Miracle-dz/UniFAR-FTUs huggingface dataset:
The VTA-BLA-NAc circuit for sex reward inhibited by VTA GABAergic neurons under stress in male mice

Anhedonia, inability to experience pleasure from rewarding or enjoyable activities, is the prominent symptom of depression that involves dysfunction of the reward processing system. Both genetic predisposition and life events are thought to increase the risk for depression, in particular life stress. The cellular mechanism underlying stress modulating the reward processing neural circuits and subsequently disrupting reward-related behaviors remains elusive. We identify the VTA-BLA-NAc pathway as being activated by sex reward. Blockade of this circuit induces depressive-like behaviors, while reactivation of VTA neurons associated with sexual rewarding experience acutely ameliorates the impairment of reward-seeking behaviors induced by chronic restraint stress. Our histological and electrophysiological results show that the VTA neuron subpopulation responding to restraint stress inhibits the responsiveness of the VTA dopaminergic neurons to sexual reward. Together, these results reveal the cellular mechanism by which stress influences the brain reward processing system and provide a potential target for depression treatment.
How to align arthropod legs

How to align leg segments between the four groups of arthropods (insects, crustaceans, myriapods, and chelicerates) has tantalized generations of researchers, as this would answer over a century of speculation about the origins and homologies of the fascinating diversity of arthropod appendages and outgrowths. Here we compare the expression and loss-of-function phenotypes of leg patterning genes in crustaceans, insects, and arachnids using our own and previously published data. We find that all arthropod leg segments correspond to each other in a one-to-one fashion. This alignment suggests that chelicerates with seven leg segments incorporated a proximal leg segment into the body wall. In addition, this alignment suggests that insect and myriapod tracheae are convergent and homologous structures: each evolved via the independent internalization of an ancestral gill (respiratory exite) on the proximal-most leg segment of their shared ancestor. A framework for understanding the homologies of arthropod appendages opens up a powerful system for studying the origins of novel structures, the plasticity of morphogenetic fields across vast phylogenetic distances, and the convergent evolution of shared ancestral developmental fields.
Targeted sensors for glutamatergic neurotransmission

Optical report of neurotransmitter release allows visualization of excitatory synaptic transmission. Sensitive genetically-encoded glutamate reporters operating with a range of affinities and emission wavelengths are available. However, without targeting to synapses, the specificity of the fluorescent signal is uncertain, compared to sensors directed at vesicles or other synaptic markers. We fused the state-of-the-art reporter iGluSnFR to glutamate receptor auxiliary proteins in order to target it to postsynaptic sites. Chimeras of Stargazin and gamma-8 that we named SnFR-γ2 and SnFR-γ8, retained function and reported spontaneous glutamate release in hippocampal cells, with apparently diffraction-limited spatial precision. In autaptic neurons on micro island cultures, evoked release could be quantitatively detected at tens of synapses in a field of view whilst evoked currents were recorded simultaneously. These experiments revealed a specific postsynaptic deficit from Stargazin overexpression, resulting in synapses with normal release but without postsynaptic responses. This defect was reverted by delaying overexpression. By working at different calcium concentrations, we determined that SnFR-γ2 is a linear reporter of the global quantal parameters and short term synaptic plasticity, whereas iGluSnFR is not. On average, half of iGluSnFR regions of interest showing evoked fluorescence changes had intense rundown, whereas less than 5% of SnFR-γ2 ROIs did. We provide an open-source analysis suite for extracting quantal parameters including release probability from fluorescence time series of individual and grouped synaptic responses. Taken together, postsynaptic targeting improves several properties of iGluSnFR and further demonstrates the importance of subcellular targeting for optogenetic actuators and reporters.
Long‐Term Integrated Nutrient Management for Rice‐Based Cropping Pattern: Effect on Growth, Yield, Nutrient Uptake, Nutrient Balance Sheet, and Soil Fertility

Abstract A 7‐year‐long field trial was conducted on integrated nutrient management for a dry season rice (Boro)–green manure (GM)–wet season rice (T. Aman) cropping system at the Bangladesh Rice Research Institute Farm, Gazipur during 1993–1999. Five packages of inorganic fertilizers, cow dung (CD), and GM dhaincha (Sesbania aculeata) were evaluated for immediate and residual effect on crop productivity, nutrient uptake, soil‐nutrient balance sheet, and soil‐fertility status. Plant height, active tiller production, and grain and straw yields were significantly increased as a result of the application of inorganic fertilizer and organic manure. Usually, the soil‐test‐based (STB) fertilizer doses for a high‐yield goal produced the highest grain yield of 6.39 t ha−1 (average of 7 years) in Boro rice. Application of CD at the rate of 5 t ha−1 (oven‐dry basis) once a year at the time of Boro transplanting supplemented 50% of the fertilizer nutrients other than nitrogen (N) in the subsequent crop of the cropping pattern. A positive effect of GM on the yield of T. Aman rice was observed. Following GM, the application of reduced doses of phosphorus (P), potassium (K), sulfur (S), and zinc (Zn) to the second crop (T. Aman) did not reduce yield, indicating the beneficial residual effect of fertilizer applied to the first crop (Boro rice) of the cropping pattern. The comparable yield of T. Aman was also observed with reduced fertilizer dose in CD‐treated plots. The total P, K, and S uptake (kg/ha/yr) in the unfertilized plot under an irrigated rice system gradually decreased over the years. The partial nutrient balance in the unfertilized plot (T1) was negative for all the nutrients. In the fertilized plots, there was an apparent positive balance of P, S, and Zn but a negative balance of N and K. This study showed that the addition of organic manure (CD, dhaincha) gave more positive balances. In the T4c treatment at 0–15 cm, the application of chemical fertilizers along with the organic manures increased soil organic carbon by (C) 0.71%. The highest concentration of total N was observed with T4c followed by T4d and T4b, where CD was applied in Boro season and dhaincha GM was incorporated in T. Aman season. The sixfold increase in soil‐available P in T4b‐, T4c‐, T4a‐treated plots was due to the addition of CD. Dhaincha GM with the combination of chemical fertilizer helps to mobilize soil‐available P by 3 to 6 ppm. The highest amount of soil‐available S was found in T4c‐ and T4a‐treated plots. It was 2.5 times higher than that of the initial soil. The application of CD and dhaincha GM along with chemical fertilizers not only increased organic C, total N, available P, and available S but also increased exchangeable K, available Zn, available iron (Fe), and available manganese (Mn) in soil.
Modifiability of residual force depression in single muscle fibers following uphill and downhill training in rats

Following active muscle shortening, steady‐state isometric force is less than a purely isometric contraction at the same muscle length and level of activation; this is known as residual force depression (rFD). It is unknown whether rFD at the single muscle fiber level can be modified via training. Here we investigated whether rFD in single muscle fibers is modifiable through downhill and uphill running in the extensor digitorum longus (EDL) and soleus (SOL) muscles in rats. Rats were run uphill or downhill 5 days/week for 4 weeks. After muscles were dissected and chemically permeabilized, single fibers were tied between a length controller and force transducer, transferred to an activating solution, with ATP and pCa of 4.2 for mechanical testing. rFD was quantified after active fiber shortening from an average sarcomere length (SL) of 3.1–2.5 µm at a relative speed of 0.15 fiber lengths/s (slow) and 0.6 fiber lengths/s (fast). rFD was calculated as the difference in force (normalized to cross‐sectional area) during the isometric steady‐state phase following active shortening and the purely isometric contraction. In addition to rFD, mechanical work of shortening and stiffness depression were also calculated. rFD was present for both the EDL (6–15%) and SOL (1–2%) muscles, with no effect of training. rFD was greater for the EDL than SOL which closely corresponded to the greater stiffness depression in the EDL, indicating a greater inhibition of cross‐bridge attachments. These results indicate that while rFD was observed, training did not appear to alter this intrinsic history‐dependent property of single muscle fibers.
Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback

Sustained attention is a cognitive ability to maintain task focus over extended periods of time (Mackworth, 1948; Chun, Golomb, & Turk-Browne, 2011). In this study, scalp electroencephalography (EEG) signals were processed in real time using a 32 dry-electrode system during a sustained visual attention task. An attention training paradigm was implemented, as designed in DeBettencourt, Cohen, Lee, Norman, and Turk-Browne (2015) in which the composition of a sequence of blended images is updated based on the participant's decoded attentional level to a primed image category. It was hypothesized that a single neurofeedback training session would improve sustained attention abilities. Twenty-two participants were trained on a single neurofeedback session with behavioral pretraining and posttraining sessions within three consecutive days. Half of the participants functioned as controls in a double-blinded design and received sham neurofeedback. During the neurofeedback session, attentional states to primed categories were decoded in real time and used to provide a continuous feedback signal customized to each participant in a closed-loop approach. We report a mean classifier decoding error rate of 34.3% (chance = 50%). Within the neurofeedback group, there was a greater level of task-relevant attentional information decoded in the participant's brain before making a correct behavioral response than before an incorrect response. This effect was not visible in the control group (interaction p=723e-4), which strongly indicates that we were able to achieve a meaningful measure of subjective attentional state in real time and control participants' behavior during the neurofeedback session. We do not provide conclusive evidence whether the single neurofeedback session per se provided lasting effects in sustained attention abilities. We developed a portable EEG neurofeedback system capable of decoding attentional states and predicting behavioral choices in the attention task at hand. The neurofeedback code framework is Python based and open source, and it allows users to actively engage in the development of neurofeedback tools for scientific and translational use.
Implicit Regularization and Momentum Algorithms in Nonlinearly Parameterized Adaptive Control and Prediction

Stable concurrent learning and control of dynamical systems is the subject of adaptive control. Despite being an established field with many practical applications and a rich theory, much of the development in adaptive control for nonlinear systems revolves around a few key algorithms. By exploiting strong connections between classical adaptive nonlinear control techniques and recent progress in optimization and machine learning, we show that there exists considerable untapped potential in algorithm development for both adaptive nonlinear control and adaptive dynamics prediction. We begin by introducing first-order adaptation laws inspired by natural gradient descent and mirror descent. We prove that when there are multiple dynamics consistent with the data, these non-Euclidean adaptation laws implicitly regularize the learned model. Local geometry imposed during learning thus may be used to select parameter vectors—out of the many that will achieve perfect tracking or prediction—for desired properties such as sparsity. We apply this result to regularized dynamics predictor and observer design, and as concrete examples, we consider Hamiltonian systems, Lagrangian systems, and recurrent neural networks. We subsequently develop a variational formalism based on the Bregman Lagrangian. We show that its Euler Lagrange equations lead to natural gradient and mirror descent-like adaptation laws with momentum, and we recover their first-order analogues in the infinite friction limit. We illustrate our analyses with simulations demonstrating our theoretical results.
A machine learning‐based risk scoring system for infertility considering different age groups

The application of artificial intelligence (AI) methods in medical field is increasing year by year; however, few studies have applied AI methods in the reproductive field. In view of the complexity of infertility diagnosis and treatment, a machine learning‐based risk scoring system for infertility was constructed in this paper to help clinicians better grasp the patient's condition. First, eight key features of infertility are screened out by feature selection. Second, the entropy‐based feature discretization method was used to divide the feature abnormal intervals, and the random forest was used to determine the weight of each feature. Finally, the pregnancy outcome can be predicted according to the overall risk score of patients, which is helpful for doctors to choose targeted treatment more efficiently. It is worth noting that, to further improve the accuracy of the diagnosis, we also divided the patients into age groups and constructed the corresponding risk scoring system for patients of different age groups. The stability test results show the good performance of the system. The risk scoring system for infertility built in this paper is a meaningful exploration of the application of AI in the field of reproduction.
Laboratory measurements of diffusion coefficients for trichloroethylene and orthoxylene in undisturbed tuff

Exploratory laboratory research was performed to evaluate the fate of two organic contaminants in the unsaturated zone of the Bandelier Tuff at Los Alamos National Laboratory chemical waste site. This research was undertaken in support of the geohydrological characterization of the unsaturated zone and ultimately to facilitate environmental transport predictions. In these vapor phase diffusitivity studies a laboratory method was developed for direct measurement of gaseous diffusion through undisturbed cores of Bandelier Tuff
Distinct Neural Correlates of Linguistic and Non-Linguistic Demand

Abstract In this study, we investigated how the brain responds to task difficulty in linguistic and non-linguistic contexts. This is important for the interpretation of functional imaging studies of neuroplasticity in post-stroke aphasia, because of the inherent difficulty of matching or controlling task difficulty in studies with neurological populations. Twenty neurologically normal individuals were scanned with fMRI as they performed a linguistic task and a non-linguistic task, each of which had two levels of difficulty. Critically, the tasks were matched across domains (linguistic, non-linguistic) for accuracy and reaction time, such that the differences between the easy and difficult conditions were equivalent across domains. We found that non-linguistic demand modulated the same set of multiple demand (MD) regions that have been identified in many prior studies. In contrast, linguistic demand modulated MD regions to a much lesser extent, especially nodes belonging to the dorsal attention network. Linguistic demand modulated a subset of language regions, with the left inferior frontal gyrus most strongly modulated. The right hemisphere region homotopic to Broca’s area was also modulated by linguistic but not non-linguistic demand. When linguistic demand was mapped relative to non-linguistic demand, we also observed domain by difficulty interactions in temporal language regions as well as a widespread bilateral semantic network. In sum, linguistic and non-linguistic demand have strikingly different neural correlates. These findings can be used to better interpret studies of patients recovering from aphasia. Some reported activations in these studies may reflect task performance differences, while others can be more confidently attributed to neuroplasticity.
Spatial Spectrum-Based Channel Estimation for Wideband mmWave System With Beam Squint

Channel estimation for millimeter wave (mmWave) systems is challenging due to their large antenna arrays. Owing to the sparse scattering nature of the mmWave channel, channel estimation can be performed by estimating the directions and the gains of paths. Most existing schemes assume that a wideband mmWave channel exhibits a common sparsity in the frequency domain. Unfortunately, they ignore the beam squint effect caused by the wide bandwidth, resulting in severe performance loss. In this paper, we investigate the wideband channel estimation problem with beam squint. Specifically, by utilizing measurement signals at all subcarriers, we propose a spatial spectrum-based scheme for a subarray architecture that requires only a single training slot. We first prove that the scheme can accurately obtain the spatial spectrum from a theoretical perspective. Then, we design the beamforming weights of the subarray to avoid pseudo peaks and analyze the inherent spectrum ambiguity phenomenon under the subarray architecture. Finally, to cope with beam squint, we divide the entire bandwidth into multiple subbands and design a combination criterion for the spatial spectrum of each subband. During this process, we prove that the spectrum ambiguity is eliminated, and the joint estimation of the path directions can be obtained. Simulation results demonstrate that the proposed scheme has better estimation accuracy than other methods and significantly reduces the required number of training slots.
What is Meant by Permissionless Blockchains?

The term permissionless has established itself within the context of blockchain and distributed ledger research to characterize protocols and systems that exhibit similar properties to Bitcoin. However, the notion of what is meant by permissionlessness is often vague or left implicit within the various literature, rendering it imprecise and hard to compare. We hereby shed light onto this topic by revising research that either incorporates or deﬁnes the term permissionless and systematically expose the properties and characteristics that its utilization intends to capture. Based on this review, we highlight current shortcomings and blind spots within the available deﬁnitions. In particular, the ability to freely perform transactions between users is often not adequately incorporated and diﬀerent actor roles are left unspeciﬁed. Furthermore, the topics of privacy and governance appear to be largely overlooked.
Crystal structure of Mn(II)(H2O)(2,13-dimethyl-3,6,9,12,18-pentaazabicyclo[ 12.3.1]octadeca-1(18),2,12,14,16-pentaene)-bis-(maleonitriledithiolate) nickel(II), C23H25MnN9NiOS4

Abstract C23H25MnN9NiOS4, monoclinic, P21/c (no. 14), a = 19.48(1) Å, b = 7.462(4) Å, c = 21.41(1) Å, β = 109.824(8)°, V = 2928.6 Å3, Z = 4, Rgt(F) = 0.0811, wRref(F2) = 0.2123, T = 293 K.
A Data Augmentation Approach to Distracted Driving Detection

Distracted driving behavior has become a leading cause of vehicle crashes. This paper proposes a data augmentation method for distracted driving detection based on the driving operation area. First, the class activation mapping method is used to show the key feature areas of driving behavior analysis, and then the driving operation areas are detected by the faster R-CNN detection model for data augmentation. Finally, the convolutional neural network classification mode is implemented and evaluated to detect the original dataset and the driving operation area dataset. The classification result achieves a 96.97% accuracy using the distracted driving dataset. The results show the necessity of driving operation area extraction in the preprocessing stage, which can effectively remove the redundant information in the images to get a higher classification accuracy rate. The method of this research can be used to detect drivers in actual application scenarios to identify dangerous driving behaviors, which helps to give early warning of unsafe driving behaviors and avoid accidents.
Circuit-PSI With Linear Complexity via Relaxed Batch OPPRF

Abstract In 2-party Circuit-based Private Set Intersection (Circuit-PSI), P0 and P1 hold sets S0 and S1 respectively and wish to securely compute a function f over the set S0 ∩ S1 (e.g., cardinality, sum over associated attributes, or threshold intersection). Following a long line of work, Pinkas et al. (PSTY, Eurocrypt 2019) showed how to construct a concretely efficient Circuit-PSI protocol with linear communication complexity. However, their protocol requires super-linear computation. In this work, we construct concretely efficient Circuit-PSI protocols with linear computational and communication cost. Further, our protocols are more performant than the state-of-the-art, PSTY – we are ≈ 2.3× more communication efficient and are up to 2.8× faster. We obtain our improvements through a new primitive called Relaxed Batch Oblivious Programmable Pseudorandom Functions (RB-OPPRF) that can be seen as a strict generalization of Batch OPPRFs that were used in PSTY. This primitive could be of independent interest.
Magnetic RSA

In a recent paper Géraud-Stewart and Naccache [GSN21] (GSN) described an non-interactive process allowing a prover P to convince a veriﬁer V that a modulus n is the product of two randomly generated primes ( p, q ) of about the same size. A heuristic argument conjectures that P cannot control p, q to make n easy to factor. GSN’s protocol relies upon elementary number-theoretic properties and can be implemented eﬃciently using very few operations. This contrasts with state-of-the-art zero-knowledge protocols for RSA modulus proper generation assessment. This paper proposes an alternative process applicable in settings where P co-generates a modulus n “ p 1 q 1 p 2 q 2 with a certiﬁcation authority V . If P honestly cooperates with V , then V will only learn the sub-products n 1 “ p 1 q 1 and n 2 “ p 2 q 2 . A heuristic argument conjectures that at least two of the factors of n are beyond P ’s control. This makes n appropriate for cryptographic use provided that at least one party (of P and V ) is honest. This heuristic argument calls for further cryptanalysis.