Preferential Multi-Target Search in Indoor Environments using Semantic SLAM

In recent years, the demand for service robots capable of executing tasks beyond autonomous navigation has grown. In the future, service robots will be expected to perform complex tasks like 'Set table for dinner'. High-level tasks like these, require, among other capabilities, the ability to retrieve multiple targets. This paper delves into the challenge of locating multiple targets in an environment, termed 'Find my Objects.' We present a novel heuristic designed to facilitate robots in conducting a preferential search for multiple targets in indoor spaces. Our approach involves a Semantic SLAM framework that combines semantic object recognition with geometric data to generate a multi-layered map. We fuse the semantic maps with probabilistic priors for efficient inferencing. Recognizing the challenges introduced by obstacles that might obscure a navigation goal and render standard point-to-point navigation strategies less viable, our methodology offers resilience to such factors. Importantly, our method is adaptable to various object detectors, RGB-D SLAM techniques, and local navigation planners. We demonstrate the 'Find my Objects' task in real-world indoor environments, yielding quantitative results that attest to the effectiveness of our methodology. This strategy can be applied in scenarios where service robots need to locate, grasp, and transport objects, taking into account user preferences. For a brief summary, please refer to our video: https://tinyurl.com/PrefTargetSearchComment: 6 pages, 8 figure

Direct Hydroxylation of Phenol to Dihydroxybenzenes by H2O2 and Fe-based Metal-Organic Framework Catalyst at Room Temperature

A semi-crystalline iron-based metal-organic framework (MOF), in particular Fe-BTC, that contained 20 wt.% Fe, was sustainably synthesized at room temperature and extensively characterized. Fe-BTC nanopowders could be used as an efficient heterogeneous catalyst for the synthesis of dihydroxybenzenes (DHBZ), from phenol with hydrogen peroxide (H2O2), as oxidant under organic solvent-free conditions. The influence of the reaction temperature, H2O2 concentration and catalyst dose were studied in the hydroxylation performance of phenol and MOF stability. Fe-BTC was active and stable (with negligible Fe leaching) at room conditions. By using intermittent dosing of H2O2, the catalytic performance resulted in a high DHBZ selectivity (65%) and yield (35%), higher than those obtained for other Fe-based MOFs that typically require reaction temperatures above 70◦C. The long-term experiments in a fixed-bed flow reactor demonstrated good Fe-BTC durability at the above conditionsThe authors thank the financial support by Consejo Nacional de Ciencia y Tecnología (CONACYT) for the grant number 764635 and the project 256296; and to TNM for the supporting project 5627.19.P. Also, to the Spanish Ministerio de Ciencia, Innovación y Universidades (MICINN) and FEDER program (EU) through the projects: CTM2016-76454-R (MICINN) and RTI2018-095052-B-I00 ((MCIU/AEI/FEDER, UE

A Systems Biology Interpretation of Array Comparative Genomic Hybridization (aCGH) Data through Phylogenetics

Array Comparative Genomic Hybridization (aCGH) is a rapid screening technique to detect gene deletions and duplications, providing an overview of chromosomal aberrations throughout the entire genome of a tumor, without the need for cell culturing. However, the heterogeneity of aCGH data obfuscates existing methods of data analysis. Analysis of aCGH data from a systems biology perspective or in the context of total aberrations is largely absent in the published literature. We present here a novel alternative to the functional analysis of aCGH data using the phylogenetic paradigm that is well-suited to high dimensional datasets of heterogeneous nature, but has not been widely adapted to aCGH data. Maximum parsimony phylogenetic analysis sorts out genetic data through the simplest presentation of the data on a cladogram, a graphical evolutionary tree, thus providing a powerful and efficient method for aCGH data analysis. For example, the cladogram models the multiphasic changes in the cancer genome and identifies shared early mutations in the disease progression, providing a simple yet powerful means of aCGH data interpretation. As such, applying maximum parsimony phylogenetic analysis to aCGH results allows for the differentiation between drivers and passenger genes aberrations in cancer specimens. In addition to offering a novel methodology to analyze aCGH results, we present here a crucial software suite that we wrote to carry out the analysis. In a broader context, we wish to underscore that phylogenetic analysis of aCGH data is a non-parametric method that circumvents the pitfalls and frustrations of standard analytical techniques that rely on parametric statistics. Organizing the data in a cladogram as explained in this research article provides insights into the disease common aberrations, as well as the disease subtypes and their shared aberrations (the synapomorphies) of each subtype. Hence, we report the method and make the software suite publicly and freely available at http://software.phylomcs.com so that researchers can test alternative and innovative approaches to the analysis of aCGH data

Aristonectes quiriquinensis, sp. nov., a new highly derived elasmosaurid from the upper Maastrichtian of central Chile

This paper describes a new species of elasmosaurid plesiosaur, Aristonectes quiriquinensis, sp. nov., based on a partial skeleton recovered from upper Maastrichtian beds of the Quiriquina Formation of central Chile. The material described here consists of two skeletons, one collected near the village of Cocholgue, and a second juvenile specimen from Quiriquina Island. Prior to these finds, Aristonectes was viewed as a monospecific genus, including only the enigmatic Aristonectes parvidens, the holotype of which consists of an incomplete skull and incomplete postcranium. Other material referred to the genus includes an incomplete juvenile skull and other postcranial material from the upper Maastrichtian of Antarctica, as well as a partial skull from the Quiriquina Formation of central Chile. The relationships of Aristonectes have been controversial, with competing theories assigning the genus to Cryptoclididae, Elasmosauridae, and Aristonectidae; however, there is a developing consensus that Aristonectes is a derived elasmosaurid, and this paper gives strong evidence for this view. Comparison of the specimen here studied with the holotype of A. parvidens demonstrates that A. quiriquinensis is a distinct species. The completeness of the adult skeleton allows the first confident size estimates for adult Aristonectes. It is a large plesiosaurian with a relatively large skull with numerous homodont teeth, a moderately long and laterally compressed neck, and relatively narrow trunk, with slender and elongate forelimbs. The two specimens are restricted to the upper Maastrichtian of central Chile, posing questions concerning the austral circumpolar distribution of different elasmosaurids towards the end of the Cretaceous.Fil: Otero, Rodrigo A.. Universidad de Chile; ChileFil: Soto Acuña, Sergio. Museo Nacional de Historia Natural de Santiago; Chile. Universidad de Chile; ChileFil: O'Keefe, Frank Robin. Marshall University; Estados UnidosFil: O'gorman, Jose Patricio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Paleontología Vertebrados; ArgentinaFil: Stinnesbeck, Wolfgang. Heidelberg University; AlemaniaFil: Suárez, Mario E.. Museo Nacional de Historia Natural de Santiago; Chile. Universidad de Chile; ChileFil: Rubilar-Rogers, David. Museo Nacional de Historia Natural de Santiago; Chile. Universidad de Chile; ChileFil: Salazar, Christian. Museo Nacional de Historia Natural de Santiago; Chile. Universidad de Chile; ChileFil: Quinzio Sinn, Luis Arturo. Universidad de Concepción; Chil

Accuracy of Fitbit Activity Trackers During Walking in a Controlled Setting

Activity trackers are widely used to measure daily physical activity. Many devices have been shown to measure steps more accurately at higher intensities, however, it is also important to determine the accuracy of these new devices at measuring steps while walking at a pace similar to that used during most daily activities. PURPOSE: To assess the accuracy of 6 popular activity trackers at measuring steps while walking on a treadmill. METHODS: Twenty-six college students (Mean±SD; 22.1±3.7yrs; 25.1±4.0kg/m2; 13 male) walked 500 steps at 3mph on a treadmill while wearing 6 different activity trackers (Pedometer, Fitbit Blaze, Charge HR, Alta, Flex, Zip, One). The Charge HR was placed two fingers above the right wrist while the Flex was next to the wrist bone. The Blaze was placed two fingers above the left wrist while the Alta was next to the wrist bone. The Fitbit Zip and the One were aligned with the hipbone on the left and right waistband respectively. Steps were counted by a trained researcher using a hand tally counter. Missing values were replaced with the mean value for that device. Step counts were correlated between Fitbit devices and the pedometer and tally counter using Pearson correlations. Significance was set at p\u3c0.05. Mean bias scores were calculated between the step counts for each device and the tally counter. Mean Absolute Percent Error (MAPE) values were also calculated for each device relative to the tally counter. RESULTS: Fitbit Zip and One were significantly correlated with the tally counter (r=0.50, p\u3c0.05; r=0.68, p\u3c0.01, respectively) while the other devices were not significantly correlated. Mean bias and MAPE values were as follows: Device (Mean Bias/MAPE) Pedometer (-0.2±39.2/3.8±6.8), Blaze (34.5±67.1/9.9±11.3), Charge HR (-12.6±61.5/7.0±10.3), Alta (-85.0±70.8/17.1±14.1), Flex (49.5±242.4/19.7±45.3), Zip (1.8±3.4/0.4±0.6), One (0.2±2.1/0.3±0.3). Fitbit Zip and One were within one half percent of actual steps while wrist-worn Fitbits ranged from 7.0-19.7% from actual step counts. CONCLUSION: Consistent with previous research, activity trackers worn at the waist provide the most accurate step counts compared to wrist-worn models. Differences found in wrist-worn models may result in significant over- or underestimation of activity levels when worn for long periods of time

CrimeNet: Neural Structured Learning using Vision Transformer for violence detection

The state of the art in violence detection in videos has improved in recent years thanks to deep learning models, but it is still below 90% of average precision in the most complex datasets, which may pose a problem of frequent false alarms in video surveillance environments and may cause security guards to disable the artificial intelligence system. In this study, we propose a new neural network based on Vision Transformer (ViT) and Neural Structured Learning (NSL) with adversarial training. This network, called CrimeNet, outperforms previous works by a large margin and reduces practically to zero the false positives. Our tests on the four most challenging violence-related datasets (binary and multi-class) show the effectiveness of CrimeNet, improving the state of the art from 9.4 to 22.17 percentage points in ROC AUC depending on the dataset. In addition, we present a generalisation study on our model by training and testing it on different datasets. The obtained results show that CrimeNet improves over competing methods with a gain of between 12.39 and 25.22 percentage points, showing remarkable robustness.MCIN/AEI/ 10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR ” HORUS project - Grant n. PID2021-126359OB-I0

Validity of Daily Physical Activity Measurements of Fitbit Charge 2

Physical activity monitors collect continuous data to provide a summary of daily activity. The Fitbit Charge 2 monitors heart rate as well as steps, calories, and active minutes throughout the day. There is currently no research validating the Fitbit Charge 2 at measuring daily physical activity levels in a real life setting. PURPOSE: To compare measures of daily steps and active minutes of Fitbit Charge 2 with a research-grade accelerometer. METHODS: Sixteen active college students (Mean±SD; 23±4.9yrs; 16.43±10.19%fat; 9 male) consented to be part of the study. Participants wore an ActiGraph GT3X accelerometer and Fitbit Charge 2 concurrently for seven consecutive days. Both devices were programed with each participant’s information and the participants were instructed to perform their daily activities wearing both devices and only remove them to shower and to sleep. Data were considered valid when participants wore both devices for at least 10 hours on 4 or more days of the week. Steps and active minutes (moderate-vigorous physical activity) were recorded by each device. Mean bias was calculated by subtracting ActiGraph steps and active minutes from those obtained from the Fitbit Charge 2 for each day and an average daily mean bias was calculated using values from all seven days. Absolute percentage error was also calculated [100(|Fitbit Charge 2 - ActiGraph|)/ActiGraph] to indicate the overall 7-day difference between the Fitbit Charge 2 and ActiGraph. Pearson correlations and paired sample t-test were performed to compare Fitbit Charge 2 measurements with the corresponding ActiGraph measurements with significance considered at p\u3c0.05. RESULTS: The Fitbit Charge 2 overestimated steps by 2,451.3±2085.4 compared to the ActiGraph using the daily average steps over the seven days. This was 32.2±40.7% above the ActiGraph measurement. Average mean bias for daily active minutes was -52.1±58.9 with the Fitbit Charge 2 underestimating compared to the ActiGraph. Active minutes for the Fitbit Charge 2 were an average of 69±26.1% away from the ActiGraph. Steps for the Fitbit Charge 2 were significantly correlated to ActiGraph steps (r=0.575, p=0.02) while active minutes were not significantly correlated (r= -0.255, p=0.34). Paired sample t-test results showed a significant difference between the Fitbit Charge 2 steps and active minutes compared with the ActiGraph (p\u3c0.01 for both). CONCLUSION: The Fitbit Charge 2 may be useful for measuring steps in a free-living environment, however active minutes are significantly underestimated

Comparison of Smartphone Pedometer Apps on a Treadmill versus Outdoors

Previous research has focused on the accuracy of smartphone pedometer apps in laboratory settings, however less information is available in outdoor (free living) environments. PURPOSE: Determine the accuracy of 5 smartphone apps at recording steps at a walking speed in a laboratory versus an outdoor setting. METHODS: Twenty-three healthy college students consented (Mean±SD; 22±3.8yrs; BMI 24.9±4.13kg/m2) to participate in 2 separate visits. During the first visit participants walked 500 steps at 3mph on a treadmill while wearing a pedometer and a smartphone placed in the pocket using 5 pedometer apps concurrently (Moves, Google Fit (G-Fit), Runtastic, Accupedo, S-Health). During the second visit, participants walked 400 meters at 3mph on a sidewalk outside. Actual steps for each visit were recorded using a hand tally counter device. Zero and negative values were replaced with the mean value for that trial. Statistical analyses were performed using IBM SPSS 23.0. Mean bias scores were calculated between the step count for each app and the respective tally count for each trial. Mean bias scores were correlated between trials for each app using Pearson correlations and significance was set at p\u3c0.05. Mean Absolute Percent Error (MAPE) values were also calculated for each app for both trials. RESULTS: G-Fit recorded 2 zero values and 2 negative values and Moves recorded 1 zero value. Mean bias scores were significantly correlated between the indoor and outdoor protocols for the pedometer (r=0.67, p\u3c0.01) and S-Health (r=0.46, p\u3c0.5). The remaining apps were not correlated between protocols. The outdoor protocol producing a greater mean bias for the outdoor protocol for G-Fit, Runtastic, and Accupedo (mean bias ± SD indoor, outdoor; -4.3±53.1, -19.3±120.0; -10.7±63.3, -33.4±118.7; 16.0±143.6, 79.0±75.0; respectively) and a greater mean bias for the indoor protocol for the pedometer, Moves, and S-Health (mean bias indoor, outdoor; -1.4±41.5, 0.0±34.1; -117.4±196.7, -42.2±209.6; 11.3±28.4, 0.0±58.7; respectively). MAPE was below 5% for the pedometer and S-Health for both trials. CONCLUSION: Apps with the lowest error in a controlled setting may be less affected when used in other settings, while apps with greater variation in a controlled setting may be affected when used in a different environment

Normative Anthropometric and Physical-Function Scores for Costa Rican Older Adults

INTRODUCTION: The aging population is becoming significantly large in several countries due to improved health conditions and higher life expectancy. For instance, Costa Rican elderly have 17% less mortality at 90 yr. of age than elderly from high-income countries, and in Costa Rica life expectancy is higher for men than for women. In developed countries such as Spain, a large number of sedentary elderly have been found with elevated body fat percentage, which might impact their overall health and quality of life. Although the international scientific literature is extensive, the physical and functional status of Central American elderly is unknown. PURPOSE: The purpose of the study was to construct normative scores for anthropometric, adiposity and upper-arm strength variables in Costa Rican adults aged 60 to 110 yr. METHODS: Participants were 5494 Costa Rican elderly randomly selected from the Costa Rican National Population Census. These participants were assessed to determine their general health status and to obtain anthropometric, adiposity and hand grip strength measures. RESULTS: Nearly 50% of males and females showed an increased risk of metabolic complications (χ2 = 91.6; p ≤ 0.001). A higher percentage of females (64.5%) had abdominal obesity compared to males (18.6%). Males (39.8%) were more pre-obese than females (37.2%) and also type II obesity was more frequent in males (3.8%) than in females (3.5%). Males had higher body weight (4.4%) than females (3.9%), less type I obesity (13.4%) than women (17.5%) and less type III obesity (1.0%) than females (1.5%). Gender specific percentile-based norms (P10th, P25th, P50th, P75th, and P90th) were derived from data collected for each 10-year age groups (60-69, 70-79, 80-89, 90-99, and ≥100). CONCLUSION: This is the first population-based study in Central America reporting normative scores for anthropometric and physical-function variables in older adults