Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Archives: Towards New Research Interfaces Relying on the Semantic Annotation of Documents

The digitisation campaigns carried out by libraries and archives in recent years have facilitated access to documents in their collections. However, exploring and exploiting these documents remain difficult tasks due to the sheer quantity of documents available for consultation. In this article, we show how the semantic annotation of the textual content of study corpora of archival documents allow to facilitate their exploitation and valorisation. First, we present a methodological framework for the construction of new interfaces based on textual semantics, then address the current technological obstacles and their potential solutions. We conclude by presenting a practical case of the application of this framework.
Sperm Flagellum Volume Determines Freezability in Red Deer Spermatozoa

The factors affecting the inter-individual differences in sperm freezability is a major line of research in spermatology. Poor sperm freezability is mainly characterised by a low sperm velocity, which in turn is associated with low fertility rates in most animal species. Studies concerning the implications of sperm morphometry on freezability are quite limited, and most of them are based on sperm head size regardless of the structural parts of the flagellum, which provides sperm motility. Here, for the first time, we determined the volumes of the flagellum structures in fresh epididymal red deer spermatozoa using a stereological method under phase contrast microscopy. Sperm samples from thirty-three stags were frozen and classified as good freezers (GF) or bad freezers (BF) at two hours post-thawing using three sperm kinetic parameters which are strongly correlated with fertility in this species. Fourteen stags were clearly identified as GF, whereas nineteen were BF. No significant difference in sperm head size between the two groups was found. On the contrary, the GF exhibited a lower principal piece volume than the BF (6.13 µm3 vs 6.61 µm3, respectively, p = 0.006). The volume of the flagellum structures showed a strong negative relationship with post-thawing sperm velocity. For instance, the volume of the sperm principal piece was negatively correlated with sperm velocity at two hours post-thawing (r = −0.60; p<0.001). Our results clearly show that a higher volume of the sperm principal piece results in poor freezability, and highlights the key role of flagellum size in sperm cryopreservation success.
MRNaB: Mixed Reality-based Robot Navigation Interface using Optical-see-through MR-beacon

Recent advancements in robotics have led to the development of numerous interfaces to enhance the intuitiveness of robot navigation. However, the reliance on traditional 2D displays imposes limitations on the simultaneous visualization of information. Mixed Reality (MR) technology addresses this issue by enhancing the dimensionality of information visualization, allowing users to perceive multiple pieces of information concurrently. This paper proposes Mixed reality-based robot navigation interface using an optical-see-through MR-beacon (MRNaB), a novel approach that incorporates an MR-beacon, situated atop the real-world environment, to function as a signal transmitter for robot navigation. This MR-beacon is designed to be persistent, eliminating the need for repeated navigation inputs for the same location. Our system is mainly constructed into four primary functions:"Add","Move","Delete", and"Select". These allow for the addition of a MR-beacon, location movement, its deletion, and the selection of MR-beacon for navigation purposes, respectively. The effectiveness of the proposed method was then validated through experiments by comparing it with the traditional 2D system. As the result, MRNaB was proven to increase the performance of the user when doing navigation to a certain place subjectively and objectively. For additional material, please check: https://mertcookimg.github. io/mrnab
Symmetry-guided inverse design of self-assembling multiscale DNA origami tilings

Recent advances enable the creation of nanoscale building blocks with complex geometries and interaction specificities for self-assembly. This nearly boundless design space necessitates design principles for defining the mutual interactions between multiple particle species to target a user-specified complex structure or pattern. In this article, we develop a symmetry-based method to generate the interaction matrices that specify the assembly of two-dimensional tilings which we illustrate using equilateral triangles. By exploiting the allowed 2D symmetries, we develop an algorithmic approach by which any periodic 2D tiling can be generated from an arbitrarily large number of subunit species, notably addressing an unmet challenge of engineering 2D crystals with periodicities that can be arbitrarily larger than subunit size. To demonstrate the utility of our design approach, we encode specific interactions between triangular subunits synthesized by DNA origami and show that we can guide their self-assembly into tilings with a wide variety of symmetries, using up to 12 unique species of triangles. By conjugating specific triangles with gold nanoparticles, we fabricate gold-nanoparticle supercrystals whose lattice parameter spans up to 300 nm. Finally, to generate economical design rules, we compare the design economy of various tilings. In particular, we show that (1) higher symmetries allow assembly of larger unit cells with fewer subunits and (2) linear supercrystals can be designed more economically using linear primitive unit cells. This work provides a simple algorithmic approach to designing periodic assemblies, which may open new doors to the multiscale assembly of superlattices of nanostructured"metatoms"with engineered plasmonic functions.
Collaborative Interactive Evolution of Art in the Latent Space of Deep Generative Models

Generative Adversarial Networks (GANs) have shown great success in generating high quality images and are thus used as one of the main approaches to generate art images. However, usually the image generation process involves sampling from the latent space of the learned art representations, allowing little control over the output. In this work, we first employ GANs that are trained to produce creative images using an architecture known as Creative Adversarial Networks (CANs), then, we employ an evolutionary approach to navigate within the latent space of the models to discover images. We use automatic aesthetic and collaborative interactive human evaluation metrics to assess the generated images. In the human interactive evaluation case, we propose a collaborative evaluation based on the assessments of several participants. Furthermore, we also experiment with an intelligent mutation operator that aims to improve the quality of the images through local search based on an aesthetic measure. We evaluate the effectiveness of this approach by comparing the results produced by the automatic and collaborative interactive evolution. The results show that the proposed approach can generate highly attractive art images when the evolution is guided by collaborative human feedback.
Beyond Borders: Investigating Cross-Jurisdiction Transfer in Legal Case Summarization

Legal professionals face the challenge of managing an overwhelming volume of lengthy judgments, making automated legal case summarization crucial. However, prior approaches mainly focused on training and evaluating these models within the same jurisdiction. In this study, we explore the cross-jurisdictional generalizability of legal case summarization models.Specifically, we explore how to effectively summarize legal cases of a target jurisdiction where reference summaries are not available. In particular, we investigate whether supplementing models with unlabeled target jurisdiction corpus and extractive silver summaries obtained from unsupervised algorithms on target data enhances transfer performance. Our comprehensive study on three datasets from different jurisdictions highlights the role of pre-training in improving transfer performance. We shed light on the pivotal influence of jurisdictional similarity in selecting optimal source datasets for effective transfer. Furthermore, our findings underscore that incorporating unlabeled target data yields improvements in general pre-trained models, with additional gains when silver summaries are introduced. This augmentation is especially valuable when dealing with extractive datasets and scenarios featuring limited alignment between source and target jurisdictions. Our study provides key insights for developing adaptable legal case summarization systems, transcending jurisdictional boundaries.
ExploreTurns: A web tool for the exploration and analysis of beta turns and their contexts in proteins; application to beta-bulge and Schellman loops, Asx helix caps, and other hydrogen-bonded motifs

The most common type of protein secondary structure after the alpha helix and beta sheet is the four-residue beta turn, which plays many key structural and functional roles. Existing tools for the study of beta turns operate almost exclusively in backbone dihedral-angle (Ramachandran) space, which presents challenges for the visualization, comparison and analysis of the wide range of turn conformations. A recent study has introduced a turn-local Euclidean-space coordinate system and global alignment for turns, along with geometric parameters describing their backbone shapes, and these features and others are incorporated here into ExploreTurns, a web facility for the exploration, analysis, geometric tuning and retrieval of beta turns and their structural contexts which combines the advantages of Ramachandran- and Euclidean-space representations. Due to the widespread occurrence of beta turns, this facility, supported by its interpreter for a new general nomenclature classifying short H-bonded loops, can serve as an exploratory browser and analysis tool for most loop structure in proteins, and it is applied here to detect new H-bonded loops, including a “short Schellman loop” and a large family of motifs satisfying a proposed generalization of the beta-bulge loop. The tool is also applied to map Asx N-cap sequence preferences, profile Schellman loop/beta-turn conformations, and investigate the depth dependence of turn geometry. ExploreTurns, available at www.betaturn. com, should prove useful in research, education, and applications such as protein design, in which an enhanced Euclidean-space picture of turn/motif structure and the ability to identify and tune structures suited to particular requirements may improve performance.
2P-NucTag: on-demand phototagging for molecular analysis of functionally identified cortical neurons

Neural circuits are characterized by genetically and functionally diverse cell types. A mechanistic understanding of circuit function is predicated on linking the genetic and physiological properties of individual neurons. However, it remains highly challenging to map the functional properties of transcriptionally heterogeneous neuronal subtypes in mammalian cortical circuits in vivo. Here, we introduce a high-throughput two-photon nuclear phototagging (2P-NucTag) approach optimized for on-demand and indelible labeling of single neurons via a photoactivatable red fluorescent protein following in vivo functional characterization in behaving mice. We demonstrate the utility of this function-forward pipeline by selectively labeling and transcriptionally profiling previously inaccessible ‘place’ and ‘silent’ cells in the mouse hippocampus. Our results reveal unexpected differences in gene expression between these hippocampal pyramidal neurons with distinct spatial coding properties. Thus, 2P-NucTag opens a new way to uncover the molecular principles that govern the functional organization of neural circuits.
The effects of personality composition and decision-making processes on change preferences of self-managing teams: A business simulation

Team decision-making on organizational and strategic changes is pervasive. Yet, little is known about determinants of teams’ change preferences. We analyze how composition with respect to personality traits associated with (pro-)active behavior (locus-of-control, type-A/B behavior) influences self-managing teams’ preferences for the likelihood and magnitude of changes, and whether participative decision-making and team monitoring as core features of group decision-making counteract or reinforce change tendencies. Results from a business simulation with 42 teams largely support predictions. Stronger type-A orientation increases the likelihood of (drastic) changes. Teams dominated by internal locus-of-control members are highly responsive performance feedback in their change preferences. Participative decision-making encourages while team monitoring restricts tendencies towards extreme magnitudes.
The role of Kinesin-1 in neuronal dense core vesicle transport and lifespan regulation in C. elegans

Fast axonal transport is crucial for neuronal function and is driven by kinesins and cytoplasmic dynein. We investigated the role of the kinesin-1 motor complex in dense core vesicle (DCV) transport in C. elegans, using mutants in kinesin light chains (klc-1 and klc-2) and the kinesin motor subunit (unc-116) expressing an ida-1::gfp transgene that labels DCVs in the ALA neuron. A reduced-function unc-116(rf) mutation greatly impaired DCV transport in both directions. A klc-2(rf) reduced-function mutation decreased DCV velocity in both directions and reduced the frequency of body bends during swimming. In contrast, the klc-1(-) null mutation had no effect on anterograde transport or swimming ability, but surprisingly it increased the speed of retrograde DCV transport. We also determined lifespan, finding that klc-1(-) or klc-2(rf) single mutants were wild-type whereas the unc-116(rf), ida-1::gfp and unc-116(rf); ida-1::gfp strains were short-lived. Strikingly, the ida-1::gfp transgenic synergistically interact with either klc mutant to extend lifespan compared to wild-type and parental strains. Our findings suggest that kinesin-1 not only influences anterograde and retrograde DCV transport but also plays a role in regulating lifespan.
A fully distributed location management scheme for large PCS

Previously, Rangarajan et al. (see Proc. of the 25th International Symposium on Fault-Tolerant Computing, 1995) presented the design, specification and proof of correctness of a fully distributed location management scheme for PCS networks and argued that fully replicating location information is both appropriate and efficient for small PCS networks. In this paper, we extend our previous work by first analyzing the performance of our scheme. Then, we extend the scheme in a hierarchical environment so as to reduce the overhead and scale to large PCS networks. Through extensive numerical results, we show the superiority of our scheme compared to the current IS-41 standard.
Participant Evaluation of a Telephone-Based Osteoarthritis Self-Management Program, 2006-2009

Introduction Self-management support interventions can help improve osteoarthritis outcomes but are underused. Little is known about how participants evaluate the helpfulness of these programs. We describe participants' evaluations of a telephone-based, osteoarthritis self-management support intervention that yielded improved outcomes in a clinical trial. Methods Participants were 140 people in the intervention arm of the trial who completed an end-of-trial survey. We used mixed methods to describe participants' perceived helpfulness of the program and its components. We compared ratings of helpfulness according to participant characteristics and analyzed themes from open-ended responses with a constant comparison approach. We calculated Pearson correlation coefficients between perceived helpfulness and changes in pain, function, affect, and self-efficacy. Results The average rating of overall helpfulness on a scale from 1 to 10 was 7.6 (standard deviation, 2.3), and more than 80% of participants agreed that each component (phone calls, educational material, setting goals and action plans) was helpful. Participants had better perceived helpfulness ratings than their counterparts if they were nonwhite, had limited health literacy, had no college education, had perceived inadequate income, were older, had a spouse or were living together in a committed relationship, and had greater symptom duration and less pain. Ratings of helpfulness increased with greater improvement in outcomes. Participants frequently mentioned the health educator's calls as being helpful for staying on task with self-management behaviors. Conclusion Participants viewed this intervention and each of its components as helpful for improving osteoarthritis symptoms. In addition to the improvements in objective outcomes seen in the clinical trial, these results provide further support for the dissemination of self-management support interventions.
Postnatal Handling Induces Long-term Modifications in Central β-noradrenergic Signalling in Rats

Neonatal handling has been shown to induce a short-term reduction in the binding properties of g -adrenoceptors and in their primary biochemical responses in the young rat brain, which may account for the reduced responsiveness to stress observed in the handled rats. We have studied the persistence and duration of these changes in cerebral cortex, cerebellum and hippocampus at successive stages of life in neonatally handled rats. Binding properties of the g -adrenoceptors in handled animals were essentially similar to those of the control rats from 3 to 24 months of age. However, handling disturbed the efficacy of the g -adrenoceptor intracellular signalling since the isoprenaline-induced accumulation of cyclic AMP was reduced in cerebral cortex at 1, 12 and 24 months; in cerebellum at 12 and 18 months; and in hippocampus at 3 and 12 months. This effect might be partially dependent on a regulatory action of handling on the adenylyl cyclase enzyme itself since both basal and forskolin-induced accumulation of cyclic AMP were persistently reduced. Therefore, postnatal handling can be considered as an effective intervention that modifies sensitivity to various hormonal and neurochemical signals; these changes may be involved over a long period of time in protection against an excessive response to stress. These results suggest that the long-lasting adaptation of the adenylyl cyclase transduction system, which affects the primary biochemical response of the g -adrenoceptor, may participate in the effects of this manipulation.
Excessive synthesis of matrix metalloproteinases in exocrine tissues of NOD mouse models for Sjögren's syndrome.

OBJECTIVE Matrix metalloproteinases (MMP) and their substrates, components of the extracellular matrix, regulate environmental signals for cellular differentiation and tissue function. Changes in the levels of these enzymes may influence cell survival as well as pathology involving ectopic apoptosis. Using the non-obese diabetic (NOD) mouse model for Sjögren's syndrome, we evaluated the synthesis and expression of MMP in the exocrine target tissues of autoimmunity. METHODS NOD, immunodeficient NOD-scid, and nondiabetic NOD.B10. H2b mice were evaluated for MMP activity in their saliva and exocrine gland lysates by gelatin zymography and reverse transcriptase-polymerase chain reaction (RT-PCR). In addition, changes in protein content of saliva and gland lysates were determined by specific Western blot and by enzymatic activity of amylase and cysteine proteases. Mice continuously treated with the MMP inhibitor GM6001 were evaluated from 7 to 20 weeks of age for the contribution of MMP activity to development of these hallmark biochemical markers of Sjogren's syndrome-like disease of NOD mice. RESULTS Gelatin zymography of whole saliva and gland lysates indicated the presence of increased proteolytic activity, corresponding to proteins with a molecular mass ranging from 50 to 95 kDa, in the saliva of older (> 20 weeks of age) NOD mice as well as NOD.B10. H2b and NOD-scid mice compared to BALB/c controls. Elevated steady state levels of mRNA transcripts for the gelatinases MMP-2 and MMP-9 were detected in total RNA extracted from parotid and submandibular glands by RT-PCR. Despite prophylactic injection of the broad spectrum MMP inhibitor GM6001 into mice beginning at 7 weeks of age and continuing to 20 weeks, development of the autoimmune exocrinopathy was neither stopped nor retarded. CONCLUSION These observations suggest that excessive MMP activity is associated with autoimmune Sjögren's syndrome-like disease in NOD mice. However, a possible contribution by increased MMP activity in initiation and progression of this autoimmune disease is yet to be elucidated.
Cartographic Design and the Space–Time Cube

ABSTRACT This paper reports on the results of an empirical evaluation that aimed to define the effectiveness and efficiency of different visual variables in depicting the Space–Time Cube’s (STC) content. Existing STC applications demonstrate that the most used visual variables are size and colour hue. Less is known, however, about their usability metrics. The research sets design criteria for STC contents, such as space–time paths, based on the cartographic design theory. The visual variables colour hue, colour value, colour saturation, size and orientation have been applied in two different use case studies. Besides, to support the three-dimensional visual environment, depth cues such as shading and transparency were considered too. User tests have been executed based on real-world problems with particular attention for the visualization strategy and data complexity. The outcomes revealed the most efficient and effective visual variables to represent data of various complexities in the STC.
Deep learning models of biological visual information processing

Improved computational models of biological vision can shed light on key processes contributing to the high accuracy of the human visual system. Deep learning models, which extract multiple layers of increasingly complex features from data, achieved recent breakthroughs on visual tasks. This thesis proposes such flexible data-driven models of biological vision and also shows how insights regarding biological visual processing can lead to advances within deep learning. To harness the potential of deep learning for modelling the retina and early vision, this work introduces a new dataset and a task simulating an early visual processing function and evaluates deep belief networks (DBNs) and deep neural networks (DNNs) on this input. The models are shown to learn feature detectors similar to retinal ganglion and V1 simple cells and execute early vision tasks. To model high-level visual information processing, this thesis proposes novel deep learning architectures and training methods. Biologically inspired Gaussian receptive field constraints are imposed on restricted Boltzmann machines (RBMs) to improve the fidelity of the data representation to encodings extracted by visual processing neurons. Moreover, concurrently with learning local features, the proposed local receptive field constrained RBMs (LRF-RBMs) automatically discover advantageous non-uniform feature detector placements from data. Following the hierarchical organisation of the visual cortex, novel LRF-DBN and LRF-DNN models are constructed using LRF-RBMs with gradually increasing receptive field sizes to extract consecutive layers of features. On a challenging face dataset, unlike DBNs, LRF-DBNs learn a feature hierarchy exhibiting hierarchical part-based composition. Also, the proposed deep models outperform DBNs and DNNs on face completion and dimensionality reduction, thereby demonstrating the strength of methods inspired by biological visual processing.