Miracle-dz/UniFAR-FTUs huggingface dataset:
Biologically Visual Perceptual Model and Discriminative Model for Road Markings Detection and Recognition

The detection and recognition of arrow markings is a basic task of autonomous driving. To achieve all-day detection and recognition of arrow markings in complex environment, we propose a hybrid model by exploiting the advantages of biologically visual perceptual model and discriminative model. Firstly, the arrow markings are extracted from the complex background in the region of interest (ROI) by the biologically visual perceptual model using the frequency-tuned (FT) algorithm. Then candidates for road markings are detected as maximally stable extremal regions (MSER). In recognition stage, biologically visual perceptual model calculates the sparse solution of arrow markings using sparse learning theory. Finally, discriminative model uses the Adaptive Boosting (AdaBoost) classifier trained by sparse solution to classify arrow markings. Experimental results show that the hybrid model achieves detection and recognition of arrow markings in complex road conditions with the precision, recall, and F-measure being 0.966, 0.88, and 0.92, respectively. The hybrid model is robust and has some advantages compared with other state-of-the-art methods. The hybrid model proposed in this paper has important theoretical significance and practical value for all-day detection and recognition in complex environment.
Cardiotoxicity of antiangiogenic drugs: causes and mechanisms

Therapy with angiogenesis inhibitors is undoubtedly an advancement in cancer treatment; however, it is associated with a risk of developing cardiotoxicity, which most often manifests in myocardial contractile dysfunction or an increased risk of thromboembolic events. Heart failure is observed in 2–4% of patients treated with bevacizumab and in 3–8% of patients on antiangiogenic tyrosine kinase inhibitors. The proposed pathomechanisms underlying the impairment in systolic function during antiangiogenic drug treatment include mitochondrial dysfunction, a secondary reduction in cardiomyocyte aTP production and redox imbalance, which may contribute to pathological states known as “free radical diseases”. additionally, therapy with angiogenesis inhibitors may also cause cardiac oxidative stress. The risk factors for cardiac complications include arterial hypertension, which is a known “class effect” of this class of drugs, as well as a number of other factors such as age, comorbidities, prior radiotherapy and baseline left ventricular ejection fraction. The cardiovascular diseases are still the first cause of death in the world. The more effective oncological treatment becomes, the more often comorbidities occur. This fact seems to demand interdisciplinary approach from investigators and practitioners. This article presents the current state of knowledge on the molecular mechanisms of cardiotoxicity of antiangiogenic drugs used in routine clinical practice.
Studying potential PKCδ loss of function mutation and its downstream effects in gastric cancer progression

PKC isozymes are involved in the modulation of cellular pathways related with tumor progression, acting as a suppressor or promoter. In cancer cells, PKCs are mutated, and most common type is loss of function. This paper focuses on the effect of PKCδ mutation in gastric cancer. LOF mutation occurs throughout catalytic and kinase domains of PKCδ, disrupting activation and function of kinase. In catalytic domain, there are various potential mutation targets, such as binding groove and zinc finger. Mutation residues detected in the kinase domain, such as DFG and APE motifs, can alter catalytic function, causing interruption of activation. Also, a critical region, called hinge region, modulates caspase-3 dependent cleavage, and such tyrosine mutation in this region reduces cleavage activity, inhibiting fully activation of kinase. Importantly, LOF mutation affects cellular activity of downstream protein, p53, through inhibiting transcription, localization, and phosphorylation. For instance, C1 domain mutant suppresses binding capacity with p53, reducing transcription of p53. Disruption of cellular component, tight junction, assembling related to PKC mutation. As identified, PKCδ correlates with ZO-1, and LOF mutation prevent translocation of ZO-1 to TJ area, leading to errors in TJ assembling, promoting tumor invasion.
A Novel Dynamic and Fuzzy Value Stream Mapping (DFVSM): System Dynamics and Fuzzy Logic Integration

Value stream mapping (VSM) is a method to identify waste and activities that do not add value. One of its main disadvantages is that the parameters used in the process and material flows are deterministic. The motivation of this research is to improve the reliability of the estimation of the lead time in VSM, transitioning from a static model to a dynamic model that incorporates uncertainty and imprecision in the data, as well as to develop a novel dynamic and fuzzy value stream mapping (DFVSM) based on integrating system dynamics and fuzzy logic. One of the main contributions of this research is to develop a fuzzy system in the same system dynamics interface that incorporates uncertainty and vagueness to the efficiency and effectiveness percentage variable (OEE%) to increase the reliability of the delivery time planning. The stages of DFVSM are explicitly described and applied to real data for a textile company in southern Guanajuato. A sensitivity analysis of the proposed model was integrated which identifies the critical factors for the delivery of the order, and achievable times were proposed for the delivery times of the supplier and the client, thus reducing the expected delivery time by 28%. One of the relevant conclusions of this work is that, to plan the lead time of an order, the uncertainty of the main parameters such as supplier and customer shipping times be considered to satisfy the customer.
A Dirty Waste—How Renewable Energy Policies Have Financed the Unsustainable Waste-to-Energy Industry

The end of the 20th Century saw a major shift in the United States’ approach to energy policy. After decades focused on fossil fuel production, the country began to realize that renewable sources of energy were the way of the future. Motivated by environmental concerns and a realization that oil is a finite resource, the federal government and local governments began adopting economic policies that rewarded investment in and production of renewable, clean technology. Governments relied on both mandates and tax incentives to encourage the use of energy from sources like solar and wind power. Wasteto-Energy (“WTE”) power is another form of energy production that is classified as renewable. Thus, WTE has benefited significantly from renewable energy policies. WTE, however, is a form of energy produced by burning trash and is neither environmentally friendly nor particularly sustainable. Yet, the WTE industry owes its existence to those government programs designed to fund sustainable sources of electricity. With WTE drawing from the same pot of government resources, the policies that were written to stimulate the sustainable energy field and protect the environment have undermined those very goals by subsidizing the WTE industry. This Note summarizes the WTE process and the laws that allowed it to grow, argues that WTE is not economically sound or environmentally sustainable, and proposes legislative changes to prevent more harm from WTE in the future.
Multilinear model decomposition and predictive control of MIMO two-block cascade systems

This paper presents a new multilinear model decomposition method for multiple-input multiple-output (MIMO) two-block cascade systems and a model predictive control (MPC) algorithm for the resulting representation. First, a normal vector included angle division method is developed to decompose the operating space and determine the minimum linear model bank through evaluating the nonlinearity of the steady-state I/O surfaces. For a prescribed angle threshold, the minimum linear model bank can be constructed to approximate the original two-block cascade system sufficiently closely. Next, a multilinear MPC algorithm is designed with the proposed trajectory scheduling technique, which can reduce output oscillations caused by hard switching and avoid the difficulty of calculating/tuning complex weighting functions/parameters used in soft switching. A benchmark chemical reactor process is studied to illustrate the effectiveness and advantages of the proposed decomposition method and the predictive control algorithm.
Electrical Transport and Magnetic Properties of PbTiO3/SrRuO3 superlattices

Artificially structured oxides present exciting opportunities to design materials with specified or novel properties [1,2]. With advanced epitaxial growth techniques, multicomponent perovskite heterostructure with desired dielectric, ferroelectric and magnetic behavior can be achieved experimentally. Currently, we have successfully fabricated PbTiO3/SrRuO3 (PTO/SRO) superlattices with ultra thin SrRuO3 layers through RF magnetron off-axis sputtering [3]. The superlattice thin films (100nm) with top and bottom SrRuO3 electrodes were deposit on a TiO2 terminated SrTiO3 substrate. The structure and quality of the films were examined through transmission electron microscope (HRTEM), X-ray diffraction (XRD) and atomic force microscopy (AFM). In addition, the electrical properties were obtained using a home-built probe station, and the magnetocapacitance measurement of the samples is done with a superconducting magnet system.
A Mesoscopic Traffic Data Assimilation Framework for Vehicle Density Estimation on Urban Traffic Networks Based on Particle Filters

Traffic conditions can be more accurately estimated using data assimilation techniques since these methods incorporate an imperfect traffic simulation model with the (partial) noisy measurement data. In this paper, we propose a data assimilation framework for vehicle density estimation on urban traffic networks. To compromise between computational efficiency and estimation accuracy, a mesoscopic traffic simulation model (we choose the platoon based model) is employed in this framework. Vehicle passages from loop detectors are considered as the measurement data which contain errors, such as missed and false detections. Due to the nonlinear and non-Gaussian nature of the problem, particle filters are adopted to carry out the state estimation, since this method does not have any restrictions on the model dynamics and error assumptions. Simulation experiments are carried out to test the proposed data assimilation framework, and the results show that the proposed framework can provide good vehicle density estimation on relatively large urban traffic networks under moderate sensor quality. The sensitivity analysis proves that the proposed framework is robust to errors both in the model and in the measurements.
A Benchmark for Management Effectiveness

This study presents a tool to gauge managerial effectiveness in the form of a questionnaire that is easy to administer and score. The instrument covers eight distinct areas of organisational climate and culture of management inside a company or department. Benchmark scores were determined by administering sample-surveys to a wide cross-section of individuals from numerous firms in Southeast Louisiana, USA. Scores remained relatively constant over a seven-year timeframe. Techniques for using the benchmark by practitioners are discussed.
Low-Complexity Heuristic Algorithm for Power Allocation and Access Mode Selection in M2M Networks

A hybrid or coexisting orthogonal frequency-division multiple access (OFDMA) and nonorthogonal multiple access (NOMA) scheme is a promising approach to greatly enhance network capacity and reduce the interference in machine-to-machine (M2M) communication networks. In this article, we study the power allocation and access mode selection problem of machine-type communication devices (MTCDs), which are allowed to transmit their data packets to the base station (BS) in direct transmission mode (DTM) or cluster head forwarding mode (CHFM). Considering the transmit power optimization and data rate maximization of the MTCDs, we formulate the power allocation and access mode selection problem as a sum-rate maximization problem. Since the original maximization problem is a nonlinear fractional problem that cannot be solved conveniently, we transform the optimization problem into two subproblems, i.e., power allocation subproblem and access mode selection subproblem. The power allocation subproblem is solved for both OFDMA and NOMA schemes by applying the Lagrange dual method. To solve the access mode selection subproblem, we further divide the subproblem into DTM subproblem and CHFM subproblem and solve these subproblems successively. In particular, for the solution of the CHFM subproblem, we first propose a greedy method-based algorithm, and then, to tackle the issue of high computational complexity, we present a low complexity heuristic algorithm. In the end, we present simulation results to demonstrate the effectiveness of the proposed algorithms.
Do Price Judgments Always Influence Choice? the Effects of Retailer Discount Frequency and Depth

Consumers’ perceptions of retailers’ prices are affected by the depth and frequency of their discounts (Alba et al. 1999; Lalwani and Monroe, 2005). In past research, prices for depth and frequency retailers were revealed and their effect on price perceptions examined. We instead examine the effect of frequency and depth on retailer choice when respondents only see prices for the chosen retailer. Respondents’ buy more often from retailers offering frequent shallow discounts than from those offering deep infrequent discounts, though perceived price is lower for the latter. Choice is more strongly associated with perceived price fairness than with perceived average price.
PrivFace: Fast Privacy-Preserving Face Authentication With Revocable and Reusable Biometric Credentials

Privacy concerns of using sensitive biometric data as credentials arise with the wide adoption of user-friendly face authentication. To protect the facial features of users, two important functions, i.e., <italic>revocability</italic> and <italic>reusability</italic>, are anticipated to be realized in a privacy-preserving face authentication design. Revocability requires an effective approach to deregister or replace user credentials when the authentication server is compromised; For reusability, the same credentials should appear independently to non-cooperating applications. Accomplishing these two properties is challenging as the uniqueness of facial features. In this article, we present <sc>PrivFace</sc>, a fast privacy-preserving face authentication, supporting revocable, and reusable biometric credentials. The core innovation is a novel secure inner product protocol that employs a lightweight random masking technique instead of time-consuming public-key cryptographic operations to efficiently measure facial data similarity. We rigorously analyze the security to show that the server cannot acquire the user's sensitive biological features during the authentication. Our experiment with real-world datasets shows that <sc>PrivFace</sc> is friendly to edge smart devices, which takes less than <inline-formula><tex-math notation="LaTeX">$100 ms$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>100</mml:mn><mml:mi>m</mml:mi><mml:mi>s</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="liu-ieq1-3083970.gif"/></alternatives></inline-formula> per successful authentication on a common smartphone and outperforms the prior art J. Lei, Q. Pei <italic>et al.</italic> [1]. by <inline-formula><tex-math notation="LaTeX">$20 \times$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>20</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="liu-ieq2-3083970.gif"/></alternatives></inline-formula>. We have made the relevant codes open-source to the community for further research.
User Interfaces for Optimized Reverse Image Search

In this project, we build and evaluate a reverse image search engine that takes an image as query and returns a ranked list of images sharing similar visual properties and class labels. We explore two main research questions: how traditional image processing techniques compare to a convolutional neural model for image retrieval, and how designs can facilitate searching and improve user experiences for image search engines. A breakdown of our process includes processing the query image to extract key features, searching in a database for relevant images based on these features, and displaying a ranked list of results with a user-friendly mobile interface.
Gravity model and Pakistan - China Trade

Pakistan being an important ally of the war against terror paying huge price of not merely of innocent lives of people but huge monetary losses in many sectors of economy, one lucrative sector is international trade. Pakistan’s export potential has undergone strenuous pressures to perform according to the past performance. There was a need to reveal new export potential and lucrative sectors of economy with recommended policy changes so that new paradigm change in international trade can be initiated. This empirical study carried to meet the objective in which gravity model is used for investigating the bilateral trade between Pakistan and China. This model is being used extensively by the researchers worldwide to make predictions about volume of international trade to suggest the policy changes in international trade management. The findings confirm that the tariff rates significantly and negatively affects the Export Volume from Pakistan to China as t-stats > 1.5 which results the trade deficit to be increased, while the affinity (i.e. bilateral visits of people of Pakistan and China to each other countries, bilateral dialogues between China and Pakistan, Social integrations programs between China and Pakistan etc.) between China and Pakistan and Geography (i.e. the trading countries are both in Asia with the connected borders) significantly and positively affects the Export Volume from Pakistan to China as t-stats > 1.5, thus the trade deficit is reduced due to stated affinity and geography. The large value of F-stats also reports that the relationships of export volume from Pakistan to China with all outlined stated explanatory variables/ predictors (i.e. the gravity model for bilateral trade between Pakistan and China) will remain alive for longer period of time in future.
Adsorptive removal of ammonium ion from aqueous solution using surfactant-modified alumina

Environmental context Ammonium ion, an inorganic pollutant in agricultural land, can induce eutrophication, impacting on water quality. We investigate the adsorption of ammonium ion on surfactant-modified alumina and demonstrate highly efficient removal of ammonium ions by the alumina from two agricultural water samples. Adsorption mechanisms are also proposed based on adsorption isotherms, surface modification and the change in surface charge. Abstract The adsorptive removal of ammonium ions (NH4+) from aqueous solution using surfactant-modified alumina (SMA) was investigated. The optimum NH4+ adsorption removal conditions on SMA were systematically studied and found to be pH 4, contact time 180min, adsorbent dosage 30mgmL–1 and ionic strength 1mM NaCl. The equilibrium concentration of NH4+ was measured by capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D) and spectrophotometry. Surface modification of α-Al2O3 with the anionic surfactant sodium dodecyl sulfate (SDS) at high salt concentration induced a significant increase of removal efficiency. The change in surface charge and surface modification of α-Al2O3 by pre-adsorption of SDS and subsequent adsorption of NH4+ were evaluated by zeta potential measurements and Fourier-transform infrared spectroscopy. Under optimum adsorption conditions, NH4+ removal from two agricultural water samples achieved very high removal efficiencies of 99.5 and 96.5%. The adsorption of NH4+ onto SMA increases with decreasing NaCl concentration because desorption of SDS from the α-Al2O3 surface is minimised. Experimental results of NH4+–SMA adsorption isotherms at different ionic strengths can be represented well by a two-step adsorption model. Based on adsorption isotherms, surface charge effect and surface modification, we suggest that the adsorption mechanism of NH4+ onto SMA was mainly electrostatic attraction between cationic NH4+ and the negatively charged SMA surface.
Characteristic Excitation Wavelength Dependence of Fluorescence Emissions in Carbon "quantum" Dots

Carbon “quantum” dots (CDots), generally defined as small carbon nanoparticles with various surface passivation schemes, have emerged to represent a rapidly advancing and expanding research field. CDots are known for their bright and colorful fluorescence emissions, where the colorfulness is associated with the emissions being excitation wavelength dependent. In this work, CDots with 2,2′-(ethylenedioxy)bis(ethylamine) (EDA) for surface functionalization were studied systematically by using steady-state and time-resolved fluorescence methods. The observed fluorescence quantum yields are strongly excitation wavelength dependent, and the dependence apparently tracks closely the observed absorption profile of the EDA-CDots, whereas the excitation wavelength dependence of observed fluorescence lifetimes is much weaker, obviously decoupled from the quantum yields. Mechanistically, the presence of two sequential processes immediately following the photoexcitation of CDots leading to fluorescence is used to rati.
CHILDREARING CHALLENGES IN PARENTAL ADHD: A PILOT

An emerging body of research on the functional impairments of Attention-Deficit/Hyperactivity Disorder (ADHD) in adults notes that parents with ADHD are likely to experience challenges in several facets of childrearing (e.g., Chronis-Tuscano et al., 2008a; Murray & Johnston, 2006). Despite empirical evidence suggesting parents with ADHD have particular kinds of struggles, research evaluating the effects of adult ADHD treatment on parenting challenges is quite scarce. By contrast, a breadth of research indicates that adult ADHD interventions, particularly pharmacotherapy and cognitive-behavioral therapy (CBT), are effective in ameliorating ADHD symptoms. Further, CBT has shown to be an efficacious adjunctive treatment for ADHD and is associated with improvements in global functioning among ADHD-adults (e.g., Safren et al., 2005; Weiss et al., 2012). This dissertation proposes a conceptual framework outlining the mechanisms by which combined pharmacotherapy and CBT would be an effective treatment plan to address parenting challenges in adult ADHD. A small pilot study was conducted comparing parenting ratings between ADHD-parents and non-ADHD controls. The results of the pilot study are presented in the context of providing groundwork for a proposed randomized controlled trial to compare the efficacy of pharmacotherapy and combined treatment to treat parenting difficulties in adult ADHD. The implications and limitations of the pilot study, as well as anticipated implications and limitations of the theorized research, are discussed.