BACKGROUND: The immense comorbidity among disorders could be ascribed to common trans-diagnostic processes. The term trans-diagnostic has been of interest in both pathology and psychology. Trans-diagnostic treatments were created as opposed to treatments based on single-diagnosis treatments. It addresses the common underlying mechanisms in a range of comorbid disorders. Trans-diagnostic treatment is one of the new psychological treatments, and its efficacy has been proven on many psychological variables. The main focus of the current study is on designing unified trans-diagnostic interventions and their efficacy on the shared mechanisms of comorbid obsessive personality disorder with anxiety, depression, and obsessive-compulsive disorder.
METHODS: the sequential transformative strategy has two stages; qualitative and quantitative. In The first and qualitative section of the research, explanatory research will be carried out to investigate the trans-diagnostic intervention using a systematic review. To validate the trans-diagnostic intervention, and simultaneously with the trans-diagnostic intervention, a questionnaire has been prepared and given to 10 psychology experts and professionals in the treatment field concerning content validity by evaluators.
CONCLUSIONS: Designing unified trans-diagnosis interventions and their efficacy on the common mechanisms of comorbid obsessive personality disorder with anxiety, depression, and obsessive-compulsive disorder is an effective treatment method for helping those suffering from a personality disorder. Clinical psychologists, psychology experts, psychiatrists, and mental health experts are all the immediate beneficiaries of this study. Moreover, clients could benefit from this intervention with less money and time.

Protein secondary structure prediction (PSSP) is an important and challenging task in protein bioinformatics. Protein secondary structures (SSs) are categorized in regular and irregular structure classes. Regular SSs, representing nearly 50% of amino acids consist of helices and sheets, whereas the remaining amino acids represent irregular SSs. [Formula: see text]-turns and [Formula: see text]-turns are the most abundant irregular SSs present in proteins. Existing methods are well developed for separate prediction of regular and irregular SSs. However, for more comprehensive PSSP, it is essential to develop a uniform model to predict all types of SSs simultaneously. In this work, using a novel dataset comprising dictionary of secondary structure of protein (DSSP)-based SSs and PROMOTIF-based [Formula: see text]-turns and [Formula: see text]-turns, we propose a unified deep learning model consisting of convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) for simultaneous prediction of regular and irregular SSs. To the best of our knowledge, this is the first study in PSSP covering both regular and irregular structures. The protein sequences in our constructed datasets, RiR6069 and RiR513, have been borrowed from benchmark CB6133 and CB513 datasets, respectively. The results are indicative of increased PSSP accuracy.

This paper argues that there are reasons to believe that there is no single concept or category which demarcates all individuals who have a disability from those individuals who do not. The paper begins by describing that I call \'a Unified Concept View of Disability\' and the role that such a view plays in debates about the nature of disability. After considering reasons to think that our concept of disability is not unified in the way that the Unified Concept View assumes, I outline what a non-unified approach to disability might look like. The paper concludes by considering implications of rejecting the Unified Concept View of disability.

In this paper, we present a high-speed, unified elliptic curve cryptography (ECC) processor for arbitrary Weierstrass curves over GF(p), which to the best of our knowledge, outperforms other similar works in terms of execution time. Our approach employs the combination of the schoolbook long and Karatsuba multiplication algorithm for the elliptic curve point multiplication (ECPM) to achieve better parallelization while retaining low complexity. In the hardware implementation, the substantial gain in speed is also contributed by our n-bit pipelined Montgomery Modular Multiplier (pMMM), which is constructed from our n-bit pipelined multiplier-accumulators that utilizes digital signal processor (DSP) primitives as digit multipliers. Additionally, we also introduce our unified, pipelined modular adder/subtractor (pMAS) for the underlying field arithmetic, and leverage a more efficient yet compact scheduling of the Montgomery ladder algorithm. The implementation for 256-bit modulus size on the 7-series FPGA: Virtex-7, Kintex-7, and XC7Z020 yields 0.139, 0.138, and 0.206 ms of execution time, respectively. Furthermore, since our pMMM module is generic for any curve in Weierstrass form, we support multi-curve parameters, resulting in a unified ECC architecture. Lastly, our method also works in constant time, making it suitable for applications requiring high speed and SCA-resistant characteristics.

BACKGROUND: The Orthopaedic Trauma Association (OTA) classification scheme for open fractures has improved precision, validity and reliability over the modified Gustilo classification system. However, it needs to be modified into a simple and practical classification system to gain widespread acceptance and application.
METHODS: We devised a new \"unified\" classification of open fractures based on the Gustilo and OTA classification systems. The new classification was tested for interobserver reliability on five different fractures classified by 15 surgeons each using the Krippendorff\'s alpha. Preference of surgeons for the Gustilo, OTA and unified classifications was assessed.
RESULTS: The new classification showed excellent interobserver reliability (α = 0.93). A significantly higher number of surgeons expressed preference for the new over the Gustilo and OTA classifications for routine clinical use.
CONCLUSIONS: The new \"unified\" classification of open fractures has good validity, reliability and acceptability, and has the potential to replace all other existing classification systems.

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Mental health professionals have long been concerned with describing and proscribing a structure around the myriad variations of psychological and emotional distress that are deemed to be disordered. This has frequently been characterized as a conflict between so-called \"lumpers\" and \"splitters\"-those who advocate broad categorizations based on overarching commonalities versus those who endeavor toward a highly refined structure emphasizing unique characteristics. Many would argue that with the era of the modern Diagnostic and Statistical Manual of Mental Disorders (DSM-III to DSM-5), a splitting ideology has been dominant despite re-emerging concerns that some groups of diagnoses, particularly disorders of anxiety and other emotions, may be more similar than different. As a result of such concerns, transdiagnostic or unified models of psychopathology have burgeoned. In this review, we describe the work of Barlow, Allen, and Choate (2004), whose invited paper \"Toward a Unified Treatment for Emotional Disorders\" reignited transdiagnostic perspectives of emotional disorders. We provide an update on the scientific models and evidence-based treatments that have followed in the wake of this 2004 publication, including key areas for future study in the advancement of transdiagnostic and unified treatment of emotional disorders.

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