Miracle-dz/UniFAR-FTUs huggingface dataset:
The auditory P2 evoked by speech sounds consists of two separate subcomponents

The P2 component of the auditory evoked potential is commonly thought to reflect acoustic stimulus properties as well as prior exposure to the materials, rather than change-related cortical activity. Here, we challenge this view by showing that the P2 is strongly increased in response to voice pitch changes with a stepwise pattern compared to changes in dynamic pitch contours typical for natural speech, and also reflects the magnitude of these pitch changes. Furthermore, it is demonstrated that neither the P2 nor any other component are affected by the harmonicity of the materials. Despite no prior exposure, artificially created inharmonic versions of the speech materials elicited similar activity throughout auditory cortex. This suggests that so-called harmonic template neurons observed in animal studies are either absent or do not exist in sufficient number in human auditory cortex to detect their activity extracranially. Crucially, both morphology and source reconstructions of the EEG data showed that the P2 appears to consist of two separate subcomponents. Whereas source activity for the “P2a” was strongest in right auditory cortex, the subsequent “P2b” included generators spread across auditory cortex and association areas, bilaterally. The two subcomponents thus likely reflect processing at different stages of the auditory pathway.
Mitochondrial morphology governs ATP production rate

Life is based on energy conversion. In particular, in the nervous system significant amounts of energy are needed to maintain synaptic transmission and homeostasis. To a large extent, neurons depend on oxidative phosphorylation in mitochondria to meet their high energy demand (Pekkurnaz and Wang, 2022). For a comprehensive understanding of the metabolic demands in neuronal signaling, accurate models of ATP production in mitochondria are required. Here, we present a thermodynamically consistent model of ATP production in mitochondria based on previous work (Pietrobon and Caplan, 1985; Magnus and Keizer, 1997; Metelkin et al., 2006; Garcia et al., 2019). The significant improvement of the model is that the reaction rate constants are set such that detailed balance is satisfied. Moreover, using thermodynamic considerations, the dependence of the reaction rate constants on membrane potential, pH, and substrate concentrations are explicitly provided. These constraints assure the model is physically plausible. Furthermore, we explore different parameter regimes to understand in which conditions ATP production or its export are the limiting steps in making ATP available in the cytosol. The outcomes reveal that, under the conditions used in our simulations, ATP production is the limiting step and not its export. Finally, we performed spatial simulations with nine 3D realistic mitochondrial reconstructions and linked the ATP production rate in the cytosol with morphological features of the organelles. 1. Summary In this work, Garcia et al present a thermodynamically consistent model for ATP production in mitochondria, in which reaction rate constants are set such that detailed balance is satisfied. Simulations revealed that ATP production, but not its export, is the limiting step, and simulations with 3D mitochondrial reconstructions linked the ATP production rate in the cytosol with the morphological features of the organelles.
Automated system for training and assessing string-pulling behaviors in rodents

String-pulling tasks have been used for centuries to study coordinated bimanual motor behavior and problem solving. String pulling is rapidly learned, ethologically grounded, and has been applied to many species and disease conditions. Typically, training of string-pulling behaviors is achieved through manual shaping and baiting. Furthermore, behavioral assessment of reaching, grasping, and pulling is often performed through labor intensive manual video scoring. No system, to our knowledge, currently exists for the automated shaping and assessment of string-pulling behaviors. Here we describe the PANDA system (Pulling And Neural Data Analysis), an inexpensive hardware and software system that utilizes a continuous string loop connected to a rotary encoder, feeder, microcontroller, high-speed camera, and analysis software for assessment and training of string-pulling behaviors and synchronization with neural recording data. We demonstrate this system in unimplanted rats and rats implanted with electrodes in motor cortex and hippocampus and show how the PANDA system can be used to assess relationships between paw movements and single-unit and local-field activity. We also found that automating the shaping procedure significantly improved overall performance, with rats regularly pulling >100 meters during a 15-minute session. In conclusion, the PANDA system will be of general use to researchers investigating motor control, motivation, and motor disorders such as Parkinson’s disease, Huntington’s disease, and stroke. It will also support the investigation of neural mechanisms involved in sensorimotor integration. Highlights High-speed tracking of continuous grasping and pulling behaviors. Automated and adaptive reinforcement of string-pulling behavior. Integration with neural recording and video tracking systems. Open-source software and hardware. Supplemental Files The supplemental pdf contains additional designs and behavioral data and has been uploaded. Source code and 3D and laser cut design files can be found at: https://github.com/CowenLab/String_Pulling_System/ Videos are in the GitHub repository at: https://github.com/CowenLab/String_Pulling_System/tree/main/Videos
The successor representation subserves hierarchical abstraction for goal-directed behavior

Humans have the ability to craft abstract, temporally extended and hierarchically organized plans. For instance, when considering how to make spaghetti for dinner, we typically concern ourselves with useful “subgoals” in the task, such as cutting onions, boiling pasta, and cooking a sauce, rather than particulars such as how many cuts to make to the onion, or exactly which muscles to contract. A core question is how such decomposition of a more abstract task into logical subtasks happens in the first place. Previous research has shown that humans are sensitive to a form of higher-order statistical learning named “community structure”. Community structure is a common feature of abstract tasks characterized by a logical ordering of subtasks. This structure can be captured by a model where humans learn predictions of upcoming events multiple steps into the future, discounting predictions of events further away in time. One such model is the “successor representation”, which has been argued to be useful for hierarchical abstraction. As of yet, no study has convincingly shown that this hierarchical abstraction can be put to use for goal-directed behavior. Here, we investigate whether participants utilize learned community structure to craft hierarchically informed action plans for goal-directed behavior. Participants were asked to search for paintings in a virtual museum, where the paintings were grouped together in “wings” representing community structure in the museum. We find that participants’ choices accord with the hierarchical structure of the museum and that their response times are best predicted by a successor representation. The degree to which the response times reflect the community structure of the museum correlates with several measures of performance, including the ability to craft temporally abstract action plans. These results suggest that successor representation learning subserves hierarchical abstractions relevant for goal-directed behavior. AUTHOR SUMMARY Humans have the ability to achieve a diverse range of goals in a highly complex world. Classic theories of decision making focus on simple tasks involving single goals. In the current study, we test a recent theoretical proposal that aims to address the flexibility of human decision making. By learning to predict the upcoming events, humans can acquire a ‘model’ of the world which they can then leverage to plan their behavior. However, given the complexity of the world, planning directly over all possible events can be overwhelming. We show that, by leveraging this predictive model, humans group similar events together into simpler “hierarchical” representations, which makes planning over these hierarchical representations markedly more efficient. Interestingly, humans seem to learn and remember both the complex predictive model and the simplified hierarchical model, using them for distinct purposes.
Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI

Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is a valuable diagnostic tool due to the combination of anatomical and physiological information it provides. However, the sequential sampling of MRI presents an inherent tradeoff between spatial and temporal resolution. Compressed Sensing (CS) methods have been applied to undersampled MRI to reconstruct full-resolution images at subNyquist sampling rates. In exchange for shorter data acquisition times, CS-MRI requires more computationally intensive iterative reconstruction methods. We present several model-based image reconstruction (MBIR) methods to improve the spatial and temporal resolution of MR images and/or the computational time for multi-coil MRI reconstruction. We propose efficient variable splitting (VS) methods for support-constrained MRI reconstruction, image reconstruction and denoising with non-circulant boundary conditions, and improved temporal regularization for breast DCE-MRI. These proposed VS algorithms decouple the system model and sparsity terms of the convex optimization problem. By leveraging matrix structures in the system model and sparsifying operator, we perform alternating minimization over a list of auxiliary variables, each of which can be performed efficiently. We demonstrate the computational benefits of our proposed VS algorithms compared to similar proposed methods. We also demonstrate convergence guarantees for two
An efficient method for the fusion of light field refocused images

Light field cameras have drawn much attention due to the advantage of post-capture adjustments such as refocusing after exposure. The depth of field in refocused images is always shallow because of the large equivalent aperture. As a result, a large number of multi-focus images are obtained and an all-in-focus image is demanded. Consider that most multi-focus image fusion algorithms do not particularly aim at large numbers of source images and traditional DWT-based fusion approach has serious problems in dealing with lots of multi-focus images, causing color distortion and ringing effect. To solve this problem, this paper proposes an efficient multi-focus image fusion method based on stationary wavelet transform (SWT), which can deal with a large quantity of multi-focus images with shallow depth of fields. We compare SWT-based approach with DWT-based approach on various occasions. And the results demonstrate that the proposed method performs much better both visually and quantitatively.
A Neanderthal/Denisovan GLI3 variant contributes to anatomical variations in mice

Changes in genomic structures underlie phenotypic diversification in organisms. Amino acid-changing mutations affect pleiotropic functions of proteins, although little is known about how mutated proteins are adapted in existing developmental programs. Here we investigate the biological effects of a variant of the GLI3 transcription factor (GLI3R1537C) carried in Neanderthals and Denisovans, which are extinct hominins close to modern humans. R1537C does not compromise protein stability or GLI3 activator-dependent transcriptional activities. In contrast, R1537C affects the regulation of downstream target genes associated with developmental processes. Furthermore, genome-edited mice carrying the Neanderthal/Denisovan GLI3 mutation exhibited various alterations in skeletal morphology. Our data suggest that an extinct hominin-type GLI3 contributes to species-specific anatomical variations, which were tolerated by relaxed constraint in developmental programs during human evolution.
Efficient numerosity estimation under limited time

The ability to rapidly estimate non-symbolic numerical quantities is a well-conserved sense across species with clear evolutionary advantages. Despite its importance, the rapid representation and estimation of numerosity is surprisingly imprecise and biased. However, a formal explanation for this seemingly irrational behavior remains unclear. We develop a unified normative theory of numerosity estimation that parsimoniously incorporates in a single framework information processing constraints alongside Brownian diffusion noise to capture the effects of time exposure of sensory estimations, logarithmic encoding of numerosity representations, and optimal inference via Bayesian decoding. We show that for a given allowable biological capacity constraint our model naturally endogenizes time perception during noisy efficient encoding to predict the complete posterior distribution of numerosity estimates. This model accurately predicts many features of human numerosity estimation as a function of temporal exposure, indicating that humans can rapidly and efficiently sample numerosity information over time. Additionally, we demonstrate how our model fundamentally differs from a thermodynamically-inspired formalization of bounded rationality, where information processing is modeled as acting to shift away from default states. The mechanism we propose is the likely origin of a variety of numerical cognition patterns observed in humans and other animals.
Testing independence for multivariate time series via the auto‐distance correlation matrix

&NA; We introduce the matrix multivariate auto‐distance covariance and correlation functions for time series, discuss their interpretation and develop consistent estimators for practical implementation. We also develop a test of the independent and identically distributed hypothesis for multivariate time series data and show that it performs better than the multivariate Ljung‐Box test. We discuss computational aspects and present a data example to illustrate the method.
Control Framework for a UAV Slung-Payload Transportation System

This letter presents a control framework for transporting a UAV slung-payload, which can asymptotically stabilize not only the UAV but also the tether swing angles. By separating the system into two subsystems, the cascade control methodology is used to design the framework, which includes two sufficient conditions and suits for a large class of existing controllers. The control framework is strictly proved with the boundness of all states such that it can guarantee the asymptotic stability of the closed-loop overall system over the entire configuration space. Then, this framework is applied to a UAV trajectory tracking control problem with stability analysis. Samples of controllers are presented in the type of saturation or dynamic feedback. Finally, numerical and experimental validations are carried out on a UAV slung-payload transportation.
Quality indicators of extracted sunflower and rapeseed oil obtained with hexane and ethyl alcohol solvents

The relevance of the conducted research is conditioned by the increase in demand for oilseeds with improved and environmentally friendly qualities, namely, the replacement of a dangerous solvent in the extraction process of processing oilseeds. In this regard, this paper is aimed at investigating the use of an organic solvent, such as ethanol, in extraction technology that is safer for human health. The leading approach to studying this problem is Soxhlet extraction and microwave extraction using hexane and ethanol solvents. The fatty acid composition of the resulting product was analysed by gas chromatography. In the proposed microwave method of oil extraction with a "green" solvent, which is ethyl alcohol, physical and chemical parameters were studied and compared with those obtained by the Soxhlet method. The efficiency of microwave processing is related to the heating process, which significantly increases the internal pressure of cells, which causes their destruction. A barodiffusion flow is created, which contributes to a significant increase in the yield of the extraction oil concentration by 1.4-1.8 times over the same time period and a decrease in the extraction process time by almost 3 times. The oil obtained by extraction of raw materials in a microwave field with a solvent ethyl alcohol is more resistant to oxidation, as evidenced by a decrease in the numbers: peroxide from 4.8 to 3.8, and anisidine from 0.25 to 0.2. The acid number, which characterises the degree of freshness of the resulting oil, also decreased from 2.5 to 2.1. The research results show that the use of microwave extraction with a polar solvent, which is ethyl alcohol, was effective in improving the quality properties of the extracted oil. The use of a "green” solvent does not degrade the quality of the finished product, unlike hexane, which is harmful to human health. The materials of the study are of practical value for the fat and oil industry, namely, in the technology of extraction of oilseeds
The Values of Recommendations by Quality Assurance Papers: The Case of Vietnam

Many scientific articles on quality in higher education are published every year. Ideally, these articles are read, studied and moreover used by others. However, the usability of articles on quality in higher education by scholars and quality responsible staff in institutions is not obvious. Do the right people read the articles? And moreover, are the recommendations of these articles transportable to the different contexts they are working in? This article summarizes some of the lessons learned from the articles published in the journal Quality in Higher Education from September 2021 to October 2022. It also relates the results to the Vietnamese higher education context. In doing so, the article presents a set of useful findings of international research for higher education in Vietnam and maybe in other Asian countries in comparable contexts. Furthermore, the authors propose a way to determine the usability of research results in another context.
Mechanism of nickel-catalyzed hydroalkylation of branched 1,3-dienes

With the development of algorithms and theoretical chemistry, quantum chemical calculations have been used to explain and predict various chemical experiments. The hydroalkylation of conjugated olefins catalyzed by nickel is an important type of organic chemical reaction, and its mechanism has always been the focus of organic chemists. In this paper, a hydroalkylation reaction developed by the Mazet research group was studied in detail by means of density functional theory (DFT), and a possible mechanism model of the reaction was obtained. In this context, the attractive regioselectivity of the reaction was explored and rationally explained.
Comparison of Xpert MTB/RIF Ultra Results of Stool and Sputum in Children with Presumptive Tuberculosis in Southern Ethiopia

The introduction of stool as a readily obtainable sample and the recently developed simple one-step (SOS) stool processing method on Xpert MTB/RIF Ultra (Xpert Ultra) offer an opportunity for TB diagnosis in children. We conducted this study in secondary health facilities in Ethiopia, which are the first-level referral facilities for childhood TB diagnosis and treatment, with the aim to determine if stool-based TB diagnosis can be performed with a reasonable level of concordance with sputum tests using Xpert MTB/RIF Ultra. Eligible children 0–14 years old with presumptive pulmonary TB were asked to provide stools in addition to routinely requested sputum samples. We determined the level of agreement between the stool and sputum test results. Of the 373 children included in the study, 61% were <5 years of age and 56% were male. Thirty-six children (9.7%) were diagnosed with TB, and all started treatment. The rate of concordance between stool and sputum was high, with a kappa value of 0.83 (p < 0.001). There were more Xpert Ultra positive results on stool (n = 27 (7.2%)) than on sputum/NGA (n = 23 (6.2%)). Laboratories in secondary hospitals can perform stool-based TB diagnosis in children, with high concordance between stool and sputum test results reaffirming the applicability of the SOS stool method.
Integral spectroscopy of black hole transients and multi-wavelengh study of a new accreting binary system

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A joint indoor positioning scheme exploiting pedestrian dead reckoning and radio frequency tomography

ABSTRACT The pedestrian dead reckoning (PDR) is a popular technique for recognizing a pedestrian’s trajectory. However, its inherent disadvantage of susceptibility to error accumulation limits its performance as the travelled distance is increased. Various techniques are combined with PDR to mitigate the error accumulation by regular position resetting. The radio frequency (RF) Tomography is an emerging technology for localization by sensing the received signal strength (RSS) fluctuation on a line-of-sight wireless link (LOSL). Conventional RF Tomography based schemes need specific large-scale networks and face with the problem of harsh environments and high hardware costs. Thus in this paper, we proposed the flexible and practical GF operators for PDR resetting work, in which we introduce the displacement estimation by PDR technique and the LOSL triggering sequence to build a PDR geometrical formulation (PDR-GF) model, and then this model is optimized by Particle Swarm Optimization (PSO) algorithm for crossing point (CP) estimation on the LOSLs. Finally, the estimated CP is in turn used for regular position resetting. Practical experiments are performed to evaluate the proposed positioning scheme. According to the results, the proposed scheme can achieve a finer accuracy of less than 1 m, outperforming the existing RSS-PDR positioning scheme.
Fractal analysis of Dow Jones industrial index returns

The Dow Jones Industrial Average 30 (DJIA30) Index was analyzed to show that models based on the Fractal Market Hypothesis (FMH) are preferable to those based on the Efficient Market Hypothesis (EMH). In a first step, Rescaled Range Analysis was applied to search for long term dependence between index returns. The Hurst coefficient was computed as a measure of persistence in the trend of the observed time series. A Monte Carlo simulation based on both Geometric Brownian Motion (GBM) and Fractional Brownian Motion (FBM) models was used in the second step to investigate the forecasting ability of each model in a situation where information about future prices is lacking. In the third step, the volatility of the index returns obtained from the simulated GBM and FBM was considered together with that produced by a GARCH(1,1) model in order to determine the approach that minimizes the Value at Risk (VaR) and the