Search Results (125)

This follow-up scientific case study builds on prior research to explore the computational challenges of applying quantum algorithms to financial asset management, focusing specifically on solving the graph-cut problem for investment recommendation. Unlike our prior study, which focused on idealized QAOA performance, this work introduces a graph compression pipeline that enables QAOA deployment under real quantum hardware constraints. This study investigates quantum-accelerated spectral graph compression for financial asset recommendations, addressing scalability and regulatory constraints in portfolio management. We propose a hybrid framework combining the Quantum Approximate Optimization Algorithm (QAOA) with spectral graph theory to solve the Max-Cut problem for investor clustering. Our methodology leverages quantum simulators (cuQuantum and Cirq-GPU) to evaluate performance against classical brute-force enumeration, with graph compression techniques enabling deployment on resource-constrained quantum hardware. The results underscore that efficient graph compression is crucial for successful implementation. The framework bridges theoretical quantum advantage with practical financial use cases, though hardware limitations (qubit counts, coherence times) necessitate hybrid quantum-classical implementations. These findings advance the deployment of quantum algorithms in mission-critical financial systems, particularly for high-dimensional investor profiling under regulatory constraints. Full article

A novel algorithm was proposed for solving the max-cut problem, which seeks to identify the cut with the maximum weight in a given graph. Our technique is based on the bundle approach, applied to a newly formulated semidefinite relaxation. This research establishes the theoretical convergence of our approximation technique and presents the numerical results obtained on several large-scale graphs from the BiqMac library, specifically with 100, 250, and 500 nodes. The resulting performance was compared with that produced by two alternative semidefinite programming-based approximation methods, namely the BiqMac and BiqBin solvers, by comparing the CPU time and the number of function calls. The primary objective of this work was to enhance the scalability and computational efficiency in solving the max-cut problem, particularly for large-scale graph instances. Despite the development of numerous approximation algorithms, a persistent challenge lies in effectively handling problems with a large number of constraints. Our algorithm addresses this by integrating a novel semidefinite relaxation with a bundle-based optimization framework, achieving faster convergence and fewer function calls. These advancements mark a meaningful step forward in the efficient resolution of NP-hard combinatorial optimization problems. Full article

The entanglement entropy of a random tensor network (RTN) is studied using tools from free probability theory. Random tensor networks are simple toy models that help in understanding the entanglement behavior of a boundary region in the anti-de Sitter/conformal field theory (AdS/CFT) context. These can be regarded as specific probabilistic models for tensors with particular geometry dictated by a graph (or network) structure. First, we introduce a model of RTN obtained by contracting maximally entangled states (corresponding to the edges of the graph) on the tensor product of Gaussian tensors (corresponding to the vertices of the graph). The entanglement spectrum of the resulting random state is analyzed along a given bipartition of the local Hilbert spaces. The limiting eigenvalue distribution of the reduced density operator of the RTN state is provided in the limit of large local dimension. This limiting value is described through a maximum flow optimization problem in a new graph corresponding to the geometry of the RTN and the given bipartition. In the case of series-parallel graphs, an explicit formula for the limiting eigenvalue distribution is provided using classical and free multiplicative convolutions. The physical implications of these results are discussed, allowing the analysis to move beyond the semiclassical regime without any cut assumption, specifically in terms of finite corrections to the average entanglement entropy of the RTN. Full article

Soybean (Glycine max L.) is vulnerable to environmental stresses, such as heavy rainfall and high winds, which promote lodging and reduce plant performance during the monsoon season. To mitigate these issues, we evaluated the effects of plant topping, a practice involving the removal of apical buds, on plant architecture, physiological traits, and grain yield in four soybean cultivars over two growing seasons (2021–2022). Plant topping was performed at the V6-7 stage by cutting 30–35 cm above the ground. Plant topping reduced plant height by up to 23.5% and decreased leaf area index (by 8.0–16.4%), potentially improving light penetration into the lower canopy. Although chlorophyll concentration declined temporarily (297.8 vs. 272.8 mg m⁻² for non-topping vs. topping, respectively), NDVI remained stable, indicating delayed senescence. Chlorophyll fluorescence parameters revealed cultivar-specific stress responses, particularly in Taegwang, which showed elevated ABS/RC, TR₀/RC, and DI₀/CS values under plant topping. Grain yield was generally unaffected, except in Jinpung, which increased by 34% under plant topping in 2021 (2701 kg ha⁻¹ vs. 3621 kg ha⁻¹ for non-topping vs. topping). In conclusion, plant topping may help improve canopy structure and light distribution without compromising yield, potentially reducing lodging risk and offering a cultivar-specific management strategy. Full article

Objectives: Inflammation plays an important role in cancer development, and various inflammation parameters are used as potential prognostic markers. This study aimed to evaluate the effectiveness of the combined use of HALP and H index in predicting pathological response to neoadjuvant therapy in patients with HER2-positive early-stage breast cancer. Method: This retrospective cohort study was conducted on 146 HER2-positive breast cancer patients treated in two centers. To stratify patients by their predicted probability of pathological response, HALP and H index values were combined into a composite biomarker score called the combined response score (CRS). Patients were classified into three groups based on biomarker levels: 0 = low CRS (low predictive score), 1 = intermediate CRS, and 2 = high CRS (high predictive score). These groups reflect predicted response likelihood and do not represent actual pathological outcomes. Pathological response results were evaluated according to the combined response score. Pathological complete response (pCR) was defined as residual cancer burden (RCB) 0, indicating no residual invasive tumor in breast or lymph nodes. Results: The mean age of 146 early-stage breast cancer patients included in our study was 52.3 ± 11.3 (min: 29-max: 83). In the ROC analysis, the optimum cut-off value for the HALP score in pathological response classification was found to be 36 (AUC = 0.608, sensitivity = 76.29%, specificity = 44.9%, PPV = 73%, NPV = 47.89%) and 2.3 for the H index (AUC = 0.641, sensitivity = 65.98%, specificity = 51.02%, PPV = 72.73%, NPV = 43.1%). While the pathological complete response rate was 66.4% in all patients, it was 81.8% in those with a combined score of 2, 51% in those with a score of 1, and 58.6% in those with a score of 0 (p < 0.001). In the logistic regression analysis, the probability of pathological response in patients in the combined score = 2 group is 3.77 times higher than in group 0. In the Fagan nomogram, the pretest probability of pathological response is 66%, while the post-test probability for combined response score group 2 is 81.5%, and for the low-H index < 2.3 and the high-HALP ≥ 36 patient group, our estimate for pathological complete response increases to 82%. Conclusions: The HALP-H index combined score is an important predictor of pathological response in early-stage HER2-positive breast cancer patients, independent of histological type and stage. This new score may enable personalized approaches in treatment planning. Full article

The Maximum Colored Cut problem aims to seek a bipartition of the vertex set of a graph, maximizing the number of colors in the crossing edges. It is a classical Max-Cut problem if the host graph is rainbow. Let $mcc\left(G\right)$ denote the maximum number of colors in a cut of an edge-colored graph G. Let $C_k$ be a cycle of length k; we say G is PC-$C_k$-free if G contains no properly colored $C_k$. We say G is a p-edge-colored graph if there exist p colors in G. In this paper, we first show that if G is a PC-$C_3$-free p-edge-colored complete 4-partite graph, then $mcc\left(G\right)=p$. Let $k\ge 3$ be an integer. Then, we show that if G is a PC-$C_4$-free p-edge-colored complete k-partite graph, then $mcc\left(G\right)\ge min\{p-1,15p/16\}$. Finally, for a p-edge-colored complete graph G, we prove that $mcc\left(G\right)\ge p-1$ if G is PC-$C_4$-free, and $mcc\left(G\right)\ge min\{p-6,7p/8\}$ if G is PC-$C_5$-free and $p\ge 7$. Full article

Servo-free tilt-rotor UAVs decouple position and attitude control without using servos, which cuts structural weight and removes the travel limits of traditional designs. In many applications—such as aerial platform operations and airborne photogrammetry—large attitude changes are required during hover. Conventional control-allocation schemes tend to distribute thrust unevenly, making actuators prone to saturation. To overcome these challenges, we propose a thrust-balancing control-allocation strategy specifically for passive-hinge tilt-rotor octocopters. The presented method integrates min–max optimization with the force decomposition (FD) algorithm, effectively handling actuator saturation while maintaining low computational complexity. Additionally, an offline-trained neural network is employed to replace the online optimization process, enabling the complete controller to operate on the flight control board without relying on an onboard computer. Simulation and experiment results confirm the effectiveness of the proposed strategy, demonstrating enhanced control performance and its practical feasibility for real-world UAV applications. Full article

Background/objectives: We aimed to characterize the dynamic pattern of circulating tumor DNA (ctDNA) during hypofractionated radiation therapy (RT) in patients with lung cancer and assess its clinical relevance. Metholds: Prospectively, 24 patients diagnosed with early-stage lung cancer underwent curative RT with 60–64 Gy in 4–20 fractions. Blood samples were collected at baseline (D0) and on post-RT days 1–3 and 7 (D1–3 and D7). The ctDNA was longitudinally analyzed using LiquidSCAN. To find a feasible index associated with outcome, total VAF(%), max VAF(%), total GE (hGE/mL) and max GE (hGE/mL), were evaluated. Results: Thirteen patients with available samples were analyzed with a median 22.2-month follow-up (range, 5.2–34.3 months). Four patients experienced progression between 7.9 and 16.6 months after RT (PD group), and the nine presented no evidence of disease (NED group). The Dmax, the day with the highest ctDNA level among D0–7, was significantly different between the groups with total GE and max GE (p = 0.035 and 0.021, respectively). According to the ROC curves, the max GE showed the best AUC (86.1%) and the cut-off value of the Dmax was 1.5 (sensitivity: 66.7%, specificity: 100%, positive-predictive value: 100%, and negative-predictive value: 57.1%). Tumor size ≥ 3 cm, squamous histology, and a daily dose 3–4 Gy were correlated with the Dmax = D2–3. The Dmax showed better disease control rate with marginal significance (p = 0.081). Conclusions: The timing of early ctDNA elevation may have the potential to predict RT response. The max GE may be an index to verify the ctDNA levels after RT. Full article

The max-cut problem is a well-known topic in combinatorial optimization, with a wide range of practical applications. Given its NP-hard nature, heuristic approaches—such as genetic algorithms, tabu search, and harmony search—have been extensively employed. Recent research has demonstrated that harmony search can outperform genetic algorithms by effectively avoiding redundant searches, a strategy similar to tabu search. In this study, we propose a modified genetic algorithm that integrates tabu search to enhance solution quality. By preventing repeated exploration of previously visited solutions, the proposed method significantly improves the efficiency of traditional genetic algorithms and achieves performance levels comparable to harmony search. The experimental results confirm that the proposed algorithm outperforms standard genetic algorithms on the max-cut problem. This work demonstrates the effectiveness of combining tabu search with genetic algorithms and offers valuable insights into the enhancement of heuristic optimization techniques. The novelty of our approach lies in integrating solution-level tabu constraints directly into the genetic algorithm’s population dynamics, enabling redundancy prevention without additional memory overhead, a strategy not previously explored in the proposed hybrids. Full article

This study explores the application of quantum computing in asset management, focusing on the use of the Quantum Approximate Optimization Algorithm (QAOA) to solve specific classes of financial asset recommendation problems. While quantum computing holds promise for combinatorial optimization tasks, its application to portfolio management faces significant challenges in scalability for practical implementations. In this work, we model the problem using a graph representation where nodes represent investors, and edges reflect significant similarities in asset choices. We test the proposed method using quantum simulators, including cuQuantum, Cirq-GPU, and Cirq with IonQ, and compare the performance of quantum optimization against classical brute-force methods. Our results suggest that quantum algorithms may offer computational advantages for certain use cases, though classical heuristics also provide competitive performance for smaller datasets. This study contributes to the ongoing investigation into the potential of quantum computing for real-time financial decision-making, providing insights into both its applicability and limitations in asset management for larger and more complex investor datasets. Full article

Background/Objectives: This study piloted a 24-week bodybuilding program combining resistance training (RT) with a dietary bulk-and-cut protocol in middle-aged adult males. Methods: Seven untrained males (33 ± 3.0 years; BMI = 35.0 ± 4.6 kg/m²; body fat = 36 ± 5%) completed a 24-week intervention combining RT with a dietary protocol consisting of 12-week cycles of caloric bulking (0–12 weeks) and cutting (12–24 weeks). The participant retention rate was 64%, while compliance with training was 96.7%, and adherence to dietary cycles was over 93%. To assess the preliminary efficacy of the intervention, venous blood samples and measurements of body composition (BodPod), muscle strength, and VO₂max (cycle ergometer) were collected at baseline (week 0) and following the bulking (week 12) and cutting (week 24) cycles. Circulating lipids (triglycerides, total, low-density, and high-density cholesterol), C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-10 (IL-10) were measured in serum. Results: The training led to significant increases in muscle strength, especially in the deadlift (+46%, p < 0.001) and squat (+65%, p < 0.001). Improvements in body composition were characterized by an increase in fat-free mass and a decrease in body fat percentage over the 24-week intervention (+3% and −6%, respectively, p < 0.05). Lipids, CRP, IL-6, and IL-10 did not change significantly, but there was a notable reduction in TNF-α (time effect p = 0.05, _pη² = 0.39), with 15% lower concentrations at week 24 compared to baseline, indicating reduced inflammation. Conclusions: Overall, the pilot intervention achieved high compliance and adherence rates, leading to improvements in body composition and lower resting TNF-α concentrations in a group of middle-aged males with obesity. Full article

This study aims to determine whether maximal oxygen consumption (VO2max) or predicted postoperative (ppo)-VO2max could still reliably predict postoperative complications and deaths in lung cancer patients undergoing pneumonectomy and which values could be more reliably considered as the optimal threshold. Methods: We retrospectively collected data of consecutive patients undergoing pneumonectomy for primary lung cancer at the European Oncological Institute (April 2019–April 2023). Routine preoperative assessment included cardiopulmonary exercise testing (CPET) and a lung perfusion scan. We evaluated the morbidity and mortality rates; associations between morbidity, mortality, VO2max, and ppoVO2max values were investigated through ANOVA or Fisher’s exact test as appropriate. Receiver operating characteristic (ROC) curves were applied to further explore the relation between VO2max, ppoVO2max values, and 90-day mortality. Results: The cardiopulmonary morbidity rate was 32.2%; the 30-day and 90-day mortality rates were 2.2% and 6.7%. The PpoVO2max values were significantly lower in patients experiencing cardiopulmonary complications or deaths compared to the whole cohort, whereas VO2max, though showing a trend towards lower values, did not reach statistical significance. A VO2max value threshold of 15 mL/kg/min correlated significantly with 90-day mortality, while a ppoVO2max cut-off of 10 mL/kg/min was significantly associated with cardiopulmonary complications and 30-day and 90-day mortality rates. ROC curve analysis revealed ppoVO2max as a better predictor of 90-day mortality compared to VO2max. Conclusions: CPET and a lung perfusion scan are two key elements for the preoperative evaluation of patients undergoing pneumonectomy, since it provides a holistic assessment of cardiopulmonary functionality. We recommend the routine calculation of ppoVO2max, particularly when adopting a 10 mL/kg/min threshold. Full article

This paper introduces an improved Grover Adaptive Search (GAS) algorithm. The GAS algorithm has been prove to achieve quadratic acceleration in the Constrained Polynomial Binary Optimization (CPBO) problem. Nevertheless, the acceleration effect of the GAS algorithm can be decreased by the poor threshold selection. This article uses the Quantum Approximate Optimization Algorithm (QAOA) to improve the initial threshold selection, thereby accelerating the convergence speed of the original GAS algorithm. The acceleration effect of the improved GAS algorithm is presented by the Max-Cut problem and the CPBO problem. Full article

In recent years, due to the expansion of cities, the transformation of agricultural areas, the forestry activities carried out solely for wood production, and the spread of transportation networks, natural habitats have become increasingly fragmented, and suitable habitats for wildlife are rapidly decreasing. As a result, natural areas are being divided, connections are being cut off, species’ living spaces are shrinking, and species and habitats are being isolated. This fragmentation significantly hinders the natural movements of large mammals (Ursus arctos, Sus scrofa, and Canis lupus), leading to reduced genetic diversity and threatening the long-term viability of their populations. This research, conducted in the Ballıdağ and Kurtgirmez regions of the Western Black Sea Region of Türkiye, aimed to determine the movement corridors of the brown bear (Ursus arctos), wild boar (Sus scrofa), and wolf (Canis lupus) in the area and to evaluate the habitat connections for these species. This study relied on data obtained through field studies and the previous literature. Ecological modeling was used with the Maximum Entropy Method (MaxEnt) to understand the relationships between these species and environmental variables, and the barriers posed by the latter. Ecological corridor maps were created to evaluate the effects of habitat fragmentation in the region and species’ potential to maintain critical connection points despite this fragmentation using Circuitscape software based on the Circuit Theory approach. As a result of the analysis, it was determined that the AUC values were between 0.75 and 0.8; the most important variables in the models were road density, vegetation, and elevation; focal points and resistance surface areas were determined for three large mammal species; and important ecological corridors were defined between the Ballıdağ and Kurtgirmez regions. This study revealed that preserving habitat connections and reducing fragmentation is critical for the long-term existence of predator species and ecosystem health. Full article

A review of binder phases used for sintering diamond powders under high pressure and high temperature conditions along with an outline of the properties of polycrystalline diamonds or composite materials intended for cutting tools, wire drawing dies, and drilling rocks are presented. The interaction of diamond with metals from group VIII of the periodic table, carbon-forming metals, carbides, MAX phases and with silicides, borides, and alkali carbonates is presented. The interaction of the bonding phases with diamond was determined. The influences of sintering process parameters, amounts, and methods of introducing of these phases on the basic mechanical properties and thermal resistance of diamond materials are analyzed. The investigated material properties are compared with the properties of commercial PCD with a cobalt and the SiC binder phase. Full article