Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Hop-Count-Based Source-to-Destination Distance Estimation in Wireless Sensor Networks With Applications in Localization

In wireless sensor networks (WSNs), estimation of the true distance between a source and its destination based on the hop counts between them is an important research problem. The basic idea of several hop-count-based distance-estimation algorithms is to seek an analytical/heuristic transformation from the observed destination's hop-count information to an unknown source-to-destination distance (s2d-distance). We observe that the neighbors of a destination can have different hop counts with respect to the same source, and such information can be used to improve the s2d-distance estimation. Based on this observation, we propose a new s2d-distance estimation algorithm termed hop-count-based neighbor partition (HCNP). Unlike many existing methods, the proposed algorithm not only uses the hop-count information of a destination but also exploits the hop-count information of the destination's neighbors to estimate the s2d-distance. We analyze its statistical property and compare it with other s2d-distance estimation algorithms that only use a destination's hop-count information. We also derive an approximation of the lower bound on the minimum node density required for the HCNP algorithm to achieve a prescribed accuracy. To demonstrate the usefulness of the proposed method, we apply the HCNP algorithm in the localization of WSNs. Comparative studies with the state-of-the-art hop-count-based localization methods show that the proposed approach is superior.
Explaining the longitudinal association between puberty and depression: Sex differences in the mediating effects of peer stress

Abstract This research investigated whether exposure to peer stress serves as one pathway through which pubertal development contributes to depression over time, differentially for girls and boys. Youth (N = 149; 9.6–14.8 years) and their caregivers provided information at two waves, 1 year apart, on puberty (Wave 1), peer stress (occurring between Waves 1 and 2), and depression (Waves 1 and 2). Structural equation modeling analyses examined sex differences in the extent to which peer stress mediated the impact of pubertal status and timing on subsequent depression (i.e., tests of moderated mediation). Significant sex-moderated mediation was found for both pubertal status and timing. As indicated by moderate effect proportions, in girls, heightened peer stress partially mediated the longitudinal association between (a) more advanced pubertal status and depression; and (b) linear, but not curvilinear, pubertal timing (i.e., earlier maturation) and depression. This research contributes to our growing understanding of the interplay among physical, psychological, and social processes involved in the sex difference in adolescent depression.
H2 inhalation therapy in patients with moderate Covid 19 (H2 COVID) : a prospective ascending-dose phase 1 clinical trial

Introduction: The Covid-19 pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has triggered a serious global health crisis, resulting in millions of reported deaths since its initial identification in China in November 2019. The global disparities in immunization access emphasize the urgent need for ongoing research into therapeutic interventions. This study focuses on the potential use of molecular dihydrogen (H2) inhalation as an adjunctive treatment for Covid-19. H2 therapy shows promise in inhibiting intracellular signaling pathways associated with inflammation, particularly when administered early in conjunction with nasal oxygen therapy. Methods: This Phase I study, characterized by an open-label, prospective, monocentric, and single ascending dose design, seeks to assess the safety and tolerability of the procedure in individuals with confirmed SARS-CoV-2 infection. Employing a 3+3 design, the study includes three exposure durations (target durations): 1 day (D1), 3 days (D2), and 6 days (D3). Results: We concluded that the Maximum Tolerated Duration is at least three days. Every patient showed clinical improvement and excellent tolerance to H2 therapy. Discussion/conclusion: To the best of our knowledge, this phase 1 clinical trial is the first to establish the safety of inhaling a mixture of H2 (3.6%) and N2 (96.4%) in hospitalized Covid-19 patients. The original device and method employed ensure the absence of explosion risk. The encouraging outcomes observed in the 12 patients included in the study justify further exploration through larger, controlled clinical trials.
Lung Nodule Growth Analysis from 3D CT Data with a Coupled Segmentation and Registration Framework

In this paper we propose a new framework to simultaneously segment and register lung and tumor in serial CT data. Our method assumes nonrigid transformation on lung deformation and rigid structure on the tumor. We use the B- Spline-based nonrigid transformation to model the lung deformation while imposing rigid transformation on the tumor to preserve the volume and the shape of the tumor. In particular, we set the control points within the tumor to form a control mesh and thus assume the tumor region follows the same rigid transformation as the control mesh. For segmentation, we apply a 2D graph-cut algorithm on the 3D lung and tumor datasets. By iteratively performing segmentation and registration, our method achieves highly accurate segmentation and registration on serial CT data. Finally, since our method eliminates the possible volume variations of the tumor during registration, we can further estimate accurately the tumor growth, an important evidence in lung cancer diagnosis. Initial experiments on five sets of patients ' serial CT data show that our method is robust and reliable.
Event-based analysis of video

Dynamic events can be regarded as long-term temporal objects, which are characterized by spatio-temporal features at multiple temporal scales. Based on this, we design a simple statistical distance measure between video sequences (possibly of different lengths) based on their behavioral content. This measure is non-parametric and can thus handle a wide range of dynamic events. We use this measure for isolating and clustering events within long continuous video sequences. This is done without prior knowledge of the types of events, their models, or their temporal extent. An outcome of such a clustering process is a temporal segmentation of long video sequences into event-consistent sub-sequences, and their grouping into event-consistent clusters. Our event representation and associated distance measure can also be used for event-based indexing into long video sequences, even when only one short example-clip is available. However, when multiple example-clips of the same event are available (either as a result of the clustering process, or given manually), these can be used to refine the event representation, the associated distance measure, and accordingly the quality of the detection and clustering process.
Application of Receiver Operating Characteristic Analysis to Refine the Prediction of Potential Digoxin Drug Interactions

In the 2012 Food and Drug Administration (FDA) draft guidance on drug-drug interactions (DDIs), a new molecular entity that inhibits P-glycoprotein (P-gp) may need a clinical DDI study with a P-gp substrate such as digoxin when the maximum concentration of inhibitor at steady state divided by IC50 ([I1]/IC50) is ≥0.1 or concentration of inhibitor based on highest approved dose dissolved in 250 ml divide by IC50 ([I2]/IC50) is ≥10. In this article, refined criteria are presented, determined by receiver operating characteristic analysis, using IC50 values generated by 23 laboratories. P-gp probe substrates were digoxin for polarized cell-lines and N-methyl quinidine or vinblastine for P-gp overexpressed vesicles. Inhibition of probe substrate transport was evaluated using 15 known P-gp inhibitors. Importantly, the criteria derived in this article take into account variability in IC50 values. Moreover, they are statistically derived based on the highest degree of accuracy in predicting true positive and true negative digoxin DDI results. The refined criteria of [I1]/IC50 ≥ 0.03 and [I2]/IC50 ≥ 45 and FDA criteria were applied to a test set of 101 in vitro-in vivo digoxin DDI pairs collated from the literature. The number of false negatives (none predicted but DDI observed) were similar, 10 and 12%, whereas the number of false positives (DDI predicted but not observed) substantially decreased from 51 to 40%, relative to the FDA criteria. On the basis of estimated overall variability in IC50 values, a theoretical 95% confidence interval calculation was developed for single laboratory IC50 values, translating into a range of [I1]/IC50 and [I2]/IC50 values. The extent by which this range falls above the criteria is a measure of risk associated with the decision, attributable to variability in IC50 values.
Effect of platelet-derived growth factor-BB on tissue integration of cross-linked and non-cross-linked collagen matrices in a rat ectopic model.

AIM To test whether or not the network structure and the addition of recombinant human platelet-derived growth factor-BB (rhPDGF-BB) to a chemically cross-linked collagen matrix (CCM)- and a non-cross-linked collagen matrix (NCCM)-influenced tissue integration, angiogenesis, and matrix degradation. MATERIALS AND METHODS Four treatment modalities were randomly assigned to four unconnected pouches in the back of 50 rats: (i) CCM-S (soaked in saline), (ii) CCM-P (plus rhPDGF-BB), (iii) NCCM-S (soaked in saline), and (iv) NCCM-P (plus rhPDGF-BB). The animals were sacrificed at 2, 4, 8, 16, and 24 weeks. Descriptive histology and histomorphometric assessments were performed thereby evaluating matrix thickness, the number of vessels (angiogenesis), and connective tissue formation. Means and standard deviations were calculated. Robust linear mixed modeling was used to test the effect of group (NCCM vs CCM), rhPDGF-BB, and time point of sacrifice (2, 4, and 8 weeks). RESULTS The thickness of NCCM groups revealed stability (range 440-570 μm) over 8 weeks, while the matrices were no longer present at 16 and 24 weeks. CCM matrices demonstrated a maximal thickness at 2 weeks (2689 ± 187 μm for CCM-S and 2693 ± 389 μm for CCM-P), a decrease of roughly 40% at 8 weeks, but were still present at 16 and 24 weeks. Vascularization of NCCM gradually increased over time with a peak (mean 17.0; SD 1.7) for NCCM-S and NCCM-P (22.0 ± 34.8) at 8 weeks. Angiogenesis in CCM was significantly more pronounced at early time points with a peak at 2 weeks (29.3 ± 16.8 for CCM-S and 30.3 ± 18.4 for CCM-P). No statistically significant effect of rhPDGF-BB was observed for any of the evaluated parameters (all P > 0.05). CONCLUSIONS The compact layer (in NCCM) delayed angiogenesis and connective tissue formation, while the spongeous cross-linked matrix of CCM facilitated early vascularization and demonstrated network presence over a longer time span.
Forest Cover Database Updates Using Multi-Seasonal RapidEye Data—Storm Event Assessment in the Bavarian Forest National Park

Abstract: This study is a part of a research program that investigates the potential of RapidEye (RE) satellite data for timely updates of forest cover databases to reflect both regular management activities and sudden changes due to bark beetle and storms. Applied here in the Bavarian Forest National Park (BFNP) in southeastern Germany, this approach detected even small changes between two data takes, thus, facilitating documentation of regular management activities. In the case of a sudden event, forest cover databases also serve as a baseline for damage assessment. A storm event, which occurred on 13 July, 2011, provided the opportunity to assess the effectiveness of multi-seasonal RE data for rapid damage assessment. Images of sufficient quality (<20% cloud cover) acquired one day before the storm event were used as a baseline. Persistent cloud cover meant that the first “after event” image of sufficient quality was acquired six weeks later, on 22 August, 2011. Aerial images (AI) for the official damage assessment done by the BFNP administration were acquired on that same day. The RE analysis for damage assessment was completed two weeks after the post-event data take with an overall accuracy of 96% and a kappa coefficient of 0.86. In contrast, the official aerial image survey from the BFNP
The Hilbert Space Theoretical Foundation of Semi-Nonparametric Modeling

Semi-nonparametric (SNP) models are models where only a part of the model is parametrized, and the non-specified part is an unknown function which is represented by an infinite series expansion. Therefore, SNP models are in essence models with infinitely many parameters. The theoretical foundation of series expansions of functions is Hilbert space theory, in particular the properties of Hilbert spaces of square integrable real functions. In Hilbert spaces of functions there exist sequences of orthonormal functions such that any function in this space can be represented by a linear combination of these orthonormal functions. Such orthonormal sequences are called complete. The main purpose of this chapter is to show how these orthonormal functions can be constructed and how to construct general series representations of density and distribution functions. Moreover, in order to explain why this can be done the necessary Hilbert space theory involved will be reviewed as well.
Biochemical Characterization of CD1d Expression in the Absence of β2-Microglobulin*

CD1d is a major histocompatibility complex class I-like molecule that exhibits a distinct antigen processing pathway that functions in the presentation of hydrophobic antigens to T cells. CD1d has been previously shown to be expressed on the cell surface of human intestinal epithelial cell lines in vivo and a transfected cell line in vitro independently of β2-microglobulin (β2m). To define the relationship between CD1d and β2m and characterize the biochemical structure of CD1d in the absence of β2m, we have used a newly generated series of CD1d transfectants and CD1d-specific antibodies. These studies show that in the absence of β2m, CD1d is expressed on the cell surface as a 45-kDa glycoprotein that is sensitive to endoglycosidase-H and is reduced to 37-kDa after N-glycanase digestion. In contrast, in the presence of β2m, CD1d is expressed on the cell surface as a 48-kDa endoglycosidase-H-resistant glycoprotein. Pulse-chase metabolic labeling studies demonstrate that acquisition of endoglycosidase-H resistance of CD1d is observed in the presence of β2m but not in the absence of β2m even after a 24-h chase period. Thus, CD1d is able to be transported to the cell surface independently of β2m; however, in the absence of β2m, the glycosylation pattern of CD1d is altered and consistent with an immature glycoprotein.
On the concrete hardness of Learning with Errors

Abstract The learning with errors (LWE) problem has become a central building block of modern cryptographic constructions. This work collects and presents hardness results for concrete instances of LWE. In particular, we discuss algorithms proposed in the literature and give the expected resources required to run them. We consider both generic instances of LWE as well as small secret variants. Since for several methods of solving LWE we require a lattice reduction step, we also review lattice reduction algorithms and use a refined model for estimating their running times. We also give concrete estimates for various families of LWE instances, provide a Sage module for computing these estimates and highlight gaps in the knowledge about algorithms for solving the LWE problem.
PlanetData Network of Excellence FP 7 – 257641 D 1 . 5 Trend and anomaly detection in non-structured data Coordinator :

for dissemination) Non-structured or unstructured data is data that doesn’t conform to an explicit and well-defined formal data model. This deliverable focuses on textual and network data. We discuss several statistical properties by which these types of data differ from more structured data. Trend and anomaly detection is the process of discovering patterns in the data that do not conform to normal or expected behaviour; it has many applications and draws upon techniques from several related disciplines. We present the state of the art and directions for future work in several areas relevant to trend and anomaly detection in textual and network data: text processing of informal documents, online learning, adaptive data summarization, event processing, social media management, network sampling, and network evolution.
The smart city apps as the core of place branding strategy: a comparative analysis of innovation cases

espanolEl fenomeno de las ciudades inteligentes representa el desarrollo logico y natural de las ciudades tradicionales debido a la mejora de las tecnologias de la comunicacion aplicadas a los servicios que prestan diariamente. Los ciudadanos y los contenidos que van dirigidos a ellos deberian ser prioritarios, sin embargo parecen estar ausentes en la gran mayoria de estudios e investigaciones. Este trabajo se centra en el analisis de aplicaciones digitales de ciudades espanolas pioneras en el area de las smart cities y de las innovaciones que mejoran la participacion de los ciudadanos y su integracion en el nuevo ecosistema digital. EnglishThe phenomenon of the smart cities represents the logical and natural development of traditional cities due to the improvement of communication technologies applied to the services they provide on daily operating processes. In the cities’ process of comprehensive transformation, the citizens and the content aimed at them should appear in order of priority. This research focuses its attention on the analysis of digital apps by pioneering Spanish smart cities as well as innovations that enhance citizens participation and their integration into the new digital ecosystem in Spain. EuskaraHiri adimendunen fenomenoa hiri tradizionalen garapen logikoa eta naturala da, komunikazioaren teknologien hobekuntzak aplikatzen baitira egunero ematen diren zerbitzuetan. Herritarrek eta haiei zuzendutako edukiek izan behar lukete lehentasuna, baina, dirudienez, ez dira agertzen azterketa eta ikerketa gehienetan. Lan honek hiri adimendunen arloan aitzindari izan diren Espainiako zenbait hiriren aplikazio digitalak ditu aztergai, bai eta herritarren parte-hartzea eta jendea ekosistema digital berrian integratzea hobetzen duten berrikuntzak ere.
Within-Session Reliability of fNIRS in Robot-Assisted Upper-Limb Training

Functional near-infrared spectroscopy (fNIRS) seems opportune for neurofeedback in robot-assisted rehabilitation training due to its noninvasive, less physical restriction, and no electromagnetic disturbance. Previous research has proved the cross-session reliability of fNIRS responses to non-motor tasks (e.g., visual stimuli) and fine-motor tasks (e.g., finger tapping). However, it is still unknown whether fNIRS responses remain reliable 1) in gross-motor tasks, 2) within a training session, and 3) for different training parameters. Hence, this study aimed to investigate the within-session reliability of fNIRS responses to gross-motor tasks for different training parameters. Ten healthy participants were recruited to conduct right elbow extension-flexion in three robot-assisted modes. The Passive mode was fully motor-actuated, while Active1 and Active2 modes involved active engagement with different resistance levels. FNIRS data of three identical runs were used to assess the within-session reliability in terms of the map- (<inline-formula> <tex-math notation="LaTeX">${R}^{{2}}$ </tex-math></inline-formula>) and cluster-wise (<inline-formula> <tex-math notation="LaTeX">${R}_{\textit {over}\textit {lap}}$ </tex-math></inline-formula>) spatial reproducibility and the intraclass correlation (ICC) of temporal features. The results revealed good spatial reliability (<inline-formula> <tex-math notation="LaTeX">${R}^{{2}}$ </tex-math></inline-formula> up to 0.69, <inline-formula> <tex-math notation="LaTeX">${R}_{\textit {over}\textit {lap}}$ </tex-math></inline-formula> up to 0.68) at the subject level. Besides, the within-session temporal reliabilities of Slope, Max/Min, and Mean were between good and excellent (<inline-formula> <tex-math notation="LaTeX">$0.60< $ </tex-math></inline-formula> ICC < 0.86). We also found that the within-session reliability was positively correlated with the intensity of the training mode, except for the temporal reliability of HbO in Active2 mode. Overall, our results demonstrated good within-session reliability of fNIRS responses, suggesting fNIRS as reliable neurofeedback for constructing closed-loop robot-assisted rehabilitation systems.
Coordinated Dispersal and Pre-Isthmian Assembly of the Central American Ichthyofauna

&NA; We document patterns of coordinated dispersal over evolutionary time frames in heroine cichlids and poeciliine live‐bearers, the two most species‐rich clades of freshwater fishes in the Caribbean basin. Observed dispersal rate (DO) values were estimated from time‐calibrated molecular phylogenies in Lagrange+, a modified version of the ML‐based parametric biogeographic program Lagrange. DO is measured in units of “wallaces” (wa) as the number of biogeographic range‐expansion events per million years. DO estimates were generated on a dynamic paleogeographic landscape of five areas over three time intervals from Upper Cretaceous to Recent. Expected dispersal rate (DE) values were generated from alternative paleogeographic models, with dispersal rates proportional to target area and source‐river discharge volume, and inversely proportional to paleogeographic distance. Correlations between DO and DE were used to assess the relative contributions of these three biogeographic parameters. DO estimates imply a persistent dispersal corridor across the Eastern (Antillean) margin of the Caribbean plate, under the influence of prevailing and perennial riverine discharge vectors such as the Proto‐Orinoco‐Amazon river. Ancestral area estimation places the earliest colonizations of the Greater Antilles and Central America during the Paleocene‐Eocene (ca. 58–45 Ma), potentially during the existence of an incomplete Paleogene Arc (˜59 Ma) or Lesser Antilles Arc (˜45 Ma), but predating the GAARlandia land bridge (˜34–33 Ma). Paleogeographic distance is the single best predictor of DO. The Western (Central American) plate margin did not serve as a dispersal corridor until the Late Neogene (12–0 Ma), and contributed relatively little to the formation of modern distributions.
Psychiatric Symptom Patterns of Chronic Epileptics Attending a Neurological Clinic: A Controlled Investigation

Summary The psychiatric morbidity of chronic epileptic out-patients unknown to psychiatric agencies was assessed using two questionnaire measures of psychopathology (GHQ and CCEI). Nearly half of the epileptics were classified as probable psychiatric cases. Psychiatric morbidity was both more prevalent and more severe in this group than in a comparison group of chronic neurological out-patients. Depression, anxiety and hysterical symptomatology were the commonest characteristics of psychiatrically impaired epileptics. The type and severity of epilepsy were found to influence both the degree and pattern of psychiatric morbidity. Contrary to previous findings, age of onset had no relation to psychopathology.