A Lightweight Learning Method for Stochastic Configuration Networks Using Non-Inverse Solution

Stochastic configuration networks (SCNs) face time-consuming issues when dealing with complex modeling tasks that usually require a mass of hidden nodes to build an enormous network. An important reason behind this issue is that SCNs always employ the Moore–Penrose generalized inverse method with high complexity to update the output weights in each increment. To tackle this problem, this paper proposes a lightweight SCNs, called L-SCNs. First, to avoid using the Moore–Penrose generalized inverse method, a positive definite equation is proposed to replace the over-determined equation, and the consistency of their solution is proved. Then, to reduce the complexity of calculating the output weight, a low complexity method based on Cholesky decomposition is proposed. The experimental results based on both the benchmark function approximation and real-world problems including regression and classification applications show that L-SCNs are sufficiently lightweight.

Development of pharmaceutical care tools for people living with HIV treated at a medium- and high-complexity hospital

The exposure of people living with HIV (PLHIV) to antiretrovirals (ARV) can cause significant adverse effects, contributing to their low adherence to treatment. The pharmacist can contribute to the optimization of PLHIV drug therapy through pharmacotherapeutic monitoring, favoring adherence to ARV therapy and, consequently, suppression of the viral load. The objective of the present study was to develop a pharmacotherapeutic monitoring routine for PLHIV in outpatient follow-up at a medium- and high-complexity hospital in the city of Rio de Janeiro. This is an experimental development project that consists of using knowledge from practical experience and research from the specialized literature to subsidize the structuring of a new service to support PLHIV. The work was divided into three parts: development of the necessary instruments for pharmaceutical care, elaboration of standard operating procedures (SOPs) for patient care, and testing of routines and work tools. The educational leaflets for patients and information boards were developed through a literature search, whereas the pharmaceutical documentation instruments and SOP were developed through adaptations of the Dáder Method. All work instruments were subjected to a test to evaluate the need for changes to improve the service.

ROL DEL PERSONAL DE ENFERMERIA EN LOS TRATAMIENTOS DE REPRODUCCIÓN ASISTIDA HUMANA

Existen una gran cantidad de parejas infértiles que se someten actualmente a algún tratamiento de reproducción asistida de baja complejidad (Inseminación Artificial), o de alta complejidad (Fecundación In Vitro, Inyección Intracitoplasmática de espermatozoides (ICSI en sus siglas en inglés) y para la realización de los mismo se necesita de una correcta coordinación entre todo el personal médico, de laboratorio y de enfermería, donde este último, en sus distintos roles, será el encargado de la preparación de la paciente para que esta pueda afrontar en las mejores condiciones posibles el tratamiento, lo que a su vez facilitará un mejor entendimiento y cumplimiento de las indicaciones, una menor tasa de abandono de tratamiento y mejores resultados en la consecución de un embarazo. El objetivo principal es dar a conocer los roles que cumple actualmente el personal de enfermería como son el asistencial tanto en el consultorio como en el quirófano, brindar apoyo emocional y educativo a las pacientes y participar en proyectos de investigación institucionales. Palabras clave: enfermería, cuidados de enfermería, infertilidad, inseminación, fertilización in vitro. ABSTRACT There are a large number of infertile couples currently undergoing assisted reproduction treatment of low complexity (Artificial Insemination), or high complexity (In Vitro Fertilization, Intracytoplasmic Sperm Injection (ICSI)) and for the realization of the same requires proper coordination between all medical personnel, The latter, in their different roles, will be in charge of preparing the patient so that she can face the treatment in the best possible conditions, which in turn will facilitate a better understanding and compliance with the indications, a lower rate of abandonment of treatment and better results in achieving a pregnancy. The main objective is to raise awareness of the roles currently performed by the nursing staff, such as assistance both in the office and in the operating room, to provide emotional and educational support to patients and to participate in institutional research projects. Keywords: nursing, nursing care, infertility, insemination, in vitro fertilization

Controllable Fused Semantic Segmentation with Adaptive Edge Loss for Remote Sensing Parsing

High-resolution remote sensing images have been put into the application in remote sensing parsing. General remote sensing parsing methods based on semantic segmentation still have limitations, which include frequent neglect of tiny objects, high complexity in image understanding and sample imbalance. Therefore, a controllable fusion module (CFM) is proposed to alleviate the problem of implicit understanding of complicated categories. Moreover, an adaptive edge loss function (AEL) was proposed to alleviate the problem of the recognition of tiny objects and sample imbalance. Our proposed method combining CFM and AEL optimizes edge features and body features in a coupled mode. The verification on Potsdam and Vaihingen datasets shows that our method can significantly improve the parsing effect of satellite images in terms of mIoU and MPA.

Role of Clostridium Perfringens in Neonatal Necrotizing Enterocolitis and the Utility of Anaerobic Blood Cultures

Introduction: Clostridium perfringens is a gram-positive anaerobic bacillus that causes various clinical diseases, including necrotizing enterocolitis in newborns. The progression could be fulminant and lethal. Presentation of the cases: We report 3 cases of necrotizing enterocolitis due to C. perfringens from 2 high-complexity public centers in Chile. Conclusion: Strong clinical suspicion combined with early microbiological identification may modify patient evolution. Anaerobic blood cultures have become a fundamental diagnostic method; therefore, having this tool in neonatal units would be useful

Profiling Cancer Cells by Cell-SELEX: Use of Aptamers for Discovery of Actionable Biomarkers and Therapeutic Applications Thereof

The identification of tumor cell-specific surface markers is a key step towards personalized cancer medicine, allowing early assessment and accurate diagnosis, and development of efficacious targeted therapies. Despite significant efforts, currently the spectrum of cell membrane targets associated with approved treatments is still limited, causing an inability to treat a large number of cancers. What mainly limits the number of ideal clinical biomarkers is the high complexity and heterogeneity of several human cancers and still-limited methods for molecular profiling of specific cancer types. Thanks to the simplicity, versatility and effectiveness of its application, cell-SELEX (Systematic Evolution of Ligands by Exponential Enrichment) technology is a valid complement to the present strategies for biomarkers’ discovery. We and other researchers worldwide are attempting to apply cell-SELEX to the generation of oligonucleotide aptamers as tools for both identifying new cancer biomarkers and targeting them by innovative therapeutic strategies. In this review, we discuss the potential of cell-SELEX for increasing the currently limited repertoire of actionable cancer cell-surface biomarkers and focus on the use of the selected aptamers as components of innovative conjugates and nano-formulations for cancer therapy.

Utility of Machine Learning Approach with Neuropsychological Tests in Predicting Functional Impairment of Alzheimer’s Disease

Background: In assessing the levels of clinical impairment in dementia, a summary index of neuropsychological batteries has been widely used in describing the overall functional status. Objective: It remains unexamined how complex patterns of the test performances can be utilized to have specific predictive meaning when the machine learning approach is applied. Methods: In this study, the neuropsychological battery (CERAD-K) and assessment of functioning level (Clinical Dementia Rating scale and Instrumental Activities of Daily Living) were administered to 2,642 older adults with no impairment (n = 285), mild cognitive impairment (n = 1,057), and Alzheimer’s disease (n = 1,300). Predictive accuracy on functional impairment level with the linear models of the single total score or multiple subtest scores (Model 1, 2) and support vector regression with low or high complexity (Model 3, 4) were compared across different sample sizes. Results: The linear models (Model 1, 2) showed superior performance with relatively smaller sample size, while nonlinear models with low and high complexity (Model 3, 4) showed an improved accuracy with a larger dataset. Unlike linear models, the nonlinear models showed a gradual increase in the predictive accuracy with a larger sample size (n > 500), especially when the model training is allowed to exploit complex patterns of the dataset. Conclusion: Our finding suggests that nonlinear models can predict levels of functional impairment with a sufficient dataset. The summary index of the neuropsychological battery can be augmented for specific purposes, especially in estimating the functional status of dementia.

Social and Educational Context of the Poverty of People with Disabilities in Poland

The article points out the high complexity and multidimensionality of the hot social issue of poverty as well as the related unemployment, and the precariousness of people with disabilities in Poland. The author notes that despite the currently promoted pro-inclusion activities and solutions for their benefit in connection with the implementation the assumptions of the Convention on the Rights of Persons with Disabilities in Poland, with insufficient support, these problems may multiply and aggravate the disability and special needs of these people. People with disabilities still too often live in conditions of poverty that have a negative impact on their development and functioning in all spheres or areas of social life, as well as in the open labour market. In the process of compensating for the shortcomings related to having been brought up in a poor family, education has a significant role to play. Therefore, the author stresses its significant importance for the process of equalizing educational opportunities for children, as well as for the weaknesses noticed in its space, which hinder this process. The author pays equal attention to the threat of these people with unemployment and precariousness, which often destabilize their lives and hinder inclusion in the local and wider community.

From LTL to unambiguous Büchi automata via disambiguation of alternating automata

Due to the high complexity of translating linear temporal logic (LTL) to deterministic automata, several forms of “restricted” nondeterminism have been considered with the aim of maintaining some of the benefits of deterministic automata, while at the same time allowing more efficient translations from LTL. One of them is the notion of unambiguity. This paper proposes a new algorithm for the generation of unambiguous Büchi automata (UBA) from LTL formulas. Unlike other approaches it is based on a known translation from very weak alternating automata (VWAA) to NBA. A notion of unambiguity for alternating automata is introduced and it is shown that the VWAA-to-NBA translation preserves unambiguity. Checking unambiguity of VWAA is determined to be PSPACE-complete, both for the explicit and symbolic encodings of alternating automata. The core of the LTL-to-UBA translation is an iterative disambiguation procedure for VWAA. Several heuristics are introduced for different stages of the procedure. We report on an implementation of our approach in the tool and compare it to an existing LTL-to-UBA implementation in the tool set. Our experiments cover model checking of Markov chains, which is an important application of UBA.