bluuebunny/crossref_metadata_2025 huggingface dataset:
The Prospective Associations of Lipid Metabolism-Related Dietary Patterns with the Risk of Diabetes in Chinese Adults
Authors: Liu Qi , Wen Qiaorui , Lv Jun , Shi Zumin , Guo Yu , Pei Pei , Du Huaidong , Yang Ling , Chen Yiping , Zhang Xiaofang , Schmidt Dan , Sansome Sam , Chen Junshi , Yu Canqing , Chen Zhengming , Li Liming ,   on behalf of the China Kadoorie Biobank (CKB) Collaborative Group
Published: February 2022

Background: This study aimed to identify lipid metabolism-related dietary patterns with reduced rank regression (RRR) among Chinese adults and examine their associations with incident diabetes. Methods: We derived lipid metabolism-related dietary patterns using an RRR with 21 food groups as predictors as well as total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, body mass index (BMI), and waist circumference from the responses of 17,318 participants from the second resurvey of the China Kadoorie Biobank (CKB). The dietary scores were calculated for the entire cohort. We followed up 479,207 participants for diabetes incidence from the baseline and used multivariable Cox regression models to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). Results: Two lipid metabolism-related dietary patterns were extracted. The dietary pattern—characterized by high intakes of fish, poultry, and other staples as well as fresh fruit and vegetables—was correlated with a higher BMI, waist circumference, and LDL cholesterol. Participants in the highest quintile (Q5) had a 44% increased risk of diabetes incidence when compared with those in the lowest quintile (Q1) (HR = 1.44; 95% CI: 1.31–1.59). Conclusions: A dietary pattern characterized by high intakes of both animal and plant foods was related to obesity and dyslipidemia and could increase the risk of diabetes incidence.
Targeting the Gut Microbiota of Vertically HIV-Infected Children to Decrease Inflammation and Immunoactivation: A Pilot Clinical Trial
Authors: Sainz Talía , Diaz Laura , Rojo David , Clemente María Isabel , Barbas Coral , Gosalbes María José , Jimenez-Hernandez Nuria , Escosa Luis , Guillen Sara , Ramos José Tomás , Muñoz-Fernández María Ángeles , Navarro María Luisa , Mellado María José , Serrano-Villar Sergio
Published: February 2022

Aims: Children with HIV exhibit chronic inflammation and immune dysfunction despite antiretroviral therapy (ART). Strategies targeting persistent inflammation are needed to improve health in people living with HIV. The gut microbiota likely interacts with the immune system, but the clinical implications of modulating the dysbiosis by nutritional supplementation are unclear. Methods: Pilot, double-blind, randomized placebo-controlled trial in which 24 HIV-infected on ART were randomized to supplementation with a daily mixture of symbiotics, omega-3/6 fatty acids and amino acids, or placebo four weeks, in combination with ART. We analyzed inflammatory markers and T-cell activation changes and their correlations with shifts in fecal microbiota. Results: Twenty-four HIV-infected children were recruited and randomized to receive a symbiotic nutritional supplement or placebo. Mean age was 12 ± 3.9 years, 62.5% were female. All were on ART and had HIV RNA < 50/mL. We did not detect changes in inflammatory (IL-6, IL-7, IP-10), microbial translocation (sCD14), mucosal integrity markers (IFABP, zonulin) or the kynurenine to tryptophan ratio, or changes in markers of the adaptive immune response in relation to the intervention. However, we found correlations between several key bacteria and the assessed inflammatory and immunological parameters, supporting a role of the microbiota in immune modulation in children with HIV. Conclusions: In this exploratory study, a four-week nutritional supplementation had no significant effects in terms of decreasing inflammation, microbial translocation, or T-cell activation in HIV-infected children. However, the correlations found support the interaction between gut microbiota and the immune system.
Development and Validation of Nutrition Literacy Questionnaire for the Chinese Elderly
Authors: Aihemaitijiang Sumiya , Ye Chen , Halimulati Mairepaiti , Huang Xiaojie , Wang Ruoyu , Zhang Zhaofeng
Published: February 2022

(1) Background: Improving nutrition literacy is crucial for maintaining a healthier state of the elderly to achieve healthy ageing. Therefore, it is necessary to develop a Nutrition Literacy Questionnaire for the Chinese Elderly (NLQ-E). (2) Methods: an NLQ-E was developed according to the core components of nutrition literacy for the elderly. Internal consistency, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to validate the reliability and validity of the NLQ-E. A cross-sectional study of 1490 elderly people was used to analyze the application of the NLQ-E. (3) Results: The NLQ-E was constructed with 3 domains (knowledge and understanding, healthy lifestyle and dietary behavior and skill), with a total of 25 questions. The overall NLQ-E had acceptable reliability and validity (Cronbach’s α = 0.678, χ2/DF = 4.750, RMSEA = 0.045, PCFI = 0.776 and PNFI = 0.759). The average nutrition literacy score of the subjects in this cross-sectional study was 65.95 (65.95 ± 10.93). The OR between the nutrition literacy score and multimorbidity was 0.965 (95% CI: 0.954, 0.976); (4) Conclusions: We developed and validated the NLQ-E and found that the nutrition literacy level of the Chinese elderly was generally low. This study is of great value to improve the nutrition literacy of the elderly and effectively prevent nutrition-related chronic diseases and multimorbidity.
Antiviral Agents against Flavivirus Protease: Prospect and Future Direction
Authors: Samrat Subodh K. , Xu Jimin , Li Zhong , Zhou Jia , Li Hongmin
Published: February 2022

Flaviviruses cause a significant amount of mortality and morbidity, especially in regions where they are endemic. A recent example is the outbreak of Zika virus throughout the world. Development of antiviral drugs against different viral targets is as important as the development of vaccines. During viral replication, a single polyprotein precursor (PP) is produced and further cleaved into individual proteins by a viral NS2B-NS3 protease complex together with host proteases. Flavivirus protease is one of the most attractive targets for development of therapeutic antivirals because it is essential for viral PP processing, leading to active viral proteins. In this review, we have summarized recent development in drug discovery targeting the NS2B-NS3 protease of flaviviruses, especially Zika, dengue, and West Nile viruses.
Potential Role of Birds in the Epidemiology of Coxiella burnetii, Coxiella-like Agents and Hepatozoon spp.
Authors: Ebani Valentina Virginia , Mancianti Francesca
Published: February 2022

Birds may be involved in the epidemiology of infectious and/or parasitic diseases which affect mammals, including humans. Q fever, caused by Coxiella burnetii, is an important zoonosis causing economic losses mainly due to pathologies induced in ruminants. Even though birds are known to be potential reservoirs of C. burnetii, their role in the epidemiological cycle of the pathogen is not completely verified. In recent years, new bacteria identified as Coxiella-like agents, have been detected in birds affected by different pathologies; the potential role of these bacteria as pathogens for mammals is not currently known. Hepatozoon spp. are haemoprotozoa, causing arthropod borne affections within several vertebrate classes. The infection of vertebrate host develops after ingestion of the arthropod final hosts containing oocysts; different tissues and blood cells are then colonized by other parasite stages, such as merozoites and gamonts. In avian hosts, there are several recognized Hepatozoon species; however, their life cycle and pathogenicity have not been fully elucidated. Referring to a carrier role by avian species and their ticks in the epidemiology of canine hepatozoonosis, the only clinically relevant affection caused by this parasite genus, they would act as carriers of infected ticks and, when Hepatozoon americanum is involved, as paratenic hosts, as well.
A Review of Raman-Based Technologies for Bacterial Identification and Antimicrobial Susceptibility Testing
Authors: Zhang Weifeng , He Shipei , Hong Weili , Wang Pu
Published: February 2022

Antimicrobial resistance (AMR) is a global medical threat that seriously endangers human health. Rapid bacterial identification and antimicrobial susceptibility testing (AST) are key interventions to combat the spread and emergence of AMR. Although current clinical bacterial identification and AST provide comprehensive information, they are labor-intensive, complex, inaccurate, and slow (requiring several days, depending on the growth of pathogenic bacteria). Recently, Raman-based identification and AST technologies have played an increasingly important role in fighting AMR. This review summarizes major Raman-based techniques for bacterial identification and AST, including spontaneous Raman scattering, surface-enhanced Raman scattering (SERS), and coherent Raman scattering (CRS) imaging. Then, we discuss recent developments in rapid identification and AST methods based on Raman technology. Finally, we highlight the major challenges and potential future efforts to improve clinical outcomes through rapid bacterial identification and AST.
Review on All-Fiber Online Raman Sensor with Hollow Core Microstructured Optical Fiber
Authors: Ding Haonan , Hu Dora Juan Juan , Yu Xingtao , Liu Xiaoxian , Zhu Yifan , Wang Guanghui
Published: February 2022

Raman spectroscopy is widely used for qualitative and quantitative analysis of trace components in scientific fields such as food safety monitoring, drug testing, environmental monitoring, etc. In addition to its demonstrated advantages of fast response, non-destructive, and non-polluting characteristics, fast online Raman detection is drawing growing attention for development. To achieve this desirable capability, hollow core optical fibers are employed as a common transmission channel for light and fluid in the Raman sensor. By enhancing the interaction process between light and matter, the detection sensitivity is improved. At the same time, the Raman spectroscopy signal light collection efficiency is significantly improved. This article summarizes enhancement techniques reported for Raman sensors, followed by a detailed review on fiber-based Raman sensor techniques including theoretical analyses, fabrication, and application based on hollow core photonic crystal fibers and capillary-based hollow core fibers. The prospects of using these fibers for Raman spectroscopy are discussed.
Assessment of a New Trifocal Diffractive Corneal Inlay for Presbyopia Correction Using an Adaptive Optics Visual Simulator
Authors: Martínez-Espert Anabel , Montagud-Martínez Diego , Ferrando Vicente , Furlan Walter D. , Monsoriu Juan A.
Published: February 2022

In this work, we analyze a proposal of a new intracorneal diffractive lens for presbyopia correction that could allow good, distance, intermediate and near vision. By using an adaptive optics visual simulator, we study the influence of two factors in the inlay performance: the spherical aberration (SA) and the potential errors of in thickness, induced in the manufacturing process. We show that the inlay through-the-focus imaging performance can be customized with the SA value, favoring either distance–intermediate or intermediate–near vision. Moreover, we found that with thickness variations of 10%, the inlay still maintains its trifocal nature.
Design of a Hybrid Split-Delay Line for Hard X-ray Free-Electron Lasers
Authors: Xu Yihui , Wu Chen , Fan Jiadong , Wang Zhen , Tong Yajun , Huang Qiushi , Yang Chuan , Dong Xiaohao , Jiang Huaidong , Liu Zhi
Published: February 2022

High repetition-rate X-ray free-electron lasers (XFELs) enable the study of fast dynamics on microsecond time scales. Split-delay lines (SDLs) further bring the time scale down to femtoseconds by splitting and delaying the XFEL pulses. Crystals and multilayers are two common types of optical elements in SDLs, offering either long delay ranges or high temporal accuracy. In this work, we introduce the design of a hybrid SDL for the coherent diffraction endstation of Shanghai High Repetition Rate XFEL and Extreme Light Facility (SHINE). It uses crystals for the first branch and multilayers for the second one, thus simultaneously offering a relatively long delay range and high temporal accuracy. Moreover, a third branch can be installed to switch the SDL to the all-crystal configuration for longer delay ranges.
Pairwise Coded mCAP with Chaotic Dual-Mode Index Modulation for Secure Bandlimited VLC Systems
Authors: Nie Yungui , Zhang Wei , Yang Yanbing , Deng Xiong , Liu Min , Chen Chen
Published: February 2022

In this paper, for the first time, we propose and experimentally demonstrate a novel pairwise coding (PWC)-based multiband carrierless amplitude and phase (mCAP) modulation with chaotic dual-mode index modulation (DM) for secure bandlimited visible light communication (VLC) systems. The combination of mCAP and DM can sustain a higher spectral efficiency (SE) compared with mCAP with conventional index modulation (IM), while PWC can be employed to efficiently mitigate the signal-to-noise ratio (SNR) imbalance caused by the low-pass frequency response of light emitting diodes (LEDs). Moreover, the DM is enhanced by a two-dimensional (2D) chaotic encryption scheme to guarantee the security of the useful information in VLC systems. Simulation and experimental results successfully verify the superiority of the proposed PWC-based mCAP-DM scheme with two-level chaotic encryption over other benchmark schemes.
Color Transparency in p¯A Reactions
Authors: Larionov Alexei B.
Published: February 2022

Exclusive channels of antiproton annihilation on the bound nucleon are sensitive to mesonic interactions with the target residue. If the hard scale is present, then such interactions should be reduced due to color transparency (CT). In this paper, the d(p¯,π−π0)p reaction is discussed at a large center-of-mass angle. Predictions for the future PANDA (antiProton ANnihilations at DArmstadt) experiment at FAIR (Facility for Antiproton and Ion Research, Darmstadt, Germany) are given for nuclear transparency ratios calculated within the generalized eikonal approximation and the quantum diffusion model of CT.
Degradation of Carbendazim by Molecular Hydrogen on Leaf Models
Authors: Zhang Tong , Wang Yueqiao , Zhao Zhushan , Xu Sheng , Shen Wenbiao
Published: February 2022

Although molecular hydrogen can alleviate herbicide paraquat and Fusarium mycotoxins toxicity in plants and animals, whether or how molecular hydrogen influences pesticide residues in plants is not clear. Here, pot experiments in greenhouse revealed that degradation of carbendazim (a benzimidazole pesticide) in leaves could be positively stimulated by molecular hydrogen, either exogenously applied or with genetic manipulation. Pharmacological and genetic increased hydrogen gas could increase glutathione metabolism and thereafter carbendazim degradation, both of which were abolished by the removal of endogenous glutathione with its synthetic inhibitor, in both tomato and in transgenic Arabidopsis when overexpressing the hydrogenase 1 gene from Chlamydomonas reinhardtii. Importantly, the antifungal effect of carbendazim in tomato plants was not obviously altered regardless of molecular hydrogen addition. The contribution of glutathione-related detoxification mechanism achieved by molecular hydrogen was confirmed. Our results might not only illustrate a previously undescribed function of molecular hydrogen in plants, but also provide an environmental-friendly approach for the effective elimination or reduction of pesticides residues in crops when grown in pesticides-overused environmental conditions.
Multiparent-Derived, Marker-Assisted Introgression Lines of the Elite Indian Rice Cultivar, ‘Krishna Hamsa’ Show Resistance against Bacterial Blight and Blast and Tolerance to Drought
Authors: Badri Jyothi , Lakshmidevi Gandhudi , JaiVidhya L. R. K. , Prasad Madamsetty Srinivasa , Laha Gouri Shankar , Lakshmi Vattikutti Jhansi , Isetty Subhakara Rao , Padmashree Revadi , Balakrishnan Divya , Varanasi Yasaswini Vishnu Priya , Jukanti Aravind Kumar , Singh Uma Maheshwar , Singh Vikas Kumar , Kumar Arvind , Ram T. , Subba Rao Lella Venkata , Sundaram Raman Meenakshi
Published: February 2022

Major biotic stresses viz., bacterial blight (BB) and blast and brown plant hopper (BPH) coupled with abiotic stresses like drought stress, significantly affect rice yields. To address this, marker-assisted intercross (IC) breeding involving multiple donors was used to combine three BB resistance genes—xa5, xa13 and Xa21, two blast resistance genes—Pi9 and Pi54, two BPH resistance genes—Bph20 and Bph21, and four drought tolerant quantitative trait loci (QTL)—qDTY1.1, qDTY2.1, qDTY3.1 and qDTY12.1—in the genetic background of the elite Indian rice cultivar ‘Krishna Hamsa’. Three cycles of selective intercrossing followed by selfing coupled with foreground selection and phenotyping for the target traits resulted in the development of 196 introgression lines (ILs) with a myriad of gene/QTL combinations. Based on the phenotypic reaction, the ILs were classified into seven phenotypic classes of resistance/tolerance to the following: (1) BB, blast and drought—5 ILs; (2) BB and blast—10 ILs; (3) BB and drought—9 ILs; (4) blast and drought—42 ILs; (5) BB—3 ILs; (6) blast—84 ILs; and (7) drought—43 ILs; none of the ILs were resistant to BPH. Positive phenotypic response (resistance) was observed to both BB and blast in 2 ILs, BB in 9 ILs and blast in 64 ILs despite the absence of corresponding R genes. Inheritance of resistance to BB and/or blast in such ILs could be due to the unknown genes from other parents used in the breeding scheme. Negative phenotypic response (susceptibility) was observed in 67 ILs possessing BB-R genes, 9 ILs with blast-R genes and 9 ILs harboring QTLs for drought tolerance. Complex genic interactions and recombination events due to the involvement of multiple donors explain susceptibility in some of the marker positive ILs. The present investigation successfully demonstrates the possibility of rapid development of multiple stress-tolerant/resistant ILs in the elite cultivar background involving multiple donors through selective intercrossing and stringent phenotyping. The 196 ILs in seven phenotypic classes with myriad of gene/QTL combinations will serve as a useful genetic resource in combining multiple biotic and abiotic stress resistance in future breeding programs.
Mining of Potential Gene Resources for Breeding Nutritionally Improved Maize
Authors: Hou Quancan , Zhang Tianye , Sun Kangtai , Yan Tingwei , Wang Linlin , Lu Lu , Zhao Wei , Qi Yuchen , Long Yan , Wei Xun , Wan Xiangyuan
Published: February 2022

Maize is one of the leading food crops and its kernel is rich in starch, lipids, protein and other energy substances. In addition, maize kernels also contain many trace elements that are potentially beneficial to human health, such as vitamins, minerals and other secondary metabolites. However, gene resources that could be applied for nutrient improvement are limited in maize. In this review, we summarized 107 genes that are associated with nutrient content from different plant species and identified 246 orthologs from the maize genome. In addition, we constructed physical maps and performed a detailed expression pattern analysis for the 246 maize potential gene resources. Combining expression profiles and their potential roles in maize nutrient improvement, genetic engineering by editing or ectopic expression of these genes in maize are expected to improve resistant starch, oil, essential amino acids, vitamins, iron, zinc and anthocyanin levels of maize grains. Thus, this review provides valuable gene resources for maize nutrient improvement.
Effect of Nelumbo nucifera Petals Extract on Antioxidant Activity and Sperm Quality in Charolais Cattle Sperm Induced by Mancozeb
Authors: Laoung-on Jiraporn , Jaikang Churdsak , Saenphet Kanokporn , Sudwan Paiwan
Published: February 2022

The white Nelumbo nucifera petals aqueous extraction (NAE) was prominent in phytochemical content, antioxidant activity, and enhanced rat sperm viability induced by FeSO4, a heavy metal. Mancozeb (MZ) contains heavy metals and is widely used for fungal control in agriculture and industry. It induces oxidative stress and causes of spermatogenesis and reproductive organs’ abnormalities in both humans and animals. The aims of the present study were to investigate the effects of white Nelumbo nucifera petals aqueous extraction (WNAE) on sperm quality in cattle sperm induced by MZ. Moreover, this study investigated phytochemical compounds by liquid chromatography-mass spectrometry. A protein profile related to sperm quality with SDS-page and sperm energy preservation for each treatment was determined. The results found nine phytochemical compounds, in which quercetin-3-O-arabinoglycoside was a major flavonoid that was found in the WNAE. MZ induced free radicals in cells, leading to LPO and protein oxidation, while decreasing sperm motility, sperm viability, acrosome integrity, and normal sperm morphology. The cattle sperm found four proteins related to sperm quality including MWs of 17, 31, 34, and 55 kDa. The WNAE effectively increased energy preservation, sperm motility, sperm viability, acrosome integrity, and normal sperm morphology. The WNAE enhanced sperm qualities by reducing oxidative stress. It might be suggested that WNAE has benefits for sperm preservation which may be used to guard against toxicity in animals or humans exposed to MZ contaminants.
Nutrigenomics in Animal Feeding: Digital Gene Expression Analysis in Poultry Fed Tenebrio molitor Larvae Meal
Authors: Soglia Dominga , Viola Irene , Nery Joana , Maione Sandra , Sartore Stefano , Lasagna Emiliano , Perini Francesco , Gariglio Marta , Bongiorno Valentina , Moretti Riccardo , Chessa Stefania , Sacchi Paola , Bergero Domenico , Biasato Ilaria , Gasco Laura , Schiavone Achille
Published: February 2022

The purpose of this study was to investigate the effects of high levels of Tenebrio molitor dietary inclusion (15%) on molecular mechanisms that influence poultry health in a broiler chicken diet. The global gene expression of four tissues (breast, liver, jejunum, and caecum) was evaluated using the RNA-Seq approach. The analysis of differentially expressed genes suggested that the use of Tenebrio molitor leads to the overexpression of genes related to protein elongation required for tissue growth and development in the gut and liver. It would also appear to contain nutrients that reduce the expression of genes related to the immune system and inflammation of the mucosa. The dietary inclusion of Tenebrio molitor in poultry could also lead to a possible inactivation of the growth factor and a reduction of tissue free-radicals. No genes alterations have been detected in liver RNA expression that would discourage the use of larvae in feeding broilers.
Climate Neutrality Concepts for the German Chemical–Pharmaceutical Industry
Authors: Schmidt Axel , Köster Dirk , Strube Jochen
Published: February 2022

This paper intends to propose options for climate neutrality concepts by taking non-German international experiences and decisions made into account. Asia-Pacific and Arabic countries do have already same lessons learned by large-scale projects with regard to economic evaluations. Quite a few conceptual studies to generate the climate neutrality of the chemical–pharmaceutical industry in Germany have been published recently. Most of the studies differ even in magnitude but do not refer to or evaluate the other ones. These are all first theoretical feasibility studies. Experimental piloting is not far developed; only few and only stand-alone parts are operated, with no overall concepts. Economic evaluation is missing nearly completely. Economic analysis shows a factor 3 more expensive green technologies. Even if a large optimization potential of about 30% during manufacturing optimization is assumed as significant, cost increases would result. To make green products nevertheless competitive, the approach is to increase the carbon-source cost analogue, e.g., by CO2/ton taxes by around EUR 100, which would lead to about factor 3 higher consumer prices regarding the material amount. Furthermore, some countries would not participate in such increases and would have benefits on the world market. Whether any customs-duties policy could balance that is generally under question. Such increasing costs are not imaginable for any social-political system. Therefore, the only chance to realize consequent climate neutrality is to speed up research on more efficient and economic technologies, including, e.g., reaction intensification technologies such as plasma ionization, catalyst optimization, section coupling to cement, steel and waste combustion branches as well as pinch technology integration and appropriate scheduling. In addition, digital twins and process analytical technologies for consequent process automation would help to decrease costs. All those technologies seem to lead to even less personnel, but who need to be highly educated to deal with complex integrated systems. Research and education/training has to be designed for those scenarios. Germany as a resource-poor country could benefit from its human resources. Germany is and will be an energy importing country.
CWM-CGAN Method for Renewable Energy Scenario Generation Based on Weather Label Multi-Factor Definition
Authors: He Guixiong , Liu Kaicheng , Wang Songcen , Lei Yang , Li Jiaxi
Published: February 2022

With the increasing installed capacity of renewable energy in the energy system, the uncertainty of renewable energy has an increasingly prominent impact on power system planning and operation. Renewable energy such as wind and solar energy is greatly affected by the external weather. How to use a reasonable method to describe the relationship between weather and renewable energy output, so as to measure the uncertainty of renewable energy more accurately, is an important problem. To solve this problem, this paper proposes a renewable energy scenario generation method based on a conditional generation countermeasure network and combination weighting method (CWM-CGAN). In this method, the combination of AHP and the entropy weight method is used to analyze the meteorological factors, the weather classification is defined as the condition label in the conditional generation countermeasure network, and the energy scenario is generated by the conditional generation confrontation network. In this paper, the proposed method is tested with actual PV data, and the results show that the proposed model can describe the uncertainty of PV more accurately.
Preparation of Polymer Composite Selective Permeable Membrane with Graphene Oxide and Application for Chemical Protective Clothing
Authors: Du Haolin , Li Zenghe , Li Heguo , Zhao Yue , Li Xiaopeng , Liu Jing , Ji Zuohui
Published: February 2022

Chemical warfare agents (CWA) can poison people through the skin and cause injury, and the use of chemical protective clothing (CPC) is an important way to protect personnel from injury. CPC performance strongly depends on chemical protective materials, and satisfactory protective materials must meet various requirements, including protective performance, physiological comfort, mechanical performance, and cost effectiveness. Here, low-cost materials were used to prepare PVDF sodium sulfonate composite membranes with different contents of modified graphene oxide (GO-SSS). Their tensile properties, contact angle, permeability, and selectivity were tested and analyzed. The results show that when the addition ratio of GO-SSS to the bare membrane is 0.5%, the composite membrane has desirable permeation selectivity of water vapor/CWA simulant vapor and desirable mechanical properties. Hence, our sodium sulfonate composite membrane of PVDF with GO-SSS is an ideal material for potential applications in CPC.
Prediction-Interval-Based Credibility Criteria of Prognostics Results for Practical Use
Authors: An Dawn
Published: February 2022

Prognostics is an AI-based technique for predicting the degrading/damaging behavior and remaining useful life (RUL) of a system, which facilitates a cost-effective and smart maintenance process. Many prognostics methods have been developed for various applications, such as bearings, aircraft engines, batteries, and fuel cell stacks. Once a new prognostics method is developed, it is evaluated using several metrics based on the true value of the RUL. However, these typical evaluation metrics are not applicable in real-world applications, as the true RUL cannot be known before the actual failure of a system. There are no ways to determine the reliability of prognostics results in practice. Therefore, this article presents the credibility criteria of prognostics results based on prediction intervals (PI), which are known values, unlike the true RUL. The PI-based credibility criteria for prognostics results are explained with two simple examples under different levels of noise to help with the decision making on prognostics results in the industrial field.
Exergy and Exergoeconomic Analyses of Air Conditioning Applications Integrated with an Air Membrane Exchanger
Authors: Almutairi Abdulrahman S. , Alenezi Abdulrahman H. , AlHajeri Hamad M. , Alazemi Saad F. , AlMutairi Hamad H. , Alzuwayer Bashar
Published: February 2022

The results obtained from the exergoeconomic and exergy analysis of a model of a generic air conditioning (A/C) system without and with an air membrane exchanger using three commercially available refrigerants: R410A, R407C, and R134a, are reported. The model used specialized software that was validated against recently published data and showed good agreement. A/C systems are energy intensive and consume a significant portion of global electricity. Improving their efficiency by even a small amount will produce considerable savings, reduce running costs, and lower pollution emissions. The efficiency of the same A/c system without and with a membrane was investigated for different ambient temperatures, relative humidities (RHs), and pressure ratios of the compressor. It was shown that the inclusion of a membrane improved the efficiency of the system for all three refrigerants tested, particularly at higher ambient temperature. Both the coefficient of performance and exergetic efficiency reduced with the increase in the pressure ratio due to increasing fuel exergy and losses. In all system components except one, it was found that the source of the cost is inefficiencies; hence, increasing the efficiency at the expense of the non-exergy cost will improve the cost effectiveness of the entire system.
Construct and Priority Ranking of Factors Affecting Crowdfunding for Green Products
Authors: Zhang Xiu-Yue , Tu Jui-Che , Gu Shurui , Lu Tzu-Hsuan , Yi Minzhe
Published: February 2022

This article aims to target the key factors that could positively affect crowdfunding success for green products in order to promote crowdfunding efficiency and green supply chain management. Methods: Data were collected through expert interviews and questionnaires and then processed through analytic hierarchy process (AHP) analysis. Statistical tool: This study used Expert Choice as the software for AHP analysis. Sampling: There were 20 participants (20 effective) in pretesting and 30 (23 effective) in formal testing. Participants were followers of green products in Taiwan. Results: (1) Twenty-four factors were abstracted to form the final construct; (2) the 24 key factors could be divided into 2 hierarchies, with 5 primary factors and 19 secondary factors; (3) among the 5 primary factors, “green diversified context” was the most influential; (4) among the 19 secondary factors, “product material is safe and non-toxic” was the most important. Conclusions: Funders would be likely to finance green products on crowdfunding platforms if these products fit the 24 key factors in orders. Implications: This research contributes to product life cycle theory and crowdfunding theory and practically improves the sustainability of green products.
Supercritical Foaming and Impregnation of Polycaprolactone and Polycaprolactone-Hydroxyapatite Composites with Carvacrol
Authors: Satpayeva Alina , Rojas Adrián , Tyrka Marcin , Ksepko Ewelina , Galotto María José , Zizovic Irena
Published: February 2022

Polycaprolactone (PCL) and polycaprolactone-hydroxyapatite (PCL-HA) scaffolds were produced by foaming in supercritical carbon dioxide (scCO2) at 20 MPa, as well as in one-step foaming and impregnation process using carvacrol as an antibacterial agent with proven activity against Gram-positive and Gram-negative bacteria. The experimental design was developed to study the influence of temperature (40 °C and 50 °C), HA content (10 and 20 wt.%), and depressurization rate (one and two-step decompression) on the foams’ morphology, porosity, pore size distribution, and carvacrol impregnation yield. The characterization of the foams was carried out using scanning electron microscopy (SEM, SEM-FIB), Gay-Lussac density bottle measurements, and Fourier–transform infrared (FTIR) analyses. The obtained results demonstrate that processing PCL and PCL-HA scaffolds by means of scCO2 foaming enables preparing foams with porosity in the range of 65.55–74.39% and 61.98–67.13%, at 40 °C and 50 °C, respectively. The presence of carvacrol led to a lower porosity. At 40 °C and one-step decompression at a slow rate, the porosity of impregnated scaffolds was higher than at 50 °C and two- step fast decompression. However, a narrower pore size distribution was obtained at the last processing conditions. PCL scaffolds with HA resulted in higher carvacrol impregnation yields than neat PCL foams. The highest carvacrol loading (10.57%) was observed in the scaffold with 10 wt.% HA obtained at 50 °C.
Special Issue “Computational Finance and Risk Analysis in Insurance”
Authors: Korn Ralf
Published: February 2022

This Special Issue focuses on the rapid development of computational finance as well as on classical risk analysis issues in insurance that also benefit from modern computational methods [...]
Modelling and Assessment of Single-Frequency PPP Time Transfer with BDS-3 B1I and B1C Observations
Authors: Wang Shengli , Ge Yulong , Meng Xiaolin , Shen Pengli , Wang Kaidi , Ke Fuyang
Published: February 2022

BDS-3 is now providing global positioning, navigation and timing (PNT) services. BDS-3 has new B1C, B2a and B2b signals compared to BDS-2. This work presents two single-frequency (SF) PPP time transfer models using BDS-3, B1C and B1I observations, and studies the performance of BDS-3 SF PPP time transfer by using 30-day data of 10 globally distributed stations from a multi-GNSS experiment (MGEX). We found that the ionospheric constraint SF PPP (SF1) time transfer model outperforms the method of SF PPP with the receiver clock offset at first epoch as the datum (SF2). Importantly, the statistical uncertainty of SF1 was less than 1 nanosecond, with (0.75, 0.71) ns in the average scheme for all time-links, using both B1I and B1C observations, respectively. The frequency stability of SF1 with B1C observations was improved from 1.73% to 13.04% in the short-term and from 0.88% to 17.49% in the long term, compared to that of B1I for all time-links. Hence, SF1 with B1C observations was recommended for SF PPP time transfer.
Research on Shore-Based River Flow Velocity Inversion Model Using GNSS-R Raw Data
Authors: Zhang Yun , Yan Ziyu , Yang Shuhu , Meng Wanting , Gu Siqi , Qin Jin , Han Yanling , Hong Zhonghua
Published: February 2022

Global navigation satellite system reflectometry technology (GNSS-R) is rarely used for river flow velocity inversion, and in particular, there is currently no research using the BeiDou Navigation Satellite System reflectometry technology (BDS-R) for river flow velocity inversion. In this paper, a carrier phase observation of river flow velocity inversion model is proposed. The interference phase is the integral of the Doppler frequency. The raw intermediate frequency (IF) data sets are processed through an open-loop method to obtain the Doppler frequency observation generated by river flow and then realize velocity inversion. The shore-based river current measurement was conducted on the south bank of Dashengguan Yangtze River in Nanjing city, Jiangsu Province, for nearly two hours on 22 April 2021. After realizing the inversion of river flow velocity in GPS L1, the combined inversion of BDS B1I GEO satellite and IGSO satellite is realized for the first time, which demonstrates the feasibility of river flow velocity inversion using BDS reflected signals. Compared with the real river flow velocity, the GPS L1 PRN 4 (1st period) inversion precision reaches up to 0.028 m/s (mean absolute error, MAE) and 0.036 m/s (root mean square error, RMSE). In parallel, BDS GEO 2 inversion precision can reach 0.048 m/s (MAE) and 0.063 m/s (RMSE), and BDS IGSO 10 inversion precision is 0.061 m/s (MAE) and 0.073 m/s (RMSE). These results illustrate that satellite elevation change rate and distance between specular points and current meter may have a negative effect on the accuracy of river flow velocity inversion. Specular points obstructed by obstacles or too far from the velocity meter may introduce uncertain error in both MAE and RMSE. Neither the satellite elevation nor the signal strength has an obvious correlation with inversion precision, which is consistent with the theoretical principle.
Reducing the Residual Topography Phase for the Robust Landscape Deformation Monitoring of Architectural Heritage Sites in Mountain Areas: The Pseudo-Combination SBAS Method
Authors: Xu Hang , Chen Fulong , Zhou Wei , Wang Cheng
Published: February 2022

Monitoring deformation of architectural heritage sites is important for the quantitative evaluation of their stability. However, deformation monitoring of sites in mountainous areas remains challenging whether utilizing global navigation satellite system (GNSS) or interferometric synthetic aperture radar (InSAR) techniques. In this study, we improved the small baseline subset (SBAS) approach by introducing the pseudo-baseline combination strategy to avoid the errors caused by inaccurate external DEM, resulting in robust deformation estimations in mountainous areas where the architectural heritage site of the Great Wall is located. First, a simulated dataset and a real dataset were used to verify the reliability and effectiveness of the algorithm, respectively. Subsequently, the algorithm was applied in the landscape deformation monitoring of the Shanhaiguan section of the Great Wall using 51 Sentinel-1 scenes acquired from 2016 to 2018. A thematic stability map of the Shanhaiguan Great Wall corridor was generated, revealing that the landscape was generally stable save for local instabilities due to to unstable rocks and wall monuments. This study demonstrated the capabilities of adaptive multitemporal InSAR (MTInSAR) approaches in the preventive landscape deformation monitoring of large-scale architectural heritage sites in complex terrain.
Development of a Coaching System for Functional Electrical Stimulation Rowing: A Feasibility Study in Able-Bodied Individuals
Authors: Tajali Shirin , Fok Kai Lon , Theventhiran Pirashanth , Ye Gongkai , Yokoyama Hikaru , Nakagawa Kento , Masani Kei
Published: February 2022

Background: Functional electrical stimulation (FES) during rowing has substantial effects on cardiovascular health in individuals with spinal cord injuries. Currently, manual stimulation control where stimulation is operated by rowers is mostly utilized. However, it takes time to obtain the skill to initiate FES at the optimal timing. The purpose of this study was to develop a coaching system that helps rowers to initiate FES at the optimal timing. Methods: The optimal range for FES application was identified based on the electromyography of the left quadriceps in 10 able-bodied individuals (AB). Then, the effects of the coaching system on the timing of button-pressing, power, and work were investigated in 7 AB. Results: Vastus lateralis (VL) activation began consistently before the seat reached the anterior-most position. Therefore, seat position at the onset of VL was used as the variable to control the switch timing in the coaching system. The results revealed significantly higher power and work outputs in the coaching than the no-coaching condition (median power coaching: 19.10 W, power no-coaching: 16.48 W, p = 0.031; median work coaching: 109.74 J, work no-coaching: 65.25 J, p = 0.047). Conclusions: The coaching system can provide the optimal timing for FES, resulting in improved performance.
Two-Dimensional Transmission of Four-Dimensional LDPC-Coded Modulation with Slepian Sequences for DSP-Free 40 km Metro Network Applications
Authors: Han Xiao , Djordjevic Ivan B.
Published: February 2022

The growing data demands are pushing researchers to pay more attention to spectrally efficient modulation formats. The four-dimensional (4D) signal constellation modulation format has been investigated for metro networks’ applications to achieve better power efficiency. To cope with such modulation formats, the requirement of better digital signal processing (DSP) is also increasing rapidly. More complicated DSPs bring us extra costs; thus, the DSP-free coherent receivers are also investigated because of the high-power consumption of conventional DSP-based receivers, but the transceivers upgrading also results in extra costs. In this invited paper we implement a 4-dimentional modulation format based on Slepian sequences. We applied LDPC coding and experimentally investigated the BER performance in a two-dimensional (2D) 40 km fiber link transmission and demonstrate that being error free is possible without employing the complicated DSP. We compared our proposed modulation scheme with regular 16QAM and found it outperforms 16QAM with DSP over back-to-back transmission by 3.8 dB improvement in OSNR when BER = 10−5, while over 40 km metro network communication link our proposed 4D modulation signals are still successfully transmitted, and the LDPC-coding still works properly with such a new transmission strategy. On the other hand, DSP-free transmission of LDPC-coded 16-QAM exhibits an early error floor phenomenon.
Spectral Diagnostic Model for Agricultural Robot System Based on Binary Wavelet Algorithm
Authors: Wu Weibin , Tang Ting , Gao Ting , Han Chongyang , Li Jie , Zhang Ying , Wang Xiaoyi , Wang Jianwu , Feng Yuanjiao
Published: February 2022

The application of agricultural robots can liberate labor. The improvement of robot sensing systems is the premise of making it work. At present, more research is being conducted on weeding and harvesting systems of field robot, but less research is being conducted on crop disease and insect pest perception, nutritional element diagnosis and precision fertilizer spraying systems. In this study, the effects of the nitrogen application rate on the absorption and accumulation of nitrogen, phosphorus and potassium in sweet maize were determined. Firstly, linear, parabolic, exponential and logarithmic diagnostic models of nitrogen, phosphorus and potassium contents were constructed by spectral characteristic variables. Secondly, the partial least squares regression and neural network nonlinear diagnosis model of nitrogen, phosphorus and potassium contents were constructed by the high-frequency wavelet sensitivity coefficient of binary wavelet decomposition. The results show that the neural network nonlinear diagnosis model of nitrogen, phosphorus and potassium content based on the high-frequency wavelet sensitivity coefficient of binary wavelet decomposition is better. The R2, MRE and NRMSE of nn of nitrogen, phosphorus and potassium were 0.974, 1.65% and 0.0198; 0.969, 9.02% and 0.1041; and 0.821, 2.16% and 0.0301, respectively. The model can provide growth monitoring for sweet corn and a perception model for the nutrient element perception system of an agricultural robot, while making preliminary preparations for the realization of intelligent and accurate field fertilization.
A New Framework for Precise Identification of Prostatic Adenocarcinoma
Authors: Ayyad Sarah M. , Badawy Mohamed A. , Shehata Mohamed , Alksas Ahmed , Mahmoud Ali , Abou El-Ghar Mohamed , Ghazal Mohammed , El-Melegy Moumen , Abdel-Hamid Nahla B. , Labib Labib M. , Ali H. Arafat , El-Baz Ayman
Published: February 2022

Prostate cancer, which is also known as prostatic adenocarcinoma, is an unconstrained growth of epithelial cells in the prostate and has become one of the leading causes of cancer-related death worldwide. The survival of patients with prostate cancer relies on detection at an early, treatable stage. In this paper, we introduce a new comprehensive framework to precisely differentiate between malignant and benign prostate cancer. This framework proposes a noninvasive computer-aided diagnosis system that integrates two imaging modalities of MR (diffusion-weighted (DW) and T2-weighted (T2W)). For the first time, it utilizes the combination of functional features represented by apparent diffusion coefficient (ADC) maps estimated from DW-MRI for the whole prostate in combination with texture features with its first- and second-order representations, extracted from T2W-MRIs of the whole prostate, and shape features represented by spherical harmonics constructed for the lesion inside the prostate and integrated with PSA screening results. The dataset presented in the paper includes 80 biopsy confirmed patients, with a mean age of 65.7 years (43 benign prostatic hyperplasia, 37 prostatic carcinomas). Experiments were conducted using different well-known machine learning approaches including support vector machines (SVM), random forests (RF), decision trees (DT), and linear discriminant analysis (LDA) classification models to study the impact of different feature sets that lead to better identification of prostatic adenocarcinoma. Using a leave-one-out cross-validation approach, the diagnostic results obtained using the SVM classification model along with the combined feature set after applying feature selection (88.75% accuracy, 81.08% sensitivity, 95.35% specificity, and 0.8821 AUC) indicated that the system’s performance, after integrating and reducing different types of feature sets, obtained an enhanced diagnostic performance compared with each individual feature set and other machine learning classifiers. In addition, the developed diagnostic system provided consistent diagnostic performance using 10-fold and 5-fold cross-validation approaches, which confirms the reliability, generalization ability, and robustness of the developed system.