Miracle-dz/UniFAR-FTUs huggingface dataset:
Microglia Depletion Selectively Eliminates a Singular Form of Hippocampal Long-Term Potentiation

There has been considerable recent interest in the possibility that microglia contribute to synaptic plasticity and some forms of learning. We report here that elimination of the cells in young adult male mice with a 7-12 day treatment with an antagonist (PLX5622) of the colony stimulating factor 1 receptor causes a profound but highly selective impairment to long-term potentiation (LTP) expressed by lateral perforant path (LPP) synapses with the dentate gyrus. Input/output functions and frequency facilitation to repetitive stimulation were not measurably affected. Direct infusion of PLX5622 into slices from naiive mice did not reduce the magnitude of LPP-LTP. Microglial depletion had no detectable effect on LTP in either the medial perforant path input to the dentate gyrus or the Schaffer-commissural projections between fields CA3 and CA1. We conclude that microglia discretely regulate the unusual form of LTP expressed by the LPP and thus exert region-specific effects on circuit function within hippocampus.
Sensing the Full Dynamics of the Human Hand with a Neural Interface and Deep Learning

Theories about the neural control of movement are largely based on movement-sensing devices that capture the dynamics of predefined anatomical landmarks. However, neuromuscular interfaces such as surface electromyography (sEMG) can potentially overcome the limitations of these technologies by directly sensing the motor commands transmitted to the muscles. This allows for the continuous, real-time prediction of kinematics and kinetics without being limited by the biological and physical constraints that affect motion-based technologies. In this work, we present a deep learning method that can decode and map the electrophysiological activity of the forearm muscles into movements of the human hand. We recorded the kinematics and kinetics of the human hand during a wide range of grasping and individual digit movements covering more than 20 degrees of freedom of the hand at slow (0.5 Hz) and fast (1.5 Hz) movement speeds in healthy participants. The input of the model consists of three-hundred EMG sensors placed only on the extrinsic hand muscles. We demonstrate that our neural network can accurately predict the kinematics and contact forces of the hand even during unseen movements and with simulated real-time resolution. By examining the latent space of the network, we find evidence that it has learned the underlying anatomical and neural features of the sEMG that drive all hand motor behaviours.
Representations of complex contexts: A role for hippocampus

The hippocampus plays a critical role in supporting episodic memory, in large part by binding together experiences and items with surrounding contextual information. At present, however, little is known about the roles of different hippocampal subfields in supporting this item-context binding. To address this question, we constructed a task in which items were affiliated with differing types of context – cognitive associations that vary at the local, item level and membership in temporally organized lists that linked items together at a global level. Participants made item recognition judgments while undergoing high-resolution fMRI imaging. We performed voxel pattern similarity analyses to answer the question of how human hippocampal subfields represent retrieved information about cognitive states and the time at which a past event took place. As participants recollected previously presented items, activity patterns in the CA23DG subregion carried information about prior cognitive states associated with these items. We found no evidence to suggest reinstatement of information about temporal context at the level of list membership, but exploratory analyses revealed representations of temporal context at a coarse level in conjunction with representations of cognitive contexts. Results are consistent with characterizations of CA23DG as a critical site for binding together items and contexts in the service of memory retrieval.
Legal Text Classification and Summarization using Transformers and Joint Text Features

This paper presents the approaches undertaken while performing relevance classification on legal documents and thereby making summaries of them using extractive summarization for task 2 of the track ‘Artificial Intelligence for Legal Assistance’[1] proposed by the Forum of Information Retrieval Evaluation in 2021[2]. The approaches for relevance classification include fine tuning BERT for the down stream task of relevance classification and then using joint text features to classify relevance.
Effect of natural and artificial photoperiods and fluctuating temperature on age of first mating and mating frequency in the navel orangeworm, Amyelois transitella effects on mating

The effect of weak illumination during part or all of the scotophase on mating frequency of navel orangeworm, Amyelois transitella (Walker) (Lepidoptera: Pyralidae), was examined in environmental chambers under long photoperiods and constant warm temperature (colony conditions) or shorter photoperiods and a cooler thermoperiod intended to mimic spring conditions in our region. These data were compared to mating frequencies in sentinel females placed in the field during the first three weeks of May. Under colony conditions weak illumination in the final hour of the scotophase resulted in ~90% mating on the first day after eclosion; significantly greater mating compared to complete darkness throughout the scotophase, weak illumination throughout the scotophase, or weak illumination for both the first and last hour of the scotophase. In an environmental chamber programmed to simulate spring conditions, little mating occurred on the first night after eclosion and three nights were required for more than 50% of the females to mate. There was no difference in mating frequency with between moths exposed to complete darkness throughout the scotophase and those provided with weak illumination in the last half hour of the scotophase or throughout the scotophase. This delay in age of first mating was consistent with field observations with sentinel females at May in the central San Joaquin Valley. The authors conclude that, along with greater longevity and later oviposition, first mating occurs at a later age in spring conditions compared to summer conditions in this species. Planned studies of the effect of delayed mating in first and second flights will need to take these factors into account.
Discrimination of the fundamental frequency by children: a comparison of two alternative procedures

This study investigated the fundamental frequency ( F 0 ) discrimination of complex tones by children under two decision paradigms. Children aged 4, 5, 6, 10 and young adults participated in the study. In the 2-interval, 2-alternative forced-choice (2I-2A FC) decision paradigm, participants were asked to decide whether the two pairs of tones were the same or different. In the 3-interval, 2-alternative forced-choice (3I-2A FC) decision paradigm, they were required to identify the tone in the second or third interval that was identical to the first tone. The F 0 discrimination ability was examined with reference to a standard tone with 120Hz F 0 . The results showed that children’s F 0 discrimination under both decision paradigms reached adult level by 10 years of age. The results also indicated that the F 0 discrimination thresholds found in the 2I-2A FC decision paradigm were significant smaller than those found in the 3I-2A FC decision paradigm. No interaction effect was observed between the effect of age and task-related demand on memory. The findings give implication for the choice of decision-making paradigm in further investigation on the perception studies in normally developing children and the working memory studies in children with disordered development.
Recurrent fine structures in Jovian S-burst emission

Recent digital observations of Jovian S–emission are presented. They have been performed with high sensitivity (10 Jy) at the Kharkov UTR–2 radiotelescope, using receivers with high time and frequency resolutions (down to 5 ms and 13 kHz, and 2 ms at 30 selected frequencies), over long tracking times (hours) and a broad spectral range (>10 ÷ 15 MHz). Their analysis allows us to constrain the S–bursts source location and radiation pattern as a function of frequency, and to draw information about the geometrical structure of the Io Flux Tube (IFT) and its dynamics. New features of the Jovian S–emission are revealed, related to the evolution of the S– bursts fine structure during storms. Several observed characteristics of S–emission are discussed in the frame of a generation model [Ryabov, 1992, 1994] in which S–bursts are the final product of ruptures of small–scale current filaments circling around the IFT surface, including the overall phenomenology of S–bursts dynamic spectra (complexity as a function of the source observed – Io–B, Io–C, etc. – , evolution of the S–bursts fine structure during storms, occurrence distributed in several spectral sub–bands and their fluctuations and drifts) and morphological details (individual bursts crossing the spectral gap between bands, fixed–frequency durations, dotted patterns in the frequency–time plane, complex fine structures including positive drifts). Special attention is given to repeatable fine structures in the f–t plane, and interpretations are proposed.
Research Progress of Personnel Positioning Technology in Coal Mine Based on UWB

The technology of personnel positioning in coal mine has important practical significance for coal mine safety production and information management. In this paper, the characteristics of the underground personnel positioning system in coal mine and the judging basis of the positioning system are summarized, and the advantages of UWB positioning technology are put forward by comparing the technical features of wireless communication technologies such as Wifi, Zigbee, WSN, RFID and UWB. Based on the analysis of the difficulties and influencing factors of personnel positioning technology in coal mine, the development status of UWB positioning technology in recent years and its application in personnel positioning in coal mine are summarized, this paper compares the technical characteristics of TOF, TOA and TDOA, three kinds of location methods commonly used in UWB location technology, and summarizes the technical status of the improvement and optimization of location algorithms in recent years, the purpose of this paper is to provide reference and direction for the development of personnel positioning technology and the application of UWB technology in coal mine.
A Coarse Grained Reconfigurable Architecture for SHA-2 Acceleration

The development of high-speed SHA-2 hardware with high flexibility is urgently needed because SHA-2 functions are widely employed in numerous fields, from loT devices to cryp-to currency. Unfortunately, the existing SHA-2 circuits have difficulty in achieving high flexibility and hardware efficiency. Therefore, this paper proposes a coarse-grained reconfigurable architecture (CGRA) for accelerating SHA-2 computation, named a CGRA SHA-2 accelerator. To effectively support various algorithms and requirements, three optimization techniques are proposed to achieve high flexibility and hardware efficiency. First, an on-demand pro-cessing element array is proposed to enable flexible computation for long and short messages. Second, a dual-ALU processing element (D-PE) is proposed to compute various SHA-2 functions. Third, the pipelined dual-ALU architecture is proposed to reduce the critical paths, leading to remarkably improved performance and hardware efficiency. The accuracy of our proposed accelerator is verified on a real hardware platform (the Xilinx Alveo U280 FPGA). Besides, the experimental results on several FPGAs prove that the proposed CGRA SHA-2 accelerator is significantly higher performance, hardware efficiency, and flexibility than existing works.
Feature Based Opinion Mining for Mobile Reviews

Item surveys or client criticism has become an ideal platform for sellers to promote their goods and clients to expand their knowledge and purchase wisely. As the online system of buying and selling is expanding, a measure of client audits additionally has been expanded undeniably. Thus it is an intense assignment for retailers just as clients to peruse the surveys related with the item. Notion examination settle this issue by looking over free content audits and giving the assessment synopsis. Highlight based supposition based investigation strategies expands the granularity of notion of examination by dissecting extremity related with highlights in the given free content. The main objective of this work is to plan a system that predicts extremity and to plan a score which determines the stratum of extremity. Resulting component-level scores are summed up as per the clients’ need of interest.
Continuous Estimation of Lower Limb Prosthesis Based on GBDBN and BP Network

A method for continuous estimation of sagittal joint angles based on surface electromyography(sEMG) signals and BP neural networks is proposed for the problem of continuous motion control of lower limb prostheses. We use the sEMG signals of eleven muscles related to knee and ankle joint motions and calculate the knee and ankle joint angles at the same time. First, a feature extraction method based on Gaussian-Bernoulli deep belief network (GBDBN) was used to extract the optimal feature vector from the multichannel sEMG signals, and then, the optimal features were mapped to the knee-ankle joint angles using a BP network. The root mean square error (RMSE) and Pearson correlation coefficient were used as evaluation indexes. The results show that the feature extraction method with the GBDBN proposed in this paper is superior to the conventional method, and the features extracted by the GBDBN and the BP network are a better combination for building prediction models.
Distributed Algorithms for the Graph Biconnectivity and Least Common Ancestor Problems

Graph connectivity analysis is one of the primary ways to analyze the topological structure of social networks. Graph biconnectivity decompositions are of particular interest due to how they identify cut vertices and cut edges in a network. We present the first, to our knowledge, implementation of a distributed-memory parallel biconnectivity algorithm. As part of our algorithm, we also require the computation of least common ancestors (LCAs) of non-tree edge endpoints in a BFS tree. As such, we also propose a novel distributed algorithm for the LCA problem. Using our implementations, we observe up to a 14.8× speedup from 1 to 128 MPI ranks for computing a biconnectivity decomposition.
A Simpler Proof of the Four Functions Theorem and Some New Variants

The celebrated Four Functions Theorem of Ahlswede and Daykin is a functional correlation inequality on distributive lattices with myriad applications. Ruozzi proved a variant of the inequality and used it to settle a major conjecture in the area of graphical models. We prove a new functional correlation inequality in the same vein which simplifies the proof of both the Four Functions Theorem and of Ruozzi’s inequality and suggests a unified picture for correlation inequalities on distributive lattices.
Modern Theory of Thermoelectricity

In recent years, there have been important developments in the design and fabrication of new thermoelectrics. While a decade ago, progress was mainly empirical, recent advances in theoretical methods have led to a deeper understanding of the parameters that affect the performance of materials in thermoelectric devices. These have brought the goal of producing materials with the required characteristics for commercial application a significant step closer. A search for efficient materials requires a fully microscopic treatment of the charge and heat transport, and the aim of this book is to explain all thermoelectric phenomena from this modern quantum-mechanical perspective. In the first part on phenomenology, conjugate current densities and forces are derived from the condition that the rate of change of the entropy density of the system in the steady state is given by the scalar product between them. The corresponding transport coefficients are explicitly shown to satisfy Onsager's reciprocal relations. The transport equations are solved for a number of cases, and the coefficient of performance, the efficiency, and the figure of merit are computed. State-of-the-art methods for the solution of the transport equations in inhomogeneous thermoelectrics are presented. A brief account on how to include magnetization transport in the formalism is also given. In the second part, quantum mechanical expressions for the transport coefficients are derived, following the approach by Luttinger. These are shown to satisfy Onsager's relations by construction. Three lattice models, currently used to describe strongly correlated electron systems, are introduced: the Hubbard, the Falicov-Kimball, and the periodic Anderson model (PAM), and the relevant current density operators are derived for each of them. A proof of the Jonson-Mahan theorem, according to which all transport coefficients for these models can be obtained from the integral of a unique transport function multiplied by different powers of the frequency, is given. The third part compares theory and experiment. First for the thermoelectric properties of dilute magnetic alloys, where the theoretical results are obtained from poor man's scaling solutions to single impurity models. Then it is shown that the experimental data on heavy fermions and valence fluctuators are well reproduced by the transport coefficients computed for the PAM at low and high temperature. Finally, results obtained from first principles calculations are shown, after a short introduction to density functional theory and beyond. A number of useful appendices complete the book.
U-Net Fundus Retinal Vessel Segmentation Method Based on Multi-scale Feature Fusion

In the task of retinal blood vessel segmentation, the existing algorithm has the problem of low segmentation accuracy due to the complex morphology of the retinal small blood vessel structure and the uneven illumination of the image. To solve this problem, this paper improves on the traditional U-Net and proposes a Res-HSPP U-Net. Firstly, the original convolution of the encoding and decoding parts is changed to the Res-HSPP structure, which can balance the width and depth of the network. At the same time, the dilated convolution group is used to obtain a larger receptive field and the fusion of multi-scale feature vector information to enhance the ability to extract the features of small blood vessels and reduce the problem of loss of detailed information. Secondly, the ECA attention module is introduced to learn the feature channels after convolution, increase the weight of the effective feature channels, and strengthen the features of small blood vessels. Compared with other channel attention modules, the ECA module has the characteristics of light weight and higher computational efficiency. The algorithm in this paper is verified on the public dataset DRIVE (Digital Retinal Images For Vessel Extraction). The final performance indicators are: accuracy rate of 96.87%, specific rate of 98.54%, sensitivity of 82.87%, F1-score of 82.51%. Experiment results show that the performance of this algorithm is better than that of advanced algorithms in recent years.
A Deep Reinforcement Learning Motion Control Strategy of a Multi-rotor UAV for Payload Transportation with Minimum Swing

This paper addresses the problem of controlling a multirotor UAV with a cable-suspended load. In order to ensure the safe transportation of the load, the swinging motion, induced by the strongly coupled dynamics, has to be minimized. Specifically, using the Twin Delayed Deep Deterministic Policy Gradient (TD3) Reinforcement Learning algorithm, a policy Neural Network is trained in a model-free manner which navigates the vehicle to the desired waypoints while, simultaneously, compensating for the load oscillations. The learned policy network is incorporated into the cascaded control architecture of the autopilot by replacing the common PID position controller and, thus, communicating directly with the inner attitude one. The performance of the proposed policy is demonstrated through a comparative simulation and experimental study while using an octorotor UAV.
Accelerated Monte Carlo method for computation of photon migration by matrix description of photon direction

A new accelerated Monte Carlo method that uses matrix description of photon migration (instead of vector description) for computation of photon migration in highly scattering media is presented. This method requires two multi-clock floating-point instructions (one division and one square root operation) less for each scattering event than the standard method. Theoretical considerations show that the new method reduces calculation time about 4% for personal computers with a one-pipeline floating-point coprocessor, or more on computers having multi-pipeline floating-point units. Tests performed on selected types of personal computers have shown a few percent (from 2.5% to 6%) decrease in computation time when the new method was used.
Dirty Paper Coding for Consecutive Messages with Heterogeneous Decoding Deadlines in the Finite Blocklength Regime

To improve reliability in latency-critical applications, a point-to-point communication system with heterogeneous decoding deadlines is considered. Unlike existing work, this system allows for a message to arrive before the decoding deadline of a prior message. A new coding scheme with finite blocklength codewords is introduced exploiting the dirty paper coding principle. Rigorous bounds are derived for achievable error probabilities. Moreover, numerical results illustrate that the proposed scheme outperforms time sharing for a wide range of blocklengths.
Further characterisation of the time-dependent vascular effects of ∆ 9 -tetrahydrocannabinol (THC).

We have previously shown that over time (2 h), the active ingredient of cannabis, ∆ 9 tetrahydrocannabinol (THC) produces peroxisome proliferator-activated receptor gamma (PPAR γ) -mediated vasorelaxation of conduit arteries. We have now investigated whether incubation with THC affects agonist-stimulated contractile (methoxamine) and endothelium-dependent vasorelaxant (acetylcholine) responses in the rat superior mesenteric artery (G0) and aorta by myography. We have also investigated whether similar responses are observed in isolated resistance (G3) vessels of the mesenteric bed. In both the aorta and G0, incubation with THC (10 µ M) for 2 h, but not 10 min, significantly attenuated the contractile responses to methoxamine. This effect of THC was abolished in the presence of the enzyme catalase, which breaks down hydrogen peroxide (H 2 O 2 ), and was reduced in the presence of the superoxide dismutase (SOD) inhibitor, DETCA, but was not PPAR γ -mediated. THC also inhibited calcium influx in a H 2 O 2 -dependent manner. In G0, but not the aorta, incubation with THC (10 µ M, 2 h) significantly enhanced endothelium-dependent vasorelaxation. This was inhibited by a PPAR γ antagonist (GW9662), catalase and DETCA, but not by the NO synthase inhibitor L-NAME. By contrast, G3, no time-dependent of and THC led to potentiation of contractile responses and blunting appears to data further vascular actions highlight effects of in different arterial of