Functional upgrading in China’s export processing sector

Functional upgrading occurs when a firm acquires more sophisticated functions within an existing value chain. In this paper, we analyze if there is evidence of this type of upgrading in China’s export processing regime by investigating dynamics in the relative prevalence of Import & Assembly (IA) versus Pure Assembly (PA) processing trade over the period 2000-2013. Firms in both regimes provide similar manufacturing services to foreign companies, but IA firms also conduct the sophisticated tasks of quality control, searching, financing and storing imported materials. Consistent with a trend of functional upgrading, we show that the share of IA trade in total processing trade has increased rapidly during the period 2000-2006, both overall and within product categories. Furthermore, we find that this trend has gone hand in hand with improvements in a sector’s labor productivity and unit values. Against expectations, we find that this process has slowed down notably during the period 2006-2013.status: publishe

A new framework for sign language alphabet hand posture recognition using geometrical features through artificial neural network (part 1)

Hand pose tracking is essential in sign languages. An automatic recognition of performed hand signs facilitates a number of applications, especially for people with speech impairment to communication with normal people. This framework which is called ASLNN proposes a new hand posture recognition technique for the American sign language alphabet based on the neural network which works on the geometrical feature extraction of hands. A user’s hand is captured by a three-dimensional depth-based sensor camera; consequently, the hand is segmented according to the depth analysis features. The proposed system is called depth-based geometrical sign language recognition as named DGSLR. The DGSLR adopted in easier hand segmentation approach, which is further used in segmentation applications. The proposed geometrical feature extraction framework improves the accuracy of recognition due to unchangeable features against hand orientation compared to discrete cosine transform and moment invariant. The findings of the iterations demonstrate the combination of the extracted features resulted to improved accuracy rates. Then, an artificial neural network is used to drive desired outcomes. ASLNN is proficient to hand posture recognition and provides accuracy up to 96.78% which will be discussed on the additional paper of this authors in this journal

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality