bluuebunny/crossref_metadata_2025 huggingface dataset:
Laboratory Tests on Swelling Properties of Field-Coring Gypsum Rock in Tunnels
Authors: Xu Chongbang , Fan Haoju , Zhao Xu , Fan Lifeng , Wang Peng
Published: January 2023

The reaction between gypsum rock and water results in swelling deformation and swelling pressure. Swelling deformation and swelling pressure cause damage to underground engineering such as tunnels. It is of significance to study the swelling characteristics of gypsum rock. The variation in maximum radial free-swelling ratio, axial free-swelling ratio, lateral restricted-swelling ratio and lateral restricted-swelling pressure of gypsum rock with a water immersion time of 2880 min were investigated experimentally. The early swelling characteristics were further discussed and described by an S-shaped model. The results show that the swelling ratio and swelling pressure increase rapidly as the immersion time increases for the first 120 min. Subsequently, the swelling ratio and swelling pressure increase slowly and become stable as the immersion time further increases. At the 120th minute, the maximum radial free-swelling ratio, axial free-swelling ratio, lateral restricted-swelling ratio and lateral restricted-swelling pressure of gypsum rock reach more than 80% of their final values (2880 min in the present study). Based on the swelling characteristics of gypsum rock during the first 120 min, an S-shaped swelling-time model was introduced to describe the early swelling behavior of gypsum rock.
Evaluation of the Specific Capacitance of High-Entropy Oxide-Based Electrode Materials in View of Their Use for Water Desalination via Capacitive Method
Authors: Triolo Claudia , Santangelo Saveria , Petrovičovà Beatrix , Musolino Maria Grazia , Rincón Inés , Atxirika Ainhoa , Gil Silvia , Belaustegui Yolanda
Published: January 2023

Water pollution and scarcity are serious concerns for the growing world population. To meet the ever-pressing demand of fresh water, a variety of desalting techniques of seawater have been developed. Due to its environmental friendliness, high efficiency, easy regeneration of the electrodes, ambient operating pressure, and low operating potential suitable for the use in remote areas, the capacitive deionization (CDI) method is one of the most sustainable among them. This work focuses on the preparation of high-entropy oxides (HEOs) and carbon/HEO composites and the evaluation of their specific capacitance in view of their possible use as CDI electrode materials. CrMnFeCoNi-HEO, having spinel structure (sHEO), is obtained in the form of nanoparticles (NPs) and nanofibers (NFs) by the sol–gel method and electrospinning, respectively. Composite NFs with embedded sHEO NPs or MgCoNiCuZn-HEO NPs with rock-salt structure (rHEO) are also produced. In the 5–100 mV s−1 scan rate range, the specific capacitance improves in the order C/rHEO NFs (8–32 F g−1) ≅ sHEO NPs (9–32 F g−1) < sHEO NFs (8–43 F g−1) < C/sHEO NFs (12–66 F g−1). The highest capacitance is obtained when the beneficial contributions of the carbon matrix and smaller-sized HEO NPs are synergistically coupled.
Effective Microorganisms and Olive Mill Wastewater Used as Biostimulants to Improve the Performance of Tanacetum balsamita L., a Medicinal Plant
Authors: Faraloni Cecilia , Giordano Cristiana , Arcidiaco Lorenzo , Benelli Carla , Di Lonardo Sara , Anichini Monica , Stefani Federico , Petruccelli Raffaella
Published: January 2023

The use of biostimulants and/or biofertilizers has acquired considerable importance and can contribute to the sustainable management agriculture, reducing the use of chemical fertilizers, pesticides, and water. This study aims to assess the effects of Effective Microorganisms (EM) and Olive Mill Wastewater (OMW) on the growth, photosynthetic performance and polyphenols content of the medicinal plant Tanacetum balsamita. The EM and OMW were used at two dilution rates. The EM was added to 5% v/v and 10% v/v, while OMW was added to 2.5% v/v and 5% v/v in plants at the early growth stage. After 75 days of treatment, all the treated plants had a leaf number and leaf area almost 2-fold higher than in the Control plants. Moreover, the treatments, at all the concentrations applied had a positive effect on the photosynthetic activity, with an improvement both in terms of the quantum yield of photosynthesis and electrons transport efficiency. The best photosynthetic and growth performances in the treated plants coincided with the higher production of phenolic compounds; indeed, after 75 days, the content of chlorogenic acid, caffeic acid, and isochlorogenic acid was even 2-fold of the Control plants. Also, rutin content was 1.28–1.50-fold respect to the Control extracts. The highest phenolic compound content was reflected by the highest antiradical activity, found in the extracts of the treated plants. The effectiveness of EM to increase the growth and quality of plants and in particular, the potential use of OMW on the cultivated crop was confirmed to this study.
Mechanism and Application of Layered Grouting Reinforcement for Fractured Coal and Rock Roadway
Authors: Liao Ze , Feng Tao
Published: January 2023

This paper takes the ZF3806 working face of Shuiliandong Coal Mine in Binxian County, Shaanxi Province as the engineering background. Aiming at the problems of the development of surrounding rock cracks and roof breakage encountered in the process of roadway excavation and support and based on the composite beam theory, the method of layered grouting reinforcement of roadways is proposed according to the deformation and failure of the roadway roof and the internal drilling conditions. At the same time, combined with the splitting grouting mechanism, the roadway is strengthened and supported by layered grouting of “shallow bolt grouting + deep cable grouting”. The “shallow” and “deep” form a complete and stable composite beam support structure. After grouting, the bending moments of “shallow” and “deep” support beams decrease by 20.78 × 106 N·m and 26.50 × 106 N·m, respectively. The support scheme is applied to the field test, and the grouting effect is analyzed and monitored. The research results show the layered grouting support scheme of “shallow bolt grouting + deep cable grouting” can significantly improve the structural integrity of the roadway roof. The displacement of the two sides is within the controllable range, and the support role of the bolt and cable is entirely played through grouting. The roof displacement of the roadway is reduced by 65% on average, and the bolt failure and steel belt fracture are significantly reduced, which effectively controls the deformation and damage of the roadway and reduces the maintenance cost of the roadway while ensuring safe mining. The study’s findings could be useful in treating broken surrounding rock in other coal mine roadways.
Special Issue on Carbon Capture and Utilization
Authors: Pires José C. M. , Gonçalves Ana L.
Published: January 2023

Carbon dioxide (CO2) emissions to the atmosphere have drastically increased in recent decades, with the energy and transport sectors representing major fractions of total greenhouse gas (GHG) emissions [...]
The Key Role of Laser Ultrasonics in the Context of Sustainable Production in an I 4.0 Value Chain
Authors: Hartl Karin , Sorger Marcel , Stockinger Martin
Published: January 2023

The advancement of laser ultrasonics has increased rapidly in recent years, providing applications for materials characterization as well as for industrial utilization, as a quality control device. The wide-ranging capabilities for high-temperature in-situ analysis of a variety of microstructural characteristics offers a multitude of possibilities for usage in R&D. To date, this is the only known method that has been successfully deployed for in-situ materials characterization, as well as in the harsh environment of the metalworking industry. Combined with the enablers, introduced by the fourth industrial revolution, and the conjunction of a laser ultrasonic system with a Smart Production Lab, it has great potential to contribute to lower rejection rates, better recyclability, and consequently to a more sustainable production. In this review, the potential for systemic sustainability is explained throughout a part of the value chain, in the context of Industry 4.0. In addition, the integration of the methodology into a miniaturized Smart Production Lab is demonstrated, with the intention of incorporating it as a substantial part of the creation of a digital twin. Such a lab is designed to serve as an interface between laboratory and industry, in order to reveal the possibilities of digital transformation, Industry 4.0, and the application of highly flexible systems such as the laser-ultrasonic system for companies.
Acceleration of Particle Swarm Optimization with AVX Instructions
Authors: Safarik Jakub , Snasel Vaclav
Published: January 2023

Parallel implementations of algorithms are usually compared with single-core CPU performance. The advantage of multicore vector processors decreases the performance gap between GPU and CPU computation, as shown in many recent pieces of research. With the AVX-512 instruction set, there will be another performance boost for CPU computations. The availability of parallel code running on CPUs made them much easier and more accessible than GPUs. This article compares the performances of parallel implementations of the particle swarm optimization algorithm. The code was written in C++, and we used various techniques to obtain parallel execution through Advanced Vector Extensions. We present the performance on various benchmark functions and different problem configurations. The article describes and compares the performance boost gained from parallel execution on CPU, along with advantages and disadvantages of parallelization techniques.
Magnetic Levitation Actuation and Motion Control System with Active Levitation Mode Based on Force Imbalance
Authors: Liu Guancheng , Lu Yonghua , Xu Jiajun , Cui Zhanxiang , Yang Haibo
Published: January 2023

Accurate large-displacement magnetic levitation actuation and its stability remain difficult in non-liquid environments. A magnetic levitation actuation and motion control system with active levitation mode is proposed in this paper. The actuating force of the system is generated by the external magnetic field. A neural network proportion-integration-differentiation (PID) controller is designed for active actuation, and a force imbalance principle is built for the step motion mode. Dual electromagnetic actuators are configured to generate a superimposed magnetic field, ensuring that the electromagnetic force on the ball is more uniform and stable than single actuators. Dual-hall-structure sensors are used to measure displacement, thereby reducing overshoot and ensuring stability whilst motivating the ball. Due to the high adaptability of the neural network to complex systems with nonlinear and ambiguous models, the PID controller composed of neurons has stronger adaptability through tuning the PID controller parameters automatically. Furthermore, the proposed controller can solve the shortcoming that the deviation between the controlled object and the steady-state operating point increases and the tracking performance deteriorates rapidly. The strong robustness and stability in active levitation and motion control is achieved during both ascending and descending processes.
Full-Field Mode Shape Identification Based on Subpixel Edge Detection and Tracking
Authors: Kong Xuan , Yi Jinxin , Wang Xiuyan , Luo Kui , Hu Jiexuan
Published: January 2023

Most research on computer vision (CV)-based vibration measurement is limited to the determination of discrete or coarse mode shapes of the structure. The continuous edge of the structure in images has rich optical features, and thus, by identifying and tracking the movement of the structure’s edge, it is possible to determine high-resolution full-field mode shapes of the structure without a preset target. The present study proposes a CV-based method of full-field mode shape identification using the subpixel edge detection and tracking techniques. Firstly, the Canny operator is applied on each frame of the structure vibration video to extract the pixel-level edges, and the improved Zernike orthogonal moment (ZOM) subpixel edge detection technique is adopted to relocate the precise structure edges. Then, all the detected edge points are tracked to obtain the full-field dense displacement time history that is subsequently used to determine the structure frequencies and compute full-field mode shapes by combining the covariance driven stochastic subspace identification (SSI-COV) with the hierarchical cluster analysis. Finally, the proposed method is verified on the aluminum cantilever beam in the laboratory and the Humen Bridge in the field. The results show that the proposed method is able to detect more precise structure edges and identify the full-field displacement and mode shapes of structures without the need for installing artificial targets on the structure in advance, which provides valuable information for the structural condition assessment, especially for structures with small-amplitude vibrations.
Global Resources Management: A Systematic Review and Framework Proposal for Collaborative Management of CPPS
Authors: Varela Leonilde R. , Trojanowska Justyna , Cruz-Cunha Maria Manuela , Pereira Miguel Ângelo , Putnik Goran D. , Machado José M.
Published: January 2023

Nowadays, global resources management intersects with collaboration and Industry 4.0 paradigms, namely for collaboratively managing cyber-physical systems. Only organizations that cooperate with their business partners, along with their suppliers and remaining stakeholders, including their clients, will be able to permit and promote the much-needed endowing of agility, effectiveness, and efficiency in their management processes. For that, suitable decision-making paradigms, along with underlying approaches, will be needed, in order to properly fulfil current companies’ decision requirements and practices. The main purpose of this paper is to show that this can be achieved by applying combined global resources management paradigms and approaches, to reach collaboration further supported by recent technology made available through Industry 4.0. In doing so, the interaction of companies and stakeholders, supported by appropriate networks, along with varying kind of other communication and problem-solving technology, will enable them to promote and reinforce interoperation to reach the best-suited management decisions, by considering each ones’ objectives and priorities, along with common goals. To this end, in this paper, a systematic literature review methodology is used to synthetize the main contributions about the relation of these domains. The study carried out and the results obtained permitted us to realize that dynamic, integrated, distributed, parallel, intelligent, predictive, and real-time-based decision paradigms are of the upmost importance currently, but are still just scarcely being combined, which is suggested though its encompassing through a proposed collaborative management framework that is recommended to be applied, either in industry or academia, to improve global resources management processes and practices.
Security and Privacy Issues in IoT-Based Big Data Cloud Systems in a Digital Twin Scenario
Authors: Stergiou Christos L. , Bompoli Elisavet , Psannis Konstantinos E.
Published: January 2023

Due to its unique type of services, Cloud Computing could operate as a “base technology” for other technologies; this attracts researchers to develop sustainable Cloud systems. It is a new generation of services that offers an opportunity for users to access and manage their information, applications, and data regardless of place and time. Nevertheless, there is a type of service that can include large amounts of data, called Big Data, and it consists of the rapid use of the Internet of Things (IoT) to produce large data sets. In this work, initially, we present Cloud Computing (CC) and Big Data (BD) exported from IoT, focusing on the security and management challenges of both. Notably, we combine the two aforementioned technologies to examine their related characteristics and discover new perspectives and opportunities for their integration and to achieve a sustainable environment called a Digital Twin scenario. Subsequently, we present how Cloud Computing contributes to IoT-based Big Data, aiming to fill a scientific gap in the sector of their integration regarding security and privacy. Finally, we additionally survey the security challenges of the integrated model of BD and CC and then propose a novel security algorithm for sustainable Cloud systems in a Digital Twin scenario. The experimental results presented are based on the use of the encryption algorithms AES, RC5, and RSA, and our proposed model extends the advances of CC and IoT-based BD, offering a highly novel and scalable service platform to achieve better privacy and security services.
Total Solar Irradiance and Stroke Mortality by Neural Networks Modelling
Authors: Geronikolou Styliani , Zimeras Stelios , Tsitomeneas Stephanos , Cokkinos Dennis , Chrousos George P.
Published: January 2023

The purpose of this study was to examine the potential effect of solar energy on vascular stroke mortality in a Greek region by using neural networks analysis. The time period studied was from 1985 to 1989. We employed the Active Cavity Radiometer Irradiance Monitoring (ACRIM) data as the main representatives of total solar irradiance (TSI) and correlated them with stroke deaths obtained from the Piraeus City Registry. The ACRIM data (parameters included TSI, TSI uncertainty, and EPOCH: time given by ACRIM) were correlated with stroke deaths using Principal Components Analysis (PCA), regressions, and, finally, neural networks. TSI was the most important parameter for the years 1985, 1986, 1987, and 1989, while EPOCH: time given by ACRIM was important for the year 1988. When considering the entire period 1985–1989, the key parameter emerged was EPOCH: time given by ACRIM. Neural networks are useful tools in exposomic investigation regarding solar energy and vascular strokes.
Identification of a Function to Fit the Flow Duration Curve and Parameterization of a Semi-Arid Region in North China
Authors: Ma Lan , Liu Dengfeng , Huang Qiang , Guo Fengnian , Zheng Xudong , Zhao Jing , Luan Jinkai , Fan Jingjing , Ming Guanghui
Published: January 2023

The discharge process has undergone major changes in many river basins throughout the world as a result of the simultaneous influences of global climate change and human activity. Flow duration curves (FDCs) are crucial indicators of river basins’ hydrological processes. However, it is challenging to compare FDCs in a quantitative way. This study will identify the best function with which to fit the flow duration curve in a semi-arid region of North China, so as to quantify the FDC, and parameterize the function of the FDC of the region in order to describe the FDCs of ungauged basins. In this work, six small- and medium-sized catchments in North China are selected as the study area, and three functions, i.e., log normal, generalized Pareto and H2018 functions, were chosen to fit the FDC at nineteen hydrological stations. The relationship between the parameters of the FDC and the basin characteristics, such as the climatic factors and geographical features, were analyzed. A regression formula of the parameters of the FDC function was established, and its spatial and temporal distributions were examined. Based on the evaluation of four indicators, the Nash–Sutcliffe efficiency, the root mean square relative error, the logarithmic Nash efficiency coefficient and the coefficient of determination, the results demonstrate that the H2018 function can match FDCs the best. Through the annual runoff, annual precipitation, precipitation in summer, potential evapotranspiration, catchment area, mean elevation, length of the main channel and maximum flow frequency, the parameters of a, b, and k in the H2018 function can be formulated. The regression formula constructed in this study can obtain a regional flow duration curve with satisfactory performance, which provides a reference for the validation of remote-sensing-based runoff data in ungauged regions.
Spatiotemporal Characteristics and Influencing Factors of Summer Heatwaves in Hexi Oasis during 1962–2020
Authors: Lu Juan , Liu Puxing , Wang Huiyu
Published: January 2023

Based on the daily gridded (0.5° × 0.5°) maximum temperature data during 1962–2020, the spatiotemporal characteristics of heatwaves in Hexi Oasis, Gansu Province, China and their influencing factors are investigated. The results showed that for the last 59 years, the overall trends of high-temperature heatwaves in Hexi Oasis were prolonged duration (0.276 d/10a), increased frequency (0.007 times/10a), and decreased intensity (−0.072 °C/10a). In terms of spatial variation, there was a gradually decreasing trend from northwest to southeast for both the duration and frequency of heatwaves. In the contrary, heatwaves with higher intensity were mainly distributed over the southeastern and central parts of Hexi Oasis. The Mann–Kendall (M-K) analysis demonstrated that the mutation years of the duration and intensity of heatwaves are 2009 and 1992, respectively, while the frequency remained nearly constant for the last 59a. In addition, the cycles for the duration (2.6a and 7.2a), frequency (2.8a and 7.6a), and intensity (2.6a) of heatwaves agree well with those of atmospheric circulation and El Niño events, indicating that the above events have a great impact on the heatwaves. The influencing factors analyzation implies that the heatwaves are mainly influenced by Asian zone polar vortex area index (APVAI), East Asia major trough (EAT), Qinghai-Tibetan Plateau index (TPI), and carbon dioxide emissions (CDE). Additionally, it is concluded that the intensity of heatwaves was negatively correlated with the size of the subtropical high-pressure area in the western Pacific Ocean.
Effects of Chronic Caffeine Consumption on Synaptic Function, Metabolism and Adenosine Modulation in Different Brain Areas
Authors: Lopes Cátia R. , Oliveira Andreia , Gaspar Ingride , Rodrigues Matilde S. , Santos Joana , Szabó Eszter , Silva Henrique B. , Tomé Ângelo R. , Canas Paula M. , Agostinho Paula , Carvalho Rui A. , Cunha Rodrigo A. , Simões Ana Patrícia , Lopes João Pedro , Ferreira Samira G.
Published: January 2023

Adenosine receptors mainly control synaptic function, and excessive activation of adenosine receptors may worsen the onset of many neurological disorders. Accordingly, the regular intake of moderate doses of caffeine antagonizes adenosine receptors and affords robust neuroprotection. Although caffeine intake alters brain functional connectivity and multi-omics analyses indicate that caffeine intake modifies synaptic and metabolic processes, it is unclear how caffeine intake affects behavior, synaptic plasticity and its modulation by adenosine. We now report that male mice drinking caffeinated water (0.3 g/L) for 2 weeks were behaviorally indistinguishable (locomotion, mood, memory) from control mice (drinking water) and displayed superimposable synaptic plasticity (long-term potentiation) in different brain areas (hippocampus, prefrontal cortex, amygdala). Moreover, there was a general preservation of the efficiency of adenosine A1 and A2A receptors to control synaptic transmission and plasticity, although there was a tendency for lower levels of endogenous adenosine ensuring A1 receptor-mediated inhibition. In spite of similar behavioral and neurophysiological function, caffeine intake increased the energy charge and redox state of cortical synaptosomes. This increased metabolic competence likely involved a putative increase in the glycolytic rate in synapses and a prospective greater astrocyte–synapse lactate shuttling. It was concluded that caffeine intake does not trigger evident alterations of behavior or of synaptic plasticity but increases the metabolic competence of synapses, which might be related with the previously described better ability of animals consuming caffeine to cope with deleterious stimuli triggering brain dysfunction.
LongBondEliminator: A Molecular Simulation Tool to Remove Ring Penetrations in Biomolecular Simulation Systems
Authors: Sarkar Daipayan , Kulke Martin , Vermaas Josh V.
Published: January 2023

We develop a workflow, implemented as a plugin to the molecular visualization program VMD, that can fix ring penetrations with minimal user input. LongBondEliminator, detects ring piercing artifacts by the long, strained bonds that are the local minimum energy conformation during minimization for some assembled simulation system. The LongBondEliminator tool then automatically treats regions near these long bonds using multiple biases applied through NAMD. By combining biases implemented through the collective variables module, density-based forces, and alchemical techniques in NAMD, LongBondEliminator will iteratively alleviate long bonds found within molecular simulation systems. Through three concrete examples with increasing complexity, a lignin polymer, an viral capsid assembly, and a large, highly glycosylated protein aggrecan, we demonstrate the utility for this method in eliminating ring penetrations from classical MD simulation systems. The tool is available via gitlab as a VMD plugin, and has been developed to be generically useful across a variety of biomolecular simulations.
The Impact of Single-Level ACDF on Neural Foramen and Disc Height of Surgical and Adjacent Cervical Segments: A Case-Series Radiological Analysis
Authors: Maugeri Rosario , Brunasso Lara , Sciortino Andrea , Scerrati Alba , Buscemi Felice , Basile Luigi , Giammalva Giuseppe Roberto , Costanzo Roberta , Bencivinni Francesco , Bruno Eleonora , Matranga Domenica , Maniscalco Laura , Gioia Francesco , Tumbiolo Silvana , Iacopino Domenico Gerardo
Published: January 2023

Background: ACDF has become one of the established procedures for the surgical treatment of symptomatic cervical spondylosis, showing excellent clinical results and effective improvements in neural functions and neck pain relief. The main purpose of ACDF is neural decompression, and it is considered by some authors as an indirect result of the intervertebral distraction and cage insertion and the consequent restoration of the disc space and foramen height. Methods: Radiological data from 28 patients who underwent single-level ACDF were retrospectively collected and evaluated. For neural foramen evaluation, antero-posterior (A-P) and cranio-caudal (C-C) diameters were manually calculated; for intervertebral disc height the anterior, centrum and posterior measurement were calculated. All measurements were performed at surgical and adjacent (above and below) segments. NRS, NDI and also the mJOA and Nurick scale were collected for clinical examination and complete evaluation of patients’ postoperative outcome. Results: The intervertebral disc height in all its measurements, in addition to the height (C-C diameter) of the foramen (both right and left) increase at the surgical segment when comparing pre and postop results (p < 0.001, and p = 0.033 and p = 0.001). NRS and NDI radiculopathy scores showed improved results from pre- to post-op evaluation (p < 0.001), and a negative statistical correlation with the improved disc height at the surgical level. Conclusions: The restoration of posterior disc height through cage insertion appears to be effective in increasing foraminal height in patients with symptomatic preoperative cervical foraminal stenosis.
A Comprehensive Review on Anti-Inflammatory Response of Flavonoids in Experimentally-Induced Epileptic Seizures
Authors: Rabidas Shyam Sunder , Prakash Chandra , Tyagi Jyoti , Suryavanshi Jyoti , Kumar Pavan , Bhattacharya Jaydeep , Sharma Deepak
Published: January 2023

Flavonoids, a group of natural compounds with phenolic structure, are becoming popular as alternative medicines obtained from plants. These compounds are reported to have various pharmacological properties, including attenuation of inflammatory responses in multiple health issues. Epilepsy is a disorder of the central nervous system implicated with the activation of the inflammatory cascade in the brain. The aim of the present study was to summarize the role of various neuroinflammatory mediators in the onset and progression of epilepsy, and, thereafter, to discuss the flavonoids and their classes, including their biological properties. Further, we highlighted the modulation of anti-inflammatory responses achieved by these substances in different forms of epilepsy, as evident from preclinical studies executed on multiple epilepsy models. Overall, the review summarizes the available evidence of the anti-inflammatory potential of various flavonoids in epilepsy.
Unpacking Detrimental Effects of Network Externalities on Privacy Invasion, Communication Overload and Mobile App Discontinued Intentions: A Cognition-Affect-Conation Perspective
Authors: Pang Hua , Ruan Yang , Wang Yiwei
Published: January 2023

Recently, mobile apps are rapidly emerging as an important information instrument, with the potential to boost convenience and efficiency in everyday life. The adoption of mobile apps can exert a positive influence on individuals, but also lead to adverse perceptions in different ways. The crucial issue arising is what motivates people’s discontinued use of such services. Furthermore, the roles of communication overload and privacy invasion between network externalities and discontinued use intentions have not been thoroughly examined. The primary objective of this article is to investigate if negative network externalities may result in privacy invasion, communication overload and discontinued intentions, and how the underlying mechanism operates. This current research collected and evaluated data from 696 mobile app users utilizing the structural equation model (SEM) technique. The findings demonstrate that perceived critical mass and perceived complementarity positively affect the privacy invasion of mobile app users. Particularly, it was discovered that privacy invasion and communication overload mediate the association between network externalities and mobile app discontinued use intentions. This article may not only enrich the ongoing contemporary critical discussion on new information technology usage, but also offer significant theoretical and practical implications for mobile app researchers and practitioners.
Numerical Analysis of Mechanical Behavior of Self-Centering Joint between CFDST Column and RC Beam
Authors: Yan Xueyuan , Shi Shen , Liu Xuhong , Mao Huimin
Published: January 2023

The existing connection between the concrete-filled double steel tubular (CFDST) column and the reinforced concrete (RC) beam is difficult to repair and reuse after damage. In this paper, a self-centering joint between the CFDST column and the RC beam is proposed. The self-centering of the joint is realized by prestressed steel strands, and the energy dissipation is realized by friction. The overall purpose of the research is to analyze the influence of steel strand and friction on the mechanical behavior of the joint. By comparing the envelope curve and the restoring force model of a numerical joint model with theoretical values, accuracy of the numerical model was verified. Then, joints with different parameters, including the friction, prestress of steel strands, and ratio of the resisting moment provided by steel strands to the resisting moment provided by friction in the opening moment of joints, were numerically analyzed. The results showed that the joints with greater friction and prestress of steel strands had higher bearing capacity. Increasing the friction could increase the energy dissipation capacity of the joint, but it would increase the residual deformation of the joint. To reduce residual deformation, the prestress of steel strands should be increased. When the resultant force of the pretension of steel strands was greater than friction, the steel head could be kept pressed on the connecting block, making the stress changes of steel strands and the self-centering performance of the joint stable.
Risk Factor and Replacement Therapy Analysis of Pre- and Postoperative Endocrine Deficiencies for Craniopharyngioma
Authors: Cheng Lidong , Zhu Hongtao , Wang Jing , Wu Sisi , Zhang Suojun , Wang Junwen , Shu Kai
Published: January 2023

Background: Pituitary hormone deficiency (PHD) is one of the most common symptoms and postoperative complications of craniopharyngiomas (CPs). However, the risk factors for PHD in CPs are little known. The purpose of this study was to analyze the risk factors of pre- and postoperative PHD and to investigate replacement therapy for CP patients. Methods: A retrospective study of 126 patients diagnosed with CP was performed. Univariate analysis was performed using Pearson’s chi-squared test or Fisher’s exact test, and a multiple logistic binary regression model was used to identify the influencing factors of pre- and postoperative PHD in craniopharyngioma. Results: Children and patients with hypothalamic involvement were more likely to have preoperative PHD. Patients with suprasellar lesions had a high risk of postoperative PHD, and preoperative PHD was a risk factor for postoperative PHD. Conclusion: Children have a high incidence of preoperative PHD. Preoperative PHD can serve as an independent risk factor for postoperative PHD. Preoperative panhypopituitarism can serve as an indication of pituitary stalk sacrifice during surgery. The management of replacement therapy for long-term postoperative endocrine hormone deficiency in patients with craniopharyngioma should be enhanced.
Association between Prior Cytotoxic Therapy, Antecedent Hematologic Disorder, and Outcome after Allogeneic Hematopoietic Cell Transplantation in Adult Acute Myeloid Leukemia
Authors: Orvain Corentin , Rodríguez-Arbolí Eduardo , Othus Megan , Sandmaier Brenda M. , Deeg H. Joachim , Appelbaum Frederick R. , Walter Roland B.
Published: January 2023

(1) Background: Secondary acute myeloid leukemia (AML), i.e., AML arising from prior therapy (therapy-related) and/or an antecedent hematologic disorder (AHD) is generally associated with worse outcomes compared to de novo AML. However, recognizing the prognostic importance of genetic characteristics rather than clinical history, secondary AML is now considered a diagnostic qualifier rather than a separate disease entity. (2) Methods: To assess the association between clinical history and AML outcomes in the context of allogeneic hematopoietic cell transplantation (HCT), we retrospectively analyzed 759 patients with de novo AML, 115 with AHD AML, and 105 with therapy-related AML who received first allografts while in first or second remission. (3) Results: At the time of HCT, these three cohorts differed significantly regarding many patient and disease-specific characteristics, including age (p < 0.001), gender (p < 0.001), disease risk (p = 0.005), HCT-CI score (p < 0.001), blood count recovery (p = 0.003), first vs. second remission (p < 0.001), remission duration (p < 0.001), measurable residual disease (MRD; p < 0.001), and conditioning intensity (p < 0.001). Relative to patients with de novo AML, relapse rates were similar for patients with AHD (hazard ratio [HR] = 1.07, p = 0.7) and therapy-related AML (HR = 0.86, p = 0.4) after multivariable adjustment, as were relapse-free survival (HR = 1.20, p = 0.2, and HR = 0.89, p = 0.5) and overall survival (HR = 1.19, p = 0.2, and HR = 0.93, p = 0.6). Non-relapse mortality was higher for AHD AML (HR = 1.59, p = 0.047). (4) Conclusions: These data suggest that the clinical history by itself contains limited prognostic value for adults with AML undergoing allografting, supporting the most recent approach to use this information as a diagnostic qualifier rather than a disease entity.
Advances in Imaging-Based Biomarkers in Renal Cell Carcinoma: A Critical Analysis of the Current Literature
Authors: Posada Calderon Lina Posada , Eismann Lennert , Reese Stephen W. , Reznik Ed , Hakimi Abraham Ari
Published: January 2023

Cross-sectional imaging is the standard diagnostic tool to determine underlying biology in renal masses, which is crucial for subsequent treatment. Currently, standard CT imaging is limited in its ability to differentiate benign from malignant disease. Therefore, various modalities have been investigated to identify imaging-based parameters to improve the noninvasive diagnosis of renal masses and renal cell carcinoma (RCC) subtypes. MRI was reported to predict grading of RCC and to identify RCC subtypes, and has been shown in a small cohort to predict the response to targeted therapy. Dynamic imaging is promising for the staging and diagnosis of RCC. PET/CT radiotracers, such as 18F-fluorodeoxyglucose (FDG), 124I-cG250, radiolabeled prostate-specific membrane antigen (PSMA), and 11C-acetate, have been reported to improve the identification of histology, grading, detection of metastasis, and assessment of response to systemic therapy, and to predict oncological outcomes. Moreover, 99Tc-sestamibi and SPECT scans have shown promising results in distinguishing low-grade RCC from benign lesions. Radiomics has been used to further characterize renal masses based on semantic and textural analyses. In preliminary studies, integrated machine learning algorithms using radiomics proved to be more accurate in distinguishing benign from malignant renal masses compared to radiologists’ interpretations. Radiomics and radiogenomics are used to complement risk classification models to predict oncological outcomes. Imaging-based biomarkers hold strong potential in RCC, but require standardization and external validation before integration into clinical routines.
Oxygenated Hydrocarbons from Catalytic Hydrogenation of Carbon Dioxide
Authors: Isahak Wan Nor Roslam Wan , Shaker Lina Mohammed , Al-Amiery Ahmed
Published: January 2023

Once fundamental difficulties such as active sites and selectivity are fully resolved, metal-free catalysts such as 3D graphene or carbon nanotubes (CNT) are very cost-effective substitutes for the expensive noble metals used for catalyzing CO2. A viable method for converting environmental wastes into useful energy storage or industrial wealth, and one which also addresses the environmental and energy problems brought on by emissions of CO2, is CO2 hydrogenation into hydrocarbon compounds. The creation of catalytic compounds and knowledge about the reaction mechanisms have received considerable attention. Numerous variables affect the catalytic process, including metal–support interaction, metal particle sizes, and promoters. CO2 hydrogenation into different hydrocarbon compounds like lower olefins, alcoholic composites, long-chain hydrocarbon composites, and fuels, in addition to other categories, have been explained in previous studies. With respect to catalyst design, photocatalytic activity, and the reaction mechanism, recent advances in obtaining oxygenated hydrocarbons from CO2 processing have been made both through experiments and through density functional theory (DFT) simulations. This review highlights the progress made in the use of three-dimensional (3D) nanomaterials and their compounds and methods for their synthesis in the process of hydrogenation of CO2. Recent advances in catalytic performance and the conversion mechanism for CO2 hydrogenation into hydrocarbons that have been made using both experiments and DFT simulations are also discussed. The development of 3D nanomaterials and metal catalysts supported on 3D nanomaterials is important for CO2 conversion because of their stability and the ability to continuously support the catalytic processes, in addition to the ability to reduce CO2 directly and hydrogenate it into oxygenated hydrocarbons.
Aluminosilicates Catalysts Synthesis from Low-Grade Indonesian Kaolin for the Acetalization Reaction
Authors: Hartati Hartati , A’yuni Qurrota , Saputri Nastiti Heru , Mardho Dea Zaqiatul , Firda Putri Bintang Dea , Hartono Hartono , Bahruji Hasliza , Nugraha Reva Edra , Sholeha Novia Amalia , Prasetyoko Didik
Published: January 2023

Aluminosilicate and ZSM-5 catalyst were synthesized from local materials, low-grade Indonesian kaolin. High quartz impurities content in the low-grade kaolin was successfully reduced by the consecutive treatment process including washing, centrifugation, and Fe3+ treatment. All the synthesized catalyst showed mesoporous structure with pore diameter around 3.5 nm. The catalytic activity was investigated in the acetalization of 3,4-dimethoxybenzaldehyde and propylene glycol, then the effect of a different base (TPAOH and NaOH) and Fe3+ addition in the treatment process to the catalytic activity was discussed. The catalytic activity of the aluminosilicate catalyst outperforms the ZSM-5. Interestingly, it is found that the catalytic activity of the catalyst can be enhanced by addition of Fe3+ in the aluminosilicate, with enhanced the conversion from 32.2% to 81.6%, whereas Fe3+ addition to ZSM-5 showed slightly increased conversion value from 0% to 3.65%. All catalysts showed high selectivity of 100% of the reaction product 2-(3,4-dimethoxy-phenyl)-4-methyl-1,3-dioxolane.
Optimization of 3D Immunofluorescence Analysis and Visualization Using IMARIS and MeshLab
Authors: Abu Bakar Zulzikry Hafiz , Bellier Jean-Pierre , Wan Ngah Wan Zurinah , Yanagisawa Daijiro , Mukaisho Ken-ichi , Tooyama Ikuo
Published: January 2023

The precision of colocalization analysis is enhanced by 3D and is potentially more accurate than 2D. Even though 3D improves the visualization of colocalization analysis, rendering a colocalization model may generate a model with numerous polygons. We developed a 3D colocalization model of FtMt/LC3 followed by simplification. Double immunofluorescence staining of FtMt and LC3 was conducted, and stacked images were acquired. We used IMARIS to render the 3D colocalization model of FtMt/LC3 and further processed it with MeshLab to decimate and generate a less complex colocalization model. We examined the available simplification algorithm using MeshLab in detail and evaluated the feasibility of each procedure in generating a model with less complexity. The quality of the simplified model was subsequently assessed. MeshLab’s available shaders were scrutinized to facilitate the spatial colocalization determination. Finally, we showed that QECD was the most effective method for reducing the polygonal complexity of the colocalization model without compromising its quality. In addition, we would recommend implementing the x-ray shader, which we found useful for visualizing colocalization. As 3D was found to be more accurate in quantifying colocalization, our study provides a novel and dependable method for rendering 3D models for colocalization analysis.
iPSC-Derived Striatal Medium Spiny Neurons from Patients with Multiple System Atrophy Show Hypoexcitability and Elevated α-Synuclein Release
Authors: Henkel Lisa M. , Kankowski Svenja , Moellenkamp Thiemo M. , Smandzich Nadine J. , Schwarz Sigrid , Di Fonzo Alessio , Göhring Gudrun , Höglinger Günter , Wegner Florian
Published: January 2023

Multiple system atrophy of the parkinsonian type (MSA-P) is a rare, fatal neurodegenerative disease with sporadic onset. It is still unknown if MSA-P is a primary oligodendropathy or caused by neuronal pathophysiology leading to severe, α-synuclein-associated neurodegeneration, mainly in the striatum. In this study, we generated and differentiated induced pluripotent stem cells (iPSCs) from patients with the clinical diagnosis of probable MSA-P (n = 3) and from three matched healthy controls into GABAergic striatal medium spiny neurons (MSNs). We found a significantly elevated release and neuronal distribution for α-synuclein, as well as hypoexcitability in the MSNs derived from the MSA-P patients compared to the healthy controls. These data suggest that the striatal hypoexcitable neurons of MSA-P patients contribute to a pathological α-synuclein burden which is likely to spread to neighboring cells and projection targets, facilitating disease progression.
Electrical Remodelling in Cardiac Disease
Authors: Ravens Ursula , Peyronnet Rémi
Published: January 2023

The human heart responds to various diseases with structural, mechanical, and electrical remodelling processes [...]
Fully Transparent and Highly Sensitive pH Sensor Based on an a-IGZO Thin-Film Transistor with Coplanar Dual-Gate on Flexible Polyimide Substrates
Authors: Hyun Tae-Hwan , Cho Won-Ju
Published: January 2023

In this paper, we propose a fully transparent and flexible high-performance pH sensor based on an amorphous indium gallium zinc oxide (a-IGZO) thin-film transistor (TFT) transducer with a coplanar dual-gate structure on polyimide substrates. The proposed pH sensor system features a transducer unit consisting of a floating gate (FG), sensing gate (SG), and control gate (CG) on a polyimide (PI), and an extended gate (EG) sensing unit on a separate glass substrate. We designed a capacitive coupling between (SG) and (CG) through the FG of an a-IGZO TFT transducer to contribute to sensitivity amplification. The capacitance ratio (CSG/CCG) increases linearly with the area ratio; therefore, the amplification ratio of the pH sensitivity was easily controlled using the area ratio of SG/CG. The proposed sensor system improved the pH sensitivity by up to 359.28 mV/pH (CSG/CCG = 6.16) at room temperature (300 K), which is significantly larger than the Nernstian limit of 59.14 mV/pH. In addition, the non-ideal behavior, including hysteresis and drift effects, was evaluated to ensure stability and reliability. The amplification of sensitivity based on capacitive coupling was much higher than the increase in the hysteresis voltage and drift rate. Furthermore, we verified the flexibility of the a-IGZO coplanar dual-gate TFT transducer through a bending test, and the electrical properties were maintained without mechanical damage, even after repeated bending. Therefore, the proposed fully transparent and highly sensitive a-IGZO coplanar dual-gate TFT-based pH sensor could be a promising wearable and portable high-performance chemical sensor platform.