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Structurally and functionally optimized silk fibroin-alginate-based biomimetic scaffolds reinforced with nanobioceramics for bone tissue engineering applications
No full textIn this study, we prepared chemically crosslinked silk fibroin (SF) and sodium alginate (Alg) biomimetic scaffolds reinforced with bioceramic nanohydroxyapatite (nHAp) for bone tissue engineering (BTE) applications. The pore sizes of these scaffolds were effectively controlled by varying the composition of the SF/nHAp/Alg biocomposites. The scaffold prepared with a 40:20:40 SF: nHAp: Alg ratio exhibited excellent swelling properties, reaching over 1700% within 70 min. In vitro degradation studies demonstrated that these biomimetic scaffolds exhibited controlled degradation, taking over 30 days to achieve 50% degradation. The scaffolds also showed good mechanical properties; they maintained structural integrity and did not break, even under a load approximately 800 times their own weight. Additionally, scaffolds loaded with synthetic peptide salmon calcitonin effectively controlled initial burst release and enabled sustained therapeutics delivery for up to two weeks. The biocompatibility of the scaffolds was evaluated using in vitro cell viability and hemolysis assays, which revealed good safety for human dermal fibroblast cells and negligible toxicity to rabbit red blood cells. Importantly, the scaffolds promoted cell proliferation and alkaline phosphatase secretion in human bone marrow stem cells. Histological and immunological analyses in a scaffold-implanted mouse model have demonstrated biocompatibility, supporting osteoclastic resorption and osteoblastic mineralization by downregulating RANKL. Furthermore, the chick chorioallantoic membrane assay showed the excellent angiogenic properties of the scaffold. These results suggest that the bioceramic-reinforced SF/Alg biomimetic scaffold has significant potential for use in BTE
Addressing investor concerns: a Chinese financial question-answering benchmark with LLM-based evaluation
No full textIn recent years, large language models (LLMs) have shown impressive performance across various natural language processing tasks and are increasingly adopted in high-stakes fields such as financial analysis. However, their effectiveness in Chinese financial contexts is hindered by the scarcity of high-quality, domain-specific datasets. To bridge this gap, we present the Chinese Financial Question Answering (CFQA) dataset, a novel resource designed to advance research in financial analysis. CFQA is constructed from publicly available annual reports of multiple Chinese listed companies, paired with corresponding questions and human-annotated answers. Evaluation results reveal that existing QA methods perform poorly on this dataset. CFQA introduces several unique challenges: (1) source documents are in PDF format with complex tabular structures, making information extraction difficult; (2) the length and intricacy of financial reports complicate answer retrieval; and (3) the questions are tightly focused on domain-specific financial content
P2TS: a preemptive approach for priority-aware task scheduling in computing power networks
No full textAs an emerging computing paradigm, Computing Power Networks (CPNs) are dedicated to coordinating and managing network resources and computing resources to achieve interconnectivity in computing power perception. Efficient collaborative computing of massive data can be achieved through the scheduling function of CPNs. However, existing scheduling research mainly focuses on selecting network links and computing nodes, lacking consideration for task execution after scheduling, which may degrade the Quality of Service (QoS), leading to widespread failures and significant losses. To address this issue, we design a priority-aware preemptive task scheduling (P2TS) strategy for CPNs to jointly optimize task scheduling and execution in terms of success rate, average processing delay, and load balancing. Specifically, at the execution level, we propose a priority-aware preemptive mechanism (P2M) to optimize post-scheduling task execution. Then, at the scheduling level, we apply deep reinforcement learning (DRL) to optimize the scheduling process supporting the P2M in CPNs. A series of simulations are conducted to demonstrate the superiority of our strategy
SRAA: a secure and revocable access authentication scheme in cross-domain vehicular twin networks
No full textVehicular twin networks (VTN) create virtual agents of vehicular entities through digital twin (DT) technology, replacing physical counterparts in connecting and exchanging traffic information in cyberspace, overcoming physical range constraints and extending information sources for enhanced vehicular decision support. However, the inherent openness of VTN renders communication between DTs, vulnerable to security threats, such as tampering and impersonation, especially in scenarios where DTs are distributed across multiple cloud domains. These issues result in erroneous decisions to threaten vehicular safety because DTs may receive compromised information. To address these challenges, this article proposes a secure and revocable access authentication scheme in the cross-domain VTN. In the scheme, DTs should be authorized first to obtain identity-bound symmetric functions before joining the VTN, and then perform secure access authentication and key agreement with others based on chameleon hash functions for both intradomain and cross-domain communication. Moreover, a dynamic revocation mechanism is introduced to remove malicious DTs from VTN. Formal verification using the Tamarin tool demonstrates that the proposed scheme achieves diverse security properties. Performance evaluation further shows that the proposed scheme outperforms most related schemes in terms of computational and communication overhead
Fungal panzootic increasingly threatens temperate amphibian species while impact has stabilised in equatorial regions
No full textGlobal amphibian declines outpace the loss of most organisms on Earth. The panzootic fungal disease chytridiomycosis, caused by Batrachochytrium dendrobatidis ( Bd ), is widely regarded as a predominant driver behind amphibian biodiversity erosion. However, a comprehensive global‐scale analysis of the relationship between Bd and extinction risk remains lacking. Using a global database of Bd ‐detections and IUCN Red List extinction risk, we show that current amphibian declines are associated with Bd in temperate regions only, whereas historical analyses reveal a past peak of Bd ‐related declines across more equatorial areas during 1980–2004, that has diminished in intensity in recent decades (2004–2020). In contrast, temperate species show a lack of Bd ‐related declines during 1980–2004 but significant declines are currently ongoing. We suggest that the shorter activity seasons in temperate regions may have acted as ‘natural lockdowns’ that delayed the annihilating effects of Bd in susceptible species. Conversely, year‐round activity in more amphibian‐dense, equatorial areas may have triggered a faster transition into post‐epizootic dynamics, characterised by a continuous high‐intensity outbreak followed by amphibian population stabilisation and pathogen persistence at lower levels
Cross-scale chip removal process analysis and optimization using hybrid CFD-DEM simulation
No full textDrilling is a critical process in the manufacturing of aerospace components, and the quality of drilled connection holes directly determines the service reliability of high-end equipment. During drilling, different materials produce chips of varying sizes (ranging from micrometers to millimeters), leading to issues such as high temperature and tool wear. Efficient removal of these multi-scale chips is essential for improving drilling quality. However, the narrow and complex internal structure of enclosed or semi-enclosed chip removal systems often result in inefficient chip evacuation. In addition, experimental observation of airflow and chip velocity within such system is challenging, hence numerical simulation of the chip removal process become a practical alternative. This study utilizes a hybrid approach combining CFD and DEM simulation (CFD-DEM) to systematically investigate the characteristics of cross-scale chip removal processes. Simulation results show that the diffused airflow and low/negative velocity flow regions of the existing system are unfavorable for chip removal. To address this issue, different eccentric designs and diversion holes were introduced, and their impacts on the chip removal performance have been evaluated. The results were then used to guide the optimization of the chip removal system. Through combined/optimized eccentric design and diversion hole design, the overall chip removal performance of the system shows a significant improvement (48.27%)
Decolonising pharmacy education: Broadening epistemic perspectives and advancing curricular inclusion
No full textIntroduction: Pharmacy education curricula remain predominantly influenced by Westernbiomedical paradigms, often marginalising diverse cultural and Indigenous health perspectives,which limits culturally responsive patient care.Perspective: Integrating epistemic pluralism, critical consciousness, and cultural safety frameworksfrom broader healthcare education can foster curricula reflective of diverse healing traditions.Curricular co-creation with marginalised communities further supports inclusive pharmacyeducation.Implications: Effective decolonisation requires comprehensive curriculum audits, targeted facultytraining in inclusive pedagogies, authentic community engagement, and alignment with regulatory standards. Interdisciplinary collaboration enriches pharmacy curricula, preparing culturallycompetent pharmacists to address health disparities and provide patient-centred care in diversecommunities.This paper offers a conceptual and advocacy-oriented perspective that outlines why and howpharmacy education should be reoriented through decolonising principles
A survey study on meta-heuristic-based feature selection approaches of intrusion detection systems in distributed networks
No full textWith the emergence of IoT and expanding the coverage of distributed networks such as cloud and fog, security attacks and breaches are becoming distributed and expanded too. Cybersecurity attacks can disrupt business continuity or expose critical data, leading to significant failures. The Intrusion Detection Systems (IDSs) as a remedy in such networks play a critical role in this ecosystem to find an attack at the earliest time and the countermeasure is performed if necessary. Artificial intelligence techniques such as machine learning-based and meta-heuristic-based approaches are being pervasively applied to prepare smarter IDS components from logged network traffic. The network traffic is recorded in the form of data sets for further analysis to detect traffic behavior from past treatments. Feature selection is a prominent approach in creating the prediction model to recognize feature network connection is normal or not. Since the feature selection problem in large datasets is NP-Hard and utilizing only heuristic-based approaches is not as efficient as desired, meta-heuristic-based approaches attract research attention to prepare highly accurate prediction models. To address the issue, this paper presents a subjective classification of published literature. Then, this presents a survey study on meta-heuristic-based feature selection approaches in preparing efficient IDSs. It investigates several kinds of literature from different angles and compares them in terms of used metrics in the literature to give broad insights into readers for advantages, challenges, and limitations. It can pave the way by highlighting research gaps for further processing and improvement in the future by interested researchers in the field.</p
Institutional pressure and pollution control: Small and medium-sized enterprises
No full textPurposeSmall and medium-sized enterprises (SMEs) are critical to China's sustainable development. This study aims to empirically investigate the influence of government and customer pressures on the purchasing decisions of pollution control equipment among Chinese SMEs.Design/methodology/approachWe first conduct an exploratory case study involving four Chinese SMEs to identify the key attributes of pollution control equipment and the decision-making processes within SMEs regarding equipment procurement. We then design a discrete choice experiment based on the insights gained from these case studies. Data are collected from 313 Chinese SMEs and analysed using a random parameter logit model.FindingsThe results indicate that government pressure positively motivates SMEs to purchase pollution control equipment, whereas customer pressure exerts a negative effect. Government and customer pressures enhance the positive impact of the equipment's gaseous waste purification capability on SMEs' purchasing decisions. However, they do not influence the effect of sewage purification capability on such decisions.Originality/valueThe findings enhance understanding of the role of institutional pressure in the green transformation of Chinese SMEs. Additionally, the results provide valuable insights into the equipment capabilities that Chinese SMEs prioritise when purchasing pollution control equipment under the influence of institutional pressure
EP250207b is not a collapsar fast X-ray transient. Is it due to a binary compact object merger?
No full textFast X-ray transients (FXTs) are short-lived extragalactic X-ray sources. Recent progress through multiwavelength follow-up of Einstein Probe-discovered FXTs has shown that several are related to collapsars, which can also produce -ray bursts (GRBs). In this paper, we investigate the nature of the FXT EP250207b. The Very Large Telescope/Multi Unit Spectroscopic Explorer spectra of a nearby (15.9 kpc in projection) lenticular galaxy reveal no signs of recent star formation. If this galaxy is indeed the host, EP250207b lies at a redshift , implying a peak observed absolute magnitude for the optical counterpart of . At the time when supernovae (SNe) would peak, it is substantially fainter than all SN types. These results are inconsistent with a collapsar origin for EP250207b. The properties favour a binary compact object merger-driven origin. The X-ray, optical, and radio observations are compared with predictions of several types of extragalactic transients, including afterglow and kilonova models. The data can be fitted with a slightly off-axis viewing angle afterglow. However, the late-time ( d) optical/near-infrared counterpart is too bright for the afterglow and also for conventional kilonova models. This could be remedied if that late emission is due to a globular cluster or the core of a (tidally disrupted) dwarf galaxy. If confirmed, this would be the first case where the multiwavelength properties of an FXT are found to be consistent with a compact object merger origin, increasing the parallels between FXTs and GRBs. We finally discuss whether the source could originate in a higher redshift host galaxy