Miracle-dz/UniFAR-FTUs huggingface dataset:
Temperature effects on the global patterns of photosynthetic quantum efficiency

The photosynthetic quantum efficiency (φ0) is a key input parameter for modelling gross primary productivity in terrestrial biosphere models. Historically, these models assumed φ0 to be constant, based on leaf measurements under unstressed conditions and within a narrow temperature range. However, increasing evidence suggests a temperature-dependent φ0 on temperature, though it remains unclear whether this response is generalized or if it propagates to the ecosystem. Here, we derived φ0(T) at the ecosystem level for sites distributed globally, using sub-daily eddy covariance measurements of CO2 exchange and above/below-canopy measurements of photosynthetic flux density to derive the fraction of absorbed photosynthetically active radiation (fAPAR). We found that φ0(T) shows a consistent bell-shaped response curve with temperature in all the sites we analysed. These patterns held when analysed with a larger global dataset using remotely sensed fAPAR. Furthermore, we observed that the values of φ0(T) are not markedly different among biomes, instead, there is a gradual transition of the peak φ0(T) which decreases following an aridity gradient. Additionally, we noted varying sensitivity to temperature among the different sites, with sensitivity increasing as growth temperature decreases.
Providing information about wild animal psychology impacts public attitudes beyond ecological information

Anthropomorphism is often used to encourage positive wildlife attitudes in people but is rarely based on actual animal psychology research. It is unclear whether, or how, disseminating animal psychology research to the general public impacts attitudes towards wildlife. Through a national-level survey (n = 1,364 participants), we tested whether providing information about the boldness and problem-solving abilities of a wild carnivore, the red fox (Vulpes vulpes), influences people’s attitudes and beliefs about this species. Half of participants were given information on fox psychology (either a video or a press release about fox boldness and problem-solving), the other half were given content unrelated to animal ecology (either a video or a press release about fox habitat use). Afterwards, all participants completed the same 24-item questionnaire evaluating fox-related attitudes and beliefs. While attitudes and beliefs relating specifically to overall fox tolerance remained unaffected by content (fox ecology vs fox psychology) or format (video vs written), 19.9% of people agreed that the fox psychology information changed their attitudes to foxes (272 participants). Across all participants, perceived attitude change, based on a Likert scale, was significantly higher for participants watching videos (3.73+0.06) versus a press release (3.54+0.06), and for fox psychology content (3.76+0.06) versus fox ecology content (3.50+0.06). This perceived attitude change was also positively correlated with overall fox tolerance. Thus, information about animal psychology may influence other facets to people’s attitudes beyond general tolerance (e.g., interest factor), particularly through videos, and this effect may be greater than information about a species’ basic ecology. Highlights Anthropomorphism impacts attitudes and beliefs about wildlife The influence of animal psychology research is unclear We tested if fox psychology research influences people’s attitudes People given fox psychology information reported greater attitude change The effect was greater than information about fox ecology
Lateral inhibition in V1 controls neural & perceptual contrast sensitivity

Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.
Meiotic drive, postzygotic isolation, and the Snowball Effect

As populations diverge, they accumulate incompatibilities which reduce gene flow and facilitate the formation of new species. Simple models suggest that the genes that cause Dobzhansky-Muller incompatibilities should accumulate at least as fast as the square of the number of substitutions between taxa, the so-called snowball effect. We show, however, that in the special— but possibly common— case in which hybrid sterility is due primarily to cryptic meiotic (gametic) drive, the number of genes that cause postzygotic isolation may increase nearly linearly with the number of substitutions between species.
Anterior cingulate cortex neurons in macaques encode social image identities

The anterior cingulate cortex gyrus (ACCg) has been implicated in prosocial behaviors involving complex reasoning about social cues. While this indicates that the ACCg is involved in social behavior, it remains unclear whether ACCg neurons also encode social information during goal-directed actions without social consequences. To address this, we assessed how social information is processed by ACCg neurons in a reward localization task. Two rhesus monkeys performed the task using either social or nonsocial visual guides to locate rewarding targets. We found that monkeys can use both sets of guides, and many neurons in the ACCg distinguished social from nonsocial trials. Yet, this encoding was no more common in ACCg than in the prearcuate cortex (PAC), which has not been strongly linked to social behavior. However, unlike PAC, ACCg neurons were more likely to encode the unique identity of social visual guides compared to nonsocial, even though identity was irrelevant to the reward localization task. This suggests that ACCg neurons are uniquely sensitive to social information that differentiates individuals, which may underlie its role in complex social reasoning.
COMPLEXITY MEASURES OF PSYCHOTIC BRAIN ACTIVITY IN THE FMRI SIGNAL

When viewing the brain as a sophisticated, nonlinear dynamic system, employing complexity measures offers a valuable way to measure the intricate and dynamic aspects of spontaneous psychotic brain activity. These measures can help us identify irregularities and patterns in complex systems. In our study, we utilized fuzzy recurrence plots and sample entropy to evaluate the dynamic characteristics of psychiatric disorders. This assessment focused on understanding the temporal and spatial neural activity patterns, and more specifically, we applied complexity measures to investigate the functional connectivity within the psychotic brain. This involves understanding how different brain regions synchronize their activity, and complexity measures can reveal the patterns of these connections. It provides a means to understand how different brain regions interact and communicate under resting-state abnormal conditions. This study offers evidence demonstrating that fuzzy recurrence plots can serve as descriptors for functional connectivity and discusses their relevance to sample entropy in the context of the psychotic brain. In summary, complexity measures offer valuable insights that enrich our comprehension of atypical brain activity and the complexities present in the psychotic brain1.
An agent based model (ABM) to reproduce the boolean logic behaviour of neuronal self organized communities through pulse delay modulation and generation of logic gates

The human brain is arguably the most complex “machine” to ever exist. Its detailed functioning is yet to be fully understood, let alone modeled. Neurological processes have logical signal-processing aspects and biophysical aspects, and both affect the brain structure, functioning and adaptation. Mathematical approaches based on both information and graph theory have been extensively used in an attempt to approximate its biological functioning, along with Artificial Intelligence approaches inspired by its logical functioning. In this article, we present an approach to model some aspects of the brain learning and signal processing, mimicking the metastability and backpropagation found in the real brain while also accounting for neuroplasticity. Several simulations are carried out with this model, to demonstrate how dynamic neuroplasticity, neural inhibition and neurons migration can remodel the brain logical connectivity to syncronize signal processing and obtain target latencies. This work demonstrates the importance of dynamic logical and biophysical remodelling in brain plasticity.
Exploring viral particle, soil, and extraction buffer physicochemical characteristics and their impacts on extractable viral communities

Soil viruses are expected to be pivotal members of soil ecosystems, and recent advances in viral size fraction metagenomic (viromic) approaches have substantially improved our ability to interrogate soil viral ecology. However, the first step of viromics relies on extraction buffers to effectively remove viral particles from the soil matrix for downstream analysis, and viral extraction efficiency at this stage could be affected by the interplay between viral particles, soils, and extraction buffer chemistry. Here, we investigated whether extraction buffer chemistry affected extractable viral community composition measured by viromics from different soil types, for both biological (samples collected 1 meter apart) and technical (subsamples from the same soil homogenate) replicates. We first investigated protein-supplemented phosphate-buffered saline pH (PPBS, pHs 4.5, 5.5, 6.5, and 7.5) on a forest, grassland and wetland soil that exhibited different soil edaphic properties, and then we tested different buffer chemistries (PPBS, Carbonated Buffer, Glycine, and Saline Magnesium) on just the wetland soil. Spatial distance, or where the sample was taken in the field (i.e., biological replicate), was the primary driver of extractable viral community composition across all buffers and soils tested. Differences in viral community composition according to extraction buffer properties were only observed in the grassland technical replicates at PPBS buffer pH 4.5, as well as in both the wetland technical and biological replicates treated with different buffer chemistries, but the effects of buffer chemistry were secondary to spatial distance in all cases where spatial distance was a factor. The lack of buffering capacity in the grassland soil technical replicates likely increased sorption of some viral particles at pH 4.5, but neither protein composition nor isoelectric point (both calculated bioinformatically) explained this phenomenon. Given that most soil viral ecological studies to date include sample collection schemes over distances much farther apart than the 1-meter distances considered here, results suggest that extraction buffer chemistry is likely of much lower importance than ecological considerations, such as spatial distance, in the design of future soil viral ecological investigations. HIGHLIGHTS Spatial distance was the main driver of extractable viral community composition. Extraction buffer chemistry secondarily structured wetland viral communities. At pH 4.5, PPBS buffer likely increased viral sorption in homogenized grassland soil. Increased sorption was not explained by estimated viral protein isoelectric points.
Functional brain networks are associated with both sex and gender in children

Sex and gender are associated with human behavior throughout the lifespan and across health and disease, but whether they are associated with similar or distinct neural phenotypes is unknown. Here, we demonstrate that, in children, sex and gender are uniquely reflected in the intrinsic functional connectivity of the brain. Unimodal networks are more strongly associated with sex while heteromodal networks are more strongly associated with gender. These results suggest sex and gender are irreducible to one another not only in society but also in biology.
Association Between Action Video Game Playing Experience and Visual Search in Real-life Multisensory scenes

Prior studies investigating the effects of playing action video games on attentional control have demonstrated improvements on a variety of basic psychophysical tasks. However, as of yet, there is little evidence indicating that the cognitive benefits of playing action video games generalize to naturalistic multisensory scenes – a fundamental characteristic of our natural, everyday life environments. The present study addressed the generalization of attentional control enhancement due to AVGP experience to real-life like scenarios by comparing the performance of action video-game players (AVGPs) with non-players (NVGPs) on a visual search task using naturalistic, dynamic audio-visual scenes. To this end, a questionnaire collecting data on gaming habits and sociodemographic data as well as a visual search task was administered online to a gender-balanced sample of 60 participants of age 18 to 30 years. According to the standard hypothesis, AVGPs outperformed NVGPs in the search task overall, showing faster reaction times without sacrificing accuracy. In addition, in replication of previous findings, semantically congruent cross-modal cues benefited performance overall. However, according to our results, despite the overall advantage in search, and the multisensory congruence benefit, AVGPs did not exploit multisensory cues more efficiently than NVGPs. Exploratory analyses with gender as a variable indicated that the advantage of AVG experience to both genders should be done with caution
Value of Incorporating Satellite-Derived Land Cover Data in MM5/PLACE for Simulating Surface Temperatures

Abstract The Parameterization for Land–Atmosphere–Cloud Exchange (PLACE) module is used within the Fifth-Generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) to determine the importance of individual land surface parameters in simulating surface temperatures. Sensitivity tests indicate that soil moisture and the coverage and thickness of green vegetation [as manifested by the values of fractional green vegetation coverage (fVEG) and leaf area index (LAI)] have a large effect on the magnitudes of surface sensible heat fluxes. The combined influence of LAI and fVEG is larger than the influence of soil moisture on the partitioning of the surface energy budget. Values for fVEG, albedo, and LAI, derived from 1-km-resolution Advanced Very High Resolution Radiometer data, are inserted into PLACE, and changes in model-simulated 1.5-m air temperatures in Oklahoma during July of 1997 are documented. Use of the land cover data provides a clear improvement in afterno.
TR 03-011 Performance Evaluation of a Multi-Robot Search & Retrieval System : Experiences with MinDART

The costs of developing mobile robot teams can be reduced if they are designed to exploit swarm techniques. In this methodology many simple homogeneous units solve complex tasks through emergent behavior. The challenge lies in selecting an appropriate control strategy for the individual units. Complexity in design costs both money and time, therefore a control strategy should be just complex enough to perform the task successfully in a variety of environments, relative to some performance measure. To explore the effects of control strategies and environmental factors on performance, we have conducted two sets of foraging experiments using real robots (the Minnesota Distributed Autonomous Robotic Team). The first set of experiments tested the efficacy of localization capabilities, in addition to the effects of team size and target distribution. The second set tested the efficacy of communication. We found that more complex control strategies do not necessarily improve task completion times, however they can reduce variance in performance measures. This can be valuable information for designers who need to assess the potential costs and benefits of increased complexity in design.
Mindfulness-based stress reduction (MBSR) for improving health, quality of life and social functioning in adults: a systematic review and meta-analysis

This review summarizes all studies that compare the effect of a MBSR program to a control group intervention, in which the participants had been randomly allocated to be in either the MBSR group or a control group. The review summarizes the results in two categories. First, where the effect of the MBSR program was compared to an inactive group (either a wait list group or one receiving ordinary care also received by the MBSR group). Second, where MBSR was compared with an alternative active group intervention. Based on this review it is reasonable to consider MBSR a moderately well-documented method for helping adults improve their health and cope better with the challenges and stress that life brings. New research should improve the way the trials are conducted addressing the pitfalls in research on mind-body interventions.
ACUTE EFFECTS OF OUTDOOR SURFACES ON RUNNING GAIT SYMMETRY AND REGULARITY ASSESSED BY TRUNK ACCELEROMETRY

The purpose of this study was to investigate if trunk accelerometry measures were influenced by outdoor surface while running. A sample of highly-trained (n=12) and recreational (n=17) ran on three independent surfaces, namely asphalt, synthetic track, and wood-chip. Dependent accelerometry measures were step frequency (SFREQ), step symmetry (SSYM), stride regularity (SREG), axis contribution to total amplitude (RMSRATIO) and sample entropy (SEN). Surface effects on accelerometry measures were consistent for both running groups. Several significant differences existed between wood-chip and either asphalt or synthetic track. The results suggest that surface specific considerations should be made when quantifying trunk accelerometry measures related to running gait symmetry and regularity during running.
Sensor-Based In-situ Process Control of Robotic Wire Arc Additive Manufacturing Integrated with Reinforcement Learning

: Wire and Arc Additive Manufacturing (WAAM) is a manufacturing technique capable of fabricating large-scale metallic components in a layer-by-layer fashion. As an emerging technology, there still exist numerous challenges that need to be overcome to ensure the geometrical accuracy of the part produced. With an increasing number of deposited layers, geometrical errors often accumulate in height and the accumulated heat becomes significant, leading to the slumping of the beads. The quality of the part can be enhanced through in-situ real-time feedback control. However, as the WAAM process is a time-variant process that is highly non-linear and multi-dimensional, it is difficult to model the process relating the process parameters to the final quality of the produced part. To address this challenge, a sensor-based in-situ process control framework integrated with reinforcement learning (RL) artificial intelligence (AI) is proposed to iteratively learn the impacts of various process parameters to finally control the output geometry of a single-bead multi-layer part. The proposed control frameworks are then implemented and simulated on a robotic large-scale WAAM system.
Benefits of Enacting and Observing Gestures on Foreign Language Vocabulary Learning: A Systematic Review and Meta-Analysis

The integration of physical movements, such as gestures, into learning holds potential for enhancing foreign language (L2) education. Uncovering whether actively performing gestures during L2 learning is more, or equally, effective compared to simply observing such movements is central to deepening our understanding of the efficacy of movement-based learning strategies. Here, we present a meta-analysis of seven studies containing 309 participants that compares the effects of gesture self-enactment and observation on L2 vocabulary learning. The results showed that gesture observation was just as effective for L2 learning as gesture enactment, based on free recall, cued L2 recognition, and cued native language recognition performance, with a large dispersion of true effect across studies. Gesture observation may be sufficient for inducing embodied L2 learning benefits, in support of theories positing shared mechanisms underlying enactment and observation. Future studies should examine the effects of gesture-based learning over longer time periods with larger sample sizes and more diverse word classes.
Influence of the Damage of Cotton Bollworm and Corn Borer to Ear Rot in Corn

The influence of cotton bollworm and corn borer on ear rot in corn was studied.The test varieties were Zhengdan958,Xianyu335 and Jundan20 which widely grown in North China.The result showed that the damage done by corn borer had more effect on ear rot in corn on the conditions of high rainfall and high humidity;however,cotton bollworm had more destructive effect on the conditions of low rainfall and low humidity.For one kind of insect,the ear rot was in favor of the condition of high rainfall and high humidity.
Concept Parameters as a New Mechanism of Generic Programming for C # Language

As was shown in earlier studies, mainstream object-oriented (OO) languages C # and Java provide weaker support for generic programming (GP) as compared with functional languages such as Haskell or SML. Having explored the instruments for GP in modern OO languages Scala, Ceylon, Kotlin, Rust, and Swift, we have found out that all of them, as well as C # and Java, stick to the same approach to constraining type parameters, which we called the “Constraints-are-Types” approach. It turns out that the approach has several inevitable limitations, and because of that Haskell type classes still provide better support for GP than modern object-oriented languages do. This research is aimed to discover a mechanism that would allow to radically improve the support for generic programming in OO languages. We identify the requirements that such mechanism should satisfy, present a design of the appropriate mechanism (concept parameters), and propose a sketch of its implementation for the C # language.