The polarisome is required for segregation and retrograde transport of protein aggregates.

The paradigm sirtuin, Sir2p, of budding yeast is required for establishing cellular age asymmetry, which includes the retention of damaged and aggregated proteins in mother cells. By establishing the global genetic interaction network of SIR2 we identified the polarisome, the formin Bni1p, and myosin motor protein Myo2p as essential components of the machinery segregating protein aggregates during mitotic cytokinesis. Moreover, we found that daughter cells can clear themselves of damage by a polarisome- and tropomyosin-dependent polarized flow of aggregates into the mother cell compartment. The role of Sir2p in cytoskeletal functions and polarity is linked to the CCT chaperonin in sir2Delta cells being compromised in folding actin. We discuss the findings in view of recent models hypothesizing that polarity may have evolved to avoid clonal senescence by establishing an aging (soma-like) and rejuvenated (germ-like) lineage.

Optical Flow-Based Obstacle Detection for Mid-Air Collision Avoidance.

The sky may seem big enough for two flying vehicles to collide, but the facts show that mid-air collisions still occur occasionally and are a significant concern. Pilots learn manual tactics to avoid collisions, such as see-and-avoid, but these rules have limitations. Automated solutions have reduced collisions, but these technologies are not mandatory in all countries or airspaces, and they are expensive. These problems have prompted researchers to continue the search for low-cost solutions. One attractive solution is to use computer vision to detect obstacles in the air due to its reduced cost and weight. A well-trained deep learning solution is appealing because object detection is fast in most cases, but it relies entirely on the training data set. The algorithm chosen for this study is optical flow. The optical flow vectors can help us to separate the motion caused by camera motion from the motion caused by incoming objects without relying on training data. This paper describes the development of an optical flow-based airborne obstacle detection algorithm to avoid mid-air collisions. The approach uses the visual information from a monocular camera and detects the obstacles using morphological filters, optical flow, focus of expansion, and a data clustering algorithm. The proposal was evaluated using realistic vision data obtained with a self-developed simulator. The simulator provides different environments, trajectories, and altitudes of flying objects. The results showed that the optical flow-based algorithm detected all incoming obstacles along their trajectories in the experiments. The results showed an F-score greater than 75% and a good balance between precision and recall.

A Real-Time Automated Defect Detection System for Ceramic Pieces Manufacturing Process Based on Computer Vision with Deep Learning.

Defect detection is a key element of quality control in today's industries, and the process requires the incorporation of automated methods, including image sensors, to detect any potential defects that may occur during the manufacturing process. While there are various methods that can be used for inspecting surfaces, such as those of metal and building materials, there are only a limited number of techniques that are specifically designed to analyze specialized surfaces, such as ceramics, which can potentially reveal distinctive anomalies or characteristics that require a more precise and focused approach. This article describes a study and proposes an extended solution for defect detection on ceramic pieces within an industrial environment, utilizing a computer vision system with deep learning models. The solution includes an image acquisition process and a labeling platform to create training datasets, as well as an image preprocessing technique, to feed a machine learning algorithm based on convolutional neural networks (CNNs) capable of running in real time within a manufacturing environment. The developed solution was implemented and evaluated at a leading Portuguese company that specializes in the manufacturing of tableware and fine stoneware. The collaboration between the research team and the company resulted in the development of an automated and effective system for detecting defects in ceramic pieces, achieving an accuracy of 98.00% and an F1-Score of 97.29%.

Augmented Humanity: A Systematic Mapping Review.

Augmented humanity (AH) is a term that has been mentioned in several research papers. However, these papers differ in their definitions of AH. The number of publications dealing with the topic of AH is represented by a growing number of publications that increase over time, being high impact factor scientific contributions. However, this terminology is used without being formally defined. The aim of this paper is to carry out a systematic mapping review of the different existing definitions of AH and its possible application areas. Publications from 2009 to 2020 were searched in Scopus, IEEE and ACM databases, using search terms "augmented human", "human augmentation" and "human 2.0". Of the 16,914 initially obtained publications, a final number of 133 was finally selected. The mapping results show a growing focus on works based on AH, with computer vision being the index term with the highest number of published articles. Other index terms are wearable computing, augmented reality, human-robot interaction, smart devices and mixed reality. In the different domains where AH is present, there are works in computer science, engineering, robotics, automation and control systems and telecommunications. This review demonstrates that it is necessary to formalize the definition of AH and also the areas of work with greater openness to the use of such concept. This is why the following definition is proposed: "Augmented humanity is a human-computer integration technology that proposes to improve capacity and productivity by changing or increasing the normal ranges of human function through the restoration or extension of human physical, intellectual and social capabilities".

Machine Learning Techniques for Arousal Classification from Electrodermal Activity: A Systematic Review.

This article introduces a systematic review on arousal classification based on electrodermal activity (EDA) and machine learning (ML). From a first set of 284 articles searched for in six scientific databases, fifty-nine were finally selected according to various criteria established. The systematic review has made it possible to analyse all the steps to which the EDA signals are subjected: acquisition, pre-processing, processing and feature extraction. Finally, all ML techniques applied to the features of these signals for arousal classification have been studied. It has been found that support vector machines and artificial neural networks stand out within the supervised learning methods given their high-performance values. In contrast, it has been shown that unsupervised learning is not present in the detection of arousal through EDA. This systematic review concludes that the use of EDA for the detection of arousal is widely spread, with particularly good results in classification with the ML methods found.

Security Mechanisms of a Mobile Health Application for Promoting Physical Activity among Older Adults.

Physical activity contributes to the maintenance of health conditions and functioning. However, the percentage of older adults who comply with the recommendations for physical activity levels is low when compared to the same percentages on younger groups. The SmartWalk system aims to encourage older adults to perform physical activity (i.e., walking in the city), which is monitored and adjusted by healthcare providers for best results. The study reported in this article focused on the implementation of SmartWalk security services to keep personal data safe during communications and while at rest, which were validated considering a comprehensive use case. The security framework offers various mechanisms, including an authentication system that was designed to complement the pairs of usernames and passwords with trusted execution environments and token-based features, authorization with different access levels, symmetric and asymmetric key cryptography, critical transactions review, and logging supported by blockchain technology. The resulting implementation contributes for a common understanding of the security features of trustful smart cities' applications, which conforms with existing legislation and regulations.

Feeling of Safety and Comfort towards a Socially Assistive Unmanned Aerial Vehicle That Monitors People in a Virtual Home.

Unmanned aerial vehicles (UAVs) represent a new model of social robots for home care of dependent persons. In this regard, this article introduces a study on people's feeling of safety and comfort while watching the monitoring trajectory of a quadrotor dedicated to determining their condition. Three main parameters are evaluated: the relative monitoring altitude, the monitoring velocity and the shape of the monitoring path around the person (ellipsoidal or circular). For this purpose, a new trajectory generator based on a state machine, which is successfully implemented and simulated in MATLAB/Simulink®, is described. The study is carried out with 37 participants using a virtual reality (VR) platform based on two modules, UAV simulator and VR Visualiser, both communicating through the MQTT protocol. The participants' preferences have been a high relative monitoring altitude, a high monitoring velocity and a circular path. These choices are a starting point for the design of trustworthy socially assistive UAVs flying in real homes.

Determining the ambient influences and configuration of optimised environments for emotional wellbeing of older adults.

It is now widely recognised that aspects such as tiredness or mood state can have an impact on an individual's wellbeing. However, there also exist other less studied factors that might be influential, and whose analysis is important to maximise personal wellbeing. The aim of this study was to determine the influence of a set of 12 selected factors. Using the analysis of a 20-experiment case study by soft computing techniques the intention was to establish the most appropriate configuration for each factor to compose an optimal living environment to foster wellbeing. The analysis revealed that ambient lighting and stress level are the factors that most impact emotional wellbeing. To a lesser extent, being able to take a break, ambient temperature and ambient noise play a relatively determining role. The findings of this work can be used to establish a living environment for older persons that favours their emotional wellbeing. Practitioner summary: This study analyses the level of influence of a set of ambient factors on the emotional wellbeing of older people, conducting, to this end, a series of controlled experiments, and concluding that ambient lighting and stress level are the factors most relevant to promote a better living environment.KEY POINTSOlder adults' emotional interpretation of pictures depends on the environment and ambient factors.Ambient factors, such as lighting and stress, have a significant, positive effect on visual interpretation of stimuli and greater wellbeing.The use of soft computing techniques facilitates the quantification of the influence of factors affecting emotional wellbeing.

Anion Recognition by Neutral Chalcogen Bonding Receptors: Experimental and Theoretical Investigation.

Invited for the cover of this issue are the groups of Antonio Frontera at the Universitat de les Illes Balears and Antonio Caballero at the Universidad de Murcia. The image depicts one of the tellurophene based receptors described in this work. Read the full text of the article at 10.1002/chem.201905786.

Anion Recognition by Neutral Chalcogen Bonding Receptors: Experimental and Theoretical Investigations.

The utilization of neutral receptors for the molecular recognition of anions based on chalcogen bonding (ChB) is an undeveloped area of host-guest chemistry. In this manuscript, the synthesis of two new families of sulfur, selenium, and tellurium-based ChB binding motifs are reported. The stability of the thiophene, selenophene, and tellurophene binding motifs has enabled the determination of the association constants for ChB halide anion binding in the polar aprotic solvent THF by 1 H, 77 Se, and 125 Te NMR experiments. Two different aromatic cores are used and one or two Ch-binding motifs are incorporated with the purpose of encapsulating the anion, offering up to two concurrent chalcogen bonds. Theoretical calculations and NMR experiments reveal that, for S and Se receptors, hydrogen-bonding interactions involving the acidic H atom adjacent to the chalcogen atom are energetically favored over the ChB interaction. However, for the tellurophene binding motif, the σ-hole interaction is competitive and more favored than the hydrogen bond.

Selective fluorescence sensing of H2PO4- by the anion induced formation of self-assembled supramolecular polymers.

The utilization of anions to induce the formation of self-assembled supramolecular polymers in solution is an undeveloped area of host-guest chemistry. We report in this manuscript a comparative study of two tripodal anion receptors by hydrogen or halogen bonding interactions to form self-assembled supramolecular structures induced by the presence of anions. DOSY NMR and DLS experiments provided evidence for the formation of supramolecular structures in solution in both halogen and hydrogen bond donors with H2PO4- anions. The nucleation and elongation constants obtained using the thermodynamic model indicate that the polymers grow following an isodesmic mechanism. Emission studies demonstrate that only the formation of the supramolecular polymer between the halogen bond donor receptor and H2PO4- anions results in the appearance of the excimer emission band.

Arousal Detection in Elderly People from Electrodermal Activity Using Musical Stimuli.

The detection of emotions is fundamental in many areas related to health and well-being. This paper presents the identification of the level of arousal in older people by monitoring their electrodermal activity (EDA) through a commercial device. The objective was to recognize arousal changes to create future therapies that help them to improve their mood, contributing to reduce possible situations of depression and anxiety. To this end, some elderly people in the region of Murcia were exposed to listening to various musical genres (flamenco, Spanish folklore, Cuban genre and rock/jazz) that they heard in their youth. Using methods based on the process of deconvolution of the EDA signal, two different studies were carried out. The first, of a purely statistical nature, was based on the search for statistically significant differences for a series of temporal, morphological, statistical and frequency features of the processed signals. It was found that Flamenco and Spanish Folklore presented the highest number of statistically significant parameters. In the second study, a wide range of classifiers was used to analyze the possible correlations between the detection of the EDA-based arousal level compared to the participants' responses to the level of arousal subjectively felt. In this case, it was obtained that the best classifiers are support vector machines, with 87% accuracy for flamenco and 83.1% for Spanish Folklore, followed by K-nearest neighbors with 81.4% and 81.5% for Flamenco and Spanish Folklore again. These results reinforce the notion of familiarity with a musical genre on emotional induction.

Triazole-Containing [FeFe] Hydrogenase Mimics: Synthesis and Electrocatalytic Behavior.

Through a Cu-catalyzed Huisgen cycloaddition between terminal alkynes and azides (CuAAC) reaction, azide [(µ-SCH2)2N(4-N3C6H4)Fe2(CO)6] has demonstrated to be a robust and versatile reagent able to incorporate the [(µ-SR)2Fe2(CO)6] fragment on a wide range of substrates, ranging from aromatic compounds to nucleosides, metallocenes, or redox and luminescent markers. The [FeIFeI]/[Fe0FeI] and [Fe0FeI]/[Fe0Fe0] reduction potentials of the triazole derivatives prepared are comparable to those of other aminodithiolate (adt) Fe-Fe hydrogenase mimics. The presence of the triazole linker influences the electrochemical behavior of these complexes depending on the strength of the acid employed.

Anion Recognition Strategies Based on Combined Noncovalent Interactions.

This review highlights the most significant examples of an emerging field in the design of highly selective anion receptors. To date, there has been remarkable progress in the binding and sensing of anions. This has been driven in part by the discovery of ways to construct effective anion binding receptors using the dominant N-H functional groups and neutral and cationic C-H hydrogen bond donors, as well as underexplored strong directional noncovalent interactions such as halogen-bonding and anion-π interactions. In this review, we will describe a new and promising strategy for constructing anion binding receptors with distinct advantages arising from their elaborate design, incorporating multiple binding sites able to interact cooperatively with anions through these different kinds of noncovalent interactions. Comparisons with control species or solely hydrogen-bonding analogues reveal unique characteristics in terms of strength, selectivity, and interaction geometry, representing important advances in the rising field of supramolecular chemistry.

Absence of mitochondrial translation control proteins extends life span by activating sirtuin-dependent silencing.

Altered mitochondrial functionality can extend organism life span, but the underlying mechanisms are obscure. Here we report that inactivating SOV1, a member of the yeast mitochondrial translation control (MTC) module, causes a robust Sir2-dependent extension of replicative life span in the absence of respiration and without affecting oxidative damage. We found that SOV1 interacts genetically with the cAMP-PKA pathway and the chromatin remodeling apparatus. Consistently, Sov1p-deficient cells displayed reduced cAMP-PKA signaling and an elevated, Sir2p-dependent, genomic silencing. Both increased silencing and life span extension in sov1Δ cells require the PKA/Msn2/4p target Pnc1p, which scavenges nicotinamide, a Sir2p inhibitor. Inactivating other members of the MTC module also resulted in Sir2p-dependent life span extension. The data demonstrate that the nuclear silencing apparatus senses and responds to the absence of MTC proteins and that this response converges with a pathway for life span extension elicited by reducing TOR signaling.

Digital Technology for Internet Access by Patients With Early-Stage Schizophrenia in Spain: Multicenter Research Study.

BACKGROUND: Digital technology and social networks are part of everyday life in the current internet age, especially among young people. To date, few studies have been published worldwide on the pattern of use of digital technology devices and applications in patients with early-stage schizophrenia and even fewer comparing them with healthy participants (not using data from general population surveys) from the same demographic areas. In Spain, no such study has been carried out. OBJECTIVE: The aim of this study was to analyze how patients with early-stage schizophrenia use internet and social networks compared with healthy participants matched by age and gender and also to examine which devices are utilized to access internet resources. METHODS: A cross-sectional, multicentric study was carried out through a semistructured interview asking about the use of digital technology devices and internet. The sample comprised 90 patients and 90 healthy participants. The semistructured interview was conducted on 30 outpatients and 30 healthy subjects in each of the 3 different cities (Madrid, Alicante, and Cuenca). Student t test was used for continuous variables and chi-square test for categorical variables. In the case of ordinal variables, nonparametric Mann-Whitney U and Kruskal-Wallis H tests for independent samples were performed to compare groups. RESULTS: The results indicated that a large proportion of patients with early-stage schizophrenia have access to different digital devices and use them frequently. In addition, both groups coincide in the order of preference and the purpose for which they use the devices. However, a lower frequency of use of most digital technology devices was detected in patients compared with healthy participants. In the case of some devices, this was due to the impossibility of access and not a lack of interest. CONCLUSIONS: To our knowledge, this is the first study to analyze patterns of internet access and use of digital technology devices and applications in Spanish patients with early-stage schizophrenia compared with healthy participants from the same demographic areas. The results on significant access and use of digital technology and internet shown in this cross-sectional study will allow enhanced and more efficient treatment strategies to be planned, utilizing digital technology devices, for patients with early-stage schizophrenia.

A retrospective and prospective 12-month observational study of the socioeconomic burden of moderate to severe irritable bowel syndrome with constipation in Spain.

INTRODUCTION: The socioeconomic burden of irritable bowel syndrome with constipation (IBS-C) has never been formally assessed in Spain. PATIENTS AND METHODS: This 12-month (6-month retrospective and prospective periods) observational, multicentre study assessed the burden of moderate-to-severe IBS-C in Spain. Patients were included if they had been diagnosed with IBS-C (Rome III criteria) within the last 5 years and had moderate-to-severe IBS-C (IBS Symptom Severity Scale score [IBS-SSS] ≥175) at inclusion. The primary objective was to assess the direct cost to the Spanish healthcare system (HS). RESULTS: A total of 112 patients were included, 64 (57%) of which had severe IBS-C at inclusion. At baseline, 89 (80%) patients reported abdominal pain and distention. Patient quality of life (QoL), measured by the IBS-C QoL and EQ-5D instruments, was found to be impaired with a mean score of 59 and 57 (0-100, worst-best), respectively. Over the 6-month prospective period the mean IBS-C severity, measured using the IBS-SSS showed some improvement (315-234 [0-500, best-worst]). During the year, 89 (80%) patients used prescription drugs for IBS-C, with laxatives being the most frequently prescribed (n=70; 63%). The direct cost to the HS was €1067, and to the patient was €568 per year. The total direct cost for moderate-to-severe IBS-C was €1635. DISCUSSION: The majority of patients reported continuous IBS-C symptoms despite that 80% were taking medication to treat their IBS-C. Overall healthcare resource use and direct costs were asymmetric, with a small group of patients consuming the majority of resources.

Configurational Entropy in Multicomponent Alloys: Matrix Formulation from Ab Initio Based Hamiltonian and Application to the FCC Cr-Fe-Mn-Ni System.

Configuration entropy is believed to stabilize disordered solid solution phases in multicomponent systems at elevated temperatures over intermetallic compounds by lowering the Gibbs free energy. Traditionally, the increment of configuration entropy with temperature was computed by time-consuming thermodynamic integration methods. In this work, a new formalism based on a hybrid combination of the Cluster Expansion (CE) Hamiltonian and Monte Carlo simulations is developed to predict the configuration entropy as a function of temperature from multi-body cluster probability in a multi-component system with arbitrary average composition. The multi-body probabilities are worked out by explicit inversion and direct product of a matrix formulation within orthonomal sets of point functions in the clusters obtained from symmetry independent correlation functions. The matrix quantities are determined from semi canonical Monte Carlo simulations with Effective Cluster Interactions (ECIs) derived from Density Functional Theory (DFT) calculations. The formalism is applied to analyze the 4-body cluster probabilities for the quaternary system Cr-Fe-Mn-Ni as a function of temperature and alloy concentration. It is shown that, for two specific compositions (Cr 25Fe 25Mn 25Ni 25 and Cr 18Fe 27Mn 27Ni 28), the high value of probabilities for Cr-Fe-Fe-Fe and Mn-Mn-Ni-Ni are strongly correlated with the presence of the ordered phases L1 2 -CrFe 3 and L1 0-MnNi, respectively. These results are in an excellent agreement with predictions of these ground state structures by ab initio calculations. The general formalism is used to investigate the configuration entropy as a function of temperature and for 285 different alloy compositions. It is found that our matrix formulation of cluster probabilities provides an efficient tool to compute configuration entropy in multi-component alloys in a comparison with the result obtained by the thermodynamic integration method. At high temperatures, it is shown that many-body cluster correlations still play an important role in understanding the configuration entropy before reaching the solid solution limit of high-entroy alloys (HEAs).

Interlocked Supramolecular Polymers Created by Combination of Halogen- and Hydrogen-Bonding Interactions through Anion-Template Self-Assembly.

We present the synthesis and oxoanion-assembling properties of a monomer with a naphthalene ring as a central core decorated with two arms containing iodotriazolium rings as anion binding sites. Interactions with SO42-, H2PO4-, and HP2O73- anions, via a cooperative mechanism, afforded new supramolecular materials stabilized by a combination of halogen- and hydrogen-bonding interactions. 1H NMR experiments and solid-state structure provided evidence for the initial formation of a supramolecular linear chain, nucleation step, and then two different supramolecular chains are interpenetrated with each other, elongation steps, involving the formation of hydrogen bonds between two oxygens of the anion from one of the chains and the naphthalene inner protons from the other chain. Scanning electron microscopy studies revealed that the morphology of the crystals changed dramatically with the nature of the anion added.

A Finite State Machine Approach to Algorithmic Lateral Inhibition for Real-Time Motion Detection †.

Many researchers have explored the relationship between recurrent neural networks and finite state machines. Finite state machines constitute the best-characterized computational model, whereas artificial neural networks have become a very successful tool for modeling and problem solving. The neurally-inspired lateral inhibition method, and its application to motion detection tasks, have been successfully implemented in recent years. In this paper, control knowledge of the algorithmic lateral inhibition (ALI) method is described and applied by means of finite state machines, in which the state space is constituted from the set of distinguishable cases of accumulated charge in a local memory. The article describes an ALI implementation for a motion detection task. For the implementation, we have chosen to use one of the members of the 16-nm Kintex UltraScale+ family of Xilinx FPGAs. FPGAs provide the necessary accuracy, resolution, and precision to run neural algorithms alongside current sensor technologies. The results offered in this paper demonstrate that this implementation provides accurate object tracking performance on several datasets, obtaining a high F-score value (0.86) for the most complex sequence used. Moreover, it outperforms implementations of a complete ALI algorithm and a simplified version of the ALI algorithm—named “accumulative computation”—which was run about ten years ago, now reaching real-time processing times that were simply not achievable at that time for ALI.