Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Detection of SPX Family and Profiling of CoSPX-MFS3 in Regulating Low-Phosphate Stress in Tea-Oil Camellia

Camellia oleifera a member of the family Theaceae, is a phosphorus (P) tolerator native to southern China. The SPX gene family critically regulates plant growth and development and maintains phosphate (Pi) homeostasis. However, the involvement of SPX genes in Pi signaling in Tea-Oil Camellia remains unknown. In this work, 20 SPX genes were identified and categorized into four subgroups. Conserved domains, motifs, gene structure, chromosomal location and gene duplication events were also investigated in the SPX gene family. Defense and stress responsiveness cis-elements were identified in the SPX gene promoters, which participated in low-Pi stress responses. Based on transcriptome data and qRT-PCR results, nine CoSPX genes had similar expression patterns and eight genes (except CoPHO1H3) were up-regulated at 30 days after exposure to low-Pi stress. CoSPX-MFS3 was selected as a key candidate gene by WGCNA analysis. CoSPX-MFS3 was a tonoplast protein. Overexpression of CoSPX-MFS3 in Arabidopsis promoted the accumulation of total P content and decreased the anthocyanin content. Overexpression of CoSPX-MFS3 could enhance low-Pi tolerance by increased biomass and organic acid contents in transgenic Arabidopsis lines. Furthermore, the expression patterns of seven phosphate starvation genes were higher in transgenic Arabidopsis than those in the wild type. These results highlight novel physiological roles of the SPX family genes in C. oleifera under low-Pi stress, and lays the foundation for a deeper knowledge of the response mechanism of C. oleifera to low-Pi stress.
Delay Margin in Controlling a Furuta Pendulum

This paper focuses on the design of an LQR based control scheme for the stabilization of the Furuta Pendulum in its unstable equilibrium point at the upright position. More precisely, we are interested in characterizing the corresponding delay margin under the assumption that the feedback loop includes time-delay. The paper provides an explicit tool to compute the critical delay value in the state feedback loop and a delicate tuning to reach larger delay values. In order to illustrate the effectiveness of the proposed control scheme, some numerical results are presented.
Analysis and research on road garbage recognition and detection based on mobile garbage collection robot

Mobile grasping robots have broad application prospects in fields such as logistics warehousing, smart homes, crop harvesting, and road garbage collection. They can significantly improve production efficiency, reduce labor costs, and make people's lives more convenient. However, due to complex backgrounds and lighting conditions, mobile grasping robots are prone to missing or misidentifying objects during grasping. This paper proposes a method based on the YoloV5 network, which uses Imgaug data augmentation to enhance and transform image data, as well as lightweight improvements to the YoloV5 network structure. Experimental results show that this method can effectively solve this problem.
Spin-statistics relation for quantum Hall states

We prove a generic spin-statistics relation for the fractional quasiparticles that appear in abelian quantum Hall states on the disk. The proof is based on an efficient way for computing the Berry phase acquired by a generic quasiparticle translated in the plane along a circular path, and on the crucial fact that once the gauge-invariant generator of rotations is projected onto a Landau level, it fractionalizes among the quasiparticles and the edge. Using these results we define a measurable quasiparticle fractional spin that satisfies the spin-statistics relation. As an application, we predict the value of the spin of the composite-fermion quasielectron proposed by Jain; our numerical simulations agree with that value. We also show that Laughlin's quasielectrons satisfy the spin-statistics relation, but carry the wrong spin to be the anti-anyons of Laughlin's quasiholes. We continue by highlighting the fact that the statistical angle between two quasiparticles can be obtained by measuring the angular momentum whilst merging the two quasiparticles. Finally, we show that our arguments carry over to the non-abelian case by discussing explicitly the Moore-Read wavefunction.
MINIMIZING DISSEMINATION ON LARGE GRAPHS

OF THE THESIS Minimizing Dissemination on Large Graphs by Long T. Le Thesis Director: Professor Tina Eliassi-Rad Given the topology of a graph G and a budget k, can we quickly find the best k edges to delete that minimize dissemination on G? Stopping dissemination on a graph is important in variety of fields such as epidemic control and network administration. Understanding the tipping point is crucial to the success of minimizing dissemination. The tipping point of an entity (e.g, virus or memo) on an arbitrary graph only depends on (i) the topology of graph and (ii) the characteristics of the entity. In this work, we assume that we cannot control the characteristics of the entity such as its strength, death rate, and propagation rate. Thus, we can only modify the topology of the graph. In particular, we consider the problem of removing k edges from the graph. In order to minimize the dissemination, we need to reduce the graph’s connectivity. The connectivity of a graph is determined by the largest eigenvalue of its adjacency matrix. Therefore, reducing the leading eigenvalue can minimize the dissemination. In social graphs, the small gap between the largest eigenvalue and the second largest eigenvalue creates a challenge for minimizing the leading eigenvalue. In this work, we propose a scalable algorithm called MET (short for Multiple Eigenvalues Tracking), which minimize the largest eigenvalue. MET can work well even if the gap between the top eigenvalues is small. We also propose a learning approach called LearnMelt, which is useful when the exact topology of graph is not available. We evaluate our algorithms on different types of graphs such as technological autonomous system networks and various social networks.
Le problème de Lehmer relatif en dimension supérieure

Nous generalisons en dimension superieure un theoreme d'Amoroso et Zannier concernant le probleme de Lehmer relatif. Nous minorons la hauteur d'un point d'un tore en fonction de son indice d'obstruction sur ℚ ab , l'extension abelienne maximale de ℚ, a condition qu'il ne soit pas contenu dans une sous-variete de torsion de petit degre. Nous en deduisons une minoration du minimum essentiel d'une sous-variete non contenue dans un sous-groupe algebrique propre en fonction de son indice d'obstruction sur ℚ ab . Nous montrons ainsi, a un epsilon pres, les conjectures les plus fines qui peuvent etre formulees dans ce cadre.
ESTIMATING TREE BOLE HEIGHT WITH BAYESIAN ANALYSIS.

Aim of study : The classical method for estimating a height-diameter model is based on the Least Squares Method (LSM) and the fit of a regression line. The Bayesian method has an exclusive advantage, compared with the classical method, in that the parameters to be estimated are considered as random variables. In this study, the Simple Linear Regression (SLR) model and the Bayesian model were used to estimate bole height from breast height diameter. Area of study : We used data of the forest stands of Rhodope (north-eastern Greece). Materials and methods : The variables that we used were the tree bole height and the diameter at breast height. Main results : The results showed that there is an improvement in prediction accuracy with the Bayesian model; however, this didn't lead to narrower confidence intervals of the predicted value, compared to SLR. Research essentials : Narrower confidence intervals are not necessarily achieved with Bayesian methods; confidence intervals' width is related to both statistical analyses and nature of data (in this case, species ecology and structure - composition of the stands where the sampled trees belong).
Probabilistic labelling for enhancement of vessel networks applied to retinal images

Occlusive vascular disease affecting arterial circulations is the major and fastest growing health problem worldwide, and underlies common conditions such as heart attack, stroke and peripheral vascular disease. Although vascular diseases may be assessed according to clinical history, screening may be required to evaluate health conditions or courses of treatment. Vasculature in the retina and other organs such as the brain have similar anatomical properties and regulatory mechanisms. Changes in the morphology of retinal vasculature may be associated with vascular-related conditions such as hypertension and stroke. Owing to its high cost-effectiveness, eye fundus photography is often used to study changes in the retinal vasculature. This research proposes a probabilistic pixel labelling method based on analysis of local and global features of the image to enhance the detail of vessel structures. Our approach produces a probability map that could be further used by contextual approaches (e.g. Markov Random Fields) for segmenting vessel networks as future application. We first correct contrast variation due to non-uniform illumination and reflections produced by eye tissue using statistical methods to locally estimate the contrast behind vasculature structures. Our labelling method is based on the Hessian matrix to locally estimate the maximum probability of the principal local curvature—given by eigenvalues—matching an ideal vessel curvature. We defined a realistic model based on imaging physics to produce the ideal vessel curvature governed by the Beer-Lambert Law for estimating the absorption of energy as it is propagated through uniformly filled objects. The local maximum posterior probability—based on Bayes’ rule—was eventually estimated by combining the prior (using the proposed background estimation) and the likelihood produced by Monte Carlo simulations. The proposed method in this research was compared with one of the most popular vessel detectors due to Frangi showing similar results.
Mid-Regional Pro-Adrenomedullin and N-Terminal Pro-B-Type Natriuretic Peptide Measurement: A Multimarker Approach to Diagnosis and Prognosis in Acute Heart Failure

Background: Acute heart failure (AHF) is a major cause of hospitalization and mortality worldwide. Early and accurate diagnosis, as well as effective risk stratification, are essential for optimizing clinical management and improving patient outcomes. In this context, biomarkers have gained increasing interest in recent years as they can provide important diagnostic and prognostic information in patients with AHF. Aim and Methods: The primary objective of the present study was to compare the levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP), mid-regional pro-adrenomedullin (MR-proADM), and C-reactive protein (CRP) between patients diagnosed with acute heart failure (AHF) and those without AHF and sepsis. Furthermore, the study aimed to assess the diagnostic and prognostic value of the use of a multimarker approach in AHF patients. To achieve these objectives, a total of 145 patients with AHF and 127 patients without AHF and sepsis, serving as the control group, were consecutively enrolled in the study. Results: Levels of MR-proADM (median: 2.07; (25th–75th percentiles: 1.40–3.02) vs. 1.11 (0.83–1.71) nmol/L, p < 0.0001), and NT-proBNP (5319 (1691–11,874) vs. 271 (89–931.5) pg/mL, p < 0.0001) were significantly higher in patients with AHF compared to controls, whereas CRP levels did not show significant differences. The mortality rate in the AHF group during in-hospital stay was 12%, and the rate of new re-admission for AHF within 30 days after discharge was 10%. During in-hospital follow-up, Cox regression analyses showed that levels of NT-proBNP > 10,132 pg/mL (hazard ratio (HR) 2.97; 95% confidence interval (CI): 1.13–7.82; p = 0.0284) and levels of MR-proADM > 2.8 nmol/L (HR: 8.57; CI: 2.42–30.28; p = 0.0009) predicted mortality. The combined use of MR-proADM and NT-proBNP provided significant additive predictive value for mortality and new re-admission for AHF at 30 days after discharge. A logistic regression analysis showed that the presence of NT-proBNP pg/mL > 12,973 pg mL and/or MR-proADM > 4.2 nmol/L predicted hospital re-admission within 30 days (OR: 3.23; CI: 1.05–9.91; p = 0.041). Conclusion: The combined assay of MR-proADM and NT-proBNP could be helpful in accurately identifying AHF and in defining prognosis and re-admission for AHF. The complementary use of these biomarkers can provide a useful clinical evaluation of AHF while also orienting clinicians to the pathophysiology underlying heart damage and assisting them in tailoring therapy.
Terahertz pulse imaging: A novel denoising method by combing the ant colony algorithm with the compressive sensing

Abstract Terahertz (THz) pulse imaging exhibits a potential application in biomedicine, nondestructive detection and safety inspection. However, the THz time-domain spectroscopy system will affect the THz image quality. To improve the THz image quality, in this article we proposed a novel method by combining the ant colony algorithm with the compressive sensing method. First, the image edge is detected by using the ant colony algorithm. Subsequently, the compressive sensing method based on signal sparse representation and the reconstruction algorithm from partial Fourier is applied on the non-edge image for noise reduction. Finally, the reconstruction result is obtained by combining the noise reduced non-edge image with the edge image. The experimental results on three kinds of images prove that the proposed method can preserve the edge information during noise reduction.
Blockchain System for Secure and Efficient UAV-to-Vehicle Communication in Smart Cities

—In a smart city environment, Intelligent Trans-portation System (ITS) enables the vehicle to generate and communicate messages for safety applications. There exists a challenge where the integrity of the message needs to be verified before passing it on to other vehicles. There should be a provision to motivate the honest vehicles who are reporting the true event messages. To achieve this, traffic regulations and event detections can be linked with blockchain technology. Any vehicle violating traffic rules will be issued with a penalty by executing the smart contract. In case any accident occurs, the vehicle nearby to the spot can immediately send the event message to Unmanned Aerial Vehicle (UAV). It will check for its credibility and proceed with rewards. The authenticity of the vehicle inside the smart city area is verified by registering itself with UAVs deployed near the city entrance. This is enabled to reduce the participation of unauthorized vehicles inside the city zone. The Secure Hash Algorithm (SHA256) and Elliptic Curve Digital Signature Algorithm (ECDSA-192) are used for communication. The result of computation time for certificate generation and vehicles involvement rate is presented.
Dual-mode optical sensing: three-dimensional imaging and seeing around a corner

Abstract. The application of nonline-of-sight (NLoS) vision and seeing around a corner has been demonstrated in the recent past on a laboratory level with round trip path lengths on the scale of 1 m as well as 10 m. This method uses a computational imaging approach to analyze the scattered information of objects which are hidden from the sensor’s direct field of view. A detailed knowledge about the scattering surfaces is necessary for the analysis. The authors evaluate the realization of dual-mode concepts with the aim of collecting all necessary information to enable both the direct three-dimensional imaging of a scene as well as the indirect sensing on hidden objects. Two different sensing approaches, laser gated viewing (LGV) and time-correlated single-photon counting, are investigated operating at laser wavelengths of 532 and 1545 nm, respectively. While LGV sensors have high spatial resolution, their application for NLoS sensing suffers from a low temporal resolution, i.e., a minimal gate width of 2 ns. On the other hand, Geiger-mode single-photon counting devices have high temporal resolution (250 ps), but the array size is limited to some thousand sensor elements. The authors present detailed theoretical and experimental evaluations of both sensing approaches.
Compactness in the ə̄-Neumann problem

The ¯ ∂ -Neumann operator on (0 , q )-forms (1 ≤ q ≤ n ) on a bounded convex domain Ω in C n is compact if and only if the boundary of Ω contains no complex analytic (equivalently: aﬃne) variety of dimension greater than or equal to q .
Raz-McKenzie simulation: new gadget and unimprovability of Thickness Lemma

Assume that we have an outer function $f:\{0, 1\}^n \to \{0, 1\}$ and a gadget function $g:A\times B \to\{0, 1\}$ and we want to lower bound deterministic communication complexity of a composed function $f\circ g^n$, denoted here by $D^{cc}(f\circ g^n)$, in terms of deterministic query complexity of $f$, denoted here by $D^{dt}(f)$. The study of such questions, now usually called \emph{Simulation Theorems}, was initiated in the work of Raz and McKenzie (\cite{raz1997separation}). Recently, Chattopadhyaay et al. (\cite{chattopadhyay2017simulation}) introduced a very convenient tool to study such questions, they called this tool \emph{hitting distributions}. Using this tool, they proved that $D^{cc}(f \circ g^n) = \Omega\left(D^{dt}(f) \cdot D^{cc}(g)\right)$, where $g$ is either Inner Product or Gap Hamming Distance gadget on $k$ bits, and $f$ is any function depending on at most $2^{ck}$ variables for some absolute constant $c$. In this work we use hitting distributions to show Simulation Theorem for a new gadget. Our gadget is the following one: Alice holds $a\in \mathbb{F}_{p^2}$, Bob holds $b\in \mathbb{F}_{p^2}$ and they want to know whether $a - b$ is a square in $\mathbb{F}_{p^2}$. We show that $D^{cc}(f \circ g^n) = \Omega\left(D^{dt}(f) \cdot D^{cc}(g)\right)$, where $g$ is our gadget and $f$ is any function depending on at most $p^c$ variables for some constant $c$ (note that this bound is exponential in the size of gadget, which is $O(\log p)$). We also investigate hitting distributions for disjointness predicate on $k$-element subsets of $\{1, 2, \ldots, n\}$. Finally, we study Thickness Lemma, a combinatorial statement from the proof of Simulation Theorems of G\"{o}\"{o}s et al and Chattopadhyaay et al., and show that this Lemma can not be improved.
An Underwater Image Restoration Method Based on Adaptive Brightness Improvement and Local Image Descattering

This letter proposes an effective underwater image restoration method that consists of a local image descattering and an adaptive brightness improvement. First, we establish an adaptive objective function for improving the brightness of underwater image according to the best-preserved channel of an image, and an augmented Lagrange multiplier-based alternating direction minimization algorithm is derived to solve the optimization problem. Second, we introduce a local transmission estimation method that takes into account the different attenuation of light on the red, green, and blue channels, which overcomes the limitation that existing methods heavily depend on global transmission over the entire image. Extensive experiments on real-world underwater images demonstrate the effectiveness of the proposed method in underwater image restoration. Moreover, our method shows good generalization capability for enhancing remote sensing and nighttime images.
Pyrolysis of Colombian spent coffee grounds (SCGs), characterization of bio-oil, and study of its antioxidant properties

ABSTRACT Coffee is the second most consumed beverage in the world. Spent coffee grounds (SCGs) are promising raw material for pyrolysis. The Kissinger-Akahira-Sunose model (KAS) and Ozawa-Flynn Wall (OFW), determined the pyrolysis activation energy to be 142.40 and 66.08 kJ/mol, respectively. The pyrolysis products were bio-oil with a 22.5% yield and a calorific power of 28.91 MJ/kg. The bio-oil composition was 50.86% fatty acids, 31.65% linear hydrocarbons, and 11.31% aromatics, as determined by GC-MS. The total phenolic content (TPC) was 362 ± 44 mg GA g−1, with DPPH activity of 24.8 ± 2% inhibition and antioxidant activity of 108.5 ± 13.6 mg L−1 of Trolox equivalents. The results showed that bio-oil could be used as a biofuel and a source of chemical compounds.
Decadal Changes in the Linkage Between Autumn Sea Ice and the Winter Eurasian Temperature in the 20th Century

The Warm Arctic‐Cold Eurasia pattern in recent decades has attracted extensive attention and has been partly attributed to rapid sea‐ice loss; however, such a link has been unstable over the past century. Here, we use centennial reanalyzes to investigate the multi‐decadal changes in the linkage between autumn Barents‐Kara sea‐ice and winter Eurasian temperature during the 20th century. Results show a negative Arctic‐Eurasian connection in 1901–1945 (P1), an inconspicuous connection in 1946–1985 (P2), and a significantly positive correlation in 1986–2013 (P3), with distinct stratospheric and tropospheric pathways mechanisms. The contrasting relationships between P1 and P3 are likely due to the different magnitudes of sea‐ice loss and the predominant roles of the atmosphere or sea‐ice in driving different Eurasian temperature effects. As further verification, the best group of Coupled Model Intercomparison Project simulations, which captured the realistic stratospheric pathway in recent decades, can reproduce the historical decadal changes in the Arctic‐Eurasian linkage.
Some Bayes estimators for Pareto Type-II progressive censored data

Two-parameter Pareto distribution is not only a potential model for lifetesting problems, also established its important role in variety of other prob-lems such as size of cities, rms and business mortality. In present article,two-parameter Pareto distribution is considered as the underlying model forthe study. Some Bayes estimators are obtained for shape parameter underknown as well as unknown case of scale parameter. A Progressive Type-IIcensored data is considered and performances of the procedures are studiedin terms of relative eciency, based on simulated and a real life data.
On the control of the linear Kuramoto−Sivashinsky equation

In this paper we study the null controllability property of the linear Kuramoto−Sivashinsky equation by means of either boundary or internal controls. In the Dirichlet boundary case, we use the moment theory to prove that the null controllability property holds with only one boundary control if and only if the anti-diffusion parameter of the equation does not belong to a critical set of parameters. Regarding the Neumann boundary case, we prove that the null controllability property does not hold with only one boundary control. However, it does always hold when either two boundary controls or an internal control are considered. The proof of the latter is based on the controllability-observability duality and a suitable Carleman estimate.
A multi-core fiber based interferometer for high temperature sensing

In this paper, we have verified and implemented a Mach–Zehnder interferometer based on seven-core fiber for high temperature sensing application. This proposed structure is based on a multi-mode-multi-core-multi-mode fiber structure sandwiched by a single mode fiber. Between the single-mode and multi-core fiber, a 3 mm long multi-mode fiber is formed for lead-in and lead-out light. The basic operation principle of this device is the use of multi-core modes, single-mode and multi-mode interference coupling is also utilized. Experimental results indicate that this interferometer sensor is capable of accurate measurements of temperatures up to 800 °C, and the temperature sensitivity of the proposed sensor is as high as 170.2 pm/°C, which is much higher than the current existing MZI based temperature sensors (109 pm/°C). This type of sensor is promising for practical high temperature applications due to its advantages including high sensitivity, simple fabrication process, low cost and compactness.