APS logDaemon and client library

This document serves as a User`s Manual and Reference for the logDaemon and client library. This package provides a general distributed message logging system. A logDaemon may be started anywhere on a subnet. A client which has linked in the client library is provided functions to open a connection to the logDaemon, log messages, and close the connection. The logDaemon maintains one or more log files (in simple ASCII or SDDS format) and an e-mail list based on specifications in a configuration file. Incoming messages are logged to the appropriate file and/or result in e-mail being sent

Social Support Protected Mental Health during the COVID-19 Pandemic

Social support can protect mental health from the stressors of life during times of widespread crisis, like the COVID-19 pandemic. Using nationally representative data on U.S. working-age adults (18-64), this brief shows that those who reported having emotional support from family and friends were less likely to report negative mental health effects from the COVID-19 pandemic (32.9%) compared to those without emotional support (50.2%). Adults with higher levels of instrumental support – being able to count on someone for a $200 loan or for a place to live - were also less likely than those without those types of support to report negative mental health impacts during the pandemic. Public health approaches that focus on strengthening existing social networks within local communities may be especially helpful during population-level crises

Monitoring commercial conventional facilities control with the APS control system: The Metasys-to-EPICS interface

As controls needs at the Advanced Photon Source matured from an installation phase to an operational phase, the need to monitor the existing conventional facilities control system with the EPICS-based accelerator control system was realized. This existing conventional facilities control network is based on a proprietary system from Johnson Controls called Metasys. Initially read-only monitoring of the Metasys parameters will be provided; however, the ability for possible future expansion to full control is available. This paper describes a method of using commercially available hardware and existing EPICS software as a bridge between the Metasys and EPICS control systems

Business models in servitization

This chapter sheds light on the different business models of manufacturing companies that have servitized their business operations. This chapter presents four distinctive yet simultaneously pursued business models for servitized manufacturers: (1) the product business model, (2) the service-agreement business model (3) the process-oriented business model, and (4) the performance-oriented business model. Depending on the direction taken, dedicated customer needs targeted, value propositions adopted, and services and solutions provided, a servitized manufacturer should decide which business model(s) the firm will adopt with different customers.fi=vertaisarvioitu|en=peerReviewed

Do practicing clinicians agree with expert ratings of neonatal intensive care unit quality measures?

To assess the level of agreement when selecting quality measures for inclusion in a composite index of neonatal intensive care quality (Baby-MONITOR) between two panels: one comprised of academic researchers (Delphi) and another comprised of academic and clinical neonatologists (Clinician)

Research on China’s Fiscal Policy in the Promotion of Technological Innovation

创新日益成为一个国家、民族兴旺发达的决定性因素，科技进步和技术创新不仅成为时代的主旋律，而且也变成了学术界、产业界、科技界以及中央和地方各级政府讨论经济发展问题的主流话语。企业是技术创新的主体和技术创新体系的中心，因此，促进企业技术创新不仅有利于企业提高其经济效益和增强其市场竞争力，而且有利于促进一国的经济增长。 财税政策作为一种重要的政府政策工具，应在促进企业技术创新过程中发挥重要作用。虽然我国政府制定了多项财政支持政策和一系列的税收优惠政策，从多个方位和不同层面来提高企业技术创新能力、促进和引导技术创新，并取得了一定的成效。然而，目前我国促进企业技术创新的财税政策仍然存在一定的问题，其根...Innovation is increasingly becoming a decisive factor in national prosperity, technological progress and technical innovation has not only become the main theme of the times, but also become the mainstream discourse of the academia, industry, technology and the central or local governments discussing economic development issues. Enterprises is the technological innovation main force and the center...学位：经济学硕士院系专业：经济学院财政系_财政学(含税收学)学号：X200633000

Muscle Invasive Bladder Cancer: From Diagnosis to Survivorship

Bladder cancer is the fifth most commonly diagnosed cancer and the most expensive adult cancer in average healthcare costs incurred per patient in the USA. However, little is known about factors influencing patients' treatment decisions, quality of life, and responses to treatment impairments. The main focus of this paper is to better understand the impact of muscle invasive bladder cancer on patient quality of life and its added implications for primary caregivers and healthcare providers. In this paper, we discuss treatment options, side effects, and challenges that patients and family caregivers face in different phases along the disease trajectory and further identify crucial areas of needed research

The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC) is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. We will discuss the use of recurrent (LSTM) and convolutional neural networks to find and fit tracks in toy detector data