bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emission analysis for a new tubular aeroengine combustor in atmospheric test rig conditions
Authors: Topal Ahmet , Turan Onder 
Published: September 2022

Purpose
The purpose of this study is to have semiempirical correlations for carbon monoxide (CO), unburned hydrocarbon (UHC) and nitrogen oxide (NOx) emissions that are collected and calibrated by using experimental data of a tubular-type combustor.

Design/methodology/approach
Combustor uses a coflow radial-type air-blast atomizer and is especially designed for the empirical correlation issues. Air mass flow rate, air inlet temperature and air-to-fuel ratio parameters have been changed and different inlet conditions have been created for combustor tests. Six different inlet temperatures from 475 to 350 K have been set for each air mass flow rate. Air mass flow rate values from 0.035 to 0.050 kg/s have been used to create varied combustor aerodynamic loadings.

Findings
Increasing combustor inlet temperature decreases the CO and UHC emissions. However, it has an adverse effect in NOx emissions. Moreover, CO and UHC emissions have an increasing trend by the mass flow rate rise that results an extra aerodynamic loading.

Research limitations/implications
It is difficult to obtain real operating parameters for the combustor. Therefore, as a different approach in respect of the literature, rig test parameters have been used for thermodynamic calculations. Additionally, emission calculations of the combustor design point have been performed based on a conditioned test environment. Moreover, combustor outlet temperature and emission values have been scanned and mean values used for the analysis.

Practical implications
To perform preliminary calculations for these pollutants, designers need experimentally calibrated correlations for the similar combustors.

Social implications
If the application area of the designed engine is a civil aircraft, emissions are one of the most important issues because of the strict regulations of International Civil Aviation Organization. Therefore, aviation companies are continuously working on reducing of emissions.

Originality/value
A comprehensive study for the preliminary emission calculation of newly designed gas turbine combustors was performed to investigate semiempirical correlations in the atmospheric test rig.
Analysing value creation in social housing construction in remote communities – application to Nunavik (Canada)
Authors: Suárez José Luis , Gosselin Louis , Lehoux Nadia 
Published: September 2022

PurposeRemote and isolated indigenous communities in Nunavik (Canada) currently face a number of housing related challenges. This paper proposes a conceptual framework to identify the factors affecting value creation within the supply chain of social housing construction in that region. The term “social” refers to the fact that governments subsidise construction and operation of these buildings intended for low-income households.Design/methodology/approachThe research used a literature review and information collected from 3 semi-structured interviews with key stakeholders to identify the desired features of improvement or solutions (e.g. prefabrication) with respect to value creation. A SWOT analysis, an influence/dependence map and a causal loop diagram were developed to represent the supply chain.FindingsLocal job creation and the number of buildings to build were identified as the key factors that can roughly represent value creation. Energy resources, construction time, type and amount of labour force, shipping constraints, number of replacement parts and waste disposal were identified as the main factors constraining the range of solutions to implement.Practical implicationsThe framework can be used to support the decision-making in supply chain management and the design of solutions for remote areas such as Nunavik.Originality/valueThis paper is the first to analyse value creation in social building construction in remote and isolated communities such as those from Nunavik. Conceptual models achieved within the framework allowed identifying the factors that could roughly represent this value creation, as well as logical relationships that link them with other factors.
Modified unipolar SPWM inverter for solar PV applications using MATLAB/Simulink model interfaced with dSPACE DS1104
Authors: L. Ashok Kumar , R. Kumaravel 
Published: September 2022

Purpose
The purpose of this paper is to check the Solar Photovoltaic (PV) inverter working condition with modified unipolar switching pulse. The gate pulse for the inverter switches is generated in MATLAB simulation and interfaced with hardware protype. Simulation results can be compared with hardware results.

Design/methodology/approach
A considerable amount of research has been done on different Pulse Width Modulation (PWM) techniques. Based on the findings, a modified Unipolar Sinusoidal PWM technique was created with one reference signal and two carrier signals+ (one for the positive half cycle and the other for the negative half cycle) and simulated in the MATLAB/Simulink platform. The prototype inverter module receives the simulated switching pulses via dSPACE DS1104 hardware software interfacing board. The hardware implementation has been done, and the hardware results compared with simulation results for various input voltage levels using resistive load.

Findings
This modified switching pulse has dead band and additional hardware setup is not required. 3-phase multi-level inverter output waveform has been achieved with six switches in this method and with low filter values, pure sine wave output can be obtained in simulation. By this method of switching pulse generation and testing, for every modification in switching pulse hardware gate driver is not required. Resulting time consumption and money investment are lower.

Originality/value
Modified Unipolar SPWM pulse generation technique is novel method for solar PV inverter. The switching pulse has been designed and tested in both MATLAB/Simulation and hardware prototype inverter. Hardware and software results are identical. This method of pulse generation and hardware implementation has not been done anywhere before.
Macroeconomic co-benefits of DRR investment: assessment using the Dynamic Model of Multi-hazard Mitigation CoBenefits (DYNAMMICs) model
Authors: Yokomatsu Muneta , Mochizuki Junko , Joseph Julian , Burek Peter , Kahil Taher 
Published: September 2022

PurposeThe authors present a dynamic macroeconomic model for assessment of disaster risk reduction (DRR) policies under multiple hazards. The model can be used to analyze and compare various potential policies in terms of their economic consequences. The decomposition of these effects into multiple benefits helps policy makers and other stakeholders better understand the ex ante and ex-post advantages of DRR investments. The purpose of this paper is to address these issues.Design/methodology/approachA dynamic real business cycle model is at the core of this research. In the model multiple natural hazards modeled stochastically cause shocks to the economy. Economic outcomes, most importantly, output can be assessed before and after disasters and under various DRR policies. The decomposition of benefits aims to quantify the concept of triple dividends.FindingsIn case study applications in Tanzania and Zambia, the authors find that investments into physical infrastructure and risk transfer instruments generate a variety of benefits even in the absence of disaster. A land use restriction with planned relocation for example reduces output in the short run but in the long run increases it. Overall, policy effects of various DRR interventions evolve in a nonmonotonic manner and should be evaluated over a long period of time using dynamic simulation.Originality/valueThe novelty of this study lies in the economic quantification of multiple benefits described in the triple dividends literature. This helps comparing ex ante, ex-post and volatility-related economic effects of multiple disasters and related physical and financial DRR investment options. As observed in the case studies, the model can also identify overlooked temporal heterogeneity of co-benefits of DRR investments.
How designed work environment and enacted work interactions impact creativity and work–life balance
Authors: Mattarelli Elisa , Cochis Carlotta , Bertolotti Fabiola , Ungureanu Paula 
Published: September 2022

PurposeThis paper investigates how (1) a work environment designed to sustain creativity (i.e. through flexible arrangements and elements of the social-organizational work environment) and (2) the amount of enacted work interactions among employees, interpreted as facilitators of new idea generation (i.e. outdegree centrality in instrumental networks), differently impact creativity and work–life balance.Design/methodology/approachThe authors conducted a quantitative study in a knowledge-intensive multinational company and collected data through a survey on a sample of 207 workers.FindingsFindings highlight that flexible work arrangements are positively related to increased work–life balance but not to creativity, whereas having access to a social-organizational work environment designed to foster creativity is associated to an increased level of idea generation, but to a reduction in work–life balance. In addition, centrality in instrumental social networks is also associated to a reduction of work–life balance. Findings thus point to a potential trade-off between structures aimed at increasing creativity and initiatives aimed at engendering work–life balance.Originality/valueThe research contributes to the current debate on new organizational practices for innovation and creativity, highlighting their unexpected implications for workers. The research also contributes to the literature on work–life balance by unraveling previously unexplored antecedents, i.e. social networks and the social-organizational work environment designed for creativity.
Training satisfaction relative to turnover intention: the mediating role of employee loyalty
Authors: Albtoosh Qais , Ngah Abdul Hafaz , Yusoff Yusliza Mohd 
Published: September 2022

PurposeThe purpose of this study is to focus on Turnover intention (TI) which is gaining significance in the Jordanian government sector as well as in many other international institutions. Organizations tend to seek valuable benefits from the human resource capital they have to achieve their competitive advantages. However, TI becomes a global issue as well as in Jordanian public context. The research framework of this study is based on the satisfaction and social psychological literature.Design/methodology/approachBy applying the convenience sampling method, data were collected through an online questionnaire; 354 respondents from the governmental sector participated in this study. Data were analyzed using the statistical software Smart PLS.FindingsResults revealed that mind wandering (MW) has a negative impact on training satisfaction (TS) while trainer efficacy (TE) has a positive impact on TS. Meanwhile, work–life conflict (WLC) was not significantly related to TS. TS has a negative impact on TI and a positive impact on employee loyalty (EL). However, EL has a negative impact on TI, and, at the same time, it mediates the relationship between TS and TI. Moreover, the study demonstrates sequential mediation for TI.Originality/valueThe research adds to the body of knowledge by testing a new framework. Moreover, it introduces sequential mediation for TI.
Effectiveness of sponsoring the video assistant referee system: a comparative exploratory study
Authors: Alonso Dos Santos Manuel , Sánchez-Franco Manuel J. , Torres-Moraga Eduardo , Calabuig Moreno Ferran 
Published: September 2022

PurposeThis study explores the effect of video assistant referee (VAR) sponsorship on spectator response and compares it with advertising and conventional sponsorship.Design/methodology/approachAn experiment with 809 subjects is conducted by analyzing 20 one-minute video clip stimuli from a Premier League soccer game divided into four formats: two formats of VAR sponsorship, advertising, and conventional sponsorship.FindingsThe results show that the indicators of recall, credibility, and perceived congruence improve when the VAR sponsorship format is used.Originality/valueThis is the first manuscript to examine the effectiveness of a new type of sponsorship: VAR sponsorship. This manuscript provides metrics that will guide practitioners on whether to use this type of sponsorship.
Open problems in medical federated learning
Authors: Yoo Joo Hun , Jeong Hyejun , Lee Jaehyeok , Chung Tai-Myoung 
Published: September 2022

Purpose
This study aims to summarize the critical issues in medical federated learning and applicable solutions. Also, detailed explanations of how federated learning techniques can be applied to the medical field are presented. About 80 reference studies described in the field were reviewed, and the federated learning framework currently being developed by the research team is provided. This paper will help researchers to build an actual medical federated learning environment.

Design/methodology/approach
Since machine learning techniques emerged, more efficient analysis was possible with a large amount of data. However, data regulations have been tightened worldwide, and the usage of centralized machine learning methods has become almost infeasible. Federated learning techniques have been introduced as a solution. Even with its powerful structural advantages, there still exist unsolved challenges in federated learning in a real medical data environment. This paper aims to summarize those by category and presents possible solutions.

Findings
This paper provides four critical categorized issues to be aware of when applying the federated learning technique to the actual medical data environment, then provides general guidelines for building a federated learning environment as a solution.

Originality/value
Existing studies have dealt with issues such as heterogeneity problems in the federated learning environment itself, but those were lacking on how these issues incur problems in actual working tasks. Therefore, this paper helps researchers understand the federated learning issues through examples of actual medical machine learning environments.
Apigenin in cancer therapy: Prevention of genomic instability and anticancer mechanisms
Authors: Moslehi Masoud , Rezaei Sepideh , Talebzadeh Pourya , Ansari Mohammad Javed , Jawad Mohammed Abed , Jalil Abduladheem Turki , Rastegar‐Pouyani Nima , Jafarzadeh Emad , Taeb Shahram , Najafi Masoud 
Published: September 2022

AbstractThe incidence of cancer has been growing worldwide. Better survival rates following the administration of novel drugs and new combination therapies may concomitantly cause concern regarding the long‐term adverse effects of cancer therapy, for example, second primary malignancies. Moreover, overcoming tumour resistance to anticancer agents has been long considered as a critical challenge in cancer research. Some low toxic adjuvants such as herb‐derived molecules may be of interest for chemoprevention and overcoming the resistance of malignancies to cancer therapy. Apigenin is a plant‐derived molecule with attractive properties for chemoprevention, for instance, promising anti‐tumour effects, which may make it a desirable adjuvant to reduce genomic instability and the risks of second malignancies among normal tissues. Moreover, it may improve the efficiency of anticancer modalities. This paper aims to review various effects of apigenin in both normal tissues and malignancies. In addition, we explain how apigenin may have the ability to protect usual cells against the genotoxic repercussions following radiotherapy and chemotherapy. Furthermore, the inhibitory effects of apigenin on tumours will be discussed.
Impact of a selective narrow network with comprehensive patient navigation on access, utilization, expenditures, and enrollee experiences
Authors: Brown Timothy T. , Hague Emily , Neumann Alicia , Rodriguez Hector P. , Shortell Stephen M. 
Published: September 2022

AbstractObjectiveTo examine the effect of enrollee switching from a broad‐network accountable care organization (ACO) health maintenance organization (HMO) to a “high performance” ACO‐HMO with a selective narrow network and comprehensive patient navigation system on access, utilization, expenditures, and enrollee experiences.Data SourcesSecondary administrative data were obtained for 2016–2020, and primary interview and survey data in 2021.Study DesignFixed‐effects instrumental variable analyses of administrative data and regression analyses of survey data. Outcomes included access, utilization, expenditures, and enrollee experience. Background information was gathered via interviews.Data Collection/Extraction MethodsWe obtained medical expenditure/enrollment and access data on continuously enrolled members in a broad‐network ACO‐HMO (n = 24,555), a subset of those who switched to a high‐performance ACO‐HMO in 2018 (n = 7664); interviews of organizational leaders (n = 13); and an enrollee survey (n = 512).Principal FindingsHealth care effectiveness data and information Set (HEDIS) access measures were not different across plans. However, annual utilization dropped by 15.5 percentage points (95% CI: 18.1, 12.9) more in the high‐performance ACO‐HMO, with relative annual expenditures declining by $1251 (95% CI: $1461, $1042) per person per year. High‐performance ACO‐HMO enrollees were 10.1 percentage points (95% CI 0.001, 0.201) more likely to access primary care usually or always as soon as needed and 11.2 percentage points (95% CI 0.007, 0.217) more likely to access specialty care usually or always as soon as needed. Plan satisfaction was 7.1 percentage points (95% CI: −0.001, 0.138) higher in the high‐performance ACO‐HMO. Interviewees noted the comprehensive patient navigation system was designed to ensure patients remained in the narrow network to receive care.ConclusionsACO and HMO contracts with selective narrow networks supported by comprehensive patient navigation can reduce expenditures and improve specialty access and patient satisfaction compared to broad‐network plans that lack these features. Payers should consider implementing narrow networks with comprehensive support systems.
Advances in functional photonic crystal materials for the analysis of chemical hazards in food
Authors: Dai Shijie , Li Qianjin , Li Wei , Zhang Yaodan , Dou Menghua , Xu Ruimin , Wang Tingting , Lu Xiaoyue , Wang Fenying , Li Jianlin 
Published: September 2022

AbstractChemical contaminants in food generally include natural toxins (mycotoxins, animal toxins, and phytotoxins), pesticides, veterinary drugs, environmental pollutants, heavy metals, and illegal additives. Developing a low‐cost, simple, and rapid detection technology for harmful substances in food is urgently needed. Analytical methods based on different advanced materials have been developed into rapid detection methods for food samples. In particular, photonic crystal (PC) materials have a unique surface periodic structure, structural color, a large surface area, easy integration with photoelectronic and magnetic devices which have great advantages in the development of rapid, low‐cost, and highly sensitive analytical methods. This review focuses on the PC materials in the view of their fabrication processes, functionalized recognition components for the specific recognition of hazardous substances, and applications in the separation, enrichment, and detection of chemical hazards in real samples. Suspension array based on three‐dimensional PC microspheres by droplet‐based microfluidic assembly is a great promising and powerful platform for food safety detection fields. For the PCs selective analysis, biological antibodies, aptamers, and molecularly imprinted polymers (MIPs) could be modified for specific recognition of target substances, particularly MIPs because of their low‐cost and easy mass production. Based on these functional PCs, various toxic and hazardous substances can be selectively enriched or recognized in real samples and further quantified in combination of liquid chromatography method or optical detection methods including fluorescence, chemiluminescence, and Raman spectroscopy.
The impact of antimeric lower limb length asymmetry on adult stature estimation
Authors: Ingvoldstad Megan E. , Walter Brittany S. 
Published: September 2022

AbstractAntimeric lower limb length asymmetry is frequently noted when measuring human skeletal remains. As lower limb bones are often used to estimate stature from unidentified remains, the forensic anthropologist who notes a disparity must then determine which lower limb bone or bones will produce an estimate that most accurately and precisely captures the unknown individual's stature. To help forensic anthropologists make informed decisions when remains exhibit lower limb antimeric asymmetry, left and right femora and fibulae maximum lengths were analyzed from 78 DPAA‐identified individuals with measured statures. Results revealed 87.2% of individuals exhibited lower limb antimeric asymmetry, statistically significant differences between lower limb lengths, decreasing estimate accuracy when asymmetry increased, and that using a 99% prediction interval for disparities ≥5.0 mm nearly ensured documented measured stature would be captured. These findings were validated on independent samples of 20 adult males from the DPAA and 146 males and females from the Terry, Hamann‐Todd, and Bass Collections. Preliminary results were largely supported; however, the accuracy reduction with increasing asymmetry observed in the DPAA data was not replicated. Based on these findings, we encourage bilateral measurement taking to identify lower limb antimeric asymmetry, caution against combining bone lengths from opposite sides, and recommend using a 99% prediction interval when lower limb length antimeric asymmetry is ≥5.0 mm and if using the FORDISC 3 Trotter M Stats database. When C Stats or F Stats are used, the prediction intervals associated with these less homogeneous databases are large enough to absorb error due to antimeric asymmetry.
Estimating the effect of death penalty moratoriums on homicide rates using the synthetic control method
Authors: Oliphant Stephen N. 
Published: September 2022

AbstractResearch SummaryResearch examining death penalty deterrence has been characterized as inconclusive and uninformative. The present analysis heeds a recommendation from prior research to examine single‐state changes in death penalty policy using the synthetic control method. Data from the years 1979–2019 were used to construct synthetic controls and estimate the effects of death penalty moratoriums on homicide rates in Illinois, New Jersey, Washington, and Pennsylvania. Moratoriums on capital punishment resulted in nonsignificant homicide reductions in all four states.Policy ImplicationsInconsistent with a deterrence hypothesis, no evidence of a deterrent effect attributable to death penalty statutes was found. Given the gravity and finality of state‐sanctioned execution, it is important that policy makers consider the weight of evidence of the death penalty's capacity to deter, as well as issues of equity, justice, and fairness, in their decision making about death penalty policy.