nils-herrmann/clean_scirepeval huggingface dataset:
Does low self esteem predict depression and anxiety? A meta analysis of longitudinal studies.
Venue: Psychological bulletin
Year: 2013

Low self esteem and depression are strongly related, but there is not yet consistent evidence on the nature of the relation. Whereas the vulnerability model states that low self esteem contributes to depression, the scar model states that depression erodes self esteem. Furthermore, it is unknown whether the models are specific for depression or whether they are also valid for anxiety. We evaluated the vulnerability and scar models of low self esteem and depression, and low self esteem and anxiety, by meta analyzing the available longitudinal data (covering 77 studies on depression and 18 studies on anxiety) The mean age of the samples ranged from childhood to old age. In the analyses, we used a random effects model and examined prospective effects between the variables, controlling for prior levels of the predicted variables. For depression, the findings supported the vulnerability model: The effect of self esteem on depression (b .16) was significantly stronger than the effect of depression on self esteem (b .08) In contrast, the effects between low self esteem and anxiety were relatively balanced: Self esteem predicted anxiety with b .10, and anxiety predicted self esteem with b .08. Moderator analyses were conducted for the effect of low self esteem on depression; these suggested that the effect is not significantly influenced by gender, age, measures of self esteem and depression, or time lag between assessments. If future research supports the hypothesized causality of the vulnerability effect of low self esteem on depression, interventions aimed at increasing self esteem might be useful in reducing the risk of depression.
Analysis and Design of a Millimeter Wave Cavity Backed Circularly Polarized Radiator Based on Fundamental Theory of Multi Port Oscillators
Venue: IEEE Journal of Solid State Circuits
Year: 2017

This paper presents the design and implementation of a millimeter wave fundamental frequency circularly polarized radiator, which employs a multi port cavity as the core of a high <inline formula> <tex math notation="LaTeX"$Q$ /tex math>/inline formula> resonator, a power combiner, and an antenna. A general theory of multi port oscillators and in particular, the widely used circularly symmetric oscillator topologies is presented, which quantitatively investigates and predicts all possible oscillation states, their associated modes of operation, and the oscillation stability. The outcomes of this theory are utilized to design a power optimized eight port rotationally symmetric radiator, excited at the oscillation state with a 45 phase difference between the adjacent ports, which, in turn, enables a high efficiency circularly polarized radiation. Fabricated in 0.13 <inline formula> <tex math notation="LaTeX"\mu \text{m} /tex math>/inline formula> BiCMOS process, this cavity backed circularly polarized radiator operates at the frequency of 114 GHz and achieves 14.2 dBm equivalent isotropic radiated power (EIRP) 5.2% dc to EIRP conversion efficiency, 8.2 dBm radiated power, 1.3% dc to radiation efficiency, and 99.3 dBc/Hz phase noise at 1 MHz offset, without using silicon lens.
A cross sectional assessment of the long term effects of brief strategic family therapy for adolescent substance use.
Venue: The American journal on addictions
Year: 2015

Young adult drug use and law breaking behaviors often have roots in adolescence. These behaviors are predicted by early drug use, parental substance use disorders, and disrupted and conflict ridden family environments.  To examine long term outcomes of Brief Strategic Family Therapy (BSFT) compared to treatment as usual (TAU) in the rates of drug use, number of arrests and externalizing behaviors in young adults who were randomized into treatment conditions as adolescents.  261 of 480 adolescents who had been randomized to BSFT or TAU in the BSFT effectiveness study were assessed at a single time, 3 7 years post randomization.  Assessments of drug use, externalizing behaviors, arrests and incarcerations were conducted using Timeline Follow Back, Adult Self Report, and self report, respectively. Drug use, arrests and incarcerations were examined using negative binomial models and externalizing behaviors were examined using linear regression.  When compared with TAU, BSFT youth reported lower incidence of lifetime (IRR 0.68, 95%CI [0.57, 0.81] and past year (IRR 0.54, 95%CI [0.40, 0.71] arrests; lower rates of lifetime (IRR 0.63, 95%CI [0.49, 0.81] and past year (IRR 0.70, 95%CI [0.53, 0.92] incarcerations; and lower scores on externalizing behaviors at follow up (B 0.42, SE .15, p .005) There were no differences in drug use.  BSFT may have long term effects in reducing the number of arrests, incarcerations and externalizing problems. These effects could be explained by the improvements in family functioning that occurred during the effectiveness study. This study contributes to the literature by reporting on the long term outcomes of family therapy for adolescent drug abuse.
Improving hole cleaning using low density polyethylene beads at different mud circulation rates in different hole angles
Year: 2019

In oil and gas exploration and development, drilling a hole is one of the first and most expensive operations. The continuous demand from industry to reduce costs and operational problems has resulted in numerous innovative drilling technologies that allow us to drill directionally. Nevertheless, hole cleaning has become a problematic issue in directional drilling because drill cuttings tend to be deposited on the lower side of the deviated hole. Excess accumulation of cuttings significantly reduces the rate of penetration and indirectly increases the operational cost. To improve the cuttings transport efficiency in a deviated hole, low density polyethylene (LDPE) beads were introduced into water based mud for hole cleaning. LDPE beads travel rapidly through the mud column due to buoyancy and move the cuttings forward by drag and collision. The interaction between the LDPE beads and cuttings facilitates the cuttings transport process and prevents the cuttings from settling. In this study, different concentrations of LDPE beads (i.e. 1% to 5% by volume) and different flow rates (i.e. 0.4 L/s, 0.6 L/s, and 1.0 L/s) were used to determine the effects on cuttings transport efficiency. In addition, the hole angle was varied from vertical to horizontal to evaluate the significance of LDPE beads in assisting in transporting cuttings. The results denote that more cuttings can be removed from a hole with higher concentrations of LDPE beads in water based mud. This finding is due to the higher frequency of collisions, which in turn produces larger impulsive force. In addition, the improvement in cuttings transport efficiency enabled by LDPE beads is more significant in a vertical hole than in a highly deviated hole. In summary, LDPE beads are a promising additive for drilling mud to effectively remove drilled cuttings from a hole.
Growth of large size SnSe crystal via directional solidification and evaluation of its properties
Year: 2020

SnSe crystal is an attractive IV VI thermoelectric (TE) material. In this work, a O25 x 50 mm3 SnSe crystal was prepared using a directional solidification method. The as grown crystal has standard Pnma structure at room temperature. The band gap Eg is determined to be 0.96 eV which agrees well with the theoretical value. Thermal expansion measurements show that SnSe crystal has significant anisotropic expansion behaviors. The linear thermal expansion along and directions are positive but is negative in direction. Pnma Cmcm phase transition has remarkable influence on thermal expansion performance. The electronic and thermal transport properties of SnSe crystal along (100) plane are investigated. It is found the highest power factor PF 6.20 mWcm 1K 2 and the lowest total thermal conductivity ktot 0.46 W/m K both occur near Pnma Cmcm phase transition temperature. Finally, the maximum ZT 1.05 appears around 800 K suggesting SnSe crystal is a candidate for middle temperature TE material.
CNN based Camera Model Classification and Metric Learning Robust to JPEG Noise Contamination
Venue: 2020 11th International Conference on Awareness Science and Technology (iCAST)
Year: 2020

Pattern noise based source camera identification is a promising technology for preventing crimes such as illegal uploading and secret photography. In order to identify the source camera model of an input image, recently, highly accurate camera model classification methods based on convolutional neural networks (CNNs) have been proposed. However, the pattern noise in an image is typically contaminated by JPEG compression, and the degree of contamination depends on the quality factor (Q Factor) Therefore, it could be that JPEG compression of different Q factors from that of training samples degenerates the accuracy for CNN based camera model classification. In this paper, we propose a CNN based camera model classification and metric learning trained with the JPEG base a noise suppression technique. In the experiments, we evaluate camera model classification accuracy and metric learning performance for various Q Factors. We demonstrate that JPEG based noise suppression improves camera model classification accuracy from 87.25% to 99.89% on average. We also demonstrate JPEG based noise suppression improves the robustness of metric learning to JPEG contamination.
Network Synchronization and Localization Based on Stolen Signals
Venue: SIROCCO
Year: 2011

We consider an anchor free, relative localization and synchronization problem where a set of n receiver nodes and m wireless signal sources are independently, uniformly, and randomly distributed in a disk in the plane. The signals can be distinguished and their capture times can be measured. At the beginning neither the positions of the signal sources and receivers are known nor the sending moments of the signals. Now each receiver captures each signal after its constant speed journey over the unknown distance between signal source and receiver position. Given these nm capture times the task is to compute the relative distances between all synchronized receivers. In a more generalized setting the receiver nodes have no synchronized clocks and need to be synchronized from the capture times of the stolen signals. For unsynchronized receivers we can compute in time O(nm) an approximation of the positions and the clock offset within an absolute error of O(logm/m) with probability 1 m c e c'n (for any c O(1) and some c 0) For synchronized receivers we can compute in time O(nm) an approximation of the correct relative positions within an absolute error margin of O(log2 m/m2) with probability 1 m c e c'n. This error bound holds also for unsynchronized receivers if we consider a normal distribution of the sound signals, or if the sound signals are randomly distributed in a surrounding larger disk. If the receiver nodes are connected via an ad hoc network we present a distributed algorithm which needs at most O(nm log n) messages in total to compute the approximate positions and clock offsets for the network within an absolute error of O(logm/m) with probability 1 n c if m n.
Denoising Relation Extraction from Document level Distant Supervision
Venue: EMNLP
Year: 2020

Distant supervision (DS) has been widely used to generate auto labeled data for sentence level relation extraction (RE) which improves RE performance. However, the existing success of DS cannot be directly transferred to the more challenging document level relation extraction (DocRE) since the inherent noise in DS may be even multiplied in document level and significantly harm the performance of RE. To address this challenge, we propose a novel pre trained model for DocRE, which denoises the document level DS data via multiple pre training tasks. Experimental results on the large scale DocRE benchmark show that our model can capture useful information from noisy DS data and achieve promising results.
Employee Innovation Process: An Integrative Model
Venue: Journal of Innovation Management
Year: 2019

Enormous research has focused on investigating innovation process in organisations but only a few are devoted to employee innovation process, thus limiting our understanding of how to organise, foster and successfully manage employee innovation process in organisation. Drawing from the literature, this study extends the two phase model of innovation process comprising creativity and innovation by proposing a three phase employee innovation process model that integrates innovation adoption. Using stratified sampling technique and structured questionnaires, data were collected from 430 middle managers of four mobile telecommunication companies in Nigeria. Results of the regression and path analyses to test the hypotheses and model fit support a revised three phase employee innovation process model showing that employee creativity has direct causal effect on employee innovation and employee innovation adoption, and employee innovation has direct causal effect on employee innovation adoption. Dispositional factors have stronger direct causal effect on employee creativity than contextual factors and contextual factors have stronger direct causal effects on employee innovation than dispositional factors. Both dispositional and contextual factors have similar direct causal effects on employee innovation adoption, though dispositional factors have a stronger causal effects. The study has provided new, empirically based insights into the study of innovation process from employee unit of analysis by extending the innovation process with adoption as a phase concluding the innovation process. Implications for theory and practice are discussed.
STUDIES ON THE REMOVAL OF MALACHITE GREEN AND METHYLENE BLUE DYES FROM AQUEOUS SOLUTIONS OF THEIR BINARY MIXTURE BY ADSORBTION OVER COMMERCIAL ACTIVATED CARBON AND TAMARIND KERNEL POWDER
Year: 2012

The waste water originating from textile processing industries is a complex mixture of potentially polluting substances consisting of textile dyes, heavy metals associated with dyes and the other auxiliaries used during process. Adsorption appears to offer the best prospects for over all treatment of dye stuff effluent. As Commercial Activated Carbon used as adsorbent for adsorption is very expensive, there is a need for an alternative for it. In this context, we have planned to use Tamarind Kernel Powder (TKP) a biological waste material as a low cost adsorbent 1 Literature survey reveals that removal of various dyes using different low cost adsorbens have been carried out extensively. But a study on removal of dyes from their aqueous solution from their binary mixture is very scarce. The present work deals with combined removal of (Malachite Green Methylene Blue) dyes from the aqueous solution of their binary mixture using the low cost adsorbent Tamarind Kernel Powder (TKP) and Commercial Activated Carbon (CAC) and to compare the effectiveness of the adsorbent TKP with CAC in the removal of dyes. Variation of initial concentration, pH dose, and contact time affected the adsorption process. From the results of present study, we can conclude that adsorption processes are applicable for adsorption of dyes from aqueous solution of their binary mixture. TKP can be used as low cost adsorbent as an alternative adsorbent to CAC in waste water treatment for the removal of dyes. We find that TKP has an efficiency comparable to that of CAC, expect for the optimum dose.
How the Facebook Arabic Page "We Are All Khaled Said" Helped Promote the Egyptian Revolution
Year: 2015

This study analyzes how the owner of the Facebook Arabic page "We Are All Khaled Said" both catalyzed and took advantage of opportunities in the Egyptian political climate in order to help promote the country's 2011 revolution. Using a content analysis of posts on the Facebook page before and throughout the Egyptian revolution, the case study finds that the owner of the page, Wael Ghonim, served as a long term trainer or coach, educating his online followers about the abuses of Egyptian President Hosni Mubarak's regime and helping them gradually become more comfortable with political activism, so that when a triggering event the Tunisian revolution occurred, he was able to move his followers into the streets to protest. Two other particularly successful tactics were utilized by Ghonim: He capitalized on a powerful personal story that of a young man brutally killed by the police in order to elicit emotion and help others identify with the cause, and he used lofty rhetoric to convince his followers that their actions could actually make a difference. The case study disproves Gladwell's (2010) claim that social media is a platform for shallow and networked interactions, finding both that the grievances and ideas shared on this page were remarkably substantive and that the movement was not a network but rather a hierarchy, led by Ghonim until his imprisonment. The study suggests that social media is a more powerful platform for promoting political change than previously appreciated and offers important lessons for political activists.
Promises and Endogenous Reneging Costs
Year: 2017

We present a novel theoretical mechanism that explains the capacity for non enforceable communication about future actions to improve efficiency. We explore a two player partnership game where, before choosing a level of effort to exert on a joint project, each player makes a cheap talk promise to their partner about their own future effort. We allow agents to incur a psychological cost of reneging on their promises. We demonstrate a strong tendency for evolutionary processes to select agents who incur intermediate costs of reneging, and show that these intermediate costs induce second best optimal outcomes.
Pre Intensive Care Unit Cognitive Status, Subsequent Disability, and New Nursing Home Admission among Critically Ill Older Adults
Venue: Annals of the American Thoracic Society
Year: 2018

Cognitive impairment is common among older adults, yet little is known about the association of pre intensive care unit cognitive status with outcomes relevant to older adults maintaining independence after a critical illness.  To evaluate whether pre intensive care unit cognitive status is associated with post intensive care unit disability, new nursing home admission, and mortality after a critical illness among older adults.  In this prospective cohort study, 754 persons aged 70 years or more were monitored from March 1998 to December 2013 with monthly assessments of disability. Cognitive status was assessed every 18 months, using the Mini Mental State Examination (range, 0 30) with scores classified as 28 or higher (cognitively intact) 24 27 (minimal impairment) and less than 24 (moderate impairment) The primary outcome was disability count (range, 0 13) assessed monthly over 6 months after an intensive care unit stay. The secondary outcomes were incident nursing home admission and time to death after intensive care unit admission. The analytic sample included 391 intensive care unit admissions.  The mean age was 83.5 years. The prevalence of moderate impairment, minimal impairment, and intact cognition (the comparison group) was 17.3, 46.2, and 36.5% respectively. In the multivariable analysis, moderate impairment was associated with nearly a 20% increase in disability over the 6 month follow up period (adjusted relative risk, 1.19; 95% confidence interval, 1.04 1.36) and minimal impairment was associated with a 16% increase in post intensive care unit disability (adjusted relative risk, 1.16; 95% confidence interval, 1.02 1.32) Moderate impairment was associated with more than double the likelihood of a new nursing home admission (adjusted odds ratio, 2.37; 95% confidence interval, 1.01 5.55) Survival differed significantly across the three cognitive groups (log rank P 0.002) but neither moderate impairment (adjusted hazard ratio, 1.19; 95% confidence interval, 0.65 2.19) nor minimal impairment (adjusted hazard ratio, 1.00; 95% confidence interval, 0.61 1.62) was significantly associated with mortality in the multivariable analysis.  Among older adults, any impairment (even minimal) in pre intensive care unit cognitive status was associated with an increase in post intensive care unit disability over the 6 months after a critical illness; moderate cognitive impairment doubled the likelihood of a new nursing home admission. Pre intensive care unit cognitive impairment was not associated with mortality from intensive care unit admission through 6 months of follow up. Pre intensive care unit cognitive status may provide prognostic information about the likelihood of older adults maintaining independence after a critical illness.
Data driven sustainable supply chain management performance: A hierarchical structure assessment under uncertainties
Venue: Journal of Cleaner Production
Year: 2019

This study contributes to the literature by assessing data driven sustainable supply chain management performance in a hierarchical structure under uncertainties. Sustainable supply chain management has played a significant role in the general discussion of business management. While many attributes have been addressed in prior studies, there remains no convincing evidence that big data analytics improve the decision making process regarding sustainable supply chain management performance. This study proposes applying exploratory factor analysis to scrutinize the validity and reliability of the proposed measures and uses qualitative information, quantitative data and social media applied fuzzy synthetic method decision making trial and evaluation laboratory methods to identify the driving and dependence factors of data driven sustainable supply chain management performance. The results show that social development has the most significant effect. The results also indicate that long term relationships, a lack of sustainable knowledge or technology, reverse logistic, product recovery techniques, logistical integration, and joint development are the most effective criteria for enhancing sustainable supply chain management performance. The theoretical and managerial implications are discussed.
Processing algorithms for quantum remote sensing image data
Venue: Optical Engineering Applications
Year: 2019

Since Professor Siwen Bi proposed quantum remote sensing (QRS) in early 2001, the first QRS imaging prototype was developed after many stages of researches. Based on the results, our group has also undertaken in depth theoretical and algorithmic experiments on QRS image processing. It's both a quantum system simulation algorithm, preparing for the future quantum physical devices and calculation technology, and an expansion of quantum theories to RS image processing fields. It combines quantum mechanics theory and RS image processing technology, which introduces a new research direction for RS image processing technology. Now our researches achievements include a quantum denoising algorithm theory and simulation, a quantum enhancement algorithm theory and simulation, and a quantum segmentation algorithm theory research and simulation. A RS denoising algorithm based on the quantum inspired concept is proposed for image denoising. Key benefits of the algorithm, which include improvements in transmission and accuracy, are demonstrated experimentally. Experiments showed that the peak signal to noise ratio (PSNR) for the proposed algorithm is improved by over 2dB and the edge retention index (EPI) is 0.1 higher than that for common methods. Given the low contrast ratio and brightness as well as insufficient detail for some RS images, a quantum algorithm based on the combination of a quantum inspired and unsharp masking to enhance and segment the RS image data was proposed. Results showed that the contrast ratio and brightness of images processed by the quantum algorithm improved, the image entropy and peak signal to noise ratio is higher.