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Microplastic Contamination of the Turkish Worm Lizard (<i>Blanus strauchi</i> Bedriaga, 1884) in Muğla Province (Türkiye)
No full textBecause of their diversity, microplastics (MPs), which are synthetic particles smaller than 5 mm, are highly bioavailable and widely distributed. The prevalence of microplastics in aquatic habitats has been extensively studied but less is known about their presence in terrestrial environments and biota. This study examined MP intake in terrestrial environments utilizing gastrointestinal tracts (GITs), with a particular focus on the Turkish worm lizard (Blanus strauchi). Suspected particles discovered in the GITs were removed, measured, and characterized based on size, shape, color, and polymer type in order to evaluate MP ingestion. Out of 118 samples analyzed, 29 specimens (or 24.57%) had microplastic particlesMP length did not significantly correlate with snout-vent length (SVL) and weight. These correlations were tested to determine whether the size or weight of Blanus strauchi influenced the amount or size of MPs found within the GITs. Also, MP consumption by the worm lizard did not correlate with the year of sampling. All particles identified as fibers through FT-IR spectroscopy analysis. The most common type of microplastic was polyethylene terephthalate (PET). The most often detected color was blue, with mean MP lengths ranging from 133 mu m to 2929 mu m. It has been demonstrated that worm lizards inhabiting soil or sheltering under stones in bushy areas with sparse vegetation consume MPs. Predation is regarded to be the most likely way through which MPs infiltrate terrestrial food webs
3D-printed guide template for cervical stabilization surgery: A case report
No full textIntroduction: Cervical spine injuries are a growing global public health concern. Management depends on injury severity, with severe cases requiring surgical decompression and stabilization. Emerging technologies such as 3D-printed patient-specific templates offer enhanced accuracy and safety in pedicle screw placement compared to traditional freehand techniques. Research question: Can 3D-printed patient-specific guide templates improve the safety, efficiency, and outcomes of cervical spine fusion procedures compared to conventional techniques? Case report: A 62-year-old male with a cervical spinal injury underwent emergency decompression at an external facility. Subsequent imaging revealed iatrogenic instability due to multi-level laminectomies (C3-C6). Preoperative CT data were processed using software (Mimics v14, MeshMixer) to design patient-specific templates, printed with a 3D Ultimaker 2 printer. These sterilized templates were used intraoperatively for navigation, aiding in transpedicular screw placement at C2, C7, and T1 levels, with lateral mass screws placed for C3-C6 using a freehand technique. Results: Intraoperative fluoroscopy confirmed accurate screw placement with no vertebral artery injury or malposition. Postoperative CT validated precise alignment, and no hematoma or complications were observed. The use of 3D templates reduced operative time and radiation exposure compared to traditional methods. Discussion: 3D-printed templates offer a cost-effective and accessible alternative to robotic systems, enhancing precision and minimizing complications. Literature supports their safety, accuracy, and potential to reduce operative time, blood loss, and radiation exposure. Conclusion: 3D-printed templates represent an effective and innovative tool for improving cervical spine surgery outcomes. Future advancements in 3D-printing technologies could further optimize spinal stabilization and fusion procedures
Joint Tomek Links (JTL): An Innovative Approach to Noise Reduction for Enhanced Classification Performance
No full textNoisy data is a prevalent issue in data mining, significantly impacting the performance of classification algorithms. Mathematical methods are crucial in tackling this obstacle, particularly in optimizing noise detection and data preprocessing. This study proposes a novel approach-Joint Tomek Links (JTL)- to identify and eliminate noisy instances by detecting pairs of nearest neighbors from different classes. It first finds the Tomek links and then refines a probabilistic method to determine which instance from a pair will be removed. In our approach, a random tree classifier serves as the base model. We conducted experiments on 40 benchmark datasets spanning various domains, achieving an average classification accuracy of 83.26% for JTL. The results demonstrate that the JTL attains an average improvement of 5.33% in accuracy compared to the original classification with a random tree. Furthermore, JTL surpasses existing techniques, delivering a noteworthy gain in accuracy by 12.30% on the same datasets. These findings underscore the effectiveness of JTL in enhancing data quality and boosting classification performance in data mining tasks
Toolbox of spin-Adapted generalized Pauli constraints
No full textWe establish a toolbox for studying and applying spin-Adapted generalized Pauli constraints (GPCs) in few-electron quantum systems. By exploiting the spin symmetry of realistic N-electron wave functions, the underlying one-body pure N-representability problem simplifies, allowing us to calculate the GPCs for larger system sizes than previously accessible. We then uncover and rigorously prove a superselection rule that highlights the significance of GPCs: whenever a spin-Adapted GPC is (approximately) saturated-referred to as (quasi)pinning-the corresponding N-electron wave function assumes a simplified structure. Specifically, in a configuration interaction expansion based on natural orbitals only very specific spin configuration state functions may contribute. To assess the nontriviality of (quasi)pinning, we introduce a geometric measure that contrasts it with the (quasi)pinning induced by simple (spin-Adapted) Pauli constraints. Applications to few-electron systems suggest that previously observed quasipinning largely stems from spin symmetries
A Missed Opportunity in the Cyprus Question? The Enosis Cum Dhekelia Base Formula and the Çağlayangil-Toumbas Talks (June-December 1966)
No full textA prior information-based estimation method for fitting pearson distributions: Applications in process capability and bounded data studies
No full textThe distributions to fit the data set using the moments are called the Pearson distribution family. This study proposes a novel alternative to the method of moments, which is based on some prior information (namely the lower limit, the upper limit, and the mode) about the data. In the proposed method, a theoretical distribution can be fitted with only the first moment of the data without the need for a higher-order moment if we have the limit information. The method is exemplified in a process capability context. The tolerance information provided by the customer can be used as prior information in the proposed method. An increasingly significant sub-branch of capability indices studies involves creating process capability indices for one-sided asymmetric tolerances. Using the upper and lower specification limits and the target value information provided by the customer, an acceptable process distribution can be defined as the base distribution by the proposed method and the process capability index can be calculated
TRIGGERS AND ORGAN INVOLVEMENTS OF IgA VASCULITIS: IS THERE A NEED TO SPLIT UP IgA VASCULITIS
No full text
Effect of eHealth Interventions on Medication Adherence in Kidney Transplant Recipients: Meta-Analysis of Randomised Controlled Trials
No full textBackground: Kidney transplant recipients must take immunosuppressive drugs for life, and medication non-adherence is a primary risk factor for graft loss and death. With the advancement of technology, electronic health applications are widely used in chronic disease management and offer the potential to improve medication adherence in kidney transplant recipients. Aim: This meta-analysis aims to evaluate randomised controlled trials (RCTs) that assess the effectiveness of eHealth interventions in improving medication adherence among kidney transplant recipients. Methods: This study, which was designed as a systematic review and meta-analysis, followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocols in the planning and reporting phases. Electronic databases and manual literature searches were the two main data sources. Full-text RCTs in PubMed, Medline, Web of Science and Scopus databases were systematically searched. The searches covered studies from 2014 to March 2024. Results: The search yielded 524 articles. Eight RCTs with 779 participants were included in the analysis. The meta-analysis results indicated that, compared with the control group, adherence rates (RR: 1.19; 95% CI: 1.06–1.35; p = 0.01. Heterogeneity: Q = 8.69; p = 0.28; I2 = 19%) and adherence scores (SMD: 0.17; 95% CI: 0.05–0.29; p = 0.02. Heterogeneity: Q = 0.45; p = 0.93; I2 = 0%) significantly increased in the eHealth intervention group compared with the control group. Conclusion: The findings of this report show that eHealth interventions to improve medication adherence in kidney transplant recipients show favourable outcomes compared with standard care. We recommend eHealth interventions to improve long-term survival and patient outcomes in kidney transplant recipients
