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Maintaining Equilibrium: Finding Our Way Therapeutically in a Digitally Disrupted Marketplace
No full textThe internet, social media, and digital technologies play an increasingly pervasive role in how people relate and communicate, access and consume information in our society. This grounded theory study explores the experiences of 27 psychodynamic psychotherapists and the impact that these digital technologies have on identity development. A tentative grounded theory emerged, suggesting that for the field of psychotherapy, digital technologies like the Internet and online social media are operating as a marketplace disruptor, uprooting certain foundations of psychotherapy and requiring therapists to reconceptualize and redefine how psychotherapy operates. Pressures to curate personal and professional digital identities that can be searched by prospective patients have resulted in unprecedented difficulties creating space between selves and challenged notions of privacy. Meanwhile, the internet provides patients with unfettered access to whatever information is available online. To this end, self-disclosure could be considered the product that has been most fundamentally altered by this disrupted market, justifying the need to conceptualize digital self-disclosures as a new category of therapeutic self-disclosure. Findings suggest that in an effort to regain footing and establish equilibrium in a digitally disrupted market, therapists make decisions that at times conflict with core values of psychotherapy — often with limited awareness. This study underscores the importance of taking broad ranging, proactive steps to respond to this marketplace disruption. It offers suggestions related to running training programs, for established psychotherapists to confront generational gaps in practice and in supervision, and for continued areas of research
Recife: The Cradle of Jewish America
Get PDFRecife is the location of the first synagogue and the first Jewish community in the New World. The original Jewish community was formed during the period of the Dutch occupation and was mostly Sephardic. It wasn\u27t until the second decade of the twentieth century that Jewish life in Recife was rekindled, this time mostly Ashkenazi. Even though the two periods of Jewish life are distinct, they both show signs of a similar underlying vitality
How Childhood Traumatic Experiences Shape Elements of Adult Personality and Mental Health
Get PDFMental illness can guide the path an adult chooses to take in their life. This paper will explore that having adverse childhood experiences can heighten the risk of PTSD and suicide risk in adulthood. Adults can develop disorders, and personality changes, because of events that happened in their childhood. The current research compiled examines “How Childhood Traumatic Experiences Shape Elements of Adult Personality and Mental Health”. This statement raises many important ideas, as there is a stigma that surrounds mental illness. Due to these stigmas, many people who suffer from mental illness are neglected or refuse to seek help. This has created a world that does not understand mental health, nor how much it can affect a person, adult or child. Many adults, as a result of their childhood trauma, experience changes in their adult personality and their mental health. This can happen through: loss of home, divorce, separation from their family during emergency situations, lack of presence of an adult in childhood, and families in poverty. To further explore this research, interviews were conducted with eight different people who experienced different variations of childhood traumas. The second set of interviews were conducted with a psychologist and a kindergarten teacher who didn’t experience childhood traumas themselves, but see it in other individuals on an everyday basis. Childhood trauma is evaluated further, with the review of the movie The Perks of Being a Wallflower which explores the trauma of the main character, Charlie, and how his teenage years are affected due to his childhood experiences. We base much of what we know about PTSD from the experiences of military veterans. This current research has looked at other possible triggers for the development of PTSD stemming from childhood trauma. Thus future research is needed to evaluate if there is a difference in the development of PTSD. The research would take into 3 consideration those who have experienced childhood trauma before entering the military and/or veterans who have experienced childhood traumatic experiences and the correlation with suicide risk and adult mental illness
Automated Cell Division Detection and Classification in Early Mouse and Human Embryos
No full textInfertility affects millions of couples every year. The most effective treatment for infertility is in-vitro fertilization (IVF). Embryo selection, which has become a critical part of IVF treatments, is the process of selecting the most viable embryos to transfer and maximize the chance of pregnancy while minimizing the risks resulting from multiple births. Advancements in time-lapse microscopy have provided a stepping stone for better assessments of embryo quality but have also placed a greater burden on embryologists having to review a steadily growing number of images. Recent developments in artificial intelligence and convolutional neural networks (CNN) have shown great potential in computer-aided analysis of images. In this work, we explore ways to use CNNs to automate the embryo selection. In particular, we focus on predicting the timings of cell divisions in early human embryos, which have been shown to correlate well with pregnancy outcomes. In conclusion, we present a method to aid embryologists with annotating embryos and in a future version we think our method will be a part of a fully automated system for selecting the most viable embryos
Walking Out: Schools, Students, and Civil Disobedience
Get PDFThis Article begins in Part I by reviewing the history and impact of youth civil disobedience and the special issues school walkouts raise. Part II then discusses the legal doctrines that guide school administrators and courts as they aim to strike a suitable balance between free expression and the day-to day operations of a school. Part III analyzes the different approaches school districts have taken, and offers specific advice to school districts dealing with future walkouts. Part IV cautions that the only constitutionally permitted response by school districts is to subject students to the same consequences they would face for not attending class under ordinary circumstances. The Article concludes with reflections on the importance of ensuring that the long tradition of student engagement in progressive social movements is preserved and supported
Improving Software Defect Assignment Accuracy with the LSTM and Rule Engine Model
No full textAfter a software defect is reported with a title and a text description, a competent developer needs to be assigned to fix it. The accuracy of this assignment has big impact on the quality of the resulting software, and the speed of the debugging process. Traditionally this software defect assignment process is conducted by product managers based on his/her knowledge of the software and the developers, which is not very scalable. In the recent years, this defect assignment problem has been formulated as a problem of (1) feature extraction from the defect title and description, and (2) classification of the resulting feature sets to the developers. Machine learning has been used to automate this software defect assignment problem. The research improves the existing approaches in automatic defect assignment by (1) improving the feature extraction by NLP and Vector for Words technology, (2) introducing rule-based engine aka expert system to better character the strength of each developer, instead of the traditional characterizing a developer only by the descriptions of the bugs he/she has resolved; (3) combining the two layers model of our model (Layer 1, NLP and Vector for Words and Layer 2, Long Short-Term Memory and Rule-based Engine). The optimal results are achieved on the CHROME dataset based on our new model of Long Short-Term Memory(LSTM) with Rule-based Engine in comparison with the traditional ML model - Naïve Bayes model. The proposed neural network model extracts text features on its own, considering not only the word order messages that the word bag model ignores, but also the grammatical and semantic characteristics of the text. Rule-based Engine has absorbed developers’ history data, and activity information. The structure of these two layers network model with Rule-based Engine is relatively simple, i.e. the model is parallel structure, ideal for parallel computing, plus a dedicated hardware processing accelerator GPU makes the model not only high accuracy, but also faster. The new approach that we introduced in the research shows that it has better accuracy than traditional Naïve Bayes model and pure LSTM model. The new model can expand and migrate the system to generic bug assignment problems. The model is expandable and migratable
