Miracle-dz/UniFAR-FTUs huggingface dataset:
Cyber-Physical Attack Launched From EVSE Botnet

With the development of electric vehicles, millions of electric vehicle service equipment (EVSE) are integrated into the power grid. These EVSEs are weakly protected from cyber-attacks. By exploiting vulnerabilities, attackers could establish a botnet integrating hundred-MW-level EVSE loads from the Internet. Dynamic load-altering attack (DLAA) is powerful to amplify the load disturbance to destabilize the power grid. However, different from large-scale loads controlled by existing DLAA, the EVSE botnet is formulated by tens of thousands of bots widely distributed on various power grid nodes, rendering it challenging to be coordinated. In this article, we analyze the approach to launching a DLAA from the distributed EVSE botnet. Firstly, we adopt a time-division model to evaluate the impact of communication limitations on the attack vectors of the botnet. Then we develop an analytical model to calculate the coordinated effect of attack vectors from different nodes and with varying phase angles; thus, we provide a foundation for the optimal coordination of distributed bots. Subsequently, considering the power grid has adopted defense measures to eliminate or suppress the attack, we formulate an optimization algorithm to make the attack robust against these potential defense measures. Numerical simulations validate the effectiveness of the proposed approach.
Effects of Parental Disability on Children's Schooling: The Surprising Role of Parental Education

We show that negative effects of parental disability on schooling investments are larger for economically advantaged families. Among children with a veteran father, private school attendance declines with the severity of a father's service-related disability by more when fathers have completed college relative to when fathers have not. Paternal disability also lowers the mobility of young adults, suggesting that reduced educational investment persists into young adulthood. Lost earnings are one mechanism; disability decreases labor supply for all, but foregone earnings are larger for highly educated fathers. Losses are offset by Veterans Affairs transfers for less educated fathers but not for educated fathers.
Optimal selection of frequencies for Diffuse Optical Tomography

The use of diffuse photon density waves (DPDW) at multiple modulation frequencies is a significant tool for Diffuse Optical Tomography (DOT). Use of higher frequencies offers higher contrast between scattering and absorbing objects and allows higher resolution to be achieved. Here we focus on the optimal use of frequencies in simultaneously resolving absorbing and scattering objects using simulated data.
Anti-biases track-to-track association based on relaxation labeling

The problem of anti-biases track-to-track association is addressed. The theoretical analysis is given concerning how the topology structure of the point set formed by multi-target tracks is affected by sensor biases, and the topology difference between two point sets is represented by the non-rigid transformation. A point matching model for anti-biases track-to-track association is established, and a relaxation labeling based non-rigid point matching algorithm is proposed.Performance comparisons are implemented in terms of various typical simulation scenarios, such as different range biases,angle biases, target intensities and detection probabilities. Simulation experiments are conducted to verify the superiority of the proposed approach compared to other competing algorithms.
β-decay angular correlations with neutral atom traps

We review the use of laser cooling and trapping techniques for nuclear beta-decay angular correlations. Coincidences between the beta (β) and recoiling nucleus allow the determination of the neutrino (ν) momentum more directly than previously possible. Highly spin-polarized samples are also possible, with polarization known from atomic observables, and the nuclear recoils both in singles and in coincidence with the β add interesting observables. Ongoing experiments are trapping elements that provide pure Fermi, pure Gamow–Teller, and mixed Gamow–Teller transitions to distinguish sources of new physics. To compete with the next generation of neutron β-decay experiments, cases are being carefully chosen to minimize or at least know recoil-order corrections.
Proceeding of Non-rigid Motion Analysis

The visual analysis of non rigid motion is becoming a major area in computer vision. A classification of non rigid motion performed by objects on various degrees of non rigidity is elucidated in this paper according to the curvature changes of the objects, indicating that an 8 class scheme can cover all the objects from rigidity to high non rigidity. A large number of existing approaches in this area are surveyed and divided into two major categories: feature based methods and model based methods, and the advantages and disadvantages of the two classes are discussed respectively. The last section of this paper expatiates on the difficulties confronted by non rigid motion analysis and expects its possible future directions. Non rigid motion analysis is a burgeoning research area but still in its early development. The available body of research has begun to make inroads into only a few of the many difficult problems. Most of the extant models are far from perfect and people are far from a general solution to this problem. Some related research fields, such as speech recognition and computer graphics, may benefit this field.
Effect of Fusarium oxysporum infection on strawberry under calcium, iron, and zinc deficiency conditions

Fusarium wilt, caused by Fusarium oxysporum , is considered one of the essential diseases of strawberries. The importance of nutrient supply against Fusarium infection has been studied, while the severity of Fusarium wilt under nutrient deficiency remains unknown. The effect of F. oxysporum on strawberries under calcium (Ca), iron (Fe), and zinc (Zn) deficiency was studied. As plant material, the strawberry ( Fragaria × ananassa Duch) cultivar ‘Albion’ was used. After growth for two months in the nutrient solution, plants were exposed to Ca, Fe, or Zn deficiency conditions (except control). Next, the plants were exposed to mineral deficiency conditions for two months. Finally, a group of non-deficient (control) and mineral-deficient plants were subjected to Fusarium infection. Disease development and severity were monitored over three weeks. At the end of the experiment, the highest plant decline index was found under Ca deficiency followed by Fe and Zn ones. Fusarium infection caused a decrease in the chlorophyll concentration. Nutrient deficiency or Fusarium infection decreased cell expansion. Fusarium + Ca deficiency decreased xylem conduit diameter. Fusarium + Ca deficiency decreased theoretical stem hydraulic conductivity, while other treatments increased the value. According to the results, the Fusarium wilt severity was higher under Ca deficiency. The results of the experiment suggest that the strawberry growers must deal with Ca deficiency in Fusarium - infected plants.
Am I ready to graduate? Management majors’ perceived collegiate skill development

We examine 15 skills of graduating management majors as measured by self-rated perceptions of change during their college tenure. The sample includes 520,052 students from 697 higher education institutions in the United States. The research questions are: (1) As judged by management majors themselves, how much have their skills changed as a result of higher education? (2) How do these self-perceptions compare to other students? (3) What is the estimated impact of a management degree on these changes? Notable findings include that at least 90% of students reporting stronger, if not much stronger, skills in the categories of general knowledge, critical thinking, analytics, problem solving, and knowledge of their chosen field (management). However, other skills such as leadership are reported by 16% of management students as experiencing no change. The ratings of communication skills categories of public speaking and writing reported 17% of each category as no change or weaker skills is these areas. Study findings are discussed along with recommendations for future research.
A SLAM Algorithm Based on Central Difference Particle Filter

There are two serious drawbacks in FastSLAM (Simultaneous localization and mapping),which are the deriva-tion of the Jacobian matrices and the linear approximations of nonlinear functions.To overcome the serious drawbacks of the previous frameworks,this paper provides a robust SLAM algorithm based on the Sterling polynomial interpolation.It uses the central difference filter (CDF) to compute the proposal distribution in Rao-Blackwellized particle filter,then to initialize and update each feature state.For practical application,an effective mechanism for feature management is proposed.This approach improves the state estimation accuracy,and requires a smaller number of particles than previous approaches.Both simulation and experimental results are used to validate the effectiveness of the proposed algorithm.
Evaluation of the relationship between ABO and Rh blood groups system with diabetes mellitus type 2 among Patients in Al-Muthanna Governorate

Background: The ABO blood types are linked to a number of serious chronic medical conditions. An link between the ABO blood group and risk for type 2 diabetes has been discovered in earlier investigations. The purpose of the research is to determine if type 2 diabetes and the ABO blood types are related in any way. Methods: A case control study that was carried out over the course of two years and eight months in the medical ward of Al-Khidhir General Hospital and a private clinic in the province of Al-Muthanna. There were 400 adults that took part, split into two groups as follows: 200 people with type 2 diabetes who were already getting treatment made up the case group, whereas 200 healthy people made up the control group. Each participant gave a blood sample, which was used for a blood group, Rh, and random blood sugar test. Results: Blood group O was shown to be the most likely to be protective against the development of type 2 DM (OR= 0.71) whereas blood group B was revealed to be a significant independent risk factor for increased chance of developing type 2 DM (OR= 2.07). As this research indicated, blood group B is associated with a high prevalence of type 2 diabetes, while blood group O has the least relationship, blood group is thought to be a risk factor and may help in disease assessment. Since people with blood group B are more prone to develop type 2 diabetes, clinicians should exercise more caution and close supervision of these patients.
Computational complexity of robust stability and regularity in families of linear systems

In an engineering system modeled by linear ordinary differential equations, the location of eigenvalues is a useful indicator of time domain response for analysis and design. For many engineering applications, a typical stability specification might require that all eigenvalues have negative real part, or are confined to some specified region of the complex plane. When the system model depends on unknown constants, one would like to test whether the desired eigenvalue locations are maintained for all possible values of the constant parameters. This type of computation is refered to as a "robust stability" test. This dissertation delineates forms of parameter dependence in the system matrix that allow tractable tests of robust stability, versus those forms of parameter dependence that lead to intractable computations in the worst case. Similar conclusions for the corresponding tests of matrix regularity, or robust nonsingularity, are provided as well. In order to achieve algorithm-independent determinations of computational complexity, use is made of NP-completeness theory and the theory of approximation complexity for NP-hard optimization problems. The key finding is that testing robust stability or regularity of matrix families with characteristic polynomials having coefficients that are bilinear functions of parameters is NP-hard. This implies that unless P = NP, which is widely believed to be false, worst-case computation time for any such test will be exponential in input size. For the same class of matrix families, it is proven that computing the rightmost eigenvalue is MAX-SNP-hard, which means that unless P = NP there can be no polynomial-time approximation scheme which achieves worst-case approximation ratio arbitrarily close to 1. Combining these determinations with results in the literature, the class of matrix families with characteristic polynomials having coefficients dependent in an affine fashion on parameters is established as the most general for which practical robust stability or regularity tests are possible.
An anchor-free 3D object detection method with camera and liDAR based on H23D R-CNN

As an important part of automatic driving technology, the performance of perception determines the safety and availability of automatic driving. Generally, we need specific three-dimensional target information, which is difficult to gain from the camera. As a result, LiDAR plays a significant role in 3D detection due to its advantages of high resolution, immunity and capability to obtain specific location information. In order to overcome the problem that LiDAR often fails to detect objects with similar structures, we propose a method with Camera and LiDAR model based on H23D RCNN, which can be divided into three sections. Firstly, a Foreground View (FV) map and a Bird Eye’s View (BEV) map are transformed from original point cloud, and the FV features, and image feature will augment the expression ability of features from the BEV maps and point cloud. Then, we introduce a center-based detection head on the BEV maps to generate the heatmaps and box refinement to minimize the redundancy and accelerate the operation of the model. Finally, we present the result of the second stage on the point features to acquire more accurate 3D bounding boxes. To validate our model, we test it on the official KITTI dataset and get a better performance compared to the original method and also get a nearly 5ms speed up.
Proposal of m-Index for Rating Fracture and Damage Models by Their Ability to Represent a Set of Distinctive Experiments

: A recent comparative study revealed that the commonly offered experimental validations of peridynamics and phase-field fracture models have been insufficient because they involved only nondistinctive experiments, i.e., experiments that can be closely fitted by different models that at the same time give very different predictions in important practical applications. The comparisons showed that the peridynamic and phase-field models are incapable of simulating a set of 11 distinctive experiments — experiments that are critical for assessing the accuracy of different models and are representative of fracture behavior of engineering structures. Practical applications would be helped by common adoption of a model index that would compare the predictive capability of various fracture models quantitatively. Proposed here for further discussion is an example of a possible numerical index, the m-Index, which attempts to characterize how well the optimal calibration of model parameters can match the experimental evidence, such as the fracture patterns, measured response curves, size effect, and crack-parallel stress effect. Included are only the distinctive experiments. As an example, the m-Index is here calculated for a set of seven fracture models whose performance was previously compared with 11 distinctive experiments. This previous comparison of seven models is here extended to an eighth model, proposed as a fresh improvement of peridynamics. The choice of distinctive experiments is one of the subjects calling for further discussion. Despite inevitable imperfections, a widely adopted index for appraising new material models would mitigate waste of researchers ’ effort and grant funds, as well as the space in scientific journals and conference programs. DOI: 10.1061/JENMDT.EMENG-6887. © 2023 American Society of Civil Engineers.
An Improved Edge-Detection Method Based On Canny Algorithm

Being an optimal edgedetection algorithm,Canny algorithm has some good characteristics,such as border closure and so onThis paper not only introduces the Canny algorithm but also makes some improvement to the canny algorithm and brings forward an improved edgedetection algorithm based on dynamic thresholdThe improved algorithm makes up for the disadvantage of canny algorithm,which would lose some edges during detecting nonstandard images with blurred edgesThe algorithm is a practical edgedetection algorithm
Mask wearing detection algorithm based on improved YOLOv5

The new coronavirus can be transmitted through respiratory droplets and other means. By properly wearing a mask, the transmission of the virus can effectively be prevented. A mask wearing detection method based on improved YOLOv5 is proposed to address the problem of low accuracy of mask detection due to complex factors current mask detection algorithms, such as occlusion, dense crowds and small-scale targets. By combining with a bi-directional feature pyramid network to improve the neck backbone networks, the fusion of high-resolution and low-resolution features is enhanced to improve the accuracy of small-scale target detection. Landmarks, a key point feature for faces, is also introduced into the detection layer of YOLOv5, which improves the detection accuracy of occlusion and dense crowds. The experimental results show that the algorithm can meet the requirements of accuracy and real timeliness of the mask wearing detection under conditions with limited resources.
Hematopoietic Progenitor Cell Counts of the Leukapheresis Product Determined Using Sysmex XN Analyzers Predict a Sufficient Number of CD34+ Stem Cells in a Peripheral Blood Stem Cell Harvest for Autologous Transplantation

Objective Several institutions outsource CD34+ cell counting of leukapheresis products, limiting rapid measurements, as results are obtained the next day. This problem is compounded with plerixafor use, a stem cell-mobilizing drug that increases leukapheresis efficiency but requires administration the day before leukapheresis. Use of this drug for a second leukapheresis procedure before the first-day leukapheresis CD34+ count results are confirmed causes unnecessary leukapheresis and expensive plerixafor administration. We investigated whether or not measuring hematopoietic progenitor cells in leukapheresis products (AP-HPCs) using a Sysmex XN-series analyzer could resolve this problem. Methods We retrospectively compared the absolute AP-HPC value per body weight with the CD34+ (AP-CD34+) count in 96 first-day leukapheresis product samples obtained between September 2013 and January 2021. Comparisons were also conducted according to regimen: granulocyte colony-stimulating factor (G-CSF) monotherapy, chemotherapy plus G-CSF, or plerixafor mobilization. Results AP-CD34+ and AP-HPC counts correlated strongly (rs=0.846) overall and, in particular, under chemotherapy plus G-CSF (rs=0.92) but correlated mildly under G-CSF monotherapy (rs=0.655). AP-HPCs could not completely be dichotomized based on an AP-CD34+ threshold of 2×106/kg for any stimulation procedure. In most cases with AP-HPCs ＞6×106/kg, the AP-CD34+ count exceeded 2.0×106/kg, but in 5.7% of these cases, the AP-CD34+ count was ＜2.0×106/kg. A cut-off of AP-HPCs ＞4.843×106/kg yielded a sensitivity of 71% and specificity of 96% for predicting AP-CD34+ ≥2×106/kg. Conclusion AP-HPCs can identify cases in which sufficient stem cells have been collected.
Force model identification for magnetic suspension systems via magnetic field measurement

In magnetic suspension analysis, a simplified model of the current-to-distance relationship is not sufficient to design an optimal control. Due to the nonlinearity of the magnetic field, an accurate model, which is a function of the suspended object, suspension distance, core material, and operation conditions, is difficult to obtain. An improved force-model-identification method for magnetic suspension systems establishes reliable parameters for describing the magnetic field characteristics. The parameter for each test sample can be calculated under the specified operating conditions after some magnetic field measurements. The results lead to effective controller design for magnetic suspension systems. >
Targeting Transcriptional CDKs 7, 8, and 9 with Anilinopyrimidine Derivatives as Anticancer Agents: Design, Synthesis, Biological Evaluation and In Silico Studies

Cyclin-dependent kinases (CDKs) are promising targets in chemotherapy. In this study, we report a series of 2-anilinopyrimidine derivatives with CDK inhibitory activity. Twenty-one compounds were synthesized and their CDK inhibitory and cytotoxic activities were evaluated. The representative compounds demonstrate potent antiproliferative activities toward different solid cancer cell lines and provide a promising strategy for the treatment of malignant tumors. Compound 5f was the most potent CDK7 inhibitor (IC50 = 0.479 µM), compound 5d was the most potent CDK8 inhibitor (IC50 = 0.716 µM), and compound 5b was the most potent CDK9 inhibitor (IC50 = 0.059 µM). All the compounds satisfied the Lipinski’s rule of five (molecular weight < 500 Da, number of hydrogen bond acceptors <10, and octanol–water partition coefficient and hydrogen bond donor values below 5). Compound 5j is a good candidate for lead optimization because it has a non-hydrogen atom (N) of 23, an acceptable ligand efficiency value of 0.38673, and an acceptable ligand lipophilic efficiency value of 5.5526. The synthesized anilinopyrimidine derivatives have potential as anticancer agents.
Research on image blind super-resolution algorithm based on generative adversarial networks

In the blind super-resolution reconstruction task, it is easy to fall into a single degradation. In order to solve this problem, we add the dropout mechanism before the last convolutional layer of the network, which can effectively prevent co-adapting, so that the network can be well restored to various degradations. To enhance the network's ability to extract high-frequency details, a HAM attention mechanism is introduced behind the residual block, which can reconstruct clearer textures. Aiming at the problem of ubiquitous artifacts in images generated in fine-grained and structured areas in the generative confrontation network, the LDL loss is introduced to make the area better restored. Experimental results show that the method proposed in this paper can achieve high performance and is closer to natural images in subjective vision.
Towards a robust Terra

In this work mantle convection simulation with Terra is investigated from a numerical point of view, theoretical analysis as well as practical tests are performed. The stability criteria for the numerical formulation of the physical model will be made clear. For the incompressible case and the Terra specific treatment of the anelastic approximation, two inf-sup stable grid modifications are presented, which are both compatible with hanging nodes. For the Q1hQ12h element pair a simple numeric test is introduced to prove the stability for any given grid. For the Q1h Pdisc 12h element pair and 1-regular refinements with hangig nodes an existing general proof can be adopted. The influence of the slip boundary condition is found to be destabilizing. For the incompressible case a cure can be adopted from the literature. The necessary conditions for the expansion of the stability results to the anelastic approximation will be pointed out. A numerical framework is developed in order to measure the effect of different numerical approaches to improve the handling of strongly varying viscosity. The framework is applied to investigate how block smoothers with different block sizes, combination of different block smoothers, different prolongation schemes and semi coarsening influence the multigrid performance. A regression-test framework for Terra will be briefly introduced.