bluuebunny/crossref_metadata_2025 huggingface dataset:
Unity of the Existence of God and the Knowledge of God in the Phenomenological Ontology of Henry
Authors: Cui Weifeng
Published: October 2022

This study approaches the question of the unity between the existence of God and the knowledge of God. Henry’s phenomenology of life, as a phenomenological ontology, offers a phenomenological way to rethink the existence of God and our cognition of God by seeking the essence in life’s self-donation. As a phenomenological heritage of Husserl’s intentional phenomenology, Henry’s phenomenology of self-affection (auto-affection) clarifies the essence of God in the dimension of subjective body or in the flesh. This truth, which presents our absolute immanence, is, in its depth, a divine revelation between God and human. When we experience our own existence in the tonality of corporal life, we receive the existence of God and the knowledge of God.
‘Why Does This Happen to Me?’ Religious and Spiritual Struggles among Psychiatric Inpatients in The Netherlands: A Narrative Analysis
Authors: van Nieuw Amerongen-Meeuse Joke C. , Schaap-Jonker Hanneke , Westerbroek Gerlise , Braam Arjan W.
Published: October 2022

Background. Religious and spiritual (R/S) struggles may impact mental health treatment and recovery processes. The current study investigates how R/S struggles play a role in mental illness and what approaches are experienced as helpful. Methods. Thirty-five semi-structured interviews with clinical mental health patients in a Christian (N = 15) and a secular (N = 20) mental health clinic were narratively analyzed. Results. R/S struggles are common in people who suffer from mental illness and often coexist together with R/S support, mostly fluctuating over time. In summary, patients experience R/S struggles as negative feelings (e.g., loneliness, shame, mistrust) and the absence of positive feelings (e.g., hope and peace). These are influenced by someone’s R/S background and beliefs, as well as by the illness and other events. All participants appreciated a receptive approach (1) and many preferred an active approach (2) by mental health professionals. Some patients reported benefits from a directive approach (3). Conclusions. R/S struggles are tightly connected with other aspects that play a role in patients with mental illness. Mental health professionals are recommended to listen to patients’ narratives and carefully consider whether or not further interventions, in order to enhance R/S support and reduce R/S struggles, might be appropriate.
Grounding the Conscience
Authors: Menuge Angus John Louis
Published: October 2022

Most people rely on their conscience as a source of moral intuitions needed to test ethical proposals. Assume that the conscience can deliver knowledge of moral obligations under the right conditions. What ontological resources are needed to explain such a faculty? That depends on (1) the nature of moral obligations, and (2) what it takes to be receptive to them. I argue that close attention to (1) and (2) shows that materialism cannot account for the conscience, but that Christian theism plausibly provides the requisite resources. This is because moral obligations are naturally received as commands, they are prescriptive, personal, and express a kind of universal normative necessity that cannot be grounded in the local contingencies of a materialist world. Moral obligations are expressed as commands of practical reason, and they are knowable only if the world is governed by a divine personal Logos, and there are “Logos beings”, beings like God in their receptivity to these commands. Moral obligations are themselves immaterial entities and only a being with an immaterial dimension of the right sort can be receptive to them. This argument parallels a version of the argument from reason that sees theism as the best explanation of our logical reasoning abilities.
Tree Species Classification Based on Fusion Images by GF-5 and Sentinel-2A
Authors: Chen Weihua , Pan Jie , Sun Yulin
Published: October 2022

Forest ecosystem detection and assessment usually requires accurate spatial distribution information of forest tree species. Remote sensing technology has been confirmed as the most important method for tree species acquisition, and space-borne hyperspectral imagery, with the advantages of high spectral resolution, provides a better possibility for tree species classification. However, the present in-orbit hyperspectral imager has proved to be too low in spatial resolution to meet the accuracy needs of tree species classification. In this study, we firstly explored and evaluated the effectiveness of the Gram-Schmidt (GS) Harmonic analysis fusion (HAF) method for image fusion of GaoFen-5 (GF-5) and Sentinel-2A. Then, the Integrated Forest Z-Score (IFZ) was used to extract forest information from the fused image. Next, the spectral and textural features of the fused image, and topographic features extracted from DEM were selected according to random forest importance ranking (Mean Decreasing Gini (MDG) and Mean Decreasing Accuracy (MDA)), and imported into the random forest classifier to complete tree species classification. The results showed that: comparing some evaluation factors such as information entropy, average gradient and standard deviation of the fused images, the GS fusion image was proven to have a higher degree of spatial integration and spectral fidelity. The random forest importance ranking showed that WBI, Aspect, NDNI, ARI2, FRI were more important for tree species classification. Both the classification accuracy and kappa coefficients of the fused images were significantly greatly improved when compared to those of original GF-5 images. The overall classification accuracy ranged from 61.17% to 86.93% for different feature combination scenarios, and accuracy of the selected method based on MDA achieved higher results (OA = 86.93%, Kappa = 0.85). This study demonstrated the feasibility of fusion of GF-5 and Sentinel-2A images for tree species classification, which further provides good reference for application of in-orbit hyperspectral images.
Long-Term Baseflow Responses to Projected Climate Change in the Weihe River Basin, Loess Plateau, China
Authors: Zhang Junlong , Zhao Panpan , Zhang Yongqiang , Cheng Lei , Song Jinxi , Fu Guobin , Wang Yetang , Liu Qiang , Lyu Shixuan , Qi Shanzhong , Huang Chenlu , Ma Mingwei , Zhang Guotao
Published: October 2022

Climate change is a significant force influencing catchment hydrological processes, such as baseflow, i.e., the contribution of delayed pathways to streamflow in drought periods and is associated with catchment drought propagation. The Weihe River Basin is a typical arid and semi-arid catchment on the Loess Plateau in northwest China. Baseflow plays a fundamental role in the provision of water and environmental functions at the catchment scale. However, the baseflow variability in the projected climate change is not well understood. In this study, forcing meteorological data were derived from two climate scenarios (RCP4.5 and RCP8.5) of three representative general circulation models (CSIRO-Mk3-6-0, MIROC5, and FGOALSg2) in CMIP5 and then were used as inputs in the Soil and Water Assessment Tool (SWAT) hydrological model to simulate future streamflow. Finally, a well-revised baseflow separation method was implemented to estimate the baseflow to investigate long-term (historical (1960–2012) and future (2010–2054) periods) baseflow variability patterns. We found (1) that baseflow showed a decreasing trend in some simulations of future climatic conditions but not in all scenarios (p < 0.05), (2) that the contribution of baseflow to streamflow (i.e., baseflow index) amounted to approximately 45%, with a slightly increasing trend (p ≤ 0.001), and (3) an increased frequency of severe hydrological drought events in the future (2041–2053) due to baseflows much lower than current annual averages. This study benefits the scientific management of water resources in regional development and provides references for the semi-arid or water-limited catchments.
Retrieval of Farmland Surface Soil Moisture Based on Feature Optimization and Machine Learning
Authors: Zhao Jianhui , Zhang Chenyang , Min Lin , Guo Zhengwei , Li Ning
Published: October 2022

Soil moisture is an important parameter affecting environmental processes such as hydrology, ecology, and climate. Synthetic aperture radar (SAR) microwave remote sensing is an important means of farmland surface soil moisture (SSM) measurement. The inversion of farmland SSM by microwave remote sensing is greatly affected by vegetation cover. To address this problem, a multisource remote sensing inversion method of farmland SSM based on feature optimization and machine learning is proposed in this paper. Six typical machine learning algorithms suitable for small sample training, including random forest, radial basis function neural network, generalized regression neural network, support vector regression, genetic algorithm–back propagation neural network, and extreme learning machine, were selected in this paper. The features extracted from Sentinel-1/2 and Radarsat-2 remote sensing data were analyzed by Pearson correlation, and those with high correlation coefficients were selected to form the optimal feature subset as the input for the subsequent machine learning models. Then, the SSM collaborative inversion models under different machine learning algorithms were constructed, and comparative experiments were set up to select the optimal prediction model. The models’ accuracy under different feature parameters were studied, and the difference in the performance between the dual-polarization SAR data and the quad-polarization SAR data in SSM inversion was explored. The experimental results showed that among the six models, the random forest model had a higher inversion accuracy, with a coefficient of determination of 0.6395 and a root mean square error of 0.0264 cm3/cm3. Meanwhile, the inversion accuracy could be greatly improved after feature optimization, and the inversion accuracy of the quad-polarization SAR data combined with optical remote sensing data, was better than that of the dual-polarization SAR data combined with optical remote sensing data.
Rupture Process of the 2022 Mw6.6 Menyuan, China, Earthquake from Joint Inversion of Accelerogram Data and InSAR Measurements
Authors: Huang Chuanchao , Zhang Guohong , Zhao Dezheng , Shan Xinjian , Xie Chaodi , Tu Hongwei , Qu Chunyan , Zhu Chuanhua , Han Nana , Chen Junxian
Published: October 2022

We obtained the rupture process and slip distribution of the 2022 Mw6.6 Menyuan earthquake by jointly inverting accelerogram data and InSAR measurements. The near-field InSAR measurements provide good constraints on the shallow slip distributions (<6 km). The accelerogram data enable us to better resolve the deeper coseismic slip (>6 km). The combination of two types of data provided improved constrains on slip distribution of the 2022 Menyuan earthquake. The results from joint inversion of InSAR and accelerogram data reveal a 26-km-long rupture length, which roughly agrees with the mapped length from the optically identified surface rupture trace and the InSAR deformation field. We imaged a major asperity with a dimension of 14 × 6 km at 4 km depth updip of the hypocenter. The maximum slip is estimated to be 3.8 m at 4 km depth. The duration of the 2022 Menyuan earthquake is ~14 s, and 90% of the seismic moment is released in the first 10 s. The total seismic moment is estimated to be 1.31 × 1 × 1019 N·m, equivalent to a moment magnitude of Mw6.7. Our results highlight that the moderate but shallow rupture during the 2022 Menyuan earthquake could intensify the seismic damage on the surface, confirmed by field investigations.
Continual Contrastive Learning for Cross-Dataset Scene Classification
Authors: Peng Rui , Zhao Wenzhi , Li Kaiyuan , Ji Fengcheng , Rong Caixia
Published: October 2022

With the development of remote sensing technology, the continuing accumulation of remote sensing data has brought great challenges to the remote sensing field. Although multiple deep-learning-based classification methods have made great progress in scene classification tasks, they are still unable to address the problem of model learning continuously. Facing the constantly updated remote sensing data stream, there is an inevitable problem of forgetting historical information in the model training, which leads to catastrophic forgetting. Therefore, we propose a continual contrastive learning method based on knowledge distillation and contrastive learning in this paper, which is named the Continual Contrastive Learning Network (CCLNet). To overcome the problem of knowledge forgetting, we first designed a knowledge distillation module based on a spatial feature which contains sufficient historical knowledge. The spatial and category-level knowledge distillation enables the model to effectively preserve the already learned knowledge in the current scene classification model. Then, we introduced contrastive learning by leveraging the comparison of augmented samples and minimizing the distance in the feature space to further enhance the extracted feature during the continual learning process. To evaluate the performance of our designed model on streaming remote sensing scene data, we performed three steps of continuous learning experiments on three datasets, the AID, RSI, and NWPU datasets, and simulated the streaming of remote sensing scene data with the aggregate of the three datasets. We also compared other benchmark continual learning models. The experimental results demonstrate that our method achieved superior performance in the continuous scene classification task.
Energy-Efficient Uplink Scheduling in Narrowband IoT
Authors: Yassine Farah , El Helou Melhem , Lahoud Samer , Bazzi Oussama
Published: October 2022

This paper presents a detailed study of uplink scheduling in narrowband internet of things (NB-IoT) networks. As NB-IoT devices need a long battery lifetime, we aim to maximize energy efficiency while satisfying the main requirements for NB-IoT devices. Also, as the NB-IoT scheduling problem is divided into link adaptation problem and resource allocation problem, this paper investigates the correlation between these two problems. Accordingly, we propose two scheduling schemes: the joint scheduling scheme, where the two problems are combined as one optimization problem, and the successive scheduling scheme that manages each problem separately but successively. Each scheme aims to maximize energy efficiency while achieving reliable transmission, satisfying delay requirements, and guaranteeing resource allocation specifications. Also, we investigate the impact of the selected devices to be served on the total energy efficiency. Accordingly, we propose two device selection techniques to maximize the total energy efficiency. The first technique exhaustively searches for the optimal devices, while the second sorts the devices based on a proposed priority score. The simulation results compare the successive and the joint scheduling schemes. The results show that the joint scheme outperforms the successive scheme in terms of energy efficiency and the number of served devices but with higher complexity. Also, the results highlight the impact of each proposed selection technique on the scheduling schemes’ performance.
Forest Fire Detection Using New Routing Protocol
Authors: AL-Dhief Fahad Taha , Muniyandi Ravie Chandren , Sabri Naseer , Hamdan Mosab , Latiff Nurul Mu’azzah Abdul , Albadr Musatafa Abbas Abbood , Khairi Mutaz Hamed Hussien , Hamzah Muzaffar , Khan Suleman
Published: October 2022

The Mobile Ad-Hoc Network (MANET) has received significant interest from researchers for several applications. In spite of developing and proposing numerous routing protocols for MANET, there are still routing protocols that are too inefficient in terms of sending data and energy consumption, which limits the lifetime of the network for forest fire monitoring. Therefore, this paper presents the development of a Location Aided Routing (LAR) protocol in forest fire detection. The new routing protocol is named the LAR-Based Reliable Routing Protocol (LARRR), which is used to detect a forest fire based on three criteria: the route length between nodes, the temperature sensing, and the number of packets within node buffers (i.e., route busyness). The performance of the LARRR protocol is evaluated by using widely known evaluation measurements, which are the Packet Delivery Ratio (PDR), Energy Consumption (EC), End-to-End Delay (E2E Delay), and Routing Overhead (RO). The simulation results show that the proposed LARRR protocol achieves 70% PDR, 403 joules of EC, 2.733 s of E2E delay, and 43.04 RO. In addition, the performance of the proposed LARRR protocol outperforms its competitors and is able to detect forest fires efficiently.
Computational Vibro-Acoustic Time Reversal for Source and Novelty Localization
Authors: Panagiotopoulos Christos G. , Kouzoupis Spyros , Tsogka Chrysoula
Published: October 2022

Time reversal has been demonstrated to be effective for source and novelty detection and localization. We extend here previous work in the case of a coupled structural-acoustic system, to which we refer to as vibro-acoustic. In this case, novelty means a change that the structural system has undergone and which we seek to detect and localize. A single source in the acoustic medium is used to generate the propagating field, and several receivers, both in the acoustic and the structural part, may be used to record the response of the medium to this excitation. This is the forward step. Exploiting time reversibility, the recorded signals are focused back to the original source location during the backward step. For the case of novelty detection, the difference between the field recorded before and after the structural modification is backpropagated. We demonstrate that the performance of the method is improved when the structural components are taken into account during the backward step. The potential of the method for solving inverse problems as they appear in non destructive testing and structural health monitoring applications is illustrated with several numerical examples obtained using a finite element method.
The Impact of FDI on China’s Urban–Rural Income Gap
Authors: Shi Lifan , Zhu Changchun , Tang Decai , Boamah Valentina
Published: October 2022

Since the reform and opening up some forty years ago, China has suffered from a capital shortage problem. To both solve this problem and satisfy its economic and social needs, China has been bringing in foreign investment, much of which has gone toward economic reconstruction. However, with the continuous inflow of foreign direct investment (FDI) into China, not only has the gap between rich and poor become increasingly wide but, due to China’s unique dualistic economic structure, the gap between urban and rural areas also appears to be widening. This aspect of the problem has attracted the attention of scholars around the world, as it may affect the future sustainable development of China’s economy and society. Cognizant of the need for practical solutions, this study conducts a more in-depth study of the relationship between foreign direct investment and the urban–rural income gap in China. Based on a review of previous studies and panel data from 30 Chinese provinces, this paper argues that FDI will affect this income gap through mechanisms such as employment structure, industrial structure and international trade. The findings of this study suggest that FDI inflows will first improve income inequality between urban and rural Chinese at a point in time but then have a worsening effect. In addition, China’s three major economic zones are examined, with results showing that the overall impact of FDI on the urban–rural income gap in China displays an inverted ‘U’ curve. Today, the impact of FDI on the urban–rural income gap is on the right-hand side of the curve, with regional differences in its impact. Urban–rural income inequality in the eastern region responds the most to FDI.
Remediation of Heavy Metal-Contaminated Soils with Soil Washing: A Review
Authors: Zheng Xiao-Jun , Li Qi , Peng Hao , Zhang Jian-Xiong , Chen Wei-Jiang , Zhou Bu-Chan , Chen Ming
Published: October 2022

Soil with heavy metals’ contamination has caused worldwide concern, and there is an increasing interest in the application of washing agents for the remediation of soils with heavy metals’ contamination. The review summarizes the recent findings about soil washing with different washing agents. For soil washing technologies, the solubilizing capability, toxicity, and biocompatibility of agents are essential concerns. Washing agents can enhance heavy metals’ desorption and removal from soil. Inorganic acids/bases/salts, synthetic surfactants, and synthetic chelators are often limited due to their adverse effects on soil. Biosurfactants, HAs (humic acids), and LMWOA (low-molecular-weight organic acids) are suggested washing agents, but the limitation of their low production needs to be conquered. Moreover, both washing with a mixture agent and sequential washing have often been adopted to improve the overall capacity of the washing agent for decontamination. Mixture washing can obtain the synergetic effect for soil washing and increase washing efficiency. Sequential washing can apply an agent with a high heavy metals removal rate. However, this may cause environmental risks in the early stage, and then remove the washing agent injected in the early stage by the secondary washing stage. Overall, the already known cases reveal the good prospect of soil washing for soil remediation.
Performance of Equity Fund Investment Strategies in Poland
Authors: Kravchuk Igor
Published: October 2022

The modern development of the investment funds industry is underpinned by the understanding of the efficiency and quality of asset management regarding the use of various investment strategies. The purpose of the article is to examine investment strategy performance in equity funds domiciled in Poland using standard relative and absolute measures. The proposed method uses the Sharpe ratios, the Treynor ratio and the Jensen ratios. The research covers investment funds, spanning the period 2017–2021. The study (using the Sharpe and Traynor ratios) finds that the financial instruments for investment funds domiciled in Poland may be attractive to conservative investors, as they provide excessive returns compared to the returns of risk-free assets and inflation, but for riskier investors, most of the investment funds analyzed were unattractive (negative value of the returns of funds compared to stock indices). Absolute measures of fund performance, using the Jensen ratio, are limited for comparing all groups of investment strategies. A specific negative feature in the study of investment strategies based on the Jensen ratio is their inefficiency, that is, all statistically significant values of this ratio are negative. The management of ESG-funds with investments in the European financial market was more efficient than most conventional investment funds.
An Integrated Sensitivity and Uncertainty Quantification of Fragility Functions in RC Frames
Authors: Nasrollahzadeh Kourosh , Hariri-Ardebili Mohammad Amin , Kiani Houman , Mahdavi Golsa
Published: October 2022

Uncertainty quantification is a challenging task in the risk-based assessment of buildings. This paper aims to compare reliability-based approaches to simulating epistemic and aleatory randomness in reinforced concrete (RC) frames. Ground motion record-to-record variability is combined with modeling uncertainty which is propagated by either an approximate first-order second-moment or Latin Hypercube sampling methods. The sources of uncertainties include post-yield hardening stiffness, cyclic energy dissipation capacity, and the plastic and post-cap rotation capacities of beam-column elements. All nonlinear simulations are performed with two methods: detailed incremental dynamic analysis, and the simplified SPO2IDA. The combination of all parametric methods is used to analyze two RC frames (four-story and eight-story), and the results are further post-processed to drive fragility functions. Several assumptions were investigated in curve fitting, functional form, uncertainty, and confidence intervals. The results indicate the importance of modeling uncertainty in higher seismic intensity levels. While there is a negligible difference in fragility curve fitting, its variability due to optimal intensity measure parameters is dominant.
Experimental Investigation on Vibration Control of a Suspended Particle-Tuned Liquid Damper
Authors: Lu Zheng , Zhou Mengyao , Ren Hongmei
Published: October 2022

The particle-tuned liquid damper (PTLD) can combine the functions of baffles and energy-dissipating materials, such as highly viscous liquids, by integrating the particle dampers into a conventional tuned liquid damper (TLD). However, the particles distributed only at the bottom of the container cannot drive the motion of water in the middle layer to function effectively. Therefore, a suspended particle-tuned liquid damper (SPTLD) is proposed in this study and its effectiveness and reliability are examined compared with the conventional TLD through shaking table tests. Based on the experimental results, a parametric analysis of the SPTLD is further conducted to investigate the damping mechanism of the SPTLD, including the number of particles, the excitations with various amplitudes, and the use of suspended versus floating particles in liquid. The test results revealed that SPTLD successfully controlled the structural acceleration responses under seismic excitations with good reliability; the peak acceleration response was reduced by 67.4% and the RMS value was reduced by 75.9%. In the SPTLD, the particles filled in the container can drive more liquid to effectively participate in the sloshing motion, and the superimposed damping effects involving collisions and the energy-dissipation mechanisms of buoyancy and hydraulic resistance in the SPTLD lead to an improvement in the vibration control performance. Furthermore, the comparison of SPTLD and the floating particle-tuned liquid damper (FPTLD) demonstrates the better availability of SPTLD in practical applications, especially for some slender structures with limited plane space on the top floor.
Information Sharing in Competing Supply Chains with Carbon Emissions Reduction Incentives
Authors: Zhang Weidong , Wang Fuqiang
Published: October 2022

This paper investigates the incentives of firms to share demand information in two competing supply chains. We consider a model in which each supply chain consists of a manufacturer and a retailer, and the manufacturers decide their products’ carbon emissions reduction levels. Through information sharing, manufacturers can adjust their wholesale price and the level of carbon emissions reduction according to the demand signal. The results reveal that information sharing always benefits the manufacturer. Information-sharing arrangements are more likely to occur when the manufacturer’s carbon emissions reduction efficiency or the customer’s low-carbon product preference is relatively high. Moreover, under Cournot competition, the retailer’s incentive to share information increases when information is less accurate or the competition is less intense. By sharing demand information, manufacturers will invest more in reducing the carbon emissions of their products. Therefore, there are two effects of information sharing: the “economic effect” on the benefits of all parties and the “environmental effect” on reducing carbon emissions. Our findings highlight the economic and environmental incentives of information sharing in the supply chain and the synthesis impacts of low-carbon preferences, efficiency of carbon emissions reduction, and the competition intensity on the retailer’s incentives to share information.
Two-Step Multi-Objective Reliability-Based Design Optimization of Aircraft Wing Structures
Authors: Sleesongsom Suwin , Kumar Sumit , Bureerat Sujin
Published: October 2022

The multi-objective reliability-based design optimization (MORBDO) of an aircraft structure employing a non-probabilistic model, at present, still has a high level of analysis complexity while solving the possibility safety index (PSI) as they are a triple-loop nested problem. Many techniques have been proposed to expedite the process of solving their inner loop with a single objective function; however, research on applying multi-objective optimization to complete this task is required. This research paper aims to reduce the solution complexity in the MORBDO of an aircraft wing structure, which is a symmetrical part of the aircraft structure. The present framework is comprised of a two-step technique that begins with the multi-objective optimization (MODO) of the wing structure, followed by its reliability analysis. A non-probabilistic model is adopted for uncertainty consideration, contrary to frequently used probabilistic models. The reliability design problem has aircraft wing mass, flutter speed, and the possibility safety index as objective functions. According to the results, the proposed MORBDO technique is highly effective in reducing the complexity of aircraft wing structural design and can generate more conservative and feasible design solutions with various PSI values. Such a design can be achieved within a single run, which has not been done in previous studies. The results show that the highest reliability aircraft wing structure mass is 104.8504 kg at a flutter speed of 584.5670 m/s. Additionally, the developed framework explicitly states the relationship between MODO and MORBDO.
The Impacts of Digital Technology on Service Design and Experience Innovation: Case Study of Taiwan’s Cultural Heritage under the COVID-19 Pandemic
Authors: Ng Wai-Kit , Hsu Fu-Tien , Chen Chun-Liang
Published: October 2022

The aim of this research is to identify the digital technology impact and experience innovation of cultural heritages in the context of the epidemic. The authors created an analytical framework and used a qualitative exploratory multi-case study of three cultural heritages in Taiwan. The findings indicate that digital technology has facilitated further innovations in cultural heritages under the epidemic to be closer to consumers’ daily life and more connected with the young generation. Compared to traditional cultural heritages, profit-making cultural heritages need sales of its products to sustain operations, while live streaming, which is interactive, is rising as a new way to promote sales. Using multiple digital platforms can maintain consumers’ interest in the cultural heritages, encouraging follow-up visits and thus resulting in more traffic online and offline. This paper illustrates the advantages of digital technology in the context of the epidemic, highlighting the innovative technology of live streaming and social platforms introduced that are different from the traditional cultural heritages.
Assessment of Shoreline Changes for the Selangor Coast, Malaysia, Using the Digital Shoreline Analysis System Technique
Authors: Abdul Maulud Khairul Nizam , Selamat Siti Norsakinah , Mohd Fazly Amri , Md Noor Noorashikin , Wan Mohd Jaafar Wan Shafrina , Kamarudin Mohd Khairul Amri , Ariffin Effi Helmy , Adnan Nor Aizam , Ahmad Anizawati
Published: October 2022

Coastal areas are fragile and changeable due to natural and anthropogenic factors. The resulting changes could have a significant impact on the coastal community. Thus, monitoring shoreline changes for environmental protection in the Selangor coastal area is an important task to address these issues. The main objective of this study is to analyse the pattern of shoreline changes and predict the shoreline position along the Selangor coast. The geospatial approach can provide information on the history and pattern of shoreline changes. This study used temporal datasets and satellite imagery (SPOT 5) to monitor the shoreline changes throughout the 11 identified study areas. It comprises three methods: shoreline change envelope (SCE), net shoreline movement (NSM), and end-point rate (EPR). The findings indicated that the Selangor coast was more exposed to the erosion phenomenon than to the accretion phenomenon, with 77.3% and 22.7%, respectively. This study reveals significant erosion phenomena in 2 out of 11 areas: Bagan Pasir and Pantai Kelanang. Meanwhile, significant accretion occurred at Bagan Sungai Burong and Sungai Nibong. Consequently, providing complete information would be helpful for researchers, decision-makers, and those in charge of planning and managing the coastal zone.
Gene Expression Analysis of Adapted Insect Cells during Influenza VLP Production Using RNA-Sequencing
Authors: Silvano Marco , Correia Ricardo , Virgolini Nikolaus , Clarke Colin , Alves Paula M. , Isidro Inês A. , Roldão António
Published: October 2022

Adaptive laboratory evolution has been used to improve production of influenza hemagglutinin (HA)-displaying virus-like particles (VLPs) in insect cells. However, little is known about the underlying biological mechanisms promoting higher HA-VLP expression in such adapted cell lines. In this article, we present a study of gene expression patterns associated with high-producer insect High Five cells adapted to neutral pH, in comparison to non-adapted cells, during expression of influenza HA-VLPs. RNA-seq shows a decrease in the amount of reads mapping to host cell genomes along infection, and an increase in those mapping to baculovirus and transgenes. A total of 1742 host cell genes were found differentially expressed between adapted and non-adapted cells throughout infection, 474 of those being either up- or down-regulated at both time points evaluated (12 and 24 h post-infection). Interestingly, while host cell genes were found up- and down-regulated in an approximately 1:1 ratio, all differentially expressed baculovirus genes were found to be down-regulated in infected adapted cells. Pathway analysis of differentially expressed genes revealed enrichment of ribosome biosynthesis and carbohydrate, amino acid, and lipid metabolism. In addition, oxidative phosphorylation and protein folding, sorting and degradation pathways were also found to be overrepresented. These findings contribute to our knowledge of biological mechanisms of insect cells during baculovirus-mediated transient expression and will assist the identification of potential engineering targets to increase recombinant protein production in the future.
Comparison and Harmonization of Different Semi-Automated and Automated qRT-PCR Assays in the Assessment of SARS-CoV-2
Authors: Dierks Sascha , Thiele Karin , Bohne Wolfgang , Lugert Raimond , Weig Michael , Groß Uwe , von Ahsen Nicolas , Schanz Julie , Fischer Andreas , Schnelle Moritz
Published: October 2022

In SARS-CoV-2 diagnostics, cycle threshold (Ct) values from qRT-PCRs semi-quantitatively estimate a patient’s viral load. However, relevant analytical differences between qRT-PCR assays are often neglected. This study was designed (i) to identify such differences between five commonly used assays and (ii) to demonstrate a straightforward strategy to harmonize them. QRT-PCRs for SARS-CoV-2 were carried out in 85 oropharyngeal swab samples using three fully automated (Alinity m, cobas®6800 and GeneXpert) and two semi-automated (genesig® and RIDA®GENE) assays. Qualitative results (positive/negative) showed excellent comparability between the fully automated assays, but not between the Alinity m and semi-automated methods. Ct values significantly varied between all the methods, with the median values ranging from 22.76 (Alinity m) to 30.89 (RIDA®GENE) and 31.50 (genesig®), indicating the lowest sensitivity for semi-automated methods. Passing–Bablok analysis further revealed systemic biases. Assay-specific viral load concentration calculations—based on generated individual standard curves—resulted in much better comparability between the assays. Applying these calculations, significant differences were no longer detectable. This study highlights relevant analytical differences between SARS-CoV-2 qRT-PCR assays, leading to divergent decisions about the mandatory isolation of infected individuals. Secondly, we propose a strategy to harmonize qRT-PCR assays to achieve better comparability. Our findings are of particular interest for laboratories utilizing different assays.
Estimation of R0 for the Spread of the First ASF Epidemic in Italy from Fresh Carcasses
Authors: Loi Federica , Di Sabatino Daria , Baldi Ileana , Rolesu Sandro , Gervasi Vincenzo , Guberti Vittorio , Cappai Stefano
Published: October 2022

After fifty years of spread in the European continent, the African swine fever (ASF) virus was detected for the first time in the north of Italy (Piedmont) in a wild boar carcass in December, 2021. During the first six months of the epidemic, the central role of wild boars in disease transmission was confirmed by more than 200 outbreaks, which occurred in two different areas declared as infected. The virus entered a domestic pig farm in the second temporal cluster identified in the center of the country (Lazio). Understanding ASF dynamics in wild boars is a prerequisite for preventing the spread, and for designing and applying effective surveillance and control plans. The aim of this work was to describe and evaluate the data collected during the first six months of the ASF epidemic in Italy, and to estimate the basic reproduction number (R0) in order to quantify the extent of disease spread. The R0 estimates were significantly different for the two spatio-temporal clusters of ASF in Italy, and they identified the two infected areas based on the time necessary for the number of cases to double (td) and on an exponential decay model. These results (R0 = 1.41 in Piedmont and 1.66 in Lazio) provide quantitative knowledge on the epidemiology of ASF in Italy. These parameters could represent a fundamental tool for modeling country-specific ASF transmission and for monitoring both the spread and sampling effort needed to detect the disease early.
Designed Ankyrin Repeat Proteins: A New Class of Viral Entry Inhibitors
Authors: Walser Marcel , Mayor Jennifer , Rothenberger Sylvia
Published: October 2022

Designed ankyrin repeat proteins (DARPins) are engineered proteins comprising consensus designed ankyrin repeats as scaffold. Tightly packed repeats form a continuous hydrophobic core and a large groove-like solvent-accessible surface that creates a binding surface. DARPin domains recognizing a target of interest with high specificity and affinity can be generated using a synthetic combinatorial library and in vitro selection methods. They can be linked together in a single molecule to build multispecific and multifunctional proteins without affecting expression or function. The modular architecture of DARPins offers unprecedented possibilities of design and opens avenues for innovative antiviral strategies.
Maintenance of Antibody Response in Egyptian Healthcare Workers Vaccinated with ChAdOx1 nCoV-19 Vaccine during Delta and Omicron Variants Pandemic: A Prospective Study
Authors: Hammad Noha M. , Kadry Heba M. , Malek Mai M. , Bahgat Shereen Mohamed , Abdelsalam Noha M. , Afifi Amira Hamed Mohamed , Abo-alella Doaa Alhussein
Published: October 2022

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a constantly evolving virus, resulting in an increased burden on the existing COVID-19 vaccines. Healthcare workers (HCWs) are the first line of defense against the coronavirus disease 2019 (COVID-19) pandemic and have been prioritized among the risk categories receiving the COVID-19 vaccine. This work aimed to investigate the maintenance of antibody response of the Oxford–AstraZeneca vaccine (ChAdOx1/nCoV-19). Methods: Anti-spike immunoglobulin G (IgG) was measured at baseline point (immediately prior to vaccination) and 12- and 24-week (w) points following vaccination. Adverse reactions to the vaccine were reported. Participants were followed up for the incidence of COVID-19 during the 12 w interval between vaccination doses for 24 w after the second dose. Results: A total of 255 HCWs participated in the study. Prior to vaccination, 54.1% experienced COVID-19, 88.2% were seropositive after the first dose, while seropositivity reached 95.7% after the second dose. Following the first and second doses, the anti-spike IgG serum level was significantly higher in subjects with past COVID-19 than in others (p < 0.001 and =0.001, respectively). Conclusions: The Oxford–AstraZeneca vaccine is generally safe and provides a highly effective long-term humoral immune response against the Delta and Omicron variants of SARS-CoV-2.
Patterns of prescribing in primary care leading to high-dose opioid regimens: a mixed-method study
Authors: Bailey John , Nafees Sadia Bashir , Gill Simon , Jones Lucy , Poole Rob
Published: October 2022

Background

There are concerns about continuing increases in the number of patients prescribed long-term opioids and the prescribing of 'strong' opioids for chronic pain. Little is known about patients who are prescribed these long-term, high-dose drugs.

Aim

To understand patterns of opioid prescribing that lead to long-term, high-dose use.

Design & setting

A mixed-method study of the opioid prescription histories of patients using high doses in a North Wales GP practice.

Method

All patients on high-dose opioids during the census week were identified. Summary graphs of the prescription histories were prepared. Qualitative analysis was conducted individually by four researchers. A workshop was held to arrive at a consensus about common features and to inform further quantitative analysis.

Results

A quarter of high-dose regimens were initiated outside the practice, either in a different primary care practice or in secondary care. The majority of the remaining patients showed a pattern of dose increases to high levels over a short period (median 3.5 months). None showed a pattern of gradual increases over a longer timescale. Most of the patients remained on high doses continuously once a daily dose of ≥120 mg oral morphine equivalent (OME) was reached.

Conclusion

These findings suggest that high-dose opioid regimens develop quickly in response to unknown clinical factors. An expected insidious upward drift in dose was not seen. The findings have implications for the prevention of potentially dangerous long-term, high-dose opioid prescribing. A dose of 60 mg OME or more is suggested as a useful 'red flag'.
A persistência da linha: lógicas processuais e linearidade nas tecnologias da comunicação
Authors: Estefani Thales
Published: October 2022

A consciência histórica do ser humano é inaugurada, de acordo com Vilém Flusser, a partir do desenvolvimento da linguagem verbal. Este é o cerne da ideia de “pensamento-em-linha” elaborada pelo filósofo. Tendo este conceito como inspiração temática e ponto de partida, busca-se demonstrar a persistência de lógicas processuais lineares e das metáforas da linha nas estruturas e formas expressivas das tecnologias da comunicação humana no decorrer da história. Entendidas como processos, as tecnologias da comunicação não são encaradas, entretanto, como contínuos indiscrimináveis desde suas remotas origens na linguagem e na contagem; são pontuadas e descritas sinteticamente, enfatizando suas incessantes inovações. É realizada uma breve digressão ao período da Revolução Industrial, orientada para compreender o consequente desenvolvimento das tecnologias computacionais, relatando suas origens na aplicação de teorias matemáticas à indústria têxtil. Em seguida, são abordados os efeitos dessas tecnologias sobre a criação das mais recentes expressões comunicacionais contemporâneas, como os jogos digitais e a realidade virtual. Neste ensaio, a linha é vista como um símbolo do desenvolvimento comunicacional, mesmo nos emaranhados e nós que constituem a multilinearidade das possibilidades da comunicação humana.
Ficção televisiva brasileira e covid-19: reconfigurações e estratégias de programação
Authors: Lemos Ligia Prezia , Rocha Larissa Leda F.
Published: October 2022

Este trabalho, inicialmente apresentado em junho de 2020 no Congresso Virtual da Associação Brasileira de Pesquisadores em Cibercultura - ABCiber, foi revisto, atualizado e ampliado desde então, com a intenção de acompanhar a retificação dos dados produzidos, de modo acelerado, pelo campo. Temos como objetivo observar as alterações na produção, circulação e audiência da ficção televisiva brasileira, durante um ano — de março de 2020 a março de 2021 —, considerando a emergência da pandemia de Covid-19 e o processo de distanciamento social no Brasil, ainda que o mesmo tenha se apresentado em diferentes momentos e intensidades nas diversas regiões do país. Para isso foi realizado um levantamento de dados tanto em instituições de pesquisa como em artigos jornalísticos visando observar as mudanças comportamentais da sociedade em decorrência da pandemia e também os ajustes necessários feitos pela indústria cultural nacional diante das alterações exigidas pela necessidade de segurança sanitária. Depois, os dados levantados foram associados a uma revisão de literatura, tendo como base o pensamento complexo de Morin (2010). A coleta de dados, bem como a análise dos mesmos foram concentrados nas produções da Globo e em suas estratégias de programação no período.
BROAD-RS: agent based architecture for educational context-aware recommendation
Authors: Rezende Paulo , Campos Fernanda
Published: October 2022

Educational resources have great potential to increase the design and composition of online classes. Educational recommendation system aims to identify student’s profile and context to suggest suitable resources to his/her preferences and enrich, flexibilize and dynamize class contents. This work presents XXXXXXX (XXXXX Recommendation System) architecture. It is capable of performing context-aware recommendation of Learning Objects, based on ontologies for modeling student profile and context in an e-learning environment. It was implemented in a multiagent system. The evaluation was performed in a real Software Engineering class, for students of higher education in Computing area. The main steps were: the teacher made the class plan and registered the Learning Objects, the student used the application in different contexts and the recommendation Learning Objects was executed at two different moments. Considering the case study the results pointed to the feasibility of the architecture.
Licenciatura em Computação da UFJF: 10 anos de história e desafios
Authors: Campos Fernanda , Scortegagna Liamara
Published: October 2022

O artigo apresenta a trajetória dos dez anos de história do Curso de Licenciatura em Computação da Universidade Federal de Juiz de Fora, ofertado na modalidade de Educação a Distância e destaca dois desafios: a gestão da Educação a Distância e a evasão do Curso. O objetivo é compartilhar as experiências e situações vivenciadas ao longo desse período de tempo e refletir sobre estratégias que visem à redução desses desafios. Apresentamos ainda, a contextualização da Educação a Distância na Universidade Federal de Juiz de Fora e as principais características do projeto pedagógico do Curso como objetivos, perfil dos egressos, grade curricular, estágios, oferta nos polos de apoio presenciais e os atores do processo educacional da licenciatura.