Contextualizing the Revised Patient Perception of Patient-Centeredness (Pppc-R) Scale in Primary Healthcare Settings: a Validity and Reliability Evaluation Study

BACKGROUND: An English version of the Patient Perception of Patient-Centeredness (PPPC) scale was recently revised, and it is necessary to test this instrument in different primary care populations. AIM: This study aimed to assess the validity and reliability of a Chinese version of the PPPC scale. DESIGN: A mixed method was used in this study. The Delphi method was used to collect qualitative and quantitative data to address the content validity of the PPPC scale by calculating the Content Validity Index, Content Validity Ratio, the adjusted Kappa, and the Item Impact Score. Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) were used to assess the construct validity of the PPPC scale through a cross-sectional survey. The internal consistency was also assessed. SETTING/PARTICIPANTS: In the Delphi consultation, seven experts were consulted through a questionnaire sent by email. The cross-sectional survey interviewed 188 outpatients in Guangzhou city and 108 outpatients in Hohhot City from community health service centers or stations face-to-face. RESULTS: The 21 items in the scale were relevant to their component. The Item-level Content Validity Index for each item was higher than 0.79, and the average Scale-level content validity index was 0.97 in each evaluation round. The initial proposed 4-factor CFA model did not fit adequately. Still, we found a 3-factor solution based on our EFA model and the validation via the CFA model (model fit: [Formula: see text], P \u3c 0.001, RMSEA = 0.044, CFI = 0.981; factor loadings: 0.553 to 0.888). Cronbach\u27s α also indicated good internal consistency reliability: The overall Cronbach\u27s α was 0.922, and the Cronbach\u27s α for each factor was 0.851, 0.872, and 0.717, respectively. CONCLUSIONS: The Chinese version of the PPPC scale provides a valuable tool for evaluating patient-centered medical service quality

Towards the circular nitrogen economy - a global meta-analysis of composting technologies reveals much potential for mitigating nitrogen losses

Composting is an important technology to treat biowastes and recycle nutrients, but incurs nitrogen (N) losses that lower the value of the final products and cause pollution. Technologies aimed at reducing N losses during composting have inconsistent outcomes. To deepen insight into mitigation options, we conducted a global meta-analysis based on 932 observations from 121 peer-reviewed published studies. Overall, N losses averaged 31.4% total N (TN), 17.2% NH-N, and 1.4% NO-N, with NH-N accounting for 55% of TN losses. The primary drivers affecting N losses were composting method, type of biowaste, and duration of composting. N losses were significantly impacted by the carbon-to-nitrogen (C/N) ratio of the input materials (feedstock of nutrient dense biowastes and C-rich bulking agents), moisture content and pH. Our analysis revealed N-conserving optima with C/N ratios of 25-30, 60-65% moisture content and pH 6.5-7.0. In situ mitigation technologies that control feedstock and processing conditions reduced average N losses by 31.4% (TN), 35.4% (NH-N) and 35.8% (NO-N). Biochar and magnesium-phosphate salts emerged as the most effective N-conserving strategies, curbing losses of TN by 30.2 and 60.6%, NH by 52.6 and 69.4%, and NO by 66.2 and 35.4% respectively. We conclude that existing technologies could preserve ~0.6\ua0Tg of biowaste-N globally, which equates to 16% of the chemical N-fertilizer used in African croplands, or 39% of the annual global increases of 1.58\ua0Tg fertilizer-N. However, the adoption of N-conserving technologies is constrained by a lack of knowledge of best practice, suitable infrastructure, policies and receptive markets. To realize an N-conserving composting industry that supports sustainable practices and the circular nitrogen economy, stakeholders have to act collectively. Benefits will include lowering direct and indirect greenhouse gas emissions associated with agriculture, and facilitating the recarbonization of soils

Cold Climate during Bud Break and Flowering and Excessive Nutrient Inputs Limit Apple Yields in Hebei Province, China

Apples have become a major source of income for smallholder farmers in Bohai Bay. However, the annual productivity of apples in the area is relatively low and the interannual yield gap varies drastically. Identifying the apple yield gap and interannual production constraints can potentially promote the sustainable development of apple production. Based on track monitoring data of 45 smallholder farmers from 2016 to 2018, the yield gap and constraint factors were determined by adopting boundary analysis methodology. The results showed that the yield potential of apples during 2016–2018 was 75, 108, and 87 t ha−1, and actual yields were 36.8, 52.3, and 35.2 t ha−1, respectively. The explainable yield gaps were 40.5, 56.9, and 55.1 t ha−1. Soil, management, and climatic factors limit apple yield improvement. Among these, low temperatures during the bud break and flowering periods can induce yield losses. Soil nutrient content and fertilizer management are also important limiting factors that have polynomial relationships with yield. Too much fertilizer and high levels of nutrients in the soil have already caused yield losses in some fields. Sound scientific guidance to help farmers adopt reasonable management techniques adapted to climate change is necessary to close the yield gap

Cold Climate during Bud Break and Flowering and Excessive Nutrient Inputs Limit Apple Yields in Hebei Province, China

Apples have become a major source of income for smallholder farmers in Bohai Bay. However, the annual productivity of apples in the area is relatively low and the interannual yield gap varies drastically. Identifying the apple yield gap and interannual production constraints can potentially promote the sustainable development of apple production. Based on track monitoring data of 45 smallholder farmers from 2016 to 2018, the yield gap and constraint factors were determined by adopting boundary analysis methodology. The results showed that the yield potential of apples during 2016–2018 was 75, 108, and 87 t ha−1, and actual yields were 36.8, 52.3, and 35.2 t ha−1, respectively. The explainable yield gaps were 40.5, 56.9, and 55.1 t ha−1. Soil, management, and climatic factors limit apple yield improvement. Among these, low temperatures during the bud break and flowering periods can induce yield losses. Soil nutrient content and fertilizer management are also important limiting factors that have polynomial relationships with yield. Too much fertilizer and high levels of nutrients in the soil have already caused yield losses in some fields. Sound scientific guidance to help farmers adopt reasonable management techniques adapted to climate change is necessary to close the yield gap

Developing evidenced-based quality assessment checklist for real practice in primary health care using standardized patients: a systematic review

The aim of this review was to explore the quality assessment checklists development methods in previous researches using standardized patients (SPs), as well as to propose an evidence-based checklist development procedure for quality assessment of common conditions in primary health care (PHC) settings

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6 $\times$ 6 $\times$ 6 m$^3$ liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6x6x6m3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

The DUNE Far Detector Vertical Drift Technology, Technical Design Report

International audienceDUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals