bluuebunny/crossref_metadata_2025_split huggingface dataset:
Human-Computer Interaction Facial Recognition in Music Teaching System Based on Parameter extraction algorithm
Authors: Huang Qian 
Published: March 2023

Abstract
Speech recognition technology becomes the focus of attention of major research institutions in the world. People hope that machines can understand human voice commands and that they can control machines with voice. Therefore, the research and development of voice recognition will make people's lives easier in the near future. The feature parameter selected in this paper is the Mel-Zepstr coefficient. It analyzes the MFCC parameter extraction process in detail and proposes an improved MFCC extraction algorithm. Compared with the traditional MFCC extraction algorithm, the calculation amount is reduced by nearly 50% and the feature is improved. With the increasing use of mobile robots in the service industry, technologies for human-computer interaction (such as face recognition) have attracted more and more attention. In order to meet the real-time and efficiency requirements of real robot platforms, and to improve the accuracy of feature extraction under various lighting conditions and facial recognition technology positions, this paper, facial recognition and feature tracking are analyzed. In setting the voice recognition and face recognition module function of human-computer interaction, this article will combination of traditional music teaching and related new technologies, the facial recognition and voice recognition, strengthen the function of music teaching system, in the traditional classroom teaching, homework management, music practice, on the basis of the information to inform, From two aspects of voice and face, to meet the music classroom online when the need for information function. It can not only enable music teachers to observe each student's expression and action through facial recognition, strengthen expression management, but also enable music teachers to analyze each student's musical expression, so as to provide more comprehensive guidance for students.
Olive oil and coconut oil improved the quality and digestibility of set soybean yoghurt
Authors: Cai Wen qi , Cao Shufang , Xia Mingjie , Zhang Guangchen , Huo Dafei , Yang Lina , Liu He 
Published: March 2023

Abstract

Most set soybean yoghurts have the problem of poor taste and flavor, and the overall quality is not as good as that of fermented milk. In order to improve the quality of set soybean yoghurt and to improve the flavor of set soybean yoghurt, a plant oil with pleasant flavor was added in the preparation of set soybean yoghurt. The effects of the addition of olive oil and coconut oil on the physicochemical quality, sensory quality, and nutritional quality of set soybean yoghurt, as well as the effects of fermentation and in vitro digestion on the distribution of oil in set soybean yoghurt, were investigated. Three kinds of set soybean yoghurt without oil, with coconut oil, and with olive oil were prepared. The results of GC–MS analysis showed that the set soybean yoghurt without oil contained only two esters and one alcohol: delta-dodecalactone, 5-decanolide, andR-(−)-2-butanol. The set soybean yoghurt with olive oil was characterized by five volatile flavors: hexanoic acid, 2-nonanol, phenylacetaldehyde, 3-heptylacrolein, and acetylpyrazine. The set soybean yoghurt with coconut oil was characterized by nine volatile flavors: 5-hydroxyoctanoic acid lactone, ethyl caprylate, ethyl caprate, ethyl laurate, 2-tridecanone, dihydro-2-methyl-3(2H)-thiophenone, lauric acid, 1-octanol, and 2-decanol. Gas chromatographic analysis showed that the set soybean yoghurt without added oil contained seven free fatty acids. The set soybean yoghurt with olive oil contained 10 kinds of free fatty acids and was high in oleic acid. The set soybean yoghurt with coconut oil contains nine kinds of fatty acids and is rich in lauric acid. By laser confocal microscopy observation, the oil droplets in the three groups of set soybean yoghurt were aggregated after fermentation, and the oil droplets in the three groups of set soybean yoghurt were reduced after digestion. Research has proved that adding an appropriate amount of olive oil or coconut oil to set soybean yoghurt can improve the taste and the flavor, and that the addition of oil does not increase the digestive burden.
Ancient, veteran and other listed trees as nest sites for wild honey bee, Apis mellifera, colonies
Authors: Visick Oliver David , Ratnieks Francis Leonard Waldemar 
Published: March 2023

Abstract

Implications for insect conservation: Our results show that ancient, veteran and other listed trees provide valuable nesting habitat for wild honey bee colonies in southeast England. Based on an occupancy rate of 2% and a recent estimate of 2 million TSIs in England, it is possible that TSIs support tens of thousands wild honey bee colonies across Britain and that wild colonies are a significant component of total colony numbers in areas with a high density of TSIs (>50 per km2). Wild honey bee (Apis mellifera) colonies naturally nest in old cavity-bearing trees throughout their range, but this important nesting habitat is in global decline. Here we determine the use of ancient, veteran and other listed trees as nest sites by wild honey bee colonies in Britain and investigate the effect of tree size, age, genus and management on occupancy. Over 1,000 trees of special interest (TSIs) were located in southeast England using the Ancient Tree Inventory (ATI) of the Woodland Trust, a charity that protects and promotes trees in Britain. 2% of all TSIs and 4% of TSIs with cavities were occupied by wild honey bee colonies (n=20). Occupancy positively correlated with tree diameter and nearest neighbour distance, suggesting that colonies are more common in large open-grown trees. Wild colonies occupied sweet chestnut (Castanea sativa) and maiden (unmanaged) trees more frequently than expected (7% and 2.7%, respectively, versus 2% overall). Sweet chestnuts have a large mean diameter (1.6m) and proportion of trees with cavities (73%), but these were no different from average in maiden trees (1.4m and 47%, respectively) and did not help explain occupancy.
Amorphous MOFs layer boosts the performance of metal anodes
Authors: Xiang Yang , Zhou liyuan , tan pingping , Dai Shuai , Wang Yannan , Bao Shu-Juan , Jiang Yinzhu , Lu Yingying , Xu Maowen , Zhang Xuan 
Published: March 2023

AbstractEmploying metal anodes can greatly increase volumetric/gravimetric energy density versus a conventional ion-insertion anode. However, metal anodes are plagued by dendrites, corrosion, and interfacial side reactions issues. Herein, a compact and flexible amorphous MOF layer was successfully synthesized and used as protective layer on metal anode aqueous zinc-ion battery (AZIB). Compared with the crystalline MOF layer, the unique amorphous MOF layer can inhibit dendrite growth at the grain boundary and eliminate ions migration near the grain boundary, showing high interfacial adhesion and large ion migration number (tZn2+ = 0.82). Besides, the amorphous MOF layer can effectively depress unfavored behaviors, e.g., corrosion of zinc anode, hydrogen evolution reaction, and dendrite growth on zinc surface. The prepared Zn anode with the amorphous MOF layer exhibited an ultra-long cycle life (ten months, 7000 h) and a low voltage (< 40 mV) at 1 mA cm-2 in a symmetrical cell. Even at 10 mA cm-2, it still showed a high stability for more than 5500 cycles (1200 h). The enhanced performance is realized for full cells paired with a MnO2 cathode. Besides, a flexible symmetrical battery with the Zn@A-ZIF-8 anode exhibited a good cyclability under different bending angle (0°, 90°, and 180°). Moreover, various metal substrates were successfully coated with compact A-ZIF-8. The A-ZIF-8 layer can obviously improve the stability metal anodes, including Zn, Mg and Al. The results not only demonstrate the high potential of amorphous MOFs decorated Zn anodes for AZIBs, but also propose a new family of protective layers for metal anodes.
A Self-Assessment on Online Learning Efficiency by Medical Students in a Chinese Medical University during the Early Phase of the COVID-19 Outbreak
Authors: Shen Ying , Yang Danqing , Ma Jiaqi , Huang Minting , Lan Yumei , Fan Shujing , Zuo Yanli 
Published: March 2023

Abstract
Background
At the initial stage of COVID-19 outbreak, most medical education institutions in China had to accept the sudden shift from classroom teaching to nearly 100% online instruction for different curricula. However, little has been known about medical students’ learning efficiency when learning has been completely conducted online. This study aimed at investigating medical students’ perspectives on online learning efficiency during the early phase of the COVID-19 outbreak and finding possible factors that could damage online learning efficiency.
Methods
Between May and July, 2020, the authors electronically distributed a self-designed questionnaire to all the 780 medical students who attended the Rural-oriented Free Tuition Medical Education program in Guangxi Medical University that locates in the southwestern China. Data on participant demographics, learning phases, academic performance, and perceptions regarding learning efficiency of online and classroom learning were collected. Wilcoxon rank sum test, Kruskal Wallis test, and polynomial Logistic regression were employed to detect differences of learning efficiency between online and classroom learning, and associations among learning phases, academic performance and online learning efficiency.
Results
A total of 612 medical students validly responded to this survey (valid response rate 78.46%), and they reported more positive perceptions of efficiency in the circumstance of face-to-face learning than of online learning despite of gender (P<0.001), learning phases (P<0.01), and academic performance (P<0.01). Learning phases and academic performance positively corelated with online learning efficiency (P<0.01). In responders’ opinion, the five top factors that most damaged online learning efficiency were low academic motivation, poor course design, inferiority in online teaching ability, limited interactions between faculty and students or among students, and insufficient learner engagement.
Conclusion
This study indicates obviously negative impact brought by pure online learning on perceived learning efficiency of medical students, and positive associations amid learning phases, academic performance, and online learning efficiency. We advise that instead of pure online instruction, more effort should be put into developing new online course design to improve learning efficiency when online instruction is conducted in large scale, and learning phase and academic performance should be taken into account for effective implementation of online learning.
Amyloid-Eszett (Aß), a false positive of amyloid-beta (Aβ), in the neurodegenerative disease literature: A bibliometric assessment
Authors: Nazarovets Serhii , Silva Jaime A. Teixeira da 
Published: March 2023

Abstract
One of the most prominent neurodegenerative diseases is Alzheimer’s disease (AD), one cause of which is the extracellular aggregation of amyloid-beta (Aβ). Some literature related to AD has represented the Greek letter β with the German letter Eszett (ß), resulting in the formation of a non-existent compound, amyloid-Eszett(Aß). This study aimed to quantify the AD-related literature in the Web of Science Core Collection carrying a mention of this false positive. A search on November 22, 2022 revealed 134 results. The highest incidence of false positives per year was observed in 2012 (41 cases). The journal with the highest incidence of amyloid-ß was the Journal of Neurochemistry (nine times), most cases (58) were found in Wiley journals, while authors with a US affiliation accounted for most (38) false positives. A Scopus search on the same date revealed 327 false positives, highest in 2020 (50 cases), most in Journal of Alzheimer's Disease (34 times), and most frequently by corresponding authors with a US affiliation (92 times). This erroneous substitution of a Greek letter (in Aβ) by a German one (Aß), despite giving a non-existent compound, will likely not change the underlying scientific conclusions of the affected papers, although errata might be useful to enlighten others, including metadata managers and journal copyeditors, so as not to repeat the same mistake.
Impact of translation on biomedical information extraction from real-life clinical notes
Authors: Gérardin Christel , Xiong Yuhan , Wajsbürt Perceval , Carrat Fabrice , Tannier Xavier 
Published: March 2023

Abstract
The objective of our study is to determine whether using English tools to extract and normalize French medical concepts on translations provides comparable performance to French models trained on a set of annotated French clinical notes.
We compare two methods: a method involving French language models and a method involving English language models. For the native French method, the Named Entity Recognition (NER) and normalization steps are performed separately. For the translated English method, after the firsttranslation step, we compare a two-step method and a terminology- oriented method that performs extraction and normalization at the same time. We used French, English and bilingual annotated datasets to evaluate all steps (NER, normalization and translation) of our algorithms.
Concerning the results, the native French method performs better than the translated English one with a global f1 score of 0.51 [0.47;0.55] against 0.39 [0.34;0.44] and 0.38 [0.36;0.40] for the two English methods tested.
In conclusion, despite the recent improvement of the translation models, there is a signifi- cant performance difference between the two approaches in favor of the native French method which is more efficient on French medical texts, even with few annotated documents.
Coherence based automatic short answer scoring using sentence Embedding
Authors: DADI RAMESH , Sanampudi Suresh Kumar 
Published: March 2023

Abstract
Automatic essay scoring is an essential educational application in natural language processing (NLP). This automated process will alleviate the burden and increase the reliability and consistency of the assessment. With the advance in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy. However, the actual goals are not attained, like embedding essays into vectors with cohesion and coherence, and providing feedback to students is still challenging. In this paper, we proposed coherence-based embedding of an essay into vectors using sentence-BERT (Bidirectional Encoder Representations from Transformers). We trained these vectors on Long Short-Term Memory (LSTM) and Bi-LSTM (Bidirectional Long Short-Term Memory) to capture sentence connectivity with other sentences' semantics. We used two different datasets; one is standard ASAP Kaggle, and another is a domain-specific dataset with almost 2500 responses from 650 students. Our model performed well on both datasets, with an average QWK (Quadratic Weighted Kappa ) score of 0.76. Furthermore, we achieved good results compared to other prescribed models, and we also tested our model on adversarial responses of both datasets and observed decent outcomes.
Development of an index predicts the in-patient mortality of COVID-19 patients presenting at a hospital in rural Michigan.
Authors: Varriano Brenda , Bhagat Yuvraj , Lepley Thomas , Sassine Antoine , Zikos Dimitrios , Ragina Neli , Megaly Maher , Tan Jaime , Haddad Nicholas 
Published: March 2023

Abstract
Background
Laboratory test results and chief complaints (CC) for patients hospitalized with COVID-19 can contribute to a better understanding of inpatient mortality risk. This study used a combination of lab test results on admission, demographic information, comorbidity data, and reported patient chief complaints to create a predictive model for inpatient mortality from COVID-19.
Methods
Clinical data were collected from a regional hospital (MI, USA). 1,093 COVID-19 patients were admitted. The CC, lab variables, and health comorbidities were inserted into a multiple binary logistic regression model alongside comorbidity information and the lab results, which was used to create a risk estimation tool for inpatient mortality in patients hospitalized with COVID-19.
Results
1,088 cases were included in the analysis. 23.25% of the hospitalized COVID-19 patients (N = 253) died. The average age of patients who died was 77.14 years (+/- 13.99) vs 64.22 years (+/- 18.35) for those who did not die. 49.9% (N = 545) of patients were female. Mortality was higher in non-white patients [OR = 3.7 (95% CI: 1.14–12.1)], those older in age [OR = 1.1 (95% CI: 1.04–1.14)]; those with a prior myocardial infarction/coronary artery disease [OR = 2.7 (95% CI: 1.02–7.03)], those with hypertension [OR = 5.2 (95% CI: 1.14–12.1)] and those with higher WBC counts [OR = 1.2 (95% CI = 1.02–1.50)]. High total protein indicated decreased mortality [OR = 0.4 (95% CI = 0.20–0.84)].
Conclusions
Multiple comorbidities are associated with greater mortality in those hospitalized with COVID-19. Understanding these risks will aid clinicians and healthcare systems in decision-making and allocation of resources to control disease burden.
Knowledge, Attitudes and Associated Factors of pre-hospital care Among Health Care Workers in Three Selected pre hospital care Center in Addis Ababa, Ethiopia, 2022
Authors: Koster Yohannes , Silesh Alemayehu 
Published: March 2023

Abstract

Back Ground:Pre-hospital care is an emergency medical care which is given to patients before arrival in hospital after activation of emergency medical services which is acknowledged as a crucial period, when irreversible pathology and secondary injury can be prevented. The aim of EMS focuses on providing timely care to victims of sudden and life-threatening injuries or emergencies in order to prevent needless mortality or long-term morbidity.Objective:To assessKnowledge, Attitudes and Associated Factors of pre-hospital care Among Health Care Workers in Three Selected pre hospital care Center in Addis Ababa, Ethiopia, 2022.Methods:institutional based cross sectional study design was conducted among HCW. The target population was HCW working at the pre-hospital care at three selected center Addis Ababa. The researcher was used questionnaire which is adopted from previous similar study. A questionnaire was distributed to consenting HCW for completion. Data was checked, cleared and entered in to SPSS version 25, then frequencies, distribution, mean computed and analysis were done to obtain the significant association by p=.25 at bivariate level then executed to multivariate logistic regression at p value 0.05.Result:One hundred thirty five study participants were included in this study with a response rate of 96.4%. The mean ages of the respondents were 29.2 years (SD ± 4.86). Almost three fourth of the study participants 96(71.1%) were in age between 26 and 35 years. Majority of the study participants 126(93.3%) responds that they knew about basic life support/advanced life support. 79(58.5 %) of the health care workers had good knowledge and 56(41.5%) had poor knowledge about pre-hospital care.Conclusion and recommendation:More than half of (58.5 %) of the health care workers had good knowledge about pre-hospital care and more than a half, eighty four (62.2%) had positive attitude towards pre-hospital care. Profession, educational status and training were significantly associated with knowledge of health care workers to wards pre-hospital care with p-value less than 0.05. Knowledge of the respondent and getting training were significantly associated attitude of health care workers towards pre-hospital care with p-value less than 0.05
Green synthesized Ag/rGO embedded flexible cotton SERS substrate for detection of methylene blue
Authors: Gokulakrishnan J , Sekhar K. C. , Koppole Kamakshi 
Published: March 2023

Abstract
Ag/rGO nanocomposite SERS substrates are widely used for the detection of contaminations in water and food adulterants. In this work, we prosed a novel green route to synthesize Ag/rGO nanocomposite for SERS-based detection of methylene blue (MB). Ag/rGO nanocomposite is synthesized by simultaneous reduction of AgNO3 and GO with the leaf extract of Jasmine fluminense. Further, the flexible SERS substrate is fabricated by directly coating the synthesized Ag/rGO nanocomposite on cotton fabric and used for SERS-based detection of MB. The SERS studies on MB show a linear response of 0.97 over a wide detection range of 10− 3 to 10− 9 M with a minimum detection limit of 10− 9 M. The enhancement factor for MB at a concentration of 10− 9 M is 5.33 × 105 with a high signal-to-noise ratio of 31.69. This study emphasizes the potential of green synthesized Ag/rGO embedded flexible cotton SERS substrate for the traceable fingerprint detection of MB.
The causal relationship between cheese intake and atherosclerosis: A two-sample mendelian randomization study
Authors: WEN Song , HUANG Zehan , HE Guodong , ZHANG Bin , HUANG Yuqing 
Published: March 2023

Abstract
Background Previous observational studies have yielded conflicting results regarding the association between cheese intake and atherosclerosis, and the relative contribution to each subtype (coronary atherosclerosis, peripheral atherosclerosis, cerebral atherosclerosis and arterial stiffness) remains unclear. We sought to systematically investigate the causal link between cheese intake and atherosclerosis.
Methods A two-sample MR study was conducted to investigate the causal relationship between cheese intake and atherosclerosis subtypes. Summary statistics from genome-wide associations of cheese intake (N= 451,486 individuals), coronary atherosclerosis (N= 14,334 cases, 346,860 controls), peripheral atherosclerosis (N= 6,631 cases, 162,201 controls), arterial stiffness (N= 151,053 individuals, no available cases/controls), cerebral atherosclerosis (N= 104 cases, 218,688 controls), and atherosclerosis (excluding cerebral, coronary and PAD) (N= 6,599 cases, 212,193 controls) were used in the MR study. Inverse variance weighted (IVW) analysis was utilized for the study's main result, and weighted median, MR Egger, and weighted mode analyses were used as complementary analyses to IVW. Moreover, the results were robustly examined through a sensitivity analysis.
Results Genetically predicted cheese intake was positively associated with coronary atherosclerosis (OR=0.98, 95%CI=0.97–0.99, P=0.002), peripheral atherosclerosis (OR=0.56, 95%CI=0.37–0.84, P=0.006), arterial stiffness (OR=0.87, 95%CI=0.81–0.94, P=0.001), and atherosclerosis (excluding cerebral, coronary and PAD) (OR=0.65, 95%CI=0.43–0.98, P=0.037) in the inverse variance weighted analysis. However, no causal relationship between cheese intake and cerebral atherosclerosis was observed (OR=0.91, 95%CI=0.07–11.28, P=0.941).
Conclusion Our two-sample MR analysis revealed that cheese intake was significantly associated with an increased risk of coronary atherosclerosis, peripheral atherosclerosis, arterial stiffness, and atherosclerosis (excluding cerebral, coronary and PAD). However, no causal relationship between cheese intake and cerebral atherosclerosis was observed in the MR analysis.