equimolar mixture of epidermal growth factor receptor (EGFR)-targeted and untargeted SERS NPs. The binding potential (BP; proportional to receptor concentration) of EGFR – a cell-surface receptor associated with cancer – was estimated from kinetic modeling of targeted and untargeted NP concentrations in response to serial rinsing. EGFR BPs in healthy, U251 and A431 tissues were 0.06 ± 0.14, 1.13 ± 0.40 and 2.23 ± 0.86, respectively, which agree with flow-cytometry measurements and published reports. The ability of this approach to quantify the BP of cell-surface biomarkers in fresh tissues opens up an accurate new approach to analyze tumor margins intraoperatively.

Shipment value of the Taiwanese semiconductor industry reached US$35.503 billion in the third quarter of 2021, up by 10.3% sequentially and 33.0% year on year. The industry’s shipment value is estimated to have reached US$130.8 billion in 2021, up 31.8% year-on-year. This report discusses the key issues in major subsectors of the Taiwanese semiconductor industry including IC design, manufacturing, and packaging and testing, also known as OSAT (Outsourced Semiconductor Assembly and Test); looks into the industry’s development in the third quarter of 2021 to forecast its development in the fourth quarter of 2021 and onwards.

Shipment value of the Taiwanese semiconductor industry reached US$27.688 billion in the fourth quarter of 2020, up 3.7% sequentially and 26.2% year on year. This report looks into key developments and issues in three major subsectors of the Taiwanese semiconductor industry, including IC design, semiconductor manufacturing, and packaging and testing, also known as OSAT (Outsourced Semiconductor Assembly and Test), in the fourth quarter of 2020 and the first quarter of 2021; examines thestrategies of major players in each subsector and their development trends.

Chip demand has continued in high gear since the fourth quarter of 2020 due to upwind in the stay-at-home trend amid the COVID-19 outbreak. Shipment value of the Taiwanese fabless IC industry in the second quarter of 2021 registered 19.7% sequential and 79.5% year-on-year growth, arriving at US10.1 billion. Following the rapid increase in demand for chips in the first half of 2021, shipment value of the industry is anticipated to have reached US$10.7 billion in the third quarter of 2021, up 5.7% sequential and 45.3% year-on-year growth.

South Korea’s Magnachip Semiconductor announced on March 29 that it would accept the acquisition proposal of Wise Road Capital, a Chinese private investment fund. The all-cash transaction has an equity value of approximately US$1.4 billion. Although the Committee on Foreign Investment in the United States (CFIUS) issued an interim order on June 15 blocking the deal, this deal has been put on hold. But, if the deal goes as planned, Magnachip shareholders will receive US$29.00 in cash for each share of Magnachip's common stock they currently hold, while Wise Road will acquire Magnachip’s OLED (Organic Light-Emitting Diode) display driver IC design business and 8-inch wafer facility (Fab 3) located in Gumi. This report analyzes the implications and significance of the acquisition and then discusses China’s strategy to develop a display driver IC supply chain through this acquisition.

The report finds that the demand for fabless ICs continued in high gear in the fourth quarter of 2020 owing to the stay-at-home economy that has driven notebook PC shipments amid the COVID-19 outbreak worldwide. Thus, shipment value of the Taiwanese fabless IC industry in the fourth quarter of 2020 registered over 42.7% year-on-year growth, arriving at US$7.7 billion. Since the demand for chips will continue into the first half of 2021, shipment value of the industry is anticipated to have reached US$7.9 billion in the first quarter of 2021, registering over 55% growth compared to the same period last year.