bluuebunny/crossref_metadata_2025 huggingface dataset:
The conformation of the nSrc specificity-determining loop in the Src SH3 domain is modulated by a WX conserved sequence motif found in SH3 domains
Authors: Longshore-Neate Frederick , Ceravolo Caroline , Masuga Cole , Tahti Elise F. , Blount Jadon M. , Smith Sarah N. , Amacher Jeanine F.
Published: December 2024

Cellular signaling networks are modulated by multiple protein-protein interaction domains that coordinate extracellular inputs and processes to regulate cellular processes. Several of these domains recognize short linear motifs, or SLiMs, which are often highly conserved and are closely regulated. One such domain, the Src homology 3 (SH3) domain, typically recognizes proline-rich SLiMs and is one of the most abundant SLiM-binding domains in the human proteome. These domains are often described as quite versatile, and indeed, SH3 domains can bind ligands in opposite orientations dependent on target sequence. Furthermore, recent work has identified diverse modes of binding for SH3 domains and a wide variety of sequence motifs that are recognized by various domains. Specificity is often attributed to the RT and nSrc loops near the peptide-binding cleft in this domain family, particularly for Class I binding, which is defined as RT and nSrc loop interactions with the N-terminus of the ligand. Here, we used the Src and Abl SH3 domains as a model to further investigate the role of the RT and nSrc loops in SH3 specificity. We created chimeric domains with both the RT and nSrc loop sequences swapped between these SH3 domains, and used fluorescence anisotropy assays to test how relative binding affinities were affected for Src SH3- and Abl SH3-specific ligands. We also used Alphafold–Multimer to model our SH3:peptide complexes in combination with molecular dynamics simulations. We identified a position that contributes to the nSrc loop conformation in Src SH3, the amino acid immediately following a highly conserved Trp that creates a hydrophobic pocket critical for SH3 ligand recognition. We defined this as the WX motif, where X = Trp for Src and Cys for Abl. A broad importance of this position for modulating nSrc loop conformation in SH3 domains is suggested by analyses of previously deposited SH3 structures, multiple sequence alignment of SH3 domains in the human proteome, and our biochemical and computational data of mutant Src and Abl SH3 domains. Overall, our work uses experimental approaches and structural modeling to better understand specificity determinants in SH3 domains.
Investigation of the correlation between AGRN expression and perineural invasion in colon cancer
Authors: Chen Lei , Zhang Haijia , Gao Kaiyue , Meng Fanqi , Yang Funing , Li Jiannan , Wang Lijie , Tai Jiandong
Published: December 2024

Background and Purpose

Colon cancer is one of the most common gastrointestinal malignancies. According to the traditional view, the primary modes of transmission include direct dissemination, hematogenous metastasis, and lymph node metastasis. In recent years, the role of perineural invasion (PNI) in the spread and metastasis of tumors has received immense attention. However, there are still relatively few reports on the potential mechanisms and biomarkers of PNI occurrence and development in colon cancer.

Method

We identified genes linked to the onset and progression of PNI in colon cancer using bioinformatics tools and extensive databases. Gene function enrichment analysis was used to explore the potential roles of these genes in tumor proliferation, invasion, and PNI. A collection of postoperative pathological specimens from colon cancer patients who underwent surgery, related clinicopathological data, and immunohistochemistry were used to validate AGRN expression in PNI tissues.

Results

Bioinformatics analysis revealed that AGRN is overexpressed in colon cancer tissues and correlates with poor patient prognosis. The findings from gene association and enrichment studies indicate that AGRN and its associated genes may play a role in PNI development and progression in colon cancer by simultaneously enhancing tumor cell invasion and neural cell growth. Immunohistochemical analysis of clinical samples confirmed that AGRN expression is elevated in colon cancer tissues with PNI.

Conclusion

We found that AGRN is significantly overexpressed in colon cancer tissues exhibiting PNI and is linked to poor patient survival. AGRN and its related genes may contribute to PNI by promoting tumor cell invasion and neural cell growth. Hence, AGRN may play a crucial role in the initiation and progression of PNI in colon cancer.
Circadian rhythm and epilepsy: a nationally representative cross-sectional study based on actigraphy data
Authors: Tang Tianyou , Zhou YuDong , Zhai Xuan
Published: December 2024

Objective

The study aims to assess the relationship between epilepsy and circadian rhythms.

Method

This study included a cohort of 7,410 participants sourced from the 2013–2014 National Health and Nutrition Examination Survey (NHANES) database. The investigation focused on the comparative analysis of seven nonparametric indices associated with circadian rhythms (Interdaily Stability (IS), Intradaily Variability (IV), Relative Amplitude (RA), L5, M10, L5 start time, and M10 start time) between the overall population and patients with epilepsy. Logistic regression analysis was utilized to assess the potential correlation between the rest-activity circadian rhythm patterns and the presence of epilepsy within the cohort.

Results

Compared to the general population, individuals with epilepsy exhibited lower values of IS and M10. Multivariable logistic regression analysis, when IS, RA, and M10 were categorized into four groups based on quartiles, revealed that the odds ratio (IS: OR = 0.36, 95% CI: 0.13, 0.89; RA: OR = 0.25, 95% CI: 0.06, 0.77; M10: OR = 0.24, 95% CI: 0.06, 0.73) for the highest quartile was lower than that for the lowest quartile. Furthermore, after adjustment for confounding factors, participants in the highest quartile compared to those in the lowest quartile of IV and M10 start time demonstrated a higher prevalence of epilepsy.

Conclusion

Individuals with epilepsy demonstrate significant alterations in circadian rhythms.
Quantifying the split-elbow sign: a comprehensive study in amyotrophic lateral sclerosis
Authors: He Sheng-Yi , Cai Wei-Chen , Su Wei-Ming , Duan Qing-Qing , Jiang Zheng , Yin Kang-Fu , Gu Xiao-Jing , Chen Yong-Ping , Cao Bei
Published: December 2024

Purpose

The split-elbow sign (SES), characterized by preferential dysfunction of the biceps brachii compared to the triceps, is a clinical feature observed in amyotrophic lateral sclerosis (ALS). However, the quantified SES index has not been extensively investigated, and its role in diagnosing ALS remains unknown. Therefore, this study aimed to investigate the split-elbow index (SEI) derived from compound muscle action potential (CMAP), motor unit number index (MUNIX), and echo intensity (EI) in ALS.

Methods

A cohort comprising 70 individuals diagnosed with ALS, along with 41 disease controls and 40 healthy controls, was recruited for the study. The SEI was calculated by dividing the recorded values of CMAP, MUNIX, and EI obtained over the biceps brachii by the corresponding value measured in the triceps, resulting in SEICMAP, SEIMUNIX, and SEIEI, respectively. Receiver operating characteristic (ROC) curves of the three methods were used for comparison. Statistical analyses were performed using SPSS V.26.0 and R software.

Results

Both SEICMAP and SEIMUNIX exhibited significant reductions in ALS patients compared to that in controls (PSEICMAp < 0.0001, PSEIMUNIX < 0.0001), while SEIEI showed an elevation (P < 0.0001). Furthermore, there was a notable decrease in SEIMUNIX values as the disease progressed (p < 0.001). Moreover, ROC for SEIMUNIX exhibited superior diagnostic performance (AUC = 0.846), and a comprehensive diagnostic approach combining SEICMAP, SEIMUNIX, and SEIEI resulted in AUC (0.90) on the ROC curve.

Conclusion

Our study suggested that SES has emerged as a significant clinical characteristic in ALS and indicated the potential of SES indicators as biomarkers for both diagnosis and assessment of disease progression in ALS.
cTBS over ventral cortex enhances depth perception
Authors: Or Justin K. N. , Chang Dorita H. F.
Published: December 2024

Stereoscopic capacities vary widely across the normal population. It has become increasingly apparent, however, that mechanisms underlying stereoscopic depth perception retain a considerable degree of plasticity through adulthood. Here, we contrast the capacity for neurostimulation in the form of continuous theta-burst stimulation (cTBS) over strategically-chosen sites in the visual cortex to bring about improvements in stereoscopic depth perception. cTBS was delivered to occipital cortex (V1/V2), lateral occipital complex (LOC), along with a control site (Cz). We measured performance on depth and luminance discrimination tasks before and after stimulation. We found a significant improvement in depth (but not luminance) discrimination performance following cTBS over LOC. By contrast, cTBS over occipital cortex and Cz did not affect performance on either task. These findings suggest that ventral (lateral-occipital) cortex is a key node for governing plasticity of stereoscopic vision in visually normal human observers. We speculate that cTBS exerts inhibitory influences that may suppress internal noise within the nervous system, leading to an improved read-out of depth features.
CT-based habitat radiomics for predicting treatment response to neoadjuvant chemoimmunotherapy in esophageal cancer patients
Authors: Kong Weibo , Xu Junrui , Huang Yunlong , Zhu Kun , Yao Long , Wu Kaiming , Wang Hanlin , Ma Yuhang , Zhang Qi , Zhang Renquan
Published: December 2024

Introduction

We used habitat radiomics as an innovative tumor biomarker to predict the outcome of neoadjuvant therapy for esophageal cancer.

Methods

This was a two-center retrospective clinical study in which pretreatment CT scans of 112 patients with esophageal cancer treated with neoadjuvant chemoimmunotherapy and surgery between November 2020 and July 2023 were retrospectively collected from two institutions. For training (n = 85) and external testing (n = 27), patients from both institutions were allocated. We employed unsupervised methods to delineate distinct heterogeneous regions within the tumor area.

Results

To represent the prediction effect of different models, we plotted the AUC curves. The AUCs of the habitat models were 0.909 (0.8418–0.9758, 95% CI) and 0.829 (0.6423–1.0000, 95% CI) in the training and external test cohorts, respectively. The AUCs of the nomogram models were 0.914 (0.8483–0.9801, 95% CI) and 0.849 (0.6752–1.0000, 95% CI) in the training and external test cohorts, respectively.

Discussion

The results revealed that the model based on habitat data outperforms traditional radiomic analysis models. In addition, when the model is combined with clinical features, it improves the predictive accuracy of pathological complete response in patients undergoing neoadjuvant chemoimmunotherapy.
Cup-to-disc ratio measured clinically and via OCT in pediatric patients being monitored as glaucoma suspects for suspicious optic discs
Authors: Zimmermann Caroline Maria , Cardakli Nur , Kraus Courtney Lynn
Published: December 2024

Purpose

Compare cup-to-disc ratio (CDR) measured by clinical assessment and optical coherence tomography (OCT) in pediatric eyes being monitored as glaucoma suspects for suspicious optic disc appearance.

Design

Retrospective cross-sectional study.

Methods

An institutional study following 221 eyes from 122 unique pediatric glaucoma suspects being monitored due to increased or asymmetric appearance of CDR. Ophthalmologic findings, including visual acuity, intraocular pressure, CDR measured by clinical assessment, average retinal nerve fiber layer thickness, and average CDR measured by OCT, were recorded for each participant’s initial and final examinations. CDRs measured clinically and by OCT were compared at both initial and final presentations.

Results

Average age at presentation was 9.0 years old (95% CI: 8.0-9.9), and mean length of follow-up was 5.0 years (95% CI: 5.4-4.5). At initial presentation, 53 eyes had CDRs recorded by both clinical assessment and OCT, and at final presentation, 93 eyes had CDRs measured by both modalities. CDR measured by OCT was significantly larger than CDR measured clinically on initial and final presentation (p=0.002, p<0.001).

Conclusions

Measurements of CDR by clinician assessment were significantly smaller than measurements obtained via OCT imaging. However, the average difference between CDR measured clinically and by OCT was <0.1. Thus, OCT may be a suitable way to measure CDR in pediatric glaucoma suspects, especially when clinical exam proves difficult. Further research is needed to assess CDR in glaucoma suspects using OCT longitudinally and in the context of other optic disc measurements, such as disc area.
Design and validation of a real-time cassava planter seed quality monitoring system based on optical fiber sensors and rotary encoders
Authors: Yan Bin , Cui Zhende , Deng Ganran , Li Guojie , Zheng Shuang , He Fengguang , Li Ling , Chen Pinlan , Wang Xilin , Zhou Sili , Dai Ye , Qin Shuangmei , Liu Zehua
Published: December 2024

Targeting the issues of seed leakage and cutting segment adhesion due to poor seed feeding and cutting in real-time seed-cutting cassava planters, this study developed a seeding quality monitoring system. Based on the structure and working principle of the seed cutting and discharging device, the installation methods of the matrix fiber optic sensor and rotary encoder were determined. By combining the operational characteristics of the planter’s ground wheel drive with seed cutting and seed dropping, a monitoring model correlating the sowing parameters with seed dropping time was established; a monitoring window was created by extracting and processing the rotary encoder pulse signal, and the number of seeds sown after each opposing cutter’s operation was calculated based on the pulse width information within the monitoring window. The monitoring system’s statistics were compared and analyzed with the manual statistics, and the bench test showed that the monitoring system designed in this study offers high accuracy. When the simulated rotational speed of the opposing cutter ranges from 10 to 30 rpm, the average monitoring error between the monitored and actual seeding quantities for the left and right rows is less than 1.4%. The monitoring system can promptly and accurately activate sound and light alarms for faults, achieving a 100% success rate in alarms and an average fault response time of less than 0.4 seconds. Field tests demonstrate that the average error in seeding volume is 0.91%, and the monitoring system can timely alert to faults occurring in the planter. The system fulfills the requirements for real-time monitoring of cassava seeding volume at various operating speeds in field conditions, and can serve as a reference for monitoring operational parameters in subsequent cassava combine harvesters.
Patterns and correlates of two-year changes in depressive symptoms for autistic adults
Authors: Zheng Shuting , Farmer Cristan , Taylor Julie Lounds , Adams Ryan , Olson Lindsay , Bishop Somer
Published: December 2024

Background

Autistic adults are at elevated risk for depression. However, longitudinal data on the trajectory of depressive symptoms and its associated factors in autistic adults are scarce.

Methods

A community sample of 315 autistic adults participated in a two-year longitudinal study from the beginning of (March 2020) to the recovery from the COVID-19 pandemic (March 2022). They provided five waves of data on self-reported depressive symptoms and sociodemographic and life circumstances information.

Results

Multilevel model results showed that autistic adults reported large between-individual variability in self-reported depressive symptoms, and on average, they experienced an increase (i.e., worsening) in self-reported depressive symptoms over the two years of the study. Autistic adults with a depression history and lower annual household income reported higher levels of depressive symptoms. More importantly, autistic adults reported lower depressive symptoms when they were engaged in work or school, and those who had higher levels of depressive symptoms at the start of the study were more reactive to changes in work or school participation.

Conclusions

Findings from the current study have implications for potential venues of depression treatment in autistic adults around promoting employment/education, providing symptom monitoring, and addressing mental health disparities for those with lower incomes.
Effects of alcohol-related problems on the costs of frequent emergency department use: an economic analysis of a case–control study in Spain
Authors: Oliveras Clara , Bruguera Pol , Cordero-Torres Imanol , Millán-Hernández Andrea , Pons-Cabrera Maria Teresa , Guzmán Cortez Pablo Rodrigo , Gómez-Ramiro Marta , Vázquez Mireia , Borràs Roger , Asenjo-Romero Maria , Vieta Eduard , Gual Antoni , López-Pelayo Hugo , Balcells-Oliveró Mercè
Published: December 2024

Introduction

Alcohol-related problems increase the probability of frequent emergency department (ED) use. In this study, we compared the direct healthcare expenses incurred during a single visit among frequent and non-frequent ED users and analyzed the impact of alcohol-related issues in healthcare costs arising from ED usage.

Methods

The study relied on secondary analyses of economic data from a 1:1 matched case–control study with the primary aim of identifying the clinical characteristics of hospital ED frequent users in a Mediterranean European environment with a public, universal, and tax-funded health system. The participants ranged in age from 18 to 65 years and underwent ED visits at a high-complexity Spanish hospital (cases ≥5 times, controls <5) from December 2018 to November 2019. Each case was matched to a control with the same age, gender, and date of attendance at the ED. Clinical data and direct healthcare costs for a single ED visit were obtained by a retrospective review of the first electronic medical register. Costs and duration of stay were compared between cases and controls using paired-samples t-tests, and ED users with and without alcohol-related problems were compared using bivariate (independent-samples t-tests, one-way analysis of variance, Chi square tests, and multiple linear regression) and multivariate analyses (multiple linear regression models with backward stepwise selection algorithm, and dependent variable: total mean direct costs).

Results

Among 609 case–control pairs (total n = 1218), mean total healthcare direct costs per ED visit were 22.2% higher among frequent compared with non-frequent users [mean difference 44.44 euros; 95% confidence interval (CI) 13.4–75.5; t(608) = 2.811; p = 0.005]. Multiple linear regression identified length of stay, triage level, ambulance arrival, and the specialty discharging the patient as associated with total healthcare costs for frequent users. In bivariate analyses, a history of alcohol-related problems was associated with a 32.5% higher mean total healthcare costs among frequent users [mean difference 72.61 euros; 95% confidence interval 25.24–119.97; t(320.016) = 3.015; p = 0.003].

Conclusion

The findings confirm the high cost of frequent ED use among people with alcohol-related problems, suggesting that costs could be reduced through implementation of intervention protocols.
SARS-CoV-2 seroprevalence and antibody trajectories after easing of COVID-19 restrictions: a longitudinal study in China
Authors: Ling Feng , Xu Zenghao , Sun Jimin , Wang Xiaoxiao , Feng Yan , Liu Ying , Chen Yijuan , Wang Jinna , Chen Zhiping , Chen Kun
Published: December 2024

Background

We aimed to evaluate the seroprevalence of SARS-CoV-2 and investigate the trajectories of protective immunity and associated risk factors in eastern China between March and November 2023 after the easing of COVID-19 restrictions.

Materials and methods

We conducted repeated population-based seroepidemiologic studies using a multistage, population-stratified, cluster random sampling method. We measured neutralizing antibodies (nAbs) using a fluorescence immunoassay. We calculated both overall and stratified seroprevalence. The latent class growth mixed model (LCGMM) was used to analyze the dynamic trajectories of antibodies, and a multinomial logistic regression model was used to identify factors associated with different antibody trajectory patterns.

Results

A total of 6,147 participants were included at baseline, with a median age of 53.61 years. Both observed and adjusted seroprevalence remained high and stable throughout the study period. The LCGMM identified four distinct antibody trajectories: 75.22% of participants had a high and stable antibody trajectory, while nearly 8% of them exhibited an increase, decline, or low-stable antibody trajectory. Younger participants, women, those fully vaccinated, and individuals with a history of previous infection were more likely to have high and stable antibody trajectories.

Conclusion

The majority of the population maintained sustained protective immunity after the outbreak, following the easing of COVID-19 restrictions across the country.
Graph theoretic visualization of patient and health worker messaging in the EHR
Authors: Zia ul Haq Muhammad , Hornback Andrew , Harzand Arash , Gutman David Andrew , Gallaher Bradley , Schoenberg Evan D. , Zhu Yuanda , Wang May D. , Anderson Blake
Published: December 2024

Introduction

The electronic health record (EHR) has greatly expanded healthcare communication between patients and health workers. However, the volume and complexity of EHR messages have increased health workers' cognitive load, impeding effective care delivery and contributing to burnout.

Methods

To understand these potential detriments resulting from EHR communication, we analyzed EHR messages sent between patients and health workers at Emory Healthcare, a large academic healthcare system in Atlanta, Georgia. We quantified the burden of messages interacted with by each health worker type and visualized the communication patterns using graph theory. Our analysis included 76,694 conversations comprising 144,369 messages sent between 47,460 patients and 3,749 health workers across 85 healthcare specialties.

Results

On average, nurses/certified nursing assistants/medical assistants (nurses/CNA/MA) interacted with the most messages (350), followed by non-physician practitioners (NPP) (241), physicians (166), and support staff (155), with the average conversation involving 10.51 interactions before resolution. Network analysis of the communication flow revealed that each health worker was connected to approximately two other health workers (average degree = 2.10). In message sending, support staff led in closeness centrality (0.44), followed by nurses/CNA/MA (0.41), highlighting their key role in fast information spread. For message reception, nurses/CNA/MA (0.51) and support staff (0.41) also had the highest values, underscoring their vital role in the communication network on the receiving end as well.

Discussion

Our analysis demonstrates the feasibility of applying graph theory to understand communication dynamics between patients and health workers and highlights the burden of EHR-based messaging.
How can microfinance institutions successfully navigate a competitive advantage and financial performance? Exploring the role of ambidextrous leadership and intellectual capital
Authors: Effendi Syahrul , So Idris Gautama , Setiadi Nugroho Juli , Soepriyanto Gatot
Published: December 2024

The main objective of this study was to investigate how ambidextrous leadership contributes to competitive advantage and financial performance in Indonesia's microfinance institutions (MFIs). A secondary aim was to analyze the moderating effect of intellectual capital on the relationship between ambidextrous leadership and competitive advantage and the mediating role of competitive advantage in the indirect link between ambidextrous leadership and financial performance. Data were collected from 88 firms in the MFI sector through purposive sampling. The Moderation-Mediation (MODMED) procedure was used to assess four proposed relationships. The results indicated that ambidextrous leadership is crucial for achieving competitive advantage, with intellectual capital as a moderator in this relationship. Furthermore, competitive advantage was found to significantly explain financial performance and serve as an intermediary in the connection between ambidextrous leadership and financial performance. This study addresses the existing literature gap by examining ambidextrous leadership's influence on competitive advantage. It also introduces a fresh perspective by suggesting that intellectual capital acts as a boundary condition in the link between ambidextrous leadership and competitive advantage. The findings offer pragmatic insights for organizations, particularly MFIs in Indonesia, to enhance their competitive advantage through effective leadership and strategic management of intellectual resources.
A Review on Data-Driven Model-Free Sliding Mode Control
Authors: Castellanos-Cárdenas Duby , Posada Norha L. , Orozco-Duque Andrés , Sepúlveda-Cano Lina M. , Castrillón Fabio , Camacho Oscar E. , Vásquez Rafael E.
Published: December 2024

Sliding mode control (SMC) has been widely used to control linear and nonlinear dynamics systems because of its robustness against parametric uncertainties and matched disturbances. Although SMC design has traditionally addressed process model-based approaches, the rapid advancements in instrumentation and control systems driven by Industry 4.0, coupled with the increased complexity of the controlled processes, have led to the growing acceptance of controllers based on data-driven techniques. This review article aims to explore the landscape of SMC, focusing specifically on data-driven techniques through a comprehensive systematic literature review that includes a bibliometric analysis of relevant documents and a cumulative production model to estimate the deceleration point of the scientific production of this topic. The most used SMC schemes and their integration with data-driven techniques and intelligent algorithms, including identifying the leading applications, are presented.
Monitoring and Analyzing Driver Physiological States Based on Automotive Electronic Identification and Multimodal Biometric Recognition Methods
Authors: Zhou Shengpei , Zhang Nanfeng , Duan Qin , Liu Xiaosong , Xiao Jinchao , Wang Li , Yang Jingfeng
Published: December 2024

In an intelligent driving environment, monitoring the physiological state of drivers is crucial for ensuring driving safety. This paper proposes a method for monitoring and analyzing driver physiological characteristics by combining electronic vehicle identification (EVI) with multimodal biometric recognition. The method aims to efficiently monitor the driver’s heart rate, breathing frequency, emotional state, and fatigue level, providing real-time feedback to intelligent driving systems to enhance driving safety. First, considering the precision, adaptability, and real-time capabilities of current physiological signal monitoring devices, an intelligent cushion integrating MEMSs (Micro-Electro-Mechanical Systems) and optical sensors is designed. This cushion collects heart rate and breathing frequency data in real time without disrupting the driver, while an electrodermal activity monitoring system captures electromyography data. The sensor layout is optimized to accommodate various driving postures, ensuring accurate data collection. The EVI system assigns a unique identifier to each vehicle, linking it to the physiological data of different drivers. By combining the driver physiological data with the vehicle’s operational environment data, a comprehensive multi-source data fusion system is established for a driving state evaluation. Secondly, a deep learning model is employed to analyze physiological signals, specifically combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The CNN extracts spatial features from the input signals, while the LSTM processes time-series data to capture the temporal characteristics. This combined model effectively identifies and analyzes the driver’s physiological state, enabling timely anomaly detection. The method was validated through real-vehicle tests involving multiple drivers, where extensive physiological and driving behavior data were collected. Experimental results show that the proposed method significantly enhances the accuracy and real-time performance of physiological state monitoring. These findings highlight the effectiveness of combining EVI with multimodal biometric recognition, offering a reliable means for assessing driver states in intelligent driving systems. Furthermore, the results emphasize the importance of personalizing adjustments based on individual driver differences for more effective monitoring.
A Tertiary Study for Process Mining
Authors: Kouzari Elia , Stamelos Ioannis
Published: December 2024

Background: This tertiary study lists the secondary studies published in the process mining domain and provides an analysis related to a set of research questions. It is the first tertiary study in this area. The objective is to provide information about the available secondary studies in process mining, respond to research questions relating to the thematic areas covered in the studies, as well as trends regarding their quality, and report on findings for publication venues, citations, guidelines used, and demographics. Method: A tertiary study based on systematic secondary studies published up to March 2023. A total of 25 secondary studies related to process mining have been identified following the application of inclusion/exclusion criteria and quality assessment. Results: The most popular thematic areas addressed are technologies and applications for process mining and healthcare. The secondary studies in process mining have a medium quality score of 3.5. The guidelines introduced by Kitchenham over the years are preferred in secondary studies in this field. There is no trend related to the number of primary studies included in secondary studies in process mining. Conclusion: Although numerous secondary studies exist for process mining, there is still room for more research, specifically in the areas highlighted in this study. Future researchers can use this study for reference, and they can also use the listed research topics to dive deep into the issues identified.
Enhancing Intrusion Detection Systems with Dimensionality Reduction and Multi-Stacking Ensemble Techniques
Authors: Alsaffar Ali Mohammed , Nouri-Baygi Mostafa , Zolbanin Hamed
Published: December 2024

The deployment of intrusion detection systems (IDSs) is essential for protecting network resources and infrastructure against malicious threats. Despite the wide use of various machine learning methods in IDSs, such systems often struggle to achieve optimal performance. The key challenges include the curse of dimensionality, which significantly impacts IDS efficacy, and the limited effectiveness of singular learning classifiers in handling complex, imbalanced, and multi-categorical traffic datasets. To overcome these limitations, this paper presents an innovative approach that integrates dimensionality reduction and stacking ensemble techniques. We employ the LogitBoost algorithm with XGBRegressor for feature selection, complemented by a Residual Network (ResNet) deep learning model for feature extraction. Furthermore, we introduce multi-stacking ensemble (MSE), a novel ensemble method, to enhance attack prediction capabilities. The evaluation on benchmark datasets such as CICIDS2017 and UNSW-NB15 demonstrates that our IDS surpasses current models across various performance metrics.
A Temporal Graph Network Algorithm for Detecting Fraudulent Transactions on Online Payment Platforms
Authors: Saldaña-Ulloa Diego , De Ita Luna Guillermo , Marcial-Romero J. Raymundo
Published: December 2024

A temporal graph network (TGN) algorithm is introduced to identify fraudulent activities within a digital platform. The central premise is that digital transactions can be modeled via a graph network where various entities interact. The data used to build an event-based temporal graph (ETG) were sourced from an online payment platform and include details such as users, cards, devices, bank accounts, and features related to all these entities. Based on these data, seven distinct graphs were created; the first three represent individual interaction events (card registration, device registration, and bank account registration), while the remaining four are combinations of these graphs (card–device, card–bank account, device–bank account, and card–device–bank account registration). This approach was adopted to determine if the graph’s structure influenced the detection of fraudulent transactions. The results demonstrate that integrating more interaction events into the graph enhances the metrics, meaning graphs containing more interaction events yield superior fraud detection results than those based on individual events. In addition, the data used in this work correspond to Latin American payment transactions, which is relevant in the context of fraud detection since this region has the highest fraud rate in the world, yet few studies have focused on this issue.
Time-Delay-Based Sliding Mode Tracking Control for Cooperative Dual Marine Lifting System Subject to Sea Wave Disturbances
Authors: Cong Yiwen , Li Gang , Li Jifu , Tian Jianyan , Ma Xin
Published: December 2024

Dual marine lifting systems are complicated, fully actuated mechatronics systems with multi-input and multi-output capabilities. The anti-swing cooperative lifting control of dual marine lifting systems with dual ships’ sway, heave, and roll motions is still open. The uncertainty regarding system parameters makes the task of achieving stable performance more challenging. To adjust both the attitude and position of large distributed-mass payloads to their target positions, this paper presents a time-delay-based sliding mode-tracking controller for cooperative dual marine lifting systems impacted by sea wave disturbances. Firstly, a dynamic model of a dual marine lifting system is established by using Lagrange’s method. Then, a kinematic coupling-based cooperative trajectory planning strategy is proposed by analyzing the coupling relationship between the dual marine lifting system and dual ship motion. After that, an improved sliding mode tracking controller is proposed by using time-delay estimation technology, which estimates unknown system parameters online. The finite-time convergence of full-state variables is rigorously proven. Finally, the simulation results verify the designed controller in terms of anti-swing control performance. The hardware experiments revealed that the proposed controller significantly reduces the actuator positioning errors by 83.33% compared with existing control methods.
Distributed Coordination D-Stabilization in Cyclic Pursuit Formations of Dynamical Multi-Agent Systems
Authors: Park Jun-Gyu , Kim Yeongjae , Kim Tae-Hyoung
Published: December 2024

In this study, the cyclic pursuit formation stabilization problem in target-enclosing operations by multiple homogeneous dynamic agents is investigated. To this end, a Lyapunov D-stability problem is first formulated to cover the transient performance requirements for multi-agent systems. Then, a simple diagrammatic Lyapunov D-stability criterion for cyclic pursuit formation is derived. The formation control scheme combined with a cyclic-pursuit-based distributed online path generator satisfying this condition guarantees both the required transient performance and global convergence properties with theoretical rigor. It is shown that the maximization of the connectivity gain in a cyclic-pursuit-based online path generator can be reduced to an optimization problem subject to linear matrix inequality constraints derived using the generalized Kalman-Yakubovich–Popov lemma. This approach provides a permissible range of connectivity gain, which not only guarantees global formation stability/convergence properties but also satisfies the required performance specification. Several numerical examples are provided to confirm the effectiveness of the proposed method.
Platform-Dependent Entrepreneurship: A Systematic Review
Authors: Yu Songping , Sekiguchi Tomoki
Published: December 2024

Digital platforms have facilitated the emergence of novel entrepreneurial opportunities that rely on a platform for market entry and access to resources. This systematic review synthesizes current knowledge on how platforms impact and shape “platform-dependent entrepreneurship” and how platform-dependent entrepreneurs (PDEs) respond to power asymmetries. The results of the review suggest that platforms lower barriers to entry but also lead to PDEs’ dependence and precarity. Specifically, platform governance significantly impacts PDEs’ behavior by shaping their market access, visibility, and opportunities through various mechanisms. In response, PDEs employ several strategies to preserve their autonomy, such as engaging in multi-homing, capitalizing on branding, and conducting activities outside of the platform. Thus, PDEs’ entrepreneurial identity is co-constructed through the interplay of individual agencies and platform dynamics as they navigate tensions in the platform ecosystem. Based on this review, we present a research agenda for the future that has substantial implications for the theory and application of PDEs in the literature.
Micronutrient Content of Aboveground Biomass as Influenced by Different Proportions of Medicago media Pers. in Two-Component Alfalfa–Grass Mixtures
Authors: Olszewska Marzenna
Published: December 2024

The aim of this study was to determine the effect of different proportions of hybrid alfalfa (Medicago media Pers.) in two-component mixtures with festulolium (Festulolium braunii (K. Richt.) A. Camus) and orchard grass (Dactylis glomerata L.) on the micronutrient content of aboveground biomass. The study was conducted in 2011–2013 in Poland. The experiment had a split-plot design with four replications, and the experimental variables were as follows: (i) mixtures: Dactylis glomerata (Dg) + Medicago media (Mm) and Festulolium braunii (Fb) + Medicago media (Mm), and (ii) proportion of Medicago media seeds in the mixture: 30%, 50%, and 70%. Pure-sown Dactylis glomerata and pure-sown Festulolium braunii were the control treatments. The proportion of hybrid alfalfa in the biomass yield of mixtures increased throughout the study, and this species was the dominant component of the sward already in the second year, regardless of the proportion of sown seeds. Orchard grass exerted greater competitive pressure on alfalfa than festulolium. Pure-sown Dactylis glomerata accumulated more manganese (Mn) and iron (Fe) than pure-sown Festulolium braunii; no significant differences in the copper (Cu) and zinc (Zn) content of aboveground biomass were found between species. The aboveground biomass of mixtures was characterized by higher Cu content and lower Mn content than the biomass of grass monocultures. As a component of mixtures, alfalfa had a negative influence on the Fe content of aboveground biomass (dry matter basis). No significant differences in Cu and Mn content were observed between the mixtures. The Fb50% + Mm50% mixture had the highest Zn content, and the Fb70% + Mm30% mixture had the highest Fe content. The present findings suggest that practical two-component alfalfa–grass mixtures should be composed based on species competitiveness and selection of a grass component adapted to local agroecological conditions, rather than on the proportion of alfalfa seeds in the mixture.
Lighting Patterns Regulate Flowering and Improve the Energy Use Efficiency of Calendula Cultivated in Plant Factories with Artificial Lighting
Authors: Munyanont Maitree , Lu Na , Rachma Dannisa Fathiya , Ruangsangaram Thanit , Takagaki Michiko
Published: December 2024

Calendula is an edible flower with highly beneficial bioactive compounds for human health. Environmental factors such as light influence flower yield and quality. Calendula is cultivated under controlled environments in plant factories with artificial lighting (PFALs), which enhance its productivity. However, electricity is the main operating cost, with fees based on the time of use in some countries. This study aimed to investigate the effects of lighting patterns on calendula growth and yield. Two varieties of calendula seedlings were cultivated in a PFAL and subjected to six different lighting patterns, i.e., 6 h/6 h, 12 h/12 h, 6 h/2 h, and 18 h/6 h (light/dark) and two continuous lighting patterns with varying light intensities (24 h-200 and 24 h-400). The results indicated that plants cultivated under the 6 h/2 h, 18 h/6 h, 24 h-200, and 24 h-400 conditions showed a more rapid appearance of the first flower bud than those cultivated under the 6 h/6 h and 12 h/12 h conditions. The number of flowers and the fresh and dried weights tended to increase with a longer photoperiod. Interestingly, the total carotenoid content (TCC) of “Citrus Orange” increased under 6 h/6 h and 12 h/12 h conditions compared with the others. For “Orange Gem”, continuous lighting (24 h) increased the total phenolic content (TPC) and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity in flowers compared with the 6 h/6 h 12 h/12 h, and 6 h/2 h treatments. The energy use efficiency (EUE) under the 24 h-200 condition was the highest in terms of flower yield and secondary metabolite production. These results suggest that lighting patterns can be used to modulate the growth and flowering of calendula and to maximize EUE.
The Bacterial Root Microbiome in Ecuadorian Andean Maize
Authors: Sanchez-Garnica Manoella A. , Lozano-Granda Angel F. , Ramirez-Villacis Dario X. , Barriga-Medina Noelia , Urresta-Palacios Luis F. , Garzon-Proaño Brigitte A. , Proaño-Arias Stefania , Andrade-Bolaños Hector J. , Leon-Reyes Antonio
Published: December 2024

Elucidating the intricate interplay between microorganisms and crops, mainly maize (Zea mays), holds promise for devising agronomic interventions to augment yield, inducing defense mechanisms against pests and pathogens, and alleviating abiotic stresses. In pursuit of comprehending the composition of the maize root microbiomes across different genotypes, we conducted a thorough characterization of the root and rhizosphere microbiome of three indigenous Ecuadorian Andean maize cultivars, UCE-Amarillo, INIAP-122, and UCE-Pepa grown in a native soil, employing high-throughput DNA sequencing targeting the 16S rRNA gene. Root tissues and rhizosphere were collected from 18 plants from each cultivar, plus 18 bulk soil samples. Alpha diversity metrics, such as the Chao and Shannon indices, were employed to assess microbial richness and evenness, revealing a notably lower diversity within the root microbiome than the rhizosphere and bulk soil compartments. Furthermore, discernible plant genotype-driven microbiome assembly patterns were observed across all compartments. Taxonomic profiling unveiled a conspicuous absence of Actinobacteria and an elevated abundance of Proteobacteria within the root microbiome. Moreover, 34 amplicon sequence variants (ASVs) were present in all the root and rhizosphere samples (100% occupancy) from the three cultivars, making these the core microbiome of the indigenous Ecuadorian Andean maize. The highly consistent root and rhizosphere colonization across cultivars make these 34 ASVs great candidates as bioinoculants for maize in the Andean region of Ecuador. Target isolation and functional characterization of these microbes are necessary for future applications to enhance their resistance to biotic and abiotic stresses.
Effects of Rhizobium Inoculation on Rhizosphere Soil Microbial Communities, Physicochemical Properties, and Enzyme Activities in Caucasian Clover Under Field Conditions
Authors: Ma Yiming , Suo Yuan , Qi Haibo , Tang Fang , Wang Mingjiu
Published: December 2024

Excessive use of chemical fertilizers in agriculture has become a major global source of pollution, leading to issues such as soil compaction, reduced fertility, eutrophication of water bodies, and air pollution. To address these challenges, the application of biofertilizers, such as rhizobial inoculants, has gradually become an effective, low-cost, and sustainable solution. In this study, the variety Trifolium ambiguum Bieb. (Mengnong clover No. 1) was used as the test material, and two rhizobial strains (R1 and R2) were employed for field inoculation trials. In April 2022, Caucasian clover was planted in an experimental field at Inner Mongolia Agricultural University. Each plot measured 3 m × 4 m and was arranged in a completely randomized design with three replications. In the regreening stage of 2023, rhizobial inoculation treatments were applied, with a control group included for comparison. This research examined the effects of rhizobial inoculation on the growth indicators of Caucasian clover, soil physicochemical properties, soil enzyme activities, and soil microbial communities. The results showed that rhizobial treatment increased the plant height and yield of Caucasian clover, improved soil physicochemical properties and enzyme activities, and positively affected soil microbial diversity and abundance. These changes enhanced soil fertility and optimized microbial community structure, promoting plant growth. The inoculation effect of strain R1 was superior to R2. In conclusion, rhizobial inoculants R1 and R2 can serve as effective biofertilizers for agricultural production.
The Effect of Selenium Sources and Rates on Cowpea Seed Quality
Authors: Pereira Rhayra Zanol , Fontes Luiz Eduardo de Morais Fernandes , Silva Vinícius Martins , Zuffo Alan Mario , Custódio Ceci Castilho , Sá Francisco Vanies da Silva , Reis André Rodrigues dos , Alves Charline Zaratin
Published: December 2024

Selenium (Se) is a beneficial element for plants and is essential for human nutrition. In plants, it plays an important role in the formation of selenocysteine and selenomethionine and in the activation of hydrolytic enzymes, which can aid in seed germination and reduce abiotic stress during germination. The objective of this study was to evaluate the effects of the application of selenium sources and rates to the soil on the physiological quality of cowpea seeds. The experimental design was a randomized block with four replications and a factorial scheme (7 × 2). Two sources of Se (sodium selenate and sodium selenite) and seven rates (0, 2.5, 5, 10, 20, 40 and 60 g ha−1) were used. Physiological characterization was carried out by first counting of germination, germination, emergence, accelerated aging, cold testing, electrical conductivity, length and dry biomass of shoots and roots. Germination after accelerated aging increased with selenate, even at higher rates, whereas selenite provided benefits at lower rates. Selenation linearly increased germination after the cold test and linearly reduced electrolyte leakage as the Se rate increased. The soil application of Se is beneficial for cowpea seed quality. Compared with those treated with sodium selenite, cowpea plants treated with sodium selenate through the soil produce more vigorous seeds. The application of 10 g ha−1 Se in the form of sodium selenate provides seedlings with faster germination and root development and is an alternative for rapid stand establishment.