Context-Aware Personalized Activity Modeling in Concurrent Environment

Activity recognition, having endemic impact on smart homes, faces one of the biggest challenges in learning a personalized activity model completely by using a generic model especially for parallel and interleaved activities. Furthermore, inhabitant’s mistaken object interaction may entail in another spurious activity at smart homes. Identifying and removing such spurious activities is another challenging task. Knowledge driven techniques used for recognizing activity models are static in nature, lack contextual representation and may not comprehend spurious actions for parallel/interleaved activities. In this paper, a novel approach for completing the personalized model specific to each inhabitant at smart homes using generic model (incomplete) is presented that can recognize the sequential, parallel, and interleaved activities dynamically while removing the spurious activities semantically. A comprehensive set of experiments and results based upon number of correct (true positivity) or incorrect (false negativity) recognition of activities assert effectiveness of presented approach within a smart hom

Carcinoma En Cuirasse: A Rare but Striking Cutaneous Manifestation of Metastatic Breast Cancer

Carcinoma en cuirasse is a rare cutaneous metastatic presentation of breast cancer with a poor prognosis. We report a female in her 70s with a prior history of left breast ductal carcinoma in situ status post-radiation and lumpectomy who presented with skin thickening of the left breast and a few solid masses in bilateral breasts. Biopsy showed invasive ductal carcinoma of the left breast (estrogen receptor [ER]/progesterone receptor positive [PR], human epidermal growth factor receptor-2 [HER2] negative) and ductal carcinoma in situ of the right breast (ER/PR positive). She underwent a right breast lumpectomy; however, the left breast mastectomy was aborted due to the worsening of her skin findings on preoperative examination. A skin biopsy revealed poorly differentiated invasive ductal carcinoma. She was diagnosed with stage 4 breast cancer, specifically carcinoma en cuirasse. Systemic treatment was initiated, followed by a left breast mastectomy. A surgical biopsy was HER2-positive, and therefore anti-HER2 therapy was given. She remains on maintenance therapy with an excellent response at present.Any unexplained skin findings in breast cancer patients should prompt consideration of carcinoma en cuirasse. With ongoing treatment advances, many newer therapy options are available for metastatic breast cancer. Based on our case, we think that patients with this disease can have better outcomes

Driven Diffusive Systems: How Steady States Depend on Dynamics

In contrast to equilibrium systems, non-equilibrium steady states depend explicitly on the underlying dynamics. Using Monte Carlo simulations with Metropolis, Glauber and heat bath rates, we illustrate this expectation for an Ising lattice gas, driven far from equilibrium by an `electric' field. While heat bath and Glauber rates generate essentially identical data for structure factors and two-point correlations, Metropolis rates give noticeably weaker correlations, as if the `effective' temperature were higher in the latter case. We also measure energy histograms and define a simple ratio which is exactly known and closely related to the Boltzmann factor for the equilibrium case. For the driven system, the ratio probes a thermodynamic derivative which is found to be dependent on dynamics

Clinical, Radiological, and Molecular Findings of Acute Encephalitis in a COVID-19 Patient: A Rare Case Report.

We report a case of encephalitis in a young male patient with severe coronavirus disease 2019 (COVID-19) who initially presented with typical symptoms of fever, dry cough, and shortness of breath but later on developed acute respiratory distress syndrome and required mechanical ventilation. Two days post-extubation, the patient developed new-onset generalized tonic-clonic seizures and confusion. MRI of the brain was done and it showed an abnormal signal in the bilateral medial cortical frontal region. His cerebral spinal fluid (CSF) analysis revealed a characteristic picture of a viral infection with a high white blood cell count and normal glucose and protein levels. After ruling out all common causes of viral encephalitis such as herpes simplex virus (HSV) and based on the review of available literature regarding the neurological manifestations of COVID-19, this case was labeled as acute viral encephalitis secondary to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection

Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field

Surgical skill assessment is important for surgery training and quality control. Prior works on this task largely focus on basic surgical tasks such as suturing and knot tying performed in simulation settings. In contrast, surgical skill assessment is studied in this paper on a real clinical dataset, which consists of fifty-seven in-vivo laparoscopic surgeries and corresponding skill scores annotated by six surgeons. From analyses on this dataset, the clearness of operating field (COF) is identified as a good proxy for overall surgical skills, given its strong correlation with overall skills and high inter-annotator consistency. Then an objective and automated framework based on neural network is proposed to predict surgical skills through the proxy of COF. The neural network is jointly trained with a supervised regression loss and an unsupervised rank loss. In experiments, the proposed method achieves 0.55 Spearman's correlation with the ground truth of overall technical skill, which is even comparable with the human performance of junior surgeons.Comment: MICCAI 201

Context-Aware Personalized Activity Modeling in Concurrent Environment

Activity recognition, having endemic impact on smart homes, faces one of the biggest challenges in learning a personalized activity model completely by using a generic model especially for parallel and interleaved activities. Furthermore, inhabitant’s mistaken object interaction may entail in another spurious activity at smart homes. Identifying and removing such spurious activities is another challenging task. Knowledge driven techniques used for recognizing activity models are static in nature, lack contextual representation and may not comprehend spurious actions for parallel/interleaved activities. In this paper, a novel approach for completing the personalized model specific to each inhabitant at smart homes using generic model (incomplete) is presented that can recognize the sequential, parallel, and interleaved activities dynamically while removing the spurious activities semantically. A comprehensive set of experiments and results based upon number of correct (true positivity) or incorrect (false negativity) recognition of activities assert effectiveness of presented approach within a smart hom

Entropy production and fluctuation relations for a KPZ interface

We study entropy production and fluctuation relations in the restricted solid-on-solid growth model, which is a microscopic realization of the KPZ equation. Solving the one dimensional model exactly on a particular line of the phase diagram we demonstrate that entropy production quantifies the distance from equilibrium. Moreover, as an example of a physically relevant current different from the entropy, we study the symmetry of the large deviation function associated with the interface height. In a special case of a system of length L=4 we find that the probability distribution of the variation of height has a symmetric large deviation function, displaying a symmetry different from the Gallavotti-Cohen symmetry.Comment: 21 pages, 5 figure

Locked-in Syndrome in a Young Patient Due to SARS-CoV-2: A Case Report

© Copyright © 2020 Sattar, Iqbal, Haider, Zia, Niazi, Hanif, Ali and Khan. Coronavirus disease 2019 (COVID-19), apart from commonly involving the respiratory system, has its impact on the central nervous system, with a wide spectrum of clinical presentations ranging from headaches to ischemic strokes. The ongoing research regarding this novel disease has found that there is a very high prevalence of thrombotic episodes especially in critically ill patients when compared to severe presentation of other viral illnesses. This COVID-19-associated coagulopathy has a very complex etiology with the ability to form thrombus in arteries, veins, and microvasculatures of different organs. We present a unique case of a young woman with underlying COVID-19 who unfortunately developed locked-in syndrome due to bilateral pontine infarction during the course of her illness

Novel biodegradable poly(gamma-glutamic acid)–amphotericin B complexes show promise as improved amphotericin B formulations

Commercially available amphotericin B (AmB) formulations are limited by cytotoxicities, lower efficacies, shelf-life related issues or high production costs. AmB complexes based on poly(gamma-glutamic acid) (PGGA) have been prepared and evaluated for their efficacies against AmB-deoxycholate (Fungizone®) and liposomal AmB (AmBisome®). Physical characterizations showed that AmB/PGGA complexes are nanoscopic (20-40 nm) with a negative zeta potential (−51.0 mV), water-soluble, stable in solution (up to 4 weeks, at 4 °C and 25 °C), and have a theoretical drug loading (up to 76.9%). In vitro, AmB/PGGA complexes exhibited an improved and comparable cytotoxicity profile as compared with Fungizone® and AmBisome® respectively, with respect to hemolytic activity and up-regulation of cytokine productions (TNF-α and IL-1ß). AmB/PGGA complexes were significantly more efficacious in vivo than both Fungizone® and AmBisome® in experimental murine candidiasis. These results provide strong evidence that AmB/PGGA complexes have a better efficacy and safety profile than the currently approved AmB products