Miracle-dz/UniFAR-FTUs huggingface dataset:
Dependent variable selection in phylogenetic generalized least squares regression analysis under Pagel’s lambda model

Phylogenetic generalized least squares (PGLS) regression is widely used to analyze evolutionary relationships between two traits. In contrast to the equal treatment of analyzed traits in conventional correlation methods such as Pearson and Spearman’s rank tests, we must designate one trait as the independent variable and the other as the dependent variable. We retrieved an empirical dataset containing the optimal growth temperature, minimal doubling time, CRISPR-Cas, and prophage contents of 262 bacteria from a recent publication and conducted 16000 simulations of the evolution of two traits along a binary tree with 100 terminal nodes, using different models and variances. Correlations in these two datasets were examined by PGLS regression using Pagel’s λ model. By examining correlations in the empirical dataset, we found that switching independent and dependent variables resulted in conflicting results in 26.3% of cases. PGLS regression analysis of the 16000 simulated data showed that the frequency of conflicting outcomes from switching dependent and independent variables depends on the strength of the relationship between the two analyzed traits. Switching dependent and independent variables would strongly affect the parameter estimation of the PGLS regressions if the two variables differ significantly in their phylogenetic signals. To assess correlations in each simulation, we established a gold standard by analyzing changes in traits along phylogenetic branches. Next, we tested seven potential criteria for dependent variable selection: log-likelihood, Akaike information criterion, R2, p-value, Pagel’s λ, Blomberg et al.’s K, and the estimated λ in Pagel’s λ model. We determined that the last three criteria performed equally well in selecting the dependent variable and were superior to the other four. Since Pagel’s λ and Blomberg et al.’s K values are indicators of phylogenetic signals, which are commonly calculated at the beginning of phylogenetic comparative studies, we suggest using the trait with a higher λ or K value as the dependent variable for practicality in future PGLS regressions. In analyzing the evolutionary relationship between two traits, we should designate the trait with a stronger phylogenetic signal as the dependent variable even if it could logically assume the cause in the relationship.
Artificial cerebellum on FPGA: Realistic real-time cerebellar spiking neural network model capable of real-world adaptive motor control

The cerebellum plays a central role in motor control and learning. Its neuronal network architecture, firing characteristics of component neurons, and learning rules at their synapses have been well understood in terms of anatomy and physiology. A realistic artificial cerebellum with mimetic network architecture and synaptic plasticity mechanisms may allow us to analyze cerebellar information processing in real world by applying it to adaptive control of actual machines. Several artificial cerebellums have previously been constructed, but they required a high-performance hardware to run in real time for real-world machine control. Presently, we implemented an artificial cerebellum with the size of 104 spiking neuron models on a field-programmable gate array (FPGA) which is compact, lightweight, portable, and low-power-consumption. In the implementation three novel techniques are employed: 1) 16-bit fixed-point operation with randomized rounding, 2) fully connected spike information transmission, 3) alternative memory that uses pseudo-random number generators. We demonstrate that the FPGA artificial cerebellum runs in real time, and its component neuron models behave as those in the corresponding artificial cerebellum configured on a personal computer in Python. We applied the FPGA artificial cerebellum to adaptive control of a machine in real-world and demonstrate that the artificial cerebellum is capable of adaptively reducing control error after sudden load changes. This is the first implementation and demonstration of a spiking artificial cerebellum on an FPGA applicable to real-world adaptive control. The FPGA artificial cerebellum may provide neuroscientific insights into cerebellar information processing in adaptive motor control and may be applied to various neuro-devices to augment and extend human motor control capabilities.
Long-range repression by ecdysone receptor on complex enhancers of the insulin receptor gene

The insulin signaling pathway is evolutionarily conserved throughout metazoans, playing key roles in development, growth, and metabolism. Misregulation of this pathway is associated with a multitude of disease states including diabetes, cancer, and neurodegeneration. Genome-wide association studies indicate that natural variants in putative intronic regulatory elements of the human insulin receptor gene (INSR) are associated with metabolic conditions, however, this gene’s transcriptional regulation remains incompletely studied. INSR is widely expressed throughout development and was previously described as a ‘housekeeping’ gene. Yet, there is abundant evidence that this gene is expressed in a cell-type specific manner, with dynamic regulation in response to environmental signals. The Drosophila insulin-like receptor gene (InR) is homologous to the human INSR gene and was previously shown to be regulated by multiple transcriptional elements located primarily within the introns of the gene. These elements were roughly defined in ∼1.5 kbp segments, but we lack an understanding of the potential detailed mechanisms of their regulation, as well as the integrative output of the battery of enhancers in the entire locus. Using luciferase assays, we characterized the substructure of these cis-regulatory elements in Drosophila S2 cells, focusing on regulation through the ecdysone receptor (EcR) and the dFOXO transcription factor. The direct action of EcR on Enhancer 2 reveals a bimodal form of regulation, with active repression in the absence of the ligand, and positive activation in the presence of 20E. By identifying the location of activators of this enhancer, we characterized a long-range of repression acting over at least 475 bp, similar to the action of long-range repressors found in the embryo. dFOXO and 20E have contrasting effects on some of the individual regulatory elements, and for the adjacent enhancers 2 and 3, their influence was/was not found to be additive, indicating that enhancer action on this locus can/cannot be characterized in part by additive models. Other characterized enhancers from within this locus exhibited “distributed” or “localized” modes of action, suggesting that predicting the joint functional output of multiple regulatory regions will require a deeper experimental characterization. The noncoding intronic regions of InR have demonstrated dynamic regulation of expression and cell type specificity. This complex transcriptional circuitry goes beyond the simple conception of a ‘housekeeping’ gene. Further studies are aimed at identifying how these elements work together in vivo to generate finely tuned expression in tissue- and temporal-specific manners, to provide a guide to understanding the impact of natural variation in this gene’s regulation, applicable to human genetic studies.
Oxamniquine derivatives overcome Praziquantel treatment limitations for Schistosomiasis

Human schistosomiasis is a neglected tropical disease caused by Schistosoma mansoni, S. haematobium, and S. japonicum. Praziquantel (PZQ) is the method of choice for treatment. Due to constant selection pressure, there is an urgent need for new therapies for schistosomiasis. Previous treatment of S. mansoni included the use of oxamniquine (OXA), a drug that is activated by a schistosome sulfotransferase (SULT). Guided by data from X-ray crystallography and Schistosoma killing assays more than 350 OXA derivatives were designed, synthesized, and tested. We were able to identify CIDD-0150610 and CIDD-0150303 as potent derivatives in vitro that kill (100%) of all three Schistosoma species at a final concentration of 71.5 μM. We evaluated the efficacy of the best OXA derivates in an in vivo model after treatment with a single dose of 100 mg/kg by oral gavage. The highest rate of worm burden reduction was achieved by CIDD -150303 (81.8%) against S. mansoni, CIDD-0149830 (80.2%) against S. haematobium and CIDD-066790 (86.7%) against S. japonicum. We have also evaluated the ability of the derivatives to kill immature stages since PZQ does not kill immature schistosomes. CIDD-0150303 demonstrated (100%) killing for all life stages at a final concentration of 143 μM in vitro and effective reduction in worm burden in vivo against S. mansoni. To understand how OXA derivatives fit in the SULT binding pocket, X-ray crystal structures of CIDD-0150303 and CIDD-0150610 demonstrate that the SULT active site will accommodate further modifications to our most active compounds as we fine tune them to increase favorable pharmacokinetic properties. Treatment with a single dose of 100 mg/kg by oral gavage with co-dose of PZQ + CIDD-0150303 reduced the worm burden of PZQ resistant parasites in an animal model by 90.8%. Therefore, we conclude that CIDD-0150303, CIDD-0149830 and CIDD-066790 are novel drugs that overcome some of PZQ limitations, and CIDD-0150303 can be used with PZQ in combination therapy.
Signatures of heuristic-based directed exploration in two-step sequential decision task behaviour

Processes formalized in classic Reinforcement Learning (RL) theory, such as model-based (MB) control and exploration strategies have proven fertile in cognitive and computational neuroscience, as well as computational psychiatry. Dysregulations in MB control and exploration and their neurocomputational underpinnings play a key role across several psychiatric disorders. Yet, computational accounts mostly study these processes in isolation. The current study extended standard hybrid models of a widely-used sequential RL-task (two-step task; TST) employed to measure MB control. We implemented and compared different computational model extensions for this task to quantify potential exploration mechanisms. In two independent data sets spanning two different variants of the task, an extension of a classical hybrid RL model with a heuristic-based exploration mechanism provided the best fit, and revealed a robust positive effect of directed exploration on choice probabilities in stage one of the task. Posterior predictive checks further showed that the extended model reproduced choice patterns present in both data sets. Results are discussed with respect to implications for computational psychiatry and the search for neurocognitive endophenotypes.
A chemical genetic screen uncovers novel seed priming agents capable of persistent perturbation of anthocyanin regulation in Arabidopsis thaliana

Priming is a general term for a phenomenon in which exposure to an early environmental stimulus results in a more rapid or vigorous response when the plant is exposed to subsequent challenges. Various types of priming have been described: ‘systemic acquired resistance’ against biotic stimuli, ‘epigenetic stress memory’ induced by repeated abiotic stimuli, and ‘seed priming’ treatments which apply water and additional adjuncts to seeds to improve crop performance. Using a high-throughput chemical genomic approach, thousands of small molecules were screened to identify compounds capable of ‘chemical priming’, asking if these could serve as artificial environments to persistently induce altered response to later abiotic challenges when applied as seed treatments. Attenuation of expected visual anthocyanin accumulation was chosen as a screening phenotype due to the visual nature of these pigments, as well as their biological roles in development and stress response. Several novel structural categories of molecules were identified that had the ability to reduce total anthocyanin accumulation in 7-18-day old seedlings induced by later low temperature challenge, persisting days after the removal of the compounds. Application variables were explored with thought to future use of the priming compounds as functional treatments: a dose-dependent relationship was established, additional effects on growth and development were documented to ensure minimal detrimental side effects on the treated plants, and the necessary temporal window of treatment was explored and reduced. Cross testing of the priming treatments identified by low temperature screening for ability to reduce anthocyanin induction by alternative exogenous and endogenous conditions showed consistent attenuative effect and revealed that the effect of priming on this metabolic phenotype was not specific to low temperature response. The presented research represents a proof-of-concept for the functional potential of seed priming with novel compounds, and highlights anthocyanin accumulation as a flexible component of plant stress response.
Poster: How to Raise a Robot - Beyond Access Control Constraints in Assistive Humanoid Robots

Humanoid robots will be able to assist humans in their daily life, in particular due to their versatile action capabilities. However, while these robots need a certain degree of autonomy to learn and explore, they also should respect various constraints, for access control and beyond. We explore incorporating privacy and security constraints (Activity-Centric Access Control and Deep Learning Based Access Control) with robot task planning approaches (classical symbolic planning and end-to-end learning-based planning). We report pre-liminary results on their respective trade-offs and conclude that a hybrid approach will most likely be the method of choice.
Privacy-Preserving Multi-Party Access Control for Third-Party UAV Services

Third-Party Unmanned Aerial Vehicle (UAV) Services , a.k. a. Drone-as-a-Service (DaaS) , are an increasingly adopted business model, which enables possibly unskilled users, with no background knowledge, to operate drones and run automated drone-based tasks. Although these services provide significant advantages, the resources provided by drones are typically owned by multiple parties. Thus, Third-Party UAV services require adopting multi-party access con-trol solutions. In this context, the leakage of the access control policies specified by the data owners might disclose confidential information and, thus, they should be protected as well. In this work, we propose a privacy-preserving multi-party access control solution tailored to the application scenarios of Third-Party UAV Services. Our solution advances an existing privacy-preserving multi-party access control framework based on Secure Function Evaluation to fit the distributed and heterogeneous nature of drone deployments. Through an extensive experimental evaluation, we demonstrate our solution can perform private policy evaluation on constrained devices in a reasonable time while requiring limited communication, memory, and energy overhead.
Matter-antimatter rearrangements using the R-matrix method

Antihydrogen atoms, H ― , are now routinely created and can be stored for long enough to allow comparison with ordinary matter. A major goal of these efforts is to test potential physics beyond the Standard Model. This will require further developments in the experiments including the accumulation of more antihydrogen atoms and their storage over longer times. The latter is limited by the unavoidable presence of normal hydrogen molecules. Interactions of H ― with H2 lead to the destruction of the hard-won antimatter. Little is known about these interactions but quantitative information will be crucial in guiding experimental developments. Physically realistic modelling of rearrangement scattering of “heavy” antimatter particles (antiprotons, p ― , and antihydrogen atoms) by normal matter molecules, such as H2 + H ― → Pn + Ps + H (where Pn represents protonium and Ps positronium), requires the development of new theoretical and computational methodologies. R-matrix theory offers a strong prospect for tackling such problems having proved itself in atomic, molecular and optical physics. It divides the problem into a computationally demanding but energy-independent inner region and simpler energy-dependent outer regions. We propose to adapt the new RmatReact ultracold chemistry approach for the more complex molecular matter-antimatter problems. Here, developments required for the inner region, the boundary and outer regions are outlined. We also report some preliminary bound-state calculations on the {p,p, p ― } system and a study of the required mixed coordinate systems for the general effective 3-body case and their transformations at the R-matrix boundary surfaces.
Examining perceptions of a telemedicine network for pediatric emergency medicine: a mixed-methods pilot study

Background Use of telemedicine for healthcare delivery in the emergency department can increase access to specialized care for pediatric patients without direct access to a children's hospital. Currently, telemedicine is underused in this setting. Objectives This pilot research project aimed to evaluate the perceived effectiveness of a telemedicine program in delivering care to critically ill pediatric patients in the emergency department by exploring the experiences of parents/caregivers and physicians. Methods Sequential explanatory mixed methods were employed, in which quantitative methods of inquiry were followed by qualitative methods. Data were collected through a post-used survey for physicians, followed by semi-structured interviews with physicians and parents/guardians of children treated through the program. Descriptive statistics were used to analyze the survey data. Reflexive thematic analysis was used to analyze interview data. Results The findings describe positive perceptions of telemedicine for emergency department pediatric care, as well as barriers and facilitators to its use. The research also discusses implications for practice and recommendations for overcoming barriers and supporting facilitators when implementing telemedicine programming. Conclusion The findings suggest that a telemedicine program has utility and acceptance among parents/caregivers and physicians for the treatment of critically ill pediatric patients in the emergency department. Benefits recognized and valued by both parents/caregivers and physicians include rapid connection to sub-specialized care and enhanced communication between remote and local physicians. Sample size and response rate are key limitations of the study.
Palmprint recognition based on gating mechanism and adaptive feature fusion

As a type of biometric recognition, palmprint recognition uses unique discriminative features on the palm of a person to identify his/her identity. It has attracted much attention because of its advantages of contactlessness, stability, and security. Recently, many palmprint recognition methods based on convolutional neural networks (CNN) have been proposed in academia. Convolutional neural networks are limited by the size of the convolutional kernel and lack the ability to extract global information of palmprints. This paper proposes a framework based on the integration of CNN and Transformer-GLGAnet for palmprint recognition, which can take advantage of CNN's local information extraction and Transformer's global modeling capabilities. A gating mechanism and an adaptive feature fusion module are also designed for palmprint feature extraction. The gating mechanism filters features by a feature selection algorithm and the adaptive feature fusion module fuses them with the features extracted by the backbone network. Through extensive experiments on two datasets, the experimental results show that the recognition accuracy is 98.5% for 12,000 palmprints in the Tongji University dataset and 99.5% for 600 palmprints in the Hong Kong Polytechnic University dataset. This demonstrates that the proposed method outperforms existing methods in the correctness of both palmprint recognition tasks. The source codes will be available on https://github.com/Ywatery/GLnet.git.
OpenCL-accelerated first-principles calculations of all-electron quantum perturbations on HPC resources

We have proposed, for the first time, an OpenCL implementation for the all-electron density-functional perturbation theory (DFPT) calculations in FHI-aims, which can effectively compute all its time-consuming simulation stages, i.e., the real-space integration of the response density, the Poisson solver for the calculation of the electrostatic potential, and the response Hamiltonian matrix, by utilizing various heterogeneous accelerators. Furthermore, to fully exploit the massively parallel computing capabilities, we have performed a series of general-purpose graphics processing unit (GPGPU)-targeted optimizations that significantly improved the execution efficiency by reducing register requirements, branch divergence, and memory transactions. Evaluations on the Sugon supercomputer have shown that notable speedups can be achieved across various materials.
Multistable perception elicits compensatory alpha activity in older adults

Multistable stimuli lead to the perception of two or more alternative perceptual experiences that spontaneously reverse from one to the other. This property allows researchers to study perceptual processes that endogenously generate and integrate perceptual information. These endogenous processes appear to be slowed down around the age of 55 where participants report significantly lower perceptual reversals. This study aimed to identify neural correlates of this aging effect during multistable perception utilizing a multistable version of the stroboscopic alternative motion paradigm (SAM: endogenous task) and a control condition (exogenous task). Specifically, age-related differences in perceptual destabilization and maintenance processes were examined through alpha responses. Electroencephalography (EEG) of 12 older and 12 young adults were recorded during SAM and control tasks. Alpha band activity (8–14 Hz) was obtained by wavelet-transformation of the EEG signal and analyzed for each experimental condition. Endogenous reversals induced gradual decrease in posterior alpha activity in young adults which is a replication of previous studies’ findings. Alpha desynchronization was shifted to anterior areas and prevalent across the cortex except the occipital area for older adults. Alpha responses did not differ between the groups in the control condition. These findings point to recruitment of compensatory alpha networks for maintenance of endogenously generated percepts. Increased number of networks responsible for maintenance might have extended the neural satiation duration and led to decreased reversal rates in older adults.