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AI image classification algorithms have shown promising results when applied to skin cancer detection. Most public skin cancer image datasets are comprised of dermoscopic photos and are limited by selection bias, lack of standardization, and lend themselves to development of algorithms that can only be used by skilled clinicians. The SLICE-3D ("Skin Lesion Image Crops Extracted from 3D TBP") dataset described here addresses those concerns and contains images of over 400,000 distinct skin lesions from seven dermatologic centers from around the world. De-identified images were systematically extracted from sensitive 3D Total Body Photographs and are comparable in optical resolution to smartphone images. Algorithms trained on lower quality images could improve clinical workflows and detect skin cancers earlier if deployed in primary care or non-clinical settings, where photos are captured by non-expert physicians or patients. Such a tool could prompt individuals to visit a specialized dermatologist. This dataset circumvents many inherent limitations of prior datasets and may be used to build upon previous applications of skin imaging for cancer detection. [ABSTRACT FROM AUTHOR]

Sensory Over-Responsivity (SOR) is an increasingly recognized challenge among children with neurodevelopmental concerns (NDC). To investigate, we characterized the incidence of auditory and tactile over-responsivity (AOR, TOR) among 82 children with NDC. We found that 70% of caregivers reported concern for their child's sensory reactions. Direct assessment further revealed that 54% of the NDC population expressed AOR, TOR, or both – which persisted regardless of autism spectrum disorder (ASD) diagnosis. These findings support the high prevalence of SOR as well as its lack of specificity to ASD. Additionally, AOR is revealed to be over twice as prevalent as TOR. These conclusions present several avenues for further exploration, including deeper analysis of the neural mechanisms and genetic contributors to sensory processing challenges. [ABSTRACT FROM AUTHOR]

Objectives: Analyse alternative methods of intrathecal antibody detection by comparing chemiluminescent immunoassay (CLIA) and enzyme-linked immunosorbent assay (ELISA) techniques to determine if CLIA can replace ELISA in the diagnosis of CNS infections. Methods: A panel of 280 paired samples—cerebrospinal fluid (CSF) and serum—with known antibody reactivities (Varicella, n = 60; Measles, n = 120) and negative samples (n = 100) were used to evaluate the performance of six serological test kits (Enzygnost, VirClia®, and Serion ELISA (Measles and Variella). Results: For Measles virus IgG, the VirClia® IgG monotest revealed 97% and 94% positive and negative agreement to the Enzygnost as reference test, respectively. In contrast, Serion ELISA kits yielded values of 18% and 90%. For the Varicella Zoster virus (VZV) IgG, the VirClia® IgG monotest showed 97% and 90% positive and negative agreement compared to Enzygnost. The Serion ELISA kits showed values of 55% and 86%, respectively. ROC analysis revealed that the areas under the curve for Measles and VZV IgGs were 0.7 and 0.852, respectively, using the Serion kit, and 0.963 and 0.955, for Vircell S.L CLIA technique. VirClia® monotest values were calculated using an antibody index cut-off of 1.3. Conclusion: The findings indicate that CLIA testing can improve antibody detection in CSF samples, aiding the diagnosis of infectious neurological impairments. [ABSTRACT FROM AUTHOR]

Brain tumour microstructure is potentially predictive of changes following treatment to cognitive functions subserved by the functional networks in which they are embedded. To test this hypothesis, intra-tumoural microstructure was quantified from diffusion-weighted MRI to identify which tumour subregions (if any) had a greater impact on participants' cognitive recovery after surgical resection. Additionally, we studied the role of tumour microstructure in the functional interaction between the tumour and the rest of the brain. Sixteen patients (22–56 years, 7 females) with brain tumours located in or near speech-eloquent areas of the brain were included in the analyses. Two different approaches were adopted for tumour segmentation from a multishell diffusion MRI acquisition: the first used a two-dimensional four group partition of feature space, whilst the second used data-driven clustering with Gaussian mixture modelling. For each approach, we assessed the capability of tumour microstructure to predict participants' cognitive outcomes after surgery and the strength of association between the BOLD signal of individual tumour subregions and the global BOLD signal. With both methodologies, the volumes of partially overlapped subregions within the tumour significantly predicted cognitive decline in verbal skills after surgery. We also found that these particular subregions were among those that showed greater functional interaction with the unaffected cortex. Our results indicate that tumour microstructure measured by MRI multishell diffusion is associated with cognitive recovery after surgery. [ABSTRACT FROM AUTHOR]

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Background: Sensory processing dysfunction (SPD) is linked to altered white matter (WM) microstructure in school-age children. Sensory over-responsivity (SOR), a form of SPD, affects at least 2.5% of all children and has substantial deleterious impact on learning and mental health. However, SOR has not been well studied using microstructural imaging such as diffusion MRI (dMRI). Since SOR involves hypersensitivity to external stimuli, we test the hypothesis that children with SOR require compensatory neuroplasticity in the form of superior WM microstructural integrity to protect against internalizing behavior, leaving those with impaired WM microstructure vulnerable to somatization and depression. Methods: Children ages 8–12 years old with neurodevelopmental concerns were assessed for SOR using a comprehensive structured clinical evaluation, the Sensory Processing 3 Dimensions Assessment, and underwent 3 Tesla MRI with multishell multiband dMRI. Tract-based spatial statistics was used to measure diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics from global WM and nineteen selected WM tracts. Correlations of DTI and NODDI measures with measures of somatization and emotional disturbance from the Behavioral Assessment System for Children, 3rd edition (BASC-3), were computed in the SOR group and in matched children with neurodevelopmental concerns but not SOR. Results: Global WM fractional anisotropy (FA) is negatively correlated with somatization and with emotional disturbance in the SOR group but not the non-SOR group. Also observed in children with SOR are positive correlations of radial diffusivity (RD) and free water fraction (FISO) with somatization and, in most cases, emotional disturbance. These effects are significant in boys with SOR, whereas the study is underpowered for girls. The most affected white matter are medial lemniscus and internal capsule sensory tracts, although effects of SOR are observed in many cerebral, cerebellar, and brainstem tracts. Conclusion: White matter microstructure is related to affective behavior in children with SOR. [ABSTRACT FROM AUTHOR]

The application of evolutionary algorithms (EAs) to complex engineering optimization problems may present difficulties as they require many evaluations of the objective functions by computationally expensive simulation procedures. To deal with this issue, surrogate models have been employed to replace those expensive simulations. In this work, a surrogate-assisted evolutionary optimization procedure is proposed. The procedure combines the differential evolution method with a k -nearest neighbors (k-NN) similarity-based surrogate model. In this approach, the database that stores the solutions evaluated by the exact model, which are used to approximate new solutions, is managed according to a merit scheme. Constraints are handled by a rank-based technique that builds multiple separate queues based on the values of the objective function and the violation of each constraint. Also, to avoid premature convergence of the method, a strategy that triggers a random reinitialization of the population is considered. The performance of the proposed method is assessed by numerical experiments using 24 constrained benchmark functions and 5 mechanical engineering problems. The results show that the method achieves optimal solutions with a remarkably reduction in the number of function evaluations compared to the literature. [ABSTRACT FROM AUTHOR]

Phytoextraction of rare earth elements (REE) from contaminated soils has gained importance during the last few decades. The Poços de Caldas municipality in Brazil is known for its mineral richness, including large reserves of REE. In this study, we report light REE (La, Ce, Sm, Pr, and Nd) in soils and plants collected in an area. Composite soil samples and plant individuals were collected, and total concentrations of LREE in soils were determined by wavelength dispersive X-ray fluorescence (WDXRF). The plant available LREE concentrations in soils were estimated upon the acetic acid method (F1 fractions) of the stepwise sequential extraction procedure, together with plant content that was analysed by inductively coupled plasma mass spectrometry (ICP-MS). The total sum concentrations of tested LREE in soils varied from 5.6 up to 37.9 g kg−1, the bioavailable fraction was ca. 1%, and a linear relationship was found between them. The only exception was Sm, whose availability was lesser and did not show a linear relationship. The concentration of LREE in non-accumulator plants varied from 1.3–950 mg kg−1 for Ce, La 1.1–99 mg kg−1, Sm 0.04–9.31 mg kg−1, Pr 0.1–24.1 mg kg−1, and Nd 0.55–81 mg kg−1. The concentration of LREE among shoots did not show a linear relation either with the available fraction or total content. The screening also revealed Christella dentata (Forssk.) Brownsey & Jermy, Thelypteridaceae family, as a promising hyperaccumulator species. The concentrations of LREE among shoots of six individuals of this species were in the ranges from 115 to 1872 mg kg−1 for Ce, La 190–703 mg kg−1, Sm 9–48 mg kg−1, Pr 32–144 mg kg−1, and Nd 105–478 mg kg−1. [ABSTRACT FROM AUTHOR]

Few studies assessing the effects of COVID-19 on mental health include prospective markers of risk and resilience necessary to understand and mitigate the combined impacts of the pandemic, lockdowns, and other societal responses. This population-based study of young adults includes individuals from the Neuroscience in Psychiatry Network (n = 2403) recruited from English primary care services and schools in 2012–2013 when aged 14–24. Participants were followed up three times thereafter, most recently during the initial outbreak of the COVID-19 outbreak when they were aged between 19 and 34. Repeated measures of psychological distress (K6) and mental wellbeing (SWEMWBS) were supplemented at the latest assessment by clinical measures of depression (PHQ-9) and anxiety (GAD-7). A total of 1000 participants, 42% of the original cohort, returned to take part in the COVID-19 follow-up; 737 completed all four assessments [mean age (SD), 25.6 (3.2) years; 65.4% female; 79.1% White]. Our findings show that the pandemic led to pronounced deviations from existing mental health-related trajectories compared to expected levels over approximately seven years. About three-in-ten young adults reported clinically significant depression (28.8%) or anxiety (27.6%) under current NHS guidelines; two-in-ten met clinical cut-offs for both. About 9% reported levels of psychological distress likely to be associated with serious functional impairments that substantially interfere with major life activities; an increase by 3% compared to pre-pandemic levels. Deviations from personal trajectories were not necessarily restricted to conventional risk factors; however, individuals with pre-existing health conditions suffered disproportionately during the initial outbreak of the COVID-19 pandemic. Resilience factors known to support mental health, particularly in response to adverse events, were at best mildly protective of individual psychological responses to the pandemic. Our findings underline the importance of monitoring the long-term effects of the ongoing pandemic on young adults' mental health, an age group at particular risk for the emergence of psychopathologies. Our findings further suggest that maintaining access to mental health care services during future waves, or potential new pandemics, is particularly crucial for those with pre-existing health conditions. Even though resilience factors known to support mental health were only mildly protective during the initial outbreak of the COVID-19 pandemic, it remains to be seen whether these factors facilitate mental health in the long term. [ABSTRACT FROM AUTHOR]

Background: Gliomas are typically considered to cause relatively few neurological impairments. However, cognitive difficulties can arise, for example during treatment, with potential detrimental effects on quality of life. Accurate, reproducible, and accessible cognitive assessment is therefore vital in understanding the effects of both tumor and treatments. Our aim is to compare traditional neuropsychological assessment with an app-based cognitive screening tool in patients with glioma before and after surgical resection. Our hypotheses were that cognitive impairments would be apparent, even in a young and high functioning cohort, and that app-based cognitive screening would complement traditional neuropsychological assessment. Methods: Seventeen patients with diffuse gliomas completed a traditional neuropsychological assessment and an app-based touchscreen tablet assessment pre- and post-operatively. The app assessment was also conducted at 3- and 12-month follow-up. Impairment rates, mean performance, and pre- and post-operative changes were compared using standardized Z-scores. Results: Approximately 2–3 h of traditional assessment indicated an average of 2.88 cognitive impairments per patient, while the 30-min screen indicated 1.18. As might be expected, traditional assessment using multiple items across the difficulty range proved more sensitive than brief screening measures in areas such as memory and attention. However, the capacity of the screening app to capture reaction times enhanced its sensitivity, relative to traditional assessment, in the area of non-verbal function. Where there was overlap between the two assessments, for example digit span tasks, the results were broadly equivalent. Conclusions: Cognitive impairments were common in this sample and app-based screening complemented traditional neuropsychological assessment. Implications for clinical assessment and follow-up are discussed. [ABSTRACT FROM AUTHOR]

The human brain is a highly plastic 'complex' network—it is highly resilient to damage and capable of self-reorganisation after a large perturbation. Clinically, neurological deficits secondary to iatrogenic injury have very few active treatments. New imaging and stimulation technologies, though, offer promising therapeutic avenues to accelerate post-operative recovery trajectories. In this study, we sought to establish the safety profile for 'interventional neurorehabilitation': connectome-based therapeutic brain stimulation to drive cortical reorganisation and promote functional recovery post-craniotomy. In n = 34 glioma patients who experienced post-operative motor or language deficits, we used connectomics to construct single-subject cortical networks. Based on their clinical and connectivity deficit, patients underwent network-specific transcranial magnetic stimulation (TMS) sessions daily over five consecutive days. Patients were then assessed for TMS-related side effects and improvements. 31/34 (91%) patients were successfully recruited and enrolled for TMS treatment within two weeks of glioma surgery. No seizures or serious complications occurred during TMS rehabilitation and 1-week post-stimulation. Transient headaches were reported in 4/31 patients but improved after a single session. No neurological worsening was observed while a clinically and statistically significant benefit was noted in 28/31 patients post-TMS. We present two clinical vignettes and a video demonstration of interventional neurorehabilitation. For the first time, we demonstrate the safety profile and ability to recruit, enroll, and complete TMS acutely post-craniotomy in a high seizure risk population. Given the lack of randomisation and controls in this study, prospective randomised sham-controlled stimulation trials are now warranted to establish the efficacy of interventional neurorehabilitation following craniotomy. [ABSTRACT FROM AUTHOR]

Aquaculture is looking for substitutes for fishmeal and fish oil to maintain its continued growth. Zooplankton is the most nutritious option, but its controlled mass production has not yet been achieved. In this context, we have developed a monoalgal 'green water' closed-loop bioreactor with the microalgae Tetraselmis chui that continuously produced the harpacticoid copepod Tigriopus californicus. During 145 days of operation, the 2.2 m3 bioreactor produced 3.9 kg (wet weight) of Tigriopus with (dry weight) 0.79 ± 0.29% eicosapentaenoic acid (EPA), 0.82 ± 0.26% docosahexaenoic acid (DHA), 1.89 ± 0,60% 3S,3'S-astaxanthin and an essential amino acid index (EAAI) of 97% for juvenile Atlantic salmon. The reactor kept the pH stable over the operation time (pH 8.81 ± 0.40 in the algae phase and pH 8.22 ± 2.96 in the zooplankton phase), while constantly removed nitrate (322.6 mg L−1) and phosphate (20.4 mg L−1) from the water. As a result of the stable pH and nutrient removal, the bioreactor achieved zero effluent discharges. The upscaling of monoalgal, closed-loop 'green water' bioreactors could help standardize zooplankton mass production to supply the aquafeeds industry. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a visual analytics approach aimed at helping machine learning experts analyze the hidden states of layers in recurrent neural networks. Our technique allows the user to interactively inspect how hidden states store and process information throughout the feeding of an input sequence into the network. The technique can help answer questions, such as which parts of the input data have a higher impact on the prediction and how the model correlates each hidden state configuration with a certain output. Our visual analytics approach comprises several components: First, our input visualization shows the input sequence and how it relates to the output (using color coding). In addition, hidden states are visualized through a nonlinear projection into a 2-D visualization space using t-distributed stochastic neighbor embedding to understand the shape of the space of the hidden states. Trajectories are also employed to show the details of the evolution of the hidden state configurations. Finally, a time-multi-class heatmap matrix visualizes the evolution of the expected predictions for multi-class classifiers, and a histogram indicates the distances between the hidden states within the original space. The different visualizations are shown simultaneously in multiple views and support brushing-and-linking to facilitate the analysis of the classifications and debugging for misclassified input sequences. To demonstrate the capability of our approach, we discuss two typical use cases for long short-term memory models applied to two widely used natural language processing datasets. 3AkgHYPUvew9RocThgM64- Video abstract. [ABSTRACT FROM AUTHOR]

Dead neonatal mice are currently used as bait for delivery of toxin to invasive brown treesnakes (Boiga irregularis) on Guam; once deployed in the field the mice are highly attractive to the snakes but only for about four days. An artificial bait containing a mixture of fats mimicking those in skin of the mice is also highly attractive to the snakes and remains attractive 2–3 times longer. The artificial bait, however, costs more than the mice, and is more difficult to attach to the capsules of a novel aerial bait delivery system. This paper describes a reformulation of the bait which reduced the ingredient cost to 11% of its former value, without compromising its attractiveness to free-ranging snakes. Three lipid formulations using different source materials to produce the same fatty acid profile target were tested along with two levels of pork fat to yield six test formulations. No differences in bait disappearance were noted in field testing of the baits, indicating that decisions regarding bait formulation could be made on the basis of cost without sacrificing efficacy. Separately, testing of 17 commercially available adhesives identified five for field testing. Among these, two demonstrated strong, weather-resistant bonds between the oily surface of the artificial baits and the bait capsules as evidenced by only 13.4% and 4.5% of baits falling off suspended capsules. Importantly, neither of these adhesives impacted bait removal by snakes in field trials in comparison to baits with no adhesive.. The results represent an advance in technology development for landscape-scale suppression of brown treesnake populations. [ABSTRACT FROM AUTHOR]

Adolescents are prone to social influence from peers, with implications for development, both adaptive and maladaptive. Here, using a computer-based paradigm, we replicate a cross-sectional effect of more susceptibility to peer influence in a large dataset of adolescents 14 to 24 years old. Crucially, we extend this finding by adopting a longitudinal perspective, showing that a within-person susceptibility to social influence decreases over a 1.5 year follow-up time period. Exploiting this longitudinal design, we show that susceptibility to social influences at baseline predicts an improvement in peer relations over the follow-up period. Using a Bayesian computational model, we demonstrate that in younger adolescents a greater tendency to adopt others' preferences arises out of a higher uncertainty about their own preferences in the paradigmatic case of delay discounting (a phenomenon called 'preference uncertainty'). This preference uncertainty decreases over time and, in turn, leads to a reduced susceptibility of one's own behaviour to an influence from others. Neuro-developmentally, we show that a measure of myelination within medial prefrontal cortex, estimated at baseline, predicts a developmental decrease in preference uncertainty at follow-up. Thus, using computational and neural evidence, we reveal adaptive mechanisms underpinning susceptibility to social influence during adolescence. People often change their preferences to conform with others. Using a longitudinal design, the authors show that such conformity decreases over the course of adolescence and that this reduction in conformity is accompanied by a decreasing degree of uncertainty about what to like. [ABSTRACT FROM AUTHOR]

Understanding our Galaxy's structure, formation, and evolution will, over the next decades, continue to benefit from the wonderful large survey by Gaia, for astrometric, kinematic, and spectroscopic characterization, and by large spectroscopic surveys for chemical characterization. The weak link for full exploitation of these data is age characterization, and stellar age estimation relies predominantly on mass estimates. The ideas presented in this White Paper shows that a seismology survey is the way out of this situation and a natural complement to existing and planned surveys. These ideas are strongly rooted in the past decade's experience of the so-called Seismology revolution, initiated with CoRoT and Kepler. The case of red giant stars is used here as the best current illustration of what we can expect from seismology for large samples, but premises for similar developments exist in various other classes of stars covering other ranges of age or mass. Whatever the star considered, the first information provided by stellar pulsations is always related to the mean density and thus to the mass (and age). In order to satisfy the need for long-duration and all-sky coverage, we rely on a new instrumental concept which decouples integration time and sampling time. We thus propose a long (~1 year) all-sky survey which would perfectly fit between TESS, PLATO, and the Rubin Observatory (previously known as LSST) surveys to offer a time domain complement to the current and planned astrometric and spectroscopic surveys. The fine characterization of host stars is also a key aspect for the interpretation and exploitation of the various projects -- anticipated in the framework of the Voyage 2050 programme -- searching for atmospheric characterization of terrestrial planets or, more specifically, looking for a signature of life, in distant planets. [ABSTRACT FROM AUTHOR]

Background: Intraoperative functional mapping with direct electrical stimulation during awake surgery for patients with diffuse low-grade glioma has been used in recent years to optimize the balance between surgical resection and quality of life following surgery. Mapping of executive functions is particularly challenging because of their complex nature, with only a handful of reports published so far. Here, we propose the recording of neural activity directly from the surface of the brain using electrocorticography to map executive functions and demonstrate its feasibility and potential utility. Methods: To track a neural signature of executive function, we recorded neural activity using electrocorticography during awake surgery from the frontal cortex of three patients judged to have an appearance of diffuse low-grade glioma. Based on existing functional magnetic resonance imaging (fMRI) evidence from healthy participants for the recruitment of areas associated with executive function with increased task demands, we employed a task difficulty manipulation in two counting tasks performed intraoperatively. Following surgery, the data were extracted and analyzed offline to identify increases in broadband high-gamma power with increased task difficulty, equivalent to fMRI findings, as a signature of activity related to executive function. Results: All three patients performed the tasks well. Data were recorded from five electrode strips, resulting in data from 15 channels overall. Eleven out of the 15 channels (73.3%) showed significant increases in high-gamma power with increased task difficulty, 26.6% of the channels (4/15) showed no change in power, and none of the channels showed power decrease. High-gamma power increases with increased task difficulty were more likely in areas that are within the canonical frontoparietal network template. Conclusions: These results are the first step toward developing electrocorticography as a tool for mapping of executive function complementarily to direct electrical stimulation to guide resection. Further studies are required to establish this approach for clinical use. [ABSTRACT FROM AUTHOR]

Neurodevelopmental disorders have a heritable component and are associated with region specific alterations in brain anatomy. However, it is unclear how genetic risks for neurodevelopmental disorders are translated into spatially patterned brain vulnerabilities. Here, we integrated cortical neuroimaging data from patients with neurodevelopmental disorders caused by genomic copy number variations (CNVs) and gene expression data from healthy subjects. For each of the six investigated disorders, we show that spatial patterns of cortical anatomy changes in youth are correlated with cortical spatial expression of CNV genes in neurotypical adults. By transforming normative bulk-tissue cortical expression data into cell-type expression maps, we link anatomical change maps in each analysed disorder to specific cell classes as well as the CNV-region genes they express. Our findings reveal organizing principles that regulate the mapping of genetic risks onto regional brain changes in neurogenetic disorders. Our findings will enable screening for candidate molecular mechanisms from readily available neuroimaging data. How neurodevelopmental disorder-associated risk genes are translated into spatially patterned brain vulnerabilities is unclear. Here, the authors show that disorder-specific patterns of neuroanatomical changes are aligned to brain expression maps of disease risk genes in healthy subjects. [ABSTRACT FROM AUTHOR]

Purpose: Pexidartinib (PLX3397) is a colony-stimulating factor-1 receptor (CSF-1R) inhibitor under clinical evaluation for potential CNS tumor treatment. This study aims to evaluate plasma pharmacokinetic parameters and estimate CNS penetrance of pexidartinib in a non-human primate (NHP) cerebrospinal fluid (CSF) reservoir model.Methods: Five male rhesus macaques, each with a previously implanted subcutaneous CSF ventricular reservoir and central venous lines, were used. NHPs received a single dose of 40 mg/kg pexidartinib (human equivalent dose of 800 mg/m2), administered orally as 200 mg tablets. Serial paired samples of blood and CSF were collected at 0-8, 24, 48, and 72 h. Pexidartinib concentrations were assayed by Integrated Analytical Solutions, Inc. (Berkeley, CA, USA) using HPLC/MS/MS. Pharmacokinetic (PK) analysis was performed using noncompartmental methods.Results: Samples from four NHPs were evaluable. Average (± SD) plasma PK parameters were as follows: Cmax = 16.50 (± 6.67) μg/mL; Tmax = 5.00 (± 2.58) h; AUClast = 250.25 (± 103.76) h*μg/mL; CL = 0.18 (± 0.10) L/h/kg. In CSF, pexidartinib was either quantifiable (n = 2), with Cmax values of 16.1 and 10.1 ng/mL achieved 2-4 h after plasma Tmax, or undetected at all time points (n = 2, LLOQCSF = 5 ng/mL).Conclusion: Pexidartinib was well-tolerated in NHPs, with no Grade 3 or Grade 4 toxicities. The CSF penetration of pexidartinib after single-dose oral administration to NHPs was limited. [ABSTRACT FROM AUTHOR]

The process of assessing the suitability of reuse of a software component is complex. Indeed, software systems are typically developed as an assembly of existing components. The complexity of the assessment process is due to lack of clarity on how to compare the cost of adaptation of an existing component versus the cost of developing it from scratch. Indeed, often pursuit of reuse can lead to excessive rework and adaptation, or developing suites of components that often get neglected. This paper is an important step towards modelling the complex reuse assessment process. To assess the success factors that can underpin reuse, we analyze the cognitive factors that belie developers' behavior during their decision-making when attempting to reuse. This analysis is the first building block of a broader aim to synthesize a framework to institute activities during the software development lifecycle to support reuse. [ABSTRACT FROM AUTHOR]

Gifted children learn more rapidly and effectively than others, presumably due to neurophysiological differences that affect efficiency in neuronal communication. Identifying the topological features that support its capabilities is relevant to understanding how the brain structure is related to intelligence. We proposed the analysis of the structural covariance network to assess which organizational patterns are characteristic of gifted children. The graph theory was used to analyse topological properties of structural covariance across a group of gifted children. The analysis was focused on measures of brain network integration, such as, participation coefficient and versatility, which quantifies the strength of specific modular affiliation of each regional node. We found that the gifted group network was more integrated (and less segregated) than the control group network. Brain regional nodes in the gifted group network had higher versatility and participation coefficient, indicating greater inter-modular communication mediated by connector hubs with links to many modules. Connector hubs of the networks of both groups were located mainly in association with neocortical areas (which had thicker cortex), with fewer hubs in primary or secondary neocortical areas (which had thinner cortex), as well as a few connector hubs in limbic cortex and insula. In the group of gifted children, a larger proportion of connector hubs were located in association cortex. In conclusion, gifted children have a more integrated and versatile brain network topology. This is compatible with the global workspace theory and other data linking integrative network topology to cognitive performance. [ABSTRACT FROM AUTHOR]

Duplex stainless steel (DSS) UNS S32205 presents high resistance to oxidation, corrosion, and corrosion under stress associated with good mechanical properties, thus being widely used in oil exploration and chemical treatment systems. Due to these characteristics, studies on surface quality are justified in the machining of such materials. In this work, dry machining end-milling tests were performed with positive geometry cutting tools (coated carbide inserts with tip radius of 0.4 mm) with different cutting parameters. Each cutting parameter was evaluated in three levels, combined through Box-Behnken Design of experiments (BBD): cutting speed (30, 45, 60 m/min), feed per tooth (0.05, 0.1, 0.15 mm/tooth), and depth of cut (0.2, 0.4, 0.6 mm). Two surface roughness parameters (Ra and Rz) were measured in the machined surfaces under different cutting combinations. Roughness profiles were analyzed for the highest and lowest measured values of surface roughness, and Abbott-Firestone Curve (AFC) and amplitude-probability distribution (APD) represented its statistical profile. In this way, appropriate combination of cutting parameters for minimum Ra and Rz parameters obtained after finishing end-milling of UNS S32205 were determined, as well as AFC and APD of these values, thus allowing the characterization of the performance of tool-workpiece pair in DSS cutting, resulting in Ra and Rz values of 0.182 and 1.302 μm, respectively. Low surface roughness values were validated using BBD, representation of the statistical profile, and optimization of cutting parameters improved the little bibliographical material in DSS milling. [ABSTRACT FROM AUTHOR]

Background and Objectives: Generalized anxiety disorder (GAD) is a persistent anxiety disorder with a high rate of relapse. While several trials have demonstrated the efficacy of pharmacotherapy for GAD treatment, fewer studies have investigated its efficacy in preventing symptom relapse in long-term treatment. The aim of this study is to evaluate if long-term pharmacotherapy may prevent relapses in GAD patients. Methods: This is a systematic review of the relapse prevention trials with GAD patients. Results: Eight trials were included in this review with 5304 patients in total. All patients showed a higher risk of relapse if treatment was not maintained for at least 6 months after remission, with hazard ratios ranging from 0.12 to 0.58 and mostly moderate effect sizes (0.19-1.06). Conclusion: Long-term pharmacotherapy may prevent symptom relapse in GAD patients. As the relapse rate is very high, the data support the continuation of pharmacotherapy for as long as possible. [ABSTRACT FROM AUTHOR]

One of the most important features of mobile robots is their capability to gather data from areas beyond human reach. This capability has increased the demand for the use of robots undertaking exploration tasks, which has naturally led to the need for efficient methods to process the obtained data. Image mosaicing is a useful tool for obtaining a high-resolution visual representation of a large area that has been explored using optical sensors. In this paper, we present an efficient image mosaicing approach that utilizes submapping methods to obtain a map of a surveyed area with reduced computational effort. The approach uses a modified agglomerative hierarchical clustering method to form submaps according to similarity information obtained through feature descriptor matching, and takes advantage of this submapping to reduce the computation and time costs. Comparative results on real challenging underwater datasets are presented. [ABSTRACT FROM AUTHOR]

This paper proposes a vision-only online mosaicing method for underwater surveys. Our method tackles a common problem in low-cost imaging platforms, where complementary navigation sensors produce imprecise or even missing measurements. Under these circumstances, the success of the optical mapping depends on the continuity of the acquired video stream. However, this continuity cannot be always guaranteed due to the motion blurs or lack of texture, common in underwater scenarios. Such temporal gaps hinder the extraction of reliable motion estimates from visual odometry, and compromise the ability to infer the presence of loops for producing an adequate optical map. Unlike traditional underwater mosaicing methods, our proposal can handle camera trajectories with gaps between time-consecutive images. This is achieved by constructing minimum spanning tree which verifies whether the current topology is connected or not. To do so, we embed a trajectory estimate correction step based on graph theory algorithms. The proposed method was tested with several different underwater image sequences and results were presented to illustrate the performance. [ABSTRACT FROM AUTHOR]

Informal interactions with clients are prone to errors in interpretation and communication which can later result in errors in the ensuing requirements models. Resolving such errors early can prevent rework or the building of a system that is non-compliant with the client's intention. In developing complex systems and highly interactive systems, such as agent oriented systems, those errors in requirement analysis are even more likely. By focussing on the quality of interactions between the future users of the system and the human modellers, this article presents an innovative validation and verification process to support analysis of requirement analysis. We use domain knowledge to validate compliance with the client's intention. Using layered abstractions, we formulate the validation process which is methodology independent. An interactive support tool is implemented to support the developers using the requirement analysis process. The process is conducted iteratively to accommodate the lifecycle defined by most methodologies. The process and the tool are validated and illustrated using two different development exemplars illustrating different domains and different development methodologies. [ABSTRACT FROM AUTHOR]

The suitability for pharmaceutical and cosmetic application of fourteen clay samples, eight raw and six commercialized samples, from Minas Gerais and São Paulo states, Brazil, were evaluated and their mineralogy, chemical and radiological composition were determined. Results indicated that the samples are composed mainly of quartz, kaolinite and feldspar, enriched in AlO and TiO, Cd, Cs, Sb, Se, Th, and U and depleted in SiO, MgO, PO, and Ca. Concentrations found are unlikely to present any harm in topical applications, and all the radiological parameters were below the global average or the established limits. [ABSTRACT FROM AUTHOR]

The brown treesnake ( Boiga irregularis) was accidentally introduced to Guam in the 1940s from the Admiralty Islands. A native of Australia, Papua New Guinea, and the Solomon Islands, the brown treesnake (BTS) continues to threaten the economy and ecology of Guam and is currently the subject of a cooperative program to control snake populations on the island and prevent its spread throughout the Pacific Rim. Delivery of toxic baits is a primary component of population suppression efforts. While many food items tested as baits for toxicant delivery provide relevant food prey cues leading to investigatory behaviors in BTS, only a few items tested in the past two decades have adequately promoted reliable consumption. Chief among them is the dead neonatal mouse (DNM). A series of chemical and bioassays were performed to identify materials with similar sensory qualities as DNM. Among the many items tested in a series of field experiments with free-ranging BTS in Guam, a processed meat product treated with an artificial mouse fat mixture was found to be removed from bait stations at rates greater than previously tested DNM substitutes and approaching removal rates of DNM. Furthermore, the test baits demonstrated excellent durability under field conditions. Further development of this bait offers great potential to satisfy many desirable attributes for BTS baiting operations. [ABSTRACT FROM AUTHOR]