Exploring Networks of Lexical Variation in Russian Sign Language

When describing variation at the lexical level in sign languages, researchers often distinguish between phonological and lexical variants, using the following principle: if two signs differ in only one of the major phonological components (handshape, orientation, movement, location), then they are considered phonological variants, otherwise they are considered separate lexemes. We demonstrate that this principle leads to contradictions in some simple and more complex cases of variation. We argue that it is useful to visualize the relations between variants as graphs, and we describe possible networks of variants that can arise using this visualization tool. We further demonstrate that these scenarios in fact arise in the case of variation in color terms and kinship terms in Russian Sign Language (RSL), using a newly created database of lexical variation in RSL. We show that it is possible to develop a set of formal rules that can help distinguish phonological and lexical variation also in the problematic scenarios. However, we argue that it might be a mistake to dismiss the actual patterns of variant relations in order to arrive at the binary lexical vs. phonological variant opposition.

Combination of waveforms in modern spinal cord stimulation

Background After the surge of burst stimulation, different waveforms were developed to optimize results in spinal cord stimulation. Studies have shown higher responder rates for multiwave therapy, but since the launch of such multiwave systems, little is known about the patients’ preference regarding waveforms in the long-term follow-up. No study connected particular waveforms to specific pain etiologies or required stimulation parameters so far. Method Thirty-four patients with refractory chronic neuropathic pain were treated with spinal cord stimulation systems providing multiwave therapy between September 2018 and October 2019. Patients with a follow-up of at least 6 months were selected; 10 subjects were excluded due to revision surgery, infection, and loss to follow-up. Data regarding pain intensity and preferred waveform for the trial, the implantation, 3-month and 6-month follow-up were recorded. Results During the trial phase, 10 patients (43.5%) achieved significant pain relief using tonic stimulation, 5 using burst (21.7%), 3 using microburst (13.0%), and 4 using a combination of tonic and microburst (17.4%). One single patient preferred Contour stimulation during the trial. After 3 months, 6 patients preferred microburst (25%), 6 preferred tonic (25%), 5 used a combination of tonic and microburst (20.8%), and 5 patients used burst (20.8%). After 6 months, similar results were obtained. Contour and Whisper were used in complex cases failing to other waveforms. Conclusions Tonic stimulation, isolated or in combination, remains an important component in spinal cord stimulation, being used by almost half of the patients. Over time, the usage of microburst increased considerably. Whisper and Contour, although battery-consuming, are good salvage options in complex cases.

Asymptotics solutions of a singularly perturbed integro-differential fractional order derivative equation with rapidly oscillating coefficients

In this paper, the regularization method of S.A.Lomov is generalized to the singularly perturbed integrodifferential fractional-order derivative equation with rapidly oscillating coefficients. The main goal of the work is to reveal the influence of the oscillating components on the structure of the asymptotics of the solution to this problem. The case of the absence of resonance is considered, i.e. the case when an integer linear combination of a rapidly oscillating inhomogeneity does not coincide with a point in the spectrum of the limiting operator at all points of the considered time interval. The case of coincidence of the frequency of a rapidly oscillating inhomogeneity with a point in the spectrum of the limiting operator is called the resonance case. This case is supposed to be studied in our subsequent works. More complex cases of resonance (for example, point resonance) require more careful analysis and are not considered in this work.

Integrative Psychotherapy With Physicians In the Trenches: Convergence of Cognitive, Existential, and Psychodynamic Processes

In this article, I present insights gleaned from over a decade of working in therapy with physicians in the trenches who practice at general hospitals located in an area afflicted by the community and political violence, and recently, by the COVID-19 pandemic. Psychotherapy with these physicians requires an integrative psychotherapeutic approach that heeds their changing needs. Espousing cognitive-existential psychodynamics (CEP), a theory-based psychotherapeutic perspective developed for complex cases, I show how cognitive, existential, and psychodynamic processes strongly converge during the treatment of physicians in the trenches. Such convergence is manifested in issues of mental representations (of death, medicine, and the hospital) and choice/meaning.

Deep Learning, a Not so Magical Problem Solver: A Case Study with Predicting the Complexity of Breast Cancer Cases

Using guideline-based clinical decision support systems (CDSSs) has improved clinical practice, especially during multidisciplinary tumour boards (MTBs) in cancer patient management. However, MTBs have been reported to be overcrowded, with limited time to discuss all cases. Complex breast cancer cases that need further MTB discussions should have priority in the organization of MTBs. In order to optimize MTB workflow, we attempted to predict complex cases defined as non-compliant cases despite the use of the decision support system OncoDoc. After previously obtaining insufficient performance with machine learning algorithms, we tested Multi Layer Perceptron for classification, compared various samplers to compensate data imbalance combined with cross- validation, and optimized all models with hyperparameter tuning and feature selection with no improvement and lacklustre results (F1-score: 31.4%).

Are Semantic Annotators Able to Extract Relevant Complexity-Related Concepts from Clinical Notes?

Clinical decision support systems (CDSSs) implementing cancer clinical practice guidelines (CPGs) have the potential to improve the compliance of decisions made by multidisciplinary tumor boards (MTB) with CPGs. However, guideline-based CDSSs do not cover complex cases and need time for discussion. We propose to learn how to predict complex cancer cases prior to MTBs from breast cancer patient summaries (BCPSs) resuming clinical notes. BCPSs being unstructured natural language textual documents, we implemented four semantic annotators (ECMT, SIFR, cTAKES, and MetaMap) to assess whether complexity-related concepts could be extracted from clinical notes. On a sample of 24 BCPSs covering 35 complexity reasons, ECMT and MetaMap were the most efficient systems with a performance rate of 60% (21/35) and 49% (17/35), respectively. When using the four annotators in sequence, 69% of complexity reasons were extracted (24/35 reasons).

Intrathoracic transposition of the omentum

Complex chest and lung infections with bronchial fistula are life-threatening situations with a mortality rate of up to 20%. If medical treatment fails, these patients require aggressive procedures to heal. Transposition of the omentum is a valuable, nonstandard option in these complex cases with aggressive infection involving the pleural space, with or without a bronchial fistula, when medical treatment is unsuccessful. We present a 29-year-old female patient diagnosed with primary immunodeficiency and invasive fungal infection with involvement of the left upper lobe and mediastinal and vertebral bodies treated with a lobectomy and intrathoracic transposition of the omentum.

The demands of comorbidity: Implications for the explanation and classification of mental disorder

<p>A central goal of psychiatric classification is to assist in the assessment and treatment of those who experience mental disorder. This challenge takes on greater significance in complex cases, especially given the high prevalence of psychiatric comorbidity. High rates of comorbidity also challenge the validity of current psychiatric nosology. Etiological classification has been promoted as an alternative to improve the state of psychiatric diagnosis. However, comorbidity makes specific conceptual, explanatory and methodological demands of any such classification strategy. In this thesis, a demand for coherent and integrative explanation of comorbidity acts as a standard by which to assess the strength of different causal models of mental disorder and their resultant concepts. Integrative pluralism is presented as an epistemological framework well-suited to the complexity of this scientific challenge.</p>

The demands of comorbidity: Implications for the explanation and classification of mental disorder

<p>A central goal of psychiatric classification is to assist in the assessment and treatment of those who experience mental disorder. This challenge takes on greater significance in complex cases, especially given the high prevalence of psychiatric comorbidity. High rates of comorbidity also challenge the validity of current psychiatric nosology. Etiological classification has been promoted as an alternative to improve the state of psychiatric diagnosis. However, comorbidity makes specific conceptual, explanatory and methodological demands of any such classification strategy. In this thesis, a demand for coherent and integrative explanation of comorbidity acts as a standard by which to assess the strength of different causal models of mental disorder and their resultant concepts. Integrative pluralism is presented as an epistemological framework well-suited to the complexity of this scientific challenge.</p>