Miracle-dz/UniFAR-FTUs huggingface dataset:
Confidence Intervals for Sparse Penalized Regression With Random Designs

Abstract With the abundance of large data, sparse penalized regression techniques are commonly used in data analysis due to the advantage of simultaneous variable selection and estimation. A number of convex as well as nonconvex penalties have been proposed in the literature to achieve sparse estimates. Despite intense work in this area, how to perform valid inference for sparse penalized regression with a general penalty remains to be an active research problem. In this article, by making use of state-of-the-art optimization tools in stochastic variational inequality theory, we propose a unified framework to construct confidence intervals for sparse penalized regression with a wide range of penalties, including convex and nonconvex penalties. We study the inference for parameters under the population version of the penalized regression as well as parameters of the underlying linear model. Theoretical convergence properties of the proposed method are obtained. Several simulated and real data examples are presented to demonstrate the validity and effectiveness of the proposed inference procedure. Supplementary materials for this article are available online.
A review on deep learning in planetary gearbox health state recognition: methods, applications, and dataset publication

Planetary gearboxes have various merits in mechanical transmission, but their complex structure and intricate operation modes bring large challenges in terms of fault diagnosis. Deep learning has attracted increasing attention in intelligent fault diagnosis and has been successfully adopted for planetary gearbox fault diagnosis, avoiding the difficulty in manually analyzing complex fault features with signal processing methods. This paper presents a comprehensive review of deep learning-based planetary gearbox health state recognition. First, the challenges caused by the complex vibration characteristics of planetary gearboxes in fault diagnosis are analyzed. Second, according to the popularity of deep learning in planetary gearbox fault diagnosis, we briefly introduce six mainstream algorithms, i.e. autoencoder, deep Boltzmann machine, convolutional neural network, transformer, generative adversarial network, and graph neural network, and some variants of them. Then, the applications of these methods to planetary gearbox fault diagnosis are reviewed. Finally, the research prospects and challenges in this research are discussed. According to the challenges, a dataset is introduced in this paper to facilitate future investigations. We expect that this paper can provide new graduate students, institutions and companies with a preliminary understanding of methods used in this field. The dataset can be downloaded from https://github.com/Liudd-BJUT/WT-planetary-gearbox-dataset.
Inkjet-based bioprinting for tissue engineering

Inkjet bioprinting, a derivative of traditional inkjet technology, is gaining recognition in the fields of life sciences and tissue engineering due to its ability to produce picoliter volume droplets at high speeds in a non-contact fashion. This method has impressively evolved from enabling the production of 2-dimensional (2D) prints to complex 3-dimensional (3D) structures, and is increasingly being used in the manufacturing of electronic components. More recently, this technology has been effectively adapted for a variety of medical applications, such as cell patterning, scaffold construction, and 3D tissue fabrication. In this review, we delve into the principles and biological uses of inkjet technology. We provide an in-depth discussion on the latest developments in inkjet bioprinting, with a focus on cell patterning and 3D fabrication of tissue models, including multilayered lung, bladder, and skin. We also explore the potential of high-throughput 3D-bioprinted tissue models in toxicology and drug efficacy testing.
Enhanced Expansion of Human Pluripotent Stem Cells and Somatic Cell Reprogramming Using Defined and Xeno-Free Culture Conditions

Human embryonic stem cells and induced pluripotent stem cells (hPSC) have an unprecedented opportunity to revolutionize the fields of developmental biology as well as tissue engineering and regenerative medicine. However, their applications have been significantly limited by the lack of chemically defined and xeno-free culture conditions. The demand for the high-quality and scaled-up production of cells for use in both research and clinical studies underscores the need to develop tools that will simplify the in vitro culture process while reducing the variables. Here, we describe a systematic study to identify the optimal conditions for the initial cell attachment of hPSC to tissue culture dishes grafted with polymers of N-(3-Sulfopropyl)-N-Methacryloxyethyl-N, N-Dimethylammoniun Betaine (PMEDSAH) in combination with chemically defined and xeno-free culture media. After testing multiple supplements and chemicals, we identified that pre-conditioning of PMEDSAH grafted plates with 10% human serum (HS) supported the initial cell attachment, which allowed for the long-term culture and maintenance of hPSC compared to cells cultured on Matrigel-coated plates. Using this culture condition, a 2.1-fold increase in the expansion of hPSC was observed without chromosomal abnormalities. Furthermore, this culture condition supported a higher reprogramming efficiency (0.37% vs. 0.22%; p < 0.0068) of somatic cells into induced pluripotent stem cells compared to the non-defined culture conditions. This defined and xeno-free hPSC culture condition may be used in obtaining the large populations of hPSC and patient-derived iPSC required for many applications in regenerative and translational medicine.
Attracting solvers' participation in crowdsourcing contests: The role of linguistic signals in task descriptions

Many companies gain external expertise, lower their costs and generate publicity by using crowdsourcing platforms to complete tasks by leveraging the power of the crowd. However, the number of solvers attracted by crowdsourcing tasks varies widely. Although some well‐known crowdsourcing contests have attracted large numbers of participants, many tasks still suffer from low participation rates. Prior research aimed at solving this problem has focused on factors such as task rewards and durations while overlooking whether a well‐written description might motivate solvers to choose a task. Based on signalling theory, this study investigates the effect of task descriptions on solvers' participation by focusing on informational and affective linguistic signals. Our model is validated by analysing 13 929 descriptions posted in single‐winner tasks on epwk.com, a Chinese competitive crowdsourcing platform. For informational linguistic signals, the results reveal that there are inverted U‐shaped relationships between both concreteness and specificity and solver participation, whereas linguistic accuracy has a positive effect on solver participation. For affective linguistic signals, positive emotional words have a positive relationship with solver participation, whereas negative emotional words have the opposite effect. Theoretical and practical implications are discussed.
Optimal design of robust feedforward compensator with gain and phase specifications

This paper deals with the design of the robust feedforward compensator for improving the tracking performance of control systems with gain and phase specifications. The feedforward compensator is designed for single‐input–single‐output continuous‐time linear systems with constrained input and model uncertainty. The design objective is to make the transfer characteristic from command to output be one in the presence of the input saturation and the model uncertainty. To do that, the design of the feedforward compensator is formulated as a new gain‐phase optimization problem with both the gain and phase specifications. Then, the design procedures are proposed by using frequency‐matching method based on the closed‐loop frequency response. The proposed method provides a good trade‐off between system performance and control input to overcome performance reduction due to input saturation, and guarantees the robustness of the overall system in the presence of the model uncertainty. Two design examples illustrate that the frequency characteristics and the transient response of the control system are improved by the proposed method.
Decline of one of the southernmost northern elephant seal (Mirounga angustirostris) colonies and its relationship with a warm sea environment

Over several decades, air temperature and sea surface temperature (SST) have increased in the northeastern Pacific, as has the frequency of large-scale warm anomalies in SST. The objective of this study was to evaluate the impact of these warm anomalies on the production of northern elephant seal (Mirounga angustirostris; NES) pups from the colony of the San Benito Archipelago, located in the central-western region of the Baja California Peninsula. Pup and adult female counts from the 2002 to 2019 breeding seasons were compiled to determine the trend in the abundance of the colony and its current state. In addition, birth rate variations during the study period were assessed. Likewise, the presence of warm anomaly events in the SST in the potential foraging area of adult females (PFA) was analyzed. The San Benito colony decreased at an average annual rate of 3.6% from 2002 to 2019, with an estimated abundance of 4,723 individuals (95% CI: 3,821–5,615) in 2019. However, the birth rate remained constant (mean 0.68 ± 0.08), even though several warm anomaly events associated with El Niño and The Blob phenomena were detected in the PFA. Our results suggest that large-scale warm anomalies in the SST do not severely impact NES pup production, thus the decline of the San Benito colony since the late 1900s could be due to other environmental factors, such as the increase in air temperature associated with climate change.
DIPHTHONGISATION OF /iː/ IN WEST FRISIAN

Contemporary West Frisian (ISO 639-2 fry; henceforth: Frisian) has a rich and symmetrical vowel system, with nine short and nine long monophthongs as well as numerous rising, falling and centring diphthongs. However, the vowel system of this minority language is changing, some of these changes are induced by contact with Dutch, others are more likely to be internal changes. One such sound change in progress is observed in the long high vowel / iː /, which younger speakers tend to realise as a centring diphthong [ iˑə ]. Consequently, the traditional minimal pair wiid /ʋiːt/ ‘wide’ ~ wiet /ʋiˑət/ ‘wet’ becomes homophonic [ʋiˑət] . We present the first analysis of this sound change in progress. Based on acoustic analyses of the trajectory of /iː/ of 51 speakers from Boarnsterhim, we show that the youngest speakers use this centralising diphthongisation more often than older speakers. Moreover, analyses show that diphthongisation occurs more often before alveolar consonants.
Electromagnetic–Thermal Co-Design of Base Station Antennas With All-Metal EBG Structures

In order to improve the heat dissipation capability of the 5G base station, the electromagnetic and thermal performances of a base station antenna array are co-designed by adopting all-metal electromagnetic band-gap (EBG) structures. The geometrical dimension of the EBG structure is determined through balancing the electromagnetic and thermal performances of the antenna array. The operating frequency band (voltage standing wave ratio (VSWR) <inline-formula><tex-math notation="LaTeX">$< $</tex-math></inline-formula> 1.5) of the proposed antenna array can cover 3.4–3.8 GHz. Its realized gains, isolation, cross-polarized discrimination ratio, and half-power beamwidth are satisfactory compared with other state-of-the-art base station antennas. Most importantly, more than 9 <inline-formula><tex-math notation="LaTeX">$^{\circ }\mathrm{C}$</tex-math></inline-formula> temperature reduction can be observed when comparing the heat dissipation capability of the proposed antenna array with the reference antenna array.
Statistical Analysis for Long-Term Weather Forecast

Abstract: A weather forecast is a result of applying science and technology to predict the conditions of the atmosphere in a selected location and time in the future. The main input is a collection of data (atmospheric, land, and ocean), and the resulting output is meteorology (how atmospheric conditions will change). People have been trying to predict the weather by observing nature for thousands of years, but in a scientiﬁc way only since the 19th century. First manually and based mostly on changes in barometric pressure, and later in modern times with the contribution of computer-based models (numerical weather prediction). Despite the high inaccuracy of numerical weather prediction beyond 10 days, the interest in long-term weather forecasts is very high due to social reasons—energy sector, civil protection, etc.—and the scientiﬁc effort is constant. Here, we propose a statistical weather model for long-term weather forecasts based on weather/climate data time series. We will analyze atmospheric data in 850 hPa for a period of 35 years, resulting in temperature ensembles and temperature deviations for speciﬁc periods. Finally, we will contrast the results of the statistical weather model (prediction) with the real data to check the accuracy of the model
Exploring the E-learning experiences of students during Covid-19: a case study of the Khushal Khan Khattak University, Karak, Pakistan

In Pakistan, E-Learning was never a part of the regular mode of education delivery in any institution. However, due to the COVID-19 pandemic, all educational institutes, including colleges and universities, now offer online learning programs. E-Learning is internet or web-based learning now widely used in Pakistan due to the COVID-19 pandemic. This study explores the experiences of university students during COVID-19, and the case study is of Khushal Khan Khattak University in district Karak of Pakistan. A descriptive qualitative design was used by using a purposive sampling technique. Data was collected using semi-structured, face-to-face in-depth interviews. Thematic analysis was used to devise different themes based on the interviews taken. The study results revealed six major themes: Difficult in accessing E-Learning, Reservations about the shift to E-Learning, Learning Issues, Personal views and issues, Completion and comprehension of coursework, and challenges related to E-Learning. The study concluded that the abrupt remote online learning during the COVID-19 pandemic had impacted students at all stages of education.
Cantonese media promotes Chinese cultural identification: structural equation modeling based on Malaysian Chinese

Introduction Language media from one’s hometown is an important means of maintaining cultural identification, especially for minorities. Cantonese media plays an active role in shaping the Chinese cultural identification of ethnic Chinese all over the world. To date, few researchers have undertaken quantitative empirical analyses of the mechanism through which Cantonese media influences cultural identification. Methods Using data from 642 Malaysian Chinese, this study established a structural equation model with the partial least squares method. Results We found that the emotional affinity of ethnic Chinese to Cantonese media can influence identification with Chinese culture through the perceived value of Cantonese media and cognition of Chinese culture. The perceived value of Cantonese media (IE = 0.208) and cognition of Chinese culture (IE = 0.068) play partial mediation roles. Meanwhile, emotional affinity to Cantonese media influences cognition of Chinese culture (IE = 0.069) through the chain mediation of perceived value of Cantonese media and cognition of Chinese culture. Age has a partial moderating effect in the structural equation model. Compared with minors, adults’ emotional affinity to Cantonese media can eventually influence identification with Chinese culture (TEdiff = 0.126) more strongly through several mediation paths. Discussion The study suggests a need to cultivate the emotional affinity of ethnic Chinese to Cantonese media, improve the multidimensional values of Cantonese media, and endow Cantonese media with functions of cultural dialog and knowledge transmission. The international transmission of Cantonese media could play a vital role in building a cultural community for ethnic Chinese globally.
IFC-CityGML Data Integration for 3D Property Valuation

The accurate assessment of proper value in complex and increasingly high-rise urban environments is a significant challenge. Previous research has identified property value as a composite of indoor elements, such as volume and height, and 3D simulations of the outdoor environment, including variables such as view, noise, and pollution. These simulations have been preliminary performed in taxation context; however, there has been no work addressing the simulation of property valuation. In this paper, we propose an IFC-CityGML data integration approach for property valuation and develop a workflow based on IFC-CityGML 3.0 to simulate and model 3D property variables at the Level of Information Need. We evaluate this approach by testing it for two indoor variables, indoor daylight and property unit cost. Our proposed approach aims to improve the accuracy of property valuation by integrating data from indoor and outdoor environments and providing a standardized and efficient workflow for property valuation modeling using IFC and CityGML. Our approach represents a solid base for future works toward a 3D property valuation extension.
Constellation Design With Hypercube Graphs

A high peak-to-average power ratio (PAPR) is a major disadvantage of orthogonal frequency division multiplexing (OFDM) communications systems. In this letter, we present a graph-theoretic heuristic to mitigate high PAPR. In particular, we focus on searching for an optimal Gray-coded mapping to encode user messages such that minimum PAPR is obtained for a given message sequence in an <inline-formula><tex-math notation="LaTeX">$M$</tex-math></inline-formula>-ary quadrature amplitude modulation (QAM). We exploit the bijection between vertex-weighted lattice constellations and <italic>hypercube graphs</italic> to formulate the OFDM PAPR optimization as a computationally efficient integer linear program (ILP) through the application of <italic>Birkhoff's theorem</italic> to <italic>doubly stochastic matrices</italic>. Our numerical experiments show an average PAPR reduction of 9–10 dB using the hypercube-graph-based constellation map over the worst map while still within 0.5 dB of the brute-force method.
Interferometric Synthetic Aperture Radar Imaging of Ocean Surface Currents and Wavefields

Abstract : The potential of a method to remotely measure near-surface currents and dominant wave spectra using Interferometric Synthetic Aperture Radar INSAR is demonstrated. INSAR consists of a single conventional SAR augmented by an additional receiving antenna. The phase difference between corresponding SAR image scenes observed by the antennas provides an interferogram directly proportional to the ocean surface velocity field. This direct motion detection by INSAR suggests a significant advance compared with conventional SAR where the response to the moving ocean surface is indirectly related to complex modulation of the surface reflectivity by longer waves and currents. An experiment using an airborne INSAR to measure ocean surface currents and wave fields, compared with simultaneous ground truth measurements using Lagrangian drifters and wave array data was conducted in Monterey Bay. INSAR measured mean current magnitude estimates agree to within 10% compared with conventional measurements. The INSAR image wavenumber spectrum is consistent with the in situ directional spectrum and with predicted numerical refraction model outputs. Wavelength of the observed swells is better agreement (correlation better than 0.9) than wave direction. An attempt to estimate the scene coherence time for L-band SAR was made by taking advantage of the almost simultaneously acquired SAR and INSAR images. The obtained mean scene coherence time (100 msec) is consistent with sparse observed estimates in the literature.
Assessing Unstabilized Approaches: A Phenomenology Study of Assessing Unstabilized Approaches: A Phenomenology Study of the Risk Perceptions and Decision-Making Thought Process of the Risk Perceptions and Decision-Making Thought Process of General Aviation Pilots. General Aviation Pilots

The Federal Aviation Administration emphasized the need to focus on and develop human factors training as early as 1993 in official Human Factors Policy Order 9550.8. The purpose of this study was to conduct a detailed qualitative phenomenological analysis of the risk perceptions and decision-making model of collegiate aviation pilots for unstabilized approaches. The study focused on understanding how collegiate aviation pilots perceive unstable approaches, the risk associated with unstable approaches, and the factors that trigger pilots to execute a go-around. The International Air Transportation Association warns that continuing an unstabilized approach can lead to runway excursions, hard landings causing damage to aircraft, or even controlled flight into terrain. The theoretical framework guiding this study was the risk compensation theory. The researchers recruited 15 participants through purposeful sampling for a phenomenological analysis using semi-structured interviews and a short questionnaire. A phenomenological methodology enabled the researchers to bring forth into consciousness preconceived ideas about unstabilized approaches and then set them aside. To address the research questions, information collected from individual interviews was analyzed and triangulated using a qualitative questionnaire. Three major themes emerged from the data: (a) effect of internal perceptions, (b) external pressures, and (c) unique worldviews. The findings validated the risk compensation theory’s principles by exposing the influence of mental and environmental factors impairing participants’ judgment of an unstabilized approach. Further research is required for developing standardized and objective stabilization criteria that the general aviation community can accept.
Capability Maturity Model, Version 1.1

The capability maturity model (CMM), developed to present sets of recommended practices in a number of key process areas that have been shown to enhance software-development and maintenance capability, is discussed. The CMM was designed to help developers select process-improvement strategies by determining their current process maturity and identifying the issues most critical to improving their software quality and process. The initial release of the CMM, version 1.0, was reviewed and used by the software community during 1991 and 1992. A workshop on CMM 1.0, held in April 1992, was attended by about 200 software professionals. The current version of the CMM is the result of the feedback from that workshop and ongoing feedback from the software community. The technical report that describes version 1.1. is summarised. >