Distinct Methods Research Articles

Stress Simulation on Four-Bar Link-Type Transplanting Device of Semiautomatic Vegetable Transplanter

The aim of this study is to analyze the stress exerted on a four-bar link-type transplanting device using two distinct methods: stress measurement performed during a field test and stress simulation. A field test is conducted to measure stress using a strain gauge positioned at 15 specific points on the transplanting device. Subsequently, the measured strain data are converted into calculated stress data. In another method, stress is simulated using specialized multibody dynamic simulation software. The simulation results are compared with the stress measured during field tests to verify the simulation model. Based on the results, the maximum stress derived from the simulation correlates with the measured results, although notable discrepancies are shown, particularly at strain gauge positions 11 and 13. The maximum stress derived from the simulation is used to calculate the static safety factor of the transplanting device. The peak stress derived from the simulation aligns with the measured results, although significant discrepancies are observed at positions corresponding to strain gauges 4 and 10. The maximum stress (150.82 MPa) is observed on the link of the transplanting device, and the static safety factor determined via the simulation is 1.39.

Enhancing accuracy and privacy in speech-based depression detection through speaker disentanglement

Speech signals are valuable biomarkers for assessing an individual’s mental health, including identifying Major Depressive Disorder (MDD) automatically. A frequently used approach in this regard is to employ features related to speaker identity, such as speaker-embeddings. However, over-reliance on speaker identity features in mental health screening systems can compromise patient privacy. Moreover, some aspects of speaker identity may not be relevant for depression detection and could serve as a bias factor that hampers system performance. To overcome these limitations, we propose disentangling speaker-identity information from depression-related information. Specifically, we present four distinct disentanglement methods to achieve this — adversarial speaker identification (SID)-loss maximization (ADV), SID-loss equalization with variance (LEV), SID-loss equalization using Cross-Entropy (LECE) and SID-loss equalization using KL divergence (LEKLD). Our experiments, which incorporated diverse input features and model architectures, have yielded improved F1 scores for MDD detection and voice-privacy attributes, as quantified by Gain in Voice Distinctiveness (GVD) and De-Identification Scores (DeID). On the DAIC-WOZ dataset (English), LECE using ComparE16 features results in the best F1-Scores of 80% which represents the audio-only SOTA depression detection F1-Score along with a GVD of −1.1 dB and a DeID of 85%. On the EATD dataset (Mandarin), ADV using raw-audio signal achieves an F1-Score of 72.38% surpassing multi-modal SOTA along with a GVD of −0.89 dB dB and a DeID of 51.21%. By reducing the dependence on speaker-identity-related features, our method offers a promising direction for speech-based depression detection that preserves patient privacy.

Relational neurostrategy

PurposeNeurostrategy is an abductive decision-making process developed from the knowledge generated within the network of decision-makers. It links cognitive style with the team's decisional adaptability in relation to the organization's purpose. Neurostrategy differs from traditional methods, in which it addresses negative utility or decisional trauma, highlighting the variety of interests that are the main cause of team misalignment and allowing for the development of strategies to address them. Neurostrategy enables the classification of strategy deficiencies based on cohesion, coordination, communication and conduction (Co4).Design/methodology/approachThis paper introduces a novel approach called relational neurostrategy (RNS) to elucidate the knowledge processes influencing decision-making. RNS aims to “capture” the intricate processes guiding decisions, enabling the network's decisional plasticity in both forms and contents. This adaptability is crucial for effectively addressing posed challenges, while simultaneously mitigating the impact of diverse interests. The methodology also ensures transparency in the decision-making process and generates an effective solution strategy.FindingsThe RNS addresses two critical aspects of the decision-making process. Firstly, it reduces unnecessary variety stemming from multiple interpretations and secondly, it minimizes the adverse impact of diverse interests within the decision-making network. This approach results in strong and credible decisions that reflect the collective intelligence, cooperation and collaborative efforts of the network, rather than being imposed as absolute truths.Originality/valueThe RNS stands out as a distinctive decision-making method, setting itself apart from existing approaches. Its uniqueness becomes evident in its ability to address the question “what prevents the authors from … ?” from this inquiry, RNS successfully integrates unrequired variety and negative utility. By doing so, it strategically narrows down the search field to the universe of distinctions that truly constitute the problem. This innovative process not only enhances efficiency but also fosters a high level of participation in the strategic design of potential solutions. In essence, RNS brings unprecedented value by effectively navigating the intricacies of decision-making and maximizing the relevance of the identified problem space.

Utilizing Japanese Community Engagement: Understanding Malaysian Traditional Music Therapy for Children with Special Needs

This study suggests an intervention treatment relating to the dances and songs of “Dikir Barat” and “Kuda Kepang” and utilizes the distinctive methods of Malay traditional performance. Children with specific difficulties will benefit from the therapy’s emphasis on audience perception skills and socialization. The audience for this study, which comprised students and people with special needs, was polled using a survey questionnaire that was provided as part of a special concert. The descriptive analysis of the 5-point Likert scale survey’s 20 items yielded the proportion of each item. As a result, it has been found that shows, particularly those that incorporate the performing arts of singing, dancing, and acting, greatly affect and have an impact on groups with special needs. This study adds to the body of knowledge by demonstrating how conventional music therapy can encourage children with special needs to become more actively involved in their own lives as well as that of their community.

The Influence of Late Gadolinium Enhancement Cardiac Magnetic Resonance Image Analysis Imprecision on Myocardial Damage Quantification in Patients with Myocarditis: A Pilot Study

Background: Myocardial damage in myocarditis is assessed through late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR). Variability in quantifying myocarditis extent results from imprecise image segmentation and inconclusive data on quantification method selection. To improve analysis precision, segmentation steps are systematically ranked based on their inherent risks of error. Additionally, data on two distinct quantification methods are presented. Methods: Using newly developed software, four experts analyzed five LGE-CMR left ventricular (LV) short-axis (SAx) images of myocarditis patients in three sessions. Regions of interest (ROIs) (myocardial (ROImyoc), reference (ROIref), and exclusion region (ROIexcl)) were identified and used to calculate LGE extent with 3σ (intensity above three standard deviations (σ) in reference) and the full width at half maximum (FWHM) method (intensity above 50% of maximum signal in reference). The reference LGE extent was calculated and the influence of the ROIs on LGE extent variability was determined. Interobserver and intraobserver variability were evaluated as 1-intraclass correlation coefficient (ICC). Results: LGE extent variability was 6.2 ± 0.6% for 3σ and 4.0 ± 0.6% for FWHM. The contributions of ROImyoc, ROIref, and ROIexcl were 1.5 ± 0.2%, 2.7 ± 0.4%, and 2 ± 0.3%, respectively, for 3σ, and 1.1 ± 0.1%, 1.6 ± 0.4%, and 1.3 ± 0.3%, respectively, for FWHM. LGE extent was lower in FWHM. Interobserver variability was 0.56 for 3σ and 0.43 for FWHM. The intraobserver variability was higher for the 3σ method in all four observers. Conclusion: ROIref selection contributed most to LGE extent variability. FWHM yielded lower LGE extent and lower inter- and intraobserver variability. Due to low statistical significance, the findings are only partially confirmed.

Leveraging decision diagrams to solve two-stage stochastic programs with binary recourse and logical linking constraints

We generalize an existing binary decision diagram-based (BDD-based) approach of Lozano and Smith (MP, 2022) to solve a special class of two-stage stochastic programs (2SPs) with binary recourse, where the first-stage decisions impact the second-stage constraints. First, we extend the second-stage problem to a more general setting where logical expressions of the first-stage solutions enforce constraints in the second stage. Then, as our primary contribution, we introduce a complementary problem, that appears more naturally for many of the same applications of the former approach, and a distinct BDD-based solution method, that is more efficient than the existing BDD-based approach on commonly applicable problem classes. In the novel problem, second-stage costs, rather than constraints, are impacted by expressions of the first-stage decisions. In both settings, we convexify the second-stage problems using BDDs and parameterize either the BDD arc costs or capacities with first-stage solutions. We extend this work by incorporating conditional value-at-risk and propose the first decomposition method for 2SP with binary recourse and a risk measure. We apply these methods to a novel stochastic problem, namely stochastic minimum dominating set problem, and present numerical results to support their effectiveness.

Bactericera tremblayi (Wagner, 1961) (Hemiptera: Triozidae): The Prevalent Psyllid Species in Leek Fields of Northwestern Spain.

Bactericera tremblayi (Wagner, 1961) (Hemiptera: Triozidae), the onion and leek psyllid, belongs to the Bactericera nigricornis Förster complex, along with B. trigonica and B. nigricornis. In contrast to the other two species, there has been a notable absence of studies examining the distribution and seasonal occurrence of B. tremblayi, despite its association with significant issues in leek crops. Surveys were conducted between 2017 and 2020 in the main leek-growing area of Castile and Leon (Spain). An extensive survey encompassing 29 distinct plots was monitored with sweep nets and visual inspection, counting plants with immature forms at three times in the crop cycle. Additionally, a total of seven seasonal monitoring surveys were conducted in the same area of study. Plots were monitored every ten days, employing three distinct sampling methods including horizontal green tile water traps, sweep nets, and visual inspection, counting the juvenile stages by plant. The results revealed that B. tremblayi predominated as the primary species of jumping plant-lice in leek crops throughout the entire crop cycle. To date, there exists no documented incidence of pathogenic agents within symptomatic leeks. Consequently, the manifestation of severe symptoms is highly likely to be a direct consequence of the feeding activity of the onion psyllid. Populations of B. tremblayi were present in leek crops from May-July to harvest (September-November). Adults were captured in horizontal green water traps several days before they were found in sweep net samples, making the former effective in capturing early immigrant individuals. The maximum peaks of B. tremblayi were observed at the end of the crop cycle, particularly during late-season cycles characterized by lower mean temperatures. During observations made in a controlled environment, temperature exerted a significant influence on the developmental time of all stages of B. tremblayi. The complete development from egg to adult occurred within a temperature range of 15 to 25 °C. At 30 °C, the survival of eggs and N1 nymphs was limited and B. tremblayi did not complete its developmental cycle. The optimum temperature for the development of B. tremblayi provided by the models used was close to 24 °C with the application of Briere, Taylor, and Lactin models and around 21 °C with the SSI model. These results provided a good adjustment in predicting the survival patterns of B. tremblayi under the studied environmental conditions.

Integrating Positive Psychology through ESP Learning for Science Classes in Senior High School

This research aims to identify positive psychology through ESP learning in science classes at senior high schools in Indonesia. This study used qualitative method. The data collection method employed interviews and observations to obtain more detailed information regarding the research findings. Three distinct data collection methods involved observation, interview, and questionnaire. The qualitative data analysis method was from data summarization, data presentation, and drawing conclusions. Research instruments used triangulation, which involved interviews, observations, and documentation. Based on the findings, it can be concluded that positive psychology serves as a connection or link between humanism and transpersonal. The concept of developing personality potential is evident in Positive Psychology, which also incorporates transcendence as one of its virtues, particularly in relation to spirituality and meaningfulness. The ESP learning concept can enable students to actively participate in foreign language teaching practices in the natural science learning process.

New kid in town: Pinna rudis spreads in the eastern Mediterranean

In the Mediterranean Sea, the genus Pinna encompasses two large fan-shaped bivalve species, Pinna nobilis and Pinna rudis. Historically, both species coexisted in the western Mediterranean until a mass mortality event (MME) brought P. nobilis to the brink of extinction. Notably, P. rudis remained unaffected by the MME, and its recent successful recruitment and further spread have been hypothesized to be linked to the local extinction of P. nobilis. Although P. rudis has been sparsely recorded in the eastern Mediterranean Sea (with some of these records being doubtful), reports emerging in the summer of 2023 from researchers and citizens have unveiled its sudden spread in the region. This study documents the recent presence of P. rudis within Greek waters through a dedicated survey and molecularly confirmation through two distinct molecular methods. Information derived from a citizen science initiative, following photo-identification of the species was also included. Furthermore, an updated review of the distribution of P. rudis in the Mediterranean Sea, integrating data from literature and online repositories is provided. This research confirms the recent spread of P. rudis in Crete, the Greek Ionian Sea, and Cyprus (first verified records of the species in the regions), in marine areas where P. nobilis has become extinct, further strengthening the hypothesis that P. rudis has benefited from the collapse of P. nobilis populations.

Pre-treatment of canine plasma with heat, rather than acid, efficiently enhances Dirofilaria immitis antigen detection

BackgroundThe dissociation of antigen-antibody complexes has been utilized to enhance the accuracy of serological tests for infectious diseases, including Dirofilaria immitis. Currently, the antigen detected by available tests is primarily a glycoprotein found in the reproductive tract of female worms. However, this antigen can become inaccessible when bound to excessive circulating antibodies, leading to reduced test sensitivity and false-negative results. Acid and heat treatments of the sera or plasma have been established as reliable methods for inducing immune complex dissociation (ICD). Previous antigen testing for heartworm infection in dogs and cats has demonstrated that these treatments improve the diagnostic sensitivity without compromising specificity. This study aims to evaluate the performance of four distinct ICD methods in the detection of D. immitis antigen.MethodsWe utilized twofold serial dilutions of a well-characterized plasma (ranging from 1:2 to 1:4096) obtained from a D. immitis-infected dog to simulate the diverse antigen levels encountered in real-life infected dogs. The presence of antigen in the diluted samples, both without treatment and treated with four ICD protocols, was assessed in triplicate visually using DiroCHEK® by observing color changes. OD values were also obtained using the microplate reader SpectraMax® i Series-Spectramax Id3. A Factorial ANOVA test was conducted to compare the OD values between samples with and without treatments.ResultsThe highest dilution at which color changes were observed was 1:128 for untreated samples and for samples subjected to acid treatments in ICD-3 and the hybrid ICD-4 protocol. In contrast, both heat treatment protocols (ICD-1 and ICD-2) exhibited color changes at a 512-fold dilution. The OD values in samples subjected to heat treatment were significantly higher than those in untreated samples, up to dilutions of 512-fold. Although OD values tended to be higher in samples subjected to acid treatment and the hybrid protocol compared to untreated samples up to a 128-fold dilution, this difference was not significant as the samples underwent further dilution.ConclusionsOur findings affirm that heat treatments, rather than acid treatment, efficiently enhance the detection of D. immitis antigen by liberating the sequestered antigen from the immune complexes.

Thermal degradation kinetics, thermodynamics and pyrolysis behaviour of polycarbonate by TGA and Py-GC/MS

This paper elucidates the thermal and catalytic (mordenite and y-zeolite) pyrolysis characteristics of Polycarbonate (PC) as well the kinetics and thermodynamic parameters of the thermal decomposition of PC. Three distinct isoconversional methods, namely the Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Starkin methods, were employed to evaluate the kinetic and thermodynamic parameters. The average activation energies determined with the KAS, FWO, and Starink methods were 245.81, 235.36, and 249.99 kJ/mol respectively, and they were reduced by 17 % and 21 % when mordenite and y-zeolite were utilized as catalysts, respectively, according to the calculations performed with the KAS method. Py-GC/MS analyses showed that phenolic components were found to be dominant in the oil product obtained under non-catalytic conditions. Micropores in the structure of y-zeolite constitute 54.4 % of the total surface area, while micropores in the structure of mordenite constitute 95.5 % of the total surface area. Depending on the structure of the catalysts used, phenolic components decreased slightly, and aromatic and PAH (Polycyclic Aromatic Hydrocarbons) components replaced these components. As a result, phenolic compounds in the oil product obtained with y-zeolite (56.7 %) were less than those produced with mordenite (61.02 %). PAHs were 12.9 % and 7.5 % in the presence of y-zeolite and mordenite, respectively. Thus, the results evidence the molecular size of zeolite catalysts, as well as their acidic structure, which are crucial factors in the conversion of phenolic compounds.

Empirical Analysis of the Relationship between Project Delivery Method on Project Performance in the Yemen Construction Industry

This empirical paper analyzed the relationship between project delivery methods on project performance within the Yemen construction industry (YCI). This research incorporated two distinct project delivery methods (PDM) namely the traditional Design-Bid-Build (DBB) and Design-Build (DB) and gauging project performance (PP) through the lens of the triple constraints (time, cost, and quality) as the criteria for measuring success. A conceptual model was theorized and operationalized in a survey of 375 project managers and consultants from two Yemeni governorates, Aden and Hadramout. The questionnaire employed a 5-point Likert Scale. Subsequently, the data were evaluated using multivariate regression. The empirical findings revealed a significant relationship between the choice of project delivery method and project performance. Thus, exerting a positive influence on project success. This study contributes to the existing body of knowledge in two significant ways. First, by scrutinizing the dynamic mechanisms through which project delivery methods impact project performance. Secondly, offers valuable insights for decision-makers in the Yemeni construction industry (YCI) to plan their objectives and achieve the requisite project performance levels.

Ultrafast microfluidic solvent extraction and machine learning-assisted impedimetric sensor for multidetermination of scaling ions in crude oils

Flow assurance plays an important role in designing safe and efficient operation techniques along oil and gas explorations. In this way, approaches able to provide fast and field-deployable monitoring of scaling ions in crude oils may benefit the petrochemical industry in its long-standing mission to devise ideal flow conditions by aiding the adoption of optimum dosages of off-the-shelf products. We first describe a scalable platform toward rapid (∼10 min) determination of multiple scaling ions in crude oils. Our platform is based on turbulence-mediated ultrafast and efficient microfluidic solvent extraction (μSE) combined with impedimetric sensors and machine learning to determine different ions from a single impedance plot. 3D-printed μSE devices were able to afford ultra-fast (residence time of ∼1.0 s) extractions. Nanocellulose-based foams allowed us for rapidly separating the water-oil phases, with the aqueous phase being sampled for posterior detection. Scalable sensors obtained by distinct prototyping methods provided the multidetermination of ions in 50 produced water samples (Mg2+, Ca2+, Sr2+, and Cl⁻) and 49 crude oils (Ca2+ and Cl⁻). The accuracies ranged from ∼96 to 100%. Importantly, ML models trained on standard solutions delivered poor accuracy, showing the relevance of learning supervised algorithms with real samples to deliver accurate capacitive analyses.

Gender conflict resolution in Nigerian and African American standup performances

Stand-up comedy, a prominent facet of live theatrical entertainment, occupies a unique position in the entertainment industry, embodying a key element of popular culture. This comedic form reflects the sociological dynamics of both historical and contemporary societies, influencing and engaging both local and international audiences. Beyond providing psycho-physical therapy for performers, stand-up comedy plays a pivotal role in shaping societal perceptions. This article focuses on a gender-focused analysis of stand-up comedy, exploring its implications for domestic growth, marriage unity, and love. Utilizing three digital recordings featuring stand-up comedians, namely Bright Okpocha (Basket Mouth), Ayo Makun (AY), and Eddie Murphy, the study examines their unique approaches to addressing gender-based violence and resolving conflicts. The selection criteria were based on the comedians' distinct counseling methods and perspectives on gender-related issues. Drawing on Richard Schechner's performance theory, the analysis employs both performance and content analyses to elucidate the spectrum of gender conflicts and resolutions presented by the comedians. The findings underscore the importance of mutual understanding and communication in resolving gender conflicts. The article also delves into the influence of parental roles in household management and the pursuit of material wealth. Emphasizing the significant role of counseling modes, the study concludes that stand-up comedy, with its oratory counseling mode and therapeutic elements, serves as an effective means of addressing gender conflicts, contributing to mutual understanding and successful resolutions within society.

On the thermal impact during drilling operations in guided dental surgery: An experimental and numerical investigation

In recent years, a major development in dental implantology has been the introduction of patient-specific 3D-printed surgical guides. The utilization of dental guides offers advantages such as enhanced accuracy in locating the implant sites, greater simplicity, and reliability in performing bone drilling operations. However, it is important to note that the presence of such guides may contribute to a rise in cutting temperature, hence increasing the potential hazards of thermal injury to the patient's bone. The aim of this study is to examine the drilling temperature evolution in two distinct methods for 3D-printed surgical dental guides, one utilizing an internal metal bushing system and the other using external metal reducers. Cutting tests are done on synthetic polyurethane bone jaw models using a lab-scale automated Computer Numeric Control (CNC) machine to find out the temperature reached by different drilling techniques and compare them to traditional free cutting configurations. Thermal imaging and thermocouples, as well as the development of numerical simulations using finite element modeling, are used for the aim. The temperature of the tools' shanks experienced an average rise of 2.4 °C and 4.8 °C, but the tooltips exhibited an average increase of around 17 °C and 24 °C during traditional and guided dental surgery, respectively. This finding provides confirmation that both guided technologies have the capability to maintain temperatures below the critical limit for potential harm to bone and tissue. Numerical models were employed to validate and corroborate the findings, which exhibited identical outcomes when applied to genuine bone samples with distinct thermal characteristics.

Generating Correlations for Specific Volume, Enthalpy, and Entropy of Opteon: Utilizing a Novel Data Fitting Method

Establishing precise data correlations is a fundamental necessity for effective design, simulation, and optimization of chemical processes. While several correlation-generating methods for data fitting exist, each brings a unique degree of complexity and accuracy. This study introduces a distinctive method, appropriately named, Proportional Nodes Method, for correlating data on surfaces with two independent variables, focusing on precise estimations of correlations for boundary curves and nodal variation at selected points. The application of the proportional node method results in a lower average percentage deviation than the Chebyshev polynomial method (±0.978 for the method utilizing Chebyshev polynomials and ±0.5378 for the Proportional Nodes Method). This novel method exhibits lower complexity and generates correlations with superior simplicity and accuracy. Furthermore, the method effectively develops correlations for three properties—specific volume, enthalpy, and entropy of superheated Opteon, a widely-used refrigerant in automotive air-conditioners. The resulting data shows a satisfactory percentage deviation from the actual data (<+0.22% for a specific volume, <+0.124 for enthalpy and <+0.125 for entropy). In addition, correlations have been generated for the saturated vapour. This method's potential extends to developing correlations for non-overlapping data with two independent variables, making it a powerful tool for chemical process optimization.

Flexibility of differentiation procedures in calculus

Calculus is perhaps the most widely taught and researched upper-secondary/post-secondary mathematics subject the world over. The research literature is amassing greater clarity around students’ understandings of calculus, yet calculus instruction tends to be at odds with this literature, maintaining a focus on procedural aspects of the subject. This current work explores one central procedural topic, differentiation, through the broader lens of procedural flexibility. Both students and experts calculated the derivatives to a collection of functions in multiple ways, selected their preferred method and commented on their preference. Many students demonstrated a knowledge of multiple procedures and an ability to select appropriate solutions. Experts produced a greater number of distinct solution methods, including some not found among the student responses. The primary impact of this paper is a more nuanced understanding of ‘flexibility’ as a construct, buttressed by contrasting student and expert data, especially as it concerns procedures in higher-level mathematics. These results are expected to contribute to a bridge between the research on and practice of calculus instruction.

Multi-field coupling analysis of mechanical responses in methane hydrate exploitation with a practical numerical approach combining T + H with DEM

The methane hydrate (MH) is widely distributed in deep-sea sedimentary layers, considered as the most promising clean energy to replace conventional oil and gas in the 21st century. Large-scale exploitation of MH may lead to a series of geotechnical engineering problems. To numerically estimate the seabed stability during MH exploitation which should involve multi-field coupling simulation of complex mechanical behaviors of methane hydrate bearing sediment (MHBS), a new practical hybrid numerical method is proposed, which combines the TOUGH + HYDRATE (T + H) code, targeting multiphase flow analysis of hydrate-bearing geologic systems, with the improved Distinct Element Method (DEM). Porosity, temperature, pressure, salinity fields are exchanged between DEM and T + H to realize the thermal-hydro-mechanical-chemical (THMC) coupling and to reproduce the progressive discontinuous failure process. The results of verification show obvious uniformity between numerical and analytical results for one-dimensional (1D) consolidation and 1D heat conduction tests on soils. The paper tries to analyze evolutions of THMC fields, gas production, hydrate bond breakage and other mechanical behaviors of actual depressurization production by using this method, focusing on geotechnical risks of exploitation. In addition, study observes significant changes within certain range from the wellbore for gas production and mechanical responses in the early stage.

Ten-Year Impact of Cover Crops on Soil Organic Matter Quantity and Quality in Semi-Arid Vineyards

Soil organic matter depletion is a significant concern in agricultural soils, impacting crucial aspects of ecosystem health, especially soil properties such as fertility and soil moisture retention. Adopting sustainable soil management practices, such as cover crops, can mitigate this issue. In this study, we analyzed the soil organic carbon (SOC) content and quality in vineyards using two distinct management methods: permanent spontaneous cover crops and conventional tillage. Dissolved organic carbon (DOC) was quantified and chemically characterized using UV–visible spectroscopy. Our results showed an increase of 4.7 Mg C/ha in the carbon stock (50 cm depth) after 10 years of implementing vegetation covers compared with tilled soil. Additionally, cover crop management increased less humified soluble carbon in surface soil layers, while tillage transformed the solubilized carbon. This finding is important because tilled soil becomes more accessible to microbial degradation and leaching, which, in the long term, leads to a SOM content decrease. In conclusion, an increase in carbon stock was observed when using cover crops due to the incorporation of fresh organic matter, whereas tilled soils showed a depletion of carbon stock, including the mobilization of more stable carbon.

A Dataset of Pulsed Thermography for Automated Defect Depth Estimation

Pulsed thermography is an established nondestructive evaluation technology that excels at detecting and characterizing subsurface defects within specimens. A critical challenge in this domain is the accurate estimation of defect depth. In this paper, a new publicly accessible pulsed infrared dataset for PVC specimens is introduced. It was enriched with 3D positional information to advance research in this area. To ensure the labeling quality, a comparative analysis of two distinct data labeling methods was conducted. The first method is based on human domain expertise, while the second method relies on 3D CAD images. The analysis showed that the CAD-based labeling method noticeably enhanced the precision of defect dimension quantification. Additionally, a sophisticated deep learning model was employed on the data, which were preprocessed by different methods to predict both the two-dimensional coordinates and the depth of the identified defects.