Miracle-dz/UniFAR-FTUs huggingface dataset:
EXTENT: Enabling Approximation-Oriented Energy Efficient STT-RAM Write Circuit

Spin Transfer Torque Random Access Memory (STT-RAM) has garnered interest due to its various characteristics such as non-volatility, low leakage power, high density. Its magnetic properties have a vital role in STT switching operations through thermal effectiveness. A key challenge for STT-RAM in industrial adaptation is the high write energy and latency. In this paper, we overcome this challenge by exploiting the stochastic switching activity of STT-RAM cells and, in tandem, with circuit-level approximation. We enforce the robustness of our technique by analyzing the vulnerability of write operation against radiation-induced soft errors and applying a low-cost improvement. Due to serious reliability challenges in nanometer-scale technology, the robustness of the proposed circuit is also analyzed in the presence of CMOS and magnetic tunnel junction (MTJ) process variation. Compared to the state-of-the-art, we achieved 33.04% and 5.47% lower STT-RAM write energy and latency, respectively, with a 3.7% area overhead, for memory-centric applications.
“Threatening” mechanism of disorder: evidence from attentional bias

ABSTRACT The absence of ordered information (“disordered” information) in the environment has various negative influences on individuals: “The world is random” model postulates that disordered information has negative influences through a process of “perceiving disorder leads to threatening feelings”. In experiment 1, attentional bias to disorderly pictures was measured by dotprobe tasks. The results revealed that individuals bias more attention to physical environmental disordered pictures and this process occurs at the strategic processing stage. In experiment 2, the attentional bias of participants to threatening pictures was measured under a disorderliness/orderliness state. The results showed that individuals bias attention to threatening stimuli in the disordered state and this also occurred at the strategic processing stage. In experiment 3, results from Implicit Association Tasks (IATs) showed that individuals implicitly associate disorder and threat concepts. These results empirically demonstrated that disordered information can induce threatening feelings and verified the “The world is random” model.
The Impact of Digital Finance on Green Total Factor Energy Efficiency: Evidence at China’s City Level

The rapid development of digital finance has delivered significant benefits, such as sustainable development and economic growth. We explore the relationship between digital finance and green total factor energy efficiency (GTFEE) for the first time, filling a gap in the existing literature. This paper uses dynamic panel models to explore digital finance’s impact on GTFEE at the Chinese city-level panel data from 2011 to 2018. The results show that digital finance can significantly improve urban GTFEE, and the findings remain robust with various tests. Second, the mechanism analysis indicates that digital finance can improve GTFEE by promoting urban green technology innovation and industrial structure upgrading. Further study shows that digital finance has a better effect on the improvement of GTFEE in central and western cities, small cities and non-resource-based cities, but has no significant or small impact on GTFEE in eastern cities, large cities and resource-based cities, reflecting the inclusiveness of digital finance.
Fast-Gated 16 × 16 SPAD Array With 16 on-Chip 6 ps Time-to-Digital Converters for Non-Line-of-Sight Imaging

We present the design and characterization of a fully-integrated array of $16 \times 16$ Single-Photon Avalanche Diodes (SPADs) with fast-gating capabilities and 16 on-chip 6 ps time-to-digital converters, which has been embedded in a compact imaging module. Such sensor has been developed for Non-Line-Of-Sight imaging applications, which require: i) a narrow instrument response function, for a centimeteraccurate single-shot precision; ii) fast-gated SPADs, for time-filtering of directly reflected photons; iii) high photon detection probability, for acquiring faint signals undergoing multiple scattering events. Thanks to a novel multiple differential SPAD-SPAD sensing approach, SPAD detectors can be swiftly activated in less than 500 ps and the full-width at half maximum of the instrument response function is always less than 75 ps (60 ps on average). Temporal responses are consistently uniform throughout the gate window, showing just few picoseconds of time dispersion when 30 ns gate pulses are applied, while the differential non-linearity is as low as 250 fs. With a photon detection probability peak of 70% at 490 nm, a fill-factor of 9.6% and up to $1.6 \cdot 10^{8}$ photon time-tagging measurements per second, such sensor fulfills the demand for fully-integrated imaging solutions optimized for non-line-of-sight imaging applications, enabling to cut exposure times while also optimizing size, weight, power and cost, thus paving the way for further scaled architectures.
Participation and learning in prek teacher workgroups: a communities of practice analysis of mathematics-focused professional development

ABSTRACT Professional collaboration is widely seen as an important component in educator professional development, but we know little about the interactional processes that undergird teacher learning in collaborative workgroups. This paper focuses on four collaborative workgroups in a yearlong, mathematics-focused professional development series for pre-Kindergarten teachers. Using a communities of practice framework, we analyzed teacher workgroup conversations to understand how these interactions mediated teachers’ learning. We identified three modes of participation that characterized workgroup conversations and influenced the availability and quality of learning opportunities afforded to participants: interpersonal management, validation, and collective reasoning. Findings provide insight into how interactional processes in teacher workgroups may advance or inhibit teachers’ learning.
Exploring psychological vulnerability and responses to the COVID-19 lockdown in Greece

This study explores the psychosocial impact of the COVID-19 pandemic on the population in Greece during the general lockdown period. Specifically, depression, anxiety and stress scores, as well as the factors associated with vulnerability to developing mental health conditions during this period, were investigated. A total of 911 adults participated in an online survey by completing a self-reporting questionnaire that included demographic questions, DASS-42 items (anxiety, stress and depression scales) and other questions related to personal experience. Regression modelling uncovered a significant relationship between gender and DASS scores, with women having significantly higher scores than men for all mental health problems. Participants aged 20–39 years were especially vulnerable to experiencing poor mental health. Unemployed participants reported having worse mental health than others. Having more perceived psychosocial support during the pandemic was associated with lower overall scores. Thus, women, young adults and the unemployed exhibited particularly high levels of vulnerability, while individuals who received social support from relatives and friends during the lockdown were more resilient to the effects of social isolation.
Quantifier elimination for approximate Beals-Kartashova factorization

The only known constructive factorization algorithm for linear partial differential operators (LPDOs) is Beals-Kartashova (BK) factorization \cite{bk2005}. One of the most interesting features of BK-factorization: at the beginning all the first-order factors are constructed and afterwards the factorization condition(s) should be checked. This leads to the important application area - namely, numerical simulations which could be simplified substantially if instead of computation with one LPDE of order $n$ we will be able to proceed computations with $n$ LPDEs all of order 1. In numerical simulations it is not necessary to fulfill factorization conditions exactly but with some given accuracy, which we call approximate factorization. The idea of the present paper is to look into the feasibility of solving problems of this kind using quantifier elinination by cylindrical algebraic decomposition.
Quantum Information Transfer between Topological and Superconducting Qubits

We describe a scheme that enables a strong Jaynes-Cummings coupling between a topological qubit and a superconducting flux qubit. The coupling strength is dependent on the phase difference between two superconductors on a topological insulator and may be expediently controlled by a phase controller. With this coherent coupling and single-qubit rotations arbitrary unitary operations on the two-qubit hybrid system of topological and flux qubits can be performed. Numerical simulations show that quantum state transfer and entanglement distributing between the topological and superconducting flux qubits may be performed with high fidelity.
Design of an Anisotropic Reconfigurable Reflective Polarization Converter for Realizing Circular Polarization-Reconfigurable Antenna

A polarization-reconfigurable antenna is presented here with the help of an anisotropic reconfigurable reflective polarization converter (RRPC). Proposed design consists of a monopole antenna as a source and an electronically switchable polarizer. Depending on the conducting states of only eight PIN diodes, which are placed on the top surface of the polarizer, linearly polarized (LP) wave generated by the monopole can be converted into left-hand circularly polarized (LHCP), right-hand circularly polarized (RHCP), and LP wave. Proposed RRPC has a ground plane on the back side and it is positioned below the source antenna with an air gap of 0.13 λ0 where λ is calculated at the antenna's operating frequency of 3.5 GHz. Overall configuration of the antenna is compact with a dimension of (0.31×0.31×0.19) λ03. As fewer active elements are used in the proposed design, complexity of the circuit for biasing and losses would be less. To the best of authors’ knowledge, it is first time reported work on active reflective polarizer, which not only has LP-to-CP polarization conversion ability but also it possesses electronic polarization switching ability in between LHCP, RHCP, and LP states.
Defining Common Inter-Session and Inter-Subject EEG Channels Using Spatial Selection Method

Redundancy of information on brain signals can lead to reduce brain-computer interface (BCI) performance in applications. To overcome this, EEG channel selection is performed to reduce and/or eliminate a number of channels with irrelevant information. In the previous studies, there is energy calculation methods that have been proposed to perform EEG channel selection to improve BCI performance in classifying the brain command of motor imagery stimulation. In this study, channel selection scheme on motor movement signal will be experimented by using spatial selection method. This study performs the common active channel mechanism that divided into two parts: 1) common active channels between sessions, which known as common Inter-session channels and common active channels. These two techniques can be used by all subjects to interpret motor movement type known as common Inter-subject channels. In order to validate the performance of the proposed framework, CSP (common spatial pattern) is used as a feature extraction method and k-NN with k = 3 as the classification method. The obtained results shows that the proposed channel selection technique is able to choose common active channels in five combination numbers on Inter-sessions and Inter-subjects of the acquired EEG signals. Both types of common active channels are proven to improve BCI performance with an accuracy increase of up to 66%.
Darboux Slant Ruled Surfaces

In this study, we introduce Darboux slant ruled surfaces in the Euclidean 3-space which is defined by the property that the Darboux vector of orthonormel frame of ruled surface makes a constant angle with a fixed, non-zero direction. We obtain the characterizations of Darboux slant ruled surfaces regarding the conical curvature kappa and give the relations between Darboux slant ruled surfaces and some other slant ruled surfaces.
Automatic coloration of pattern based on color parsing of Sung porcelain

In order to improve the coloration efficiency of fashion design, an automatic color matching mechanism based on adaptive color clustering of image scenes is proposed for clothing patterns. Taking images of Sung porcelain as an example, 300 porcelain images from six different kilns were collected as testing samples. The porcelain area of each sample image was detected by image segmentation and denoising. The bipartite K-means clustering algorithm was utilized to adaptively extract the main colors of each sample. Also, the secondary clustering was carried out to obtain the main color values, proportions and co-occurrence ratios of each kiln’s image. A dynamic color matching mechanism integrating the number of color clusters, co-occurrence ratio, and structure characteristics of the target pattern, was designed and automatic color parsing and matching software was developed. The experiment results show that the color matching control parameters, source images, pattern shape, and other factors affect the main color selection sequence and the final matching effect. The time consumed for single sample color extraction and pattern automatic color matching are all less than 1 s, which can quickly realize the pattern color migration based on image scenes and further provide auxiliary decision-making for clothing pattern color design.
Energy-Efficient Service Placement Based on Equivalent Bandwidth in Cell Zooming Enabled Mobile Edge Cloud Networks

Mobile edge computing is popular for providing services with low latency and high privacy. It becomes more powerful by leveraging the widely deployed Small cell Base Stations (SBS) with zooming cells for energy-efficient service placement. However, the literature ignores the joint optimization of SBS power control and service placement. The Quality of Services (QoS) guarantee is also challenging, taking into account the component dependency and parallelization in multi-component services and the resource slicing for separated service deployment. Moreover, prior works assume the same amount of allocated resources of links on a placed path for service edge allocation, leading to the ossification of resource allocation and inevitable resource fragments. Towards the above challenges, this paper addresses the energy-efficient and flexible service placement in cell zooming enabled Mobile Edge Cloud (MEC) networks. The delay of multi-component services is constructed depending on the allocated resource slice. Besides, the joint optimization of service placement and SBS power control is formulated and transformed into a Mixed Integer Linear Programming (MILP). More importantly, the equivalent bandwidth for an edge allocation is defined and analyzed to obtain flexible edge placement with minimum resource cost. Leveraging the results of MILP, an Energy-efficient Service placement algorithm based on equivalent Bandwidth in Cell zooming enabled MEC networks (ESBC) is proposed to improve the probability of successful service placement with QoS guarantee by optimizing the delay distribution among components and edges and reducing resource fragments. Finally, simulation results validate the effectiveness of the proposed methods.
Physical Traits and Reproductive Measurements Associated with Early Conception in Beef Replacement Heifers

Simple Summary Developing and raising replacement beef heifers requires a large capital investment for producers. Therefore, it is imperative to discover traits and management practices to eliminate subfertile heifers prior to breeding and pregnancy determination. In this study, four years of data was analyzed from a centralized heifer development yard in the Midwest of the United States. The objective of this study was to analyze various heifer physical characteristics and management practices in order to quantify their impact on pregnancy and date of conception. Physical measurements can be used to improve the ability to select and develop heifers for improved reproductive longevity. Veterinarians have an opportunity to work with their clients to utilize this information to select replacements that fit the ranch environment. This should result in increased reproductive efficiency and cost optimization for the replacement heifer enterprise. Abstract Developing and raising replacement heifers requires a large capital investment for producers. Therefore, it is imperative to discover traits and management practices to eliminate subfertile heifers prior to breeding and pregnancy determination. In this study, four years of data was analyzed from a centralized beef heifer development yard in the Midwest of the United States. The objective of this study was to analyze various heifer physical characteristics and management practices in order to quantify their impact on pregnancy and date of conception. Logistic regression models were built to investigate risk factors associated with conception to artificial insemination (AI), pregnancy by natural service after AI exposure, and pregnancy in the first 21-days of the breeding season. Age at entry, average daily gain from entry to breeding, pelvic width, and year were associated with AI pregnancy (p < 0.05). On the second model, average daily gain from entry to yearling weight, weight at breeding, weight at pregnancy diagnosis, and age at AI were significantly associated with pregnancy. There were no associations with reproductive tract score with any of the response variables analyzed. These results indicate there are physical measurements that can be used to improve the ability to select and develop heifers for improved reproductive performance.
Improving regression estimation: Averaging methods for variance reduction with extensions to general convex measure optimization

A general theoretical framework for Monte Carlo averaging methods of improving regression estimates is presented with application to neural network classification and time series prediction. Given a population of regression estimators, it is shown how to construct a hybrid estimator which is as good as or better than, in the MSE sense, any estimator in the population. It is argued that the ensemble method presented has several properties: It efficiently uses all the regressors of a population--none need be discarded. It efficiently uses all the available data for training without over-fitting. It inherently performs regularization by smoothing in functional space which helps to avoid over-fitting. It utilizes local minima to construct improved estimates whereas other regression algorithms are hindered by local minima. It is ideally suited for parallel computation. It leads to a very useful and natural measure of the number of distinct estimators in a population. The optimal parameters of the ensemble estimator are given in closed form. It is shown that this result derives from the notion of convexity and can be applied to a wide variety of optimization algorithms including: Mean Square Error, a general class of $L\sb{p}$-norm cost functions, Maximum Likelihood Estimation, Maximum Entropy, Maximum Mutual Information, the Kullback-Leibler Information (Cross Entropy), Penalized Maximum Likelihood Estimation and Smoothing Splines. The connection to Bayesian Inference is discussed. Experimental results on the NIST OCR database, the Turk and Pentland human face database and sunspot time series prediction are presented which demonstrate that the ensemble method dramatically improves regression performance on real-world classification tasks.
What is an Optimal Allocation in Hong Kong Stock, Real Estate, and Money Markets: An Individual Asset, Efficient Frontier Portfolios, or a Naïve Portfolio? Is This a New Financial Anomaly?

ABSTRACT To test for arbitrage opportunities and market efficiency in the Hong Kong money, stock, and real estate markets, we find that the money market stochastically dominates both the stock and real estate markets. Furthermore, the real estate market dominates the stock market, the money market dominates nearly all the efficient frontier portfolios, none of the efficient portfolios dominates the money market, and the money market also dominates the equal-weighting portfolio. This infers that in some cases investors could achieve higher expected ex-ante utility by investing in an individual asset rather than a portfolio. Our conclusions drawn from the pre-COVID-19 period are the same as those drawn from the entire period and the conclusions drawn from the COVID-19 period are the same as those drawn from the entire period except that the money market only stochastically dominates some of the efficient frontier portfolios. Our findings question diversification benefits in the Hong Kong capital market during our sample period, including both the pre-COVID-19 and COVID-19 periods.
Vascular loops in cerebellopontine angle in patients with unilateral idiopathic sudden sensorineural hearing loss: Evaluations by three radiological grading systems

We aimed to investigate the impact of the position, configuration and neurovascular contact of the anterior inferior cerebellar artery (AICA) in cerebellopontine angle (CPA) and internal auditory canal (IAC) on the clinical features of patients with unilateral idiopathic sudden sensorineural hearing loss (ISSNHL).
Novel Drug and Gene Delivery System and Imaging Agent Based on Marine Diatom Biosilica Nanoparticles

Mesoporous silica nanoparticles (MSNs) have great potential for applications as a drug delivery system (DDS) due to their unique properties such as large pore size, high surface area, biocompatibility, biodegradability, and stable aqueous dispersion. The MSN-mediated DDS can carry chemotherapeutic agents, optical sensors, photothermal agents, short interfering RNA (siRNA), and gene therapeutic agents. The MSN-assisted imaging techniques are applicable in cancer diagnosis. However, their synthesis via a chemical route requires toxic chemicals and is challenging, time-consuming, and energy-intensive, making the process expensive and non-viable. Fortunately, nature has provided a viable alternative material in the form of biosilica from marine resources. In this review, the applications of biosilica nanoparticles synthesized from marine diatoms in the field of drug delivery, biosensing, imaging agents, and regenerative medicine, are highlighted. Insights into the use of biosilica in the field of DDSs are elaborated, with a focus on different strategies to improve the physico-chemical properties with regards to drug loading and release efficiency, targeted delivery, and site-specific binding capacity by surface functionalization. The limitations, as well as the future scope to develop them as potential drug delivery vehicles and imaging agents, in the overall therapeutic management, are discussed.