bluuebunny/crossref_metadata_2025 huggingface dataset:
Microextrusion Printing of Multilayer Hierarchically Organized Planar Nanostructures Based on NiO, (CeO2)0.8(Sm2O3)0.2 and La0.6Sr0.4Co0.2Fe0.8O3−δ
Authors: Simonenko Tatiana L. , Simonenko Nikolay P. , Gorobtsov Philipp Yu. , Simonenko Elizaveta P. , Kuznetsov Nikolay T.
Published: December 2022

In this paper, NiO, La0.6Sr0.4Co0.2Fe0.8O3-δ (LSCF) and (CeO2)0.8(Sm2O3)0.2 (SDC) nanopowders with different microstructures were obtained using hydrothermal and glycol–citrate methods. The microstructural features of the powders were examined using scanning electron microscopy (SEM). The obtained oxide powders were used to form functional inks for the sequential microextrusion printing of NiO-SDC, SDC and LSCF-SDC coatings with resulting three-layer structures of (NiO-SDC)/SDC/(LSCF-SDC) composition. The crystal structures of these layers were studied using an X-ray diffraction analysis, and the microstructures were studied using atomic force microscopy. Scanning capacitance microscopy was employed to build maps of capacitance gradient distribution over the surface of the oxide layers, and Kelvin probe force microscopy was utilized to map surface potential distribution and to estimate the work function values of the studied oxide layers. Using SEM and an energy-dispersive X-ray microanalysis, the cross-sectional area of the formed three-layer structure was analyzed—the interfacial boundary and the chemical element distribution over the surface of the cross-section were investigated. Using impedance spectroscopy, the temperature dependence of the electrical conductivity was also determined for the printed three-layer nanostructure.
Fabrication and Calibration of Pt-Rh10/Pt Thin-Film Thermocouple
Authors: Wang Fengxiang , Lin Zhenyu , Zhang Zhijie , Li Yanfeng , Chen Haoze , Liu Jiaqi , Li Chao
Published: December 2022

Aiming at the dynamic testing of the ignition temperature of micro-initiating explosives, a novel Pt-Rh10/Pt thin-film thermocouple was designed in this paper. The author carried out the preparation of the thermocouple by using a screen printing process on an Al2O3 ceramic substrate. The formed thermocouple was made of Pt-Rh10 wire and Pt wire as compensation wires, with a size of ≤ 1 mm and a thickness of about 6 μm. In the testing process, the static calibration of the thermocouple at 50~600 °C and 650~1500 °C was completed by a portable temperature verification furnace and a horizontal high temperature verification furnace, and the results showed that the Seebeck coefficient of the thermocouple was about 10.70 μV/°C, and its output voltage–temperature curve was similar to that of a standard S-type thermocouple, which achieved the effective temperature measurement up to 1500 °C. The dynamic response of Pt-Rh10/Pt thin-film thermocouple was then tested and studied using the pulsed laser method, and the results show that the time constant of the thermocouple prepared in this paper is about 535 μs, which has the characteristics of fast response and high precision high-temperature testing. Compared with the traditional thin-film thermocouple, the thermocouple has excellent electrical conductivity, more oxidation resistance, the surface layer is not easy to peel off and other advantages.
Relationship between Dough Properties and Baking Performance of Panned Bread: The Function of Maltodextrins and Natural Gums
Authors: AbuDujayn Abdulmajeed A. , Mohamed Abdellatif A. , Alamri Mohamed Saleh , Hussain Shahzad , Ibraheem Mohamed A. , Qasem Akram A. Abdo , Shamlan Ghalia , Alqahtani Nashi K.
Published: December 2022

The effectiveness of hydrocolloids (2% maximum in various combinations) from various sources, including maltodextrins (MD) with polymerization degree (DP) 18 and ziziphus gum (ZG), on the dough properties and quality of panned bread, as well as the possibility of using them to delay the bread staling process, have been investigated after 24, 72, and 96 h of storage. By evaluating the pasting capabilities of wheat flour slurry, dough properties, and the final product, the effects of the ziziphus gum (ZG) and maltodextrins (MD) were ascertained. A TA-TXT texture analyzer, a texture profile analysis test, and Micro-doughLab were used to evaluate the dough mixing properties. Additionally, a hedonic sensory evaluation of the overall acceptance of the bread, as well as its texture, aroma, taste, and color, was done. It is clear that MD had a more distinct impact than ZG on the way dough was mixed, the texture of the gel, and the finished product. The combination of MD and ZG significantly altered the bread’s physical characteristics and its aging over time. The decreased peak viscosity and noticeably smaller setback of wheat flour gels, which corresponded to lower gel hardness, serve as evidence of reduced amylose retrogradation. At 2%, MD outperformed ZG in terms of increasing water absorption, dough stability, and bread loaf volume. With the exception of the blend that included three times as much MD as ZG, all mixes, including the control, exhibited an increase in bread firmness as a function of time after storage. Overall, the panelists liked (score of 5 and above) the bread made with mixes that had either MD or ZG, or a combination of both.
A Hypered Deep-Learning-Based Model of Hyperspectral Images Generation and Classification for Imbalanced Data
Authors: Naji Hasan A. H. , Li Tianfeng , Xue Qingji , Duan Xindong
Published: December 2022

Recently, hyperspectral image (HSI) classification has become a hot topic in the geographical images research area. Sufficient samples are required for image classes to properly train classification models. However, a class imbalance problem has emerged in hyperspectral image (HSI) datasets as some classes do not have enough samples for training, and some classes have many samples. Therefore, the performance of classifiers is likely to be biased toward the classes with the largest samples, and this can lead to a decrease in the classification accuracy. Therefore, a new deep-learning-based model is proposed for hyperspectral images generation and classification of imbalanced data. Firstly, the spectral features are extracted by a 1D convolutional neural network, whereas a 2D convolutional neural network extracts the spatial features and the extracted spatial features and spectral features are catenated into a stacked spatial–spectral feature vector. Secondly, an autoencoder model was developed to generate synthetic images for minority classes, and the image samples were balanced. The GAN model is applied to determine the synthetic images from the real ones and then enhancing the classification performance. Finally, the balanced datasets are fed to a 2D CNN model for performing classification and validating the efficiency of the proposed model. Our model and the state-of-the-art classifiers are evaluated by four open-access HSI datasets. The results showed that the proposed approach can generate better quality samples for rebalancing datasets, which in turn noticeably enhances the classification performance compared to the existing classification models.
CSANet: Cross-Scale Axial Attention Network for Road Segmentation
Authors: Cao Xianghai , Zhang Kai , Jiao Licheng
Published: December 2022

Road segmentation from remote sensing images is an important task in many applications. However, due to the high density of roads and the complex background, the roads are often occluded by trees. This makes accurate road segmentation a challenge task. Most existing road segmentation networks rely on convolutions with small kernels; however, these methods often cannot obtain satisfying results because the long-range dependencies are not captured and the intrinsic relationships between feature maps at different scales are not fully exploited. In this paper, a deep neural network based on a cross-scale axial attention mechanism is proposed to address this problem. This model enables low-resolution features to aggregate global contextual information from high-resolution features. Among them, the axial attention mechanism realizes global attention by using vertical and horizontal attention sequentially. With this strategy, the dense long-range dependencies can be captured with extremely low computational cost. The cross-scale mechanism enables the model to effectively combine the high-resolution fine-grained features and the low-resolution coarse-grained features. The proposed method enables the network to propagate the information without losing details. Our method achieves IoUs of 58.98 and 65.28 on the Massachusetts Roads dataset and DeepGlobe dataset and outperforms other methods.
A Review of Data-Driven Approaches and Techniques for Fault Detection and Diagnosis in HVAC Systems
Authors: Matetić Iva , Štajduhar Ivan , Wolf Igor , Ljubic Sandi
Published: December 2022

Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings’ energy is mostly used for heating and/or cooling. These systems heavily rely on sensory measurements and typically make an integral part of the smart building concept. As such, they require the implementation of fault detection and diagnosis (FDD) methodologies, which should assist users in maintaining comfort while consuming minimal energy. Despite the fact that FDD approaches are a well-researched subject, not just for improving the operation of HVAC systems but also for a wider range of systems in industrial processes, there is a lack of application in commercial buildings due to their complexity and low transferability. The aim of this review paper is to present and systematize cutting-edge FDD methodologies, encompassing approaches and special techniques that can be applied in HVAC systems, as well as to provide best-practice heuristics for researchers and solution developers in this domain. While the literature analysis targets the FDD perspective, the main focus is put on the data-driven approach, which covers commonly used models and data pre-processing techniques in the field. Data-driven techniques and FDD solutions based on them, which are most commonly used in recent HVAC research, form the backbone of our study, while alternative FDD approaches are also presented and classified to properly contextualize and round out the review.
Evaluation of Social Stability Risk of Adjusting Goods Vehicle Calculation Method Based on Optimal Combination Weighting—Cloud Model
Authors: Chong Pengyun , Yin Hui , Wang Chaofeng , Wang Pengcheng , Li Linqing , Wu Di , Li Jingwei , Ding Dong
Published: December 2022

In order to solve the social stability risk problem of the adjusting goods vehicle calculation method (AGVCM) in the cancellation of toll stations at expressway provincial boundaries, a social stability risk evaluation model was proposed. Firstly, based on the possible time stages of the AGVCM, we built the social stability risk evaluation index system of the AGVCM including 4 levels, 3 grades, and 60 indicators. Secondly, we used the semantic information of cloud model to transform qualitative description and quantitative evaluation, calculated the risk level for social stability risk evaluation of AGVCM according to an integrated cloud algorithm, and proposed an optimal combination weighting—cloud model for the social stability risk evaluation of AGVCM. Finally, the feasibility of the evaluation model is verified by a case study in Yunnan province in China. The results showed that the cloud model’s numerical characteristic of social stability risk evaluation of AGVCM in Yunnan based on the optimal combination weighting—cloud model is (0.28, 0.073, 0.0008), implying the risk level is “small” and the conclusion is basically consistent with current standards. The model contains rich process information, which is helpful to better effectively eliminate the subjectivity and arbitrariness in the evaluation process of identifying the key factors affecting the project risk level.
Can Mechanization Promote Green Agricultural Production? An Empirical Analysis of Maize Production in China
Authors: Wang Yakun , Jiang Jingli , Wang Dongqing , You Xinshang
Published: December 2022

This study systematically analyzes the impact of China’s maize Green Total Factor Productivity (GTFP) and mechanization on GTFP, providing a reference for reasonably playing the role of mechanization and improving China’s agricultural GTFP. Based on the difference in crop types and regional applicability of agricultural mechanization, this study selects maize as the research crop to analyze the impact of agricultural mechanization level on GTFP. In this study, the SBM-ML model is used to measure China’s maize GTFP, reveal the temporal and regional change characteristics of maize GTFP, and clarify the optimization direction of maize GTFP from the perspective of regional differences and resource endowment differences. This study uses the threshold regression model to systematically analyze the impact of agricultural mechanization on GTFP and its mechanism. Results are given as follows: (1) The growth of China’s maize production GTFP fluctuates greatly in each year, and the growth of maize GTFP depends on the alternate promotion of technical efficiency and technical progress. Greenhouse gas emissions have a significant impact on GTFP. Excessive use of pesticides and fertilizers is the biggest obstacle to the improvement of maize GTFP. (2) There are also specific regional differences in the factors that affect the improvement of maize GTFP efficiency in different regions. The impact of mechanization on agricultural GTFP varies among regions. (3) The development level of agricultural mechanization at different stages has different promotion effects on maize GTFP. Agricultural mechanization has a two-way effect on maize GTFP. The factors of land type and land area will not limit the promotion of agricultural mechanization to maize GTFP. (4) Agricultural financial investment, environmental pollution control efforts, agricultural science and technology expenditure and other factors play a positive role in improving GTFP. (5) In future production, we should pay attention to the combination of agricultural mechanization and regional production characteristics, optimize the allocation of agricultural machinery, and strengthen the coordination between agricultural mechanization and moderate scale operation. The findings of our study provide useful policy implications for the promotion and development of agriculture in China.
Digital Economy Development and Green Economic Efficiency: Evidence from Province-Level Empirical Data in China
Authors: Kong Lingzhang , Li Jinye
Published: December 2022

The digital economy development promotes green transformation in China’s economy. Based on provincial-level data from 2011–2019, an ArcGIS spatial analysis is used to explore the spatial and temporal evolution patterns of the digital economy development and green economic efficiency. The digital economy development’s impact on the green economic efficiency is tested through fixed effect, mediation effect, and spatial Durbin models. The digital economy development and green economic efficiency increased during the study period. Spatial patterns of high-level areas spread to form “clusters” with surrounding areas. The digital economy development’s catalytic effect on the green economic efficiency holds after robustness and endogeneity tests. A heterogeneity analysis shows that the digital economy development promotes the green economic efficiency in the eastern and central regions; the impact on the western region is non-significant. Compared with industry digitalization, digital industrialization has a stronger promoting effect on the green economic efficiency. The digital economy development better facilitates the green economic efficiency in regions with high digital economy development levels and Big Data experimental areas. The digital economy development promotes green economic efficiency through human capital, industrial structure upgrading, and technological innovation; industrial structure upgrading has a stronger mediating effect, reaching 40%. The digital economy development facilitates the regional green economic efficiency and significantly promotes green economic efficiency in neighboring regions through spatial spillover effects.
Characterization and Thermal Treatment of the Black Mass from Spent Lithium-Ion Batteries
Authors: Mousa Elsayed , Hu Xianfeng , Ånnhagen Ludvig , Ye Guozhu , Cornelio Antonella , Fahimi Ario , Bontempi Elza , Frontera Patrizia , Badenhorst Charlotte , Santos Ana Cláudia , Moreira Karen , Guedes Alexandra , Valentim Bruno
Published: December 2022

Recycling lithium-ion batteries is crucial for the environment and the sustainability of primary resources. In this paper, we report on the characterization of two grades of black mass from spent lithium-ion batteries (with typical lithium–nickel–manganese–cobalt oxide cathode compositions) and their behavior during heating trials. This study paves the way for optimizing lithium-ion battery recycling processes by fully characterizing black mass samples before and after heating. A gas release under pyrolytic conditions was detected using a multicomponent mass spectrometer and included dimethyl carbonate, diethyl carbonate, oxygenated hydrocarbons, hydrocarbons, and other miscellaneous gases. This can be attributed to the evaporation of volatile organic compounds, conductive salt, organic polyvinylidene fluoride binder, and an organic separator such as polypropylene. Thermal treatment led to the partial decomposition of the binder into char and newly formed fluorine cuboids. The compaction of the cathode decreased, but the remaining binder limited recycling processes. By heating the black mass samples to 900 °C, the intensity of the X-ray diffraction graphitic carbon peak decreased, and the lithium metal oxides were reduced to their corresponding metals. The graphite in the black mass samples was structurally more disordered than natural graphite but became more ordered when heated.
Language Development for English-Medium Instruction: A Longitudinal Perspective on the Use of Cohesive Devices by Chinese English Majors in Argumentative Writing
Authors: Pu Liping , Heng Renquan , Xu Bingchao
Published: December 2022

In alignment with a strong increase of fully or partially English-taught programmes worldwide, intense research interest has been drawn to English as a medium of instruction (EMI) in higher education. In the meanwhile, much research has been done concerning cohesion and coherence in second language writing, which reveals that the appropriate use of cohesive devices will ultimately lead to text coherence. This study adopts a longitudinal perspective to examine the use of cohesive devices by Chinese English majors in argumentative writing in the EMI context. Thirty-one second-year Chinese English majors participated in this study. They were given three writing prompts at the initial, middle, and final time-points of one academic year, respectively. Altogether, 93 argumentative writings were collected, and 30 cohesion indices were selected and investigated at local, global and text levels via two automatic computational tools: Coh-Metrix and TAACO. The major findings of the study indicate (1) Chinese English majors were capable of a variety of cohesive devices in their writing. They tended to use local cohesive devices, especially connectives, more than global and text cohesive devices; (2) Most of the cohesion indices demonstrated growth. Of the 30 selected cohesion indices, 13 presented significant development over one academic year, and among them, 3 were at local level, 10 at global level and 3 at text level. Informed of the possible learning trajectories of cohesive devices, teachers may be guided to focus on their teaching in some specific areas of cohesion, and students may be more aware of what contributes to their writing performance and what to emphasize when writing in English.
Evaluation of Non-Invasive Gargle Lavage Sampling for the Detection of SARS-CoV-2 Using rRT-PCR or Antigen Assay
Authors: Bouska Ondrej , Jaworek Hana , Koudelakova Vladimira , Kubanova Katerina , Dzubak Petr , Slavkovsky Rastislav , Siska Branislav , Pavlis Petr , Vrbkova Jana , Hajduch Marian
Published: December 2022

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused considerable disruption worldwide. For efficient SARS-CoV-2 detection, new methods of rapid, non-invasive sampling are needed. This study aimed to investigate the stability of SARS-CoV-2 in a novel medium for gargle-lavage (GL) self-sampling and to compare the performance of SARS-CoV-2 detection in paired self-collected GL and clinician-obtained nasopharyngeal swab (NPS) samples. The stability study for SARS-CoV-2 preservation in a novel medium was performed over 14 days (4 °C, 24–27 °C, and 37 °C). In total, 494 paired GL and NPS samples were obtained at the University Hospital in Olomouc in April 2021. SARS-CoV-2 detection in paired samples was performed with a SARS-CoV-2 Nucleic Acid Detection Kit (Zybio, Chongqing Municipality, Chongqing, China), an Elecsys® SARS-CoV-2 Antigen assay (Roche Diagnostics, Mannheim, Germany), and a SARS-CoV-2 Antigen ELISA (EUROIMMUN, Lübeck, Germany). The stability study demonstrated excellent SARS-CoV-2 preservation in the novel medium for 14 days. SARS-CoV-2 was detected in 55.7% of NPS samples and 55.7% of GL samples using rRT-PCR, with an overall agreement of 91.9%. The positive percent agreement (PPA) of the rRT-PCR in the GL samples was 92.7%, and the negative percent agreement (NPA) was 90.9%, compared with the NPS samples. The PPA of the rRT-PCR in the NPS and GL samples was 93.2% when all positive tests were used as the reference standard. Both antigen detection assays showed poor sensitivity compared to rRT-PCR (33.2% and 36.0%). rRT-PCR SARS-CoV-2 detection in self-collected GL samples had a similar PPA and NPA to that of NPSs. GL self-sampling offers a suitable and more comfortable alternative for SARS-CoV-2 detection.
A Glimpse on the Evolution of RNA Viruses: Implications and Lessons from SARS-CoV-2
Authors: Šimičić Petra , Židovec-Lepej Snježana
Published: December 2022

RNA viruses are characterised by extremely high genetic variability due to fast replication, large population size, low fidelity, and (usually) a lack of proofreading mechanisms of RNA polymerases leading to high mutation rates. Furthermore, viral recombination and reassortment may act as a significant evolutionary force among viruses contributing to greater genetic diversity than obtainable by mutation alone. The above-mentioned properties allow for the rapid evolution of RNA viruses, which may result in difficulties in viral eradication, changes in virulence and pathogenicity, and lead to events such as cross-species transmissions, which are matters of great interest in the light of current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemics. In this review, we aim to explore the molecular mechanisms of the variability of viral RNA genomes, emphasising the evolutionary trajectory of SARS-CoV-2 and its variants. Furthermore, the causes and consequences of coronavirus variation are explored, along with theories on the origin of human coronaviruses and features of emergent RNA viruses in general. Finally, we summarise the current knowledge on the circulating variants of concern and highlight the many unknowns regarding SARS-CoV-2 pathogenesis.
Urban Flood Loss Estimation and Evacuation Design Based on a 500-Year Extreme Flood Event in Syracuse City
Authors: Si Yunrui , Li Junli , Si Youbin
Published: December 2022

To understand the potential risk of flooding in Syracuse City, New York State, USA, this research attempted to accomplish the flood hazard assessment for a simulated 500-year flood event in the downstream floodplain of Onondaga Creek within Syracuse. Based on the commonly used category of flood damages, the flood damage of Syracuse was divided into loss of buildings and loss of population. The results showed that the city’s center would have the highest damage rate for buildings and a total of 1139 buildings would be inundated, of which 326 buildings would be severely damaged by more than 80%. Furthermore, about 7390 people would be directly affected by the flood event, among which approximately 900 people might lose their lives. Communities near Onondaga Creek were assigned designated evacuation shelters based on the accessibility and distance to the shelters. The shortest available evacuation routes were calculated. More shelters should be provided in the central downtown area, with its large population, and distributed along the western bank of Onondaga Creek. This research offered a first approximate flood loss estimation that might lead to more attention and studies concerning a potential flood hazard in the future. It also provided science-based guidelines for city authorities to refer to in practical flood hazard mitigation.
Assessment of Undergraduate Students’ Attitudes Towards Learning English Based on Academic Major, Class Level, and Gender Variables
Authors: Muftah Muneera
Published: December 2022

The goal of this study is to investigate undergraduate students' attitudes toward learning English based on their academic major, class level, and gender. A total of 150 undergraduate students (65 males and 85 females) distributed in different class levels and different colleges and departments were surveyed using a Likert-type scale. Statistical differences indicated that students had a mixed bag of attitudes about the English language, with some being positive and others being negative. The findings revealed that students in science-related majors and Kindergarten Education had a higher interest in learning English than other students; all students in science-related majors believed that learning English is beneficial; felt more confident and had more positive attitudes toward their English instructors than those in Education-related ones. In addition, juniors were more enthusiastic about learning English as a second language and had more positive attitudes toward it than freshmen. Likewise, female students obtained more positive attitudes in terms of interest and instructor subscales. However, ANOVA analysis of indicated no significant differences in self-confidence and usability subscales between male and female students. In light of the research's conclusions, some practical implications are explored to assist students in adopting a positive attitude toward English language learning.
The Non-European Nature of the Bulgarian Socio-Economic Model
Authors: Minkov Zhivko
Published: December 2022

The article looks at the contemporary socio-economic model in Bulgaria arguing that it does not correspond to the broad European tradition of being sensitive to the presence of significant social imbalances in the society. The author insists that this is one of the primary factors for the controversial economic outcomes and the existence of deepening social problems in the country. The argumentation goes through evaluation of the formation process of the new socio-economic model in Bulgaria after 1989 and the assessment of the economic and social outcomes for the period until 2022. On this basis it is concluded that maintaining the current policy in the medium-term will inevitably undermine not only the economic prospects, but also the quality and stability of Bulgarian democracy.
Using Anchor to Create Podcasts for Youth Audiences
Authors: Mott Rebecca , Preston Kate , Brandt Heath
Published: December 2022

The Anchor podcasting tool provides an innovative way for Extension professionals to deliver information to youth, as well as promote further engagement. This article describes the process our team followed to create a series of career podcasts for middle school students using Anchor. We discuss benefits and considerations to keep in mind if you are considering launching a podcast of your own.
Life Long Learning Preferences of General Surgeons After Covid-19 : Hybrid Model
Authors: EKİCİ Mehmet Fatih , YILDIRIM Ali Cihat , ZEREN Sezgin
Published: December 2022

Aim:

For a surgeon during his professional career; Increasing their knowledge and experience, improving their professional skills and sharing their knowledge and experience is a necessity rather than a choice. The COVID-19 pandemic has revealed new choices in the concept of lifelong learning, with virtual meetings scheduled by surgeons using videoconferencing applications over the internet. In this study, we evaluated the compliance of general surgeons to webinars during the COVID-19 outbreak and their future training expectations with a questionnaire.

Design:

A questionnaire of 20 questions was prepared. The questionnaire was administered questions without aiming to obtain the personal information of the participants. . This survey was announced on the social media application Twitter. Survey questions were answered by 108 participants.

Results:

In the survey participated by surgeons, we concluded that short-term presentations, edited surgery videos and question-answer activities will be preferred more, and webinars held in the evening will be preferred more than those planned at the weekend. During the pandemic, it was determined that surgeons preferred free webinars and attended more national and international meetings compared to the pre-pandemic period. Respondents stated that they would prefer hybrid meetings in the future.

Results:

Considering the results of our social media-mediated survey: there is an intense participation in online seminars by surgeons. We also concluded that in the near future, surgeons will prefer hybrid training models rather than face-to-face training to improve and update themselves.
Про підхід до визначення відповідності між пікселями камери і проєктора у мультимедійному тирі
Authors: Яременко Сергій Володимирович , Крак Юрій Васильович
Published: December 2022

Предметом вивчення в статті є геометричні перетворення у системі«проєктор–екран–камера» для визначення відповідності між пікселямикамери і проєктора у мультимедійному тирі. Метою є розробка математичної моделі та алгоритму визначення відповідності між пікселямикамери і проєктора. Це потрібно для співставлення положення центроїдалазерної плями від пострілу в матриці камери і мішені, що генеруєтьсяу матриці проєктора. Завдання: формалізувати задачу виникнення геометричних спотворень у системі «проєктор–екран–камера»; розробитиматематичну модель визначення відповідності між пікселями камериі проєктора; вибрати ефективний алгоритм її вирішення. Використовуваними методами є: математична модель вирівнювання зображення наоснові гомографії, метод бінаризації з вибором значення порога методом Оцу; метод Дугласа–Пекера, який зменшує кількість точок, що апроксимують криву. Отримано такі результати. Згідно аналізу геометричних спотворень у системі «проєктор–екран–камера» сформульовано задачу розробки моделі для вирівнювання зображення з метоювизначення відповідності між пікселями камери і проєктора. Розроблено математичну модель і алгоритм вирівнювання точок зображення мішені у матриці камери з точками зображення мішені у матриці проєктора. Розроблено і програмно реалізовано алгоритм визначення відповідності між пікселями камери і проєктора. Математичнізалежності для визначення відповідності між пікселями камери і проєктора встановлено на основі матриці гомографії. Коефіцієнти матриціобчислюються за відповідними кутовими точками прямокутника матриці проєктора і його спотвореного трапецеїдального зображення наматриці камери. Розроблено алгоритм автоматичного визначення вершин трапеції та встановлення відповідності між пікселями камериі проєктора. Проведено аналіз та експериментальні дослідження факторів, що впливають на точність алгоритму: точність визначення вершин трапеції, за якими знаходяться коефіцієнти матриці гомографії; ступіньзаповнення області огляду камери зображенням із проєктора; відповідність роздільної здатності камери і проєктора. Дано рекомендації щодозменшення їхнього впливу. Зроблено такі висновки. Наукова новизнаотриманих результатів полягає в наступному: розроблено і експериментально досліджено математичну модель визначення відповідності міжпікселями камери і проєктора у мультимедійному тирі через вирівнюваннязображення, що відображається з екрана проєктора у камері, на основігомографії. До цього для вирівнювання зображень у мультимедійному тирі використовувалась модель на основі 2D-перетворень, у якій взаємнеположення у просторі проєктора, екрана і камери не враховується.Оскільки у гомографії враховуються тільки лінійні перетворення, у подальшому планується удосконалити модель — врахувати нелінійніспотворення, що виникають у об’єктивах камери і проєктора.
Pemanfaatan Limbah Jerami, Sekam, dan Urine Sapi sebagai Pupuk Organik untuk Meningkatkan Pertumbuhan dan Produksi Padi
Authors: Istiqomah Istiqomah , Eka Kusumawati Dian , Dita Serdani Army , Abdul Choliq Fery
Published: December 2022

Rice cultivation activities can produce organic waste such as straw and husks which can be processed into solid organic fertilizer and liquid smoke. In addition to agricultural waste, organic material from livestock waste can also be used as organic fertilizer, one of which is cow urine which can be processed into cow biourine. This research aimed to determine the effect of organic fertilizer  from straw, husk and cow biourine on the growth and production of rice. The research used factorial randomized block design (RAKF) with 2 factors. The first factor is solid organic fertilizer which consists of treatment without solid organic fertilizer, straw ash, and rice husk biochar. The second factor is liquid organic fertilizer which consists of treatment without liquid fertilizer, cow biourine, and husk liquid smoke. The observed parameters were plant height, number of tillers, leaf chlorophyll content, number of panicles, weight of 1000 seeds, and weight of grain per hectare. The results showed that there was an interaction between solid organic fertilizer (rice husk biochar and straw ash) and liquid organic fertilizer (husk liquid smoke and cow biourine) in increasing plant height, number of tillers, number of panicles, and yields. Separate treatment of solid organic fertilizer and liquid organic fertilizer affected the leaf chlorophyll content of rice plants. The application of rice husk biochar and cow biourine fertilizer resulted in the highest plant height, number of tillers, and number of panicles. In rice yields, the highest yields were found in rice husk biochar combined with cow biourine and husk biochar combined with husk liquid smoke.
Archeologický výzkum na nádvoří radnice v Českých Budějovicích
Authors: Čapek Ladislav
Published: December 2022

Cílem studie je představení post-exkavační metody práce se stratigrafickými a keramickými daty za účelem vytvoření relativní chronologie mnohovrstevnaté městské lokality na základě rozfázovaného sekvenčního modelu. K interakci mezi stratigrafickými a keramickými daty jsou využity exploatorní a vícerozměrové (multivariační) statistické metody seriace, korespondenční a faktorové analýzy. Příkladová studie vychází z výzkumu nádvoří městské radnice v Českých Budějovicích, který proběhl v letech 1996–1997, jehož výsledky byly v nedávné době vyhodnoceny a publikovány. Shrnuty jsou zde hlavní vývojové fáze osídlení od počátků založení města v roce 1265 do výstavby renesanční radnice v polovině 16. století a k nim odpovídající statisticky vyčleněné keramické horizonty. V článku jsou rovněž nastíněny možnosti dynamické interpretace rozfázovaného sekvenčního Harrisova diagramu v souvislosti se sociálními a behaviorálními přístupy ke studiu archeologických stratifikací, které ukazují na řadu druhů lidských aktivit v zastavěném městském prostředí.
KINETICS, EQUILIBRIUM AND THERMODYNAMICS OF CONGO RED REMOVAL BY CATIONIZED CELLULOSE OBTAINED FROM CEREAL BY-PRODUCTS
Authors:   Institute of General and Inorganic Chemistry, Bulgarian Academy of Sciences,  Acad. G. Bonchev Str., 111113 Sofia, Bulgaria, VASSILEVA PAUNKA S. , UZUNOV IVAN M. ,   Institute of General and Inorganic Chemistry, Bulgarian Academy of Sciences,  Acad. G. Bonchev Str., 111113 Sofia, Bulgaria, VOYKOVA DIMITRINKA K. ,   Institute of General and Inorganic Chemistry, Bulgarian Academy of Sciences,  Acad. G. Bonchev Str., 111113 Sofia, Bulgaria
Published: December 2022

The present study deals with the removal efficiency towards Congo red dye of two cationized cellulose adsorbents prepared from cereal by-products. Rice and einkorn husks were used as raw materials to extract and separate the cellulose by alkali and bleaching treatments. The cellulose materials were modified with N,N-dimethyl-1-octadecylamine to prepare cationized adsorbents. Instrumental methods, such as XRD, DTA, FTIR and SEM, as well as low-temperature nitrogen adsorption, were used for their characterization. The results showed that the quaternary ammonium group was successfully grafted onto the cellulose structures. The survey mainly focused on the effect of process parameters on the adsorption capacity of the investigated materials, including contact time, initial Congo red concentrations, solution pH and temperature. The adsorption process was well described by the pseudo-second-order and Langmuir models. The values of entropy, enthalpy and Gibbs free energy for the Congo red removal were determined.
"GREEN SYNTHESIS OF NANO-SILVER/SODIUM ALGINATE/CARBOXYMETHYL XANTHAN GUM HYDROGEL AND EVALUATION OF ITS ANTI-INFLAMMATORY AND ANTI-Helicobacter pylori ACTIVITY "
Authors:   Department of Chemistry, Faculty of Science and Arts, Najran University, Najran, Saudi Arabia, ELMEHBAD NOURA Y. , MOHAMED NADIA A. ,   Department of Chemistry, College of Science, Qassim University, Qassim, Saudi Arabia, ABD EL-GHANY NAHED A. ,   Department of Chemistry, Faculty of Science, Cairo University, Giza, 12613, Egypt, ABDEL-AZIZ MARWA M. ,   Regional Center for Mycology and Biotechnology, Al-Azhar University, Cairo, 11651, Egypt
Published: December 2022

A crosslinked sodium alginate (SA)/carboxymethyl xanthan gum (CMXG) hydrogel was prepared by blending an equivalent weight ratio of SA and CMXG, followed by crosslinking using CaCl2. Moreover, two nanocomposites were prepared by in situ dispersion of two different concentrations of silver nanoparticles (AgNPs) into the matrix of the prepared hydrogel. The analysis displayed that the order of COX-2 inhibition by the tested samples was SA ˂ CMXG ˂ crosslinked SA/CMXG hydrogel ˂ SA/CMXG/AgNPs1% ˂ SA/CMXG/AgNPs3% ˂ Celecoxib. AgNP composites exhibited a potent inhibition tendency, and their activity increased with increasing the AgNPs content. The recorded MIC values revealed that the MIC values that cause 50% inhibition (IC50) of COX-2 enzyme activity were 14.2 and 3.6 µg/mL for SA/CMXG/AgNPs1% and SA/CMXG/AgNPs3%, respectively, corresponding to 0.28 µg/mL for the standard drug Celecoxib. Moreover, SA/CMXG/AgNPs composites showed a greater inhibition efficiency of H. pylori than their parent SA/CMXG hydrogel. Their inhibitory efficiency increased with increasing their AgNPs content; SA/CMXG/AgNPs1% and SA/CMXG/AgNPs3% exhibited 100% inhibition against H. pylori growth at MIC of 3.9 and 1.95 µg/mL, respectively. The anti-H. pylori activity of SA/CMXG/AgNPs 3% was higher than that of the standard drug Clarithromycin, especially at the low concentrations ranging from 0.24 to 0.98 µg/mL. These results make SA/CMXG/AgNPs3% a promising anti-H. pylori agent.
Application Prospects of Hybrid Magnetic Circuits in High Frequency Power Transformers
Authors: Paul Arun
Published: December 2022

In medium to high frequency power transformers, apart from minimizing the power loss in the core and copper, the design of its thermal circuit plays an important role in containing the temperature rise in different parts. It is extremely complex because there exist multiple loss centers with different heat removal characteristics. Moreover, the power loss is concentrated around a small core volume and the rest of it is available for convection and radiation. This article proposes to use a hybrid core configuration to improve the heat removal feature of the transformer. This article establishes through practical validation on suitability i.e., the magnetic compatibility of cores in the hybrid magnetic circuit. It further explores the application prospect of the proposed concept where the thermal performances have been compared using different core types in two different application domains. In the first case, the core could always remain energized to its rated value, and in the second design, both the windings could always draw their respective rated current.
BGEM™: Assessing Elevated Blood Glucose Levels Using Machine Learning and Wearable Photo plethysmography Sensors
Authors: Shi Bohan
Published: December 2022

Diabetes mellitus (DB) is the most challenging and fastest-growing global public health challenge. An estimated 10.5% of the global adult population has been suffering from diabetes, and almost half of them are undiagnosed. The growing at-risk population further exacerbated the scarce health resources where the adults worldwide with impaired glucose tolerance (IGT) and impaired fasting glycaemia (IFG) were estimated at around 10.6% and 6.2%, respectively. All the current diabetes screening methods are invasive and opportunistic and must be conducted in a hospital or a laboratory by trained professionals. At-risk subjects might remain undetected for years and miss the precious time window for early intervention in preventing or delaying the onset of diabetes and its complications. This study was conducted at  KK Women's and Children's Hospital of Singapore, and five hundred participants were recruited (mean age 38.73 $\pm$ 10.61 years; mean BMI 24.4 $\pm$ 5.1 kg/m\textsuperscript{2}). The blood glucose levels, for most participants, were measured before and after 75g of sugary drink using both the conventional glucometer (Accu-Chek Performa) and the wrist-worn wearable. The results obtained from the glucometer were used as the ground truth measurements. We propose leveraging photoplethysmography (PPG) sensors and machine learning techniques to incorporate this into an affordable wrist-worn wearable device to detect elevated blood glucose levels ($\geqslant 7.8 mmol/L $) non-invasively. Multiple machine learning models were trained and assessed with 10-fold cross-validation using subject demographic data and critical features extracted from the PPG measurements as predictors. Support vector machine (SVM) with a  radial basis function kernel has the best detection performance with an average accuracy of 84.7%, a sensitivity of 81.05%, a specificity of 88.3%,  a precision of 87.51%, a geometric mean of 84.54% and F-score of 84.03%. Hence, PPG measurements can be utilized to identify subjects with elevated blood glucose measurements and assist in the screening of subjects for diabetes risk.
Fast-moving object counting with an event camera
Authors: Bialik Kamil , Kowalczyk Marcin , Blachut Krzysztof , Kryjak Tomasz
Published: December 2022

This paper proposes the use of an event camera as a component of a vision system that enables counting of fast-moving objects - in this case, falling corn grains. These type of cameras transmit information about the change in brightness of individual pixels and are characterised by low latency, no motion blur, correct operation in different lighting conditions, as well as very low power consumption. The proposed counting algorithm processes events in real time. The operation of the solution was demonstrated on a stand consisting of a chute with a vibrating feeder, which allowed the number of grains falling to be adjusted. The objective of the control system with a PID controller was to maintain a constant average number of falling objects. The proposed solution was subjected to a series of tests to determine the correctness of the developed method operation. On their basis, the validity of using an event camera to count small, fast-moving objects and the associated wide range of potential industrial applications can be confirmed.
Elicitation Approaches and Techniques for Automating Business Processes
Authors: Menezes Thiago
Published: December 2022

Several organizations have invested in business process automation software to improve their processes. Unstandardized processes with high variance and unstructured data encumber the requirements elicitation for business process automation software. This study conducted a literature review to discover methods for understanding business processes and eliciting requirements for business process automation software. The review revealed many methods used to understand business processes, but only one was employed to elicit requirements for business process automation software. In addition, the review identified some challenges with methods for eliciting requirements in this context.
Fully Digital Second-order Level-crossing Sampling ADC for Data Saving in Sensing Sparse Signals
Authors: Renteria-Pinon Mario , Tang Xiaochen , Ramirez-Angulo Jaime , TANG WEI
Published: December 2022

This paper presents a fully integrated second-order level-crossing sampling data converter for sensing sparse signals with real-time detection of turning points. Compared with con- ventional level-crossing sampling ADCs which sample at fixed voltage levels, the proposed circuits update tracking thresholds using linear prediction, which forms sloped sampling levels. The prediction and calculation are done digitally by modifying the digital control logic of a conventional SAR ADC. The system sepa- rates the sampling and quantization processes and only selects the turning points in the input waveform for quantization. The output of the proposed data converter consists of both the quantized amplitudes of the selected sampling points and the timestamps between the selected sampling points. The main advantages of the proposed circuits are data savings and power savings for the following digital signal processing or communication circuits. The test chip was fabricated using a 180nm CMOS process. When sensing sparse signals such as ECG signals, the proposed ADC saves 30% compared to a conventional SAR ADC with an equal quantizer resolution and achieves a compression factor of 6.17. 
Non-Interference Pattern Evolving to Interference Pattern --- Cross Double Slit Experiment with Precise Rule of Convex Lens
Authors: peng hui
Published: December 2022

The standard interpretation of Young’s double slit experiment is that the light behaves as waves before and after passing through the diaphragm of the double slit. Recently, the photon chamber has been proposed and utilized to study the behavior of photons near the detecting screen. The experiments show that the light behaves as photons propagating along the straight-line trajectories that distribute as waves. Furthermore, the photon chamber placed near the double slit shows the non-interference pattern.

blob:https://www.techrxiv.org/d6d50163-0598-4007-9243-ca11c2d05e95

In this article we show how the non-interference pattern evolves gradually to the interference pattern in the same cross double slit experiment: (1) the convex lens is placed at 50 mm from the diaphragm of the cross double slit, the non-interference pattern shows and has four primary maximum intensities (Figure (a)); (2) at 100 mm, the four primary maximum intensities disappeared (Figure (b)); (3) at 200 mm (Figure (c)); (4) at 600 mm, the interference pattern shown (Figure (d)), namely the non-interference pattern evolves to the interference pattern. The optics wave and electromagnetic wave theories cannot interpret this phenomenon and thus, is incomplete. This phenomenon provides information for further theoretical development. The cross double slit experiment is complex than the double slit experiments. We briefly discuss the complexity of the cross double slit experiment and show the comparison of both.