Miracle-dz/UniFAR-FTUs huggingface dataset:
EyelashNet

Eyelashes play a crucial part in the human facial structure and largely affect the facial attractiveness in modern cosmetic design. However, the appearance and structure of eyelashes can easily induce severe artifacts in high-fidelity multi-view 3D face reconstruction. Unfortunately it is highly challenging to remove eyelashes from portrait images using both traditional and learning-based matting methods due to the delicate nature of eyelashes and the lack of eyelash matting dataset. To this end, we present EyelashNet, the first eyelash matting dataset which contains 5,400 high-quality eyelash matting data captured from real world and 5,272 virtual eyelash matting data created by rendering avatars. Our work consists of a capture stage and an inference stage to automatically capture and annotate eyelashes instead of tedious manual efforts. The capture is based on a specifically-designed fluorescent labeling system. By coloring the eyelashes with a safe and invisible fluorescent substance, our system takes paired photos with colored and normal eyelashes by turning the equipped ultraviolet (UVA) flash on and off. We further correct the alignment between each pair of photos and use a novel alpha matte inference network to extract the eyelash alpha matte. As there is no prior eyelash dataset, we propose a progressive training strategy that progressively fuses captured eyelash data with virtual eyelash data to learn the latent semantics of real eyelashes. As a result, our method can accurately extract eyelash alpha mattes from fuzzy and self-shadow regions such as pupils, which is almost impossible by manual annotations. To validate the advantage of EyelashNet, we present a baseline method based on deep learning that achieves state-of-the-art eyelash matting performance with RGB portrait images as input. We also demonstrate that our work can largely benefit important real applications including high-fidelity personalized avatar and cosmetic design.
Vertebrate-eating jumping spiders (Araneae: Salticidae) revisited: consumption of geckos and bird hatchlings

Abstract. In this paper, vertebrate predation by jumping spiders (Salticidae) was revisited, taking into account incidents of this kind recently published in the scientific literature or on the internet. Our study revealed that vertebrate predation by salticids is more widespread than previously thought, geographically and taxonomically. Roughly ninety percent of all reported cases refer to predation on anurans (Hylidae and Ranixalidae) and lizards (Dactyloidae and Gekkonidae) by salticids from the subfamily Salticinae (Hyllus spp., Phidippus spp., and an unidentified species presumably related to Hasarius Simon, 1871). In the remaining cases, salticids from the subfamily Salticinae (Paraphidippus cf. aurantius (Lucas, 1833) and Phidippus audax (Hentz, 1845)) were observed attacking bird hatchlings (families Paridae and Trochilidae), weighing ≈4–6 times more than the spiders. In two instances, the spiders were observed biting the hatchlings, but only in one single case, a salticid was seen feeding on a hatchling.
Measurement Invariance Analysis on the Revised Cheek and Buss Shyness Scale in a U.S. and Japanese College Sample

In the present study, we tested the factor structure of the 20-item Revised Cheek and Buss Shyness Scale (RCBS; Cheek & Melichor, 1985) in a U.S. sample and used measurement invariance analysis to explore its cross-cultural validity in a previously collected Japanese sample (Sato et al., 2018). We additionally measured related personality traits (Big Five; Locus of Control, LOC; and Behavioral Inhibition System/Behavioral Activation System, BIS/BAS) to examine whether each predicted shyness. Participants were undergraduate students in the United States (N = 525) and Japan (N = 508). Exploratory factor analysis (n = 261) revealed a unidimensional structure for shyness to be the best fit. Measurement invariance analysis (n = 256 for United States) showed that the RCBS did not establish configural invariance, the weakest level in measurement invariance, suggesting that it may not be a cross-culturally valid and reliable tool to assess shyness. We thus did not perform any cross-cultural comparisons of variables, as initially intended. Results from a hierarchical multiple regression in the U.S. sample found extraversion to negatively predict shyness, β = −. 59, p < . 001, and neuroticism, β = . 18, p < . 001, LOC (external), β = . 14, p < . 001, and BIS, β = . 19, p < . 001, to positively predict shyness. Gender was not a significant predictor, β = . 09, p = . 075. Future work may focus on the development of a Japanese shyness measure independent from U.S. conceptualizations to improve the cross-cultural validity and reliability of shyness measures.
TOWARD SECURE AS WELL AS EFFECTIVE COMMUNICATION FOR THE NET OF DETAILS

: Internet of Things has been widely applied in everyday life, ranging from transportation and healthcare to smart homes. As most IoT devices carry constrained resources and limited storage capacity, sensing data need to be transmitted to and stored at resource-rich platforms, such as a cloud. IoT applications need to retrieve sensing data from the cloud for analysis and decision-making purposes. Ensuring the authenticity and integrity of the sensing data is essential for the correctness and safety of IoT applications. We summarize the new challenges of the IoT data communication with authenticity and integrity and argue that existing solutions cannot be easily adapted to resource constraint IoT devices. We present two solutions called dynamic tree chaining and geometric star chaining that provide efficient and secure communication for the Internet of Things. Extensive simulations and prototype emulation experiments driven by real IoT data show that the proposed system is more efficient than alternative solutions in terms of time and space.
Optimal Data Analysis Based on Unsupervised Learning New Projection K-Means Initialization Clustering Algorithm and EMCA

: - Data mining could be a method of extracting desired and helpful data from the pool of information. Clusterin data processing is that the grouping of information points with some common similarity. Cluster is a vital aspect of information mining. It simply clusters the information sets into given no. of clusters. Various no. of ways are used for the information cluster among that K-suggests that is that the most generally used cluster formula. During this paper, we've briefed within the kind of a review work done by completely different researcher’s victimization K-means cluster formula. As a partition primarily based cluster algorithmic program, K-Means is wide employed in several areas for the options of its efficiency and simply understood. However, it's documented that the K-Means algorithmic program could get suboptimal solutions, looking at the selection of the initial cluster centers. During this paper, they propose a projection-based K-Means low-level formatting formula. The planned formula initial uses standard mathematician kernel density estimation techniques to search out the extremely density information areas in one dimension. Then the projection step is to iteratively use density estimation from the lower variance dimensions to the upper variance ones till all the scale square measure computed. Experiments on actual datasets show that our technique will get similar results compared with different standard ways with fewer computation tasks.
Active power filters: a review

There has been considerable interest in the development and applications of active filters because of the increasing concern over power quality, at both distribution and consumer levels, and the need to control reactive power and voltage stability at transmission levels. The existing approaches are classified and assessed to provide a framework of references for both researchers in this field and for generators, suppliers and consumers of electrical power who are, or may be, concerned about the problems associated with power quality and are considering installing active filters for their particular sets of problems.
Simulation and two-dimensional analytical modeling of subthreshold slope in ultrathin-film SOI MOSFETs down to 0.1 mu m gate length

The subthreshold slope in ultra-thin-film fully depleted SOI MOSFETs is investigated for channel lengths from the long channel region down to 0.1 mu m. A doping effect is found which allows improvement of the S-factor by increasing the channel doping concentration. In order to explain this phenomenon and to clarify the mechanism of S-factor degradation at short gate lengths, a two-dimensional analytical model is developed. A modified boundary condition for the two-dimensional Poisson equation is introduced to account for the nonlinear potential distribution inside the buried oxide. It is found that the S-factor short-channel degradation is governed by three mechanisms: the rise of capacitances at the channel source and drain ends due to the two-dimensional potentional distribution; the subthreshold current flow at the back channel surface; and the modulation of the effective current channel thickness during the gate voltage swing in the subthreshold region. The analytical model results are compared to those of numerical device simulation, and a good agreement is found. >
Conformal Time-series Forecasting

Current approaches for (multi-horizon) time-series forecasting using recurrent neural networks (RNNs) focus on issuing point estimates, which are insufﬁcient for informing decision-making in critical application domains wherein uncertainty estimates are also required. Existing methods for uncertainty quantiﬁcation in RNN-based time-series forecasts are limited as they may require signiﬁcant alterations to the underlying architecture, may be computationally complex, may be difﬁcult to calibrate, may incur high sample complexity, and may not provide theoretical validity guarantees for the issued uncertainty intervals. In this work, we extend the inductive conformal prediction framework to the time-series forecasting setup, and propose a lightweight uncertainty estimation procedure to address the above limitations. With minimal exchangeability assumptions, our approach provides uncertainty intervals with theoretical guarantees on frequentist coverage for any multi-horizon forecast predictor and any dataset. We demonstrate the effectiveness of the conformal forecasting framework by comparing it with existing baselines on a variety of synthetic and real-world datasets.
Personnel Selection Using Interval 2‐Tuple Linguistic VIKOR Method

Personnel selection is a very important activity in the human resource management of an organization. However, in many practical circumstances, due to time pressure and lack of information about candidates, decision makers generally tend to provide linguistic assessments and use different linguistic term sets to express their opinions during the personnel selection process. In this article, the VIKOR method combined with interval 2‐tuple linguistic variables is proposed to choose appropriate individuals among candidates in a group decision‐making environment. The interval 2‐tuple linguistic variable, which comprises two linguistic terms and two real numbers, is more flexible and precise to deal with linguistic information in solving personnel selection problems. To demonstrate the applicability and effectiveness of the proposed interval 2‐tuple linguistic VIKOR method, a numerical example of personnel selection in a tertiary care hospital is provided.
Evaluation of holistic approaches to predicting the concentrations of heavy metals in pots-cultivated durum wheat ( Triticum durum L . )

AGBIR Vol.37 No.5 September-2021 College of Resources and Environment, Huazhong Agricultural University, Wuhan, China; Faculty of Agronomy and Agricultural Sciences University of Dschang, Cameroon; Department of Life and Earth Sciences, Higher Teachers’ Training College, University of Maroua, P.O. Box 55, Maroua, Cameroon; Institute of Agricultural Research for Development (IRAD), Nkoemvoe, P.O. Box 65, Ebolowa'a, Cameroon; Central Agricultural Research Institute, Suakoko, Bong CountyLiberia; Department of sciences, University of Yaounder,Yaoundé,Cameroon
GOLD AN ALTERNATE FORM OF CURRENCY

Adherence to the gold standard is a condition of all IMF member countries. Upon these conditions, they have freely accepted the code of behaviour. Maintaining the price of money at home at a gold equivalent is often associated with gold currency. Those who advocated for the gold standard stood on one side, while those opposed it stood on the other. The gold standard plays an essential role in preventing monetary authorities from evading responsibility for their actions. This argument also applies to the gold-bullion standard and the gold-exchange standard to a lesser degree because of the inconveniences of holding gold bullion or gold exchange. There is a point of weakness in the theory that wise men won't save their money when prices rise. To keep and enhance the usage of the gold currency unit while also promoting the monetary gold unit in international payments and backing this with coinage and paper money, they work to preserve and expand the use of the gold currency unit. In addition, they are working to prevent global transactions from using only gold coins, currency, and paper money. They also aim to cut down on monetary gold usage and prohibit central banks and governments from making international trade with gold coins, currency, and paper money. Paper money, subsidiary coins, and deposit currency in monetary systems have been increasing, and as a result, these systems have turned into commodity-standard systems. It is necessary to implement managerial controls to manage an organisation effectively. However, rules that empower the free enterprise to operate should be set up to free managers from overseeing operations constantly. Regardless of the currency, it is linked to, and there will always be a commodity-standard factor in the mix.
Stress grading for high voltage motor and generator coils

Stress grading on high voltage motor and generator stator windings is becoming more important as the electrical stress in the ground insulation is increased. While there are a variety of possible ways to relieve surface stress, non-linear resistive tapes have been almost universally adopted because of their simplicity and efficiency. However, selection and quality control on these materials has been problematic, as the means to characterize these materials has not been clearly set out. Most types of material can be characterized in terms of two parameters, a threshold stress and a gradient index, which can be determined from simple current and voltage measurements. It is hoped, therefore, that manufactures of grading products will adopt such measurements and publish these values as a matter of course. This will enable coil manufacturers to improve the specification and quality control of stress grading coatings. >
Static relays permit enhanced protection

Multi-function multi-phase static overcurrent relays, using digital technology available today, provide basic time, (51) (51G) (51N) and instantaneous (50) (50G) (50N) three phase and ground overcurrent protection, and may offer some or all of the following additional functions: undervoltage (27); overvoltage (59); reverse phase sequence (47); negative phase sequence voltage (47N); directional overcurrent (67) (67N); frequency (81O/U); reverse interlocking trip coil monitoring; and battery monitoring. This article describes two applications that use some of the additional functions in such a relay: reverse interlocking, also using the directional overcurrent (67) function; and ground fault detection for systems utilizing high resistance grounding. The first application was installed on a 4160 volt power system which was supplied by two 5000 kVA transformers.
Has Global Agricultural Trade Been Resilient Under Covid-19? Findings from an Econometric Assessment of 2020

Global agricultural trade, which increased at the end of 2020, has been described as "resilient" to the impacts of the COVID-19 coronavirus pandemic;however, the size and channels of its quantitative impacts are not clear. Using a reduced-form, gravity-based econometric model for monthly trade, the researchers estimate the effects of COVID-19 incidence rates, policy restrictions imposed by governments to curb the outbreak, and the de facto reduction in human mobility/lockdown effect on global agricultural trade through the end of 2020. The researchers find that while agricultural trade remained quite stable through the pandemic, the sector as a whole did not go unscathed. First, the researchers estimate that COVID-19 reduced agricultural trade by the approximate range of 5 to 10 percent at the aggregate sector level;a quantified impact two to three times smaller in magnitude than our estimated impact on trade occurring in the non-agricultural sector. Second, the researchers find sharp differences across individual commodities. In particular, the researchers find that non-food items (hides and skins, ethanol, cotton, and other commodities), meat products including seafood, and higher value agri-food products were most severely impacted by the pandemic;however, the COVID- 19 trade effect for the majority of food and bulk agricultural commodity sectors were found to be insignificant, or in a few cases, positive. Finally, the researchers also examine the effects across low vs high income countries, the changing dynamics of the pandemic's effect on trade flows, and the effects along the extensive product margins of trade.
PROMISCUOUS ELITES, THE REVOLVING DOOR, AND ECONOMIC DEVELOPMENT

This paper analyzes the interconnection between elites and its effects on economic growth. For decades, the bureaucratic elite has been joining the business elite after leaving office, and this in growing numbers. This relationship has been termed “the revolving door” in English, “pantouflage” in French, and “amakudari“ [descent from heaven] in Japanese. The purpose of this paper is to explain why this social behavior takes place, and why the political elite does not try to prevent it. Moreover, this paper shows that the bureaucratic elite obtains excessive bureaucratic power, and that promiscuous elites and the existence of the revolving door actually lead to lower economic growth.
Evaluation of the Usefulnes and Usability of Cockpit Situation Display Perspectives for Rov Operations in Approach Civil Air Space

A distributed simulation of ROV operations was conducted by NASA Ames Flight Deck Display Research Laboratory (FDDRL) and the Center for Aeronautic Technologies (CSAAT) at California State University, Long Beach. The goals of this simulation were 1) to examine ROV operators' ability to maintain standard terminal separation from other aircraft and ROVs, 2) to examine the possibility of operating ROVs in terminal airspace without major disruptions in the inbound traffic flows, and 3) to evaluate proposed ROV operator tools. The current paper focuses on this third goal. Specifically the paper describes the motivation behind the development of the manipulatable 2D/3D Cockpit Situation Display (CSD), and examines its usefulness and usability. Data from questionnaires, and from observations of how the CSD was used, suggest that both the CSD format, and the ability to manipulate the CSD viewing angle, were useful and usable. However, workload appeared to play an important role in the perceived usefulness and usability of the CSD.
Fourier Behind Entanglement: A Spectral Approach to the Quantum Internet

In this study, the bridge between quantum fourier transform (QFT) and the most important effect inside quantum physics—entanglement—is presented. Moreover, all the applications of entanglement are impregnated by this equivalence, which concludes in the first spectral approach to the quantum Internet of the literature, which will allow the development of configurations that are more immune to noise as well as fault‐tolerant. Several protocols used in the quantum Internet are implemented on a 5‐qubit international business machine quantum (IBM Q) platform, experimentally verifying the aforementioned equivalence.
The sensitivity of probabilistic convective‐scale forecasts of an extratropical cyclone to atmosphere–ocean–wave coupling

The benefits of dynamical atmosphere–ocean–wave coupling in probabilistic weather forecasts generated using convective‐scale ensemble prediction systems are to date unknown. We investigate the respective impacts of atmosphere–ocean–wave coupling, and initial condition (IC), lateral boundary condition (LBC), and stochastic physics perturbations within a convective‐scale ensemble coupled system for an extratropical cyclone case study. Towards this aim, we developed the first 18‐member, 2.2 km grid spacing ensemble regional coupled system (Ensemble‐RCS) with domain covering the British Isles and surrounding seas. Ensemble‐RCS coupled and uncoupled simulations of cyclone Ciara (February 2020) were performed. Adding stochastic perturbations to the model physics parametrizations enhances the ensemble spread of the uncoupled atmosphere‐only ensemble driven by IC and LBC perturbations, while slightly reducing (by up to 0.5 m · s −1 ) the median of the ensemble 95th percentile 10‐m wind speeds from its value of about 24 m · s −1 at peak time. A substantial proportion of this impact is attributable to Charnock parameter perturbations alone. By coupling the atmosphere‐only ensemble, with stochastic physics, to the ocean, the ensemble median and spread is mainly unaffected. However, additional coupling to waves reduces the median wind speed by 1 m · s −1 , which leads to reductions of up to 70% in strong wind strike probability, and halving of the spatial coverage of high values (>50%) of this probability. Finally, we demonstrate the usefulness of two metrics originally developed for precipitation verification – the neighbourhood‐based Fraction Skill Score (FSS) and the object‐based Structure, Amplitude, Location (SAL) – for examining the spread in convective‐scale ensemble forecasts. It is concluded that coupling has a consistent impact across the ensemble members. Remarkably, the impact of coupling to waves is found to be comparable in size to that of adding IC, LBC and stochastic physics perturbations to the uncoupled atmosphere‐only ensemble simulation, implying that the dynamical coupling to ocean and sea‐state are important aspects of model uncertainty.
Keratinocyte differentiation and proteolytic pathways in skin (patho)physiology.

Epidermis is a stratified epithelium that forms the barrier between the organism and its environment. It is mainly composed of keratinocytes at different stages of differentiation. Stratum corneum is the outermost layer of the epidermis and is formed of multiple layers of anucleated keratinocytes called corneocytes. We aim to highlight the roles of epidermal differentiation and proteolysis in skin diseases. Skin biopsies isolated from Spink5-/- mice, the established model of Netherton syndrome (NS), and from patients with NS, seborrheic dermatitis (SD) and psoriasis, as well as healthy controls, were analyzed by histology and immunohistochemistry. Our results showed that NS, SD, and psoriasis are all characterized by abnormal epidermal differentiation, manifested by hyperplasia, hyperkeratosis, and parakeratosis. At the molecular level, abnormal differentiation is accompanied by increased expression of involucrin and decreased expression of loricrin in NS and psoriasis. Increased epidermal proteolysis associated with increased kallikrein-related peptidases (KLK) expression is also observed in both NS and psoriatic epidermis. Further, reduced expression of desmosomal proteins is observed in NS but increased in psoriasis. Since desmosomal protein are proteolytic substrates and control keratinocyte differentiation, their altered expression directly links epidermal proteolysis to differentiation. In conclusion, abnormal cellular differentiation and proteolysis are interconnected and underlie the pathology of NS, SD and psoriasis.