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Thanh Hoa Province is located in North Central Vietnam and the Province contains a large area of 393,361.33 hectares of natural forest. A complexity of landforms has given this Province a high level of biodiversity potential. However, the reptile fauna of Thanh Hoa Province is still underestimated. Previous studies documented 111 species of reptiles from this Province.As a result of our field surveys in Pu Luong and Xuan Lien Nature Reserves, we report five species of reptiles for the first time from Thanh Hoa Province, Vietnam, namely Plestiodon tamdaoensis, Scincella devorator (Scincidae), Elaphe taeniura, Pareas macularius and Pseudoxenodon macrops (Colubridae), with novel data about morphological characteristics. In addition, we provide an updated checklist of 116 species of reptiles from Thanh Hoa Province. The reptile fauna of Thanh Hoa Province also contains a number of species of conservation concern: 22 species listed in the Red Data Book of Vietnam, 22 species listed in the IUCN Red List, 18 species listed in the Vietnam Governmental Decree No. 84; and 21 species listed in CITES appendices.

This study clarifies the impact of the carbon border adjustment mechanism (CBAM) on the export activities of enterprises that produce six main affected industrial products: iron and steel, cement, fertilizer, aluminium, electricity, and hydrogen. Secondary data is included in descriptive statistics, thereby analyzing the context, current situation and economic-technical impact on the export activities of each item, especially the 05 items that Vietnam exports to the EU market. From there, the article proposes recommendations and strategies to respond to the opportunities and challenges brought by CBAM. Research results show that CBAM puts pressure on export businesses at an early stage. However, in the long term, this policy will help businesses increase competitiveness and create surplus value with reduced costs.

Based on the examination of specimens of Amolops minutus Orlov & Ho, 2007 and A. ottorum Pham, Sung, Pham, Le, Zieger & Nguyen, 2019, we found that there is no significant morphological difference between them. Phylogenetic analysis also showed that A. minutus and A. ottorum belong to the same taxon. In addition, we discovered the distribution of A. minutus in China.In this study, we provide the first molecular data of Amolops minutus and regard A. ottorum as a junior synonym of A. minutus. In addition, we report the first record of A. minutus from China, based on nine specimens collected from Guanyinshan Provincial Nature Reserve in southern Yunnan Province and present an updated diagnosis of this species, based on literature data and newly-collected specimens.

The Sparreboom's Crocodile Newt (Tylototriton sparreboomi) is a recently discovered species of crocodile newts from Vietnam and it is currently known only from Sin Ho District in Lai Chau Province. Due to the limited information available on its population status and distribution, the species has been classified as Data Deficient in the IUCN Red List. As a result of our field surveys in 2021 and 2022 in north-western Vietnam, novel data on distribution and population status of and threats to this poorly-known species were collected. We combined the newly-discovered locations with previous occurrence records and used the data as input for modelling the potential distribution of the Sparreboom's Crocodile Newt. The results showed that the Sparreboom's Crocodile Newt’s potential distribution encompasses areas in Lai Chau, Dien Bien and Son La Provinces, Vietnam, as well as a section in Jinping County, Yunnan Province, China. Based on the findings, we suggest that protected areas in the eastern side of Hoang Lien Mountain Range, such as Che Tao, Muong La, Hoang Lien – Van Ban and Bat Xat Nature Reserves and Hoang Lien National Park in Vietnam and Jinping Feishuling Nature Reserve in China be priority sites for the species conservation. Future research and conservation initiatives should prioritise efforts in such areas in an effort to find and protect new populations of the newt.

Abstract Background The Dixon-Woods et al. Candidacy Framework, a valuable tool since its 2006 introduction, has been widely utilized to analyze access to various services in diverse contexts, including healthcare. This social constructionist approach examines micro, meso, and macro influences on access, offering concrete explanations for access challenges rooted in socially patterned influences. This study employed the Candidacy Framework to explore the experiences of individuals living with rheumatoid arthritis (RA) and their formal care providers. The investigation extended to assessing supports and innovations in RA diagnosis and management, particularly in primary care. Methods This systematic review is a Critical Interpretive Synthesis (CIS) of qualitative and mixed methods literature. The CIS aimed to generate theory from identified constructs across the reviewed literature. The study found alignment between the seven dimensions of the Candidacy Framework and key themes emerging from the data. Notably absent from the framework was an eighth dimension, identified as the “embodied relational self.” This dimension, central to the model, prompted the proposal of a revised framework specific to healthcare for chronic conditions. Results The CIS revealed that the eight dimensions, including the embodied relational self, provided a comprehensive understanding of the experiences and perspectives of individuals with RA and their care providers. The proposed Candidacy 2.0 (Chronic Condition (CC)) model demonstrated how integrating approaches like Intersectionality, concordance, and recursivity enhanced the framework when the embodied self was central. Conclusions The study concludes that while the original Candidacy Framework serves as a robust foundation, a revised version, Candidacy 2.0 (CC), is warranted for chronic conditions. The addition of the embodied relational self dimension enriches the model, accommodating the complexities of accessing healthcare for chronic conditions. Trial Registration This study did not involve a health care intervention on human participants, and as such, trial registration is not applicable. However, our review is registered with the Open Science Framework at https://doi.org/10.17605/OSF.IO/ASX5C .

In this paper, we present a single input-single output (SISO) model – 1-DOF drone. This model is simple but difficult to be controlled due to its nonlinear characteristic. We also present a self-made hardware platform for this model in laboratory. Thence, classical PID control is examined on both simulation and experiment. This algorithm is proved to work well. Thence, this model is a nonlinear SISO solution for classical training model for laboratory.

This article presents the results of research on building learning materials in accordance with the requirements to be achieved of the thematic “Physics with Environmental Protection Education (PEPE)” in the Physics 10 to support Blended learning according to the orientation of The General Education Program (GEP) in 2018. Specifically, the learning materials have been built for teaching PEPE applying physics teaching theory. Additionally, practical research methods are used in combination with statistical approaches to identify difficulties when teaching PEPE, thereby establishing criteria for developing instructional materials and determining the strengths, weaknesses, and suitability of the developed materials in the current blended teaching. These support materials assist teachers in teaching the PEPE, helping students develop their physics competencies to meet the subject's learning outcomes, as well as nurturing their patriotism and responsibility in environmental protection. This material can be applied as reference, teaching and assessment material. The survey of teachers and students shows that the learning materials are positively received, but it is necessary to develop more learning material content and pedagogical experiments to support the learning of high school students more effectively.

The research examines the impact of servant leadership on the innovation capability of higher education institutions in Vietnam. Through the application of structural equation modeling (SEM), the results demonstrated the importance and direct impact of servant leadership style - characterized by prioritizing development and rights of those who follow - to the capability of universities to innovate and the behaviors of knowledge sharing; in which, the knowledge sharing factor plays a partial mediating role. Thereby, a number of recommendations have been proposed to promote servant leadership and enhance innovation capabilities at universities across the country.

This paper presents a new approach to the L2(R) norm decay rates of the Fourier oscillatory integral operators for some classes of degenerate phases. In particular, the sharp norm decay rates of the Fourier oscillatory integral operators for homogeneous-type polynomial phases, and those for a class of nonsmooth polynomial hybrid phase functions are obtained.

There are many potential approaches to marine carbon dioxide removal (mCDR), of which ocean iron fertilization (OIF) has the longest history of study. However, OIF studies to date were not primarily designed to quantify the durability of carbon (C) storage, nor how wise OIF might be as an mCDR approach. To quantify C sequestration, we introduce a metric called the “centennial tonne,” defined as 1,000 kg of C isolated from atmospheric contact for on average at least 100 years. We present the activities needed to assess OIF from a scientific and technological perspective, and additionally, how it might be responsibly studied and potentially deployed. The five activities include: field studies in the Northeast Pacific; improved modeling for field studies, data assimilation and predictions at larger scales; improvements in monitoring, reporting and verification (MRV) for C, and also MRV for tracking ecological and environmental impacts; and developing new iron sources and their delivery, to increase efficiencies and reduce costs. The fifth activity is to understand whether public and community support exists for OIF, and what governance structures might support further research and possible deployment of OIF. This article is written by a multidisciplinary experts group called Exploring Ocean Iron Solutions (ExOIS) that is organized around a responsible code of conduct. Of the mCDR approaches, OIF has the potential to be low cost, scalable, and rapidly deployable. Reducing CO2 emissions must lead the way, but there is also an urgency to decide under what conditions and whether OIF might be deployed or not.

Since the establishment of the Vu Quang National Park in 2002 in Ha Tinh Province, central Vietnam, several surveys on the amphibian fauna have been undertaken in this protected area. In 2009, Nguyen et al. provided a list of 23 amphibian species from Vu Quang National Park. In addition, a new species was described in 2021 from the National Park, namely Vietnamophryne vuquangensis.As a result of our field surveys in 2013 and 2023, a total of 29 species of amphibians was recorded from the Vu Quang National Park. Six of them are recorded for the first time from Ha Tinh Province, comprising three species of Megophryidae, one species of Dicroglossidae, one species of Ranidae and one species of Rhacophoridae. In addition, we provide morphological data and ecological notes on the aforementioned species.

Background: Despite advances in the early detection and treatment of breast cancer (BC), inequity persists, and the BC mortality rate remains approximately 40% higher among Black and African American (B/AA) women compared to White (W) women. Methods: In response to The University of Kansas Cancer Center’s Catchment Area Steering Committee identified priorities, the Breast Cancer Health Equity Task Force (BCHETF) leveraged data-driven insights to develop targeted interventions that promote BC prevention and early detection among B/AA women. Results: By synthesizing data, we mapped census tracts with high B/AA population density to identify targeted areas to focus screening and outreach efforts with an evidence-based intervention (EBI). The BCHETF and researchers are also engaged in ongoing projects to explore patient-level experiences of BC care among B/AA women through focus groups and address provider-level gaps in the delivery of BC risk assessment and screening with telementoring and practice facilitation. Discussion: Targeting efforts through data visualization has been helpful, but limitations remain. Here, we describe the BCHETFs concerted and ongoing efforts to address BC health disparities among B/AA women, facilitate improvements in BC screening access and outcomes, and promote health equity for all.

Summary: Despite recent advances in the mechanism of oxidized DNA activating NLRP3, the molecular mechanism and consequence of oxidized DNA associating with NLRP3 remains unknown. Cytosolic NLRP3 binds oxidized DNA which has been released from the mitochondria, which subsequently triggers inflammasome activation. Human glycosylase (hOGG1) repairs oxidized DNA damage which inhibits inflammasome activation. The fold of NLRP3 pyrin domain contains amino acids and a protein fold similar to hOGG1. Amino acids that enable hOGG1 to bind and cleave oxidized DNA are conserved in NLRP3. We found NLRP3 could bind and cleave oxidized guanine within mitochondrial DNA. The binding of oxidized DNA to NLRP3 was prevented by small molecule drugs which also inhibit hOGG1. These same drugs also inhibited inflammasome activation. Elucidating this mechanism will enable the design of drug memetics that treat inflammasome pathologies, illustrated herein by NLRP3 pyrin domain inhibitors which suppressed interleukin-1β (IL-1β) production in macrophages.

Yersinia (Y.) enterocolitica is an important foodborne pathogenic species that is mainly transmitted by the consumption of contaminated meat, particularly pork. To combat the bacteria along the food chain, the application of strictly lytic phages may be a promising tool. As the temperatures in the gut of animals and during food processing can differ significantly, a phage cocktail intended to be used for applications should comprise phages that are active at various temperatures. In this study, we isolated and characterized three phages with a myoviridal morphology (vB_YenM_P8, vB_YenM_P744 and vB_YenM_P778), which lysed the most important Y. enterocolitica serotypes O:3, O:9 and O:5,27 at a low multiplicity of infection (MOI) and at low temperatures down to 6°C. While vB_YenM_P8 is a member of the T4 family, vB_YenM_P744 and vB_YenM_P778 are novel phages that do not show relationship to known phages. The three phages were mixed in a cocktail with the already described phages vB_YenM_P281 and vB_YenP_Rambo. The cocktail revealed a strong lytic activity and lysed a mixture of Y. enterocolitica serotypes at room temperature (RT) within few hours with a reduction of up to 4.8 log10 units. Moreover, at even lower temperatures the mixture was significantly reduced after incubation overnight. The strongest reductions were determined at 6°C (4.0 log10 units) suggesting that the cocktail can lyse the psychrophilic Y. enterocolitica also during food processing. To determine possible phage resistance, 100 colonies that survived the infection by the phages were isolated and analysed regarding their serotype and phage susceptibility. Most isolates belonged to serotype O:9, but all of them were still sensitive to at least one phage of the cocktail.

The 3D printing technique for sand mold exhibited the good response of precast concrete structure manufacturing process. The designed sandwich core structure, including solid core, diamond core, honeycomb core, pyramid core and round O core were constructed by silica sand with different thickness and different relative density ratios from 0.5 to 0.9 and investigated by mechanical experiment, finite element modeling and digital image correlation. The solid block showed the greatest compressive strength 6.15 MPa and flexural strength 3.85 MPa. The sand core with density ratios of 0.9 performed a significant response with greater 10–50% in strength, compared with specimens with ratios 0.5 and 0.7. The sandwich composites with honeycomb and pyramid core showed a sequence of stability and enhancement with 2–3 times in difference. The experimental, numerical and digital results indicate that the core structure can be optimized to control and apply to 3D printing sand mold and precast concrete structure with a good agreement with under 15% in comparison and verification. These findings offered a good insight into the study of mechanical behavior of sandwich structure in the application and industry.

Abstract Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond that accessible by ab initio methods and play an increasingly important role in the study and design of materials. However, MLIPs are only as accurate and robust as the data on which they are trained. Here, we present DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling as an approach to select a robust training set of structures from a large and complex configuration space. By applying DIRECT sampling on the Materials Project relaxation trajectories dataset with over one million structures and 89 elements, we develop an improved materials 3-body graph network (M3GNet) universal potential that extrapolates more reliably to unseen structures. We further show that molecular dynamics (MD) simulations with the M3GNet universal potential can be used instead of expensive ab initio MD to rapidly create a large configuration space for target systems. We combined this scheme with DIRECT sampling to develop a reliable moment tensor potential for titanium hydrides without the need for iterative augmentation of training structures. This work paves the way for robust high-throughput development of MLIPs across any compositional complexity.

Log anomaly detection is a crucial task in monitoring IT systems along with metrics and traces. An anomaly could be detected by either one of two types of logs: individual logs or log sequences. While an individual log indicates an independent system status, combining multiple logs describes the execution paths of systems. Once the patterns of log sequences deviate much from normal execution behaviors, that might indicate system anomalies. For log anomaly detection using log sequences, supervised learning methods are preferable due to their high performance. However, these methods require labeled data to train models. As systems evolve, the number of logs increases significantly, which makes labeling data labor-intensive and impractical. Therefore, other learning techniques, such as semi-supervised or unsupervised, are better alternatives for detection. In practice, detecting log anomalies is quite challenging because of several problems, such as unstable logs, new types of logs, and unexplored log semantics. To address these problems and enhance detection performance, we propose a lightweight semi-supervised multi-task learning method named MultiLog in this paper. The key components of the proposed method are pre-trained language model BERT, dimension reduction, attention mechanism from Transformer, and multi-task learning. Similar to previous studies, we conduct comprehensive experiments on three widely used datasets: HDFS, BGL, and Thunderbird. In terms of efficiency, our proposed model is 50 times smaller while the F1-Scores are maintained compared to the original model. In terms of effectiveness, the proposed model outperforms baseline methods and achieves performance comparable to supervised learning models.

This paper presents a Blockchain-based framework for providing Blockchain services for purposes of stability in terms of consensus protocol infrastructure and governance mechanisms and accessible auxiliary services suitable for the vast majority of current business needs, including fundamental factors such as digital identity with autonomous identity, building solutions to ensure transaction privacy with zero-knowledge proofs, and other services related to digital assets. The proposed framework helps promote digital transformation for businesses, especially small and medium enterprises with limited resources and costs, to apply Blockchain technology to their business models, increasing competitive advantages and assisting the companies in focusing on business logic while still using Blockchain technology in their functions.

Abstract Background With more clinical trials are offering optional participation in the collection of bio-specimens for biobanking comes the increasing complexity of requirements of informed consent forms. The aim of this study is to develop an automatic natural language processing (NLP) tool to annotate informed consent documents to promote biorepository data regulation, sharing, and decision support. We collected informed consent documents from several publicly available sources, then manually annotated them, covering sentences containing permission information about the sharing of either bio-specimens or donor data, or conducting genetic research or future research using bio-specimens or donor data. Results We evaluated a variety of machine learning algorithms including random forest (RF) and support vector machine (SVM) for the automatic identification of these sentences. 120 informed consent documents containing 29,204 sentences were annotated, of which 1250 sentences (4.28%) provide answers to a permission question. A support vector machine (SVM) model achieved a F-1 score of 0.95 on classifying the sentences when using a gold standard, which is a prefiltered corpus containing all relevant sentences. Conclusions This study provides the feasibility of using machine learning tools to classify permission-related sentences in informed consent documents.