bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Interlayer on the Development of Steam Chamber in Steam Stimulation during Heavy Oil Recovery
Authors: Fan Hongjun , Fan Tingen , Deng Junhui , Zhang Lijun , Zheng Wei , Chen Lifeng , Ge Zunzeng , Xie Haojun , Liang Xu
Published: June 2023

Cyclic steam stimulation is an effective thermal recovery method for heavy oil recovery. The key potential mechanism is the growth of the steam chamber after steam injection. Taking the LD5X heavy oil reservoir as an example, besides the interlayer developed in this area, the top water and bottom water distribute above and below the interlayer. These factors may have adverse effects on the development of the steam chamber, thus affecting the final heavy oil exploitation. In this work, our goal is to study the effects of interlayer permeability and well–interlayer distance on CSS performance (in the presence of top and bottom water). We developed a high-temperature-resistant interlayer. Based on the simulated interlayer, the field scale model was converted into a laboratory element model through the similarity criterion. In order to quantitatively evaluate the performance of steam stimulation, a thermal detector was used to measure the dynamic growth of the steam chamber and record the production data. The experimental results show that the self-made interlayer has high-temperature resistance, adjustable permeability, and little difference between the physical parameters and the target interlayer. During the cyclic steam stimulation process, the steam chamber presents two different stages in the presence of the top water area, namely the normal production stage and the top water discharge stage. The bottom water has little effect on the growth of the steam chamber. The small interlayer permeability, the increase in horizontal well–interlayer distance, and the existence of the interlayer will delay the top water leakage during steam stimulation. This study has reference significance for us to develop heavy oil resources with a top water barrier when implementing steam stimulation technology.
Coupled Thermal-Hydraulic-Mechanical Modeling of Near-Well Stress Evolution in Naturally Fractured Formations during Drilling
Authors: Song Yong , Wang Zhenlin , Wang Wei , Yu Peirong , Chen Gang , Lin Jiaying , Zhu Bolong , Guo Xuyang
Published: June 2023

Naturally fractured formations usually have strong heterogeneities. Drilling and production operations in such formations can involve unwanted formation failure risks such as wellbore collapse and wellbore fracturing. This study presents a coupled thermal-hydraulic-mechanical numerical model for near-well stress evolutions during drilling in naturally fractured formations. The evolution of pressure, temperature, and geo-mechanical responses on the wellbore wall and in the near-well region is simulated. The effects of wellbore pressure, internal friction angle, and natural fracture length on formation rock risks are discussed. A failure index is used to quantify the formation rock failure risks. The existence of natural fractures magnifies the heterogeneous system response induced by drilling. Increasing the wellbore pressure from a relatively low value can improve the support for the wellbore wall, which reduces the failure risks caused by shearing. In mechanically weak formations, the effect of natural fractures on formation rock failure becomes more significant. When the natural fracture length is large, the near-well region tends to have greater failure risks as the formations become more mechanically weak. This study provides a quantitative understanding of the effects of drilling and formation parameters on failure risks.
Network-Based Prediction of Side Effects of Repurposed Antihypertensive Sartans against COVID-19 via Proteome and Drug-Target Interactomes
Authors: Kiouri Despoina P. , Ntallis Charalampos , Kelaidonis Konstantinos , Peana Massimiliano , Tsiodras Sotirios , Mavromoustakos Thomas , Giuliani Alessandro , Ridgway Harry , Moore Graham J. , Matsoukas John M. , Chasapis Christos T.
Published: June 2023

The potential of targeting the Renin-Angiotensin-Aldosterone System (RAAS) as a treatment for the coronavirus disease 2019 (COVID-19) is currently under investigation. One way to combat this disease involves the repurposing of angiotensin receptor blockers (ARBs), which are antihypertensive drugs, because they bind to angiotensin-converting enzyme 2 (ACE2), which in turn interacts with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. However, there has been no in silico analysis of the potential toxicity risks associated with the use of these drugs for the treatment of COVID-19. To address this, a network-based bioinformatics methodology was used to investigate the potential side effects of known Food and Drug Administration (FDA)-approved antihypertensive drugs, Sartans. This involved identifying the human proteins targeted by these drugs, their first neighbors, and any drugs that bind to them using publicly available experimentally supported data, and subsequently constructing proteomes and protein–drug interactomes. This methodology was also applied to Pfizer’s Paxlovid, an antiviral drug approved by the FDA for emergency use in mild-to-moderate COVID-19 treatment. The study compares the results for both drug categories and examines the potential for off-target effects, undesirable involvement in various biological processes and diseases, possible drug interactions, and the potential reduction in drug efficiency resulting from proteoform identification.
‘It Was Just the Club from Nowhere:’ The Montgomery Bus Boycott, the Gastro-Politics of Black Domestic Women, and Liberation Theology Futures
Authors: Cook Julian Armand
Published: June 2023

This article posits Georgia Gilmore and the “Club to Nowhere”—a crucial fundraising arm of the Montgomery Bus Boycott—as a critical vector in a larger tradition in the U.S. In Black movements for Black liberation, food and food production are engaged as a communal pedagogy for constructing agency, behavioral reform, economic power, resistance, and sustainable social transformation. While Montgomery preachers made speeches, activists strategized, and male leaders debated the place of women in the Black liberation project, Gilmore and her cadre of Black women domestics secured thousands of dollars to fund the movement by selling soul food staples. Through their labor, “The From Nowhere” transformed the socio-political and epistemological positionality of Black domestic women into a valuable intellectual resource for generating a movement for social change. Consequently, Gilmore reminds contemporary and future liberation theologians that interrogating and re-envisioning our epistemologies is essential to sustainable revolutionary social praxes. Working at the juncture of history, ethics, and critical theory, I look to Gilmore and “The Club from Nowhere” for historical reflection on the intersections of food, race, gender, and the future of liberation theologies.
Literature Review on Recent Trends and Perspectives of Collaborative Robotics in Work 4.0
Authors: Weidemann Carlo , Mandischer Nils , van Kerkom Frederick , Corves Burkhard , Hüsing Mathias , Kraus Thomas , Garus Cyryl
Published: June 2023

This literature review presents a comprehensive analysis of the use and potential application scenarios of collaborative robots in the industrial working world, focusing on their impact on human work, safety, and health in the context of Industry 4.0. The aim is to provide a holistic evaluation of the employment of collaborative robots in the current and future working world, which is being increasingly driven by the automation and digitization of production processes, and which can be outlined using the term Work 4.0. In this context, the forms of work organization, and the demands and impacts on humans are changing profoundly. Collaborative robots represent a key technology to aid the transition. The review utilizes expert interviews for identifying relevant keywords, and follows the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) framework to evaluate peer-reviewed literature between 2002 and January 2022. The analysis includes forms of interaction, and the distribution of roles, control interfaces, safety procedures, and ergonomics and health. In addition, the review offers a heatmap displaying the research topics of 715 publications for each year, and a database of these publications in BibTeX format that is publicly accessible. The review highlights the challenges, potential benefits, and trends of using collaborative robots in the industrial working world, emphasizing the importance of a careful evaluation of their impact on human work, safety, and health. It offers a tool set for researchers and practitioners to further explore and evaluate the employment of collaborative robots in Work 4.0.
Deciphering Small-Scale Seasonal Surface Dynamics of Rock Glaciers in the Central European Alps Using DInSAR Time Series
Authors: Buchelt Sebastian , Blöthe Jan Henrik , Kuenzer Claudia , Schmitt Andreas , Ullmann Tobias , Philipp Marius , Kneisel Christof
Published: June 2023

The Essential Climate Variable (ECV) Permafrost is currently undergoing strong changes due to rising ground and air temperatures. Surface movement, forming characteristic landforms such as rock glaciers, is one key indicator for mountain permafrost. Monitoring this movement can indicate ongoing changes in permafrost; therefore, rock glacier velocity (RGV) has recently been added as an ECV product. Despite the increased understanding of rock glacier dynamics in recent years, most observations are either limited in terms of the spatial coverage or temporal resolution. According to recent studies, Sentinel-1 (C-band) Differential SAR Interferometry (DInSAR) has potential for monitoring RGVs at high spatial and temporal resolutions. However, the suitability of DInSAR for the detection of heterogeneous small-scale spatial patterns of rock glacier velocities was never at the center of these studies. We address this shortcoming by generating and analyzing Sentinel-1 DInSAR time series over five years to detect small-scale displacement patterns of five high alpine permafrost environments located in the Central European Alps on a weekly basis at a range of a few millimeters. Our approach is based on a semi-automated procedure using open-source programs (SNAP, pyrate) and provides East-West displacement and elevation change with a ground sampling distance of 5 m. Comparison with annual movement derived from orthophotos and unpiloted aerial vehicle (UAV) data shows that DInSAR covers about one third of the total movement, which represents the proportion of the year suited for DInSAR, and shows good spatial agreement (Pearson R: 0.42–0.74, RMSE: 4.7–11.6 cm/a) except for areas with phase unwrapping errors. Moreover, the DInSAR time series unveils spatio-temporal variations and distinct seasonal movement dynamics related to different drivers and processes as well as internal structures. Combining our approach with in situ observations could help to achieve a more holistic understanding of rock glacier dynamics and to assess the future evolution of permafrost under changing climatic conditions.
Trends of Grassland Resilience under Climate Change and Human Activities on the Mongolian Plateau
Authors: Wu Jincheng , Sun Ziyun , Yao Ying , Liu Yanxu
Published: June 2023

Grassland resilience is influenced by climate change and human activities. However, little is known about how grassland resilience has changed, driven by climate change and human activities, on the Mongolian Plateau. We calculated grassland resilience on the Mongolian Plateau from 2000 to 2021 using the kernel normalized difference vegetation index (kNDVI), quantified the trends of grassland resilience using a newly proposed “critical slowing down” indicator with a machine learning algorithm, and compared the driving forces for these changes between Inner Mongolia and Mongolia. The findings of this study demonstrate that heightened levels of precipitation and reduced temperature contribute to the enhanced resilience of grassland ecosystems on the Mongolian Plateau. Conversely, the presence of grazing activities exhibits a detrimental effect on such resilience. In semi-arid regions, approximately 43% of grassland areas are undergoing a discernible decline in resilience. This decline is particularly pronounced in regions characterized by heightened levels of grazing intensity. In addition, resilience declined in 54% of areas with population growth compared with 32% in areas with population decline. Inner Mongolia, with its higher intensity of human activities, has a more serious decline in ecological resilience than Mongolia, indicating that further ecological restoration measures are needed.
Utö Observatory for Analysing Atmospheric Ducting Events over Baltic Coastal and Marine Waters
Authors: Rautiainen Laura , Tyynelä Jani , Lensu Mikko , Siiriä Simo , Vakkari Ville , O’Connor Ewan , Hämäläinen Karoliina , Lonka Harry , Stenbäck Ken , Koistinen Jarmo , Laakso Lauri
Published: June 2023

Maritime safety relies on navigation, detection, and radio communication technologies that function through electromagnetic radiation. Propagation of electromagnetic radiation can be impacted by a disruptive phenomenon known as ducting. Our four-week study using a X-band coastal radar and various meteorological and marine observations, including vertical profiles of temperature, humidity and wind, in early spring 2022 concluded that the combination of measurements at the Utö observatory provides a reliable means of detecting ducting in the Archipelago Sea. The modified refractivity calculated from the vertical profiles for the 22–59 m and 32–59 m altitude layers and coastal radar over-the-horizon observations agree 77% and 85% of the time, respectively. As such, the modified refractivity gradient can be considered a good indicator for over-the-horizon detection with the Utö coastal radar over the open sea. The horizontal wind profiles also revealed a low-level jet at the radar height that often coincided with the ducting observations. To quantify the results, we created an empirical ducting index which showed that ducting is spatially variable, showing the capabilities of the Utö observatory for research oriented towards monitoring and improving maritime safety and security.
Hyperspectral Image Classification Based on Dense Pyramidal Convolution and Multi-Feature Fusion
Authors: Zhang Junsan , Zhao Li , Jiang Hongzhao , Shen Shigen , Wang Jian , Zhang Peiying , Zhang Wei , Wang Leiquan
Published: June 2023

In recent years, hyperspectral image classification techniques have attracted a lot of attention from many scholars because they can be used to model the development of different cities and provide a reference for urban planning and construction. However, due to the difficulty in obtaining hyperspectral images, only a limited number of pixels can be used as training samples. Therefore, how to adequately extract and utilize the spatial and spectral information of hyperspectral images with limited training samples has become a difficult problem. To address this issue, we propose a hyperspectral image classification method based on dense pyramidal convolution and multi-feature fusion (DPCMF). In this approach, two branches are designed to extract spatial and spectral features, respectively. In the spatial branch, dense pyramid convolutions and non-local blocks are used to extract multi-scale local and global spatial features in image samples, which are then fused to obtain spatial features. In the spectral branch, dense pyramidal convolution layers are used to extract spectral features in image samples. Finally, the spatial and spectral features are fused and fed into fully connected layers to obtain classification results. The experimental results show that the overall accuracy (OA) of the method proposed in this paper is 96.74%, 98.10%, 98.92% and 96.67% on the four hyperspectral datasets, respectively. Significant improvements are achieved compared to the five methods of SVM, SSRN, FDSSC, DBMA and DBDA for hyperspectral classification. Therefore, the proposed method can better extract and exploit the spatial and spectral information in image samples when the number of training samples is limited. Provide more realistic and intuitive terrain and environmental conditions for urban planning, design, construction and management.
Bluetooth-Based Healthcare Information and Medical Resource Management System
Authors: Chang Chao-Shu , Wu Tin-Hao , Wu Yu-Chi , Han Chin-Chuan
Published: June 2023

This paper presents a healthcare information and medical resource management platform utilizing wearable devices, physiological sensors, and an indoor positioning system (IPS). This platform provides medical healthcare information management based on the physiological information collected by wearable devices and Bluetooth data collectors. The Internet of Things (IoT) is constructed for this medical care purpose. The collected data are classified and used to monitor the status of patients in real time with a Secure MQTT mechanism. The measured physiological signals are also used for developing an IPS. When the patient is out of the safety zone, the IPS will send an alert message instantly by pushing the server to remind the caretaker, easing the caretaker’s burden and offering extra protection for the patient. The presented system also provides medical resource management with the help of IPS. The medical equipment and devices can be tracked by IPS to tackle some equipment rental problems, such as lost and found. A platform for the medical staff work coordination information exchange and transmission is also developed to expedite the maintenance of medical equipment, providing the shared medical information to healthcare and management staff in a timely and transparent manner. The presented system in this paper will finally reduce the loading of medical staff during the COVID-19 pandemic period.
Associating Functional Neural Connectivity and Specific Aspects of Sensorimotor Control in Chronic Stroke
Authors: Baker Adam , Schranz Christian , Seo Na Jin
Published: June 2023

Hand sensorimotor deficits often result from stroke, limiting the ability to perform daily living activities. Sensorimotor deficits are heterogeneous among stroke survivors. Previous work suggests a cause of hand deficits is altered neural connectivity. However, the relationships between neural connectivity and specific aspects of sensorimotor control have seldom been explored. Understanding these relationships is important for developing personalized rehabilitation strategies to improve individual patients’ specific sensorimotor deficits and, thus, rehabilitation outcomes. Here, we investigated the hypothesis that specific aspects of sensorimotor control will be associated with distinct neural connectivity in chronic stroke survivors. Twelve chronic stroke survivors performed a paretic hand grip-and-relax task while EEG was collected. Four aspects of hand sensorimotor grip control were extracted, including reaction time, relaxation time, force magnitude control, and force direction control. EEG source connectivity in the bilateral sensorimotor regions was calculated in α and β frequency bands during grip preparation and execution. Each of the four hand grip measures was significantly associated with a distinct connectivity measure. These results support further investigations into functional neural connectivity signatures that explain various aspects of sensorimotor control, to assist the development of personalized rehabilitation that targets the specific brain networks responsible for the individuals’ distinct sensorimotor deficits.
Modified Gini Index Detector for Cooperative Spectrum Sensing over Line-of-Sight Channels
Authors: Guimarães Dayan Adionel
Published: June 2023

Recently, the Gini index detector (GID) has been proposed as an alternative for data-fusion cooperative spectrum sensing, being mostly suitable for channels with line-of-sight or dominant multi-path components. The GID is quite robust against time-varying noise and signal powers, has the constant false-alarm rate property, can outperform many the state-of-the-art robust detectors, and is one of the simplest detectors developed so far. The modified GID (mGID) is devised in this article. It inherits the attractive attributes of the GID, yet with a computational cost far below the GID. Specifically, the time complexity of the mGID obeys approximately the same run-time growth rate of the GID, but has a constant factor approximately 23.4 times smaller. Equivalently, the mGID takes approximately 4% of the computation time spent to calculate the GID test statistic, which brings a huge reduction in the latency of the spectrum sensing process. Moreover, this latency reduction comes with no performance loss with respect to the GID.
Prediction of Joint Angles Based on Human Lower Limb Surface Electromyography
Authors: Zhao Hongyu , Qiu Zhibo , Peng Daoyong , Wang Fang , Wang Zhelong , Qiu Sen , Shi Xin , Chu Qinghao
Published: June 2023

Wearable exoskeletons can help people with mobility impairments by improving their rehabilitation. As electromyography (EMG) signals occur before movement, they can be used as input signals for the exoskeletons to predict the body’s movement intention. In this paper, the OpenSim software is used to determine the muscle sites to be measured, i.e., rectus femoris, vastus lateralis, semitendinosus, biceps femoris, lateral gastrocnemius, and tibial anterior. The surface electromyography (sEMG) signals and inertial data are collected from the lower limbs while the human body is walking, going upstairs, and going uphill. The sEMG noise is reduced by a wavelet-threshold-based complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) reduction algorithm, and the time-domain features are extracted from the noise-reduced sEMG signals. Knee and hip angles during motion are calculated using quaternions through coordinate transformations. The random forest (RF) regression algorithm optimized by cuckoo search (CS), shortened as CS-RF, is used to establish the prediction model of lower limb joint angles by sEMG signals. Finally, root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) are used as evaluation metrics to compare the prediction performance of the RF, support vector machine (SVM), back propagation (BP) neural network, and CS-RF. The evaluation results of CS-RF are superior to other algorithms under the three motion scenarios, with optimal metric values of 1.9167, 1.3893, and 0.9815, respectively.
Recent Progress in Micro- and Nanotechnology-Enabled Sensors for Biomedical and Environmental Challenges
Authors: Tovar-Lopez Francisco J.
Published: June 2023

Micro- and nanotechnology-enabled sensors have made remarkable advancements in the fields of biomedicine and the environment, enabling the sensitive and selective detection and quantification of diverse analytes. In biomedicine, these sensors have facilitated disease diagnosis, drug discovery, and point-of-care devices. In environmental monitoring, they have played a crucial role in assessing air, water, and soil quality, as well as ensured food safety. Despite notable progress, numerous challenges persist. This review article addresses recent developments in micro- and nanotechnology-enabled sensors for biomedical and environmental challenges, focusing on enhancing basic sensing techniques through micro/nanotechnology. Additionally, it explores the applications of these sensors in addressing current challenges in both biomedical and environmental domains. The article concludes by emphasizing the need for further research to expand the detection capabilities of sensors/devices, enhance sensitivity and selectivity, integrate wireless communication and energy-harvesting technologies, and optimize sample preparation, material selection, and automated components for sensor design, fabrication, and characterization.
Intra- and Extra-Hospitalization Monitoring of Vital Signs—Two Sides of the Same Coin: Perspectives from LIMS and Greenline-HT Study Operators
Authors: Pietrantonio Filomena , Vinci Antonio , Maurici Massimo , Ciarambino Tiziana , Galli Barbara , Signorini Alessandro , La Fazia Vincenzo Mirco , Rosselli Francescantonio , Fortunato Luca , Iodice Rosa , Materazzo Marco , Ciuca Alessandro , Cicerchia Lamberto Carlo Maria , Ruggeri Matteo , Manfellotto Dario , Rosiello Francesco , Moriconi Andrea
Published: June 2023

Background: In recent years, due to the epidemiological transition, the burden of very complex patients in hospital wards has increased. Telemedicine usage appears to be a potential high-impact factor in helping with patient management, allowing hospital personnel to assess conditions in out-of-hospital scenarios. Methods: To investigate the management of chronic patients during both hospitalization for disease and discharge, randomized studies (LIMS and Greenline-HT) are ongoing in the Internal Medicine Unit at ASL Roma 6 Castelli Hospital. The study endpoints are clinical outcomes (from a patient’s perspective). In this perspective paper, the main findings of these studies, from the operators’ point of view, are reported. Operator opinions were collected from structured and unstructured surveys conducted among the staff involved, and their main themes are reported in a narrative manner. Results: Telemonitoring appears to be linked to a reduction in side-events and side-effects, which represent some of most commons risk factors for re-hospitalization and for delayed discharge during hospitalization. The main perceived advantages are increased patient safety and the quick response in case of emergency. The main disadvantages are believed to be related to low patient compliance and an infrastructural lack of optimization. Conclusions: The evidence of wireless monitoring studies, combined with the analysis of activity data, suggests the need for a model of patient management that envisages an increase in the territory of structures capable of offering patients subacute care (the possibility of antibiotic treatments, blood transfusions, infusion support, and pain therapy) for the timely management of chronic patients in the terminal phase, for which treatment in acute wards must be guaranteed only for a limited time for the management of the acute phase of their diseases.
An Analytical Solution for Inverse Kinematics of SSRMS-Type Redundant Manipulators
Authors: Qin Li , Wei Xiao , Lv Liangliang , Han Liangliang , Fang Guangqiang
Published: June 2023

Compared with non-redundant manipulators, the self-motion of 7-DOF redundant manipulators results in an infinite number of inverse kinematics solutions for a desired end-effector pose. This paper proposes an efficient and accurate analytical solution for inverse kinematics of SSRMS-type redundant manipulators. This solution is applicable to SRS-type manipulators with the same configuration. The proposed method involves introducing an alignment constraint to restrain the self-motion and to decompose the spatial inverse kinematics problem into three independent planar subproblems simultaneously. The resulting geometric equations depend on the part of the joint angles, respectively. These equations are then computed recursively and efficiently using the sequences of (θ1,θ7), (θ2,θ6), and (θ3,θ4,θ5), generating up to sixteen sets of solutions for a given desired end-effector pose. Additionally, two complementary methods are proposed for overcoming the possible singular configuration and judging unsolvable poses. Finally, numerical simulations are conducted to investigate the performance of the proposed approach in terms of average calculation time, success rate, average position error, and the ability to plan a trajectory with singular configurations.
Emerging Memtransistors for Neuromorphic System Applications: A Review
Authors: You Tao , Zhao Miao , Fan Zhikang , Ju Chenwei
Published: June 2023

The von Neumann architecture with separate memory and processing presents a serious challenge in terms of device integration, power consumption, and real-time information processing. Inspired by the human brain that has highly parallel computing and adaptive learning capabilities, memtransistors are proposed to be developed in order to meet the requirement of artificial intelligence, which can continuously sense the objects, store and process the complex signal, and demonstrate an “all-in-one” low power array. The channel materials of memtransistors include a range of materials, such as two-dimensional (2D) materials, graphene, black phosphorus (BP), carbon nanotubes (CNT), and indium gallium zinc oxide (IGZO). Ferroelectric materials such as P(VDF-TrFE), chalcogenide (PZT), HfxZr1−xO2(HZO), In2Se3, and the electrolyte ion are used as the gate dielectric to mediate artificial synapses. In this review, emergent technology using memtransistors with different materials, diverse device fabrications to improve the integrated storage, and the calculation performance are demonstrated. The different neuromorphic behaviors and the corresponding mechanisms in various materials including organic materials and semiconductor materials are analyzed. Finally, the current challenges and future perspectives for the development of memtransistors in neuromorphic system applications are presented.
Adaptive Fuzzy Logic Deep-Learning Equalizer for Mitigating Linear and Nonlinear Distortions in Underwater Visible Light Communication Systems
Authors: Rajalakshmi Radhakrishnan , Pothiraj Sivakumar , Mahdal Miroslav , Elangovan Muniyandy
Published: June 2023

Underwater visible light communication (UVLC) has recently come to light as a viable wireless carrier for signal transmission in risky, uncharted, and delicate aquatic environments like seas. Despite the potential of UVLC as a green, clean, and safe alternative to conventional communication methods, it is challenged by significant signal attenuation and turbulent channel conditions compared to long-distance terrestrial communication. To address linear and nonlinear impairments in UVLC systems, this paper presents an adaptive fuzzy logic deep-learning equalizer (AFL-DLE) for 64 Quadrature Amplitude Modulation-Component minimal Amplitude Phase shift (QAM-CAP)-modulated UVLC systems. The proposed AFL-DLE is dependent on complex-valued neural networks and constellation partitioning schemes and utilizes the Enhanced Chaotic Sparrow Search Optimization Algorithm (ECSSOA) to improve overall system performance. Experimental outcomes demonstrate that the suggested equalizer achieves significant reductions in bit error rate (55%), distortion rate (45%), computational complexity (48%), and computation cost (75%) while maintaining a high transmission rate (99%). This approach enables the development of high-speed UVLC systems capable of processing data online, thereby advancing state-of-the-art underwater communication.
Sensor Topology Optimization in Dense IoT Environments by Applying Neural Network Configuration
Authors: Papastergiou George , Xenakis Apostolos , Chaikalis Costas , Kosmanos Dimitrios , Chatzimisios Periklis , Samaras Nicholas S.
Published: June 2023

In dense IoT deployments of wireless sensor networks (WSNs), sensor placement, coverage, connectivity, and energy constraints determine the overall network lifetime. In large-size WSNs, it is difficult to maintain a trade-off among these conflicting constraints and, thus, scaling is difficult. In the related research literature, various solutions are proposed that attempt to address near-optimal behavior in polynomial time, the majority of which relies on heuristics. In this paper, we formulate a topology control and lifetime extension problem regarding sensor placement, under coverage and energy constraints, and solve it by applying and testing several neural network configurations. To do so, the neural network dynamically proposes and handles sensor placement coordinates in a 2D plane, having the ultimate goal to extend network lifetime. Simulation results show that our proposed algorithm improves network lifetime, while maintaining communication and energy constraints, for medium- and large-scale deployments.
Research on Apple Recognition Algorithm in Complex Orchard Environment Based on Deep Learning
Authors: Zhao Zhuoqun , Wang Jiang , Zhao Hui
Published: June 2023

In the complex environment of orchards, in view of low fruit recognition accuracy, poor real-time and robustness of traditional recognition algorithms, this paper propose an improved fruit recognition algorithm based on deep learning. Firstly, the residual module was assembled with the cross stage parity network (CSP Net) to optimize recognition performance and reduce the computing burden of the network. Secondly, the spatial pyramid pool (SPP) module is integrated into the recognition network of the YOLOv5 to blend the local and global features of the fruit, thus improving the recall rate of the minimum fruit target. Meanwhile, the NMS algorithm was replaced by the Soft NMS algorithm to enhance the ability of identifying overlapped fruits. Finally, a joint loss function was constructed based on focal and CIoU loss to optimize the algorithm, and the recognition accuracy was significantly improved. The test results show that the MAP value of the improved model after dataset training reaches 96.3% in the test set, which is 3.8% higher than the original model. F1 value reaches 91.8%, which is 3.8% higher than the original model. The average detection speed under GPU reaches 27.8 frames/s, which is 5.6 frames/s higher than the original model. Compared with current advanced detection methods such as Faster RCNN and RetinaNet, among others, the test results show that this method has excellent detection accuracy, good robustness and real-time performance, and has important reference value for solving the problem of accurate recognition of fruit in complex environment.
DRU-Net: Pulmonary Artery Segmentation via Dense Residual U-Network with Hybrid Loss Function
Authors: Zulfiqar Manahil , Stanuch Maciej , Wodzinski Marek , Skalski Andrzej
Published: June 2023

The structure and topology of the pulmonary arteries is crucial to understand, plan, and conduct medical treatment in the thorax area. Due to the complex anatomy of the pulmonary vessels, it is not easy to distinguish between the arteries and veins. The pulmonary arteries have a complex structure with an irregular shape and adjacent tissues, which makes automatic segmentation a challenging task. A deep neural network is required to segment the topological structure of the pulmonary artery. Therefore, in this study, a Dense Residual U-Net with a hybrid loss function is proposed. The network is trained on augmented Computed Tomography volumes to improve the performance of the network and prevent overfitting. Moreover, the hybrid loss function is implemented to improve the performance of the network. The results show an improvement in the Dice and HD95 scores over state-of-the-art techniques. The average scores achieved for the Dice and HD95 scores are 0.8775 and 4.2624 mm, respectively. The proposed method will support physicians in the challenging task of preoperative planning of thoracic surgery, where the correct assessment of the arteries is crucial.
Revitalize Traditional Agriculture: Chinese Consumer Perception and Preference of “Modern” Organic and Sustainable Traditional Rice Products
Authors: Wang Erpeng
Published: June 2023

Many smallholder farmers in developing countries have used sustainable traditional agricultural techniques to ensure food safety and sustainability over the centuries. However, the value of sustainable traditional agricultural products, especially as an inexpensive substitution for “modern” organic products in developing countries, is rarely studied. Using the contingent valuation method, we compared Chinese consumers’ perceptions of and preferences for sustainable traditional agricultural products and “modern” organic products. Our results show that sustainable traditional agriculture can signal environment-friendly practices and food safety, and consumer willingness to pay for sustainable traditional agricultural products is higher than those of “modern” organic products. Considering the high demand for sustainable traditional agricultural products, revitalizing sustainable traditional agriculture may be a good way to balance sustainability and feasibility in developing countries.
Species Diversity of Deadwood in Chinese Fir Plantations Differs between Mixed Planting and Thinning Treatments
Authors: Li Muxuan , Li Yuanfa , Ye Shaoming , Hao Jian , Zhang Lianjin
Published: June 2023

The occurrence of deadwood is inevitable during the process of plantation conversion, but the influences of conversion and the potential environmental effect on deadwood species diversity remain unclear. We established two fixed plots in Chinese fir thinned forest (TF) and Chinese fir and Michelia macclurei Dandy mixed forest (MF) (100 × 80 and 120 × 60 m2, respectively). We classified the deadwood into groups based on origin and by status, and analyzed deadwood species diversity using four common diversity indices. We also investigated the contribution of topographic factors to tree mortality using redundancy analysis. The species composition of deadwood differed markedly between the MF and TF. The species diversity and variety of deadwood status were greater for the TF than MF, although abundance was lower. Topography was poorly correlated with deadwood in the MF, while in the TF, altitude was strongly correlated with deadwood from Chinese fir, shade-intolerant late-coming populations, and fallen wood. Slope was negatively correlated with late-coming populations and fallen wood, but deadwood correlations with convexity were weak. These results indicate that cultivation methods strongly alter the species composition, status, abundance and diversity of deadwood in plantations. Topographic factors and targeted cultivation practices promote the formation of deadwood.
A Comparative Analysis of Standard and Nano-Structured Glass for Enhancing Heat Transfer and Reducing Energy Consumption Using Metal and Oxide Nanoparticles: A Review
Authors: Jastaneyah Zuhair , Kamar Haslinda M. , Alansari Abdulrahman , Al Garalleh Hakim
Published: June 2023

The thrust to find new technology and materials has been greatly increasing due to environmental and technological challenges in the progressive world. Among new standard materials and advanced nano-materials that possess a huge potential and superior thermal, mechanical, optical, and magnetic properties, which have made them excellent and suitable components for mechanical engineering applications. The current review paper deals with recent enhancements and advances in the properties of nano-structured glasses and composites in terms of thermal and mechanical properties. A fabrication method of nano-structured glass has briefly been discussed and the phase change material (PCM) method outlined. The comprehensive review of thermal and optical properties confirms that nano-fabricated glasses show both direct and indirect running of band gaps depending on selective nano-structuring samples. The electrical and magnetic properties also show enhancement in electrical conductivity on nano-structured glasses compared to their standard counterparts. The realistic changes in thermal and mechanical properties of nano-structured glasses and composites are commonly attributed to many micro- and nano-structural distribution features like grain size, shape, pores, other flaws and defects, surface condition, impurity level, stress, duration of temperature effect on the selective samples. Literature reports that nano-structuring materials lead to enhanced phonon boundary scattering which reduces thermal conductivity and energy consumption.
The Impact of Housing Support Expenditure on Urban Residents’ Consumption—Evidence from China
Authors: Shang Li , Zhang Xiaoling , Tang Decai , Ma Xiaoxue , Lu Chunfeng
Published: June 2023

Consumption plays an important role in economic growth and sustainable economic development. The Chinese government emphasizes the theme of promoting high-quality development. This aim has led to the implementation of strategies to expand domestic demand through a deep structural reform in the supply chain, enhance the endogenous power and reliability of the large domestic cycle, improve the quality and level of the international cycle, and accelerate the construction of a modern economic system. Based on the clarification of the consumption effect of housing support expenditure, this paper uses a combination of theoretical and empirical analysis to clarify the relationship between housing support expenditure and urban residents’ consumption. This is carried out to seek a breakthrough point for raising the total level of urban residents’ consumption expenditure in China from the level of housing support. This study revealed that government housing support has a certain degree of influence on the total level of urban residents’ consumption expenditure and that the government’s support of housing support is conducive to improving the total level of urban residents’ consumption expenditure. Also, if the housing price is not controlled and adjusted, the effect of government housing support on urban residents’ consumption expenditure will be greatly reduced, which will affect the lives of urban residents in the long run. Finally, suggestions and countermeasures for improving the overall level of urban residents’ consumption and the sustainable development of the social economy in China are provided.
Sustainable Water Harvesting for Improving Food Security and Livelihoods of Smallholders under Different Climatic Conditions of India
Authors: Panwar Pankaj , Machiwal Deepesh , Kumari Vandita , Kumar Sanjay , Dogra Pradeep , Manivannan S. , Bhatnagar P. R. , Tomar J. M. S. , Kaushal Rajesh , Jinger Dinesh , Sarkar Pradip Kumar , Baishya L. K. , Devi Ningthoujam Peetambari , Kakade Vijaysinha , Singh Gaurav , Singh Nongmaithem Raju , Singh S. Gojendro , Patel Abhishek , Renjith P. S. , Pal Sharmistha , Bhatt V. K. , Sharma N. K. , Khola O. P. S. , Radhakrishnan Sheetal K. , Kasthuri Thilagam V. , Bhutia P. L. , Nath Kouberi , Das Rekha , Daschaudhuri Dhiman , Kumar Arun , Panwar G. S. , Dwivedi S. V. , Kumar Sanjeev , Singh B. K.
Published: June 2023

In India, the per capita availability of water is projected to be 1465 m3 and 1235 m3 by the years 2025 and 2050, respectively, and hence, India would be a water-stressed country as per the United Nations’ standard of less than 1700 m3 per capita water availability. India is predominantly an agricultural-dominant country. Rainfed agriculture in the country contributes 40% of food grain production and supports half of the human population and two-thirds of the livestock population. The country has 15 different agro-climatic zones, and each agro-climatic region has its own constraints of water availability and management along with the potential for their optimum utilization. Such situations warrant the formulation of regional-level strategies. Efforts were made to integrate and evaluate the feasibility of water harvesting and its utilization at twelve different sites representing six different agro-climatic conditions spanning pan India. It was found that water harvesting through tanks/ponds is a feasible approach and can increase the crop production as well as diversification. The results reveal that the range of crop diversification index increased from 0.49–0.85 to 0.65–0.98; the crop productivity index increased from 0.28–0.66 to 0.66–0.90; the cultivated land utilization index increased from 0.05–0.69 to 0.34–0.84; and the crop water productivity index increased from 0.20–0.51 to 0.56–0.96, among other production and diversification indices, due to additional water availability through rainwater harvesting intervention. Moreover, the gross return increased from INR 43,768–704,356 to INR 220,840–1,469,108 ha−1, representing a 108 to 400% increase in the returns due to the availability of water. The findings of this study suggest that the water harvesting in small ponds/tanks is economical and feasible, requires less technological intervention, and increases crop diversification in all the studied agro-climatic conditions, and hence, the same needs to be encouraged in the rainfed areas of the country.
Sustainable Dyeing Process for Nylon 6 Fabrics by Rhubarb Flower Using Different Bio-Mordants
Authors: Shahmoradi Ghaheh Fatemeh , Haji Aminoddin , Daneshvar Elaheh
Published: June 2023

The purpose of this study is to propose a fully sustainable dyeing process for nylon 6. In order to achieve this goal, Rhubarb flower parts were used to produce a brown hue on nylon 6 fabric. The effects of dyeing parameters such as dyeing time, temperature, dyebath pH, M:L, salt addition, dispersing agent, and dye concentration on color strength were investigated. Using 100%owf dye in an acidic medium at boil and the material to liquor ratio of 1:30 for 75 min was determined to be the optimal condition for dyeing nylon 6 with rhubarb flower. In order to achieve acceptable color fastness, four natural mordants were applied, including walnut husks, pistachio hulls, pine cones, and green coffee. Colorimetric measurements revealed that mordanting did not affect the hue of the color compared to the non-mordant sample. In addition, diverse natural mordants produced the same color (i.e., brown) with varying color strengths, of which 10%owf walnut husk generated the strongest color. Bio-mordanted samples were also found to have excellent color fastness, thereby providing an effective substitute for metal mordants.
Building Information Modelling Implementation Model for Sustainable Building Projects in Developing Countries: A PLS-SEM Approach
Authors: Abdel-Tawab Maged , Kineber Ahmed Farouk , Chileshe Nicholas , Abanda Henry , Ali Ali Hassan , Almukhtar Avar
Published: June 2023

When building homes, sustainability principles should be followed throughout the process to achieve maximum advantages. Building information modeling (BIM) activities can aid in achieving sustainable goals. Third-world countries’ building industry implements informal approaches to information dissemination through email newsletters and websites. This research seeks to provide a model for the application of BIM and its relationship with overall sustainable success (OSS) in building projects. BIM activities were identified from the literature, and a survey form was distributed to 180 professionals in the Egyptian construction industry. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to establish the structure of BIM activities and assess their correlation with project success, revealing BIM accounts for 30% of sustainability. The study’s findings inform decision-making to improve project sustainability and reduce costs by introducing BIM to developing countries’ construction industries.