Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Denture Feature Matching Point Cloud Data Based on Deep Learning

With the vigorous development of modern science and technology, to effectively solve the shortcomings of traditional oral diagnosis and treatment, digital oral diagnosis and treatment models are based on three-dimensional reconstruction technology to restore the surface information of denture models, making it easier for doctors to accurately diagnose and treat patients' conditions. Deep learning provides new ideas for denture point cloud feature matching. In this paper, the EdgeConv structure is introduced to improve the network for denture point cloud matching. The experimental outcomes demonstrate that the improved network for matching features of denture point clouds performs well in comparison to the traditional ICP algorithm. Compared with the PCRNet network, the MSE_R is reduced by 0.716, and the MSE_t is reduced by 0.064. The improved network has stronger feature extraction capabilities for local features, resulting in point cloud registration outcomes that are closer to the actual point cloud registration. Additionally, the network's performance is more consistent and stable.
The Predictive Value of Essen and SPI-II on the Risk of 5-Year Recurrence in Chinese Patients with Acute Ischemic Stroke

Background The risk prediction score for stroke recurrence is an important tool for stratifying patients based on the risk of cerebrovascular events and selecting potential preventive treatments. Objective The study aimed to validate the Essen Stroke Risk Score (ESRS) and Stroke Prognosis Instrument II (SPI-II) for predicting long-term risk of stroke recurrence and combined vascular events in Chinese patients with acute ischemic stroke (AIS). Methods A total of 876 consecutive patients with non-atrial fibrillation AIS were recruited. The Kaplan-Meier (KM) method was used to estimate the cumulative incidence of stroke recurrence and combined vascular events in different subgroups stratified by the ESRS and SPI-II scores. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the predictive value of the two scores for stroke recurrence and combined vascular events. Results The KM estimate for 5-year cumulative incidence of stroke recurrence and combined vascular events was 28.7% (95% confidence interval [CI], 25.4–32.0) and 35.6% (95% CI, 32.3–38.9), respectively, in Chinese AIS patients. The risk of stroke recurrence and combined vascular events were increased significantly with increasing ESRS and SPI-II scores. The ESRS and SPI-II scores had similar predictive accuracy for stroke recurrence (AUC 0.57 [95% CI 0.52–0.64] vs 0.59 [95% CI 0.55–0.64]) and combined vascular events (AUC 0.59 [95% CI 0.55–0.63] vs 0.62 [95% CI 0.58–0.66]) at 5 years. Conclusion In Chinese patients with AIS, both ESRS and SPI-II scores were able to stratify the risk of 5-year recurrent stroke and combined vascular events. The predictive power of the two scores were modest and a prediction model suitable for Chinese IS populations is needed.
SW-database-codesign for compressed bitmap

—Compressed bitmap indices are heavily used in scientiﬁc and commercial database systems because they largely improve query performance for various workloads. Early research focused on ﬁnding tailor-made index compression schemes that are amenable for modern processors. Improving performance further typically comes at the expense of a lower compression rate, which is in many applications not acceptable because of memory limitations. Alternatively, tailor-made hardware allows to achieve a performance that can only hardly be reached with software running on general-purpose CPUs. In this paper, we will show how to create a custom instruction set framework for compressed bitmap processing that is generic enough to implement most of the major compressed bitmap indices. For evaluation, we implemented WAH, PLWAH, and COMPAX operations using our framework and compared the resulting implementation to multiple state-of-the-art processors. We show that the custom-made bitmap processor achieves speedups of up to one order of magnitude by also using two orders of magnitude less energy compared to a modern energy-efﬁcient Intel processor. Finally, we discuss how to embed our processor with database-speciﬁc instruction sets into database system environments.
Shapes for Appurtenances in Stilling Basins

Baffle pier experiments in hydraulic jump type of stilling basins indicate that wedge-shaped blocks with a vertex angle of 120○ dissipate more energy in a shorter length than rectangular blocks. The wedge blocks with the downstream portion cut-back at an angle of 90○ are expected to be free from cavitation.
Practical approaches to management of the marine prehistoric environment

Abstract Since so little is still known of the marine prehistoric environment, present management actions tend to be guided by the gathering of disparate sets of data obtained as part of regulatory practice and/or from opportunistic finds that are not necessarily specifically targeted towards archaeology. Our view is that we need to develop a clearly defined set of questions about the marine prehistoric cultural resource to enable the design of targeted scientific research, as part of both the regulatory process and marine management generally. In this paper we argue that it is crucial to understand both natural and anthropogenic context, and this necessarily includes work on the Quaternary geology. Furthermore, we argue for a greater regulatory emphasis on identifying and initiating what we should do (for the long term) rather than what we can and are doing (for the short term) to identify the best means to manage the prehistoric marine environment.
New geophysical constraints on a failed subduction initiation: The structure and potential evolution of the Gagua Ridge and Huatung Basin

We modeled the velocity structure of the Huatung Basin and Gagua Ridge using offshore wide‐angle seismic data along four ∼E‐W transects. These transects are accompanied by several multichannel seismic reflection (MCS) profiles that highlight the shallow deformation in this area east of Taiwan. Although it is agreed that the Gagua Ridge was the product of a transient compressional episode in the past, relatively few data have been collected that reveal the deeper structure resulting from this enigmatic process. The velocity models show evidence for normal, to thin, oceanic crustal thicknesses in the Huatung Basin and West Philippine Basin. Moho reflections from the associated MCS profiles confirm the thickness observed in the velocity models. The velocity models indicate significant crustal thickening associated with the Gagua Ridge, to 12–18 km along its entire length. Most importantly, the two central velocity models also show a significant asymmetry in the crustal thickening, suggesting a westward underthrusting of >20 km of WPB oceanic crust beneath that of the Huatung Basin. This geometry is extremely unexpected given interpretations that indicate the Huatung Basin could be significantly older than the West Philippine Basin (Early Cretaceous versus Eocene). Our observations, along with recent geophysical data concerning the age of the Huatung Basin, indicate that the Gagua Ridge was the result of a failed subduction event during the Miocene that may have existed simultaneously and for a short time, competed with the Manila subduction zone to the west in accommodating convergence between the Eurasia and Philippine Sea plates. In this scenario, the present‐day Gagua Ridge represents a snapshot of a failed subduction initiation preserved in the geologic record.
Examining Built Environment Effects on Metro Ridership at Station-to-Station Level considering Circle Heterogeneity: A Case Study from Xi’an, China

Transit-oriented development is described as a geographic unit with multicircle structures. Most studies have analysed the impact of the built environment within station catchment areas on metro passenger flows from a macro perspective and have lacked analysis of the circle heterogeneity. Few relevant studies have independently investigated the impact of the built environment on the passenger flow in each circle and indeed neglected the systematic interaction between inner circles and circles in the TOD area. In this study, the 800 m buffer from the station was equally divided into four circles. Based on the gravity model, the representative built environment features around the metro stations on both sides were extracted using the block attention module (BAM). Subsequently, Shapley Additive exPlanation (SHAP) was used to explore the influence of different built environment variables on passenger flow at each circle between the origin and destination stations. The results indicate the following: (1) the station-to-station passenger flow is significantly affected by the availability of transfers and the distance between the origin and destination stations; (2) the impact of different built environments on ridership significantly varies within different circles; and (3) the built environment has a similar impact on average daily passenger flow on both sides. Therefore, this study proposes strategies to optimize the metro passenger flow by developing different land use in different circles and updating the urban spatial structure.
Optimal and Charge-Sustainable Energy Management Systems for Industrial DC Grids

Industrial Direct Current (DC) grids are increasingly considered since they can have economical advantages, and can lead to an improved sustainability, flexibility and reliability. However, to meet these challenges, an Energy Management System (EMS) is needed to decide when and how much to charge or discharge the storage elements. In this paper we present an EMS formulation based on Model Predictive Controller (MPC). Such methods have been applied to other energy management applications, and in this paper we adapt and apply them to the use case of industrial DC grids. We further propose a novel method to extend our EMS to ensure long term charge-sustainability is achieved, with less tuning difficulties than existing methods face. Both the application of EMS to industrial DC and the extension towards charge sustainability are illustrated on a set of simulation examples.
UvA-DARE (

We present a study of the adequacy of current methods that are used for POS-tagging historical Dutch texts, as well as an exploration of the inﬂuence of employing different techniques to improve upon the current practice. The main focus of this paper is on (unsupervised) methods that are easily adaptable for different domains without requiring extensive manual input. It was found that modernising the spelling of corpora prior to tagging them with a tagger trained on contemporary Dutch results in a large increase in accuracy, but that spelling normalisation alone is not sufﬁcient to obtain state-of-the-art results. The best results were achieved by training a POS-tagger on a corpus automatically annotated by projecting (automatically assigned) POS-tags via word alignments from a contemporary corpus. This result is promising, as it was reached without including any domain knowledge or context dependencies. We argue that the insights of this study combined with semi-supervised learning techniques for domain adaptation can be used to develop a general-purpose diachronic tagger for Dutch.
Integral education and Ubuntu: A participatory action research project in South Africa

Background: South Africa is beset with violent, antisocial practices and ways of life hindering peaceful co-existence and participatory democracy. This makes a targeted early education programme to develop a socially responsible generation imperative.Aim: Based on a larger research project, this study aimed to highlight the value of participatory action research in determining the outcomes of an early childhood development (ECD) Integral Education (IE) and Ubuntu approach for incorporation in the education and training of practitioners.Setting: Three ECD practitioners were selected to participate in this study, which was located in a township in the south of Durban in three preschools (urban, semi-urban and rural). Methods: Lewin’s PAR method was used to explore, develop and evaluate an intervention for change. Data were collected through focus group and participant interviews, observations and journal entries and then analysed thematically.Results: The findings revealed that, personally and professionally, the practitioners experienced positive changes through adopting an integral approach that included becoming more introspective and reflective in their practice.Conclusion: Educating and training early childhood practitioners to develop the appropriate knowledge, skills, attitudes and values to adopt and implement an ECD IE and Ubuntu approach are essential for developing a new generation of socially responsible citizens for participatory democracy in South Africa.Contribution: The findings highlighted key components of an ECD IE practitioner training programme based on the integrality of the mind, body, heart, spirit and community. Thus, the development of a caring, compassionate and humane society in democratic South Africa can be enabled.
The thrust and normal faults of the Ullapool–Strath Kanaird region and their implications for NW Highland tectonics

Synopsis In the Ullapool to Strath Kanaird region of the NW Highlands the thrusts of the Moine thrust zone generally show a foreland propagating sequence but there are important anomalies. The Moine thrust itself appears to be a late structure, slicing across the earlier thrust stacks. There are several ages of normal fault movement. An early set formed synchronous with thrusting and involved extension in a WNW–ESE direction, parallel to general thrust transport, but also extension NE–SW, perpendicular to thrusting. These variations in movement indicate non-plane strain conditions, with important implications for section restoration. The early normal faults are either cut by or decouple on the Sole thrust to the Moine thrust system. There are late normal faults however, which are well-developed in the Ullapool area, and these are probably Mesozoic in age.
Model Design and Research of Power Communication Equipment Evaluation Based on AI

Power communication equipment is a fundamental element of the power system, and the safe and economic operation of the power grid depends on its normal operating condition. It is of great significance to study the power equipment assessment method based on artificial intelligence algorithms for comprehensively, timely and accurately grasping the operation status of power equipment and its development trend. The system studied in this paper is mainly implemented by embedded system, and the operation and test are realized through system construction, including real-time monitoring, data statistics and alarm analysis. The results can be directly applied to the communication operation and maintenance of all units in the system, which is innovative and can easily complete the transformation of intellectual property rights into products.
The Standard Model of Particle Physics: Limitations and Beyond

Over the course of the last thirty years, a persuasive argument has been presented in favor of the now acknowledged “standard model” of elementary particles and forces. The "Standard Model" is a theoretical framework that is constructed based on empirical observations and is utilized to make predictions and establish correlations with novel data. The table of elements represents a significant milestone in the field of chemistry, since it enabled researchers to make informed predictions regarding the characteristics of numerous elements and compounds that had not yet been thoroughly examined. Nonrelativistic quantum theory, as a widely accepted framework, has successfully established correlations between experimental outcomes throughout numerous investigations. Similar to its predecessors in several disciplines, the “standard model of particle physics” has exhibited remarkable efficacy in its ability to forecast a diverse array of phenomena. In a similar vein to the limitations of regular quantum mechanics in the relativistic regime, it is anticipated that the “standard model” will not hold true at infinitesimally small scales. Nevertheless, the notable achievement of the “standard model” strongly indicates that it will continue to serve as a highly accurate representation of the natural world, even at distance scales as minute as 10–18 m.
A Systematic Review of In Vitro Studies Using Microchip Platforms for Identifying Periodontopathogens from the Red Complex

Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola, collectively recognized as periodontopathogens within the red complex, have been extensively studied in clinical samples collected from individuals with periodontitis. A lab-on-a-chip (LOC) is a miniature mechanism that integrates various laboratory operations onto a single microchip or a small-scale platform. This systematic review evaluates the application of LOC technology in identifying microorganisms from the red complex. This study adhered to PRISMA recommendations, and the review process encompassed several databases. In the electronic search, a total of 58 reports were found, and ultimately, 10 studies were considered relevant for inclusion. All these studies described effective, rapid, and reliable LOC systems for detecting and amplifying P. gingivalis, T. forsythia, and T. denticola. Compared to traditional methods, the LOC approach demonstrated minimal reagent requirements. Additionally, the results indicated that the amplification process took approximately 2 to 8 min, while detection could be completed in as little as 2 min and 40 s, resulting in a total experimental duration of around 11 min. Integrating miniaturization, speed, accuracy, and automation within microchip platforms makes them promising tools for detecting and amplifying microorganisms associated with the red complex in periodontal diseases.
Effects of Maize–Crop Rotation on Soil Physicochemical Properties, Enzyme Activities, Microbial Biomass and Microbial Community Structure in Southwest China

Introducing cover crops into maize rotation systems is widely practiced to increase crop productivity and achieve sustainable agricultural development, yet the potential for crop rotational diversity to contribute to environmental benefits in soils remains uncertain. Here, we investigated the effects of different crop rotation patterns on the physicochemical properties, enzyme activities, microbial biomass and microbial communities in soils from field experiments. Crop rotation patterns included (i) pure maize monoculture (CC), (ii) maize–garlic (CG), (iii) maize–rape (CR) and (iv) maize–annual ryegrass for one year (Cir1), two years (Cir2) and three years (Cir3). Our results showed that soil physicochemical properties varied in all rotation patterns, with higher total and available phosphorus concentrations in CG and CR and lower soil organic carbon and total nitrogen concentrations in the maize–ryegrass rotations compared to CC. Specifically, soil fertility was ranked as CG > Cir2 > CR > Cir3 > CC > Cir1. CG decreased enzyme activities but enhanced microbial biomass. Cir2 decreased carbon (C) and nitrogen (N) acquiring enzyme activities and soil microbial C and N concentrations, but increased phosphorus (P) acquiring enzyme activities and microbial biomass P concentrations compared to CC. Soil bacterial and fungal diversity (Shannon index) were lower in CG and Cir2 compared to CC, while the richness (Chao1 index) was lower in CG, CR, Cir1 and Cir2. Most maize rotations notably augmented the relative abundance of soil bacteria, including Chloroflexi, Gemmatimonadetes and Rokubacteria, while not necessarily decreasing the abundance of soil fungi like Basidiomycota, Mortierellomycota and Anthophyta. Redundancy analysis indicated that nitrate-N, ammonium-N and microbial biomass N concentrations had a large impact on soil bacterial communities, whereas nitrate-N and ammonium-N, available P, soil organic C and microbial biomass C concentrations had a greater effect on soil fungal communities. In conclusion, maize rotations with garlic, rape and ryegrass distinctly modify soil properties and microbial compositions. Thus, we advocate for garlic and annual ryegrass as maize cover crops and recommend a two-year rotation for perennial ryegrass in Southwest China.
Pilot Assignment for Cell-Free Massive MIMO: A Spectral Clustering Approach

In this letter, we study the pilot assignment scheme in the uplink cell-free massive multiple-input multiple-output system. To accurately depict the potential co-pilot interference (CPI) among the user terminals (UTs), we introduce the normalized contribution value of AP to the received signal strength at the UT. A weighted conflict clustering graph is constructed by using the potential CPI to define the weight of the edge that connects the co-pilot UTs. Then, the pilot assignment optimization is transformed into a Min-Cut problem, which is further converted as a more effective normalized cut to find a partition of the UTs into disjoint clusters for minimizing the overall CPI. We develop a two-stage algorithm via spectral clustering to solve the relaxed problem efficiently. Numerical results are provided to validate the superiority of the proposed algorithm as compared to the existing methods in terms of the uplink average sum-rate and the quality of channel estimation.
Improving Intrusion Detection Systems for IoT Devices using Automated Feature Generation based on ToN_IoT dataset

The Internet of Things (IoT) has witnessed exponential growth in recent years, leading to a diverse and interconnected ecosystem of devices. However, this rapid expansion has also made IoT vulnerable to various security threats and attacks. The interconnected nature of IoT devices and their extensive integration into everyday life make them enticing targets for malicious actors. Consequently, the development and deployment of effective intrusion detection systems for IoT environments have become crucial. In the literature, it has been observed that feature engineering, feature extraction, and other preprocessing steps are problematic. The general trend has been to develop intrusion detection systems using complex models such as deep learning concepts, while reducing the effort spent on feature engineering. In this study, the importance of feature engineering is addressed, and it is demonstrated that effective results can be achieved with simple models when proper preprocessing and feature generation steps are applied. An intrusion detection system for IoT devices has been implemented in the ToN_IoT dataset by employing appropriate preprocessing steps and, additionally, utilizing mechanisms for automatic feature generation. In the experiments conducted on the ToN-IoT dataset, we propose a simple model that gives comparable results with the state-of-the-art deep learning models. This model utilizes a basic random forest algorithm and benefits f rom a different t raining scheme that take the benefits of grouping, stratification, re sampling, and automated feature generation strategies. We achieved 99.99% ROC-AUC values for both train and independent test sets. The proposed method shows mostly better performances for specifity, precision, recall, and F1-score than deep learning based models.