Miracle-dz/UniFAR-FTUs huggingface dataset:
Generating Bus Traffic Patterns

— During the block level verification of the modules in an ASIC using SystemVerilog with the UVM methodology [1] we were required to generate specific traffic patterns for a bus protocol as requested by the architect (design engineers, system architect, etc .). Particularly the specification of the traffic pattern was problematic, as it was ambiguous and could be interpreted differently by the architect and the verification engineers. For improved reusability across various verification environments and platforms the traffic patterns could instead be accurately expressed by using a domain specific language (DSL) [2]. The DSL could then easily be converted into executable code for producing the expected traffic patterns
The Alignment Problem in Curriculum Learning

In curriculum learning, teaching involves cooperative selection of sequences of data via plans to facilitate eﬃcient and eﬀective learning. One-oﬀ cooperative selection of data has been mathematically formalized as entropy-regularized optimal transport and the limiting behavior of myopic sequential interactions has been analyzed, both yielding theoretical and practical guarantees. We recast sequential cooperation with curriculum planning in a reinforcement learning framework and analyze performance mathematically and by simulation. We prove that inﬁnite length plans are equivalent to not planning under certain assumptions on the method of planning, and isolate instances where monotonicity and hence convergence in the limit hold, as well as cases where it does not. We also demonstrate through simulations that argmax data selection is the same across planning horizons and demonstrate problem-dependent sensitivity of learning to the teacher’s planning horizon. Thus, we ﬁnd that planning ahead yields eﬃciency at the cost of eﬀectiveness. This failure of alignment is illustrated in particular with grid world examples in which the teacher must attempt to steer the learner away from a particular location in order to reach the desired grid square. We conclude with implications and directions for eﬃcient and eﬀective curricula.
OTT_A_254823 10667..10675

1Department of Anorectal Surgery, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China; 2Department of Anesthesiology, Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan 646000, People’s Republic of China; 3Department of Pharmacy, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong Key Laboratory of Individualized Drug Therapy, Nanchong, Sichuan, 637000, People’s Republic of China; 4Department of Gastrointestinal Surgery, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China; 5Scientific Research Department, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China Background: Many studies found that VPS53, one of the subunits of the golgi-associated
Toward a MILP Modeling Framework for Distribution System Restoration

Large-scale blackouts and extreme weather events in recent decades raise the concern for improving the resilience of electric power infrastructures. Distribution service restoration (DSR), a fundamental application in outage management systems, provides restoration solutions for system operators when power outages happen. As distribution generators (DGs) and remotely controllable devices are increasingly installed in distribution systems, an advanced DSR framework is needed to perform optimally coordinated restoration that can achieve maximal restoration performance. This paper introduces a DSR modeling framework, which can generate optimal switching sequences and estimated time of restoration in the presence of remotely controllable switches, manually operated switches, and dispatchable DGs. Two mathematical models, a variable time step model and a fixed time step model, are presented and compared. The proposed models are formulated as a mixed-integer linear programming model, and their effectiveness is evaluated via the IEEE 123 node test feeder.
The Effects of 24-Week, High-Concentration Hydrogen-Rich Water on Body Composition, Blood Lipid Pro ﬁ les and In ﬂ ammation Biomarkers in Men and Women with Metabolic Syndrome: A Randomized Controlled Trial Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy

Purpose: Metabolic syndrome is associated with several medical risk factors including dyslipidemia, hyperglycemia, and obesity, which has become a worldwide pandemic. The sequelae of this condition increase the risk of cardiovascular and neurological disease and increased mortality. Its pathophysiology is associated with redox dysregulation, excessive in ﬂ ammation, and perturbation of cellular homeostasis. Molecular hydrogen (H 2 ) may attenuate oxidative stress, improve cellular function, and reduce chronic in ﬂ ammation. Pre-clinical and clinical studies have shown promising effects of H 2 -rich water (HRW) on speci ﬁ c features of metabolic syndrome, yet the effects of long-term, high-concentration HRW in this prevalent condition remain poorly addressed. Methods: We conducted a randomized, double-blinded, placebo-controlled trial in 60 subjects (30 men and 30 women) with metabolic syndrome. An initial observation period of one week was used to acquire baseline clinical data followed by randomization to either placebo or high-concentration HRW (> 5.5 millimoles of H 2 per day) for 24 weeks. Results: Supplementation with high-concentration HRW signi ﬁ cantly reduced blood cholesterol and glucose levels, attenuated serum hemoglobin A1c, and improved biomarkers of in ﬂ ammation and redox homeostasis as compared to placebo ( P < 0.05). Furthermore, H 2 tended to promote a mild reduction in body mass index and waist-to-hip ratio. Conclusion: Our results give further credence that high-concentration HRW might have promising effects as a therapeutic modality for attenuating risk factors of metabolic syndrome.
M ULTICULTURAL F ESTIVAL P ERFORMANCE A S A S ITE O F L IBERATION F ROM P ERFORMANCE D ICHOTOMY : I NVESTIGATING A LLEGATIONS

A BSTRACT This paper explores the artistic and aesthetic means of disrupting existent performance ideologies in Zimbabwe. It looks into the ways in which festival performance is beneficial through its creation of a platform that cuts across various performance traditions in Zimbabwe. With special reference to the Harare International Festival of the Arts (HIFA) as a multicultural festival, this paper identifies how the production of Allegations (2009) allows different forms of performance traditions to thrive. It emanates from the realization that, performance in Zimbabwe has been occurring separately with racial binaries marring the performance industry. Through the use of Resistance and Performance theories, I highlight how HIFA through Allegations, discards reduplication of separation by allowing both indigenous and foreign performance traditions to exist in the same performance space.
Low Cost Ultra-Wideband Millimeter-Wave Phased Arrays

Many high performance wireless applications continue to be integrated onto increasingly small platforms, such as satellites, UAVs, and handheld devices. Lowprofile and ultra-wideband antenna arrays have emerged as a potential solution, by allowing many disparate functions to be consolidated into a shared, multi-functional aperture. Simultaneously, the demand for high data rate communications has driven these applications to higher frequencies, with many now exploring the use of the millimeter-wave spectrum. However, existing UWB arrays often utilize complex feed structures which cannot scale to these frequencies. The development of wideband millimeter-wave arrays compatible with low-cost commercial fabrication processes is critical to enabling these small and highly connected platforms. Tightly Coupled Arrays are one family of low-profile and wideband arrays which have demonstrated superior bandwidth and wide scanning capability. However, the feed design of these arrays is limited to operation below 5 GHz, and suffers from reduced efficiency when scanning. In this work, the feed is modified to improve efficiency by eliminating a Wilkinson power divider, and mitigating the resultant cavity resonances with the application of shorting pins. Likewise, strenuous fabrication requirements are relaxed, allowing fabrication at higher frequencies. This effort is approached initially through the intermediate frequencies in the X-, Kuand Ka-bands, and is demonstrated to allow the new design to scale up 49 GHz. An 8× 8 prototype
Foreground-aware Dense Depth Estimation for 360 Images

With 360 imaging devices becoming widely accessible, omnidirectional content has gained popularity in multiple ﬁelds. The ability to estimate depth from a single omnidirectional image can beneﬁt applications such as robotics navigation and virtual reality. However, existing depth estimation approaches produce sub-optimal results on real-world omnidirectional images with dynamic foreground objects. On the one hand, capture-based methods cannot obtain the foreground due to the limitations of the scanning and stitching schemes. On the other hand, it is challenging for synthesis-based methods to generate highly-realistic virtual foreground objects that are comparable to the real-world ones. In this paper, we propose to augment datasets with realistic foreground objects using an image-based approach, which produces a foreground-aware photorealistic dataset for machine learning algorithms. By exploiting a novel scale-invariant RGB-D correspondence in the spherical domain, we repurpose abundant non-omnidirectional datasets to include realistic foreground objects with correct distortions. We further propose a novel auxiliary deep neural network to estimate both the depth of the omnidirectional images and the mask of the foreground objects, where the two tasks facilitate each other. A new local depth loss considers small regions of interests and ensures that their depth estimations are not smoothed out during the global gradient’s optimization. We demonstrate the system using human as the foreground due to its complexity and contextual importance, while the framework can be generalized to any other foreground objects. Experimental results demonstrate more consistent global estimations and more accurate local estimations compared with state-of-the-arts.
Strategic Alignment: Towards a Holistic Perspective Embracing Complexity – Advancing the Research Agenda

: Strategic alignment has been extensively researched and reviewed. However, the field seems to have reached a stagnant stage in regard to the theoretical, methodological and philosophical foundations employed. In addition, existing research has been criticised due to its inability to capture the messy reality of organisations as well as it being undesirable for firms – as organisations must always change. This paper offers a review of the critique and address them in a constructive manner that reveals the underlying assumptions of which the criticisms are derived. In doing so, new perspective is offered that draws on concepts of complexity theory such as emergence and co-evolution. Special issues have proposed embracing complexity – but the publications to date do not reflect this. Therefore the aim is to offer a stepping stone for further research that builds on the foundation and insights provided by previous alignment research.
Rosmarinic acid monotherapy is better than the combination of rosmarinic acid and telmisartan in preventing podocyte detachment and inhibiting the progression of diabetic nephropathy in rats

Background: Podocyte injury and its subsequent detachment play a critical role in the development and progression of diabetic nephropathy (DN). The objective of this study was to investigate the effect of rosmarinic acid (RA) in preventing podocyte detachment and inhibiting the progression of DN in streptozotocin (STZ)-induced diabetic in rats. Methods: We used 20 adult male Wistar rats as experimental animals, which were randomly divided into 5 groups (n=4 per group): nondiabetic rat group (negative control) and 4 groups of STZ-induced diabetic rats, namely, 1 group untreated diabetic rats (positive control) and 3 groups treated diabetic rats with RA 75 mg/kg, telmisartan (TMS) 1 mg/kg and combination of RA 75 mg/kg with TMS 1 mg/kg), respectively. After 8 weeks of therapy, urinary levels of podocin, nephrin and albumin and also serum cystatin C levels were examined by ELISA. The expression of p65 nuclear factor-kB by immunohistochemistry whereas expression of podocin and nephrin glomerulus were examined by immuno ﬂ uorescence. Results: In the treated diabetic groups, we found that urinary level of podocin and nephrin, albumin urine excretion and serum cystatin C levels were signi ﬁ cantly lower than the positive control group. Compared to negative controls, the group of treated diabetic rats did not differ signi ﬁ cantly in preventing increased excretion of urinary nephrin and podocin. Meanwhile, treatment with RA monotherapy was signi ﬁ cantly better than TMS or a combination of RA with TMS in reducing albumin excretion and preventing decreased kidney function. Conclusion: In STZ-induced diabetic rats, RA can prevent podocyte detachment. Treatment with RA and TMS either monotherapy or in combination can inhibit the development and progression of DN. However, the combination of both did not show a synergistic effect, even have higher urinary albumin excretion and worse kidney function compared to the RA monotherapy.
Comparing Future Autonomous Electric Taxis With an Existing Free-Floating Carsharing System

When considering autonomous mobility on demand (AMoD) trends, it is probably safe to assume that they will have a large market share in the near future. In the introductory phases, users of current non-autonomous mobility on demand services such as ride-hailing and carsharing are expected to be among the first users of AMoD systems. The research presented in this paper aims to estimate fares for an AMoD system in this early stages based on rental and financial data provided by a free-floating CS provider. It demonstrates that an autonomous taxi (aTaxi) model requires less vehicles to serve the same demand resulting in the possibility to lower fares. In our model, user behavior is represented by defining three maximal waiting times and three monetary values reflecting their dissatisfaction in the case, where they cannot be served in due time. Two bipartite optimization problems for vehicle-to-user and relocation assignments build the core of the introduced aTaxi model. Fleet size and relocation parameters are chosen according to a utility function representing profit and opportunity costs of users not being served. We compute the reduction in fares to break-even with the current CS profit. Results of a case-study in Munich, Germany, indicate that one aTaxi can replace 2.8–3.7 CS vehicles. The aTaxi operator can therefore reduce fares by 29%–35% to achieve the same profit assuming the same cost structures as in free-floating CS.
Classiﬁcation Of Skin Lesions By Topological Data Analysis Alongside With Neural Network

In this paper we use TDA mapper alongside with deep convolutional neural networks in the classi-ﬁcation of 7 major skin diseases. First we apply kepler mapper with neural network as one of its ﬁlter steps to classify the dataset HAM10000. Mapper visualizes the classiﬁcation result by a simplicial complex, where neural network can not do this alone, but as a ﬁlter step neural network helps to classify data better. Furthermore we apply TDA mapper and persistent homology to understand the weights of layers of mobilenet network in diﬀerent training epochs of HAM10000. Also we use persistent diagrams to visualize the results of analysis of layers of mobilenet network.
Research on Effects of Paid Search Advertising Based on Customer loyalty Segmentation

: For e-commerce enterprises, it can help enterprises adjust their advertising strategies more effectively by determining the impact of paid search advertising on different customer groups. Therefore, this paper constructs a comprehensive evaluation model of immediate effect and carry-over effect of paid search advertising, and empirically discusses the impact of paid search advertising on different loyalty-based market segments. The results show that paid search advertising has the greatest impact on high-loyalty customers, while the carry-over effect on potential customers is longer. Thus, we can find that the role of paid search advertising is not only to attract new customers, but also to maintain high-loyalty customers.
A Neurocomputational Investigation of the Other-Race Effect

Perception of own and other-races have been the focus of extensive research to investigate both the mechanisms of face processing, as well as the advantage of recognizing faces of one own’s race relative to faces of a different race, termed the other-race effect (ORE). However, the underlying neural and computational nature of this phenomenon remains unclear. The current study examines the ORE using two different approaches: facial image reconstruction, and deep convolutional neural networks (DCNNs). Asian and Caucasian participants were recruited for this study. Significant features underlying the perception of face representation were first derived, and then used to reconstruct face images that were presented as visual stimuli. Reconstructions of perceived faces were all above chance level for all participants. In addition, DCNNs were utilized, as well as trained to further explain the ORE at a computational level. The present work shows potential in examining a classical effect in vision research with an unprecedented level of detail, as well as revealing the practicality of DCNNs in investigating race-oriented phenomena.
Efficiency analysis of a modular H-bridge based on SiC MOSFET

ABSTRACT Several new high-performance power semiconductors have appeared during the last decade, being the silicon carbide (SiC) MOSFETs the most promising to be commercialised as an alternative of Si IGBT. This paper presents the performance analysis of a controller for a full H-bridge based on SiC MOSFET technology used for high frequency and medium voltage applications. The switching performance of a modular H-bridge is analysed and the efficiency/losses and temperature dissipation are experimentally measured in order to help engineers to design and develop circuits using this power semiconductor. A comparison between SiC MOSFET and Si MOSFET is also presented.
Analysis of interaction effects between WECs in four types of wave farms

The development of wave energy converters (WECs) is often carried out based on detailed analysis of a single unit. However, successful prototypes that will become commercial will be installed in wave farms where additional effects due to interactions between the WECs will occur. Such interaction effects have been studied in several investigations, but mostly using frequency-domain analyses, or time-domain analyses with a simplified model of the WEC system. The current study presents results from time-domain coupled simulations, which are used to calculate, among others, the levelised cost of energy (LCoE) and fatigue lives of moorings of the WEC system. Four types of wave arrays were compared using the same point-absorbing WEC but with different mooring designs and array patterns. The fatigue damage of the moorings was found to increase for the arrays with strong hydrodynamic interactions from the wave field and mechanical couplings in the mooring design. The results show that the LCoE value for a WEC array farm is sensitive to the hydrodynamic interaction between WECs and the mechanical couplings in the mooring design.
Processing and indexing of electron backscatter patterns using open-source software

A new method to increase the signal-to-noise ratio S/N of electron backscatter patterns (EBSPs) based upon principal component analysis (PCA) is presented. The PCA denoising method is applied to ten scans of EBSPs from the same region of interest of a recrystallised nickel sample acquired with a decreasing S/N, achieved by reducing the exposure time while increasing the camera gain accordingly. That PCA denoising increases S/N in EBSPs is demonstrated by comparing indexing success rates after both Hough and dictionary indexing (HI and DI) of the Ni patterns having undergone one of four processing routes: i) standard static and dynamic background corrections (standard corrections), ii) standard corrections and pattern averaging with the four closest neighbours, iii) standard corrections and PCA denoising, and iv) standard corrections and pattern averaging followed by PCA denoising. Both pattern averaging and PCA denoising increases the indexing success rates for both indexing approaches for the studied Ni scans, with the former processing route providing the better success rates. The best success rates are obtained after pattern averaging followed by PCA denoising. The potential of PCA denoising to reveal additional pattern details compared to standard corrections and pattern averaging is demonstrated in a pattern from an orthoclase (KAlSi3O8) grain in a geological sample. Software code, and the Ni data sets, are released alongside this article as part of KikuchiPy, an open-source software package dedicated to processing and analysis of EBSPs.
Anomaly Detection Configured as a Combination of State Observer and Mahalanobis-Taguchi Method for a Rocket Engine

In this paper, anomaly detection that is configured as a combination of state observer and Mahalanobis-Taguchi (MT) method is proposed for real time fault detection of rapid and dynamic phenomena such as rocket engine operation. Real time anomaly detecting is recognized as one of the most important elements to realize advanced reusable space transportation system. Conventionally, bottom-up type anomaly detecting logic based on failure mode and effect analysis (FMEA) is usually used for this purpose, however, it requires large amount of time and labor. The proposed method can improve this process. In the present method, error values between calculated ones through rocket engine simulator constructed on autoregressive moving average model and extended Kalman filter (EKF) and measured ones are standardized with existing normal operation data of the rocket engine so as to compute Mahalanobis’ distance, which expresses degree of anomaly. We performed engine hot firing tests in simulated anomaly conditions. The obtained data was processed with the present method, and the simulated anomaly in the tests was detected as expected.