Two-dimensional Representation Research Articles

Magnification-driven B-spline interpolation for cone-beam projection and backprojection.

Discretizing tomographic forward and backward operations is a crucial step in the design of model-based reconstruction algorithms. Standard projectors rely on linear interpolation, whose adjoint introduces discretization errors during backprojection. More advanced techniques are obtained through geometric footprint models that may present a high computational cost and an inner logic that is not suitable for implementation on massively parallel computing architectures. In this work, we take a fresh look at the discretization of resampling transforms and focus on the issue of magnification-induced local sampling variations by introducing a new magnification-driven interpolation approach for tomography. Starting from the existing literature on spline interpolation for magnification purposes, we provide a mathematical formulation for discretizing a one-dimensional homography. We then extend our approach to two-dimensional representations in order to account for the geometry of cone-beam computed tomography with a flat panel detector. Our new method relies on the decomposition of signals onto a space generated by nonuniform B-splines so as to capture the spatially varying magnification that locally affects sampling. We propose various degrees of approximations for a rapid implementation of the proposed approach. Our framework allows us to define a novel family of projector/backprojector pairs parameterized by the order of the employed B-splines. The state-of-the-art distance-driven interpolation appears to fit into this family thus providing new insight and computational layout for this scheme. The question of data resampling at the detector level is handled and integrated with reconstruction in a singleframework. Results on both synthetic data and real data using a quality assurance phantom, were performed to validate our approach. We show experimentally that our approximate implementations are associated with reduced complexity while achieving a near-optimal performance. In contrast with linear interpolation, B-splines guarantee full usage of all data samples, and thus the X-ray dose, leading to more uniform noise properties. In addition, higher-order B-splines allow analytical and iterative reconstruction to reach higher resolution. These benefits appear more significant when downsampling frames acquired by X-ray flat-panel detectors with small pixels. Magnification-driven B-spline interpolation is shown to provide high-accuracy projection operators with good-quality adjoints for iterative reconstruction. It equally applies to backprojection for analytical reconstruction and detector datadownsampling.

METHODS OF DIGITIZATION OF CULTURAL HERITAGE. THE CASE STUDY OF THE TERME DI DIOCLEZIANO

Abstract. The city of Rome looks like a succession of stratifications that have led to the formation of an architectural panorama that is unique in the world. The different eras and architectural styles that have defined the city in the two millennia of history make each of its parts unique. The punctual, areal and linear archaeological complexes unequivocally define the fabric of the city. The research investigates the theme of the analysis and representation of cultural heritage. It focuses on urban coexistences, not valued or in need of a new approach that modifies the way in which we relate. The research focuses on the way in which monumental archeologies interact with the contemporary urban fabric. The case study taken into consideration, to understand the archaeological survey methodologies for the digitization of cultural heritage, is the monumental complex of the Terme di Diocleziano in Rome. The ultimate goal is therefore to define an integrated survey methodology through which it is possible to set up a digital development work for archeologies. A development that is not limited to the two-dimensional representation of architecture but also three-dimensional, and informative at the model and geographic systems level.

Assessing the Weight-Bearing Surface in Dysplastic Acetabulae: The Sourcil Index.

BackgroundAlthough a variety of standardized measurements have been described to evaluate acetabular dysplasia, no single measurement is without limitations. We describe the Sourcil Index (SI), a novel measure of the weight-bearing surface of the acetabulum on anteroposterior pelvis films. The SI is the angle formed by the medial and lateral margins of the sourcil and the center of rotation of the femoral head.MethodsAnteroposterior pelvis radiographs of skeletally mature patients from 2015 were reviewed. Studies with fractures or implants were excluded. Films were read by 2 orthopedic surgeons and a radiologist 3 times each, 8 weeks apart. The SI, Sharp's Angle (SA), and lateral center edge angle (LCEA) were recorded. Pearson intraclass correlation coefficients with 95% confidence intervals were calculated. The SI was then compared to the SA and LCEA to preliminarily assess diagnostic accuracy.ResultsFive hundred thirty-five hips in 292 patients met inclusion. Intraobserver reliability is as follows: SI = 0.95 (0.93-0.98), LCEA = 0.89 (0.82 -0.96), and SA = 0.90 (0.85-0.96). Interobserver reliability is as follows: SI = 0.90 (0.84-0.94), SA = 0.78 (0.64-0.86), and LCEA = 0.73 (0.56-0.82). There were 51 dysplastic hips within this cohort.ConclusionThe SI is a reproducible measurement on plain radiographs. The SI is a two-dimensional representation of the size of the weight-bearing surface of the acetabulum and could provide an estimation of joint contact pressures. Used with existing measures, the SI may provide a more nuanced understanding of acetabular morphology.

Are gamma passing rate and dose-volume histogram QA metrics correlated?

The quality of a measured distribution of dose delivered against its corresponding radiotherapy plan is routinely assessed by gamma index (GI) and dose-volume histogram (DVH) metrics. Any correlation between error detection rates, as based on either of these approaches, while argued, has never been convincingly demonstrated. The dependence of the strength of correlation between the GI passing rate ( ) and DVH quality assurance (QA) metrics on various elements of the therapy plan has not been systematically investigated. A formal analysis of the relation between and DVH metrics has been undertaken, leading to a relationship which may partly approximate with respect to the DVH. This relationship was further validated by studying examples of simulated clinical radiotherapy plans and by studying the correlation between and the derived relationship using a simple two-dimensional representations of the planning target volume (PTV) and organs at risk (OAR), where penumbra regions, distance-to-agreement tolerances and dose delivery errors were systematically varied. It is shown formally that there cannot be any correlation between and other commonly applied DVH-derived QA measures. However, may be partly approximated given the planned and measured DVH. The derived approximation (the " -slope indicator") may be clinically useful in some practical cases of radiotherapy plan QA. In formal terms, there cannot be any correlation between and any common DVH-calculated patient-specific measures, with respect to PTV or OAR. However, as demonstrated analytically and further confirmed in our simulation studies, the approximation derived in this study (the " -slope indicator") may in some cases offer a degree of correlation between and the PTV and OAR DVH QA metrics in measured and planned patient-specific dose distributions-which may be potentially useful in clinical practice.

Systematic Method for the Exploration, Representation, and Classification of the Diphenylalanine Solvatomorphic Space.

An understanding of the conditions that govern the self-assembly process of peptides is a fundamental step toward the design of new nanostructures that possess interesting properties. In this work, we first synthesize and explore extensively diphenylalanine (FF) self-assembling crystals formed in different solvents (i.e., solvatomorphs) using polarized optical microscopy and transmission electron microscopy. Then, we develop a numerical method that allows an unambiguous classification of the solvatomorphs through a K-means automatic clustering method. In addition, we generate a two-dimensional (2D) representation of the solvatomorphic space together with the clustering results via a principal component analysis (PCA). The classification is based on structural similarities of solvatomorphs as revealed by the analysis of their respective infrared spectra. Among the 20 samples considered, 4 clear clusters are extracted within which the compounds show very similar crystalline structures. The information extracted allows us to assign many of the peaks that appear in the complex IR spectra of the samples considered. The implementation of the overall procedure we propose, i.e., "GAULOIS" and "REFRACT-R", is transferable to other types of spectra and paves the way for a systematic, fast, and accurate classification method applicable to various types of experimental spectroscopic data.

A Study on Seizure Detection of EEG Signals Represented in 2D.

A seizure is a neurological disorder caused by abnormal neuronal discharges in the brain, which severely reduces the quality of life of patients and often endangers their lives. Automatic seizure detection is an important research area in the treatment of seizure and is a prerequisite for seizure intervention. Deep learning has been widely used for automatic detection of seizures, and many related research works decomposed the electroencephalogram (EEG) raw signal with a time window to obtain EEG signal slices, then performed feature extraction on the slices, and represented the obtained features as input data for neural networks. There are various methods for EEG signal decomposition, feature extraction, and representation, and most of the studies have been based on fixed hardware resources for the design of the scheme, which reduces the adaptability of the scheme in different application scenarios and makes it difficult to optimize the algorithms in the scheme. To address the above issues, this paper proposes a deep learning-based model for seizure detection, mainly characterized by the two-dimensional representation of EEG features and the scalability of neural networks. The model modularizes the main steps of seizure detection and improves the adaptability of the model to different hardware resource constraints, in order to increase the convenience of the algorithm optimization or the replacement of each module. The proposed model consists of five parts, and the model was tested using two epilepsy datasets separately. The experimental results showed that the proposed model has strong generality and good classification accuracy for seizure detection.

Development of a lumped-parameter code for efficient assessment of in-vessel melt retention strategy of LWRs

Motivated by efficient assessment of the in-vessel retention (IVR) strategy employed in some designs of light water reactors, a lumped-parameter code named as transIVR was developed in the present study, which has the features as (i) quick estimates of transient one- and two-layer melt pool heat transfer with reasonable accuracies; and (ii) two-dimensional representation of heat conduction in the reactor pressure vessel wall, facilitating the coupled thermo-mechanical analysis of the reactor pressure vessel under thermal loads. The transIVR code was first benchmarked against the UCSB FIBS case of two-layer configuration and then validated against the LIVE-7V experiment. Both cases showed good predictions in the IVR-interested parameters like the heat flux profile, residual wall thickness and energy split. It indicates the code's capability in predicting two-layer and transient melt pool heat transfers, respectively. Finally, the code was coupled with ANSYS Mechanical for the efficient assessment of vessel integrity. Good results were achieved in the validation against the vessel failure experiment FOREVER-EC2. Hence, the transIVR code is an efficient tool suitable to address related safety concerns of light water reactors, including IVR efficacy and vessel integrity (with its coupling to mechanical solvers).

Worldline numerics applied to custom Casimir geometry generates unanticipated intersection with Alcubierre warp metric

While conducting analysis related to a DARPA-funded project to evaluate possible structure of the energy density present in a Casimir cavity as predicted by the dynamic vacuum model, a micro/nano-scale structure has been discovered that predicts negative energy density distribution that closely matches requirements for the Alcubierre metric. The simplest notional geometry being analyzed as part of the DARPA-funded work consists of a standard parallel plate Casimir cavity equipped with pillars arrayed along the cavity mid-plane with the purpose of detecting a transient electric field arising from vacuum polarization conjectured to occur along the midplane of the cavity. An analytic technique called worldline numerics was adapted to numerically assess vacuum response to the custom Casimir cavity, and these numerical analysis results were observed to be qualitatively quite similar to a two-dimensional representation of energy density requirements for the Alcubierre warp metric. Subsequently, a toy model consisting of a 1 upmu m diameter sphere centrally located in a 4 upmu m diameter cylinder was analyzed to show a three-dimensional Casimir energy density that correlates well with the Alcubierre warp metric requirements. This qualitative correlation would suggest that chip-scale experiments might be explored to attempt to measure tiny signatures illustrative of the presence of the conjectured phenomenon: a real, albeit humble, warp bubble.

SDSS-IV MaNGA: Refining Strong Line Diagnostic Classifications Using Spatially Resolved Gas Dynamics

Abstract We use the statistical power of the MaNGA integral-field spectroscopic galaxy survey to improve the definition of strong line diagnostic boundaries used to classify gas ionization properties in galaxies. We detect line emission from 3.6 million spaxels distributed across 7400 individual galaxies spanning a wide range of stellar masses, star formation rates, and morphological types, and find that the gas-phase velocity dispersion σ Hα correlates strongly with traditional optical emission-line ratios such as [S ii]/Hα, [N ii]/Hα, [O i]/Hα, and [O iii]/Hβ. Spaxels whose line ratios are most consistent with ionization by galactic H ii regions exhibit a narrow range of dynamically cold line-of-sight velocity distributions (LOSVDs) peaked around 25 km s−1 corresponding to a galactic thin disk, while those consistent with ionization by active galactic nuclei (AGNs) and low-ionization emission-line regions (LI(N)ERs) have significantly broader LOSVDs extending to 200 km s−1. Star-forming, AGN, and LI(N)ER regions are additionally well separated from each other in terms of their stellar velocity dispersion, stellar population age, Hα equivalent width, and typical radius within a given galaxy. We use our observations to revise the traditional emission-line diagnostic classifications so that they reliably identify distinct dynamical samples both in two-dimensional representations of the diagnostic line ratio space and in a multidimensional space that accounts for the complex folding of the star-forming model surface. By comparing the MaNGA observations to the SDSS single-fiber galaxy sample, we note that the latter is systematically biased against young, low-metallicity star-forming regions that lie outside of the 3″ fiber footprint.

Analyzing the similarity of protein domains by clustering Molecular Surface Maps

Many biochemical and biomedical applications such as protein engineering or drug design are concerned with finding functionally similar proteins, however, this remains to be a challenging task. We present a new imaged-based approach for identifying and visually comparing proteins with similar function that builds on the hierarchical clustering of Molecular Surface Maps. Such maps are two-dimensional representations of complex molecular surfaces and can be used to visualize the topology and different physico-chemical properties of proteins. Our method is based on the idea that visually similar maps also imply a similarity in the function of the mapped proteins. To determine map similarity, we compute descriptive feature vectors using image moments, color moments, or a Convolutional Neural Network and use them for a hierarchical clustering of the maps. We demonstrate the feasibility of our approach using two data sets: an ensemble of hand-selected proteins with known similarities used for verification and an ensemble of ketolase enzymes, where we analyzed the individual domains using our method. Our method is integrated in an interactive visualization application, which allows users to explore and analyze the results. It visualizes the hierarchical clustering and offers linked views that provide details for a comparative data analysis.

Automated classification of lung sound signals based on empirical mode decomposition

Chronic obstructive pulmonary disease (COPD) is a chronic non-reversible lung disease. Other acute respiratory illness due to infections are termed as non-chronic. In general, the pulmonologist carries preliminary screening by accessing lung sounds. In this paper, we propose a methodology to automatically classify lung sounds associated with non-chronic and chronic categories. To accomplish the task, at first, the empirical mode decomposition (EMD) is applied to lung sound signals to obtain intrinsic mode functions (IMFs). Considering the availability of IMFs in entire dataset and by using a hybrid strategy, first four IMFs have been selected for feature extraction purpose. The IMFs are then further processed to construct two-dimensional (2D) and higher-dimensional (HD) phase space representation (PSR). The feature space includes the 95% confidence ellipse area from 2D-PSR and interquartile range (IQR), mean, median, standard deviation, skewness and kurtosis of Euclidian distances computed from HD-PSR. The process is carried out for the first four IMFs corresponding to the non-chronic and chronic categories of the lung sounds. Neighborhood component analysis is used to select best performing features. The computed and selected features depict a significant ability to discriminate the two categories of lung sound signals. To perform classification, we use ensemble classifiers. Simulation outcomes on ICBHI 2017 lung sound dataset show the ability of the proposed method in effectively classifying non-chronic and chronic lung sound signals. Ensemble of Bagged tree provides the highest classification accuracy of 97.14% over feature space constituted by 10D-PSR of fourth IMF.

New Concepts of Flow Cytometry Analysis in Oncohematology: Application to Diagnosis and Follow up (Minimal Residual Disease) in AML, ALL and MDS

IntroductionThe development of mass cytometry (CyTOF), using up to 40 concomitant tags for a given sample, has led to the generation of large databases. In order to properly analyze these extensive files, new software solutions have been devised using either mathematical reduction of multidimensional spaces or clustering methods allowing for two-dimensional representations. Such tools as SPADE (SPanning-tree progression Analysis of Density-Normalized events), t-SNE (t-Stochastic Neighborhood Embedding) and FlowSOM (Flow Self Organizing Map) therefore were published with CyTOF data. They have however seldom been used to analyze classical flow cytometry (FCM) data, although current instruments generate 10-12 parameters analyzes that would be good candidates for such analyzes. Here we report on the new paradigm of using such tools to interpret harmonized classical FCM data in particular for minimal residual disease (MRD).Materials and MethodsMultiparametric FCM was performed using panels and recommendations proposed by the Harmonemia group (Lacombe F et al. Leukemia 2016), on a Navios® instrument (Beckman Coulter, Miami, FL) since 2013, yielding a cohort of diagnosis (D) and follow-up (FU) samples of 460 AML (160 D, 300 FU), 695 ALL (129 D, 566 FU), and 150 MDS (100 D, 50 FU). In parallel, 45 normal bone marrow (NBM) samples (respectively 22 for AML and MDS cases and 23 for ALL cases) were processed in the same conditions as pathological samples with the relevant immunophenotyping panels (three combinations for AML/MDS and 3 others for ALL). All files were first processed using specific R-software scripts and Bioconduct or CRAN packages to normalize fluorescence and light diffusion intensity including shift intensity, compensation and biexponential/logical adjustment. Harmonized flow cytometry files (HF) ([1305 pathological + 45 NBM files] x 3 panels corresponding to a total of 4050 HF files) were then generated and used for further analysis.NBM files were adjusted and merged in a single, events-adjusted, representative file of NBM (R-NBM). For each case, merges of this R-NBM, D and FU files were processed using 3 different analysis ways 1) principal component analysis (PCA), 2) t-SNE and 3) FlowSOM. New resulting parameters were generated for each combination of R-NBM, D and FU merged files, i.e. PCA, t-SNE and FlowSOM. These parameters could then be analyzed using the Kaluza® software (Beckman Coulter). Graphical representations of all analyses were then performed in an automated unsupervised manner with Kaluza®, allowing for a direct comparison of NBM and pathological samples for each case. Interestingly, HF files generated by the R software, being integrated in the system, could also be classically analyzed by Kaluza®, in a supervised manner, by drawing gates around PCA/t-SNE clusters or FlowSOM nodes of interest. Such gates allowed to further analyze data by backgating on classical biparametric representations of antibody combinations as well as on the classical CD45/SSC bone marrow cartography.ResultsBoth t-SNE and FlowSOM provide a clear identification of normal and abnormal subsets, while PCA is less discriminative. Comparative simultaneous representations of the three types of samples - (D), (FU) and (NBM)- allow for both a rapid visualization and accurate quantification of normal and abnormal cell subpopulations. The FlowSOM solution further allows to identify and visually characterize specific subsets both within the diagnostic clone and along normal hematopoietic differentiation. FU samples can then be easily analyzed for the persistence of abnormal immunophenotypic characteristics, both in AML and ALL. Even unsupervised results allow for a rapid appreciation and quantification of MRD. Besides, such comparisons, between NBM and D samples provide a new approach of the complexity of MDS. Moreover, both supervised and unsupervised results were comparable.ConclusionThe combination of automated sophisticated multidimensional representation of numerous subsets and their in-depth analysis by classical manual tools of FCM analysis is a truly revolutionary approach. The strength of FCM, which retains and analyses morphological characteristics of the cells, is thus combined to the precision of mathematical analyzes developed for CyTOF. These versatile new tools open the way for a new era of classical FCM analysis in hematological malignancies. [Display omitted] DisclosuresDupont:Beckman Coulter: Employment.

Development and use of augmented reality models to teach medicinal chemistry

Background and purposeStudents in the doctor of pharmacy curriculum have varied backgrounds in their chemical training and also their ability to make mental conversions from two-dimensional chemical representations, on lecture slides or textbook images, to three-dimensional cognitive understanding. In order to bridge the gap, augmented reality (AR) models were developed to provide an alternative learning medium for the students. AR was selected to take advantage of the ubiquitous presence of smartphones, without incurring the expense of Virtual Reality hardware. Educational activity and settingAR models were developed and introduced in the classroom in three phases. Student survey responses were used to improve the utility of the models in between phases. Active learning exercises were developed that required both individual and group interactions to complete. FindingsAn optimized AR model creation workflow was developed that allowed each AR model to be created and posted in about 30 min. Depending on the phase of the study, 69% to 88% of the students found the AR models easy to use and 58% to 83% wanted to see more AR models used in future lectures. A majority (76%) of the students viewed the AR models on their smartphones. SummaryAugmented reality modules were created for use in medicinal chemistry courses in the pharmacy curriculum. Models were introduced in phases and included iterative improvements based on student feedback. The AR exercises provided active learning opportunities and were well received. The majority of students would like additional AR modules used in the course.

A New Interpretation of the Grid System Reform in the Late Period

This paper offers a new art-historical interpretation of the grid reform of anthropomorphic representations in Egypt around the mid-seventh century BC. The objective of this paper is two-fold. First, it will demonstrate the problems with previous interpretations, which depended, on the one hand, upon the written record of Diodorus Siculus regarding the Egyptian method of statue production, and upon comparative analyses of the two-dimensional representation of human figures on the other. Secondly, this paper is devoted to providing a new understanding of the art-historical context of the grid reform. This reform – in which Late Period Egyptians abandoned the tradition that had been utilised for nearly 1,800 years and created a completely new system by uniting the Egyptian metrological system and the traditional method of grid projection – less reflects improvement in the appearance of the image, and rather demonstrates a metaphysical development that had never been seen or experienced before.

Learning Classical Planning Strategies with Policy Gradient

A common paradigm in classical planning is heuristic forward search. Forward search planners often rely on simple best-first search which remains fixed throughout the search process. In this paper, we introduce a novel search framework capable of alternating between several forward search approaches while solving a particular planning problem. Selection of the approach is performed using a trainable stochastic policy, mapping the state of the search to a probability distribution over the approaches. This enables using policy gradient to learn search strategies tailored to a specific distributions of planning problems and a selected performance metric, e.g. the IPC score. We instantiate the framework by constructing a policy space consisting of five search approaches and a two-dimensional representation of the planner’s state. Then, we train the system on randomly generated problems from five IPC domains using three different performance metrics. Our experimental results show that the learner is able to discover domain-specific search strategies, improving the planner’s performance relative to the baselines of plain bestfirst search and a uniform policy.

A two-dimensional representation of musical chords using the simplicity of frequency and period ratios as coordinates

Musical chords play an essential role, especially in Western music, and the corresponding consonance–dissonance contrasts and emotional continua are still the targets of investigation in psychoacoustics and neurophysiology. In the present study, we define the simplicity of frequency ratios and simplicity of period ratios for the constituents of a chord and propose that those measures should be used as the two coordinate axes in the plane for plotting chords. In this plane, the major and minor chords are reflections of each other with respect to the diagonal . The other chord pair in the same relationship is the major–minor seventh (dominant seventh) and the half-diminished seventh chords. The other triads and seventh chords do not make such pairs of different categories of chords. It was also found that at least for triads, the sum and the difference seem to correspond to subjective consonance and the melancholic/sad emotional ratings, respectively. Implications of these findings are discussed. The proposed simple presentation may help interpret and model psychoacoustic and neurophysiological results on musical chords.

Role Oral and Maxillofacial Imaging in Upper Airway Assessment

Evaluation of upper airway space is a routine procedure in orthodontic diagnosis and treatment planning.The two-dimensional representation of three-dimensional structures as afforded by the radiographic image incephalometry provides limited diagnostic information. Cone Beam Computed Tomography was developedwith the purpose of providing a superior imaging modality in dento-maxillofacial diagnosis. Objective:To review the limits, functions and anomalies of different areas that make up the upper airway, to provideinformation about specific methods most widely used by specialists for their evaluation, and to describe andevaluate the information level and diagnostic accuracy of methods such as lateral cephalometric analysisand Cone Beam CT (CBCT). Conclusions: It is essential to know upper airway assessment methods, whichinclude a clinical examination, a radiographic evaluation and CBCT. These will indicate possible functionalchanges that could interfere with treatment.

Dogs fail to recognize a human pointing gesture in two-dimensional depictions of motion cues

Few studies have investigated biological motion perception in dogs and it remains unknown whether dogs recognise the biological identity of two-dimensional animations of human motion cues. To test this, we assessed the dogs’ (N = 32) responses to point-light displays of a human performing a pointing gesture towards one of two pots. At the start of the experiment the demonstrator was a real-life person, but over the course of the test dogs were presented with two-dimensional figurative representations of pointing gestures in which visual information was progressively removed until only the isolated motion cues remained. Dogs’ accuracy was above chance level only with real-life and black-and-white videos, but not with the silhouette or the point-light figure. Dogs’ accuracy during these conditions was significantly lower than in the real-life condition. This result could not be explained by trial order since dogs’ performance was still not higher than chance when only the point-light figure condition was presented after the initial demonstration. The results imply that dogs are unable to recognise humans in two-dimensional depictions of human motion cues only. In spite of extensive exposure to human movement, dogs need more perceptual cues to detect equivalence between human two-dimensional animations and the represented living entity.

Novel carbon-rich B–C compounds in orthorhombic phase: First-principles calculations

A novel carbon-rich B–C compounds B2C3 in orthorhombic phase is proposed in this work. Firstly, the stability of B2C3 has been demonstrated, the thermodynamic stability, dynamic stability, and mechanical stability of B2C3 are confirmed by the formation enthalpies, phonon spectra and elastic constants, respectively. As a semiconductor material with indirect band gap, B2C3 has a larger mechanical anisotropy in Poisson's ratio, Young's modulus, and shear modulus by three-dimensional distribution and two-dimensional representation, while in some main planes, the mechanical anisotropy in Poisson's ratio, Young's modulus, and shear modulus of B2C3 are slightly smaller than that of other B–C compounds. In addition, B2C3 shows negative Poisson's ratio in (111), (100), (010), and (001) planes, which can supply more potential areas to be used than other boron carbide compounds.

Reflections on Working with Defenses and Resistances in the Context of Teletherapy

This article focuses on the challenges we face as bioenergetic therapists when doing teletherapy. It addresses the difficulty of working with defenses and resistances in a context where the client is not physically present and where we only see part of the body through a screen, in a two-dimensional representation (sessions on video) or not at all (phone sessions). It offers practical suggestions to compensate for what cannot be apprehended directly due to distant communication. It also offers some research data on the level of efficacy and on the quality of the relationship, when teletherapy is compared with face-to-face therapy. Finally, it offers practical suggestions with regards to visual fatigue and as well as some elements of understanding Zoom fatigue.