bluuebunny/crossref_metadata_2025 huggingface dataset:
Image Semantic Segmentation Fusion of Edge Detection and AFF Attention Mechanism
Authors: Jiao Yijie , Wang Xiaohua , Wang Wenjie , Li Shuang
Published: November 2022

Deep learning has been widely used in various fields because of its accuracy and efficiency. At present, the improvement of image semantic segmentation accuracy has become the area of most concern. In terms of increasing accuracy, improved semantic segmentation models have attracted more attention. In this paper, a hybrid model is proposed to solve the problems of edge splitting and small objects disappearing from complex scene images. The hybrid model consists of three parts: (1) an improved HED network, (2) an improved PSP-Net, (3) an AFF attention mechanism. Continuous edges can be obtained by combining the improved HED network with an improved PSP-Net. The AFF attention mechanism can improve the segmentation effect of small target objects by enhancing its response recognition ability for specific semantic scenes. The experiments were carried out on Cityspaces, SIFT Flow, NYU-V2 and CamVid datasets, and the experimental results show that the segmentation accuracy of our method is improved by 2% for small target objects, and by 3% for scenes with complex object edges.
Visual-Predictive Data Analysis Approach for the Academic Performance of Students from a Peruvian University
Authors: Orrego Granados David , Ugalde Jonathan , Salas Rodrigo , Torres Romina , López-Gonzales Javier Linkolk
Published: November 2022

The academic success of university students is a problem that depends in a multi-factorial way on the aspects related to the student and the career itself. A problem with this level of complexity needs to be faced with integral approaches, which involves the complement of numerical quantitative analysis with other types of analysis. This study uses a novel visual-predictive data analysis approach to obtain relevant information regarding the academic performance of students from a Peruvian university. This approach joins together domain understanding and data-visualization analysis, with the construction of machine learning models in order to provide a visual-predictive model of the students’ academic success. Specifically, a trained XGBoost Machine Learning model achieved a performance of up to 91.5% Accuracy. The results obtained alongside a visual data analysis allow us to identify the relevant variables associated with the students’ academic performances. In this study, this novel approach was found to be a valuable tool for developing and targeting policies to support students with lower academic performance or to stimulate advanced students. Moreover, we were able to give some insight into the academic situation of the different careers of the university.
Research on Thermal Imaging Usage as a Method for Detecting Bacillus subtilis Bacteria in Mortadella
Authors: Lipińska Edyta , Pobiega Katarzyna , Piwowarek Kamil , Hać-Szymańczuk Elżbieta
Published: November 2022

Meat and meat products are important sources of valuable proteins and other nutrients, but they are also a conducive environment for microorganisms’ growth and can easily corrupt. In order to ensure the safety and quality of these products throughout its entire shelf-life, reliable microbial contamination assessment techniques must be used. Despite their effectiveness, traditional diagnostics methods are expensive and time consuming. Therefore, new timesaving, reliable techniques are searched for. Infrared thermography could be a good alternative method in this area. As a quick technique to detect microorganisms, it can overcome the limitations of traditional microbiological food-quality assessment methods. It has numerous advantages, such as the possibility of taking immediate temperature measurements and short processing times for obtaining a thermal image, non-contact and non-destructive measurements, and, unlike other methods, real-time measurement monitoring. Real-time monitoring is particularly important for modern production systems. The purpose of this research study is to develop a methodology for microbiological quality control of mortadella inoculated with Bacillus subtilis ATCC 6633 bacteria using a thermal imaging camera with an uncooled microbolometric detector. It was found that the thermal imaging measurements used in this research study enabled the distinction of contaminated samples (min. 106 CFU/g) from sterile samples. The tests should only record the temperature of the samples during the first 25 s after previously performing activations at −18 °C ± 1 °C for 60 s. This is where differences between the samples are most pronounced. Estimating the trend line of the sample’s cooling process is advisable.
Bayesian and Non-Bayesian Inference for Unit-Exponentiated Half-Logistic Distribution with Data Analysis
Authors: Hassan Amal S. , Fayomi Aisha , Algarni Ali , Almetwally Ehab M.
Published: November 2022

Unit distributions are typically used in probability theory and statistics to illustrate useful quantities with values between zero and one. In this paper, we investigated an appropriate transformation to propose the unit-exponentiated half-logistic distribution (UEHLD), which is also beneficial for modelling data on the unit interval. This distribution’s mathematical features are supplied, including moments, probability-weighted moments, incomplete moments, various entropy measures, and stress–strength reliability. Using well-known estimation techniques such as the maximum likelihood, maximum product of spacing, and Bayesian inference, the estimators of the parameters relevant to the proposed distribution were determined. A comprehensive simulation analysis is provided to examine the performance of parameter estimation approaches on finite samples. The proposed distribution was realistically applied to data on economic growth and data on the tensile strength of polyester fibers to provide an explanation. Furthermore, the analysis of COVID-19 data from Britain as a medical statistical dataset is provided. The experimental results demonstrate that the suggested UEHLD yields a better comparison with some new unit distributions, as well as other unbounded distributions.
EEG-Based Emotion Recognition Using Convolutional Recurrent Neural Network with Multi-Head Self-Attention
Authors: Hu Zhangfang , Chen Libujie , Luo Yuan , Zhou Jingfan
Published: November 2022

In recent years, deep learning has been widely used in emotion recognition, but the models and algorithms in practical applications still have much room for improvement. With the development of graph convolutional neural networks, new ideas for emotional recognition based on EEG have arisen. In this paper, we propose a novel deep learning model-based emotion recognition method. First, the EEG signal is spatially filtered by using the common spatial pattern (CSP), and the filtered signal is converted into a time–frequency map by continuous wavelet transform (CWT). This is used as the input data of the network; then the feature extraction and classification are performed by the deep learning model. We called this model CNN-BiLSTM-MHSA, which consists of a convolutional neural network (CNN), bi-directional long and short-term memory network (BiLSTM), and multi-head self-attention (MHSA). This network is capable of learning the time series and spatial information of EEG emotion signals in depth, smoothing EEG signals and extracting deep features with CNN, learning emotion information of future and past time series with BiLSTM, and improving recognition accuracy with MHSA by reassigning weights to emotion features. Finally, we conducted experiments on the DEAP dataset for sentiment classification, and the experimental results showed that the method has better results than the existing classification. The accuracy of high and low valence, arousal, dominance, and liking state recognition is 98.10%, and the accuracy of four classifications of high and low valence-arousal recognition is 89.33%.
Modelling a Novel Scheme of Mining Geothermal Energy from Hot Dry Rocks
Authors: Li Hong , Ji Kun , Tao Ye , Tang Chun’an
Published: November 2022

On the basis of a conceptual model for an Excavation based Enhanced Geothermal System (EGS-E), which proposed to extract heat from Hot Dry Rock at depth through dominantly adopting shaft, roadways, and caved rock failure techniques but not depending on either wellbore drilling or fracturing stimulation, a novel extensive version of heat extraction is proposed in this paper. Considering its mechanical stability issues, the new scheme contains two fields apart away: the ones are near-field by piping flow to touch the tunnel wall; the others are far-field through filling and driving fluid within the voids of collapsed rock. The former is represented as a tunnel unit being installed hollow linear, which can extract and produce heat precisely according to structural design and accurate operative prediction. The latter is represented as interconnective fissures being induced by stope excavation due to gravitational weight and unloading of a deep-buried squeeze. The EGS-E uses a two-stage heat exchange system of “fluid-rock” and “fluid-fluid.” Then, a 3D transient thermal-hydraulic model is established to demonstrate the heat extraction performance. The temperature field and accumulated heat energy are investigated. The modeling work provides a tentative workflow to simulate an EGS-E system and, most probably for the first time, demonstrated that the deep underground Hot Dry Rock heat mining turns out to be preliminarily studied in a quantitative way.
What Is the Internal Pressure That Initiates Damage in Cementitious Materials during Freezing and Thawing? A Micromechanical Analysis
Authors: Timothy Jithender J. , Haynack Alexander , Kränkel Thomas , Gehlen Christoph
Published: November 2022

Damage induced by repetitive freezing and thawing processes is one of the critical factors that affect concrete durability in cold climates. This deterioration process manifests as surface scaling and internal damage. The damage processes are governed by physicochemical mechanisms that are active across multiple scales. In this contribution, we present a novel multiscale theoretical framework for estimating the critical pressure required for microcrack initiation during freezing and thawing of cementitious mortar. Continuum micromechanics and fracture mechanics is used to model the phenomena of microcrack initiation and growth. Damage at the microscale is upscaled to the level of the specimen using multilevel homogenization. The critical pressure is estimated using poromechanics at the microscopic scale. A theoretical analysis shows that in the frozen state, the material can resist higher pressures. As a consequence, the material is more susceptible to damage during thawing. The micromechanical predictions are within the range of the predictions obtained by electrokinetic theory.
Equivalent Current Systems of Quiet Ionosphere during the 24th Solar Cycle Derived from the Geomagnetic Records in China
Authors: Zhao Xudong , He Yufei , Wu Yingyan , Li Qi
Published: November 2022

External and internal equivalent current systems of solar quiet (Sq) were obtained using the spherical harmonic analysis (SHA) method with a “mirror” technique based on geomagnetic records from 46 stations in China during 2008–2019. It is the first attempt to investigate Sq currents using so many stations in the China region for a long period. On the basis of criterion Kp ≤ 2+, geomagnetic vector data were selected to represent monthly Sq variations. After calculating the equivalent currents for each month and each Lloyd season, Sq variation was analyzed in relation to the solar cycle and season. The intensities of both external and internal Sq currents were found consistent with solar activity for the same month or season, while the positions of the current foci were evidently unaffected by solar activity. The intensities of Sq currents also exhibited primary semiannual (annual) variation in the periods of high (low) solar activity. The latitude of the internal current vortex showed evident seasonal variation in Lloyd seasons with high (low) values in the D (J) season, while the external current vortex exhibited no obvious seasonal variation. The strongest correlation between external and internal foci was found in D season, and the internal current foci usually appeared 20–40 min earlier than the external ones. Owing to the complex mechanisms behind Sq variation, some findings will need further analysis in the future.
An End-to-End Deep Learning Approach for Quantitative Microwave Breast Imaging in Real-Time Applications
Authors: Ambrosanio Michele , Franceschini Stefano , Pascazio Vito , Baselice Fabio
Published: November 2022

(1) Background: In this paper, an artificial neural network approach for effective and real-time quantitative microwave breast imaging is proposed. It proposes some numerical analyses for the optimization of the network architecture and the improvement of recovery performance and processing time in the microwave breast imaging framework, which represents a fundamental preliminary step for future diagnostic applications. (2) Methods: The methodological analysis of the proposed approach is based on two main aspects: firstly, the definition and generation of a proper database adopted for the training of the neural networks and, secondly, the design and analysis of different neural network architectures. (3) Results: The methodology was tested in noisy numerical scenarios with different values of SNR showing good robustness against noise. The results seem very promising in comparison with conventional nonlinear inverse scattering approaches from a qualitative as well as a quantitative point of view. (4) Conclusion: The use of quantitative microwave imaging and neural networks can represent a valid alternative to (or completion of) modern conventional medical imaging techniques since it is cheaper, safer, fast, and quantitative, thus suitable to assist medical decisions.
Computational Modeling of Microwave Tumor Ablation
Authors: Radmilović-Radjenović Marija , Bošković Nikola , Radjenović Branislav
Published: November 2022

Microwave ablation is recognized as a minimally invasive, fast-recovery treatment for destroying cancer cells using the heat generated by microwave energy. Despite the unquestionable benefits of microwave ablation, the interaction of the microwave applicator with the tissue may result in localized heating and damage to the surrounding tissue. The majority of the tissue damage can be removed by clarifying the conditions for their development. In addition to experimental methods, computer modeling has proven to be an effective tool for optimizing the performance of microwave ablation. Furthermore, because the thermal spread in biological tissue is difficult to measure, developing a predictive model from procedural planning to execution may have a substantial influence on patient care. The comprehension of heat transport in biological tissues plays a significant role in gaining insight into the mechanisms underlying microwave ablation. Numerical methods that enable ablation size control are required to guarantee tumor destruction and minimize damage to healthy tissues. Various values of input power and ablation time correspond to different tumor shapes ensuring the preservation of healthy tissues. The optimal conditions can be estimated by performing full three-dimensional simulations. This topical review recapitulates numerous computational studies on microwave tumor ablation. Novel areas emerging in treatment planning that exploit the advantages of numerical methods are also discussed. As an illustration, the results of the three-dimensional simulations of real liver tumors in the 3D-IRCADb-01 database are presented and analyzed. The simulation results confirm that numerical methods are very useful tools for modeling microwave tumor ablation with minimal invasiveness and collateral damage.
FGF9 Promotes Expression of HAS2 in Palatal Elevation via the Wnt/β-Catenin/TCF7L2 Pathway
Authors: Sun Yidan , Ying Xiyu , Li Ruomei , Weng Mengjia , Shi Jiajun , Chen Zhenqi
Published: November 2022

Background: Fgf9 mutation was found in cleft palate patients. Our previous study indicated that Fgf9 promotes timely elevation of palate by regulating hyaluronic acid (HA) accumulation at embryonic day 13.5 (E13.5). HA is synthesized by hyaluronic acid synthases (HAS) isoforms 1, 2, or 3. However, how FGF9 regulates HA in palatogenesis is still unclear. Methods: Using Ddx4-Cre mice, we generated the Fgf9−/− mouse model (with exon 2 deletion). Immunohistochemistry was used to detect the location and expression of HAS2 in WT and the Fgf9−/− palate at E13.5. We also predicted the association between Fgf9 and Has2 within the developing palate by performing a bioinformatics analysis. The expression of β-catenin, HAS2, and TCF7L2 were verified by Western blotting after knockout of Fgf9. Rescue experiments were performed by ELISA in vitro. Results: Fgf9−/− mice exhibited 100% penetrance of the cleft palate. A knockout of Fgf9 confirmed that HAS2 and TCF7L2 expression was positively correlated with FGF9. TCF7L2 binds to the Has2 promoter, exhibiting the high specificity predicted by JASPAR. Additionally, increased HA expression by BML-284, TCF-dependent agonist, was blocked in Fgf9−/− palate because of the significant decline in TCF7L2 expression. Conclusions: FGF9 promotes HAS2 expression via Wnt/β-catenin/TCF7L2 pathway with TCF7L2 activating transcription of Has2 in the palate.
A Fast-Tracking-Particle-Inspired Flow-Aided Control Approach for Air Vehicles in Turbulent Flow
Authors: Yang Hengye , Bewley Gregory P. , Ferrari Silvia
Published: November 2022

Natural phenomena such as insect migration and the thermal soaring of birds in turbulent environments demonstrate animals’ abilities to exploit complex flow structures without knowledge of global velocity profiles. Similar energy-harvesting features can be observed in other natural phenomena such as particle transport in turbulent fluids. This paper presents a new feedback control approach inspired by experimental studies on particle transport that have recently illuminated particles’ ability to traverse homogeneous turbulence through the so-called fast-tracking effect. While in nature fast tracking is observed only in particles with inertial characteristics that match the flow parameters, the new fast-tracking feedback control approach presented in this paper employs available propulsion and actuation to allow the vehicle to respond to the surrounding flow in the same manner as ideal fast-tracking particles would. The resulting fast-tracking closed-loop controlled vehicle is then able to leverage homogeneous turbulent flow structures, such as sweeping eddies, to reduce travel time and energy consumption. The fast-tracking approach is shown to significantly outperform existing optimal control solutions, such as linear quadratic regulator and bang-bang control, and to be robust to changes in the vehicle characteristics and/or turbulent flow parameters.
Hollow-Channel Paper Analytical Devices Supported Biofuel Cell-Based Self-Powered Molecularly Imprinted Polymer Sensor for Pesticide Detection
Authors: Wang Yanhu , Shi Huihui , Sun Jiantao , Xu Jianjian , Yang Mengchun , Yu Jinghua
Published: November 2022

Herein, a paper-based glucose/air biofuel cell (BFC) was constructed and implemented for self-powered pesticide detection. Our developed paper-based chip relies on a hollow-channel to transport fluids rather than capillarity, which reduces analysis times as well as physical absorption. The gold nanoparticles (Au NPs) and carbon nanotubes (CNTs) were adapted to modify the paper fibers to fabricate the flexible conductive paper anode/cathode electrode (Au–PAE/CNT–PCE). Molecularly imprinted polymers (MIPs) using 2,4-dichlorophenoxyacetic acid (2,4-D) as a template were synthesized on Au–PAE for signal control. In the cathode, bilirubin oxidase (BOD) was used for the oxygen reduction reaction. Based on a competitive reaction between 2,4-D and glucose-oxidase-labeled 2,4-D (GOx-2,4-D), the amount of GOx immobilized on the bioanode can be simply tailored, thus a signal-off self-powered sensing platform was achieved for 2,4-D determination. Meanwhile, the coupling of the paper supercapacitor (PS) with the paper-based chip provides a simple route for signal amplification. Combined with a portable digital multi-meter detector, the amplified signal can be sensitively readout. Through rational design of the paper analytical device, the combination of BFC and PS provides a new prototype for constructing a low-cost, simple, portable, and sensitive self-powered biosensor lab-on-paper, which could be easily expanded in the field of clinical analysis and drug delivery.
Ultrasensitive Electrochemical Detection of Butylated Hydroxy Anisole via Metalloporphyrin Covalent Organic Frameworks Possessing Variable Catalytic Active Sites
Authors: Chu Huacong , Sun Xin , Zha Xiaoqian , Khan Shifa Ullah , Wang Yang
Published: November 2022

Three novel two-dimensional metalloporphyrin COFs (MPor−COF−366, M = Fe, Mn, Cu) were fabricated by changing the metal atoms in the center of the porphyrin framework. The physicochemical characteristics of MPor−COF−366 (M = Fe, Mn, Cu) composites were fully analyzed by diverse electron microscopy and spectroscopy. Under optimal conditions, experiments on determining butylated hydroxy anisole (BHA) at FePor−COF−366/GCE were conducted using differential pulse voltammetry (DPV). It is noted that the FePor−COF−366/GCE sensor showed excellent electrocatalytic performance in the electrochemical detection of BHA, compared with MnPor−COF−366/GCE and CuPor−COF−366/GCE. A linear relationship was obtained for 0.04–1000 μM concentration of BHA, with a low detection limit of 0.015 μM. Additionally, the designed sensor was successfully employed to detect BHA in practical samples, expanding the development of COF-based composites in electrochemical applications.
Differential Effects of Chronic Methamphetamine Treatment on High-Frequency Oscillations and Responses to Acute Methamphetamine and NMDA Receptor Blockade in Conscious Mice
Authors: Hudson Matthew R. , Foreman Joshua , Rind Gil , Manning Elizabeth E. , Jones Nigel C. , van den Buuse Maarten
Published: November 2022

Dysregulation of high-frequency neuronal oscillations has been implicated in the pathophysiology of schizophrenia. Chronic methamphetamine (METH) use can induce psychosis similar to paranoid schizophrenia. The current study in mice aimed to determine the effect of chronic METH treatment on ongoing and evoked neuronal oscillations. C57BL/6 mice were treated with METH or vehicle control for three weeks and implanted with extradural recording electrodes. Two weeks after the last METH injection, mice underwent three EEG recording sessions to measure ongoing and auditory-evoked gamma and beta oscillatory power in response to an acute challenge with METH (2 mg/kg), the NMDA receptor antagonist MK-801 (0.3 mg/kg), or saline control. A separate group of mice pretreated with METH showed significantly greater locomotor hyperactivity to an acute METH challenge, confirming long-term sensitisation. Chronic METH did not affect ongoing or evoked gamma or beta power. Acute MK-801 challenge reduced ongoing beta power whereas acute METH challenge significantly increased ongoing gamma power. Both MK-801 and METH challenge suppressed evoked gamma power. Chronic METH treatment did not modulate these acute drug effects. There were minor effects of chronic METH and acute METH and MK-801 on selected components of event-related potential (ERP) waves. In conclusion, chronic METH treatment did not exert neuroplastic effects on the regulation of cortical gamma oscillations in a manner consistent with schizophrenia, despite causing behavioural sensitisation.
Acoustic Stimulation Improves Memory and Reverses the Contribution of Chronic Sleep Deprivation to Pathology in 3xTgAD Mice
Authors: Liu Shunjie , Lei Qingfeng , Liu Yunyun , Zhang Xiaofeng , Li Zhong
Published: November 2022

Objective: Acoustic stimulation during sleep is believed to enhance slow waves, which are critical to memory consolidation. However, clinical trials of acoustic stimulation have yielded mixed results concerning its effectiveness in improving human memory. A few studies have implied that acoustic stimulation ameliorates the pathology of Alzheimer’s disease (AD) in mice with normal sleep. Here, we explored the effect of acoustic stimulation on 3xTgAD mice suffering from chronic sleep deprivation, as these data may shed light on the potential use of acoustic stimulation in AD patients with insomnia. Methods: Twenty-four 8-month-old 3xTgAD mice were randomly and equally divided into three groups: the normal sleep group (S group), the sleep deprivation group (SD group), and the acoustic stimulation group (AS group). During a 14-day sleep intervention, the SD and AS groups received 6 h of sleep deprivation per day, and the AS group also received acoustic stimulation in the dark phase. Then, the mice underwent Morris water maze (MWM) tests and arterial spin labelling (ASL) magnetic resonance imaging (MRI) scans and were sacrificed for pathological evaluation. Results: The three groups showed similar stress levels. The S and AS groups exhibited better spatial memory, better brain perfusion, and milder amyloid β (Aβ) and tau pathology than the SD group, although no significant discrepancies were found between the S and AS groups. Conclusions: Acoustic stimulation may exert a protective effect in 3xTgAD mice by improving spatial memory, enhancing the blood supply of the brain, and reversing the contribution of chronic sleep deprivation to Aβ and tau pathology to mimic the effect of normal sleep patterns.
Seismic Performance of Flat Steel Plate Shear Walls with Atmospheric Corrosion
Authors: Ma Xiaoming , Hu Yi , Cheng Xinyuan , Jiang Liqiang , Li Yun , Zheng Hong
Published: November 2022

The seismic performance of four different kinds of steel plate shear walls (SPSWs) before and after corrosion are investigated in this paper, including flat steel plate shear walls (FSPSWs), SPSWs with vertical slots in the middle (VSSPSWs), SPSWs with orthogonal stiffeners (OSPSWs) and SPSWs with silts on both sides (BSPSWs). A numerical model that can be validated by existing quasi-static cyclic tests is developed by ABAQUS 6.13. The seismic performance of SPSWs under cyclic loading and atmospheric corrosion is investigated. The results show that (1) compared with FSPSWs, the ultimate shearing strength, initial stiffness, energy dissipation, and ductility of OSPSWs are significantly improved under cyclic loads when both VSSPSWs and BSPSWs are reduced in ultimate shearing strength and energy dissipation. (2) The performance of the FSPSW is most affected by atmospheric corrosion but setting stiffeners can significantly improve the hysteretic performance after corrosion. Meanwhile, the effect of the VSSPSW is better than that of the BSPSW in decreasing the ultimate shearing strength, although both decrease more tardily than that of the FSPSW. (3) The relationships between the ultimate shearing strength and corrosion time of SPSWs are fitted into four equations in this paper, which can be used in practical situations.
The Traditional Wisdom in Fire Prevention Embodied in the Layout of Ancient Villages: A Case Study of High Chair Village in Western Hunan, China
Authors: Zhang Fupeng , Shi Lei , Liu Simian , Zhang Chi , Xiang Tansheng
Published: November 2022

The purpose of this paper is to reveal the reasons for the survival of ancient villages in western Hunan in the face of a long-term high risk of fire, which has led to their heritage status. The study selected a representative ancient village in the western Hunan region, High chair village, as a case study to explain the siting and village layout. The fire risk of High chair village was investigated in terms of dwelling materials, structural forms, fire-related activities, and street dimensions. Monitoring instruments and fire dynamics simulator (FDS) were used to reveal the “survival design strategy” of village sites, layouts, and street patterns. The results revealed that the village layout of High chair Village, sheltered from the wind and gathering Qi, was conducive to the formation of a stable wind environment to reduce the risk of fire spread. Furthermore, the windspeed was weakened by the crooked streets and alleys and, in case of fire, this street environment was also conducive to slowing down the spread of fire. It is important to collect traditional knowledge of fire mitigation developed through a long history of disasters, so that mitigation methods can be applied in the development and conservation of modern traditional villages and further passed on to future generations.
A Design Methodology for the Seismic Retrofitting of Existing Frame Structures Post-Earthquake Incident Using Nonlinear Control Systems
Authors: Shmerling Assaf , Gerdts Matthias
Published: November 2022

A structural design methodology for retrofitting weakened frame systems following earthquakes is developed and presented. The design procedure refers to frame systems in their degraded strength and stiffness states and restores their dynamic performance using nonlinear control systems. The control law associated with the employed systems regards the gains between the negative state feedback and the control force, which consists of linear, nonlinear, and hysteretic portions. Structural optimization is introduced in designing the nonlinear control systems, and the controller gains are optimized using the fixed-point iteration to improve the frame system’s dynamic performance. The fixed-point iteration method relates to first-order PDE equations; hence, a new state-space formulation for weakened inelastic frame systems is developed and presented using the frame system’s lateral force equilibrium equation. The design scheme and optimization strategy differ from designing passive control systems, given that the nonlinear control system’s force consists of linear, nonlinear, and hysteretic portions. The utilization of the fixed-point iteration in the structural design area is by itself a novel application due to its robustness in addressing the gains of any type of nonlinear control system. This paper’s nonlinear control system chosen to exhibit the application is Buckling Restrained Braces (BRBs) since force consists of linear and hysteretic portions. The implementation of hysteretic control force is rare in structural control applications. In the case of BRBs, the fixed-point iteration optimizes the cross-sectional areas. Two system optimization examples of 3-story and 15-story inelastic frames are provided and described. The examples demonstrate the fixed-point iteration’s applicability and robustness in optimizing control gains of nonlinear systems and regulating the dynamic response of weakened frame structures.
Public–Private Partnerships for Higher Education Institutions in the United States
Authors: Khallaf Rana , Kang Kyubyung , Hastak Makarand , Othman Kareem
Published: November 2022

Public–private Partnerships have become a common delivery method for diverse types of projects ranging from transportation and energy infrastructure to social infrastructure. Previous research has mainly focused on PPPs for infrastructure and other non-social projects. Although PPP projects for higher education institutions share some common attributes with their traditional counterparts, they also have unique aspects such as institutional culture as well as structure of ownership and management. Hence, the objectives of this research were to (1) conduct a systematic collection and analysis of PPP projects in higher education institutions in the United States; and (2) conduct a gap analysis to provide recommendations for future projects and lessons learned from past ones. A gap analysis of the published data on higher education PPPs was undertaken, identifying 45 educational PPP projects in the United States. The main areas of study were type of project (e.g., housing, commercial, mixed use, etc.), size, and investment made. Additionally, a questionnaire survey was disseminated to experts in the field to collect data on these projects and report on them. The results showed an increasing trend in project size between 1994 and 2018 with the majority being for housing developments while a smaller percentage was for commercial and utility projects. A geographical representation shows a large number of projects clustered in the Southern and Northeastern regions of the United States. Additionally, a questionnaire survey was used to identify samples of these projects and present them as a case study. The number of PPPs is expected to rise due to funding cuts and state appropriation cuts. Finally, the proposed recommendations can also be extrapolated for other social or infrastructure projects.
A Spatially Varying Ground Motion Model with an Evolving Energy Spectrum
Authors: Qin Han , Li Luyu
Published: November 2022

Besides phase variability, amplitude variability is one of the two manifestations of the spatially varying ground motion (SVGM) in the frequency domain. Neglecting the amplitude variability of the earthquake spectra can result in an underestimation of the structural responses. Few existing amplitude variability models can be used for estimating spectra at a distance from a reference location. In this paper, a new amplitude variability model describing the evolution of the energy spectra is developed based on records of five earthquake events acquired from the SMART 1 array. The similarity between the spectra of two locations is used as a metric for measuring the spectrum changes. The energy spectra at a distance from a reference location are found to be composed of two parts, including the averaged spectra and the random variation part. In the new model, the former is estimated by the moving average of the reference spectrum, while the envelope of the latter is approximated by the wavelet approximation of the reference spectrum’s Fourier amplitude spectrum. The parameters of five models for each event and a general model for all five events are identified. Monte Carlo simulations are used for testing the models. The results validate the new model in terms of capturing the similarity changes of actual earthquakes.
Effects of Different Kinds of Defoamer on Properties of Geopolymer Mortar
Authors: Luo Yiping , Li Bowen , Wang Defa , Lv Yurong , Jiang Zhonghua , Xue Guobin
Published: November 2022

As a new type of green inorganic material, geopolymers have excellent mechanical properties, durability, and less environmental pollution. It is considered a new building material that can replace cement, but it also has some disadvantages such as high viscosity, poor fluidity, and more apparent pores after hardening. In this study, the uniaxial compressive strength test of geopolymer mortar was carried out, and the effects of alkali equivalent, alkali activator modulus, bone glue ratio, and silica fume content on the mechanical properties of geopolymer mortar were analyzed. The test results show that when the alkali equivalent is 13%, the alkali activator modulus is 1.4, the bone glue ratio is 2.0, the silicon powder content is 8%, and the metakaolin-based geopolymer mortar has higher uniaxial compressive strength. Through the comparative test of adding different kinds of defoamers and dosage, the effect of defoamers on the compressive strength, fluidity, density, and water-absorption of geopolymer mortar was further studied. The fluidity, density, and water-absorption were improved, and the uniaxial compressive strength was reduced. The formation of cementitious material in the mortar was confirmed by scanning electron microscope (SEM) observation. It was found that the pore structure and pore distribution changed with the content of different defoaming agents, and the microstructure of mortar after defoaming agent material treatment was shown. The proportion and distribution of Na, Al, and Si atoms were analyzed by energy dispersive spectroscopy (EDS). This experimental study shows that the defoamer can be an effective additive for geopolymer mortar.
Categorisation of Requirements in the Ontology-Based Framework for Employer Information Requirements (OntEIR)
Authors: Dwairi Shadan , Mahdjoubi Lamine
Published: November 2022

Employer Information Requirements (EIR) are the keystone for developing a successful Building Information Modelling (BIM) project. However, clients’ lack of skill and experience in categorising and defining these requirements often undermines the performance of a construction project and, ultimately, the ability of the finished product to meet their needs. By definition, EIR shortcomings include incomplete and inconsistent requirements and specifications, and whilst some work has been performed to try to address these, this area is still underdeveloped. This paper reports on the development of a transformative approach to the categorisation of requirements in a meaningful way, enabling effective filtering so that stakeholders can access just the information they need for the task at hand. The Ontology-based framework for Employer Information Requirements (OntEIR) seeks to provide a step change in categorisation by identifying ‘static’ and ‘dynamic’ requirements, including related types and sub-types. OntEIR has been rigorously validated by a group of BIM experts, and the results have revealed that this approach to categorisation significantly improved the elicitation and understanding of requirements.
Unpacking the “Black Box”: Understanding the Effect of Strength of Ties on Inter-Team Conflict and Project Success in Megaprojects
Authors: Zeng Hui , Cao Jiming , Fu Qun
Published: November 2022

Megaprojects have been redefined as dynamic collaboration networks, which are characterized by the strength of the ties between teams. In China, megaprojects have long been criticized for low productivity, poor project implementation processes, and inter-team confrontation. Few studies in the construction domain have explored the relationship between the strength of ties, inter-team conflict, and project success. This research aims to investigate the relationship between the strength of ties, inter-team conflict, and project success in megaprojects. Strong ties and weak ties reflect the strength of ties. Inter-team conflict is measured by task-related conflict and relationship-related conflict. A questionnaire survey was conducted on Chinese megaprojects, and 306 questionnaires were collected. The data were analyzed by a structural equation model. The results indicate that strong ties positively impact task-related conflict while negatively impacting relationship-related conflict. Weak ties positively impact inter-team conflict. Task-related conflict and relationship-related conflict have positive and negative effects on project success, respectively. The effect of the strength of the ties on a project’s success is mediated by conflict. This study adds to existing research on the strength of ties and emphasizes the significance of megaproject network governance. The results reveal the constructive effects of the strength of ties and task-related conflict, as well as the non-constructive effects of relationship-related conflict. This provides a reference for megaproject managers to implement project governance.
Interfacial Electronic Rearrangement and Synergistic Catalysis for Alkaline Water Splitting in Carbon-Encapsulated Ni (111)/Ni3C (113) Heterostructures
Authors: Li Xiaoyu , Peng Zhenbo , Jia Dongmei , Wang Yikang , Wu Wenbo , Deng Ping , Xu Mengqiu , Xu Xudong , Jia Gan , Ye Wei , Gao Peng
Published: November 2022

The realization of efficient water electrolysis is still blocked by the requirement for a high and stable driving potential above thermodynamic requirements. An Ni-based electrocatalyst, is a promising alternative for noble-metal-free electrocatalysts but tuning its surface electronic structure and exposing more active sites are the critical challenges to improving its intrinsic catalytic activity. Here, we tackle the challenge by tuning surface electronic structures synergistically with interfacial chemistry and crystal facet engineering, successfully designing and synthesizing the carbon-encapsulated Ni (111)/Ni3C (113) heterojunction electrocatalyst, demonstrating superior hydrogen evolution reaction (HER) activities, good stabilities with a small overpotential of −29 mV at 10 mA/cm2, and a low Tafel slope of 59.96 mV/dec in alkaline surroundings, approximating a commercial Pt/C catalyst and outperforming other reported Ni-based catalysts. The heterostructure electrocatalyst operates at 1.55 V and 1.26 V to reach 10 and 1 mA cm−2 in two-electrode measurements for overall alkaline water splitting, corresponding to 79% and 98% electricity-to-fuel conversion efficiency with respect to the lower heating value of hydrogen.
Advanced Glycation End Products and Inflammation in Type 1 Diabetes Development
Authors: Du Chenping , Whiddett Rani O. , Buckle Irina , Chen Chen , Forbes Josephine M. , Fotheringham Amelia K.
Published: November 2022

Type 1 diabetes (T1D) is an autoimmune disease in which the β-cells of the pancreas are attacked by the host’s immune system, ultimately resulting in hyperglycemia. It is a complex multifactorial disease postulated to result from a combination of genetic and environmental factors. In parallel with increasing prevalence of T1D in genetically stable populations, highlighting an environmental component, consumption of advanced glycation end products (AGEs) commonly found in in Western diets has increased significantly over the past decades. AGEs can bind to cell surface receptors including the receptor for advanced glycation end products (RAGE). RAGE has proinflammatory roles including in host–pathogen defense, thereby influencing immune cell behavior and can activate and cause proliferation of immune cells such as islet infiltrating CD8+ and CD4+ T cells and suppress the activity of T regulatory cells, contributing to β-cell injury and hyperglycemia. Insights from studies of individuals at risk of T1D have demonstrated that progression to symptomatic onset and diagnosis can vary, ranging from months to years, providing a window of opportunity for prevention strategies. Interaction between AGEs and RAGE is believed to be a major environmental risk factor for T1D and targeting the AGE-RAGE axis may act as a potential therapeutic strategy for T1D prevention.
Mitochondrial Cardiomyopathy: Molecular Epidemiology, Diagnosis, Models, and Therapeutic Management
Authors: Yang Jinjuan , Chen Shaoxiang , Duan Fuyu , Wang Xiuxiu , Zhang Xiaoxian , Lian Boonxuan , Kou Meng , Chiang Zhixin , Li Ziyue , Lian Qizhou
Published: November 2022

Mitochondrial cardiomyopathy (MCM) is characterized by abnormal heart-muscle structure and function, caused by mutations in the nuclear genome or mitochondrial DNA. The heterogeneity of gene mutations and various clinical presentations in patients with cardiomyopathy make its diagnosis, molecular mechanism, and therapeutics great challenges. This review describes the molecular epidemiology of MCM and its clinical features, reviews the promising diagnostic tests applied for mitochondrial diseases and cardiomyopathies, and details the animal and cellular models used for modeling cardiomyopathy and to investigate disease pathogenesis in a controlled in vitro environment. It also discusses the emerging therapeutics tested in pre-clinical and clinical studies of cardiac regeneration.
PI3K Isoform-Specific Regulation of Leader and Follower Cell Function for Collective Migration and Proliferation in Response to Injury
Authors: Basta Morgan D. , Menko A. Sue , Walker Janice L.
Published: November 2022

To ensure proper wound healing it is important to elucidate the signaling cues that coordinate leader and follower cell behavior to promote collective migration and proliferation for wound healing in response to injury. Using an ex vivo post-cataract surgery wound healing model we investigated the role of class I phosphatidylinositol-3-kinase (PI3K) isoforms in this process. Our findings revealed a specific role for p110α signaling independent of Akt for promoting the collective migration and proliferation of the epithelium for wound closure. In addition, we found an important role for p110α signaling in orchestrating proper polarized cytoskeletal organization within both leader and wounded epithelial follower cells to coordinate their function for wound healing. p110α was necessary to signal the formation and persistence of vimentin rich-lamellipodia extensions by leader cells and the reorganization of actomyosin into stress fibers along the basal domains of the wounded lens epithelial follower cells for movement. Together, our study reveals a critical role for p110α in the collective migration of an epithelium in response to wounding.
Electrochemical Sensors Based on Metal-Porous Carbon Nanozymes for Dopamine, Uric Acid and Furazolidone
Authors: Xiong Jianhui , Yang Yuxi , Wang Linyu , Chen Shouhui , Du Yan , Song Yonghai
Published: November 2022

A series of electrochemical sensors based on metal-porous carbon nanozymes were developed for the detection of dopamine (DA), uric acid (UA) and furazolidone (FZ). The metal-porous carbon nanozymes were prepared by calcination of porous crystalline covalent-organic frameworks (COFs) loaded metal ions. By carbonizing, the COFs was transformed into carbon nanosheets (CN) and metal ions were reduced into 5–10 nm MNPs loaded on CN uniformly (CuNPs/CN, FeNPs/CN, NiNPs/CN and CoNPs/CN). These porous MNPs/CN nanozymes were used for electrochemical detection of DA, AA and FZ, showing good performance. The electrochemical sensor based on CuNPs/CN nanozymes was used to simultaneously measure DA and UA. The linear range of DA detection was 0.015 μ–140 μM, the linear range of UA detection was 0.03 μM–175 μM, and the sensitivity of DA and UA were 1.03 μA μM−1 cm−2 and 0.52 μA μM−1 cm−2. The sensitivity of sensors based on FeNPs/CN, CoNPs/CN and NiNPs/CN nanozymes to detect DA were 1.30 μA cm−2 μM−1, 1.07 μA cm−2 μM−1 and 0.88 μA cm−2 μM−1, the linear ranges were 35 nM–200 μM, 42 nM–250 μM and 52 nM–250 μM. The sensitivity of detecting UA were 0.310 μA cm−2 μM−1, 0.587 μA cm−2 μM−1 and 0.360 μA cm−2 μM−1, the linear ranges were 145 nM–900 μM, 77 nM–700 μM and 125 nM–800 μM. Finally, CuNPs/CN was also used to construct a FZ sensor with a linear range of 61.5 nM–200 μΜ and a detection limit of 20.1 nM. The sensors also have good reproducibility and repeatability.
Association of Image-Defined Risk Factors with Clinical, Biological Features and Outcome in Neuroblastoma
Authors: Laura Balanescu , Radu Balanescu , Patricia Cimpeanu , Andreea Moga
Published: November 2022

Background: Neuroblastoma (NB) is the most common pediatric extracranial solid tumor and the most common cancer encountered in children younger than 12 months of age. Localized tumors have a good prognosis, but some cases undergo treatment failure and recurrence. The aim of the study was to analyze the link between the neuroblastoma risk factors and the prognosis for patients diagnosed with NB. Method: All patients admitted to the department of Pediatric Surgery, “Grigore Alexandrescu” Clinical Emergency Hospital for Children, between 1 January 2010 and 1 July 2022 were included in this analysis when diagnosed with neuroblastoma. Results: Thirty-one patients with NB were admitted to the surgical department, 20 boys and 11 girls. We observed an association between large tumors and positive imaging-defined risk factor (IDRF) status; The Fisher test showed an association between the tumor’s diameter when bigger than 8 cm and a positive IDRF status, with p < 0.001. We supposed that positive IDRF status at diagnosis may be linked to other prognostic factors. We discovered that an NSE value over 300 was associated with IDRF status (p < 0.001, phi = 0.692) and death. Conclusions: This study confirms the impact of IDRF status at diagnosis as it can be clearly correlated with other risk factors, such as a high level of NSE, MYCN amplification status, large tumor size, incomplete tumor resection, and an unfavorable outcome.