Miracle-dz/UniFAR-FTUs huggingface dataset:
A Nomogram for Identifying HR+/Her2− Breast Cancer Patients with Positive Sentinel Lymph Nodes and Omitted Axillary Lymph Node Dissection Who Need Abemaciclib Therapy

Background The efficacy of abemaciclib in high-risk patients with early-stage HR+/Her2− breast cancer has been verified by MonarchE. However, accurately determining the number of axillary lymph node (ALN) metastases remains challenging. The Z0011 trial changed the axillary management strategy, eliminating the need for axillary lymph node dissection (ALND) in patients with 1–2 sentinel lymph node (SLN) metastases. Therefore, further exploration is needed to identify patients who could benefit from abemaciclib therapy. Material/Methods This retrospective study included cT1-2N0M0 HR+/Her2− patients with 1–2 positive SLNs who underwent ALND. Clinicopathological data were collected, and logistic regression analyses identified independent predictors for ≥4 positive ALNs. A predictive nomogram was developed, and discrimination and calibration were evaluated using the C-index and calibration curve. Clinical efficacy was assessed using decision curve analysis (DCA). Results We enrolled 444 patients, with 77 (17.3%) having ≥4 positive ALNs. Independent predictors for ≥4 positive ALNs included abnormal ALN on ultrasound, mammographic calcifications, T stage, and the number of positive SLNs. The nomogram demonstrated an AUC of 0.777 (95% CI: 0.735–0.815, P<0.001), and internal validation showed good calibration and discrimination (C-index, 0.802; 95% CI: 0.779–0.824). DCA revealed a positive net benefit for risk levels ranging from 5% to 54%. Conclusions This nomogram is a convenient and reliable tool to predict the risk of ≥4 positive ALNs in HR+/Her2− patients. It aids in protocol selection by identifying SLN-positive patients who may benefit from abemaciclib therapy without ALND.
Factors Influencing Students’ Choice of Enrollmnt in Accounting Professional Program: Evidence From Malaysian Private Higher Institution

In choosing a career decision of an individual, a student’s choice of enrolment at the tertiary education level is one of the vital elements that influence students’ preference for program selection. This study explores the accounting students’ choice of e nrolment in the professional qualification ACCA course and the factors that influence their decisions to take the ACCA course at Kolej University Poly-Tech MARA,
Trapped modes in thin and infinite ladder like domains: existence and asymptotic analysis

We are interested in a 2D propagation medium which is a localized perturbation of a reference homogeneous periodic medium. This reference medium is a "thick graph", namely a thin structure (the thinness being characterized by a small parameter $\varepsilon$ > 0) whose limit (when $\varepsilon$ tends to 0) is a periodic graph. The perturbation consists in changing only the geometry of the reference medium by modifying the thickness of one of the lines of the reference medium. The question we investigate is whether such a geometrical perturbation is able to produce localized eigenmodes. We have investigated this question when the propagation model is the scalar Helmholtz equation with Neumann boundary conditions . This amounts to solving an eigenvalue problem for the Laplace operator in an unbounded domain. We use a standard approach of analysis that consists in (1) find a formal limit of the eigenvalue problem when the small parameter tends to 0, here the formal limit is an eigenvalue problem for a second order differential operator along a graph; (2) proceed to an explicit calculation of the spectrum of the limit operator; (3) deduce the existence of eigenvalues as soon as the thickness of the ladder is small enough and construct an asymptotic expansion of the eigenvalues with respect to the small parameter. Following this approach, we prove the existence of localized modes provided that the geometrical perturbation consists in diminishing the width of one rung. Using the matched asymptotic expansion method, we obtain an asymptotic expansion at any order of the eigenvalues, which can be used for instance to compute a numerical approximations of these eigenvalues and associated eigenvectors.
PERFORMANCE IN SOE TWO TIERS BOARD SYSTEM BASED ON THE IMPLICATION FROM GOOD CORPORATE GOVERNANCE AND TUNNELING OR PROPPING THROUGH RELATED PARTY TRANSACTIONS

This study is to provide empirical evidence about the performance of State-Owned Enterprises in Indonesia with a two-tier board system, on the effect of GCG and tunneling or propping through related transactions. This research uses data in the form of annual reports of State-Owned Enterprises. The results of this study showed that 69% were showing related transactions indicated tunneling and 31% showed related transactions indicated propping. Furthermore, the results obtained that the performance was simultaneously affected by GCG and tunneling. Partially GCG has a positive effect on performance, while tunneling or propping does not affect. The limitation of this research is that there are only 22 state-owned companies whose shares are partly owned by the public, during 2014-2019. The implication is that SOE need to continue to improve GCG to improve SOE’s performance, so that the possibility of tunneling which is a form of detrimental control can be minimized. This study shows that tunneling in state-owned companies is not in the form of taking cash or assets, but taking profits through control, coercion, and regulation. This study uses the performance measure based on the Malcolm Baldridge criteria.
Why the 2020 Belarusian Protests Failed to Oust Lukashenka

Abstract This article uses a comparison with Ukraine to investigate why protests against Lukashenka in 2020 failed to oust the Belarusian dictator. First, in contrast to his counterparts in Ukraine, Lukashenka successfully built new authoritarian economic and coercive institutions in the 1990s that raised the costs of opposition activity and reduced challengers’ access to business support. Second, Belarus has lacked a strong national identity that was critical to opposition success in Ukraine. In Ukraine, relatively powerful anti-Russian nationalism repeatedly motivated a core group of anti-incumbent activists and facilitated the opposition’s control over local power structures that supported protest activities at critical moments. In Belarus, weak national identity and consequent dearth of committed activists in national government institutions in the 1990s hampered efforts to challenge Lukashenka’s consolidation of authoritarian power. In addition, weaker national identity undermined the capacity of opposition forces to control local power structures that might have aided opposition protest.
EVALUATION OF SPOT-5 IMAGE FUSION USING MODIFIED PAN-SHARPENING METHODS

Image fusion, commonly known as pan-sharpening, is a method that combines two data: a panchromatic image that has geometric detail information with the highest spatial resolution and multi-spectral image that has the highest color information but with the lowest resolution. Pan-sharpening is very important for various remote sensing applications, such as to improve the image classification, to change the detection using temporal data, to increase the geometric, image segmentation, and to improve the visibility of certain object that does not appear on certain data. This study aims to compare the existing pan-sharpening methods such as Brovey, Brovey modification using green and red band, Gram-Schmidt, HPF, Multiplicative, and SFIM.The quality of the pan-sharpening result should be evaluated, this study used Universal Image Quality Index (UIQI/Q index); this evaluation methodgives the opportunity to choose which method is best to provide the most similar spectral information with the original multispectral image. A pan-sharpening qualitative analysis shows that there has been a sharpening process on all pan-sharpening images. Based on spectral visualization (color display), several pan-sharpening methods such as HPF multiplicative method provides brighter colorsand Brovey transformation method displays dark colors. Gram-Schmidt method also provides a different color from the original multispectral image. A pan-sharpening quantitative analysis shows that the best pan-sharpening method with UIQI value> 0.9 is Brovey modification using green and red band. This is due to the green band (500-590 nm) and the red band(610-680 nm) wavelength are in the panchromatic band (480-710 nm) of the SPOT-5 Data.
A frequency tuner for resonant inverters suitable for magnetic hyperthermia applications

In this study, a frequency tuner system is developed for generating variable frequency magnetic fields for magnetic hyperthermia applications. The tuning device contains three specially designed phase lock loop devices that drive a resonant inverter working in the frequency band of 180–525 kHz. This tuner system can be adapted for other resonant inverters employed in the studies of ferrofluids with superparamagnetic nanoparticles. The performance of the whole system is also examined. Our findings were in agreement with the theoretical expectations of phase locking and frequency tuning. The system is tested for samples of a solid magnetic material of cylindrical shape and ferrofluids with differing concentrations of powdered magnetite. The observations indicate significant frequency changes of the magnetic field due to heating of the samples. These frequency variations can be a source of errors, which should not be neglected in experiments determining the specific absorption rate or power dissipated density.
Gaussian mixed model in support of semiglobal matching leveraged by ground control points

Abstract. Semiglobal matching (SGM) has been widely applied in large aerial images because of its good tradeoff between complexity and robustness. The concept of ground control points (GCPs) is adopted to make SGM more robust. We model the effect of GCPs as two data terms for stereo matching between high-resolution aerial epipolar images in an iterative scheme. One term based on GCPs is formulated by Gaussian mixture model, which strengths the relation between GCPs and the pixels to be estimated and encodes some degree of consistency between them with respect to disparity values. Another term depends on pixel-wise confidence, and we further design a confidence updating equation based on three rules. With this confidence-based term, the assignment of disparity can be heuristically selected among disparity search ranges during the iteration process. Several iterations are sufficient to bring out satisfactory results according to our experiments. Experimental results validate that the proposed method outperforms surface reconstruction, which is a representative variant of SGM and behaves excellently on aerial images.
Refinements to Effect Sizes for Tests of Categorical Moderation and Differential Prediction

We provide a follow-up treatment of Nye and Sackett’s (2017) recently proposed dMod standardized effect-size measures for categorical-moderation analyses. We offer several refinements to Nye and Sackett’s effect-size equations that increase the precision of dMod estimates by accounting for asymmetries in predictor distributions, facilitate the interpretation of moderated effects by separately quantifying positive and negative differences in prediction, and permit the computation of nonparametric effect sizes. To aid in the implementation of our refinements to dMod, we provide software written in the R programming language that computes Nye and Sackett’s effect sizes with all of our refinements and that includes options for easily computing bootstrapped standard errors and bootstrapped confidence intervals.
Accounting information system implementation in batik small and medium-sized enterprises

One of the obstacles faced by batik small and medium-sized enterprises (SMEs), compared to large batik manufacturers, is limited financial and infrastructure resources. In the meantime, large batik manufacturers are supported by vast resources, modern infrastructure, skilled human resources, and a vast network on both the national and international levels. In order to obtain a competitive advantage, batik SMEs must be able to manage its resources effectively and efficiently and establish a hierarchy for resource allocation. On the other side, it is also necessary for the government to play a role, particularly in the form of policy and assistance, in order to ensure the survival of batik SMEs. This study seeks to maximize the potential of batik SMEs by implementing both manual and computerized accounting information systems (AIS) and the outcomes provide solutions to the problems posed by the lack of managerial professionalism in batik SMEs in Indonesia. Observation, in-depth interviews, and focus group discussions are used to collect data for the years 2020 and 2021. The data is then analyzed using an interaction method that emphasizes the connection between data reduction, data presentation, verification, and conclusion drawing. Therefore, this study produces both manual and computer-based accounting information systems for batik SMEs in Indonesia.
ON BONNESEN-STYLE ALEKSANDROV-FENCHEL INEQUALITIES IN ℝn

In this paper, we investigate the Bonnesen-style AleksandrovFenchel inequalities in Rn, which are the generalization of known Bonnesen-style inequalities. We first define the i-th symmetric mixed homothetic deficit ∆i(K,L) and its special case, the i-th Aleksandrov-Fenchel isoperimetric deficit ∆i(K). Secondly, we obtain some lower bounds of (n− 1)-th Aleksandrov Fenchel isoperimetric deficit ∆n−1(K). Theorem 4 strengthens Groemer’s result. As direct consequences, the stronger isoperimetric inequalities are established when n = 2 and n = 3. Finally, the reverse Bonnesen-style Aleksandrov-Fenchel inequalities are obtained. As a consequence, the new reverse Bonnesen-style inequality is obtained.
Non-Isolated Ultra-High Voltage-Gain-Coupled Inductor-Based DC–DC Converter

In this brief, an improved non-isolated coupled inductor-based high step-up DC-DC converter is proposed, with ultra-high voltage gain thanks to an active switched inductor. Utilizing a three-winding coupled inductor (CI) adds two more freedom degrees arising from its turns ratios that leads to a wide output voltage range. Several capacitive and inductive power transferring methods with no circulating current are used to recycle the stored energy in passive components. Two series-connected output ports and a passive clamp make the output and switch voltage stresses more tolerable, respectively. In addition, synchronized operation of switches leads to an easily implementable control system. Operation of the proposed converter in continuous conduction mode is analyzed thoroughly along with boundary and discontinuous conduction modes. Moreover, components design guideline is provided, and to evaluate the features, the converter is compared with some recent converters. Eventually, the experimental results of a 300 W laboratory prototype are given to validate the theoretical analysis.
Observational bounds on extended theories of gravity from energy conditions

The attempt to describe the recent accelerated expansion of the universe includes different propositions for dark energy models and modified gravity theories. Establish their features in order to discriminate and even rule out part of these models using observational data is a fundamental issue of cosmology. In the present work we consider a class of extended theories of gravity (ETGs) that are minimally coupled to the ordinary matter fields. In this context, and assuming a homogeneous and isotropic spacetime, we derive the energy conditions for this ETG class, which provide bounds for the ETG modifications. We then put constraints on these bounds using a model-independent approach to reconstruct the deceleration function along with the Joint Light-curve Analysis (JLA) supernova sample, 11 baryon acoustic oscillation and 22 cosmic-chronometer measurements. We also obtain an additional bound imposing the strong energy condition only on the ordinary matter. The main result of this work is a set of bounds that every considered ETG must fulfill given the aforementioned assumptions. We apply these bounds to verify the fulfillment/violation of the energy conditions in the context of general relativity. For instance, the strong energy condition is violated, corresponding to an accelerated expansion, with more than $5.22\sigma$ confidence interval considering the whole reconstruction interval. Finally, we show how these bounds can restrict the dynamics of the ETGs by imposing general assumptions on the ETG effective energy density. In this case, there is a preference for a phantom like behavior depending on how this quantity evolves.
Streamlining utilisation of the assembly line using computer simulation

The increase in computer computing power and the development of simulation software make it possible to realise very accurate predictions of the impact of decisions on systems. The cost of investments in streamlining logistics and manufacturing systems is usually high. Therefore, verifying whether the implemented improvement will have a real intended impact on the system is necessary. The use of simulation helps reduce the risk of uncertainty in such projects. The article describes the simulation performed in the software Tecnomatix Plant Simulation 15.2 and their use in its described methodology for simulation study with achieved results. The study was carried out to streamline manual assembly in a company engaged in the production of car seats, namely car rear seats and their manipulation processes. The simulation itself was supposed to answer the question of whether it is possible to produce faster customer line tact and whether it is possible to reduce the number of workers without influencing line performance. The very design of the content and number of simulation experiments was realised in two main aspects. These aspects are whether changing the organisation of the workplace will bring the desired effect and whether the installation of new equipment can improve performance even more. The resulting solution helped reduce the investment uncertainty and estimated that the best two solutions would increase the assembly line performance by 0.94% or 6.89%, respectively.
Multi-spectral uncooled infrared sensors fabricated using encapsulated metal-insulator-metal plasmonic metamaterial absorbers

Multispectral uncooled infrared (IR) sensors are attracting interest for use in applications such as gas analysis, hazardous material recognition, and biological analysis. However, conventional sensors require additional filters or a resonant structure in the vertical direction. To address this challenge, we investigated plasmonic metamaterial absorbers (PMAs) such as plasmonic crystals (PCs), metal–insulator–metal (MIM), and mushroom-type PMAs. Such PMAs exhibit wavelength-selective absorption by surface plasmon resonance (SPR, and the absorption wavelength can be controlled by modifying the features of the surface pattern (e.g., the periodicity of dimples and the micropatch size). Previously, we fabricated thermopiles with PC-type PMAs and used them for wavelength-selective detection. Although PC-type PMAs have advantages such as easy fabrication, robustness against structural fluctuations, and a wide operating wavelength range, they suffer from an incidence-angle dependence and require a large absorber volume. Here, we fabricated thermopiles with encapsulated MIM (EMIM)-type PMAs using a complementary metal oxide semiconductor process. The devices consist of a top encapsulated layer, periodic top micropatches, a flat insulator layer, and a bottom reflector. The encapsulated layer functions as a protective layer. Like MIM-type PMAs, the EMIM-type PMAs exhibit incidence-angle independence and a thin absorber volume, where the top micropatch induces localized SPR with the bottom reflector, and its size mainly determines the absorption wavelength. Spectral measurements showed that wavelength-selective IR detection can be performed in the mid-IR wavelength range without any additional filters. We expect the obtained results to contribute to the realization of advanced functional uncooled IR sensors and expand their range of applications.
The Influence of Employment Quality of China’s Floating Population on Consumption

With the increasingly prominent problems of over investment and weak domestic demand, the economic development urgently needs to shift to a consumption-driven model. The development of urbanization can promote the consumer demand of residents, thereby boosting domestic demand and reversing the traditional economic development model of relying on investment in the past. The increase in the urban rate is inseparable from the urban migration of the mobile population, and the deep meaning of the migration lies in the urbanization of the mobile populations lifestyle, consumption pattern and consumption structure. However, due to the obstacles of the household registration system, it is difficult to improve the employment quality of the mobile population under the existing employment system, and the stability and security of employment are not perfect, resulting in a low level of consumption. The mobile population has huge consumption potential. Research on how to improve the employment environment of the mobile population and increase its consumption level has important practical significance for promoting our domestic demand.
Robust LiDAR-Based Vehicle Detection for On-Road Autonomous Driving

The stable detection and tracking of high-speed vehicles on the road by using LiDAR can input accurate information for the decision-making module and improve the driving safety of smart cars. This paper proposed a novel LiDAR-based robust vehicle detection method including three parts: point cloud clustering, bounding box fitting and point cloud recognition. Firstly, aiming at the problem of clustering quality degradation caused by the uneven distribution of LiDAR point clouds and the difference in clustering radius between point cloud clusters in traditional DBSCAN (TDBSCAN) obstacle clustering algorithms, an improved DBSCAN algorithm based on distance-adaptive clustering radius (ADBSCAN) is designed, and a point cloud KD-Tree data structure is constructed to speed up the traversal of the algorithm; meanwhile, the OPTICS algorithm is introduced to enhance the performance of the proposed algorithm. Then, by adopting different fitting strategies for vehicle contour points in various states, the adaptability of the bounding box fitting algorithm is improved; Moreover, in view of the shortcomings of the poor robustness of the L-shape algorithm, the principal component analysis method (PCA) is introduced to obtain stable bounding box fitting results. Finally, considering the time-consuming and low-accuracy training of traditional machine learning algorithms, advanced PointNet in deep learning technique is built to send the point cloud within the bounding box of a high-confidence vehicle into PointNet to complete vehicle recognition. Experiments based on our autonomous driving perception platform and the KITTI dataset prove that the proposed method can stably complete vehicle target recognition and achieve a good balance between time-consuming and accuracy.