nils-herrmann/clean_scirepeval huggingface dataset:
A Semantic Modelling Framework Based Method for Building Reconstruction from Point Clouds
Venue: Remote. Sens.

Over the past few years, there has been an increasing need for semantic information in automatic city modelling. However, due to the complexity of building structure, the semantic reconstruction of buildings is still a challenging task because it is difficult to extract architectural rules and semantic information from the data. To improve the insufficiencies, we present a semantic modelling framework based approach for automated building reconstruction using the semantic information extracted from point clouds or images. In this approach, a semantic modelling framework is designed to describe and generate the building model, and a workflow is established for extracting the semantic information of buildings from an unorganized point cloud and converting the semantic information into the semantic modelling framework. The technical feasibility of our method is validated using three airborne laser scanning datasets, and the results are compared with other related works comprehensively, which indicate that our approach can simplify the reconstruction process from a point cloud and generate 3D building models with high accuracy and rich semantic information.
Comparison of ZEB1 and Leica C10 indoor laser scanning point clouds

We present a comparison of point cloud generation and quality of data acquired by Zebedee (Zeb1) and Leica C10 devices which are used in the same building interior. Both sensor devices come with different practical and technical advantages. As it could be expected, these advantages come with some drawbacks. Therefore, depending on the requirements of the project, it is important to have a vision about what to expect from different sensors. In this paper, we provide a detailed analysis of the point clouds of the same room interior acquired from Zeb1 and Leica C10 sensors. First, it is visually assessed how different features appear in both the Zeb1 and Leica C10 point clouds. Next, a quantitative analysis is given by comparing local point density, local noise level and stability of local normals. Finally, a simple 3D room plan is extracted from both the Zeb1 and the Leica C10 point clouds and the lengths of constructed line segments connecting corners of the room are compared. The results show that Zeb1 is far superior in ease of data acquisition. No heavy handling, hardly no measurement planning and no point cloud registration is required from the operator. The resulting point cloud has a quality in the order of centimeters, which is fine for generating a 3D interior model of a building. Our results also clearly show that fine details of for example ornaments are invisible in the Zeb1 data. If point clouds with a quality in the order of millimeters are required, still a high end laser scanner like the Leica C10 is required, in combination with a more sophisticated, time consuming and elaborative data acquisition and processing approach.
Semantic enrichment of a point cloud based on an octree for multi storey pathfinding

Acquiring point clouds of indoor environments became increasingly accessible in recent years. However, the resulting 3D point cloud data is unstructured, and does not contain enough information to be useful for complex tasks like pathfinding. Indoor models which are currently derived from point clouds do not include furniture and stairs. The necessary graph to enable multi storey pathfinding is not available in the point cloud. This thesis proposes a workflow to semantically enrich indoor point clouds using an octree data structure. Meaning is added to the point cloud scene that allows to act as a basis for a graph. This graph can then follow navigation constraints of humans through an indoor environment. The approach for semantic enrichment of this study is capable of separating storeys, detecting floors, walls, stairs and obstacles like furniture. Strict preconditions are used, like walls being perpendicular to each other and using noise free point clouds. The implementation works as a proof of concept and the octree proves to be a helpful data structure. The contribution is a novel approach of using octrees for the semantic enrichment of indoor point clouds, including the detection of stairs. Combining and extending different works from various fields of research helped to develop the presented methodology. The semantic classification of floors and stairs in 3D point clouds allows to create a graph across multiple storeys. A big part of the methodology was implemented and tested on different types of buildings and scanned with dissimilar kinds of laser scanners. Mobile scanners were found to be advantageous, because they are less dependent on the line of sight. On top of that, they can provide a path of the scanner, which is precious information that can support several structuring improvements of the acquired data. The octree generalises the point cloud to leafs and adds a structure to the empty space. This does not only improve the calculation performance, but also provides more distinguishable results. Concluding, the thesis proposes to extent the framework to cover a wider range of architectural structures. Furthermore, future research should deepen the knowledge for the stair detection of the presented conceptual framework. As the representation of stairs differ for every scanner, future research should focus on point clouds acquired by one kind of scanner first.
The effect of rail travel time on airline fares: First evidence from the Italian passenger market

The empirical evidence shows that travel time is crucial for rail transport to be a competitor to air transport. However, there are no papers testing whether travel time has a direct effect on airline pricing. This paper is a step towards filling this gap. We test and quantify the effect of rail travel time on airline fares, using unique data at flight level. We find that airlines design pricing strategies taking into consideration the travel time of competing rail transport service. Airlines are found to set, on average, higher fares as rail travel time increases. However, the competitive pressure induced by rail travel time is perceived by airlines only as the day of departure gets closer: from the 40th to the day before departure it increases while it gradually decreases as the departure date gets further away.
Environmental Factors in Renal Disease: The Contribution of Urinary TractInfections in Nigerian Renal Disease Burden Research

Asymptomatic and mild nature of urinary tract infections (UTIs) make them underrated, overlooked but dangerous, because they are prelude to most renal diseases. Like asymptomatic UTIs, some renal diseases are symptomless until they have reached advanced stage, making their victims easily vulnerable to complications before actual diagnosis of renal disease may be made. This study was aimed at surveying the environmental factors responsible for the renal disease burden of Nigeria with a particular focus on the contributions of UTIs.  Urine samples from renal disease patients of the University of Nigeria teaching hospital (UNTH) Enugu, Nigeria were analyzed for bacteriuria using standard microbiological procedures.  An overall incidence of 28% bacteriuria was obtained, based on the criterion of significant bacteriuria 105 colonies/ml) While fungal yeasts, Candida albicans contributed 30% various bacterial species jointly accounted for 70% of the entire microbial agents responsible for UTIs among the subjects. Subsequent Gram's, microscopy and biochemical characterization tests revealed seven bacterial species viz Escherichia coli (29% Klebsiella spp (22% Proteus mirabilis (14% Pseudomonas aeruginosa (7% Streptococcus faecalis (7% Staphylococcus aureus (7% and Staphylococcus epidermidis (14% Gender distribution of the isolates showed that S. aureus was isolated from the males while E. coli, Proteus mirabilis, Streptococcus faecalis and Pseudomonas aeruginosa from the females; Klebsiella spp was isolated from the males (33% and females (67% respectively, while S. epidermidis was isolated equally (50% from both sexes. Adoption of leucocytes' presence in urine as part of diagnostic criteria revealed significant bacteriuria with significant pyuria (21% significant pyuria without significant bacteriuria (52% and significant bacteriuria without significant pyuria (7% no significant bacteriuria without significant pyuria (20% Also, urinalyses gave proteinuria (84% haematuria (45% and glycosuria (6%  The study revealed an overall incidence of 28% bacteriuria. Though UTIs by sundry bacterial organisms and fungal Candida albicans made reckonable contributions to the renal disease load of UNTH, Enugu, additional evidence from urinalyses revealing proteinuria, glycosuria and haematuria, etc. suggest that apart from the UTIs, diabetes mellitus and/or urinary schistosomiasis (possibly accounting for the haematuria) are part of the diseases complex defined by yet to be identified factors (possibly including chemical entities) in our environment that determine the burden and patterns of renal diseases profile of Nigeria. Further search is thus warranted.
Tests of General Relativity with GW150914.
Venue: Physical review letters

The LIGO detection of GW150914 provides an unprecedented opportunity to study the two body motion of a compact object binary in the large velocity, highly nonlinear regime, and to witness the final merger of the binary and the excitation of uniquely relativistic modes of the gravitational field. We carry out several investigations to determine whether GW150914 is consistent with a binary black hole merger in general relativity. We find that the final remnant's mass and spin, as determined from the low frequency (inspiral) and high frequency (postinspiral) phases of the signal, are mutually consistent with the binary black hole solution in general relativity. Furthermore, the data following the peak of GW150914 are consistent with the least damped quasinormal mode inferred from the mass and spin of the remnant black hole. By using waveform models that allow for parametrized general relativity violations during the inspiral and merger phases, we perform quantitative tests on the gravitational wave phase in the dynamical regime and we determine the first empirical bounds on several high order post Newtonian coefficients. We constrain the graviton Compton wavelength, assuming that gravitons are dispersed in vacuum in the same way as particles with mass, obtaining a 90% confidence lower bound of 10^{13} km. In conclusion, within our statistical uncertainties, we find no evidence for violations of general relativity in the genuinely strong field regime of gravity.
Small Molecule PROTACS: New Approaches to Protein Degradation.
Venue: Angewandte Chemie

The current inhibitor based approach to therapeutics has inherent limitations owing to its occupancy based model: 1) there is a need to maintain high systemic exposure to ensure sufficient in vivo inhibition, 2) high in vivo concentrations bring potential for off target side effects, and 3) there is a need to bind to an active site, thus limiting the drug target space. As an alternative, induced protein degradation lacks these limitations. Based on an event driven model, this approach offers a novel catalytic mechanism to irreversibly inhibit protein function by targeting protein destruction through recruitment to the cellular quality control machinery. Prior protein degrading strategies have lacked therapeutic potential. However, recent reports of small molecule based proteolysis targeting chimeras (PROTACs) have demonstrated that this technology can effectively decrease the cellular levels of several protein classes.
Psicopatologia en el paciente con obesidad

In the past two decades the traditional definition of obesity has been challenged because it emphasizes the centrality of adipose tissue (a less inert and more interconnected tissue than previously thought) and it preserves the 19th century model that reduces the problem into simple imbalance between energetic incomes and expenditures vaguely modulated by psychosocial and neuroendocrine factors considered as mere adjuvants.  To relate psychopathology and obesity prioritizing the emotional behavioral origin of adiposity, and start the breakdown of the general obesity group into emotional and behavioral profiles that warrant differential treatments.  Descriptive data of 180 patients treated in the Overweight and Obesity Program of Infanta Leonor University Hospital (Madrid, Spain) a semi structured interview and psychometric tests were performed. Association tests between affective (anxiety and depression) and Body Mass Index (BMI) variables are shown.  Most patients showed high scores in psychopathology; 80.9% had major depressive symptomatology, 56.39% had high anxiety trait, 48.26% had high anxiety state, 24.4% met criteria for binge eating disorder and 11.9% of bulimia nervosa; 17.3% had criteria for posttraumatic stress disorder.  Our results support the association between obesity and psychopathology.
Vertical or Horizontal Scaling for Web Information Systems

As the number of Web users and the amount of information produced keep growing rapidly, information systems need to be scaled up constantly. Usually scaling methods of information systems suffer from being chosen by experience, this paper studied on quantitative optimal selection of vertical/horizontal scaling methods. According to investigation and statistics, we assumed the cost growth formula of the key performance parameters reasonably. Then five key parameters of systems were chosen to construct Kiviat graphs and the areas of Kiviat graphs were computed to evaluate system performance. Next, the quantitative function relation between the performance of information system and the cost of system scaling was established, and then three optimal selection algorithms for system scaling were proposed. Finally, some case studies demonstrate that algorithms are feasible and have a great significance for guiding system scaling.
Information processing with large scale optical integrated circuits
Venue: 2016 IEEE International Conference on Rebooting Computing (ICRC)

Photonic integrated circuits (PICs) offer an enticing platform for further advances in computation. Photonic communications hardware is already widely used within datacenters and is now reaching into the board and chip level. This trend is driving the development of more complex PICs that are more tightly integrated into computing systems. This PIC technology could be attractive for building photonic computational accelerators and for incorporating all optical signal processing tasks into photonic communications and sensing. At Hewlett Packard Labs, we are using a silicon photonics platform to build complex PICs with many hundreds of components, including nonlinear components. We use these PICs to test various approaches to photonic computation, including neuromorphic approaches as well as traditional logic circuits. For example, we are currently fabricating a circuit to solve the so called Ising problem, a classic problem of solid state physics that turns out to be equivalent to a number of combinatorial optimization problems. The circuit is closely related to Hopfield neural networks. In parallel, we are investigating PICs based on photonic crystals in an InGaAs platform. These PICs offer radically reduced power consumption compared to CMOS circuits, potentially consuming less than 1 fJ per elementary operation.
Importancia de la educacion emocional en la formacion inicial del profesorado

Aquest article presenta la importancia de formar en competencies emocionals als futurs docents de les diferents etapes educatives. L'Educacio Emocional a tot esser huma, i en especial als docents, permet donar resposta als nous reptes que planteja la societat del segle XXI: educar per a potenciar la capacitat critica en una societat del coneixement, capacitat per tolerar la frustracio, postergar la recompensa i immediatesa i, sobretot, guiar els futurs adults cap a la competencia entesa com a adaptacio, superacio i realitzacio intra i interpersonal, no com a rivalitat i poder.
Acquired and Congenital Hemolytic Anemia
Venue: Pediatrics in Review

1. Suzie A. Noronha, MD* 1. *Division of Pediatric Hematology/Oncology, University of Rochester, Golisano Children's Hospital, Rochester, NY. 1. Pediatricians and other general practitioners may not be aware of the significance of central nervous system disease in children who have sickle cell disease, particularly the more subtle silent infarct. 2. Pediatricians frequently fail to order a reticulocyte count or detect splenomegaly on physical examination before referring a patient with anemia. These findings are critical to diagnosing hemolytic anemia. After completing this article, the reader should be able to: 1. Recognize clinical features of hemolysis, including reticulocytosis and splenomegaly. 2. List the different types of acquired autoimmune hemolytic anemias that can manifest throughout childhood. 3. Understand the role of transfusion in the management of neurologic disease in patients who have sickle cell disease. 4. Review the spectrum of disease of a and b thalassemias. 5. Recognize clinical findings associated with hereditary spherocytosis. 6. Determine when to suspect glucose 6 phosphate dehydrogenase deficiency and how to counsel families on triggers to avoid. Hemolytic anemia (HA) affects a substantial proportion of the pediatric population globally. Many children are hospitalized every year due to sequelae of this heterogeneous disease. Clinicians should be facile in recognizing its presentation. HA may be defined as increased destruction of red blood cells (RBCs) RBCs are cleared from the circulation via extravascular or intravascular mechanisms (Figure) HA can be caused by congenital or acquired RBC abnormalities (Table 1) Figure. Mechanism of extravascular versus intravascular hemolysis. RBC=red blood cell. Courtesy of Jessica Shand, MD. View this table: Table 1. Classification of Common Hemolytic Anemias Extravascular hemolysis is mediated by the reticuloendothelial system (RES) of the spleen and liver. Most HAs, such as warm autoimmune hemolytic anemia (AIHA) sickle cell disease (SCD) and hereditary spherocytosis (HS) are characterized by extravascular hemolysis. The hallmark of extravascular hemolysis is
The effect of head related filtering and ear specific decoding bias on auditory attention detection.
Venue: Journal of neural engineering

We consider the problem of Auditory Attention Detection (AAD) where the goal is to detect which speaker a person is attending to, in a multi speaker environment, based on neural activity. This work aims to analyze the influence of head related filtering and ear specific decoding on the performance of an AAD algorithm.  We recorded high density EEG of 16 normal hearing subjects as they listened to two speech streams while tasked to attend to the speaker in either their left or right ear. The attended ear was switched between trials. The speech stimuli were administered either dichotically, or after filtering using Head Related Transfer Functions (HRTFs) A spatio temporal decoder was trained and used to reconstruct the attended stimulus envelope, and the correlations between the reconstructed and the original stimulus envelopes were used to perform AAD, and arrive at a percentage correct score over all trials.  We found that the HRTF condition resulted in significantly higher AAD performance than the dichotic condition. However, speech intelligibility, measured under the same set of conditions, was lower for the HRTF filtered stimuli. We also found that decoders trained and tested for a specific attended ear performed better, compared to decoders trained and tested for both left and right attended ear simultaneously. In the context of the decoders supporting hearing prostheses, the former approach is less realistic, and studies in which each subject always had to attend to the same ear may find over optimistic results.  This work shows the importance of using realistic binaural listening conditions and training on a balanced set of experimental conditions to obtain results that are more representative for the true AAD performance in practical applications.
Multimodal human attention detection for reading from facial expression, eye gaze, and mouse dynamics
Venue: SIAP

Affective computing has recently become an important area in human computer interaction research. Techniques have been developed to enable computers to understand human affects or emotions, in order to predict human intention more precisely and provide better service to user to enhance user experience. In this paper, we investigate into the detection of human attention level as a useful from of human affect, which could be influential in intelligent e learning applications. We adopt ubiquitous hardware available in most computer systems, namely, webcam and mouse. Information from multiple input modalities is fused together for effective human attention detection. We invite human subjects to carry out experiments in reading articles when being imposed upon different kinds of distraction to induce them into different levels of attention. Machine learning techniques are applied to identify useful features to recognize human attention level by building up user independent models. Our result indicate performance improvement with multimodal inputs from webcam and mouse over that of a single device. We believe that our work has revealed and intersting affective computing direction with potential application in e learning.
Multimodal human attention detection for reading
Venue: SAC

Affective computing in human computer interaction research enables computers to understand human affects or emotions to provide better service. In this paper, we investigate the detection of human attention useful in intelligent e learning applications. Our principle is to use only ubiquitous hardware available in most computer systems, namely, webcam and mouse. Information from multiple modalities is fused together for effective human attention detection. We invite human subjects to carry out experiments in reading articles being subjected to different kinds of distraction to induce different attention levels. Machine learning techniques are applied to identify useful features to recognize human attention level. Our results indicate improved performance with multimodal inputs, suggesting an interesting affective computing direction.