Miracle-dz/UniFAR-FTUs huggingface dataset:
Large Scale Pursuit-Evasion Under Collision Avoidance Using Deep Reinforcement Learning

This paper examines a pursuit-evasion game (PEG) involving multiple pursuers and evaders. The decentralized pursuers aim to collaborate to capture the faster evaders while avoiding collisions. The policies of all agents are learning-based and are subjected to kinematic constraints that are specific to unicycles. To address the challenge of high dimensionality encountered in large-scale scenarios, we propose a state processing method named Mix-Attention, which is based on Self-Attention. This method effectively mitigates the curse of dimensionality. The simulation results provided in this study demonstrate that the combination of Mix-Attention and Independent Proximal Policy Optimization (IPPO) surpasses alternative approaches when solving the multi-pursuer multi-evader PEG, particularly as the number of entities increases. Moreover, the trained policies showcase their ability to adapt to scenarios involving varying numbers of agents and obstacles without requiring retraining. This adaptability showcases their transferability and robustness. Finally, our proposed approach has been validated through physical experiments conducted with six robots.
LIKELIHOOD INFERENCE IN SOME FINITE MIXTURE MODELS By

Parametric mixture models are commonly used in applied work, especially empirical economics, where these models are often employed to learn for example about the proportions of various types in a given population. This paper examines the inference question on the proportions (mixing probability) in a simple mixture model in the presence of nuisance parameters when sample size is large. It is well known that likelihood inference in mixture models is complicated due to 1) lack of point identification, and 2) parameters (for example, mixing probabilities) whose true value may lie on the boundary of the parameter space. These issues cause the profiled likelihood ratio (PLR) statistic to admit asymptotic limits that differ discontinuously depending on how the true density of the data approaches the regions of singularities where there is lack of point identification. This lack of uniformity in the asymptotic distribution suggests that confidence intervals based on pointwise asymptotic approximations might lead to faulty inferences. This paper examines this problem in details in a finite mixture model and provides possible fixes based on the parametric bootstrap. We examine the performance of this parametric bootstrap in Monte Carlo experiments and apply it to data from Beauty Contest experiments. We also examine small sample inferences and projection methods.
Pointwise error estimates for a generalized Oseen problem and an application to an optimal control problem

We derive pointwise error estimates for a generalized Oseen when it is approximated by a low order Taylor‐Hood finite element scheme in two dimensions. The analysis is based on estimates for regularized Green's functions associated with a generalized Oseen problem on weighted Sobolev spaces and weighted interpolation results. We apply the maximum norm results to obtain convergence in an optimal control problem governed by a generalized Oseen equation and present a numerical example that allows us to show the behavior of the error.
Less warming projected during heavy winter precipitation in the Cascades and Sierra Nevada

Local rates of warming from increased greenhouse gas concentrations can be different during heavy precipitation than during other times. This variable warming can influence precipitation extremes through the Clausius–Clapeyron relationship and modulate the rate of snowfall decline. Large ensembles of simulations from a regional climate model were used to project, with high signal‐to‐noise ratio, changes in the daily winter temperature versus precipitation intensity relationship from the contemporary period to a mid‐21st century scenario over the Cascades and Sierra Nevada of the United States. Warming rates decreased with increasing precipitation intensity over all montane regions, with the strongest relationship in the northern Cascades (1.2 °C less warming at 100 mm day−1 than at trace amounts). The relationship may be linked to the projected north Pacific meridional warming gradient, as the moisture of the largest precipitation events originates at lower latitudes where warming is less, though other factors may contribute.
SOCIAL MEDIA IMPACT ON UNIVERSITY REPUTATION AND ENROLLMENT

This study examines the influence of social media on university reputation and enrolment, specifically focusing on private universities in the Klang Valley. As digital communication continues to permeate every aspect of society, higher education institutions must adapt to remain competitive and attract prospective students. The primary objective of this research is to explore the relationship between a university's online presence and students' enrolment decisions. A quantitative survey method was employed, drawing a representative sample of students from private universities in the Klang Valley. Data were collected using a structured questionnaire that assessed students' perceptions of university reputation, social media usage, and the role of online presence in their enrolment choices. Preliminary findings indicate a positive correlation between an institution's social media presence and both its perceived reputation and enrolment rates. The study highlights the significance of effective social media strategies for private universities, emphasizing the need for institutions to leverage digital platforms to enhance their reputation and attract potential students. Further research is recommended to explore the long-term impact of social media on university performance and student success.
Geology of the ‘Coltre della Val Marecchia’ (Romagna-Marche Northern Apennines, Italy)

ABSTRACT A detailed geological map at 1:50,000 scale of the Marecchia Valley and adjoining areas (Northern Apennines, NA, Italy) is presented here. The Marecchia Valley represents a geological ‘unicum’ for the NA and it has been the focus of scientific debate for a long time, due to the occurrence in the area of the ‘Coltre della Val Marecchia (CVM)’, a complex stack of allochthonous and semi-allochthonous units emplaced in a foredeep basin during the Late Miocene to Early Pliocene. In order to clarify the geological evolution for this area, the lithostratigraphic relationships and the tectonic framework have been studied, allowing better understanding of the complex relationships between tectonics and sedimentation. The main result has been a new evolutionary framework for this sector of the orogen during the Late Miocene-Early Pliocene. Several new findings about the geological-structural setting and stratigraphy, result from the geological map presented here. These are overall supported by stratigraphic and tectonic evidence, which suggest time and modes of the CVM allochthonous emplacement within the Messinian-early Pliocene foredeep successions. Relationships between the allochthonous and autochthonous formations allowed recognition of two different bodies in the CVM, gravitationally emplaced following different trajectories and timing.
The economic impact of Mexico City’s smoke-free law

Objective To evaluate the economic impact of Mexico City’s 2008 smoke-free law d The Non-Smokers’ Health Protection Law on restaurants, bars and nightclubs. Material and methods We used the Monthly Services Survey of businesses from January 2005 to April 2009 d with revenues, employment and payments to employees as the principal outcomes. The results are estimated using a differences-in-differences regression model with ﬁxed effects. The states of Jalisco, Nuevo Leo´n and Me´xico, where the law was not in effect, serve as a counterfactual comparison group. Results In restaurants, after accounting for observable factors and the ﬁxed effects, there was a 24.8% increase in restaurants’ revenue associated with the smoke-free law. This difference is not statistically signiﬁcant but shows that, on average, restaurants did not suffer economically as a result of the law. Total wages increased by 28.2% and employment increased by 16.2%. In nightclubs, bars and taverns there was a decrease of 1.5% in revenues and an increase of 0.1% and 3.0%, respectively, in wages and employment. None of these effects are statistically signiﬁcant in multivariate analysis. Conclusions There is no statistically signiﬁcant evidence that the Mexico City smoke-free law had a negative impact on restaurants’ income, employees’ wages and levels of employment. On the contrary, the results show a positive, though statistically non-signiﬁcant, impact of the law on most of these outcomes. Mexico City’s experience suggests that smoke-free laws in Mexico and elsewhere will not hurt economic productivity in the restaurant and bar industries.
A Novel Hybrid Approach to Masked Face Recognition using Robust PCA and GOA Optimizer

The use of face masks has become ubiquitous across a wide range of industries and professions, including healthcare, food service, construction, manufacturing, retail, hospitality, transportation, education, and public safety. To overcome this challenge, masked face recognition has emerged as a vital technology in recent years. By utilizing advanced algorithms and deep learning techniques, masked face recognition enables accurate identification and authentication of individuals even in scenarios where masks are worn. This paper presents a novel method for recognizing faces with masks. The proposed method integrates deep learning-based mask detection, landmark and oval face detection, and robust principal component analysis (RPCA) to accurately identify and authenticate individuals wearing masks. A pretrained ssd-MobileNetV2 model is utilized to detect the presence and location of masks on a face, while landmark and oval face detection are used to identify and extract important facial features. RPCA is applied to separate the occluded and non-occluded components of an image, making the method more reliable in identifying faces with masks. To further optimize the performance of the proposed method, the Gazelle Optimization Algorithm (GOA) is used to optimize both the KNN features and the number of k for KNN. Experimental results demonstrate that the proposed method outperforms existing methods in terms of accuracy and robustness to occlusion, achieving a recognition rate of 97%. This represents a significant improvement over existing methods for masked face recognition. The proposed method has the potential to be applied in a wide range of real-world scenarios, such as security systems, access control, and public health measures. The results of this study demonstrate that the integration of deep learning-based mask detection, landmark and oval face detection, and RPCA can improve the accuracy and reliability of masked face recognition, even in challenging and complex environments. The proposed method can be further improved and extended in future research to address other challenges in this field.
Lexical tone as a cue in statistical word learning from bilingual input

Learners can track word-referent co-occurrences across individually-ambiguous naming events to form correct word-referent mappings, termed statistical word learning (SWL). Prior research largely focuses on learning from a single language input, where a referent co-occurs with a single word (1:1 mapping). Here, we tested adults’ SWL from a simulated bilingual environment, where one referent co-occurred with two words (2:1 mapping) and the two words were either differentiated by a linguistic cue (Mandarin lexical tones, Cued condition) or not (Uncued condition). Results showed that in the Cued condition, Chinese–English bilinguals (N = 38) outperformed Spanish–English bilinguals (N = 56) and English monolinguals (N = 55), while Spanish–English bilinguals and English monolinguals performed similarly. The three groups did not differ in the Uncued condition. Self-reported learning confidence and strategies showed limited conscious awareness of learning. Results demonstrate that familiarity with a linguistic cue boosts overall statistical word learning from bilingual input.
Analyzing the spatial interactions between rainfall levels and flooding prediction in São Paulo

Rainfall is one of the primary triggers for many geological and hydrological natural disasters. While the geological events are related to mass movements in land collapse due to waterlogging, the hydrological ones are usually assigned to runoff or flooding. Studies in the literature propose predicting mass movement events as a function of accumulated rainfall levels recorded at distinct periods. According to these approaches, a two‐dimensional rainfall levels feature space is segmented into the occurrence and non‐occurrence decision regions by an empirical critical curve (CC). Although this scheme may easily be extended to other purposes and applications, studies in the literature need to discuss its use for flooding prediction. In light of this motivation, the present study is unfolded in (1) verifying that defining CCs in the rainfall levels feature space is a practical approach for flooding prediction and (2) analyzing how geospatial components interact with rainfall levels and flooding prediction. A database containing the rainfall levels recorded for flooding and non‐flooding events in São Paulo city, Brazil, regarding the period 2015–2016, was considered in this study. The results indicate good accuracy for flooding prediction using only partial rain, which can be improved by adding physical characteristics of the flooding locations, demonstrating a direct correlation with spatial interactions, and rainfall levels.
Real Property Tax Collection in Sta. Josefa, Agusan Del Sur, Philippines: An Exploratory Research Analysis

This research study is conceptualized to provide information on the real property tax collection in Sta. Josefa, Agusan del Sur. This employs a documentary-descriptive-research method using secondary sources of information generated from archives, and documents such as the Certified List of Real Property Tax Delinquencies, and the Electronic New Government Accounting System. Moreover, JASP is utilized to illustrate the tax collection delinquency on real property with and without government intervention. The findings of this study include that there is a compelling linkage between government intervention on tax collection of real property. It describes the importance of the interventions as a way of improving collection efficiency and reducing tax delinquency.
Delivering soil water information to growers and consultants

An understanding of soil water processes and knowledge of how individual soils store water are important components of risk management in Australian dryland agriculture. Awareness of soil water status at sowing or when considering nitrogen application, can directly assist in operational decision making, as well as provide the basis on which to investigate more strategic crop and systems issues, using simulation tools such as APSIM (Keating et al. 2003) and its derivative product Yield Prophet ® (Hochman et al. 2005). When used as an input to simulation, location specific soil water information provides the opportunity to explore, at the paddock scale, the impact of management decisions on crop yield and gross margin (such as variety selection, sowing date, fertiliser timing and application rate) at low cost and little risk. As a result of a lack of specific soil water information for many regions of Australia, this project has focussed on farmer and consultant skills training in soil water management and the development of a database of soil characteristics appropriate for use at the paddock scale. This poster focuses on the type of training available to the agricultural fraternity and the functionality of the soils database.
10. DATA REPORT: MULTIPROXY GEOCHEMICAL CHARACTERIZATION OF OAE-RELATED BLACK SHALES AT SITE 1276, NEWFOUNDLAND BASIN

During Ocean Drilling Program Leg 210, a greatly expanded sedimentary sequence of continuous Cretaceous black shales was recovered at Site 1276. This section corresponds to the Hatteras Formation, which has been documented widely in the North Atlantic Ocean. The cored sequence extends from the lowermost Albian, or possibly uppermost Aptian, to the Cenomanian/Turonian boundary and is characterized by numerous gravity-flow deposits and sporadic, finely laminated black shales. The sequence also includes several sedimentary intervals with high total organic carbon (TOC) contents, in several instances of probable marine origin that may record oceanic anoxic events (OAE). These layers might correspond to the Cenomanian–Turonian OAE 2; the midCenomanian event; and OAE 1b, 1c, and 1d in the Albian. In addition, another interval with geochemical characteristics similar to OAE-type layers was recognized in the Albian, although it does not correspond to any of the known OAEs. This study investigates the origin of the organic matter contained within these black shale intervals using TOC and CaCO3 contents, Corg/Ntot ratios, organic carbon and nitrogen isotopes, trace metal composition, and rock-eval analyses. Most of these black shale intervals, especially OAE 2 and 1b, are characterized by low δ15N values (<0‰) commonly observed in mid-Cretaceous black shales, which seem to reflect the presence of an altered nitrogen cycle with rates of nitrogen fixation significantly higher than in the modern ocean. 1Arnaboldi, M. , and Meyers, P.A. , 2006. Data report: multiproxy geochemical characterization of OAErelated black shales at Site 1276, Newfoundland Basin. In Tucholke, B.E. , Sibuet, J.-C. , and Klaus, A. (Eds.), Proc. ODP, Sci. Results, 210: College Station, TX (Ocean Drilling Program), 1–16. doi:10.2973/odp.proc.sr.210. 102.2006 2Marine Geology and Geochemistry Program, Department of Geological Sciences, The University of Michigan, 1100 North University Avenue, Ann Arbor MI 48109-1063, USA. Correspondence author: marna@umich.edu Initial receipt: 21 November 2005 Acceptance: 5 May 2006 Web publication: 21 November 2006 Ms 210SR-102 M. ARNABOLDI AND P.A. MEYERS DATA REPORT: MULTIPROXY GEOCHEMICAL CHARACTERIZATION 2
Seismic Interpretation of Contractional Fault-Related Folds

This AAPG Seismic Atlas serves as an instructional guide and resource for the interpretation of complex structures imaged in seismic reflection profiles using quantitative fault-related folding theories. The emphasis is on contractional fault-related folds, including fault-bend folds, fault-propagation folds, detachment folds, shear fault-bend folds, imbricate thrust systems, and structural wedges. These types of structures form the majority of the large hydrocarbon traps in both orogenic and passive-margin fold and thrust belts worldwide. The Atlas is divided into two complimentary parts. The first section illustrates the application of fault-related folding theories to many well-imaged seismic examples by way of step-by-step interpretations and ubiquitous models. A compilation of 25 case studies from petroleum basins around the world comprises the second section of the Atlas. The volume is intended to assist E&P professionals involved in seismic interpretation for the purposes of trap delineation and reservoir characterization, to aid those who evaluate structural interpretations in order to assign and reduce drilling risks, and to serve as a manual for anyone interested in applying the theories of fault-related folding to seismic interpretation.
STUDY OF THE LATENT HEAT ENERGY AND THE SENSIBLE HEAT ENERGY IN THE ATMOSPHERE OVER YANGTZE-HUAIHE RIVER VALLEY DURING SUMMER FLOOD AND DROUGHT

The physical causes leading to the occurrence of drought and flood disasters are mainly due to the anomaly of water and heat budget and circulation resulting from the abnormal energy transport in the atmosphere and on earth.Taking the data of water and heat in the years with summer flood and drought, the latent heat energy and sensible heat energy in the whole atmosphere column over Yangtze-Huaihe area and in each of the ten atmosphere layers in the column from the ground to 150 LPa are calculated. The features of the temporal and spatial n of the energy, its transport and convergence(divergence) are analyzed and compared. Thus the causes of disaster formation are explored.
Cognitive deficits profiles in the first-episode of schizophrenia, clinical high risk of psychosis, and genetically high-risk of psychosis

Background Cognitive deficits are core characteristics of schizophrenia, presenting before the emergence of psychotic symptoms. Individuals with a clinical high-risk for psychosis (CHR) and those with genetically high-risk of psychosis (GHR) also exhibit cognitive impairments. Nonetheless, it remains uncertain in which domains of cognitive impairments in these two groups were more similar to those of schizophrenia patients. Moreover, it is unclear which domains of impairment are caused by quality factors and which are more related to the state of disease. This research initiative aimed to extensively examine the distinct cognitive impairment profiles among the CHR, GHR, and first-episode schizophrenia (FES) cohorts. Methods We compared the cognitive functions of the three groups and a healthy control group (HCs) using the MATRICS Consensus Cognitive Battery (MCCB). The participants for this study were recruited from the Beijing Anding Hospital of Capital Medical University. Our sample consisted of 56 patients with FES, 42 with CHR, 26 with GHR, and 62 HCs. The participants across all groups were matched in terms of gender, age, and level of education. Results Individuals with FES, GHR, and CHR showed significant impairment across the majority of MCCB domains, with the exception of visual learning, in comparison to HCs. None of the MCCB domains demonstrated a discerning ability to accurately differentiate between individuals with CHR and those with GHR. In the speed of processing and attention/vigilance domains, individuals with GHR and CHR exhibited scores between those of FES and HCs, with all group differences reaching statistical significance. This pattern of results indicates an intermediate level of cognitive function in individuals with GHR and CHR. Conversely, the levels of impairment observed in working memory and verbal learning were relatively consistent across all three groups: FES, CHR, and GHR. Notably, individuals in the CHR group exhibited performance akin to that of the HCs in the reasoning/problem-solving domain, while showing significant differences from the FES group, with the CHR individuals demonstrating better performance. Additionally, individuals with GHR displayed performance in social cognition similar to that of the HCs, while also demonstrating significant distinctions from the FES group, with the GHR individuals demonstrating better performance. Conclusion Significant cognitive deficits exist in individuals with CHR, GHR, and FES, and these deficits vary across domains. Processing speed and attention/vigilance could potentially serve as robust biomarkers for identifying individuals at a risk of psychosis. The impairment observed in reasoning/problem-solving abilities might signify a qualitative trait, whereas deficits in social recognition could indicate a state characteristic specific to schizophrenia.