Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationships between Human Disturbance and Wildlife Land Use in Urban Habitat Fragments

Abstract: Habitat remnants in urbanized areas typically conserve biodiversity and serve the recreation and urban open‐space needs of human populations. Nevertheless, these goals can be in conflict if human activity negatively affects wildlife. Hence, when considering habitat remnants as conservation refuges it is crucial to understand how human activities and land uses affect wildlife use of those and adjacent areas. We used tracking data (animal tracks and den or bed sites) on 10 animal species and information on human activity and environmental factors associated with anthropogenic disturbance in 12 habitat fragments across San Diego County, California, to examine the relationships among habitat fragment characteristics, human activity, and wildlife presence. There were no significant correlations of species presence and abundance with percent plant cover for all species or with different land‐use intensities for all species, except the opossum (Didelphis virginiana), which preferred areas with intensive development. Woodrats (Neotoma spp.) and cougars (Puma concolor) were associated significantly and positively and significantly and negatively, respectively, with the presence and prominence of utilities. Woodrats were also negatively associated with the presence of horses. Raccoons (Procyon lotor) and coyotes (Canis latrans) were associated significantly and negatively and significantly and positively, respectively, with plant bulk and permanence. Cougars and gray foxes (Urocyon cinereoargenteus) were negatively associated with the presence of roads. Roadrunners (Geococcyx californianus) were positively associated with litter. The only species that had no significant correlations with any of the environmental variables were black‐tailed jackrabbits (Lepus californicus) and mule deer (Odocoileus hemionus). Bobcat tracks were observed more often than gray foxes in the study area and bobcats correlated significantly only with water availability, contrasting with results from other studies. Our results appear to indicate that maintenance of habitat fragments in urban areas is of conservation benefit to some animal species, despite human activity and disturbance, as long as the fragments are large.
Effects of two selective 5-HT2C receptor-acting compounds into the ventral hippocampus of rats exposed to the elevated plus-maze

This study investigated the effects of two selective serotonin2C (5-hydroxytryptamine, 5-HT2C) receptor-acting compounds into the ventral hippocampus (VH) of rats exposed to the elevated plus-maze (EPM). In the first experiment, rats were exposed to the EPM 10 min following VH infusions of either vehicle or the selective 5-HT2C-receptor agonist RO-60-0175 (0.3, 1.0, 3.0 and 10.0µg). In addition to conventional parameters of open arm exploration (i.e. percentages of open arm entries and of time spent in these arms), risk assessmentrelated behaviors were recorded as anxiety-like measures in EPM scoring. RO-60-0175 selectively decreased open arm exploration at the dose of 1.0 µg, while inducing locomotor-suppressant effects at the two highest doses. In the second experiment, VH infusions of the selective 5-HT2C antagonist RS 102221 (0.75, 1.25 and 2.5 µg) did not affect open arm exploration, while reducing risk assessment in the closed ones. This behavioral profile of risk assessment is suggestive of an anxiolytic-like action. These results further corroborate our previous findings showing that VH 5-HT2C receptor activation elicits anxiogenic-like and locomotor-suppressant effects, and suggest that the selective blockade of this receptor is accompanied by an anxiolytic-like action as detected by ethologically derived measures in the EPM.
Classification of autism spectrum disorder from resting-state fMRI with mutual connectivity analysis

In this study, we investigate if differences in interaction between different brain regions for subjects with autism spectrum disorder (ASD) and healthy controls can be captured using resting-state fMRI. To this end, we investigate the use of mutual connectivity analysis with Local Models (MCA-LM), which estimates nonlinear measures of interaction between pairs of time-series in terms of cross-predictability. These pairwise measures provide a high-dimensional representation of connectivity profiles for subjects and are used as features for classification. Subsequently, we perform feature selection, reducing the dimension of the input space with the Kendall’s τ coefficient method. The Random Forests (RF) and AdaBoost classifiers are used. Performing machine learning on functional connectivity measures is commonly known as multi-voxel pattern analysis (MVPA). Traditionally, measures of functional connectivity are obtained with cross-correlation. Hence, as a metric to evaluate MCA-LM against, we also investigate classification performance with cross-correlation. The high area under receiver operating curve (AUC) and accuracy values for 100 different train/test separations across both classifiers using MCA-LM (mean AUC ranges between 0.78 - 0.85 and mean accuracy between 0.7 - 0.81) compared with standard MVPA analysis using cross-correlation between fMRI time-series (mean AUC ranges between 0.54 - 0.6 and mean accuracy between 0.50 - 0.57), across all the number of features selected demonstrates that such a nonlinear measure may be better suited at extracting information from the time-series data and has potential for the development of novel neuro-imaging biomarkers for ASD.
Spectral analysis of data

Experimental evidence suggests that spectral techniques are valuable for a wide range of applications. A partial list of such applications include (i) semantic analysis of documents used to cluster documents into areas of interest, (ii) collaborative filtering --- the reconstruction of missing data items, and (iii) determining the relative importance of documents based on citation/link structure. Intuitive arguments can explain some of the phenomena that has been observed but little theoretical study has been done. In this paper we present a model for framing data mining tasks and a unified approach to solving the resulting data mining problems using spectral analysis. These results give strong justification to the use of spectral techniques for latent semantic indexing, collaborative filtering, and web site ranking.
Community Finding : Partitioning Considered Harmful

Considering a clique as a conservative definition of community structure, we examine how partitioning algorithms interact with cliques. We show that on a wide range of empirical networks, from different domains, significant numbers of cliques are split across different partitions by popular algorithms. We examine the largest connected component of the subgraph formed by retaining only edges in cliques, and apply partitioning strategies that explicitly minimise the number of cliques split. We conclude that, due to the connectedness of many networks, any partitioning community finding algorithm must fail to return at least some significant structure. Moreover, contrary to traditional intuition, strong ties and cliques frequently do cross community boundaries.
Spectral-Spatial Attention Networks for Hyperspectral Image Classification

Many deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN), have been successfully applied to extracting deep features for hyperspectral tasks. Hyperspectral image classification allows distinguishing the characterization of land covers by utilizing their abundant information. Motivated by the attention mechanism of the human visual system, in this study, we propose a spectral-spatial attention network for hyperspectral image classification. In our method, RNN with attention can learn inner spectral correlations within a continuous spectrum, while CNN with attention is designed to focus on saliency features and spatial relevance between neighboring pixels in the spatial dimension. Experimental results demonstrate that our method can fully utilize the spectral and spatial information to obtain competitive performance.
Distal‐less homeobox genes of insects and spiders: genomic organization, function, regulation and evolution

The Distal‐less (Dll) genes are homeodomain transcription factors that are present in most Metazoa and in representatives of all investigated arthropod groups. In Drosophila, the best studied insect, Dll plays an essential role in forming the proximodistal axis of the legs, antennae and analia, and in specifying antennal identity. The initiation of Dll expression in clusters of cells in mid‐lateral regions of the Drosophila embryo represents the earliest genetic marker of limbs. Dll genes are involved in the development of the peripheral nervous system and sensitive organs, and they also function as master regulators of black pigmentation in some insect lineages. Here we analyze the complete genomes of six insects, the nematode Caenorhabditis elegans and Homo sapiens, as well as multiple Dll sequences available in databases in order to examine the structure and protein features of these genes. We also review the function, expression, regulation and evolution of arthropod Dll genes with emphasis on insects and spiders.
Dosage Effects of BDNF Val66Met Polymorphism on Cortical Surface Area and Functional Connectivity

The single nucleotide polymorphism (SNP) that leads to a valine-to-methionine substitution at codon 66 (Val66Met) in BDNF is correlated with differences in cognitive and memory functions, as well as with several neurological and psychiatric disorders. MRI studies have already shown that this genetic variant contributes to changes in cortical thickness and volume, but whether the Val66Met polymorphism affects the cortical surface area of healthy subjects remains unclear. Here, we used multimodal MRI to study whether this polymorphism would affect the cortical morphology and resting-state functional connectivity of a large sample of healthy Han Chinese human subjects. An SNP-wise general linear model analysis revealed a “dosage effect” of the Met allele, specifically a stepwise increase in cortical surface area of the right anterior insular cortex with increasing numbers of the Met allele. Moreover, we found enhanced functional connectivity between the anterior insular and the dorsolateral prefrontal cortices that was linked with the dosage of the Met allele. In conclusion, these data demonstrated a “dosage effect” of BDNF Val66Met on normal cortical structure and function, suggesting a new path for exploring the mechanisms underlying the effects of genotype on cognition.
Metric Accuracy of Digital Elevation Models from WorldView-3 Stereo-Pairs in Urban Areas

WorldView-3 satellite is providing images with an unprecedented combination of high spatial and spectral resolution. The stereo capabilities and the very high resolution of the panchromatic band (0.31 m) have been fostering new applications in urban areas, where the complexity of the morphology requires a higher level of detail. The present technical note aims to test the accuracy of digital elevation models that can be obtained by WorldView-3 stereo-pairs in these particular contexts, with an operational state-of-the-art algorithm. Validation is performed using check points and existing models of the area (from LiDAR data and oblique aerial images). The experiments, conducted over the city of Bologna (Italy) with six images, proved that roof surfaces and open spaces can be reconstructed with an average error of 1–2 pixels, but severe discrepancies frequently occur in narrow roads and urban canyons (up to several metres in average). The level of completeness achievable with only one pair is extremely variable (ranging from 50% to 90%), due to the combined effect of the geometry of acquisition and the specific urban texture. Better results can be obtained by using more than one pair. Furthermore, smaller convergence angles can be beneficial for the reconstruction of specific urban structures, such as soaring towers.
Calibration of Normalised Ces Production Functions in Dynamic Models

Normalising CES production functions in the calibration of basic dynamic models allows to choose technology parameters in an economically plausible way. When variations in the elasticity of substitution are considered, normalisation is necessary in order to exclude arbitrary effects. As an illustration, the effect of the elasticity of substitution on the speed of convergence in the Ramsey model is computed with different normalisations.
Radiometric Inter-Consistency of VIIRS DNB on Suomi NPP and NOAA-20 from Observations of Reflected Lunar Lights over Deep Convective Clouds

The Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) is capable of observing reflected lunar radiances at night with its high gain stage (HGS), and the radiometric calibration is traceable to the sun through gain transfer from the low gain stage (LGS) calibrated near the terminator with the solar diffuser. Meanwhile, deep convective clouds (DCC) are known to have a stable reflectance in the visible spectral range. Therefore, the reflected lunar radiance at night from the DCC provides a unique dataset for the inter-calibration of VIIRS DNB on different satellites such as Suomi National Polar-orbiting Partnership (NPP) and NOAA-20, as well as quantifying the lunar radiance as a function of lunar phase angle. This study demonstrates a methodology for comparing nighttime Suomi NPP and NOAA-20 VIIRS DNB measured DCC reflected lunar radiance at various phase angles using data from July 2018 to March 2019 with an 86 second sampling interval and comparing Suomi NPP VIIRS DNB measured lunar radiances with those from lunar model predictions. The result shows good consistency between these two instruments on the two satellites, although a low bias in the NOAA-20 VIIRS DNB of ~5% is found. Also, observed lunar radiance from VIIRS DNB on Suomi NPP is found to be consistent with model predictions within 3% ± 5% (1σ) for a large range of lunar phase angles. However, discrepancies are significant near full moon, due to lunar opposition effects, and limitations of the lunar models. This study is useful not only for monitoring the DNB calibration stability and consistency across satellites, but also may help validate lunar models independently.
Stimulight: Exploring Social Interaction to Reduce Physical Inactivity among Office Workers

Prolonged sitting at the workplace is a growing public health concern. In this paper, we propose the activity-focused design framework which provides an overview of recent work in HCI to stimulate physcial activity or to reduce sedentary behavior. Next, based on this framework, we present Stimulight, an intelligent system designed to explore the effect of providing personal and/or social feedback on the activity pattern of office workers. To test the intuitiveness of the feedback modalities of our design, three different feedback conditions were explored in a lab study with 61 participants. Our results show a positive effect of visualizing and sharing physical activity patterns with co-workers. Based on our findings, we present design implications and offer perspectives for future work on how to use social feedback mechanisms to encourage social interaction in the workplace to enhance physically active behavior among office workers.
Accurate Measurement of Tropical Forest Canopy Heights and Aboveground Carbon Using Structure From Motion

Unmanned aerial vehicles are increasingly used to monitor forests. Three-dimensional models of tropical rainforest canopies can be constructed from overlapping photos using Structure from Motion (SfM), but it is often impossible to map the ground elevation directly from such data because canopy gaps are rare in rainforests. Without knowledge of the terrain elevation, it is, thus, difficult to accurately measure the canopy height or forest properties, including the recovery stage and aboveground carbon density. Working in an Indonesian ecosystem restoration landscape, we assessed how well SfM derived the estimates of the canopy height and aboveground carbon density compared with those from an airborne laser scanning (also known as LiDAR) benchmark. SfM systematically underestimated the canopy height with a mean bias of approximately 5 m. The linear models suggested that the bias increased quadratically with the top-of-canopy height for short, even-aged, stands but linearly for tall, structurally complex canopies (>10 m). The predictions based on the simple linear model were closely correlated to the field-measured heights when the approach was applied to an independent survey in a different location ( R 2 = 67% and RMSE = 1.85 m), but a negative bias of 0.89 m remained, suggesting the need to refine the model parameters with additional training data. Models that included the metrics of canopy complexity were less biased but with a reduced R 2 . The inclusion of ground control points (GCPs) was found to be important in accurately registering SfM measurements in space, which is essential if the survey requirement is to produce small-scale restoration interventions or to track changes through time. However, at the scale of several hectares, the top-of-canopy height and above-ground carbon density estimates from SfM and LiDAR were very similar even without GCPs. The ability to produce accurate top-of-canopy height and carbon stock measurements from SfM is game changing for forest managers and restoration practitioners, providing the means to make rapid, low-cost surveys over hundreds of hectares without the need for LiDAR.
Magmatic underplating of crust beneath the Laccadive Island, NW Indian Ocean

SUMMARY We investigate the crust and uppermost mantle velocity structure beneath the Laccadive Island through the inversion of teleseismic receiver functions following the neighbourhood algorithm. The velocity structure suggests that the 16-km thick-oceanic crust is underplated by 8-km thick high-velocity layer (Vs ∼ 4.25–4.4 km s −1 ; Vp ∼ 7.35–7.6 km s −1 ). The uppermost mantle shear velocity is ∼4.6 km s −1 (Vp ∼ 8.18 km s −1 ). The Moho at 24 km is possibly formed due to underplating of mantle-derived picritic melt at the base of oceanic crust produced during the interaction of the Indian plate with the Reunion hotspot. Continuity of crustal-underplated material beneath the Laccadive could be traced to the Laxmi Ridge in the north and to the Reunion Island in the south, suggesting this to be possible trace of the Reunion hotspot.
Let Us Say What We Mean: Towards Operational Definitions for Techno-Spirituality Research

Recent years have seen a dramatic increase in HCI research on the use of technology in spiritual practices and environments. Some of these works cover spiritual/transcendent experiences associated with these contexts, but strikingly few of them describe in any way the experiences they studied or aimed to support, let alone give definitions of the terms they use for those experiences. Even fewer papers cite any literature on the relevant experiences. We have to ask: How do the authors understand the experiences their work is aiming to observe, invite, or support? How do they know when and whether they have observed, invited, or supported the kinds of experiences they target? How do they know what they are studying? This paper discusses the presence and absence of definitions of terms for spiritual/transcendent experiences in HCI research, and of citations of relevant literature. It speculates about possible reasons for the oversight, proposes some definitions aimed at filling the gap, and suggests an approach to operationalizing some of the proposed definitions.
Should an Agent Be Ignoring It?: A Study of Verbal Abuse Types and Conversational Agents' Response Styles

Verbal abuse is a hostile form of communication ill-intended to harm the other person. With a plethora of AI solutions around, the other person being targeted may be a conversational agent. In this study, involving 3 verbal abuse types (Insult, Threat, Swearing) and 3 response styles (Avoidance, Empathy, Counterattacking), we examine whether a conversational agent's response style under varying abuse types influences those emotions found to mitigate people's aggressive behaviors. Sixty-four participants, assigned to one of the abuse type conditions, interacted with the three conversational agents in turn and reported their feelings about guiltiness, anger, and shame after each session. Our study results show that, regardless of the abuse type, the agent's response style has a significant effect on user emotions. Participants were less angry and more guilty with the empathetic agent than the other two agents. Our study findings have direct implications for the design of conversational agents.
Dual Methylation Pathways in Lignin Biosynthesis

Caffeoyl–coenzyme A (CoA) O-methyltransferase (CCoAOMT) has been proposed to be involved in an alternative methylation pathway of lignin biosynthesis. However, no direct evidence has been available to confirm that CCoAOMT is essential for lignin biosynthesis. To understand further the methylation steps in lignin biosynthesis, we used an antisense approach to alter O-methyltransferase (OMT) gene expression and investigated the consequences of this alteration. We generated transgenic tobacco plants with a substantial reduction in CCoAOMT as well as plants with a simultaneous reduction in both CCoAOMT and caffeic acid O-methyltransferase (CAOMT). Lignin analysis showed that the reduction in CCoAOMT alone resulted in a dramatic decrease in lignin content. The reduction in CCoAOMT also led to a dramatic alteration in lignin composition. Both guaiacyl lignin and syringyl lignin were reduced in the transgenic plants. However, guaiacyl lignin was preferentially reduced, which resulted in an increase in the S/G (syringl/guaiacyl) ratio. We have also analyzed lignin content and composition in transgenic plants having a simultaneous reduction in both CCoAOMT and CAOMT. The reduction in both OMTs resulted in a further decrease in total lignin content. This is in sharp contrast to the effect that resulted from the reduction in CAOMT alone, which only decreased the syringl lignin unit without a reduction in overall lignin content. These results unequivocally demonstrate that methylation reactions in lignin biosynthesis are catalyzed by both CCoAOMT and CAOMT.
Synthesis of Leaf-on and Leaf-off Unmanned Aerial Vehicle (UAV) Stereo Imagery for the Inventory of Aboveground Biomass of Deciduous Forests

Applications of stereo imagery acquired by cameras onboard unmanned aerial vehicles (UAVs) as practical forest inventory tools are hindered by the unavailability of ground surface elevation. It is still a challenging issue to remove the elevation of ground surface in leaf-on stereo imagery to extract forest canopy height without the help of lidar data. This study proposed a method for the extraction of forest canopy height through the synthesis of UAV stereo imagery of leaf-on and leaf-off, and further demonstrated that the extracted forest canopy height could be used for the inventory of deciduous forest aboveground biomass (AGB). The points cloud of the leaf-on and leaf-off stereo imagery was firstly extracted by an algorithm of structure from motion (SFM) using the same ground control points (GCP). The digital surface model (DSM) was produced by rasterizing the point cloud of UAV leaf-on. The point cloud of UAV leaf-off was processed by iterative median filtering to remove vegetation points, and the digital terrain model (DTM) was generated by the rasterization of the filtered point cloud. The mean canopy height model (MCHM) was derived from the DSM subtracted by the DTM (i.e., DSM-DTM). Forest AGB maps were generated using models developed based on the MCHM and sampling plots of forest AGB and were evaluated by those of lidar. Results showed that forest AGB maps from UAV stereo imagery were highly correlated with those from lidar data with R2 higher than 0.94 and RMSE lower than 10.0 Mg/ha (i.e., relative RMSE 18.8%). These results demonstrated that UAV stereo imagery could be used as a practical inventory tool for deciduous forest AGB.