Large Number Research Articles

Research on the Application of Slant Hole Grouting Process in the Undermining Hollow Area of Urban Main Road

China has a huge number of underground goaf, when the new city main road crosses the goaf, a large number of non-migratable buildings may be left on the ground due to economic problems, resulting in the goaf does not have the condition of vertical drilling and grouting, so the slant hole grouting technology is of great significance in research. In this paper, we take a city main road under construction in Changchun City as an example to study the application of slant hole drilling grouting in the hollow area, and hope that it can provide reference examples for similar projects.

Estimates of Air Pollutant Emissions by Vehicle Fleet in the State of Pará, Brazil: Impacts and Trends

Objective: aims to estimate emissions of the main atmospheric pollutants from vehicular sources in the state of Pará, to continue the environmental agenda of monitoring air quality. Theoretical Framework: The growing global concern about air quality in urban areas is driven by the environmental and public health impacts caused by air pollution. The concentration of pollutants from vehicle sources represents one of the main challenges, especially in densely populated regions such as the capital and other major cities in the state of Pará, where the automotive fleet has increased significantly. Method: The methodology used combined "bottom-up" and "top-down" methods to calculate emissions of carbon monoxide (CO), nitrogen oxides (NO) and total hydrocarbons (HC) for different vehicle categories and fuel types. Data on licensed vehicle fleets and fuel consumption obtained from DETRAN-PA and ANP were used. Results and Discussion: The results revealed that gasoline-powered vehicles are responsible for the majority of CO and HC emissions, while diesel vehicles emit the largest amounts of NO into the atmosphere. Motorcycles were identified as the largest source of emissions due to their larger number in the circulating fleet. Our results also highlight the importance of assessing and monitoring vehicle emissions to develop effective air pollution control strategies. Research Implications: The information obtained in this study is unprecedented for the study area, and can therefore support the formulation of environmental policies aimed at reducing emissions of atmospheric pollutants in the state of Pará, thus promoting an improvement in air quality and public health. Originality/Value: This paper makes an unprecedented contribution to national and international literature on environmental pollution in large urban centers. On the eve of the largest climate and environment conference on the planet (COP30) to be held in Pará, Amazonas, this research joins efforts in relation to the monitoring, forecasting and mitigation of air pollution, considered one of the main environmental problems of today.

A Deep Learning Application of Capsule Endoscopic Gastric Structure Recognition Based on a Transformer Model.

Gastric structure recognition systems have become increasingly necessary for the accurate diagnosis of gastric lesions in capsule endoscopy. Deep learning, especially using transformer models, has shown great potential in the recognition of gastrointestinal (GI) images according to self-attention. This study aims to establish an identification model of capsule endoscopy gastric structures to improve the clinical applicability of deep learning to endoscopic image recognition. A total of 3343 wireless capsule endoscopy videos collected at Nanfang Hospital between 2011 and 2021 were used for unsupervised pretraining, while 2433 were for training and 118 were for validation. Fifteen upper GI structures were selected for quantifying the examination quality. We also conducted a comparison of the classification performance between the artificial intelligence model and endoscopists by the accuracy, sensitivity, specificity, and positive and negative predictive values. The transformer-based AI model reached a relatively high level of diagnostic accuracy in gastric structure recognition. Regarding the performance of identifying 15 upper GI structures, the AI model achieved a macroaverage accuracy of 99.6% (95% CI: 99.5-99.7), a macroaverage sensitivity of 96.4% (95% CI: 95.3-97.5), and a macroaverage specificity of 99.8% (95% CI: 99.7-99.9) and achieved a high level of interobserver agreement with endoscopists. The transformer-based AI model can accurately evaluate the gastric structure information of capsule endoscopy with the same performance as that of endoscopists, which will provide tremendous help for doctors in making a diagnosis from a large number of images and improve the efficiency of examination.

Phytochemistry and Pharmacological Activity of Malva sylvestris L: A Detailed Insight.

Malva sylvestris L., is commonly referred to as Mallow and is found in Europe, Asia and Africa. This has been traditionally used for inflammation, gastrointestinal disturbances, skin disorders, menstrual pains, and urological disorders. This review covers phytoconstituents and Pharmacological activities of M. sylvestris. The plant contains a large number of phytochemical constituents having diverse pharmacological activities. The plant contains many phenolic compounds responsible for its strong antioxidant activity. Coumarins from Mallow have a potential anticancer activity. Malva sylvestris also contains essential as well as non-essential elements and minerals. Many researchers have provided evidence that Malva sylvestris is a good candidate for use as a medicinal herb and has good nutritional value. The leaves, in particular, offer properties like anticancer, skin whitening, and anti-aging. Furthermore, the aqueous extract was recently shown to have an anti-ulcerogenic effect. Malva sylvestris has a high potential for use in cosmetics such as skin whitening and anti-aging treatments. Methanolic extracts of Malva sylvestris leaves, and flowers showed strong antibacterial activity against a common plant pathogen bacterium. The plant also contains Malvone A, which is responsible for antibacterial action. The plant also possesses anti-inflammatory, analgesic, wound healing properties and various other activities.

Turbulent characteristics of momentum flux in the marine atmospheric boundary layer of North Bay of Bengal

We use a 16-month-long, 20 Hz wind data from a mooring deployed in the Bay of Bengal (BoB) to study the characteristics of turbulent wind stress (u′w′)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${u}{\\prime}{w}{\\prime})$$\\end{document} events in the marine atmospheric boundary layer (MABL). Quadrant analysis of the motion-corrected u′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${u}{\\prime}$$\\end{document} and w′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${w}{\\prime}$$\\end{document} suggests that sweep and ejections, representing downward stress transfer into the ocean, dominate the u′w′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${u}{\\prime}{w}{\\prime}$$\\end{document} (~ 140%). In comparison, outward and inward interactions representing an upward stress transfer into the atmosphere provide the counter-contribution (~ 40%). We found a wind speed (ws) dependency on stress transfer for ws > 3 m/s, while for low ws, the swell-dominated ocean state modulates the u′w′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${u}{\\prime}{w}{\\prime}$$\\end{document} with a significant reverse stress transfer into the atmosphere, especially during intermonsoon periods. It is found that for weak winds (ws\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ws$$\\end{document}< 3 m/s), the number of turbulent events (N) is less, but they frequently repeat with more considerable flux per event (f^)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\widehat{f})$$\\end{document}, with outward and inward interactions (sweeps and ejections) dominating during intermonsoon periods (monsoon periods). For medium to strong winds, sweeps and ejections dominate u′w′.\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${u}{\\prime}{w}{\\prime}.$$\\end{document} Ejections are found to be the most efficient method of stress transfer in the BoB, contributing 80% of u′w′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${u}{\\prime}{w}{\\prime}$$\\end{document}, compared to sweeps contributing ~ 60% and interaction processes contributing ~ − 20% each to the u′w′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${u}{\\prime}{w}{\\prime}$$\\end{document}. Though the duration of sweep events is larger than ejections and with comparable flux energy per event (f^\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\widehat{f}$$\\end{document}), the larger number N of ejection events makes it the dominant stress transfer mechanism in the Bay in all seasons.

Abstract B102: Impact of previous genetic counseling and reaction to genetic test results among Hispanic/Latino colorectal cancer patients in ENLACE: A cancer Moonshot study

Abstract Background: Inequities in access to genetic testing exist among Hispanic/Latino (H/L) individuals, a population disproportionately affected by colorectal cancer (CRC) burden. Past studies demonstrate the value of genetic counseling (GC) on improving patient understanding of genetic testing utility, but few studies have focused on H/L individuals. Therefore, we assessed the impact of having prior-GC on genetic testing knowledge among patients enrolled in the ENLACE study, a NCI-Moonshot-funded study of participant engagement in genomic characterization among H/L CRC patients. Methods: The ENLACE study enrolled participants from two healthcare facilities since 2022: Los Angeles General Medical Center (LA Gen, a safety-net hospital) and USC Norris Comprehensive Cancer Center (Norris, a university medical center). Baseline surveys to assess sociodemographic characteristics, genetic literacy and comprehension (GLAC), and genetic knowledge (KnowGene) were evaluated. Following somatic and germline return-of-results (ROR), Feelings About genomiC Testing Results (FACToR) for germline sequencing, the impact of somatic testing on cancer patient knowledge, attitudes, and expectations, and Decisional Regret for genomics research participation were evaluated. Results: A total of 105 H/L CRC participants completed surveys at baseline, and 39 post ROR. Most were recruited at LA Gen (n = 72), are male (n = 56), and Mexico-born (n = 55). Fifty participants (33, LA Gen; 17, Norris) had GC prior to study enrollment. No difference was found in the sociodemographic characteristics of participants with prior-GC by facility (p = 0.24). When stratified by prior-GC and facility there were no differences in GLAC and KnowGene scores, using univariate analysis (all p-values &amp;gt; 0.05). Post-ROR total FACToR score, which ranges from 0-48 with higher scores indicating greater functional impairment, was low with a median of 11 (IQR = 5.0-23.0) and no differences were seen for prior-GC or without (p = 0.2). Participants had low decisional regret with a median score of 2.5 (IQR = 0-25.0), on a 0-100 scale. When examining opinions about genetic testing in cancer care, 84% (n = 33) of patients agreed or strongly agreed that genetic testing based on today’s technology would significantly improve their cancer treatment and care. Conclusion: There was no association with prior-GC and baseline genetic knowledge scores. Post-ROR, the cohort had low functional impairment and decisional regret from genetic testing, suggesting that these H/L patients have a favorable reaction to their genetic test results. A limitation of this evaluation is that it does not consider the effect of GC during ROR, completed for some patients, on post-ROR responses. As the study progresses, larger numbers will allow us to stratify by germline test results and dosage of GC. These findings support the need for impactful genetics education tools and communication methods to ensure greater understanding of genetics for H/L individuals to maximize genetic testing utility. Citation Format: Natalia Gutierrez, Joel Sanchez Mendez, Julie O. Culver, Charite R. Ricker, Carmen Chavez, Lucia Enriquez, Sandra Algaze, John D. Carpten, Heinz-Josef Lenz, Mariana C. Stern. Impact of previous genetic counseling and reaction to genetic test results among Hispanic/Latino colorectal cancer patients in ENLACE: A cancer Moonshot study [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B102.

Beyond the 95s: What happens when uniform program targets are applied across a heterogenous HIV epidemic in Eastern and Southern Africa?

The UNAIDS 95-95-95 targets are an important metric for guiding national HIV programs and measuring progress towards ending the HIV epidemic as a public health threat by 2030. Nevertheless, as proportional targets, the outcome of reaching the 95-95-95 targets will vary greatly across, and within, countries owing to the geographic diversity of the HIV epidemic. Countries and subnational units with a higher initial prevalence and number of people living with HIV (PLHIV) will remain with a larger number and higher prevalence of virally unsuppressed PLHIV—persons who may experience excess morbidity and mortality and can transmit the virus to others. Reliance on achievement of uniform proportional targets as a measure of program success can potentially mislead resource allocation and progress towards equitable epidemic control. More granular surveillance information on the HIV epidemic is required to effectively calibrate strategies and intensity of HIV programs across geographies and address current and projected health disparities that may undermine efforts to reach and sustain HIV epidemic control even after the 95 targets are achieved.

Calculator for predicting the probability of faculty promotion in an academic medical centre

ObjectiveThe academic medical centre (AMC), with over 2200 faculty members, annually manages approximately 300 appointments and promotions. Considering these large numbers, we explored whether machine learning could predict the probability...

An adjustable vane-shaped nozzle-based modulated pre-swirl system for gas turbine aero-engine: Structure parameters and aerodynamic performance analysis

The pre-swirl system of an aero engine provides cooling air with suitable temperature and pressure for turbine blades, rarely contributing to thrust. However, the traditional pre-swirl system with a fixed geometry leads to significant wastage of cooling air during part-load conditions, such as subsonic cruising, resulting in a decrease in engine performance. Unlike the existing approach, which uses valves to close a part of the pipeline, a novel modulated pre-swirl system based on the adjustment of the vane-shaped nozzle is proposed to overcome the flow nonuniformity in the circumferential air supply. The effects of the number of pre-swirl nozzles and receiver hole parameters (number, length, and structure) on the system performance are discussed in design and subsonic cruising conditions. The results demonstrate that increasing the number of pre-swirl nozzles significantly improved the flow adjustment efficiency and performance of the modulated pre-swirl system. A larger number and shorter length of receiver holes resulted in a higher system temperature drop in both design and subsonic cruising conditions. With regard to the configurations of the receiver holes, the vane-shaped receiver hole exhibited optimal aerodynamic performance. Compared to the baseline case, the system with Np = 60, NRec = 60, lRec = 3 mm, and vane-shaped receiver hole showed a 27.6 % and 26.7 % improvement in the temperature drop efficiency in the design and subsonic cruising conditions, respectively.

Probabilistic Contrastive Learning for Long-Tailed Visual Recognition.

Long-tailed distributions frequently emerge in real-world data, where a large number of minority categories contain a limited number of samples. Such imbalance issue considerably impairs the performance of standard supervised learning algorithms, which are mainly designed for balanced training sets. Recent investigations have revealed that supervised contrastive learning exhibits promising potential in alleviating the data imbalance. However, the performance of supervised contrastive learning is plagued by an inherent challenge: it necessitates sufficiently large batches of training data to construct contrastive pairs that cover all categories, yet this requirement is difficult to meet in the context of class-imbalanced data. To overcome this obstacle, we propose a novel probabilistic contrastive (ProCo) learning algorithm that estimates the data distribution of the samples from each class in the feature space, and samples contrastive pairs accordingly. In fact, estimating the distributions of all classes using features in a small batch, particularly for imbalanced data, is not feasible. Our key idea is to introduce a reasonable and simple assumption that the normalized features in contrastive learning follow a mixture of von Mises-Fisher (vMF) distributions on unit space, which brings two-fold benefits. First, the distribution parameters can be estimated using only the first sample moment, which can be efficiently computed in an online manner across different batches. Second, based on the estimated distribution, the vMF distribution allows us to sample an infinite number of contrastive pairs and derive a closed form of the expected contrastive loss for efficient optimization. Other than long-tailed problems, ProCo can be directly applied to semi-supervised learning by generating pseudo-labels for unlabeled data, which can subsequently be utilized to estimate the distribution of the samples inversely. Theoretically, we analyze the error bound of ProCo. Empirically, extensive experimental results on supervised/semi-supervised visual recognition and object detection tasks demonstrate that ProCo consistently outperforms existing methods across various datasets.

Novel Aspects and Directions in Pest Control and Management - Proteins with Insecticidal Properties

Abstract: In addition to the economic losses because of insect pests, a significant part of insect pests can instantly lead to the deterioration and mildew of agricultural products, which all have great hidden hazards to human health. In view of insect pests, the principle means of control and prevention in China is spraying chemical agents. Nevertheless, spraying a large number of chemical factors to control insect pests for a long time will not only have a consequential impact on the ecological environment, but also make insect pests boost resistance, and because a large number of chemical residues on the surface of crops will also have an unfavourable impact on the human body. The detection and application of insecticidal proteins are of great significance for the progress of modern insecticidal science. This article studies the research progress of insecticidal proteins and considering their target pests, lists their common insecticidal utilization scenarios, and anticipates the development direction of insecticidal proteins in the future.

TAG: Teacher-Advice Mechanism With Gaussian Process for Reinforcement Learning.

Reinforcement learning (RL) still suffers from the problem of sample inefficiency and struggles with the exploration issue, particularly in situations with long-delayed rewards, sparse rewards, and deep local optimum. Recently, learning from demonstration (LfD) paradigm was proposed to tackle this problem. However, these methods usually require a large number of demonstrations. In this study, we present a sample efficient teacher-advice mechanism with Gaussian process (TAG) by leveraging a few expert demonstrations. In TAG, a teacher model is built to provide both an advice action and its associated confidence value. Then, a guided policy is formulated to guide the agent in the exploration phase via the defined criteria. Through the TAG mechanism, the agent is capable of exploring the environment more intentionally. Moreover, with the confidence value, the guided policy can guide the agent precisely. Also, due to the strong generalization ability of Gaussian process, the teacher model can utilize the demonstrations more effectively. Therefore, substantial improvement in performance and sample efficiency can be attained. Considerable experiments on sparse reward environments demonstrate that the TAG mechanism can help typical RL algorithms achieve significant performance gains. In addition, the TAG mechanism with soft actor-critic algorithm (TAG-SAC) attains the state-of-the-art performance over other LfD counterparts on several delayed reward and complicated continuous control environments.

Prenatal diagnosis of tracheo-oesophageal fistula/oesophageal atresia: is MRI helpful?

Oesophageal atresia (OA) with or without tracheo-oesophageal fistula (TOF) affects 2.75 per 10,000 births within the UK. It is most frequently suspected on antenatal imaging when the stomach is absent or appears small. Studies have shown fetal magnetic resonance imaging (MRI) has greater diagnostic accuracy than ultrasound; however, there remains uncertainty over what size constitutes a small stomach and how frequently this correlates with a diagnosis of TOF/OA. A retrospective study of patients referred for fetal MRI due to suspicions of TOF/OA on antenatal ultrasound from 2011 to 2022. We also included patients with a fetal MRI suspecting TOF/OA who had been referred for other reasons. The indication, MRI findings and postnatal outcome were compared to assess diagnostic accuracy. For each case, the size of the stomach bubble was measured on MRI, and stomach volumes in a control group were measured for comparison. The positive predictive value for USS was 45.5% and 51.7% for fetal MRI. Fetal MRI had a negative predictive value and sensitivity of 100% (p = 0.027). The control group showed a strong positive correlation between stomach size and increasing gestational age (R2 = 0.69, p < 0.001), but this correlation was less positive in the TOF/OA group (R2 = 0.26, p = 0.03), and the stomach volumes in TOF/OA were consistently lower than the control group. The receiver operating characteristic curve illustrates that an absent stomach or unmeasurably small stomach is more diagnostic of TOF/OA as volumes ≤0.06 ml had 90% sensitivity. Fetal MRI can accurately exclude TOF/OA but only has marginally improved positive predictive value over ultrasound. Research with larger numbers is required to further aid the development of a cut-off value for what can be considered a pathologically small stomach. There are several features on imaging that raise the suspicion of TOF/OA. Fetal MRI has some improved diagnostic accuracy compared with antenatal ultrasound alone; however, it is only marginally better. Absence of stomach bubble and presence of oesophageal dilatation combined on fetal MRI are more diagnostic of TOF/OA.

Endovascular Aortic Repair With the E-Tegra Device: Preliminary Outcomes From a Multicenter National Registry.

Endovascular aortic repair (EVAR) is currently expanding its feasibility thanks to design innovations, but hostile proximal necks and narrow iliac arteries are still a constraint, as expressed by the Instructions for Use (IFU) of most devices. Our aim is to report the preliminary results of the E-Tegra endograft in infrarenal abdominal aortic aneurysms (AAAs) performed in 15 high-volume centers. The e-Tegra Italian endoGraft REgistry (TIGRE) is a prospectively maintained database of consecutive EVAR with the E-Tegra stent-graft across 15 participating centers between March 2021 and March 2023. The registry records baseline clinical data, anatomic measurements of the abdominal aorta, perioperative and postoperative outcomes, with a scheduled follow-up period of 3 years for all patients. This is a preliminary analysis of the first results updated to January 2024. The primary endpoints are technical and clinical success, perioperative mortality, freedom from endograft rupture, and aortic-related mortality. The secondary endpoints are freedom from reintervention, and any type of endoleak (EL). The results were analyzed in relation with the anatomic characteristics of the AAAs, namely, iliac axes tortuosity and proximal neck hostility. The registry included 147 consecutive EVAR (138 elective and 9 in emergent setting), 7 of which were associated with an iliac branch implantation. Ninety patients had at least 1 criterion of anatomical hostility, and 25 were treated outside the device IFU. Primary technical success was achieved in 146 cases (99.3%) and assisted success in 147 (100%), with no perioperative mortality. After a median follow-up period of 20 months, no aneurysm-related mortality occurred. Reinterventions were 5: 2 for type IB EL and 3 for type II ELs with aneurysm sac increase. Five more type II ELs with aneurysm sac stability are under observation. No differences in terms of reinterventions were noted between aneurysms with standard and hostile anatomy. The E-Tegra endograft is safe and effective in treating AAAs with standard and hostile anatomy, with a low rate of complications and reinterventions, although longer-term outcomes and larger numbers are needed to compare its performances related to specific anatomic criteria. This multi-center nationwide Registry reports a real-world experience of EVAR performed with the E-Tegra abdominal endograft across 15 high-volume Centers, providing early- and mid-term device-specific results, which will help vascular surgeons in endograft selection. In particular, this study focuses on clinical results obtained in treating aneurysms with hostile anatomy, analyzing the performances of the E-Tegra endograft in cases of hostile proximal necks and narrow or tortuous iliac axes.

Stable Isotope Analysis and Chronology Building at the Hokfv-Mocvse Cultural Site, the Earliest Evidence for South Atlantic Shell-Ring Villages

Abstract Circular shell rings along the South Atlantic coast of the United States are vestiges of the earliest sedentary villages in North America, dating to 4500–3000 BP. However, little is known about when Indigenous communities began constructing these shell-ring villages. This article presents data from the Hokfv-Mocvse Shell Ring on Ossabaw Island, Georgia. Although shell rings are often associated with the earliest ceramics in North America, no ceramics were encountered in our excavations at Hokfv-Mocvse, and the only materials recovered were projectile points similar to points found over 300 km inland. Bayesian modeling of radiocarbon dates indicates that the ring was occupied between 5090 and 4735 cal BP (95% confidence), making it the earliest dated shell ring in the region. Additionally, shell geochemistry and oyster paleobiology data suggest that inhabitants were living at the ring year-round and had established institutions at that time to manage oyster fisheries sustainably. Hokfv-Mocvse therefore provides evidence for Indigenous people settling in year-round villages and adapting to coastal environments in the region centuries before the adoption of pottery. The establishment of villages marks a visible archaeological shift toward settling down and occupying island ecosystems on a more permanent basis and in larger numbers than ever before in the region.

Spatial Agglomeration Mining of Urban Recreational Amenities: the Case of the Greater Bay Area in China

Understanding how urban recreational amenities are agglomerated and clustered with each other is crucial. This paper attempts to reveal the features of such spatial agglomeration patterns by innovatively developing a model termed as spatial agglomeration mining. Based on the case of Greater Bay Area in China, it achieves three conclusions. First, recreational amenities are highly agglomerated rather than evenly distributed at both regional and urban scales. Second, the regional and urban agglomeration patterns are similar in the sense that the agglomeration core is mainly composed of convenience-service amenities, while the periphery is mainly composed of leisure and entertainment amenities. Third, cities with similar size and economic functions share a similar structure, whereas amenities with a larger number do not guarantee a more central position in the clusters. This study sheds light on the general principle’s relativeness among amenities for urban investors and managers to make better decisions.

Does the Duty of Rescue support a moral obligation to vaccinate? Seasonal influenza and the Institutional Duty of Rescue

Seasonal influenza poses a significant public health risk in many countries worldwide. Lower immunity and less influenza virus circulating during the pandemic has resulted in a significant increase in cases...

Natural Language Processing Pretraining Language Model for Computer Intelligent Recognition Technology

Computer intelligent recognition technology refers to the use of computer vision, Natural Language Processing (NLP), machine learning and other technologies to enable computers to recognize, analyze, understand and answer human language and behavior. The common applications of computer intelligent recognition technology include image recognition, NLP, face recognition, target tracking, and other fields. NLP is a field of computer science, which involves the interaction between computers and natural languages. NLP technology can be used to process, analyze and generate natural language data, such as text, voice and image. Common NLP technology applications include language translation, emotion analysis, text classification, speech recognition and question answering system. Language model is a machine learning model, which uses a large number of text data for training to learn language patterns and relationships in text data. Although the language model has made great progress in the past few years, it still faces some challenges, including: poor semantic understanding, confusion in multilingual processing, slow language processing and other shortcomings. Therefore, in order to optimize these shortcomings, this article would study the pre-training language model based on NLP technology, which aimed at using NLP technology to optimize and improve the performance of the language model, thus optimizing the computer intelligent recognition technology. The model had a higher language understanding ability and more accurate prediction ability. In addition, the model could learn language rules and structures by using a large number of corpus, so as to better understand natural language. Through experiments, it could be known that the data size and total computing time of the traditional Generative Pretrained Transformer-2 (GPT-2) language model were 10 GB and 97 hours respectively. The data size and total computing time of BERT (Bidirectional Encoder Representations from Transformer) were 12 GB and 86 hours respectively. The data size and total computing time of the pre-training language model based on NLP were 18 GB and 71 hours respectively. Obviously, the pre-training language model based on NLP had a larger data size and shorter computing time. The experimental results showed that the NLP technology could better optimize the language model and effectively improve its various capabilities. This article opened up a new development direction for computer intelligent recognition technology and provided excellent technical support for the development of language models.

Language Model Method for Collocation Rules of Parts of Speech in Machine Translation System

With the development of the times, modern society has now entered the Internet of Things (IoT) information age and Machine Translation (MT) plays an important role in increasingly frequent cross-language communication. In recent years, China's artificial intelligence industry has been in a stage of rapid construction, and the scale of its core industries has grown explosively, and a large number of artificial intelligence companies, including issuers, have emerged. Part of speech has always been a major problem in MT. One of the reasons is that there are a large number of multi-category words in Chinese and a large number of polysemy words in English, so part of speech collocation problems account for a large proportion of MT errors, which to some extent affects the credibility and accuracy of the translation. To reduce the error problem in MT of part of speech collocation, this paper used Machine Learning (ML) methods to study the Language Model (LM) of part of speech collocation based on recurrent neural network (NN) and compared it with the traditional statistical LM. In terms of the accuracy rate of the two LMS in the automatic evaluation index of machine translation, the experimental results show that the recursive NN LM established by the ML method had an accuracy rate of 80.42% and 83.57%, respectively, for the part-of-speech matching rules of the IoT machine translation system in the dialogue between Chinese and English and the translation of articles. The accuracy of traditional statistical LM evaluation was 71.29% and 69.52%, respectively. Compared to traditional statistical LM, the accuracy of translation was higher. This showed that the recurrent NN LM reduced the number of errors in the collocation of parts of speech in MT and improved the accuracy and credibility of MT.

A new design of an electrospinning apparatus for tissue engineering applications.

The electrospinning technique is being widely explored in the biomedical field due to its simplicity to produce meshes and its capacity to mimic the micro-nanostructure of the natural extracellular matrix. For skin tissue engineering applications, wound dressings made from electrospun nanofibers present several advantages compared to conventional dressings, such as the promotion of the hemostasis phase, wound exudate absorption, semi-permeability, easy conformability to the wound, functional ability and no scar induction. Despite being a relatively simple technique, electrospinning is strongly influenced by polymer solution characteristics, processing parameters and environmental conditions, which strongly determine the production of fibers and their morphology. However, most electrospinning systems are wrongly designed, presenting a large number of conductive components that compromises the stability of the spinning process. This paper presents a new design of an electrospinning system solving the abovementioned limitations. The system was assessed through the production of polycaprolactone (PCL) and gelatin nanofibers. Different solvents and processing parameters were considered. Results show that the proposed electrospinning system is suitable to produce reproducible and homogeneous electrospun fibers for tissue engineering applications.