Miracle-dz/UniFAR-FTUs huggingface dataset:
Insect-inspired Spatio-temporal Downsampling of Event-based Input

As vision sensors for autonomous systems, event based cameras provide numerous benefits over conventional cameras including higher dynamic range and temporal resolution as well as lower bandwidth and power requirements. However, while downsampling is regularly used in standard computer vision, there are no reliable techniques to do this for event data, resulting in a bottleneck for event-based computer vision systems. Here we extend our previous work, explain the challenges that need to be overcome by any effective event-based downsampling algorithm and present a novel biologically-inspired process that can adeptly downsample event streams by factors of up to 16 times compared to the original resolution. We show that our downsampled event streams achieve high fidelity with a hypothetical low-resolution event camera and improve classification performance on highly downsampled versions of the DVS gesture dataset. Furthermore, we demonstrate that compared to a naïve event-based downsampling, our approach massively reduces the number of spikes that downstream neuromorphic processors have to handle.
the Belgian trial with azithromycin for acute COPD exacerbations requiring hospitalization: an investigator-initiated study protocol for a multicenter, randomized, double-blind, placebo-controlled trial

Background: Long-term use of macrolide antibiotics is effective to prevent exacerbations in chronic obstructive pulmonary disease (COPD). As risks and side effects of long-term intervention outweigh the benefits in the general COPD population, the optimal dose, duration of treatment, and target population are yet to be defined. Hospitalization for an acute exacerbation (AE) of COPD may offer a targeted risk group and an obvious risk period for studying macrolide interventions. Methods/design: Patients with COPD, hospitalized for an AE, who have a smoking history of $ 10 pack-years and had $ 1 exacerbation in the previous year will be enrolled in a multicenter, randomized, double-blind, placebo-controlled trial (NCT02135354). On top of a standardized treatment of systemic corticosteroids and antibiotics, subjects will be randomized to receive either azithromycin or placebo during 3 months, at an uploading dose of 500 mg once a day for 3 days, followed by a maintenance dose of 250 mg once every 2 days. The primary endpoint is the time-to-treatment failure during the treatment phase (ie, from the moment of randomization until the end of intervention). Treatment failure is a novel composite endpoint defined as either death, the admission to intensive care or the requirement of additional systemic steroids or new antibiotics for respiratory reasons, or the diagnosis of a new AE after discharge. Discussion: We investigate whether azithromycin initiated at the onset of a severe exacerbation, with a limited duration and at a low dose, might be effective and safe in the highest risk period during and immediately after the acute event. If proven effective and safe, this targeted approach may improve the treatment of severe AEs and redirect the preventive use of azithromycin in COPD to a temporary intervention in the subgroup with the highest unmet needs.
The Effect of Interocular Contrast Differences on the Appearance of Augmented Reality Imagery

Augmented reality (AR) devices seek to create compelling visual experiences that merge virtual imagery with the natural world. These devices often rely on wearable near-eye display systems that can optically overlay digital images to the left and right eyes of the user separately. Ideally, the two eyes should be shown images with minimal radiometric differences (e.g., the same overall luminance, contrast, and color in both eyes), but achieving this binocular equality can be challenging in wearable systems with stringent demands on weight and size. Basic vision research has shown that a spectrum of potentially detrimental perceptual effects can be elicited by imagery with radiometric differences between the eyes, but it is not clear whether and how these findings apply to the experience of modern AR devices. In this work, we first develop a testing paradigm for assessing multiple aspects of visual appearance at once, and characterize five key perceptual factors when participants viewed stimuli with interocular contrast differences. In a second experiment, we simulate optical see-through AR imagery using conventional desktop LCD monitors and use the same paradigm to evaluate the multi-faceted perceptual implications when the AR display luminance differs between the two eyes. We also include simulations of monocular AR systems (i.e., systems in which only one eye sees the displayed image). Our results suggest that interocular contrast differences can drive several potentially detrimental perceptual effects in binocular AR systems, such as binocular luster, rivalry, and spurious depth differences. In addition, monocular AR displays tend to have more artifacts than binocular displays with a large contrast difference in the two eyes. A better understanding of the range and likelihood of these perceptual phenomena can help inform design choices that support high-quality user experiences in AR.
A MASS POISONING OFWHITE-BACKED AND LAPPET-FACED VULTURESIN GONAREZHOU NATIONAL PARK

In this article we report a mass poisoning of vultures in the Gonarezhou National Park in Zimbabwe. This was one of the largest mass killings of vultures ever recorded and the largest recorded in Zimbabwe. On many of the carcasses the upper beaks were removed, suggesting the involvement of superstition and/or traditional medicine practices. The reasons for, and consequences of, such vulture harvesting are discussed.
VapC12 ribonuclease toxin modulates host immune response during Mycobacterium tuberculosis infection

Mechanistic understanding of antibiotic persistence is a prerequisite in controlling the emergence of MDR cases in Tuberculosis (TB). We have reported that the cholesterol-induced activation of VapC12 ribonuclease is critical for disease persistence in TB. In this study, we observed that relative to the wild type, mice infected with ΔvapC12 induced a pro-inflammatory response, had a higher pathogen load, and responded better to the anti-TB treatment. In a high-dose infection model, all the mice infected with ΔvapC12 succumbed early to the disease. Finally, we reported that the above phenotype of ΔvapC12 was dependent on the presence of the TLR4 receptor. Overall, the data suggests that failure of a timely resolution of the early inflammation by the ΔvapC12 infected mice led to hyperinflammation, altered T-cell response and high bacterial load. In conclusion, our findings suggest the role of the VapC12 toxin in modulating the innate immune response of the host in ways that favor the long-term survival of the pathogen inside the host.
The genome of the Wollemi pine, a critically endangered “living fossil” unchanged since the Cretaceous, reveals extensive ancient transposon activity

We present the genome of the living fossil, Wollemia nobilis, a southern hemisphere conifer morphologically unchanged since the Cretaceous. Presumed extinct until rediscovery in 1994, the Wollemi pine is critically endangered with less than 60 wild adults threatened by intensifying bushfires in the Blue Mountains of Australia. The 12 Gb genome is among the most contiguous large plant genomes assembled, with extremely low heterozygosity and unusual abundance of DNA transposons. Reduced representation and genome re-sequencing of individuals confirms a relictual population since the last major glacial/drying period in Australia, 120 ky BP. Small RNA and methylome sequencing reveal conservation of ancient silencing mechanisms despite the presence of thousands of active and abundant transposons, including some transferred horizontally to conifers from arthropods in the Jurassic. A retrotransposon burst 8-6 my BP coincided with population decline, possibly as an adaptation enhancing epigenetic diversity. Wollemia, like other conifers, is susceptible to Phytophthora, and a suite of defense genes, similar to those in loblolly pine, are targeted for silencing by sRNAs in leaves. The genome provides insight into the earliest seed plants, while enabling conservation efforts.
Distributed representations of behaviorally-relevant object dimensions in the human visual system

Object vision is commonly thought to involve a hierarchy of brain regions processing increasingly complex image features, with high-level visual cortex supporting object recognition and categorization. However, object vision supports diverse behavioral goals, suggesting basic limitations of this category-centric framework. To address these limitations, we mapped a series of behaviorally-relevant dimensions derived from a large-scale analysis of human similarity judgments directly onto the brain. Our results reveal broadly distributed representations of behaviorally-relevant information, demonstrating selectivity to a wide variety of novel dimensions while capturing known selectivities for visual features and categories. Behaviorally-relevant dimensions were superior to categories at predicting brain responses, yielding mixed selectivity in much of visual cortex and sparse selectivity in category-selective clusters. This framework reconciles seemingly disparate findings regarding regional specialization, explaining category selectivity as a special case of sparse response profiles among representational dimensions, suggesting a more expansive view on visual processing in the human brain.
FPGA Placement using Space Filling Curves : Theory Meets Practice 1

Research in VLSI placement, an NP-hard problem, has branched in two different directions. The first one employs iterative heuristics with many tunable parameters to produce near-optimal solution but without theoretical guarantee on its quality. The other one considers placement as graph embedding and designs approximation algorithms with provable bounds on the quality of the solution. In this paper, we aim at unifying the above two directions. First, we extend the existing approximation algorithms for graph embedding in 1D and 2D mesh to those for hypergraphs, which typically model circuits to be placed on a FPGA. We prove an O(d √ log n log log n) approximation bound for 1D and O(d log n log log n) approximation bound for the 2D mesh, where d is the maximum degree of hyperedges and n the number of vertices in the hypergraph. Next, we propose an efficient method based on linear arrangement of the CLBs, and the notion of space filling curves, for placing the configurable logic blocks (CLBs) of a netlist on island-style FPGAs with an approximation guarantee of O(d 4 √ log n √ k log log n). For the set of FPGA placement benchmarks, the running time is near-linear in the number of CLBs, thus allowing for scalability towards large circuits. We obtained on an average a 33× speedup with only 1.31× degradation in the quality of solution with respect to that produced by the popular FPGA tool VPR, thereby demonstrating the suitability of this very fast method for FPGA placement, with a provable performance guarantee.
Role of 18F-fluorodeoxyglucose positron emission tomography in preoperative assessment of cytologically indeterminate thyroid nodules.

OBJECTIVE The objective of the study was to determine the diagnostic accuracy of (18)F-fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET) in the preoperative diagnosis of thyroid nodules with indeterminate fine-needle aspiration biopsy results. METHODS Forty-two consecutive patients with thyroid nodules with indeterminate cytological results participated in this study. Abnormal (18)F-FDG PET uptake was assessed visually and by measuring the maximum standardized uptake value (SUVmax) in thyroid topography. All these results were compared with the final pathological results. RESULTS The presence of focal uptake correlated with a greater risk of malignancy (P = 0.018). All 11 malignant nodules had focal uptake (sensitivity of 100%). Of the 31 patients with benign nodules, there were 19 with positive uptake (specificity of 38.7%). The pre-PET probability of cancer was 26.2% (11 of 42), and this probability increased to 36.7% after PET for those patients whose exam showed focal uptake (11 of 30). The preoperative use of (18)F-FDG PET would result in a significant reduction (39%, 12 of 31) in the number of thyroidectomies performed in patients with benign lesions. SUVmax could not improve this degree of accuracy. There was no correlation between thyroid nodule size and SUVmax value (P = 0.96). Patients with carcinomas were younger than patients with benign lesions (P = 0.048). There was no other clinical, laboratory, or ultrasonographic variable related to malignancy. CONCLUSIONS (18)F-FDG PET provides high sensitivity to malignant lesions and may be a potentially useful tool in the evaluation of thyroid nodules with indeterminate cytological findings. For these nodules the number of unnecessary thyroidectomies in a hypothetical algorithm using (18)F-FDG PET would be reduced by 39%.
Disentangling the neural correlates of semantic and domain-general control: The roles of stimulus domain and task process

Control processes are critical for the context-appropriate use of meaningful stimuli. Similar definitions have been adopted in two distinct literatures focusing on identifying the neural correlates of ‘semantic control’ and of executive control across domains (the ‘multiple demand network’). Surprisingly, despite their proposed functions varying only in relation to domain-specificity, these networks appear to differ anatomically. However, prior comparisons are confounded by variations in task design. To what extent might varying task requirements drive differences in activation patterns that are typically attributed to stimulus domain? Here, for the first time, we use functional MRI to disentangle the effects of task process and stimulus domain during cognitively demanding tasks. Participants performed an odd-one-out task requiring rule-switching, inhibition and selection processes, and an n-back working memory task, each with meaningful semantic and non-semantic stimuli, in a factorial design. Both stimulus domain and task process affected the control regions activated, indicating that task process is indeed a key factor confounding prior studies. However, core semantic control regions (left inferior frontal gyrus, left posterior temporal cortex) also showed a preference for semantic stimuli even with matched task processes, while more peripheral semantic control regions, overlapping the multiple demand network (dorsomedial prefrontal cortex, right inferior frontal gyrus), showed little preference across task or stimulus. Conversely, most multiple demand network regions were preferentially engaged for non-semantic stimuli. These results highlight the mutual importance of stimulus domain and task process in driving variation in control region engagement, both across and between semantic control and multiple demand networks. SIGNIFICANCE STATEMENT The flexible, context-appropriate use of concepts requires the selection, inhibition and manipulation of meaningful information. These control processes are thought to be supported by different areas for conceptual processing compared to other task domains. This proposed ‘special’ character of semantic control has important ramifications for the nature of executive control. However, prior assessments confound the presence of meaningful stimuli with the task operations performed. Here we disentangle the effects of task process and stimulus domain for the first time, finding critical effects of both factors on the pattern of activated control regions. The results enhance our understanding of the semantic control network and how it differs from and interacts with the domain-general multiple demand network, functionally characterising each control region.
Family lexicon: using language models to encode memories of personally familiar and famous people and places in the brain

Knowledge about personally familiar people and places is extremely rich and varied, involving pieces of semantic information connected in unpredictable ways through past autobiographical memories. In this work we investigate whether we can capture brain processing of personally familiar people and places using subject-specific memories, after transforming them into vectorial semantic representations using language models. First we asked participants to provide us with the names of the closest people and places in their lives. Then we collected open-ended answers to a questionnaire, aimed at capturing various facets of declarative knowledge. We collected EEG data from the same participants while they were reading the names and subsequently mentally visualizing their referents. As a control set of stimuli, we also recorded evoked responses to a matched set of famous people and places. We then created original semantic representations for the individual entities using language models. For personally familiar entities, we used the text of the answers to the questionnaire. For famous entities, we employed their Wikipedia page, which reflects shared declarative knowledge about them. Through whole-scalp time-resolved and searchlight encoding analyses we found that we could capture how the brain processes one’s closest people and places using person-specific answers to questionnaires, as well as famous entities. Encoding performance was significant in a large time window (200-800ms). In terms of spatio-temporal clusters, two main axes where encoding scores are significant emerged, in bilateral temporo-parietal electrodes first (200-500ms) and frontal and posterior central electrodes later (500-700ms). We also found that XLM, a contextualized language model or large language model, provided superior encoding scores when compared with a simpler static language model as word2vec. Overall, these results indicate that language models can capture subject-specific semantic representations as they are processed in the human brain, by exploiting small-scale distributional lexical data. My parents had five children. We now live in different cities, some of us in foreign countries, and we don’t write to each other often. When we do meet up we can be indifferent or distracted. But for us it takes just one word. It takes one word, one sentence, one of the old ones from our childhood, heard and repeated countless times. All it takes is for one of us to say “We haven’t come to Bergamo on a military campaign,” or “Sulfuric acid stinks of fart,” and we immediately fall back into our old relationships, our childhood, our youth, all inextricably linked to those words and phrases. excerpt from Family Lexicon, by Natalia Ginzburg
Reconstruction of compartmentalized genome-scale metabolic models using deep learning for over 800 fungi

Eukaryotic metabolism is organized into subcellular compartments enclosed by lipid-membranes. Since most metabolites do not move freely across the membranes, the compartmentalization influences metabolic pathway connectivities. Thus, compartmentalizing the pathways also in genome-scale metabolic models (GEMs) is essential for accurate predictions of eukaryotic cells’ metabolic phenotypes. Compartmentalization has manually been introduced into the model Eukaryote GEMs like for yeast Saccharomyces cerevisiae. Non-model organisms’ GEMs can be automatically reconstructed from genome data. However, the existing GEM reconstruction methods do not introduce compartmentalization into the models. To that end, we integrated our novel deep learning protein localization prediction and protein functional annotation into a top-down GEM reconstruction for automatically creating species-specific compartmentalized GEMs. We developed also a universal fungal GEM for top-down reconstruction of species-specifically compartmentalized GEMs and reconstructed models for 834 species. The novel protein localization prediction outperformed the state of the art in classifying proteins into multiple compartments and integrating the enzyme localization predictions to functional annotations improved the top-down model reconstruction. Interestingly, the clustering of the fungal GEMs reconstructed with predicted species-specific enzyme localization resembled more closely the phylogenetic relationships of the species than that of the GEMS without the compartmentalization. Compartmentalization of metabolism in fungi differs from other eukaryotes but the enzyme subcellular localizations vary also among fungal species. The Fungal kingdom encompasses species important for human health, environment, and industrial biotechnology. The reconstructed fungal GEM set offers valuable tools for e.g., predicting metabolic phenotypes of e.g., mushrooms or single-cellular fungi, the roles of eukaryotes in microbial communities, designs optimizing eukaryotic hosts for industrial chemical production, and identifying drug targets against pathogenic fungi. Beyond fungi, the compartmentalized GEM reconstruction method allows combining other universal GEMs for developing cell type specific GEMs for higher eukaryotes including plants, insects, and mammals.
iATPSnFR2: a high dynamic range fluorescent sensor for monitoring intracellular ATP

We developed a significantly improved genetically encoded quantitative adenosine triphosphate (ATP) sensor to provide real-time dynamics of ATP levels in subcellular compartments. iATPSnFR2 is a variant of iATPSnFR1, a previously developed sensor that has circularly permuted super-folder GFP inserted between the ATP-binding helices of the ε-subunit of a bacterial F0-F1 ATPase. Optimizing the linkers joining the two domains resulted in a ∼ 5-6 fold improvement in the dynamic range compared to the previous generation sensor, with excellent discrimination against other analytes and affinity variants varying from 4 μM to 500 μM. A chimeric version of this sensor fused to either the HaloTag protein or a suitably spectrally separated fluorescent protein, provides a ratiometric readout allowing comparisons of ATP across cellular regions. Subcellular targeting of the sensor to nerve terminals reveals previously uncharacterized single synapse metabolic signatures, while targeting to the mitochondrial matrix allowed direct quantitative probing of oxidative phosphorylation dynamics. Significance Statement Adenosine triphosphate (ATP) is a key metabolite necessary for cellular life. Here we develop a next-generation genetically encoded ratiometric fluorescent ATP sensor that allows subcellular tracking of ATP levels in living cells. The large dynamic range makes it possible to follow the dynamics of this metabolite across cells and subcellular regions under different metabolic stressors. We expect that iATPSnFR2 will provide researchers with exciting new opportunities to study ATP dynamics with temporal and spatial resolution that has, until now, been unavailable.