bluuebunny/crossref_metadata_2025 huggingface dataset:
Remaining Oil Distribution Law and Development Potential Analysis after Polymer Flooding Based on Reservoir Architecture in Daqing Oilfield, China
Authors: Fu Hongtao , Bai Zhenqiang , Guo Hu , Yang Kena , Guo Chunping , Liu Mingxi , Liang Lihao , Song Kaoping
Published: May 2023

Polymer flooding has drawn more and more attention in the world for its high incremental oil recovery factor and relative low costs compared with water flooding and other chemically enhanced oil recovery techniques. However, for many oilfields, such as Daqing Oilfield, China, that have already been flooded with polymers, how to further improve recovery remains a big problem. Traditional intralayer, interlayer and plane heterogeneity studies cannot accurately characterize the remaining oil distribution after polymer flooding. To solve this problem, we established a method to quantitatively describe the reservoir’s architecture. Then, the architecture elements were dissected hierarchically and the interface of each architecture level in Daqing Oilfield was identified. The distribution pattern and development potential of the remaining oil after polymer flooding under the influence of reservoir architecture was analyzed. The results show that, regarding the sedimentary process from north to south in Daqing Oilfield, the channel becomes narrower, the thickness decreases, the point bar’s width increases and the thickness of the meandering river decreases. The braided bar scale becomes larger and the thickness becomes smaller in the braided river. According to the reservoir’s architecture, the remaining oil was divided into four categories of plane remaining oil (abandoned channel occlusion type, interfluvial sand body occlusion type, inter-well retention type and well pattern uncontrollable type) and three types of vertical remaining oil (in-layer interlayer occlusion type, rhythm type and gravity type). About 40% of the original oil in place (OOIP) of Daqing Oilfield has not yet been produced, which indicates that there is great potential for development. This study is important for improving oil recovery in polymer-flooded reservoirs.
Study of Prepared Lead-Free Polymer Nanocomposites for X- and Gamma-ray Shielding in Healthcare Applications
Authors: Alsaab Abdulrhman Hasan , Zeghib Sadek
Published: May 2023

Polymer composites were synthesized via melt mixing for radiation shielding in the healthcare sector. A polymethyl-methacrylate (PMMA) matrix was filled with Bi2O3 nanoparticles at 10%, 20%, 30%, and 40% weight percentages. The characterization of nanocomposites included their morphological, structural, and thermal properties, achieved using SEM, XRD, and TGA, respectively. The shielding properties for all synthesized samples including pristine PMMA were measured with gamma spectrometry using a NaI (Tl) scintillator detector spanning a wide range of energies and using different radioisotopes, namely Am-241 (59.6 keV), Co-57 (122.2 keV), Ra-226 (242.0), Ba-133 (80.99 and 356.02 keV), Cs-137 (661.6 keV), and Co-60 (1173.2 and 1332.5 keV). A substantial increase in the mass attenuation coefficients was obtained at low and medium energies as the filler weight percentage increased, with minor variations at higher gamma energies (1173 and 1332 keV). The mass attenuation coefficient decreased with increasing energy except under 122 keV gamma rays due to the K-absorption edge of bismuth (90.5 keV). At 40% loading of Bi2O3, the mass attenuation coefficient for the cesium 137Cs gamma line at 662 keV reached the corresponding value for the toxic heavy element lead. The synthesized PMMA-Bi2O3 nanocomposites proved to be highly effective, lead-free, safe, and lightweight shielding materials for X- and gamma rays within a wide energy range (<59 keV to 1332 keV), making them of interest for healthcare applications.
Innovative Device and Procedure for In Situ Quantification of the Self-Healing Ability and Kinetics of Self-Healing of Polymeric Materials
Authors: Paez-Amieva Yuliet , Carpena-Montesinos Jaime , Martín-Martínez José Miguel
Published: May 2023

A new device and procedure for the in situ quantification of the extent of the self-healing and the kinetics of self-healing of polymeric materials were proposed. The device consisted of flowing an inert gas below the sample placed in a hermetically closed chamber. When the sample was perforated/damaged, the gas passed through the hole made in the polymeric material and the gas flow rate declined as the self-healing was produced. Once the gas flow rate stopped, the self-healing was completed. The proposed method was simple, quick, and reproducible, and several in situ self-healing experiments at different temperatures could be performed in the same sample. As a proof of concept, the new device and method have been used for measuring the self-healing ability of different polyurethanes.
Characterization of Agarose Gels in Solvent and Non-Solvent Media
Authors: Roux Denis C. D. , Jeacomine Isabelle , Maîtrejean Guillaume , Caton François , Rinaudo Marguerite
Published: May 2023

Agarose is known to form a homogeneous thermoreversible gel in an aqueous medium over a critical polymer concentration. The solid-liquid phase transitions are thermoreversible but depend on the molecular structure of the agarose sample tested. The literature has mentioned that agarose gels could remain stable in non-solvents such as acetone or ethanol. However, there has been no characterization of their behavior nor a comparison with the gels formed in a good solvent such as water. In the first step of this article, the structure was characterized using 1H and 13C NMR in both D2O and DMSO-d6 solvents. DMSO is a solvent that dissolves agarose regardless of the temperature. First, we have determined a low yield of methyl substitution on the D-galactose unit. Then, the evolution of the 1H NMR spectrum was monitored as a function of temperature during both increasing and decreasing temperature processes, ranging from 25 to 80 °C. A large thermal hysteresis was obtained and discussed, which aided in the interpretation of rheological behavior. The hysteresis of NMR signals is related to the mobility of the agarose chains, which follows the sol/gel transition depending on the chains’ association with H-bonds between water and the -OH groups of agarose for tightly bound water and agarose/agarose in chain packing. In the second step of the study, the water in the agarose gel was exchanged with ethanol, which is a non-solvent for agarose. The resulting gel was stable, and its properties were characterized using rheology and compared to its behavior in aqueous media. The bound water molecules that act as plasticizers were likely removed during the exchange process, resulting in a stronger and more brittle gel in ethanol, with higher thermal stability compared to the aqueous gel. It is the first time that such gel is characterized without phase transition when passing from a good solvent to a non-solvent. This extends the domains of application of agarose.
Manufacture and Characterization of Polylactic Acid Filaments Recycled from Real Waste for 3D Printing
Authors: Bergaliyeva Saltanat , Sales David L. , Delgado Francisco J. , Bolegenova Saltanat , Molina Sergio I.
Published: May 2023

This paper studies the thermal, morphological, and mechanical properties of 3D-printed polylactic acid (PLA) blends of virgin and recycled material in the following proportions: 100/0, 25/75, 50/50, and 75/25, respectively. Real waste, used as recycled content, was shredded and sorted by size without a washing step. Regular dog-bone specimens were 3D printed from filaments, manufactured in a single screw extruder. Thermogravimetric analysis indicated that adding PLA debris to raw material did not significantly impact the thermal stability of the 3D-printed samples and showed that virgin and recycled PLA degraded at almost the same temperature. Differential scanning calorimetry revealed a significant reduction in crystallinity with increasing recycled content. Scanning electron microscopy showed a more homogenous structure for specimens from 100% pure PLA, as well as a more heterogeneous one for PLA blends. The tensile strength of the PLA blends increased by adding more recycled material, from 44.20 ± 2.18 MPa for primary PLA to 52.61 ± 2.28 MPa for the blend with the highest secondary PLA content. However, this study suggests that the mechanical properties of the reprocessed parts and their basic association are unique compared with those made up of virgin material.
Computational Study of Security Risk Evaluation in Energy Management and Control Systems Based on a Fuzzy MCDM Method
Authors: Alhakami Wajdi
Published: May 2023

Numerous cyberattacks on connected control systems are being reported every day. Such control systems are subject to hostile external attacks due to their communication system. Network security is vital because it protects sensitive information from cyber threats and preserves network operations and trustworthiness. Multiple safety solutions are implemented in strong and reliable network security plans to safeguard users and companies from spyware and cyber attacks, such as distributed denial of service attacks. A crucial component that must be conducted prior to any security implementation is a security analysis. Because cyberattack encounters in power control networks are currently limited, a comprehensive security evaluation approach for power control technology in communication networks is required. According to previous studies, the challenges of security evaluation include a power control process security assessment as well as the security level of every control phase. To address such issues, the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) based on multiple criteria decision-making (MCDM) is presented for a security risk assessment of the communication networks of energy management and control systems (EMCS). The methodology focuses on quantifying the security extent in each control step; in order to value the security vulnerability variables derived by the protection analysis model, an MCDM strategy incorporated as a TOPSIS is presented. Ultimately, the example of six communication networks of a power management system is modelled to conduct the security evaluation. The outcome validates the utility of the security evaluation.
Secondary Motion of Non-Spherical Particles in Gas Solid Flows
Authors: Ates Cihan , Arweiler Joel , Hadad Habeb , Koch Rainer , Bauer Hans-Jörg
Published: May 2023

Objective of this study is to investigate the effect of secondary motion of particles in multiphase gas-solid flows parametrically and test the relative impacts of particle shape and orientation information on particle distribution. For that purpose, predictive accuracies of simplified drag coefficient models are assessed for the conditions relevant to a wood recovery plant operating at dilute flow regime. After demonstrating the strong impact of the shape and orientation information on the force balance for single particles, we compared the steady state Eulerian-Lagrangian simulation results for particle volume fractions, residence times and particle diameter distributions within the chamber for different (i) superficial gas velocities (5 m/s, 7.5 m/s), (ii) orientation tendencies and (iii) particle shapes. Transient simulations are performed until the system reaches steady state conditions by monitoring the mass flow rates of the particulate phases leaving the chamber. The secondary motion of non-spherical particles is represented by stochastic sampling from the available experimental data. Analysis of the force balance on single particles revealed log-scale variations if the orientation of the particles with respect to flow fluctuates. Variations in the single particle force balances are found to be still visible in the CFD analysis, where the secondary motion of particles drastically changed the particle distribution in the chamber. The native non-spherical model which only accounts for the shape correction was found to over-predict the entrainment, leading to a significantly different particle volume fraction and diameter distributions. Spherical particle assumption also caused significant errors in the particle distribution, which increases as aspect ratio of the cylindrical particle diverges from one. Results show that particle orientation statistics are extremely important to capture the particle mixing and segregation patterns at dilute regime, which cannot be captured with such simplifying assumptions.
Diaconal Church Initiatives and Social/Public Welfare in Postwar Japan: A Descriptive Overview
Authors: Van der Watt Stéphan
Published: May 2023

This article reflects on post-WWII developments and the current state of church-related diaconal initiatives in Japan. Pioneering Christians have made significant contributions to the development of social welfare since the Meiji Era (1868–1912). Despite still being a radical minority of around only 1 percent of Japan’s population, the nationwide network of Japanese Christian churches, educational institutions, and social welfare organizations makes Christianity’s presence felt on a much wider scale. With its focus on postwar efforts, this article gives a brief overview that ranges from education to social reform and medical care, all of which were traditionally incorporated under the notion of “Christian Social Welfare” (Kirisutokyō Shakai Fukushi). The research integrates Japanese and English sources in a methodical, rigorous literature study in response to the following main question: Why is there a complicated relationship in postwar Japan between church practices defined as diakonia and the work of Christian-based social welfare organizations? This article discovers how diakonia as a theological concept is re-orientating the core identity and mission of churches in Japan. A case study from the Reformed Church of Japan’s diaconal activities is presented to highlight the conclusion that a complex relationship remains between social welfare organizations and wider church practices enacted under the rubric of diakonia.
Authoritarian Use of Religion to Delegitimize and Securitize the Opposition
Authors: Yilmaz Ihsan , Demir Mustafa , Shipoli Erdoan
Published: May 2023

This article examines the use of religion by an authoritarian ruling party to delegitimize political opposition through securitization. The case study presented is the ruling AKP in Turkey, which initially promised to desecuritize the Kurdish issue to co-opt the Kurdish opposition but eventually resorted to the demonization narratives and repressive policies of the secular Turkish state; however, in addition to labeling the Kurdish opposition as terrorists, the AKP deployed religion to legitimize its repressive policies on religious grounds. The Turkish case shows that not in legitimizing (via desecuritization), but in delegitimizing opposition (via securitization) religion has been the main tool deployed by the ruling party. This finding needs to be tested in other contexts and cases. Additionally, since this paper only focuses on the narrative of the AKP’s religious delegitimization, further research is needed to measure its efficacy and impact.
Intersectional Differences in Health Care Outcomes among Patients with Musculoskeletal Disorders in Germany
Authors: Brzoska Patrick , Annac Kübra , Yilmaz-Aslan Yüce
Published: May 2023

In all regions of the world, musculoskeletal disorders are a significant contributor to the burden of chronic illnesses. The effectiveness of treatments, such as rehabilitation, may vary intersectionally across demographic and other categories. The present study examines this intersectionality with respect to a lack of improvement in health conditions after rehabilitation of patients in Germany. Routine data from 298,617 patients aged 18–65 years residing in Germany who received rehabilitation because of arthropathies, dorsopathies, or soft tissue disorders during 2006–2016 were included in the analysis. Odds of the outcome were compared across demographic groups and across diagnostic sub-groups by means of multivariable logistic regression. Interaction terms were included to examine intersectional differences across these groups and over time. Women were more likely than men to have an impairment despite treatment (adjusted odds ratio [aOR] = 1.11; 95%-CI = 1.08, 1.13). In addition, patients in semi-skilled/unskilled employment were at higher odds of a poor outcome compared to patients in skilled positions (aOR = 1.13; 95%-CI = 1.10–1.17). Nationality also affected health care outcomes, with Turkish nationals and nationals from a Yugoslav successor state having higher odds of a poor outcome than Germans (aOR = 1.56; 95%-CI = 1.45–1.67 and aOR = 1.52; 95%-CI = 1.41–1.65, respectively). The findings highlight the importance of an intersectional perspective in health research and practice and can support the development of strategies and measures that aim to reduce disparities in health care.
Economic Activities and Management Issues for the Environment: An Environmental Kuznets Curve (EKC) and STIRPAT Analysis in Turkey
Authors: Ojaghlou Mortaza , Ugurlu Erginbay , Kadłubek Marta , Thalassinos Eleftherios
Published: May 2023

The emission of air pollutants from energy production and consumption is a major cause of environmental problems. In addition, urbanisation and CO2 emissions have become major environmental concerns that are closely related to climate change and sustainable economic growth. The purpose of this paper is to investigate the long-run relationship among CO2 emissions, energy consumption, economic activities, and management issues for Turkey for the period between 1980 and 2021. The STIRPAT hypothesis and the environmental Kuznets curve (EKC) hypothesis were employed by using dynamic conditional correlation (DCC) and ARDL bound methodologies for these goals. The findings indicate that there is a long-run relationship between variables of the STIRPAT model. The coefficient of economic expansion and energy consumption affected CO2 emissions positively, which means that energy consumption and the expansion of economic activity have significant effects on environmental degradation. Those results are also confirmed by the environmental Kuznets curve (EKC) model. In addition, the N-shaped environmental Kuznets curve (EKC) is developed for Turkey. The DCC model also shows that economic growth increases CO2 emissions significantly, and energy productivity can be considered for decreasing CO2 emissions.
A Deep Learning-Based Innovative Technique for Phishing Detection in Modern Security with Uniform Resource Locators
Authors: Aldakheel Eman Abdullah , Zakariah Mohammed , Gashgari Ghada Abdalaziz , Almarshad Fahdah A. , Alzahrani Abdullah I. A.
Published: May 2023

Organizations and individuals worldwide are becoming increasingly vulnerable to cyberattacks as phishing continues to grow and the number of phishing websites grows. As a result, improved cyber defense necessitates more effective phishing detection (PD). In this paper, we introduce a novel method for detecting phishing sites with high accuracy. Our approach utilizes a Convolution Neural Network (CNN)-based model for precise classification that effectively distinguishes legitimate websites from phishing websites. We evaluate the performance of our model on the PhishTank dataset, which is a widely used dataset for detecting phishing websites based solely on Uniform Resource Locators (URL) features. Our approach presents a unique contribution to the field of phishing detection by achieving high accuracy rates and outperforming previous state-of-the-art models. Experiment results revealed that our proposed method performs well in terms of accuracy and its false-positive rate. We created a real data set by crawling 10,000 phishing URLs from PhishTank and 10,000 legitimate websites and then ran experiments using standard evaluation metrics on the data sets. This approach is founded on integrated and deep learning (DL). The CNN-based model can distinguish phishing websites from legitimate websites with a high degree of accuracy. When binary-categorical loss and the Adam optimizer are used, the accuracy of the k-nearest neighbors (KNN), Natural Language Processing (NLP), Recurrent Neural Network (RNN), and Random Forest (RF) models is 87%, 97.98%, 97.4% and 94.26%, respectively, in contrast to previous publications. Our model outperformed previous works due to several factors, including the use of more layers and larger training sizes, and the extraction of additional features from the PhishTank dataset. Specifically, our proposed model comprises seven layers, starting with the input layer and progressing to the seventh, which incorporates a layer with pooling, convolutional, linear 1 and 2, and linear six layers as the output layers. These design choices contribute to the high accuracy of our model, which achieved a 98.77% accuracy rate.
Optimizing Battery Charging Using Neural Networks in the Presence of Unknown States and Parameters
Authors: Pozzi Andrea , Barbierato Enrico , Toti Daniele
Published: May 2023

This work investigates the effectiveness of deep neural networks within the realm of battery charging. This is done by introducing an innovative control methodology that not only ensures safety and optimizes the charging current, but also substantially reduces the computational complexity with respect to traditional model-based approaches. In addition to their high computational costs, model-based approaches are also hindered by their need to accurately know the model parameters and the internal states of the battery, which are typically unmeasurable in a realistic scenario. In this regard, the deep learning-based methodology described in this work was been applied for the first time to the best of the authors’ knowledge, to scenarios where the battery’s internal states cannot be measured and an estimate of the battery’s parameters is unavailable. The reported results from the statistical validation of such a methodology underline the efficacy of this approach in approximating the optimal charging policy.
Magnetic Particle Spectroscopy for Point-of-Care: A Review on Recent Advances
Authors: Yari Parsa , Rezaei Bahareh , Dey Clifton , Chugh Vinit Kumar , Veerla Naga Venkata Ravi Kumar , Wang Jian-Ping , Wu Kai
Published: May 2023

Since its first report in 2006, magnetic particle spectroscopy (MPS)-based biosensors have flourished over the past decade. Currently, MPS are used for a wide range of applications, such as disease diagnosis, foodborne pathogen detection, etc. In this work, different MPS platforms, such as dual-frequency and mono-frequency driving field designs, were reviewed. MPS combined with multi-functional magnetic nanoparticles (MNPs) have been extensively reported as a versatile platform for the detection of a long list of biomarkers. The surface-functionalized MNPs serve as nanoprobes that specifically bind and label target analytes from liquid samples. Herein, an analysis of the theories and mechanisms that underlie different MPS platforms, which enable the implementation of bioassays based on either volume or surface, was carried out. Furthermore, this review draws attention to some significant MPS platform applications in the biomedical and biological fields. In recent years, different kinds of MPS point-of-care (POC) devices have been reported independently by several groups in the world. Due to the high detection sensitivity, simple assay procedures and low cost per run, the MPS POC devices are expected to become more widespread in the future. In addition, the growth of telemedicine and remote monitoring has created a greater demand for POC devices, as patients are able to receive health assessments and obtain results from the comfort of their own homes. At the end of this review, we comment on the opportunities and challenges for POC devices as well as MPS devices regarding the intensely growing demand for rapid, affordable, high-sensitivity and user-friendly devices.
Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints
Authors: Wang Peng , Ma Hongwei , Zhang Ye , Cao Xiangang , Wu Xudong , Wei Xiaorong , Zhou Wenjian
Published: May 2023

Aiming at the problems of grab failure and manipulator damage, this paper proposes a dynamic gangue trajectory planning method for the manipulator synchronous tracking under multi-constraint conditions. The main reason for the impact load is that there is a speed difference between the end of the manipulator and the target when the manipulator grabs the target. In this method, the mathematical model of seven-segment manipulator trajectory planning is constructed first. The mathematical model of synchronous tracking of dynamic targets based on a time-minimum manipulator is constructed by taking the robot’s acceleration, speed, and synchronization as constraints. The model transforms the multi-constraint-solving problem into a single-objective-solving problem. Finally, the particle swarm optimization algorithm is used to solve the model. The calculation results are put into the trajectory planning model of the manipulator to obtain the synchronous tracking trajectory of the manipulator. Simulation and experiments show that each joint of the robot’s arm can synchronously track dynamic targets within the constraint range. This method can ensure the synchronization of the position, speed, and acceleration of the moving target and the target after tracking. The average position error is 2.1 mm, and the average speed error is 7.4 mm/s. The robot has a high tracking accuracy, which further improves the robot’s grasping stability and success rate.
An Unmanned Surface Vehicle (USV): Development of an Autonomous Boat with a Sensor Integration System for Bathymetric Surveys
Authors: Sotelo-Torres Fernando , Alvarez Laura V. , Roberts Robert C.
Published: May 2023

A reliable yet economical unmanned surface vehicle (USV) has been developed for the bathymetric surveying of lakes. The system combines an autonomous navigation framework, environmental sensors, and a multibeam echosounder to collect submerged topography, temperature, and wind speed and monitor the vehicle’s status during prescribed path-planning missions. The main objective of this research is to provide a methodological framework to build an autonomous boat with independent decision-making, efficient control, and long-range navigation capabilities. Integration of sensors with navigation control enabled the automatization of position, orientation, and velocity. A solar power integration was also tested to control the duration of the autonomous missions. The results of the solar power compared favorably with those of the standard LiPO battery system. Extended and autonomous missions were achieved with the developed platform, which can also evaluate the danger level, weather circumstances, and energy consumption through real-time data analysis. With all the incorporated sensors and controls, this USV can make self-governing decisions and improve its safety. A technical evaluation of the proposed vehicle was conducted as a measurable metric of the reliability and robustness of the prototype. Overall, a reliable, economic, and self-powered autonomous system has been designed and built to retrieve bathymetric surveys as a first step to developing intelligent reconnaissance systems that combine field robotics with machine learning to make decisions and adapt to unknown environments.
Environmental Stability Design of the Aerial Mapping Camera Based on Multi-Dimensional Compound Structure
Authors: Yang Hong , Yuan Guoqin , Pan Jie , Zhou DeYun
Published: May 2023

Environmental stability technology plays an important role in improving the adaptive range, image resolution and ensuring the stability of geometric parameters of aerial mapping camera. Traditional environmental stability methods directly implement active and passive thermal design to optical systems, which is easy to lead to radial temperature difference of optical components, and cannot eliminate the influence of pressure change. To solve the above problem, a method of environment stability design based on multi-dimensional structure is proposed. Firstly, the aerial mapping camera is designed as imaging system component (core) and sealing cylinder (periphery), and a sealed air insulation sandwich is formed between the two parts to realize the sealing design. A thermal interface is reserved outside the seal to avoid the radial thermal stress caused by direct heating of the optical parts, and a multi-dimensional Environmental stability structure is formed. Secondly, the core and the external thermal environment of aerial mapping camera in complex aviation environment are modeled and theoretically analyzed. Finally, the effectiveness and stability of the multi-dimensional structure method is verified by the thermal simulation and the flight. The results show that the thermal control power is 240 W, the thermal gradient of the optical system is less than 5 °C, the radial temperature difference is less than 0.5 °C. High quality image and ground measurement accuracy are obtained. Compared with tradition thermal control methods, the proposed method has the advantages of accuracy and low power consumption, which can effectively reduce the power consumption and difficulty of the thermal control.
The Validity and Reliability of Self-Reported Adherence to Using Offloading Treatment in People with Diabetes-Related Foot Ulcers
Authors: Ababneh Anas , Finlayson Kathleen , Edwards Helen , Armstrong David G. , Najafi Bijan , van Netten Jaap J. , Lazzarini Peter A.
Published: May 2023

Adherence to using offloading treatment is crucial to healing diabetes-related foot ulcers (DFUs). Offloading adherence is recommended to be measured using objective monitors. However, self-reported adherence is commonly used and has unknown validity and reliability. This study aimed to assess the validity and reliability of self-reported adherence to using removable cast walker (RCW) offloading treatment among people with DFUs. Fifty-three participants with DFUs using RCWs were included. Each participant self-reported their percentage adherence to using their RCW of total daily steps. Participants also had adherence objectively measured using dual activity monitors. After one week, a subset of 19 participants again self-reported their percentage adherence to investigate test–retest reliability. Validity was tested using Pearson’s r and Bland–Altman tests, and reliability using Cohen’s kappa. Median (IQR) self-reported adherence was greater than objectively measured adherence (90% (60–100) vs. 35% (19–47), p < 0.01). There was fair agreement (r = 0.46; p < 0.01) and large 95% limits of agreement with significant proportional bias (β = 0.46, p < 0.01) for validity, and minimal agreement for test–retest reliability (K = 0.36; p < 0.01). The validity and reliability of self-reported offloading adherence in people with DFU are fair at best. People with DFU significantly overestimate their offloading adherence. Clinicians and researchers should instead use objective adherence measures.
HPnet: Hybrid Parallel Network for Human Pose Estimation
Authors: Li Haoran , Yao Hongxun , Hou Yuxin
Published: May 2023

Hybrid models which combine the convolution and transformer model achieve impressive performance on human pose estimation. However, the existing hybrid models on human pose estimation, which typically stack self-attention modules after convolution, are prone to mutual conflict. The mutual conflict enforces one type of module to dominate over these hybrid sequential models. Consequently, the performance of higher-precision keypoints localization is not consistent with overall performance. To alleviate this mutual conflict, we developed a hybrid parallel network by parallelizing the self-attention modules and the convolution modules, which conduce to leverage the complementary capabilities effectively. The parallel network ensures that the self-attention branch tends to model the long-range dependency to enhance the semantic representation, whereas the local sensitivity of the convolution branch contributes to high-precision localization simultaneously. To further mitigate the conflict, we proposed a cross-branches attention module to gate the features generated by both branches along the channel dimension. The hybrid parallel network achieves 75.6% and 75.4%AP on COCO validation and test-dev sets and achieves consistent performance on both higher-precision localization and overall performance. The experiments show that our hybrid parallel network is on par with the state-of-the-art human pose estimation models.
Context Recognition Algorithms for Energy-Efficient Freezing-of-Gait Detection in Parkinson’s Disease
Authors: Borzì Luigi , Sigcha Luis , Olmo Gabriella
Published: May 2023

Freezing of gait (FoG) is a disabling clinical phenomenon of Parkinson’s disease (PD) characterized by the inability to move the feet forward despite the intention to walk. It is one of the most troublesome symptoms of PD, leading to an increased risk of falls and reduced quality of life. The combination of wearable inertial sensors and machine learning (ML) algorithms represents a feasible solution to monitor FoG in real-world scenarios. However, traditional FoG detection algorithms process all data indiscriminately without considering the context of the activity during which FoG occurs. This study aimed to develop a lightweight, context-aware algorithm that can activate FoG detection systems only under certain circumstances, thus reducing the computational burden. Several approaches were implemented, including ML and deep learning (DL) gait recognition methods, as well as a single-threshold method based on acceleration magnitude. To train and evaluate the context algorithms, data from a single inertial sensor were extracted using three different datasets encompassing a total of eighty-one PD patients. Sensitivity and specificity for gait recognition ranged from 0.95 to 0.96 and 0.80 to 0.93, respectively, with the one-dimensional convolutional neural network providing the best results. The threshold approach performed better than ML- and DL-based methods when evaluating the effect of context awareness on FoG detection performance. Overall, context algorithms allow for discarding more than 55% of non-FoG data and less than 4% of FoG episodes. The results indicate that a context classifier can reduce the computational burden of FoG detection algorithms without significantly affecting the FoG detection rate. Thus, implementation of context awareness can present an energy-efficient solution for long-term FoG monitoring in ambulatory and free-living settings.
Case Study: Modeling a Grain Bin for Safe Entry Retrofit
Authors: Dyer Michael , Gorucu Serap , Bock Randall , Thomas Roderick , Liu Jude , Fetzer Linda
Published: May 2023

All new grain bins produced after 2018 are recommended to have anchor points capable of handling a 2000 lb loading for attachment of bin entry lifeline systems. This study aims to assess the feasibility of a safe entry anchor point retrofit by using finite element analysis (FEA). We used a grain bin owned by Penn State for 3D FEA modeling in SolidWorks. To validate the model results from the FEA model, first strain and then deflection measurements were conducted on the grain. Strain gauges were applied to the grain bin in five locations and strain values were obtained after applying static loads. The strain gauge measurements from the experimental study were compared to the strain output from the FEA simulation. The error seen was far greater than was expected. The most pertinent error source was strain gauge installation error and equipment failure. Then, the vertical roof deflection of the bin was measured using a precision phase-comparison laser while applying incremental static loads to the retrofitted rescue anchor points. The FEA model results were compared to the experimentally measured deflection results. A 3D FEA model of a grain bin was created. A high amount of error was observed in deflections between the measured and FEA modeling. The errors have resulted from the assumptions made during the model creation. However, the SolidWorks Simulation model still may be used to estimate loading scenarios in a safe and non-destructive way. Based on the research findings, the project team recommends that the suitability of any bin to safely accommodate a lifeline and anchor point system must be verified on a case-by-case basis. Evaluation by a professional structural engineer and consulting with the manufacturer are recommended. This recommendation extends to all-grain bins, including those post-2018.
Effect of Na+ on the Adsorption Behavior of Polystyrene Nanoparticles onto Coal and Quartz Surfaces
Authors: Sun Yujin , Jiang Ning , Dong Xianshu , Fan Yuping , Yang Maoqing , Xiong Peng , Chen Yuran
Published: May 2023

The recovery of difficult-to-float coal using traditional nonpolar hydrocarbon oil collectors can be challenging, particularly for low-rank or oxidized coal. Thus, there is a need for more efficient flotation agents. Nanoparticle flotation collector technology has become increasingly popular in the field of mineral processing, and the presence of various ions in the slurry can significantly affect the interaction between collectors and mineral surfaces. In this study, cationic polystyrene (PS) nanoparticles were prepared using an emulsion polymerization method, and the effects of Na+ ion concentration on the in situ adsorption and desorption processes, adsorption layer configuration, and adsorption kinetics of PS particles on amorphous carbon (coal model) and SiO2 sensors (quartz mineral model) were analyzed using the quartz crystal microbalance with dissipation (QCM-D) technique. Our results showed that the hydrophobic PS nanoparticles irreversibly adsorbed onto both amorphous carbon and SiO2 sensors under different environmental conditions, and their adsorption capacity decreased gradually with increasing Na+ ion concentration. Increasing Na+ ion concentration from 0 M to 1.0 M resulted in a 24.4% and 30.9% decrease in equilibrium adsorption capacities of PS nanoparticles onto amorphous carbon and SiO2 surfaces, respectively. The adsorption rate of PS nanoparticles onto the SiO2 surface was much greater than that on the amorphous carbon surface. The adsorption rate constant of PS nanoparticles onto SiO2 surfaces was 0.782 at 0.1 M Na+ ion concentration, while its adsorption rate constant onto amorphous carbon surfaces was only 0.060. Moreover, the adsorption process was found to be more in line with the quasi-primary kinetic model. These findings suggest that PS nanoparticles may serve as promising flotation collectors for the recovery of difficult-to-float coal, and highlight the importance of considering the effect of dissolved ions on the adsorption properties of flotation collectors.
Contextual Factors in Ethnic-Racial Socialization in White Families in the United States
Authors: Nieri Tanya , Huft Justin
Published: May 2023

Recent demographic shifts and sociopolitical events in the United States have led to a racial reckoning in which white people are engaging with issues of race and racism in new ways. This study addressed the need for research to better understand contextual factors in ethnic-racial socialization (ERS)—strategies in white families to teach children about their own and other people’s ethnicity or race. It examined the relation of neighborhood, school, and social network ethnic-racial composition and U.S. region of residence to participants’ perceptions of ethnic-racial socialization by parents. It employed a large, national survey sample of white young adults reporting on their ERS while growing up and a comprehensive set of ERS strategies. We found that the ethnic-racial composition of the family’s social network, but not the neighborhood or school, was related to exposure to ERS: the whiter the network, the less frequent the socialization, particularly antiracism socialization and exposure to diversity. We also found that Southern residents were more likely than residents in the West and Midwest to be exposed to the strategies of preparation for bias, mainstream socialization, and silent racial socialization. The findings show that these two contextual factors relate to both the frequency and content of the ERS a white child receives.
Productivity and Impact of Sustainable Development Goals (SDGs)-Related Academic Research: A Bibliometric Analysis
Authors: Alfirević Nikša , Malešević Perović Lena , Mihaljević Kosor Maja
Published: May 2023

In this paper, we conduct a bibliometric analysis of the global research related to the UN Sustainable Development Goals (SDGs) and the United Nations sustainability agenda. Our analysis builds upon the Elsevier Scopus-indexed scientific outputs since all those are classified for SDG relationships at indexing. We follow the recently published research protocol and use the Elsevier Scopus engine and the SciVal bibliometric reporting and benchmarking tool to analyze the productivity and impact of the global SDG-related research in the 2017–2022 period. We report on the most influential authors and publication outlets for SDG-related research, focusing on the collaboration patterns and their relationship to research productivity and impact. We also use keyword analysis and science mapping to describe the intellectual structure of the SDG research and its implications, which could be interpreted in terms of the “bandwagon effect”.
A Review of Antibiotics, Antibiotic Resistant Bacteria, and Resistance Genes in Aquaculture: Occurrence, Contamination, and Transmission
Authors: Yuan Xia , Lv Ziqing , Zhang Zeyu , Han Yu , Liu Zhiquan , Zhang Hangjun
Published: May 2023

Antibiotics are commonly used to prevent and control diseases in aquaculture. However, long-term/overuse of antibiotics not only leaves residues but results in the development of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs). Antibiotics, ARB, and ARGs are widespread in aquaculture ecosystems. However, their impacts and interaction mechanisms in biotic and abiotic media remain to be clarified. In this paper, we summarized the detection methods, present status, and transfer mechanisms of antibiotics, ARB, and ARGs in water, sediment, and aquaculture organisms. Currently, the dominant methods of detecting antibiotics, ARB, and ARGs are UPLC−MS/MS, 16S rRNA sequencing, and metagenomics, respectively. Tetracyclines, macrolides, fluoroquinolones, and sulfonamides are most frequently detected in aquaculture. Generally, antibiotic concentrations and ARG abundance in sediment are much higher than those in water. Yet, no obvious patterns in the category of antibiotics or ARB are present in organisms or the environment. The key mechanisms of resistance to antibiotics in bacteria include reducing the cell membrane permeability, enhancing antibiotic efflux, and structural changes in antibiotic target proteins. Moreover, horizontal transfer is a major pathway for ARGs transfer, including conjugation, transformation, transduction, and vesiculation. Identifying, quantifying, and summarizing the interactions and transmission mechanisms of antibiotics, ARGs, and ARB would provide useful information for future disease diagnosis and scientific management in aquaculture.
Occurrence and Distribution of Antibiotics in a Tropical Mariculture Area of Hainan, China: Implications for Risk Assessment and Management
Authors: Qin Yongqiang , Ren Xiaoyü , Ju Hanye , Zhang Yankun , Liu Jin , Zhang Jiliang , Diao Xiaoping
Published: May 2023

With the rapid global demand for mariculture products in recent years, the use of antibiotics has increased intensively in the mariculture area. Current research on antibiotic residues in mariculture environments is limited, and less information is available on the presence of antibiotics in tropical waters, limiting a comprehensive understanding of their environmental presence and risk. Therefore, this study investigated the environmental occurrence and distribution of 50 antibiotics in the near-shore aquaculture waters of Fengjia Bay. A total of 21 antibiotics were detected in 12 sampling sites, including 11 quinolones, 5 sulfonamides, 4 tetracyclines, and 1 chloramphenicol; the quinolones pyrimethamine (PIP), delafloxacin (DAN), flurofloxacin (FLE), ciprofloxacin (CIP), norfloxacin (NOR), pefloxacin (PEF), enrofloxacin (ENO), and minocycline (MNO) of the tetracycline class were detected in all sampling points. The total antibiotic residue concentrations in the study area ranged from 153.6 to 1550.8 ng/L, the tetracycline antibiotics were detected in the range of 10 to 1344.7 ng/L, and the chloramphenicol antibiotics were detected in the range of 0 to 106.9 ng/L. The detected concentrations of quinolones ranged from 81.3 to 136.1 ng/L, and the residual concentrations of sulfonamide antibiotics ranged from 0 to 313.7 ng/L. The correlation analysis with environmental factors revealed that pH, temperature, conductivity, salinity, NH3−-N, and total phosphorus had a strong correlation with antibiotics. Based on PCA analysis, the main sources of antibiotic pollution in the area were determined to be the discharge of farming wastewater and domestic sewage. The ecological risk assessment indicated that the residual antibiotics in the water environment of the near-shore waters of Fengjiawan had certain risks to the ecosystem. Among them, CIP, NOR, sulfamethoxazole (TMP), ofloxacin (OFL), enrofloxacin (ENO), sulfamethoxazole (SMX), and FLE showed medium to high risk. Therefore, it is recommended to regulate the use of these antibiotics and the discharge and treatment of culturing wastewater, and measures should be taken to reduce the environmental pollution caused by antibiotics and to monitor the long-term ecological risk of antibiotics in the region. Overall, our results provide an important reference for understanding the distribution and ecological risk of antibiotics in Fengjiawan.
The Impact of Flooding on Snail Spread: The Case of Endemic Schistosomiasis Areas in Jiangxi Province, China
Authors: Lv Shang-Biao , He Ting-Ting , Hu Fei , Li Yi-Feng , Yuan Min , Xie Jing-Zi , Li Zong-Guang , Li Shi-Zhu , Lin Dan-Dan
Published: May 2023

Flooding is the main natural factor in snail diffusion, and it has a negative impact on schistosomiasis transmission. There are few studies on the spread and migration of snails following a flood; therefore, we aimed to investigate the influence of flooding on snail diffusion and explore the characteristics and laws of snail diffusion in Jiangxi Province. By using a retrospective survey and cross-sectional survey, the data on snail spreading in Jiangxi Province from 2017 to 2021 were collected. The distribution, nature, and area of snail spread were systematically analyzed in combination with the hydrological situation, types of region, and types of flood. From 2017 to 2021, a total of 120 snail-spread environments were found, including in 92 hilly areas and in 28 lake areas. The areas caused by flood and by other means numbered 6 and 114, respectively. The proportions of recurrence, expansion, and first-time occurrences were 43.42%, 38.16%, and 18.42%, respectively, and the 14 new snail environments were only distributed in the hilly areas. With the exception of 2018, the ratio of snail-spread areas in the hilly region was higher than that in lake region in other years. The average density of live snails was 0.0184–1.6617 no./0.1 m2 and 0.0028–0.2182 no./0.1 m2 in the hilly region. Among the 114 environments affected by floods, 86 consisted of hilly environments, including 66 spreading environments affected by rainstorm floods, and 20 rainstorm debris flow environments. There were 28 lake areas, of which 10 were in the Jiangxi section of Yangtze River and were affected by rainstorm floods. Snail spread following flooding has a certain ‘lag effect,’ and = simple annual changes in hydrological characteristics have little effect on the diffusion of snails or on their density = in the affected environment, but it is more closely related to local floods. The hilly environments are more susceptible to floods than the lake region, and the risk of snail spread is much higher in the hilly than in the lake region.