Miracle-dz/UniFAR-FTUs huggingface dataset:
Life cycle simulation for the inverse manufacturing

This paper proposes a methodology for configuring modular products and planning its product life cycles at the conceptual design stage by simulating their life cycle models. Based on the simulation results we also discuss feasibility of the inverse manufacturing, from the integrated viewpoints of the environmental consciousness, corporate sustainability, and customer's cost compared to a traditional life cycle with four types (recycling type, reuse+recycling type, maintenance+recycling type and maintenance+reuse+recycling type) using the data of a refrigerator. Modularization of product is a hopeful approach for reducing maintenance costs and reuse costs. To assist modular design, we also developed optimized modular configuration of a product.
Circuit hot carrier reliability simulation in advanced CMOS process technology development

To establish the relation between circuit AC hot carrier (HC) degradation and DC testable parameters in early development stage of a deep submicron technology becomes the critical part of the process integration. DC Hot Carrier parameters, e.g. Idsat and Idlin, were found to be correlated to AC Ring Oscillator frequency degradation. The impact of crosstalk induced voltage overshoot to invertor hot carrier degradation was quantified by simulation. A set of designable parameters were used to ensure deep submicron technology hot carrier reliability.
[Prostatitis studies in China from 2000 to 2020: A Knowledge Atlas-based study on the development trend of contemporary disciplines].

Objective To review and analyze the trend of researches on prostatitis in China in the past two decades. METHODS We searched the core collection of China National Knowledge Infrastructure (CNKI) for studies on prostatitis, and analyzed the data obtained using Excel, Citespace and VOSviewer. RESULTS Totally, 1 216 original articles were identified, with 3 271 keywords, ≥3-time high-frequency keywords accounting for 12.9%, with "", "", "chronic prostatitis", "prostatitis", and "" as the top 5 ones, each with a centrality higher than 300. Major prostatitis-related studies focused on the 8 keywords, namely, prostatitis, prostatic fluid, rats, prostate, syndromes, efficacy observation, compound (in traditional Chinese medicine, TCM), and therapeutic application. The included literature involved 2 808 authors, with 402 involved more than twice and most of them in a scattered manner. The major topics of prostatitis studies varied in the past two decades, focusing on TCM therapies, promotion of blood circulation and stasis and comprehensive nursing in 2000－2001, on animal models, CD4+ lymphocytes and other experimental molecules in 2007－2010, on urodynamics, risk factors and specific antigens in 2013－2016, and on literature information resources in 2016. CONCLUSIONS The immune mechanism remains a hot topic in the future researches on prostatitis. In terms of treatment of the disease, TCM has a potential value, and more practice and studies are required for an optimal combination of TCM and Western medicine. Strengthened collaborative efforts are needed to establish an authoritative source channel for the keywords, and incorporate it into the national standard system, and above all, to integrate the prostatitis study into multi-disciplinary researches, eliminate academic barriers, encourage collaborative innovation with multiple parties, and promote the exchanges and development in this field.
Hemodynamic, endocrine, and gene expression mechanisms regulating equine ovarian follicular and cellular development

Ovulatory follicle development and associated oocyte maturation involve complex coordinated molecular and cellular mechanisms not yet fully understood. This study addresses the relationships among follicle diameter, follicle wall blood flow, follicular‐fluid factors, and gene expression for follicle growth, steroidogenesis, angiogenesis, and apoptosis in granulosa/cumulus cells and oocytes during different stages from the beginning of largest/ovulatory follicle to impending ovulation in mares. The most remarkable findings were (i) a positive association between follicle development, follicle blood flow, intrafollicular follicle‐stimulating hormone (FSH), luteinizing hormone (LH), estradiol, progesterone, and messenger RNA (mRNA) expression for FSHR and LHCGR in granulosa cells of the largest/ovulatory follicle; (ii) a plateau or decrease in follicle diameter and blood flow and granulosa cell mRNA for FSHR, LHCGR, IGF1R, VEGFR2, CYP19A1, and CASP3 at the preovulatory stage; (iii) higher StAR and BCL2 and lower CASP3 mRNA in granulosa cells at the time of impending ovulation; (iv) greater IGF1R mRNA for granulosa cells at the predeviation stage; and (v) lower FSHR, LHCGR, IGF1R, and VEGFR2 mRNA in cumulus cells and greater LHCGR and IGF1R mRNA in oocytes at the ovulatory stage. This study is a critical advance in the understanding of molecular mechanisms of follicle development and oocyte maturation and is expected to be vital for future studies targeting potential markers.
Breakfast skipping and cognitive and emotional engagement at school: a cross-sectional population-level study

Abstract Objective: Research on the consequences of breakfast skipping among students tends to focus on academic outcomes, rather than student well-being or engagement at school. This study investigated the association between breakfast skipping and cognitive and emotional aspects of school engagement. Design: Cross-sectional study using data from a population-level survey of children and adolescents’ well-being and engagement at school. Linear regression with adjustment for confounders was used to estimate the effect of breakfast skipping on school engagement. Setting: Government schools (i.e. public schools) in South Australia. Participants: The participants were students, Grades 4–12, who completed the Wellbeing and Engagement Collection in 2019. The analysis sample included 61 825 students. Results: Approximately 9·6 % of students reported always skipping breakfast, with 35·4 % sometimes skipping and 55·0 % never skipping. In the adjusted linear regression models, children and adolescents who always skipped breakfast reported lower levels of cognitive engagement (β = −0·26 (95 % CI −0·29, −0·25)), engagement with teachers (β = −0·17 (95 % CI −0·18, −0·15)) and school climate (β = −0·17 (95 % CI −0·19, −0·15)) compared with those who never skipped breakfast, after controlling for age, gender, health, sleep, sadness and worries, parental education, socio-economic status and geographical remoteness. Conclusion: Consistent with our hypothesis, skipping breakfast was associated with lower cognitive and emotional engagement, which could be due to mechanisms such as short-term energy supply and long-term health impacts. Therefore, decreasing the prevalence of breakfast skipping could have a positive impact on school engagement.
Study on Elman Neural Networks Algorithms Based on Factor Analysis

When we manipulate high dimensional data with Elman neural network, many characteristic variables provide enough information, but too many network inputs go against designing of the hidden-layer of the network and take up plenty of storage space as well as computing time, and in the process interfere the convergence of the training network, even influence the accuracy of recognition finally. Factor Analysis (FA) concentrates the information that is carried by numerous original indexes which form the index system, and then stores it to the factor, and can according to the precision that the actual problem needs, through controlling the number of the factors, to adjust the amount of the information. In this paper we make full use of the advantages of FA and the properties of Elman neural network structures to establish FA-Elman algorithm. The new algorithm reduces dimensions by FA, and carry on network training and simulation with low dimensional data that we get, which obviously simplifies the network structure, and in the process, improves the training speed and generalization capacity of the Elman neural network.
The role of the dominant attribution style and daily hassles in the symptoms of depression and anxiety

ABSTRACT Cognitive theories of depression and anxiety posit that attribution bias plays a central role in the onset and maintenance of anxiety and depression. The main goal of the current study was to examine the association of the Weakest Link as an individual’s dominant attribution style, and daily hassles, with depressive and anxious symptoms, and to examine the moderating effect of the Weakest Link on the relationships of daily hassles with depressive and anxious symptoms. 686 undergraduate students recruited from three universities completed questionnaires that measured dominant attribution style, daily hassles, and depressive symptoms and anxious symptoms. Moderation analysis showed that daily hassles and Weakest Link were independent predictors of both depressive and anxious symptoms. Individuals with high Weakest Link scores reported high levels of both depressive and anxious symptoms in the presence of high levels of daily hassles. In conclusion, the current study provides support for moderation effect of the dominant attribution style on the relationship between daily hassles and the symptoms of depression and anxiety.
Teo‐shaped slotted‐circular‐patch antenna for circularly polarized radiation and RF energy harvesting

A novel circularly polarized (CP) Teo‐shaped slotted‐circular‐patch antenna is proposed for RF energy harvesting. The antenna consists of a Teo‐shaped slotted‐circular‐patch and an aperture‐coupled feeding network. A Teo‐shaped slot is embedded at the center of a circular‐patch and its size and rotation are optimized for wide‐beam CP radiation. The antenna prototype shows the 3‐dB axial ratio (AR) bandwidth of 100 MHz (2.4–2.5 GHz) with 10‐dB return loss bandwidth is 33% (1.89–2.66 GHz). The 3‐dB AR beamwidth is around 100° with gain more than 6.0 dBic across the desired band. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:2752–2758, 2015
Knockdown of CCL28 inhibits endometriosis stromal cell proliferation and invasion via ERK signaling pathway inactivation

Endometriosis (EM), the presence of functional endometrial glands and stroma outside the uterine cavity, is a common gynecological disorder. At present, the pathogenesis of EM has not been fully elucidated, so there is still a lack of effective therapy. The present study aimed to explore the role of C-C motif chemokine ligand 28 (CCL28) and its underlying mechanism in endometrial stromal cells to propose a novel therapy for EM treatment. The expression of CCL28 and CC chemokine receptor 10 (CCR10) were examined. After CCL28 knockdown or overexpression by lentivirus infection, cell proliferation and invasion were measured. It was revealed that compared with normal, the expression levels of CCL28 and CCR10 were significantly elevated in endometrial tissues of patients with EM. Knockdown of CCL28 in endometrial stromal cells significantly suppressed cell proliferation and invasion, and this was accompanied by significantly reduced expression levels of CCR10, MMP2, MMP9, integrin β1 (ITGB1) and phosphorylated (p)-ERK/ERK ratio. The addition of the CCL28 recombinant protein had an opposite effect to CCL28 downregulation. Furthermore, the ERK inhibitor, PD98059, reduced CCL28-induced cell proliferation and invasion, as well as the expression levels of MMP2, MMP9, ITGB1 and p-ERK. Therefore, the present study indicated that CCL28 may contribute to the progression of EM by regulating MMP2, MMP9 and ITGB1 expression and function via the activation of the ERK signaling pathway.
Gesture-Based Human–Machine Interaction: Taxonomy, Problem Definition, and Analysis

The possibility for humans to interact with physical or virtual systems using gestures has been vastly explored by researchers and designers in the last 20 years to provide new and intuitive interaction modalities. Unfortunately, the literature about gestural interaction is not homogeneous, and it is characterized by a lack of shared terminology. This leads to fragmented results and makes it difficult for research activities to build on top of state-of-the-art results and approaches. The analysis in this article aims at creating a common conceptual design framework to enforce development efforts in gesture-based human–machine interaction (HMI). The main contributions of this article can be summarized as follows: 1) we provide a broad definition for the notion of functional gesture in HMI; 2) we design a flexible and expandable gesture taxonomy; and 3) we put forward a detailed problem statement for gesture-based HMI. Finally, to support our main contribution, this article presents and analyzes 83 most pertinent articles classified on the basis of our taxonomy and problem statement.
Assessment of the Size Effect in Fatigue Analysis of Butt Welds and Cruciform Joints

Reduced fatigue capacity of welded structures for larger thicknesses was introduced in design standards approximately 30 years ago. A significant amount of research on this topic was performed during the following years. In general the presence of a size effect was agreed upon. The size effect is considered to be dependent on the plate thickness at the considered hot spot in addition to size of attachment plate and type of dynamic loading. Only simplified recommendations on the size effect are included in most fatigue design standards. One reason for this is normal scatter in fatigue test data and also somewhat different recommendations based on these data in the literature. This has made it difficult to arrive at full agreement on recommended fatigue analysis procedures. In this paper a review of literature and design standards are presented together with a calibration of analysis method with fatigue test data. The effect of different parameters contributing to the size effect is illustrated. An attempt has been made to use the calibrated analysis model to also quantify the size effect based on crack growth analyses. Finally some recommendations on size effect to be used in fatigue design standards are presented.Copyright © 2014 by ASME
Lassoed Boosting and Linear Prediction in Equities Market

We consider a two-stage estimation method for linear regression that uses the lasso in Tibshirani (1996) to screen variables and re-estimate the coeﬃcients using the least-squares boosting method in Friedman (2001) on every set of selected variables. Based on the large-scale simulation experiment in Hastie et al. (2020), the performance of lassoed boosting is found to be as competitive as the relaxed lasso in Meinshausen (2007) and can yield a sparser model under certain scenarios. An application to predict equity returns also shows that lassoed boosting can give the smallest mean squared prediction error among all methods under consideration.
Transit Route Network Design Problem: Review

Efficient design of public transportation networks has attracted much interest in the transport literature and practice, with many models and approaches for formulating the associated transit route network design problem (TRNDP) having been developed. The present paper systematically presents and reviews research on the TRNDP based on the three distinctive parts of the TRNDP setup: design objectives, operating environment parameters and solution approach.
Self-assembled Ge/Si dots for faster field-effect transistors

Self-assembled and coherently strained germanium nanostructured dots are grown on prepatterned Si substrates along ordered lines. These precisely aligned nanocrystals are proposed to make up the central unit of a dot-based field-effect transistor (DotFET). The strain-induced band edge splitting and the inherently smaller effective masses of charge carriers in Ge/Si dots promise faster transistors than are possible for conventional pure Si devices. Thick relaxed buffer layers-mandatory for any existing high-speed SiGe field-effect devices-are no longer required. The DotFET is straight-forward, defect-free, and fully compatible with current complementary metal-oxide-semiconductor (CMOS) technology.
Analysis of Algorithm design in the Fast Internet Traceback scheme

The rising threat of cyber attacks, especially DDoS, makes the IP traceback problem very relevant to today's Internet security. The Fast Internet Traceback (FIT) [1] is a novel scheme which just use only 1 bit to derive the distance from the receiver and the last marking FIT enabled router, so it significantly decreased number of received packets needed for victim to reconstruct the attack path, and could derive the actual legacy hops between the receiver and the last marking FIT enabled router. In this paper, we make the analysis to know how the algorithm in the FIT scheme is designed.
Advanced Turbine Technology Applications Project (ATTAP)-Overview;Status;and Outlook

The ATTAP aims at proving the performance and life of structural ceramic components in the hot gas path of an automotive gas turbine engine. This Department of Energy (DOE)-sponsored, NASA-managed program is being addressed by a General Motors (GM) team drawing expertise from the Advanced Engineering Staff (AES) and from Allison. The program includes design, process development and fabrication, rig and engine testing, and iterative development of selected key ceramic components for the AGT-5 engine. A reference powertrain design (RPD) based on this engine predicts acceleration, driveability, and fuel economy characteristics exceeding those of both current engines and the DOE goals.A low-apsect-ratio ceramic turbine rotor design has been successfully engine-demonstrated at 2200°F and 100% speed, including survival of impact and other hostile flow path conditions. Turbine flow path components have been designed for the 2500°F cycle, using improved monolithic ceramics targeted for Year 2 fabrication. Major development/fabrication efforts have been subcontracted at Carborundum, GTE Labs, Corning Glass, Garrett Ceramic Components, and Manville. Feasibility studies were initiated with Ceramics Process Systems and Drexel University.Copyright © 1989 by ASME
Online Trading Models with Deep Reinforcement Learning in the Forex Market Considering Transaction Costs

In recent years, a wide range of investment models have been created using artificial intelligence. Automatic trading by artificial intelligence can expand the range of trading methods, such as by conferring the ability to operate 24 hours a day and the ability to trade with high frequency. Automatic trading can also be expected to trade with more information than is available to humans if it can sufficiently consider past data. In this paper, we propose an investment agent based on a deep reinforcement learning model, which is an artificial intelligence model. The model considers the transaction costs involved in actual trading and creates a framework for trading over a long period of time so that it can make a large profit on a single trade. In doing so, it can maximize the profit while keeping transaction costs low. In addition, in consideration of actual operations, we use online learning so that the system can continue to learn by constantly updating the latest online data instead of learning with static data. This makes it possible to trade in non-stationary financial markets by always incorporating current market trend information.
Nearly Optimal Linear Convergence of Stochastic Primal-Dual Methods for Linear Programming

There is a recent interest on first-order methods for linear programming (LP). In this paper,we propose a stochastic algorithm using variance reduction and restarts for solving sharp primal-dual problems such as LP. We show that the proposed stochastic method exhibits a linear convergence rate for solving sharp instances with a high probability. In addition, we propose an efficient coordinate-based stochastic oracle for unconstrained bilinear problems, which has $\mathcal O(1)$ per iteration cost and improves the complexity of the existing deterministic and stochastic algorithms. Finally, we show that the obtained linear convergence rate is nearly optimal (upto $\log$ terms) for a wide class of stochastic primal dual methods.
Topological Lifshitz transitions, orbital currents, and interactions in low-dimensional Fermi gases in synthetic gauge fields

Low-dimensional systems of interacting fermions in a synthetic gauge field have been experimentally realized using two-component ultra-cold Fermi gases in optical lattices. Using a two-leg ladder model that is relevant to these experiments, we have studied the signatures of topological Lifshitz transitions and the effects of the inter-species interaction U on the gauge-invariant orbital current in the regime of large intra-leg hopping Ω. Focusing on non-insulating regimes, we have carried out numerically exact density-matrix renormalization-group (DMRG) calculations to compute the orbital current at fixed particle number as a function of the interaction strength and the synthetic gauge flux per plaquette. Signatures of topological Lifshitz transitions where the number Fermi points changes are found to persist even in the presence of very strong repulsive interactions. This numerical observation suggests that the orbital current can be computed from an appropriately renormalized mean-field band structure, which is also described here. Quantitative agreement between the mean-field and the DMRG results in the intermediate interaction regime where U ≲ Ω is demonstrated. We also have observed that interactions can change the sign of the current susceptibility at zero field and induce Lifshitz transitions between two metallic phases, which is also captured by the mean-field theory. Correlation effects beyond mean-field theory in the oscillations of the local inter-leg current are also reported. We argue that the observed robustness against interactions makes the orbital current a good indicator of the topological Lifshitz transitions.
Draft Genome Sequence of Aestuariibacter halophilus Type Strain JC2043

Aestuariibacter halophilus strain JC2043, a Gram-negative gammaproteobacterium, is often used as a reference organism for assigning taxonomy within the family Alteromonadaceae. Isolates of this species have also been investigated for compound degradation (e.g., phthalates and oil) and biofilm association. Presented here is the draft genome sequence of A. halophilus strain JC2043. ABSTRACT Aestuariibacter halophilus strain JC2043, a Gram-negative gammaproteobacterium, is often used as a reference organism for assigning taxonomy within the family Alteromonadaceae. Isolates of this species have also been investigated for compound degradation (e.g., phthalates and oil) and biofilm association. Presented here is the draft genome sequence of A. halophilus strain JC2043.
Flood Management: Bradford Paper

In February 1990 severe storms hit most of Britain, and in Towyn, a seaside resort in North Wales – the effects were dramatic. The force of the sea caused a breach in the sea defences which resulted in large‐scale flooding affecting in the region of 2,400 properties and causing in the biggest evacuation to take place in Britain since the war. The disaster had not been anticipated by the local authority and no one had experience of dealing with this scale of event. As with most disasters, a large number of people were involved and scores of organizations carried out a multitude of tasks under difficult circumstances. Many of the problems were long‐term, especially those dealing with stress and aftercare. Despite the complexity and scale of the tasks the local authority, working with other organizations, successfully dealt with this disaster. Addresses some of the many problems faced at Towyn and examines the management systems and network systems which evolved to deal with this event.