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Abstract Background Accurate breed identification is essential for the conservation and sustainable use of indigenous farm animal genetic resources. In this study, we evaluated the phylogenetic relationships and genomic breed compositions of 13 sheep breeds using SNP and InDel data from whole genome sequencing. The breeds included 11 Chinese indigenous and 2 foreign commercial breeds. We compared different strategies for breed identification with respect to different marker types, i.e. SNPs, InDels, and a combination of SNPs and InDels (named SIs), different breed-informative marker detection methods, and different machine learning classification methods. Results Using WGS-based SNPs and InDels, we revealed the phylogenetic relationships between 11 Chinese indigenous and two foreign sheep breeds and quantified their purities through estimated genomic breed compositions. We found that the optimal strategy for identifying these breeds was the combination of DFI_union for breed-informative marker detection, which integrated the methods of Delta, Pairwise Wright's FST, and Informativeness for Assignment (namely DFI) by merging the breed-informative markers derived from the three methods, and KSR for breed assignment, which integrated the methods of K-Nearest Neighbor, Support Vector Machine, and Random Forest (namely KSR) by intersecting their results. Using SI markers improved the identification accuracy compared to using SNPs or InDels alone. We achieved accuracies over 97.5% when using at least the 1000 most breed-informative (MBI) SI markers and even 100% when using 5000 SI markers. Conclusions Our results provide not only an important foundation for conservation of these Chinese local sheep breeds, but also general approaches for breed identification of indigenous farm animal breeds.

AbstractThe acute toxicity (sometimes called “overdose” or “poisoning”) crisis has affected Canadians from all walks of life and of all ages—children, youth, adults including older adults have died.

RésuméLa crise des intoxications aiguës (parfois appelées « surdoses » ou « empoisonnements ») touche la population canadienne à toutes les étapes de vie, que ce soit les jeunes, les adultes ou les aînés.

Background: To challenge dominant conceptions of children and innovate nursing education, our team created an open-access training module (https://childsxethics.net/) addressing ethical considerations for children undergoing surgery. Objective: To evaluate the level of Bloom’s Taxonomy cognitive, affective, and psychomotor learning reached by graduate nursing students after completing the training module. Methods: A qualitative descriptive study was conducted using Bloom’s Taxonomy. Data sources comprised of participants’ course assignments. Results: Participants (n=19) wrote 19 online reflections, 43 peer responses and completed two group assignments. The module and associated class assignments promoted high levels of cognitive and affective learning. The type of assignment influenced participants’ levels of learning. Cognitive and affective learning processes were enhanced when integrating reflections and fostering interactions among learners. Implications: Study findings will inform future iterations of the training module. Our innovative educational resource will facilitate the recognition of children as active moral agents and improve their surgical experiences.

Abstract Background With the introduction of digital phenotyping and high-throughput data, traits that were previously difficult or impossible to measure directly have become easily accessible, offering the opportunity to enhance the efficiency and rate of genetic gain in animal production. It is of interest to assess how behavioral traits are indirectly related to the production traits during the performance testing period. The aim of this study was to assess the quality of behavior data extracted from day-wise video recordings and estimate the genetic parameters of behavior traits and their phenotypic and genetic correlations with production traits in pigs. Behavior was recorded for 70 days after on-test at about 10 weeks of age and ended at off-test for 2008 female purebred pigs, totaling 119,812 day-wise records. Behavior traits included time spent eating, drinking, laterally lying, sternally lying, sitting, standing, and meters of distance traveled. A quality control procedure was created for algorithm training and adjustment, standardizing recording hours, removing culled animals, and filtering unrealistic records. Results Production traits included average daily gain (ADG), back fat thickness (BF), and loin depth (LD). Single-trait linear models were used to estimate heritabilities of the behavior traits and two-trait linear models were used to estimate genetic correlations between behavior and production traits. The results indicated that all behavior traits are heritable, with heritability estimates ranging from 0.19 to 0.57, and showed low-to-moderate phenotypic and genetic correlations with production traits. Two-trait linear models were also used to compare traits at different intervals of the recording period. To analyze the redundancies in behavior data during the recording period, the averages of various recording time intervals for the behavior and production traits were compared. Overall, the average of the 55- to 68-day recording interval had the strongest phenotypic and genetic correlation estimates with the production traits. Conclusions Digital phenotyping is a new and low-cost method to record behavior phenotypes, but thorough data cleaning procedures are needed. Evaluating behavioral traits at different time intervals offers a deeper insight into their changes throughout the growth periods and their relationship with production traits, which may be recorded at a less frequent basis.

IntroductionSubstance-related acute toxicity deaths (ATDs) are a public health crisis in Canada. Youth are often at higher risk for substance use due to social, environmental and structural factors. The objectives of this study were to understand the characteristics of youth (aged 12–24 years) dying of accidental acute toxicity in Canada and examine the substances contributing to and circumstances surrounding youth ATDs. MethodsData from a national chart review study of coroner and medical examiner data on ATDs that occurred in Canada between 2016 and 2017 were used to conduct descriptive analyses with proportions, mortality rates and proportionate mortality rates. Where possible, youth in the chart review study were compared with youth in the general population and youth who died of all causes, using census data. ResultsOf the 732 youth who died of accidental acute toxicity in 2016–2017, most (94%) were aged 18 to 24 years. Youth aged 20 to 24 who were unemployed, unhoused or living in collective housing were overrepresented among accidental ATDs. Many of the youth aged 12 to 24 who died of accidental acute toxicity had a documented history of substance use. Fentanyl, cocaine and methamphetamine were the most common substances contributing to death, and 38% of the deaths were witnessed or potentially witnessed. ConclusionThe findings of this study point to the need for early prevention and harm reduction strategies and programs that address mental health, exposure to trauma, unemployment and housing instability to reduce the harms of substance use on Canadian youth.

IntroductionLes décès attribuables à une intoxication aiguë due à une substance sont à l’origine d’une crise de santé publique au Canada. Les jeunes courent souvent un risque accru de consommation de substances en raison de facteurs sociaux, environnementaux et structurels. Les objectifs de cette étude étaient de comprendre les caractéristiques des jeunes (12 à 24 ans) qui décèdent en raison d’une intoxication aiguë accidentelle au Canada ainsi que d’analyser les substances qui contribuent aux décès par intoxication aiguë chez les jeunes et les circonstances entourant ces décès. MéthodologieNous avons utilisé les données d’une étude nationale portant sur l’examen des dossiers des données de coroners et de médecins légistes concernant les décès par intoxication aiguë survenus au Canada en 2016 et 2017 afin de réaliser des analyses descriptives à partir des proportions, des taux de décès et des taux proportionnels de décès. Dans la mesure du possible, les jeunes faisant partie de l’étude sur l’examen des dossiers ont été comparés, au moyen de données de recensement, aux jeunes dans la population générale et aux jeunes décédés toutes causes confondues. RésultatsSur les 732 jeunes décédés par intoxication aiguë accidentelle en 2016-2017, la plupart (94 %) avaient entre 18 et 24 ans. Les jeunes de 20 à 24 ans sans emploi et vivant dans un logement collectif ou sans domicile étaient surreprésentés parmi les décès accidentels par intoxication aiguë. Parmi les jeunes de 12 à 24 ans décédés en raison d’une intoxication aiguë accidentelle, beaucoup avaient des antécédents documentés de consommation de substances. Le fentanyl, la cocaïne et la méthamphétamine ont été les substances ayant le plus fréquemment contribué aux décès, et 38 % des décès ont eu lieu en présence d’un témoin ou potentiellement en présence d’un témoin. ConclusionLes résultats de cette étude soulignent la nécessité de mettre en place des mesures de prévention précoce, des stratégies de réduction des méfaits et des programmes portant sur la santé mentale, l’exposition à un événement traumatisant ainsi que le chômage et l’instabilité résidentielle, afin de réduire les méfaits de la consommation de substances chez les jeunes Canadiens.

In diplomacy and statecraft studies, it has been established that the invisible yet omnipresent language interpreters often assume a critical role at international meetings of politicians and diplomats. In contrast to interpreting in everyday settings, interpreting in political and diplomatic settings is high-profile and exclusive for two main reasons. On the one hand, political events and diplomatic missions often involve high-ranking and high-power officials from the field of politics and diplomacy, usually heads of the state, ministers, and military commanders. On the other hand, the impact of these communicative events is far-reaching, extending to peace negotiations, conflict resolutions, and post-conflict peace-building efforts. The outcome of these operations is highly visible and substantive to vulnerable groups and mobile populations, including but not limited to child victims, war-afflicted adults, and displaced and stateless populations.

Abstract Background Most genomic prediction applications in animal breeding use genotypes with tens of thousands of single nucleotide polymorphisms (SNPs). However, modern sequencing technologies and imputation algorithms can generate ultra-high-density genotypes (including millions of SNPs) at an affordable cost. Empirical studies have not produced clear evidence that using ultra-high-density genotypes can significantly improve prediction accuracy. However, (whole-genome) prediction accuracy is not very informative about the ability of a model to capture the genetic signals from specific genomic regions. To address this problem, we propose a simple methodology that detects chromosome regions for which a specific model (e.g., single-step genomic best linear unbiased prediction (ssGBLUP)) may fail to fully capture the genetic signal present in such segments—a phenomenon that we refer to as signal leakage. We propose to detect regions with evidence of signal leakage by testing the association of residuals from a pedigree or a genomic model with SNP genotypes. We discuss how this approach can be used to map regions with signals that are poorly captured by a model and to identify strategies to fix those problems (e.g., using a different prior or increasing marker density). Finally, we explored the proposed approach to scan for signal leakage of different models (pedigree-based, ssGBLUP, and various Bayesian models) applied to growth-related phenotypes (average daily gain and backfat thickness) in pigs. Results We report widespread evidence of signal leakage for pedigree-based models. Including a percentage of animals with SNP data in ssGBLUP reduced the extent of signal leakage. However, local peaks of missed signals remained in some regions, even when all animals were genotyped. Using variable selection priors solves leakage points that are caused by excessive shrinkage of marker effects. Nevertheless, these models still miss signals in some regions due to low linkage disequilibrium between the SNPs on the array used and causal variants. Thus, we discuss how such problems could be addressed by adding sequence SNPs from those regions to the prediction model. Conclusions Residual single-marker regression analysis is a simple approach that can be used to detect regional genomic signals that are poorly captured by a model and to indicate ways to fix such problems.

Abstract Background Whole-genome sequence (WGS) data harbor causative variants that may not be present in standard single nucleotide polymorphism (SNP) chip data. The objective of this study was to investigate the impact of using preselected variants from WGS for single-step genomic predictions in maternal and terminal pig lines with up to 1.8k sequenced and 104k sequence imputed animals per line. Methods Two maternal and four terminal lines were investigated for eight and seven traits, respectively. The number of sequenced animals ranged from 1365 to 1491 for the maternal lines and 381 to 1865 for the terminal lines. Imputation to sequence occurred within each line for 66k to 76k animals for the maternal lines and 29k to 104k animals for the terminal lines. Two preselected SNP sets were generated based on a genome-wide association study (GWAS). Top40k included the SNPs with the lowest p-value in each of the 40k genomic windows, and ChipPlusSign included significant variants integrated into the porcine SNP chip used for routine genotyping. We compared the performance of single-step genomic predictions between using preselected SNP sets assuming equal or different variances and the standard porcine SNP chip. Results In the maternal lines, ChipPlusSign and Top40k showed an average increase in accuracy of 0.6 and 4.9%, respectively, compared to the regular porcine SNP chip. The greatest increase was obtained with Top40k, particularly for fertility traits, for which the initial accuracy based on the standard SNP chip was low. However, in the terminal lines, Top40k resulted in an average loss of accuracy of 1%. ChipPlusSign provided a positive, although small, gain in accuracy (0.9%). Assigning different variances for the SNPs slightly improved accuracies when using variances obtained from BayesR. However, increases were inconsistent across the lines and traits. Conclusions The benefit of using sequence data depends on the line, the size of the genotyped population, and how the WGS variants are preselected. When WGS data are available on hundreds of thousands of animals, using sequence data presents an advantage but this remains limited in pigs.

Background: Female physicians and patients experience gender bias in healthcare. The purpose of this research is to explore medical students’ gender bias toward physicians and patients and whether their bias varies by gender. Methods: We surveyed medical students at Memorial University between November 2020 and April 2021. We recruited participants through Facebook, email, and e-posters. We collected demographic information, including gender and class year. We used the Nijmegen Gender Awareness in Medicine Scale to measure gender sensitivity, gender role ideology toward patients, and gender role ideology toward doctors. We analyzed the data using averages and t-tests. Results: Mean gender sensitivity scores were 4/5 indicating high gender sensitivity. Gender role ideology toward doctors mean scores were 2/5 indicating that students did not hold strong stereotypical views toward doctors. Although male students scored higher than female students (p

Abstract Background Genome-wide association studies (GWAS) aim at identifying genomic regions involved in phenotype expression, but identifying causative variants is difficult. Pig Combined Annotation Dependent Depletion (pCADD) scores provide a measure of the predicted consequences of genetic variants. Incorporating pCADD into the GWAS pipeline may help their identification. Our objective was to identify genomic regions associated with loin depth and muscle pH, and identify regions of interest for fine-mapping and further experimental work. Genotypes for ~ 40,000 single nucleotide morphisms (SNPs) were used to perform GWAS for these two traits, using de-regressed breeding values (dEBV) for 329,964 pigs from four commercial lines. Imputed sequence data was used to identify SNPs in strong ( $$\ge$$ ≥ 0.80) linkage disequilibrium with lead GWAS SNPs with the highest pCADD scores. Results Fifteen distinct regions were associated with loin depth and one with loin pH at genome-wide significance. Regions on chromosomes 1, 2, 5, 7, and 16, explained between 0.06 and 3.55% of the additive genetic variance and were strongly associated with loin depth. Only a small part of the additive genetic variance in muscle pH was attributed to SNPs. The results of our pCADD analysis suggests that high-scoring pCADD variants are enriched for missense mutations. Two close but distinct regions on SSC1 were associated with loin depth, and pCADD identified the previously identified missense variant within the MC4R gene for one of the lines. For loin pH, pCADD identified a synonymous variant in the RNF25 gene (SSC15) as the most likely candidate for the muscle pH association. The missense mutation in the PRKAG3 gene known to affect glycogen content was not prioritised by pCADD for loin pH. Conclusions For loin depth, we identified several strong candidate regions for further statistical fine-mapping that are supported in the literature, and two novel regions. For loin muscle pH, we identified one previously identified associated region. We found mixed evidence for the utility of pCADD as an extension of heuristic fine-mapping. The next step is to perform more sophisticated fine-mapping and expression quantitative trait loci (eQTL) analysis, and then interrogate candidate variants in vitro by perturbation-CRISPR assays.

Let $\rho $ be a symmetric measure of Lebesgue type, i.e., \begin{equation*} \rho =\frac{1}{2}(\mu \times \delta _0+\delta _0\times \mu ), \end{equation*} where the component measure $\mu $ is the Lebesgue measure supported on $[t, t+1]$ for $t\in \mathbb{Q}\setminus \lbrace -\frac{1}{2}\rbrace $ and $\delta _{0}$ is the Dirac measure at $0$. We prove that $\rho $ is a spectral measure if and only if $ t \in \frac{1}{2}\mathbb{Z}$. In this case, $L^2(\rho )$ has a unique orthonormal basis of the form \[ \left\lbrace e^{2\pi i (\lambda x-\lambda y)}:\lambda \in \Lambda _0\right\rbrace , \] where $\Lambda _0$ is the spectrum of the Lebesgue measure supported on $[-t-1,-t]\cup [t,t+1]$. Our result answers some questions raised by Lai, Liu and Prince [JFA, 2021].

To investigate the influence of rotational speed and drilling pressure on the milling efficiency of flat-bottomed milling shoes, a three-dimensional milling model of flat-bottomed milling shoes and deformed casing was established by using ABAQUS finite element software, and the optimal parameter combinations of milling efficiency were investigated at rotational speeds of 70~90r/min and drilling pressures of 5~25kN. The results show that: with the increase of drilling pressure and rotational speed, the mass loss of casing and the amount of footage of the grinding shoe increase, and the grinding and milling efficiency is optimal under the process parameters of rotational speed of 90r/min and drilling pressure of 15kN. This paper provides an analytical method for the subsequent optimization and improvement of the evaluation of the pipe repair process and promotes the technological development of the research on the casing change mechanism and prevention and control countermeasures in shale gas wells.

Carbon sequestration refers to the technology of capturing carbon and storing it safely instead of directly discharging CO2 into the atmosphere. Rock salt is a promising CO2 reservoir, and the underground rock salt structure formed by salt cavern reservoirs in geological history has a natural sealing function. Storing carbon dioxide in salt caves can ensure that carbon dioxide is stably stored underground for a long time. However, at present, there are few studies on carbon sequestration in abandoned salt caves. This study analyses the characteristics of carbonate-evaporite strata in the high fold zone of eastern Sichuan and qualitatively evaluates Triassic carbonate-evaporite layers formed in the depth range of 800-3000 m in various sedimentary basins in Chongqing. A large set of carbonates-evaporites are developed in Chongqing, and the carbonate rocks near evaporites have low porosity and permeability, which can be used as CO2 storage caprock in salt cavities. Thick evaporated strata can also provide a good cover for CO2 storage in abandoned salt caves, which has great potential space resources.

ABSTRACTTo understand the influence of corrosion and fracturing of prestressed steel on structural deformation, accelerated corrosion testing was carried out using a self-made test beam and applying DC power. Distributed optical fibre sensing technology based on pulse prepumped Brillouin optical time-domain analysis (PPP-BOTDA) was used to monitor the deformation of the prestressed concrete beam in the process of corrosion and fracture in real time. The finite-element model of local corrosion fracture of prestressed steel is established, and the monitoring results are verified based on various corrosion fracture simulation methods. The results show that when the sensing optical fibre pasted on the beam is less than 150 mm from the prestressed steel, the significant change of concrete strain when the steel breaks can be monitored and the fracture location can be determined at the same time. However, when the distance is greater than 150 mm, the change in monitoring data with the strain is not obvious. The distributed optical fibre sensing technology has high monitoring efficiency and abundant measurement data, and the underwater environment does not affect the transmission of monitoring data. This technology is applicable to the deformation monitoring of large prestressed concrete structures and could be widely used in practical engineering.

Rock cutting methods for disc cutters with coupled static–dynamic loads and static loads are explored and compared through rock breaking experiments to improve the TBM excavation efficiency. Results indicate that the rock breaking characteristics, including rock debris, cutting force, and rock breaking efficiency, significantly varies with different cutting methods. The average size of rock fragmentation produced under coupled static–dynamic loads is 1.6 times larger than that under static loads. The cutting forces of disc cutter under the coupled static–dynamic loads are larger than those under static loads when the cutting depth $(h)$ is lower than 4 mm, whereas is contrary when $h$ exceeds 4 mm. The specific energy of disc cutter under the coupled static–dynamic load is approximately 1.5 times smaller than that under the static load, indicating the cutting method with the coupled static–dynamic load can significantly improve the cutting performance. There is an optimal cutter spacing $(S)$ for the cutter under each cutting method. The optimal $S$ under the coupled static–dynamic loads is larger than that with static loads. This study provides new insights into improving the tunneling efficiency in high-strength rock conditions.

Ply wrinkles in CFRP laminates are common and can lead to significant failure in composite structures if not properly assessed during the design, manufacturing, and service phases. Evaluating wrinkle geometries can be difficult as they are influenced by multiple factors, such as asymmetry, wavelength, and amplitude, which impact the structure's mechanical performance. High-frequency eddy current testing has proven effective for detecting in-plane waviness and out-of-plane wrinkles. However, the complex nature of CFRP structures and electrical anisotropy may hinder the effectiveness of an eddy current in-line monitoring system if not taken into account. In this study, an advanced modelling approach is employed to simulate the structural variation of the conductivity tensor. A designated wrinkle area, characterized by reduced electrical conductivity, is integrated with structural modelling to replicate a realistic coupon sample containing a wrinkle defect. Four proposed configurations are used to virtually test the samples, and their detection capabilities are analyzed quantitatively.

In recent years, pre-made food has become more and more popular in the market; thus, its revenues account for a huge part of the whole food market, especially in China, which accounts for one-third of the Asian food market. Therefore, the crux of this paper is to analyse the situation of the pre-made food industry and discover its market shares, product category and target population. Besides, this paper mainly focusses on Anjoy Foods Group Co., Ltd., which is a leading pre-made food enterprise in China, and finds its superior elements. Consequently, it shows that Anjoy Foods has excellent financing performance and multiple marketing methods to promote its product. At the final, this paper mentioned several suggestions that pre-made food merchants and the government can implement. For example, they can diversify products to satisfy more detailed requirements, improve technology to upgrade products’s taste and nutrition, and enhance food safety supervision to dispel customers’ concerns about food safety hazards.

Strain zp-2095, a moderately halophilic bacteria, was isolated from the rhizosphere soil of Suaeda glauca plant, in the Aiding lake, Xinjiang, China. Molecular identification result indicated strain zp- 2095 is a member of Marinobacter. It could dissolve organophosphorus and produce amylase and cellulase. Strain zp-2095 has the function of fixing nitrogen which is helpful for plant through maintaining nitrogen in the soil. Siderophore, which can enhance the plant's absorption of iron, was produced by strain zp-2095. The results of petri dish growth promotion experiments indicated strain zp-2095 markedly increased the lateral root number of tomato under varying saline-alkali stress (p

Lancea tibetica is a valuable medicinal herb uniquely found in the Tibetan plateau. The photosynthetic pigments within its leaves are one of the indispensable substances for photosynthesis. However, The Tibetan plateau is one of the regions with the most intense solar radiation in the world. It has extreme solar radiation conditions. These extreme solar radiation conditions have multiple effects on local ecological conditions. In this study, the absorption spectrum of wild and laboratory Lancea tibetica leaves was observed using equipment like a spectrometer, followed by analyzing its characteristics. The results show that short-wavelength solar ultraviolet radiation has considerable small energy penetrating through plant leaves, and most of the energy is reflected by leaves or only a small proportion of energy is absorbed. Within the visible solar spectrum, most of the energy of the purple and indigo light is absorbed by leaves, with the absorbance of carotenoids being 0.731 at the maximum absorbent peak of 470nm. The transmitted intensity of the solar spectrum at this point is 0.38W·m -2·nm -1, accounting for an absorption of nearly 81.42%. In the green light spectrum, the transmitted intensity is relatively high given the leaves’ ability to retain the stability of their systems. The absorption of chlorophyll a and b is mainly concentrated in the red-light part, with transmitted intensity at 665nm and 649 nm being 0.80W·m -2·nm -1 and 0.34W·m -2·nm -1 only, playing a significant part in photosynthesis. The near infrared spectrum mainly consists of solar thermal energy, and the leaves of Lancea tibetica absorb less thermal radiation compared with ultraviolet and visible spectra.

Fusarium oxysporum is a serious pathogenic fungus that can cause peanut root rot, leading to reduced peanut yield, plant death, and severely hindering the development of agriculture and economy in peanut cultivation region. This study isolated a large number of bacterial strains from soil samples of wild plants such as Suaeda salsa, Tamarix, and Phragmites australis in the Aydingkol Lake area of Xinjiang, and evaluated their biocontrol and capability of promote plant growth. Finally, an actinomycete strain A537 was isolated and screened from the non-rhizosphere soil of Suaeda salsa. The sequencing results of 16s RNA indicate that A537 belongs to the genus Streptomyces. The plate confrontation assay showed that strain A537 has a wide antifungal spectrum and has certain antagonistic activities to various plant pathogens such as Fusarium oxysporum, Fusarium solani, Diplodia gossypina, Fusarium equiseti, Fusarium acuminatum, Verticillium dahlia, Rhizoctonia cerealis, Fusarium pseudograminearum and Fusarium graminearum. In addition, in vitro evaluation of PGP traits showed that strain A537 has the capability of phosphate solubilization, IAA production, siderophore production, ACC deaminase production and cellulases production. Different concentrations of culture filtrate of strain A537 have a certain antagonistic activities on Fusarium oxysporum, with an inhibition rate of 76.54 ± 6.79%. The results indicate that strain Streptomyces sp. A537 has the potential for biological control and growth promotion, and can be used as a novel biocontrol agent against peanut root rot.

The rapid popularity of short video platforms has provided new ways for the dissemination of educational content. This study aims to explore the impact of WeChat channels on primary school students’ English reading ability. Technology has expedited the growth of online education and video-based learning, with WeChat channels becoming one of the most widely used venues for students in China to share videos. With the assistance of parents, teachers, schools, and government education sectors, WeChat channels have the potential to play a more significant and positive role in the English learning field in the current era. The research results show that WeChat channels have developed into a vital video platform for students to find helpful English learning materials. The purpose of this study is to examine the effects, both good and negative, of the quickly evolving video platforms on primary school students’ English reading abilities in order to provide a basis for further research.

As International Atomic Energy Agency has stated in its Handbook on Nuclear Law, "Even in situations for which the highest standard of safety has been achieved, the occurrence of nuclear accidents cannot be completely excluded." Therefore, the international legal framework for nuclear damage compensation liability has been evolving since the establishment of Nuclear Energy Agency of Organization for Economic Co-operation and Development (OECD NEA) and International Atomic Energy Agency (IAEA). Over the years, various international treaties have been enacted to address the compensation of nuclear damage and to establish liability regimes for nuclear incidents. To date, these treaties have established a series of legal principles of nuclear damage liability, such as the sole liability principle, the strict liability principle, the financial guarantee principle etc., which have been developing since establishment. This paper offers an overview of the historical development of the principles of these international treaties for nuclear damage liability and thus draws upon both primary and secondary sources, including treaties, official documents, academic literature, and reports by international organizations. The paper reveals that with the awareness of protecting public's rights having been significantly strengthened, the range of compensation has been broader, the matters of immunity from liability for operators of nuclear power plants have been reduced, the limitation of the compensation amount has been higher etc. In conclusion, the international legal regime for nuclear damage liability has been showing a shift from protecting the development of the nuclear industry to a joint protection of both public health and rights and the nuclear industry.

The evaluation and management of sustaining casing pressure (SCP) in injection/production wells of underground gas storage(UGS) is an important part of the wellbore integrity. SQ underground gas storage has experienced ten complete injection/production cycles, which puts forward high requirements on management of well integrity. At present, there are different degrees of SCP of injection/production wells of SQ UGS, which seriously threatens the safety of the UGS. This paper analyzes casing pressure in different injection/ production stages and working conditions of injection/production wells, combined with API RP 90-2, NORSOK, ISO/TS 16530-2, SY/T5724-2008 standards. We established an SCP evaluation process and a static and dynamic SCP risk evaluation system, and then proposed a four-level risk control mode for UGS injection/production wells. We formulated a production management method for wells with SCP, constantly improved the operating environment of UGS wells. We managed the injection /production wells with SCP higher than the MAWOP, especially the annular leak problem of well S7. The SCP treatment achieves effective plugging, guarantees the integrity of the injection /production wells, and achieves good repair effect, which has certain guiding significance for the evaluation of the integrity of the injection/production wells of the UGS and the management of the SCP.

In order to improve the annual average optical efficiency of a tower solar power plant, a simulated heliostat field layout optimization model is constructed using ray tracing method to calculate the shadow shading efficiency. is constructed using ray tracing method to calculate the shadow shading efficiency. Genetic algorithms are used to encode the variables such as solar pitch angle, solar azimuth angle, and coordinates of heliostat mirrors in chromosomal individuals in binary regions, and to find the near-optimal solutions in iterative populations through the use of ray tracing method. Simulation results show that the model can significantly optimize the layout of the tower solar power system. Simulation results show that the model can significantly optimize the layout of the tower solar power plant and improve the annual average optical efficiency. neighboring heliostats is at 0.398 times the sum of the length and width, the optical efficiency of the Khi Solar One power plant reaches 61.83%, which is an improvement of 15.74% compared to that of the Khi Solar One power plant. improvement of 15.74% compared to this engineering example.

In recent years, the combination of building information model (BuildingInformationModeling, BIM) and vision technology has been widely used in the field of engineering construction, especially in the application of complex foundation pit engineering has shown great potential. Due to the complexity of the underground environment and the difficulty of construction, the complex foundation pit engineering puts forward higher requirements for the design, construction and management. This paper mainly discusses the engineering, aiming to improve the construction efficiency, improve the engineering quality and ensure the construction safety.

Since the inception of the smart city concept, it has garnered widespread attention. This paper elucidates the concept of smart city construction, focusing on the case study of China Communications Construction’s Future City. It analyzes its development positioning, vision, and trends, and conducts an integrated analysis of its construction and management based on the City Information Model (CIM). Furthermore, it proposes the development direction of “Future City by China Communications Construction” in smart city construction, aiming to contribute to the construction of innovative smart cities.

Tourism has emerged as a vital driver for global economic growth and development. However, amidst the relentless pursuit of tourist arrivals and financial gains, there is growing recognition of the importance of prioritizing quality over quantity in tourism development. This study explores the concept of new quality productive forces and their implications for achieving high-quality development within tourism. It examines the multifaceted dimensions of new quality productive forces, including innovation, efficiency, and sustainability, and elucidates the transformative potential of new quality productive forces in reshaping the tourism operating and fostering long-term economic resilience and sustainability.

Urban trees contribute to decarbonisation. However, the removal of trees may release the stored carbon within them. In Hong Kong, Acacia confusa and Leucaena leucocephala are being removed, but with unknown carbon impacts. This industry-academia-government collaborative research aimed to: (1) report the amount of carbon stored inside Acacia confusa and Leucaena leucocephala harvested from slopes; (2) estimate the carbon storage of a tree using dendrometric measurements; and (3) explain the variation in carbon content percentage of urban trees with respect to tree species, part of the tree, and position within the part. 10 Acacia confusa and 10 Leucaena leucocephala were harvested during March–September, 2023. Each tree was weighed for carbon storage estimation. Results showed that Acacia confusa had higher mean wood volume, biomass and carbon storage than Leucaena leucocephala. The mean carbon content of the analysed samples (45.53−52.58%) were mostly significantly different from 50%. But the difference may become insignificant depending on how volatile carbon loss was controlled. Diameter at breast height (mm) was a significant predictor of carbon storage (kg) for both Acacia. confusa (β = 0.9574) and Leucaena leucocephala (β = 0.3909). Significant interaction between tree species and tree part on carbon content percentage was confirmed. This research demonstrated the impacts of past arboricultural decisions on present decarbonisation plans.

Jingzhu (JZ) is a newly cultivated subshrub-like herbaceous plant with a dense cuticle and complex cell walls covering its outer surface (which can affect the efficiency of chemical impregnation in pulping and papermaking processes). Cellulase hydrolyzes cellulose to glucose and it is an effective way to break the surface permeability barrier. In the present research, we characterized the effects of different cellulase doses on the enzymatic products and microstructures of JZ. Based on the ion chromatography and UV spectrophotometry results, an increase in cellulase dosage promoted the solubilization of lignin and five monosaccharides. Scanning electron microscopy (SEM) and scanning electron microscope-energy dispersive X-ray spectroscopy (SEM-EDS) indicated cellulase promoted exfoliation of the stratum corneum on the JZ surface, decreasing surface silicon content. X-ray diffraction (XRD) indicated cellulase hydrolyzes more vigorously at higher dosages within a certain range. These results demonstrated that using cellulase before pulping could disrupt the external structure of the raw materials, providing favorable conditions for the penetration of chemicals. This study provides a theoretical reference for the pulp and paper industry to develop new non-wood raw materials for pulp and paper.

In present work, Fields Activated Sintering Technology (FAST), has been applied to successfully sinter the high-entropy alloy (HEA) samples. Based on the analysis of the microstructure, relative density and microhardness of the sintered HEA samples, the influence of sintering temperature and pulsed magnetic field treatment (PMT) has been investigated. In terms of performance, HEA samples fabricated using PMT-powder sintering exhibit superior properties compared to UT-powders. Regarding elemental distribution, pre-treating the powders with a pulsed magnetic field can enhance the uniformity of the alloyed powder components. Furthermore, elevated sintering temperatures have been observed to substantially accelerate the densification process, thereby improving the relative density of the sintered samples.

This paper reports the study of the process chain for sheet metal forming using multi-point tooling for stamping at elevated temperatures and developing a complete production line integrating heating, intermediate fast-cooling, forming and aging. It aims to deliver a high-efficient and cost-effective sheet-metal forming technology with improved process capability and flexibility for the forming of high-strength sheet metal parts. Multi-point tooling sets are employed to test the flexibility of hot/warm-forming the lightweight high-strength metal sheets with fast tooling reconfigurability. The intermediate cooling with high cooling rates was achieved with a contact cooling system recently developed at the University of Strathclyde. With this pilot line, the aluminium sheets heated to the solution heat treatment (SHT) temperature were subjected to the intermediate cooling prior to forming with multi-point tooling. The cooling step is fast and controllable, with different cooling rates tested. The tests conducted on the pilot line demonstrated significant enhancement of the forming limit and manufacturing flexibility.

Pulsed magnetic field treatment, as a novel, quick and environmentally friendly post-processing approach can directly modify the coated tools without causing damage. This study examined the wear performance of the TiAlSiN-coated cemented carbide block specimens treated by the pulsed magnetic fields in both dry friction and cutting fluid friction. The findings show that TiAlSiN coating block specimens subjected to pulsed magnetic fields exhibit better wear resistance in both friction conditions. The wear rate of the coating decreases by 21.49% in a dry friction environment, and the friction process becomes more stable while the wear width of the coating decreases by 4.60% in the cutting fluid friction environment. In addition, the nano-indentation tests show that the hardness and elastic modulus of the coating increases by 6.58% and 5.64%, and the coating binding force increases by 15.27% after the treatment.

The hybrid photovoltaic/thermoelectric generator (PV/TEG) technology is an advanced and efficient technology that combines the power from PV and TEGs to generate sustainable electricity. This hybrid approach optimizes energy output and ensures cleaner power by connecting IoT devices. Comprehensive studies have been conducted in the past to improve the efficiency of TEG modules. Various material parameters of TEG legs, such as the Seebeck coefficient, thermal conductivity, and electrical resistivity, and geometric parameters, including the cross-sectional area, leg size, leg height and the number of leg pairs, influence the TEG characteristic and determine with this the performance of the hybrid system. This work explores the influence of the TEG leg lengths and numbers of TEGs at various weather conditions on the power generation of a hybrid PV/TEG device, using an analytical model verified by experiments. The paper also analyses the performance characteristics of TEGs along with the hybrid PV/TEG system and concludes that the maximum output power from the TEG module in the hybrid PV/TEG model can be achieved by increasing the leg length.

Wind energy, as renewable energy, is critical in targeting carbon neutrality or net zero emissions in order to address global climate change. Compared with onshore wind turbines, offshore wind turbines enjoy generally higher wind speed, thus producing more electric energy. However, the harsh marine environment, including high winds, wave-induced vibrations and and sea and rain corrosion and erosion, can lead to structural damage, reduced operational efficiency and increased maintenance cost. This paper presents a novel Internet of Things (IoT) platform for structural health monitoring (SHM) of the offshore wind turbine’s key component, the wind turbine blades. This research focuses on developing a comprehensive, real-time monitoring system that utilises advanced sensor networks, edge computing, and advanced predictive algorithms to strengthen on-time maintenance of turbine blades, while avoiding unnecessary and costly regular maintenance.

The project M2DESCO is directed at addressing new challenges for developing next-generation high-entropy-alloy-based multi-component green (free of toxic substances) and sustainable (rare earth free & minimum critical metal elements) coatings with predictable functionalities, performance and life - aiming at increasing wear resistance by 100%, corrosion/oxidation resistance by 50~60 %, and effectively reducing the criticality of coating materials by at least 70%. To achieve these goals, the project is to integrate artificial intelligence/machine learning AI/ML underpinned, highly effective and highly efficient Computational Modelling that is guided by a novel Safe and Sustainability by Design Framework and facilitated by high-throughput characterisations and evaluations, to speed up the material-design to coating-product development process (reducing the development cycle-time by 400~500%). At the same time, M2DESCO is to enable optimal alloy/material design and coating process optimisation for high efficiency and high quality, so to reduce the overall product manufacturing cost (due to use of the new tooling developed) by 20%. The advancement of M2DESCO will contribute significantly to combating the loss in EU region caused by corrosion and wear, to the enhancement of the global profile and leadership of the EU material modelling/research community, to strengthening of the innovation capability of the EU coating industry/business.

This paper focuses on a ‘cloud infrastructure’ (MTaaS) that has been developed to support and coordinate integrated services and supply chain management. This will enable the seamless operation of a dynamic and adaptive system providing customer-centred material testing services. The cloud system is designed not only for decision making regarding the evaluation of the situations brought by industry and translating them into upscaling, characterisation and service workflows, but also for promoting existing products, improving facility usage and providing expertise consultancy. The development of MTaaS involves specifying the cloud infrastructure requirement, defining the back-end and front-end system architecture and modules, and outlining the operation fields of each module along with associated terminology, parameters and contents. This includes handling material testing service registration, verification, marketing, composition, preparation, offering, processing, monitoring as well as customer inquiries, monitoring and feedback. These efforts make MTaaS integrate product, service and customer-related information into a single platform, encompassing necessary operation related data, customer related data, inventory data and supply chain data.

The plastic injection moulding process is a critical manufacturing technique renowned for its high productivity, cost-effectiveness, and ability to produce intricate plastic components for various industries including medical and aerospace. The quality of the manufactured parts is influenced by several parameters, such as machine settings and mould characteristics, particularly thermal aspects. This paper specifically investigates the influence of primary machine parameters on part quality, excluding considerations of time, mould features, and cooling channel geometries. By focusing on the machine parameters and employing advanced machine learning methods, a comprehensive understanding is developed on how these factors can be utilised to predict the quality of the parts produced. The findings provide valuable insights into optimising the injection moulding process to enhance product quality and consistency.

The paper reports an investigation into two rapid sheet metal cooling designs that are suitable for applications in hot-stamping production -air cooling and contact cooling, aiming at improving formability of the high-strength aluminium sheets for the forming of components with complex geometries with enhanced overall process efficiency. The investigation involved both numerical modelling and experimental trials using an in-house developed prototype cooling tools. A series of contact cooling experiments were conducted, considering process variables such as initial blank temperatures, cooling die temperatures, die materials, surface conditions, etc. The results demonstrated that the cooling rate of the aluminium blank could be accurately controlled by both methods with appropriate pre-setting of the equipment and control of the process parameters. The integration of the cooling system into a polit hot-stamping production was also tried, considering industry-scale applications related factors. The results can serve as a design guidance for an industry to introduce such cooling methods and manufacturing facilities.

Field-Assisted Sintering Technology (FAST), an advanced consolidation technique, was employed to synthesise low-temperature thermoelectric n-type Bi2Te2.7Se0.3 for energy harvesting applications. A systematic investigation of sintering parameters, including pressure, temperature, holding time, and heating rates, was conducted to optimise the material’s properties. Post-sintering characterisation encompassed measurements of relative density, thermal conductivity, electrical resistivity, and Seebeck coefficient. Factor analysis revealed the hierarchical influence of sintering variables, with temperature emerging as the most critical parameter, followed by pressure and holding time. The study successfully identified optimal FAST sintering conditions for Bi2Te2.7Se0.3, resulting in enhanced thermoelectric properties. This research demonstrates the efficacy of FAST in producing high-quality, low-temperature thermoelectric materials and provides valuable insights into the relationship between processing parameters and material performance.

Femtosecond laser nanomachining represents a frontier in precision manufacturing, excelling in micro-and nanopatterning across diverse materials. However, its wider adoption is hindered by unintended surface damage or modifications stemming from complex non-linear laser-material interactions. Moreover, traditional effective process optimisation effort to mitigate these issues typically necessitate extensive and time-consuming trial-and-error testing. In this scenario, machine learning (ML) has emerged as a powerful solution to address these challenges. This paper provides an overview of ML’s contributions to making femtosecond laser machining a more deterministic and efficient technique. Leveraging data from laser parameters and both in-situ and ex-situ imaging of processing outcomes, ML techniques—spanning supervised learning, unsupervised learning, and reinforcement learning—can significantly enhance process monitoring, process modeling and prediction, parameter optimisation, and autonomous beam path planning. These developments propel femtosecond laser towards an essential tool for micro-and nanomanufacturing, enabling precise control over machining outcomes and deepening our understanding of the laser machining process.

In this study, we performed electric pulse treatment (EPT) on the cold-deformed 316L stainless steel. The effects of EPT on the temperature rise characteristics, tensile properties and microstructure of cold-deformed 316L SS were investigated. The results show that changes in current density have a significant effect on the surface temperature and tensile properties. Compared with the UT samples, at a current density of 44 A/mm2, the elongation after fracture reached a peak of 39.8% (the enhancement rate is 14.4%), while the ultimate tensile strength of all the EPTed samples shows no significant change. Interestingly, although the sample experienced an increase in temperature during the EPT process, the phase composition and grain structure remained unchanged significantly. This implies that the improvement in the ductility of the samples may be attributed to the reduction of micropores. The present research provides new light to the enhancement of ductility of cold-deformed 316L stainless steel.

The IN738 nickel-based superalloy has a high Al, Ti and γ’ (Ni3 [Al, Ti]) content phase that causes notable crack sensitivity when processed by laser powder bed fusion (LPBF). After examining the effects of Ti and Co on the microstructure and mechanical properties of IN738 alloy processed by LPBF, this research revealed that a moderate decrease in Ti content and an increase in Co content resulted in a wide range of processing parameters to obtain crack-free LPBF specimens. The samples were treated by different heat-treatment processes and then investigated by scanning electron microscopy (SEM). The newly designed IN738G exhibited an excellent combination of tensile strength (1253.5 MPa) and elongation (16.37%) compared to the IN738 alloy (1115.7 MPa, 6.99%) under room-temperature conditions.