Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Patch and Multi-label Learning for Facial Action Unit and Holistic Expression Recognition

Most action unit (AU) detection methods use one-versus-all classifiers without considering dependences between features or AUs. In this paper, we introduce a joint patch and multi-label learning (JPML) framework that models the structured joint dependence behind features, AUs, and their interplay. In particular, JPML leverages group sparsity to identify important facial patches, and learns a multi-label classifier constrained by the likelihood of co-occurring AUs. To describe such likelihood, we derive two AU relations, positive correlation and negative competition, by statistically analyzing more than 350,000 video frames annotated with multiple AUs. To the best of our knowledge, this is the first work that jointly addresses patch learning and multi-label learning for AU detection. In addition, we show that JPML can be extended to recognize holistic expressions by learning common and specific patches, which afford a more compact representation than the standard expression recognition methods. We evaluate JPML on three benchmark datasets CK+, BP4D, and GFT, using within-and cross-dataset scenarios. In four of five experiments, JPML achieved the highest averaged F1 scores in comparison with baseline and alternative methods that use either patch learning or multi-label learning alone.
A modelling study of the impact of cirrus clouds on the moisture budget of the upper troposphere

We present a modelling study of the effect of cirrus clouds on the moisture budget of the layer wherein the cloud formed. Our framework simplifies many aspects of cloud microphysics and collapses the problem of sedimentation onto a 0-dimensional box model, but retains essential feedbacks between saturation mixing ratio, particle growth, and water removal through particle sedimentation. The water budget is described by two coupled first-order differential equations for dimensionless particle number density and saturation point temperature, where the parameters defining the system (layer depth, reference temperature, amplitude and time scale of temperature perturbation and inital particle number density, which may or may not be a function of reference temperature and cooling rate) are encapsulated in a single coefficient. This allows us to scale the results to a broad range of atmospheric conditions, and to test sensitivities. Results of the moisture budget calculations are presented for a range of atmospheric conditions ( T : 238–205 K; p : 325–180 hPa) and a range of time scales τ T of the temperature perturbation that induces the cloud formation. The cirrus clouds are found to efficiently remove water for τ T longer than a few hours, with longer perturbations (τ T ≳10 h) required at lower temperatures ( T ≲210 K). Conversely, we find that temperature perturbations of duration order 1 h and less (a typical timescale for e.g., gravity waves) do not efficiently dehydrate over most of the upper troposphere. A consequence is that (for particle densities typical of current cirrus clouds) the assumption of complete dehydration to the saturation mixing ratio may yield valid predictions for upper tropospheric moisture distributions if it is based on the large scale temperature field, but this assumption is not necessarily valid if it is based on smaller scale temperature fields.
LDAvis: A method for visualizing and interpreting topics

We present LDAvis, a web-based interactive visualization of topics estimated using Latent Dirichlet Allocation that is built using a combination of R and D3. Our visualization provides a global view of the topics (and how they differ from each other), while at the same time allowing for a deep inspection of the terms most highly associated with each individual topic. First, we propose a novel method for choosing which terms to present to a user to aid in the task of topic interpretation, in which we define the relevance of a term to a topic. Second, we present results from a user study that suggest that ranking terms purely by their probability under a topic is suboptimal for topic interpretation. Last, we describe LDAvis, our visualization system that allows users to flexibly explore topic-term relationships using relevance to better understand a fitted LDA model.
Toxic Effects of Nickel Oxide Bulk and Nanoparticles on the Aquatic Plant Lemna gibba L.

The aquatic plant Lemna gibba L. was used to investigate and compare the toxicity induced by 30 nm nickel oxide nanoparticles (NiO-NPs) and nickel(II) oxide as bulk (NiO-Bulk). Plants were exposed during 24 h to 0–1000 mg/L of NiO-NPs or NiO-Bulk. Analysis of physicochemical characteristics of nanoparticles in solution indicated agglomerations of NiO-NPs in culture medium and a wide size distribution was observed. Both NiO-NPs and NiO-Bulk caused a strong increase in reactive oxygen species (ROS) formation, especially at high concentration (1000 mg/L). These results showed a strong evidence of a cellular oxidative stress induction caused by the exposure to NiO. Under this condition, NiO-NPs and NiO-Bulk induced a strong inhibitory effect on the PSII quantum yield, indicating an alteration of the photosynthetic electron transport performance. Under the experimental conditions used, it is clear that the observed toxicity impact was mainly due to NiO particles effect. Therefore, results of this study permitted determining the use of ROS production as an early biomarker of NiO exposure on the aquatic plant model L. gibba used in toxicity testing.
The Impact of Influence Tactics in Information System Development Projects: A Control-Loss Perspective

Information systems development (ISD) projects are prone to high levels of failure. One of the major reasons attributed to these failures is the inability to harmonize values held by a diverse set of participants in an environment that is characterized by uncertainty due to changing requirements. In this paper, we focus on a relational approach to achieve congruence between a project manager and a team member with respect to influence tactics. Constructs of perceptual congruence and communication congruence that reflect a level of agreement and degree of shared understanding between the project manager and team members are described. A congruence model is constructed and tied to an intermediate outcome variable of control loss. One hundred and thirteen dyadic pairs of project managers and team members are surveyed in order to test the model. The results indicate that having strong relational equity and common understanding can minimize control loss. It is important to consider the perspectives of both the project manager and a team member while formulating and assessing monitoring strategies to promote the success of an ISD project. Especially, encouraging team members to discuss disagreements constructively can motivate them to perform better and keep things under control. Finally, it is critical to address the performance problems as they occur rather than wait until the completion of the project.
Readability-based Sentence Ranking for Evaluating Text Simplification

We propose a new method for evaluating the readability of simplified sentences through pair-wise ranking. The validity of the method is established through in-corpus and cross-corpus evaluation experiments. The approach correctly identifies the ranking of simplified and unsimplified sentences in terms of their reading level with an accuracy of over 80%, significantly outperforming previous results. To gain qualitative insights into the nature of simplification at the sentence level, we studied the impact of specific linguistic features. We empirically confirm that both word-level and syntactic features play a role in comparing the degree of simplification of authentic data. To carry out this research, we created a new sentence-aligned corpus from professionally simplified news articles. The new corpus resource enriches the empirical basis of sentence-level simplification research, which so far relied on a single resource. Most importantly, it facilitates cross-corpus evaluation for simplification, a key step towards generalizable results.
EXPLANATION OF INDUSTRY RETURNS USING THE VARIABLE BETA MODEL AND LAGGED VARIABLE BETA MODEL

Beta is found to be a function of several leading economic indicators and government policy variables within the context of the Variable Beta Model which incorporates economic characteristics in the single index model in a multiplicative manner. When contemporaneous macroeconomic descriptors are replaced with reporting-period-lagged macroeconomic descriptors, in the Lagged Variable Beta Model, model explanatory power increases. Findings suggest that the lagged beta model is more likely to satisfy the ordinary least squares assumptions of serially independent error terms.
Thermo-Mechanical Finite Element Model of Shell Behavior in the Continuous Casting of Steel

A coupled finite-element model, CON2D, has been developed to simulate temperature, stress, and shape development during the continuous casting of steel, both in and below the mold. The model simulates a transverse section of the strand in generalized plane strain as it moves down at the casting speed. It includes the effects of heat conduction, solidification, nonuniform superheat dissipation due to turbulent fluid flow, mutual dependence of the heat transfer and shrinkage on the size of the interfacial gap, the taper of the mold wall, and the thermal distortion of the mold. The stress model features an elastic-viscoplastic creep constitutive equation that accounts for the different responses of the liquid, semisolid, delta-ferrite, and austenite phases. Functions depending on temperature and composition are employed for properties such as thermal linear expansion. A contact algorithm is used to prevent penetration of the shell into the mold wall due to the internal liquid pressure. An efficient two-step algorithm is used to integrate these highly nonlinear equations. The model is validated with an analytical solution for both temperature and stress in a solidifying slab. It is applied to simulate continuous casting of a 120 mm billet and compares favorably with plant measurements of mold wall temperature, total heat removal, and shell thickness, including thinning of the corner. The model is ready to investigate issues in continuous casting such as mold taper optimization, minimum shell thickness to avoid breakouts, and maximum casting speed to avoid hot-tear crack formation due to submold bulging.
A proposed semantic recommendation system for e-learning: A rule and ontology based e-learning recommendation system

With proliferation of learning contents on the web, finding suitable ones has become a very difficult and complicated task for online learners, to achieve better performance. Nevertheless, recommender systems can be a solution to the problem. However, recommendation systems haven't been sufficiently used in e-learning, in comparison with other fields (i.e. commerce, medicine and so on). In this paper, we propose a semantic recommender system for e-learning by means of which, learners will be able to find and choose the right learning materials suitable to their field of interest. The proposed web based recommendation system comprises ontology and web ontology language (OWL) rules. Rule filtering will be used as recommendation technique. Our proposed recommendation system architecture consists of two subsystems; Semantic Based System and Rule Based System. Modules for either subsystem are; Observer, Learner profile, Recommendation storage and User interface.
Proteomic-Based Discovery and Characterization of Glycosylated Eosinophil-Derived Neurotoxin and COOH-Terminal Osteopontin Fragments for Ovarian Cancer in Urine

Purpose: The objective was to identify and characterize low molecular weight proteins/peptides in urine and their posttranslational modifications that might be used as a screening tool for ovarian cancer. Experimental Design: Urine samples collected preoperatively from postmenopausal women with ovarian cancer and benign conditions and from nonsurgical controls were analyzed by surface-enhanced laser desorption/ionization mass spectrometry and two-dimensional gel electrophoresis. Selected proteins from mass profiles were purified by chromatography and followed by liquid chromatography-tandem mass spectrometry sequence analysis. Specific antibodies were generated for further characterization, including immunoprecipitation and glycosylation. Quantitative and semiquantitative ELISAs were developed for preliminary validation in patients of 128 ovarian cancer, 52 benign conditions, 44 other cancers, and 188 healthy controls. Results: A protein (m/z ∼17,400) with higher peak intensities in cancer patients than in benign conditions and controls was identified and subsequently defined as eosinophil-derived neurotoxin (EDN). A glycosylated form of EDN was specifically elevated in ovarian cancer patients. A cluster of COOH-terminal osteopontin was identified from two-dimensional gels of urine from cancer patients. Modified forms EDN and osteopontin fragments were elevated in early-stage ovarian cancers and a combination of both resulted to 93% specificity and 72% sensitivity. Conclusions: Specific elevated posttranslationally modified urinary EDN and osteopontin COOH-terminal fragments in ovarian cancer might lead to potential noninvasive screening tests for early diagnosis. Urine with less complexity than serum and relatively high thermodynamic stability of peptides or metabolites is a promising study medium for discovery of the novel biomarkers which may present in many nonurinary tract neoplastic diseases.
Fading broadcast channels with state information at the receivers

Despite considerable progress on the information-theoretic broadcast channel, the capacity regions of fading broadcast channels with channel state known at the receivers but unknown at the transmitter remain unresolved. We address this subject by introducing a layered erasure broadcast channel model in which each component channel has a state that specifies the received signal levels in an instance of a deterministic binary expansion channel. We find the capacity region of this class of broadcast channels. The inner bound assigns each signal level to the user that derives the maximum expected rate from that level. The outer bound is based on a channel enhancement that creates a degraded broadcast channel for which the capacity region is known. This same approach is then used to find outer bounds to the capacity region of fading Gaussian broadcast channels.
Non-Coherent Codes over the Grassmannian

We construct a new family of space-time codes suited for multiple-antenna non-coherent communications over Rayleigh flat fading channels. These codes use all the complex degrees of freedom of the system, i.e. (M times(1-M/T)) symbols per channel use, where T is the code length and M is the number of transmit antennas. Their codewords belong to the Grassmann manifold GTldrM (C), the set of the M-dimensional vector subspaces of CT. Our codes are built from space-time codes for coherent systems via a non linear map (parameterization) called the exponential map. The relationships between some properties of the non-coherent space-time codes and their corresponding coherent codes are investigated. We also propose a simplified decoding for these classes of unitary space-time codes. We analyse the performance of these codes in terms of complexity and error probability and we compare them with some current best propositions, in particular training-based codes. The performance of our codes is substantially equivalent or slightly better than the one of training-based codes, under GLRT (Generalized Likelihood Ratio Test) decoding. When a simplified decoder is applied at the receiver, the error probability curves of the two propositions seem to be basically equivalent in the SIMO case with small block size, high spectral efficiency and high number of receive antennas, and in the 2times2 MIMO case with low spectral efficiency. In the other cases the training codes with simplified decoding seem to outperform our proposition.
Compiler-Directed Dynamic Voltage Scaling for Memory-Bound Applications

This paper presents the design and implementation of a compiler algorithm that effectively reduces the energy usage of memory-bound applications via dynamic voltage scaling (DVS). The algorithm identifies program regions where the CPU can be slowed down with negligible performance penalty. It is implemented as a source-to-source level transformation using the SUIF2 compiler infrastructure. Physical measurements on a laptop with a 600 MHz 1.2 GHz AMD Athlon 4 processor show that CPU energy savings in the range of 9.17% to 55.65% can be achieved with performance degradation in the range of 0.69% to 6.14% for theSPECfp95 benchmarks. On average, the energy and energy-delay product are reduced by 26.58% and 24.11%, respectively, at the cost of the performance slowdown of 3.26%. This paper also discusses a new methodology which attempts to approximate the minimum energy usage by any DVS algorithm. Our compiler-directed DVS algorithm is within 6% from the “optimal” case. To the best of our knowledge, this is one of the first work that evaluates DVS strategies by physical measurements.
Control of hybrid systems

This report focuses on the control of hybrid systems. The authors first describe specification and control of the closed loop behavior of the system in terms of propositional linear temporal logic. Control and coordination models are given in the formalism. The authors next present a continuous event model of the plant and formulate the hybrid system control problem. The report concludes with an application domain of hybrid system control theory.
Remote automated multi-generational growth and observation of an animal in low Earth orbit

The ultimate survival of humanity is dependent upon colonization of other planetary bodies. Key challenges to such habitation are (patho)physiologic changes induced by known, and unknown, factors associated with long-duration and distance space exploration. However, we currently lack biological models for detecting and studying these changes. Here, we use a remote automated culture system to successfully grow an animal in low Earth orbit for six months. Our observations, over 12 generations, demonstrate that the multi-cellular soil worm Caenorhabditis elegans develops from egg to adulthood and produces progeny with identical timings in space as on the Earth. Additionally, these animals display normal rates of movement when fully fed, comparable declines in movement when starved, and appropriate growth arrest upon starvation and recovery upon re-feeding. These observations establish C. elegans as a biological model that can be used to detect changes in animal growth, development, reproduction and behaviour in response to environmental conditions during long-duration spaceflight. This experimental system is ready to be incorporated on future, unmanned interplanetary missions and could be used to study cost-effectively the effects of such missions on these biological processes and the efficacy of new life support systems and radiation shielding technologies.
How often is the diagnosis bronchial asthma correct?

BACKGROUND There are studies indicating that bronchial asthma is often underdiagnosed, while only a little research has been conducted as concerns overdiagnosing asthma. OBJECTIVE We aimed to estimate the number of patients who have been given the wrong diagnosis of asthma. METHODS All patients aged above 18 years who had visited two GPs during 1994 or 1995, with the diagnosis of bronchial asthma confirmed in the medical register, were examined by a specialist in allergies. RESULTS One hundred and twenty-three patients fulfilled the criteria for being included in the study. Eighty-six patients (70%) attended the examination. Of these, 51 (59%) had bronchial asthma, six (7%) asthma in combination with chronic obstructive pulmonary disease (COPD) and 29 (34%) no asthmatic disease. CONCLUSION The study indicates that more accuracy is needed when diagnosing bronchial asthma.
ANALYZING THE PORTRAYAL OF PATRIARCHAL OPPRESSION TOWARDS THE FEMALE CHARACTERS IN J.K. ROWLING’S THE CASUAL VACANCY: A REFLECTIVE POST-FEMINIST CRITICS

The oppression and subordination towards woman mostly happened because of the patriarchal system which exists in the society. The purposes of this study are to analyze the portrayal of patriarchal symbols in the society of Pagford Town in J.K. Rowling’s The Casual Vacancy and the patriarchal system abuse or oppression towards the female characters in J.K. Rowling’s The Casual Vacancy . The results of the study show six symbols of patriarchy which is found in the novel. They are female as sex objects in public patriarchy, male as villain in public patriarchy, male as villain in private patriarchy, female as the faulty in private patriarchy, female as mother or angel in the house in private patriarchy and female as damsel in distress in private patriarchy. The study also shows the indication of abuse occurred to several female characters. The patriarchy system generated from the participation of the male and female is the main cause of the sustainability of female oppression and subordination in the society. Keywords: patriarchy, symbol, oppression, abuse, victimization, The Casual Vacancy
Procrastination of Enjoyable Experiences

The tendency to procrastinate applies not only to aversive tasks but also to positive experiences with immediate benefits. The authors propose that models of time discounting can explain this behavior, and they test these predictions with field data and experiments. A multicity study shows that people with unlimited time windows delay visiting desirable landmarks; however, procrastination is reduced when the window of opportunity is constrained. Similarly, people procrastinate in redeeming gift certificates and gift cards with long deadlines more than those with short deadlines, resulting in overall lower redemption rates. These results run counter to participants’ predictions and typical models of impulsive behavior.