Miracle-dz/UniFAR-FTUs huggingface dataset:
Pseudosatellite Dynamic Positioning of UAV Pod Based on an Improved SR-UKF Algorithm

In view of the practical engineering problem of dynamic positioning of rotor UAV pod and the strong nonlinear problem in dynamic operation of UAV, a real-time estimation of the dynamic position of the rotor UAV pod is proposed by using the SR-UKF algorithm. This algorithm uses the nonlinear propagation of UT transform to generate the point set to maintain the mean and covariance information and thus achieves higher precision. Moreover, it uses the square root of covariance instead of covariance to participate in the recursive operation, thus improving the numerical stability of the filter and reducing the amount of computation. In this work, a pseudosatellite positioning platform was constructed in a field site in Nanjing. Based on evaluation of the space geometry of pseudosatellite base station, the accuracy of several nonlinear filtering algorithms was analyzed and evaluated using GPS RTK positioning results. It was found that the SR-UKF algorithm was the most accurate and efficient algorithm. It can meet the requirements of dynamic positioning of the rotor-wing UAV pod. The experiment results of this algorithm provide a more efficient positioning algorithm and implementation means for the actual engineering of UAV pod positioning using pseudosatellite system, which has high application value.
Nuclear PTEN Regulates Thymidylate Biosynthesis in Human Prostate Cancer Cell Lines

The phosphatase and tensin homologue deleted on chromosome 10 (PTEN) tumor suppressor governs a variety of biological processes, including metabolism, by acting on distinct molecular targets in different subcellular compartments. In the cytosol, inactive PTEN can be recruited to the plasma membrane where it dimerizes and functions as a lipid phosphatase to regulate metabolic processes mediated by the phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin complex 1 (mTORC1) pathway. However, the metabolic regulation of PTEN in the nucleus remains undefined. Here, using a gain-of-function approach to targeting PTEN to the plasma membrane and nucleus, we show that nuclear PTEN contributes to pyrimidine metabolism, in particular de novo thymidylate (dTMP) biosynthesis. PTEN appears to regulate dTMP biosynthesis through interaction with methylenetetrahydrofolate dehydrogenase 1 (MTHFD1), a key enzyme that generates 5,10-methylenetetrahydrofolate, a cofactor required for thymidylate synthase (TYMS) to catalyze deoxyuridylate (dUMP) into dTMP. Our findings reveal a nuclear function for PTEN in controlling dTMP biosynthesis and may also have implications for targeting nuclear-excluded PTEN prostate cancer cells with antifolate drugs.
Robust sparse regression by modeling noise as a mixture of gaussians

ABSTRACT Regression analysis has been proven to be a quite effective tool in a large variety of fields. In many regression models, it is often assumed that noise is with a specific distribution. Although the theoretical analysis can be greatly facilitated, the model-fitting performance may be poor since the supposed noise distribution may deviate from real noise to a large extent. Meanwhile, the model is also expected to be robust in consideration of the complexity of real-world data. Without any assumption about noise, we propose in this paper a novel sparse regression method called MoG-Lasso to directly model noise in linear regression models via a mixture of Gaussian distributions (MoG). Meanwhile, the penalty is included as a part of the loss function of MoG-Lasso to enhance its ability to identify a sparse model. As for the parameters in MoG-Lasso, we present an efficient algorithm to estimate them via the EM (expectation maximization) and ADMM (alternating direction method of multipliers) algorithms. With some simulated and real data contaminated by complex noise, the experiments show that the novel model MoG-Lasso performs better than several other popular methods in both ‘p>n’ and ‘p
Genomic analysis of a new heterotic maize group reveals key loci for pedigree breeding

Genome-wide analyses of maize populations have clarified the genetic basis of crop domestication and improvement. However, limited information is available on how breeding improvement reshaped the genome in the process of the formation of heterotic groups. In this study, we identified a new heterotic group (X group) based on an examination of 512 Chinese maize inbred lines. The X group was clearly distinct from the other non-H&L groups, implying that X × HIL is a new heterotic pattern. We selected the core inbred lines for an analysis of yield-related traits. Almost all yield-related traits were better in the X lines than those in the parental lines, indicating that the primary genetic improvement in the X group during breeding was yield-related traits. We generated whole-genome sequences of these lines with an average coverage of 17.35× to explore genome changes further. We analyzed the identity-by-descent (IBD) segments transferred from the two parents to the X lines and identified 29 and 28 IBD conserved regions (ICRs) from the parents PH4CV and PH6WC, respectively, accounting for 28.8% and 12.8% of the genome. We also identified 103, 89, and 131 selective sweeps (SSWs) using methods that involved the π, Tajima’s D, and CLR values, respectively. Notably, 96.13% of the ICRs co-localized with SSWs, indicating that SSW signals concentrated in ICRs. We identified 171 annotated genes associated with yield-related traits in maize both in ICRs and SSWs. To identify the genetic factors associated with yield improvement, we conducted QTL mapping for 240 lines from a DH population (PH4CV × PH6WC, which are the parents of X1132X) for ten key yield-related traits and identified a total of 55 QTLs. Furthermore, we detected three QTL clusters both in ICRs and SSWs. Based on the genetic evidence, we finally identified three key genes contributing to yield improvement in breeding the X group. These findings reveal key loci and genes targeted during pedigree breeding and provide new insights for future genomic breeding.
High-speed optical sensing of pose, position, and surface normal for dynamic projection mapping

In this paper, we propose a new optical system to simultaneously measure the pose, position, and surface normals of a target at high speed. In the computer vision field, it is a fundamental task to measure a motion of a target, and a high-speed motion measurement system has been researched for real-time applications. In most cases, a target is idealized as a rigid body, and the motion is described as six-DoF pose and position. However, general objects are not entirely rigid, and a non-rigid motion component is significant in some applications. We focus on dynamic projection mapping as an application example and propose an integration system of rigid and non-rigid motion sensing. In order to measure the non-rigid motion, non-rigid registration between 3D point clouds is often used, but it requires high computation cost, especially in three-dimensional nearest neighbor searches. Then, we optically measure surface normal vectors of a target from 2D images as a non-rigid motion component. To achieve a high-speed and non-interference measurement, we introduce a three-band infrared optical system and the lighting setup and evaluate the coupling efficiency by demonstrating the simultaneous measurement of a pose, position, and surface normal.
Impact of BRAFV600E Mutation on Event-Free Survival in Patients with Papillary Thyroid Carcinoma: A Retrospective Study in a Romanian Population

Simple Summary Although papillary thyroid carcinoma (PTC) is generally a highly curable disease, there is a small subgroup of PTC cases that behaves more aggressively, with high rates of disease recurrence, tumor progression and distant metastases. These patients need to be accurately identified for an appropriate, more-aggressive therapeutical approach. BRAFV600E mutation is the most prevalent genetic event in PTC. However, its role as a prognostic factor remains unclear. Herein, we aimed to assess the prognostic value of BRAFV600E mutation as a single factor, as well as in synergic interaction with other demographic and pathological risk factors in a series of 127 PTCs. Our results highlight a significant impact of BRAFV600E mutation on event-free survival among PTC patients. Nevertheless, BRAFV600E mutation status should not be used as an independent predictive factor in PTC patients, but rather should be integrated in the context of other clinicopathological risk factors. Abstract We aimed to evaluate the prognostic value of BRAFV600E mutation in a series of 127 papillary thyroid carcinoma (PTC) cases as a single factor, and in synergic interaction with other standard risk factors. BRAFV600E mutation was assessed by real-time PCR. Event-free survival (EFS) was calculated between the date of the first evaluation and the date of occurrence of an adverse event or the date of the last known status. The prevalence of BRAFV600E mutation was 57.2%. The Kaplan–Meier analysis showed a significant reduction of EFS among cases harboring BRAFV600E mutation compared to non-mutated cases (p = 0.010). In addition, BRAFV600E mutation was found to better predict adverse outcomes when associated with the following risk factors: age ≥ 55 years old (p < 0.001), male gender (p < 0.001), conventional (p = 0.005) and tall cell (p = 0.014) histology, tumor size > 40 mm (p = 0.001), extrathyroidal extension (p = 0.001), multifocality (p = 0.001) and lymph node metastasis (p < 0.001). In univariate analysis, a 3.74-fold increased risk for a reduced EFS (p = 0.018) was found for BRAFV600E-mutated cases, but no increased risk was further confirmed by multivariate analysis. Our results highlight that BRAFV600E mutation cannot be used alone as an independent predictive factor in PTC patients, but is prognostically valuable if integrated in the context of other clinicopathological risk factors.
The Role of Lifestyle and Dietary Factors in the Development of Premature Ovarian Insufficiency

Premature ovarian insufficiency (POI) is a condition that arises from dysfunction or early depletion of the ovarian follicle pool accompanied by an earlier-than-normal loss of fertility in young women. Oxidative stress has been suggested as an important factor in the decline of fertility in women and POI. In this review, we discuss the mechanisms of oxidative stress implicated in ovarian ageing and dysfunction in relation to POI, in particular mitochondrial dysfunction, apoptosis and inflammation. Genetic defects, autoimmunity and chemotherapy, are some of the reviewed hallmarks of POI that can lead to increased oxidative stress. Additionally, we highlight lifestyle factors, including diet, low energy availability and BMI, that can increase the risk of POI. The final section of this review discusses dietary factors associated with POI, including consumption of oily fish, mitochondria nutrient therapy, melatonin, dairy and vitamins that can be targeted as potential interventions, especially for at-risk women and in combination with personalised nutrition. Understanding the impact of lifestyle and its implications for POI and oxidative stress holds great promise in reducing the burden of this condition.
Design of Bluetooth 5.1 Angle of Arrival Homing Controller for Autonomous Mobile Robot

With the improvement of autonomous robot navigation technologies, mobile robots can now be deployed in uncertain, real-world environments. An aspect of autonomous robot navigation in such scenarios is the capability to navigate to a real-time determined (previously unknown) location anywhere in its vicinity. This is especially pertinent for indoor navigation where existing localization technologies such as GPS do not provide sufficient accuracy of target location. In this paper, a controller design is proposed which homes a mobile robot to an object of unknown location using Bluetooth 5.1 Angle of Arrival (AoA) technology. The proposed setup consists of a target object with a Bluetooth beacon and a single Bluetooth antenna array mounted on a mobile robot. The controller uses a hybrid approach to calculating and updating the estimated target position by implementing parallax and vector position calculations from AoA and RSSI Bluetooth data. Simulations with various levels of sensor noise showed convergence to accurate target positions (mean accuracy of 0.12 m or less) in both obstacle-free and obstacle-present environments. The controller can be implemented as a standalone controller by directly commanding robot motion toward the target, or it can integrate with other existing robot navigation techniques by outputting a target position.
Multigoal Reinforcement Learning via Exploring Entropy-Regularized Successor Matching

Multigoal reinforcement learning (RL) algorithms tend to achieve and generalize over diverse goals. However, unlike single-goal agents, multigoal agents struggle to break through the exploration bottleneck with a fair share of interactions, owing to rarely reusable goal-oriented experiences with sparse goal-reaching rewards. Therefore, well-arranged behavior goals during training are essential for multigoal agents, especially in long-horizon tasks. To this end, we propose efficient multigoal exploration on the basis of maximizing the entropy of successor features and Exploring entropy-regularized successor matching, namely, E<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>SM. E<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>SM adopts the idea of a successor feature and extends it to entropy-regularized goal-reaching successor mapping that serves as a more stable state feature under sparse rewards. The key contribution of our work is to perform intrinsic goal setting with behavior goals that are more likely to be achieved in terms of future state occupancies as well as promising in expanding the exploration frontier. Experiments on challenging long-horizon manipulation tasks show that E<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>SM deals well with sparse rewards and in pursuit of maximal state-covering, E<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>SM efficiently identifies valuable behavior goals toward specific goal-reaching by matching the successor mapping.
Assessing the extent of hybridization between westslope cutthroat trout and introduced rainbow trout in the Upper Kootenay River, British Columbia

Many westslope cutthroat trout (WCT) populations in the United States of America (USA) are threatened by hybridization with non-native trout. However, less is known about the genetic status of WCT populations in Canadian portion of their range. The Upper Kootenay River in British Columbia (BC) was considered a stronghold for WCT, but a preliminary study conducted from 1999 to 2001 found evidence of recent hybridization likely caused by stocking introduced rainbow trout (RBT, Oncorhynchus mykiss) in the Koocanusa Reservoir in the late 1980s. We assessed the distribution of native WCT, RBT, and their hybrids in the Upper Kootenay River using seven co-dominant, simple sequence repeat markers, and the program NEWHYBRIDS Version 1.1 beta. We determined the genotypes of 2,670 fish collected from 31 different streams between 1999 and 2006. Most fish were classified as pure WCT (85%), whereas pure RBT, RBT backcross and F1 individuals were rare (combined 2.8%). However, a broad hybrid zone stretching over 200 km was observed with WCT backcross individuals as the dominant hybrid type present (6%). Sites with no fish migration barriers between them and the Koocanusa Reservoir (open sites) had significantly more hybrid genotypes than sites isolated above migration barriers 36 (closed sites; X = 60.15, df = 5, p < 0.00001). Open sites < 90 km from the reservoir had more RBT, RBT backcross, and F1 types than sites further from the reservoir, and hybrids appear to be the main vector for the dispersal of RBT alleles to upstream sites. The hybrid zone appears to be limited by environmentally dependent factors (ecotone model). Management efforts should focus on identifying and limiting the sources of RBT in the watershed, identifying the remaining pure WCT populations, and learning more about the movement of WCT within the hybrid zone.
Monetary Policy and Financial Sector Reform for Employment Creation and Poverty Reduction in Ghana

This report summarizes the findings of a UNDP-sponsored study on the structure of the financial sector, central bank policy, and employment outcomes in Ghana. The financial sector is the primary conduit through which monetary policy affects real economic outcomes, and monetary policy determines the resources available to financial institutions. Therefore, monetary policy must be coordinated with financial sector reforms in order to improve employment opportunities, reduce poverty and support human development. The report develops a critique of financial programming and inflation targeting, presents a series of empirical estimates on the impact of monetary policy variables in Ghana, and describes the elements of an alternative monetary policy. In addition, the report documents the institutional and structural constraints currently operating in the financial system which prevent the sector from facilitating investment, growth, and improved employment opportunities. Econometric estimates of the determinants of investment explicitly link financial variables to real economic activity. The report summarizes a series of financial sector reforms that would improve the financial sector's capacity to move Ghana onto an employment-intensive growth path.
Security Baseline for Substation Automation Systems

The use of information technology and the automation of control systems in the energy sector enables a more efficient transmission and distribution of electricity. However, in addition to the many benefits that the deployment of intelligent and largely autonomous systems brings, it also carries risks associated with information and cyber security breaches. Technology systems form a specific and critical communication infrastructure, in which powerful control elements integrating IoT principles and IED devices are present. It also contains intelligent access control systems such as RTU, IDE, HMI, and SCADA systems that provide communication with the data and control center on the outer perimeter. Therefore, the key question is how to comprehensively protect these specialized systems and how to approach security implementation projects in this area. To establish rules, procedures, and techniques to ensure the cyber security of smart grid control systems in the energy sector, it is necessary to understand the security threats and bring appropriate measures to ensure the security of energy distribution. Given the use of a wide range of information and industrial technologies, it is difficult to protect energy distribution systems using standard constraints to protect common IT technologies and business processes. Therefore, as part of a comprehensive approach to cyber security, specifics such as legislative framework, technological constraints, international standards, specialized protocols or company processes, and many others need to be considered. Therefore, the key question is how to comprehensively protect these specialized systems and how to approach security implementation projects in this area. In this article, a basic security concept for control systems of power stations, which are part of the power transmission and distribution system, is presented based on the Smart Grid domain model with emphasis on substation intelligence, according to the Purdue model. The main contribution of the paper is the comprehensive design of mitigation measures divided into mandatory and recommended implementation based on the standards defined within the MITRE ATT&CK matrix specified, concerning the specifications of intelligent distribution substations. The proposed and industry-tested solution is mapped to meet the international security standards ISO 27001 and national legislation reflecting the requirements of NIS2. This ensures that the security requirements will be met when implementing the proposed Security Baseline.
Non-conforming Coupling of Finite and Boundary Element Methods in Time Domain

The combination of finite and boundary element methods for the numerical solution of coupled problems has a long tradition. It has proved to be the method of choice for several applications among which are the acoustic-structure coupling or the soil-structure interaction. In this work, the concept of combining these two approximation methods is carried forward to dynamic problems by developing a coupling framework in which the local discretization method can be chosen independently. In fact, a Lagrange multiplier domain decomposition approach is preferred which allows for the most flexible combination of discretization methods within the same solution algorithm. Therefore, Dirchlet-toNeumann maps are realized on the discrete level for the static case or at each time step for the dynamic case. Moreover, the treatment of nonconforming interface meshes, i.e., interface discretizations which do not have coincident nodes or equal interpolation orders, is included easily into this approach. Here, the considered physical models are the acoustic wave equation and the linear elastodynamic system together with their static limits, Laplace equation and elastostatics. The different discretization methods of finite and boundary element methods are presented for the solution of these static and dynamic problems. Their combination is then carried out by establishing a Lagrange multiplier coupling framework with possibly nonconforming interface discretizations. The numerical analysis of several static and dynamic test problems is performed by each of the considered discretization methods in a single domain approach and these tests are then repeated with the newly developed coupling strategy.
Conceptualising the nexus between macro‐level ‘turbulence’ and the worker experience

In this article, we introduce the special issue on conceptualising the nexus between macro‐level ‘turbulence’ and the worker experience. We discuss ‘turbulence’ as economic, political, social, technological, and environmental crises occurring in the macro‐environment and affecting the world of work. We argue that human resource management plays a critical role in supporting not only the organisation, but also workers, to navigate through macro‐level events. Based on the contributions included in this Special Issue, we suggest a novel framework that situates and expands the role of the Human Resources (HR) function in contemporary organisations by proposing a new role, the Proactive Carer. We argue that the debates around the role of HR and HR professionals have so far been too narrow and internally focused. It is time to expand this role to be externally facing, proactively monitoring the macro‐environment for significant events, anticipating any significant changes for workers, and designing interventions to minimise any negative impact. We conclude by highlighting avenues for future research.