Appl. Sci., Volume 13, Issue 16 (August-2 2023) – 440 articles

The current study aimed at developing an effective organosolv treatment, with the objective to obtain potato peel extracts highly enriched in polyphenols. To this end, two low-cost solvents were employed, 1- and 2-propanol, which are considered green, but they have been rather poorly studied compared to other conventional solvents, such as ethanol. Treatment development also embraced the use of sulfuric acid, a well-examined catalyst in organosolv processes. Treatment evaluation on the basis of response surface optimization and severity demonstrated that 1-propanol was a more effective solvent, providing a maximum yield in total polyphenols of 19.28 mg chlorogenic acid equivalents per g of dry potato peel weight, attained with 40% 1-propanol/1.5% (w/v) sulfuric acid at a treatment time of 60 min and a temperature of 90 °C. This treatment was of lower severity compared to the one with 2-propanol, and it also provided almost 24% higher total polyphenol yield. The extracts produced contained chlorogenic acid as the major constituent, accompanied by caffeic acid and minor amounts of p-coumaric acid. This is the first report on such an organosolv treatment of potato peels to recover polyphenolic compounds with high efficiency. Full article

Ticks are significant vectors of pathogens in human and veterinary medicine and have been identified as (re)emerging health threats. The primary objective of this study was to collect new data on the fauna of hard ticks within the region of Istria with a focus on spatial distribution using a geographical information system (GIS). All tick specimens were collected over three years (2020–2023), and this research included all 41 self-government units of Istria and Brijuni Islands National Park. Ticks were collected using the flagging/dragging method and manually from hosts (humans, domestic, or wild animals). In addition, morphological identification using tick keys was performed. The obtained data were used to create maps and feed models and to predict risk assessments. Collected data reveal the predominant presence of Ixodes ricinus, accounting for (n = 446) or 48.1% of the tick population. Rhipicephalus sanguineus (Ixodida: Ixodidae) follows with (n = 253) or 27.23%, and Hyalomma marginatum represents (n = 136) or 14.64% of the tick species collected using the host method in the region. Tick–host relationships are complex and influenced by a range of ecological and environmental factors. The results of this research will contribute to a better understanding, identification, and prediction of the changes in their geographic ranges and help in the prevention and control of zoonosis transmitted to humans by ticks. The obtained results mapped using GIS support the first study on the spatial distribution of ticks in the region of Istria in Croatia. Full article

Magnetic levitation can reduce particulate contamination that occurs during wafer transportation in the semiconductor manufacturing process. This technology radically eliminates contact between the wafer and the transport system, reducing friction, wear, and particle generation. Therefore, it is suitable for achieving high cleanliness in the ultra-fine line-width semiconductor production process and solving the need for particle removal in a vacuum environment. In this study, the roller and linear motion guide components of the wafer transfer system were replaced with a magnetic levitation module, and a robot arm was installed on top to transport a single wafer. A posture controller and a current controller were designed, and test equipment simulating the wafer transfer system was also manufactured and tested. Regarding mover and system identification, a sine sweep test was performed on the motion axis of the five degrees of freedom. Through the obtained system identification, it was possible to design the posture controller more precisely. Moreover, through levitation in standstill experiments and high-speed operation experiments, the wafer transport system can be used to verify dust-free high-speed transport and accurate positioning performance. Full article

As the fertile topsoil is constantly washed away and agricultural production is decreased, soil erosion is a serious environmental issue that affects the entire planet. All river basins experience changes in land use that affect sediment dynamics, soil erodibility, and hydrologic response. The main reason for the faster erosion rates is frequently attributed to those alterations. In the current study, the Intensity of Erosion and Outflow (IntErO) model was used to estimate the sediment yield and maximum outflow from three river basins in Cluj County, Transylvania, Romania. Because the county is hilly and has significant erosion issues, it is essential to have a solid understanding of how soil erosion occurs in river basins. This will allow for more precise planning of soil conservation projects and will allow for more effective management of the severity of the erosion processes. The IntErO model offers quick, efficient, and feasible insight into how changing land use affects soil erosion processes. The testing of the procedures that have been put into place is an essential component of the ongoing development of watershed management strategies at the regional level. The relief characteristics and predominant land use of the three selected prototype river basins significantly influenced the resulting real soil losses. The application of the IntErO model in assessing soil erosion rates in the Transylvanian hills represents a novel approach. The findings of this study hold potential for informing policymakers in the formulation of more robust regulations pertaining to soil and water conservation. Consequently, the implementation of such measures is expected to contribute to the safeguarding of river basin soils. Full article

This study assessed the stress distribution (in eighty-one 3D models of the second lower premolar) in a stainless-steel bracket and enamel crown under 0.5 N of intrusion, extrusion, rotation, translation, and tipping during a horizontal periodontal breakdown of 0–8 mm. The FEA simulations (totaling 405) employed five failure criteria and assessed the adequacy and accuracy of Von Mises (VM), Tresca (T), Maximum Principal (S1), Minimum Principal (S3), and Hydrostatic Pressure. T and VM criteria showed no change in stress display areas during the periodontal breakdown, seeming to be more correct and adequate than the other three (with unusual stress displays). Both VM and T (found to be more adequate) generated maximum stress areas on the attachment side and the entire base of the bracket, confirming the non-homogenous stress distribution areas and the risks of bond failure. Rotation, translation, and tipping were the most stressful movements and showed slightly lower quantitative values for 8 mm bone loss when compared with the intact periodontium, while intrusion and extrusion showed the opposite behavior (slight increase). Periodontal breakdown did not influence the stress display in the bracket and its surrounding enamel area during the five orthodontic movements. Full article

A dynamic numerical method is established to simulate the stability of the surrounding rocks of the retained roadway in FLAC3D, along with a double-yield constitutive model to simulate the re-compaction process of gangue and a strain-softening constitutive model to simulate the strain-softening characteristic of the coal and the grouted fragmented coal after yielding. The simulation reveals that the grouting slurry diffusion range, the mining affecting the stage behind the working face and the retained coal rib deformation are closely interrelated. Under severe mining-induced stress, the integrity of the surrounding rock is more likely to be destroyed, accompanied by a large number of cracks developing and gradually expanding in the surrounding rocks. The roadway deformation increases in a rapid manner. Meanwhile, the grouting diffusing range increases gradually. The simulation conducted in this study indicates that the optimum support effect can be achieved by grouting in the section before and after the working face affected by the high mining-induced stress. A timely grouting can be used to construct an enhanced surrounding rock-bolting-grouting support system and maintain the stability of the retained roadway. Full article

Pile groups are frequently employed to reinforce soft soil foundations, while the piling process frequently disturbs the adjacent foundation. The shielding effect, which prevents the transmission of disturbances from pile installation, is indispensable for minimizing engineering disturbances and optimizing pile group construction techniques. However, current research focuses predominantly on characterizing the phenomenon of shielding, with a limited exploration of the mechanism. To eliminate the limitation, a numerical investigation of the shielding mechanism of pile groups in a pile–soil system is performed this study. Using the finite difference program FLAC^3D and the cavity expansion theory, a three-dimensional numerical model of a pile–soil foundation was created. During the sequential penetration of piles, the response characteristics of the soil surrounding the piles were investigated. Displacement field was first investigated to determine the presence of shielding effects in the pile group and then highlighted the effective role of the existing piles in controlling deformation. Furthermore, through a combined analysis of the stress and strain fields during piling, the mechanism of the shielding effect induced by pile construction is proposed, which is attributed to the direct obstruction effect of piles and the “soil arching effect” created by the soil between piles. The former is reflected by the direct barrier of the existing pile to the soil displacement induced via the installation of the new piles. The latter is reflected by the obstruction of soil between two existing piles to the displacement of soil passing through the two existing piles. This research provides a comprehensive understanding of the mechanical behavior of the pile–soil system and has practical implications for controlling disturbances and optimizing construction techniques in piling engineering projects. Full article

Air quality in tourist reception areas can be a significant health concern. It also plays an increasingly important role when it comes to choosing tourist destinations. NO₂ is a harmful gas that can cause an increased number of cancer or respiratory diseases. The development of satellite remote sensing techniques now enables a much broader spectrum of air quality analysis than mere point measurements at environment monitoring stations. In the study, the spatial diversity of nitrogen dioxide air pollution over tourist reception areas in Poland was assessed. The lowest pollution was found in national parks and tourist regions. The most polluted air was found in tourist reception areas located near industrial regions and large urban agglomerations. Temporal variation—annual and monthly—and spatial variation were determined (for the period 2019–2021). The highest concentrations, exceeding the WHO recommended value (40 μmol/m²), occurred in the winter and autumn. Low pollution was found in most reception areas in the summer (except cities). In 2020, due to restrictions related to the SARS-CoV-2 epidemic, the NO₂ pollution decreased (10–20%). In the cold half of the year (October–April), NO₂ concentrations greater than 40 μmol/m² occurred for about 20% of national parks, 50% of health resorts, 30% of tourist regions, and 100% of provincial capitals. Full article

Internet of Things technology opens the horizon to a broader scope of intelligent applications in smart cities. However, the massive amount of traffic exchanged among devices may cause security risks, especially when devices are compromised or vulnerable to cyberattack. An intrusion detection system is the most powerful tool to detect unauthorized attempts to access smart systems. It identifies malicious and benign traffic by analyzing network traffic. In most cases, only a fraction of network traffic can be considered malicious. As a result, it is difficult for an intrusion detection system to detect attacks at high detection rates while maintaining a low false alarm rate. This work proposes an integrated framework to detect suspicious traffic to address secure data communication in smart cities. This paper presents an approach to developing an intrusion detection system to detect various attack types. It can be carried out by implementing a Principal Component Analysis method that eliminates redundancy and reduces system dimensionality. Furthermore, the proposed model shows how to improve intrusion detection system performance by implementing an ensemble model. Full article

Human pose estimation, as the basis of advanced computer vision, has a wide application perspective. In existing studies, the high-capacity model based on the heatmap method can achieve accurate recognition results, but it encounters many difficulties when used in real-world scenarios. To solve this problem, we propose a lightweight pose regression algorithm (RepNet) that introduces a multi-parameter network structure, fuses multi-level features, and combines the idea of residual likelihood estimation. A well-designed convolutional architecture is used for training. By reconstructing the parameters of each level, the network model is simplified, and the computation time and efficiency of the detection task are optimized. The prediction performance is also improved by the output of the maximum likelihood model and the reversible transformation of the underlying distribution learned by the flow generation model. RepNet achieves a recognition accuracy of 66.1 AP on the COCO dataset, at a computational speed of 15 ms on GPU and 40 ms on CPU. This resolves the contradiction between prediction accuracy and computational complexity and contributes to research in lightweight pose estimation. Full article

The proper application of millimeter-sized spherical porous ceramic supports in catalytic operations relies on their ease of handling, convenient separation, recyclability, high-catalyst-solid loading, and the optimum mass transfer of reactants and products. However, common granulation techniques of spherical carriers entail complex liquid-phase-based processes under severe conditions and the use of toxic or expensive reagents. The present study discusses the manufacturing of porous ceramic granules derived from an inexpensive silica source (diatomite, solid network) and a biopolymer cross-linked by ion exchange (sodium alginate, patterning structure). The results indicated that, with fixed granulation conditions, porous diatomite granules with a sphericity of approximately 0.9 could be successfully obtained by optimization of the diatomite/sodium alginate dispersion to a 30.07 wt.% solid content and 1560 mPa·s viscosity (at ~0.3 s⁻¹). Moreover, the described manufacturing process was proven effective in developing hierarchically porous diatomite granules that were heat-treated at 1200 °C with high sphericity (~0.9), acceptable compressive strength (5.17 ± 0.31 MPa), and porosity features (total porosity: 69.0 ± 2.9%, macropore size: 2.777 μm, mesopore size: 35.34 nm), establishing them as well-matched support materials for either catalytic or adsorption applications. Full article

In this paper, seismic exploration methods are reviewed with a particular emphasis on the use of the reflection seismology to investigate the subsurface structures and characterize active faults. The paper provides a descriptive overview, intended for a non-specialist audience, of the methods and of their recent developments aimed at improving the resolution, accuracy, and computational efficiency of seismic imaging. Techniques such as seismic ray tomography, full-waveform inversion and pre-stack depth migration are briefly introduced, highlighting their potential applications in structural geology studies. The main seismic attributes that have become increasingly important in the interpretation of faults and fractures are also presented, along with some examples of application. Finally, some case studies of active fault characterization are discussed. From these examples, the crucial role played nowadays by the seismic exploration methods for structural studies and for active fault characterization is evident. Full article

Existing research on integrated innovation primarily focuses on the integration of product functions or technologies in the engineering field, with limited exploration of cross-domain integration of biological knowledge. Various organisms exhibit various advantageous biological characteristics, and the multi-biological knowledge embedded within these characteristics can inspire designers to implement product integrated innovation. Biologically Inspired Design (BID) is a method that seeks inspiration from nature to achieve innovation in the engineering field. However, existing BID processes mainly apply the features of a single biological prototype. Against this background, this paper emphasizes how to achieve cross-domain integrated innovation through multi-biological knowledge. First, a method for generating integrated innovation ideas is proposed, achieved through obtaining biological prototypes and analyzing biological performance. Second, by obtaining the principal solution through the three mapping methods of biological effects, behaviors, and structures, a method for building the conceptual structure of integrated innovation is proposed. Finally, in conjunction with the Theory of Inventive Problem Solving (TRIZ), a product-integrated innovation design process model based on biological inspiration is constructed. The method is validated with an example of a six-legged firefighting robot. Full article

Additive manufacturing processes are among the most innovative manufacturing processes of this century. Powder-based direct metal deposition (DMD) is one of these processes. In the DMD process, local shielding takes place via the powder nozzle. The process is therefore critical for oxidation, especially for materials with an affinity for oxidation such as titanium, aluminum and their alloys. In order to study the oxidation behavior in more detail, the present gas dynamics must be further understood. Wirth and Wegener have made a first approach with their gas flow simulation. In this study, a measurement method for spatial oxygen concentration determination is presented. It can be shown that the spatial oxygen concentration follows the nozzle geometry. Furthermore, the coaxial nozzle is superior to the three-jet nozzle with respect to a low oxygen concentration from a carrier gas to shielding gas volume flow ratio of equal to or greater than 0.4. Finally, it can be shown that the use of a shielding gas chamber eliminates the optimization of the gas flow settings. Full article

Background: Minutes after an injury to the spinal cord, structural and functional reorganization of the connected brain areas may be initiated. Exercise enhances this neuroplasticity in the further course of the condition, which might modulate the connectivity patterns in brain regions responsible for movement execution and imagination. However, connectivity patterns have not been analyzed as a correlate for activity effects on neuroplasticity after spinal cord injury (SCI). We hypothesize that wheelchair sport has a modulating effect on the cortical connectivity in patients with SCI, such that distinguished activity patterns can be observed between sportive and non-sportive individuals with SCI and healthy participants. Methods: Sportive (n = 16) and non-sportive (n = 7) patients with SCI as well as sportive (n = 16) and non-sportive (n = 14) healthy participants were instructed to either observe, imagine, or conduct an observed movement while high-density EEG (HD-EEG) was recorded. Functional connectivity was computed from the recorded signals, and the coefficients were compared between groups and conditions using a non-parametric repeated measures analysis. Results: We found that depending on being sportive or not, patients with SCI and controls would react differently to the conditions, but the effects depended on the location in the brain as well as the analyzed frequency range (p < 0.05). Further analysis indicates that non-sportive patients showed higher connectivity received by the right posterior parietal cortex and a lower connectivity received by the left M1 compared to sportive patients. These effects were mainly observed during movement imagination, not during movement. Sportive and non-sportive participants in the healthy control group showed smaller differences than the patients. Conclusions: The results suggest a modulative effect of sports on connectivity patterns during movement imagination and to some extent during movement. This effect was predominantly found in patients with SCI, and to a lesser extent in healthy participants with opposing connectivity patterns. We suggest that this might be due to increased cortical excitability and the elevated brain derived neurotrophic factor (BDNF) level in patients with SCI that is enhanced by exercise. Full article

To evaluate the significance of the geometrical parameters of a passive pre-chamber on engine performance, this study investigated the design of a plug-and-play passive pre-chamber in a 15 L heavy-duty natural gas engine. Multi-dimensional numerical investigations were conducted for parametric studies involving lateral angle, orifice diameter, and vertical angle. A compressive flow solver was employed for Navier–Stoke equations, coupled with detailed sub-models and a chemical kinetic scheme. The combustion model was calibrated and could well predict the engine combustion and operating performance. Seven pre-chamber schemes were evaluated, and four optimal ones were selected for experimental tests. The characteristics of the scavenging process, turbulent jet ignition, and main-chamber combustion were investigated and analyzed. The results show that, considering the trade-off between the ignition energy and the scavenging efficiency, the ratio of the pre-chamber to clearance volume is recommended to be 0.2~0.7%, and the corresponding area–volume ratio is 0.003~0.006 mm⁻¹. Compared with the original natural gas engine, the pre-chamber retrofit can save up to 13.2% of fuel consumption, which presents a significant improvement in fuel economy. Full article

Penetration testing is an important method to evaluate the security degree of a network system. The importance of penetration testing attack path planning lies in its ability to simulate attacker behavior, identify vulnerabilities, reduce potential losses, and continuously improve security strategies. By systematically simulating various attack scenarios, it enables proactive risk assessment and the development of robust security measures. To address the problems of inaccurate path prediction and difficult convergence in the training process of attack path planning, an algorithm which combines attack graph tools (i.e., MulVAL, multi-stage vulnerability analysis language) and the double deep Q network is proposed. This algorithm first constructs an attack tree, searches paths in the attack graph, and then builds a transfer matrix based on depth-first search to obtain all reachable paths in the target system. Finally, the optimal path for target system attack path planning is obtained by using the deep double Q network (DDQN) algorithm. The MulVAL double deep Q network(MDDQN) algorithm is tested in different scale penetration testing environments. The experimental results show that, compared with the traditional deep Q network (DQN) algorithm, the MDDQN algorithm is able to reach convergence faster and more stably and improve the efficiency of attack path planning. Full article

Amid the incessant evolution of the Internet, an array of cybersecurity threats has surged at an unprecedented rate. A notable antagonist within this plethora of attacks is the SQL injection assault, a prevalent form of Internet attack that poses a significant threat to web applications. These attacks are characterized by their extensive variety, rapid mutation, covert nature, and the substantial damage they can inflict. Existing SQL injection detection methods, such as static and dynamic detection and command randomization, are principally rule-based and suffer from low accuracy, high false positive (FP) rates, and false negative (FN) rates. Contemporary machine learning research on SQL injection attack (SQLIA) detection primarily focuses on feature extraction. The effectiveness of detection is heavily reliant on the precision of feature extraction, leading to a deficiency in tackling more intricate SQLIA. To address these challenges, we propose a novel SQLIA detection approach harnessing the power of an enhanced TextCNN and LSTM. This method begins by vectorizing the samples in the corpus and then leverages an improved TextCNN to extract local features. It then employs a Bidirectional LSTM (Bi-LSTM) network to decipher the sequence information inherent in the samples. Given LSTM’s modest effectiveness for relatively long sequences, we further integrate an attention mechanism, reducing the distance between any two words in the sequence to one, thereby enhancing the model’s effectiveness. Moreover, pre-trained word vector features acquired via BERT for transfer learning are incorporated into the feature section. Comparative experimental results affirm the superiority of our deep learning-based SQLIA detection approach, as it effectively elevates the SQLIA recognition rate while reducing both FP and FN rates. Full article

Effort estimation is always quite a challenge, especially for agile software development projects. This paper describes the process of building a Bayesian network model for effort prediction in agile development. Very few studies have addressed the application of Bayesian networks to assess agile development efforts. Some research has not been validated in practice, and some has been validated on one or two projects. This paper aims to bring the implementation and use of Bayesian networks for effort prediction closer to the practitioners. This process consists of two phases. The Bayesian network model for task effort estimation is constructed and validated in the first phase on real agile projects. A relatively small model showed satisfactory estimation accuracy, but only five output intervals were used. The model was proven to be useful in daily work, but the project manager wanted to obtain more output intervals, although increasing the number of output intervals reduces the prediction accuracy. In the second phase, the focus is on increasing the number of output intervals while maintaining satisfactory accuracy. The advanced model for task effort estimation is developed and tested on real projects of two software firms. Full article

In the field of job recruitment, a classic recommendation system consists of users, positions, and user ratings on positions. Its key task is to predict the unknown rating data of users on positions and then recommend positions that users are interested in. However, traditional recommendation methods only rely on user rating data for jobs and provide recommendation services for recruiters and candidates through simple information matching. This simple recommendation strategy not only causes a lot of information waste but also cannot effectively utilize the multi-source heterogeneous data information in the field of job recruitment. Therefore, this paper proposes a job recommendation model based on users’ attention levels and tensor decomposition for specific recruitment positions. This model puts forward assumptions based on browsing time for the special behaviors and habits of users in the field of job recruitment, defines corresponding label values for different interactive behaviors, and establishes a grading method based on the attention of job seekers, thus constructing a three-dimensional tensor of “job seeker user-position-attention layered”. Then, a recommendation model is constructed by decomposing the three-dimensional tensor. The effectiveness of the model is verified by comparative experiments with other recommendation algorithms. Full article

The shoulder is a unique and complex joint in the human body with three bones and four joints, which makes it the most unstable joint in the body due to the amount of motion. To improve approaches toward understanding the performance of overhead throwing movements, this systematic review summarizes the type of analysis related to shoulder biomechanics involving overhead sporting motions. A search of seven databases identified 33 eligible studies, which were subsequently scored using the Modified Coleman Methodology Score scale. A total of nine articles from badminton, seven from baseball, five from volleyball, five from tennis, three from cricket, and one from softball were reviewed. All 33 studies evaluated shoulder kinematics and 12 of them also investigated the forces and torques (kinetics). The most common methods used were 3D motion analysis (76%), digital video cameras (15%), electromagnetic tracking system (6%), and finally 3% used IMU sensors. Overall, shoulder external rotation during the back swing, internal rotation, and elbow extension during the forward acceleration phase were the strongest predictors of high velocity overhead throwing movement. The findings provide some useful insights and guidance to researchers in their future contribution to the existing body of literature on shoulder overhead throwing movement biomechanics. Full article

We present a linear optical protocol for teleporting and correcting both temporal and frequency errors in two time–frequency qubit states. The first state is the frequency (or time-of-arrival) cat qubit, which is a single photon in a superposition of two frequencies (or time-of-arrival), while the second is the time–frequency Gottesman–Kitaev–Preskill (GKP) state, which is a single photon with a frequency comb structure. The proposed optical scheme could be valuable for reducing the error rate in quantum communication protocols involving one of these qubits. Full article

Harnessing commonsense knowledge poses a significant challenge for machine comprehension systems. This paper primarily focuses on incorporating a specific subset of commonsense knowledge, namely, script knowledge. Script knowledge is about sequences of actions that are typically performed by individuals in everyday life. Our experiments were centered around the MCScript dataset, which was the basis of the SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge. As a baseline, we utilized our Three-Way Attentive Networks (TriANs) framework to model the interactions among passages, questions, and answers. Building upon the TriAN, we proposed to: (1) integrate a pre-trained language model to capture script knowledge; (2) introduce multi-layer attention to facilitate multi-hop reasoning; and (3) incorporate positional embeddings to enhance the model’s capacity for event-ordering reasoning. In this paper, we present our proposed methods and prove their efficacy in improving script knowledge integration and reasoning. Full article

According to a previous study, a concrete bridge bearing vehicles traveling at lower speeds suffers from more severe apparent damage compared to one bearing vehicles traveling at higher speeds. The authors of the study subjectively inferred that the observed phenomenon is due to different vehicle load-holding durations for different vehicle speeds. However, this interpretation is not true for bridges with a smooth road surface. Based on an engineering case study of Renyihe Bridge (a concrete rigid-frame continuous highway bridge with spans of 80 m + 4 × 145 m + 80 m), this article reveals via numerical simulations that with the increase in road surface roughness, the resonant responses of the bridge are significantly amplified for cases of low vehicle speed, which can well explain the phenomenon observed by the aforementioned study. Field experiments undertaken on Renyihe Bridge further reveal the related mechanism. These experiments reveal that the frequency of the vehicle excitation for a bridge with sufficient road surface roughness might be closer to the low-order natural frequencies of a bridge with a decrease in vehicle speed. Therefore, the resonant responses are supposed to be more significantly amplified in cases of low vehicle speed after an increase in road surface roughness. Full article

With the growing demand for transportation, there has been a significant increase in road-related projects, leading to potential risks in the safety of existing structures. This paper presents a study on the influence of new tunnel construction on the stability of an adjacent existing tunnel and provides valuable insights for the safety technology evaluation of similar tunnel crossing projects. In order to evaluate the influence of tunnel excavation on adjacent tunnels, the excavation process of a new tunnel near the original tunnel is simulated using the finite element software Midas GTS. This analysis includes the evaluation of static and dynamic responses. The results indicate that the horizontal and vertical displacements caused by the excavation of the railway tunnel are minimal. Furthermore, during the blasting excavation of the railway tunnel, the vibration velocity experienced by the highway tunnel remains below the safe allowable limit. These findings demonstrate that in this project, the influence of blasting excavation for the railway tunnel on the highway tunnel is both safe and manageable. Full article

This work addresses the dynamic modeling of a negative stiffness absorber consisting of an assembly of curved beams. Design rules are derived from the orders of magnitude of stiffness and elastic energy stored by the negative stiffness elements. Although static and dynamic performances are widely documented using equivalent spring–mass system equations of motion, this paper presents a modeling approach based on beam dynamics to predict the behavior by incorporating the generation of negative stiffness with prestressed Euler beams. The static behavior is first recalled to feed the dynamic beam model with realistic orders of magnitude. The latter is derived from the beam balance instead of the spring–mass system and aims at solving the beam problem, which encompasses more realistic phenomena compared to introducing the equivalent stiffness in the spring–mass equation of motion. The consistency of the beam modeling is confirmed by comparison with available models in the literature and finite element simulations. A mock-up is built in which beam-type components are 3D-printed. Axial loading is introduced on the curved beams to evaluate its influence on the response of the isolator, and the observed softening trend complies with the theoretical predictions. Full article

Basement excavation may induce deformations of the adjacent tunnels. The response of existing tunnels to basement excavation considering the critical unloading ratio is rarely studied. In this study, a three-dimensional numerical model is established to investigate basement–tunnel interaction. Then, the numerical model is validated by simulating the centrifuge model test. Thereafter, the influences of basement geometry and tunnel location relative to the basement on the vertical deformation of the tunnel are studied. The results show that the vertical deformation of the tunnel increases linearly with the unloading ratio, which describes the degree of excavation depth above the tunnel. But there exists a critical unloading ratio of 0.6, beyond which the vertical deformation of the tunnel increases significantly. On this basis, an empirical model is proposed to predict the vertical deformation of the tunnel considering the unloading ratio. Full article

Issue reports are valuable resources for the continuous maintenance and improvement of software. Managing issue reports requires a significant effort from developers. To address this problem, many researchers have proposed automated techniques for classifying issue reports. However, those techniques fall short of yielding reasonable classification accuracy. We notice that those techniques rely on text-based unimodal models. In this paper, we propose a novel multimodal model-based classification technique to use heterogeneous information in issue reports for issue classification. The proposed technique combines information from text, images, and code of issue reports. To evaluate the proposed technique, we conduct experiments with four different projects. The experiments compare the performance of the proposed technique with text-based unimodal models. Our experimental results show that the proposed technique achieves a 5.07% to 14.12% higher F1-score than the text-based unimodal models. Our findings demonstrate that utilizing heterogeneous data of issue reports helps improve the performance of issue classification. Full article

The process of debittering table olives, known as “natural”, represents the most studied method for its peculiarities. Searching among other studies, very little evidence was found about “outside the lab” tests; this encouraged our research, given the numerous external factors that could influence the whole process. In this study, we followed batch fermentation processes inside an industrial facility, testing both spontaneous and guided processes. The starter selected was a 1:1 ratio of Lactiplantibacillus plantarum B1 strain and Saccharomyces cerevisiae SC24 strain. (10⁸ CFU/mL). Chemical-physical, microbiological, and phenolic parameters of five different barrels were analysed, with a periodic sampling (seven samplings). Results obtained confirmed logical correlations (p < 0.05 Pearson) between chemical-physical parameters (ashes vs. pulp/seed ratio, ashes vs. humidity, salt content vs. pulp/seed ratio, oil content vs. humidity) and showed a good discrimination between samples, especially regarding the phenolic profile of the different barrels (PCA and AHC). Microbiological analysis showed the evolution of microorganisms in the barrels, but the results have an unclear interpretation. No Enterobacter were found, so the safety of both process and product can be confirmed. These results highlight some criticalities of the industrial processes and represent useful data for technicians and production structures in order to improve the quality of the product and minimize losses. Full article