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Micro-expression is an expression that reveals one's true feelings and can be potentially applied in various domains such as healthcare, safety interrogation, and business negotiation. The micro-expression recognition is thus far being judged manually by psychologists and trained experts, which consumes a lot of human effort and time. Recently, the development of the deep learning network has proven promising performance in many computer vision-related tasks. Amongst, micro-expression recognition adopts the deep learning methodology to improve the feature learning capability and model generalization. This paper introduces a lightweight apex-based enhanced network that improves by extending one of the state-of-the-art, shallow triple stream three-dimensional CNN. Concretely, the network is first pre-trained with a macro-expression dataset to encounter the small data problem. The features were extracted from CASME II, SMIC, and SAMM datasets. Moreover, thorough recognition results comparison of the datasets are the optical flow-guided features. Besides, an eye masking technique is introduced to reduce noise interference such as eye blinking and glasses reflection issues. The results obtained have an accuracy of 79.19 % and an F1-score of 75.9 % . Comprehensive experimentation had been conducted on the composite dataset that consists of is provided by comparing it with recent methods. Detailed qualitative and quantitative results are reported and discussed. [ABSTRACT FROM AUTHOR]

This paper aims to reveal more of the hidden secrets of the Cheops Pyramid in terms of the descending rays of the sun during the equinox falling upon the azimuth of the diagonal secant position at the solar successions. The methodology used to complete this investigation project is based on the collection and analysis of data related to the erection principles practiced when the pyramid was constructed during the era of the Fourth Dynasty Egyptian Pharaoh Khufu. These principles are the key for the geometrical representations of the balanced states across the residual depictions of the sun's position relative to the Cheops Pyramid during the equinox. This research has found that the apex is an inevitable predetermined inclusion within the theorem of universal expansion. Moreover, the inclinations of the pyramid were set to predetermine the location of its plumb line, thereby serving as a guiding factor in erecting the blocks of the Cheops Pyramid. The main conclusion is that there is a strong relationship between the Cheops Pyramid geometry, the erection of its steps, and the solar equinox. [ABSTRACT FROM AUTHOR]

Purpose: The orbital apex is the narrowest part of the orbit, housing the link between the intracranial cavity and orbit. Knowledge of orbital apex anatomy is crucial to selecting a surgical approach and reducing the risk of complications. Our purpose is to summarize current knowledge on surgical anatomy and attempt to reach a consensus on definition of the orbital apex. Methods: The online databases of Embase, the Cochrane library, Web of Science and PubMed (MEDLINE) were queried in a comprehensive bibliographic search on the (surgical) anatomy of the orbital apex and consisted of a combination of two subjects, using indexed terms and free text: "Orbital Apex" and "Orbital Anatomy." Results: A total of 114 relevant papers were included in this review. Numerous anatomical variations are described in the literature. Variations of the optic canal include duplication (0.64%) and keyhole anomaly (2.65%). Variations in pneumatization of the anterior clinoid process were unilateral in almost 10%, bilateral in 9%, and normal in 72%. A rare variant of the superior orbital fissure (SOF) is Warwick's foramen, which appears as if the lowest portion of the SOF was separated from the main fissure by a transverse bony bridge. Conclusion: The definition of the orbital apex varies in the literature, and further research would most likely identify additional variations. A universal definition reporting these variations and pathology and imaging findings is essential for determining the optimal surgical approach to the orbital apex. [ABSTRACT FROM AUTHOR]

Abstract When a person attempts to conceal an emotion, the genuine emotion is manifest as a micro-expression. Exploration of automatic facial micro-expression recognition systems is relatively new in the computer vision domain. This is due to the difficulty in implementing optimal feature extraction methods to cope with the subtlety and brief motion characteristics of the expression. Most of the existing approaches extract the subtle facial movements based on hand-crafted features. In this paper, we address the micro-expression recognition task with a convolutional neural network (CNN) architecture, which well integrates the features extracted from each video. We introduce the Optical Flow Features from Apex frame Network (OFF-ApexNet). This is a new feature descriptor that combines the optical flow guided context with the CNN. Firstly, we obtain the location of the apex frame from each video sequence as it portrays the highest intensity of facial motion among all frames. Then, the optical flow information are attained from the apex frame and a reference frame (i.e., onset frame). Finally, the optical flow features are fed into a pre-designed CNN model for further feature enhancement as well as to carry out the expression classification. To evaluate the effectiveness of OFF-ApexNet method, comprehensive evaluations are conducted on three public spontaneous micro-expression datasets (i.e., SMIC, CASME II and SAMM). The promising recognition result suggests that the proposed method can optimally describe the significant micro-expression details. In particular, we report that, in a multi-database with leave-one-subject-out cross-validation (LOSOCV) experimental protocol, the recognition performance reaches 74.60% of recognition accuracy and F-measure of 71.04%. We also note that this is the first work that performs cross-dataset validation on three databases in this domain. Highlights • Only two frames from each video were utilized to represent significant motion features. • A feature extractor that incorporates both the handcrafted and data-drive features were proposed. • Promising performances were obtained in three micro-expression databases. • A comparison of the proposed method with the state-of-the-arts was reported. [ABSTRACT FROM AUTHOR]

Abstract One of the tenets of mammalian auditory physiology is that the frequency selectivity at the cochlear base decreases as a function of stimulus level. Changes in frequency selectivity have been shown to be accompanied by changes in response phases as a function of stimulus level. The existence of such nonlinear properties has been revealed by the analysis of either direct or indirect recordings of mechanical vibrations of the cochlea. Direct measurements of cochlear mechanical vibrations, however, have been carried out with success primarily in cochlear regions that are tuned to frequencies >7 kHz, but not in regions sensitive to lower frequencies. In this paper we continue to analyze recently published data from measurements of sound-induced vibrations at four locations near the apex of the intact guinea pig cochlea, in a region encompassing approximately 25% of its total length. Analysis of the responses at all locations reveal level-dependent phase properties that are rather different from those usually reported at the base of the cochlea of laboratory animals such as the chinchilla. Cochlear group delays, for example, increase or remain constant with increasing stimulus. Similarly, frequency selectivity at all the regions increases as a function of stimulus level. Highlights • The base and the apex of the cochlea process sounds in a different fashion. • Nonlinear amplification of vibrations at the apex is smaller than at the base. • Nonlinear phase changes at the apex and at the base are different. • Group delays increase or remain constant with stimulus level at the apex. • Frequency selectivity increases with stimulus level at the apex. [ABSTRACT FROM AUTHOR]

Despite recent interest and advances in facial micro-expression research, there is still plenty of room for improvement in terms of micro-expression recognition. Conventional feature extraction approaches for micro-expression video consider either the whole video sequence or a part of it, for representation. However, with the high-speed video capture of micro-expressions (100–200 fps), are all frames necessary to provide a sufficiently meaningful representation? Is the luxury of data a bane to accurate recognition? A novel proposition is presented in this paper, whereby we utilize only two images per video, namely, the apex frame and the onset frame. The apex frame of a video contains the highest intensity of expression changes among all frames, while the onset is the perfect choice of a reference frame with neutral expression. A new feature extractor, Bi-Weighted Oriented Optical Flow (Bi-WOOF) is proposed to encode essential expressiveness of the apex frame. We evaluated the proposed method on five micro-expression databases—CAS(ME) 2 , CASME II, SMIC-HS, SMIC-NIR and SMIC-VIS. Our experiments lend credence to our hypothesis, with our proposed technique achieving a state-of-the-art F1-score recognition performance of 0.61 and 0.62 in the high frame rate CASME II and SMIC-HS databases respectively. [ABSTRACT FROM AUTHOR]

Remote sensing has been successfully utilized to distinguish and quantify sediment properties in the intertidal environment. Classification approaches of imagery are popular and powerful yet can lead to site- and case-specific results. Such specificity creates challenges for temporal studies. Thus, this paper investigates the use of regression models to quantify sediment properties instead of classifying them. Two regression approaches, namely multiple regression (MR) and support vector regression (SVR), are used in this study for the retrieval of bio-physical variables of intertidal surface sediment of the IJzermonding, a Belgian nature reserve. In the regression analysis, mud content, chlorophyll a concentration, organic matter content, and soil moisture are estimated using radiometric variables of two airborne sensors, namely airborne hyperspectral sensor (AHS) and airborne prism experiment (APEX) and and using field hyperspectral acquisitions by analytical spectral device (ASD). The performance of the two regression approaches is best for the estimation of moisture content. SVR attains the highest accuracy without feature reduction while MR achieves good results when feature reduction is carried out. Sediment property maps are successfully obtained using the models and hyperspectral imagery where SVR used with all bands achieves the best performance. The study also involves the extraction of weights identifying the contribution of each band of the images in the quantification of each sediment property when MR and principal component analysis are used. [ABSTRACT FROM AUTHOR]

Atmospheric correction plays a crucial role among the processing steps applied to remotely sensed hyperspectral data. Atmospheric correction comprises a group of procedures needed to remove atmospheric effects from observed spectra, i.e. the transformation from at-sensor radiances to at-surface radiances or reflectances. In this paper we present the different steps in the atmospheric correction process for APEX hyperspectral data as applied by the Central Data Processing Center (CDPC) at the Flemish Institute for Technological Research (VITO, Mol, Belgium). The MODerate resolution atmospheric TRANsmission program (MODTRAN) is used to determine the source of radiation and for applying the actual atmospheric correction. As part of the overall correction process, supporting algorithms are provided in order to derive MODTRAN configuration parameters and to account for specific effects, e.g. correction for adjacency effects, haze and shadow correction, and topographic BRDF correction. The methods and theory underlying these corrections and an example of an application are presented. [ABSTRACT FROM AUTHOR]

APEX (Airborne Prism EXperiment) is a high spectral and spatial resolution hyperspectral sensor developed by a Swiss-Belgian consortium on behalf of the European Space Agency. Since the acceptance of the instrument in 2010, it has been operated jointly by the Flemish Institute for Technological Research (VITO, Mol, Belgium) and the Remote Sensing Laboratories (RSL, Zurich, Switzerland). During this period, several flight campaigns have been performed across Europe, gathering over 4 Terabytes of raw data. Following radiometric, geometric and atmospheric processing, this data has been provided to a multitude of Belgian and European researchers, institutes and agencies, including the European Space Agency (ESA), the European Facility for Airborne Research (EUFAR) and the Belgian Science Policy Office (BelSPO). The applications of APEX data span a wide range of research topics, e.g. landcover mapping (mountainous, coastal, countryside and urban regions), the assessment of important structural and (bio)physical characteristics of vegetative and non-vegetative species, the tracing of atmospheric gases, and water content analysis (chlorophyll, suspended matter). Recurrent instrument calibration, accurate flight planning and preparation, and experienced pilots and instrument operators are crucial to successful data acquisition campaigns. In this paper, we highlight in detail these practical aspects of a typical APEX data acquisition campaign. [ABSTRACT FROM AUTHOR]

Hyperspectral imagery originating from airborne sensors is nowadays widely used for the detailed characterization of land surface. The correct mapping of the pixel positions to ground locations largely contributes to the success of the applications. Accurate geometric correction, also referred to as 'orthorectification', is thus an important prerequisite which must be performed prior to using airborne imagery for evaluations like change detection, or mapping or overlaying the imagery with existing data sets or maps. A so-called 'ortho-image' provides an accurate representation of the earth's surface, having been adjusted for lens distortions, camera tilt and topographic relief. In this paper, we describe the different steps in the geometric correction process of APEX hyperspectral data, as applied in the Central Data Processing Center (CDPC) at the Flemish Institute for Technological Research (VITO, Mol, Belgium). APEX ortho-images are generated through direct georeferencing of the raw images, thereby making use of sensor interior and exterior orientation data, boresight calibration data and elevation data. They can be referenced to any userspecified output projection system and can be resampled to any output pixel size. [ABSTRACT FROM AUTHOR]

National sport governing bodies (NSGBs) are distinct from other nonprofits in the way that they are mechanisms instituted to govern other sport organizations that deliver the services in their respective sports. This formal status places a NSGB at the summit or apex of a network of organizations dealing with the same sport. This conceptual paper describes the nature of the apex of a network of sport organizations and describes the unique functions associated with that role. [ABSTRACT FROM AUTHOR]

SWAT (Soil and Water Assessment Tool) and APEX (Agricultural Policy/Environmental eXtender) are respectively large and small watershed simulation models derived from EPIC (Environmental Policy Integrated Climate), a field-scale agroecology simulation model. All three models are coded in Fortran and have evolved over several decades. They are widely used to analyze anthropogenic influences on soil and water quality and quantity. Much of the original Fortran code has been retained even though Fortran has been through several cycles of development. Fortran now provides functionality originally restricted to languages like C, designed to communicate directly with the operating system and hardware. One can now use an object-oriented style of programming in Fortran, including inheritance, run-time polymorphism and overloading. In order to enhance their utility in research and policy-making, the models are undergoing a major revision to use some of the new Fortran features. With these new programming paradigms the developers of SWAT, APEX, and EPIC are working to make communication between the two models seamless. This paper describes the ongoing revision of these models that will make them easier to use, maintain, modify and document. It is intended that they will converge as they continue to evolution, while maintaining their distinctive features, capabilities and identities. [ABSTRACT FROM AUTHOR]

The traditional techniques of chemo-mechanical instrumentation and disinfection of the root canal system used in mature teeth are limited by the immature tooth's anatomy. The open apex is difficult or impossible to seal with conventional root filling methods because of the absence of an apical stop. Furthermore, the arrested development of the dentinal walls at the time of pulp necrosis leaves a weak tooth with thin dentinal walls that are susceptible to fracture. The purpose of the paper is to present the case of a patient wherein revascularization of the necrotic infected pulp space of an immature permanent mandibular molar was induced by stimulation of a blood clot from the periapical tissues into the canal space. The treatment approach can help rescue infected immature teeth by physiologically strengthening the root walls. [ABSTRACT FROM AUTHOR]

APEX (A gricultural P olicy/ E nvironmental e X tender) is an oft-used agroecosystem model but has limited use in groundwater-driven watersheds due to a simplistic representation of groundwater processes. This paper presents the linkage of APEX and the groundwater flow model MODFLOW into a single modeling code. The mapping of recharge, groundwater head, and groundwater-surface water interactions are handled internally via subroutines. The APEX-MODFLOW model is applied to three watersheds in the United States for testing code accuracy and hydrologic state variables and fluxes: the Animas River Watershed, Colorado and New Mexico (3543 km2); the Price River Watershed, Utah (4886 km2); and the Middle Bosque River Watershed, Texas (470 km2). Whereas the hydrology of the Animas River and Price River watersheds is driven by snowmelt and spring runoff, the hydrology of the Middle Bosque River Watershed is driven by summer thunderstorms. The model can be used for scenario analysis in groundwater-driven watersheds. • New integrated hydrologic model links APEX model to MODFLOW model. • Model passes recharge, water table elevation, and gw-sw flux rates internally. • APEX-MODFLOW applied to three watersheds in Utah, Colorado, and Texas, USA. • Model results show importance of including physically based groundwater flow. [ABSTRACT FROM AUTHOR]

In recent years, numerous facial expression recognition related applications had been commercialized in the market. Many of them achieved promising and reliable performance results in real-world applications. In contrast, the automated micro-expression recognition system relevant research analysis is still greatly lacking. This is because of the nature of the micro-expression that is usually appeared with relatively lesser duration and lower intensity. However, due to its uncontrollable, subtlety, and spontaneity properties, it is capable to reveal one's concealed genuine feelings. Therefore, this paper attempts to improve the performance of current micro-expression recognition systems by introducing an efficient and effective algorithm. Particularly, we employ genetic algorithms (GA) to discover an optimal solution in order to facilitate the computational process in producing better recognition results. Prior to the GA implementation, the benchmark preprocessing method and feature extractors are directly adopted herein. Succinctly, the complete proposed framework composes three main steps: the apex frame acquisition, optical flow approximation, and feature extraction with CNN architecture. Experiments are conducted on the composite dataset that is made up of three publicly available databases, viz, CASME II, SMIC, and SAMM. The recognition performance tends to prevail the state-of-the-art methods by attaining an accuracy of 85.9% and F1-score of 83.7%. • A novel approach for micro-expression recognition was proposed. • A genetic algorithm was implemented on one of the state-of-the-art ME algorithms for feature integration. • Promising performances were obtained in three micro-expression databases. • A comparison of the proposed method with the benchmark and recent methods was reported. [ABSTRACT FROM AUTHOR]