Search Results (783)

Objectives: We aimed to compare the treatment success and patient compliance of triple therapy with levofloxacin, high-dose dual therapy with amoxicillin, and quadruple therapy with bismuth and levofloxacin as first-line treatment for Helicobacter pylori (H. pylori) eradication using amoxicillin 875 mg + clavulanic acid 125 mg instead of amoxicillin 1 g. Methods: Patients who tested positive for Helicobacter pylori in the histopathological examination of biopsies taken during upper gastrointestinal endoscopy were initially divided into three different treatment groups. There were 179 patients in the first group, 178 patients in the second group, and 182 patients in the third group. A total of 480 patients from these groups who came for follow-up were included in this study, with 160 patients in each group receiving one of three different treatment protocols. The first group received treatment with amoxicillin 875 mg + 125 mg clavulanic acid twice daily, levofloxacin 500 mg once daily, and pantoprazole 40 mg twice daily (Group 1). The second group received treatment with amoxicillin 875 mg + 125 mg clavulanic acid three times a day, along with pantoprazole 40 mg twice daily (Group 2) as treatment. The third group received treatment with amoxicillin 875 mg + 125 mg clavulanic acid, twice daily, levofloxacin 500 mg once daily, pantoprazole 40 mg twice daily, and bismuth subsalicylate 262 mg2 pieces four times a day (Group 3). H. pylori was checked with a stool antigen test 45 days after the 14-day treatment. The groups were compared in terms of treatment success and treatment compliance. Results: In Group 1, 150 (90.6%) of 160 patients tested negative for an H. pylori antigen in stool samples on day 45 after treatment. This rate was 139 (86.9%) in Group 2 and 148 (92.5%) in Group 3. There were no statistically significant differences between the three groups in terms of treatment success (p = 0.233). Side effects were observed in 10 (6.2%) patients in Group 1. Side effects were present in nine (5.6%) patients in Group 2. Side effects were observed in 12 (7.5%) patients in Group 3. There was no significant difference between the groups in terms of patient compliance (p = 0.786). Conclusions: Treatment success and side effects were similar in all three groups, with no statistical difference. The combination of amoxicillin 875 mg + clavulanic acid 125 mg is at least as effective as amoxicillin 1 g alone. Full article

This paper presents a quadruple step-down (QSD) trans-inductor voltage regulator (TLVR) converter to accommodate the high-current and fast-transient requirements of processor power supplies. Evolved from dual-step-down (DSD) topology, the QSD configuration offers stronger load capacity; three additional flying capacitors are introduced between adjacent phases to break the 25% duty cycle constraint, thereby extending the output voltage range and accelerating the transient response. Moreover, the converter’s transient response is optimized to its full potential through both multi-phase simultaneous operation and the incorporation of the dedicated TLVR architecture. A modified adaptive on-time (AOT) controller supporting four-phase simultaneous operation is employed. Designed and verified via post-layout simulation in a 180 nm BCD process with all 6 V power transistors, the converter achieves a peak efficiency of 96.1% at 24 V input and 3 V output, as well as a maximum load capacity of 20 A. Under a 19 A load current step with a 19 ns rise time, it exhibits only a 37 mV output voltage droop and a 2 μs settling time, even with a 100 μF output capacitor. Full article

The modeling and control of photovoltaic and other engineering systems highly depend on the accuracy of parameter identification. However, parameter extraction for photovoltaic equivalent models typically presents a high-dimensional, strongly nonlinear, and multimodal global optimization problem. Traditional analytical or gradient-based methods are sensitive to initial values and easily fall into local optima. To address this issue, this paper proposes a multi-strategy improvement teaching–learning-based optimization algorithm (SNTLBO). A social learning network structure with symmetric interaction topology is introduced into the classical TLBO framework to characterize the knowledge propagation relationships among individuals. Through this symmetric and balanced information exchange mechanism, learners can be guided not only by the teacher but also by multiple neighbors within the network, enabling more diverse and symmetric exploration of the search space and enhancing population diversity and global search capability. Furthermore, a teacher reputation mechanism is constructed, where historical performance is used to weight teacher influence, strengthening the guidance of high-quality solutions and accelerating convergence. Meanwhile, an adaptive teaching factor is designed to dynamically adjust the teaching intensity based on the distance between the teacher and students in the solution space, maintaining a dynamic balance (symmetry) between exploration and exploitation. To evaluate the performance of the proposed algorithm, SNTLBO is systematically compared with 11 advanced optimization algorithms on two benchmark test suites, CEC2017 (30D, 50D) and CEC2022 (10D, 20D). Non-parametric statistical tests are conducted to assess significance. The results demonstrate that SNTLBO shows competitive advantages in terms of convergence speed, solution accuracy, and stability. Finally, SNTLBO is applied to the parameter estimation of single-diode, double-diode, triple-diode, quadruple-diode, and photovoltaic module models. Experimental results show that the proposed algorithm achieves higher identification accuracy and robustness in terms of RMSE, IAE, and I–V/P–V curve fitting, verifying its effectiveness and practical value for complex global optimization and practical engineering applications. Full article

Background: Contemporary guidelines recommend rapid initiation of four classes of guideline-directed medical therapy (GDMT) for heart failure (HF) with reduced ejection fraction (HFrEF); however, real-world persistence, adherence, and dose optimization remain suboptimal. Methods: We analysed a predefined subregistry within the prospective Cardiology Research Dubrava (CaRD) registry, a real-world HF registry at a tertiary centre that includes patients across the ejection-fraction spectrum in whom contemporary HF therapy, including sodium-glucose cotransporter 2 inhibitors (SGLT2i), is introduced or optimised in routine practice. For this analysis, we included patients with newly diagnosed HFrEF (left ventricular ejection fraction (LVEF) ≤ 40%) who were discharged on all four GDMT classes; 167 of 179 patients with newly diagnosed HFrEF during the study period had an available 6-month medication assessment and comprised the final analytic cohort. The four GDMT pillars (beta-blocker; angiotensin-converting enzyme inhibitor (ACEi), angiotensin receptor blocker (ARB), or angiotensin receptor-neprilysin inhibitor (ARNI); mineralocorticoid receptor antagonist (MRA); and SGLT2i) were initiated within 4 days when clinically feasible. Medication adherence and target-dose attainment were assessed at 6, 12, and 24 months using a structured self-report questionnaire. Major adverse events (MAE) and all-cause mortality were recorded over 24 months. Patients were classified as adherent if they reported regular intake (≥80% of prescribed doses) of all four drug classes at 6 months; otherwise, they were classified as nonadherent. Results: Among the 167 analysed patients (median age 64 years, 74% men, median LVEF 30%), regular adherence at 6, 12, and 24 months was 65%, 55%, and 59% for beta-blockers; 66%, 50%, and 49% for ACEi/ARB/ARNI; 62%, 52%, and 49% for MRAs; and 84%, 57%, and 68% for SGLT2i. Target doses were achieved in 25–33% for beta-blockers, 42–50% for ACEi/ARB/ARNI, and 73–78% for MRAs. At 24 months, 56 survivors (37%) were adherent to all four drug classes. Over 24 months, all-cause mortality was 9.0% and MAE 18.6%, occurring less frequently in adherent vs. nonadherent patients (mortality 0% vs. 13.5%; MAE 8.9% vs. 23.4%). Conclusions: In this real-world, non-randomized HFrEF subregistry, in-hospital initiation of quadruple GDMT was feasible, yet maintaining long-term adherence and achieving target doses remained challenging. These data underscore the gap between guideline recommendations and routine practice and support structured follow-up and protocol-driven titration to optimize implementation. Full article

The integration of renewable energy and power electronics has intensified the occurrence of complex power quality disturbances (PQDs), which increasingly threaten grid stability. To address the challenges of multi-class PQD identification under noisy conditions, this paper proposes a novel framework that combines an enhanced time–frequency analysis method with an optimized AdaBoost decision tree. The main contributions are three-fold: (1) We develop an instantaneous frequency adaptive Fourier synchrosqueezing transform (IFAFSST) equipped with a custom adaptive operator that aligns closely with the frequency modulation patterns in PQD signals, thereby improving time–frequency energy localization. (2) The IFAFSST outputs are decomposed into low-frequency and high-frequency components, from each of which a set of 16 discriminative features is extracted. (3) An improved AdaBoost classifier is introduced, incorporating forward feature selection and Hyperband-based hyperparameter optimization to enhance classification performance. Hyperband accelerates the optimization process by dynamically allocating computing resources and iteratively eliminating suboptimal configurations, thereby enabling efficient determination of the optimal hyperparameters. The method proposed in this paper achieved an accuracy rate of 99.50% on simulated data containing 30 dB white noise and 98.30% on hardware platform data. This framework can effectively handle 23 types of interference, including seven types of single interference, 12 types of double compound interference, three types of triple compound interference, and one type of quadruple compound interference. It performs particularly well in identifying composite interference scenarios. This research has made a significant contribution to power quality analysis, providing a powerful solution with high accuracy and practical applicability, and offering great potential for the implementation of smart grid monitoring systems and the integration of renewable energy. Full article

This integrative literature review synthesises five strands of recent scholarships on port city regions (PCRs): (1) their multidimensional transitions, (2) skills foresight and future competences, (3) challenges and reforms in vocational education and training (VET) systems, (4) social inclusion and equity in skills development, and (5) innovative VET methodologies in port-adjacent sectors. Drawing on the interdisciplinary academic and policy-oriented literature, this article adopts a qualitative, integrative review approach to examine how the twin green and digital transition is reshaping port city regions and their associated skills ecosystems. The review demonstrates that PCR transitions are not only technical but socio-institutional: while Onshore Power Supplies (OPSs), alternative fuels, and digital platforms are transforming operational landscapes, the success of these innovations depends critically on the adaptive capacity of workers, training systems, and governance arrangements. The article further examines emerging pedagogical approaches in port-adjacent VET, including work-based learning, micro-credentials, and immersive training methods. Taken together, the evidence converges on a central claim: the resilience and sustainability of port city regions depend on integrated skills systems that combine foresight, inclusivity, and pedagogical innovation. Without such systems, decarbonisation and digitalisation risk exacerbating social and spatial inequalities rather than fostering sustainable growth. The article concludes by outlining implications for research, policy, and practice, calling for integrative performance metrics, longitudinal evaluation, and quadruple helix collaboration to support inclusive, competitive, and sustainable port transitions. Full article

The transition to circular models in fashion and textiles requires changes that go beyond technical innovation. The literature recognises that systemic change depends on the transformation of shared meanings around consumption and production, and that spaces for co-design and collaborative learning are crucial to generating this transformation. This article documents how Living Labs operate in this capacity, analysing the Madeback Circular Fashion Festival (May–November 2025), a pilot project of the Fashion & Textile Living Lab at the Politecnico di Milano. The study employs the Living Lab Integrative Process (LLIP) as both a design framework and an analytical lens. Adopting a qualitative and participatory method, the study documents how the three spaces of the LLIP—Problem Space, Solution Space and Implementation Space—simultaneously structured both design innovation and empirical analysis. The results point to three main contributions: (i) Living Labs can function as cultural infrastructures in which performative and narrative dimensions may contribute to the gradual normalisation of alternative practices; (ii) the Quadruple Helix operates as a living process characterised by distributed intentionality and emerging trust; and (iii) transformative learning appears through the co-production of knowledge in embodied and relational practices. The article identifies contextual factors that enabled the project—from its location in a design university to its multi-year funding—and the related constraints on transferability, concluding that Living Labs are promising infrastructures for sustainable transitions when they consciously integrate performative, cultural and relational dimensions. Full article

Temporal knowledge graphs aim to enhance the dynamic and evolutionary representation of knowledge while enabling time-based reasoning. However, the reasoning based on temporal knowledge graphs in real geographic environments suffers from low accuracy due to the difficulty in effectively utilizing complex spatio-temporal information. Spatial attributes within entities typically encompass both relative and absolute spatial information types. However, during spatio-temporal reasoning, the deep coupling between the quadruple $(entities, relations, timestamp)$ and these two spatial information types is frequently overlooked, as they remain unintegrated in inference predictions. This paper proposes a novel Multi-Task Spatial Recurrent Evolution Graph Convolutional Network (MTS-RE-GCN) framework to enable temporal knowledge graph methods to better reason about spatial entities under time-varying conditions. Experiments on the spatio-temporal dataset and the benchmark dataset (i.e., ICEWS14s, ICEWS18) with spatio-temporal features demonstrate that MTS-RE-GCN significantly outperforms the baseline models (e.g., RE-GCN, TiRGN). For entity prediction tasks, MTS-RE-GCN achieves mean reciprocal rank (MRR) scores of 0.848, 0.739, 0.566, representing improvements of 9.00%, 6.03%, 3.28%, correspondingly. This provides a comprehensive and efficient solution for spatio-temporal entity prediction in temporal knowledge graphs, holding significant implications for spatio-temporal data analysis, event prediction, and related fields. Full article

As a widely used display device, the effective display area of a digital micromirror device (DMD) is limited by its micromirror count and pitch, which cannot meet large-format target-plane display requirements. This paper proposes a large-format scene simulation system based on multi-DMD optical stitching, and uses an optical relay to overcome the inability to directly tile DMDs because of their package frames. By constructing a DMD display architecture comprising an illumination module, a relay module, a stitching module, and a projection module, the system quadruples the effective display area relative to a single DMD without sacrificing frame rate. Design results show that the system achieves an MTF greater than 0.5 at 50 lp/mm, with near-diffraction-limited performance; the RMS spot radius is less than 10 $\mathsf{\mu }$m. All key indicators meet application requirements. Full article

Through Glass Via (TGV) technology has emerged as a promising solution for advanced packaging. While glass offers lower dielectric loss than silicon, its lower thermal conductivity raises concerns about electro-thermal coupling effects in high-power, high-frequency applications. Therefore, this study conducted an electro-thermal co-design of TGV grounded Coplanar Waveguide (CPW) and Radio Frequency (RF) TGV connected CPW structures. A high-power test platform was developed to investigate the electrical and thermal performance of these structures. The temperature distribution mechanism under high-power conditions was revealed. Under high power and high frequency, the decrease in surface conductivity affected by surface state and film layer composition leads to increased loss, triggering temperature rise and forming an electrothermal coupling loop. Under continuous wave operation (5–20 W), the temperature rise reaches 92.4 °C while insertion loss increases by only 0.4 dB. Under pulsed wave operation (25–100 W, 2.5% duty cycle), the temperature rise is merely 2.1 °C with insertion loss increasing by 0.3 dB. The quadruple-redundant design and reduces heat flux density, preventing localized hotspot formation. The pulse intervals suppress thermal accumulation, leading to lower temperature rise. Therefore, continuous wave applications should prioritize thermal management, while pulsed wave applications can focus on electrical performance optimization. Full article

Background/Objectives. Globally, hepatocellular carcinoma (HCC) is the sixth most prevalent cancer and represents the third leading cause of cancer-related mortality. Despite advances in diagnosis and treatment, the overall prognosis of HCC remains poor, largely due to late-stage presentation and high rates of vascular invasion. Portal vein thrombosis constitutes a significant complication of HCC, with an occurrence rate of 35–50%. Portal vein tumour thrombosis (PVTT) represents an aggressive form that is closely linked to decreased patient survival. The incidence of PVTT increases over time, from approximately 21% in the first year after diagnosis to nearly 46% by the third year, highlighting its high prevalence and progressive nature. The introduction of immunotherapy has marked a paradigm shift in the management of HCC. Immune checkpoint inhibitors, particularly those targeting the PD-1/PD-L1 and CTLA-4 pathways, have demonstrated durable responses and significant survival benefits in certain patients with advanced HCC. Furthermore, emerging evidence suggests that combining immunotherapy with local or systemic therapies, such as trans arterial chemoembolization, hepatic arterial infusion chemotherapy, radiotherapy or tyrosine kinase inhibitors, may further enhance antitumor efficacy by modulating the tumour microenvironment and promoting synergistic immune activation. Method: This narrative review provides a comprehensive evaluation of immunotherapy in patients with HCC and PVTT, with a focus on its efficacy as both monotherapy and in combination with other treatment modalities in terms of tumour response, progression-free survival, and overall survival. It also addresses safety, patient selection, and emerging strategies to optimize outcomes in this high-risk population. Conclusions: The combination of multiple therapies could improve the patient’s prognosis by achieving objective response rate of almost 82%, disease control rate of 97% and progression free survival of 12.9 months with quadruple therapy (HAIC-TACE combined with targeted and immunotherapy). Full article

Background: Growing antibiotic resistance and the limited availability of key components in standard Helicobacter pylori treatments have driven the search for effective alternatives. Minocycline, with its broad-spectrum activity and favorable pharmacokinetics, has emerged as a promising substitute. This meta-analysis compares the safety and efficacy of minocycline-containing bismuth quadruple therapy (MBQT) to conventional first-line BQT regimens, incorporating data from the recent study by Lin et al. Methods: The inclusion criteria were randomized controlled trials (RCTs) with a target population of both treatment-naïve and previously treated patients diagnosed with Helicobacter pylori (H. pylori) infection. The intervention received by eligible patients was a minocycline–bismuth quadruple therapy (MBQT) regimen containing bismuth, minocycline, proton pump inhibitors (PPI), and any additional antibiotic with a minimum period of 2 weeks of administration. We excluded study designs other than RCT and clinical trials that include patients without confirmed H. pylori infection, animal populations, in vitro experiments, and reports of other outcomes that did not include a minimum intervention duration of 2 weeks. A comprehensive literature search was conducted on PubMed, EMBASE, Cochrane Library, and ScienceDirect from inception to 20 May 2025. After screening via Rayyan, data were extracted on an Excel spreadsheet. Quality was assessed using the Cochrane RoB 2.0 tool. Eligible randomized controlled trials (RCTs) were included and analyzed using RevMan 5.4. Outcomes assessed were intention-to-treat and per-protocol eradication rates. Adverse effects were compared among therapies. A random-effects model was used; an I² < 50% and p-value < 0.05 indicated homogeneity and significant results respectively. Results: Five RCTs with 7 interventions involving 2812 patients were included. The pooled odds ratio (OR) for MBQT in intention-to-treat (ITT) analysis was 1.25 (95% CI: 0.96–1.61), showing a non-significant trend. No heterogeneity was detected (I² = 0.0%). In the modified ITT (mITT) analysis (2 studies), MBQT showed higher eradication (OR: 1.70, 95% CI: 0.00–1042.90), but wide CI and high heterogeneity (I² = 70.7%) limited interpretation. All studies were included in the per-protocol (PP) analysis, which showed a statistically significant improvement with MBQT (OR: 1.67, 95% CI: 1.14–2.45) and low heterogeneity (I² = 5.2%), suggesting consistent results. Although not statistically significant, MBQT was associated with a slightly lower rate of adverse events compared to standard therapy (OR: 0.81, 95% CI: 0.59–1.12). I² = 50.6% showed moderate heterogeneity in safety outcomes. Discussion: the number of included RCTs was modest, with only five studies meeting eligibility criteria, and only two contributing to the modified intention-to-treat analysis. The risk-of-bias assessment showed variation in methodological quality across the included studies. Several studies exhibited high risk judgments in critical domains. particularly randomization, deviations from intervention, and selective reporting. Patients who completed the treatment benefited more from MBQT, which also had a comparable safety profile to conventional BQT regimens. In the treatment of H. pylori infection, MBQT may be considered a safe alternative for first-line treatment. Full article

Background: Multidrug-resistant bacteria have quadrupled globally, impacting effective treatment of infectious diseases. A growing concern is that many Gram-negative and Gram-positive bacteria harbor genes conferring resistance to various antibiotics including colistin. The alarming emergence of colistin resistance is exacerbated by the growing threat of MDR Salmonella species and Listeria monocytogenes (LMO), which pose an escalating risk to global public health. Materials and Methods: In the present study, red meat samples were collected from randomly selected key retail markets in the Eastern Cape province, South Africa, and were evaluated for the incidence of LMO and the Salmonella species using standard culture-based and molecular methods. The confirmed isolates were subjected to antibiotic susceptibility testing. Results: This study demonstrated the occurrence of multidrug-resistant LMO (62%) and Salmonella species (spp.) (58%) in the red meat specimen. There were high resistance rates in both LMO and Salmonella isolates, with LMO exhibiting resistance to penicillin (89%), colistin (81%), nitrofurantoin (78%), and erythromycin (29%), while Salmonella showed resistance to trimethoprim (96.87%), tetracycline, and colistin (90.62%). Antibiotic resistance genes were also detected including BlaTem, erm, Sul1, Sul2 and mcr 1–6. Notably, Salmonella did not harbor any mcr genes that were screened in this study, whereas Listeria isolates harbored the mcr 2 (10%), 3 (7%), 4 (10%), and 6 (3%), with mcr 5 being the most prevalent with 57%. Conclusions: These findings highlight a threat to food security and public health, emphasizing the need for sturdier food handling procedures to ensure safety, enhanced antimicrobial stewardship, and alternative therapeutic strategies to combat antibiotic-resistant pathogens. Full article

This paper proposes and experimentally validates a label-free microdroplet concentration detector based on a quad-resonator metamaterial. The device exploits the linear relationship between the dielectric constant of a binary mixed solution and its concentration, mapping concentration information to absorption frequency shifts with a sensitivity of 28.53 GHz/RIU. System modeling was performed through full-wave simulation. Experimental results demonstrate a highly linear relationship between resonance frequency shift and concentration across ethanol, water, and ethanol–water solutions. The relative deviation between simulation and measurement is less than 3%, validating the model’s reliability and the robustness of the detection principle. This detector supports rapid non-contact sample replacement without requiring chemical labeling or specialized packaging. It can be mass-produced on standard PDMS substrates, with each unit reusable for >50 cycles. With a single measurement time of <30 s, it meets high-throughput detection demands. Featuring low power consumption, high precision, and scalability, this device holds broad application prospects in point-of-care diagnostics, online process monitoring, and resource-constrained scenarios. Future work will focus on achieving simultaneous multi-component detection via multi-resonator arrays and integrating chip-level wireless readout modules to further enhance portability and system integration. Full article

Driven by the “dual carbon” goal and the strategy for cultivating new productive forces, China’s economy is undergoing a crucial transformation from high-speed growth to high-quality development. As a typical high-energy consumption and high-emission sector, the green and low-carbon transformation of the building materials industry directly affects the optimization of the national energy structure and the realization of ecological goals. However, traditional building material enterprises generally face practical challenges such as low resource utilization efficiency, insufficient digitalization and greening integration of the industrial chain, and weak green innovation momentum. The transformation actions of a single entity are difficult to break through systemic bottlenecks, and it is urgently necessary to establish a dynamic evolution mechanism involving multiple entities in collaboration. This paper aims to explore the evolutionary rules and stability of digital green (DG) transformation strategies of building materials enterprises (BMEs) under multi-agent interactions involving government, universities, and consumers. Centering on BMEs, a four-party evolutionary game model among the government, enterprises, universities, and consumers is constructed, and the evolutionary processes of strategic behaviors are characterized through replicator dynamic equations. Using MATLAB R2022 (Version number: 9.13.0.2049777) bnumerical simulations, this study investigates how key parameters, such as government subsidies, penalty intensity, and consumers’ green preferences, affect the transformation pathways of enterprises. The results reveal that the DG transformation behavior of BMEs is significantly influenced by governmental policy incentives and universities’ knowledge innovation. Stronger subsidies and penalties enhance enterprises’ willingness to adopt proactive DG strategies, while consumers’ green preferences further accelerate transformation through market mechanisms. Among multiple strategic combinations, active DG transformation emerges as the main evolutionarily stable strategy. This study provides a systematic multi-agent collaborative analysis framework for the transformation of BME DG, revealing the mechanisms by which policies, knowledge, and market demands influence enterprise decisions. Thus, it offers theoretical and decision-making references for the green and low-carbon transformation of the building materials industry. Full article