THE ESSENCE OF TRANSPERSONAL PSYCHOTHERAPY PART 1. HEALING OF THE PRIMARY TRAUMAS OF THE THE HUMANITY HUMANITY

Предметом исследования является трансперсональная психотерапия. Ставится вопрос об особенностях её области, метода и культурно исторического пространства её работы. Анализируется причины её особ ого места в семействе различных школ психотерапии. Вводится предположение о том, что эти причины связаны с новым пониманием сознания в трансперсональном подходе. Полученные результаты дают новые возможности понимания того, каким образом и в каком культурно историческом поле работает трансперсональная психотерапия. Метод и методология исследования основаны на анализе незавершённых переходов и связанных с ними первичных травм в историческом развитии человечества вообще и России, в частности, и классификации э тих травм. Основным вкладом автора в исследовании темы является предварительная классификация первичных трав и анализе их роли во вторичной травматизации. Введённые представления о необходимости исцеления первичных травм открывают новые возможности заботы о душе в профессиональной психотерапии. The subject of the study is transpersonal psychotherapy. The question is raised about the peculiarities of The subject of the study is transpersonal psychotherapy. The question is raised about the peculiarities of its its field, methodfield, method, as well as the , as well as the cultural and hcultural and historical space of istorical space of itsits work. The reasons for its special place in the family of various schools work. The reasons for its special place in the family of various schools of psychotherapy are analyzed. The assumption is introduced that these reasons are associated with a new understanding of of psychotherapy are analyzed. The assumption is introduced that these reasons are associated with a new understanding of consciousness in the transpersonal appconsciousness in the transpersonal approach. The obtained results provide new opportunities for understanding in what cultural and roach. The obtained results provide new opportunities for understanding in what cultural and historical field and how transpersonal psychotherapy works. The method and methodology of the study are based on the analysishistorical field and how transpersonal psychotherapy works. The method and methodology of the study are based on the analysis of of incomplete transitions and associaincomplete transitions and associated primary traumas in the historical development of ted primary traumas in the historical development of the the mankind in general and Russia in mankind in general and Russia in particular, and the classification of these traumasparticular, and the classification of these traumas is presentedis presented. The main contribution of the author . The main contribution of the author toto the study of the topic is the the study of the topic is the preliminary classification of ppreliminary classification of primary traumas and the analysis of their role in secondary traumatization. The introduced ideas about rimary traumas and the analysis of their role in secondary traumatization. The introduced ideas about the need to heal primary traumas open up new opportunities for caring for the soul in professional psychotherapy.the need to heal primary traumas open up new opportunities for caring for the soul in professional psychotherapy.

Improving the Accuracy of Network Intrusion Detection with Causal Machine Learning

In recent years, machine learning (ML) algorithms have been approved effective in the intrusion detection. However, as the ML algorithms are mainly applied to evaluate the anomaly of the network, the detection accuracy for cyberattacks with multiple types cannot be fully guaranteed. The existing algorithms for network intrusion detection based on ML or feature selection are on the basis of spurious correlation between features and cyberattacks, causing several wrong classifications. In order to tackle the abovementioned problems, this research aimed to establish a novel network intrusion detection system (NIDS) based on causal ML. The proposed system started with the identification of noisy features by causal intervention, while only the features that had a causality with cyberattacks were preserved. Then, the ML algorithm was used to make a preliminary classification to select the most relevant types of cyberattacks. As a result, the unique labeled cyberattack could be detected by the counterfactual detection algorithm. In addition to a relatively stable accuracy, the complexity of cyberattack detection could also be effectively reduced, with a maximum reduction to 94% on the size of training features. Moreover, in case of the availability of several types of cyberattacks, the detection accuracy was significantly improved compared with the previous ML algorithms.

Ethical Banking and Poverty Alleviation Banking: The Two Sides of the Same Solidary Coin

(1) Background: The growing number of banking entities linked to the field of banking since the 1980s requires a preliminary classification of this sector in order to identify the main stylized facts of this wide conglomerate of institutions oriented to financial sustainability as well as the establishment of an effective differentiation that can objectively distinguish the different types of institutions operating in this subfield of finance. The objective of this research is to obtain a frame of reference by determining the main defining characteristics of these entities and their differentiating elements, by verifying, on an analytical basis, the ways in which they provide a social service in the pursuit of financial inclusion. (2) Methods: A double methodological perspective is used jointly: Factor Analysis and Cluster Analysis. (3) Results: It was possible to delimit two significant groups: Ethical Banks per se and Poverty Alleviation Banks, defining their main differences and analogies. (4) The taxonomy conducted revealed that Ethical Banks per se are primarily established in developed countries, while Poverty Alleviation Banks focus their actions on developing nations. Based on this classification, we establish a series of practical policies that support the future deployment of sustainable banking.

A preliminary classification of different tasks that make use of uncertainty visualizations

Individuals often struggle with tasks that involve uncertainty. Uncertainty visualizations are a type of cognitive aid that provides uncertainty information to help people with performing these tasks. However, the literature has shown that uncertainty visualizations differ in the extent they improve individuals’ task performance. We hypothesize that differences in the tasks can account for some of this variability. In this study, we aimed to create an initial classification of task types based on studies on uncertainty visualizations by reviewing a diverse set of recent research involving uncertainty visualizations. We classified the experimental tasks found in these papers into four groups: uncertainty assessment, forecasting, decision making, and metacognition. Then, we reviewed the result of the experiments in terms of the similarities and differences in the use of uncertainty visualizations within and between tasks. This classification serves as a starting point for further research into the effective design of visualizations of uncertainty.

A preliminary classification of different tasks that make use of uncertainty visualizations

Individuals often struggle with tasks that involve uncertainty. Uncertainty visualizations are a type of cognitive aid that provides uncertainty information to help people with performing these tasks. However, the literature has shown that uncertainty visualizations differ in the extent they improve individuals’ task performance. We hypothesize that differences in the tasks can account for some of this variability. In this study, we aimed to create an initial classification of task types based on studies on uncertainty visualizations by reviewing a diverse set of recent research involving uncertainty visualizations. We classified the experimental tasks found in these papers into four groups: uncertainty assessment, forecasting, decision making, and metacognition. Then, we reviewed the result of the experiments in terms of the similarities and differences in the use of uncertainty visualizations within and between tasks. This classification serves as a starting point for further research into the effective design of visualizations of uncertainty.

Deep Learning on MRI Images for Diagnosis of Lung Cancer Spinal Bone Metastasis

This paper aimed to explore the adoption of deep learning algorithms in lung cancer spinal bone metastasis diagnosis. Comprehensive analysis was carried out with the aid of AdaBoost algorithm and Chan-Vese (CV) algorithm. 87 patients with lung cancer spinal bone metastasis were taken as research subjects, and comprehensive evaluation was made in terms of preliminary classification of images, segmentation results, Dice index, and Jaccard coefficient. After the case of misjudgment on whether there was hot spot was excluded, the initial classification accuracy of the AdaBoost algorithm can reach 96.55%. True positive rate (TPR) was 2.3%, and false negative rate (FNR) was 1.15%. 45 MRI images with hot spots were utilized as test set to detect the segmentation accuracy of CV, maximum between-cluster variance method (OTSU), and region growing algorithm. The results showed that the Dice index and Jaccard coefficient of the CV algorithm were 0.8591 and 0.8002, respectively, which were considerably superior to OTSU (0.6125 and 0.5541) and region growing algorithm (0.7293 and 0.6598). In summary, the AdaBoost algorithm was adopted for image preliminary classification, and CV algorithm for image segmentation was ideal for the diagnosis of lung cancer spinal bone metastasis and it was worthy of clinical promotion.

Foods of Oppression

The growing recognition of food justice as an element of food studies inquiry has opened a productive vein that allows for analyzing the effects of oppression on traditional foods of Indigenous peoples. We provide a preliminary classification of food oppression by presenting several different types of foods from a number of cultures: (1) replaced and repressed foods; (2) disempowered and misrepresented foods; and (3) foods of oppression of the dispossessed. Our main argument is that these food types represent different faces of oppression and state power that, regardless of the inherent differences, have permeated diets and imaginaries in various spatial scales and, in doing so, have caused deprivation in local communities, despite being accepted in many cases as traditional food items in oppressed cultures. We conducted a systematic literature review in Scopus focusing on the traditional foods of Indigenous people and elements of oppression and revitalization. The results of our review are discussed in light of what we identify as aspects of culinary oppression. We conclude our paper by sketching the plausible first steps for redemptory solutions based on Indigenous food work aimed at reclaiming basic revalorization and revitalization.