Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel method for user-defined human posture recognition using Kinect

Human posture recognition is very critical in human computer interaction studies. With the release of Microsoft Kinect sensor, there has been an increasing interest in using Kinect for vision based human posture recognition as user's skeleton information can be precisely inferred from the depth images generated by Kinect. In this paper we proposed a novel human posture recognition method using Microsoft Kinect sensor, which can automatically identify any user-defined postures. Skeleton information inferred from depth image of user's posture was utilized to generate 9 features representing specific body parts such as forearm, thigh, etc. These features are fed into SVM to generate posture-learning models that are then used to identify pre-defined postures. Totally 22 different postures including body, arm, leg postures were collected and PCA analysis demonstrated they were in general well separated in the feature space. Further performance evaluation using 10-fold cross-validation showed a final overall accuracy of 99.14% was successfully achieved in the test including all postures, indicating the outstanding capability of this proposed methods.
Future wildfire in circumboreal forests in relation to global warming

Despite increasing temperatures since the end of the Little Ice Age (ca. 1850), wildfire frequency has decreased as shown in many field studies from North America and Europe. We believe that global warming since 1850 may have trig- gered decreases in fire frequency in some regions and future warming may even lead to further decreases in fire frequency. Simulations of present and future fire regimes, using daily outputs from the General Circulation Model (GCM), were in good agreement with recent trends observed in fire history studies. Daily data, rather than monthly data, were used be- cause the weather and, consequently, fire behavior can change dramatically over time periods much shorter than a month. The simulation and fire history results suggest that the impact of global warming on northern forests through forest fires may not be disastrous and that, contrary to the expectation of an overall increase in forest fires, there may be large regions of the Northern Hemisphere with a reduced fire frequency.
Designing a Dynamic Buyer-Supplier Coordination Model in Electronic Markets Using Stochastic Petri Nets

Functional relationship between supplier and buyer in an open market place leads to investigate the role of both quantifiable and non-quantifiable parameters in coordination mechanism with the aim of achieving higher performance in supply chain activities. Here, we develop a supply chain model and a new agent to analyze and simulate the playersâ€™ behavior in the network. A cooperative game theory framework is utilized between buyer and supplier in order to increase the supply chain performance. The study is supported by presenting SC Net Optimizer as a tool for implementing the proposed coordination mechanism and evaluates the performance of the chain by simulation using stochastic Petri nets (SPNs). The model provides a more realistic optimization process by taking into consideration the dynamic information flow in an uncertainty environment.
The sheaf-theoretic structure of non-locality and contextuality

We use the mathematical language of sheaf theory to give a unified treatment of non-locality and contextuality, in a setting that generalizes the familiar probability tables used in non-locality theory to arbitrary measurement covers; this includes Kochen–Specker configurations and more. We show that contextuality, and non-locality as a special case, correspond exactly to obstructions to the existence of global sections. We describe a linear algebraic approach to computing these obstructions, which allows a systematic treatment of arguments for non-locality and contextuality. We distinguish a proper hierarchy of strengths of no-go theorems, and show that three leading examples—due to Bell, Hardy and Greenberger, Horne and Zeilinger, respectively—occupy successively higher levels of this hierarchy. A general correspondence is shown between the existence of local hidden-variable realizations using negative probabilities, and no-signalling; this is based on a result showing that the linear subspaces generated by the non-contextual and no-signalling models, over an arbitrary measurement cover, coincide. Maximal non-locality is generalized to maximal contextuality, and characterized in purely qualitative terms, as the non-existence of global sections in the support. A general setting is developed for the Kochen–Specker-type results, as generic, model-independent proofs of maximal contextuality, and a new combinatorial condition is given, which generalizes the ‘parity proofs’ commonly found in the literature. We also show how our abstract setting can be represented in quantum mechanics. This leads to a strengthening of the usual no-signalling theorem, which shows that quantum mechanics obeys no-signalling for arbitrary families of commuting observables, not just those represented on different factors of a tensor product.
Approximate Capacity Region for the Symmetric Gaussian Interference Channel With Noisy Feedback

Recent results have shown that feedback can significantly increase the capacity of interference networks. This paper considers the impact of noise on such gains due to feedback. In particular, this paper considers the two-user linear deterministic interference channel with noisy feedback, as a stepping stone to characterize the approximate capacity region for the two-user Gaussian interference channel with noisy feedback. First, the capacity region for the symmetric linear deterministic interference channel with noisy feedback is obtained. It is shown that noisy feedback enlarges the capacity region if and only if the number of feedback bits l is greater than a certain threshold l*. It is found that, excluding the regime (1/2) ≤ α ≤ 2, where α is the normalized interference level, in which even full feedback does not increase symmetric capacity, this threshold l* is equal to the per-user symmetric capacity without feedback. One of the key ideas is a novel converse outer bounding technique for the weighted sum rates 2R1 + R2 and R1 + 2R2. These results and the techniques developed for the linear deterministic model are then applied to characterize inner bounds and outer bounds for the symmetric Gaussian interference channel with noisy feedback. The outer bounds are shown to be at most 4.7 b/s/Hz away from the achievable rate region. As a corollary, the generalized-degrees-of-freedom region, which approximates the capacity region of the symmetric Gaussian interference channel at high SNR, is found.
Worldwide Occurrence and Impact of Human Trichinellosis, 1986–2009

To assess the global incidence and clinical effects of human trichinellosis, we analyzed outbreak report data for 1986-2009. Searches of 6 international databases yielded 494 reports. After applying strict criteria for relevance and reliability, we selected 261 reports for data extraction. From 1986 through 2009, there were 65,818 cases and 42 deaths reported from 41 countries. The World Health Organization European Region accounted for 87% of cases; 50% of those occurred in Romania, mainly during 1990-1999. Incidence in the region ranged from 1.1 to 8.5 cases per 100,000 population. Trichinellosis affected primarily adults (median age 33.1 years) and about equally affected men (51%) and women. Major clinical effects, according to 5,377 well-described cases, were myalgia, diarrhea, fever, facial edema, and headaches. Pork was the major source of infection; wild game sources were also frequently reported. These data will be valuable for estimating the illness worldwide.
Design and development of an early warning system to prevent terrorist attacks

EWAS is an early warning prototype that collects and analyzes news items from the European Media Monitor. Although, it currently processes news articles, it can easily be adapted to any other form of text. Data mining functions performed by the system are categorization, clustering, and named entity extraction. The main design concern of the system is scalability, which is achieved by a modular architecture that allows multiple instances of the same component to run in parallel. The main objective behind this research is to develop a system to identify “who is doing what” to estimate “who can do what” in order to predict “what can really happen tomorrow”.
Apathy and Pituitary Disease: It Has Nothing To Do With Depression

1. Moellentine CK, Rummans TA: The var-ied neuropsychiatric presentations ofCreutzfeldt-Jakob disease. Psychosomat-ics 1999; 40:260–2632. Norton JW, Corbett JJ: Visual perceptualabnormalities: Hallucinations and illu-sions. Semin Neurol 2000; 20:111–1213. Mathews D, Unwin DH: Quantitativecerebral blood ﬂow imaging in a patientwith the Heidenhain variant of Creutz-feldt-Jakob disease. Clin Nucl Med 2001;26:770–7734. Kropp S, Schulz-Schaeffer WJ, Finken-staedt M, et al: The Heidenhain variantof Creutzfeldt-Jakob disease. Arch Neu-rol 1999; 56:55–615. Kolmel HW: Visual illusions and hallu-cinations, in Balliere’s Clinical Neurol-ogy: International Practice and Research,vol 2, no 2: Visual Perceptual Deﬁcits,edited by Kennard C. London, BailliereTindall, 1993, pp 243–264
Efficient string matching in the presence of errors

Consider the string matching problem where differences between characters of the pattern and characters of the text are allowed. Each difference is due to either a mismatch between a character of the text and a character of the pattern or a superfluous character in the text or a superfluous character in the pattern. Given a text of length n, a pattern of length m and an integer k, we present an algorithm for finding all occurrences of the pattern in the text, each with at most k differences. The algorithm runs in O(m2 + k2n) time. Given the same input we also present an algorithm for finding all occurrences of the pattern in the text, each with at most k mismatches (superfluous characters in either the text or the pattern are not allowed). This algorithm runs in O(k(m logm + n)) time.
Traffic Analysis as a Service via a Unified Model

This paper describes a traffic analysis platform that is implemented as a service, so different government authorities or geographic locations can utilize its functionalities more efficiently and effectively. In particular, most of the research in traffic analysis is solely focused on numerical analysis, while the conceptual relationships among moving objects are rarely captured. In this paper, we investigate into traffic relationships by a unified conceptual model that captures traffic dynamics under changing contexts to facilitate service implementation. By using the unified model, we can capture domain knowledge in a robust and consumable format for our proposed services for different users and on different geographic databases. The knowledge can also be mapped into a service computational model for other value-added traffic analysis. Instead of using the previously proposed spatio-temporal ER model, we define our model by augmenting the traditional ER model with symbolic contexts to better capture spatio-temporal context variations and their relationships with moving objects. We demonstrate the expressive power of our model by using Beijing taxi trajectory data to show that our approach is effective in representing traffic relationships for analysis.
Causes and consequences of centrosome abnormalities in cancer

Centrosome amplification is a hallmark of cancer. However, despite significant progress in recent years, we are still far from understanding how centrosome amplification affects tumorigenesis. Boveri's hypothesis formulated more than 100 years ago was that aneuploidy induced by centrosome amplification promoted tumorigenesis. Although the hypothesis remains appealing 100 years later, it is also clear that the role of centrosome amplification in cancer is more complex than initially thought. Here, we review how centrosome abnormalities are generated in cancer and the mechanisms cells employ to adapt to centrosome amplification, in particular centrosome clustering. We discuss the different mechanisms by which centrosome amplification could contribute to tumour progression and the new advances in the development of therapies that target cells with extra centrosomes.
Mapping synaptic cortico‐claustral connectivity in the mouse

The claustrum is an intriguing brain structure, featuring the highest connectivity per regional volume in the brain. It is a thin and elongated structure enclosed between the striatum and the insular cortex, with widespread reciprocal connections with the sensory modalities and prefrontal cortices. Retinotopic and somatotopic organizations have been described in the claustrum, and anatomical studies in cats, monkeys, and rats have demonstrated topographic organization of cortico‐claustral connections. In this study we mapped the projections from cortical modalities (visual, auditory, somatosensory, motor, and olfactory), and prefrontal regions (anterior cingulate cortex and orbitofrontal cortex) to the claustrum in mice. Utilizing expression of a virally encoded synaptic anterograde tracer, AAV‐SynaptoTag, followed by 3D reconstruction of the cortical projections, we performed a comprehensive study of the organization of these projections within the mouse claustrum. Our results clearly demonstrate a dorsoventral laminar organization of projections from the sensory cortices to the claustrum, whereas frontal inputs are more extensive and overlap with the inputs from the sensory cortices. In addition, we find evidence supporting a core/shell organization of the claustrum. We propose that the overlap between the frontal inputs and the inputs from the sensory modalities may underlie executive regulation of the communication between the claustrum and the cortical modalities. J. Comp. Neurol. 525:1381–1402, 2017. © 2016 Wiley Periodicals, Inc.
Hiding Sensitive Patterns from Sequence Databases: Research Challenges and Solutions

Sequence data are encountered in a plethora of applications, spanning from telecommunications to web usage analysis, marketing and healthcare. Disseminating these data offers remarkable opportunities for discovering interesting patterns, but it is challenging to perform in a privacy-preserving way. Although there is a large gamut of techniques to anonymizing sequential data, the discovery of sensitive sequential patterns through data mining algorithms may still lead to serious privacy violations. This is because the mining of such patterns enables intrusive inferences about the habits of a portion of the population, or provides the means for unsolicited advertisement and user profiling. In this paper, we present the problem of hiding sensitive sequential patterns, and survey existing works that attempt to address it. In addition, we discuss the important research challenges that pertain to solving this problem, and present a roadmap for future work.
Deleterious Effects of Stress on Time Spent Together and Parents' Relationship Satisfaction

ABSTRACT Data from 90 German committed heterosexual couples who had a least one child were used to examine the associations between chronic minor external stress, quantity and quality of time spent together as a couple, and partners' relationship satisfaction. Using an extended version of the Actor Partner Interdependence Model, the authors found significant negative indirect effects from mothers' chronic minor external stress via quality, but not quantity, of shared time to both parents' reported relationship satisfaction. Mothers' chronic minor external stress was associated with fewer reported quality time activities, which were also associated with lower reports of relationship satisfaction for both mothers and fathers. The authors did not find indirect effects for fathers' chronic minor external stress. Overall, the frequency of quality time activities may be more important for mothers, as it explained 25% of variance in their relationship satisfaction, compared with 15% in fathers' relationship satisfaction. Implications for relationship researchers and clinicians are discussed.
Detection of integrons among multi-drug resistant (MDR) Escherichia coli strains isolated from clinical specimens in northern west of Iran

Transference of resistance determinants by integrons is one of the important factors that can contribute to the increase in multi-resistant bacteria. We determined the prevalence and class of integrons among multi-drug resistant (MDR) Escherichia coli strains isolated from clinical specimens in Tabriz teaching hospitals. Firstly, susceptibility of 140 isolates to 13 antibiotics was determined using the disc diffusion method. Then, prevalence and class of integrons was detected in MDR strains by PCR-RFLP. One hundred five (75%) of total 140 isolates were uropathogenic Escherichia coli (UPEC). Other pathotypes included were: diarrheagenic Escherichia coli (13; 9.3%), sepsis-associated E. coli (5; 3.6%) and newborn meningitis-associated E. coli (2; 1.4%). Antibiotic resistance patterns were as follows: amoxicillin 99.3%, gentamicin 33.6%, tetracycline 72.8%, ceftazidime 46.4%, co-trimoxazole 75%, imipenem 1.4%, ciprofloxacin 47.6%, norfloxacin 50.7%, cephalothin 77.8%, amikacin 12.1%, nitrofurantoin 12.9%, chloramphenicol 20.7% and nalidixic acid 60.7%. One hundred eighteen (84.2%) of tested isolates were multi-drug resistant. Prevalence of integrons was confirmed in 27.1% of MDR isolates. intI1 and intI2 were detected respectively in 22.05% and 5.08% of MDR strains. No intI3 was detected. Resistance to gentamicin, amikacin and chloramphenicol was significantly associated with the presence of integrons. These results showed high resistance of E. coli to routine antibiotics, however, in consideration of low prevalence of integrons among these strains, we can conclude that antibiotic resistance genes in these strains presumably carried on elements other than integrons.
An improved reliability model based on software architecture

Applications of existing architecture-based software reliability models are strictly limited to software in which the component transitions satisfy the Markov properties. When software has both deterministic and probabilistic behaviors, these models intentionally model it as Markov process, of which the reliability estimation with lowered accuracy comes as a result. The objective of this paper is to present a new reliability model that can resolve the heterogeneous software architectures which do not fully satisfy the Markov properties. We firstly extend UML sequence diagram to model heterogeneous software architecture. Secondly different types of deterministic component transitions are analyzed. And finally an algorithm generating Markov chain from heterogeneous software architecture is presented. A comparison of reliability estimation result of this new model with existing ones is given with a case study, which indicates a better estimation result could be obtained by this new model.
Guest Editors' Introduction to the Special Issue on Multimodal Human Pose Recovery and Behavior Analysis

HUMAN Pose Recovery and Behavior Analysis (HuPBA) is one of the most challenging topics in Computer Vision, Pattern Analysis and Machine Learning. It is of critical importance for application areas that include gaming, computer interaction, human robot interaction, security, commerce, assistive technologies and rehabilitation, sports, sign language recognition, and driver assistance technology, to mention just a few. In essence, HuPBA requires dealing with the articulated nature of the human body, changes in appearance due to clothing, and the inherent problems of clutter scenes, such as background artifacts, occlusions, and illumination changes. Given these inherent difficulties, the combination of alternative, complementary visual and nonvisual modalities coming from different types of sensors has drawn a lot of attention in the literature: sensor data from visual cameras like RGB, time-of-flight (ToF), infrared, light field, multispectral, underwater, or thermal wavelengths cameras, together with another non-visual sensors like audio signals, inertial measurement unit (IMU) data, electrothermal activity responses, or electroglottograph signals, among others, have been exploited and combined to estimate the pose, gesture and behavior in both single images and image sequences. The combination of these visual and non-visual modalities has increased the accuracy of computer vision approaches, although gives rise to new challenges with feature extraction, synchronization of data coming from different sensors, data fusion, and temporal series analysis. As Guest Editors of this Special Issue on Multimodal Human Pose Recovery and Behavior Analysis (M2HuPBA), we are happy to present 16 accepted papers that represent the most recent research in this field, including new methods considering still images, image sequences, depth data, stereo vision, 3D vision, audio, and IMUs, among others, while presenting new multimodal datasets, in addition to those proposed by the ChaLearn Looking at People series of workshops. We would like to thank the authors of the 57 submissions we received, and above all the outstanding and timely work performed by the reviewers. All the 57 submissions followed a rigorous TPAMI review process, where at least three external reviewers provided reviews to each paper. We would also like to thank the Editor-In-Chief (EIC), David Forsyth, for making this special issue possible. We are also grateful to the editorial staff for managing the submission process and providing us with assistance. The set of 16 accepted papers can be split into three main categories within M2HuPBA: (i) human pose recovery and tracking; (ii) action and gesture recognition; and (iii) datasets. We describe these next.
Timo Kuosmanen STOCHASTIC DOMINANCE EFFICIENCY TESTS UNDER DIVERSIFICATION

This paper focuses on Stochastic Dominance (SD) efficiency in a finite empirical panel data. We analytically characterize the sets of unsorted time series that dominate a given evaluated distribution by the First, Second, and Third order SD. Using these insights, we develop simple Linear Programming and 0-1 Mixed Integer Linear Programming tests of SD efficiency. The advantage to the earlier efficiency tests is that the proposed approach explicitly accounts for diversification. Allowing for diversification can both improve the power of the empirical SD tests, and enable SD based portfolio optimization. A simple numerical example illustrates the SD efficiency tests. Discussion on the application potential and the future research directions concludes.