bluuebunny/crossref_metadata_2025 huggingface dataset:
Need for Widely Applicable Cultural Competencies in the Healthcare of Humans and Animals
Authors: Constantinou Costas S.
Published: August 2023

This entry discusses the importance of cultural competence in the healthcare of humans and animals, its challenges, its mixed research results, and the need for widely applicable competencies. Although there is research evidence showing that cultural competence is linked with patient satisfaction, better doctor–patient relationships, adherence to therapy, and to some extent, better health outcomes, there is a huge variety of models and competencies in the literature, which has sometimes resulted in inclusive outcomes, confusion as to what constitutes the necessary competencies, and patchy implementation. In spite of the development of cultural competence in human healthcare, its implementation in veterinary medicine remains poor. On this note, the aims of this entry are to provide a brief overview of the cultural competence in healthcare and veterinary medicine and education, to outline the important facts, and to highlight the need for more standardisation in implementing and testing widely applicable cultural competencies for both human and veterinary healthcare.
Repeatability of the European Standardized Method for Measuring Sound Reflection and Sound Insulation of Noise Barriers
Authors: Guidorzi Paolo , Garai Massimo
Published: August 2023

The EN 1793-5 and EN 1793-6 standards have been in use for many years as a method for measuring the intrinsic characteristics of noise barriers installed along highways and railways. They require a sound source and a grid of microphones, to be placed near the barrier and in free field conditions, according to predetermined distances. In principle, small errors in positioning the sound source and microphone grid may affect the results obtained. An international round-robin test was carried out in 2012 to evaluate the repeatability and reproducibility of the method, but until now no studies have been carried out to evaluate and compare the repeatability of laboratory versus in-place measurements performed with the same equipment and its variance when an imperfect positioning of sound source and microphones is taken into account. In the present work, multiple series of sound reflection index and sound insulation index measurements performed on noise barriers of the same kind installed in the laboratory or along a highway are presented. The measurements were repeated in different ways: (1) in the laboratory, leaving the source and microphones unmoved to assess the repeatability of the results and of the measurement system under controlled conditions; (2) in the laboratory, repositioning for each measurement the source and microphone grid to assess the robustness of the method under real conditions but in a controlled environment; (3) in situ, along a highway open to traffic, repositioning for each measurement the source and microphone grid to assess the repeatability of the method under real conditions in a critical environment. In both reflection index and sound insulation index measurements, the standard deviation on single-number ratings in all cases examined is well below the value presented in EN 1793-5 and EN 1793-6, which was obtained from statistical analysis of the international round-robin test performed a dozen years ago, suggesting that expert operators with state-of-the art equipment can achieve much better results now.
Deepening the Accuracy of Tree Species Classification: A Deep Learning-Based Methodology
Authors: Cha Sungeun , Lim Joongbin , Kim Kyoungmin , Yim Jongsu , Lee Woo-Kyun
Published: August 2023

The utilization of multi-temporally integrated imageries, combined with advanced techniques such as convolutional neural networks (CNNs), has shown significant potential in enhancing the accuracy and efficiency of tree species classification models. In this study, we explore the application of CNNs for tree species classification using multi-temporally integrated imageries. By leveraging the temporal variations captured in the imageries, our goal is to improve the classification models’ discriminative power and overall performance. The results of our study reveal a notable improvement in classification accuracy compared to previous approaches. Specifically, when compared to the random forest model’s classification accuracy of 84.5% in the Gwangneung region, our CNN-based model achieved a higher accuracy of 90.5%, demonstrating a 6% improvement. Furthermore, by extending the same model to the Chuncheon region, we observed a further enhancement in accuracy, reaching 92.1%. While additional validation is necessary, these findings suggest that the proposed model can be applied beyond a single region, demonstrating its potential for a broader applicability. Our experimental results confirm the effectiveness of the deep learning approach in achieving a high accuracy in tree species classification. The integration of multi-temporally integrated imageries with a deep learning algorithm presents a promising avenue for advancing tree species classification, contributing to improved forest management, conservation, and monitoring in the context of a climate change.
Risk Analysis of Laboratory Fire Accidents in Chinese Universities by Combining Association Rule Learning and Fuzzy Bayesian Networks
Authors: Yang Fuqiang , Li Xin , Yuan Shuaiqi , Reniers Genserik
Published: August 2023

Targeting the challenges in the risk analysis of laboratory fire accidents, particularly considering fire accidents in Chinese universities, an integrated approach is proposed with the combination of association rule learning, a Bayesian network (BN), and fuzzy set theory in this study. The proposed approach has the main advantages of deriving conditional probabilities of BN nodes based on historical accident data and association rules (ARs) and making good use of expert elicitation by using an augmented fuzzy set method. In the proposed approach, prior probabilities of the cause nodes are determined based on expert elicitation with the help of an augmented fuzzy set method. The augmented fuzzy set method enables the effective aggregation of expert opinions and helps to reduce subjective bias in expert elicitations. Additionally, an AR algorithm is applied to determine the probabilistic dependency between the BN nodes based on the historical accident data of Chinese universities and further derive conditional probability tables. Finally, the developed fuzzy Bayesian network (FBN) model was employed to identify critical causal factors with respect to laboratory fire accidents in Chinese universities. The obtained results show that H4 (bad safety awareness), O1 (improper storage of hazardous chemicals), E1 (environment with hazardous materials), and M4 (inadequate safety checks) are the four most critical factors inducing laboratory fire accidents.
Recent Advance of Intelligent Packaging Aided by Artificial Intelligence for Monitoring Food Freshness
Authors: Li Xiaoxuan , Liu Danfei , Pu Yumei , Zhong Yunfei
Published: August 2023

Food safety is a pressing concern for human society, as it directly impacts people’s lives, while food freshness serves as one of the most crucial indicators in ensuring food safety. There exist diverse techniques for monitoring food freshness, among which intelligent packaging based on artificial intelligence technology boasts the advantages of low cost, high efficiency, fast speed and wide applicability; however, it is currently underutilized. By analyzing the current research status of intelligent packaging both domestically and internationally, this paper provides a clear classification of intelligent packaging technology. Additionally, it outlines the advantages and disadvantages of using intelligent packaging technology for food freshness detection methods, while summarizing the latest research progress in applying artificial intelligence-based technologies to food freshness detection through intelligent packaging. Finally, the author points out the limitations of the current research, and anticipates future developments in artificial intelligence technology for assisting freshness detection in intelligent packaging. This will provide valuable insights for the future development of intelligent packaging in the field of food freshness detection.
Politics beyond the Plate: Embracing Transdisciplinarity in Addressing the Gastronomic Heritage of Spain
Authors: Parasecoli Fabio , Rodriguez-Garcia Gloria
Published: August 2023

Research and initiatives in the emerging field of gastronomy require collaboration among scholars and experts from diverse backgrounds. Transdisciplinarity has been indicated as an effective approach allowing stakeholders from a variety of disciplines and professional practices to better understand and plan interventions in complex gastronomy-related issues and challenges. However, the actors collaborating in such transdisciplinary processes often represent different priorities, values, and needs, as well as varying levels of power and access to financial means. This is particularly evident when it comes to gastronomic heritage. Its identification, support, and promotion require cultural, social, and political negotiations among a great number of stakeholders. Using a pilot workshop organized in March 2023 in Madrid as a case study, this articles suggests that participatory design methods can offer instruments to ensure the effective transdisciplinarity required in gastronomy and to address the political tensions that underlie many of its aspects.
Impact of Fat Replacement by Using Organic-Candelilla-Wax-Based Oleogels on the Physicochemical and Sensorial Properties of a Model Cookie
Authors: Flores-García Cassandra Lizeth , Medina-Herrera Nancy , Rodríguez-Romero Beatriz Adriana , Martínez-Ávila Guillermo Cristian Guadalupe , Rojas Romeo , Meza-Carranco Zahidd
Published: August 2023

Oleogelation is an alternative process to improve the nutritional properties of food by creating soft-matter structures with the same functionality as commercial fats (shortenings). In this study, oleogels were produced by adding organic candelilla wax at 3% (OC03), 6% (OC06), and 9% (OC09) to extra-virgin linseed oil, and then characterized by their physicochemical properties. Furthermore, the physicochemical and sensorial properties of five cookie formulations were evaluated. Organic candelilla wax influenced the oleogel formulations, giving higher values of color (L* and b*), texture, acidity index, and melting point. In the cookie formulations, the luminosity values decreased when the percentage of oleogel was increased; reddish trends were obtained (a* values) for the cookie where 70% of the fat was replaced by the oleogel (C70), and more yellow trends were obtained (b* values) for C100. The moisture content was higher in cookies with oleogels, but it was within quality limits. The percentage of fat migration was lower in cookies with a mixture of fats and oleogels. In terms of hardness, the substitution of oleogels resulted in softer cookies. In terms of the sensory evaluation, the most accepted cookie was C70. Therefore, this study demonstrates the possibility of using organic-candelilla-wax-based oleogels in a real food model rich in unsaturated fats.
3D Printing Type 1 Bovine Collagen Scaffolds for Tissue Engineering Applications—Physicochemical Characterization and In Vitro Evaluation
Authors: Nayak Vasudev Vivekanand , Tovar Nick , Khan Doha , Pereira Angel Cabrera , Mijares Dindo Q. , Weck Marcus , Durand Alejandro , Smay James E. , Torroni Andrea , Coelho Paulo G. , Witek Lukasz
Published: August 2023

Collagen, an abundant extracellular matrix protein, has shown hemostatic, chemotactic, and cell adhesive characteristics, making it an attractive choice for the fabrication of tissue engineering scaffolds. The aim of this study was to synthesize a fibrillar colloidal gel from Type 1 bovine collagen, as well as three dimensionally (3D) print scaffolds with engineered pore architectures. 3D-printed scaffolds were also subjected to post-processing through chemical crosslinking (in N-(3-Dimethylaminopropyl)-N′-ethylcarbodiimide) and lyophilization. The scaffolds were physicochemically characterized through Fourier Transform Infrared Spectroscopy (FTIR), Thermogravimetric Analysis, Differential Scanning Calorimetry, and mechanical (tensile) testing. In vitro experiments using Presto Blue and Alkaline Phosphatase assays were conducted to assess cellular viability and the scaffolds’ ability to promote cellular proliferation and differentiation. Rheological analysis indicated shear thinning capabilities in the collagen gels. Crosslinked and lyophilized 3D-printed scaffolds were thermally stable at 37 °C and did not show signs of denaturation, although crosslinking resulted in poor mechanical strength. PB and ALP assays showed no signs of cytotoxicity as a result of crosslinking. Fibrillar collagen was successfully formulated into a colloidal gel for extrusion through a direct inkjet writing printer. 3D-printed scaffolds promoted cellular attachment and proliferation, making them a promising material for customized, patient-specific tissue regenerative applications.
Hub Gene Mining and Co-Expression Network Construction of Low-Temperature Response in Maize of Seedling by WGCNA
Authors: Yu Tao , Zhang Jianguo , Cao Jingsheng , Ma Xuena , Li Wenyue , Yang Gengbin
Published: August 2023

Weighted gene co-expression network analysis (WGCNA) is a research method in systematic biology. It is widely used to identify gene modules related to target traits in multi-sample transcriptome data. In order to further explore the molecular mechanism of maize response to low-temperature stress at the seedling stage, B144 (cold stress tolerant) and Q319 (cold stress sensitive) provided by the Maize Research Institute of Heilongjiang Academy of Agricultural Sciences were used as experimental materials, and both inbred lines were treated with 5 °C for 0 h, 12 h, and 24 h, with the untreated material as a control. Eighteen leaf samples were used for transcriptome sequencing, with three biological replicates. Based on the above transcriptome data, co-expression networks of weighted genes associated with low-temperature-tolerance traits were constructed by WGCNA. Twelve gene modules significantly related to low-temperature tolerance at the seedling stage were obtained, and a number of hub genes involved in low-temperature stress regulation pathways were discovered from the four modules with the highest correlation with target traits. These results provide clues for further study on the molecular genetic mechanisms of low-temperature tolerance in maize at the seedling stage.
The Use of Wheat Starch as Gelling Agent for In Vitro Proliferation of Blackberry (Rubus fruticosus L.) Cultivars and the Evaluation of Genetic Fidelity after Repeated Subcultures
Authors: Clapa Doina , Hârța Monica , Szabo Katalin , Teleky Bernadette-Emőke , Pamfil Doru
Published: August 2023

Micropropagation has an important role in the large-scale production of blackberry plant material, given the high proliferation rates of this species. The aim of the present study was to evaluate the proliferative capacity of blackberry grown in vitro on wheat starch-gelled culture medium compared to classical agar-gelled medium and to assess the genetic fidelity between the proliferated shoots in starch-gelled culture medium and their mother plants. Six blackberry varieties (‘Čačanska Bestrna’, ‘Chester Thornless’, ‘Driscoll’s Victoria’, ‘Loch Ness’, ‘Polar’, and ‘Karaka Black’) were tested. For the in vitro shoots proliferation, Murashige and Skoog (MS) medium supplemented with 0.5 mg dm−3 6-benzyladenine (BA) was used. The conventional medium was gelled with 0.5% plant agar, and wheat starch was used as an alternative gelling agent in a concentration of 5%. The results showed that for all blackberry cultivars, the highest number of shoots/inoculum was obtained in wheat starch-gelled culture medium, with a maximum value of 54.42 ± 4.18 presented by ‘Karaka Black’. Considering the length of the proliferated shoots, all tested cultivars presented outstanding results on the culture medium gelled with 5% wheat starch. The highest values regarding shoots length were observed on the ‘Chester Thornless’ followed by ‘Čačanska Bestrna’, and ‘Loch Ness’ with values of 5.55 ± 0.04 cm, 5.46 ± 0.06 cm, and 5.37 ± 0.09 cm, respectively. The genetic uniformity of the micropropagated shoots in relation to their mother plants was confirmed by sequence-related amplified polymorphism (SRAP) and start codon targeted (SCoT) molecular markers.
Research on Road Network Partitioning Considering the Coupling of Network Connectivity and Traffic Attributes
Authors: Ma Yingying , Xu Minglang , Qin Xiaoran , Zeng Ying , Zeng Lingyu
Published: August 2023

The urban road network is a large and complex system characterized by significant heterogeneity arising from different spatial structures and traffic demands. To facilitate effective management and control, it is necessary to partition the road network into homogeneous sub-areas. In this regard, we aim to propose a hybrid method for partitioning sub-areas with intra-area homogeneity, inter-area heterogeneity, and similar sizes, called CSDRA. It is specifically designed for bidirectional road networks with segment weights that encompass traffic flow, speed, or roadside facility evaluation. Based on community detection and spectral clustering, this proposed method comprises four main modules: initial partition, partitioning of large sub-areas, reassignment of small sub-areas, and boundary adjustment. In the preliminary partitioning work, we also design a road network reconstruction method which further helps to enhance the intra-area homogeneity and inter-area heterogeneity of partitioning results. Furthermore, to align with the requirement for comparable work units in practical traffic management and control, we control the similarity in the size of sub-areas by enforcing upper and lower bound constraints on the size of the sub-areas. We verify the outperformance of the proposed method by an experiment on the partitioning of an urban road network in Guangzhou, China, where we employ sidewalk barrier-free score data as segment weights. The results demonstrate the effectiveness of both the road network reconstruction method and the CSDRA proposed in this paper, as they significantly improve the partitioning outcomes compared with other methods using different evaluation indicators corresponding to the partitioning objectives. Finally, we investigate the influence of constraint parameters on the evaluation indicator. Our findings indicate that appropriately configuring these constraint parameters can effectively minimize sub-region size variations while having minimal impact on other aspects.
IPFS-Blockchain Smart Contracts Based Conceptual Framework to Reduce Certificate Frauds in the Academic Field
Authors: Sultana Shaik Arshiya , Rupa Chiramdasu , Malleswari Ramanadham Pavana , Gadekallu Thippa Reddy
Published: August 2023

In the digital age, ensuring the authenticity and security of academic certificates is a critical challenge faced by educational institutions, employers, and individuals alike. Traditional methods for verifying academic credentials are often cumbersome, time-consuming, and susceptible to fraud. However, the emergence of blockchain technology offers a promising solution to address these issues. The proposed system utilizes a blockchain network, where each academic certificate is stored as a digital asset on the blockchain. These digital certificates are cryptographically secured, timestamped, and associated with unique identifiers, such as hashes or public keys, ensuring their integrity and immutability. Anyone with access to the blockchain network can verify a certificate’s authenticity, using the MetaMask extension and Ethereum network, eliminating the need for intermediaries and reducing the risk of fraudulent credentials. The main strength of the paper is that the data that are stored in the blockchain are unique identifiers of the encrypted data, which is encrypted by using an encryption technique that provides more security to the academic certificates. Furthermore, IPFS is also used to store large amounts of encrypted data.
Exploring How Healthcare Organizations Use Twitter: A Discourse Analysis
Authors: Singhal Aditya , Mago Vijay
Published: August 2023

The use of Twitter by healthcare organizations is an effective means of disseminating medical information to the public. However, the content of tweets can be influenced by various factors, such as health emergencies and medical breakthroughs. In this study, we conducted a discourse analysis to better understand how public and private healthcare organizations use Twitter and the factors that influence the content of their tweets. Data were collected from the Twitter accounts of five private pharmaceutical companies, two US and two Canadian public health agencies, and the World Health Organization from 1 January 2020, to 31 December 2022. The study applied topic modeling and association rule mining to identify text patterns that influence the content of tweets across different Twitter accounts. The findings revealed that building a reputation on Twitter goes beyond just evaluating the popularity of a tweet in the online sphere. Topic modeling, when applied synchronously with hashtag and tagging analysis can provide an increase in tweet popularity. Additionally, the study showed differences in language use and style across the Twitter accounts’ categories and discussed how the impact of popular association rules could translate to significantly more user engagement. Overall, the results of this study provide insights into natural language processing for health literacy and present a way for organizations to structure their future content to ensure maximum public engagement.
Intracoronary Pacing during “Chimney Technique” in Transcatheter Aortic Valve-in-Valve Implantation: An Alternative Temporary Rapid Ventricular Stimulation?
Authors: Cafaro Alessandro , Rizzo Francesco , Fischetti Dionigi , Quarta Luca , Mussardo Marco , Mandurino-Mirizzi Alessandro , Tondo Antonio , Ciccone Marco Matteo , Iacovelli Fortunato , Colonna Giuseppe
Published: August 2023

Temporary rapid ventricular pacing (TRVP) is required during transcatheter aortic valve implantation (TAVI) in order to reduce cardiac output and to facilitate balloon aortic valvuloplasty, prosthesis deployment, and post-deployment balloon dilation. The two most frequently used TRVP techniques are right endocardial (RE)-TRVP and retrograde left endocardial temporary rapid ventricular pacing (RLE)-TRVP. The first one could be responsible for cardiac tamponade, one of the most serious procedural complications during TAVI, while the second one could often be unsuccessful. Intracoronary (IC)-TRVP through a coronary guidewire has been described as a safe and efficient procedure that could avoid such complications. We describe two clinical cases in which IC-TRVP has been effectively used during valve-in-valve TAVI with coronary protection via the “chimney technique”, after unsuccessful RLE-TRVP.
Technical Feasibility of a Thermally Activated Nanotape for Electromagnetic Interference Applications
Authors: Cai Kaiyu , Zhang Dan , Castro Jose M.
Published: August 2023

Multiwalled carbon nanotube (MWCNT) nanopaper (NP)-reinforced in-mold coating (IMC) nanocomposites were fabricated by dip soaking without organic solvent. The thermally activated IMC resin was selected to provide electromagnetic interference shielding protection for sheet molding compound (SMC) material as well as other plastic materials due to the proven good adhesion of IMC resin to the substrate. In this work, the technical feasibility of a continuous fabrication process was evaluated for a nanopaper/IMC (NP/IMC) composite. The curing behavior of the candidate IMC resin was studied for a better understanding of the fabrication of NP/IMC nanotape as a prepreg (with 10% polymerization), as well as the final curing once the nanotape was applied to the substrate. The required limiting maximum temperature to prevent curing during infiltration was established. This allows the fabrication of multilayer nanotape or coatings by stacking several layers of tape to improve the EMI shielding protection. To be specific, the average EMI shielding effectiveness for a one-layer composite was 21 dB, while it increased to 48 dB on average for a six-layer composite.
Positive Effects of Plyometric vs. Eccentric-Overload Training on Performance in Young Male Handball Players
Authors: Saez de Villareal Eduardo , Calleja-González Julio , Alcaraz Pedro E. , Feito-Blanco Javier , Ramírez-Campillo Rodrígo
Published: August 2023

This study aimed to compare the effects of two 8-week in-season strength-training programs on handball players’ physical and technical parameters. Thirty-six male athletes were randomly separated into three groups: a control group (n = 12), a plyometric training group (PG, n = 12), and an eccentric-overload training group (EG, n = 12). The PG and EG performed upper- and lower-limb plyometric or eccentric-overload exercises, respectively, three times per week. Control groups performed regular handball training. The athletes were assessed for counter movement jump (CMJ) and Abalakov vertical jump (ABK) height, 15 m linear sprint time, handball-throwing speed (i.e., penalty throw; 3-step running throw; jump throw), and cardiorespiratory endurance through the 20 m shuttle-run test. Heart rate and blood lactate were measured at the end of the endurance test. No baseline differences were noted for dependent variables between groups. The session rating of perceived exertion was similar between the intervention groups (PG = 361 ± 12.2 AU; EG = 370 ± 13.3 AU). The ANOVA revealed significant (p < 0.05; Δ = 5–9%; effect size (ES) = 0.45–1.96). Similar improvements for experimental groups compared to the control group for CMJ, ABK jump, penalty throw, 3-step running throw, and jump throw. However, interventions did not affect 15 m, cardiorespiratory endurance, nor heart rate or blood lactate after the endurance test. In conclusion, an 8-week handball intervention by performing plyometric or eccentric-overload training in-season improves the physical and technical parameters of male players when compared to regular handball practice.
Resilience as the Ability to Maintain Well-Being: An Allostatic Active Inference Model
Authors: Waugh Christian E. , Sali Anthony W.
Published: August 2023

Resilience is often characterized as the outcome of well-being maintenance despite threats to that well-being. We suggest that resilience can also be characterized as an emotional-intelligence-related ability to obtain this outcome. We formulate an allostatic active inference model that outlines the primary tools of this resilience ability as monitoring well-being, maintaining stable well-being beliefs while updating situational beliefs and flexibly prioritizing actions that are expected to lead to well-being maintenance or gathering the information needed to discern what those actions could be. This model helps to explain the role of positive emotions in resilience as well as how people high in resilience ability use regulatory flexibility in the service of maintaining well-being and provides a starting point for assessing resilience as an ability.
Optimization of Selective Laser Sintering Three-Dimensional Printing of Thermoplastic Polyurethane Elastomer: A Statistical Approach
Authors: Rahman Md Mahfuzur , Ahmed Kazi Arman , Karim Mehrab , Hassan Jakir , Roy Rakesh , Bustami Bayazid , Alam S. M. Nur , Younes Hammad
Published: August 2023

This research addresses the challenge of determining the optimal parameters for the selective laser sintering (SLS) process using thermoplastic polyurethane elastomer (TPU) flexa black powder to achieve high-quality SLS parts. This study focuses on two key printing process parameters, namely layer thickness and the laser power ratio, and evaluates their impact on four output responses: density, hardness, modulus of elasticity, and time required to produce the parts. The primary impacts and correlations of the input factors on the output responses are evaluated using response surface methodology (RSM). A particular response optimizer is used to find the optimal settings of input variables. Additionally, the rationality of the model is verified through an analysis of variance (ANOVA). The research identifies the optimal combination of process parameters as follows: a 0.11 mm layer thickness and a 1.00 laser power ratio. The corresponding predicted values of the four responses are 152.63 min, 96.96 Shore-A, 2.09 MPa, and 1.12 g/cm3 for printing time, hardness, modulus of elasticity, and density, respectively. These responses demonstrate a compatibility of 66.70% with the objective function. An experimental validation of the predicted values was conducted and the actual values obtained for printing time, hardness, modulus of elasticity, and density at the predicted input process parameters are 159.837 min, 100 Shore-A, 2.17 MPa, and 1.153 g/cm3, respectively. The errors between the predicted and experimental values for each response (time, hardness, modulus of elasticity, and density) were found to be 4.51%, 3.04%, 3.69%, and 2.69%, respectively. These errors are all below 5%, indicating the adequacy of the model. This study also comprehensively describes the influence of process parameters on the responses, which can be helpful for researchers and industry practitioners in setting process parameters of similar SLS operations.
Land Cover Extraction in the Typical Black Soil Region of Northeast China Using High-Resolution Remote Sensing Imagery
Authors: Ding Binbin , Tian Jianlin , Wang Yong , Zeng Ting
Published: August 2023

The black soil region of Northeast China is one of the most fertile soil areas in the world and serves as a crucial grain-producing region in China. However, excessive development and improper utilization have led to severe land use issues. Conducting land cover extraction in this region can provide essential data support for monitoring and managing natural resources effectively. This article utilizes GF-6 remote sensing imagery as the data source and adopts the U-Net model as the backbone network. By incorporating residual modules and adjusting the convolution kernel size, a high-precision land cover extraction model called RAT-UNet is developed. Taking Qiqihar City as an example, the RAT-UNet model is applied to extract land cover information. The results are as follows: (1) The RAT-UNet model achieves high accuracy in land cover extraction, with the following accuracies for different land types: cropland (95.11%), forestland (93.61%), grassland (68.41%), water bodies (94.67%), residential land (89.40%), and unused land (87.25%). (2) The land cover extraction performance of the RAT-UNet model is superior to DeepLabV3, U-Net, SegNet, and LinkNet34 models. This research outcome provides methodological support for the intelligent and high-precision extraction of land cover information and also offers timely data for Qiqihar city’s land use planning.
Filipino Children’s Acquisition of Nominal and Verbal Markers in L1 and L2 Tagalog
Authors: Barrios Aireen , Garcia Rowena
Published: August 2023

Western Austronesian languages, like Tagalog, have unique, complex voice systems that require the correct combinations of verbal and nominal markers, raising many questions about their learnability. In this article, we review the experimental and observational studies on both the L1 and L2 acquisition of Tagalog. The reviewed studies reveal error patterns that reflect the complex nature of the Tagalog voice system. The main goal of the article is to present a full picture of commission errors in young Filipino children’s expression of causation and agency in Tagalog by describing patterns of nominal marking and voice marking in L1 Tagalog and L2 Tagalog. It also aims to provide an overview of existing research, as well as characterize research on nominal and verbal acquisition, specifically in terms of research problems, data sources, and methodology. Additionally, we discuss the research gaps in at least fifty years’ worth of studies in the area from the 1960’s to the present, as well as ideas for future research to advance the state of the art.
Small Bowel Imaging from Stepchild of Roentgenology to MR Enterography: Part I: Guidance in Performing and Observing Normal and Abnormal Imaging Findings
Authors: Pierro Antonio , Minordi Laura Maria , Larosa Luigi , Guerri Giulia , Grimaldi Alessandro , Quinto Fabio , Rotondi Fabio , Marcellino Annalisa , Bevere Teresa , Basilico Raffaella , Iezzi Roberto , Cilla Savino
Published: August 2023

MRE has become a standard imaging test for evaluating patients with small bowel pathology, but the indications, interpretation of imaging findings, methodology, and appropriate use must be standardized and widely known. Several signs of small bowel damage in inflammatory and non-inflammatory small bowel pathology include strictures, abscess, inflammatory activity, sinus tract, wall edema, fistula, mucosal lesions, and mesentery fat hypertrophy, all of which are widely and accurately explained by MRE. MRE is a non-invasive modality that accurately assesses the intra-luminal, parietal, and extra-luminal small bowel. The differential MRE appearance allows us to distinguish between different small bowel pathologies, such as neoplastic and non-neoplastic small bowel diseases. The purpose of this paper is to present the MRE technique, as well as the interpretation of imaging findings, through the approach of a rigorous stepwise methodology.
NiFe Alloy Nanoparticles Tuning the Structure, Magnetism, and Application for Oxygen Evolution Reaction Catalysis
Authors: Raimundo Rafael A. , Silva Vinícius D. , Ferreira Luciena S. , Loureiro Francisco J. A. , Fagg Duncan P. , Macedo Daniel A. , Gomes Uílame U. , Soares Márcio M. , Gomes Rodinei M. , Morales Marco A.
Published: August 2023

In this study, Ni-Fe alloy nanoparticles were prepared using the proteic sol–gel method, followed by a reduction in H2 at 500 and 700 °C, namely hereafter as NiFe-500 and NiFe-700, respectively. The morphological, structural, and magnetic properties were tuned via the thermal treatment in H2. The samples were studied using XPS, TEM, Mössbauer spectroscopy, DC magnetic measurements, and electrochemical measurements. Ritveld refinements showed that the sample NiFe-500 has FCC (face-centered cubic) and BCC (body-centered cubic) NiFe alloys, while the sample NiFe-700 has only FCC NiFe alloy. For both samples, magnetization measurements in the range of 300–900 K showed the presence of the Griffiths phase, indicating the formation of clusters of either Fe or Ni-Fe alloys rich in Fe. The sample NiFe-500 presented ferromagnetic (FM) transitions at 533, 700, and 834 K, assigned to the alloys Ni37Fe63-FCC, Ni46Fe54-FCC, and Ni55Fe45-FCC, respectively. In contrast, we could not observe the FM transition of the BCC Ni-Fe alloy because of limitations in our experimental setup (T ≤ 900 K). Meanwhile, three FM transitions were observed for the sample NiFe-700 at 480, 655, and 825 K, attributed to the alloys Ni34Fe66-FCC, Ni43Fe57-FCC, and Ni54Fe46-FCC, respectively. At 5 K, the samples NiFe-500 and NiFe-700 have saturation magnetizations of 164.2 and 173.6 emu g−1, respectively. For application in Oxygen Evolution Reaction catalysis, the samples NiFe-500 and NiFe-700 showed different overpotentials of 319 and 307 mV at 10 mA cm−2. These low overpotential values indicate a higher electrochemical activity of the FCC Ni-Fe alloy and, for both samples, a superior electrocatalytic activity in comparison to RuO2 e IrO2 conventional catalysts. Furthermore, the samples showed high electrochemical stability in chrono potentiometric studies for up to 15 h. This current work highlights that the Ni-Fe alloys produced via the proteic sol–gel and with a reduction in H2 methods can be promising for OER systems due to their good performance and low costs.
The Predictive Power of Social Media Sentiment: Evidence from Cryptocurrencies and Stock Markets Using NLP and Stochastic ANNs
Authors: di Tollo Giacomo , Andria Joseph , Filograsso Gianni
Published: August 2023

Cryptocurrencies are nowadays seen as an investment opportunity, since they show some peculiar features, such as high volatility and diversification properties, that are triggering research interest into investigating their differences with traditional assets. In our paper, we address the problem of predictability of cryptocurrency and stock trends by using data from social online communities and platforms to assess their contribution in terms of predictive power. We extend recent developments in the field by exploiting a combination of stochastic neural networks (NNs), an extension of standard NNs, natural language processing (NLP) to extract sentiment from Twitter, and an external evolutionary algorithm for optimal parameter setting to predict the short-term trend direction. Our results point to good and robust accuracy over time and across different market regimes. Furthermore, we propose to exploit recent advances in sentiment analysis to reassess its role in financial forecasting; in this way, we contribute to the empirical literature by showing that predictions based on sentiment analysis are not found to be significantly different from predictions based on historical data. Nonetheless, compared to stock markets, we find that the accuracy of trend predictions with sentiment analysis is on average much higher for cryptocurrencies.
Design of a Port-Hamiltonian Control for an Alt-Azimuth Liquid–Mirror Telescope
Authors: Alcaraz Tapia Juan Cristobal , Castañeda Carlos E. , Vargas Rodriguez Héctor , Esquivel P.
Published: August 2023

In this work, we design a control strategy to be applied in a port-Hamilton representation of a liquid-mirror telescope for an alt-azimuth configuration. Starting from a dynamical model for an alt-azimuth liquid-mirror telescope based on Lagrange mechanics, a transformation to the port-Hamilton form is made. Such a dynamical model is obtained by computing the kinetic and potential energy of the telescope and substituting them in the Euler–Lagrange equation of motion. Then, for the transformation to the port-Hamiltonian form, we obtain the relation between the Hamiltonian and the Lagrangian. The resulting open-loop model based on the Hamiltonian function is controlled using an extension of the interconnection and damping-assignment passivity-based control aiming for a robust and accurate steady behavior in the closed loop while tracking a star’s position. For comparison purposes, two different control strategies are applied to the Lagrangian model, inverse-dynamics control and sliding mode super-twisting control. Since the light is collected by the principal mirror of the telescope while tracking a star, we make a description of the liquid mirror’s behavior. The tracking star’s position is described as a function of the observer’s position and the star’s coordinates as well as the date of observation. The simulations’ results show that the port-Hamilton control has a good transitory and steady response as well as great accuracy competing with that of inverse-dynamics control but with greater robustness and no chattering drawback.
Short-Term Prediction of Time-Varying Passenger Flow for Intercity High-Speed Railways: A Neural Network Model Based on Multi-Source Data
Authors: Su Huanyin , Mo Shanglin , Peng Shuting
Published: August 2023

The accurate prediction of passenger flow is crucial in improving the quality of the service of intercity high-speed railways. At present, there are a few studies on such predictions for railway origin–destination (O-D) pairs, and usually only a single factor is considered, yielding a low prediction accuracy. In this paper, we propose a neural network model based on multi-source data (NN-MSD) to predict the O-D passenger flow of intercity high-speed railways at different times in one day in the short term, considering the factors of time, space, and weather. Firstly, the factors that influence time-varying passenger flow are analyzed based on multi-source data. The cyclical characteristics, spatial and temporal fusion characteristics, and weather characteristics are extracted. Secondly, a neural network model including three modules is designed based on the characteristics. A fully connected network (FCN) model is used in the first module to process the classification data. A bi-directional Long Short-Term Memory (Bi-LSTM) model is used in the second module to process the time series data. The results of the first module and the second module are spliced and fused in the third module using an FCN model. Finally, an experimental analysis is performed for the Guangzhou–Zhuhai intercity high-speed railway in China, in which three groups of comparison experiments are designed. The results show that the proposed NN-MSD model can predict many O-D pairs with a high and stable accuracy, which outperforms the baseline models, and multi-source data are very helpful in improving the prediction accuracy.
The Heart Beats as It Breathes, or Is It the Other Way Around?
Authors: Vitulano Nicola
Published: August 2023

One third of human life is spent sleeping, thus the importance of sleep in the maintenance of correct homeostatic balance is well established [...]
Beneficial Effect of Curved Dilator System for Femoral Tunnel Creation in Preventing Femoral Tunnel Widening after Anterior Cruciate Ligament Reconstruction
Authors: Lee O-Sung , Kim Joong Il , Han Seok Hyeon , Lee Joon Kyu
Published: August 2023

Backgrounds and objectives: A prevalent concern in anterior cruciate ligament (ACL) reconstruction is postoperative tunnel widening. We hypothesized that employing a curved dilator system (CDS) for femoral tunnel creation can reduce this widening after ACL reconstruction compared to the use of a conventional rigid reamer. Materials and Methods: A retrospective study was conducted involving 56 patients who underwent primary ACL reconstruction between January 2012 and July 2013. The patients were categorized into two groups: the reamer group (n = 28) and CDS group (n = 28). All participants were followed up for a minimum of 2 years. Clinical assessment included the Lachman test and pivot-shift test, and the Lysholm score and subjective International Knee Documentation Committee scores. Radiographic evaluation covered the tunnel widening rate, represented as the ratio of the tunnel diameter 2 years after surgery to the tunnel diameter immediately after surgery, and the ratio (A/B) of femoral tunnel (A) to tibial tunnel (B) diameters at respective time points. Results: No significant disparities were found between the two groups in terms of clinical outcomes. However, the reamer group exhibited a greater femoral tunnel widening rate compared to the CDS group (reamer group vs. CDS group: 142.7 ± 22.0% vs. 128.0 ± 19.0% on the anteroposterior (AP) radiograph and 140.8 ± 14.2% vs. 122.9 ± 13.4% on the lateral radiograph; all p < 0.05). Two years post-operation, the A/B ratio rose in the reamer group (0.96 ± 0.05→1.00 ± 0.05 on the AP radiograph and 0.94 ± 0.03→1.00 ± 0.0.04 on the lateral radiograph; all p < 0.05), while it decreased in the CDS group (0.99 ± 0.02→0.96 ± 0.05 on the AP radiograph and 0.97 ± 0.03→0.93 ± 0.06 on the lateral radiograph; all p < 0.05). Conclusion: The use of CDS for femoral tunnel creation in primary ACL reconstruction provides a potential advantage by limiting tunnel widening compared to the conventional rigid-reamer approach.
Quench and Tempered Embrittlement of Ultra-High-Strength Steels with Transition Carbides
Authors: Mishnev Roman , Borisova Yuliya , Kniaziuk Tatiana , Gaidar Sergey , Kaibyshev Rustam
Published: August 2023

The effect of tempering after water quenching on the strength and fracture toughness of two steels with chemical compositions of 0.34%C-1.77%Si-1.35Mn-0.56%Cr-0.2%Mo-0.04%Nb-0.03Ti-0.002B and 0.44%C-1.81%Si-1.33%Mn-0.82%Cr-0.28%Mo was examined. The last steel exhibits quenching embrittlement in an as-quenched condition. At a tempering temperature of 280 °C, the precipitation of transition η–Fe2C carbides in martensitic matrix leads to increasing fracture toughness and eliminates quench embrittlement in the steel with 0.44 wt.%C. Tempered martensite embrittlement at 400 °C appears as decreased values of the Charpy V-notch impact energy, ductility and the product of strength and elongation, σB×δ (MPa×%) and is attributed to increased effective grain size for fracture, mainly. The precipitation of boundary cementite takes place at tempering at 500 °C and provides increased ductility and fracture toughness despite a decohesion along carbide/ferrite interfaces. The low severity of TME in Si-rich low-alloy medium carbon steels is attributed to the suppression of boundary cementite precipitation at tempering temperatures ≤400 °C.
Carvacrol Inhibits Quorum Sensing in Opportunistic Bacterium Aeromonas hydrophila
Authors: Lu Liushen , Wang Junwei , Qin Ting , Chen Kai , Xie Jun , Xi Bingwen
Published: August 2023

Bacterial quorum sensing (QS) plays a crucial role in chemical communication between bacteria involving autoinducers and receptors and controls the production of virulence factors in bacteria. Therefore, reducing the concentration of signaling molecules in QS is an effective strategy for mitigating the virulence of pathogenic bacteria. In this study, we demonstrated that carvacrol at 15.625 μg/mL (1/4 MIC), a natural compound found in plants, exhibits potent inhibitory activity against QS in Chromobacterium violaceum, as evidenced by a significant reduction (62.46%) in violacein production. Based on its impressive performance, carvacrol was employed as a natural QS inhibitor to suppress the pathogenicity of Aeromonas hydrophila NJ-35. This study revealed a significant reduction (36.01%) in the concentration of N-acyl-homoserine lactones (AHLs), a QS signal molecular secreted by A. hydrophila NJ-35, after 1/4 MIC carvacrol treatment. Moreover, carvacrol was found to down-regulate the expression of ahyR/I, two key genes in the QS system, which further inhibited the QS system of A. hydrophila NJ-35. Finally, based on the above results and molecular docking, we proposed that carvacrol alleviate the pathogenicity of A. hydrophila NJ-35 through QS inhibition. These results suggest that carvacrol could serve as a potential strategy for reducing the virulence of pathogenic bacteria and minimizing the reliance on antibiotics in aquaculture.