bluuebunny/crossref_metadata_2025 huggingface dataset:
How Effective Was the Global South Knowledge Exchange? The Chinese-Funded Medical Projects in Tanzania, 1968–1990s
Authors: Kifyasi Andrea Azizi
Published: February 2024

abstract: Knowledge circulation scholars have examined the North-South exchange as mainly one-way traffic, where the Global South is perceived as the recipient of knowledge from the Global North. In contrast, this article underscores Southern countries' role in technoscientific development by examining actors in Chinese-funded medical projects in Tanzania. It shows that Chinese sponsorship of Tanzania's health sector was critical not only in breaking the yoke of dependency on medical knowledge from the North but also in debunking the Global North narratives positing Africa as backward and lacking initiative in medical and industrial technologies. Employing qualitative analytical methods on pertinent archival, oral accounts and published sources, this article shows that despite the Sino-Tanzanian cooperation's potential, knowledge exchanges were arguably one-way rather than reciprocal, and the exchanged knowledge remained ineffective and unsustainable owing to ill-thought modus operandi from the onset.
European Technical Democracy? How Consumer Associations Did—or Did Not—Shape the 1980s Automotive Environmental Standards
Authors: Milor Alice
Published: February 2024

abstract: Did the 1980s automotive standards reflect the European Economic Community's move toward a "technical democracy" or a broader democratic deficit? In the early 1980s, Europe's automotive sector faced multiple challenges: the European Commission's desire to harmonize technical standards and achieve greater European integration, intense competition between manufacturers, and environmental issues like acid rain. Debates on reducing air pollution focused on unleaded petrol and catalytic converters. Two associations representing civil society in Brussels responded to the increase in environmental concerns with a 1982 joint campaign. Despite a rich historiography on pollutant emission standards, highlighting the strategies of governments and companies, no study has dealt with the role nongovernmental organizations played. Based on public and private archives, particularly those of the European Bureau of Consumers' Unions, this article argues the new regulations did not result from the EU's consultation with civil society organizations like consumer groups but rather with the automotive industry.
Optimizing satellite and core networks for a global quantum network
Authors: Karavias Vasileios , White Catherine , Lord Andrew , Payne Michael C.
Published: February 2024

Quantum key distribution (QKD) promises information theoretic security. However, the exponential decay of the secure key in optical fibers leads to limitations in long distance QKD distribution across fibers, which is necessary for global quantum networks (QNs). Satellite QKD can be used to generate keys over long distances bypassing fiber limitations and is thus a promising approach for global QNs. In this paper, we construct mixed integer linear program (MILP) models to investigate how to best connect the core fiber network to ground stations to minimize the overall network cost. We design one MILP that can provide a quantitative value for the number of satellites needed for a given configuration and another one to optimize the allocation of the core network nodes to ground stations to minimize the overall network cost. We use these models to investigate different strategies to allocate satellites to ground stations during a satellite overpass, showing that allocating satellites based on the expected transmission requirements can reduce the number of satellites needed in a network by up to 40% compared to randomly allocating the satellites to ground stations. Furthermore, we use these models to investigate securing the data center traffic in two networks, one local European network and one global network, and show that costs in the optimal configuration can be up to 40% cheaper than simply connecting core network sites to their geographically closest ground station.
Equalization system of low differential mode delay few-mode fibers based on the neural network MIMO algorithm
Authors: Guo Hao , Yan Fengping , Ren Wsenhua , Gu Zhenyu , Li Ting , Wang Xiangdong , Yang Dandan , Tan Haoyu , Chang Huan
Published: February 2024

In recent years, with the development of information networks, higher requirements for transmission capacity have been recommended. Yet, at the same time, the capacity of single-mode fiber is rapidly approaching the theoretical limit. The multidimensional multiplexing technique is an effective way to solve this problem. Since the high differential mode delay (DMD) of transmission fiber increases the complexity of demultiplexing in equalization algorithms, we use an intelligent design method to optimize the trench-assisted gradient refractive index structure in this paper. The maximum DMD of the optimized optical fiber structure is 19.6 ps/km. A least mean squares-feedforward neural network constant modulus algorithm (LMS-FNNCMA) is also designed by using the theory of the least mean squares (LMS), constant modulus algorithm (CMA), and the multiple input multiple output (MIMO) neural networks. In order to verify the accuracy of the algorithm, a polarization division multiplexing-wavelength division multiplexing-mode division multiplexing (PDM-WDM-MDM) optical transmission system is constructed through simulation. The algorithm successfully realizes the de-crosstalk over a transmission distance of 1200 km at a rate of 1.2 Tbps under simulation conditions.
Multi-band reprogrammable phase-change metasurface spectral filters for on-chip spectrometers
Authors: Zheng Qilin , Liang Li , Quan Yunan , Nan Xianghong , Sun Dongqin , Tan Yongsheng , Hu Xin , Yu Qing , Fang Zebo
Published: February 2024

Active optical metasurfaces provide a platform for dynamic and real-time manipulation of light at subwavelength scales. However, most active metasurfaces are unable to simultaneously possess a wide wavelength tuning range and narrow resonance peaks, thereby limiting further advancements in the field of high-precision sensing or detection. In the paper, we proposed a reprogrammable active metasurface that employs the non-volatile phase change material Ge2Sb2Te5 and demonstrated its excellent performance in on-chip spectrometer. The active metasurfaces support magnetic modes and feature Friedrich-Wintgen quasi bound states in the continuum, capable of achieving multi-resonant near-perfect absorption, a multilevel tuning range, and narrowband performance in the infrared band. Meanwhile, we numerically investigated the coupling phenomenon and the intrinsic relationship between different resonance modes under various structural parameters. Furthermore, using the active metasurfaces as tunable filters and combined with compressive sensing algorithms, we successfully reconstructed various types of spectral signals with an average fidelity rate exceeding 0.99, utilizing only 51 measurements with a single nanostructure. A spectral resolution of 0.5 nm at a center wavelength 2.538 µm is predicted when the crystallization fractions of GST change from 0 to 20%. This work has promising potential in on-site matter inspection and point-of-care (POC) testing.
Scan-less 3D microscopy based on spatiotemporal encoding on a single-cavity dual-comb laser
Authors: Lu Wanping , Zhu Zhiwei , Willenberg Benjamin , Pupeikis Justinas , Phillips Christopher R. , Keller Ursula , Chen Shih-chi
Published: February 2024

Dual-comb microscopy enables high-speed and high-precision optical sampling by simultaneously extracting both amplitude and phase information from the interference signals with frequency division multiplexing. In this Letter, we introduce a spatiotemporal encoding approach for dual-comb microscopy that overcomes previous limitations such as mechanical scanning, low sampling efficiency, and system complexity. By employing free-space angular-chirp-enhanced delay (FACED) and a low-noise single-cavity dual-comb laser, we achieve scan-less 3D imaging with nanometer precision and a 3D distance-imaging rate of 330 Hz, restricted only by the repetition rate difference of the dual-comb laser. Specifically, the FACED unit linearly arranges the laser beam into an array. A grating subsequently disperses this array transversely into lines, facilitating ultrafast spectroscopic applications that are 1–2 orders of magnitude quicker than traditional dual-comb methods. This spatiotemporal encoding also eases the stringent conditions on various dual-comb laser parameters, such as repetition rates, coherence, and stability. Through carefully designed experiments, we demonstrate that our scan-less system can measure 3D profiles of microfabricated structures at a rate of 7 million pixels per second. Our method significantly enhances measurement speed while maintaining high precision, using a compact light source. This advancement has the potential for broad applications, including phase imaging, surface topography, distance ranging, and spectroscopy.
Highly sensitive ZnO/Ag/BaTiO3/MoS2 hybrid structure-based surface plasmon biosensor for the detection of mycobacterium tuberculosis bacteria
Authors: Emon Wahiduzzaman , Nayan Md. Faysal , Salehin Samius , Chaki Avik , Tuba Sadia , Ishtiak Khandakar Md.
Published: February 2024

This study presents a novel biosensor utilizing surface plasmon resonance (SPR) technology, comprising og zinc oxide (ZnO), silver (Ag), barium titanate (BaTiO3), and molybdenum disulfide (MoS2). The detection of mycobacterium tuberculosis bacteria was accomplished through the utilization of the hybrid structure. The transfer matrix method (TMM) and finite element method are employed to analyze the suggested surface plasmon resonance (SPR) structure. A comparative analysis has been conducted to evaluate the angular sensitivity between normal blood samples (NBS) and cells affected by tuberculosis (TB). The optimization of the performance of the surface plasmon resonance (SPR) structure involves adjusting the thickness of ZnO, Ag and BaTiO3 layer. The accurate measurement of the full width at half maximum (FWHM), detection accuracy (DA), quality factor and figure of merits (FOM) has also been conducted. The optimal angular sensitivity has been determined to be 10 nm for ZnO, 40 nm for Ag, 1.5 nm for BaTiO3, and one layer of MoS2 with a sensitivity of 525 deg./RIU. Additionally, this study compared the effects on sensitivity of two dimensional materials graphene, WS2 and MoS2. In contrast to the currently available biosensor utilizing surface plasmon resonance (SPR), the suggested structure exhibits higher angular sensitivity. Due to its improved sensitivity, the biosensor under consideration exhibits potential for detecting a wide range of biological analytes and organic compounds.
CD38 promotes hematopoietic stem cell dormancy
Authors: Ibneeva Liliia , Singh Sumeet Pal , Sinha Anupam , Eski Sema Elif , Wehner Rebekka , Rupp Luise , Kovtun Iryna , Pérez-Valencia Juan Alberto , Gerbaulet Alexander , Reinhardt Susanne , Wobus Manja , von Bonin Malte , Sancho Jaime , Lund Frances , Dahl Andreas , Schmitz Marc , Bornhäuser Martin , Chavakis Triantafyllos , Wielockx Ben , Grinenko Tatyana
Published: February 2024

A subpopulation of deeply quiescent, so-called dormant hematopoietic stem cells (dHSCs) resides at the top of the hematopoietic hierarchy and serves as a reserve pool for HSCs. The state of dormancy protects the HSC pool from exhaustion throughout life; however, excessive dormancy may prevent an efficient response to hematological stresses. Despite the significance of dHSCs, the mechanisms maintaining their dormancy remain elusive. Here, we identify CD38 as a novel and broadly applicable surface marker for the enrichment of murine dHSCs. We demonstrate that cyclic adenosine diphosphate ribose (cADPR), the product of CD38 cyclase activity, regulates the expression of the transcription factor c-Fos by increasing the release of Ca2+ from the endoplasmic reticulum (ER). Subsequently, we uncover that c-Fos induces the expression of the cell cycle inhibitor p57Kip2 to drive HSC dormancy. Moreover, we found that CD38 ecto-enzymatic activity at the neighboring CD38-positive cells can promote human HSC quiescence. Together, CD38/cADPR/Ca2+/c-Fos/p57Kip2 axis maintains HSC dormancy. Pharmacological manipulations of this pathway can provide new strategies to improve the success of stem cell transplantation and blood regeneration after injury or disease.
Identifying metabolic adaptations characteristic of cardiotoxicity using paired transcriptomics and metabolomics data integrated with a computational model of heart metabolism
Authors: Dougherty Bonnie V. , Moore Connor J. , Rawls Kristopher D. , Jenior Matthew L. , Chun Bryan , Nagdas Sarbajeet , Saucerman Jeffrey J. , Kolling Glynis L. , Wallqvist Anders , Papin Jason A.
Published: February 2024

Improvements in the diagnosis and treatment of cancer have revealed long-term side effects of chemotherapeutics, particularly cardiotoxicity. Here, we present paired transcriptomics and metabolomics data characterizingin vitrocardiotoxicity to three compounds: 5-fluorouracil, acetaminophen, and doxorubicin. Standard gene enrichment and metabolomics approaches identify some commonly affected pathways and metabolites but are not able to readily identify metabolic adaptations in response to cardiotoxicity. The paired data was integrated with a genome-scale metabolic network reconstruction of the heart to identify shifted metabolic functions, unique metabolic reactions, and changes in flux in metabolic reactions in response to these compounds. Using this approach, we confirm previously seen changes in the p53 pathway by doxorubicin and RNA synthesis by 5-fluorouracil, we find evidence for an increase in phospholipid metabolism in response to acetaminophen, and we see a shift in central carbon metabolism suggesting an increase in metabolic demand after treatment with doxorubicin and 5-fluorouracil.
Implementing a digital solution for patients with migraine—Developing a methodology for comparing digitally delivered treatment with conventional treatment: A study protocol
Authors: Niiberg-Pikksööt Triinu , Laas Kariina , Aluoja Anu , Braschinsky Mark
Published: February 2024

Migraine is one of the most frequent and expensive neurological disease in the world. Non-pharmacological and digitally administered treatment options have long been used in the treatment of chronic pain and mental illness. Digital solutions increase the patients’ possibilities of receiving evidence-based treatment even when conventional treatment options are limited. The main goal of the study is to assess the efficacy of interdisciplinary digital interventions compared to conventional treatment. The maximum number of participants in this multi-centre, open-label, prospective, randomized study is 600, divided into eight treatment groups. The participants will take part in either a conventional or a digital intervention, performing various tests and interdisciplinary tasks. The primary outcome is expected to be a reduction in the number of headache days. We also undertake to measure various other headache-related burdens as a secondary outcome. The sample size, digital interventions not conducted via video calls, the lack of human connection, limited intervention program, and the conducting of studies only in digitally sophisticated countries are all significant limitations. However, we believe that digitally mediated treatment options are at least as effective as traditional treatment options while also allowing for a significantly higher patient throughput. The future of chronic disease treatment is remote monitoring and high-quality digitally mediated interventions.The study is approved by the Ethics Committee of the University of Tartu for Human Research (Permission No. 315T-17, 10.08.2020) and is registered at ClinicalTrials.gov: NTC05458817 (14.07.2022).
The association of HIV-related stigma and psychosocial factors and HIV treatment outcomes among people living with HIV in the Volta region of Ghana: A mixed-methods study
Authors: Nutor Jerry John , Gyamerah Akua O. , Duah Henry Ofori , Asakitogum David Ayangba , Thompson Rachel G. A. , Alhassan Robert Kaba , Hamilton Alison
Published: February 2024

Stigma and discrimination have been identified as significant barriers to HIV treatment among people living with HIV (PLWH). HIV stigma affects decision to seek HIV testing and early treatment. Evidence shows that HIV stigma undermines antiretroviral therapy (ART) adherence by affecting the psychological process such as adjusting and coping with social support. In Ghana, stigma toward PLWH occurs in many ways including rejection by their communities and family members, ostracism, and refusal to engage in social interactions such as eating, sharing a bed, or shaking hands. Therefore. we examined PLWH’s experiences with different forms of HIV-related stigma and the impact on HIV treatment outcome in the Volta region of Ghana. We employed a convergent mixed-method approach consisting of a survey with 181 PLWH, four focus group discussions with 24 survey respondents, and in-depth interviews with six providers. We performed independent samples t-test, ANOVA, and chi-square test to test associations in bivariate analysis and analyzed qualitative data using thematic analysis. In all, 49% of survey respondents reported experiencing high internalized stigma, which was associated with high social support and depression (p<0.001). In qualitative interviews, anticipated stigma was the most salient concern of PLWH, followed by internalized and enacted stigma, which all negatively impacted HIV treatment and care. Stigma was experienced on multiple levels and affected psychosocial and treatment outcomes. Findings suggest urgent need for HIV-stigma reduction intervention among PLWH and their family, providers, and community members.
Who should decide how limited healthcare resources are prioritized? Autonomous technology as a compelling alternative to humans
Authors: Rolison Jonathan J. , Gooding Peter L. T. , Russo Riccardo , Buchanan Kathryn E.
Published: February 2024

Who should decide how limited resources are prioritized? We ask this question in a healthcare context where patients must be prioritized according to their need and where advances in autonomous artificial intelligence-based technology offer a compelling alternative to decisions by humans. Qualitative (Study 1a; N = 50) and quantitative (Study 1b; N = 800) analysis identified agency, emotional experience, bias-free, and error-free as four main qualities describing people’s perceptions of autonomous computer programs (ACPs) and human staff members (HSMs). Yet, the qualities were not perceived to be possessed equally by HSMs and ACPs. HSMs were endorsed with human qualities of agency and emotional experience, whereas ACPs were perceived as more capable than HSMs of bias- and error-free decision-making. Consequently, better than average (Study 2; N = 371), or relatively better (Studies 3, N = 181; & 4, N = 378), ACP performance, especially on qualities characteristic of ACPs, was sufficient to reverse preferences to favor ACPs over HSMs as the decision makers for how limited healthcare resources should be prioritized. Our findings serve a practical purpose regarding potential barriers to public acceptance of technology, and have theoretical value for our understanding of perceptions of autonomous technologies.
The organization-level and physician-level factors associated with primary care physicians’ confidence in pandemic response: A multilevel study in China
Authors: Chen Haiming , Xu Tiange , Mitchell Rebecca , Yang Huiyun , Zhou Zhongliang , Wei Xiaolin , Wang Wenhua
Published: February 2024

Primary care physicians (PCPs) suffered from heavy workloads and health problems during COVID-19 pandemics, and building their confidence in pandemic response has great potential to improve their well-being and work performance. We identified the organizational factors associated with their confidence in pandemic response and proposed potential management levers to guide primary care response for the pandemic. We conducted a cross-sectional survey with 224 PCPs working in 38 community health centers in China. Guided by self-efficacy theory, organization-level factors (organizational structure and organizational culture) and physician-level factors (job skill variety, perceived organizational support, work-family conflict, and professional fulfillment) were selected, and two-level ordinal logit models were built to examine their association with PCPs’ confidence in pandemic response. We found that hierarchical culture (OR = 3.51, P<0.05), perceived organizational support (OR = 2.36, P<0.05), job skill variety (OR = 1.86, P<0.05), and professional fulfillment (OR = 2.26, P<0.05) were positively associated with PCPs’ confidence in pandemic response. However, the influence of organization structure and work-family conflict seemed limited. The study not only increases our understanding of the influence of organizational context on PCPs’ pandemic response confidence, but also points out potential management levers for front-line primary care managers to enhance primary care pandemic response capacity.
Enhancing shipyard transportation efficiency through dynamic scheduling using digital twin technology
Authors: Sun Miaomiao , Liang Chengji , Chang Daofang
Published: February 2024

Uncertainties, such as road restrictions at shipyards and the irregular shape of blocks, pose challenges for transporter scheduling. Efficient scheduling of multiple transporters is critical to improving transportation efficiency. The digital twin (DT) technology offers numerous benefits, enabling interactions between the virtual and real worlds, real-time mapping, and dynamic performance evaluation. Based on DT technology, this study proposes a dynamic scheduling approach for cooperative transportation utilizing multiple transporters. The scheduling problem for multiple transporters is addressed and modeled in this study, considering factors such as block size and transporter loading. To solve this problem, a framework of DT-based multiple transporters system is established in a virtual environment. By inputting block information into this system, a solution is generated using transporter scheduling rules and interference detection methods. Experimental comparisons are conducted in this paper, exploring various scenarios with different number of tasks and the application of DT. The results demonstrate that the proposed approach effectively enhances transportation efficiency and improves ship construction efficiency. Hence, this study expands the application of DT technology in dynamic scheduling of transportation in shipyards and provides new ideas for shipbuilding company managers.
A renewable approach to electric vehicle charging through solar energy storage
Authors: Umair Muhammad , Hidayat Nabil M. , Sukri Ahmad Ahmad , Nik Ali Nik Hakimi , Mawardi M. I. Mohd , Abdullah Ezmin
Published: February 2024

Developing novel EV chargers is crucial for accelerating Electric Vehicle (EV) adoption, mitigating range anxiety, and fostering technological advancements that enhance charging efficiency and grid integration. These advancements address current challenges and contribute to a more sustainable and convenient future of electric mobility. This paper explores the performance dynamics of a solar-integrated charging system. It outlines a simulation study on harnessing solar energy as the primary Direct Current (DC) EV charging source. The approach incorporates an Energy Storage System (ESS) to address solar intermittencies and mitigate photovoltaic (PV) mismatch losses. Executed through MATLAB, the system integrates key components, including solar PV panels, the ESS, a DC charger, and an EV battery. The study finds that a change in solar irradiance from 400 W/m2 to 1000 W/m2 resulted in a substantial 47% increase in the output power of the solar PV system. Simultaneously, the ESS shows a 38% boost in output power under similar conditions, with the assessments conducted at a room temperature of 25°C. The results emphasize that optimal solar panel placement with higher irradiance levels is essential to leverage integrated solar energy EV chargers. The research also illuminates the positive correlation between elevated irradiance levels and the EV battery’s State of Charge (SOC). This correlation underscores the efficiency gains achievable through enhanced solar power absorption, facilitating more effective and expedited EV charging.
Microindentation of fresh soft biological tissue: A rapid tissue sectioning and mounting protocol
Authors: McCarthy Clíona M. , McKevitt Kevin L. , Connolly Sinéad A. , Andersson Isabel , Leahy Fiona C. , Egan Siobhan , Moloney Michael A. , Kavanagh Eamon G. , Peirce Colin , Cunnane Eoghan M. , McGourty Kieran D. , Walsh Michael T. , Mulvihill John J. E.
Published: February 2024

Microindentation of fresh biological tissues is necessary for the creation of 3D biomimetic models that accurately represent the native extracellular matrix microenvironment. However, tissue must first be precisely sectioned into slices. Challenges exist in the preparation of fresh tissue slices, as they can tear easily and must be processed rapidly in order to mitigate tissue degradation. In this study, we propose an optimised mounting condition for microindentation and demonstrate that embedding tissue in a mixture of 2.5% agarose and 1.5% gelatin is the most favourable method of tissue slice mounting for microindentation. This protocol allows for rapid processing of fresh biological tissue and is applicable to a variety of tissue types.
Changes in nonalcoholic fatty liver disease and M2BPGi due to lifestyle intervention in primary healthcare
Authors: Nah Eun-Hee , Choi Yong Jun , Cho Seon , Park Hyeran , Kim Suyoung , Kwon Eunjoo , Cho Han-Ik
Published: February 2024

Background

A healthy lifestyle is the most important method for managing nonalcoholic fatty liver disease (NAFLD). Mac-2-binding protein glycosylated isomer (M2BPGi) has been suggested as a biomarker for NAFLD. This study aimed to determine the efficacy of personalized lifestyle interventions on NAFLD remission.

Methods

This single-arm intervention study recruited participants with NAFLD who underwent health checkups at seven health-promotion centers in five South Korean cities. Fatty liver diagnosis was based on ultrasonography (US). The 109 individuals were recruited for personalized lifestyle interventions of hypocaloric diets and exercise. The participants attended the lifestyle intervention programs once per month for the first 3 months, and once every 3 months for the subsequent 6 months. In addition to sessions through center visits, phone-based intervention and self-monitoring at 4-, 5-, 7-, and 8-month were provided during the 9-month intervention period. And phone-based self-monitoring were also provided monthly during the 3-month follow-up period. The primary outcome was NAFLD remission at month 12 as measured on US and magnetic resonance elastography. The secondary outcomes were the changes in metabolic factors and M2BPGi.

Results

The 108 individuals (62 males and 46 females; age 51.1±12.4 years, mean±standard deviation) were finally analyzed after the 12month intervention. Body mass index, waist circumference (WC), blood pressure, blood lipids (total cholesterol, triglycerides, and HDL-C), and fasting blood sugar levels were improved relative to baseline (all P<0.05). Fatty liver at or above the moderate grade according to US was decreased at month 12 relative to baseline (67.6% vs 50.9%) (P = 0.002). M2BPGi levels decreased during the 12-month study period (P<0.001). M2BPGi levels were moderately correlated with hepatic fat fraction by magnetic resonance imaging (r = 0.33, P = 0.05). WC (OR = 0.82, 95% CI = 0.67–1.00, P = 0.05) and HDL-C (OR = 1.17, 95% CI = 1.03–1.32, P = 0.014) were associated with remission of fatty liver in the multivariate analysis.

Conclusion

The personalized lifestyle intervention was effective in improving fatty liver and metabolic factors, but not hepatic stiffness, in NAFLD.

Trial registration

ICTRP, cris.nih.go.kr (KCT0006380).
Evaluation and prediction of carbon emission from logistics at city scale for low-carbon development strategy
Authors: Chen Junyu , Zhu Yan , Yang Chuanming , Wang Huimin , Wang Ke
Published: February 2024

Low-carbon is a part of China’s efforts to pursue the national strategy of “carbon peaking and carbon neutrality.” Meanwhile, the path of low-carbon transformation of logistics has become a topic of global concern. This study constructs a technical framework of logistics carbon emissions (LCE), which is composed of carbon emission evaluation, carbon emission prediction and low-carbon strategy. All 13 prefecture-level cities in Jiangsu, China, are the application objects in empirical research. Then, the influence analysis of the LCE efficiency based on the panel Tobit model and the evolution of LCE under different scenarios are explored. The results show that: (ⅰ) during the study period (2013–2020), the LCE in Jiangsu showed an overall upward trend, with Xuzhou, Suzhou and Nanjing being the cities with the highest carbon emissions; (ⅱ) the static efficiency of LCE in Jiangsu is at a medium level, with fluctuations in Suzhou, Changzhou, Zhenjiang, Nantong, and Suqian caused by the technical change index; (ⅲ) economic level, industrial structure, fixed asset utilization rate, and ecological environment in Jiangsu are significantly positively correlated with LCE efficiency, while education popularization and energy intensity are negative; (ⅳ) LCE in Jiangsu has been drastically reduced in the low-carbon scenario compared to the baseline scenario. On the above basis, this study proposes suggestions for the low-carbon development strategies of logistics in Jiangsu.
Early full-day leg movement kinematics and swaddling patterns in infants in rural Guatemala: A pilot study
Authors: Oh Jinseok , Ordoñez Eva Leticia Tuiz , Velasquez Elisa , Mejía Marines , Grazioso Maria del Pilar , Rohloff Peter , Smith Beth A.
Published: February 2024

Background

Tools to accurately assess infants’ neurodevelopmental status very early in their lives are limited. Wearable sensors may provide a novel approach for very early assessment of infant neurodevelopmental status. This may be especially relevant in rural and low-resource global settings.

Methods

We conducted a longitudinal observational study and used wearable sensors to repeatedly measure the kinematic leg movement characteristics of 41 infants in rural Guatemala three times across full days between birth and 6 months of age. In addition, we collected sociodemographic data, growth data, and caregiver estimates of swaddling behaviors. We used visual analysis and multivariable linear mixed models to evaluate the associations between two leg movement kinematic variables (awake movement rate, peak acceleration per movement) and infant age, swaddling behaviors, growth, and other covariates.

Results

Multivariable mixed models of sensor data showed age-dependent increases in leg movement rates (2.16 [95% CI 0.80,3.52] movements/awake hour/day of life) and movement acceleration (5.04e-3 m/s2 [95% CI 3.79e-3, 6.27e-3]/day of life). Swaddling time as well as growth status, poverty status and multiple other clinical and sociodemographic variables had no impact on either movement variable.

Conclusions

Collecting wearable sensor data on young infants in a rural low-resource setting is feasible and can be used to monitor age-dependent changes in movement kinematics. Future work will evaluate associations between these kinematic variables from sensors and formal developmental measures, such as the Bayley Scales of Infant and Toddler Development.
Wellbeing Impact Study of High-Speed 2 (WISH2): Protocol for a mixed-methods examination of the impact of major transport infrastructure development on mental health and wellbeing
Authors: Morley Katherine I. , Hocking Lucy , Saunders Catherine L. , Bousfield Jennifer W. , Bostock Jennifer , Brimicombe James , Burgoine Thomas , Dawney Jessica , Hofman Joanna , Lee Daniel , Mackett Roger , Phillips William , Sussex Jon , Morris Stephen
Published: February 2024

Although research has demonstrated that transport infrastructure development can have positive and negative health-related impacts, most of this research has not considered mental health and wellbeing separately from physical health. There is also limited understanding of whether and how any effects might be experienced differently across population groups, whether this differs according to the stage of development (e.g. planning, construction), and how changes to planned infrastructure may affect mental health and wellbeing. This paper presents a protocol for the Wellbeing Impact Study of HS2 (WISH2), which seeks to address these questions using a high-speed rail development in the UK as an applied example. WISH2 is a 10-year, integrated, longitudinal, mixed-methods project using general practices (primary medical care providers in the UK) as an avenue for participant recruitment and for providing a geographically defined population for which aggregated data on mental health indicators are available. The research comprises: (i) a combined longitudinal and repeated cross-sectional cohort study involving multiple waves of survey data collection and data from medical records; (ii) longitudinal, semi-structured interviews and focus groups with residents and community stakeholders from exposed areas; (iii) analysis of administrative data aggregated at the general practice population level; and (iv) health economic analysis of mental health and wellbeing impacts. The study findings will support the development of strategies to reduce negative impacts and/or enhance positive mental health and wellbeing impacts of high-speed rail developments and other large-scale infrastructure projects.
Predicting successful draft outcome in Australian Rules football: Model sensitivity is superior in neural networks when compared to logistic regression
Authors: Jennings Jacob , Perrett Jay C. , Wundersitz Daniel W. , Sullivan Courtney J. , Cousins Stephen D. , Kingsley Michael I.
Published: February 2024

Using logistic regression and neural networks, the aim of this study was to compare model performance when predicting player draft outcome during the 2021 AFL National Draft. Physical testing, in-game movement and technical involvements were collected from 708 elite-junior Australian Rules football players during consecutive seasons. Predictive models were generated using data from 465 players (2017 to 2020). Data from 243 players were then used to prospectively predict the 2021 AFL National Draft. Logistic regression and neural network models were compared for specificity, sensitivity and accuracy using relative cut-off thresholds from 5% to 50%. Using factored and unfactored data, and a range of relative cut-off thresholds, neural networks accounted for 73% of the 40 best performing models across positional groups and data configurations. Neural networks correctly classified more drafted players than logistic regression in 88% of cases at draft rate (15%) and convergence threshold (35%). Using individual variables across thresholds, neural networks (specificity = 79 ± 13%, sensitivity = 61 ± 24%, accuracy = 76 ± 8%) were consistently superior to logistic regression (specificity = 73 ± 15%, sensitivity = 29 ± 14%, accuracy = 66 ± 11%). Where the goal is to identify talented players with draft potential, model sensitivity is paramount, and neural networks were superior to logistic regression.
Validation of global precipitation time series products against tree ring records and remotely sensed vegetation greenness
Authors: Manvailer Vinicius , Hamann Andreas
Published: February 2024

Global interpolated climate products are widely used in ecological research to investigate biosphere-climate interactions and to track ecological response to climate variability and climate change. In turn, biological data could also be used for an independent validation of one aspect of climate data quality. All else being equal, more variance explained in biological data identifies the better climate data product. Here, we compare seven global precipitation time series products, including gauge-based datasets (CRU-TS, UDEL-TS, GPCC), re-analysis products (ERA5, CHELSA), a satellite-based dataset (PERSIANN) and a multi-source product that draws on gauge, re-analysis, and satellite data (MSWEP). We focus on precipitation variables, because they are more difficult to interpolate than temperature, and show larger divergence among gridded data products. Our validation is based on 20 years of remotely sensed vegetation greenness (MODIS-EVI) and 120 years of tree ring records from the International Tree Ring Data Bank (ITRDB). The results for the 20-year EVI based validation shows that all gauge and re-analysis data products performed similarly, but were outperformed by the multi-source MSWEP product, especially in regions with low weather station coverage, such as Africa. For analyzing long 120-year time-series, UDEL-TS showed superior performance prior to the 1940s, with especially large margins for northern Asia and the Himalayas region. For other regions, CRU-TS and GPCC could be recommended. We provide maps that can guide the best regional choice of climate product for research involving time series of biological response to historic climate variability and climate change.
Analysis and prediction of compressive and split-tensile strength of secondary steel fiber reinforced concrete based on RBF fuzzy neural network model
Authors: Ling Song , Chengbin Du , Yafeng Yao , Yongheng Li
Published: February 2024

Accurate analysis of the strength of steel-fiber-reinforced concrete (SFRC) is important for ensuring construction quality and safety. Cube compression and splitting tensile tests of steel fiber with different varieties, lengths, and dosages were performed, and the effects of different varieties, lengths, and dosages on the compressive and splitting properties of secondary concrete were obtained. It was determined that the compression and splitting strengths of concrete could be effectively improved by the addition of end-hooked and milled steel fibers. The compressive and splitting strengths of concrete can be enhanced by increasing the fiber length and content. However, concrete also exhibits obvious uncertainty owing to the comprehensive influence of steel fiber variety, fiber length, and fiber content. In order to solve this engineering uncertainty, the traditional RBF neural network is improved by using central value and weight learning strategy especially. On this basis, the RBF fuzzy neural network prediction model of the strength of secondary steel fiber-reinforced concrete was innovatively established with the type, length and content of steel fiber as input information and the compressive strength and splitting tensile strength as output information. In order to further verify the engineering reliability of the prediction model, the compressive strength and splitting tensile strength of steel fiber reinforced concrete with rock anchor beams are predicted by the prediction model. The results show that the convergence rate of the prediction model is increased by 15%, and the error between the predicted value and the measured value is less than 10%, which is more efficient and accurate than the traditional one. Additionally, the improved model algorithm is efficient and reasonable, providing technical support for the safe construction of large-volume steel fiber concrete projects, such as rock anchor beams. The fuzzy random method can also be applied to similar engineering fields.
Machine learning approaches to enhance diagnosis and staging of patients with MASLD using routinely available clinical information
Authors: McTeer Matthew , Applegate Douglas , Mesenbrink Peter , Ratziu Vlad , Schattenberg Jörn M. , Bugianesi Elisabetta , Geier Andreas , Romero Gomez Manuel , Dufour Jean-Francois , Ekstedt Mattias , Francque Sven , Yki-Jarvinen Hannele , Allison Michael , Valenti Luca , Miele Luca , Pavlides Michael , Cobbold Jeremy , Papatheodoridis Georgios , Holleboom Adriaan G. , Tiniakos Dina , Brass Clifford , Anstee Quentin M. , Missier Paolo ,   on behalf of the LITMUS Consortium investigators
Published: February 2024

Aims

Metabolic dysfunction Associated Steatotic Liver Disease (MASLD) outcomes such as MASH (metabolic dysfunction associated steatohepatitis), fibrosis and cirrhosis are ordinarily determined by resource-intensive and invasive biopsies. We aim to show that routine clinical tests offer sufficient information to predict these endpoints.

Methods

Using the LITMUS Metacohort derived from the European NAFLD Registry, the largest MASLD dataset in Europe, we create three combinations of features which vary in degree of procurement including a 19-variable feature set that are attained through a routine clinical appointment or blood test. This data was used to train predictive models using supervised machine learning (ML) algorithm XGBoost, alongside missing imputation technique MICE and class balancing algorithm SMOTE. Shapley Additive exPlanations (SHAP) were added to determine relative importance for each clinical variable.

Results

Analysing nine biopsy-derived MASLD outcomes of cohort size ranging between 5385 and 6673 subjects, we were able to predict individuals at training set AUCs ranging from 0.719-0.994, including classifying individuals who are At-Risk MASH at an AUC = 0.899. Using two further feature combinations of 26-variables and 35-variables, which included composite scores known to be good indicators for MASLD endpoints and advanced specialist tests, we found predictive performance did not sufficiently improve. We are also able to present local and global explanations for each ML model, offering clinicians interpretability without the expense of worsening predictive performance.

Conclusions

This study developed a series of ML models of accuracy ranging from 71.9—99.4% using only easily extractable and readily available information in predicting MASLD outcomes which are usually determined through highly invasive means.
Longitudinal association between e-cigarette use and respiratory symptoms among US adults: Findings from the Population Assessment of Tobacco and Health Study Waves 4–5
Authors: Karey Emma , Xu Shu , He Pan , Niaura Raymond S. , Cleland Charles M. , Stevens Elizabeth R. , Sherman Scott E. , El-Shahawy Omar , Cantrell Jennifer , Jiang Nan
Published: February 2024

Background

We assessed longitudinal effects of e-cigarette use on respiratory symptoms in a nationally representative sample of US adults by combustible tobacco smoking status.

Methods

We analyzed Waves 4–5 public-use data from the Population Assessment of Tobacco and Health Study. Study sample included adult respondents who reported no diagnosis of respiratory diseases at Wave 4, and completed Waves 4–5 surveys with no missing data on analytic variables (N = 15,291). Outcome was a validated index of functionally important respiratory symptoms based on 7 wheezing/cough questions (range 0–9). An index score of ≥2 was defined as having important respiratory symptoms. Weighted lagged logistic regression models were performed to examine the association between e-cigarette use status at Wave 4 (former/current vs. never use) and important respiratory symptoms at Wave 5 by combustible tobacco smoking status (i.e., never/former/current smokers), adjusting for Wave 4 respiratory symptom index, sociodemographic characteristics, secondhand smoke exposure, body mass index, and chronic disease.

Results

Among current combustible tobacco smokers, e-cigarette use was associated with increased odds of reporting important respiratory symptoms (former e-cigarette use: adjusted odds ratio [AOR] = 1.39, 95% confidence interval [CI]: 1.07–1.81; current e-cigarette use: AOR = 1.55, 95% CI: 1.17–2.06). Among former combustible tobacco smokers, former e-cigarette use (AOR = 1.51, 95% CI: 1.06–2.15)—but not current e-cigarette use (AOR = 1.59, 95% CI: 0.91–2.78)—was associated with increased odds of important respiratory symptoms. Among never combustible tobacco smokers, no significant association was detected between e-cigarette use and important respiratory symptoms (former e-cigarette use: AOR = 1.62, 95% CI: 0.76–3.46; current e-cigarette use: AOR = 0.82, 95% CI: 0.27–2.56).

Conclusions

The association between e-cigarette use and respiratory symptoms varied by combustible tobacco smoking status. Current combustible tobacco smokers who use e-cigarettes have an elevated risk of respiratory impairments.
The timing of HIV-1 infection of cells that persist on therapy is not strongly influenced by replication competency or cellular tropism of the provirus
Authors: Joseph Sarah B. , Abrahams Melissa-Rose , Moeser Matthew , Tyers Lynn , Archin Nancie M. , Council Olivia D. , Sondgeroth Amy , Spielvogel Ean , Emery Ann , Zhou Shuntai , Doolabh Deelan , Ismail Sherazaan D. , Karim Salim Abdool , Margolis David M. , Pond Sergei Kosakovsky , Garrett Nigel , Swanstrom Ronald , Williamson Carolyn
Published: February 2024

People with HIV-1 (PWH) on antiretroviral therapy (ART) can maintain undetectable virus levels, but a small pool of infected cells persists. This pool is largely comprised of defective proviruses that may produce HIV-1 proteins but are incapable of making infectious virus, with only a fraction (~10%) of these cells harboring intact viral genomes, some of which produce infectious virus following ex vivo stimulation (i.e. inducible intact proviruses). A majority of the inducible proviruses that persist on ART are formed near the time of therapy initiation. Here we compared proviral DNA (assessed here as 3’ half genomes amplified from total cellular DNA) and inducible replication competent viruses in the pool of infected cells that persists during ART to determine if the original infection of these cells occurred at comparable times prior to therapy initiation. Overall, the average percent of proviruses that formed late (i.e. around the time of ART initiation, 60%) did not differ from the average percent of replication competent inducible viruses that formed late (69%), and this was also true for proviral DNA that was hypermutated (57%). Further, there was no evidence that entry into the long-lived infected cell pool was impeded by the ability to use the CXCR4 coreceptor, nor was the formation of long-lived infected cells enhanced during primary infection, when viral loads are exceptionally high. We observed that infection of cells that transitioned to be long-lived was enhanced among people with a lower nadir CD4+ T cell count. Together these data suggest that the timing of infection of cells that become long-lived is impacted more by biological processes associated with immunodeficiency before ART than the replication competency and/or cellular tropism of the infecting virus or the intactness of the provirus. Further research is needed to determine the mechanistic link between immunodeficiency and the timing of infected cells transitioning to the long-lived pool, particularly whether this is due to differences in infected cell clearance, turnover rates and/or homeostatic proliferation before and after ART.