Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of Capsule Networks Regarding their Potential of Explainability and Image Rankings

Explainable Artificial Intelligence (AI) is a long-ranged goal, which can be approached from different viewpoints. One way is to simplify the complex AI model into an explainable one, another way uses postprocessing to highlight the most important input features for the classification. In this work, we focus on the explanation of image classification using capsule networks with dynamic routing. We train a capsule network on the EMNIST letter dataset and examine the model regarding its explanatory potential. We show that the length of the class specific vectors (squash vectors) of the capsule network can be interpreted as predicted probability and it correlates with the agreement between the decoded image and the original image. We use the predicted probabilities to rank images within one class. By decoding different squash vectors, we visualize the interpretation of the image as the corresponding classes. Eventually, we create a set of modified letters to examine which features contribute to the perception of letters. We conclude that this decoding of squash vectors provides a quantifiable tool towards explainability in AI applications. The explanations are trustworthy through the relation between the capsule network’s prediction and the corresponding visualization.
2D Cairo Pentagonal PdPS: Air‐Stable Anisotropic Ternary Semiconductor with High Optoelectronic Performance

Pentagonal 2D materials as a new member in the 2D material family have attracted increasing attention due to the exotic physical properties originating from the unique Cairo pentagonal tiling topology. Herein, the penta‐PdPS atomic layers as a new air‐stable 2D semiconductor with the unique puckered pentagonal low‐symmetry structure are successfully exfoliated from bulk crystals grown via chemical vapor transport (CVT). Notably, 2D penta‐PdPS exhibits outstanding electronic and optoelectronic performance under 650 nm laser: high electron mobility of ≈208 cm2 V−1 s−1, an ultrahigh on/off ratio of ≈108, a high photoresponsivity of 5.2 × 104 A W−1, a high photogain of 1.0 × 105, an ultrahigh detectivity of 1.0 × 1013 Jones, respectively. Significantly, the exceptional puckered pentagonal atomic structure of 2D PdPS makes it strong in‐plane anisotropy in optical, electronic, and optoelectronic properties, demonstrating a sizeable anisotropic ratio of carrier mobility and photocurrent with the value of up to 3.9 and 2.3, respectively. These excellent properties make 2D Cairo Pentagonal PdPS a potential candidate in nanoelectronics, optoelectronics, polarized‐nanoelectronics, which will significantly promote the development of 2D materials.
Poor Sensorium at the Time of Intubation Predicts Polymicrobial Ventilator Associated Pneumonia

Background Ventilator-associated pneumonia (VAP) is the most common nosocomial infection in the intensive care unit and is associated with a high mortality rate. Aim The study was conducted to estimate the frequency, outcomes, and predictors of polymicrobial VAP. Methods A prospective observational study was conducted in mechanically ventilated adult patients in the medical intensive care unit in a tertiary care hospital in India from July 2016 to July 2018 with a 30-day follow-up period. The patients were grouped into monomicrobial and polymicrobial VAP. We compared the 30-day outcome parameters such as discharge from hospital, in-hospital stay, death, and complications such as catheter associated urinary tract infection (CAUTI), central line associated blood stream infection (CRBSI), bacteremia and collapse of lung. The predictors of polymicrobial VAP were identified by multiple logistic regression. Results Out of 301 patients clinically diagnosed with VAP, 151 patients were excluded, and the remaining 150 developed 186 episodes of VAP during the study period. The incidence of polymicrobial VAP was 62.9%. Out of 150 patients, 51 patients had monomicrobial VAP, and 99 had polymicrobial VAP. On univariate analysis, diabetes mellitus and poor sensorium (Glasgow Coma Scale [GCS] score <8) during endotracheal intubation; 30-day outcome, mean days of mechanical ventilation after VAP diagnosis and days in ICU; and CAUTI were significantly associated with polymicrobial VAP. On multivariable logistic regression, poor sensorium (GCS score <8) at the time of endotracheal intubation was an independent predictor of polymicrobial VAP. Conclusion The incidence of polymicrobial VAP is high in the medical ICU and is associated with increased duration of mechanical ventilation, hospital stay, and incidence of CAUTI. Poor GCS score was the single independent predictor of polymicrobial VAP.
An Analytic Model for Power System Fault Diagnosis Employing Electrical Data

The existing analytic models for power system fault diagnosis generally only employ the state information of protective relays and circuit breakers,and the information redundancy is very limited.As the result,definite diagnosis results may not always be attained for complicated fault scenarios.The development of the phasor measurement unit(PMU) based wide area measurement system(WAMS) has generally made the acquisition of real-time and accurate electrical data possible.Given this background,the existing fault diagnosis analytic model is further developed with the electrical data from WAMS,and can be solved by the well-established genetic algorithm.Firstly,the fault areas are rapidly determined by using the combined data of states of circuit breakers and electrical data.Then,the fault diagnosis is carried out for the identified fault areas using the proposed analytical model.Finally,it is shown by simulation results of a sample system that the developed model is feasible and has good fault-tolerant capability.It can handle complicated fault scenarios with malfunctions of protective relays/circuit breakers as well as distorted/lost alarms.
Toward a New Hybrid Intelligent Sentiment Analysis using CNN- LSTM and Cultural Algorithms

: In this paper, we propose a new sentiment analysis approach based on the combination of deep learning and soft computing techniques. We use the GloVe word embeddings for feature extraction. For sentiment classiﬁcation, we propose to combine CNN and LSTM to decide whether the sentiment among the text is positive or negative. To tune hyperparameters, this classiﬁer is optimized using cultural algorithms.
Considerações Especiais na Prevenção de Doenças Cardiovasculares nas Mulheres

Correspondência: Gláucia Maria Moraes de Oliveira Rua Visconde de Pirajá, 330 Sala 1114. CEP 21941-901, Rio de Janeiro, RJ – Brasil E-mail: glauciamoraesoliveira@gmail.com Palavras-chave Mulheres; Prevenção; Doença Cardiovascular. As doenças cardiovasculares (DCV) são a principal causa de morte e incapacidade no Brasil, em mulheres e homens. De acordo com as estimativas do Estudo GBD 2019, entre as DCV, a doença isquêmica do coração (DIC) foi a primeira causa de morte no Brasil, seguida pelo acidente vascular cerebral (AVC). A DIC foi responsável por 12,03% (II95 10,66%-12,88%) e 12,2% (II95 11,5%-12,77%) dos óbitos e 4,78% (II95 4,08%-5,47%) e 6,48% (II95 5,92%-7,05 %) de anos de vida ajustados por incapacidade (DALYs), em mulheres e homens, respectivamente. Óbitos e DALYs por AVC foram maiores em mulheres do que em homens, 10,39% (II95 9,25-11,11%) e 8,41% (II95 7,84%-8,83%) dos óbitos e 4,62% (II 4,01%-5,18%) e 4,19% de DALYs (3,82%-4,53%), respectivamente.1
A Singlish Supported Post Recommendation Approach for Social Media

Social media is an attractive means of communication which people used to exchange information. Post recommendation eliminates the overflooding of information in social media to the users’ news feed by suggesting the best matching information based on users’ preference that in return increase the usability. Social media users use different languages and their variations where most of the Sri Lankan users are accustomed to use Sinhala and Romanized Sinhala. However, post recommendation approaches used in current social media applications do not cater to code-mixed text. Therefore, this paper proposes a novel post recommendation approach that supports Singlish. The study is separated into two major components as language identification and transliteration, and post recommendation. In this study, script identification was performed using regular expressions while a Naïve Bayes classification model that accomplished 97% of accuracy was employed for language identification of Romanized text. Transliteration of Singlish to Sinhala was conducted using a character level seq2seq BLSTM model with a BLEU score of 0.94. Furthermore, Google translation API and YAKE were used for Sinhala-English translation and keyword extraction respectively. Post recommendation model utilized a combination of rule-based and CF techniques that accomplished the RMSE of 0.2971 and MAE of 0.2304.
Red-Shifted Excitation and Two-Photon Pumping of Biointegrated GaInP/AlGaInP Quantum Well Microlasers

Biointegrated intracellular microlasers have emerged as an attractive and versatile tool in biophotonics. Different inorganic semiconductor materials have been used for the fabrication of such biocompatible microlasers but often operate at visible wavelengths ill-suited for imaging through tissue. Here, we report on whispering gallery mode microdisk lasers made from a range of GaInP/AlGaInP multi-quantum well structures with compositions tailored to red-shifted excitation and emission. The selected semiconductor alloys show minimal toxicity and allow the fabrication of lasers with stable single-mode emission in the NIR (675–720 nm) and sub-pJ thresholds. The microlasers operate in the first therapeutic window under direct excitation by a conventional diode laser and can also be pumped in the second therapeutic window using two-photon excitation at pulse energies compatible with standard multiphoton microscopy. Stable performance is observed under cell culturing conditions for 5 days without any device encapsulation. With their bio-optimized spectral characteristics, low lasing threshold, and compatibility with two-photon pumping, AlGaInP-based microlasers are ideally suited for novel cell tagging and in vivo sensing applications.
Manipulation of mechanically nanopatterned line defect assemblies in plane-parallel nematic liquid crystals

Topological line defects are ubiquitous in nature and appear at all physical scales, including in condensed matter systems, nuclear physics, and cosmology. Particularly useful systems to study line defects are nematic liquid crystals (LCs), where they describe singular or nonsingular frustrations in orientational order and are referred to as disclinations. In nematic LCs, line defects could be relatively simply created, manipulated, and observed. We consider cases where disclinations are stabilized either topologically in plane-parallel confinements or by chirality. In the former case, we report on studies in which defect core transformations are investigated, the intriguing dynamics of strength disclinations in LCs exhibiting negative dielectric anisotropy, and stabilization and manipulation of assemblies of defects. For the case of chiral nematics, we consider nanoparticle-driven stabilization of defect lattices. The resulting line defect assemblies could pave the way to several applications in photonics, sensitive detectors, and information storage devices. These excitations, moreover, have numerous analogs in other branches of physics. Studying their universal properties in nematics could deepen understanding of several phenomena, which are still unresolved at the fundamental level.
Sterling Software: An $8 Billion Success Story in the 1980s and 1990s

Abstract:From 1981 until 1999, while I was a consultant to Sterling Software, Inc., the company grew from a startup that bought four computer software companies for less than US$25 million to an international computer software and services powerhouse. During those 18 years, Sterling Williams, the CEO and driving force behind the company's growth, and Samuel E. "Sam" Wyly, the chairman of the board and its financial mastermind, operated on the principle of "Buy, don't build. " They acquired close to 80 companies, including the hostile takeover of Informatics General in 1985, a company with 10 times its sales at that time. In early 2000, Sterling Software was sold to Computer Associates International and Sterling Commerce was sold to SBC Communications for US$4 billion each. This is my description of one of the most successful and influential computer software and services companies of the 20th century.
Soft Tissue Sarcomas with Special Reference to Molecular Aberration, Chemotherapy, and Recent Advances: A Review Article

Soft tissue sarcomas (STS) are a diverse group of rare solid tumors of mesenchymal cell origin with distinct clinical and pathological features. They account for less than 1% of all adult malignancies and 15% of pediatric neoplasms. They include over hundreds of different histological subtypes. Many of these subtypes can occur at any age and are not confined to a specific site. Each subtype displays variable clinical behavior. Low incidence, variable presentation, behavior, and long-term outcomes further make it challenging to treat. There are multiple ongoing trials that focus on the anatomic site and histologic subtype to tailor the treatment. Further rarity of each histotype is a major barrier to recruit patients to randomized controlled trials. A multidisciplinary approach is mandatory in all cases of soft tissue sarcomas.The purpose of this review is to thoroughly understand the existing literature on history, incidence, epidemiology, etiology, histology, pathogenesis, diagnostic modalities, prognosis, management, and post treatment surveillance of STS. Uterine sarcomas, gastrointestinal stromal tumors (GIST), and pediatric sarcomas are not included here. It briefly highlights various molecular aberrations, changes in staging as per the American Joint Committee on Cancer (AJCC) 8, drugs that are used off-label in specific subtypes of sarcoma along with the recent advances. The classification of STS is undergoing continuous evolution. A wide variety of subtypes can only be diagnosed accurately with sophisticated molecular diagnostic tests and with the involvement of expert geneticists and pathologists to interpret it.There is no clarity on tailoring the treatment of STS to date. There is always a question on how best we can incorporate chemotherapy and radiotherapy along with surgery as a part of multimodality treatment. The heterogeneity of STS has hindered the development of robust, evidence-based treatment strategies, and our therapeutic approach is neither histology-specific nor widely standardized. Increased knowledge about sarcoma biology could help to discover new and more effective treatment strategies and help overcome the therapeutic challenge imposed by this deadly disease. Continued collaboration among various sarcoma centers globally will be of prime importance to optimize STS management. This will allow studies to be both sufficiently large and reasonably focused to generate evidence that is clinically meaningful in specific STS patient populations.
Post-hoc Global Explanation using Hypersphere Sets

We propose a novel global explanation method for a pre-trained machine learning model. Generally, machine learning models behave as a black box. Therefore, developing a tool that reveals a model’s behavior is important. Some studies have addressed this issue by approximating a black-box model with another interpretable model. Although such a model summarizes a complex model, it sometimes provides incorrect explanations because of a gap between the complex model. We define hypersphere sets of two types that respectively approximate a model based on recall and precision metrics. A high-recall set of hyperspheres provides a summary of a black-box model. A high-precision one describes the model’s behavior precisely. We demonstrate from experimentation that the proposed method provides a global explanation for an arbitrary black-box model. Especially, it improves recall and precision metrics better than earlier methods.
Veterans affairs seamless phase II/III randomized trial of standard systemic therapy with or without PET-directed local therapy for oligorecurrent prostate cancer (VA STARPORT).

TPS203 Background: Two diverging paradigms have been studied in recent years to improve the survival of men with recurrent metastatic prostate cancer (PCa). First, multiple recent phase II randomized trials have demonstrated improved long-term progression-free survival (PFS) with metastasis-directed therapy (MDT) in men with oligorecurrent PCa in the absence of systemic therapy. Yet, most patients receiving MDT for oligorecurrent PCa develop progression in new areas, arguing that systemic therapy is needed to treat occult metastases. The second approach that has recently been studied is whether escalating systemic therapy by adding novel androgen receptor axis targeted agents or chemotherapy improves outcomes in men with metastatic PCa. Multiple phase III randomized trials demonstrate that enhancing hormonal therapy with these therapeutic agents improves progression-free survival (PFS) and overall survival. Therefore, these agents have been integrated into today’s standard systemic therapy (SST) for metastatic recurrence, and SST is the current NCCN guidelines standard of care for recurrent metastatic PCa. The primary goal of our study is to determine if adding PET-directed local therapy (PDLT) to SST improves disease control compared to SST alone in Veterans with oligorecurrent PCa. Methods: VA STARPORT is a phase II/III randomized trial open at 16 VA medical centers comparing SST with or without PDLT in Veterans with oligorecurrent PCa. Key eligibility criteria include prior localized PCa with biochemical recurrence after initial curative-intent local therapy and workup including any FDA-approved PCa PET/CT that reveals oligorecurrence in 1-5 metastatic lesions. The primary endpoint is castration-resistant prostate cancer-free survival (CRPC-free survival). Secondary endpoints include radiographic PFS, clinical PFS, freedom from index lesion progression, toxicity, quality of life, and prostate cancer-specific and overall survival. SST is delivered with an intent for indefinite SST using any NCCN guideline-concordant regimen in both arms. PDLT (Arm 2) consists of surgery or radiation to metastases and any present prostate/prostate bed local recurrence. Metastasis-directed radiation can consist of stereotactic body radiotherapy or elective nodal radiotherapy per clinician discretion from dose/fractionation options defined in the protocol. All participants undergo somatic tumor sequencing using the VA National Precision Oncology Program. Germline sequencing and tumor banking in a separate biorepository study is recommended. Assuming a hazard ratio of 0.60 for SST + PDLT vs SST, two-sided alpha = 0.05 and 90% power, a total of 464 participants will be randomized to generate 166 primary events (CRPC-free survival) by the end of the 48-month active study phase. The study began enrollment in August 2021. Clinical trial information: NCT04787744.
Painful Truth: The Need to Re-Center Chronic Pain on the Functional Role of Pain

Abstract Pain is undesirable, whether it is a symptom of mild or severe illness or instead indicates disorder in the nervous system’s ability to perceive and process sensory information. Nonetheless, pain is part of the body’s ability to defend itself and promote its own survival—this is its fundamental evolutionary function. This normal expression of pain is not limited to what is considered useful because it alerts us to the initiation of illness. It also applies to pain that continues when illness or noxious stimuli persist. However, the parameters of what is here termed functional pain are not fully understood and are seldom explicitly the focus of research. This paper posits that failure to appreciate the functional role of pain in research has had significant unintended consequences and may be contributing to inconsistent research findings. To that end, the paper describes the misclassification issue at the core of chronic pain research—whether a given pain reflects functional or pathological processes—and discusses research areas where reconsidering the functional role of pain may lead to advancements.
Comparing RNN and Transformer Context Representations in the Czech Answer Selection Task

Open domain question answering now inevitably builds upon advanced neural models processing large unstructured textual sources serving as a kind of underlying knowledge base. In case of non-mainstream highlyinflected languages, the state-of-the-art approaches lack large training datasets emphasizing the need for other improvement techniques. In this paper, we present detailed evaluation of a new technique employing various context representations in the answer selection task where the best answer sentence from a candidate document is identified as the most relevant to the human entered question. The input data here consists not only of each sentence in isolation but also of its preceding sentence(s) as the context. We compare seven different context representations including direct recurrent network (RNN) embeddings and several BERT-model based sentence embedding vectors. All experiments are evaluated with a new version 3.1 of the Czech question answering benchmark dataset SQAD with possible multiple correct answers as a new feature. The comparison shows that the BERT-based sentence embeddings are able to offer the best context representations reaching the mean average precision results of 83.39% which is a new best score for this dataset.
Late Sodium Current of the Heart: Where Do We Stand and Where Are We Going?

Late sodium current has long been linked to dysrhythmia and contractile malfunction in the heart. Despite the increasing body of accumulating information on the subject, our understanding of its role in normal or pathologic states is not complete. Even though the role of late sodium current in shaping action potential under physiologic circumstances is debated, it’s unquestioned role in arrhythmogenesis keeps it in the focus of research. Transgenic mouse models and isoform-specific pharmacological tools have proved useful in understanding the mechanism of late sodium current in health and disease. This review will outline the mechanism and function of cardiac late sodium current with special focus on the recent advances of the area.
A 0.5-mm2 Solar Cell-Powered Biofuel Cell-Input Biosensing System With LED Driving for Stand-Alone RF-Less Continuous Glucose Monitoring Contact Lens

This letter presents the first solar cell (SC)-powered biofuel cell (BFC)-input biosensing system with pulse interval modulation (PIM) and pulse density modulation (PDM) LED driving capability for continuous glucose monitoring (CGM) contact lenses featuring stand-alone RF-less operation. Power supply from on-lens SCs can eliminate the necessity of wireless power delivery, and LED implementation can eliminate the necessity of wireless communication. By employing the BFC-input approach instead of using a power-hungry potentiostat, powering and sensing components are separated, which reduces the power budget from SCs. The measured power of 28/144 nW at the PIM/PDM mode with a 0.31/0.39-V supply voltage can be managed by the on-lens SCs, enabling a fully stand-alone on-lens operation under office-room ambient light whose typical illumination intensity is 800–1600 lx.