bluuebunny/crossref_metadata_2025 huggingface dataset:
Software Fault Prediction Using an RNN-Based Deep Learning Approach and Ensemble Machine Learning Techniques
Authors: Borandag Emin
Published: January 2023

Alongside the modern software development life cycle approaches, software testing has gained more importance and has become an area researched actively within the software engineering discipline. In this study, machine learning and deep learning-related software fault predictions were made through a data set named SFP XP-TDD, which was created using three different developed software projects. A data set of five different classifiers widely used in the literature and their Rotation Forest classifier ensemble versions were trained and tested using this data set. Numerous publications in the literature discussed software fault predictions through ML algorithms addressing solutions to different problems. Some of these articles indicated the usage of feature selection algorithms to improve classification performance, while others reported operating ensemble machine learning algorithms for software fault predictions. Besides, a detailed literature review revealed that there were few studies involving software fault prediction with DL algorithms due to the small sample sizes in the data sets and the low success rates in the tests performed on these datasets. As a result, the major contribution of this research was to statistically demonstrate that DL algorithms outperformed ML algorithms in data sets with large sample values via employing three separate software fault prediction datasets. The experimental outcomes of a model that includes a layer of recurrent neural networks (RNNs) were enclosed within this study. Alongside the aforementioned and generated data sets, the study also utilized the Eclipse and Apache Active MQ data sets in to test the effectiveness of the proposed deep learning method.
Development of a Fully Compliant Bistable Mechanism Based on Circular Beams with Enhanced Pitch Stiffness
Authors: Yan Liangliang , Lu Shuaishuai , Liu Pengbo
Published: January 2023

Compliant bistable mechanisms with planar configurations demonstrate two in-plane stable states through the nonlinear deformations of in-plane flexible segments, which are widely used in the field of shock sensors and threshold sensors. In these mechanisms, consistent dynamic and static bistable behaviors are difficult to maintain under the influence of an out-of-plane load. This is limited in some applications where precise displacement is required. To this end, we developed a bistable mechanism with circular beams instead of conventional straight beams, such that enhanced robustness against external loads in the out-of-plane region is obtained. An analytical kinetostatic model is established to predict the bistable behavior of the proposed mechanism, which is further verified using finite element simulations and experimental results. Compared with the prototype of the straight-beam-based bistable mechanism, the developed circular-beam bistable mechanism demonstrates improved pitch stiffness along the out-of-plane rotation and robustness against off-axis load conditions. The proposed bistable mechanism design can be extended to applications of sensors subjected to out-of-plane loads.
Recycling Bio-Based Wastes into Road-Base Binder: Mechanical, Leaching, and Radiological Implications
Authors: Peceño B. , Hurtado-Bermudez S. , Alonso-Fariñas B. , Villa-Alfageme M. , Más J. L. , Leiva C.
Published: January 2023

This work presents a physical, mechanical, durability, leaching, and radiological assay of three wastes (egg and scallop shells and olive pomace ash) as road-base binders. Two different waste/Portland-cement ratios (7.5/92.5 and 80/20) were studied. Density and compressive strength decreased when different wastes were added in every proportion. Additions of 7.5% of both shells reduce the density to about 2.5% and the compressive strength to 20%, while 80% reduces the density to 20% and the compressive strength to 90%, while the addition of biomass fly ash decreases the density and compressive strength in a higher proportion than shells. The durability against acid attack is increased when the three wastes are used, and this increase is higher when the waste dosage is increased (up to 15 times more when 80% biomass ash is used). With respect to leaching, scallop and eggshells can be used as a component of hydraulic road binder, but olive pomace ash presents leaching values higher than the limits of different regulations (Se, Pb, Ni, Mo, Cu, and As). From a radiological perspective, all road-base binders present an activity concentration index lower than 1, except when olive pomace ash was used, and the binders showed higher values of 40K due to the high potassium content of fly ash.
A New Partitioned Spatial–Temporal Graph Attention Convolution Network for Human Motion Recognition
Authors: Guo Keyou , Wang Pengshuo , Shi Peipeng , He Chengbo , Wei Caili
Published: January 2023

At present, human action recognition can be used in all walks of life, because the skeleton can transmit intuitive information without being affected by environmental factors. However, it only focuses on local information. In order to solve these problems, we introduce a neural network model for human body recognition in this paper. We propose a model named NEW-STGCN-CA. The model is based on a spatial–temporal graph convolution network (ST-GCN), which contains a new partition strategy and coordination attention (CA) mechanism. By integrating the CA attention mechanism model, we enable the network to focus on input-related information, ignore unnecessary information, and prevent information loss. Second, a new partitioning strategy is proposed for the sampled regions, which is used to enhance the connection between local information and global information. We proved that the Top-1 accuracy of the NEW-STGCN-CA model in the NTU-RGB+D 60 dataset reached 84.86%, which was 1.7% higher than the original model; the accuracy of Top-1 on the Kinetics-Skeleton dataset reached 32.40%, which was 3.17% higher than the original model. The experimental results show that NEW-STGCN-CA can effectively improve the algorithm’s accuracy while also having high robustness and performance.
Camphor-Soothed Banana Stem Biowaste in the Productivity and Sustainability of Solar-Powered Desalination
Authors: Kaviti Ajay Kumar , Akkala Siva Ram , Sikarwar Vineet Singh , Sai Snehith Pilli , Mahesh Moodapelly
Published: January 2023

The increasing need for clean water can be attributed to a number of reasons, such as population growth, industrial development, and climate change. As a result of modern industrial and agricultural methods, the amount of trash generated daily is also on the rise. Waste management and increasing demand for freshwater are two of the most pressing problems facing the human race today and in the future. This study makes an attempt to strike a balance between these two concerns by repurposing a common biowaste, the banana stem, to collect solar energy for a desalination application. Banana stems work well for interfacial solar desalination because of their capillarity and the fact that they float. Camphor-soothed banana stems were placed in a solar still to collect solar thermal energy and to transfer it to the water surrounding them, speeding up the evaporation process and resulting in more freshwater. Over the course of three days, measurements were taken with the water level held constant and the stem thickness of the bananas varied between 0.5 and 1.5 cm. Enviro-economic studies and water quality analysis were used to calculate greenhouse gas emissions, carbon dioxide mitigation, and the carbon credits obtained. Compared to a standard still, a maximum yield of 934 mL was achieved at an efficiency of 36.35 percent. The CPLs (costs per liter) for the MSS (modified solar still) and the CSS (conventional solar still) were USD 0.0503 and USD 0.0665. In comparison to its CSS counterpart, the MSS had a CPL that was 32.21 percent lower. The treated water retained a 95.77% reduction in TDS compared to salt water. The MSS is predicted to release 219.62 kg of carbon dioxide, 1.67 kg of sulfur dioxide, and 0.69 kg of nitrous oxide over its lifetime. In addition, the MSS saved USD 20.94 in carbon credits after avoiding the emission of 2.09 tonnes of CO2.
Motion Technologies in Support of Fence Athletes: A Systematic Review
Authors: Aresta Simona , Musci Mariapia , Bottiglione Francesco , Moretti Lorenzo , Moretti Biagio , Bortone Ilaria
Published: January 2023

Sports biomechanics enables thorough examination of athletic movements to enhance athletic performance and/or reduce injury risk. Few studies have looked at the possibilities of cutting-edge technology in fencing, even though it presents an intriguing scenario for sports biomechanics due to the significant demands it places on the body in terms of neuromuscular coordination, strength, power, and musculoskeletal system impact. The aim of the study is to identify and summarise current evidence on the application of motion technologies in support of fence athletes and to provide a framework for the assessment and training of fencers, including performance measures and protocols. Peer-reviewed research was identified from electronic databases using a structured keyword search. Details regarding experimental design, study group characteristics, and measured outcomes were extracted from retrieved studies, summarised, and information regrouped under themes for analysis. The methodological quality of the evidence was evaluated. Thirty-five studies were included in the present review, which showed kinetic, kinematic, muscle recruitment and coordination differences among athletes as gender and athletic training differed. Findings revealed that most of the included studies investigated the lunge technique in professional athletes using Optoelectronic Systems and force platforms as preferred motion technologies. Only nine studies reported the assessment of muscle activation during task execution (25.7%). Less than 20% of the study recurred to Artificial Intelligence/Machine Learning (AI/ML) approaches in the analysis. The potential contribution of the user’s kinematic/kinetic data and physiological measures is still underestimated. The recommendations provided in this study could help promote and support further cross-sectional and longitudinal studies in the field.
Assessment of Sieving as a Mean to Increase Utilization Rate of Biomass Fly Ash in Cement-Based Composites
Authors: Popławski Jakub , Lelusz Małgorzata
Published: January 2023

Biomass fly ash is a growing challenge for combustion by-product (CBP) management. This research was conducted to investigate the influence of activation by sieving through a 63 µm sieve and a 125 µm sieve on fresh and hardened cement mortar properties. Sieving increased the CaO content by 9.3 percentage points (p.p.) in the oxide composition of the fly ash. The 28-day Strength Activity Indices increased by 24.9 p.p. A 25% replacement rate of cement with fly ash sieved with a 63 µm sieve increased the 2-day compressive strength of mortars by 24% when compared with untreated fly ash. The 90-day compressive strength results of cement mortars with a 15% replacement rate of cement with fly ash sieved with a 63 µm sieve were similar to the control specimen results. The utilization rate of biomass fly ash can be increased to 15% of binder mass without the detrimental effect of the mechanical properties of cement mortar. SEM and TG analyses showed that activated biomass fly ash promoted the growth of the C-S-H phase and ettringite.
A System Dynamics Approach to Optimize Milk Production in an Industrial Ranch
Authors: Shahsavari-Pour Nasser , Rahimi-Ashjerdi Sajad , Heydari Azim , Fekih Afef
Published: January 2023

The milk production process on an industrial ranch consists of various and regular activities, with each requiring a proper management approach. Different variables also affect the milk production process, and the maximum milk production is achieved by identifying critical variables. This work was motivated by the Fereidan Ahrar ranch management in Isfahan, Iran, which seeks to identify and optimize important variables to increase milk production. This unit also considers livestock omission due to disease and losses as one of the important issues. This kind of omission is followed by the increased medical costs of the ranch. This paper investigated a system dynamics approach and Vensim software to simulate the milk production process considering the combination of demographic livestock and medical costs. System sensitivity was analyzed using the design of experiment (DOE) technique and some scenarios were proposed to maximize milk production by identifying and tuning important variables affecting milk production. The simulation results of the designed model showed five important variables affecting milk production. These variables include the production cycle rate, voluntary omission rate, change rates of female calves per year that are entered into the life cycle of the ranch, pregnant heifers that become dairy herds after calving, and finally, the effect of the medical costs.
Application of Extrusion-Cooking for Processing of White and Red Bean to Create Specific Functional Properties
Authors: Mitrus Marcin , Wójtowicz Agnieszka , Oniszczuk Tomasz , Combrzyński Maciej , Bouasla Abdallah , Kocira Sławomir , Czerwińska Ewa , Szparaga Agnieszka
Published: January 2023

Extrusion-cooking, as a modern and versatile processing method, may be applied to create the properties of food ingredients and active components, especially beans and legumes. Two varieties of bean (red Toska and white Aura) were extruded with twin-screw extruder under various conditions (water dosing 0.8–2.4 l h−1, screw speed 300–700 rpm). Physical properties (energy consumption, expansion ratio, water absorption and solubility, viscosity, texture, color) and chemical characteristics (protein, fiber, reducing sugars, total phenols, anthocyanins, flavonoids, antioxidant activity and reducing power) were evaluated. Regardless of the bean cultivar, energy consumption significantly increased for about 60% with the extruder screw speed increase, and at the same time, the greater water addition reduced energy consumption by about 30%. The physical properties and texture of extruded bean were significantly connected with processing conditions for both bean varieties. Chemical composition and nutritional characteristics were different for red and white bean, especially phenols and anthocyanins levels were higher in red bean extrudates; significant effects of extrusion variable conditions were found in most characteristics. Nevertheless, the knowledge of the effect of red and white beans extrusion treatment on tested characteristics allows to select processing conditions to achieve ready-to-eat extrudates or functional additives with specific features.
An Anomaly Detection-Based Domain Adaptation Framework for Cross-Domain Building Extraction from Remote Sensing Images
Authors: Zhao Shaoxuan , Zhou Xiaoguang , Hou Dongyang
Published: January 2023

Deep learning-based building extraction methods have achieved a high accuracy in closed remote sensing datasets. In fact, the distribution bias between the source and target domains can lead to a dramatic decrease in their building extraction effect in the target domain. However, the mainstream domain adaptation methods that specifically address this domain bias problem require the reselection of many unlabeled samples and retraining in other target domains. This is time-consuming and laborious and even impossible at small regions. To address this problem, a novel domain adaptation framework for cross-domain building extraction is proposed from a perspective of anomaly detection. First, the initial extraction results of images in the target domain are obtained by a source domain-based pre-trained model, and then these results are classified into building mixed and non-building layers according to the predicted probability. Second, anomalous objects in the building layer are detected using the isolation forest method. Subsequently, the remaining objects in the building layer and the objects in the non-building layer are used as positive and negative samples, respectively, to reclassify the mixed layer using the random forest classifier. The newly extracted objects are fused with the remaining objects in the building layer as the final result. Four different experiments are performed on different semantic segmentation models and target domains. Some experimental results indicate that our framework can improve cross-domain building extraction compared to the pre-trained model, with an 8.7% improvement in the F1 metric when migrating from the Inria Aerial Image Labeling dataset to the Wuhan University dataset. Furthermore, experimental results show that our framework can be applied to multiple target domains without retraining and can achieve similar results to domain adaptation models based on adversarial learning.
Machine Intelligence and Autonomous Robotic Technologies in the Corporate Context of SMEs: Deep Learning and Virtual Simulation Algorithms, Cyber-Physical Production Networks, and Industry 4.0-Based Manufacturing Systems
Authors: Nagy Marek , Lăzăroiu George , Valaskova Katarina
Published: January 2023

This study examines Industry 4.0-based technologies, focusing on the barriers to their implementation in European small- and medium-sized enterprises (SMEs). The purpose of this research was to determine the most significant obstacles that prevent SMEs from implementing smart manufacturing, as well as to identify the most important components of such an operationalization and to evaluate whether only large businesses have access to technological opportunities given the financial complexities of such an adoption. The study is premised on the notion that, in the setting of cyber-physical production systems, the gap between massive corporations and SMEs may result in significant disadvantages for the latter, leading to their market exclusion by the former. The research aim was achieved by secondary data analysis, where previously gathered data were assessed and analyzed. The need to investigate this topic originates from the fact that SMEs require more research than large corporations, which are typically the focus of mainstream debates. The findings validated Industry 4.0′s critical role in smart process planning provided by deep learning and virtual simulation algorithms, especially for industrial production. The research also discussed the connection options for SMEs as a means of enhancing business efficiency through machine intelligence and autonomous robotic technologies. The interaction between Industry 4.0 and the economic management of organizations is viewed in this study as a possible source of significant added value.
Self-Attentive Subset Learning over a Set-Based Preference in Recommendation
Authors: Liu Kunjia , Chen Yifan , Tang Jiuyang , Huang Hongbin , Liu Lihua
Published: January 2023

Recommender systems that learn user preference from item-level feedback (provided to individual items) have been extensively studied. Considering the risk of privacy exposure, learning from set-level feedback (provided to sets of items) has been demonstrated to be a better way, since set-level feedback reveals user preferences while to some extent, hiding his/her privacy. Since only set-level feedback is provided as a supervision signal, different methods are being investigated to build connections between set-based preferences and item-based preferences. However, they overlook the complexity of user behavior in real-world applications. Instead, we observe that users’ set-level preference can be better modeled based on a subset of items in the original set. To this end, we propose to tackle the problem of identifying subsets from sets of items for set-based preference learning. We propose a policy network to explicitly learn a personalized subset selection strategy for users. Given the complex correlation between items in the set-rating process, we introduce a self-attention module to make sure all set members are considered in subset selecting process. Furthermore, we introduce gumble softmax to avoid gradient vanishing caused by binary selection in model learning. Finally the selected items are aggregated by user-specific personalized positional weights. Empirical evaluation with real-world datasets verifies the superiority of the proposed model over the state-of-the-art.
Automatic Measurement of Inclination Angle of Utility Poles Using 2D Image and 3D Point Cloud
Authors: Chen Lei , Chang Jiazhen , Xu Jinli , Yang Zuowei
Published: January 2023

The utility pole inclination angle is an important parameter for determining pole health conditions. Without depth information, the angle cannot be estimated from a 2D image, and without large labeled reference pole data, it is time consuming to locate the pole in the 3D point cloud. Therefore, this paper proposes a method that processes the pole data from the 2D image and 3D point cloud to automatically measure the pole inclination angle. Firstly, the mask of the pole skeleton is obtained from an improved Mask R-CNN. Secondly, the pole point cloud is extracted from a PointNet that deals with the generated frustum from the pole skeleton mask and depth map fusion. Finally, the angle is calculated by fitting the central axis of the pole cloud data. ApolloSpace open dataset and laboratory data are used for evaluation. The experimental results show that the AP75 of improved Mask R-CNN is 58.15%, the accuracy of PointNet is 92.4%, the average error of pole inclination is 0.66°, and the variance is 0.12°. It is proved that the method can effectively realize the automatic measurement of pole inclination.
Regeneration of Intrabony Defects with Nano Hydroxyapatite Graft, Derived from Eggshell along with Periosteum as Barrier Membrane under Magnification—An Interventional Study
Authors: Vani Tammina Mohana Sri , Paramashivaiah Rashmi , Prabhuji Munivenkatappa Laxmaiah Venkatesh , Peeran Syed Wali , Fageeh Hytham , Tasleem Robina , Bahamdan Ghadah Khaled , Aldosari Lujain Ibrahim N. , Bhavikatti Shaeesta Khaleelahmed , Scardina Giuseppe Alessandro
Published: January 2023

Intrabony defects can be treated by various approaches. Use of GTR along with bone grafts is said to enhance the outcome. The periosteum has been claimed to increase the regeneration. The egg-shell-derived nano hydroxyapatite (EnHA) has shown a scope as alloplastic graft. Thus, the following study was undertaken to combine the periosteal pedicle along with EnHA for the treatment of intrabony defects under magnification to achieve optimal bone regeneration. A total of 21 patients, having intrabony defects with ≥6 mm probing depth (PD) and two or three wall defects as detected on CBCT, satisfying inclusion criteria were enrolled. The sites were randomly allocated as Group A, B and C (n = 7). The following parameters, defect density and defect fill in CBCT (at baseline and 6 months), PPD, RAL, Plaque index (PI), Gingival index (GI) and Gingival Bleeding Index (GBI) were recorded at baseline, 1, 3 and 6 months. p < 0.05 is considered as statistically significant. Bone density and bone fill values were found to be much higher in pedicle with EnHA and EnHA alone group and the values showed statistically significant results. The current clinical research showed that periosteal pedicle along with EnHA and EnHA as stand-alone therapy gave superior results compared to OFD alone, which is an innovative and feasible treatment option.
Exploring the Intersection between Software Maintenance and Machine Learning—A Systematic Mapping Study
Authors: Bastías Oscar Ancán , Díaz Jaime , López Fenner Julio
Published: January 2023

While some areas of software engineering knowledge present great advances with respect to the automation of processes, tools, and practices, areas such as software maintenance have scarcely been addressed by either industry or academia, thus delegating the solution of technical tasks or human capital to manual or semiautomatic forms. In this context, machine learning (ML) techniques play an important role when it comes to improving maintenance processes and automation practices that can accelerate delegated but highly critical stages when the software launches. The aim of this article is to gain a global understanding of the state of ML-based software maintenance by using the compilation, classification, and analysis of a set of studies related to the topic. The study was conducted by applying a systematic mapping study protocol, which was characterized by the use of a set of stages that strengthen its replicability. The review identified a total of 3776 research articles that were subjected to four filtering stages, ultimately selecting 81 articles that were analyzed thematically. The results reveal an abundance of proposals that use neural networks applied to preventive maintenance and case studies that incorporate ML in subjects of maintenance management and management of the people who carry out these tasks. In the same way, a significant number of studies lack the minimum characteristics of replicability.
Space–Time Variations of the Apparent Resistivity Associated with Seismic Activity by Using 1D-Magnetotelluric (MT) Data in the Central Part of Colombia (South America)
Authors: Vargas Carlos A. , Gomez J. Sebastian , Gomez Juan J. , Solano Juan M. , Caneva Alexander
Published: January 2023

In this work, we apply multi-temporal 1D-magnetotelluric (MT) surveys to estimate the space–time variations of the apparent resistivity ρa and correlate these changes with seismic activity in the central part of Colombia (South America). We use the time series of the Earth’s natural electric and magnetic fields registered at two MT stations of the National University of Colombia Seismological Network (RSUNAL), located in the Eastern Andean Cordillera, in the central part of Colombia, over several days. Assuming that large earthquakes may generate these types of anomalies, we identified positive results for the Mesetas earthquake (Mw6.0, Lon = 74.184° W, Lat = 3.462° N, H = 13 km-depth, 24 December 2019, UTC 19:03:55), with anomalies registered eight hours before the mainshock. The depth at which the resistivity anomaly was identified coincides with the depth of the earthquake hypocenter. The origin of these anomalies may be associated with the migration of fluids due to the change in the stress regime before, during, and after the earthquake. We hypothesize that before the occurrence of an earthquake, the stress field generates pore pressure gradients, promoting alterations in fluid migration that change the resistivity of the upper crust.
Fault Analysis of a Small PV/Wind Farm Hybrid System Connected to the Grid
Authors: Dhouib Bilel , Zdiri Mohamed Ali , Alaas Zuhair , Hadj Abdallah Hsan
Published: January 2023

The dynamic modeling, control, and simulation of renewable energy sources connected to the electrical grid are investigated in this study. Photovoltaic (PV) systems and wind systems connected to the power grid via the point of common connection (PCC) were the only two systems included in our study. Simulation and control methodologies are provided. For both PV arrays, the method of extracting maximum power point tracking (MPPT) is utilized to obtain the highest power under standard test conditions (STC: 1000 W/m2, 25 °C). A power electronics converter that can transform DC voltage into three-phase AC voltage is required to connect a PV system to the grid. Insulated gate bipolar transistors (IGBTs) are utilized in a three-level voltage source converter (VSC). The distribution network is connected to this three-phase VSC by way of a step-up transformer and filter. During synchronous rotation in the d−q reference frame, the suggested control for the three-level solar power system that is connected to the grid is constructed. To obtain a power factor as near to one as possible, the phase-locked loop (PLL) is employed to align the angle of the power grid voltage with the angle of the current coming from the inverter. Squirrel-cage induction generators (SCIGs), which are utilized as fixed speed generators and are linked directly to the power network, are the foundation of the wind system. Additionally, a pitch angle control approach is suggested to keep the wind turbine’s rotor speed stable. MATLAB/Simulink software is utilized to model and simulate the suggested hybrid system. Under fault scenarios such as the line to line to line to ground fault (LLLG fault), the suggested hybrid system’s dynamic performance is examined. The simulation results prove the ability to manage the small hybrid system that combines solar and wind power, as well as its dynamic performance.
Prevention of Bacterial Infiltration in Class 1 Temporary Restorations Using Zinc Oxide/Calcium Sulphate Filling Materials: An In Vitro Study
Authors: Buonavoglia Alessio , Trotta Adriana , Pellegrini Francesco , Iandolo Alfredo , Cordisco Marco
Published: January 2023

This study evaluated sealing properties of zinc oxide/calcium sulphate filling material (Plastor©) to prevent bacterial infiltration in simulated Class 1 cavities with and without the presence of a spacer apically the restoration. Twenty-eight experimental Eppendorf tubes containing Tryptic Soy Agar were prepared and divided into seven groups: group A (Plastor©), group B (Plastor© + cotton pellet), group C (Plastor© + cotton pellet soaked of m-cresyl acetate), group D (Plastor© + cotton pellet soaked of eugenol), group E (Plastor© + PTFE pellet), group F (positive control), and group G (negative control). All prepared vials were individually immersed in tubes containing 5 mL of a suspension of Streptococcus mutans (105 CFU/mL) previously prepared and then incubated at 37 °C for 5 and 10 days. Subsequently, agar was collected and tested for S.mutans using real-time PCR. Aliquots of each agar samples were separately seeded on TSA for S. mutans isolation. The real-time PCR tests were negative for S. mutans on all the vials at both T5 and T10, except for positive control resulted positive at both T5 and T10. The isolation tests showed bacterial growth of S. mutans only with the agar samples collected from the vials of positive control, confirming real-time PCR tests. This in vitro study evidenced complete sealing ability of zinc oxide/calcium sulphate in temporary restorations of Class 1 cavities without mechanical loading at 10 days and complete immersion in a bacterial suspension. Moreover, sealing ability is not influenced by presence of spacers.
Adopted Factorial and New In-Situ Micro-Designs for Stimulation of Matrix Acidizing of Carbonate Reservoir Rocks
Authors: Abdulrahman Aram , Salih Namam , Kamal Ibtisam , Préat Alain
Published: January 2023

Matrix acidizing has been developed in the petroleum industry for improving petroleum well productivity and minimizing near-wellbore damage. Mud acid (HF: HCl) has gained attractiveness in improving the porosity and permeability of reservoir formation. However, there are several challenges facing the use of mud acid, comprising its corrosive nature, high pH value, formation of precipitates, high reaction rate and quick consumption. Therefore, different acids have been developed to solve these problems, including organic-HF or HCl acids. Some of these acid combinations proved their effectiveness in being alternatives to mud acid in reservoir rock acidizing. The current research deals with a new acid combination based on Hydrochloric–Oxalic acids for acidizing carbonate core samples recovered from Qamchuqa Formation in Kirkuk oilfield, northern Iraq. A new in-situ micro-model adopted laboratory technique is utilized to study the microscale alteration and evolution of pore spaces, dissolved grains and identification of matrix acidizing characteristics. The in-situ micro-model is based on the injection of an identical dose of different concentrations of the new acid combination into thin section samples under an optical light microscope. The adopted procedure aims to provide unique and rapid information regarding the potential for texture and porosity modification that can be caused by the acidizing stimulation procedure. In connection, solubility tests for the untreated and treated reservoir core samples and the density of the combined acids after treatment are conducted based on designed experiments using response surface methodology (RSM). The effect of acid concentration [12% HCl: Oxalic acid (3.8–8.8%)] and acidizing temperature (from ambient to 78.8 °C) on the solubility percentage of the samples and percentage increase in the combined acid density after acidizing were optimized and modeled. The obtained results confirm that the optimum dissolution of the core samples took place using 12% HCl:3.2% Oxalic acid with an optimum solubility (%) of the carbonate core rock of 53.78% at 21.7 °C, while the optimum increase in density (%) of the combined acids was 1.54% at 78.3 °C. The promising results could be employed for matrix acidizing of carbonate reservoir rocks for other oilfields.
Age Estimation from Brain Magnetic Resonance Images Using Deep Learning Techniques in Extensive Age Range
Authors: Usui Kousuke , Yoshimura Takaaki , Tang Minghui , Sugimori Hiroyuki
Published: January 2023

Estimation of human age is important in the fields of forensic medicine and the detection of neurodegenerative diseases of the brain. Particularly, the age estimation methods using brain magnetic resonance (MR) images are greatly significant because these methods not only are noninvasive but also do not lead to radiation exposure. Although several age estimation methods using brain MR images have already been investigated using deep learning, there are no reports involving younger subjects such as children. This study investigated the age estimation method using T1-weighted (sagittal plane) two-dimensional brain MR imaging (MRI) of 1000 subjects aged 5–79 (31.64 ± 18.04) years. This method uses a regression model based on ResNet-50, which estimates the chronological age (CA) of unknown brain MR images by training brain MR images corresponding to the CA. The correlation coefficient, coefficient of determination, mean absolute error, and root mean squared error were used as the evaluation indices of this model, and the results were 0.9643, 0.9299, 5.251, and 6.422, respectively. The present study showed the same degree of correlation as those of related studies, demonstrating that age estimation can be performed for a wide range of ages with higher estimation accuracy.
Petrography and Geochemistry of Gahirat Marble in Relation to Geotechnical Investigation: Implications for Dimension Stone, Chitral, Northwest Pakistan
Authors: Bukhari Syed Amjad Ali , Basharat Muhammad , Janjuhah Hammad Tariq , Mughal Muhammad Saleem , Goher Aqeel , Kontakiotis George , Vasilatos Charalampos
Published: January 2023

The modernization of human civilization has led to the prospect of better and more durable building materials. Marble, found in various colors and textures, has been used as a building stone for centuries, either as cut stone or polished stone. The present study evaluated the petrological, geochemical, and geotechnical characterizations of the Gahirat Marble formation as a building stone. It is exposed over an area of 160 square kilometers in southwestern Chitral. The Gahirat Marble formation has been divided into two parts, i.e., the eastern and western parts. The eastern part is a coarse crystalline rock that exhibits a granulose structure and was subjected to amphibolite facies metamorphism, whereas its western part is a coarse-to-medium crystalline rock that displays a differential granulose structure and was subjected to green schist facies metamorphism. Petrographically, it is composed mainly of calcite (>92%) with minute quartz, chlorite, muscovite, biotite, garnet, and opaque minerals. The X-ray fluorescence (XRF) technique was used to analyze the chemical composition of the Gahirat Marble showing that it is a pure calciocarbonate marble (CaO: 53.16–55.02 wt.%). The specific gravity measured varies from 2.46–2.71 gm/cm3, water absorption is <0.2%, sulfate soundness is <0.65, and due to its unconfined compressive strength, it is classified as strong rock, thus conforming to ASTM C503 specifications. The results acquired from the investigated samples suggest they are suitable as dimension stones. Until now, it has been limitedly mined and marketed but can be further exploited for export trade, based upon its petrographic, geotechnical, and geochemical characterization.
Comparative Evaluation of Microhardness, Water Sorption and Solubility of Biodentin and Nano-Zirconia-Modified Biodentin and FTIR Analysis
Authors: Batul Rumesa , Makandar Saleem D. , Nawi Mohamad Arif Bin Awang , Basheer Syed Nahid , Albar Nassreen H. , Assiry Ali A. , Luke Alexander Maniangat , Karobari Mohmed Isaqali
Published: January 2023

Aim: This study compares the microhardness, water sorption and solubility of nano-zirconia-reinforced biodentin groups to commercially available biodentine. Materials and Methods: Samples were prepared by adding different percentages of nano zirconia to biodentin. Four groups were categorized as follows: group 1 used Biodentin as the control group, group 2 used 10% nano zirconia and 90% Biodentine, group 3 used 20% nano zirconia and 80% Biodentine, and group 4 used 30% nano zirconia and 70% Biodentine. A Vickers microhardness tester was used to measure the microhardness of the groups according to ISO 4049/2000. The water sorption and solubility of the divided groups were assessed using disk-shaped molds. The second weight was measured on an electronic weight machine after two weeks, and values were recorded. FTIR analysis was performed. Vickers microhardness, water sorption and solubility were analyzed using a one-way ANOVA, and for multiple comparisons, a post hoc Tukey’s HSD test with a significance level of p < 0.05 was performed. Group 3 had the highest mean microhardness measurement among all groups. The microhardness values for all groups in descending order are as follows: group 3, group 2, group 1 and group 4 (p = 0.008). Group 2 showed the lowest mean of water sorption compared among all groups. Group 2 has the lowest mean of water sorption, followed by group 3, group 1 and group 4 (p = 0.002). Group 4 showed the highest water sorption among all groups. Group 4 exhibited the highest solubility mean among all groups. Group 1 had the lowest mean of solubility, followed by group 2, group 3 and group 4 (p = 0.000). The FTIR spectra of different types of biodentin showed the absorbance peaks of the precipitates of each modified biodentin. The absorbance peaks fell between 474.63 cm−1 and 3438.33 cm−1. Conclusion: Biodentin is a competitive biomimetic material, but it lacks hardness and has more solubility. Thus, adding nano zirconia improved microhardness and reduced water sorption. The solubility of 20% nano zirconia added to biodentin was almost close to biodentin but with no significance. The 20% nano-zirconia-modified biodentin showed overall better properties compared to biodentin. The 20% nano-zirconia-modified biodentin can be used in deep cavities as a single restorative material instead of multi-layered restorations to increase longevity without microleakage and failure of restoration.
Effects of Entrance Shape and Blast Pocket on Internal Overpressure Mitigation for Protective Tunnels Exposed to External Detonation on the Ground
Authors: Shin Jinwon , Pang Seungki , Kim Dong-Keon
Published: January 2023

This study presents a numerical analysis to reduce the overpressure inside protective tunnels for external detonations. A three-dimensional computational fluid dynamics model of a tunnel subjected to detonation for a hemispherical charge with a charge weight of 555 kg and a standoff distance of 7.6 m was established, based on a mesh sensitivity study to obtain an optimal element size, stability analysis of overpressure, and validation study to evaluate the accuracy of the numerical results based on Unified Facilities Criteria (UFC) 3-340-02. A parametric analysis was performed using the validated numerical model to investigate the effects of the entrance shape and blast pockets on the reduction in the maximum overpressure. The maximum overpressures were effectively reduced as the slope angle of the tunnel entrance decreased and the length of the blast pocket divided by the tunnel width decreased. An optimized shape of the tunnel was proposed based on the numerical results, where the peak overpressures were reduced by a maximum of 64.5%. This study aims to protect facilities, personnel, and equipment and further reduce construction costs by lowering the overpressure rating of blast valves in protective tunnels.
X-ray Particle Tracking Velocimetry in an Overflowing Foam
Authors: Lappan Tobias , Herting Dominic , Ziauddin Muhammad , Stenzel Julian , Shevchenko Natalia , Eckert Sven , Eckert Kerstin , Heitkam Sascha
Published: January 2023

In mineral processing, froth flotation is based on recovering valuable mineral particles by means of the overflowing froth. Industrial-scale froth flotation cells are typically equipped with optical measurement systems, which monitor the bubble sizes and flow velocities at the froth surface. However, the velocity profile of the overflowing froth underneath its free surface is not accessible by optical observation. The present study combines X-ray radiography and particle tracking velocimetry in a laboratory-scale experiment aiming to measure local flow velocities within an optically opaque foam at a weir, which here describes a one-sided horizontal overflow. For this purpose, we prepared custom-tailored tracer particles: small 3D-printed polymer tetrahedra with tiny metal beads glued to the tetrahedral tips. In parallel to the velocity measurements by means of X-ray particle tracking, we determined the liquid fraction of the overflowing foam by electric conductivity measurements using electrode pairs. The experiment was performed with aqueous foams of two different surfactant concentrations but similar bubble size range and superficial gas velocity, yielding around 10% liquid fraction near the weir. Employing the particles as tools for flow tracing in X-ray image sequences, we measured the velocity profile in vertical direction above the weir crest and found that the maximum velocity is reached underneath the free surface of the overflowing foam.
Design and Characterization of a Single Lever Bicycle Brake with Hydraulic Pressure Proportioning
Authors: Machado Michael D. , Viswanathan Vimal K.
Published: January 2023

In 2019, the Centers for Disease Control and Prevention estimated that 329,000 Americans were injured in cycling-related incidents. Since the first bicycle brake in 1817, there has been an individual brake lever for decelerating each wheel, while on cars, there has been a single control lever for decelerating multiple wheels since 1921. To perform an emergency stop on a bicycle, the rider must proportion hand pressure on each brake lever and simultaneously vary hand pressure throughout the duration of the maneuver to match the variations of normal force on each tire. Only highly skilled riders, with years of training and practice, can correctly proportion brake pressure to maximize available traction and thus minimize stopping distances. The objective of this study is to simulate and prototype a hydraulic, single-lever bicycle brake system, integrating front and rear brake proportioning, which minimizes stopping distance compared to dual-lever simulations. A design is developed to address the brake proportioning issue. Based on the simulations and physical model, the prototype proportioning valve decreased simulated stopping distances up to 18%. Exploring a range of bike types and scenarios, stopping distances were decreased between 13% and 26%. Simulating an ideal proportioning valve, stopping distances were further decreased between 4% and 40%. These results show that there can be an advantage to brake proportioning technologies in bicycles.
Comparison of Fatigue Performances Based on Shape Change of Rail Fastening Spring
Authors: Fang Xiao-Jun , Park Yeun-Chul , Hu Jong-Wan , Sim Hyoung-Bo
Published: January 2023

The fastening spring of a rail fastening system serves as an important connection in transferring the train load to the sleeper via rails on railway tracks. During initial fastening, a large tensile stress exceeding the yield stress can occur in the fastening spring structure, making it vulnerable to fatigue owing to stress fluctuations during train use. The damage caused by fatigue in the fastening springs have been reported for rail fastening systems on several domestic and international routes; however, research on this topic is limited. This study evaluates the fatigue performance of a fastening spring, SPS9 spring steel, developed in Korea based on shape change by performing a sensitivity analysis of various factors, including the heights at the end of the fastening spring and the spring arm, overall lateral width, and the diameter of the cross section of the fastening spring. The modified Goodman fatigue diagram was applied based on the tensile stress on initial fastening and the constant stress range due to a rail vertical displacement caused by train use through finite element analysis. The fatigue analysis showed that the lateral width and diameter factors of the fastening spring are found to be important variables for fatigue performance. Moreover, as the width and diameter increase, the fatigue performance improves significantly. The fatigue safety margin increased from 64% to 82% when the width increased from −20% to +20%, and increased from 54% to 81% with the diameter increase from 13 mm to 18 mm.
Sensitivity of Cell Cultures on Time-Varying Low-Frequency Magnetic Field Changes
Authors: Judakova Zuzana , Radil Roman , Janousek Ladislav , Pobocikova Ivana
Published: January 2023

This article is focused on the in vitro experimental verification of the basic necessary conditions for valid interpretation of an ion parametric resonance prediction model of biological reaction on an externally applied, extremely low-frequency magnetic field. Experiments are performed on model organism Saccharomyces cerevisiae strain BY4741, with the intention to target calcium ions, which already produced interesting preliminary results within authors’ previous works, confirming specific magnetic field settings being bioactive. To study the nature and origin of biological reactions more exhaustingly, the research is aimed at two chosen physical aspects of ion parametric resonance theory. In the first part, experiments are set up to verify the resonance point validity for calcium ions and to perform a sensitivity analysis of the biological system response around this point. In the second part, the main attention is paid to the verification of the validity of maximum biological effect at specific BAC/BDC ratios, reflecting the ion parametric resonance theory as well as the current state of the art and knowledge. Both series of experiments have shown interesting results, confirming 29.89 Hz as a bioactive frequency for a BAC/BDC ratio of 1.8. These observations are in close correlation with the assumptions of the ion parametric resonance model for targeting calcium ions. The performed sensitivity analysis around the resonance point looks even more interesting, as conducted preliminary experiments resulted in two more pronounced bioactive frequencies of 24.89 and 34.89 Hz, in terms of biological response significance, than the resonance frequency assumed by an investigated prediction model. The narrow width of the peak, which is typical for physical phenomena of resonant nature, was not observed within this series of experiments, which would be addressed more precisely in future work of authors.