Miracle-dz/UniFAR-FTUs huggingface dataset:
Generation of High Resolution DSM Using UAV Images

SUMMARY Generating High Resolution DSM often demands highly accurate data. Among the range of terrestrial and aerial methods available to produce such a dataset, this project tests the utility of images acquired by a fixed wing, low cost Unmanned Aerial Vehicle (UAV). The data processing of UAV images have been carried out using the algorithms ranging from classical photogrammetry to modern Computer Vision (CV) algorithms. Nowadays, the use of UAV has increased to offer fast, easy and cost effective way to capture high resolution images for a comparatively smaller area. In this paper, we present a state-ofthe-art photogrammetry and image processing techniques provided by different software and their algorithms. The key element in a UAV photogrammetric data processing of the images which have been obtained with large variation in its geometry is the accurate georeferencing. 27 high resolution (2.4 cm average spatial resolution) UAV-acquired images of a sand mine at Tielt-Winge, Belgium has been used for this project. All the images have been acquired by a Sony Nex-5R digital camera mounted on a Trimble UX5 Imaging Rover, a fixed wing UAV. Although three software: LPS, AgiSoft PhotoScan and PIX4D were used for image processing. The identified algorithms and limitations in processing are valid for most other commercial photogrammetric software available on the market. The effort and the achievable accuracy of DSM result from every process are compared using the highly accurate ground control points as the reference data. The comparison of the DSM is performed through difference of DSM, RMSE and visual interpretation and to conclude SIFT algorithm and Dense Stereo matching provide good result for UAV data compared to traditional digital image matching using Forstner interest operator and ultimately provided centimeter level accuracy in the output results. However for certain areas like forest and vegetation, poor results were obtained due to poor image matching.
Aspects of Spatial Cognition in Parks

Studies of the conceptual structures that support spatial cognition, suggest a common basis for spatial and linguistic memory. Furthermore, studies of route descriptions provide evidence that selecting crucial information units in these directions is based on metacognitive knowledge that is largely independent of a specific environment. In this paper, we investigated spatial memory as revealed through drawn maps, with a view to exploring this common basis and testing for the presence of metacognitive knowledge in the production of maps. Three experiments were performed. In the first, both individuals with geomatics expertise and those without were asked to draw maps from their memories of the Plains of Abraham Park in Quebec City. These productions were then compared and analyzed. This experiment led to a rich set of results, including the observation that individuals with and without geomatics expertise proceed somewhat differently when drawing maps. In a second experiment, an independent group was asked to judge the resulting maps to determine “better” and “poorer” maps. Evidence was presented that supports the notion of metacognitive knowledge about what constitutes a good map. Finally, in a third experiment, a third group was asked to remove non-essential features from a consolidated map that incorporated all features drawn by all participants in the first experiment. This experiment likewise provided evidence of metacognitive knowledge about maps independent of the environment studied. We conclude with some remarks concerning the likely nature of the common basis that supports both linguistic and cartographic representations of environmental space.
A Hybrid Approach to Web Service Recommendation Based on QoS-Aware Rating and Ranking

As the number of Web services with the same or similar functions increases steadily on the Internet, nowadays more and more service consumers pay great attention to the non-functional properties of Web services, also known as quality of service (QoS), when finding and selecting appropriate Web services. For most of the QoS-aware Web service recommendation systems, the list of recommended Web services is generally obtained based on a rating-oriented prediction approach, aiming at predicting the potential ratings that an active user may assign to the unrated services as accurately as possible. However, in some application scenarios, high accuracy of rating prediction may not necessarily lead to a satisfactory recommendation result. In this paper, we propose a ranking-oriented hybrid approach by combining the item-based collaborative filtering and latent factor models to address the problem of Web services ranking. In particular, the similarity between two Web services is measured in terms of the correlation coefficient between their rankings instead of between the traditional QoS ratings. Besides, we also improve the measure NDCG (Normalized Discounted Cumulative Gain) for evaluating the accuracy of the top K recommendations returned in ranked order. Comprehensive experiments on the QoS data set composed of real-world Web services are conducted to test our approach, and the experimental results demonstrate that our approach outperforms other competing approaches.
Differential Association of the Conserved SUMO Ligase Zip3 with Meiotic Double-Strand Break Sites Reveals Regional Variations in the Outcome of Meiotic Recombination

During the first meiotic prophase, programmed DNA double-strand breaks (DSBs) are distributed non randomly at hotspots along chromosomes, to initiate recombination. In all organisms, more DSBs are formed than crossovers (CO), the repair product that creates a physical link between homologs and allows their correct segregation. It is not known whether all DSB hotspots are also CO hotspots or if the CO/DSB ratio varies with the chromosomal location. Here, we investigated the variations in the CO/DSB ratio by mapping genome-wide the binding sites of the Zip3 protein during budding yeast meiosis. We show that Zip3 associates with DSB sites that are engaged in repair by CO, and Zip3 enrichment at DSBs reflects the DSB tendency to be repaired by CO. Moreover, the relative amount of Zip3 per DSB varies with the chromosomal location, and specific chromosomal features are associated with high or low Zip3 per DSB. This work shows that DSB hotspots are not necessarily CO hotspots and suggests that different categories of DSB sites may fulfill different functions.
The Distribution of eIF4E-Family Members across Insecta

Insects are part of the earliest faunas that invaded terrestrial environments and are the first organisms that evolved controlled flight. Nowadays, insects are the most diverse animal group on the planet and comprise the majority of extant animal species described. Moreover, they have a huge impact in the biosphere as well as in all aspects of human life and economy; therefore understanding all aspects of insect biology is of great importance. In insects, as in all cells, translation is a fundamental process for gene expression. However, translation in insects has been mostly studied only in the model organism Drosophila melanogaster. We used all publicly available genomic sequences to investigate in insects the distribution of the genes encoding the cap-binding protein eIF4E, a protein that plays a crucial role in eukaryotic translation. We found that there is a diversity of multiple ortholog genes encoding eIF4E isoforms within the genus Drosophila. In striking contrast, insects outside this genus contain only a single eIF4E gene, related to D. melanogaster eIF4E-1. We also found that all insect species here analyzed contain only one Class II gene, termed 4E-HP. We discuss the possible evolutionary causes originating the multiplicity of eIF4E genes within the genus Drosophila.
An antigen encoded by the latency-associated transcript in neuronal cell cultures latently infected with herpes simplex virus type 1

During latent infection of neurons with herpes simplex virus type 1, viral transcription is restricted to the latency-associated transcripts (LATs). These RNAs contain open reading frames, but detection of a protein encoded by the LATs has not been reported. We used immunocytochemical techniques to demonstrate that an antiserum directed against a bacterially expressed fusion protein containing part of a LAT-encoded polypeptide recognized an antigen present in primary neurons latently infected in vitro. This antigen (called LAA, for latency-associated antigen) was not detected in mock-infected neurons, in productively infected Vero cells, or in neurons latently infected with a mutant virus carrying a deletion in the LAT gene. By Western immunoblot analysis, we demonstrated the presence of a protein with an apparent molecular mass of 80 kDa recognized by the anti-LAA antiserum in latently infected neurons.
Groupware Design for Online Diagnosis Support

In this paper, we present a groupware model that is based on the integration of Web services technologies with software agents. The purpose is to design a collaborative environment in the context of CAD (computer-aided diagnosis), enabling doctors to collaborate together in order to achieve a proper diagnosis of patients' files, and this by dynamically integrating new functionalities as Web services into their application, without stopping the diagnosis process, and hence achieving an efficient treatment. Our work is motivated by the fact that a collaborative and dynamic system is still missing in the hospitalization environment, where very few work in the literature has been done that aims to tailor the services by end-users for a better diagnosis process. We apply our model on the health care domain by providing a tailorable collaborative computer aided diagnosis.
Workload prediction for cloud computing elasticity mechanism

Elasticity is the key feature of cloud computing technology, which can automatically reduce and add resources to meet users' need. In order to achieve elasticity, we should find how and when to trigger the elasticity automatic scaling mechanism. Workload analyzing is a popular method to solve this problem. In this paper, we propose three models to predict the workload based on analyzing monitoring data. Firstly, we use time series approach to analyze monitoring data. Then, we propose a Kalman filter model to predict the cloud workload. Next, we put forward a novel pattern matching model to analyze and predict the workload. Based on these predicting, we propose a new trigger strategy for cloud computing elasticity automatic scaling mechanism. Finally, experimental results show that our models not only improve the prediction accuracy, but also reduce the automatic scaling delay.
LABOR SUPPLY AND GROWTH EFFECTS OF ENVIRONMENTAL POLICY UNDER TECHNOLOGICAL RISK

This paper analyzes the effects of technological risk on long-run growth when labor supply is elastic and production gives rise to a pollution externality. We show that the randomness of production, as well as the endogeneity of labor supply, affects the equilibrium solutions for the social planner and for the market economy. We analyze the effects of environmental policy, discuss conditions for an optimal policy, and find that the response of labor supply to changes in the model parameters and to variations in the policy instruments crucially depends on the volatility of output.
Assessment of hand hygiene compliance after hand hygiene education among health care workers in Cambodia

ABSTRACT Health care-associated infection (HCAI) is the most frequent adverse event for hospitalized patients. Hand hygiene is a simple and effective solution to protect patients from HCAI. This study aimed to introduce hand hygiene to health care workers based on the World Health Organization guideline for reducing HCAI in Cambodia and to assess their behavioral patterns on hand hygiene. All health care workers at Kampong Cham provincial hospital had lectures and practice on hand hygiene in January 2012. The surveys for hand hygiene compliance (HHC) were performed after 6 months, 1 year and 2 years, respectively. The number of surgical site infections (SSI) was counted in 2011 and 2014. Our analysis used the data of 58 workers, who were observed at all three points, although 139 workers were observed during the study period. The average of HHC at 6 months, 1 year and 2 years were 62.37%, 85.76% and 80.36%, respectively. The improved group (HHC 2 years/1 year≧1) had 32 workers, whereas the worsened group (HHC 2 years/1 year<1) had 26. There was a significant difference in departments of the two groups (P=0.011) but not in sex, age or occupations. The improved group had more workers of General (31.2% vs. 19.2%), Surgical (25.0% vs. 11.5%) and Infection (21.9% vs. 11.5%) categories compared to the worsened group. The incidence of SSI was improved from 32.26% in 2011 to 0.97% in 2014. Our results suggest that the education and the survey on hand hygiene are effective for reducing HCAI in Cambodia.
Improving English-Russian sentence alignment through POS tagging and Damerau-Levenshtein distance

The present paper introduces approach to improve English-Russian sentence alignment, based on POS-tagging of automatically aligned (by HunAlign) source and target texts. The initial hypothesis is tested on a corpus of bitexts. Sequences of POS tags for each sentence (exactly, nouns, adjectives, verbs and pronouns) are processed as “words” and DamerauLevenshtein distance between them is computed. This distance is then normalized by the length of the target sentence and is used as a threshold between supposedly mis-aligned and “good” sentence pairs. The experimental results show precision 0.81 and recall 0.8, which allows the method to be used as additional data source in parallel corpora alignment. At the same time, this leaves space for further improvement.
Augmented reality using optical flow

The paper deals with the application of Lucas-Kanade optical flow algorithm to develop an augmented reality (AR) system. Merging of a live view of the physical real world with context-related computer-rendered images to create a mixed image is a challenging problem. A virtual object has to be located in the correct pose and position in real time and perspective. Besides the occlusion problem need to be taken into consideration. In the paper a computer-vision based method for AR systems based on the fiducial marker matching is proposed. For simplicity black square was used as the marker. This method consists of two main steps. The initial step uses Hough's transformation to detect the marker initial position and to select the marker tracked points. In the second step for each image frame these selected points are being tracked using Lucas-Kanade optical flow method. The positions of the selected points are used for calculating the pose and position of a virtual object. Unlike existing method proposed system using optical flow to increase speed performance. The examples of AR applications using the proposed algorithm are provided and discussed.
Oil rents, governance quality, and the allocation of talents in developing countries

Evidence shows that the allocation of talented people is not neutral for growth. Thus, a country with a large population of law concentrators tends to develop rent-seeking activities that reduce growth. A country with a large population of engineers tends to foster innovation and strengthen growth. But what determines the allocation of talents? This question has not yet been empirically examined. This paper contributes to fill this gap. Based on a sample of 69 developing countries the paper highlights that oil rents determine the allocation of talents but this effect is not linear. It largely depends on the quality of governance. While, oil rents in well governed countries tend to orient talents towards productive activities, oil rents in badly governed countries tend to orient talents towards rent-seeking activities. These results are robust to different specifications, datasets on governance quality and estimation methods.
A Unified Anisotropic Elasto-plastic Model for Sand 1

This paper presents a unified approach to model the influence of fabric anisotropy 6 and its evolution on both the elastic and plastic responses of sand. A physically based fabric 7 tensor is employed to characterize the anisotropic internal structure of sand. It is incorporated 8 into the nonlinear elastic stiffness tensor to describe anisotropic elasticity, and is further 9 included explicitly in the yield function, the dilatancy relation and the flow rule to characterize 10 the anisotropic plastic sand response. The physical change of fabric with loading is described 11 by a fabric evolution law driven by plastic strain which influences both the elastic and the 12 plastic sand behavior. The proposed model furnishes a comprehensive consideration of both 13 anisotropic elasticity and anisotropic plasticity, particularly the nonlinear change of elastic 14 stiffness with the evolution of fabric during the plastic deformation of sand. It also offers a 15 natural and rational way to capture the non-coaxial behavior in sand caused by anisotropy. It 16 also facilitates easy determination of the initial anisotropy in sand based on simple laboratory 17 tests and avoids the various arbitrary assumptions on its value made by many previous studies. 18 The model predictions on sand behavior compare well with test data. 19 20
Clinical Cancer esearch ing , Diagnosis , Prognosis ch 1 Expression Predicts an Unfavorable Prognosis Serves as a Therapeutic Target of R ients with Neuroblastoma

Downloa pose: Notch signaling has been implicated to play a critical role in the tumorigenesis of neuroblas(NB) and can modulate calreticulin (CRT) expression that strongly correlates with tumor differenand favorable prognosis of NB. We thus sought to determine how Notch regulates CRT expression ffects NB tumor behavior. erimental Design: The Notch-dependent regulation of CRT expression in cultured NB cells was ed by confocal microscopy and Western blotting. Notch1 protein expression in 85 NB tumors amined by immunohistochemistry and correlated with the clinicopathologic/biological characters patients. The progression of NB tumors in response to attenuated Notch signaling was examined by a xenograft mouse model. ults: We showed that CRT is essential for the neuronal differentiation of NB cells elicited by inhiof Notch signaling. This effect was mediated by a c-Jun-NH2-kinase–dependent pathway. FurtherNB tumors with elevated Notch1 protein expression were strongly correlated with advanced tumor , MYCN amplification, an undifferentiated histology, as well as a low CRT expression level. Most tantly, the opposing effect between Notch1 and CRT could reciprocally affect the survival of NB ts. The administration of a γ-secretase inhibitor into a xenograft mouse model of NB significantly essed the tumor progression. clusions:Our findings provide the first evidence that a c-Jun-NH2-kinase-CRT–dependent pathway ntial for the neuronal differentiation elicited by Notch signaling blockade and that Notch1 and CRT is esse can synergistically predict the clinical outcomes of NB patients. The present data suggest that Notch signaling could be a therapeutic target for NB. Clin Cancer Res; 16(17); 4411–20. ©2010 AACR.
Adolescent Sexual Victimization

This study investigates the experience of sexual victimization among American youth. The objective is to determine who adolescents tell of their victimization and whether the choice of confidant influences the likelihood of the offender being arrested. Using data from the 1995 National Survey of Adolescents, the authors found that most adolescents do not turn to official sources but instead tell family members and friends about their sexual victimization. Although only 13% of sexual assault disclosures resulted in an arrest of the offender, arrest was more likely to occur when the assault was initially reported to the victim's mother. A much less common choice of confidant was mandatory reporters, professionals in contact with children who are required by law to report suspected and known child abuse. However, when mandatory reporters were informed, they were not consistent in reporting the offense to officials. Therefore, the authors suggest mandatory reporters are not offering the necessary support to adolescent victims of sexual abuse.
Modeling Uncertainties Using Interval Type-2 Fuzzy Logic based on Meteorological Systems

Interval type-2 fuzzy logic (IT-2 FL) is the process of developing IT-2 FL inference systems. The fuzzy inference system is basically elucidating non-linear mapping of input and output using fuzzy rules. High level of uncertainty and imprecision in database brings difficulty in determining the membership function’s suitable value. This produces computational complexities of the real-world applications. In type-2 fuzzy logic systems the membership function itself is fuzzy. In this paper, we describe how IT-2 FL can be used in modeling of data applications. As a proof-of-concept application, the system was implemented based on Meteorological and Oceanographic (MetOcean) dataset. The findings show that system has better modeling performance due to the application of type-2 fuzzy sets.
Communications in Mathematical Physics White-Noise and Geometrical Optics Limits of Wigner-Moyal Equation for Wave Beams in Turbulent Media

Starting with the Wigner distribution formulation for beam wave propagation in Hölder continuous non-Gaussian random refractive index fields we show that the wave beam regime naturally leads to the white-noise scaling limit and converges to a Gaussian white-noise model which is characterized by the martingale problem associated to a stochastic differential-integral equation of the Itô type. In the simultaneous geometrical optics the convergence to the Gaussian white-noise model for the Liouville equation is also established if the ultraviolet cutoff or the Fresnel number vanishes sufficiently slowly. The advantage of the Gaussian white-noise model is that its n-point correlation functions are governed by closed form equations.
Virtual Reality Behavioral Therapy

Mental health and substance abuse patients face many challenges in receiving effective long-term outpatient behavioral therapies, including issues related to accessibility and personalized care. Mobile health technologies, particularly those integrating virtual reality (VR), are increasingly becoming more accessible and affordable, thus providing a potential avenue to deploy outpatient behavioral therapy. This paper proposes a method to address the aforementioned challenges by personalizing and validating VR simulation content for behavioral therapy. An initial demonstration will be performed for tobacco cessation, which is a critical public health treatment area for mental illness and substance abuse. The method empirically builds smoker personas from theoretically grounded survey content. The personas are then used to design and pilot VR simulation modules tailored to behavioral interventions, which will be tested in the patient population. The VR simulation will record a subject’s emotions and brain activities in real-time through subjective (surveys) and objective (neurophysiology) measures of emotional response. The overall goal of the study is to validate the VR content by demonstrating that significant differences are seen in emotional response when presenting content personalized for the patient.