bluuebunny/crossref_metadata_2025 huggingface dataset:
Systematically tracking the hourly progression of large wildfires using GOES satellite observations
Authors: Liu Tianjia , Randerson James T. , Chen Yang , Morton Douglas C. , Wiggins Elizabeth B. , Smyth Padhraic , Foufoula-Georgiou Efi , Nadler Roy , Nevo Omer
Published: September 2023

Abstract. In the western United States, prolonged drought, warming climate, and historical fuel build-up have contributed to larger and more intense wildfires, as well as longer fire seasons. As these costly wildfires become more common, new tools and methods are essential for improving our understanding of the evolution of fires and how extreme weather conditions, including heatwaves, windstorms, droughts, and varying levels of active fire suppression, influence fire spread. Here we develop the GOES-Observed Fire Event Representation (GOFER) algorithm to derive the hourly fire progression of large wildfires and create a dataset of hourly fire perimeters, active fire lines, and fire spread rates. Using GOES-East and GOES-West geostationary satellite detections of active fires, we test the GOFER algorithm on 28 large wildfires in California from 2019–2021. The GOFER algorithm includes parameter optimizations for defining the burned-to-unburned boundary and correcting for the parallax effect from elevated terrain. We evaluate GOFER perimeters with using 12-hourly data from the VIIRS-derived Fire Event Data Suite (FEDS) and final fire perimeters from California’s Fire and Resource Assessment Program (FRAP). Although the GOES imagery used to derive GOFER has coarser resolution (2 km at the equator), the final fire perimeters from GOFER correspond reasonably well with those obtained from FRAP, with a mean Intersection-over-Union (IoU) of 0.77, in comparison to 0.83 between FEDS and FRAP. GOFER fills a key temporal gap present in other fire tracking products that rely on low-earth-orbit imagery, where perimeters are available at 12-hour intervals or longer, or at ad hoc intervals from aircraft overflights. This is particularly relevant when a fire spreads rapidly, such as at maximum hourly spread rates of over 5 km/h. Our GOFER algorithm for deriving the hourly fire progression using GOES can be applied to large wildfires across North and South America and reveals considerable variability in rates of fire spread on diurnal time scales. The resulting GOFER dataset has a broad set of applications, including the development of predictive models for fire spread and improvement of atmospheric transport models for surface smoke estimates.
Simulation of a fully coupled 3D glacial isostatic adjustment – ice sheet model for the Antarctic ice sheet over a glacial cycle
Authors: van Calcar Caroline J. , van de Wal Roderik S. W. , Blank Bas , de Boer Bas , van der Wal Wouter
Published: September 2023

Abstract. Glacial isostatic adjustment (GIA) has a stabilizing effect on the evolution of the Antarctic ice sheet by reducing the grounding line migration following ice melt. The timescale and strength of this feedback depends on the spatially varying viscosity of the Earth's mantle. Most studies assume a relatively long and laterally homogenous response time of the bedrock. However, the mantle viscosity is spatially variable, with a high mantle viscosity beneath East Antarctica and a low mantle viscosity beneath West Antarctica. For this study, we have developed a new method to couple a 3D GIA model and an ice sheet model to study the interaction between the solid Earth and the Antarctic ice sheet during the last glacial cycle. With this method, the ice sheet model and GIA model exchange ice thickness and bedrock elevation during a fully coupled transient experiment. The feedback effect is taken into account with a high temporal resolution, where the coupling time steps between the ice sheet and GIA model are 5000 years over the glaciation phase and vary between 500 and 1000 years over the deglaciation phase of the last glacial cycle. During each coupling time step, the bedrock elevation is adjusted at every ice sheet model time step, and the deformation is computed for a linearly changing ice load. We applied the method using the ice sheet model ANICE and a 3D GIA finite element model. We used results from a regional seismic model for Antarctica embedded in the global seismic model SMEAN2 to determine the patterns in the mantle viscosity. The results of simulations over the last glacial cycle show that differences in mantle viscosity of an order of magnitude can lead to differences in the grounding line position up to 700 km and to differences in ice thickness of the order of 2 km for the present day near the Ross Embayment. These results underline and quantify the importance of including local GIA feedback effects in ice sheet models when simulating the Antarctic ice sheet evolution over the last glacial cycle.
Unusual coccolithophore blooms in Scottish waters
Authors: Renshaw Richard , Bresnan Eileen , Kay Susan , McEwan Robert , Miller Peter I. , Tett Paul
Published: September 2023

Abstract. Two unusual blooms were observed in Scottish waters during summer 2021: one in the Clyde Sea and the other by the east coast of the Shetland Islands. Both had the appearance of coccolithophore blooms. Transmission electron microscopy of a sample from the Clyde Sea confirmed the presence there of the coccolithophore Emiliania huxleyi. We examine the conditions that led to these unusual blooms. In situ data are scarce, and so we draw inference from satellite data and reanalysis. For Shetland, the bloom can be seen to originate further north on the edge of the continental shelf. It is advected south and then west towards the Shetland coast by surface currents. For the Clyde Sea region, April 2021 was the coldest April of the last 30 years (National Climate Information Centre). We hypothesise that this cold weather restricted the usual spring bloom of diatoms. A restricted spring bloom would mean higher-than-usual concentrations of nutrients in the summer. It might also mean reduced numbers of grazers. These factors would provide ideal conditions for coccolithophores to flourish as temperatures and sunlight increase.
Intense wind-driven coastal upwelling in the Balearic Islands in response to Storm Blas (November 2021)
Authors: Mourre Baptiste , Reyes Emma , Lorente Pablo , Santana Alex , Hernández-Lasheras Jaime , Hernández-Carrasco Ismael , García-Jove Maximo , Zarokanellos Nikolaos D.
Published: September 2023

Abstract. This article analyses the Balearic Islands wind-driven coastal upwelling in
response to the intense and long-lasting Storm Blas, which affected the
western Mediterranean Sea in November 2021. The storm was associated with a
pronounced pressure low, generating heavy rains and intense winds and
showing some characteristics of a tropical cyclone. The Balearic Islands
area was particularly affected since the core of the storm was moving over a 1-week-long period from the south-west of this area to just above the islands of Menorca
and Mallorca. High-resolution regional forecast models indicated
that the intense north-easterly winds blowing over the region during the
first days of the storm led to the development of intense upwellings along
the north-western coasts of the islands of Mallorca and Ibiza together with a
reversal of the surface current. While the clouds associated with the storm
prevented the radiometers on board satellites to precisely observe the
evolution of the sea surface signature of the upwelling, signals of enhanced
chlorophyll concentration were still detected in the upwelling region. The
high-resolution Western Mediterranean Operational Prediction System model, which downscales
the Copernicus Marine Service Mediterranean predictions, is used to describe
the characteristics of this intense coastal-upwelling event, as well as to
analyse its singularity over the past-9-year time series through the
comparison of different coastal-upwelling indices. The upwelling event is
found to have a duration of 3 d (considering its effects on the sea
surface temperature) with a spatial offshore extension of around 20 km. It
was characterized by intense cold coastal sea surface anomalies of around
6 ∘C. While it was the most intense event over the past 9 years in terms
of local cross-shore sea surface temperature gradients, it is ranked second
in terms of the intensity of cross-shelf transports, behind the Storm Gloria
upwelling event in January 2020. This study demonstrates the benefits of
operational oceanography for the characterization of extreme events through
the provision of time series of high-resolution modelling results in the
coastal area.
The dynamical role of upper layer salinity in the Mediterranean Sea
Authors: Aydogdu Ali , Miraglio Pietro , Escudier Romain , Clementi Emanuela , Masina Simona
Published: September 2023

Abstract. The Mediterranean Sea (MED) is a semi-enclosed basin with an excess amount of evaporation compared to the water influx through precipitation at the
surface and river runoff on the land boundaries. The deficit in the water
budget is balanced by the inflow in the Strait of Gibraltar and Turkish Straits
System connecting the Mediterranean with the less saline Atlantic Ocean and
the Black Sea, respectively. There is evidence that the Mediterranean region is a hotspot in a warming climate, which will possibly change the water cycle significantly, but with large uncertainties. Therefore, it is inevitable to monitor the evolution of the essential ocean variables (EOVs) to respond to the associated risks and mitigate the related problems. In this work, we evaluate the evolution of the salinity content and anomaly between 0–300 m in the Mediterranean Sea during the last decades using the Copernicus Marine Service reanalysis and in situ objective analysis products. The results show an increasing mean salinity with a stronger trend in the eastern Mediterranean (EMED) basin. The spread of the products implies a larger variability in the western Mediterranean (WMED) basin, while the standard deviation is lower in the eastern side, especially in the Ionian and the Levantine basins.
High-frequency radar-derived coastal upwelling index
Authors: Lorente Pablo , Rubio Anna , Reyes Emma , Solabarrieta Lohitzune , Piedracoba Silvia , Tintoré Joaquín , Mader Julien
Published: September 2023

Abstract. Coastal upwelling has been extensively studied since it plays a critical role in the connectivity between offshore waters and coastal ecosystems, which has impacts on water quality, fisheries, and aquaculture production. Significant efforts have been devoted to the quantification of the intensity, duration, and variability of this phenomenon
by means of coastal upwelling indexes (CUIs), derived from wind, sea level
pressure, or sea surface temperature data. Although valuable, first-order
descriptors, such classical indexes have been reported to present some
limitations. As one of the major shortcomings is the omission of the direct
influence of ocean circulation, this work introduces a novel CUI, generated
from remotely sensed hourly surface current observations provided by a
high-frequency radar (HFR). The consistency of the proposed index (CUI-HFR)
is assessed in two different oceanographic areas during two distinct time
periods: in the north-western Iberian (NWI) peninsula for 2021 and in the
Bay of Biscay (BOB) for 2014. To this aim, CUI-HFR is compared against a traditional CUI based on hourly wind observations (CUI-WIND)
provided by two buoys. Likewise, the skill of CUI-HFR to identify upwelling
and downwelling processes is also qualitatively evaluated. Complementarily,
the prognostic capabilities of the GLOBAL analysis and forecasting system to accurately reproduce upwelling and downwelling events in the NWI area are also analysed (CUI-GLOBAL). Results obtained in these two pilot areas
revealed the following: (i) noticeable agreement between CUI-HFR and CUI-WIND, with
correlation coefficients above 0.67; and (ii) a proven ability of CUI-HFR and
CUI-GLOBAL to categorize a variety of upwelling and downwelling episodes,
which highlights their potential applicability for direct upwelling
monitoring over any coastal area of the global ocean.
Unraveling the Antecedents of CSR Authenticity in Pakistan's Textile Sector, with a Focus on the Moderating Effects of CSR Commitment
Authors: Sajid Tanvir , Afzal Seema
Published: September 2023

The Authenticity of Corporate Social Responsibility (CSR) has become a major concern of organization and particularly the textile sector of Pakistan. This study aimed to develop a conceptual framework that shows the influential factors affecting CSR Authenticity. The theoretical foundation of this framework stems out of Triple Bottom Line Theory and Stakeholder Theory. The reliable databases and repositories of research articles were searched to find the literature for this framework that included JSOTR, SAGE, Science Direct, Emerald, Wiley and Taylor & Francis. The search of literature has furnished a conceptual framework that suggests CSR FIT, CSR Impact and CSR Competencies as CSR Attributes are predictors of CSR Authenticity. Additionally, CSR Dimensions namely Environmental CSR, Economic CSR and Social CSR also predict CSR Authenticity. Moreover, it has been identified by literature that these all predictors cast their influence by the moderating effect of CSR Commitments. Finally, the study concludes by describing limitations and significance of study with directions to academicians and policy makers.
МОНИТОРИНГ ЗАРАЖЕННОСТИ РЫБ СЕМЕЙСТВА КАРПОВЫХ ЛИЧИНКАМИ OPISTHORCHIS FELINEUS НА ТЕРРИТОРИИ КОСТАНАЙСКОЙ ОБЛАСТИ
Authors: Аубакиров Марат , Н. С. Кауменов , Ш. С. Габдуллин , Е. Н. Еренко , А.М. Абдыбекова , В. Н. Домацкий
Published: September 2023

На сегодняшний день на территории Казахстана одной из наиболее значимых проблем является распространение паразитарных заболеваний среди рыб, в частности описторхоза. В Костанайской области имеется значительное количество рек и озер, что позволет обеспечивать водой многие отрасли сельского хозяйства и промышленности, способствует развитию любительского и промышленного рыболовства. В результате чего огромное значение для рыбоводства и промышленности имеет своевременная диагностика и мониторинг таких заболеваний как лигулидоз, диплостомоз, а наибольшее эпидемиологическое значение имеют в свою очередь печеночные сосальщики трематоды семейства Opisthorchidae. В следствии чего гельминтологическая безопасность рыбных продуктов для человека, а также  проблема паразитарных заболеваний влияющих на численность рыб на территории Костанайской области является на данный момент актуальной. В статье приведены сведения по эпизоотологической ситуации на территории Костанайской области по описторхозу, описаны методы осмотра, внешнего и внутреннего обследования рыбы, методы лабораторной диагностики, морфологическая характеристика и биология развития возбудителей данных заболеваний. Проведён анализ источников литературы по изучению описторхоза, распространению его возбудителя. Изучена официальная документация годовых отчетов, представленных на официальных сайтах.
 
Ключевые слова: описторхоз, Оpisthorchiidae, O. felineus, рыба, эпидемиология, водоемы
An examination of the role of gender in athlete endorsement effectiveness
Authors: Ho Keat Leng Ho Keat Leng , Ho Keat Leng Yi Xian Philip Phua , Yi Xian Philip Phua Yen-Chun Lin , Yen-Chun Lin Andre Richelieu , Andre Richelieu Shintaro Sato , Shintaro Sato Sock Miang Teo-Koh
Published: September 2023

Many companies use athletes to endorse their products and services in advertisements. This is because the model used in advertisement can influence consumer behaviour. However, given the gendered nature of sports, it is unclear whether the gender of the model affects the effectiveness of the advertisements. 63 respondents were recruited to view an advertisement featuring either a male or female athlete. Independent t-tests showed that there was no significant difference in the perception of quality (t(61)=1.61, p>.10) and purchase intention (t(61)=1.27, p>.10) between the two groups. Further analysis showed that while the male athlete captured more attention and encourage consumers to take a closer look at the advertisement and the advertised brand, it did not lead to a more positive evaluation of the advertised product. The study concludes that the process from visual attention to behavioural intention can be complex and require further study.

 
Yükseköğretimdeki Acil Uzaktan Öğretim Uygulamalarının Açık ve Uzaktan Öğrenme’nin Yönetim Bileşeni Bağlamında Değerlendirilmesi
Authors: GENÇ Hakan , KESİM Mehmet
Published: September 2023

Pandemi gibi krizlerin oluşturduğu kritik durumlarda hayata geçirilen eğitim uygulamaları iyi planlanmış bir Açık ve Uzaktan Öğrenme (AUÖ) yerine, ani kararlarla çözümler üretilmeye çalışılan bir Acil Uzaktan Öğretim olabilmektedir. Dolayısıyla kriz durumlarında nitelikli AUÖ uygulamalarının hayata geçirilebilmesi için kriz öncesinde oluşturulan planlamalara ihtiyaç duyulmaktadır. Ancak planlama öncesinde, öncelikle deneyimlenen krizlerin değerlendirilmesi gerekmektedir. Buradan hareketle bu araştırmada, deneyimlenen bir kriz durumu örneği olan Covid-19 sürecine odaklanılarak, yükseköğretimdeki Acil Uzaktan Öğretim uygulamalarının AUÖ sisteminin yönetim bileşeni bağlamında değerlendirilmesi amaçlanmaktadır. Araştırmada Keşfedici Durum Çalışması kullanılmıştır. Araştırmanın çalışma grubunu; 14 yükseköğretim kurumu, her bir kurumdan olmak üzere 14 akademisyen ve 14 öğrenen oluşturmaktadır. Araştırmanın verileri görüşmeler, dokümanlar ve araştırmacı günlüğü aracılığıyla toplanmıştır. Görüşmeler ve dokümanlar aracılığıyla toplanan verilerin analizinde betimsel analiz ve içerik analizi kullanılmıştır. Araştırma sonuçlarına göre AUÖ’nin yönetim bileşeni bağlamında, yükseköğretimdeki Acil Uzaktan Öğretim uygulamalarının, yükseköğretim kurumlarına göre birçok açıdan farklılık gösterdiği görülmektedir.
Nursing students' learning styles and attitudes towards learning: A cross-sectional study
Authors: EVRENOL ÖÇAL Simge , ÇETİN AVCI Seda , IŞIK Gülşen , YEŞİLÇINAR İlknur , CAN Sakine Zeyna , EGELİOĞLU CETİŞLİ Nuray
Published: September 2023

Learning is a different process for each person. Individual differences can be explained as each student uses different learning cycle stages. The main objectives of nursing education are to graduate competent nurses who have cognitive, social, affective, and psychomotor skills, can provide holistic care to individuals, and have lifelong learning skills. In order to achieve these objectives, it is crucial building an education process focused on the learning style of the students rather than providing only classical education methods. Having knowledge about students' learning styles contributes positively learning skills and attitudes towards learning. A cross-sectional research design was used to examine nursing students' learning styles and attitudes towards learning. A total of 444 undergraduate nursing students at a public university participated in this study. Data were collected using the Socio-Demographic Characteristics Forms, Learning Styles Inventory, and The Scale of Attitudes Towards Learning with an online questionnaire on 2021-2022 academic year. The data were analyzed using descriptive statistics and the Mann-Whitney U test. Of the nursing students, 59.2% had a learning style by doing, 83.4% by feeling, 85.6% by visual, and 63.7% by sequential. The mean score of the Attitudes towards Learning Scale was determined to be 153.26±11.16. Nursing students' attitudes and expectations towards learning were positive. Students with thinking and verbal learning styles have more positive attitudes toward learning. It is recommended to determine students' learning styles and use learning methods suitable for students in nursing education. It is thought that the more effective use of verbal learning resources in facilitating the learning of nursing students will positively affect the students' learning processes.
Hydrothermal Graphite as a Trigger for High-Temperature Orogenic Gold Mineralization at Haoyaoerhudong, Northern China
Authors: Li Wenbo , Zhang Fanghua , Qiao Xueyuan , Fu Tianyao
Published: September 2023

Carbonaceous materials are a key factor controlling mineralization processes in many world-class gold deposits. Haoyaoerhudong is the largest carbonaceous metasediment-hosted gold deposit on the north margin of the North China craton. Gold-bearing orebodies are hosted in carbonaceous slates and schists belonging to Mesoproterozoic rift-related successions. Typical hydrothermal minerals are pyrrhotite, quartz, biotite, graphite, apatite, titanite, and native gold. The ore mineralogy, combined with microthermometry and Raman spectra on fluid inclusions, has demonstrated three stages of hydrothermal activity: (I) quartz-biotite ± sulfide stage associated with gold mineralization (315°–510°C; ~4.8 wt % NaCl equiv; H2O-NaCl-CO2 ± CH4 ± N2 system); (II) quartz-sulfide stage, including quartz-sulfide stringers (IIa, 250°–334°C; ~5.4 wt % NaCl equiv; H2O-NaCl-CH4 ± CO2 ± N2 system) and fractured quartz-sulfide ores (IIb, 234°–308°C; ~4.1 wt % NaCl equiv; H2O-NaCl-N2 ± CH4 system); and (III) post-ore quartz-calcite stage (70°–219°C; ~4.8 wt % NaCl equiv; H2O-NaCl system). The molar ratios of CO2 and CH4 progressively decreased from stage I to II, consistent with the occurrence of graphite in alteration zones. Microscopic observation and Raman spectra suggest that the fine-grained graphite from altered schist (Gr-1/2) and coarse-sized graphite from gold-bearing veins (Gr-3/4) are of high crystallinity and exhibit characteristics indicating a hydrothermal origin. The δ13C values of graphite, varying from −27.1 to −26.0‰ Vienna-Pee Dee Belemnite (V-PDB), suggest that the carbon was of biogenetic origin. Apatite Sr isotopes (87Sr/86Sr: 0.708293–0.708842) and titanite Nd isotopes (εNdt: –11.76 to –14.84) also indicate contributions from carbonaceous rocks during mineralization.

Thermodynamic modeling demonstrates that graphite may have precipitated at Haoyaoerhudong due to cooling and reduction of the H2O-CO2-CH4 fluids at high temperatures. Graphite precipitation would significantly consume CO2 and effectively destabilize Au bisulfide complexes, facilitating the codeposition of pyrrhotite, graphite, and native gold at high temperatures (≥379°C). We infer that deposition of hydrothermal graphite is a crucial process for mesothermal-hypothermal mineralization in sediment-hosted orogenic gold deposits.
Unsupervised Ship Detection in SAR Imagery Based on Energy Density-Induced Clustering
Authors: Yuan Zifeng , Li Yu , Liu Yu , Liang Jiale , Zhang Yuanzhi
Published: September 2023

Article
Unsupervised Ship Detection in SAR Imagery Based on Energy Density-Induced Clustering

Zifeng Yuan 1, Yu Li 1,*, Yu Liu 1, Jiale Liang 1, and Yuanzhi Zhang 2,3

1 Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
2 School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing 100049, China
3 Key Laboratory of Lunar and Deep Space Exploration, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China
* Correspondence: yuli@bjut.edu.cn
 
 
Received: 6 March 2023
Accepted: 24 April 2023
Published: 26 September 2023
 

Abstract: Intelligent recognition of maritime ship targets from synthetic aperture radar (SAR) imagery is a hot research issue. However, interferences such as the strong sea clutter, sidelobe, small ship size and weak backscattered signal continually affect the detection results. To address this problem, a novel unsupervised machine learning-based ship detection algorithm, named energy density-induced clustering (EDIC), is proposed in this paper. It is discovered that the singular values between ship targets and interference signals are significantly different in a local region because of their various concentration degrees of signal energy intensity. Accordingly, in this study, two novel energy density features are proposed based on the singular value decomposition in order to effectively highlight the ship targets and suppress the interference. The proposed novel energy density features have the advantage of clearly distinguishing ship targets from sea surfaces regardless of the effects of interferences. To test the performance of the proposed features, unsupervised K-means clustering is conducted for obtaining ship detection results. Compared with the classical and state-of-the-art SAR ship detectors, the proposed EDIC method generally yields the best performance in almost all tested sea sample areas with different kinds of interferences, in terms of both detection accuracy and processing efficiency. The proposed energy density-based feature extraction method also has great potential for supervised classification using neural networks, random forests, etc.
Cross-Subject EEG Channel Selection Method for Lower Limb Brain-Computer Interface
Authors: Wei Mingnan , Huang Mengjie , Ni Jiaying
Published: September 2023

Article
Cross-Subject EEG Channel Selection Method for Lower Limb Brain-Computer Interface

Mingnan Wei 1,2, Mengjie Huang 3,*, and Jiaying Ni 3

1 School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China
2 Department of Computer Science, University of Liverpool, Liverpool, L69 3BX, United Kingdom
3 Design School, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China
* Correspondence: Mengjie.Huang@xjtlu.edu.cn
 
 
Received: 27 April 2023
Accepted: 30 June 2023
Published: 26 September 2023
 

Abstract: Lower limb motor imagery (MI) classification is a challenging research topic in the area of brain-computer interfaces (BCIs), and entails numerous signal channels to provide sufficient information about the background neural activity. However, practical applications often lack the environment to accommodate excessive channels due to the time-consuming setup process, inconvenient movement, and restricted application scenarios. The existing channel selection algorithms (designed for the individual subject) place a great deal of focus on the classified performance comparisons, whereas the significance of actual locations and neural functions of brain regions is disregarded. Although these algorithms require significant computation resources, their selected solutions cannot be re-used for other subjects to realize the cross-subject channel selection and improve the reusability of model due to poor interpretability and inapplicability. To date, there have been no investigations about the cross-subject channel selection problem for the lower limb MI stepping tasks. This study proposes an optimal cross-subject lower limb channel selection that selectively retains significant channels, narrows the computation scope of the selection, and obtains the optimal selection solutions. Through stepping-based MI experiments, the proposed optimal channel selection enables effective recognition in low-channel settings, thereby contributing a lot to the development of generic and convenient lower limb BCI systems. Additionally, statistical analysis reveals a significant difference in energy spectrum between left and right stepping-based MI tasks in the and  bands of the frontal lobe channels, providing new evidence that the frontal lobe dramatically affects lower limb MI tasks.
Improved Computer-Aided Diagnosis System for Nonerosive Reflux Disease Using Contrastive Self-Supervised Learning with Transfer Learning
Authors: Liao Junkai , Lam Hak-Keung , Gulati Shraddha , Hayee Bu
Published: September 2023

Article
Improved Computer-Aided Diagnosis System for Nonerosive Reflux Disease Using Contrastive Self-Supervised Learning with Transfer Learning

Junkai Liao 1, Hak-Keung Lam 1,*, Shraddha Gulati 2, and Bu Hayee 2

1 Department of Engineering, King’s College London, London, United Kingdom
2 King’s Institute of Therapeutic Endoscopy, King’s College Hospital NHS Foundation Trust, London, United Kingdom
* Correspondence: hak-keung.lam@kcl.ac.uk
 
 
Received: 5 February 2023
Accepted: 21 July 2023
Published: 26 September 2023
 

Abstract: The nonerosive reflux disease (NERD) is a common condition, the symptoms of which mainly include heartburn, regurgitation, dysphagia and odynophagia. The conventional diagnosis of NERD needs the endoscopic examination, biopsy of the lining of the esophagus (mucosa), and ambulatory pH testing over 24 to 96 hours, which is complex and time-consuming. To address this problem, a computer-aided diagnosis system for NERD (named NERD-CADS) has been proposed in our previous paper. The NERD-CADS offers a more convenient and efficient approach to diagnosing NERD, which only requires the input of endoscopic images into the computer to produce a nearly instant diagnostic result. The NERD-CADS uses a convolutional neural network (CNN) as a classifier and can classify the endoscopic images captured in the esophagus of both healthy people and NERD patients. This is, in fact, a classification problem of two classes: non-NERD and NERD. We conduct ten-fold cross-validation to verify the classification accuracy of the NERD-CADS. The experiment shows that the mean of ten-fold classification accuracy of the NERD-CADS test reaches 77.8%. In this paper, we aim to improve the classification accuracy of the NERD-CADS. We add the contrastive self-supervised learning as an additional component to the NERD-CADS (named NERD-CADS-CSSL), and investigate whether it can learn the capability of extracting representations to improve the classification accuracy. This paper combines the contrastive self-supervised learning with transfer learning, which first employs massive public image data to train the CNN by the contrastive self-supervised learning, and then uses the endoscopic images to fine-tune the CNN. In this way, the capability of extracting representations (learned by the contrastive self-supervised learning) can be transferred into the downstream task (NERD diagnosis). The experiment shows that the NERD-CADS-CSSL can obtain a higher mean (80.6%) in tests than the NERD-CADS (77.8%).
Real-Time Traffic Flow Statistics Based on Dual-Granularity Classification
Authors: Bi Yanchao , Yin Yuyan , Liu Xinfeng , Nie Xiushan , Zou Chenxi , Du Junbiao
Published: September 2023

Article
Real-Time Traffic Flow Statistics Based on Dual-Granularity Classification

Yanchao Bi, Yuyan Yin, Xinfeng Liu *, Xiushan Nie, Chenxi Zou, and Junbiao Du

1 School of Computer Science and Technology, Shandong Jianzhu University, Jinan 250101, China
* Correspondence: liuxinfeng18@sdjzu.edu.cn
 
 
Received: 17 June 2023
Accepted: 13 September 2023
Published: 26 September 2023
 

Abstract: Traffic detection devices can cause accuracy degradation over time. Considering problems such as time-consuming and laborious manual statistics, high misdetection probabilities, and model tracking failures, there is an urgent need to develop a deep learning model (which can stably achieve detection accuracy over 90%) to evaluate whether the device accuracy still satisfies the requirements or not. In this study, based on dual-granularity classification, a real-time traffic flow statistics method is proposed to address the above problems. The method is divided into two stages. The first stage uses YOLOv5 to acquire all the motorized and non-motorized vehicles appearing in the scene. The second stage uses EfficientNet to acquire the motorized vehicles obtained in the previous stage and classify such vehicles into six categories. Through this dual-granularity classification, the considered problem is simplified and the probability of false detection is reduced significantly. To correlate the front and back frames of the video, vehicle tracking is implemented using DeepSORT, and vehicle re-identification is implemented in conjunction with the ResNet50 model to improve the tracking accuracy. The experimental results show that the method used in this study solves the problems of misdetection and tracking effectively. Moreover, the proposed method achieves 98.7% real-time statistical accuracy by combining the two-lane counting method.
Anthracnose of Strawberry: Etiological and Ecological Characteristics, and Management
Authors: Nam Myeong Hyeon , Yoo Je Hyeok , Yun Tugsang , Kim Hakhun , Kim Hong Gi
Published: September 2023

Anthracnose caused by Colletotrichum spp. is a major disease of strawberry plants worldwide. The anthracnose of strawberries in Korea has occurred in most cultivated strawberry varieties since its first report in 1990. Although many studies and efforts have been made to control the disease, anthracnose continues to affect strawberry yields in Korea. In this review, we introduced various management methods to control anthracnose in strawberries, such as identifying pathogens and environmental factors involved in this disease, understanding the importance of latent infection, and developing diagnostic techniques and control methods. Through this review, we propose that researchers can elucidate a comprehensive and practical approach to control anthracnose by understanding this disease and developing strategies to prevent its spread, ultimately benefiting strawberry farmers.
Resistance Characteristics of Watermelon Cultivars to Fusarium oxysporum f. sp. niveum
Authors: Lee Soo Min , Jo Eun Ju , Kim Hun , Choi Gyung Ja
Published: September 2023

Fusarium wilt, caused by Fusarium oxysporum f. sp. niveum (Fon) is a serious disease in watermelon cultivation. Most of commercialized watermelon cultivars to Fusarium wilt are susceptible in Korea. Fon isolates were divided into four races (races 0, 1, 2, and 3), based on pathogenicity in four watermelon differentials including ‘Sugar baby’, ‘Charleston gray’, ‘Calhoun gray’ and ‘PI-296341-FR’. We obtained 7 isolates of Fon and tested to determine race of the fungal strains. Fon KACC 40902 and Fon HA were race 0 and Fon NW1, Fon NW2, Fon CW and Fon KACC 40901 were race 1. And Fon KACC 40905 was race 2, but race 3 isolate of Fon was not founded. We also tested virulence of seven Fon isolates on three-susceptible cultivars of watermelon. The isolates showed different virulence on the cultivars. In addition, to study the resistance characteristics of watermelon to Fon, we selected three moderately or highly resistant cultivars of watermelon and occurrence of Fusarium wilt in seedlings of the cultivars by seven Fon isolates was investigated. Among them, ‘Calhoun gray’ is highly resistant to six Fon isolates except Fon KACC 40905. On the other two cultivars, disease severity of Fusarium wilt caused by each isolate was positively correlated with the virulence of the Fon isolates. The results suggest that resistance of the watermelon cultivars to Fon isolates is likely affected by the virulence of the pathogen.
Determination of Antifungal Activity on Pepper Anthracnose and Plant Growth Promoting Activity of Pleurospermum camtschaticum Root Extract
Authors: Lee Inkyu , Baek Young Sun , Lee Youn Su
Published: September 2023

This study was conducted to confirm the utilization of Pleurospermum camtschaticum root extract as an organic agricultural material. Antioxidant activity of P. camtschaticum root extract, closely related to antibacterial activity, increased in a dose-dependent manner. In mycelial growth inhibitory activity, 100% P. camtschaticum root extract supressed over 70% for Colletotrichum coccodes and over 68% for Colletotrichum dematium. In the pepper fruit anthracnose development test, the size of the lesion decreased in a dose-dependent manner, which showed the same tendency as the previous results in inhibitory activity on mycelial growth. In the pepper seed germination and red pepper growth promotion test of P. camtschaticum root extract, oposite results was confirmed. The lower the concentration, the more the seed germination and growth promotion effects were shown. The phenol content of pepper leaves was also measured after pepper growth promotion test have been completed. The phenol content related to antibacterial activity increased in all treated groups compared to the untreated group. Therefore, the results of this study showed the possibility of development as an organic material.
First Report of Soft Rot Caused by Pectobacterium brasiliense on Cucumber in Korea
Authors: Hong Soo-Min , Park Kyoung-Taek , Ten Leonid N. , Back Chang-Gi , Kang In-Kyu , Lee Seung-Yeol , Jung Hee-Young
Published: September 2023

Wilted and water-soaked lesion symptoms were observed on cucumbers in greenhouses located in Daejeon, Chungcheongnam-do, Korea, in June 2021. A bacterial strain, designated KNUB-04-21, was isolated from the cucumbers, which was subsequently identified as Pectobacterium brasiliense through a phylogenetic analysis based on sequences of the 16S rRNA region, dnaX, leuS, and recA genes. The biochemical characteristics of KNUB-04-21 were also similar to those of P. brasiliense through investigation using the API ID 32 GN system. The pathogenicity of KNUB-04-21 was confirmed by inoculating it into healthy cucumber plants. The reisolated strains were also found to be same to the original strain. To our knowledge, this is the first report of P. brasiliense being identified as the causative agent of cucumber soft rot in Korea.
AutoDebias based on NeuralCF
Authors: Li Meng , Gu Zhuoya , Zheng Haolun , He Yening
Published: September 2023

Recommendation systems rely on user behavior data (ratings, clicks, etc.) to build personalized models. Nevertheless, the data collected was always observational rather than experimental, which can lead to a variety of biases. Data deviations will directly affect the operation results of the recommendation system. Users may not favor the items recommended by the system to them, so this is an imperative problem that must be resolved as soon as possible. The majority of current efforts to debias recommendation systems focus only on one or two specific biases and are not universally applicable. As a result, Chen et al. and their group developed a general debiasing framework (AutoDebias) containing most of the debias strategies, which overcomes the problem of low flexibility of most of today's debiasing techniques. However, the model still has room for improvement. Chen et al. chose Matrix Factorization (MF) as the benchmark model for AutoDebias. In our study, however, we found that NeuralCF model may be a better alternative to MF. Therefore, the goal of our work is to replace the MF base model in AutoDebias with the NeuralCF model, and to conduct relevant experiments in order to validate our hypothesis. According to experiments, when using NLL as evaluation metrics, NeuralCF has better performance than MF, which improved 14.3% in final results.
Improved time-aware debiasing models for recommender systems
Authors: Wang Sitan , Wu Xinyi , Zhao Lintong , Xue Yuru , Xia Ruihan , Sun Zhuofan
Published: September 2023

Recommender systems are affected by user selection bias during user interactions. Previously, Huang, Jin et al. proposed the TMF-DANCER model to deal with the fact that selection bias is dynamic, and the popularity of an item and user preferences may change drastically over time. However, the previous time-aware methods did not consider the continuity of time, and performing collaborative filtering with matrix factorization may not be able to capture the complex structure of user interaction data. Our methods enhance the effectiveness of time-aware debiasing by utilizing the time-varying sequential method to alleviate the discontinuity of time-based on the frequency-based method, Replacing the matrix factorization with neural collaborative filtering (NCF). We used movie lens 100k as the data for training. The experimental results indicate that methods incorporating the time-varying sequential method and NCF have better performance in rating prediction than debiasing methods without.
Cloud & IoT based indoor positioning solution with intuitive AR guidance
Authors: Peng Haobo , Cao Xuhang , Liu Xuyaun , Ding Mingyue
Published: September 2023

GPS, the most frequently used outdoor navigation system used in the contemporary world in peoples mobile phones, however, does not prove to be reliable in indoor settings. Neither do some wireless protocols such as Bluetooth and WIFI with RSSI do an effective job due to their susceptibility to physical obstacles such as walls and objects in the building. Our team came up with a solution utilizing UWB wireless communication protocol with SS-TWA to help users with an AR device, or similarly an AR application on smartphones, to navigate in indoor settings with clear graphic guidance, similar to the guiding systems already used by people in contemporary society. The map of the indoor setting and related calculations during the navigation process are all based on clouds, and we will show in detail how we implement our design. Finally, we discussed how our solution projects about indoor positioning can also be related to fields like ML, Open World and Metaverse.
Understanding the class separation process of convolutional neural networks
Authors: Yang Yiqi , Lian Xingyu , Liu Weihao , Shen Liyuan , Lin Jiayang
Published: September 2023

Extensive research shows that deep neural networks (DNNs) capture better feature representations than the previous handcrafted feature engineering, which leads to a significant performance improvement. However, it raises the question of how does the neural network spontaneously learn the intermediate representation, during the training process, to correctly separate the test data set into different categories? In this paper, based on the existing research work, we continue to take a small step towards understanding the dynamics of convolutional neural networks (CNN). Specifically, we model the test data set as a relationship graph, and each intermediate layer representation learned by CNN will transform the relationship graph correspondingly. Through these continuous transformations, we investigate the class separation process of CNN from two perspectives: 1) show the evolution of the degree of correlation between samples through the histogram of similarity between vertices; 2) by visualizing and quantifying the degree of separation (i.e., modularity) of the important relationship subgraph, we can show the contribution of each convolution layer of CNN to class separation. In the preliminary experiment, it can be found that: 1) each convolution layer of CNN gradually reduced the similarity of most edges between the samples to a very low level, that is, the dense relationship graph gradually evolved into a sparse graph; 2) the remaining important relationship subgraph consist of edges with high similarity shows evident modularity; 3) both visualization and quantification results show that the modularity of intra-class subgraph increases when the layers go deeper. Moreover, the degradation and plateau in the modularity curve reveal the existence of redundant layers. In this paper, we reveal some more in-depth dynamics of CNN, and introduced another modularity, which is widely used as the theoretical guidance tool of layer pruning. It can save more model parameters without losing the accuracy of classification.
A review of continuum robots for surgical applications
Authors: Li Kexin , Qi Ziyang , Feng Xueyan
Published: September 2023

The design of continuum robots is inspired by biological trunks, tentacles, and snakes, allowing them to navigate through some confined spaces, manipulate objects in the unstructured environments, and follow curvilinear paths. In recent decades, a wide range of designs of continuum robots have been explored and have illustrated capabilities that go beyond rigid-link robots. We have witnessed increasing efforts to use these characteristics to improve minimally invasive surgical interventions in recent years. In this paper, we summarize the key technologies and several applications of continuum robots in the surgical field. We also define the key performance index to evaluate the performance of continuum robots in the surgical field. By discussing challenges to be overcome before the potential of continuum robots as surgical devices can be fulfilled, we propose some future directions for the continuum robobts.
Effect of Annealing and Doping Process of the Zn1-xTixO Films
Authors: ÇORLU Tuğba , TEKİN Sezen , KARADUMAN ER Irmak , ACAR Selim
Published: September 2023

In this study, undoped and Ti-doped ZnO thin films grown by SILAR (Successive Ionic Layer Adsorption and Reaction) method were investigated using XRD, SEM, linear absorbance and electrical characterization. The effect of doping ratio was determined changing Ti ratios from 0.05 to 0.20. In addition, the films with the same additive ratio were annealed at 300°C for 15 minutes in nitrogen environment. Thus, the effects of both annealing and doping ratio on the thin films produced were examined in detail. When the current-voltage graphs are examined, it is observed that there is a decrease in the resistance values with doping. The best additive effect was observed for Zn0.90Ti0.10O film and the structures formed after this additive ratio returned to their initial morphology.
Dedicated Early Morning Orthopaedic Trauma Operating Room Is Associated With Shorter Time to Surgery and Decreased Length of Hospital Stay for Children Undergoing Surgical Treatment of Supracondylar Humerus Fractures: A Retrospective Cohort Study
Authors: Chen Vivian , Hara Reiko , Siddiqui Ali A. , Omar Hanna N. , Nazareth Alexander , Lightdale-Miric Nina , Phan Alex , Wren Tishya A. L. , Goldstein Rachel Y.
Published: September 2023

Introduction:

The purpose of this study was to investigate whether the use of a dedicated early morning orthopaedic trauma operating room (OR) resulted in shorter wait times, decreased surgical times, decreased length of stay (LOS), and decreased complications in children treated with urgent surgical intervention for supracondylar humerus fractures.

Methods:

This retrospective comparative cohort study at a level I pediatric trauma center included patients younger than 12 years with supracondylar humerus fractures urgently treated with closed or open reduction and percutaneous pinning. Index surgical cases from April 28, 2013, to February 26, 2020, were included. Patients with prior humerus fracture, concomitant injuries, open fracture, pulseless supracondylar fracture, or missing data were excluded. Patients were analyzed based on the type of OR: dedicated early morning orthopaedic trauma OR or typical daytime orthopaedic OR. The primary outcome was time from presentation to surgery. Secondary outcomes included surgical time, complications, and LOS.

Results:

A total of 401 patients with a mean age of 5 ± 2 (range: 1 to 11) years and a mean follow-up of 2.0 ± 2.1 (range: 0.5 to 25.0) months were included, of whom 137 patients (34%) underwent surgery in the early morning dedicated orthopaedic trauma OR. The dedicated early morning orthopaedic OR group had significantly less time from presentation to surgery (7.5 versus 9.4 hours; P = 0.0002) and shorter LOS (21.0 versus 24.0 hours; P = 0.004) compared with children treated in the typical daytime orthopaedic OR. Surgical time (31.1 versus 32.6 minutes; P = 0.40) and complication rates (5.8% versus 4.9%; P = 0.65) were similar between the groups. No revision surgery was required in either group.

Discussion:

Surgical wait times were diminished with use of the dedicated early morning OR, as was LOS. Surgical times and complication rates were similar between groups. Institutions may consider adopting a dedicated early morning orthopaedic trauma OR to improve surgical wait times and decrease LOS.

Level of evidence:

III