Miracle-dz/UniFAR-FTUs huggingface dataset:
SiamEvent: Event-based Object Tracking via Edge-aware Similarity Learning with Siamese Networks

Event cameras are novel sensors that perceive the per-pixel intensity changes and output asynchronous event streams, showing lots of advantages over traditional cameras, such as high dynamic range (HDR) and no motion blur. It has been shown that events alone can be used for object tracking by motion compensation or prediction. However, existing methods assume that the target always moves and is the stand-alone object. Moreover, they fail to track the stopped non-independent moving objects on fixed scenes. In this paper, we propose a novel event-based object tracking framework, called SiamEvent, using Siamese networks via edge-aware similarity learning. Importantly, to find the part having the most similar edge structure of target, we propose to correlate the embedded events at two timestamps to compute the target edge similarity. The Siamese network enables tracking arbitrary target edge by finding the part with the highest similarity score. This extends the possibility of event-based object tracking applied not only for the independent stand-alone moving objects, but also for various settings of the camera and scenes. In addition, target edge initialization and edge detector are also proposed to prevent SiamEvent from the drifting problem. Lastly, we built an open dataset including various synthetic and real scenes to train and evaluate SiamEvent. Extensive experiments demonstrate that SiamEvent achieves up to 15% tracking performance enhancement than the baselines on the real-world scenes and more robust tracking performance in the challenging HDR and motion blur conditions.
Three New Infinite Families of Optimal Locally Repairable Codes from Matrix-Product Codes

Locally repairable codes have become a key instrument in large-scale distributed storage systems. This paper focuses on the construction of locally repairable codes with $(r,\delta)$-locality that achieve the equality in the Singleton-type bound. We use matrix-product codes to propose two infinite families of $q$-ary optimal $(r,\delta)$ locally repairable codes of lengths up to $q^2+q$. The ingredients in the matrix-product codes are either linear maximum distance separable codes or optimal locally repairable codes of small lengths. Further analysis and refinement yield a construction of another infinite family of optimal $(r,\delta)$ locally repairable codes. The codes in this third family have unbounded lengths not divisible by $(r+\delta-1)$. The three families of optimal $(r,\delta)$ locally repairable codes constructed here are new. Previously constructed codes in the literature have not covered the same sets of parameters. Our construction proposals are flexible since one can easily vary $r$ and $\delta$ to come up with particular parameters that can suit numerous scenarios.
Visual resemblance and communicative context constrain the emergence of graphical conventions

From photorealistic sketches to schematic diagrams, drawing provides a versatile medium for communicating about the visual world. How do images spanning such a broad range of appearances reliably convey meaning? Do viewers understand drawings based solely on their ability to resemble the entities they refer to (i.e., as images), or do they understand drawings based on shared but arbitrary associations with these entities (i.e., as symbols)? In this paper, we provide evidence for a cognitive account of pictorial meaning in which both visual and social information is integrated to support effective visual communication. To evaluate this account, we used a communication task where pairs of participants used drawings to repeatedly communicate the identity of a target object among multiple distractor objects. We manipulated social cues across three experiments and a full internal replication, finding pairs of participants develop referent-specific and interaction-specific strategies for communicating more efficiently over time, going beyond what could be explained by either task practice or a pure resemblance-based account alone. Using a combination of model-based image analyses and crowdsourced sketch annotations, we further determined that drawings did not drift toward arbitrariness, as predicted by a pure convention-based account, but systematically preserved those visual features that were most distinctive of the target object. Taken together, these findings advance theories of pictorial meaning and have implications for how successful graphical conventions emerge via complex interactions between visual perception, communicative experience, and social context.
A biconvex optimization for solving semidefinite programs via bilinear factorization

Many problems in machine learning can be reduced to learning a low-rank positive semidefinite matrix (denoted as $Z$), which encounters semidefinite program (SDP). Existing SDP solvers by classical convex optimization are expensive to solve large-scale problems. Employing the low rank of solution, Burer-Monteiro's method reformulated SDP as a nonconvex problem via the $quadratic$ factorization ($Z$ as $XX^\top$). However, this would lose the structure of problem in optimization. In this paper, we propose to convert SDP into a biconvex problem via the $bilinear$ factorization ($Z$ as $XY^\top$), and while adding the term $\frac{\gamma}{2}||X-Y||_F^2$ to penalize the difference of $X$ and $Y$. Thus, the biconvex structure (w.r.t. $X$ and $Y$) can be exploited naturally in optimization. As a theoretical result, we provide a bound to the penalty parameter $\gamma$ under the assumption of $L$-Lipschitz smoothness and $\sigma $-strongly biconvexity, such that, at stationary points, the proposed bilinear factorization is equivalent to Burer-Monteiro's factorization when the bound is arrived, that is $\gamma>\frac{1}{4}(L-\sigma)_+$. Our proposal opens up a new way to surrogate SDP by biconvex program. Experiments on two SDP-related applications demonstrate that the proposed method is effective as the state-of-the-art.
Advances in Enantioselective C–H Activation/Mizoroki-Heck Reaction and Suzuki Reaction

Traditional cross-coupling reactions, like Mizoroki-Heck Reaction and Suzuki Reaction, have revolutionized organic chemistry and are widely applied in modern organic synthesis. With the rapid development of C–H activation and asymmetric catalysis in recent years, enantioselective C–H activation/cross-coupling reactions have drawn much attention from researchers. This review summarizes recent advances in enantioselective C–H activation/Mizoroki-Heck Reaction and Suzuki Reaction, with emphasis on the structures and functions of chiral ligands utilized in different reactions.
Nonlinear Modeling and Feedback Control of Boom Barrier Automation

We address modeling and control of a gate access automation system. A model of the mechatronic system is derived and identified. Then, an approximate explicit feedback linearization scheme is proposed, which ensures almost linear response between the electronic driver duty cycle input and the delivered torque. A nonlinear optimization problem is solved offline to generate a feasible trajectory associated with a feedforward action, and a low-level feedback controller is designed to track it. The feedback gains can be conveniently tuned by solving a set of convex linear matrix inequalities, performing a multiobjective tradeoff between disturbance attenuation and transient response. The proposed control strategy is tested on an industrial device. The experiments show that it can effectively meet the requirements in terms of robustness, load disturbance rejection, and tracking performance.
Gaussian Processes to speed up MCMC with automatic exploratory-exploitation effect

We present a two-stage Metropolis-Hastings algorithm for sampling probabilistic models, whose log-likelihood is computationally expensive to evaluate, by using a surrogate Gaussian Process (GP) model. The key feature of the approach, and the difference w.r. t. previous works, is the ability to learn the target distribution from scratch (while sampling), and so without the need of pre-training the GP. This is fundamental for automatic and inference in Probabilistic Programming Languages In particular, we present an alternative first stage acceptance scheme by marginalising out the GP distributed function, which makes the acceptance ratio explicitly dependent on the variance of the GP. This approach is extended to Metropolis-Adjusted Langevin algorithm (MALA).
Synthesis and application of water-soluble hyperbranched polyester modified by trimellitic anhydride

ABSTRACT In this paper, we aimed to synthesize a water-soluble hyperbranched polyester with pentaerythritol and trimethylolpropane as branching centers and trimellitic anhydride as waterborne functional groups. The condition and principle of water-soluble hyperbranched resin synthesis were explored. The trimellitic anhydride was used to synthesize water-soluble hyperbranched resin at the most appropriate temperature of 160–170°C. The properties of the resin were characterized by FTIR, hydroxyl value, molecular weight, stability, viscosity, and then the relationship among them under different synthesis conditions was further studied. Results indicated that the water-soluble hyperbranched resin had no delamination for more than 6 months at a solid content higher than 60%. Moreover, the resin was mutual soluble with water at any proportion and kept clear and transparent at same time. After water-soluble hyperbranched resin mixing with amino resin in a ratio of 2.5:1, and curing at 130–135°C for 2 hours, the chemical and mechanical properties of the coating were further measured and characterized.
Design and Analysis of a Novel 24 GHz Up-Conversion Mixer with Improved Derivative Super-Position Linearizer Technique for 5G Applications

A 24 GHz high linear, high-gain up-conversion mixer is realized for fifth-generation (5G) applications in the 65 nm CMOS process. The mixer’s linearity is increased by applying an Improved Derivative Super-Position (I-DS) technique cascaded between the mixer’s transconductance and switching stage. The high gain and stability of amplifiers in the transconductance stage of the mixer are achieved using novel tunable capacitive cross-coupled common source (TCC-CS) transistors. Using the I-DS, the third-order non-linear coefficient of current is closed to zero, enhancing the linearity. Additionally, a TCC-CS, which is realized by varactors, neutralizes the gate-to-drain parasitic capacitance (Cgd) of transistors in the transconductance stage of the mixer and contributes to the improvement of the gain and stability of the mixer. The measured 1 dB compression point OP1dB of the designed mixer is 4.1 dBm and IP1dB is 0.67 dBm at 24 GHz. The conversion gain of 4.1 dB at 24 GHz and 3.2 ± 0.9 dB, from 20 to 30 GHz is achieved in the designed mixer. Furthermore, a noise figure of 3.8 dB is noted at 24 GHz. The power consumption of the mixer is 4.9 mW at 1.2 V, while the chip area of the designed mixer is 0.4 mm2.
To Get Vaccinated, or Not to Get Vaccinated, That Is the Question: Illness Representations about COVID-19 and Perceptions about COVID-19 Vaccination as Predictors of COVID-19 Vaccination Willingness among Young Adults in The Netherlands

Mass vaccination is considered necessary to reduce the spread of COVID-19; however, vaccination willingness was found to be especially low among young adults. Therefore, based on the extended Common Sense Model, the unique effects and the interplay of illness representations about COVID-19 and perceptions about COVID-19 vaccination in explaining COVID-19 vaccination willingness was investigated using a cross-sectional design. An online survey measuring the relevant variables was filled in by 584 participants (69.9% female) between 18 and 34 years. Correlation analyses showed that all illness representation dimensions except from timeline and both dimensions of vaccination perceptions were related to vaccination willingness. The mediation analysis revealed that less personal control, more prevention control, more concerns about COVID-19 as well as more perceived necessity of and fewer concerns about the vaccination were directly related to higher vaccination willingness. Additionally, prevention control was indirectly related to higher vaccination willingness through stronger perceptions of necessity of the vaccination. The extended Common Sense Model proved to be useful in the context of illness prevention. Campaigns to improve vaccination rates should aim at increasing the perception that COVID-19 is preventable through vaccination and the personal need of the vaccination as well as at decreasing concerns about the vaccination.
Serum Vitamin D Is Associated with Antioxidant Potential in Peri-Parturient Cows

Dairy cows experience increased oxidative stress during periods of transition such as at the cessation of lactation and around the periparturient period, thus increasing disease risk. Despite routine supplementation of transition cow diets with certain vitamins in an attempt to mitigate oxidative stress, there is no currently available data directly linking vitamin supplementation with antioxidant potential (AOP) in transition cows. The objective of this study was to determine the association between serum vitamins and biomarkers of oxidative stress in healthy cows. Blood samples were collected from 240 cows at dry off (DO), close up (CU), and 2–10 days post-calving (DIM2-10). Blood samples were analyzed for vitamins (A, D, E), β-carotene, reactive oxygen species (ROS), and AOP. Spearman correlations and mixed linear regression models were used to assess associations between vitamins and measures of oxidant status. Vitamin D concentrations were positively associated with AOP at the CU and DIM2-10. Based on the positive association with AOP, additional in-vitro studies were conducted that showed vitamin D mitigated barrier integrity loss in endothelial cells during oxidative stress. These results indicate for the first time that vitamin D may have a role in promoting antioxidant potential in transition dairy cows.
Fabrication and evaluation of an optimized xenogenic decellularized costal cartilage graft: preclinical studies of a novel biocompatible prosthesis for rhinoplasty

Abstract On account of the poor biocompatibility of synthetic prosthesis, millions of rhinoplasty recipients have been forced to choose autologous costal cartilage as grafts, which suffer from limited availability, morbidity at the donor site and prolonged operation time. Here, as a promising alternative to autologous costal cartilage, we developed a novel xenogeneic costal cartilage and explored its feasibility as a rhinoplasty graft for the first time. Adopting an improved decellularization protocol, in which the ionic detergent was substituted by trypsin, the resulting decellularized graft was confirmed to preserve more structural components and better mechanics, and eliminate cellular components effectively. The in vitro and in vivo compatibility experiments demonstrated that the decellularized graft showed excellent biocompatibility and biosecurity. Additionally, the functionality assessment of rhinoplasty was performed in a rabbit model, and the condition of grafts after implantation was comprehensively evaluated. The optimized graft exhibited better capacity to reduce the degradation rate and maintain the morphology, in comparison to the decellularized costal cartilage prepared by conventional protocol. These findings indicate that this optimized graft derived from decellularized xenogeneic costal cartilage provides a new prospective for future investigations of rhinoplasty prosthesis and has great potential for clinical application.
Transfer Investigations of Lipophilic Drugs from Lipid Nanoemulsions to Lipophilic Acceptors: Contributing Effects of Cholesteryl Esters and Albumin as Acceptor Structures

When studying the release of poorly water-soluble drugs from colloidal drug delivery systems designed for intravenous administration, the release media should preferentially contain lipophilic components that represent the physiological acceptors present in vivo. In this study, the effect of different acceptor structures was investigated by comparing the transfer of fenofibrate, retinyl acetate, and orlistat from trimyristin nanoemulsion droplets into lipid-containing hydrogel particles, as well as to bovine serum albumin (BSA). A nanodispersion based on trimyristin and cholesteryl nonanoate was incorporated into the hydrogel particles (mean diameter ~40 µm) in order to mimic the composition of lipoproteins. The course of transfer observed utilizing the lipid-containing hydrogel particles as an acceptor was in relation to the lipophilicity of the drugs: the higher the logP value, the slower the transfer. There was no detectable amount of the drugs transferred to BSA in liquid solution, demonstrating clearly that albumin alone does not contribute substantially as acceptor for the lipophilic drugs under investigation in this study. In contrast, cholesteryl nonanoate contributes to a much greater extent. However, in all cases, the partition equilibrium of the drugs under investigation was in favor of the trimyristin emulsion droplets.
Advances in Gene Delivery Methods to Label and Modulate Activity of Upper Motor Neurons: Implications for Amyotrophic Lateral Sclerosis

The selective degeneration of both upper motor neurons (UMNs) and lower motor neurons (LMNs) is the pathological hallmark of amyotrophic lateral sclerosis (ALS). Unlike the simple organisation of LMNs in the brainstem and spinal cord, UMNs are embedded in the complex cytoarchitecture of the primary motor cortex, which complicates their identification. UMNs therefore remain a challenging neuronal population to study in ALS research, particularly in the early pre-symptomatic stages of animal models. A better understanding of the mechanisms that lead to selective UMN degeneration requires unequivocal visualization and cellular identification of vulnerable UMNs within the heterogeneous cortical neuronal population and circuitry. Here, we review recent novel gene delivery methods developed to cellularly identify vulnerable UMNs and modulate their activity in various mouse models. A critical overview of retrograde tracers, viral vectors encoding reporter genes and transgenic reporter mice used to visualize UMNs in mouse models of ALS is provided. Functional targeting of UMNs in vivo with the advent of optogenetic and chemogenetic technology is also discussed. These exciting gene delivery techniques will facilitate improved anatomical mapping, cell-specific gene expression profiling and targeted manipulation of UMN activity in mice. These advancements in the field pave the way for future work to uncover the precise role of UMNs in ALS and improve future therapeutic targeting of UMNs.
Using Nomogram to Predict the Hospitalization Forgone Among Internal Migrants in China: A Nationally Representative Cross-Sectional Secondary Data Analysis

Background Migrants are one of the most vulnerable populations facing many health issues. Inadequate health care access and unequal insurance are the most challenging. This study aimed to construct a nomogram to predict the risk of hospitalization forgone among internal migrants in China. Methods We analyzed the 2014 Mobile Population Social Integration and Mental Health Survey (MPSIMHS) launched by National Health and Family Planning Commission. Using the Probability Proportionate to Size Sampling method (PPS), MPSIMHS sampled from eight cities (districts) with a total sample size of 15,999. Of total 589 patients who were diagnosed with hospitalization requirement, 116 forwent their hospitalization, 473 had no forgone. Demographics, socioeconomic status, and health conditions were analyzed using univariate analysis and multivariate logistic regression. A nomogram was built and validated by applying bootstrap resampling. Results After model selection, gender, age group, marital status, migration range, insurance (having NRMI), and self-evaluated health were chosen into the nomogram to predict the risk of hospitalization forgone. The nomogram that predicted the risk of hospitalization forgone was validated for discrimination and calibration using bootstrap resampling. The calibration curves illustrated optimal agreement between the actual and predicted probabilities of the nomogram. The value of C-index from bootstrap was 0.80 (95% CI: 0.76–0.85). Conclusion This study identified some possible factors contributing to migrant’s hospitalization forgone: being single, male and middle-aged, having fixed health insurance, and having bad or great self-evaluated health. By integrating significant and easy-to-get prognostic factors, a nomogram was developed to estimate an individual patient’s risk of hospitalization forgone, which might have practical utility and the potential to assist clinicians in making hospitalization recommendations.
Isolation of Polysaccharides from Trichoderma harzianum with Antioxidant, Anticancer, and Enzyme Inhibition Properties

In this work, a total of six polysaccharides were isolated from culture filtrate (EPS1, EPS2) and mycelia (IPS1–IPS4) of Trichoderma harzianum. The HPLC analysis results showed that EPS1, EPS2, IPS1, and IPS2 were composed of mannose, ribose, glucose, galactose, and arabinose. The FT-IR, 1H, and 13C NMR chemical shifts confirmed that the signals in EPS1 mainly consist of (1→4)-linked α-d-glucopyranose. EPS1 and IPS1 showed a smooth and clean surface, while EPS2, IPS2, and IPS3 exhibited a microporous structure. Among polysaccharides, EPS1 displayed higher ABTS+ (47.09 ± 2.25% and DPPH (26.44 ± 0.12%) scavenging activities, as well as higher α-amylase (69.30 ± 1.28%) and α-glucosidase (68.22 ± 0.64%) inhibition activity than the other polysaccharides. EPS1 exhibited high cytotoxicity to MDA-MB293 cells, with an IC50 of 0.437 mg/mL, and this was also confirmed by cell staining and FACS assays. These results report the physicochemical and bioactive properties of polysaccharides from T. harzianum.
Protease, Growth Factor, and Heparanase-Mediated Syndecan-1 Shedding Leads to Enhanced HSV-1 Egress

Heparan sulfate (HS) and heparan sulfate proteoglycans (HSPGs) are considered important for the entry of many different viruses. Previously, we demonstrated that heparanase (HPSE), the host enzyme responsible for cleaving HS chains, is upregulated by herpes simplex virus-1 (HSV-1) infection. Higher levels of HPSE accelerate HS removal from the cell surface, facilitating viral release from infected cells. Here, we study the effects of overexpressing HPSE on viral entry, cell-to-cell fusion, plaque formation, and viral egress. We provide new information that higher levels of HPSE reduce syncytial plaque formation while promoting egress and extracellular release of the virions. We also found that transiently enhanced expression of HPSE did not affect HSV-1 entry into host cells or HSV-1-induced cell-to-cell fusion, suggesting that HPSE activation is tightly regulated and facilitates extracellular release of the maturing virions. We demonstrate that an HSPG-shedding agonist, PMA; a protease, thrombin; and a growth factor, EGF as well as bacterially produced recombinant heparinases resulted in enhanced HSV-1 release from HeLa and human corneal epithelial (HCE) cells. Our findings here underscore the significance of syndecan-1 functions in the HSV-1 lifecycle, provide evidence that the shedding of syndecan-1 ectodomain is another way HPSE works to facilitate HSV-1 release, and add new evidence on the significance of various HSPG shedding agonists in HSV-1 release from infected cells.