Search Results (69)

The massive volumes of data and the intensification of digital transformation are reshaping recruitment practices within organizations, particularly for specialized information technology (IT) profiles. However, existing studies have often remained conceptual, focused on developed economies, or limited to a narrow set of factors, thereby leaving important gaps in emerging contexts. Moreover, there are few studies that critically assess how Data Mining is impacting the IT recruitment process, and none that assess this in the context of Morocco. This study employs an extensive literature review to explore the role of Data Mining in facilitating the recruitment of top IT candidates, focusing on its ability to improve selection quality, reduce costs, and optimize decision-making procedures. The study provides empirical evidence from the Moroccan aeronautical and digital services sectors, an underexplored context where IT talent scarcity and rapid technological change pose critical challenges. Primary data comes from a survey of 200 IT recruitment professionals operating in these sectors in Morocco, allowing an assessment of the impact of Data Mining on IT talent acquisition initiatives. The findings reveal that a range of capabilities resulting from the application of Data Mining significantly and positively influences the success of IT recruitment processes. The novelty of the article lies in integrating six key determinants of algorithmic recruitment into a unified framework and demonstrating their empirical significance through binary logistic regression. The focus on the Moroccan context adds value to the international discussion and extends the literature on HR analytics beyond its conventional geographical and theoretical boundaries. The article thus contributes to the emerging literature on the role of digital technologies in IT recruitment that will be of interest to industry practitioners and other researchers in this field. Full article

Background/Objectives: Breastfeeding is essential to maternal and child health, and multiple factors influence its success. This study examined the factors associated with breastfeeding type among infants aged 0 to 12 weeks. Methods: A mixed-methods study, employing a convergent design, was conducted in the rooming in unit of a hospital in Espírito Santo, Brazil. A total of 296 mothers of neonates ≥ 34 weeks participated in both the quantitative and qualitative phases. The qualitative phase involved semi-structured interviews conducted in the hospital setting. In the quantitative phase, data were collected via telephone in three waves (on days 14, 40, and 90 postpartum), critical moments for establishing and maintaining breastfeeding, analyzing sociodemographic factors (age, education, marital status, number of pregnancies), clinical factors (gestational age, mode of delivery, milk production) and support factors (social and hospital). Descriptive statistical analysis and binomial and multinomial logistic regression models were used, conducted in R 4.3.3 software. The qualitative and quantitative findings were integrated through simultaneous incorporation and presented in a joint display. Results: The analysis showed that although most mothers had high adherence to prenatal care, breastfeeding counseling was insufficient. In addition to the type of delivery and immediate skin-to-skin contact, other factors were also found to be relevant to maintaining exclusive breastfeeding. Higher maternal education and a greater number of pregnancies were associated with better breastfeeding practices, albeit with variations in statistical significance. Support received during hospitalization, especially from the healthcare team, also emerged as a central element in the qualitative reports, reinforcing its role as a protective factor for continued breastfeeding. Early formula use within the first 48 h was identified as a barrier to initiating and maintaining breastfeeding. Conclusions: The duration and maintenance of exclusive breastfeeding varied over time, depending on factors such as the number of prenatal appointments, education level, number of pregnancies, mode of delivery, immediate skin-to-skin contact, and, most importantly, the use of formula in the first 48 h. The early introduction of formula in maternity wards represented a significant obstacle to breastfeeding, reinforcing the importance of integrated public policies and multidisciplinary initiatives that promote breastfeeding from birth. Full article

Three-dimensional path planning is critical for the successful operation of unmanned aerial vehicles (UAVs), automated guided vehicles (AGVs), and robots in industrial Internet of Things (IIoT) applications. In 3D path planning, the standard Particle Swarm Optimization (PSO) algorithm suffers from premature convergence and a tendency to fall into local optima, leading to significant deviations from the optimal path. This paper proposes an improved PSO (IPSO) algorithm that enhances particle diversity and randomness through the introduction of logistic chaotic mapping, while employing dynamic learning factors and nonlinear inertia weights to improve global search capability. Experimental results demonstrate that IPSO outperforms traditional methods in terms of path length and computational efficiency, showing potential for real-time path planning in complex environments. Full article

Rainfall-induced slope failures are among the most frequent and destructive natural hazards in Japan’s mountainous regions, often causing severe loss of life and damage to infrastructure. This study presents an integrated statistical framework for regional-scale landslide hazard mapping, with a focus on 0-order basins. To enhance spatial prediction accuracy, both bivariate and multivariate statistical models are employed. Bivariate models efficiently assess the relationship between individual conditioning factors and landslide occurrences but assume variable independence. Conversely, multivariate models account for multicollinearity and the combined effects of interacting factors, although they often require more complex data processing and may lack spatial clarity. To leverage the strengths of both approaches, two hybrid models were developed and applied to a 242.94 km² area in Fukuoka Prefecture, Japan. Model validation was performed using a matrix-based evaluation supported by a threshold optimization algorithm. Among the models tested, the hybrid Frequency Ratio–Logistic Regression (FR + LR) model demonstrated the highest predictive performance, achieving a success rate of 84.30%, a false alarm rate of 17.88%, and a miss rate of 12.30%. It effectively identified critical slip surfaces within zones classified as ‘High’ to ‘Very High’ susceptibility. This integrated approach offers a statistically robust, scalable, and interpretable solution for landslide hazard assessment in geomorphologically complex terrains. It provides valuable support for regional disaster risk reduction and contributes directly to achieving the Sustainable Development Goals (SDGs). Full article

The integration of artificial intelligence (AI), big data analytics, and blockchain technologies within the digital economy presents transformative opportunities for promoting low-carbon urban development. However, a systematic understanding of how these digital innovations influence urban carbon mitigation remains limited. This study addresses this gap by proposing two research questions (RQs): (1) What are the key success factors for artificial intelligence, big data, and blockchain in urban carbon emission reduction? (2) How do these technologies interact and support the transition to low-carbon cities? To answer these questions, the study employs a hybrid methodological framework combining the decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) techniques. The data were collected through structured expert questionnaires, enabling the identification and hierarchical analysis of twelve critical success factors (CSFs). Grounded in sustainability transitions theory and institutional theory, the CSFs are categorized into three dimensions: (1) digital infrastructure and technological applications; (2) digital transformation of industry and economy; (3) sustainable urban governance. The results reveal that e-commerce and sustainable logistics, the adoption of the circular economy, and cross-sector collaboration are the most influential drivers of digital-enabled decarbonization, while foundational elements such as smart energy systems and digital infrastructure act as key enablers. The DEMATEL-ISM approach facilitates a system-level understanding of the causal relationships and strategic priorities among the CSFs, offering actionable insights for urban planners, policymakers, and stakeholders committed to sustainable digital transformation and carbon neutrality. Full article

Cardiogenic shock (CS) in the setting of severe aortic stenosis (AS) presents a critical and high-risk scenario with limited therapeutic options and poor prognosis. Transcatheter aortic valve implantation (TAVI), initially reserved for inoperable or high-risk surgical candidates, is increasingly being considered in patients with CS due to improvements in device technology, operator experience, and supportive care. This review synthesizes current evidence from large registries, observational studies, and meta-analyses that support the feasibility, safety, and potential survival benefit of urgent or emergent TAVI in selected CS patients. Procedural success is high, and early intervention appears to confer improved short-term and mid-term outcomes compared to balloon aortic valvuloplasty or medical therapy alone. Critical factors influencing prognosis include lactate levels, left ventricular ejection fraction, renal function, and timing of intervention. The absence of formal guidelines, logistical constraints, and ethical concerns complicate decision-making in this unstable population. A multidisciplinary Heart Team/Shock Team approach is essential to identify appropriate candidates, manage procedural risk, and guide post-intervention care. Further studies and the development of TAVI-specific risk models in CS are anticipated to refine patient selection and therapeutic strategies. TAVI may represent a transformative option for stabilizing hemodynamics and improving outcomes in this otherwise high-mortality group. Full article

Vaccine equity and access remain critical challenges in global health, particularly in regions with complex socio-political landscapes, like the Middle East. This review examines disparities in vaccine distribution within the Middle Eastern context, analyzing the unique challenges and opportunities across the region. It provides an overview of the area’s diverse finances and its impact on healthcare accessibility. We examine vaccination rates and identify critical barriers to vaccination, which may be particular issues in developing countries, such as vaccine thermostability, logistical hurdles, financial constraints, and socio-cultural factors, or broader problems, like political instability, economic limitations, and deficiencies in healthcare infrastructure. However, we also highlight successful efforts at the regional and national levels to improve vaccine equity, along with their outcomes and impacts. Ultimately, by drawing on the experiences of previous programs and initiatives, we propose strategies to bridge the gaps in vaccine access through sustainable financing, local manufacturing, and the strengthening of health systems. This approach emphasizes the importance of regional collaboration and long-term self-sufficiency in enhancing global health security and achieving more equitable outcomes in the Middle East. Full article

Vegetation succession is a critical indicator of ecosystem structure and function and is often disrupted by the expansion of invasive species. However, ecosystem-scale studies elucidating invasion-driven succession mechanisms remain limited. This research focused on the Yancheng coastal salt marsh and analyzed the distribution variation of invasive species (Spartina alterniflora) and native species (Suaeda salsa and Phragmites australis) from 1987 to 2022 via the Google Earth Engine and random forest method. Logistic/Gaussian models were used to quantify land–sea distribution changes and vegetation succession trajectories. By integrating data on soil salinity, invasion duration, and fractional vegetation cover, generalized additive models (GAMs) were applied to identify the main factors influencing vegetation succession and to explore how Spartina alterniflora invasion affects the succession of salt marsh vegetation. The results indicated that the areas of Spartina alterniflora and Phragmites australis significantly increased by 3787.49 ha and 3452.60 ha in 35 years, respectively, contrasting with Suaeda salsa’s 82.46% decline. The FVC in the area has significantly increased by 42.10%, especially in the coexisted areas of different vegetation communities, indicating intensified interspecific competition. The overall trend of soil salinity was decreasing, with a decrease in soil salinity in native species areas from 0.72% to 0.37%. From the results of GAMs, soil salinity, tidal action, and invasion duration were significant factors influencing the distribution of native species, but salinity was not a significant factor affecting the Spartina alterniflora distribution. The findings revealed that the expansion of Spartina alterniflora changed the soil salinity and interspecific interactions, thereby altering the original plant community structure and establishing a new vegetation succession. This study enhances the understanding of the impacts of invasive species on ecosystems and offers theoretical support for salt marsh restoration. Full article

Objectives: This study aimed to evaluate the success rates of NSRCT performed by AEGD residents and to identify predictive factors associated with clinical outcomes and patient satisfaction. Methods: A retrospective chart review was conducted on cases treated between 2012 and 2021. Eligible cases included fully developed permanent teeth that underwent NSRCT and received a final restoration by general dentistry residents, with a minimum of 12 months of follow-up. Data collected included demographic information, medical history, clinical symptoms, radiographic findings, instrumentation, type and timing of final restorations, and patient satisfaction scores. Treatment success was defined as the absence of symptoms and either the resolution or stability of periapical radiolucency. Patient satisfaction and pain levels were also analyzed. Results: AEGD residents achieved radiographic and clinical RCT success rates of 93.3% and 91.5%, respectively. Multivariate logistic regression showed that the presence of an intact restoration was significantly associated with increased odds of tooth retention (odds ratio [OR] = 3.4, p < 0.001), while post placement in a straight root was also a significant predictor of survival (OR = 4.2, p = 0.02). Conversely, pre-existing radiolucency (OR = 0.37, p = 0.018) and the use of a metal post (OR = 0.23, p = 0.012) were significantly associated with lower odds of tooth retention. Worse periodontal health was significantly associated with increased odds of pain on percussion, with a 74.19% increase in odds per worsening category (OR = 1.74, p = 0.002). Patient satisfaction was significantly higher when restorations remained intact, with esthetic satisfaction increasing by a factor of 3.08 (OR = 3.08, p < 0.001) and functional satisfaction increasing by a factor of 3.9 (OR = 3.9, p < 0.001). Conclusions: Endodontic treatments performed by AEGD residents demonstrated high success rates and favorable patient-reported outcomes. Restoration integrity, periodontal health, and post and final restoration selection play critical roles in treatment success and patient satisfaction. Full article

This paper analyzes a mathematical model to investigate the complex interactions between tumor cells, immune cells (natural killer (NK) cells and CD8+ cytotoxic T lymphocytes (CTLs)) and chemotherapy. The primary objectives are to analyze tumor–immune interactions without and under treatment, identify critical thresholds for tumor eradication, and evaluate how chemotherapy parameters influence therapeutic outcomes. The model integrates NK cells and CTLs as effector cells, combining their dynamics linearly for simplicity. Tumor growth follows a logistic function, while immune–tumor interactions are modeled using a Hill function for fractional cell death. Stability and bifurcation analysis are employed to identify equilibria (tumor-free, high-tumor, and a novel middle steady state), bistability regimes, and critical parameter thresholds. Numerical simulations use experimentally validated parameter values from the literature. This mathematical analysis provides a framework for assessing the efficacy of chemotherapy by examining the dynamic interplay between tumor biology and treatment parameters. Our findings reveal that treatment outcomes are sensitive to the balance between the immune system’s biological parameters and chemotherapy-specific factors. The model highlights scenarios where chemotherapy may fail due to bistability and identifies critical thresholds for successful tumor eradication. These insights can guide clinical decision making in dosing strategies and suggest combination therapies such as immunotherapy–chemotherapy synergies to shift the system toward favorable equilibria. Full article

Digital Shipping Corridors (DSCs) are gaining traction as integrated models for increasing transparency, efficiency, and sustainability in maritime logistics. Yet, the enabling conditions for their effective implementation remain insufficiently explored. This study employs a qualitative thematic review approach, analyzing the academic literature, global policy documents, and selected case studies to identify and synthesize the critical success factors for DSC development. The analysis reveals seven interdependent factors: technological infrastructure, economic feasibility, regulatory frameworks, logistical efficiency, logistical security, stakeholder collaboration, and environmental sustainability. These factors are not independent but interact dynamically, requiring coordinated development across technical, institutional, and environmental domains. This study proposes a dynamic interaction framework that illustrates how progress in one area (e.g., digital infrastructure) depends on readiness in others (e.g., governance and cross-sector collaboration). The outcomes contribute both conceptually and practically. The framework offers a system-level understanding of DSC implementation and identifies key leverage points for intervention. The findings provide strategic guidance for policymakers, port authorities, and supply chain stakeholders pursuing digitally enabled sustainable maritime corridors. This study also highlights areas for future empirical validation, particularly in relation to governance integration and cross-border alignment. Full article

Background: Approximately 25.0% of metastatic prostate cancer patients harbour DNA damage repair mutations, including BRCA1 and BRCA2, which are actionable targets for poly(ADP-ribose) polymerase (PARP) inhibitors. Accurate detection of BRCA1/2 mutations is critical for guiding targeted therapies, but crucial pre-analytical factors, such as tissue storage duration and DNA fragmentation, drastically affect the reliability of next-generation sequencing (NGS) using real-world diagnostic specimens. Methods: This multicentre study analysed 954 formalin-fixed paraffin-embedded tissue samples from 11 centres, including 559 biopsies and 395 surgical specimens. This study examined the impact of storage duration (<1 year, 1–2 years, and >2 years) and DNA parameters (concentration and fragmentation index) on NGS success rates. Logistic regression and Cox regression analyses were used to assess correlations between these factors and sequencing outcomes. Results: NGS success rates decreased significantly with longer storage, from 87.8% (<1 year) to 69.1% (>2 years). Samples with higher DNA concentrations and fragmentation indexes had higher success rates (p < 0.001). Surgical specimens had superior success rates (83.3%) compared with biopsies (72.8%) due to better DNA quality. The DNA degradation rate was more pronounced in older samples, underscoring the negative impact of extended storage. Conclusions: Timely testing of BRCA1/2 mutations is critical for optimizing the identification of prostate cancer patients eligible for PARP inhibitors. Surgical specimens provide more reliable results than biopsies and minimizing the storage duration significantly enhances testing outcomes. Standardizing pre-analytical and laboratory procedures across centres is essential to ensure personalized treatments and improve patient outcomes. Full article

Background and Objectives: Central sensitization (CS) has been identified as a significant factor influencing persistent pain and dissatisfaction following total knee arthroplasty (TKA). However, its effect on unicompartmental knee arthroplasty (UKA) remains largely unexplored. Unlike TKA, UKA preserves most native knee structures, with less bone cut, leading to different postoperative pain mechanisms. Nevertheless, the revision rate for unexplained pain following UKA is higher than after TKA. This study investigates the influence of preoperative CS on pain and dissatisfaction after UKA. Materials and Methods: This retrospective cohort study included 121 patients who underwent primary UKA for medial compartment osteoarthritis of the knee. Patients were screened for CS preoperatively using the Central Sensitization Inventory (CSI) and categorized into a CS group (CSI ≥ 40; n = 26) and a non-CS group (CSI < 40; n = 95). Clinical outcomes, including the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Forgotten Joint Score (FJS), and patient satisfaction, were assessed at the 2-year postoperative follow-up visit. A multivariate regression analysis was used to determine the risk factors for postoperative dissatisfaction. Results: The CS group reported significantly worse postoperative WOMAC pain, function, and total scores than the non-CS group (all p < 0.05). FJS was also significantly worse in the CS group than in the non-CS group (64.4 vs. 72.7, respectively, p = 0.005). Patient satisfaction was significantly lower in the CS group than in the non-CS group (65.4% vs. 95.8%, respectively, p < 0.001). The multivariate logistic regression analysis demonstrated that patients with a CSI score ≥ 40 had an 11.349-fold increased likelihood of dissatisfaction after UKA (95% CI: 2.315–55.626, p = 0.003). Conclusions: This study underscores the importance of recognizing CS as a critical determinant of postoperative pain and functional recovery following UKA. Patients with high CSI scores experience greater pain, increased joint awareness, and overall poorer satisfaction despite technically successful surgeries. Full article

Background: Logistics and supply chain management are crucial in modern commerce, impacting global competition, and both can directly benefit by using enterprise resource planning (ERP) systems. This case study examines key success factors behind a significant operational transformation in a company in the countryside of Alagoas, Brazil. From this context, two research questions emerge: (a) What are the main success factors that drove a significant operational transformation in logistics and supply chain management, and how did these factors impact the company’s growth? (b) How does digital transformation and adopting an ERP impact the company’s logistics activities? Methods: Data were collected through on-site observations, interviews with supervisors and a manager, and analysis of company-provided documentation. Results: The study identified key processes, stakeholders, and practices, focusing on critical success factors, mission-critical processes, and the integration of core and support functions. Notable changes were observed through key logistics performance indicators, tracking the evolution from pre-implementation to post-implementation and revealing their impact on the company’s growth. Conclusions: Improved decision making between departments significantly enhanced performance and growth. The analyzed company’s success can be attributed to a process-oriented approach, digital transformation in logistics, and investment in information technology. Full article

Background and Objectives: ST elevation myocardial infarction (STEMI), particularly when complicated by cardiogenic shock (CS), is a critical condition associated with high mortality rates. Identifying predictors of in-hospital mortality can enhance patient management and outcomes. Materials and Methods: This observational, retrospective case–control study included STEMI patients, both complicated and uncomplicated by CS. Additionally, demographics, clinical characteristics, laboratory data and in-hospital mortality rates were analysed for STEMI patients with CS and those without CS. Results: This study included a total of 101 patients with STEMI, of whom 51 (50.5%) had STEMI without CS and 50 (49.5%) had STEMI with CS. No significant differences were observed in demographic characteristics or STEMI risk factors between the two groups. Emergency coronarography was performed in 90.1% of the patients, with successful thrombolysis achieved in 24.5%. Patients with CS exhibited a significantly higher mortality (52%) than those without CS (11.76%). Univariate analysis identified white blood cell counts, CK-MB, CK levels, elevated creatinine and uric acid levels and a reduced left ventricular ejection fraction (LVEF) as predictors of mortality. Logistic regression analysis revealed that LVEF and CK-MB were independent predictors of in-hospital mortality in patients with STEMI and CS. Each 1% increase in LVEF was associated with a reduced mortality risk (HR = 0.89; 95% CI 0.81–0.98; p = 0.018), while elevated CK-MB levels were linked to an increased mortality risk (HR = 1; 95% CI 1–1.01; p = 0.014). Conclusions: Reduced systolic function and elevated CK-MB levels are key predictors of in-hospital mortality and outcomes in STEMI patients with CS. These findings underscore the importance of early identification and support the development of targeted management strategies aimed at improving outcomes in this high-risk population. Full article