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System-architecture design optimization of flow-based microfluidic biochips has been extensively investigated over the past decade. Most of the prior work, however, is still based on chip architectures with dedicated storage units and this, not only limits the performance of biochips, but also increases their fabrication cost. To overcome this limitation, a distributed channel-storage architecture can be implemented, where fluid samples can be cached temporarily in flow channels instead of using a dedicated storage. This new concept of fluid storage, however, requires a careful arrangement of fluid samples to enable the channels to fulfill their dual functions. Moreover, to avoid cross-contamination between fluidic flows, wash operations are necessary to remove the residue left in flow channels. In this paper, we formulate the first system level design and wash optimization problem for microfluidic biochips with distributed channel storage, considering high-level synthesis, physical design, and wash optimization simultaneously. Given the protocol of a biochemical application and the corresponding design requirements, our goal is to generate a chip architecture with minimized cost. Meanwhile the bioassay can be executed efficiently with an optimized wash scheme. Experimental results confirm that our approach leads to short completion time of bioassays, low chip cost, and high wash efficiency.

Continuous-flow microfluidic biochips (CFMBs), also known as lab-on-a-chip platforms, have attracted considerable attentions in the past two decades and have been widely used in various laboratory procedures in biomedicine and biochemistry such as point-of-care diagnosis and protein crystallization. Besides a completely automatic execution procedure, these micrometerscale devices offer several advantages over the conventional fluidic platforms, e.g., low sample/reagent consumption, low manufacturing cost, and high execution efficiency. However, similar to the early development of integrated circuits, as the feature size of biochips keeps shrinking, tens of thousands microvalves can now be integrated into a single chip. Consequently, traditional manual-based chip design is no longer suitable and Computer-aided Design (CAD) tools have to be introduced to deal with the large-scale integration of such chips. This paper presents a comprehensive review of recent advances in the design automation of CFMBs, including CAD techniques for architecture synthesis, volume assignment and sample preparation, testing, fault-tolerant design, and washing. These tools have great significance in advancing the automation level of biochip design and further promote their wide adoption. Finally, future trends and potential research topics are discussed in detail to further improve the performance of CFMBs.

In the zinc roasting process, the stability of the roasting temperature directly affects the product quality. However, the stabilizing control of the temperature inside a large-scale zinc roaster encounters complex process characteristics, fluctuating working conditions and delayed detection of product quality. The complex concentrate supply gives rise to fluctuations of zinc concentrate composition, which in turn affects the reaction atmosphere and working conditions. The trend of the roasting temperature, which contains abundant information on the potential change of working conditions, is underused in traditional controllers, leading to difficulties in stabilizing control of large-scale zinc roasters. In this work, a trend-based event-triggering fuzzy control strategy, incorporating qualitative trend analysis and an event-triggering mechanism in fuzzy control design, is proposed for the temperature stabilizing control of a large-scale zinc roaster. Qualitative trend analysis is adopted to extract the trend information of the roasting temperature. An embedded event-triggering mechanism can handle the underlying transition of working conditions timely. Hence, the fuzzy controller increases the utilization rate of the information contained in the temperature measurements. Experiments are conducted to evaluate the feasibility and advantages of the proposed fuzzy controller.

The pandemic has changed the way people work, and more and more people are choosing to work from home (WFH). Unlike traditional work patterns, this approach has limitations and has had a significant impact on both organizations and individuals. It also brings many challenges to the work of HR practitioners. HR practitioners, as key players in strategic human resource management, need to take advantage of management innovations under the crisis to improve employees’ work flexibility and effectively address the impact of working from home. This study aims to address the need for employee skill improvement, psychological stress relief, work-family balance, and company culture reinforcement from an HRM perspective because of the impact of WFH work patterns during the COVID-19 crisis.

Background Coronavirus disease 2019 (COVID-19) has quickly spread throughout the country and the world since first broke out in Wuhan, China. The outbreak that started from January 22, 2020, in Fujian Province has been controlled as the number of indigenous cases has not increased since March. We aimed to describe the clinical characteristics of patients with COVID-19 in Fujian Province, China. Methods In this retrospective, multicenter study, we collected and analyzed the epidemiological, clinical, and laboratory data of all cases confirmed by nucleic acid tests in five designated hospitals in Fujian Province between January 22 and February 27, 2020. All patients were followed up until discharge. COVID-19 severity was classified as mild, moderate, severe, or critical. Results Of 199 discharged patients with COVID-19, 105 patients were male, with a median age of 46.3 years, and 17 patients were severe, and 5 patients were critical on admission. Hypertension and diabetes were the most common comorbidities. The symptoms at illness onset were mainly fever (76.4%), cough (60.8%), and myalgia or fatigue (27.6%). A total of 96.5% of patients had abnormal imaging findings on chest computed tomography. Lymphopenia (37.2%) and hypoxemia (13.6%) were observed. Acute respiratory distress syndrome and respiratory failure occurred in 9 patients (4.5%) and 8 patients (4.0%) respectively. One patient died and the others were cured and discharged with the median hospital stay of 19 days. Old age was negatively correlated with lymphocyte count (r = - 0.296, p < 0.001) and oxygenation index (r = - 0.263, p = 0.001). Bivariate regression analysis revealed that old age (≥ 75 years), hypertension, diabetes, and lymphopenia were correlated with the severity of COVID-19. Conclusions Patients in Fujian Province were mostly nonsevere cases with mild or moderate symptoms, and had a lower mortality than patients in Wuhan (4.3%-15%). Older age, hypertension, diabetes, and lymphopenia were risk factors for severity of COVID-19.

Background The coronavirus disease 2019 (COVID-19) has spread worldwide, leading to thousands of deaths. We aim to describe the epidemiological and clinical characteristics of patients with coronavirus disease 2019 (COVID-19) in Fujian province, China. Methods In this retrospective, multi-center study, we collected and analysed 165 patients of COVID-19 confirmed by real time PCR of nasopharyngeal swab specimens in five tertiary hospitals of Fujian province, China from Jan 22 to Feb 16, 2020. The final date of follow-up was February 21, 2020. Results Of the 165 hospitalized patients with COVID-19, 101 patients had relation with Wuhan within two weeks. Symptoms at illness onset mainly were fever (76.4%), cough (60%) and expectoration (38.2%). On admission, the severity of most patients were classified as mild or common and lymphopenia (33.9%), hypoxemia (15.2%), elevated and bilateral pneumonia (83.6%) was observed. Patients older than 65 years had significantly high frequency of hypertension, diabetes, severe classification, lymphopenia and hypoxemia than those younger than 65 years. Age correlated negatively with lymphocyte count and oxygenation index on admission while positively with duration from exposure to the time of negative RT-PCR. At the end of follow-up, 80 patients were discharged and one died. The median hospital stay was 17 days. Conclusions Patients with COVID-19 were mostly non-severe cases in Fujian province and older patients (>65 years) were more likely to have lymphopenia and hypoxemia, and to progress as severe cases of COVID-19 than those younger than 65.

Background: The severe acute respiratory coronavirus 2 (SARS-CoV-2) responsible for coronavirus disease 2019 (COVID-19) had infected more than 80000 Chinese sin

Intrahepatic cholangiocarcinoma (ICC) is an aggressive malignancy associated with unfavorable prognosis and for which no effective treatments are available. Its molecular pathogenesis is poorly understood. Genome-wide sequencing and high-throughput technologies have provided critical insights into the molecular basis of ICC while sparking a heated debate on the cellular origin. Cancer exhibits variabilities in origin, progression and cell biology. Recent evidence suggests that ICC has multiple cellular origins, including differentiated hepatocytes; intrahepatic biliary epithelial cells (IBECs)/cholangiocytes; pluripotent stem cells, such as hepatic stem/progenitor cells (HPCs) and biliary tree stem/progenitor cells (BTSCs); and peribiliary gland (PBG). However, both somatic mutagenesis and epigenomic features are highly cell type-specific. Multiple cellular origins may have profoundly different genomic landscapes and key signaling pathways, driving phenotypic variation and thereby posing significant challenges to personalized medicine in terms of achieving the optimal drug response and patient outcome. Considering this information, we have summarized the latest experimental evidence and relevant literature to provide an up-to-date view of the cellular origin of ICC, which will contribute to establishment of a hierarchical model of carcinogenesis and allow for improvement of the anatomical-based classification of ICC. These new insights have important implications for both the diagnosis and treatment of ICC patients.

The relationship between growth rates of algae and structure parameters of closed flat-panel photobioreactors was investigated. Ad/Ar (cross-section area of the downcomer/cross-section area of the riser), h0 (clearance from the upper edge of the baffles to the water level), and h1 (clearance from the lower edge of the baffles to the bottom of the reactor) were selected as the inner structure parameters. CFD (Computational Fluid Dynamics) was used to simulate the hydrodynamic parameter (TKE)d (turbulence kinetic energy of the downcomers) and the secondary parameters e (ratio between td and tc), tc (cycle time), and DZ (dead zones), which were deduced from the hydrodynamic parameters mentioned above. The effects of (TKE)d, e, tc, DZ, and the inner structure parameters on cell growth of Isochrysis galbana 3011 were analyzed using data collected in 15-L airlift flat-panel photobioreactors. A model was developed to predict algae cell growth based on these inner structure parameters, thereby providing a new method for photobioreactor optimization. Validity of the model was confirmed by experimental data of I. galbana 3011 cultured in 15-L and 300-L photobioreactors, respectively. Finally, the prospect of applying CFD to photobioreactor optimization was discussed.

Heterogeneity of Stem Cells in Human Amniotic Fluid Amniotic fluid contains a mixture of cells with capacity to differentiate into all germ layers. These cells are present in large numbers in midtrimester samples obtained for cytogenetic diagnosis, and have been identified by stem cell surface markers and transcription factors. We studied cultured samples from patients who had both direct cultures and matched cultures obtained 2 weeks later from the cytogenetics laboratory as well as patients with cytogenetics material only. Samples were cryogenically frozen, thawed, expanded in culture with excellent viability. There was considerable individual variation unrelated to gestational age or telomere length. Phenotype for embryonic markers was assessed by flow cytometry and by quantitative polymerase chain reaction. The most consistently present stem cell markers in substantial amounts were CD90, SSEA-4, & TRA-1-60. Cells with CD90, SSEA-4 & TRA-1-60 double and triple labeled also could be identified and subcultured, confirming the heterogeneity of the amniotic fluid stem cell population.

High pressure dissolving (HPD) is a very important process for alumina production. During HPD process, alumina caustic ratio (ACR) of the dissolved slurry is a very important economic technical indicator. In practice, there are many factors influencing ACR and there are different noise levels for different HPD conditions. So, it is very difficult to predict ACR with single model accurately. In this paper, an improved rival penalized competitive learning clustering algorithm is used to cluster the learning samples. Then a distributed support vector machine based soft sensor is proposed to predict ACR on-line. The simulation and practical application results showed its effectiveness.

An opposition-mutation-based particle swarm optimization algorithm is presented (OMPSO) in this paper. The proposed OMPSO employs opposition-based learning algorithms, which can accelerate the learning and searching process in soft computing. The mutation threshold of OMPSO is adapted to the evolution information of the gbest, which is very useful to keep the global search ability and fast convergence of the optimization algorithm. The OMPSO has the same tuning parameters as standard particle swarm optimization algorithm (PSO) and is easily implemented in practice. At last, OMPSO is applied to several benchmark problems. Simulation results show that proposed algorithm can find global optima effectively and quickly.