Similar Analysis Research Articles

Altered neural representation of olfactory food reward in the nucleus accumbens after acute stress

Acute stress impairs reward processing. The nucleus accumbens (NAcc) plays an important role in the processing of primary rewards such as food. The present study investigates how acute stress affects the olfactory food reward processing in the NAcc using the representational similarity analysis. Forty-eight participants underwent an olfactory fMRI session following either an acute psychosocial stress (N = 24; stress group) or a control (N = 24; control group). Brain activation was recorded during the anticipatory and the perceptual phases of high-calorie food, low-calorie food, and non-food odor stimuli. Compared to the control group, the stress group rated the high-calorie food odor as significantly more pleasant (p = 0.005). In the NAcc, acute stress significantly reduced the dissimilarity of food and non-food odors in the perceptual phase (p = 0.027) and marginally reduced the dissimilarity of high- and low-calorie foods in the anticipatory phase (p = 0.095). Significant negative correlations were observed between the level of NAcc representational differentiation for high- and low-calorie food odors during perception and the difference in pleasantness ratings between high- and low-calorie food odors (r = -0.40, p = 0.005). These findings suggest that acute stress may impair participants’ ability to discriminate between olfactory food rewards, leading individuals to seek out more palatable foods in stressful situations in order to maintain positive emotions.

EEG as a potential ground truth for the assessment of cognitive state in software development activities: A multimodal imaging study.

Cognitive human error and recent cognitive taxonomy on human error causes of software defects support the intuitive idea that, for instance, mental overload, attention slips, and working memory overload are important human causes for software bugs. In this paper, we approach the EEG as a reliable surrogate to MRI-based reference of the programmer's cognitive state to be used in situations where heavy imaging techniques are infeasible. The idea is to use EEG biomarkers to validate other less intrusive physiological measures, that can be easily recorded by wearable devices and useful in the assessment of the developer's cognitive state during software development tasks. Herein, our EEG study, with the support of fMRI, presents an extensive and systematic analysis by inspecting metrics and extracting relevant information about the most robust features, best EEG channels and the best hemodynamic time delay in the context of software development tasks. From the EEG-fMRI similarity analysis performed, we found significant correlations between a subset of EEG features and the Insula region of the brain, which has been reported as a region highly related to high cognitive tasks, such as software development tasks. We concluded that despite a clear inter-subject variability of the best EEG features and hemodynamic time delay used, the most robust and predominant EEG features, across all the subjects, are related to the Hjorth parameter Activity and Total Power features, from the EEG channels F4, FC4 and C4, and considering in most of the cases a hemodynamic time delay of 4 seconds used on the hemodynamic response function. These findings should be taken into account in future EEG-fMRI studies in the context of software debugging.

Amphibian and reptile diversity in natural landscapes and human-modified habitats of the Sahara Desert of Algeria: A better understanding of biodiversity to improve conservation

The spatial and seasonal variations in amphibian and reptile diversity were studied in different biotopes (lowlands, desert pavements “Reg,” Sabkhas “salt lakes,” date palm groves, wadis, and urban sites) at the Algerian Sahara Desert. No prior research has explored the connection between the distribution of reptiles and amphibians in Algeria’s Sahara and the environmental diversity of biotopes and landscapes. This study aimed to address this significant knowledge gap by investigating the relationships between Saharan habitats and landscapes and their impact on herpetofaunal presence, abundance, and diversity. The diversity of amphibians and reptiles was assessed based on quantitative data of species captures using nonparametric diversity indices, species richness accumulation curves, and similarity analysis. At the Region of Oued Righ (Northern Sahara Desert), we identified 3 amphibians, 19 lizards, and 10 ophidian species. These 32 species (approximately 30% of the Algerian herpetofauna) were classified into 2 orders (Anura and Squamata), 15 families, and 23 different genera. The study area included 8 protected species in Algeria and 9 endemic species to the Mediterranean region, including 1 amphibian and 7 species of reptiles. Acanthodactylus dumerilii was the most abundant species (20.5% of the total), whereas Chalcides ocellatus occurred in 32.9% of specimens. The highest values of species richness were recorded in palm groves with 22 species and Shannon’s diversity index (H’) was 3.5, whereas the lowest values were obtained in Sabkhas (5 species) and urban sites (7 species). The number of individuals experienced significant variations between study biotopes and seasons. Overall, species richness estimators (Chao2 and Jackknife1) revealed that the current survey achieved 90% of inventory completeness. Estimates and interpolations of species richness showed higher values in urban sites, palm groves, desert pavements, and wadis compared to Sabkhas and lowlands where completeness ranged between 90% and 100%. The analysis of similarity indicated low similarity values (<50%) between biotopes studied. The highest similarities were noted between the mesic biotopes (Sabkhas, wadis, and palm groves), the xeric and undisturbed biotopes (desert pavements and lowlands), whereas urban sites showed a distinct herpetofaunal community that was completely different of that recorded in Sabkhas, wadis, and lowlands.

New Quality Evaluation of Qizhi Xiangfu Pills Based on Fingerprint with Chemometric Analysis and Quantitative Analysis of Multi-Components by Single Marker.

Qizhi Xiangfu Pills (QZXFPs) is one of the most commonly used traditional Chinese medicine preparations for the treatment of dysmenorrhea, but the existing quality evaluation standards have certain shortcomings and deficiencies. An effective and scientific quality evaluation method plays a vital role in medication safety. In this study, fingerprint combined with chemometric analysis and quantitative analysis of multi-components by a single marker (QAMS) method was used to comprehensively evaluate the quality of QZXFPs. The fingerprints of 28 batches samples were established and 23 common peaks were distinguished, of which 7 peaks were identified as albiflorin, paeoniflorin, baicalin, ligustilide, cyperotundone, nootkatone and α-cyperone. The content of these seven active ingredients was determined simultaneously by the QAMS method and there was no significantly different between QAMS and the external standard method. Additionally, similarity analysis, hierarchical cluster analysis, principal component analysis and orthogonal partial least squares discrimination analysis were applied for classifying the 28 batches of samples, and to find the main components causing the quality differences between different batches. In conclusion, the established method can comprehensively evaluate the consistency of quality between different batches and provide a reference for formulation quality evaluation to ensure safe and effective application of QZXFPs.

Impact of surgical lung biopsy on lung function and survival in patients with idiopathic pulmonary fibrosis in a multi-centre registry cohort.

Establishing an accurate and timely diagnosis of idiopathic pulmonary fibrosis (IPF) is essential for appropriate management and prognostication. In some cases, surgical lung biopsy (SLB) is performed but carries non-negligible risk. The objective of this retrospective study was to determine if SLB is associated with accelerated lung function decline in patients with IPF using the Canadian Registry for Pulmonary Fibrosis. Linear mixed models and Cox proportional hazards regression models were used to compare decline in forced vital capacity (FVC)%, diffusion capacity of the lung (DLCO%) and risk of death or lung transplantation between SLB and non-SLB patients. Adjustments were made for baseline age, sex, smoking history, antifibrotic use, and lung function. A similar analysis compared lung function changes 12 months pre- and post-SLB. A total of 81 SLB patients and 468 non-SLB patients were included. In the SLB group, the post-biopsy annual FVC% decline was 2.0% (±0.8) in unadjusted, and 2.1% (±0.8) in adjusted models. There was no difference in FVC% decline, DLCO% decline, or time to death or lung transplantation between the two groups, in adjusted or unadjusted models (all p-values >0.07). In the pre-post SLB group, no differences were identified in FVC% decline in unadjusted or adjusted models (p = 0.07 for both). No association between SLB and lung function decline or risk of death or lung transplantation was identified in this multi-centre study of patients with IPF.

Suitability of Polymers for 3D-Printing Laboratory Models for Shaking Table Experiments: Discussion and Indications.

This paper presents a comprehensive assessment of the suitability of seven commercially available polymers for crafting laboratory models designed for dynamic shaking-table tests using 3D-printing technology. The objective was to determine whether 3D-printed polymer models are effective for dynamic assessments of structures. The polymers underwent experimental investigations to assess their material properties, i.e., the elastic modulus, the mass density, and the limit of linear-elastic behaviour. The following methodology was applied to obtain the correct values of elasticity moduli and yield points of the polymers: (1) the uniaxial tensile test, (2) the compression test, and (3) the three-point loading test. The filament density was determined as the ratio of sample mass to its volume. The results indicate substantial variations in stiffness, density, and elasticity limits among them. For the similarity analysis, an existing reinforced concrete chimney 120 m high was chosen as a prototype. A geometric similarity scale of 1:120 for a laboratory mock-up was adopted, and a numerical model of the mock-up was created. The similarity scales were calculated for mock-ups made of each filament. Based on these scales, numerical calculations of natural frequencies and dynamic performance under a strong earthquake were carried out for models made of different polymers. Assessment of the polymers' suitability for laboratory models revealed positive outcomes. The agreement between field experiments, shaking-table tests, and numerical predictions in terms of natural frequencies was observed. Maximum stresses resulting from the earthquake indicated the satisfactory performance of the model below the linear-elastic limit. Despite differences in material properties, the selected polymers were deemed suitable for 3D-printing models for shaking-table tests. However, the discussion raised some important considerations. The upper frequency limit of the shaking-table imposes restrictions on the number of natural frequencies that can be determined. Numerical assessments of natural frequencies are recommended to prevent underestimation and to assess the feasibility of their determination. Additionally, resonance during natural frequency determination may lead to exceeding the linear-elastic limit, affecting filament properties, and making the similarity criteria invalid. Practically, this research contributes insights for planning shaking-table tests, aiding in selecting the most suitable filament and highlighting crucial considerations to ensure reliable and accurate dynamic assessments.

Postoperative Atrioventricular Block in Pediatric Patients: Impact of Congenital Cardiac Malformations and Medications.

Postoperative atrioventricular block may occur after pediatric cardiac surgery. A small proportion of those who develop atrioventricular block will require pacemaker placement. The primary aim of this study was to determine factors associated with postoperative atrioventricular block. Secondary aims included determining factors associated with pacemaker placement in those with atrioventricular block. Data from the PHIS data were utilized to identify patients under 18 years of age who underwent cardiac surgery. Those who did and did not develop atrioventricular block. Univariable analyses and regression analyses were conducted to determine factors associated with postoperative atrioventricular block. Similar analyses were conducted to determine factors associated with pacemaker placement in those with atrioventricular block. A total of 43,716 admissions were identified. Of these, 2093 (5%) developed atrioventricular block and 480 (1% of total admissions) underwent pacemaker placement. Approximately 70% of those with atrioventricular block received steroids but this was not associated with a decrease in pacemaker placement. Risk factors (congenital malformations of the heart, comorbidities, medications) associated with increased risk of atrioventricular block and pacemaker placement were identified. Postoperative atrioventricular block occurred in 5% of pediatric admissions for cardiac surgery. Of these admissions with postoperative atrioventricular block, 23% required pacemaker placement. Isoproterenol and steroids were not associated with a reduction in the likelihood of pacemaker placement.

Establishment of Start Codon Targeted Polymorphism Molecular Markers System and Genetic Diversity Analysis of Fritillaria thunbergii

After years of selective breeding, numerous cultivars of Fritillaria thunbergii have been cultivated in various regions of Zhejiang Province, showing significant genomic and epigenetic differences. Molecular marker loci developed so far are mainly based on non-coding regions of the genome, and their identification efficiency is limited when applied to these cultivars. Therefore, this study used start codon targeted polymorphism molecular marker to detect PCR amplification of 100 Fritillaria thunbergii samples from various sources. The SCoT-PCR reaction system was optimized using a single-factor and orthogonal testing to determine the optimal conditions: DNA concentration of 4.2 ng • μL−1, primer concentration of 0.88 μmol • L−1, dNTP concentration of 0.35 mmol • L−1, Mg2+ concentration of 2.5 mmol • L−1, Supercharm Fidelity enzyme amount of 1.2 U, and total reaction volume of 25 μL. Moreover, 16 effective primers were identified, including SCoT1, SCoT2, SCoT3, SCoT7, SCoT11, SCoT12, SCoT14, SCoT17, SCoT19, SCoT23, SCoT25, SCoT26, SCoT29, SCoT35, and SCoT37. The annealing temperature for each primer was determined. Among them, SCoT14, SCoT25, SCoT29, SCoT35, and SCoT41 were specific for identifying six main cultivars: “Zhebei 1”, “Zhebei 2”, “Zhebei 3”, “Xuansanzi”, “Sanzi”, and “Duozi”. SCoT7, SCoT14, and SCoT35 were useful in tracking mutations in progeny of Zhebei 3 after radiation treatment, while SCoT29 could distinguish Zhebei 1 from Chunan. In addition, cluster analysis was conducted to simulate the genetic relationship between different cultivars, demonstrating that genetic similarity analysis is practically significant for predicting genetic correlation among different cultivars. The results not only improve the identification ability of Fritillaria thunbergii cultivars, but also help objectively evaluate their genetic stability and environmental adaptability. These achievements provide important scientific evidence for the ecological protection and utilization of germplasm resources of Fritillaria thunbergii and serve as a reference for exploring genetic diversity and evolution of traditional Chinese medicine.

Representational Dissimilarity of Faces and Places during a Working Memory Task is Associated with Subsequent Recognition Memory during Development.

Nearly 50 years of research has focused on faces as a special visual category, especially during development. Yet it remains unclear how spatial patterns of neural similarity of faces and places relate to how information processing supports subsequent recognition of items from these categories. The current study uses representational similarity analysis and functional imaging data from 9- and 10-year-old youth during an emotional n-back task from the Adolescent Brain and Cognitive Development Study 3.0 data release to relate spatial patterns of neural similarity during working memory to subsequent out-of-scanner performance on a recognition memory task. Specifically, we examine how similarities in representations within face categories (neutral, happy, and fearful faces) and representations between visual categories (faces and places) relate to subsequent recognition memory of these visual categories. Although working memory performance was higher for faces than places, subsequent recognition memory was greater for places than faces. Representational similarity analysis revealed category-specific patterns in face-and place-sensitive brain regions (fusiform gyrus, parahippocampal gyrus) compared with a nonsensitive visual region (pericalcarine cortex). Similarity within face categories and dissimilarity between face and place categories in the parahippocampus was related to better recognition of places from the n-back task. Conversely, in the fusiform, similarity within face categories and their relative dissimilarity from places was associated with better recognition of new faces, but not old faces. These findings highlight how the representational distinctiveness of visual categories influence what information is subsequently prioritized in recognition memory during development.

Exploiting Natural Language Processing to Unveil Topics and Trends of Traumatic Brain Injury Research.

Traumatic brain injury (TBI) has evolved from a topic of relative obscurity to one of widespread scientific and lay interest. The scope and focus of TBI research have shifted, and research trends have changed in response to public and scientific interest. This study has two primary goals: first, to identify the predominant themes in TBI research; and second, to delineate "hot" and "cold" areas of interest by evaluating the current popularity or decline of these topics. Hot topics may be dwarfed in absolute numbers by other, larger TBI research areas but are rapidly gaining interest. Likewise, cold topics may present opportunities for researchers to revisit unanswered questions. We utilized BERTopic, an advanced natural language processing (NLP)-based technique, to analyze TBI research articles published since 1990. This approach facilitated the identification of key topics by extracting sets of distinctive keywords representative of each article's core themes. Using these topics' probabilities, we trained linear regression models to detect trends over time, recognizing topics that were gaining (hot) or losing (cold) relevance. Additionally, we conducted a specific analysis focusing on the trends observed in TBI research in the current decade (the 2020s). Our topic modeling analysis categorized 42,422 articles into 27 distinct topics. The 10 most frequently occurring topics were: "Rehabilitation," "Molecular Mechanisms of TBI," "Concussion," "Repetitive Head Impacts," "Surgical Interventions," "Biomarkers," "Intracranial Pressure," "Posttraumatic Neurodegeneration," "Chronic Traumatic Encephalopathy," and "Blast Induced TBI," while our trend analysis indicated that the hottest topics of the current decade were "Genomics," "Sex Hormones," and "Diffusion Tensor Imaging," while the cooling topics were "Posttraumatic Sleep," "Sensory Functions," and "Hyperosmolar Therapies." This study highlights the dynamic nature of TBI research and underscores the shifting emphasis within the field. The findings from our analysis can aid in the identification of emerging topics of interest and areas where there is little new research reported. By utilizing NLP to effectively synthesize and analyze an extensive collection of TBI-related scholarly literature, we demonstrate the potential of machine learning techniques in understanding and guiding future research prospects. This approach sets the stage for similar analyses in other medical disciplines, offering profound insights and opportunities for further exploration.

The genome sequences of lytic Pseudomonas aeruginosa bacteriophages BL1, BL2, and BL3 isolated from the environment.

We isolated three environmental phages that infect Pseudomonas aeruginosa PAO1, an opportunistic pathogen, from Playa Lakes in Lubbock, TX. We report the genome sequences of isolated lytic bacteriophages BL1, BL2, and BL3. Sequence similarity analysis revealed that the viruses belonged to an unclassified species in the genus Pbunavirus within Caudoviricetes.

Contouring practices and artefact management within a synthetic CT-based radiotherapy workflow for the central nervous system

BackgroundThe incorporation of magnetic resonance (MR) imaging in radiotherapy (RT) workflows improves contouring precision, yet it introduces geometrical uncertainties when registered with computed tomography (CT) scans. Synthetic CT (sCT) images could minimize these uncertainties and streamline the RT workflow. This study aims to compare the contouring capabilities of sCT images with conventional CT-based/MR-assisted RT workflows, with an emphasis on managing artefacts caused by surgical fixation devices (SFDs).MethodsThe study comprised a commissioning cohort of 100 patients with cranial tumors treated using a conventional CT-based/MR-assisted RT workflow and a validation cohort of 30 patients with grade IV glioblastomas treated using an MR-only workflow. A CE-marked artificial-intelligence-based sCT product was utilized. The delineation accuracy comparison was performed using dice similarity coefficient (DSC) and average Hausdorff distance (AHD). Artefacts within the commissioning cohort were visually inspected, classified and an estimation of thickness was derived using Hausdorff distance (HD). For the validation cohort, boolean operators were used to extract artefact volumes adjacent to the target and contrasted to the planning treatment volume.ResultsThe combination of high DSC (0.94) and low AHD (0.04 mm) indicates equal target delineation capacity between sCT images and conventional CT scans. However, the results for organs at risk delineation were less consistent, likely because of voxel size differences between sCT images and CT scans and absence of standardized delineation routines. Artefacts observed in sCT images appeared as enhancements of cranial bone. When close to the target, they could affect its definition. Therefore, in the validation cohort the clinical target volume (CTV) was expanded towards the bone by 3.5 mm, as estimated by HD analysis. Subsequent analysis on cone-beam CT scans showed that the CTV adjustment was enough to provide acceptable target coverage.ConclusionThe tested sCT product performed on par with conventional CT in terms of contouring capability. Additionally, this study provides both the first comprehensive classification of metal artefacts on a sCT product and a novel method to assess the clinical impact of artefacts caused by SFDs on target delineation. This methodology encourages similar analysis for other sCT products.

Nurses’ Social Representations of Men’s Sexual Health Care Access: Preliminary Results

Background: Men’s access to sexual health care is influenced by the nurses’ symbolic universes, translated into maps of signification and normative idealization that structure their practices. Aim: The aim of the study was to analyze nurses’ social representations of men’s sexual health, considering the barriers and possibilities in accessing health care. Methods: Descriptive study with qualitative approach. Data were collected through an online focus group with 9 Portuguese nurses. Data were subjected to lexicographic analysis with the support of the interface IRaMuTeQ-R. Results: 269 text segments were analyzed, retaining 84.86% of the total in 4 classes: interactions between professionals and men, therapeutic itineraries, “talking” about sexual health, and men’s access to sexual health care. Similarity analysis led to 3 central cores: problem, saying, and patient. Conclusions: The training of professionals in men’s sexual health to demystify stereotypes about masculinity is fundamental. At the organizational level, it is necessary to analyze the possibilities of access and its visibility in electronic records and rethink the planning and provision of primary and differentiated care.

Analysis and study of the mechanism of narcotic addiction and withdrawal

Narcotic drugs refer to drugs that have anesthetic effects on the central nervous system, and they easily produce physical dependence and mental dependence and can be addictive due to continuous use, abuse or unreasonable use. In this paper, bioinformatics and data analysis and mining techniques were used to analyze the methylation differences in transcriptional and clinical data of narcotic addiction in public databases, to explore the mechanism of narcotic addiction, and to mine some norepinephrine drugs. This study confirmed the possibility of using norepinephrine as an auxiliary drug for drug addiction rehabilitation. In addition, we also conducted a similar analysis on the addiction of three drugs. The results showed that the differences in the body caused by the ingestion of opiates and cocaine were significantly greater than those caused by the ingestion of methamphetamine.

Dissimilarities of neural representations of extinction trials are associated with extinction learning performance and renewal level.

Renewal of extinguished responses is associated with higher activity in specific extinction-relevant brain regions, i.e., hippocampus (HC), inferior frontal gyrus (IFG), and ventromedial PFC (vmPFC). HC is involved in processing of context information, while IFG and vmPFC use such context information for selecting and deciding among competing response options. However, it is as yet unknown to what extent trials with changed versus unchanged outcome, or extinction trials that evoke renewal (i.e., extinction context differs from acquisition and test context: ABA trials) and trials that do not (i.e., same context in all phases: AAA trials) are represented differentially in extinction-relevant brain regions. In this study, we applied representational similarity analysis (RSA) to determine differences in neural representations of these trial types and their relationship to extinction error rates and renewal level. Overall, individuals with renewal (REN) and those without (NoREN) did not differ significantly in their discrimination levels between ABA and AAA extinction trials, with the exception of right posterior HC, where REN exhibited more pronounced context-related discrimination. In addition, higher dissimilarity of representations in bilateral posterior HC, as well as in several IFG regions, during extinction learning was linked to lower ABA renewal rates. Both REN and NoREN benefitted from prediction error feedback from ABA extinction errors for context- and outcome-related discrimination of trials in IFG, vmPFC, and HC, but only the NoREN group also benefitted from error feedback from AAA extinction errors. Thus, while in both groups the presence of a novel context supported formation of distinct representations, only in NoREN the expectancy violation of the surprising change of outcome alone had a similar effect. In addition, only in NoREN context-related discrimination was linked to error feedback in vmPFC. In summary, the findings show that context- and outcome-related discrimination of trials in HC, vmPFC, and IFG is linked to extinction learning errors, regardless of renewal propensity, and at the same time point towards differential context processing strategies in REN and NoREN. Moreover, better discrimination of context-related trials during extinction learning promotes less renewal during extinction recall, suggesting that renewal may be related to suboptimal context-related trial discrimination.

Attention-based speech feature transfer between speakers.

In this study, we propose a simple yet effective method for incorporating the source speaker's characteristics in the target speaker's speech. This allows our model to generate the speech of the target speaker with the style of the source speaker. To achieve this, we focus on the attention model within the speech synthesis model, which learns various speaker features such as spectrogram, pitch, intensity, formant, pulse, and voice breaks. The model is trained separately using datasets specific to the source and target speakers. Subsequently, we replace the attention weights learned from the source speaker's dataset with the attention weights from the target speaker's model. Finally, by providing new input texts to the target model, we generate the speech of the target speaker with the styles of the source speaker. We validate the effectiveness of our model through similarity analysis utilizing five evaluation metrics and showcase real-world examples.

Assessment of microwave drying for rapid and convenient analysis of medicinal plants for quality assurance.

The safety and quality of many medicinally important herbs are compromised since farmers and small organizations are involved in the cultivation, aggregation, and primary processing of these herbs. Such organizations often lack adequate quality control facilities. To improve the safety and quality of herbal products, simple, rapid, and affordable quality control systems are required. The aim of this study was to assess the suitability of microwave oven-drying for moisture content (MC) determination and sample preparation of herbs in small organizations. Microwave oven-drying (720 W) and convective oven-drying at 105°C for MC determination were compared. The effects of three different drying methods (microwave oven-drying, low-temperature convective drying, and freeze-drying) on in vitro antioxidant and polyphenol oxidase (PPO) activity were determined, similarity analysis was conducted using HPLC signature spectra, and validation was performed with LC-MS focusing on one herb. Microwave oven-drying at 720 W significantly reduced the drying time (from hours to minutes), whereas the spatial variationof temperature in convective ovens set at 105°C can cause about 10% underestimation of MC. Microwave oven-dryingshowed similar macro-properties like freeze-drying and higher extractability (10%-20%) and in vitro antioxidant capacity (33%-66%) and lower PPO activity compared to low-temperature convective drying. HPLC signature spectra revealed strongsimilarity ofsoluble components between freeze-dried and microwave oven-dried herbs. LC-MS analysis demonstrated more common compounds between freeze-driedand microwave oven-driedCentella asiatica extracts, whereas convective tray-dried samples had fewer compounds common with samples obtained by freeze-drying or microwave oven-drying. Microwave oven-drying is rapid (tens of min) and shows small batch-to-batch variation compared to oven-drying at 105°C. The in vitro antioxidant assays and signature spectra can be used for assessing the source and purity or quality of a specific herb variety.

Regional-Scale Assessment of Burn Scar Mapping in Southwestern Amazonia Using Burned Area Products and CBERS/WFI Data Cubes

Fires are one of the main sources of disturbance in fire-sensitive ecosystems such as the Amazon. Any attempt to characterize their impacts and establish actions aimed at combating these events presupposes the correct identification of the affected areas. However, accurate mapping of burned areas in humid tropical forest regions remains a challenging task. In this paper, we evaluate the performance of four operational BA products (MCD64A1, Fire_cci, GABAM and MapBiomas Fogo) on a regional scale in the southwestern Amazon and propose a new approach to BA mapping using fraction images extracted from data cubes of the Brazilian orbital sensors CBERS-4/WFI and CBERS-4A/WFI. The methodology for detecting burned areas consisted of applying the Linear Spectral Mixture Model to the images from the CBERS-4/WFI and CBERS-4A/WFI data cubes to generate shadow fraction images, which were then segmented and classified using the ISOSEG non-supervised algorithm. Regression and similarity analyses based on regular grid cells were carried out to compare the BA mappings. The results showed large discrepancies between the mappings in terms of total area burned, land use and land cover affected (forest and non-forest) and spatial location of the burned area. The global products MCD64A1, GABAM and Fire_cci tended to underestimate the area burned in the region, with Fire_cci underestimating BA by 88%, while the regional product MapBiomas Fogo was the closest to the reference, underestimating by only 7%. The burned area estimated by the method proposed in this work (337.5 km2) was 12% higher than the reference and showed a small difference in relation to the MapBiomas Fogo product (18% more BA). These differences can be explained by the different datasets and methods used to detect burned areas. The adoption of global products in regional studies can be critical in underestimating the total area burned in sensitive regions. Our study highlights the need to develop approaches aimed at improving the accuracy of current global products, and the development of regional burned area products may be more suitable for this purpose. Our proposed approach based on WFI data cubes has shown high potential for generating more accurate regional burned area maps, which can refine BA estimates in the Amazon.

Detecting Moral Features in TV Series with a Transformer Architecture through Dictionary-Based Word Embedding

Moral features are essential components of TV series, helping the audience to engage with the story, exploring themes beyond sheer entertainment, reflecting current social issues, and leaving a long-lasting impact on the viewers. Their presence shows through the language employed in the plot description. Their detection helps regarding understanding the series writers’ underlying message. In this paper, we propose an approach to detect moral features in TV series. We rely on the Moral Foundations Theory (MFT) framework to classify moral features and use the associated MFT dictionary to identify the words expressing those features. Our approach combines that dictionary with word embedding and similarity analysis through a deep learning SBERT (Sentence-Bidirectional Encoder Representations from Transformers) architecture to quantify the comparative prominence of moral features. We validate the approach by applying it to the definition of the MFT moral feature labels as appearing in general authoritative dictionaries. We apply our technique to the summaries of a selection of TV series representative of several genres and relate the results to the actual content of each series, showing the consistency of results.

Brain-like illusion produced by Skye's Oblique Grating in deep neural networks.

The analogy between the brain and deep neural networks (DNNs) has sparked interest in neuroscience. Although DNNs have limitations, they remain valuable for modeling specific brain characteristics. This study used Skye's Oblique Grating illusion to assess DNNs' relevance to brain neural networks. We collected data on human perceptual responses to a series of visual illusions. This data was then used to assess how DNN responses to these illusions paralleled or differed from human behavior. We performed two analyses:(1) We trained DNNs to perform horizontal vs. non-horizontal classification on images with bars tilted different degrees (non-illusory images) and tested them on images with horizontal bars with different illusory strengths measured by human behavior (illusory images), finding that DNNs showed human-like illusions; (2) We performed representational similarity analysis to assess whether illusory representation existed in different layers within DNNs, finding that DNNs showed illusion-like responses to illusory images. The representational similarity between real tilted images and illusory images was calculated, which showed the highest values in the early layers and decreased layer-by-layer. Our findings suggest that DNNs could serve as potential models for explaining the mechanism of visual illusions in human brain, particularly those that may originate in early visual areas like the primary visual cortex (V1). While promising, further research is necessary to understand the nuanced differences between DNNs and human visual pathways.