bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimates of the Decarbonization Potential of Alternative Fuels for Shipping as a Function of Vessel Type, Cargo, and Voyage
Authors: Law Li Chin , Mastorakos Epaminondas , Evans Stephen
Published: October 2022

Fuel transition can decarbonize shipping and help meet IMO 2050 goals. In this paper, HFO with CCS, LNG with CCS, bio-methanol, biodiesel, hydrogen, ammonia, and electricity were studied using empirical ship design models from a fleet-level perspective and at the Tank-To-Wake level, to assist operators, technology developers, and policy makers. The cargo attainment rate CAR (i.e., cargo that must be displaced due to the low-C propulsion system), the ES (i.e., TTW energy needed per ton*n.m.), the CS (economic cost per ton*n.m.), and the carbon intensity index CII (gCO2 per ton*n.m.) were calculated so that the potential of the various alternatives can be compared quantitatively as a function of different criteria. The sensitivity of CAR towards ship type, fuel type, cargo type, and voyage distance were investigated. All ship types had similar CAR estimates, which implies that considerations concerning fuel transition apply equally to all ships (cargo, containership, tankers). Cargo type was the most sensitive factor that made a ship either weight or volume critical, indirectly impacting on the CAR of different fuels; for example, a hydrogen ship is weight-critical and has 2.3% higher CAR than the reference HFO ship at 20,000 nm. Voyage distance and fuel type could result in up to 48.51% and 11.75% of CAR reduction. In addition to CAR, the ES, CS, and CII for a typical mission were calculated and it was found that HFO and LNG with CCS gave about 20% higher ES and CS than HFO, and biodiesel had twice the cost, while ammonia, methanol, and hydrogen had 3–4 times the CS of HFO and electricity about 20 times, suggesting that decarbonisation of the world’s fleet will come at a large cost. As an example of including all factors in an effort to create a normalized scoring system, an equal weight was allocated to each index (CAR, ES, CS, and CII). Biodiesel achieved the highest score (80%) and was identified as the alternative with the highest potential for a deep-seagoing containership, followed by ammonia, hydrogen, bio-methanol, and CCS. Electricity has the lowest normalized score of 33%. A total of 100% CAR is achievable by all alternative fuels, but with compromises in voyage distance or with refuelling. For example, a battery containership carrying an equal amount of cargo as an HFO-fuelled containership can only complete 13% of the voyage distance or needs refuelling seven times to complete 10,000 n.m. The results can guide decarbonization strategies at the fleet level and can help optimise emissions as a function of specific missions.
A Review on Technical Challenges and Possibilities on Energy Efficient Retrofit Measures in Heritage Buildings
Authors: Nair Gireesh , Verde Leo , Olofsson Thomas
Published: October 2022

For heritage buildings, energy-efficient retrofitting cannot be applied with the same range of possibilities as with existing buildings. Applying such improvements to heritage buildings can be challenging due to their historic and/or cultural significance and non-standard construction methods. This paper reviews the technical challenges and potential of applying energy efficient retrofit elements in heritage buildings. The retrofitting measures reviewed are draught-proofing, windows, insulation, ventilation, heating, solar photovoltaics and phase change materials. It is possible to significantly reduce energy use in heritage buildings with such retrofits. However, there is no universal way to apply energy-efficient retrofitting in heritage buildings, which is apparent in the literature, where case studies are prevalent.
Study on IMC-PID Control of Once-Through Steam Generator for Small Fast Reactor
Authors: Xiao Kai , Li Yiliang , Yang Pengcheng , Zhang Ying , Zhao Yang , Pu Xiaofei
Published: October 2022

The simplification of simulation inevitably leads to model mismatch. In this paper, a once-through steam generator (OTSG) for a small lead bismuth fast reactor (SLBFR) is established and verified, and the OTSG model is simplified by three different methods. Based on the simplified OTSG model, IMC and IMC-PID controllers are designed to verify the sensitivity of the controller to model mismatch. The results show that the sensitivity of the controller to model mismatch is related to the filter parameters. With the increase in λ, the IMC-PID controller becomes insensitive to model mismatch caused by model linearization, non-minimum phase characteristics, noise and time delay. However, the adaptability to model mismatch sacrifices the sensitivity of the system. When λ is too large, the inertia of the controller is too large, resulting in the deterioration of the fast power regulation. Through the research of this paper, the time domain response approximation method is recommended for OTSG model simplification, and λ is recommended to be between 5 and 10 for feedwater IMC-PID controller.
Supply Chain Readiness for Solar PV Expansion in Saudi Arabia
Authors: Alghamdi Nasser , Bahaj AbuBakr S. , James Patrick
Published: October 2022

The Kingdom of Saudi Arabia (KSA) has an ambitious plan to install 40 GW of solar photovoltaic (PV) capacity via large scale projects (majority of which are >100 MW) across the country by 2030. These projects are required to achieve a threshold percentage of the overall project cost as in country expenditure, termed “local content”. This threshold will rise to 40–45% by 2028, ensuring solar projects do not simply become investment opportunities for overseas companies but deliver jobs and skills development within the Kingdom. Local content is assessed across all aspects of a PV system—module, inverter, structure, etc. Typically, the PV module cost can range between ~34% to ~44% of the overall system cost. However, 56% of this module cost represents the manufacture of the solar cells. To maximise local content, the opportunity for KSA lies in module fabrication of imported solar cells. This study assesses the capacity readiness of the KSA to meet this opportunity in relation to its 2030 targets and the current policy landscape. The recently completed 300 MW Sakaka project had a local content of >30% based on the developers’ website and >35% based on our private communication. Our results indicate that this would rise by 19% for a project like Sakaka if all modules were fabricated in-country rather than being imported. The work also projected a shortfall in terms of in-country module fabrication capacity with clear implications to local content targets. The results show a shortfall in the range of 35% to 75% by 2030 depending on the adopted KSA energy policies and government support. KSA is seen to have good capacity in other PV components such as steel and float glass. In-country distribution of imported solar cells to module fabrication centres and subsequent distribution to PV farm sites has also been assessed. Our analyses indicate that a two-location solution reduces cost with new module fabrication capacity sited near Jeddah and Riyadh, minimising storage times, delivery time to site and distribution waiting times.
Feasibility Study on the Influence of Data Partition Strategies on Ensemble Deep Learning: The Case of Forecasting Power Generation in South Korea
Authors: Chuluunsaikhan Tserenpurev , Kim Jeong-Hun , Shin Yoonsung , Choi Sanghyun , Nasridinov Aziz
Published: October 2022

Ensemble deep learning methods have demonstrated significant improvements in forecasting the solar panel power generation using historical time-series data. Although many studies have used ensemble deep learning methods with various data partitioning strategies, most have only focused on improving the predictive methods by associating several different models or combining hyperparameters and interactions. In this study, we contend that we can enhance the precision of power generation forecasting by identifying a suitable data partition strategy and establishing the ideal number of partitions and subset sizes. Thus, we propose a feasibility study of the influence of data partition strategies on ensemble deep learning. We selected five time-series data partitioning strategies—window, shuffle, pyramid, vertical, and seasonal—that allow us to identify different characteristics and features in the time-series data. We conducted various experiments on two sources of solar panel datasets collected in Seoul and Gyeongju, South Korea. Additionally, LSTM-based bagging ensemble models were applied to combine the advantages of several single LSTM models. The experimental results reveal that the data partition strategies positively influence the forecasting of power generation. Specifically, the results demonstrate that ensemble models with data partition strategies outperform single LSTM models by approximately 4–11% in terms of the coefficient of determination (R2) score.
Data-Driven Proxy Models for Improving Advanced Well Completion Design under Uncertainty
Authors: Moradi Ali , Tavakolifaradonbe Javad , Moldestad Britt M. E.
Published: October 2022

In order to improve the design of advanced wells, the performance of such wells needs to be carefully assessed by taking the reservoir uncertainties into account. This research aimed to develop data-driven proxy models for the simulation and assessment of oil recovery through advanced wells under uncertainty. An artificial neural network (ANN) was employed to create accurate and computationally efficient proxy models as an alternative to physics-based integrated well–reservoir models created by the Eclipse® reservoir simulator. The simulation speed and accuracy of the data-driven proxy models compared to physic-driven models were then evaluated. The evaluation showed that while the developed proxy models are 350 times faster, they can predict the production of oil and unwanted fluids through advanced wells with a mean error of less than 1% and 4%, respectively. As a result, the data-driven proxy models can be considered an efficient tool for uncertainty analysis where several simulations need to be performed to cover all possible scenarios. In this study, the developed proxy models were applied for uncertainty quantification of oil recovery from advanced wells completed with different types of downhole flow control devices (FCDs). According to the obtained results, compared to other types of well completion design, advanced wells completed with autonomous inflow control valve (AICV) technology have the best performance in limiting the production of unwanted fluids and are able to reduce the associated risk by 91%.
Antibacterial Activity and Mechanism of Linalool against Shigella sonnei and Its Application in Lettuce
Authors: Su Ruiying , Guo Peng , Zhang Ziruo , Wang Jingzi , Guo Xinyi , Guo Du , Wang Yutang , Lü Xin , Shi Chao
Published: October 2022

Shigella sonnei (S. sonnei) infection accounted for approximately 75% of annual outbreaks of shigellosis, with the vast majority of outbreaks due to the consumption of contaminated foods (e.g., fresh vegetables, potato salad, fish, beef, etc.). Thus, we investigated the antibacterial effect and mechanism of linalool on S. sonnei and evaluated the effect of linalool on the sensory quality of lettuce. The minimum inhibitory concentration (MIC) of linalool against S. sonnei ATCC 25931 was 1.5 mg/mL. S. sonnei was treated with linalool at 1× MIC for 30 min and the amount of bacteria was decreased below the detection limit (1 CFU/mL) in phosphate-buffered saline (PBS) and Luria-Bertani (LB) medium. The bacterial content of the lettuce surface was reduced by 4.33 log CFU/cm2 after soaking with linalool at 2× MIC. Treatment with linalool led to increased intracellular reactive oxygen species (ROS) levels, decreased intracellular adenosine-triphosphate (ATP) content, increased membrane lipid oxidation, damaged cell membrane integrity, and hyperpolarized cell membrane potential in S. sonnei. The application of linalool to lettuce had no effect on the color of lettuce compared to the control. The sensory evaluation results showed that linalool had an acceptable effect on the sensory quality of lettuce. These findings indicate that linalool played an antibacterial effect against S. sonnei and had potential as a natural antimicrobial for the inhibition of this foodborne pathogen.
Identification and Application of Two Promising Peptide Ligands for the Immunodetection of Imidacloprid Residue
Authors: You Tianyang , Ding Yuan , Huang Yue , Lu Yang , Wang Minghua , Hua Xiude
Published: October 2022

As the most widely used neonicotinoid insecticide, it is of great significance to explore the immunoreagents and immunoassays for imidacloprid (IMI) residue. In immunoassays, specific peptide ligands, such as peptidomimetic and anti-immunocomplex peptides, are regarded as promising substitutes for chemical haptens. In the present work, we identified thirty sequences of peptidomimetics and two sequences of anti-immunocomplex peptides for IMI from three phage pVIII display cyclic peptide libraries, in which the anti-immunocomplex peptides are the first reported noncompetitive reagents for IMI. The peptidomimetic 1-9-H and anti-immunocomplex peptide 2-1-H that showed the best sensitivity were utilized to develop competitive and noncompetitive phage enzyme-linked immunosorbent assays (P-ELISAs), with a half inhibition concentration of 0.55 ng/mL for competitive P-ELISA and a half-saturation concentration of 0.35 ng/mL for noncompetitive P-ELISA. The anti-immunocomplex peptide was demonstrated to greatly improve the specificity compared with competitive P-ELISA. In addition, the accuracy of proposed P-ELISAs was confirmed by recovery analysis and HPLC verification in agricultural and environmental samples. These results show that the peptide ligands identified from phage display library can replace chemical haptens in the immunoassays of IMI with the satisfactory performance.
Active Packaging Films Made by Complex Coacervation of Tragacanth Gum and Gelatin Loaded with Curcumin; Characterization and Antioxidant Activity
Authors: Amani Fateme , Rezaei Atefe , Akbari Hajar , Dima Cristian , Jafari Seid Mahdi
Published: October 2022

The development of biopolymer-based green packaging films has gained remarkable attention in recent years. In this study, curcumin active films were prepared using different proportions of gelatin (GE) and a soluble fraction of tragacanth gum (SFTG) (1GE:1SFTG and 2GE:1SFTG) by complex coacervation. The various ratios of used biopolymers did not significantly impact the mechanical properties, thickness, and WVP of final films. However, biopolymers’ ratio impacted the moisture content, water solubility, swelling ratio, and release rate. Blending curcumin with biopolymers caused a reduction in tensile strength (from 1.74 MPa to 0.62 MPa for film containing 1GE:1SFTG and from 1.77 MPa to 0.17 MPa for film containing 2GE:1SFTG) and proliferation in elongation at break (from 81.48% to 122.00% for film containing 1GE:1SFTG and from 98.87% to 109.58% MPa for film containing 2GE:1SFTG). Moisture content and water solubility of films experienced a decrease after the addition of curcumin. Antioxidant activity of curcumin-loaded films was almost five times higher than neat film samples. Furthermore, the interreaction between the carboxylic group of SFTG and amide I of GE formed an amide linkage and was proven by FTIR analysis. TGA showed a drop in the thermal stability of film samples compared to the main ingredients. In general, the complex coacervate of SFTG and GE has the advantage of developing eco-friendly and low-cost packaging film in the food industry, especially for the protection of fatty foods.
Physicochemical Properties and Bacterial Community Profiling of Optimal Mahewu (A Fermented Food Product) Prepared Using White and Yellow Maize with Different Inocula
Authors: Daji Grace Abosede , Green Ezekiel , Abrahams Adrian , Oyedeji Ajibola Bamikole , Masenya Kedibone , Kondiah Kulsum , Adebo Oluwafemi Ayodeji
Published: October 2022

Mahewu is a fermented food product from maize, commonly consumed in Southern Africa. This study investigated the effect of optimizing fermentation (time and temperature) and boiling time of white maize (WM) and yellow maize (YM) mahewu, with the use of the Box–Behnken-response surface methodology (RSM). Fermentation time and temperature as well as boiling time were optimized and pH, total titratable acidity (TTA) and total soluble solids (TSS) determined. Results obtained showed that the processing conditions significantly (p ≤ 0.05) influenced the physicochemical properties. pH values of the mahewu samples ranged between 3.48–5.28 and 3.50–4.20 for YM mahewu and WM mahewu samples, respectively. Reduction in pH values after fermentation coincided with an increase in TTA as well as changes in the TSS values. Using the numerical multi-response optimisation of three investigated responses the optimal fermentation conditions were observed to be 25 °C for 54 h and a boiling time of 19 min for white maize mahewu and 29 °C for 72 h and a boiling time of 13 min for yellow maize mahewu. Thereafter white and yellow maize mahewu were prepared with the optimized conditions using different inocula (sorghum malt flour, wheat flour, millet malt flour or maize malt flour) and the pH, TTA and TSS of the derived mahewu samples determined. Additionally, amplicon sequencing of the 16S rRNA gene was used to characterise the relative abundance of bacterial genera in optimized mahewu samples, malted grains as well as flour samples. Major bacterial genera observed in the mahewu samples included Paenibacillus, Stenotrophomonas, Weissella, Pseudomonas, Lactococcus, Enterococcus, Lactobacillus, Bacillus, Massilia, Clostridium sensu stricto 1, Streptococcus, Staphylococcus, Sanguibacter, Roseococcus, Leuconostoc, Cutibacterium, Brevibacterium, Blastococcus, Sphingomonas and Pediococcus, with variations noted for YM mahewu and WM mahewu. As a result, the variations in physicochemical properties are due to differences in maize type and modification in processing conditions. This study also discovered the existence of variety of bacterial that can be isolated for controlled fermentation of mahewu.
A Novel Identified Necroptosis-Related Risk Signature for Prognosis Prediction and Immune Infiltration Indication in Acute Myeloid Leukemia Patients
Authors: Sun Yong , Wang Ruiheng , Xie Shufeng , Wang Yuanli , Liu Han
Published: October 2022

AML ranks second in the most common types of leukemia diagnosed in both adults and children. Necroptosis is a programmed inflammatory cell death form reported to be an innate immune effector against microbial and viral pathogens and recently has been found to play an eventful role in the oncogenesis, progression, and metastasis of cancer. This study is designed to explore the potential value of necroptosis in predicting prognostic and optimizing the current therapeutic strategies for AML patients. We collected transcriptome and clinical data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases and selected necroptosis-related genes with both differential significance and prognostic value. Six genes (YBX3, ZBP1, CDC37, ALK, BRAF, and BNIP3) were incorporated to generate a risk model with the implementation of multivariate Cox regression. The signature was proven to be an independent prognostic predictor in both training and validation cohorts with hazard ratios (HRs) of 1.51 (95% CI: 1.33–1.72) and 1.57 (95% CI: 1.16–2.12), respectively. Moreover, receiver operating characteristic (ROC) curve was utilized to quantify the predictive performance of the signature and satisfying results were shown with the area under the curve (AUC) up to 0.801 (3-year) and 0.619 (3-year), respectively. In addition, the subtyping of AML patients based on the risk signature demonstrated a significant correlation with the immune cell infiltration and response to immunotherapy. Finally, we incorporated risk signature with the classical clinical features to establish a nomogram which may contribute to the improvement of clinical management. To conclude, this study identified a necroptosis-related signature as a novel biomarker to improve the risk stratification, to inform the immunotherapy efficacy, and to indicate the therapeutic option of targeted therapy.
A Comprehensive Analysis of KRT19 Combined with Immune Infiltration to Predict Breast Cancer Prognosis
Authors: Mi Lusi , Liang Nan , Sun Hui
Published: October 2022

To date, no study has been conducted to explore the mechanism of KRT19 and the correlation between the expression of KRT19 and immune infiltration in breast cancer (BRCA). TCGA, TIMER2.0, UALCAN, and other databases were used to analyze the expression, prognostic roles, epigenetic variants, and possible oncogenic mechanisms of KRT19 in BRCA. As a result, KRT19 showed higher expression compared with the normal tissues in BRCA. In addition, the epigenetic variation in KRT19, including gene alteration, mutation type and sites, DNA methylation, RNA modification, and phosphorylation, showed diversity in BRCA. Further mechanistic exploration suggested that the IL-17 signaling pathway and estrogen response might play essential roles in the regulation of KRT19. Moreover, KRT19 has different regulatory biological functions in BRCA. More importantly, the expression of KRT19 was closely related to immune infiltration and combining the two could effectively predict overall survival. Finally, a nomogram based on genes associated with cancer-immunity cycle signatures, which could predict progress free interval, was constructed and evaluated successfully. In conclusion, KRT19 may play a role in the occurrence and development of BRCA through the IL-17 signaling pathway. Meanwhile, KRT19 combined with immune infiltration can evaluate the prognosis of BRCA patients.
Theoretical Investigation Applied to Scattering Water Waves by Rectangular Submerged Obstacles/and Submarine Trenches
Authors: Loukili Mohammed , Dutykh Denys , Pincemin Sandrine , Kotrasova Kamila , Abcha Nizar
Published: October 2022

A simple analytical model is presented in this work to investigate reflection coefficients due to the interactions of waves with rectangular submerged obstacles/and submarine trenches. Our intention in this work is to present a simple analytical model to simulate and study water-wave scattering by evaluating reflection coefficients. Further, our challenge is to present an analytical model that can easily investigate simultaneously the effects of rectangular submerged obstacles/and submarine trenches on wave scattering. Furthermore, reflection coefficients are investigated for different immersion ratios and relative lengths simultaneously for submarine trenches/and rectangular submerged obstacles. In addition, to ensure the validity of the presented model, our results are well compared with those of the literature. Finally, a comparison of reflection coefficients associated with the interactions of waves with rectangular submerged obstacles/and submarine trenches are presented to investigate the most efficient breakwater, and to highlight the importance of the presented model.
Enhanced Patient-Centricity: How the Biopharmaceutical Industry Is Optimizing Patient Care through AI/ML/DL
Authors: Zou Kelly H. , Li Jim Z.
Published: October 2022

Technologies utilizing cutting-edge methodologies, including artificial intelligence (AI), machine learning (ML) and deep learning (DL), present powerful opportunities to help evaluate, predict, and improve patient outcomes by drawing insights from real-world data (RWD) generated during medical care. They played a role during and following the Coronavirus Disease 2019 (COVID-19) pandemic by helping protect healthcare providers, prioritize care for vulnerable populations, predict disease trends, and find optimal therapies. Potential applications across therapeutic areas include diagnosis, disease management and patient journey mapping. Use of fit-for-purpose datasets for ML models is seeing growth and may potentially help additional enterprises develop AI strategies. However, biopharmaceutical companies often face specific challenges, including multi-setting data, system interoperability, data governance, and patient privacy requirements. There remains a need for evolving regulatory frameworks, operating models, and data governance to enable further developments and additional research. We explore recent literature and examine the hurdles faced by researchers in the biopharmaceutical industry to fully realize the promise of AI/ML/DL for patient-centric purposes.
Effects of the Government Response and Community Mobility on the COVID-19 Pandemic in Southeast Asia
Authors: Widyasari Vita , Lee Chiachi Bonnie , Lin Kuan-Han , Husnayain Atina , Su Emily Chia-Yu , Wang Jiun-Yi
Published: October 2022

Preventive policies and mobility restrictions are believed to work for inhibiting the growth rate of COVID-19 cases; however, their effects have rarely been assessed and quantified in Southeast Asia. We aimed to examine the effects of the government responses and community mobility on the COVID-19 pandemic in Southeast Asian countries. The study extracted data from Coronavirus Government Response Tracker, COVID-19 Community Mobility Report, and Our World in Data between 1 March and 31 December 2020. The government responses were measured by containment, health, and economic support index. The community mobility took data on movement trends at six locations. Partial least square structural equation modeling was used for bi-monthly analyses in each country. Results show that the community mobility generally followed government responses, especially the containment index. The path coefficients of government responses to community mobility ranged from −0.785 to −0.976 in March to April and −0.670 to −0.932 in May to June. The path coefficients of community mobility to the COVID-19 cases ranged from −0.058 to −0.937 in March to April and from −0.059 to −0.640 in September to October. It suggests that the first few months since the mobility restriction implemented is the optimal time to control the pandemic.
Late Presentation of Dyskeratosis Congenita: Germline Predisposition to Adult-Onset Secondary Acute Myeloid Leukemia
Authors: Ramos Harry , Aly Mai Mostafa , Balasubramanian Suresh Kumar
Published: October 2022

Classic dyskeratosis congenita is a hereditary disease where the majority of patients present with bone marrow failure and mucocutaneous changes: mainly skin pigmentation, nail dystrophy, oral premalignant leukoplakia, in addition to increased risk for malignancies. A 63-year-old man with a long history of untreated chronic pulmonary disease, a smoker in the past, presented initially with pancytopenia and a clinical diagnosis of myelodysplastic syndrome with excess blasts returned a month later with leukocytosis (WBC 215.9 × 106/μL) and diagnosed with acute myeloid leukemia (AML) with deletion of chromosome 7 and FLT3-TKD mutation. The patient’s mother and sister died in their 6th decade from rapidly progressing fulminant pulmonary fibrosis. He had abnormal skin pigmentation and oral leukoplakia on presentation. He was induced with 7 + 3 chemotherapy and started on midostaurin but experienced prolonged cytopenias, complicated by hypoxic acute on chronic respiratory failure requiring intubation and mechanical ventilation. D + 28 and D + 36 bone marrow examination showed trilineage hypoplasia but no blasts, though the D + 28 bone marrow biopsy revealed one metaphase with del (7) that was cleared on D + 35. The constellation of clinical features and strong family history along with del 7 and FLT3-TKD AML with preceding MDS highly suggests a germline predisposition state dyskeratosis congenita. Germline predispositions are often underrecognized as delayed onset conditions leading to AML and may have treatment and preventative implications especially genetic counseling for blood-related family members.
Quantitative Precipitation Estimation (QPE) Rainfall from Meteorology Radar over Chi Basin
Authors: Areerachakul Nathaporn , Prongnuch Sethakarn , Longsomboon Peeranat , Kandasamy Jaya
Published: October 2022

This study of the Quantitative Estimation Precipitation (QEP) of rainfall, detected by two Meteorology Radars over Chi Basin, North-east Thailand, used data from the Thai Meteorological Department (TMD). The rainfall data from 129 rain gauge stations in the Chi Basin area, covering a period of two years, was also used. The study methodology consists of: firstly, deriving the QPE between radar and rainfall based on meteorological observations using the Marshall Palmer Stratiform, the Summer Deep Convection, and Regression Model and calibrating with rain gauge station data; secondly, Bias Correction using statistical method; thirdly, determining spatial variation using three methods, namely Kriging, Inverse Distance Weight (IDW), and the Minimum Curvature Method. The results of the study demonstrated the accuracy of estimating precipitation using meteorological radar. Estimated precipitation compared against an equivalent of 2 years of rain station measurement had a probability of detection (POD) of 0.927, where a value of 1 indicated perfect agreement, demonstrating the effectiveness of the method used to calibrate the radar data. The bias correction method gave high accuracy compared with measured rainfall. Furthermore, of the spatial estimation of rainfall methods, the Kriging methodology showed the best fit between estimation of rainfall distribution and measured rainfall distribution. Therefore, the results of this study showed that the rainfall estimation, using data from a meteorology radar, has good accuracy and can be useful, especially in areas where it is not possible to install and operate rainfall measurement stations, such as in heavily forested areas and/or in steep terrain. Additionally, good accuracy rainfall data derived from radar data can be integrated with other data used for water management and natural disasters for applications to reduce economic losses, as well as losses of life and property.
Downscaling WGHM-Based Groundwater Storage Using Random Forest Method: A Regional Study over Qazvin Plain, Iran
Authors: Dastjerdi Soroush Zarghami , Sharifi Ehsan , Rahbar Rozita , Saghafian Bahram
Published: October 2022

Climate change, urbanization, and a growing population have led to a rapid increase in groundwater (GW) use. As a result, monitoring groundwater changes is essential for water managers and decision-makers. Due to the lack of reliable and insufficient in situ information, remote sensing and hydrological models may be counted as alternative sources to assess GW storage changes on regional and global scales. However, often, these hydrological models have a low spatial resolution for water-related applications on a small scale. Therefore, the main purpose of this study is to downscale the GW storage anomaly (GWSA) of the WaterGAP Global Hydrology Model (WGHM) from a coarse (0.5 degrees) to a finer spatial resolution (0.1 degrees) using fine spatial resolution auxiliary datasets (0.1 degrees), such as evaporation (E), surface (SRO), subsurface runoff (SSRO), snow depth (SD), and volumetric soil water (SWVL), from the ERA5-Land model, as well as the global precipitation (Pre) measurement (GPM-IMERG) product. The Qazvin Plain in central Iran was selected as the case study region, as it faces a severe decline in GW resources. Different statistical regression models were tested for the GWSA downscaling to find the most suitable method. Moreover, since different water budget components (such as precipitation or storage) are known to have temporal lead or lag relative to each other, the approach also incorporates a time shift factor. The most suitable regression model with the highest skill score during the training-validation was selected and applied to predict the final 0.1-degree GWSA. The downscaled results showed high agreement with the in situ groundwater levels over the Qazvin Plain on both interannual and monthly time scales, with a correlation coefficient of 0.989 and 0.62, respectively. Moreover, the downscaled product represents clear proof that the developed downscaling technique is able to learn from high-resolution auxiliary data to capture GWSA features at a higher spatial resolution. The major benefit of the proposed method lies in the utilization of only the auxiliary data that are available with global coverage and are free of charge, while not requiring in situ GW records for training or prediction. Therefore, the proposed downscaling technique can potentially be applied at a global scale and to aquifers in other geographical regions.
The Impact of Intermediate Goods Imports on Energy Efficiency: Empirical Evidence from Chinese Cities
Authors: Xiang Yu , Zheng Jing , Tu Xunhua
Published: October 2022

Improving energy efficiency is a critical way to solve energy shortage and environmental problems and achieve the goal of “double carbon”. As China expands imports and integrates into global value chains, can import trade improve energy efficiency? This topic is extremely important for solving current energy problems and promoting sustainable economic development. Based on panel data of prefecture-level cities in China, this paper uses the Super-SBM model to measure the total factor energy efficiency of cities and investigates the impact of intermediate goods imports on energy efficiency with fixed effects models and instrumental variable method (IV). The study finds that: (1) intermediate goods imports contribute to the increase of urban energy efficiency, and the mechanism test indicates that intermediate goods imports affect energy efficiency through the technology spillover effect and intermediate goods type diversification effect. (2) According to the heterogeneity analysis, the effect of intermediate goods imports on energy efficiency is more evident in eastern China and cities with low topographic relief, medium population scale, and high absorption capability. (3) Analysis of the spatial spillover effect with the SDM model shows that importing intermediate goods promotes energy efficiency in local cities and radiates energy efficiency improvement in neighboring cities.
Relational Continuity of Chronic Patients with Primary and Secondary Care Doctors: A Study of Public Healthcare Networks of Six Latin American Countries
Authors: Espinel-Flores Verónica , Tiburcio-Lara Gabriela , Vargas Ingrid , Eguiguren Pamela , Mogollón-Pérez Amparo-Susana , Ferreira-de-Medeiros-Mendes Marina , López-Vázquez Julieta , Bertolotto Fernando , Amarilla Delia , Vázquez María-Luisa
Published: October 2022

Despite relational continuity (RC) with the doctor being key to care quality for chronic patients, particularly in fragmented healthcare systems, like many in Latin America (LA), little is known about RC and its attributes, particularly regarding specialists. Aim: We aim to analyse chronic patients’ perceptions of RC with primary (PC) and secondary (SC) care doctors, and record changes between 2015 and 2017 in the public healthcare networks of six LA countries. An analysis of two cross-sectional studies applying the CCAENA questionnaire to chronic patients (N = 4881) was conducted in Argentina, Brazil, Chile, Colombia, Mexico, and Uruguay. The dependent variables of RC with PC and SC doctors were: consistency, trust, effective communication, and synthetic indexes based on RC attributes. Descriptive and multivariate analyses were performed. Although the RC index was high in 2015, especially in PC in all countries, and at both levels in Argentina and Uruguay, low perceived consistency of PC and SC doctors in Colombia and Chile and of SC doctors in Mexico revealed important areas for improvement. In 2017 the RC index of SC doctors increased in Chile and Mexico, while SC doctors’ consistency in Colombia decreased. This study reveals important gaps in achieving RC with doctors, particularly in SC, which requires further structural and organisational reforms.
Relationship between Eye Frailty and Physical, Social, and Psychological/Cognitive Weaknesses among Community-Dwelling Older Adults in Japan
Authors: Itokazu Masafumi , Ishizaka Masahiro , Uchikawa Yoshikazu , Takahashi Yoshiaki , Niida Takahiro , Hirose Tamaki , Ito Akihiro , Yakabi Akihiro , Endo Yoshiaki , Sawaya Yohei , Igawa Tatsuya , Kobayashi Kaoru , Hara Tsuyoshi , Watanabe Miyoko , Kubo Akira , Urano Tomohiko
Published: October 2022

This study investigated the relationship between eye frailty and physical, social, and psychological/cognitive weaknesses among older adults in Japan. The participants were 192 community-dwelling older adult women. We measured handgrip strength, walking speed, and skeletal muscle mass; additionally, their physical, social, and psychological/cognitive frailties were surveyed using questionnaires. Eye frailty self-checks were used to assess eye frailty. Exploratory and confirmatory factor analyses were employed to verify the validity of the eye frailty self-checks. Eye frailty prevalence and related factors were investigated by conducting a binomial logistic regression analysis, with eye frailty as the dependent variable. The factor analysis results showed that a model could be constructed with the two factors of visual acuity or contrast and visual field. The model’s goodness of fit was acceptable, supporting the validity of the self-checking construct. The Kihon checklist was the only variable with a significant relationship to eye frailty. Regarding the relationship between eye frailty and subordinate items of the Kihon checklist, social withdrawal [odds ratio (OR) 2.437, 95% confidence interval 1.145–5.188], cognitive function (OR 2.047, 95%CI 1.051–3.984), and depressed mood (OR 1.820, 95%CI 1.163–2.848) were significant. Eye frailty can be considered a factor reflecting the existence of social and psychological/cognitive frailties.
Application of a Decision Tree Model to Predict the Outcome of Non-Intensive Inpatients Hospitalized for COVID-19
Authors: Giotta Massimo , Trerotoli Paolo , Palmieri Vincenzo Ostilio , Passerini Francesca , Portincasa Piero , Dargenio Ilaria , Mokhtari Jihad , Montagna Maria Teresa , De Vito Danila
Published: October 2022

Many studies have identified predictors of outcomes for inpatients with coronavirus disease 2019 (COVID-19), especially in intensive care units. However, most retrospective studies applied regression methods to evaluate the risk of death or worsening health. Recently, new studies have based their conclusions on retrospective studies by applying machine learning methods. This study applied a machine learning method based on decision tree methods to define predictors of outcomes in an internal medicine unit with a prospective study design. The main result was that the first variable to evaluate prediction was the international normalized ratio, a measure related to prothrombin time, followed by immunoglobulin M response. The model allowed the threshold determination for each continuous blood or haematological parameter and drew a path toward the outcome. The model’s performance (accuracy, 75.93%; sensitivity, 99.61%; and specificity, 23.43%) was validated with a k-fold repeated cross-validation. The results suggest that a machine learning approach could help clinicians to obtain information that could be useful as an alert for disease progression in patients with COVID-19. Further research should explore the acceptability of these results to physicians in current practice and analyze the impact of machine learning-guided decisions on patient outcomes.
Use of Hand Creams during the Period of Frequent Disinfection in COVID-19 Pandemic—Preference Survey and Evaluation of Mercury Contamination
Authors: Puścion-Jakubik Anna , Pienkiewicz Monika , Steckiewicz Karolina , Stypułkowska Aleksandra , Grabia Monika , Bielecka Joanna , Markiewicz-Żukowska Renata , Socha Katarzyna
Published: October 2022

The skin is one of the ways the human body is exposed to toxic elements, including mercury (Hg). Hand creams are cosmetics that should be of high quality due to the fact that they can be used on irritated skin, which can facilitate the absorption of many ingredients. The study consisted of two stages: a consumer questionnaire was conducted regarding the preferences of the respondents, and then the Hg content in hand creams was determined. The survey covered 184 people with an age of 26.9 ± 7.8 years. Based on their preferences, 140 hand creams were selected for the study. The Hg content in the creams was determined by atomic absorption spectrometry with the amalgamation technique. The median content of this toxic element was 4.067 µg/kg. No influence of the country of origin, price, package size, main ingredients, and direction of action on the Hg content was shown. Noncarcinogenic risk assessment using the hazard quotient (HQ) indicated that the tested creams are safe. However, it should be emphasized that Hg has been shown in over 99% of the samples, which indicates that the content of this element in hand creams should be monitored.
Biomass, Carbon and Nitrogen Partitioning and Water Use Efficiency Differences of Five Types of Alpine Grasslands in the Northern Tibetan Plateau
Authors: Cheng Liping , Zhang Beibei , Zhang Hui , Li Jiajia
Published: October 2022

(1) Background: Grassland covers most areas of the northern Tibetan Plateau along with important global terrestrial carbon (C) and nitrogen (N) pools, so there is a need to better understand the different alpine grassland growth associated with ecosystem C, N storage and water use efficiency (WUE). (2) Methods: The plant biomass and C, N concentrations, stocks and vegetation WUE of five kinds of alpine grassland types were investigated in northern Tibetan Plateau. (3) Results: The results showed that there were significant differences among five types of alpine grasslands in aboveground biomass (AGB), belowground biomass (BGB), total biomass (TB) and root:shoot (R/S) ratio while the highest value of different indices was shown in alpine meadow type (AM). The AGB and BGB partitioning results significantly satisfied the allometric biomass partitioning theory. The C, N concentrations and C/N of the vegetation in AGB and BGB showed significant grassland type differences. The highest C, N stocks of BGB were in AM which was almost six or seven times more than the C, N stocks of AGB in alpine desert type (AD). There were significant differences in δ13C and intrinsic water use efficiency (WUEi) under five alpine grassland types while the highest mean values of foliar δ13C and WUEi were in AD. Significant negative correlations were found between WUEi and C, N concentrations, C/N of AGB and soil water content (SWC) while the correlation with BGB C/N was not significant. For AGB, BGB, TB and R/S, there were positive correlations with C, N concentrations of AGB, BGB and SWC while it had significant negative correlations with C/N of BGB. (4) Conclusions: With regard to its types, it is suggested that the AM or AS may be an actively growing grassland type in the northern Tibetan Plateau.
Holistic Assessment of Factors Associated with Exhaustion, the Main Symptom of Burnout: A Meta-Analysis of Longitudinal Studies
Authors: Shoman Yara , Rousson Valentin , Bianchi Renzo , Guseva Canu Irina
Published: October 2022

Background: This meta-analysis summarized longitudinal findings pertaining to exhaustion’s predictors. In so doing, our aim was ultimately to identify target factors for the prevention of burnout. Methods: We searched for studies that (a) examined predictors of exhaustion longitudinally and (b) reported correlation coefficients as an effect estimate. We conducted our literature search in three databases: MEDLINE, PsycINFO, and Embase. We focused on studies published between January 1990 and November 2020. Predictors were grouped into families, subfamilies, and subgroups. A meta-analysis of z-transformed correlation coefficients (rho) was performed. The results were scrutinized in relation to studies’ follow-up length. Results: We included 65 studies assessing 242 predictors of different types captured across different occupations. Our findings highlighted mostly weak associations (rho < 0.30). For six predictors—Job control, Job resources, Interactions at work, Communication and leadership, Job attitudes, and Work-family interface—longer length of follow-up involved weaker associations with exhaustion. The quality of the evidence available was generally low. Conclusions: The evidence available does not point to clear target factors for preventing burnout. The decrease in associations as the follow-up length increases may suggest a relatively short latency period, followed by recovery. Higher-quality cohorts should be conducted to better understand the etiology and course of burnout.
Associations between Fundamental Movement Skills and Moderate-to-Vigorous Intensity Physical Activity among Chinese Children and Adolescents with Intellectual Disability
Authors: Wang Taijin , Qian Yingtao , Zhong Tianwei , Qi Jing
Published: October 2022

Higher physical activity (PA) levels will obtain more health-related benefits for children and adolescents with intellectual disabilities (ID). The mastery of fundamental movement skills (FMS) potentially correlates with PA. This study aimed to examine the associations of FMS with moderate-to-vigorous intensity physical activity (MVPA) levels in children and adolescents with moderate to severe ID. Moreover, this research analyzes whether there are gender and age differences in the association between these two variables. A total of 93 children and adolescents with ID, aged 8–17 years (mean age = 13.27; SD = 3.35), were recruited from a special school located in western China. The time spent in MVPA was measured using waist-worn accelerometers. FMS proficiency was assessed using the Test of Gross Motor Development 2 (TGMD-2). Children and adolescents with ID tend to have delayed maturity of FMS patterns (locomotor skills t (92) = −16.91, p < 0.001, d = 2.48; object control skills t (92) = −25.39, p < 0.001, d = 3.72; total FMS t (92) = −21.83, p < 0.001, d = 3.20) and lower proficiency in objective control skills (t (92) = 3.989, p < 0.001, d = 0.29). A significant positive correlation was found between MVPA and FMS, and this association was moderated by gender and age. For boys, object control skills were a significant predictor of MVPA time (B = 0.842, p < 0.01), whereas locomotor skills were a significant predictor of MVPA time (B = 0.472, p < 0.05) for girls. For children with ID, object control skills were a significant predictor of MVPA time (B = 0.736, p < 0.05). Proficiency in FMS has a positive effect on increasing the level of MVPA in children and adolescents with ID. Gender and age factors should be considered when implementing FMS intervention programs.
DEPs Induce Local Ige Class Switching Independent of Their Ability to Stimulate iBALT de Novo Formation
Authors: Chudakov Dmitrii Borisovich , Konovalova Mariya Vladimirovna , Kashirina Elena Igorevna , Kotsareva Olga Dmitrievna , Shevchenko Marina Alexandrovna , Tsaregorodtseva Daria Sergeevna , Fattakhova Gulnar Vaisovna
Published: October 2022

Background: Diesel exhaust particles (DEPs) are leading to a general increase in atopic diseases worldwide. However, it is still unknown whether DEPs induce systemic B-cell IgE class switching in secondary lymphoid organs or locally in the lungs in inducible bronchus-associated lymphoid tissue (iBALT). The aim of this work was to identify the exact site of DEP-mediated B-cell IgE class switching and pro-allergic antibody production. Methods: We immunized BALB/c mice with different OVA doses (0.3 and 30 µg) intranasally in the presence and absence of two types of DEPs, SRM1650B and SRM2786. We used low (30 µg) and high (150 µg) DEP doses. Results: Only a high DEP dose induced IgE production, regardless of the particle type. Local IgE class switching was stimulated upon treatment with both types of particles with both low and high OVA doses. Despite the similar ability of the two standard DEPs to stimulate IgE production, their ability to induce iBALT formation and growth was markedly different upon co-administration with low OVA doses. Conclusions: DEP-induced local IgE class switching takes place in preexisting iBALTs independent of de novo iBALT formation, at least in the case of SRM1650B co-administered with low OVA doses.