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Some results on disjointly weakly compact sets
No full textWe give an operator characterization of disjointly weakly compact sets and show that disjointly weakly compact sets coincide with reciprocal Dunford-Pettis sets. We compare disjointly weakly compact sets with almost Grothendieck sets, relatively compact sets, and weak reciprocal Dunford-Pettis sets. Consequently, we obtain new characterizations of the weak Grothendieck property, Schur property, and Banach lattices whose dual have an order continuous norm
Is Closed-Bar Design a Better Option for All-on-Four Concept ?
No full textIs Closed-Bar Design a Better Option for All-on-FourConcept ?All-on-Four Konsepti İçin Kapalı Bar Tasarımı Dahaİyi Bir Seçenek Mi? When tilted implants are incorporated into amulti-implant prosthesis, the distribution of implants and prosthetic rigidityhelp reduce or modify these bending forces, lowering their negative impact. Analyse the stress distribution in the implant, boneand prostheses with distal implants placed at 30 and 45 degrees and evaluatethe effectiveness of a bar-supported design. Model I: A straight implant and abutment were placedat a 30° angulation in the maxillary bone, positioned at the level of thesecond premolar. Model II:The implant placement were identical to Model I. In addition, a palatal bardesign was incorporated into the framework at the level of the first molar. Model III: Astraight implant and abutment were placed at a 45° angulation in the maxillarybone, positioned at the level of the second premolar. Model IV:The implant placement were identical to Model III. Additionally, a palatal bardesign was incorporated into the framework at the level of the first molar</p
Investigation of the factors affecting post-traumatic stress disorder in survivors of the 2023 Kahramanmaraş earthquakes
No full textBackground: This study investigates the factors influencing post-traumatic stress disorder in the youth population seven months after the February 6, 2023, Kahramanmaraş earthquakes, which caused massive destruction in Türkiye and resulted in the loss of over 55,000 lives. Objective: The effects of gender, damage levels of buildings, financial resources, participation in search and rescue operations, peritraumatic distress, perceived social support, and resilience are investigated for their impacts on post-traumatic stress disorder. The goal is to examine how these factors influence post-traumatic stress disorder not only on average but also across different levels of its distribution. Method: A face-to-face survey was conducted between September and October 2023 with a randomly selected sample of 160 voluntary university students aged 18 and above who had directly experienced the earthquakes in the affected zone. The study employs quantile regression alongside classical regression and conventional statistical methods to examine the effects of various factors on post-traumatic stress disorder. Results: The prevalence rates of PTSD are 65.6 % and 35 % based on the PTSD Checklist for DSM-5 (PCL-5), using cut-off scores of 33 and 47, respectively. Classical regression results indicate that female gender (β = 7.98, p < 0.001), moderate or higher building damage (β = 5.6, p < 0.05), moderate (β = −6.3, p < 0.001) and high (β = −7.69, p < 0.01) financial resources, peritraumatic distress (β = 0.6, p < 0.001), perceived social support (β = −0.12, p < 0.05), and resilience (β = −0.66, p < 0.001) have impacts on average PTSD scores. Quantile regression results reveal that all factors are effective at various quantiles of post-traumatic stress disorder. For instance, while minor damage (β = 5.06, p < 0.05) is found to be significant at the 10th percentile, participation in search and rescue operations (β = 8.12, p < 0.01) is significant at the 80th percentile. Conclusions: The effects of gender, building damage levels, financial resources, peritraumatic distress, perceived social support, and resilience remain consistent, showing no substantial variation across the quantiles of post-traumatic stress disorder. However, in the upper tail of the PTSD distribution, participation in search and rescue operations emerges as a risk factor, exacerbating its severity
Measurement of ω meson production in pp collisions at √s = 13 TeV
No full textThe pT-differential cross section of ω meson production in pp collisions at s = 13 TeV at midrapidity (|y| < 0.5) was measured with the ALICE detector at the LHC, covering an unprecedented transverse-momentum range of 1.6 < pT< 50 GeV/c. The meson is reconstructed via the ω → π+π−π0 decay channel. The results are compared with various theoretical calculations: PYTHIA8.2 with the Monash 2013 tune overestimates the data by up to 50%, whereas good agreement is observed with Next-to-Leading Order (NLO) calculations incorporating ω fragmentation using a broken SU(3) model. The ω/π0 ratio is presented and compared with theoretical calculations and the available measurements at lower collision energies. The presented data triples the pT ranges of previously available measurements. A constant ratio of Cω/π0 = 0.578 ± 0.006 (stat.) ± 0.013 (syst.) is found above a transverse momentum of 4 GeV/c, which is in agreement with previous findings at lower collision energies within the systematic and statistical uncertainties
Unveiling the nexus of the relationship between multiplayer digital game-playing experience and workplace loneliness: a moderated serial mediation analysis
No full textBackground The role of individuals’ solo digital game-playing experience in influencing their feelings of loneliness is an important research area that has received considerable attention from researchers. However, we still know less about how the digital game-playing experience, in general, and the multiplayer digital game-playing experience, in particular, influence employees’ loneliness in the workplace. In addition, although there are limited studies investigating the link between digital game playing and loneliness, the literature presents conflicting arguments and f indings. Researchers have omitted various intervening psychological factors, such as boosting behavior and escapism motivation, as well as task characteristics, including task routineness, from the relationship between the multiplayer digital game-playing experience and loneliness. Method This study involved 120 employees from both service and manufacturing industries, representing a diverse range of ages, genders, and professional experiences, who participated in multiplayer digital gaming at work. Participants completed a self-report questionnaire measuring their multiplayer gaming experience, boosting behavior, feelings of workplace loneliness, self-expansion escapism, and the routine nature of their tasks. We employed a PLS-SEM approach using SmartPLS 4.0 to examine the relationships among these variables. Results Our study did not uncover a direct relationship between the experience of playing multiplayer digital games and feelings of loneliness. Instead, our findings revealed a significant serial mediation effect in the relationship between multiplayer digital game-playing experience and workplace loneliness, mediated explicitly through the enhancement of boosting behavior and self-expansion escapism. Our analysis indicated that (i) there exists a positive relationship between the experience of multiplayer digital game-playing and boosting behavior; (ii) boosting behavior is positively correlated with self-expansion escapism. Furthermore, we identified that self-expansion exhibits a negative relationship with workplace loneliness. Additionally, we observed that higher task routineness significantly attenuated the serial mediating relationship identified in our analysis.</p
Kentsel alanda sera gazı emisyonlarının azaltılması için pilot bir güneş enerji santrali tasarımı ve finansal analizi
No full textQuantum-Enhanced Classification of Brain Tumors Using DNA Microarray Gene Expression Profiles
No full textDNA microarray technology enables the simultaneous measurement of expression levels of thousands of genes, thereby facilitating the understanding of the molecular mechanisms underlying complex diseases such as brain tumors and the identification of diagnostic genetic signatures. To derive meaningful biological insights from the high-dimensional and complex gene features obtained through this technology and to analyze gene properties in detail, classical artificial intelligence (AI)-based approaches such as machine learning (ML) and deep learning (DL) are widely employed. However, these methods face various limitations in managing high-dimensional vector spaces and modeling the intricate relationships among genes. In particular, challenges such as hyperparameter tuning, computational costs, and high processing power requirements can hinder their efficiency. To overcome these limitations, quantum computing and quantum computing-based AI approaches are gaining increasing attention. Leveraging quantum properties such as superposition and entanglement, quantum methods enable more efficient parallel processing of high-dimensional data and offer faster and more effective solutions to problems that are computationally demanding for classical methods. In this study, a novel model called 'Deep VQC' is proposed, based on the Variational Quantum Classifier (VQC) approach. Developed using microarray data containing 54,676 gene features, the model successfully classified four different types of brain tumors-ependymoma, glioblastoma, medulloblastoma, and pilocytic astrocytoma-alongside healthy samples with high accuracy. Furthermore, compared to classical ML algorithms, the Deep VQC model demonstrated either superior or comparable classification performance. These results highlight the potential of quantum AI methods as an effective and promising approach for the analysis and classification of complex structures such as brain tumors based on gene expression features
