Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Modal Sensor Framework with Learnable Uncertainty Estimator for Pedestrian Trajectory Prediction

This paper presents a novel pedestrian trajectory prediction framework for autonomous driving systems in multimodality sensor settings where the set of sensors (i.e., camera, LiDAR, etc.) can be used for prediction task. While achiveving promising results, the existing camera-based prediction models often fail to capture more complex human motion in realworld. Our work mitigate this issue by proposing a multimodal sensor framework for pedestrian trajectory prediction (xMTP), consisting of two branches of predictors. On the first branch, we leverage the promising performances of the existing camera-based prediction models, such as BiTrap [1] and PIE [2], to model the human intentions. We refer to the existing camera-based prediction models as native predictors, that can potentially be any off-the-shelf prediction model. On the other branch, we propose a novel LiDARbased predictor (P3D) model the pedestrians' $\mathbf{3D}$ movements as LiDAR data provides rich depth information that help reason about pedestrian motions in real world. We then develop a novel learnable prediction sharing with uncertainty estimation (PSUE) to quantify the uncertainties of predictions from the two branches relative to their past performances on observed pedestrian motions to select the best prediction for the given scenarios. Through extensive experiments on commonly-used datasets: KITTI [3] and SHIFT [4], consisting of both camera and LiDAR data, we demonstrate the effectiveness of our framework in incorporating two different state-of-the-art native predictors, BiTrap [1] and PIE [2], under different pedestrian movement scenarios.
Improved Induction Network with Hierarchical Self-attention Scheme for Few-Shot Relation Classification

The vast majority of present techniques for relation classification rely heavily on large-scale labelled datasets, but when the training data is insufficient, these methods are not available. Intuitively, we can regard relation classification as a few-shot learning task when the data is hard to collect. In this paper, we present an advanced induction network with a hierarchical self-attention scheme to effectively tackle the issue of few-shot relation classification. We utilize attention-based dynamic routing algorithm to learn a query-related class representation. Besides, our hierarchical self-attention scheme, including instance-level and task-level attention, can adjust support set and capture high-level information between support set and query set. The results of our extensive experiment on FewRel dataset show that our model is adaptable to task and outperforms the state-of-the-art models.
In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems

In recent years, Artificial Intelligence (AI) has been increasingly used in traffic management and control, particularly in the smart city context. However, the vast majority of recent AI-based approaches rely on data-driven black-box models that hinder the ability to understand the behaviour and dynamics that lead to a given output. On the contrary, Good Old-Fashioned Artificial Intelligence approaches that are based on symbolic models, such as automated planning, can provide the transparency and explainability needed in real-world applications. This paper focuses on the benefits of using automated planning techniques in Intelligent Transportation Systems (ITS), with a focus on explainability. A case study is presented to demonstrate how the components of an automated planning system can support explainability, the types of explanations that can be obtained, and the way in which such explanations can be generated.
Aspects of the thermal ecology of the European tree frog Hyla arborea (Linnaeus, 1758) (Anura: Hylidae) in Western France

Summary – Body temperatures of the tree frog Hyla arborea were measured over a six-year period during overcast and sunny weather in Vendee of Western France. Body temperatures were higher dur ing sunny weather but there was no difference in body temperature variance. Body temperature vari ance was lower in comparison to the variance of leaf temperatures in sunlit areas but in agreement with leaf temperature variance in shaded areas irrespective of weather conditions. Regression analysis of body temperatures with leaf temperatures in shade or open locations during both sunny and cloudy weather indicated the closest association was with shaded leaf temperature regardless of weather con ditions. Frogs were located at median distances of 2-12 m from the nearest water mostly in shaded areas, but a smaller number were observed in sunlit areas during sunny weather in mid-afternoon. The results suggest control of body temperature in H. arborea by microhabitat selection, with shaded areas selected to avoid potentially critical high temperatures during sunny weather. However, occasional basking in open locations, even during hot weather, suggests an attempt to elevate body temperature.
Comparative Study on Intelligent Modulation Recognition Models Based on Raw Data

In recent years, intelligent modulation recognition methods for communication signals based on deep learning have attracted attention due to their advantages in feature extraction and recognition performance. However, there is limited research on the performance boundaries and optimization criteria of neural network models in existing domestic and international studies, and the datasets used in the research are relatively simple. This paper first proposes an intelligent modulation recognition model based on deep learning; Then a super dataset containing 22 traditional and emerging complex modulation modes is generated by simulation; Finally, based on this dataset, a comprehensive comparative analysis is conducted from multiple perspectives to investigate the effects of data slicing, selection and design of network models and parameters on the modulation recognition performance of the model. General patterns were obtained, providing valuable references for subsequent research and model application.
Sea Ice Concentration Estimation Via Fusion of Sentinel-1 and AMSR2 Based on Encoder-Decoder Architecture

Sea ice concentration estimation is crucial for secure ship navigation and ice hazard forecasting. In this paper, we propose a Convolutional Neural Network (CNN) architecture for sea ice concentration estimation over the Baltic Sea using two imaging modalities: Sentinel-1 and advanced microwave scanning radiometer2 (AMSR2). The main idea for fusing these two sensors is Sentinel-1 images have high spatial resolution and AMSR2 provides images independent of wind conditions. Our two-stream architecture is to preserve all possible information of the different resolution inputs, instead of interpolating the inputs to the same resolution while losing potentially useful information. We also investigate the impact of two loss functions and skip connection on the performance of the proposed CNN model. The experimental results show that CNN with focal loss function and skip connection can achieve R2 score of 90.6%.
Examining the impact of attitude, availability, price, and quality of service on broadband Internet customer satisfaction

After the COVID-19 pandemic, broadband internet utilization is predicted to continue to grow and experience a significant increase. The pandemic has changed how people work, study, communicate, shop, and carry out many aspects of daily life. Research reported that since 2018, research on broadband internet has continued to increase until now. This quantitative study examines the impact of the four critical variables on the link between attitude, availability, pricing, and quality of service (QoS) on broadband internet customer satisfaction using the Structural Equation Model approach and the Partial Lease Square technique. Three hundred and sixty-one citizen respondents in DKI Jakarta Province were collected using the snowball sampling method facilitated by Google Forms. At the same time, the COVID-19 post-pandemic was still ongoing in Indonesia. Through rigorous statistical analysis, the results show that customer satisfaction with broadband internet services is influenced by all factors, from attitude towards broadband Internet, broadband Internet availability, broadband Internet price, and service quality. The implications of this research are significant for service providers. They provide actionable insights for developing effective strategies to improve customer satisfaction and increase broadband internet subscriptions.
Investigating Cultural and Structural Influences on Optimizing Engineer-to-Order Project Delivery and Sustainability

Several culture theories, which explain the formation, embedment, and propagation of organizational culture, suggest that certain organizational culture practices of an executing organization may enable sustainable outcomes in project manufacturing. However, practices that support sustainability may not support project delivery, and vice versa. We explore the effects of organizational culture practices and structural complexity on the ability of manufacturing projects to optimize both sustainability and project delivery. We use data envelopment analysis to calculate a sustainability-delivery quotient—a measure of each organization's ability to optimize both sustainability and project delivery outcomes—for 186 projects conducted in the U.K. By conducting generalized linear modeling and censored regression of the sustainability-delivery quotient, we estimate the effects of the GLOBE organizational culture dimensions, principal components of culture dimensions, and project structural complexity indicators. Results indicate a noteworthy gap between the delivery of projects and their sustainability performance, which is worse. Both institutional and in-group collectivism may support the optimization of each. However, neither the principal components of culture dimensions nor structural complexity indicators are likely to be significant. We discuss the managerial implications.
Experimental investigation of the conditions at which the collapse line coincides with the critical state line

Abstract The conditions at which the collapse line coincides with the critical state line were investigated by means of a new ring shear device. Natural and artificially constituted sands were tested in undrained conditions to evaluate their responses to variations in relative density. The collapse and critical state lines merged in specimens at the critical density in which the shear resistance and pore pressure briefly reached a condition of zero rate of change and remained momentarily constant and equal. At a given normal stress, the friction angle at the phase transformation was equal to the friction angle at the steady state in specimens at the critical density. At densities below the critical density, the specimens exhibited purely contractive behaviour; above the critical density, the specimens’ behaviour was defined by three distinct stages of deformation of phase transformation, peak and steady states. A comparison of the friction angle at the phase transformation, steady state and threshold state in all of the soils revealed only slight differences.
Small Earthquakes Deviate from the Omega‐Square Model as Revealed by Multiple Spectral Ratio Analysis

We examine the omega‐square model by estimating the source spectra of 196 M w 3.2–4.0 shallow earthquakes in the northern Ibaraki prefecture and the Fukushima prefecture Hamadori area of Japan using multiple spectral ratio analysis. Spectral ratios of the seismograms of target events to those of multiple nearby small events (empirical Green’s function [EGF] events) allow for negation of path and site effects and are fitted by the omega‐square model. The residual spectra for different EGF events exhibit similar curves, indicating how the source spectra of the target events deviate from the omega‐square model. Many earthquakes deviate remarkably, whereas other events fit well. The possible implications of these findings are incoherencies in the rupture process, the double‐corner‐frequency model, and a high‐frequency falloff exponent value slightly higher than 2, although this is still an open question. This study will help to improve the source spectrum model, enhancing not only source studies, but strong motion assessments and other seismological studies. Online Material: Figures showing results of spectral analysis of the events with the largest and smallest peak‐to‐peak amplitudes.
Stability Analysis of Six Improved Sorghum Genotypes across Four Environments in the Southern Guinea Savanna Agroecological Zone of Nigeria

Six sorghum genotypes from the Institute for Agric Research Zaria were evaluated for stability study in four environments in the Southern Guinea Savanna in the 2009 & 2010 cropping seasons using Randomized Complete Block Designs (RCBD) with four replications in each of the locations. Analysis of Variance was carried out for each set of data collected and where significant difference was observed, mean separations was done using Duncan Multiple Range test. The regression coefficient (b) of Finlay and Wilkinson (1966), ecovalence (W 2 ) and mean squares of deviation from regression (S 2 d) of Eberhart and Russel (1966) were used as stability parameters. The highest yield genotype was SSV2006019 (6.06t/ha) while the least yield was SSV2006043 (4.02t/ha), based on the stability parameters, Genotypes SSV2006019, SSV2006039 and SSV2006040 with ecovalence values of 0.28, 0.003 and 0.14 and b values of 0.99, 0.84 and 1.01 respectively appeared to be stable and adapted to the test environments while SSV2006002 and SSV2006006 with yield values of 4.82 and 4.47t/ha respectively appears to be good for poor environments.
Combining Time Series and Cross-sectional Data for Current Employment Statistics Estimates October

Estimates from the Current Em ployment Statistics (CES) Surve y are produced based on the data collected each month from the sample of businesses that is updated once a y ear. In some estimation cells, where the sample is not large enough, t he Fay-Herriot model is used to im prove the esti mates. Under th e curre nt approach, the model co mbines information from a set of areas and is esti mated independently every month. Given the design of the survey, it may be beneficial to borrow information not only cross-sectionally but also over time. This paper explores the feasibility of applying such a model. The results are evaluated based on historical "true" employment data available on a lagged basis.
Perspectivas ribeirinha sobre os impactos da construção de usinas hidrelétricas no rio Madeira em Rondônia

Durante os ultimos 40 anos, Rondonia tem sofrido mudancas significativas, comecando com a construcao de, BR 364, e da rapida expansao da fronteira agricola nas porcoes sul e central do estado durante os anos 1970 e 1980. Durante este mesmo periodo de tempo, o Rio Madeira tambem sofreu mudancas significativas, com aumento do povoamento e urbanizacao ao longo de suas margens, a dragagem hidraulica para a exploracao de ouro, e o desenvolvimento da Hidrovia do Madeira. A construcao das barragens de Santo Antonio e Jirau, na parte superior do Rio Madeira, a montante de capital de Porto Velho representa a mais recente dessas transformacoes, com alto potencial de causar impactos significativos sobre ambientes fluviais e comunidades ribeirinhas. Embora as comunidades a montante que foram diretamente afetadas pela construcao da barragem e enchimento do reservatorio tivessem sido reassentadas, as comunidades a jusante da barragem nao foram retiradas, tendo sido informadas de que nao seriam afetadas. No entanto, os moradores da comunidade ribeirinha de Vila Sao Sebastiao e areas adjacentes comecaram a notar mudancas nos ambientes fluviais e de varzea logo apos o inicio da a construcao da barragem. Estes impactos observados foram intensificados pela inundacao historica que ocorreu durante a primavera de 2014, assim como as preocupacoes dos residentes sobre seus futuros e de sua comunidade. Este artigo tem por objetivo realizar uma analise preliminar sobre os impactos das barragens e da hidrovia observados em ambientes fluviais e comunidades ribeirinhas, atraves do ponto de vista dos moradores de Vila Sao Sebastiao, e areas adjacentes. Essas alegacoes serao avaliadas atraves do uso de entrevistas, documentacao fotografica, apoiados por uma revisao da literatura cientifica sobre a barragem, hidrovia e seus potenciais impactos.
Supershear transition mechanism induced by step over geometry

Few studies have focused on the supershear transition mechanism induced by fault step overs, although seismic observations suggest that rupture speed transitions occur at geometrical complexities on faults. Based on dynamic rupture simulations on fault systems with step overs in a 3‐D full space where the initial stresses preclude a supershear transition on a single buried fault according to the Burridge‐Andrews mechanism, we show that rupture speeds can transit from subshear on the primary fault to supershear on the secondary fault. The low normal stress zone and the high shear stress zone beyond the fault step, which radiate from the end of the primary fault if its rupture arrest is sudden, determine the supershear rupture occurrence on the secondary fault. However, a low shear stress zone traveling at the shear wave speed is also radiated, making the rupture speed return to subshear in most cases. Sustained supershear ruptures are also possible on compressional step overs under certain conditions. Self‐arresting ruptures are observed in the overlap area on the secondary fault. In a half‐space model where supershear rupture is induced by the free surface on the primary fault, the rupture speed on the secondary fault rapidly transits to subshear near the fault step if its width exceeds a critical value.
Gastric Emptying Studies in Pediatrics: A Cincinnati Children's Hospital Experience.

Gastric emptying studies are routinely performed in many nuclear medicine departments; however, there are many different techniques used to perform the procedure across the country. Creating consistency in clinical practice will aid gastroenterologists in diagnosing and treating illnesses associated with abnormalities related to gastric emptying. In 2017, Cincinnati Children's Hospital adopted adult standards for pediatric gastric emptying studies that included a standard meal along with imaging over the course of 4 h. Gastric emptying studies are the second-highest-volume examination performed in the nuclear medicine section at Cincinnati Children's Hospital. Accommodating this volume required changes in the scheduling template, scheduling questionnaire, and epic order sets, as well as identification of specific days and locations for gastric emptying studies. Both protocol standardization and workflow optimization are critically important in creating consistency in patient care. Gastric emptying can be evaluated with solid food, liquid food, or solid and liquid food simultaneously. The methodology of the study is initially determined by the ordering provider but may require special accommodations based on what the patient will tolerate. In coordination with the ordering and interpreting physicians, the nuclear medicine technologists at Cincinnati Children's Hospital have the decision-making ability to deviate from the provider's request as necessary, which helps expedite workflow and eliminates wasted time. Any deviation from the standardized protocol is documented by the nuclear medicine technologist and incorporated into the final report by the interpreting physician, as dietary information is meaningful to the ordering provider. Reference values associated with the standardized or modified protocol are also included in the final report.
SPATIAL ECOLOGY OF EUROPEAN BADGERS (MELES MELES) IN MEDITERRANEAN HABITATS OF THE NORTH-EASTERN IBERIAN PENINSULA. I: HOME RANGE SIZE, SPATIAL DISTRIBUTION AND SOCIAL ORGANIZATION

Although there are some radio-telemetry studies on badger spatial organization in sub-humid Mediterranean lowlands, cork oak woods and Atlantic highland forest (in the South, West and North of the Iberian Peninsula respectively), the present study is the first carried out in the Mediterranean forests of the NE Iberian Peninsula in the parks of Collserola and Montserrat, close to Barcelona. The home range of 13 adult badgers (6 males and 7 females) was examined with the aim of providing results to compare with previous studies in order to advance in the understanding of badger social organization with special regard to low density populations in Mediterranean environments. Mean home range size was 307.6 ha ± 96.4 (± SE) and 72.8 ha ± 15.1 for males and females respectively for MCP95 and 287.4 ± 79.1 and 85.1 ± 26.6 for FK95 with differences between Parks. In addition, the home ranges of Collserola males were over four times larger than those of females, while for Montserrat this figure was 1.5. Moreover, badger groups were formed by one to three individuals in Collserola, and at least three individuals in Montserrat. This discrepancy points to a distinct social organization associated with differences in population densities (0.6 ind./km 2 in Collserola and 1.9 ind./km 2 in Montserrat) and landscape structure conditions. Our results suggest that the home range configuration of males is driven by female distribution in space.
Impact of Different Surgical Approaches on Morbidity and Mortality in Patients with Borderline Resectable Pancreatic Head Carcinoma

Background: Radical surgical resection for pancreatic head carcinoma offers a chance for cure but unfortunately is only available to a limited number of patients. For a significant number of patients, palliative surgery remains the only option. The question of the most effective approach for patients with borderline resectable pancreatic head carcinoma (BRPHC) remains unresolved. Objective: The aim of the study was to compare the morbidity and mortality following R1 duodenocephalic pancreatectomy and double palliative bypass to explore the most optimal surgical treatment for patients with BRPHC. Methods: Our retrospective cohort study included 64 patients with BRPHC who underwent surgery from 2012 to 2019, with postoperative follow-up for three years. Morbidity and mortality parameters were examined based on the type of surgical treatment: R1 duodenocephalic pancreatectomy or palliative double bypass. Chi-square test, univariate regression, and Kaplan-Meier analysis were used as basic statistical methods in the analysis of the results. Results: Patients undergoing R1 duodenocephalic pancreatectomy had a 3.69 times higher risk of developing biliary leak (p=0.039; 95%CI:1.066, 1.181) and shorter survival compared to those undergoing palliative double bypass (p=0.022). No statistically significant association was found between the type of surgical procedure and other postoperative complications. Conclusion: Our study suggests that the double palliative bypass procedure may be a better option than R1 resection for patients with BRPHC.