bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel Formulations and Logic-Based Benders Decomposition for the Integrated Parallel Machine Scheduling and Location Problem
Authors: Li Yantong , Côté Jean-François , Callegari-Coelho Leandro , Wu Peng 
Published: December 2021

We investigate the discrete parallel machine scheduling and location problem, which consists of locating multiple machines to a set of candidate locations, assigning jobs from different locations to the located machines, and sequencing the assigned jobs. The objective is to minimize the maximum completion time of all jobs, that is, the makespan. Though the problem is of theoretical significance with a wide range of practical applications, it has not been well studied as reported in the literature. For this problem, we first propose three new mixed-integer linear programs that outperform state-of-the-art formulations. Then, we develop a new logic-based Benders decomposition algorithm for practical-sized instances, which splits the problem into a master problem that determines machine locations and job assignments to machines and a subproblem that sequences jobs on each machine. The master problem is solved by a branch-and-cut procedure that operates on a single search tree. Once an incumbent solution to the master problem is found, the subproblem is solved to generate cuts that are dynamically added to the master problem. A generic no-good cut is first proposed, which is later improved by some strengthening techniques. Two optimality cuts are also developed based on optimality conditions of the subproblem and improved by strengthening techniques. Numerical results on small-sized instances show that the proposed formulations outperform state-of-the-art ones. Computational results on 1,400 benchmark instances with up to 300 jobs, 50 machines, and 300 locations demonstrate the effectiveness and efficiency of the algorithm compared with current approaches. Summary of Contribution: This paper employs operations research methods and computing techniques to address an NP-hard combinatorial optimization problem: the parallel discrete machine scheduling and location problem. The problem is of practical significance but has not been well studied in the literature. For the problem, we formulate three novel mixed-integer linear programs that outperform state-of-the-art formulations and develop a new logic-based Benders decomposition algorithm. Extensive computational experiments on 1,400 benchmark instances with up to 300 jobs, 50 machines, and 300 locations are conducted to evaluate the performance of the proposed models and algorithms.
Socially Irresponsible Employment in Emerging-Market Manufacturers
Authors: Distelhorst Greg , McGahan Anita 
Published: December 2021

Are socially irresponsible employment practices, such as abusive discipline and wage theft, systematically tied to manufacturing outcomes in emerging-market countries? Drawing on a stream of stakeholder theory that emphasizes economic interdependencies and insights from the fields of industrial relations and human resource management, we argue that working conditions within a firm are facets of a systemic approach to value creation and value appropriation. Some manufacturers operate “low road” systems that rest on harmful practices. Others operate “high road” systems in which the need to develop employees’ human capital deters socially irresponsible employment practices. To test the theory, we conduct a large-scale study of labor violations and manufacturing outcomes by analyzing data on over four thousand export-oriented small manufacturers in 48 emerging-market countries. The analysis demonstrates that socially irresponsible employment practices are associated with inferior firm-level manufacturing outcomes even after controlling for the effects of firm size, industry, product mix, production processes, host country, destination markets, and buyer mix. The theory and results suggest an opportunity for multinational corporations to improve corporate social performance in global value chains by encouraging their suppliers to transition to systems of value creation that rely on the development of worker human capital. Funding: A. McGahan received funding from Social Sciences and Humanities Research Council [Grant 435-2016-0075].
Synthesis of health promotion concepts in children's palliative care
Authors: Bennett Virginia , Hain Richard , Pritchard Aaron W , Noyes Jane 
Published: December 2021

Background:Palliative care improves the health of children with a life-limiting condition and appears to draw implicitly on concepts shared with a model of health promotion. However, to date there has been no scrutiny about how this relationship may shape understanding about children's palliative care.Aim:To explore the influence of health promoting concepts on children's palliative care models, policies and guidelines.Data sources:Health and social care databases were searched for policies, models and guidelines published between 2000–2018. Additional searches of professional national and international healthcare websites, children's palliative care charities and UK and Ireland government websites were conducted.Methods:A best fit framework synthesis was used.Findings:A total of 55 policies and guidelines were reviewed for the framework synthesis. Eight themes were generated: (1) health promoting children's palliative care policy and guidelines; (2) planning ahead; (3) creating a supportive environment; (4) enabling coping and independence; (5) reorienting children's palliative care sectors; (6) the lengthening trajectory of need for support; (7) strengthening community engagement in children's palliative care; and (8) quality of life and value-based ideologies.Conclusion:The best fit framework synthesis confirmed a conceptual relationship between children's palliative care and health promotion. This is captured in a new model that will extend professionals' understanding.
Full-waveform LiDAR echo decomposition based on dense and residual
neural networks
Authors: Liu Gangping , Ke Jun 
Published: December 2021

For full-waveform (FW) LiDAR signals, conventional echo decomposition methods use complicated filtering or de-noising algorithms for signal pre-processing. However, the speed and accuracy of these algorithms are limited. In this paper, we study a highly efficient and accurate decomposition method based on the FW dense connection network (FDCN) or FW deep residual network (FDRN). FDCN is a lightweight and efficient network for SNR higher than 24 dB, while FDRN is a deeper neural network with multiple residual blocks and works well for low SNR such as 12 dB. We compare FDCN and FDRN with other conventional methods. With FDCN and FDRN, the mean error for estimating an echo peak location is under 0.2 ns, while the amplitude error is under 5 mV when the dynamic range is

0
∼
100

m
V

. Both errors are much lower than the values using conventional methods.
Broadband and high extinction ratio TE-pass/TM-stop polarizer at 850  nm using chirped subwavelength gratings
Authors: Liu Yu , Dong Yue , Xu Yin , Zhang Bo , Ni Yi 
Published: December 2021

A polarizer is used to eliminate undesired polarization states and maintain an orthogonal one. The polarizer we proposed is designed on a silicon nitride (

S

i

3

N

4

) on insulator platform to achieve low-loss operation at the 850 nm wavelength region. Compared with conventional polarizer structures, chirped subwavelength gratings (SWG) are introduced in the proposed device’s main body to extend the wavelength band of the leakage mode, i.e., TM polarization state. Owing to the broadband nature of leakage mode, the operating bandwidth, which is defined as the wavelength region with extinction ratio (ER) higher than 20 dB, is increased dramatically. The simulation results show that the TE polarization state passes through the proposed polarizer with a high

E
R

=

46.24

d
B

and a low insertion loss

(

I
L

)
=

0.13

d
B

at 850 nm. A bandwidth broader than 171 nm is achieved with

E
R

>

20

d
B

and

I
L

<

1

d
B

over the wavelength region from 775 to 946 nm.
Case-area targeted preventive interventions to interrupt cholera transmission: Current implementation practices and lessons learned
Authors: Sikder Mustafa , Altare Chiara , Doocy Shannon , Trowbridge Daniella , Kaur Gurpreet , Kaushal Natasha , Lyles Emily , Lantagne Daniele , Azman Andrew S. , Spiegel Paul 
Published: December 2021

Background
Cholera is a major cause of mortality and morbidity in low-resource and humanitarian settings. It is transmitted by fecal-oral route, and the infection risk is higher to those living in and near cholera cases. Rapid identification of cholera cases and implementation of measures to prevent subsequent transmission around cases may be an efficient strategy to reduce the size and scale of cholera outbreaks.

Methodology/Principle findings
We investigated implementation of cholera case-area targeted interventions (CATIs) using systematic reviews and case studies. We identified 11 peer-reviewed and eight grey literature articles documenting CATIs and completed 30 key informant interviews in case studies in Democratic Republic of Congo, Haiti, Yemen, and Zimbabwe. We documented 15 outbreaks in 12 countries where CATIs were used. The team composition and the interventions varied, with water, sanitation, and hygiene interventions implemented more commonly than those of health. Alert systems triggering interventions were diverse ranging from suspected cholera cases to culture confirmed cases. Selection of high-risk households around the case household was inconsistent and ranged from only one case to approximately 100 surrounding households with different methods of selecting them. Coordination among actors and integration between sectors were consistently reported as challenging. Delays in sharing case information impeded rapid implementation of this approach, while evaluation of the effectiveness of interventions varied.

Conclusions/Significance
CATIs appear effective in reducing cholera outbreaks, but there is limited and context specific evidence of their effectiveness in reducing the incidence of cholera cases and lack of guidance for their consistent implementation. We propose to 1) use uniform cholera case definitions considering a local capacity to trigger alert; 2) evaluate the effectiveness of individual or sets of interventions to interrupt cholera, and establish a set of evidence-based interventions; 3) establish criteria to select high-risk households; and 4) improve coordination and data sharing amongst actors and facilitate integration among sectors to strengthen CATI approaches in cholera outbreaks.
Evaluation of multi-assay algorithms for identifying individuals with recent HIV infection: HPTN 071 (PopART)
Authors: Grant-McAuley Wendy , Klock Ethan , Laeyendecker Oliver , Piwowar-Manning Estelle , Wilson Ethan , Clarke William , Breaud Autumn , Moore Ayana , Ayles Helen , Kosloff Barry , Shanaube Kwame , Bock Peter , Mandla Nomtha , van Deventer Anneen , Fidler Sarah , Donnell Deborah , Hayes Richard , Eshleman Susan H. ,   for the HPTN 071 (PopART) Study Team
Published: December 2021

Background
Assays and multi-assay algorithms (MAAs) have been developed for population-level cross-sectional HIV incidence estimation. These algorithms use a combination of serologic and/or non-serologic biomarkers to assess the duration of infection. We evaluated the performance of four MAAs for individual-level recency assessments.

Methods
Samples were obtained from 220 seroconverters (infected <1 year) and 4,396 non-seroconverters (infected >1 year) enrolled in an HIV prevention trial (HPTN 071 [PopART]); 28.6% of the seroconverters and 73.4% of the non-seroconverters had HIV viral loads ≤400 copies/mL. Samples were tested with two laboratory-based assays (LAg-Avidity, JHU BioRad-Avidity) and a point-of-care assay (rapid LAg). The four MAAs included different combinations of these assays and HIV viral load. Seroconverters on antiretroviral treatment (ART) were identified using a qualitative multi-drug assay.

Results
The MAAs identified between 54 and 100 (25% to 46%) of the seroconverters as recently-infected. The false recent rate of the MAAs for infections >2 years duration ranged from 0.2%-1.3%. The MAAs classified different overlapping groups of individuals as recent vs. non-recent. Only 32 (15%) of the 220 seroconverters were classified as recent by all four MAAs. Viral suppression impacted the performance of the two LAg-based assays. LAg-Avidity assay values were also lower for seroconverters who were virally suppressed on ART compared to those with natural viral suppression.

Conclusions
The four MAAs evaluated varied in sensitivity and specificity for identifying persons infected <1 year as recently infected and classified different groups of seroconverters as recently infected. Sensitivity was low for all four MAAs. These performance issues should be considered if these methods are used for individual-level recency assessments.
Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China
Authors: Yang Zhen , Wang Chenchen , Nie Yanwu , Sun Yahong , Tian Maozai , Ma Yuhua , Zhang Yuxia , Yuan Yimu , Zhang Liping 
Published: December 2021

Background and objectivesXinjiang is one of the areas in China with extremely severe iodine deficiency. The health of Xinjiang residents has been endangered for a long time. In order to provide reasonable suggestions for scientific iodine supplementation and improve the health and living standards of the people in Xinjiang, it is necessary to understand the spatial distribution of iodine content in drinking water and explore the influencing factors of spatial heterogeneity of water iodine content distribution.MethodsThe data of iodine in drinking water arrived from the annual water iodine survey in Xinjiang in 2017. The distribution of iodine content in drinking water in Xinjiang is described from three perspectives: sampling points, districts/counties, and townships/streets. ArcGIS was used for spatial auto-correlation analysis, mapping the distribution of iodine content in drinking water and visualizing the distribution of Geographically Weighted Regression (GWR) model parameter. Kriging method is used to predict the iodine content in water at non-sampling points. GWR software was used to build GWR model in order to find the factors affecting the distribution of iodine content in drinking water.ResultsThere are 3293 sampling points in Xinjiang. The iodine content of drinking water ranges from 0 to 128 μg/L, the median is 4.15 μg/L. The iodine content in 78.6% of total sampling points are less than 10 μg/L, and only that in the 3.4% are more than 40 μg/L. Among 1054 towns’ water samples in Xinjiang, 88.9% of the samples’ water iodine content is less than 10 μg/L. Among the 94 studied areas, the median iodine content in drinking water in 87 areas was less than 10 μg/L, those values in 7 areas were between 10–40 μg/L, and the distribution of water iodine content in Xinjiang shows clustered. The GWR model established had found that the effects of soil type and precipitation on the distribution of iodine content in drinking water were statistically significant.ConclusionsThe iodine content of drinking water in Xinjiang is generally low, but there are also some areas which their drinking water has high iodine content. Soil type and precipitation are the factors affecting the distribution of drinking water iodine content, and are statistically significant (P<0.05).
Translating best practice into real practice: Methods, results and lessons from a project to translate an English sexual health survey into four Asian languages
Authors: Vujcich Daniel , Roberts Meagan , Gu Zhihong , Kao Shih-Chi , Lobo Roanna , Mao Limin , Oudih Enaam , Phoo Nang Nge Nge , Wong Horas , Reid Alison 
Published: December 2021

Background
Migrants are underrepresented in population health surveys. Offering translated survey instruments has been shown to increase migrant representation. While ‘team translation’ represents current best practice, there are relatively few published examples describing how it has been implemented. The purpose of this paper is to document the process, results and lessons from a project to translate an English-language sexual health and blood-borne virus survey into Khmer, Karen, Vietnamese and Traditional Chinese.

Methods
The approach to translation was based on the TRAPD (Translation, Review, Adjudication, Pretesting, and Documentation) model. The English-language survey was sent to two accredited, independent translators. At least one bilingual person was chosen to review and compare the translations and preferred translations were selected through consensus. Agreed translations were pretested with small samples of individuals fluent in the survey language and further revisions made.

Results
Of the 51 survey questions, only nine resulted in identical independent translations in at least one language. Material differences between the translations related to: (1) the translation of technical terms and medical terminology (e.g. HIV); (2) variations in dialect; and (3) differences in cultural understandings of survey concepts (e.g. committed relationships).

Conclusion
Survey translation is time-consuming and costly and, as a result, deviations from TRAPD ‘best practice’ occurred. It is not possible to determine whether closer adherence to TRAPD ‘best practice’ would have improved the quality of the resulting translations. However, our study does demonstrate that even adaptations of the TRAPD method can identify issues that may not have been apparent had non-team-based or single-round translation approaches been adopted. Given the dearth of clear empirical evidence about the most accurate and feasible method of undertaking translations, we encourage future researchers to follow our example of making translation data publicly available to enhance transparency and enable critical appraisal.
The economic impact of rostering junior doctors to triage to assist nursing staff in the early part of the patient journey through the emergency department
Authors: Brain David , Johnson David , Hocking Julia , Chang Angela T. 
Published: December 2021

ObjectiveThis study aims to determine whether redeploying junior doctors to assist at triage represents good value for money and a good use of finite staffing resources.MethodsWe undertook a cost-minimisation analysis to produce new evidence, from an economic perspective, about the costs associated with reallocating junior doctors in the emergency department. We built a decision-analytic model, using a mix of prospectively collected data, routinely collected administrative databases and hospital costings to furnish the model. To measure the impact of uncertainty on the model’s inputs and outputs, probabilistic sensitivity analysis was undertaken, using Monte Carlo simulation.ResultsThe mean costs for usual care were $27,035 (95% CI $27,016 to $27,054), while the mean costs for the new model of care were $25,474, (95% CI $25,453 to $25,494). As a result, the mean difference was -$1,561 (95% CI -$1,533 to -$1,588), with the new model of care being a less costly approach to managing staffing allocations, in comparison to the usual approach.ConclusionOur study shows that redeploying a junior doctor from the fast-track area of the department to assist at triage provides a modest reduction in cost. Our findings give decision-makers who seek to maximise benefit from their finite budget, support to reallocate personnel within the ED.
Innovations, contestations and fragilities of the health system response to COVID-19 in the Gauteng Province of South Africa
Authors: Rispel Laetitia C. , Marshall Carol , Matiwane Busisiwe , Tenza Immaculate Sabelile 
Published: December 2021

Background
Gauteng province, with 26.3% of South Africa’s population, is the commercial and industrial powerhouse of the country. During the first epidemic wave in 2020, Gauteng accounted for 32.0% of South Africa’s reported COVID-19 cases.

Aim
The aim of this study was to describe the health system response to the COVID-19 pandemic during the first epidemic wave in Gauteng province and to explore the perspectives of key informants on the provincial response.

Material and methods
Using an adapted Pandemic Emergency Response Conceptual Framework, this was a qualitative case study design consisting of 36 key informant interviews and a document analysis. We used thematic analysis to identify themes and sub-themes from the qualitative data.

Results
Our case study found that Gauteng developed an innovative, multi-sectoral and comprehensive provincial COVID-19 response that aimed to address the dual challenge of saving lives and the economy. However, the interviews revealed multiple perspectives, experiences, contestations and contradictions in the pandemic response. The COVID-19 pandemic exposed and amplified the fragilities of existing systems, reflected in the corruption on personal protective equipment, poor data quality and inappropriate decisions on self-standing field hospitals. Rooted in a chronic under-investment and insufficient focus on the health workforce, the response failed to take into account or deal with their fears, and to incorporate strategies for psychosocial support, and safe working environments. The single-minded focus on COVID-19 exacerbated these fragilities, resulting in a de facto health system lockdown and reported collateral damage. The key informants identified missed opportunities to invest in primary health care, partner with communities and to include the private health sector in the pandemic response.

Conclusion
Gauteng province should build on the innovations of the multi-sectoral response to the COVID-19 pandemic, while addressing the contested areas and health system fragilities.
Characteristics of opioid prescribing to outpatients with chronic liver diseases: A call for action
Authors: Agbalajobi Olufunso M. , Gmelin Theresa , Moon Andrew M. , Alexandre Wheytnie , Zhang Grace , Gellad Walid F. , Jonassaint Naudia , Rogal Shari S. 
Published: December 2021

BackgroundChronic liver disease (CLD) is among the strongest risk factors for adverse prescription opioid-related events. Yet, the current prevalence and factors associated with high-risk opioid prescribing in patients with chronic liver disease (CLD) remain unclear, making it challenging to address opioid safety in this population. Therefore, we aimed to characterize opioid prescribing patterns among patients with CLD.MethodsThis retrospective cohort study included patients with CLD identified at a single medical center and followed for one year from 10/1/2015-9/30/2016. Multivariable, multinomial regression was used identify the patient characteristics, including demographics, medical conditions, and liver-related factors, that were associated with opioid prescriptions and high-risk prescriptions (≥90mg morphine equivalents per day [MME/day] or co-prescribed with benzodiazepines).ResultsNearly half (47%) of 12,425 patients with CLD were prescribed opioids over a one-year period, with 17% of these receiving high-risk prescriptions. The baseline factors significantly associated with high-risk opioid prescriptions included female gender (adjusted incident rate ratio, AIRR = 1.32, 95% CI = 1.14–1.53), Medicaid insurance (AIRR = 1.68, 95% CI = 1.36–2.06), cirrhosis (AIRR = 1.22, 95% CI = 1.04–1.43) and baseline chronic pain (AIRR = 3.40, 95% CI = 2.94–4.01), depression (AIRR = 1.93, 95% CI = 1.60–2.32), anxiety (AIRR = 1.84, 95% CI = 1.53–2.22), substance use disorder (AIRR = 2.16, 95% CI = 1.67–2.79), and Charlson comorbidity score (AIRR = 1.27, 95% CI = 1.22–1.32). Non-alcoholic fatty liver disease was associated with decreased high-risk opioid prescriptions (AIRR = 0.56, 95% CI = 0.47–0.66).ConclusionOpioid medications continue to be prescribed to nearly half of patients with CLD, despite efforts to curtail opioid prescribing due to known adverse events in this population.