Miracle-dz/UniFAR-FTUs huggingface dataset:
A preliminary review of cyber-detection factors: offering from a systematic review

Aim The current paper aims to provide a preliminary exploration of the characteristics associated with cyber-deception, by focusing on motivations for engagement and the psychological characteristics of those perpetrating such behaviour. It aims to further outline gaps in the literature and suggest what areas any potential model of cyber-deception could include to benefit future research. Method A systematic search of 11 databases was undertaken, with additional manual searching for relevant journals and sources. This was followed by data extraction and thematic analysis. Results A total of 21 studies were identified as meeting eligibility criteria. Six motivational themes emerged (i.e. acquiring attention and sympathy; a response to negative childhood experiences; preserving identity and presenting your ‘true’ self; to cause intentional harm and to pursue personal enjoyment; to exploit materially; deception as a stress-reliever in response to life strain), and one individual theme (i.e. perpetrator personality). Conclusions Perpetrator motivation included a varied range of factors, with more static characteristics (i.e. personality) less well captured in the literature. Future research could determine if psychological differences are of value or if the area is better understand through consideration of more dynamic (motivational) factors.
The Impact of Hydropower Energy on the Environmental Kuznets Curve in Malaysia

The present research examines the effect of hydropower energy consumption in testing the Environmental Kuznets Curve in Malaysia by using the annual time series data over the period from 1978 to 2016. The present research applied the advance econometrics to serve the purpose of investigation and therefore used the Auto Regressive Distributed Lag (ARDL) bound testing approach for assessing the presence of long-run relationship between the variables. The results of ARDL bound testing approach confirm the valid long run relationship between hydropower energy consumption and economic growth with carbon dioxide emission in Malaysia. The final outcomes confirm that hydropower energy consumption and square of economic growth have significant and negative impact on carbon dioxide emission whereas, the economic growth have a significant and positive impact on carbon dioxide emission. Furthermore, results also confirm the existence of inverted U-Shape curve in Malaysia. The results provide a solid evidence for the policymakers to focus on hydropower energy consumption while formulating the policy for the reduction of environmental degradation in Malaysia.
Predicting faults from cached history

We analyze the version history of 7 software systems to predict the most fault prone entities and files. The basic assumption is that faults do not occur in isolation, but rather in bursts of several related faults. Therefore, we cache locations that are likely to have faults: starting from the location of a known (fixed) fault, we cache the location itself, any locations changed together with the fault, recently added locations, and recently changed locations. By consulting the cache at the moment a fault is fixed, a developer can detect likely fault-prone locations. This is useful for prioritizing verification and validation resources on the most fault prone files or entities. In our evaluation of seven open source projects with more than 200,000 revisions, the cache selects 10% of the source code files; these files account for 73%-95% of faults--a significant advance beyond the state of the art
The UCSC Genome Browser database: 2015 update

Launched in 2001 to showcase the draft human genome assembly, the UCSC Genome Browser database (http://genome.ucsc.edu) and associated tools continue to grow, providing a comprehensive resource of genome assemblies and annotations to scientists and students worldwide. Highlights of the past year include the release of a browser for the first new human genome reference assembly in 4 years in December 2013 (GRCh38, UCSC hg38), a watershed comparative genomics annotation (100-species multiple alignment and conservation) and a novel distribution mechanism for the browser (GBiB: Genome Browser in a Box). We created browsers for new species (Chinese hamster, elephant shark, minke whale), ‘mined the web’ for DNA sequences and expanded the browser display with stacked color graphs and region highlighting. As our user community increasingly adopts the UCSC track hub and assembly hub representations for sharing large-scale genomic annotation data sets and genome sequencing projects, our menu of public data hubs has tripled.
The Swiss Reserve Market: Stochastic Programming in Practice

This paper presents the evolution and design of the Swiss reserve market and describes its two-stage stochastic market-clearing model. In Switzerland, the reserve market comprises weekly and daily auctions. The decision-making problem is to determine the amount of reserves that should be procured in each market stage. The stochasticity stems from daily offers which are not available at the beginning of the week, when the first-stage decisions are made. The new market-clearing model minimizes expected procurement costs of reserves, while taking reserve dimensioning criteria and market properties into consideration. Since the last week of January 2014, this model has been clearing the reserve market in Switzerland. To our knowledge, this is the first real-world implementation of a stochastic market-clearing model in electricity markets.
Multiple herbicide-resistant horseweed (Conyza canadensis) dose response to tolpyralate and tolpyralate plus atrazine and comparison to industry standard herbicides in corn

Abstract Horseweed biotypes resistant to glyphosate and ALS-inhibiting herbicides are becoming more prevalent in Canada and the United States and present a significant management challenge in field crops. Tolpyralate is a recently commercialized herbicide for use in corn that inhibits 4-hydroxyphenylpyruvate dioxygenase (HPPD), and there is little information regarding its efficacy on horseweed. Six field experiments were conducted in 2017 and 2018 at four locations in Ontario, Canada, to determine the biologically effective dose of tolpyralate and tolpyralate + atrazine and to compare label rates of tolpyralate and tolpyralate + atrazine to currently accepted herbicide standards for POST control of glyphosate and cloransulam-methyl resistant (MR) horseweed. At 8 wk after application (WAA), tolpyralate at 4.8 and 22.6 g ha–1 provided 50% and 80% control, respectively. When applied with atrazine at a 1: 33.3 tank-mix ratio, 22.3 + 741.7 g ha–1 provided 95% control of MR horseweed. The addition of atrazine to tolpyralate at label rates improved control of MR horseweed to 98%, which was similar to the control provided by dicamba: atrazine and bromoxynil + atrazine. The results of this study indicate that tolpyralate + atrazine provides excellent control of MR horseweed POST in corn. Nomenclature: Atrazine; bromoxynil; cloransulam-methyl; glyphosate; tolpyralate; horseweed; Conyza canadensis (L.) Cronq. ; field corn, Zea mays L.
Mixing characteristics of refractory black carbon aerosols determined by a tandem CPMA-SP2 system at an urban site in Beijing

Abstract. Black carbon aerosols play an important role in climate change by absorbing solar radiation and degrading visibility. In this study, the mixing state of refractory black carbon (rBC) at an urban site in Beijing was studied with a single particle soot photometer (SP2), as well as a tandem observation system with a centrifugal particle mass analyzer (CPMA) and a differential mobility analyzer (DMA), in early summer of 2018. The results demonstrated that the mass-equivalent size distribution of rBC exhibited an approximately lognormal distribution with a mass median diameter (MMD) of 171.2 nm. When the site experienced prevailing southerly winds, the MMD of rBC increased notably by 19 %. During the observational period, the ratio of the diameter of rBC-containing particles (Dp) to the rBC core (Dc) was 1.20 on average for Dc = 180 nm, indicating that the majority of rBC particles were thinly coated. The Dp / Dc value exhibited a clear diurnal pattern, with a maximum at 1400 LST and an enhancing rate of 0.013/h; higher Ox conditions increased the coating enhancing rate. Bare rBC particles were primarily in a fractal structure with a mass fractal dimension (Dfm) of 2.35, with limited variation during both clean and pollution periods, indicating significant impacts from on-road vehicle emissions. The morphology of rBC-containing particles vairied with aging processes. The mixing state of rBC particles could be indicated by the mass ratio of non-refractory matter to rBC (MR). In the present study, rBC-containing particles were primarily found in an external fractal structure when MR 6, at which the measured scattering cross section of rBC-containing particles was consistent with that based on the Mie-scattering simulation. We found only 9 % of the rBC-containing particles were in core-shell structures on clean days with a particle mass of 10 fg, and the number fraction of core-shell structures increased considerably to 32 % on pollution days. Considering the morphology change, the absorption enhancement (Eabs) was 11.7 % higher based on core-shell structures. This study highlights the combined effects of morphology and coating thickness on the Eabs of rBC-containing particles, which will be helpful for determining the climatic effects of BC.
Labor Market Performance in OECD Countries: The Role of Institutional Interdependencies

ABSTRACT Reducing rigidity in labor markets is key to lowering unemployment. Theoretical models suggest that the impact of such reforms depends on the country-specific regulatory framework. We test this hypothesis by estimating the impact of changes in six categories of regulation conditional on the country-specific regulatory environment for 26 OECD countries. We overcome problems of modeling a large set of institutional interdependencies by applying a machine learning type model selection approach. We provide evidence for the existence of higher-order institutional interdependencies. We further document that especially for changes in employment protection and the unemployment benefit system the impact on unemployment is mixed across countries.
Micro-Pitting and Wear Assessment of PAO vs Mineral-Based Engine Oil Operating under Mixed Lubrication Conditions: Effects of Lambda, Roughness Lay and Sliding Direction

Under certain operating conditions, rolling contacts have been shown to experience some challenges when lubricated with engine oils containing zinc dialkyldithophosphate (ZDDP) anti-wear additive. In order to better understand the main damage mechanisms during various operating conditions, further studies are needed. This article studies micro-pitting and wear damages of bearing steel surfaces under mixed lubrication conditions in a ball-on-disc setup, lubricated with different engine oils. Based on the results, micro-pitting and wear damage is shown to be highly case-dependent. In general, PAO-based engine oil tends to eliminate micro-pitting damage compared to mineral-based engine oil at less severe lubricating conditions. Moreover, a critical lambda was found for both oils, where the highest micro-pitting damage was observed.
Eligibility, experience rating, and unemployment insurance take‐up

In this paper, we investigate the causes and consequences of “unclaimed” unemployment insurance (UI) benefits. A search model is developed where the costs to collecting UI benefits include both a traditional “fixed” administrative cost and an endogenous cost arising from worker and firm interactions. Experience rated taxes give firms an incentive to challenge a worker's UI claim, and these challenges are costly for the worker. Exploiting data on improper denials of UI benefits across states in the U.S. system, a two‐way fixed effects analysis shows a statistically significant negative relationship between the improper denials and the UI take‐up rate, providing empirical support for our model. We calibrate the model to elasticities implied by the two‐way fixed effects regression to quantify the relative size of these UI collection costs. The results imply that on average the costs associated with firm challenges of UI claims account for 41% of the total costs of collecting, with improper denials accounting for 8% of the total cost. The endogenous collection costs imply the unemployment rate responds much slower to changes in UI benefits relative to a model with fixed collection costs. Finally, removing all eligibility requirements and allowing workers to collect UI benefits without cost shows these costs to be 4.5% of expected output net of vacancy costs. Moreover, this change has minimal impact on the unemployment rate.
Highly Sensitive Terahertz Metamaterial Sensor

A novel design of nearly perfect metamaterial absorber is proposed and analyzed for terahertz sensing applications. The full vectorial finite element method is used to simulate and analyze the reported design. The suggested structure is based on increasing the confinement of both electric and magnetic fields simultaneously at the resonance frequency. Therefore, an absorptivity of 0.99 is achieved at 2.249 THz with a narrow resonant peak and a <inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>-factor of 22.05. The resonance frequency is sensitive to the surrounding medium refractive index at fixed analyte thickness. Consequently, the reported metamaterial design can be used as a refractive index (RI) sensor with the high sensitivity of 300 GHz/RIU and the figure of merit (FoM) of 2.94 through an RI range from 1.0 to 1.39 at the analyte thickness of <inline-formula> <tex-math notation="LaTeX">$1.0~ \mu \text{m}$ </tex-math></inline-formula>. Furthermore, the proposed sensor has a sensitivity of 23.7 GHz/<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> for the detection of the sensing layer thickness variation at the fixed analyte RI of 1.35. It is worth noting that most of the biomedical samples have a refractive index range from 1.3 to 1.39. Therefore, the reported sensor can be used for biomedical applications with high sensitivity.
Ex-Incarceree/Convict Status: Beneficial for Self-Employment and Entrepreneurship?

This article considers whether ex-incarceree/convict status favorably conditions the decision to be self-employed—a proxy for entrepreneurship. With data from the U.S. General Social Survey, we estimate the parameters of simple Probit and Bivariate Probit treatment specifications of individual self-employment outcomes as a function of ex-incarceree/convict status, and several measures of individual risk-taking propensities. Parameter estimates reveal that ex-incarceree/convict status has a positive and significant treatment effect on self-employment, particularly for Black Americans, after controlling for various measures of individual risk propensities. Our results suggest that the expansion of entrepreneurship training programs and the elimination of any barriers that restrict access to start-up capital for ex-incarcerees/convicts would reduce crime and recidivism, ameliorate mass incarceration, and complement pro-growth economic policies that induce more self-employment and entrepreneurship. JEL Classification: J01, J24, L26, Z13
Same-Hill Intercropping of Different Plant Species with Faba Bean for Control of Orobanche Crenata

Allelopathic effects of some faba bean companion crops have been shown to reduce Orobanche crenata Forsk. seed germination especially in vitro. Field experiments were conducted in two locations to evaluate the effect of different companion crops grown in the same-hill with seeds of the resistant faba bean cultivars Misr 3 and Giza 843 on the number of emerged crenate broomrape spikes. Another field experiment was established to compare the effect of fenugreek intercropped on the opposite-side of the faba bean ridge method to same-hill intercropping method on the number of broomrape spikes emerged and faba bean performance. A bioassay experiment was also employed to study the effect of presence of fenugreek, fennel and radish on inhibition of O.crenata seed germination in presence of the two faba bean cultivars in vitro. The bioassay results indicated that presence of fenugreek as a companion crop inhibits O.crenata seed germination on both cultivars by almost 30%; however, the values were insignificantly different from the sole-crop. Radish on the other hand, significantly inhibited germination (73%) in presence of Misr 3 only, while fennel showed no effect on parasite seed germination. Field experiments indicated less number of emerged spikes with opposite-side of the ridge when intercropping fenugreek compared to same-hill intercropping. Results also stressed the role of the faba bean genotype in the host-parasite-companion crop complex. The effect of the companion crop on the number of parasite emerged spikes and yield improvement varied according to the location; however, under farmer’s field conditions of a large parasite seed bank, the effect of companion crops was not observed. Companion crops may show allelopathic effects on O.crenata seed germination in vitro, however, these observations need to be verified on farmers’ fields before it could be proposed as a feasible control method for O.crenata.
GENETIC CONTROL OF THE ANTIBODY RESPONSE TO TYPE III PNEUMOCOCCAL POLYSACCHARIDE IN MICE

The IgM antibody response to Type III pneumococcal polysaccharide (SSS-III) was assessed in F1, F2, and backcross progeny derived from high (BALB/cAnN) and extremely low (CBA/HN) responding parental strains of inbred mice. The results of these studies indicated that a major component involved in the antibody response is X-linked, i.e., carried on the X chromosome; this component determines responsiveness to SSS-III in an almost quantal or "all-or-none" manner. Other factors, presumably autosomal genes, regulate the magnitude of the antibody response produced by mice possessing the X-linked gene; these appear to influence independently the number of antibody-producing cells found after immunization and the amount of antibody made by such cells. Strains of inbred mice varied widely in their ability to respond to SSS-III. Responsiveness was not associated with H-2 histocompatibility type. The implications of these findings with respect to the genetic control of the antibody response to SSS-III are discussed.
Impacts of Drying-Wetting and Loading-Unloading Cycles on Small Strain Shear Modulus of Unsaturated Soils

The small strain shear modulus (Gmax) is an important parameter in geodynamic problems. In order to predict Gmax of unsaturated soils which are normally subjected to complex drying, wetting processes, effect of hydraulic hysteresis needs to be evaluated. Although several equations have been proposed in recent years, limitations still exist, requiring more research studies in this field. In this study, Gmax was investigated in a multi-stage test during several drying-wetting cycles and a loading-unloading cycle of net stress. The results revealed four key factors that directly influence the magnitude of Gmax : the void ratio, the net stress, matric suction and degree of saturation. While variations of the void ratio, net stress, and matric suction cause persistent responses of Gmax (i.e. if all other factors remain unchanged, Gmax would then be reversely proportional to the void ratio and directly proportional to the net stress and matric suction), variations in the degree of saturation result in different responses. A decrease in the degree of saturation may induce a reduction or growth of Gmax since on the one hand it reduces the effect of matric suction, while on the other hand it increases the total effect of van der Waals attractions and electric double layer repulsions. At the same stress state, a reverse trend, induced by an increase in the degree of saturation, will occur with a growth in the effect of matric suction
Control of a Soft Inchworm Robot With Environment Adaptation

Soft robots have recently evoked extensive attention because of their abilities to work effectively in unstructured environments. As an actuation technology of soft robots, dielectric elastomers (DEs) exhibit many intriguing attributes such as large strain and high energy density. This paper presents a novel, DE-based, soft crawling robot inspired by inchworms. The kinematics of the soft crawling robot is explored, and a data-driven model is developed to facilitate the controller design. The overall controller incorporates a feedforward controller, a feedback controller, and a disturbance observer (DOB). The feedback controller and the DOB will compensate the disturbance and model uncertainties resulting from the obtained dynamic model and ensure robust performance of the robot under different conditions. The effectiveness of the proposed control scheme is verified using experiments on surfaces made of different materials and with inclined angles.
Personality or Value: A Comparative Study of Psychographic Segmentation Based on an Online Review Enhanced Recommender System

Big consumer data promises to be a game changer in applied and empirical marketing research. However, investigations of how big data helps inform consumers’ psychological aspects have, thus far, only received scant attention. Psychographics has been shown to be a valuable market segmentation path in understanding consumer preferences. Although in the context of e-commerce, as a component of psychographic segmentation, personality has been proven to be effective for prediction of e-commerce user preferences, it still remains unclear whether psychographic segmentation is practically influential in understanding user preferences across different product categories. To the best of our knowledge, we provide the first quantitative demonstration of the promising effect and relative importance of psychographic segmentation in predicting users’ online purchasing preferences across different product categories in e-commerce by using a data-driven approach. We first construct two online psychographic lexicons that include the Big Five Factor (BFF) personality traits and Schwartz Value Survey (SVS) using natural language processing (NLP) methods that are based on behavior measurements of users’ word use. We then incorporate the lexicons in a deep neural network (DNN)-based recommender system to predict users’ online purchasing preferences considering the new progress in segmentation-based user preference prediction methods. Overall, segmenting consumers into heterogeneous groups surprisingly does not demonstrate a significant improvement in understanding consumer preferences. Psychographic variables (both BFF and SVS) significantly improve the explanatory power of e-consumer preferences, whereas the improvement in prediction power is not significant. The SVS tends to outperform BFF segmentation, except for some product categories. Additionally, the DNN significantly outperforms previous methods. An e-commerce-oriented SVS measurement and segmentation approach that integrates both BFF and the SVS is recommended. The strong empirical evidence provides both practical guidance for e-commerce product development, marketing and recommendations, and a methodological reference for big data-driven marketing research.