Miracle-dz/UniFAR-FTUs huggingface dataset:
The prognostic value of chemotherapy or endocrine therapy choice according to circulating tumor cell count in HR+HER2− metastatic breast cancer: a retrospective study

Background Circulating tumor cell (CTC) count have prognostic role for metastatic breast cancer (MBC). No clear biomarkers can guide selection of chemotherapy (CT) or endocrine therapy (ET) in 1st-line setting of hormone-receptor positive and human epidermal growth factor receptor 2 negative (HR+HER2−) MBC. The present study investigated the prognostic role CT or ET according to the CTC count in HR+HER2− MBC. Methods We consecutively collected the data of 53 HR+HER2− MBC patients who received 1st-line CT or ET, who had CTC count detected by our peptide-based nanomagnetic CTC isolation system (Pep@MNPs) from January 2014 to December 2015. The clinicopathological characteristics according the CTC count and 1st-line ET vs. CT were compared. Follow-up was conducted every 6 months. The primary endpoint was progression-free survival (PFS) and overall survival (OS). A Cox regression analysis was conducted to determine the prognostic roles of CTC and 1st-line therapy of ET vs. CT for PFS and OS. Results The median CTC count of the 53 patients was 2 (range, 0–18). The clinicopathological characteristics of the patients in the CTC count <2 group and the CTC count ≥2 group were similar. The patients with a CTC count <2 had a significantly longer PFS than those with a CTC count ≥2 (P=0.005, hazard ratio =4.138, 12.1 vs. 7.1 months). The patients who received CT had a significantly longer PFS than those who received ET (P=0.041, hazard ratio =2.721, 9.9 vs. 7.2 months). In the CTC count ≥2 group, the patients who received CT had a significantly longer PFS than those who received ET (P=0.048, hazard ratio =2.475, 8.7 vs. 6.3 months). In the CTC count <2 group, there was no significant difference in PFS between the CT and ET groups (P=0.071). Additionally, the CTC count had no significant effect on OS (P=0.116, hazard ratio =2.391, 54.2 vs. 34.2 months). Conclusions The present study showed that CTC count determined by the Pep@MNP system confirmed the prognostic value in the HR+HER2− MBC patients. And it might be helpful in choosing a 1st-line treatment of CT or ET for HR+HER2− MBC patients.
Stratigraphic range extension of the turtle Boremys pulchra (Testudinata, Baenidae) through at least the uppermost Cretaceous

New material of the derived baenid turtle Boremys pulchra from the Hell Creek Formation of Montana extends the stratigraphic range of the taxon through at minimum the latest Maastrichtian. Previously, the species was constrained to the Campanian of Montana and Alberta, so this extension constitutes at least 5 million years. Due to fossil reworking at the Bug Creek Anthills assemblage, where Maastrichtian and Paleocene deposits are mixed, a definitive extension for B. pulchra cannot currently include Paleocene strata. However, the presence of B. pulchra in latest Cretaceous strata, previous identification of Paleocene Boremys sp. and the general success of baenid taxa across the K–Pg boundary, make it quite plausible that B. pulchra survived the extinction event and that previously described Maastrichtian and Paleocene Boremys sp. material probably represents a new taxon. A stratigraphic extension beyond the Campanian indicates that B. pulchra survived the paleoenvironmental conditions of the latest Cretaceous, where adaptation to locally heterogeneous aquatic habitats and paleotemperature fluctuations may have facilitated latest Cretaceous and K–Pg survivorship. Additionally, ectoparasitic bore marks on the Boremys pulchra specimen described here can be attributed to the ichnotaxon Karethraichnus lakkos.
Development and Assessment of a Movement Disorder Simulator Based on Inertial Data

The detection analysis of neurodegenerative diseases by means of low-cost sensors and suitable classification algorithms is a key part of the widely spreading telemedicine techniques. The choice of suitable sensors and the tuning of analysis algorithms require a large amount of data, which could be derived from a large experimental measurement campaign involving voluntary patients. This process requires a prior approval phase for the processing and the use of sensitive data in order to respect patient privacy and ethical aspects. To obtain clearance from an ethics committee, it is necessary to submit a protocol describing tests and wait for approval, which can take place after a typical period of six months. An alternative consists of structuring, implementing, validating, and adopting a software simulator at most for the initial stage of the research. To this end, the paper proposes the development, validation, and usage of a software simulator able to generate movement disorders-related data, for both healthy and pathological conditions, based on raw inertial measurement data, and give tri-axial acceleration and angular velocity as output. To present a possible operating scenario of the developed software, this work focuses on a specific case study, i.e., the Parkinson’s disease-related tremor, one of the main disorders of the homonym pathology. The full framework is reported, from raw data availability to pathological data generation, along with a common machine learning method implementation to evaluate data suitability to be distinguished and classified. Due to the development of a flexible and easy-to-use simulator, the paper also analyses and discusses the data quality, described with typical measurement features, as a metric to allow accurate classification under a low-performance sensing device. The simulator’s validation results show a correlation coefficient greater than 0.94 for angular velocity and 0.93 regarding acceleration data. Classification performance on Parkinson’s disease tremor was greater than 98% in the best test conditions.
Making Sense of Language Signals for Monitoring Radicalization

Understanding radicalization pathways, drivers, and factors is essential for the effective design of prevention and counter-radicalization programs. Traditionally, the primary methods used by social scientists to detect these drivers and factors include literature reviews, qualitative interviews, focus groups, and quantitative methods based on surveys. This article proposes to complement social science approaches with computational methods to detect these factors automatically by analyzing the language signals expressed in social networks. To this end, the article categorizes radicalization drivers and factors following the micro, meso, and macro levels used in the social sciences. It identifies the corresponding language signals and available language resources. Then, a computational system is developed to monitor these language signals. In addition, this article proposes semantic technologies since they offer unique exploration, query, and discovery capabilities. The system was evaluated based on a set of competency questions that show the benefits of this approach.
Is This Science Video Popular? Let Us See How the Audience Reacts!

Abstract The popularity of science videos is critical for the dissemination of knowledge, and predicting the popularity of a video is a hot topic among researchers. The existing research is mainly based on the videos’ content (e.g., theme) or video-related external information (e.g., comments). However, videos with different popularity can bring different learning states and viewing experiences (emotional awakening, flow experiences). In this paper, we utilize participants’ learning states when they watch videos to predict the popularity of the videos, depending on two modal indicators, i.e., contact physiological indicators recorded by a Biopac MP150 polygraph and noncontact gesture indices recorded by a Kinect V2 body camera which can obtain data of head position. We propose two classification prediction models with each modality of indicator and filter out the indicators that make sense for modeling. Results show that the meaningful indicators in the physiological modality through stepwise logistic regression are the standard deviation of normal to normal R-R intervals (SDNN) and high-frequency heart rate variability (HF). We find that participants had higher SDNN and lower HF when watching science video with high popularity (compared with low popularity one), and the accuracy rate of classification model is 81.6%. In a same way, the selected meaningful indicators in the gesture aspect are the maximum, the standard deviation (SD) of distance between the participants’ head and Kinect. We find that the maximum and SD of head distance are smaller when participants studied highly popular science videos (contrary to the less popular videos) and the accuracy rate is 73.7%. Combining the four indicators for modeling by the direct input method, the accuracy rate is 78.9%, and the SD of head distance is probably the most important indicator for predicting popularity of videos. These results indicate that it is feasible to predict video popularity by learning states.
Understanding and defending against the security threats on mobile and IoT
 devices

Mobile devices have become an essential part of our daily life while IoT devices are being rapidly deployed in our home, factories, and infrastructures. These omnipresent devices bring in great convenience along with growing security and privacy concerns. For example, the attacks on IoT devices are becoming increasingly complex and destructive. New attack surfaces are also being opened up on mobile devices along with the wide deployment of machine learning (ML) technology, e.g., the privacy of on-device machine learning models. In this thesis, I present two novel systems and one large-scale study to understand and combat the newly emerging attacks on both IoT devices and mobile devices. The security of these two systems is built on hardware-backed trusted computing primitives to provide strong security guarantee. First, I present OAT, an attestation system that captures the integrity of both control ﬂow and critical data involved in an operation execution to detect advanced attacks on IoT devices. OAT advances the state-of-the-art attestation on IoT devices by providing strong control-ﬂow veriﬁcation and light-weight critical data integrity check. Second, I present the ﬁrst large-scale study of insuﬃcient model protection in mobile apps to uncover this less understood problem of model privacy on mobile devices. Based on the 46,753 trending Android apps collected from the US and Chinese app markets, alarmingly, this study shows that 41% of ML apps do not protect their models at all. For those apps that use model protection or encryption, we were able to extract the models from 66% of them via unsophisticated dynamic analysis techniques. Our ﬁnancial and security impact analysis on (stolen) models indicates that the consequence can be severe for both the model vendors and the app owners. Third, to protect on-device ML models, I propose ShadowNet, a secure and eﬃcient model inference system built to protect model privacy on mobile devices. ShadowNet oﬀers a novel idea to outsource the heavy part of the model inference to the untrusted world (including GPU) for acceleration without leaking the model weights. The security of ShadowNet is rooted in the TEE, which can protect the model privacy even when the OS is compromised.
Prediction of $h\to\gamma Z$ from $h\to\gamma\gamma$ at LHC for the IMDS$_3$ Model

We consider the decays $h\to\gamma\gamma,\gamma Z$ in the context of an extension of the standard model with two inert doublets and an additional $S_3$ symmetry. This model has contributions for these processes through new charged scalar-loops. Comparing our $h\to\gamma\gamma$ with the more precise available experimental data we can predict the behaviour of $h\to\gamma Z$ due that they depend on the same parameters, our estimation for this channel is 1.05 times the standard model value, but can be up to 1.16 if consider the $+1\sigma$ uncertainty from the $h\to\gamma\gamma$ data, and down to 0.96 if consider $-1\sigma$.
Optical Phonon Interacting with Electrons in Carbon Nanotubes(Condensed matter: electronic structure and electrical, magnetic, and optical properties)

Effects of interactions with electrons on optical phonons are studied in an effective-mass approximation. The longitudinal mode with displacement in the axis direction is lowered in its frequency, while the transverse mode with displacement in the circumference direction is raised, in metallic nanotubes. The shifts are opposite but their absolute values are smaller in semiconducting nanotubes. Only the longitudinal mode has a considerable broadening in metallic nanotubes. In the presence of an Aharonov–Bohm magnetic flux, the broadening appears for the transverse mode and diverges when the induced gap becomes the same as the frequency of the optical phonon.
Multiple blood pathogen infections in apparently healthy sheltered dogs in southern Thailand

ABSTRACT In developing countries such as Thailand, free-ranging dogs are frequently involved in road accidents and contribute to the cost of public healthcare. Shelters play a vital role in communities because they help to control the population of unwanted and free-ranging dogs. This study aimed to investigate blood pathogen infection in sheltered dogs, as it is one of the factors contributing to animal welfare. Blood samples were randomly collected from 141 dogs from the largest shelter (approximately 400–500 dogs in total) in southern Thailand. Blood pathogens were detected using both PCR and light microscopy. Four blood pathogens were identified: Anaplasma platys, Ehrlichia canis, Babesia canis vogeli, and Hepatozoon canis. No trypanosomes were detected. The incidence of blood parasite infection was 56.7% (80/141) by PCR, and 28.4% (40/141) by microscopy. E. canis was the most prevalent pathogen, accounting for 46.1% (65/141) of the cases, while multiple infections accounted for 22% (31/141) of the cases. A triple infection with E. canis, A. platys, and B. canis vogeli was observed in 5.7% (8/141) of the cases. Although PCR is far more sensitive than microscopy, it appears to have equivalent specificity. In conclusion, this study reported a high occurrence of blood pathogen infections in clinically healthy sheltered dogs. Many of them were infected with multiple pathogens and may have been infected before entering the shelter. These findings suggest that a blood test is necessary to screen dogs prior to their admission to the shelter to prevent disease transmission and enhance animal welfare.
Measures of Knee Capability in Handball Players Differ by Age: A Cross Sectional Study

Abstract The return to sport after knee injury is challenging. This is burdensome for sports with a high incidence of injuries, such as team handball. Various tests guide decision making, but often the athlete’s preinjury performance of these measures remains unknown. Moreover, objective return-to-sport criteria of a matching population are missing. The purpose of this study was to evaluate objective measures of knee capability in handball depending on players’ age. Two hundred sixty-one handball players performed a functional test battery designed to evaluate knee capability after an anterior cruciate ligament injury: two- and one-legged stability analysis, jumps, speed tests, and agility assessments. For age-specific evaluation, athletes were divided into three age groups (16–19; 20–29;≥30 years). Male players showed differences in two and one-legged jumping height (p<0.02) as well as power per body weight (p<0.01) between age groups. Young female players reached better results in two-and one-legged stability. Besides the quick feet test, results of females did not differ between age groups. Functional knee stability in healthy handball players is partly influenced by age, and females show better results in stability and male athletes in power measurements. This aspect should be considered for return to sports testing and underlines the importance of performance measures in athletic testing.
Genetic-molecular characterization in guava full-sib progeny

: Brazil is one of the world’s largest producers of guava ( Psidium guajava L.), a very promising fruit in the northern region of the state of Rio de Janeiro. Despite this, no guava cultivar has been developed for the region. Thus, this study proposed to examine a population of guava full sibs using microsatellite markers and to identify which genotypes are the most divergent for future crosses, to select cultivars better adapted to the soil and climatic conditions of northern Rio Janeiro. Ninety-six superior genotypes were selected according to their agronomic traits, which were characterized using 45 microsatellite markers. The genetic distance between the analyzed genotypes, their clustering pattern and the genetic structure of the population were estimated. Hierarchical cluster analysis by the neighbor joining method indicated the formation of three distinct groups. The use of molecular information revealed the existence of moderate genetic variability between the genotypes of the full-sib families. Bayesian analysis separated the genotypes into only two groups, as the individuals shared most of the analyzed genomic regions. The most genetically divergent guava genotypes, that is, those allocated to different groups, such as genotypes 5 and 85, should be recommended for future crosses to obtain segregating populations, thus giving continuity to the guava breeding program.
Chinese VFR Travel in Budapest: The Hosts’ Roles

In recent decades, there has been a dynamic growth of Chinese outbound tourism to the Central and Eastern European region, and Hungary has been one of the most visited countries. This increase in demand is linked, in part, to the important Chinese diaspora in Hungary whose members play the role of hosts in VFR travel. This paper aims to explore the social relations—guanxi—within the Chinese diaspora living in Budapest and its influence on VFR travels back and forth China. Results of the survey with 202 Chinese immigrants reveal the strong nexus between migration and VFR travel. The Chinese hosts who have been living in the country for two decades behave differently in their guanxi compared to those who have settled in Budapest recently. The article provides several practical contributions to local destination management organizations and tourism service providers to successfully reach Chinese hosts, such as providing commissions, coupons, and getting discounts.
N-Glycans in Immortalized Mesenchymal Stromal Cell-Derived Extracellular Vesicles Are Critical for EV–Cell Interaction and Functional Activation of Endothelial Cells

Mesenchymal stromal cell-derived extracellular vesicles (MSC-EV) are widely considered as a cell-free therapeutic alternative to MSC cell administration, due to their immunomodulatory and regenerative properties. However, the interaction mechanisms between EV and target cells are not fully understood. The surface glycans could be key players in EV–cell communication, being specific molecular recognition patterns that are still little explored. In this study, we focused on the role of N-glycosylation of MSC-EV as mediators of MSC-EV and endothelial cells’ interaction for subsequent EV uptake and the induction of cell migration and angiogenesis. For that, EV from immortalized Wharton’s Jelly MSC (iWJ-MSC-EV) were isolated by size exclusion chromatography (SEC) and treated with the glycosidase PNGase-F in order to remove wild-type N-glycans. Then, CFSE-labelled iWJ-MSC-EV were tested in the context of in vitro capture, agarose-spot migration and matrigel-based tube formation assays, using HUVEC. As a result, we found that the N-glycosylation in iWJ-MSC-EV is critical for interaction with HUVEC cells. iWJ-MSC-EV were captured by HUVEC, stimulating their tube-like formation ability and promoting their recruitment. Conversely, the removal of N-glycans through PNGase-F treatment reduced all of these functional activities induced by native iWJ-MSC-EV. Finally, comparative lectin arrays of iWJ-MSC-EV and PNGase-F-treated iWJ-MSC-EV found marked differences in the surface glycosylation pattern, particularly in N-acetylglucosamine, mannose, and fucose-binding lectins. Taken together, our results highlight the importance of N-glycans in MSC-EV to permit EV–cell interactions and associated functions.
Neurodynamics-based leader-follower formation tracking of multiple nonholonomic vehicles

Purpose The purpose of this paper is to consider the leader-following formation control problem for nonholonomic vehicles based on a novel biologically inspired neurodynamics approach. Design/methodology/approach The interactions among the networked multi-vehicle system is modeled by an undirected graph. First, a distributed estimation law is proposed for each follower vehicle to estimate the state including the position, orientation and linear velocity of the leader. Then, a distributed formation tracking control law is designed based on the estimated state of the leader, where a bio-inspired neural dynamic is introduced to solve the impractical velocity jumps problem. Explicit stability and convergence analyses are presented using Lyapunov tools. Findings The effectiveness and efficiency of the proposed control law are demonstrated by numerical simulations and physical vehicle experiments. Consequently, the proposed protocol can successfully achieve the desired formation under connected topologies while tracking the trajectory generated by the leader. Originality/value This paper proposes a neurodynamics-based leader–follower formation tracking algorithm for multiple nonholonomic vehicles.
C-Peptide-Positive, Autoantibody-Negative Type 1 Diabetes Mellitus

A 30-year-old female previously diagnosed with C-peptide (CP)-positive, autoantibody-negative type 1 diabetes mellitus (T1DM) at 19 years old presented to the clinic at age 28 for management of diabetes mellitus (DM) that had previously been controlled by insulin since diagnosis. Laboratory results from May 2011 showed low-normal C-peptide of 1 ng/mL (normal range: 0.8-4 ng/mL) with no corresponding glucose, glutamic acid decarboxylase (GAD)-65 antibody (GADA) of <1 U/mL (N<1.1 U/mL at the time of laboratory draw), and HbA1c of 6.4%. Almost 10 years later, in December 2020, laboratory results showed normal C-peptide of 2.1 ng/mL with a glucose of 198 mg/dL, GAD-65 antibody of 38.2 U/mL (current reference range: 0-5 U/mL), negative pancreatic islet antibody (IA), and undetectable zinc transporter 8 (ZnT8) antibody, consistent with a diagnosis of T1DM. This increase in CP indicates the possibility of pancreatic beta cell regeneration and/or increased function. The commonly accepted belief that individuals with T1DM quickly lose all function of pancreatic beta cells has led to academic consequences; many immunotherapy clinical trials’ inclusion criteria require participants to have a new diagnosis of T1DM based on the assumption that those with a longer duration of diabetes have unrecoverable cessation of insulin secretion. CP could influence inflammation, microvascular circulation, and endothelial function. Further, it could affect the neuronal and glomerular structure and/or function. These potential functions of CP are seen by the correlation between measurable CP levels and decreased diabetic complication rates.