A comparison of four data selection methods for artificial neural networks and support vector machines

The performance of data-driven models such as Artificial Neural Networks and Support Vector Machines relies to a good extent on selecting proper data throughout the design phase. This paper addresses a comparison of four unsupervised data selection methods including random, convex hull based, entropy based and a hybrid data selection method. These methods were evaluated on eight benchmarks in classification and regression problems. For classification, Support Vector Machines were used, while for the regression problems, Multi-Layer Perceptrons were employed. Additionally, for each problem type, a non-dominated set of Radial Basis Functions Neural Networks were designed, benefiting from a Multi Objective Genetic Algorithm. The simulation results showed that the convex hull based method and the hybrid method involving convex hull and entropy, obtain better performance than the other methods, and that MOGA designed RBFNNs always perform better than the other models. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.FCT through IDMEC, under LAETA grant [UID/EMS/50022/2013]info:eu-repo/semantics/publishedVersio

The evolution of food security: where are we now, where should we go next?

Food security is one of the most challenging topics globally; however, the concept of food security has taken on additional dimensions that are general and are less detailed. This study aims to identify the intellectual structure of food security research and the changes in this structure. This paper analyzed 3169 documents from the Web of Science database through a bibliometric review. A review of the published documents shows an increasing trend over the past 46 years. In accordance with co-occurrence analysis, 125 keywords were grouped into five clusters: food security and sustainable development; food security and socioeconomic factors; food security policy and governance; coping strategies for poverty, inequality, and hunger; and modern food security management. This study identifies four streams within food security research: sustainability and environmental, socioeconomic, cultural, and political factors. The paper concludes that even though food security might investigate many significant areas, other new dimensions should still be considered. Further gaps in the literature emerge that present avenues for future research directions. Reviewing indicators and techniques of food security assessment and identifying high-risk groups should be a priority

STUDYING THE EFFECT OF CATIONIC STARCH- ANIONIC NANOSILICA SYSTEM ON RETENTION AND DRAINAGE

Nanoparticles are widely used in the papermaking industry as retention/ drainage aids, usually in conjunction with a high mass cationic polyelectrolyte such as cationic starch. However, little convincing knowledge of their role and mechanism in the wet-end system is yet found. This work focused on the role of nanosilica on papermaking wet end system in response to some processing parameters (drainage, retention, and electrostatic force of the whole system). The observations indicated that the nanosilica performance is defined by interactions of nanosilica with the complex aqueous environment of wet end system. The interaction mechanism seems to rely on introduction of nanoparticles into a cationic starch-fines-fibers network, converting the fiber mat on the forming wire into a porous structure that is responsive to retention and drainage

The first case series of malaria overlapped with COVID-19 in Iran

Introduction: Although indigenous malaria cases have dramatically declined over the past decades, the COVID pandemic has continued to affect the programs designed to combat malaria, particularly in those countries where hydroxychloroquine and chloroquine have been used as medications for treating COVID. Two immigrants entered Iran illegally from neighboring countries (i.e., Afghanistan and Pakistan). This study mainly aimed to assess the effects of coronavirus disease (COVID-19) on these cases from all aspects (i.e., case-finding, diagnosis, and treatment). Case Presentation: Both cases presented with common symptoms such as fever and shaking chills. In addition, they had no sign of COVID-19, and their oxygen level and CT images were normal in some cases, but they were mistakenly treated as COVID-19 patients long after the onset of malaria symptoms. One of the suspected coronavirus cases was given chloroquine on a voluntary basis for one day, which may have been responsible for the possible relapse in vivax or resistance of plasmodium vivax to chloroquine and the recurrence of parasitemia in falciparum. Conclusions: The active case detection of malaria was affected by the COVID-19 pandemic. Case finding was dramatically decreased with the onset of coronavirus, thereby causing a spurt in malaria incidence. Moreover, the malaria treatment strategy was negatively affected by the misdiagnosis of COVID-19

PVM-based intelligent predictive control of HVAC systems

This paper describes the application of a complete MBPC solution for existing HVAC systems, with a focus on the implementation of the objective function employed. Real-time results obtained with this solution, in terms of economical savings and thermal comfort, are compared with standard, temperature regulated control.(1) (C) 2016, IFAC (International Federation of Antomatic Control) Hosting by Elsevier Ltd. All rights reserved

Early maladaptive schemas and suicidal risk in inpatients with bipolar disorder

The present study aimed to assess the associations of early maladaptive schemas (EMSs) and clinical factors (hypomanic/manic and depressive symptoms) with suicidal risk (current suicidal ideation and lifetime suicide attempts) in inpatients with bipolar disorder (BD). One hundred inpatients with BD completed the Young Schema Questionnaire-Short Form (YSQ-SF), the Bipolar Depression Rating Scale (BDRS), the Young Mania Rating Scale (YMRS), and the Beck Scale for Suicide Ideation (BSSI). 59 of patients had lifetime suicide attempts and 59 showed high suicidal risk (BSSI>/=6). BD patients with lifetime suicide attempts had higher scores on the entitlement and social isolation schemas, depression, and hypomanic/manic symptoms than those without such attempts. Patients with high suicidal risk had higher levels of depressive and hypomanic/manic symptoms as well as some EMSs than those without high suicidal risk. Logistic regression analyses revealed that hypomanic/manic symptoms as well as the entitlement and defectiveness schemas were significantly associated with current suicidal ideation. Also, the entitlement and social isolation schemas were associated with lifetime suicide attempts. These results suggest that the entitlement, social isolation, and defectiveness schemas may relate to suicidal risk in patients with BD

Altered plasticity of the parasympathetic innervation in the recovering rat submandibular gland following extensive atrophy

Adult rat submandibular glands have a rich autonomic innervation, with parasympathetic and sympathetic nerves working in synergy rather than antagonistically. Ligation of the secretory duct rapidly causes atrophy and the loss of most acini, which are the main target cell for parasympathetic nerves. Following deligation, there is a recovery of gland structure and function, as assessed by autonomimetic stimulation. This study examines whether the parasympathetic nerves reattach to new target cells to form functional neuro-effector junctions. Under recovery anaesthesia, the submandibular duct of adult male rats was ligated via an intra-oral approach to avoid damaging the chorda-lingual nerve. Four weeks later, rats were either killed or anaesthetized and the ligation clip removed. Following a further 8 weeks, both submandibular ducts were cannulated under terminal anaesthesia. Salivary flows were then stimulated electrically (chorda-lingual nerve at 2, 5 and 10 Hz) and subsequently by methacholine (whole-body infusion at two doses). Glands were excised, weighed and divided for further in vitro studies or fixed for histological examination. Ligation of ducts caused 75% loss of gland weight, with the loss of most acinar cells. Of the remaining acini, only 50% were innervated despite unchanged choline acetyltransferase activity, suggesting few parasympathetic nerves had died. Following deligation, submandibular glands recovered half their weight and had normal morphology. Salivary flows from both glands (per unit of gland tissue) were similar when evoked by methacholine but greater from the deligated glands when evoked by nerve stimulation. This suggests that parasympathetic nerves had reattached to new target cells in the recovered glands at a greater ratio than normal, confirming reinnervation of the regenerating gland

AI-based soft module for safe human–robot interaction towards 4D printing

Soft robotic modules have potential use for therapeutic and educational purposes. To do so, they need to be safe, soft, smart, and customizable to serve individuals’ different preferences and personalities. A safe modular robotic product made of soft materials, particularly silicon, programmed by artificial intelligence algorithms and developed via additive manufacturing would be promising. This study focuses on the safe tactile interaction between humans and robots by means of soft material characteristics for translating physical communication to auditory. The embedded vibratory sensors used to stimulate touch senses transmitted through soft materials are presented. The soft module was developed and verified successfully to react to three different patterns of human–robot contact, particularly users’ touches, and then communicate the type of contact with sound. The study develops and verifies a model that can classify different tactile gestures via machine learning algorithms for safe human–robot physical interaction. The system accurately recognizes the gestures and shapes of three-dimensional (3D) printed soft modules. The gestures used for the experiment are the three most common, including slapping, squeezing, and tickling. The model builds on the concept of how safe human–robot physical interactions could help with cognitive and behavioral communication. In this context, the ability to measure, classify, and reflect the behavior of soft materials in robotic modules represents a prerequisite for endowing robotic materials in additive manufacturing for safe interaction with humans