Miracle-dz/UniFAR-FTUs huggingface dataset:
Error-based or target-based? A unified framework for learning in recurrent spiking networks

The field of recurrent neural networks is over-populated by a variety of proposed learning rules and protocols. The scope of this work is to define a generalized framework, to move a step forward towards the unification of this fragmented scenario. In the field of supervised learning, two opposite approaches stand out, error-based and target-based. This duality gave rise to a scientific debate on which learning framework is the most likely to be implemented in biological networks of neurons. Moreover, the existence of spikes raises the question of whether the coding of information is rate-based or spike-based. To face these questions, we proposed a learning model with two main parameters, the rank of the feedback learning matrix R and the tolerance to spike timing τ⋆. We demonstrate that a low (high) rank R accounts for an error-based (target-based) learning rule, while high (low) tolerance to spike timing promotes rate-based (spike-based) coding. We show that in a store and recall task, high-ranks allow for lower MSE values, while low-ranks enable a faster convergence. Our framework naturally lends itself to Behavioral Cloning and allows for efficiently solving relevant closed-loop tasks, investigating what parameters (R,τ⋆) are optimal to solve a specific task. We found that a high R is essential for tasks that require retaining memory for a long time (Button and Food). On the other hand, this is not relevant for a motor task (the 2D Bipedal Walker). In this case, we find that precise spike-based coding enables optimal performances. Finally, we show that our theoretical formulation allows for defining protocols to estimate the rank of the feedback error in biological networks. We release a PyTorch implementation of our model supporting GPU parallelization.
Single Atoms with 6000-Second Trapping Lifetimes in Optical-Tweezer Arrays at Cryogenic Temperatures

We report on the trapping of single Rb atoms in tunable arrays of optical tweezers in a cryogenic environment at $\sim 4$ K. We describe the design and construction of the experimental apparatus, based on a custom-made, UHV compatible, closed-cycle cryostat with optical access. We demonstrate the trapping of single atoms in cryogenic arrays of optical tweezers, with lifetimes in excess of $\sim6000$ s, despite the fact that the vacuum system has not been baked out. These results open the way to large arrays of single atoms with extended coherence, for applications in large-scale quantum simulation of many-body systems, and more generally in quantum science and technology.
Regional disparities and their contribution to the coverage of the tetanus toxoid vaccine among women aged 15–49 years in Indonesia

Background: The prevention of Clostridium tetani bacterial infection through the administration of the tetanus toxoid (TT) vaccine in women is important. The purpose of this study was to determine the regional disparities and factors associated with TT vaccine coverage in women aged 15–49 years in Indonesia. Methods: The Indonesian Demographic Health Survey (IDHS) 2017 data was used in this study. A total of 36,028 women, aged 15–49 years were recruited using the two-stage stratified cluster sampling technique. The questionnaire used was based on the DHS Questionnaire Phase 7. Chi-squared and binary logistic regression were used in this study as part of the analysis. Results: We found that the TT vaccine coverage was 75.32% and that the majority were spread across several provinces. The provinces of Bali and Nusa Tenggara, the richer respondents, living in a rural area, visiting the health facility, having health insurance, and those currently working were factors making it more likely that the women would receive the TT vaccine. The respondents aged 15–24 years with a primary education level and the respondents who were divorced were less likely to receive the TT vaccine. Conclusion: The coverage of the TT vaccine among women can be increased by considering the regional disparities in Indonesia and the socio-economic demographic details of the respondents. Strengthening the policies from the central government in the local governments can improve the screening process and vaccine delivery outcomes. In addition, the importance of giving the TT vaccine to women needs to be relayed through health education in collaboration between health workers and the public.
Structural dynamics and binding free energy of neral-cyclodextrins inclusion complexes: molecular dynamics simulation

Abstract The inclusion complexation of neral, a cis-isomer of citral found in lemon grass (Cymbopogon citratus Stapf), and four different types of cyclodextrin (β-cyclodextrin (βCD), 2,6-dimethyl-βCD (2,6DMβCD), 2,6-dihydroxypropyl-βCD (2,6DHPβCD), and 2-hydroxypropyl-βCD (2HPβCD)) was investigated using molecular docking and molecular dynamics simulation approaches. The simulations show that the neral/CD inclusion complex could be formed in an aqueous solution with a 1:1 ratio. Three possible binding orientations were assessed for the encapsulation of neral (1neral, 7neral, and uneral) inside the hydrophobic interior of the host molecule. The uneral, in which both aldehyde and alkyl terminals point outward on the secondary rim of the CD, was observed to be the most preferential conformation in all neral/CD complexes. The theoretical calculations of the binding ability of the host–guest inclusion complexes agreed well with the experimental data, thereby supporting that the neral could bind inside the hydrophobic cavity of all CDs with nearly the same potency.
On Text Preprocessing for Early Detection of Depression on Social Media

Depression is a serious challenge to public health. Many of those who suffer from this disease use social media for information or relief. The text data produced by these users can be used to support research in this field. However, this raw information is not always suitable for use directly in machine learning. Hence, a comparative analysis was performed between different preprocessing techniques to verify the impact on the effectiveness of early depression detection on social media. The results show that the preprocessing contributes to an increase in the prediction effectiveness. Moreover, the mapping of emoticons to real emotion words was decisive to improve not only model’s effectiveness, but also to keep the balance between different evaluation measures.
Morphological descriptions and DNA barcodes of Oziella viscida n. sp. (Eriophyoidea, Phytoptidae) and two infrequently reported Trisetacus species (Nalepellidae) from Crimea

Abstract We report on a new phytoptid mite species, Oziella viscida n. sp. , collected in Western Crimea from sea rush, Juncus maritimus (Juncaceae), and give supplementary descriptions of two rarely encountered nalepellid species of the genus Trisetacus from pines: T. confusus Livshits & Vasilieva, 1982 (in Vasilieva et al. 1982) from needle sheaths of Pinus nigra ssp. pallasiana (Pinaceae), an endemic subspecies restricted to Crimea, and T. brevisetus Livshits & Sekerskaya, 1982 (in Vasilieva et al. 1982) from needle sheaths of Pinus brutia ssp. pityusa (Steven) Silba, a relatively isolated subspecies of Turkish pine (P. brutia Tenore) growing in Georgia, Caucasus and Crimea. Oziella viscida n. sp. is remarkable in that most specimens were found inhabiting the basal part of leaves and stems of J. maritimus, an area covered by a transparent, sticky exudate apparently secreted by the plant epidermis. The mites were completely embedded in this substance and, rather than crawling with their legs, were observed moving through the viscous material while bending their opisthosoma in a serpentine or wormlike manner—an adaptation that appears to be currently unreported in eriophyoids and possibly reminiscent of locomotion of ancestral “protoeriophyoids” associated with soil. In comparison to females, males of O. viscida n. sp. and T. confusus have a more distinct prodorsal shield pattern consisting of a larger number of longer lines. Three new barcode gene sequences were obtained: MZ220550 (Cox1, O. viscida n. sp., 1159 bp), MZ224497 (18S, 2012 bp, T. brevisetus), and MZ224498 (18S, 2013 bp T. confusus). A BLAST search of the 18S sequences of T. brevisetus and T. confusus shows them as slightly closer to other 18S sequences of Trisetacus from Pinaceae (95.5%–96.3% identity) than to Trisetacus from Cupressaceae (93.6%–94.0% identity). Comparison of sequences of nalepellids currently present in GenBank suggest that a complete 18S sequence KJ841938.1 (2252 bp) from China belongs to an identified Trisetacus from Pinaceae rather than to Setoptus koraiensis as labelled, highlighting the necessity to review carefully the sequences of Eriophyoidea prior to using them in phylogenetic analyses, as well as the need to recollect and resequence S. koraiensis to clarify the nature of the problematic data from GenBank assigned to this species.
The Effect of Cultural Trust on Cooperation in Two Behavioral Experiments

Trust is an important factor for cooperation in social dilemmas because of uncertainty and free-riding fears. Many contemporary social problems are characterized by uncertainty because they depend on the cooperation of thousands to resolve. Social trust as a personal belief is necessary but not sufficient for cooperation under these conditions. In contemporary social dilemmas, the trust-cooperation relationship likely depends on cultural trust: what people believe most other people believe about the trustworthiness of people in general. I test this theory in two experimental studies. In the first, cultural trust has an effect on cooperation independent of participants’ first-order social trust. In the second, I find that if participants learn that others expect them to not believe information on the trustfulness of most other people, they will behave more or less cooperatively, depending on whether the information indicates most others’ trust is high or low. I end with a discussion of the implications my findings have for addressing social dilemmas in an era of declining social trust.
The Effects of Megaproject Social Responsibility on Participating Organizations

This study focuses on the effects of megaproject social responsibility (MSR) on participating organizations’ performance. Using a survey of the participating organizations in Chinese megaprojects, this study reveals that the impact of MSR on a participant’s performance goes beyond the scope of the current megaproject. The empirical results indicate that MSR positively affects both financial and social performance of the participating organizations. The interactions of primary stakeholders weaken the positive effects of MSR on both financial and social performance, whereas the interactions of secondary stakeholders strengthen the positive effects of MSR on social performance.
Wood and bark lignin contents of trees from deciduous forests of eastern India

Abstract Lignin is a polyphenolic compound found in plant tissues, especially wood and bark. The lignin content determines the quality of wood biochar in agroecological uses, and is used in the production of synthetic resins and adhesives. Despite its importance in plant physiology and its agricultural and industrial utility, there exists a wide gap of knowledge of lignin contents of tropical hardwood trees of South Asia, except for a few species. We present here the first estimation of lignin content in wood and bark of 48 species from tropical deciduous forests of India. We show that some species are characterized by greater wood lignin (WL) compared with bark lignin (BL) content, contrary to the generalization held for hardwood trees, and suggest a plausible correspondence between the WL to BL ratio and timber quality.
Organization and engagement of a prefrontal-olfactory network during olfactory selective attention

Sensory perception is profoundly shaped by attention. Attending to an odor strongly regulates if and how a smell is perceived – yet the brain systems involved in this process are unknown. Here we report integration of the medial prefrontal cortex (mPFC), a collection of brain regions integral to attention, with the olfactory system in the context of selective attention to odors. First, we used tracing methods to establish the tubular striatum (TuS, also known as the olfactory tubercle) as the primary olfactory region to receive direct mPFC input in rats. Next, we recorded local field potentials from the olfactory bulb (OB), mPFC, and TuS while rats completed an olfactory selective attention task. Gamma power and coupling of gamma oscillations with theta phase were consistently high as rats flexibly switched their attention to odors. Beta and theta synchrony between mPFC and olfactory regions were elevated as rats switched their attention to odors. Finally, we found that sniffing was consistent despite shifting attentional demands, suggesting that the mPFC-OB theta coherence is independent of changes in active sampling. Together, these findings begin to define an olfactory attention network wherein mPFC activity, as well as that within olfactory regions, are coordinated in manners based upon attentional states.
Novel Classes and Evolutionary Turnover of Histone H2B Variants in the Mammalian Germline

Histones and their post-translational modifications facilitate diverse chromatin functions in eukaryotes. Core histones (H2A, H2B, H3, and H4) package genomes after DNA replication. In contrast, variant histones promote specialized chromatin functions, including DNA repair, genome stability, and epigenetic inheritance. Previous studies have identified only a few H2B variants in animals; their roles and evolutionary origins remain largely unknown. Here, using phylogenomic analyses, we reveal the presence of five H2B variants broadly present in mammalian genomes. In addition to three previously described variants (H2B.1, subH2B, and H2B.W), we identify and describe two new variants, H2B.L and H2B.N. Four of these five H2B variants originated in mammals, whereas H2B.L arose prior to the last common ancestor of bony vertebrates. We find that though mammalian H2B variants are subject to high gene turnover, most are broadly retained in mammals, including humans. Despite an overall signature of purifying selection, H2B variants evolve more rapidly than core H2B with considerable divergence in sequence and length. All five H2B variants are expressed in the germline. H2B.L and H2B.N are predominantly expressed in oocytes, an atypical expression site for mammalian histone variants. Our findings suggest that H2B variants likely encode potentially redundant but vital functions via unusual chromatin packaging or non-chromatin functions in mammalian germline cells. Our discovery of novel histone variants highlights the advantages of comprehensive phylogenomic analyses and provides unique opportunities to study how innovations in chromatin function evolve.
Predicting mind wandering episodes quarter hours in advances from EEG

Mind wandering occurs when spontaneous thought generation is increased while cognitive control is decreased, presumably in response to antagonistic effects of default mode- (DMN) and goal-directed network (GDN) activity. Previous studies assumed that DMN or GDN activity manifests in behavior with minimal delays and has rigid effects, i.e., DMN always facilitates generation of spontaneous thought and inhibits cognitive control. With those static response functions, the antagonism of DMN and GDN could explain the alternation of task focused and mind wandering states. But it rules out others, such as multi-tasking, where spontaneous thought and cognitive control are both increased, or rumination, where both are decreased. However, shifts from task focused to mind wandering have been shown to occur via a multi-tasking state. We therefore propose dynamic response functions, allowing delay or reversal of DMN and GDN effects. Dynamic response functions enabled us to stochastically predict mind wandering up to at least 30 min in advance from EEG measures of DMN and GDN activity in a tone counting task. Experimental results show both considerable delays and switches between task-positive and negative effects. Mind wandering was initiated by a barrage of DMN activity more than 20 minutes prior a report of mind wandering, directing the mental focus inward. Critically, facilitation of spontaneous thoughts occurred several minutes prior to the report. These thoughts sustained up to 10 min, after which a rebound to task-focused behavior was effectuated, notably without intervention from the GDN. Repeated GDN interventions, however, secured a basic level of task performance.
Behavioral state tunes mouse vision to ethological features through pupil dilation

Across animal species, sensory processing dynamically adapts to behavioral context. In the mammalian visual system, sensory neural responses and behavioral performance increase during an active behavioral state characterized by locomotion activity and pupil dilation, whereas preferred stimuli of individual neurons typically remain unchanged. Here, we address how behavioral states modulate stimulus selectivity in the context of colored natural scenes using a combination of large-scale population imaging, behavior, pharmacology, and deep neural network modeling. In visual cortex of awake mice, we identified a consistent shift of individual neuron color preferences towards ultraviolet stimuli during active behavioral periods that was particularly pronounced in the upper visual field. We found that the spectral shift in neural tuning is mediated by pupil dilation, resulting in a dynamic switch from rod-to cone-driven visual responses for constant ambient light levels. We further showed that this shift selectively enhances the discriminability of ultraviolet objects and facilitates the detection of ethological stimuli, such as aerial predators against the ultraviolet background of the twilight sky. Our results suggest a novel functional role for pupil dilation during active behavioral states as a bottom-up mechanism that, together with top-down neuromodulatory mechanisms, dynamically tunes visual representations to different behavioral demands.
Exploring Intuitive Approaches to Protein Conformation Clustering Using Regions of High Structural Variance

This paper presents a method to find structurally high variance segments of the different conformations of a single protein and uses clusters them using different distance metrics and interpretation of coordinate and angle data presented by three different methods: root mean squared derivation RMSD, t-distributed Stochastic Neighbor Embedding (t-SNE) based map, and dihedral-based clustering. The methods were applied on the human cylin-dependent kinase 2 (CDK2) protein, code P24941 uniprot using a series of python scripts and clustering packages. We test our methods on the data of the CDK2 protein as it is a highly researched protein, with practical applications of clustering in cancer research, crucial in the regulation of the cell-cycle, and has a sizeable amount of experimental data collected on the confirmation structures. While using the distance based root mean squared deviation RMSD provides data of structure to structure dissimilarity between different conformations, a simple RMSD matrix lacks to ability to describe the subsequence-wise in shape and absolute position which could be the main identifying elements for a protein’s conformation and state. To make up for this loss we explore an intuitive and more flexible method, able to accept multiple high structural variance segments, which takes coordinate based data, through a series of maps and with the help of t-SNE, and maps each segment as a feature in the clustering matrix. This method, however, would require additional testing on other proteins and modifications to verify its consistency and test its robustness. In the end we explore the pros and cons of the three methods applied on the high structural variance regions. Despite the randomness factor by the t-SNE used in mapping the coordinates to lower dimensions, the coordinate-based approach consistently performed better than the RSMD and dihedral based methods in clustering the three groups of the CDK2 protein kinase. We also found that analyzing only the substructures identified by the high variance detection algorithm consistently provided more distinct clusters with higher multi-class F1 scores.
Sequence conservation and structural features that are common within TRP channels

TRP proteins are a large family of cation selective channels, surpassed in variety only by voltage-gated potassium channels. Detailed molecular mechanisms governing how membrane voltage, ligand binding, or temperature can induce conformational changes promoting the open state of the channel are still missing for TRP channels. Aiming to unveil distinctive structural features common to the transmembrane domains within the TRP family, we performed bioinformatic analyses over a large set of TRP channel genes. Here we report a discrete and exceptionally conserved set of residues. This fingerprint is composed of eleven residues localized at equivalent three-dimensional positions in TRP channels from the different subtypes. Moreover, these amino acids are arranged in three groups, connected by a set of aromatics located at the core of the transmembrane structure. We hypothesize that differences in the connectivity between these different groups of residues harbors the apparent differences in coupling strategies used by TRP subgroups.
HyperEx: A Tool to Extract Hypervariable Regions from 16S rRNA Sequencing Data

The 16S ribosomal RNA gene is one of the most studied genes in biology. This 16S ribosomal RNA importance is due to its wide application in phylogenetics and taxonomic elucidation of bacteria and archaea. Indeed, 16S ribosomal RNA is present in almost all bacteria and archaea and has, among many other useful characteristics, a low mutation rate. The 16S ribosomal RNA is composed of nine hypervariable regions which are commonly targeted by high throughput sequencing technologies in identification or community studies like metabarcoding studies. Unfortunately, the hypervariable regions do not have the same taxonomic resolution among all bacteria taxa. This requires a preliminary in silico analysis to determine the best hypervariable regions to target in a particular study. Nevertheless, to the best of our knowledge, no automated primer-based open-source tool exists to extract hypervariable regions from complete or near-complete 16S rRNA sequencing data. Here we present HyperEx which efficiently extracts the hypervariable region of interest based on embedded primers or user-given primers. HyperEx implements the Myers algorithm for the exact pairwise sequence alignment. HyperEx is freely available under the MIT license as an operating system independent Rust command-line tool at https://github.com/Ebedthan/hyperex and https://crates.io.
A case for green-based vegetation indices: plot-scale sUAS imagery related to crop chlorophyll content on smallholder maize farms in Malawi

ABSTRACT Predictable outcomes from precision agriculture (PA) solutions require accurate measurements of crop status and a remote sensing knowledgebase that spans ecoregions. This paper evaluates the relationships between 20 multispectral vegetation indices derived from small unmanned aircraft system (sUAS) image collection and on-farm measurements of crop chlorophyll content at two smallholder experimentation maize farms in Malawi with varied nitrogen fertilizer treatments. Results of this analysis show that prominent green-based multispectral indices, such as the green normalized difference vegetation index (GNDVI), were among the models with the strongest correlations. This study is consistent with other research in this field, contributes to mounting evidence supporting a shift in status quo for greater adoption of green-based indices in PA, and offers data specific to the semi-arid sub-Saharan context.