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As the legislative pressure to reduce energy consumption is increasing, data analysis of power consumption is critical in the production planning of manufacturing facilities. In legacy studies, a machine conducting a single continuous operation has been mainly observed for power estimation. However, the production machine of a modularized line, which conducts complex discrete operations, is more like the actual factory system than an identical simple machine. During the information collection of this kind of production line, it is important to interpret mixed signals from multiple machines to ensure that there is no reduction in the information quality due to noise and signal fusion and discrete events. A data pipeline—from data collection (from different sources) to preprocessing, data conversion, synchronization, and deep learning classification—to estimate the total power use of the future process plan, is proposed herein. The pipeline also establishes an auto-labeled data set of individual operations that contributes to building an power estimation model without manual data preprocessing. The proposed system is applied to a modular factory, connected with machine controllers, using standardized protocols individually and linked to a centralized power monitoring system. Specifically, a robot arm cell was investigated to evaluate the pipeline, with the result of the power profile being synchronized with the robot program.

Mutations affecting spliceosomal proteins are the most common mutations in patients with myelodysplastic syndromes (MDS), but their role in MDS pathogenesis has not been delineated. Here we report that mutations affecting the splicing factor SRSF2 directly impair hematopoietic differentiation in vivo, which is not due to SRSF2 loss of function. By contrast, SRSF2 mutations alter SRSF2's normal sequence-specific RNA binding activity, thereby altering the recognition of specific exonic splicing enhancer motifs to drive recurrent mis-splicing of key hematopoietic regulators. This includes SRSF2 mutation-dependent splicing of EZH2, which triggers nonsense-mediated decay, which, in turn, results in impaired hematopoietic differentiation. These data provide a mechanistic link between a mutant spliceosomal protein, alterations in the splicing of key regulators, and impaired hematopoiesis. ; E.K. is supported by the Worldwide Cancer Research Fund. A.R. was supported by the NIH/NHLBI (U01 HL099993), NIH/NIDDK (K08 DK082783), the J.P. McCarthy Foundation, and the Storb Foundation. S.H. and O.A.-W. are supported by grants from the Edward P. Evans Foundation. S.H. was supported by Yale Comprehensive Cancer Center institutional funds. R.K.B. was supported by the Hartwell Innovation Fund, Damon Runyon Cancer Research Foundation (DFS 04-12), Ellison Medical Foundation (AG-NS-1030-13), NIH/NIDDK (R56 DK103854), NIH/NCI recruitment support (P30 CA015704), and Fred Hutchinson Cancer Research Center institutional funds. J.O.I. was supported by an NIH/NCI training grant (T32 CA009657) and NIH/NIDDK pilot study (P30 DK056465). C.L. is supported by a career development award grant from the Leukemia and Lymphoma Society and an ATIP-Avenir grant from the French government. O.A.-W. is supported by an NIH K08 clinical investigator award (1K08CA160647-01), a Department of Defense Postdoctoral Fellow Award in Bone Marrow Failure Research (W81XWH-12-1-0041), the Josie Robertson Investigator Program, and a Damon Runyon Clinical Investigator Award with support from the Evans Foundation. F.H.-T.A. acknowledges support from the NCCR RNA and Disease funded by the Swiss National Science Foundation and the SNF Sinergia CRSII3_127454. Y.L. and Y.M. were supported by NIH/NIGMS grant R01 GM102869 and Senior Research Fellowship Grant 101908/Z/13/Z (to Y.M.) from the Wellcome Trust. J.D. acknowledges assistance from Dr. Nezih Cereb, HistoGenetics (Ossining, NY). ; This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.ccell.2015.04.006

Declines in health service use during the Coronavirus Disease 2019 (COVID-19) pandemic could have important effects on population health. In this study, we used an interrupted time series design to assess the immediate effect of the pandemic on 31 health services in two low-income (Ethiopia and Haiti), six middle-income (Ghana, Lao People's Democratic Republic, Mexico, Nepal, South Africa and Thailand) and high-income (Chile and South Korea) countries. Despite efforts to maintain health services, disruptions of varying magnitude and duration were found in every country, with no clear patterns by country income group or pandemic intensity. Disruptions in health services often preceded COVID-19 waves. Cancer screenings, TB screening and detection and HIV testing were most affected (26–96% declines). Total outpatient visits declined by 9–40% at national levels and remained lower than predicted by the end of 2020. Maternal health services were disrupted in approximately half of the countries, with declines ranging from 5% to 33%. Child vaccinations were disrupted for shorter periods, but we estimate that catch-up campaigns might not have reached all children missed. By contrast, provision of antiretrovirals for HIV was not affected. By the end of 2020, substantial disruptions remained in half of the countries. Preliminary data for 2021 indicate that disruptions likely persisted. Although a portion of the declines observed might result from decreased needs during lockdowns (from fewer infectious illnesses or injuries), a larger share likely reflects a shortfall of health system resilience. Countries must plan to compensate for missed healthcare during the current pandemic and invest in strategies for better health system resilience for future emergencies.