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Catheter Care and Education in Breast Cancer Patients
No full textCancer patients require long-term care due to diverse and multimodal treatments such as systemic chemotherapy. Chemotherapy can last a considerable amount of time, and different catheter methods are used in patients with breast cancer, specifically for those with HER2 positivity. However, catheters should remain in place for an extended period, meaning that patients must learn to manage and live with them. Yet, various catheter-related complications such as infection, thrombus formation, and accidental catheter dislodgement can frequently be observed. Cancer patients report difficulties living with a catheter not only during treatment but also during simple daily activities such as taking a shower. The main reason for the complexity and difficulty of this process might be the lack of information on catheter care. Therefore, education of catheter care is of utmost importance to improve the quality of life of catheterized patients and to prevent complications. This chapter discusses catheterization methods used in breast cancer patients, complications, catheter care, and educational content. © 2025 Elsevier B.V., All rights reserved
Assessment of Load and Wind Power Uncertainty Modeling on Power Flow Analysis for Distribution Systems
No full text24th International Symposium INFOTEH JAHORINA-INFOTEH-Annual -- MAR 19-21, 2025 -- BOSNIA & HERCEGHarnessing renewable energy in modern power systems demands precise modeling of uncertainties to ensure efficient and reliable operation and planning. This study investigates the intricate effects of load and wind power uncertainty on power flow results for distribution systems by employing two distinct scenario-based methodologies. The first approach integrates temporal harmony between load and wind power data, clustering them simultaneously to create cohesive scenarios. Conversely, the second approach independently models load and wind power scenarios before combining them to capture variability. In order to obtain clusters, k-means clustering method is utilized in both methods where 10000 scenarios are generated using Normal and Weibull distributions for load and wind power, respectively. These methodologies are applied to a modified 33-bus radial distribution system, examining power flows, voltage profiles, and power losses under different number of scenarios.University of East Sarajevo Faculty of Electrical Engineering,Institute of Electrical and Electronics Engineers Industry Applications Society,IEEE Bosnia and Herzegovina Section,IEEE Serbia and Montenegro Section,Univerziteta u Beogradu Fakultet Elektrotehnicki,Univerzitet u Novom Sadu Fakultet tehnickih nauka,Univerzitet u Kragujevcu Fakultet tehnickih nauka u Cacku,Sveuciliste u Splitu Fakultet elektrotehnike strojarstva i brodogradnje,Ss Cyril and Methodius University in Skopje (UKiM),Alumni Association of Electrical Engineers of East Sarajev
Bottom quark energy loss and hadronization with B+ and Bs0 nuclear modification factors using pp and PbPb collisions at ?sNN=5.02 TeV
No full textThe production cross sections of B-s(0) and B+ mesons are reported in proton-proton (pp) collisions recorded by the CMS experiment at the CERN LHC with a center-of-mass energy of 5.02 TeV. The data sample corresponds to an integrated luminosity of 302 pb(-1). The cross sections are based on measurements of the B-s(0)-> J/psi(mu(+)mu(-))phi(1020)(K+K-) and B+-> J/psi(mu(+)mu(-))K+ decay channels. Results are presented in the transverse momentum (p(T)) range 7-50 GeV/c and the rapidity interval |y| 10 GeV/c, both mesons are found to be suppressed in PbPb collisions (with R-AA values significantly below unity), with less suppression observed for the Bs0 mesons. In this p(T) range, the R-AA values for the B+ mesons are consistent with those for inclusive charged hadrons and D-0 mesons. Below 10 GeV/c, both B+ and B-s(0) are found to be less suppressed than either inclusive charged hadrons or D-0 mesons, with the B-s(0) R-AA value consistent with unity. The R-AA values found for the B+ and B-s(0) are compared to theoretical calculations, providing constraints on the mechanism of bottom quark energy loss and hadronization in the quark-gluon plasma, the hot and dense matter created in ultrarelativistic heavy ion collisions.FWF; FNRS; FWO (Belgium); CNPq; CAPES; FAPERJ; FAPERGS; FAPESP (Brazil); BNSF (Bulgaria); MoST; NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG [MoER TK202]; Academy of Finland; MEC; CEA; CNRS/IN2P3 (France); SRNSF; BMBF; DFG; HGF (Germany); NKFIH (Hungary); DAE; DST; IPM; SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE; UM (Malaysia); BUAP; CONACYT; UASLP-FAI (Mexico); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); NSTDA; TUBITAK; DOE; NSF (USA); Marie-Curie program; European Research Council; Horizon 2020 Grant [675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207]; COST Action [CA16108]; Leventis Foundation; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation; Science Committee [22rl-037]; Belgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); FWO (Belgium) under the Excellence of Science - EOS [30820817]; Beijing Municipal Science & Technology Commission [Z191100007219010]; Fundamental Research Funds for the Central Universities (China); Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; Shota Rustaveli National Science Foundation [FR-22-985]; Deutsche Forschungsgemeinschaft (DFG) [EXC 2121, 390833306, 400140256 - GRK2497]; Hellenic Foundation for Research and Innovation (HFRI) [2288]; Hungarian Academy of Sciences [K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64]; Council of Science and Industrial Research, India; ICSC - National Research Center for High Performance Computing, Big Data and Quantum Computing - NextGenerationEU program (Italy); Latvian Council of Science; Ministry of Education and Science [2022/WK/14]; National Science Center [Opus 2021/41/B/ST2/01369, 2021/43/B/ST2/01552, CEECIND/01334/2018]; National Priorities Research Program by Qatar National Research Fund; ERDF a way of making Europe [MDM-2017-0765]; Programa Severo Ochoa del Principado de Asturias (Spain); National Science, Research and Innovation Fund via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation [B39G670016]; Kavli Foundation; Nvidia Corporation; SuperMicro Corporation; Welch Foundation [C-1845]; Weston Havens Foundation (USA)We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid and other centers for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LMTLT (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl-037 (Armenia); the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the Excellence of Science - EOS - be.h project n. 30820817; the Beijing Municipal Science & Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR-22-985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), among others, under Germany's Excellence Strategy - EXC 2121 Quantum Universe - 390833306, and under project number 400140256 - GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program - uNKP, the NKFIH research grants K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the Council of Science and Industrial Research, India; ICSC - National Research Center for High Performance Computing, Big Data and Quantum Computing and FAIR - Future Artificial Intelligence Research, funded by the NextGenerationEU program (Italy); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the FundacAo para a Ciencia e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MCIN/AEI/10.13039/501100011033, ERDF a way of making Europe, and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation, grant B39G670016 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA)
Slice-level classification of kidney organ presence using CNN-ViT features: Toward clinical pre-screening
No full textKidney stone disease is a major global health concern due to its rising prevalence and related complications. Although computed tomography (CT) is highly sensitive for diagnosis, its volumetric nature increases radiologists' workload and review time. This study proposes a lightweight and low-cost deep learning-based pre-classification model to distinguish between CT slices containing the kidney and those that do not, as a preliminary step for kidney stone detection systems. The model aims to eliminate irrelevant slices and direct only meaningful images to both the second-stage AI model and the radiologist. Vision Transformer (ViT) was used to capture the global spatial context of the kidney, while ResNet18 extracted local features. These features were fused and classified using a shallow neural network. The model was tested within an interactive interface built using real patient data and integrated into a pilot application. Results showed that the proposed system achieved an average of 64.1% time saving per patient (similar to 24 minutes) by filtering out non-relevant slices, with 89.4% accuracy, 89.4% recall, and 89.5% specificity. These findings suggest that the model is a practical and efficient pre-screening component for clinical workflows and highlights the importance of pilot testing and expert feedback before real-world deployment of AI systems.Scientific and Technological Research Council of Turkiye (TUBITAK) [123E442]; TUBITAKThis study was supported by the Scientific and Technological Research Council of Turkiye (TUB & Idot;TAK) under project number 123E442. The author thanks TUB & Idot;TAK for their financial support and encouragement throughout the project. The author would like to thank the Department of Radiology at Kastamonu Research and Training Hospital for providing access to the anonymized CT imaging data used in this study
Analysis of optimal warehouse location selection for a food company using MEREC and CoCoSo methods
No full textBu tez çalışmasında, İzmir ilindeki Aliağa, Buca, Çiğli, Dikili, Foça, Karaburun, Kemalpaşa ve Menemen ilçelerinden birinde bir gıda firması için en uygun depo yerinin belirlenmesi amaçlanmıştır. Çalışmada, depo yeri seçiminde etkili olan yol ağı, lojistik bağlantılar, ulaşım güzergahlarına mesafe, depo kapasitesi, kira maliyetleri, işletme maliyetleri, pazar erişimi, rekabet durumu, çevre düzenlemeleri, doğal afet riskleri ve çalışan erişimi gibi çok sayıda kriter dikkate alınmıştır. Araştırma kapsamında, karar verme sürecinin etkin bir şekilde yürütülmesi için MEREC (Kriter Kaldırma Etkisi Yöntemi) ve CoCoSo (Birleşik Uzlaşma Çözümü Yöntemi) kullanılmıştır. MEREC yöntemi, her bir kriterin önem derecesini belirlemek için kullanılırken, CoCoSo yöntemi alternatiflerin genel sıralamasını yaparak en uygun depo yerini seçmiştir. Çalışmada kullanılan kriterler hem maliyet odaklı hem de fayda odaklı olarak değerlendirilmiş ve ilçeler bu doğrultuda karşılaştırılmıştır. Analiz sonuçlarına göre, belirlenen kriterler çerçevesinde en uygun depo yerinin seçimi gerçekleştirilmiş ve gıda firması için en avantajlı konum belirlenmiştir. Elde edilen bulgular, firmaların depo yeri seçiminde stratejik kararlarını destekleyecek nitelikte olup, özellikle lojistik maliyetlerin optimizasyonu ve operasyonel verimlilik açısından önemli katkılar sağlamaktadır.In this thesis, it is aimed to determine the most suitable warehouse location for a food company among the districts of Aliağa, Buca, Çiğli, Dikili, Foça, Karaburun, Kemalpaşa, and Menemen in İzmir. Various criteria such as road network, logistics connections, proximity to transportation routes, warehouse capacity, rental costs, operational costs, market access, competition status, environmental regulations, natural disaster risks, and employee accessibility were considered in the warehouse location selection process. For effective decision-making, the MEREC (Method based on the Removal Effects of Criteria) and CoCoSo (Combined Compromise Solution) methods were utilized. The MEREC method was used to determine the importance weights of each criterion, while the CoCoSo method was applied to rank the alternatives and select the optimal warehouse location. The criteria used were evaluated both from cost-oriented and benefit-oriented perspectives, comparing the districts accordingly. As a result of the analysis, the most suitable warehouse location was selected based on the specified criteria, and the most advantageous location for the food company was determined. The findings obtained provide significant support for companies' strategic decisions in warehouse location selection, particularly contributing to the optimization of logistics costs and operational efficiency
Ancient Era Hospitals “Asclepions” and their Heritage to the Day
No full textAsclepios is the god of medicine and health in mythology. In ancient times, healing was sought in the worship of Asclepios. Ancient hospitals built in the name of Asclepios are called “Asclepion”. In ancient times, around three hundred and twenty Asclepions were built within the borders of Greece and Türkiye today. The most important of these ancient hospitals are located in Epidauros, Pergamon, Kos, Athens and Knidos. There was also a health center (an ancient hospital) in Allianoi. In this study, the most significant locations, architectural features, treatment methods, historical and cultural roles of the ancient hospitals among the Asclepions in Western Anatolia and Greece were investigated. When the treatment methods in Asclepions are examined, it is seen that holistic medical practices were applied with a biopsychosocial approach to the patients called guests. Diseases were not seen as one-dimensional but as the result of complex processes and negative environmental, social and psychological interactions. Patients were treated with respect as beings with mental, ethical, emotional, social, moral and natural characteristics. Centuries earlier in Asclepions, the first functional applications of hospital architecture and individual and holistic medical approaches are seen. We think that today's hospital architecture and treatment approaches have many features that can be learned from the heritage of ancient hospitals in history
HALP Score as a Prognostic Biomarker in Tricuspid Valve Surgery: Association with in-Hospital and Long-Term Mortality
No full textPurpose: Tricuspid valve surgery is associated with significant perioperative and long-term risks. The Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) score is an integrated biomarker reflecting nutritional, inflammatory, and hematologic status. HALP score has proven prognostic utility, yet its relevance in tricuspid valve surgery is not well established. This study aimed to evaluate the association between preoperative HALP score and both in-hospital and long-term mortality in patients undergoing tricuspid valve surgery. Patients and Methods: This retrospective study included adult patients (>= 18 years) who underwent isolated or combined tricuspid valve surgery between 2014 and 2021. The HALP score was calculated as platelet count x hemoglobin x albumin / lymphocyte count. Patients were grouped into low and high HALP score categories based on the mean HALP score. Laboratory parameters, echocardiographic findings, and mortality rates were compared. Laboratory and echocardiographic data, as well as mortality outcomes, were compared. Logistic regression was used to identify independent predictors of in-hospital mortality, while Cox proportional hazards and Kaplan-Meier analyses assessed long-term mortality. ROC curve analysis was performed to determine the optimal HALP cutoff. Results: Among 277 patients, 28 (10.1%) experienced in-hospital mortality and 45 (16.1%) died during follow-up. Patients who died had significantly lower HALP scores (p < 0.001). Univariate analysis showed that age, atrial fibrillation, EuroSCORE, low hemoglobin, low albumin, lymphopenia, low HALP score, chronic kidney disease, and perioperative complications were associated with in-hospital mortality. However, only advanced CKD and perioperative complications remained significant in multivariate analysis. HALP score was independently associated with long-term mortality (p < 0.001). The optimal HALP cutoff was 0.2998 Conclusion: Lower preoperative HALP scores are associated with increased long-term mortality after tricuspid valve surgery. Although not predictive of in-hospital mortality, the HALP score may help identify high-risk patients using routine laboratory values
Design of Cardiac Pacemaker Controller Based on Reinforcement Learning
No full textBBAP.2024.011This study investigates the derivation of PID controller parameters, commonly used for pacemaker control, using both genetic algorithm (GA) and reinforcement learning (RL) methods. We compare the PID parameters obtained by RL with those obtained by GA, a well-known and often preferred method in the literature. The aim of the study is to analyze the performance of the control parameters obtained by both methods and to determine which approach is more effective in pacemaker applications. In particular, comparisons on important control criteria such as rise time, settling time and overshoot of the system will reveal the advantages and disadvantages of these methods
KIRIM’IN VAR OLUŞ MÜCADELESİNDE EDİGE KIRIMAL’IN ROLÜ VE ÖNEMİ
No full textMustafa Edige Kırımal, Ceditçilik hareketinin yarattığı ortamdan beslenerek büyüyen ikinci kuşak Kırım Türk aydınlarındandır. Aslen Lehistan Tatarlarından olan Kırımal, 1911’de Bahçesaray’da doğmuş, ilk ve orta okul öğrenimini Kırım’da gerçekleştirmiş, ardından Kırım’ın seçkin okullarından olan Akmescit Pedagoji Enstitü-sü’nde okumuştur. Ömrünü Kırım davasına vakfetmiş olmasından mütevellit, Kırım’ın ahvali kendisinin yaşantı-sını belirlemiştir. Yüksek tahsili sırasında gizli olarak yürütülen millî faaliyetlerde aktif rol oynamış, ön plana çık-mıştır. Sovyet Hükümeti’nin baskılarının artmasıyla İran üzerinden 1932 yılında İstanbul’a geçmiş böylelikle Emel Dergisi’nin etrafında toplanan grubun içerisinde yer almıştır. 1939’da Vilnius Üniversitesi’nin Siyasal Bilgiler Fakültesi’nde öğrenimini tamamlamış, Polonya’ya üniversite tahsili sebebiyle giden Kırımlı gençlerle birlikte millî faaliyetlerini burada da sürdürmüştür. Almanların Kırım Yarımadası’nı işgal etmesi üzerine Edige Kırımal Müste-cip Ülküsal ile Nazi Almanya’sıyla temaslarda bulunmuştur. Bu girişimlerin gayesi savaşta zor durumda kalan Kırım Türklerine yardım edebilmek ve Kırım’ı bağımsızlığa kavuşturabilmektir. Savaşın sona ermesiyle Kırımal Almanya’da kalmış ve Kırım Türklerinin haklarını savunmaya devam etmiştir. Bu çalışma ile ikinci kuşak Kırım Türk aydınlarından Edige Kırımal’ın Kırım Türklerinde İsmail Gaspıralı’dan beri ortaya çıkan eser bırakma gele-neğinin bir sonucu olarak meydana getirdiği kültürel, siyasi ve toplumsal konularda yürüttüğü çalışmalarıyla, Kırım’ın var oluş mücadelesine verdiği katkı ayrıca diğer Kırım Türk aydınlarından ayrılan yönlerinin ön plana çıkarılması hedeflenmiştir
Combination of Paramedian Dorsal Component Excision and Low Septal Strip Septoplasty: A Hybrid Rhinoplasty Technique with Endonasal Approach
No full textBackgroundIn dorsal preservation techniques of rhinoplasty, problems such as residual and recurrent hump and dorsal irregularities are encountered. In this study, we combined paramedian dorsal component excision with low septal strip septoplasty by preserving the keystone area. The clinical results of this combination on the dorsum were evaluated.Patient and MethodsNinety-four patients who underwent hybrid rhinoplasty technique with paramedian dorsal component excision and low septal strip septoplasty combination between January 2023 and March 2024 were included in the study. All cases were primary rhinoplasty, and endonasal approach was performed in all cases. Patient demographics, complications, revision surgeries and follow-up were analyzed retrospectively.ResultsA total of 65 female and 29 male patients were included in the study. The mean age of the patients is 32.30 +/- 9.55 years (18-57). The mean follow-up period was 10.08 +/- 2.78 months (6-15 months). Complications were observed in 6.38% of the patients (n = 6/94). All these patients underwent revision surgery. Revision surgeries were performed for tip drooping in three patients, dorsal irregularities in two patients and nasal deviation in one patient.ConclusionsProviding ideal dorsal aesthetic lines with hump treatment is one of the most important parts of dorsal preservation rhinoplasty techniques. Our hybrid technique, which combines a low septal strip with paramedian dorsal component excision, can effectively reduce hump recurrence and achieve ideal dorsal aesthetic lines.Level of Evidence IIIThis journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266