bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultrastructure morphology of antennae and mouthparts of in-vasive pest Aethina tumida (Coleoptera: Nitidulidae)
Authors: Chen Xiao-Xiao , Chen Rui-Ling , He Ding-Kun , Huang Min 
Published: October 2022

AbstractThe small hive beetle (SHB), as one of the six major pathogens of honeybee, has invaded China in recent years and caused serious harm to the apiculture industry of China. In order to explore the feeding mechanism ofAethina tumida, we used scanning electron microscopy for the first time to conduct a detailed study on the morphology and structure of antennae and mouthparts, including the distribution and abundance of sensilla. The results showed that its clavate antennae and chewing mouthparts are similar to those of other nitidulid on the structure and types of sensilla. There are 5 types of sensilla were identified on antennae: 3 subtypes of sensilla chaetica (SC), 1 type of sensilla trichodea (SP), 6 subtypes of sensilla basiconica (SB), 2 subtypes of sensilla styloconica (SS) and 1 type of Böhm bristles (BB); 8 types of sensilla on mourthparts: 1 type of SC, 8 subtypes of SB, 2 subtypes of SP, 2 subtypes of SS, 1 type of SM, 1 type of sensilla coelocinica (Sco), 2 subtypes of campaniformia (Scam) and 1 type of BB. We also compared the differences of sensilla with the only reported nitiduline speciesOmositacolonand inferred their sensory function.
The correlation between Comprehensive Geriatric Assessment parameters and cognitive impairment in elderly inpatients
Authors: Ju Yanmin , Liang Hong , Yang Di , Cao Mengyu , Jin Huijing , Leng Jiyan 
Published: October 2022

Abstract
Background: Cognitive impairment is common in elderly inpatients and is associated with many diseases and leads to adverse outcomes. However, there is currently no reversible treatment, so preventing cognitive impairment is critical.
Objective: Statistical methods were used to explore the correlation between the Comprehensive Geriatric Assessment and cognitive impairment in elderly inpatients.
Methods: A cross-sectional study of 168 hospitalized patients aged 60 years and older from the Comprehensive Geriatric Assessment database was conducted. Develop a Comprehensive Geriatric Assessment checklist to screen for general characteristics, the ability of daily life, geriatric depression, frailty, nutritional status, anthropometric measurements (body mass index, body fat percentage, and lower limb muscle mass), and blood biochemical markers (hemoglobin, albumin, prealbumin, triglycerides, low density lipoprotein cholesterol, high density lipoprotein cholesterol, and fasting blood glucose). Mini-mental State Examination was also conducted for each elderly patient to screen for cognitive impairment. Multiple linear logistic regression analysis was used to determine the correlation between Comprehensive Geriatric Assessment parameters and geriatric cognitive impairment.
Results: Finally, there were 26 patients (15.48%) in the cognitive impairment group with a median age of 89.00 years, and 142 patients (84.52%) in the normal cognitive function group with a median age of 79.00 years. Patients in the cognitive impairment group were older (P<0.001), had poorer ability of daily life (P<0.001), and had higher low density lipoprotein cholesterol concentrations (P=0.002) compared with the control group. In the multiple linear logistic regression analysis, Mini-mental State Examination scores was inversely associated with age (β=-0.089, P<0.001), activities of daily living and instrumental activities of daily living scores (β=-0.146, P<0.001), and low density lipoprotein cholesterol concentrations (β=-0.906, P<0.001).
Conclusion: Our findings suggest that Comprehensive Geriatric Assessment parameters such as age, the ability of daily life, and low density lipoprotein cholesterol concentrations are associated with cognitive impairment. Mini-mental State Examination scores were inversely correlated with age, activities of daily living and instrumental activities of daily living scores, and low-density lipoprotein cholesterol concentrations. Improving the ability to perform daily living and low-density lipoprotein cholesterol concentrations may help prevent cognitive impairment.
Carbon Emission Prediction Model of Metal Mine Underground Mining Stage
Authors: Wenbo Wu , Wei Wang , Yong Hu , Gaofeng Ren , Yuwei Yin 
Published: October 2022

Abstract
At present, the carbon emissions in China's mining industry can only be calculated based on the amount of energy consumed in the mining process. However, there are not enough effective means to reasonably estimate the carbon emissions before mining. Given the above problems, based on the ' top-down ' carbon emission accounting method provided by IPCC, this study selects the production processes including drilling, blasting, ventilation, drainage, compressed air, transportation, and filling as the carbon emission accounting boundary, and proposes a carbon emission prediction model for the underground mining stage of metal mines. The model can estimate the carbon emission after mining according to the mining design data before the start of mining activities. Taking a gold-copper mine in Daye City, Hubei Province as an example, the theoretical carbon emissions in mining per cubic meter’s rock mass in each process are calculated according to its production design data. Among them, the carbon emissions of compressed air and ventilation are the highest, reaching 22.00 kg CO2/m3, and 10.10 kg CO2/m3, respectively. By contrast, the carbon emissions of rock drilling, drainage, and filling material pumping are 5.87 kg CO2/m3, 6.80 kg CO2/m3, and 7.79 kg CO2/m3, respectively. To validate the model, the calculation results are compared with the actual energy consumption data of the mine. The estimated overall relative error is 10.68 %. Finally, it is calculated that when the free carbon quota ratio is 50 % and the carbon price is 93 yuan/t, the carbon emission cost of the gold-copper Mine will reach 0.89 yuan/t and 0.51 yuan/t.
Exercise rescues cognitive impairment through the fibrinogen pathway in diabetes
Authors: Lu Dongwei , Qu Chujie , Fang Mei , Sun Dong , Zhang Junjian 
Published: October 2022

Abstract

Background:Fibrinogen is proved to play a vital role in the activation of neuroinflammation. Exercise rescues the cognitive deficits due to diabetes. However, the molecular protective mechanism of exercise mediated by fibrinogen cascade following BBB leakage still remains elusive in diabetes.Methods:This research focused on assessing the influence of fibrinogen on neuroinflammation and blood-brain barrier(BBB) and the role of exercise in improving cognitive function in diabetic rats by using stereotaxic FGG-AAV(fibrinogen gamma chain with adeno-associated viral vector )injection procedures.Results:Exercise improved learning and memory function by inhibiting fibrinogen level in diabetic rats. Exercise intervention decreased the production and activation of microglia and astroglia of diabetic rats. Increased FGG expression in diabetic rats significantly inhibited the protective effects of exercise on hippocampal EB leakage, BBB-related protein ZO-1 and Claudin-5 expression, and MMP-9 protein expression level. The expression level of inflammatory factors IL-1β and TNFαwere inhibited in exercise group, while overexpressing FGG level would compromise the protective effects of exercise.Conclusion:Exercise can improve cognitive impairment in diabetic rats by down-regulating the expression of fibrinogen, inhibiting the neuroinflammation process, and reducing blood-brain barrier damage.
How much does genetics add to screening? Breast cancer risk stratification using genetic and non-genetic risk assessment tools for 246,142 women in the UK Biobank.
Authors: Li Jingmei , Ho Peh Joo , Lim Elaine , Hartman Mikael , Wong Fuh Yong 
Published: October 2022

Abstract
Background
The topic of whether genetic screening for cancer risk should be implemented is complex. Using UK Biobank data, we 1) computed optimal risk thresholds for the detection of breast cancer, 2) examined the overlap of high-risk individuals identified by different risk predictors, and 3) evaluated the performance of risk predictor combinations.
Patients and methods
We studied 246,142 women without breast cancer at study entry. Risk predictors assessed include: the Gail model (GAIL), family history of breast cancer (FH, binary), 313-SNP breast cancer polygenic risk score (PRS), and carriership of loss-of-function variants in at least one of the 9 breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51D, RAD51C, and TP53) (LoF). Absolute risk for developing invasive breast cancer was computed. Youden J-index was used to select optimal thresholds for defining high-risk.
Results
In total, 147,399 were considered at high risk for development of breast cancer within the next two years by at least one of the four breast cancer risk assessment tools examined (Gail2 − year>0.5%: 47%, PRS2 − year>0.7%: 30%, FH: 6%, and LoF: 1%); 92,851 (38%) were flagged by only one risk predictor. Seventy-nine percent of the breast cancers that did develop within the next two years were from the high-risk group. When compared to a random sample, the biggest gain in proportion of breast cancer cases was found within women at PRS high-risk, followed by GAIL, FH and LoF. The best-performing combinatorial model comprises a union of high-risk women identified by PRS, FH, and LoF (AUC2 − year [95% CI]: 62.2 [60.8 to 63.6]). Assigning individual weights to each risk prediction tool appeared to increase the discriminatory ability.
Conclusion
Our findings suggest that risk-based breast cancer screening may require a multi-pronged approach that includes PRS, breast cancer predisposition genes, family history, and other recognized risk factors.
Tensile and surface hydrophobicity investigation of the novel synthesized cellulose derivative films
Authors: Kallakas Heikko , Kilumets Catherine , Tarasova Elvira , Krasnou Illia , Savest Natalja , Gudkova Viktoria , Ahmadian Iman , Krumme Andres , Kers Jaan 
Published: October 2022

Abstract
Thermoplastic cellulose esters are promising materials for bioplastic packaging. For that usage, it is important to understand their mechanical and surface wettability properties. In this study, series of cellulose esters are prepared such as laurate, myristate, palmitate and stearate. The aim of the study is to investigate the tensile and surface wettability properties of the novel synthesized cellulose derivatives to understand their suitability as bioplastic packaging material. Cellulose derivatives are first synthesized from microcrystalline cellulose (MCC), then dissolved in pyridine solution and after solvent casted to thin films. Cellulose derivatives acetylation process is characterized with the FTIR method. Cellulose esters hydrophobicity is evaluated with contact angle measurement. The mechanical properties of the films are tested with the tensile test. For all of the synthesized films, FTIR provide clear evidence of acylation by showing presence of characteristic peaks. Films mechanical properties are comparable to generally used plastics such as LDPE and HDPE. Furthermore, with the increase in side-chain length, the water barrier properties improved. These results show that they are potentially suitable materials for films and packaging materials.
Between Fixed and Extending Means for Quantifying Historical Drought Events
Authors: Al-Kilani Muhammad Rasool , Al-Bakri Jawad , Rahbeh Michel 
Published: October 2022

Abstract
Drought analysis has become an essential task, due to the impacts of drought on global food security and all aspects of human life. However, drought monitoring does not follow a specific formula but is more a process, thus it is important to examine the details accounted by using different approaches. The Standardized Precipitation Index (SPI), the most widely used for quantifying drought, represents drought intensity for a given time window based on a long-term precipitation mean for a time series. This paper briefly discusses the use of “fixed” or “extending” means; a meteorologist or a webapp recording drought in real time and documenting values in a fixed archive may be using an extending mean, as their long-term mean may change each subsequent year. Meanwhile, someone calculating SPI for historical years may consider that the mean precipitation time series up to his current time as the long term “fixed” mean. In this paper, the 3-month SPI for Al-Mafraq in Northern Jordan was calculated for the period 2011 – 2019, once using a fixed mean, and once using an extending mean method. The results show that no considerable difference in values can be detected (mean absolute error = 2%), but different drought categories may result from the two methods, particularly in the beginning of the time series. This paper strongly suggests that all details involved in calculating drought indices should be communicated when sharing drought-related data, and some terminology should be agreed upon. This paper also presents some suggestions when considering an approach or software for drought analysis and quantifying historical drought.
Bio-based Building Material Solutions for Environmental Benefits over Conventional Construction Products - Life Cycle Assessment of Regenerative Design Strategies (1/2)
Authors: Mouton Lise , Allacker Karen , Röck Martin 
Published: October 2022

Abstract
The focus in reducing environmental impacts of buildings is shifting from the operational stage to the full life cycle, with particular attention to embodied greenhouse gas (GHG) emissions of construction materials. The application of bio-based construction materials is promoted for potentially reducing material-related embodied GHG and even enabling carbon fixation. In part one of this study (1/2), we apply life cycle assessment (LCA) to critically examine regenerative design strategies, starting by investigating embodied GHG emissions as well as other environmental impact indicators of different bio-based building element variants – assessing timber-, straw- and hemp-based solutions - in a European context. The results show that bio-based building elements tend to have considerably lower embodied GHG emissions than conventional solutions, e.g., brick or concrete-based elements. Analyzing the environmental hotspots across the life cycle of selected bio-based construction options, we identify their most contributing environmental indicators to be global warming potential (GWP), particulate matter (PM) and land use (LU); and the most important life cycle stages to be material production, maintenance and replacement, particularly of finishes. To investigate carbon removal potentials, we calculated biogenic carbon contents of selected bio-based options, identifying straw-based building elements as the most promising solution due to high biogenic carbon content and fast (yearly) re-growth cycles. Our study highlights the environmental potentials of using bio-based construction solutions to substitute conventional building materials. In addition, the study identifies important environmental trade-offs within bio-based material alternatives that demand consideration and further study in future research.
Quality of Cold Plasma Treated Casein Peptide Targeting SARS-CoV2: An In-silico Approach
Authors: Dash Samarpita , Jaganmohan R. 
Published: October 2022

Abstract
Raw cow milk being a highly nutritive but its contamination is one of the factors that has to be considered. Thermal treatment is generally adopted for decontamination of milk but at the same time it degrades the protein quality. Hence, there is a need for new treatment method with least processing technology to maintain the food quality. These challenges forced the scientist to introduce non-thermal technologies. The objective of the present study to elucidate the effect of optimized set up for plasma bubbling on casein protein and peptide with respect to raw cow milk. Structural characterization of casein was done using FTIR. The casein protein hydrophobicity was maintained well and Mascot result revealed a non-detrimental effect to α-s1casein peptide upon the treatment. Specifically, casein peptides are good source of ACE inhibitory peptides. While, ACE2 receptor is responsible for binding of SARS-CoV2. Therefore, this study implemented on most effective ACE inhibitory peptide (RYLGY) which was observed in Mascot analysis, for both control and treated sample arising from peak at 1267m/z in MALDI-TOF of α-s1-casein. The peptide was considered for in-silico docking approach against SARS-CoV2. Interestingly, ACE2-RBD-peptide complex showed good binding score, suggesting that the peptide molecule disturbed the complex formation.
Secure and Trust-based Model for E-Commerce application
Authors: Gao Weiji , Ding Zhihua , Crespo Rubén González , Martínez Oscar Sanjuán 
Published: October 2022

Abstract
The reviews of customers in E-Commerce Systems are typically considered key resources, are reflecting the experiences, sentiments, and readiness of the customer to buy products. All such data may include perspectives of customers on matters of interest, feelings, and opinions. Various studies have demonstrated that individuals with comparable attitudes about the topics are more inclined to trust one another. This study explores searching for and adopting e-commerce services with sentimentsand recommendations that involve some customer trust.A trust-based model for the E-commerce application (TM-ECA) model is proposed in this article. From that perspective, an e-commerce system examines a strategy for examining sentimental similarities based on mining to examine consumers' similarities and confidence. Trust is divided into two classifications: direct trust and common trust that is a connection of trust among two people. The direct level of trust is acquired through feeling resemblance, and a pair of words for retrieving comparable characteristics isavailable.The transitivity characteristic determines the spread of trust. The smallest path is selected to express confidence and offer an enhanced smallest path method to identify the link between consumers' confidence in transmission using the suggested confidence model. To check the correctness and practicality of methods and the designs, a website for e-commerce evaluates the method. The testing results show that the sentimental evaluation of resemblance can be an effective way of finding confidence among e-commerce system customers.
Removal of acid yellow dye 17 from aqueous solutions using an activated bone char
Authors: Kerie Endalkachew , Alemu Agegnehu 
Published: October 2022

Abstract
Textile dyes are causing serious environmental problems in the world. The treatment of dyes from textile wastewater is necessary to protect the environment. Adsorbents with high adsorption potential from local materials are required to solve these problems. In this study, the treatment of acid yellow 17 dye from aqueous solutions was carried out using an activated bone char, collected from slaughterhouses. The dye removal performance was measured using a UV-Vis spectrometer. Adsorption experiments were carried out in a batch process under different operating conditions including initial dye concentration, adsorbent dose, contact time, and solution pH. From the experimental data, the maximum dye removal efficiency of 91.43% was achieved at an optimum pH of 2, contact time of 120 min, initial dye concentration of 50 mg/L, and adsorbent dose of 20 g/L. Adsorption models: adsorption isotherm and adsorption kinetics of acid yellow 17 dye onto the activated animal bone char, the data fitted well with the Langmuir isotherm model (R2 = 0.9245) and pseudo-second-order model (R2 = 0.9967), respectively. This study indicated that the activated bone char, which is obtained from animal slaughterhouses and discharged as waste into the environment has a high potential to remove acid yellow 17 dye from polluted water.
Pharmacologic Treatment of Type 2 Diabetes in the U.S., Sweden, and Israel
Authors: Lyu Beini , Sang Yingying , Selvin Elizabeth , Chang Alex R. , Alexander G. Caleb , Cohen Cheli Melzer , Coresh Josef , Shalev Varda , Chodick Gabriel , Karasik Avraham , Carrero Juan-Jesus , Fu Edouard L. , Xu Yang , Grams Morgan E. , Shin Jung-Im 
Published: October 2022

OBJECTIVE
To characterize and compare glucose-lowering medication use in type 2 diabetes in the U.S., Sweden, and Israel, including adoption of newer medications and prescribing patterns.

RESEARCH DESIGN AND METHODS
We used data from the National Health and Nutrition Examination Survey (NHANES) from the U.S., the Stockholm CREAtinine Measurements (SCREAM) project from Sweden, and Maccabi Healthcare Services (Maccabi) from Israel. Specific pharmacotherapy for type 2 diabetes between 2007 and 2018 was examined.

RESULTS
Use of glucose-lowering medications among patients with type 2 diabetes was substantially lower in NHANES and SCREAM than in Maccabi (66.0% in NHANES, 68.4% in SCREAM, and 88.1% in Maccabi in 2017–2018). Among patients who took at least one glucose-lowering medication in 2017–2018, metformin use was also lower in NHANES and SCREAM (74.1% in NHANES, 75.9% in SCREAM, and 92.6% in Maccabi) whereas sulfonylureas use was greater in NHANES (31.5% in NHANES, 16.0% in SCREAM, and 14.9% in Maccabi). Adoption of dipeptidyl peptidase 4 inhibitors and sodium–glucose cotransporter 2 inhibitors (SGLT2i) was slower in NHANES and SCREAM than in Maccabi. History of atherosclerotic cardiovascular disease, heart failure, reduced kidney function, or albuminuria was not consistently associated with greater use of SGLT2i or glucagon-like peptide 1 receptor agonists (GLP1RA) across the three countries.

CONCLUSIONS
There were substantial differences in real-world use of glucose-lowering medications across the U.S., Sweden, and Israel, with more optimal pharmacologic management in Israel. Variation in access to care and medication cost across countries may have contributed to these differences. SGLT2i and GLP1RA use in patients at high risk was limited in all three countries during this time period.
Formalizing choice of priority investment strategy
Authors: Fyedorova Natalya Vasilevna , Akperov Imran Gurruevich 
Published: October 2022

The paper considers the development of a method of forming and evaluating the priority of investment strategies aimed at creating technological (production) objects. A formalized approach to the formation and ranking
of investment projects is presented: the statement of the investment problem is formalized; a formalized analytical expression of the investment project is given. Possible factors and components of investment as components of an investment project are considered. Factors and criteria for evaluating the projects, ranking options, the role of the investor, a regulatory body and a decision maker in the formation of the project evaluation are considered. The role and directions of forming the components of the descriptive factor, financial and non-financial restrictions are shown. Methods of developing and ranking strategies for investing in technical and technological projects have been developed and presented in the form of a flowchart and of analytical constructions. Formalization of the processes of development and evaluation of investment projects will provide a systematic approach to the investment design, create the conditions for algorithmization and automation of priority investment strategies formation and selection.