Miracle-dz/UniFAR-FTUs huggingface dataset:
The Contribution of Dispersion across Plants to the Increase in US Earnings Dispersion 1

Using an extensive set of establishment and individual data, we estimate the extent to which the variance of earnings among establishments increased in 1977-2002 and its contribution to the increased dispersion of US earnings among individuals. We find that more than 70 percent of the increase in the variance of earnings in this period occurred across establishments. More than two thirds of the growth in establishment wage dispersion arises from changes within detailed industry and region. Two industries contributed disproportionately to earnings inequality. Business services accounted for a growing share of the total variance in log earnings across plants, while the increased variance in earnings in finance, insurance, and real estate accounted for one-fifth of the growth in variance in the whole economy. Decomposing the increase in earnings among establishments between rising inequality among existing establishments and changes in inequality due to the earnings of establishments that enter or exit the economy we find that the bulk of the increase occurred among existing establishments. We reject explanations that attribute the increase in the variance among establishments to increased returns to human capital or increased sorting of observable skills across plants. The factor most closely related to the increased dispersion in earnings across plants is the increase in the dispersion in labor productivity among plants. Evidence of rent sharing and of the growing importance of inter establishment wage dispersion run, given the declining strength of union, counter to the usual analysis of wage-setting in a competitive market. JEL Codes: J3; J31; D3
On the (in)feasibility of fine grained power control

Spectral efficiency has been a major focus of research in wireless networks. Recent theoretical work has shown that ideal medium access protocol using optimal power control can improve channel utilization by up to a factor of √ρ, where ρ is the density of nodes in the region [1]. Although power control mechanisms have been extensively studied in theory and simulations, their practical evaluation has not been done throughly. Most of the power control mechanisms proposed in literature [3, 4, 5] assume a very fine grained handle on transmit power of wireless nodes and exercise this control to provide sophisticated mechanisms of sharing wireless medium among competing flows. In this work, we investigate the (in)feasibility of fine-grained power control in wireless networks using real testbed experiments. We perform detailed experiments to highlight fundamental issues with power control mechanisms, that cannot be captured by using a network simulator. Our experiments indicate that fine grained power control may not be a viable solution for indoor wireless networks and most power control mechanisms may need to be adapted to be suitable for practical settings.
The Research of Route Planning Approach for Flight

In recent years, the use of aircrafts has increased alongside economic development. To make optimal use of this transportation mode, flight route planning must be conducted to minimize route distance, energy consumption, and enhance safety. Several predefined tracks are observed during an entire flight. In this paper, the flight route is simplified as a combination of lines and arc segments. When flying through a track point, the aircraft should make a turn first, and then move straight to the next track point. The relationship between the radius of the turning circle and the route distance is discussed in different situations. A conclusion is derived from analyzing the turning radius and the total distance that the aircraft has to fly. A route planning approach to the flight route is proposed in this study, wherein an appropriate radius of the turning circle is identified according to the current aircraft state. The intersection of the consecutive line and arc segment is computed to obtain the distance between two track points. The route planning approach terminates when the aircraft arrives at the designated destination.
Lithium Aluminosilicate Residue as Raw Material in the Production of Sustainable Concrete Masonry Units: A Brazilian Case

Spodumene (LiAlSi2O6) is a natural occurring mineral which is processed to produce lithium carbonate (LiCO3) and lithium hydroxide (LiOH), both used for several industrial and medical applications. The processing of spodumede generates a lithium aluminosilicate residue with no commercial value in Brazil, which is therefore landfilled. This paper studied the effect of the partial replacement of Portland cement (PC) in the production of sustainable concrete masonry units (CMU) for construction. The residue was thoroughly characterized and its interaction with PC was also assessed. Several mixes of CMU were manufactured and compared with a reference mix (without residue). Results indicated that the lithium aluminosilicate is highly reactive and may replace PC in the concrete formulations.
A Survey on Design Approaches to Circumvent Permanent Faults in Networks-on-Chip

Increasing fault rates in current and future technology nodes coupled with on-chip components in the hundreds calls for robust and fault-tolerant Network-on-Chip (NoC) designs. Given the central role of NoCs in today’s many-core chips, permanent faults impeding their original functionality may significantly influence performance, energy consumption, and correct operation of the entire system. As a result, fault-tolerant NoC design gained much attention in recent years. In this article, we review the vast research efforts regarding a NoC’s components, namely, topology, routing algorithm, router microarchitecture, as well as system-level approaches combined with reconfiguration; discuss the proposed architectures; and identify outstanding research questions.
High accuracy patient-image registration using ultrasonography

In point-based registration between the patient and the image, skin -affixed fiducial markers can only be attached to the patient skin. Registration accuracy is relatively high in the region around the markers. However, the accuracy gradually decreases proportionally to the distance from the surface where the markers are attached. To decrease the target registration error (TRE) rather than the fiducial registration error (FRE) around the target, reference points should be located near the target organ. In order to decrease the TRE, a method is proposed that makes it possible to register an anatomical landmark as a reference point around the target using ultrasonography.
Role of clinical questionnaires in optimizing everyday care of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a leading cause of disability in all its stages, and death in patients with moderate or severe obstruction. At present, COPD is suboptimally managed; current health is often not measured properly and hardly taken into account in management plans, and the future risk for patients with regard to health status and quality of life is not being evaluated. This review addresses the effect of COPD on the lives of patients and examines ways in which existing assessment tools meet physicians’ needs for a standardized, simple method to measure consistently the full impact of COPD on patients in routine clinical practice. Current assessment of COPD severity tends to focus on airflow limitation, but this does not capture the full impact of the disease and is not well correlated with patient perception of symptoms and health-related quality of life. Qualitative studies have demonstrated that patients usually consider COPD impact in terms of frequency and severity of symptoms, and physical and emotional wellbeing. However, patients often have difficulty expressing their disease burden and physicians generally have insufficient time to collect this information. Therefore, it is important that methods are implemented to help generate a more complete understanding of the impact of COPD. This can be achieved most efficiently using a quick, reliable, and standardized measure of disease impact, such as a short questionnaire that can be applied in daily clinical practice. Questionnaires are precision instruments that contribute sensitive and specific information, and can potentially help physicians provide optimal care for patients with COPD. Two short, easy-to-use, specific measures, ie, the COPD Assessment Test and the Clinical COPD Questionnaire, enable physicians to assess patients’ health status accurately and improve disease management. Such questionnaires provide important measurements that can assist primary care physicians to capture the impact of COPD on patients’ daily lives and wellbeing, and improve long-term COPD management.
A GMDH-Based Traffic Flow Forecasting Model

Traffic flow forecasting, the core element of intelligent transportation system, plays an important role in traffic information services and traffic guidance. Since neural network prediction needs plenty of training samples, it cannot guarantee the real-timeness of traffic flow forecasting. In this paper, a GMDH network was constructed by self-organization, and the network was applied to traffic flow forecasting, hence a GMDH-based traffic flow forecasting model. Owing to the fact that a GMDH network is trained without much prior knowledge, and the network structure is characterized by self-organization and globallyoptimal selection, a short-time prediction model by the network has a good performance. The model was simulated with MATLAB, and the simulative results indicated that the model was the right tool for datafitting. The average relative error of prediction was only 3.35%, and the model was valid.
Signatures of Selection in the Genomes of Commercial and Non-Commercial Chicken Breeds

Identifying genomics regions that are affected by selection is important to understand the domestication and selection history of the domesticated chicken, as well as understanding molecular pathways underlying phenotypic traits and breeding goals. While whole-genome approaches, either high-density SNP chips or massively parallel sequencing, have been successfully applied to identify evidence for selective sweeps in chicken, it has been difficult to distinguish patterns of selection and stochastic and breed specific effects. Here we present a study to identify selective sweeps in a large number of chicken breeds (67 in total) using a high-density (58 K) SNP chip. We analyzed commercial chickens representing all major breeding goals. In addition, we analyzed non-commercial chicken diversity for almost all recognized traditional Dutch breeds and a selection of representative breeds from China. Based on their shared history or breeding goal we in silico grouped the breeds into 14 breed groups. We identified 396 chromosomal regions that show suggestive evidence of selection in at least one breed group with 26 of these regions showing strong evidence of selection. Of these 26 regions, 13 were previously described and 13 yield new candidate genes for performance traits in chicken. Our approach demonstrates the strength of including many different populations with similar, and breed groups with different selection histories to reduce stochastic effects based on single populations.
Current and Future Clinical Applications of Zinc Transporter-8 in Type 1 Diabetes Mellitus

Objective:To evaluate the utility of zinc transporter-8 (ZnT8) in the improvement of type 1 diabetes mellitus (T1DM) diagnosis and prediction, and to explore whether ZnT8 is a potential therapeutic target in T1DM. Data Sources:A search was conducted within the medical database PubMed for relevant articles published from 2001 to 2015. The search terms are as follows: “ZnT8,” “type 1 diabetes,” “latent autoimmune diabetes in adults,” “type 2 diabetes,” “islet autoantibodies,” “zinc supplement,” “T cells,” “&bgr; cell,” “immune therapy. ” We also searched the reference lists of selected articles. Study Selection:English-language original articles and critical reviews concerning ZnT8 and the clinical applications of islet autoantibodies in diabetes were reviewed. Results:The basic function of ZnT8 is maintaining intracellular zinc homeostasis, which modulates the process of insulin biosynthesis, storage, and secretion. Autoantibodies against ZnT8 (ZnT8A) and ZnT8-specific T cells are the reliable biomarkers for the identification, stratification, and characterization of T1DM. Additionally, the results from the animal models and clinical trials have shown that ZnT8 is a diabetogenic antigen, suggesting the possibility of ZnT8-specific immunotherapy as an alternative for T1DM therapy. Conclusions:ZnT8 is a novel islet autoantigen with a widely potential for clinical applications in T1DM. However, before the large-scale clinical applications, there are still many problems to be solved.
F — Band injection locked tripler based on Colpitts oscillator

This paper presents an F band injection locked frequency tripler (ILFT). The ILFT is based on transformer coupling into the resonator of differential Colpitts oscillator. The locking range of the Tripler is between 90 to 115 GHz thus achieving 24.5% locking range. Transformers are used to couple the signals in and out of the ILFT, without additional power consuming buffers. The ILFT was implemented in 90 nm CMOS process, with a maximum power consumption of the circuit is 17 mW and area of 0.284 mm2 including bond pads.
Destabilizing balanced‐budget consumption taxes in multi‐sector economies

We examine the impact of balanced-budget consumption taxes on the existence of expectations-driven business cycles in two-sector economies with infinitely-lived households. We prove that, whatever the relative capital intensity difference across sectors, aggregate instability can occur if the consumption tax rate is not too low. Moreover, we show through a numerical exercise based on empirically plausible tax rates that endogenous business-cycle fluctuations may be a source of instability for all OECD countries, including the US.
FACTORS INFLUENCING THE ADOPTION OF CLOUD COMPUTING: A REVIEW OF LITERATURE

Cloud computing reflect a new way in consuming and using IT infrastructures and IT resources. When adopting cloud computing, users are required to dismantle their current technologies, transferring the control of their IT infrastructures and data over to third party (cloud service providers). This is a distinctive departure from other information systems (IS) and information technology (IT) that has penetrated the market to date. This study reviewed and synthesizes the view of past literatures on cloud computing adoption, and suggests critical factors that need to be properly addressed by the adopting organizations leading to successful embracement of the cloud technologies. Consequently, a conceptual framework is proposed. The framework is demonstratively derived from the reviewed literature and has the potential to shed new light in the current state of knowledge on cloud computing adoption and implementation.
Inpainting using geometrical grouplets

In this paper, we propose a two-steps image inpainting algorithm that relies on geometrical grouplets. The grouplet orthogonal bases, that were introduced by Mallat in [1], are constructed with multiscale association field that groups pixels to take advantage of geometrical image regularities. These bases are used to represent the complex geometry of the image to be inpainted. Having well represented the image geometry by using geometrical grouplets, missing data are synthesized by propagating the geometrical information from outside to the inside of the inpainting zone. The first step of the algorithm consists of computing the multiscale association field and the grouplet transform of the image. In the second step, the integral curves of the association field are computed and propagated inside the inpainting zone to fill in the missing data. This step is accomplished by minimizing a functional whose role is to reconstruct the missing or damaged zone independently of the size and topology of the inpainting domain. Extensive experiments are carried out in order to validate and compare the algorithm both quantitatively and qualitatively. They show the advantages of our algorithm and its readily application to real world cases.
Application of a hybridized cuckoo search-genetic algorithm to path optimization for PCB holes drilling process

The drilling path optimization problem is a NP-hard combinatorial optimization problem. Due to complexity and exponential growth of solution space with respect to the problem size, drilling path optimization problem attracts a great interest among the academicians. In this paper, a hybrid algorithm cuckoo search with genetic algorithm (hybrid-CSGA) is applied to solve the path optimization problem for printed circuit board (PCB) holes drilling process. It is shown that hybrid-CSGA reaches the near-optimal solution much earlier than the CS and GA approach for small and large size problem instances. The computational experience conducted in this research indicates that the proposed method is robust, efficient, capable to find the best path for the PCB holes drilling path optimization problem.
CoPreTHi: A Web tool which combines transmembrane protein segment prediction methods

CoPreTHi is a Java based web application, which combines the results of methods that predict the location of transmembrane segments in protein sequences into a joint prediction histogram. Clearly, the joint prediction algorithm, produces superior quality results than individual prediction schemes. The program is available at http://o2.db. uoa.gr/CoPreTHi.
A case study on web application vulnerability scanning tools

This paper attempts to share about the tools that we used to perform vulnerability analysis within the organization. A study about background of tools that we had selected shall be elaborate in detail. As an experiment for the case study, we had performed vulnerability scanning that covered three different types of area; vulnerability scanning using different type of tools, vulnerability scanning using Nessus with different type of policy configuration and vulnerability scanning using Nessus with different time of executing the scanning. A detail description about the testing data, for example the project that we select and criteria for the scanning policy that we use will be explained. Result and finding from vulnerability scanning will be discussed in detail.
How Can Selection of Biologically Inspired Features Improve the Performance of a Robust Object Recognition Model?

Humans can effectively and swiftly recognize objects in complex natural scenes. This outstanding ability has motivated many computational object recognition models. Most of these models try to emulate the behavior of this remarkable system. The human visual system hierarchically recognizes objects in several processing stages. Along these stages a set of features with increasing complexity is extracted by different parts of visual system. Elementary features like bars and edges are processed in earlier levels of visual pathway and as far as one goes upper in this pathway more complex features will be spotted. It is an important interrogation in the field of visual processing to see which features of an object are selected and represented by the visual cortex. To address this issue, we extended a hierarchical model, which is motivated by biology, for different object recognition tasks. In this model, a set of object parts, named patches, extracted in the intermediate stages. These object parts are used for training procedure in the model and have an important role in object recognition. These patches are selected indiscriminately from different positions of an image and this can lead to the extraction of non-discriminating patches which eventually may reduce the performance. In the proposed model we used an evolutionary algorithm approach to select a set of informative patches. Our reported results indicate that these patches are more informative than usual random patches. We demonstrate the strength of the proposed model on a range of object recognition tasks. The proposed model outperforms the original model in diverse object recognition tasks. It can be seen from the experiments that selected features are generally particular parts of target images. Our results suggest that selected features which are parts of target objects provide an efficient set for robust object recognition.
The effect of parental emotional stability among Indian adolescent's psychosocial adjustment in Kerala, India

In India, the emotional stability of the parents has become an increasingly serious societal issue but unfortunately, it is not given importance within the Indian context. To help address this problem, the present study attempted to investigate the influence of perceived parental emotional stability on adolescents’ psychosocial adjustment being mediated by parental bond, family relationship, and parental self-efficacy. The results of the study found that the higher the participants’ perception of their parental emotional stability, the more positive the perception of their family relationship, the higher the perception of their parental self-efficacy and subsequently, the higher is their reported level of psychosocial adjustment. It also found that the higher the participants’ perception of their parental emotional stability, the lower the perception of their parental bonding, the higher the perception of their parental self-efficacy and subsequently, the higher is their reported level of psychosocial adjustment.
Job-shop-systems: continuous modeling and impact of external dynamics

Due to highly cross-linked material flows with various dependences the dynamics of job-shop-systems is often complex. In order to improve the understanding of these dynamics and to support the system's design, planning and control simulation is applied. Based on the discrete properties of job-shop-systems mostly discrete-event simulation (DES) is employed. However, DES entails rather high modeling efforts and is limited in its time frames. In this article we investigate the potentials of a continuous modeling approach and apply the derived model to study the impact of external market dynamics on the system's behavior and its logistics key figures.
Voice-Driven Animation

We introduce a method for learning a mapping between signals, and use this to drive facial animation directly from vocal cues. Instead of depending on heuristic intermediate representations such as phonemes or visemes, the system learns its own representation, which includes dynamical and contextual information. In principle, this allows the system to make optimal use of context to handle ambiguity and relatively long-lasting facial co-articulation effects. The output is a series of facial control parameters, suitable for driving many different kinds of animation ranging from photo-realistic image warps to 3D cartoon characters. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Information Technology Center America; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Information Technology Center America. All rights reserved. Copyright c Mitsubishi Electric Information Technology Center America, 1998 201 Broadway, Cambridge, Massachusetts 02139 Publication History:– 1. 6jul98 first circulated. 2. 26aug98 accepted to Workshop on Perceptual User Interfaces, November 1998, San Francisco 3. 21sep98 final version uploaded to workshop web site. Voice-driven animation Matthew Brand and Ken Shan MERL—a Mitsubishi Electric Research Lab 201 Broadway, Cambridge, MA, 02139 brand@merl.com