Miracle-dz/UniFAR-FTUs huggingface dataset:
Scene Detection in Videos Using Shot Clustering and Symbolic Sequence Segmentation

Video indexing requires the efficient segmentation of the video into scenes. In the method we propose, the video is first segmented into shots and key-frames are extracted using the global k-means clustering algorithm that represent each shot. Then an improved spectral clustering method is applied to cluster the shots into groups based on visual similarity and a label is assigned to each shot according to the group that it belongs to. Next, a method for segmenting the sequence of shot labels is applied, providing the final scene segmentation result. Numerical experiments indicate that the method we propose correctly detects most of the scene boundaries while preserving a good trade off between recall and precision.
Neurodevelopment of children exposed in utero to treatment of maternal malignancy

Cancer is the second most common cause of death during the reproductive years, complicating approximately 1/1000 pregnancies. The occurrence of cancer during gestation is likely to increase as a result of a woman's tendency to delay childbearing. Improved diagnostic techniques for malignancies increases detection of cancer during pregnancy. Malignant conditions during gestation are believed to be associated with an increase in poor perinatal and fetal outcomes that are often due to maternal treatment. Physicians should weigh the benefits of treatment against the risks of fetal exposure. To date, most reports have focused on morphologic observations made very close to the time of delivery with little data collected on children's long-term neurodevelopment following in utero exposure to malignancy and treatment. Because the brain differentiates throughout pregnancy and in early postnatal life, damage may occur even after first trimester exposure. The possible delayed effects of treatment on a child's neurological, intellectual and behavioural functioning have never been systematically evaluated. The goal of this report was to summarize all related issues into one review to facilitate both practitioners’ and patients’ access to known data on fetal risks and safety. © 2001 Cancer Research Campaign http://www.bjcancer. com
Stereotyped spatial patterns of functional synaptic connectivity in the cerebellar cortex

Motor coordination is supported by an array of highly organized heterogeneous modules in the cerebellum. How incoming sensorimotor information is channeled and communicated between these anatomical modules is still poorly understood. In this study, we used transgenic mice expressing GFP in specific subsets of Purkinje cells that allowed us to target a given set of cerebellar modules. Combining in vitro recordings and photostimulation, we identified stereotyped patterns of functional synaptic organization between the granule cell layer and its main targets, the Purkinje cells, Golgi cells and molecular layer interneurons. Each type of connection displayed position-specific patterns of granule cell synaptic inputs that do not strictly match with anatomical boundaries but connect distant cortical modules. Although these patterns can be adjusted by activity-dependent processes, they were found to be consistent and predictable between animals. Our results highlight the operational rules underlying communication between modules in the cerebellar cortex. DOI: http://dx.doi. org/10.7554/eLife.09862. 001
The Diagnostic Value of the Upper Lip Bite Test Combined with Sternomental Distance, Thyromental Distance, and Interincisor Distance for Prediction of Easy Laryngoscopy and Intubation: A Prospective Study

BACKGROUND:Accuracy of upper lip bite test (ULBT) has been compared with the Mallampati classification. In this study, we investigated whether the combination of the ULBT classification with sternomental distance (SMD), thyromental distance (TMD), and interincisor distance (IID) or a composite score can improve the ability to predict easy laryngoscopy and intubation compared with each test alone. METHODS:In a prospective study, 380 patients who were scheduled for elective surgery were selected randomly and enrolled in the study. Before inducing anesthesia, the airways were assessed, and ULBT class, SMD, TMD, and IID determined. Laryngoscopic view according to the Cormack and Lehane grading system was determined after induction of anesthesia and Grades 3 and 4 defined as “difficult intubation. ” By using receiver operating characteristic analysis, the best cutoff points of the tests were calculated. Finally, sensitivity, specificity, positive and negative predictive values and accuracy of these tests and their combinations with the ULBT were calculated. RESULTS:The prevalence of difficult intubation was 5% (n = 19). Class III ULBT, IID <4.5 cm, TMD <6.5 cm, and SMD <13 cm were defined as predictors of difficult intubation. There was no significant difference regarding difficult intubation based on gender (P < 0.05), whereas there were significant differences between the older tests and laryngeal view (P < 0.05, Mc-Nemar test). Specificity and accuracy of the ULBT were significantly higher than TMD, SMD, and IID individually (specificity was 91.69%, 82.27%, 70.64%, and 82.27%, respectively, and accuracy was 91.05%, 71.32%, 81.84%, and 76.58%, respectively). The combination of the ULBT with SMD provided the highest sensitivity. CONCLUSION:We conclude that the specificity and accuracy of the ULBT is significantly higher than the other tests and is more accurate in airway assessment. However, the ULBT in conjunction with the other tests could more reliably predict easy laryngoscopy or intubation.
The Welfare Effects of Supply-Side Regulations in Medicare Part D

The efficiency of publicly-subsidized, privately-provisioned social insurance programs depends on the interaction between insurer behavior and public subsidies. We study this interaction within Medicare Part D Prescription Drug Plan (PDP) markets. Using a structural model of supply and demand, we find: consumers purchase too few and too socially-costly PDP plans; insurers price near marginal cost; the primary driver of welfare is the opportunity cost of government spending on other Medicare programs; and the current subsidization policy achieves a level of total welfare close to that obtained under an optimal in-kind subsidy, but is far from the social planner's first-best solution.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber. org.
Distributed situation awareness in dynamic systems: theoretical development and application of an ergonomics methodology

The purpose of this paper is to propose foundations for a theory of situation awareness based on the analysis of interactions between agents (i.e. both human and non-human) in subsystems. This approach may help to promote a better understanding of technology-mediated interaction in systems, as well as helping in the formulation of hypotheses and predictions concerning distributed situation awareness. It is proposed that agents within a system each hold their own situation awareness, which may be very different from (although compatible with) that of other agents. It is argued that we should not always hope for, or indeed want, sharing of this awareness, as different system agents have different purposes. This view marks situation awareness as a dynamic and collaborative process binding agents together on tasks on a moment-by-moment basis. Implications of this viewpoint for the development of a new theory of, and accompanying methodology for, distributed situation awareness are offered.
The First Detection of Cobalt in a Damped Lyman Alpha System

We present the first ever detection of Cobalt in a Damped Lyman Alpha system (DLA) at z ~ 2. In addition to providing important clues to the star formation history of these high redshift galaxies, we discuss how studying the Co abundance in DLAs may also help to constrain models of stellar nucleosynthesis in a regime not probed by Galactic stars.
An improved mentoring model for student teachers on practicum in primary schools in Zimbabwe

As part of a drive to improve the quality of teachers, Zimbabwe introduced a schoolbased mentoring model in 1995, a move which regrettably seems not have borne fruit. Therefore, this study sought to propose an improved mentoring model for initial teacher training for primary school teachers. Efforts to improve the current mentoring could, however, be facilitated if they were informed by an empirically-based understanding of the shortcomings of the existing mentoring system for student teachers and teachers. In order to attain the above objective, this study adopted a multisite case study design, guided by the interpretive paradigm. A core of nine primary schools, drawn from the rural, urban and peri-urban areas of the Masvingo Province in Zimbabwe, was purposively selected to participate in the study. In the participating schools, key participants were student teachers and mentors, while school principals participated when they had time. A secondary group of primary schools were also identified to be used as validation of findings in a wider setting. An in-depth literature study on teacher education and mentoring was also carried out and this, combined with empirical data, illuminated the issues being investigated. The empirical data were primarily gathered through focus group and face-to-face individual semi-structured interviews, while participant observation (used in conjunction with informal unstructured interviews) and questionnaires were used to verify and triangulate data collected through the interviews. To safeguard the ethical integrity of the study, ethical approval from the relevant university committee, as well as the official consent of educational authorities, was obtained beforehand, as was the informed consent of individual participants. The research established that the support rendered to student teachers in the participating primary schools was largely inadequate and of a shallow mode, focusing primarily on facilitating the mastery of technical skills and the provision of psycho-social support, while being sorely deficient in empowering the student teachers with the skills and attitudes to reflectively and critically engage with their own and others‟ teaching practices. The mentoring was taking place in the context of field experience, organised
Langevin Dynamics with Continuous Tempering for High-dimensional Non-convex Optimization

Minimizing non-convex and high-dimensional objective functions are challenging, especially when training modern deep neural networks. In this paper, a novel approach is proposed which divides the training process into two consecutive phases to obtain better generalization performance: Bayesian sampling and stochastic optimization. The first phase is to explore the energy landscape and to capture the "fat" modes; and the second one is to fine-tune the parameter learned from the first phase. In the Bayesian learning phase, we apply continuous tempering and stochastic approximation into the Langevin dynamics to create an efficient and effective sampler, in which the temperature is adjusted automatically according to the designed "temperature dynamics". These strategies can overcome the challenge of early trapping into bad local minima and have achieved remarkable improvements in various types of neural networks as shown in our theoretical analysis and empirical experiments.
High Resolution Air Pollution Maps in Urban Environments Using Mobile Sensor Networks

We propose three modeling methods using a mobile sensor network to generate high spatio-temporal resolution air pollution maps for urban environments. In our deployment in Lausanne (Switzerland), dedicated sensing nodes are anchored to the public buses and measure multiple air quality parameters including the Lung Deposited Surface Area (LDSA), a state of the art metric for quantifying human exposure to ultra fine particles. In this paper, our focus is on generating LDSA maps. In particular, since the sensor network coverage is spatially and temporally dynamic, we leverage models to estimate the values for the locations and times where the data are not available. We first discretize the area topologically based on the street segments in the city and we then propose the following three prediction models: i) a log-linear regression model based on nine meteorological (e.g., Temperature and precipitations) and gaseous (e.g., NO 2 and CO) explanatory variables measured at two static stations in the city, ii) a novel network-based log-linear regression model that takes into account the LDSA values of the most correlated streets and also the nine explanatory variables mentioned above, iii) a novel Probabilistic Graphical Model (PGM) in which each street segment is considered as one node of the graph, and inference on conditional joint probability distributions of the nodes results in estimating the values in the nodes of interest. More than 44 millions of geo- and time-stamped LDSA measurements (i.e., More than 14 months of real data) are used in this paper to evaluate the proposed modeling approaches in various time resolutions (hourly, daily, weekly and monthly). The results show that the three approaches bring significant improvements in R2, RMSE and FAC metrics compared to a baseline K-Nearest Neighbor method.
The effect of natural adjuvants (G2, G2F) on lung inflammation of sensitized guinea pigs

Objective: The effects of natural adjuvants were examined on total and differential WBC counts in lung lavage of sensitized guinea pigs. Materials and Methods: In three sensitized groups of guinea pigs including: untreated sensitized animals (S), sensitized animals treated with adjuvant G2 (S+G2) and G2F (S+G2F) as well as non-sensitized group (C) (n=6 for each group), total and differential WBC counts of lung lavage were examined. Sensitization of animals was achieved by injection and inhalation of ovalbumin (OA). Results: The results showed increased total WBC, eosinophil, neutrophil, and basophil counts, and decreased lymphocytes in lung lavage of sensitized animals compared with the control group (p<0.01 for all cases). However, neutrophil, lymphocyte, eosinophil, and basophil counts in lung lavage were decreased in treated groups with either G2 or G2F but total WBC was decreased in lung lavage of treated group with only G2. Conclusion: These results indicate important preventive effects of two natural adjuvants, especially G2, on lung inflammation of sensitized guinea pigs.
An empirical assessment of the residual income valuation model 1 This paper has benefited from the c

This paper provides an empirical assessment of the residual income valuation model proposed in Ohlson (Ohlson, J.A., 1995. Earnings, book values and dividends in security valuation. Contemporary Accounting Research 11, 661—687). We point out that existing empirical research relying on Ohlson’s model is similar to past research relying explicitly on the dividend-discounting model. We establish that the key original empirical implications of Ohlson’s model stem from the information dynamics that link current information to future residual income. Our empirical results generally support Ohlson’s information dynamics. However, we find that our empirical implementation of Ohlson’s model provides only minor improvements over existing attempts to implement the dividend-discounting model by capitalizing short-term earnings’ forecasts in perpetuity. ( 1999 Published by Elsevier Science B.V. All rights reserved. JEL classification: M41; G14
Fine-grained Product Features Extraction and Categorization in Reviews Opinion Mining

With the growth of user-generated contents on the Web, product reviews opinion mining increasingly becomes a research practice of great value to e-commerce, search and recommendation. Unfortunately, the number of reviews is rising up to hundreds or even thousands, especially for some popular items, which makes it a laborious work for the potential buyers and the manufacturers to read through them to make a wise decision. Besides, the free format and the uncertainty of reviews expressions, make fine-grained product features extraction and categorization a more difficult task than traditional information extraction techniques. In this work, we propose to treat product feature extraction as a sequence labeling task and employ a discriminative learning model using Conditional Random Fields (CRFs) to tackle it. We innovatively incorporate the part-of-speech features and the sentence structure features into the CRFs learning process. For product feature categorization, we introduce the semantic knowledge-based and distributional context-based similarity measures to calculate the similarities between product feature expressions, then an effective graph pruning based categorizing algorithm is proposed to classify the collection of feature expressions into different semantic groups. The empirical studies have proved the effectiveness and efficiency of our approaches compared with other counterpart methods.
Centre De Referència En Economia Analítica Barcelona Economics Working Paper Series How Binding Are Legal Limits? Transitions from Temporary to Permanent Work in Spain How Binding Are Legal Limits? Transitions from Temporary to Permanent Work in Spain 2. the Data

In the mid-1980s, most accessions to permanent employment in several European countries have been through …xed-term contracts. This paper studies the duration pattern of …xed-term contracts and the determinants of their conversion into permanent ones in Spain, where the share of …xed-term employment is the highest in Europe. We estimate a duration model for temporary employment, with competing risks of terminating into permanent employment versus alternative states, and ‡exible duration dependence. Our estimated conversion rate has a clear, pronounced spike at 3 years of duration, coinciding with the legal maximum duration of these contracts, suggesting that some …xed-term contracts are only converted when there is no other way to retain the worker. Also, there is a spike around 1 year of duration, indirectly suggesting that some …xed-term contracts may be used as screening devices: workers who successfully pass the screening may obtain a conversion much before the legal duration limit. Several European labor markets have been characterized by a wide use of permanent contracts with stringent and costly …ring regulations. In the mid-1980s, in order to …ght the high and persistent levels of unemployment, some European countries enhanced the ‡exibility of their labor markets by allowing employers to hire workers on a …xed-term basis, with negligible termination costs upon contract expiry. Typically, there exists a legal duration limit in the use of these contracts, after which an employer can either o¤er the worker a contract of undetermined duration or dismiss her. Since their introduction, …xed-term contracts have been widely used and they account for most new hirings in all sectors and occupations, especially in countries characterized by high levels of employment protection (OECD 1993). European labor markets have become more dynamic in terms of higher in ‡ows and out ‡ows between unemployment and employment, but there has not been a sizeable bene…cial impact on aggregate unemployment. The consequences of the introduction of …xed-term contracts have raised interest and concern among both academics and policy-makers (see Booth et al. 2002 and OECD 2002). Some consensus has formed among economists that the introduction of …xed-term contracts does not necessarily increase employment, while creating dualism in the labor market (see, among others, Bentolila and Dolado 1994, Blanchard and Landier 2000 and Güell 2000). An important aspect of the use of …xed-term contracts is their pattern of promotion into regular contracts of inde…nite duration. Mixed employment e¤ects of the introduction of …xed-term contracts and …
Photorealistic Building Reconstruction from Mobile Laser Scanning Data

Abstract: Nowadays, advanced real-time visualization for location-based applications, such as vehicle navigation or mobile phone navigation, requires large scale 3D reconstruction of street scenes. This paper presents methods for generating photorealistic 3D city models from raw mobile laser scanning data, which only contain georeferenced XYZ coordinates of points, to enable the use of photorealistic models in a mobile phone for personal navigation. The main focus is on the automated processing algorithms for noise point filtering, ground and building point classification, detection of planar surfaces, and on the key points (e.g., corners) of building derivation. The test site is located in the Tapiola area, Espoo, Finland. It is an area of commercial buildings, including shopping centers, banks, government agencies, bookstores, and high-rise residential buildings, with the tallest building being 45 m in height. Buildings were extracted by comparing the overlaps of X and Y coordinates of the point clouds between the cutoff-boxes at different and transforming the top-view of the point clouds of each overlap into a binary image and applying standard image processing technology to remove the non-building points, and finally transforming this image back into point clouds. The purpose for using points from cutoff-boxes instead of all points for building detection is to reduce the influence of tree points close to the building facades on building extraction. This method can also be extended to transform point clouds in different views into binary images for various other object extractions. In order to ensure the building geometry completeness, manual check and correction are needed after the key points of building derivation by automated algorithms. As our goal is to obtain photorealistic 3D models for walk-through views, terrestrial images were captured and used for texturing building facades. Currently, fully
Exploring the police support volunteer experience: findings from a national survey

ABSTRACT There are an estimated 8000 Police Support Volunteers (PSVs) in England and Wales, contributing around 650,000 hours each year to an expanding variety of tasks to support their local constabularies. Despite this, the evidence base around the experiences of being a PSV is remarkably limited. Drawing on findings from the first national survey of police volunteers in England and Wales, undertaken in the early 2016 with just over 1000 PSV responses, this article explores key factors that are associated with the overall experience of being a PSV pointing towards the significance of management, support, supervision, connection, contribution and development on volunteer morale. The article sets these findings within the strategic context of future developments for PSVs, considers practical actions for improving volunteer experience, and highlights the importance of further research into being a volunteer in policing.
Ratchet vs Blase Investors and Asset Markets

This paper proposes a new wealth-dependent utility function for the inter-temporal consumption and portfolio problem, in which the reference (bliss) consumption level is a function of wealth. Ratchet effects obtain when higher wealth increases the reference consumption level; blase behavior occurs when higher wealth reduces it. We have three contributions: (i) we identify closed-form solutions for optimal consumption and portfolio rules; (ii) we use the optimal rules to estimate the model using aggregate portfolio data, and (iii) we derive and discuss the pricing implications of our results. Our estimates are consistent with blase behavior and counter-cyclical risk aversion.