Miracle-dz/UniFAR-FTUs huggingface dataset:
Determining the Spring to Summer Transition in the Missouri Ozarks Using Synoptic Scale Atmospheric Data

There is abundant anecdotal evidence available to suggest that the transition from a spring to summer season flow regime is often quite abrupt. This same transition renders longrange forecasting problematic as the forecast time period crosses through the spring and summer seasons. Despite these problems, the transition from spring-to-summer flow regimes is a problem that has not been examined in detail in the published literature. In this study, the transition is examined from a regional perspective over a 20-year period (1981 – 2000) and includes the development of a criterion for identifying the transition based on using routinely available synoptic observations. Within the East-central Ozarks region of Missouri, the transition from spring-to-summer season flow regimes is often abrupt, and is identified as occurring in mid-June. The transition could also be identified for the entire Northern Hemisphere using the 500 hPa wave amplitude index for some years during the 1980’s. The results found here are consistent with the results of the one other study found in the literature that also addresses the spring-tosummer transition issue for the entire Northern Hemisphere. Additionally, this study found that the average date of summer onset in the region is June, and the 20-year set of summer onset dates was normally distributed with respect to this mean. It was also shown that there is an abrupt change in the average period between heavy precipitation events. Finally, it is demonstrated that late arriving summers are generally associated with a transition in the phase of the El Nino and Southern Oscillation (ENSO), especially the La Nina phase, while early arriving summers are generally associated with steady-state ENSO conditions.
Thurston norms, $L^2$-norms, geodesic laminations, and Lipschitz maps

For closed hyperbolic $3$-manifolds $M$ with volume less than a constant $V$, we prove an inequality regarding the geometric $L^2$-norm and the topological Thurston norm, which is qualitatively sharp and verifies a conjecture of Brock and Dunfield in this case. Generically, we show that the $L^2$-norm is less than a constant $c(V)$ times the Thurston norm by showing that any least area closed surface is disjoint from the thin part. We then study the connection between the Thurston norm, best Lipschitz circle-valued maps, and maximal stretch laminations, building on the recent work of Daskalopoulos and Uhlenbeck, and Farre, Landesberg and Minsky. We show that the distance between a level set and its translation is the reciprocal of the Lipschitz constant, bounded by the topological entropy of the pseudo-Anosov monodromy if $M$ fibers. For infinitely many examples constructed by Rudd, we show the entropy is bounded from below by one-third the length of the circumference.
Soft Wrist Exosuit Actuated by Fabric Pneumatic Artificial Muscles

Recently, soft actuator-based exosuits have gained interest, due to their high strength-to-weight ratio, inherent safety, and low cost. We present a novel wrist exosuit actuated by fabric pneumatic artificial muscles that can move the wrist in flexion/extension and ulnar/radial deviation. We derive a model representing the torque exerted by the exosuit and introduce a model-based optimization methodology for the selection of placement parameters of the exosuit muscles. We evaluate the accuracy of the model by measuring the exosuit torques throughout the full range of wrist flexion/extension. When accounting for the displacement of the mounting points, the model predicts the exosuit torque with a mean absolute error of 0.279 Nm, which is 26.1% of the average measured torque. To explore the capabilities of the exosuit to move the human body, we measure its range of motion on a passive human wrist; the exosuit is able to achieve 55.0% of the active biological range in flexion, 69.1% in extension, 68.6% in ulnar deviation, and 68.4% in radial deviation. Finally, we demonstrate the device controlling the passive human wrist to move to a desired orientation in the flexion/extension plane and along a two-degree-of-freedom trajectory.
Phylogenetic invariants: straightforward from the general Markov to equivariant models

In the last decade, some algebraic tools have been successfully applied to phylogenetic reconstruction. These tools are mainly based on the knowledge of equations describing algebraic varieties associated to phylogenetic trees evolving under Markov processes of molecular substitution, the so called phylogenetic invariants. Although the theory involved allows to explicitly obtain these equations for all equivariant models (which include some of the most popular nucleotide substitution models), practical uses of these algebraic tools have been restricted to the case of the general Markov model. Arguably, one of the reasons for this restriction is that knowledge of linear representation theory is required before making these equations explicit. With the aim of enlarging the practical uses of algebraic phylogenetics, in this paper we prove that phylogenetic invariants for trees evolving under equivariant models can be derived from phylogenetic invariants for the general Markov model, without the need of representation theory. Our main result states that the algebraic variety corresponding to a phylogenetic tree evolving under an equivariant model is an irreducible component of the variety corresponding to the same tree under the general Markov model cut with the linear space defined by the model. We also prove that, for any equivariant model, those phylogenetic invariants that are relevant for practical uses (e.g. tree reconstruction) can be simply deduced from a single rank constraint on the matrices obtained by flattening the joint distribution at the leaves of the tree. This condition can be easily tested from singular values of the matrices and extends our results from trees to phylogenetic networks.
Auxiliary loss to attention head for end to end speaker diarization

This study introduces a novel auxiliary function for use in the Self-Attention End-to-End Speaker Diarization (SA-EEND) model, aiming to achieve accurate speaker label prediction within overlapping speech regions. Previous research has lacked effective methods for leveraging speaker information within the model to enhance auxiliary model training and has not taken into account variations in the distribution of different speech activity patterns. This study proposes a novel auxiliary function to facilitate speaker label prediction within overlapping speech regions. By considering both the overall speech activity patterns and the task-specific speech activity patterns for different speakers, we adjust the weight matrices of the multi-head self-attention mechanism in the Transformer layers. We also select loss functions that can improve the learning performance for labels with fewer occurrences, resulting in better speaker discrimination. Experimental evaluations were conducted on Mini LibriSpeech. Although the results exhibited some limitations, there were still notable advancements made. 關鍵詞：語者標記、端到端語者標記、注 意力機制、輔助損失函數
Category Mapping for Zero-shot Text Classification

The existing method of using large pre-trained models with prompts for zero-shot text classification possesses powerful representation ability and scalability. However, its commercial availability is relatively limited. The approach of employing class labels and existing datasets to fine-tune smaller models for zero-shot classification is comparatively straightforward, yet it might lead to weaker model generalization ability. This paper introduces three meth-ods to enhance the accuracy and generalization capability of pre-trained models in zero-shot text classification tasks: 1) utilizing pre-trained language models and structuring inputs into a standardized multiple-choice format; 2) creating a text classification training dataset using Wikipedia text data and refin-∗
Efficacy of non-conventional synthetic DMARDs for patients with rheumatoid arthritis-associated interstitial lung disease: a systematic review and meta-analysis

Objectives We conducted a systematic review and meta-analysis to determine the efficacy of non-conventional synthetic disease-modifying antirheumatic drug (ncs-DMARD) strategies on patients with rheumatoid arthritis (RA)-associated interstitial lung disease (ILD). Methods PubMed, EMBASE, the Cochrane Library and Web of Science were searched for relevant articles from inception to 1 June 2022. The results obtained from the analysis were expressed as mean difference (MD), effect size and 95% CI. Results A total of 17 studies, including 1315 patients with RA-ILD, were eligible. The ncs-DMARDs included abatacept, rituximab, tocilizumab, tumour necrosis factor and Janus kinase inhibitors. Compared with the baseline, there were no significant changes in forced vital capacity (FVC), forced expiratory volume in the first second (FEV1) and diffusion lung capacity for carbon monoxide (DLCO) values in the pooled data after ncs-DMARD treatment (alone or combined with conventional therapy) (p=0.36 for FVC; p=0.96 for FEV1 and p=0.46 for DLCO). Of note, FVC was obviously increased in rituximab subgroup (MD=−4.62, 95% CI −8.90 to −0.33, p=0.03). Also, high-resolution CT non-progression rate and fatality rate due to ILD progression in patients with RA-ILD were 0.792 (95% CI 0.746 to 0.834, p=0.015) and 0.049 (95% CI 0.035 to 0.065, p=0.000), respectively. Conclusion ncs-DMARDs alone or combined with conventional therapy might be an optimal and promising treatment for stabilising or improving ILD in patients with RA-ILD. PROSPERO registration number CRD42022356816.
Use of CT, ED presentation and hospitalisations 12 months before and after a diagnosis of cancer in Western Australia: a population-based retrospective cohort study

Objective To examine the use of CT, emergency department (ED)-presentation and hospitalisation and in 12 months before and after a diagnosis of cancer. Design Population-based retrospective cohort study. Setting West Australian linked administrative records at individual level. Participants 104 009 adults newly diagnosed with cancer in 2004–2014. Main outcome measures CT use, ED presentations, hospitalisations. Results As compared with the rates in the 12th month before diagnosis, the rate of CT scans started to increase from 2 months before diagnosis with an increase in both ED presentations and hospitalisation from 1 month before the diagnosis. These rates peaked in the month of diagnosis for CT scans (477 (95% CI 471 to 482) per 1000 patients), and for hospitalisations (910 (95% CI 902 to 919) per 1000 patients), and the month prior to diagnosis for ED (181 (95% CI 178 to 184) per 1000 patients) then rapidly reduced after diagnosis but remained high for the next 12 months. While the patterns of the health services used were similar between 2004 and 2014, the rate of the health services used during after diagnosis was higher in 2014 versus 2004 except for CT use in patients with lymphohaematopoietic cancer with a significant reduction. Conclusion Our results showed an increase in demand for health services from 2 months before diagnosis of cancer. Increasing use of health services during and post cancer diagnosis may warrant further investigation to identify factors driving this change.
Quantifying Network Level Improvement due to Beamforming on the Performance of Large-Scale Dense Urban IoT Networks

There have been many papers that show the physical layer advantages of beamforming. However, to the best of our knowledge, none have dealt with the large-scale network level performance evaluation. While it is clear that beamforming brings a positive effect on network performance, that improvement has not been quantified. This is important given that, despite its advantages, large-scale beamforming deployment also implies additional CAPEX and OPEX costs for service providers. This paper presents a large-scale network layer simulation study that aims at quantifying some network layer Key Performance Indicators improvement achieved by the massive introduction of beamforming in the network. We first show how we adapted a simulation-efficient packet scheduling procedure to our large-scale PIoT simulator engine. Then, we perform extensive simulations on a real network of the city of Montréal with 30000 UEs (User Equipment) and 3019 antennas. Among many results it was found that, on average, more than 30 ms of waiting delay reduction can be achieved with beamforming. Also, for applications with very short packet inter arrival time, the total traffic serviced more than doubled. Simulation results also show that while the increase in the number of beams improves performance, there is also a saturation effect that can be perceived at the network level. It was also found that when the traffic arrival is Poisson, the benefits of beamforming are less striking, which suggests that the type of application traffic may have an influence in the beneficial impact of beamforming at the network level, opening the path for further investigation. Finally, given that the simulator front end is publicly available at http://piotsimulation.com , the paper also shows the potentiality for the community to perform what-if cross layer analysis in a real-sized urban network.
SoftDECA: Computationally Efficient Physics-Based Facial Animations

Facial animation on computationally weak systems is still mostly dependent on linear blendshape models. However, these models suffer from typical artifacts such as loss of volume, self-collisions, or erroneous soft tissue elasticity. In addition, while extensive effort is required to personalize blendshapes, there are limited options to simulate or manipulate physical and anatomical properties once a model has been crafted. Finally, second-order dynamics can only be represented to a limited extent. For decades, physics-based facial animation has been investigated as an alternative to linear blendshapes but is still cumbersome to deploy and results in high computational cost at runtime. We propose SoftDECA, an approach that provides the benefits of physics-based simulation while being as effortless and fast to use as linear blendshapes. SoftDECA is a novel hypernetwork that efficiently approximates a FEM-based facial simulation while generalizing over the comprehensive DECA model of human identities, facial expressions, and a wide range of material properties that can be locally adjusted without re-training. Along with SoftDECA, we introduce a pipeline for creating the needed high-resolution training data. Part of this pipeline is a novel layered head model that densely positions the biomechanical anatomy within a skin surface while avoiding self-intersections.
New Machine Learning Hybrid Models to Lower Position Errors for Bluetooth-Based Indoor Localizations

In recent times, there has been a significant development of critical IoT-based applications in the field of indoor localization (e.g., locating an asset or person). The utilization of Machine Learning (ML) algorithms to enhance accuracy in the presence of interference has generated considerable interest among researchers in this domain. This research paper introduces two hybrid models, namely the Asymmetric and Symmetric Line-Shifting hybrid models, which integrate novel line shifting algorithms with ML classifiers and regressors. The primary objective of these models is to reduce positioning errors. By shifting learned and predicted Reference Points using ML algorithms, the models calculate centroids that closely align with the targets' locations. Through real-world analysis, it was demonstrated that the new models achieved lower Root Mean Square Error (RMSE) and improved R-squared values compared to those obtained using the Constant Line Shifting algorithm (e.g., 52% and 29%, respectively). Moreover, both models outperformed the version without Reference Point shifting in terms of RMSE and R-squared values (e.g., 76% and 273%, respectively). Consequently, the proposed hybrid models are deemed accurate and reliable for many indoor localization applications.
Interactions of netrin-1 through its glycosylation sites immobilize Deleted in Colorectal Cancer (DCC) by favoring its constitutive clustering

Netrin-1 is a protein that attracts neurons expressing the membrane receptor Deleted in Colorectal Cancer DCC. In colon carcinoma, the interaction between netrin-1 and DCC prevents apoptosis. Crystallographic data suggest that these processes involve the clustering of DCC, the observation of which in cells remains elusive, as do the molecular determinants of DCC-netrin-1 interactions and their impact on DCC organization and mobility. To address these questions, we used fluorescence photobleaching, single-particle tracking and super-resolution techniques to characterize DCC organization and mobility on the cell surface. Our results show that netrin-1 impedes DCC mobility in the plasma membrane by promoting the growth of constitutive DCC nanoclusters at the expense of free DCC. Furthermore, we show that these effects are mediated primarily by the three glycosylation sites in the LamVI domain of netrin-1 and, to a lesser extent, by the C-terminal domain and its RGD binding site.
Establishing CRISPR-Cas9 in the sexually dimorphic moss, Ceratodon purpureus

The development of CRISPR technologies provides a powerful tool for understanding the evolution and functionality of essential biological processes. Here we demonstrate successful CRISPR-Cas9 genome editing in the dioecious moss species, Ceratodon purpureus. Using an existing selection system from the distantly related hermaphroditic moss, Physcomitrium patens, we generated knock-outs of the APT reporter gene by employing CRISPR targeted mutagenesis under expression of native U6 snRNA promoters. Next, we used the native homology-directed repair (HDR) pathway, combined with CRISPR-Cas9, to knock-in two reporter genes under expression of an endogenous RPS5A promoter in a newly developed landing site in C. purpureus. Our results show that the molecular tools developed in P. patens can be extended to other mosses across this ecologically important and developmentally variable group. These findings pave the way for precise and powerful experiments aimed at identifying the genetic basis of key functional variation within the bryophytes and between the bryophytes and other land plants. Significance Statement We have developed CRISPR-Cas9 genome editing tools and protocols for the sexually dimorphic moss, Ceratodon purpureus to generate gene knock-outs and knock-ins within targeted loci. This work facilitates future functional genomic experiments in this fast growing, haploid, dioecious system and suggests these tools will function across much of moss diversity.
Acoustomechanically activatable liposomes for ultrasonic drug uncaging

Ultrasound-activatable drug-loaded nanocarriers enable noninvasive and spatiotemporally-precise on-demand drug delivery throughout the body. However, most systems for ultrasonic drug uncaging utilize cavitation or heating as the drug release mechanism and often incorporate relatively exotic excipients into the formulation that together limit the drug-loading potential, stability, and clinical translatability and applicability of these systems. Here we describe an alternate strategy for the design of such systems in which the acoustic impedance and osmolarity of the internal liquid phase of a drug-loaded particle is tuned to maximize ultrasound-induced drug release. No gas phase, cavitation, or medium heating is necessary for the drug release mechanism. Instead, a non-cavitation-based mechanical response to ultrasound mediates the drug release. Importantly, this strategy can be implemented with relatively common pharmaceutical excipients, as we demonstrate here by implementing this mechanism with the inclusion of a few percent sucrose into the internal buffer of a liposome. Further, the ultrasound protocols sufficient for in vivo drug uncaging with this system are achievable with current clinical therapeutic ultrasound systems and with intensities that are within FDA and society guidelines for safe transcranial ultrasound application. Finally, this current implementation of this mechanism should be versatile and effective for the loading and uncaging of any therapeutic that may be loaded into a liposome, as we demonstrate for four different drugs in vitro, and two in vivo. These acoustomechanically activatable liposomes formulated with common pharmaceutical excipients promise a system with high clinical translational potential for ultrasonic drug uncaging of myriad drugs of clinical interest. One Sentence Summary Incorporating a few percent sucrose into a liposome transforms it into an immediately translatable vehicle for noninvasive, on-demand ultrasound-targeted drug delivery.
Gene expression analyses reveal differences in children’s response to malaria according to their age

In Bandiagara, Mali, children experience on average two clinical malaria episodes per season. However, even in the same transmission area, the number of uncomplicated symptomatic infections, and their parasitemia, vary dramatically among children. To examine the factors contributing to these variations, we simultaneously characterized the host and parasite gene expression profiles from 136 children with symptomatic falciparum malaria and analyzed the expression of 9,205 human and 2,484 Plasmodium genes. We used gene expression deconvolution to estimate the relative proportion of immune cells and parasite stages in each sample and to adjust the differential gene expression analyses. Parasitemia explained much of the variation in both host and parasite gene expression and revealed that infections with higher parasitemia had more neutrophils and fewer T cells, suggesting parasitemia-dependent neutrophil recruitment and/or T cell extravasation to secondary lymphoid organs. The child’s age was also strongly correlated with gene expression variations. Plasmodium falciparum genes associated with age suggested that older children carried more male gametocytes, while host genes associated with age indicated a stronger innate response (through TLR and NLR signaling) in younger children and stronger adaptive immunity (through TCR and BCR signaling) in older children. These analyses highlight the variability in host responses and parasite regulation during P. falciparum symptomatic infections and emphasize the importance of considering the children’s age when studying and treating malaria infections. One Sentence Summary Human and P. falciparum gene expression differs according to the infection’s parasitemia and the child’s age, highlighting an age-dependent response to malaria and complex cellular and molecular -host/parasite interactions.
THE EFFECT OF URBAN DENSITY, GREEN SPACES AND MOBILITY PATTERNS IN CITIES' ENVIRONMENTAL QUALITY: AN EMPIRICAL STUDY OF THE METROPOLITAN AREA OF THESSALONIKI

It has been proved that urban development patterns affect in various ways cities’ environmental quality. To this purpose, one of the factors that have been examined is the role of urban green spaces, in balancing the effects of human activities in dense urban landscapes. One of the major external costs of dense urban environment is smog and greenhouse gas emissions that are heavily related to existing mobility patterns. High levels of concentration of such emissions along with high urban density are considered to be the main reason for cities’ environmental degradation. In this context this paper presents the results of a study investigating how urban green spaces can improve air quality, in major transportation axis within the city of Thessaloniki. In order to do so, urban density along the axis, green space per capita, green space spatial distribution, mobility patterns and transport emissions volumes are being considered. Comparison of these indices among the transportation axis under study indicates that there is a positive relation between building density, urban density and volume of emissions observed, while a dispersed rather than a concentrated pattern of green spaces could better help improve cities’ environmental quality.