Alcohol use and misuse and their relation to sociodemograhic factors are well studied among university students in Western European countries and the USA, but less is known about students in Eastern Europe. The historical past as communistic countries might have affected the social life among these populations, which is again one of the main factors determining the alcohol consumption among university students. The aim of our study was to assess the association of selected sociodemographic factors with different patterns of alcohol use among university students in Slovakia.A sample of 813 young adults  from four universities in Kosice answered questions about their sociodemographic background and about alcohol use. To obtain a detailed picture of different aspects, alcohol use was measured by four variables: frequency of alcohol use, heavy episodic drinking, frequency of drunkenness and problem drinking. Four separate logistic regression models were used to assess the association between sociodemographic and alcohol-related variables. To assess the potentially different effects in both genders, all two-way interactions with gender were tested.While 41% of the students drank alcohol once a week or more often, 77% reported heavy episodic drinking and 49% had been drunk more than once in the last month. Problem drinking existed in 23.3% of the sample. Gender was consistently associated with all four alcohol-related variables, with males being at higher risk. A higher study year was associated only with lower levels of heavy episodic drinking, but displayed no association with the other studied variables. Living with parents during the semester was consistently associated with less frequent heavy episodic drinking, drunkenness episodes, and problem drinking while having an intimate relationship was associated with less problem drinking only.Our findings for the university students from Slovakia are in line with previous studies in Western Europe. Additionally, it appears that frequent alcohol use, excessive alcohol use (heavy episodic drinking and drunkenness) and problem drinking among university students represent a continuum and are influenced by the same sociodemographic factors. Young adulthood is in many cultures the stage of life in which the highest levels of alcohol consumption occur -3. AfterA substantial body of research indicates that males are more likely to drink alcohol, consume higher amounts of alcohol and are more likely to be alcohol dependent in comparison with females. These findings are consistent across different countries and cultures -11. FurtSeveral studies have shown that students increase their alcohol consumption during their first year at college -25. The The relationship between parental socioeconomic status (SES) and adolescent alcohol drinking is poorly understood, with inconsistent or even contradictory evidence. While some studies have identified a higher risk of excessive drinking among adolescents from lower SES groups ,30, otheUniversity and campus environments include friendship networks and unions in which drinking alcohol is common, endorsed and part of social life. Heavy drinking among students is associated with living away from the parental home in several studies -37. LiviThere is a strong increase in alcohol use during adolescent years , but accMost of the research on drinking behavior among university students was conducted in the USA or in Western Europe -45 and cThe study addresses the following questions: (1) what is the prevalence of specific drinking patterns , (2) are these drinking patterns associated with selected sociodemographic variables  and (3) do the associations between sociodemographic variables and drinking patterns differ for both genders in university students in Slovakia.In 2007 as part of the Cross-National Student Health Study (CNSHS) , data weParticipation in the study was voluntary and anonymous. Students were informed that by completing the questionnaire they were providing their informed consent to participate. They were also told that they could terminate the participation at any point while filling out the questionnaire. The permission to conduct the study was granted by the participating institutions: Faculty of Medicine, Faculty of Science, Faculty of Law, Faculty of Public Administration and Faculty of Arts all from the University of PJ Safarik, the University of Veterinary Medicine and Pharmacy in Kosice and the Technical University of Kosice.The frequency of alcohol consumption was measured using the following question: "Over the past three months how often have you drunk alcohol, for example, beer?" The possible answers were: "never," "once a week or less," "once a week," "a few times each week," "every day," "a few times each day". We dichotomized the variable into "drinking less than once a week" versus "drinking once a week or more". The results regarding drinking patterns are reported in Table The frequency of heavy episodic drinking was measured by asking: "Think back again over the last 30 days. How many times (if any) have you had five or more drinks on one occasion?" (A "drink" is a glass/bottle/can of beer (ca 50 cl), a glass/bottle/can of cider (ca 50 cl), 2 glasses/bottles of alcopops (ca 50 cl), a glass of wine (ca 15 cl), a glass of spirits (ca 5 cl) or a mixed drink). The options for answers were "never," "once," "twice," "3-5 times" "6-9 times" and "10 or more times." We classified respondents into non-episodic drinkers (if they responded "never") and heavy episodic drinkers .To identify students with higher risk behavior who drink to excess or to get drunk, we used the question "How many times have you been drunk during the last four weeks?" The options for answers here were: "never", "once or twice", "3-4 times," and "5 or more times." Responses were dichotomized into "never" versus all other.Cut down on your drinking? Have people Annoyed you by criticizing your drinking? Have you ever-felt bad or Guilty about your drinking? Have you ever had a drink in the morning to get rid of a hangover? (Eye opener). Each question is answered either "yes" or "no." Two or three affirmative answers suggest problem drinking, while four positive responses raise a serious suspicion of alcohol dependence. Mean inter-item correlation (MIIC) was 0.26  was assessed using two measures: parental education and the self-perceived income sufficiency of the student. We first asked about the father's and mother's educational status separately--"What is the highest education level of your mother, father?"--with these answer options: "No formal education," "Secondary vocational school," "A levels," "Bachelor's degree," "Master's degree and Ph.D. or equivalent." The educational levels of parents were subsequently collapsed, for the purpose of analysis, into two categories: low (A levels and lower degree) versus high (bachelor's and higher degree). Afterwards, the educational levels of parents (low vs. high) were combined into the following four groups: both parents high, both parents low, mother high and father low, and father high and mother low. Perceived income sufficiency was measured by asking: "How sufficient do you consider your income?" with four Likert scale responses  which were dichotomized into "always sufficient" versus "other." Students were also asked about the type of accommodation they lived in during the semester. The responses were dichotomised into "I live with my parents" versus "I do not live with my parents." Finally, participants were asked whether they were currently in an intimate relationship.First, we conducted a descriptive analysis of the study population. Next, we used the phi coefficient to assess the correlation between the dichotomised variables related to alcohol . Phi valThe composition of this sample was as follows: 43.3% of students came from the University of PJ Safarik; 16.5% from the University of Veterinary Medicine and 40.2% from the Technical University. There was a gender distribution of 63.8% females and 36.2% males. Other main descriptive characteristics of the study population are presented in Table A total of 41.1%  of the sample drank alcohol once a week or more often. 77.0% of males and 52.1% of females were heavy episodic drinkers (consuming 5 or more drinks on a single occasion), while 49.1%  had been drunk more than once during the last month. Problem drinking (two or more positive responses in CAGE) was estimated for 32.3% of males and 14.3% of females.After correlating all drinking-related variables, we found that the strongest relation was between heavy episodic drinking and frequency of drunkenness . Correlations between problem drinking and other alcohol-use-related variables were relatively weak, for example for frequency of drinking and problem drinking  and heavy episodic drinking and problem drinking . These findings justify the analyses of the alcohol-related variables in separate models.The results from multivariable logistic regression models are summarized in Table p < 0.05) interactions with respect to any alcohol-related variable.To assess the potentially different effects in both genders, interactions of all other sociodemographic variables with gender were tested, which revealed no significant  as well as lowly-educated families (both parents with a low education level)--faced a higher risk of problem drinking. If students from higher SES families experienced more restraints during adolescence, they might be more prone to excessive drinking when gaining independence. On the other hand, students from lower SES groups might experience a more permissive environment with regard to alcohol and develop problem drinking . In famiLeaving the parental home often coincides with an increase in heavy alcohol use . We founWe found that having an intimate partner was associated with two alcohol-related variables: respondents with an intimate partner were less involved in frequent drinking and problem drinking than students who were not in an intimate relationship. Although the findings for other drinking patterns were not significant, the same trend was observed for frequency of drunkenness. As a potential explanation of this phenomenon, Silbereisen suggested that involvement in a relationship is accompanied by changes in leisure activities; partners go to pubs or discos less often and seek each other's company in private settings . AnotherIn this survey sociodemographic correlates of four different patterns of alcohol use among university students in Slovakia were studied. Given the self-reported measures of drinking, some underreporting, for example for problem drinking, which is socially undesirable, might have occurred. In line with the National Survey on Drug Use and Health we used the same criterion (5 or more drinks) for measuring heavy episodic drinking for both genders, while many authors argue that four drinks or more should be used for females ,80. Due A further limitation is the cross-sectional design, which makes impossible to formulate conclusive statements about causality. We cannot exclude possible biases regarding missing or incorrect information due to social expectation bias in self-reported data, but we made several steps to guarantee confidentiality, which typically reduces social expectation bias. Since the response rate was relatively high and the survey covered different areas and not only the here studied questions, selection bias is likely limited. Some measures used in our study are short and might not have derived the whole information. For example, socio-economic status was measured only indirectly. There are also limitations related to the representativeness of the sample of the present study for all students in Slovakia. While we studied a relatively systematic sample from three universities in one town, the prevalence of alcohol use may be different in other parts of Slovakia.Overall, the current study confirmed associations between alcohol use and problem drinking and some sociodemographic factors in university students in Slovakia which is in agreement with studies from other populations. It seems that a different historical past did not influence patterns of alcohol use, however, we cannot say whether the situation observed in 2007 is a consequence of recent adaptations or was already in place before the political changes of the early 1990s. Additionally, our findings indicate that frequent alcohol use, excessive alcohol use (heavy episodic drinking and drunkenness), and problem drinking (CAGE) among university students represent a continuum and are influenced by the same sociodemographic and psychosocial factors. Male gender and living in a university campus environment were associated with excessive and problem alcohol use patterns. Another factor that affects student problem drinking is an intimate relationship. For the study year and the SES we were not able to confirm the expected associations, however. These findings should be taken into account when developing prevention programs.The authors declare that they have no competing interests.RS developed the research question, conducted the analyses and drafted the manuscript. OO and JPvD commented extensively on the manuscript. RTM developed the study design, supervised the analysis, contributed to interpretation and writing. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/11/849/prepub


In many court cases, surveillance videos are used as significant court evidence. As these surveillance videos can easily be forged, it may cause serious social issues, such as convicting an innocent person. Nevertheless, there is little research being done on forgery of surveillance videos. This paper proposes a forensic technique to detect forgeries of surveillance video based on sensor pattern noise (SPN). We exploit the scaling invariance of the minimum average correlation energy Mellin radial harmonic (MACE-MRH) correlation filter to reliably unveil traces of upscaling in videos. By excluding the high-frequency components of the investigated video and adaptively choosing the size of the local search window, the proposed method effectively localizes partially manipulated regions. Empirical evidence from a large database of test videos, including RGB /infrared video, dynamic-/static-scene video and compressed video, indicates the superior performance of the proposed method. The benefits of digital images, such as facility in editing, sharing and storing, motivate people to use digital images instead of analog images. At the same time, the very nature of digital data, which can be easily manipulated, encourages abuse of the digital images; hence, the authentication of images has become one of the biggest issues regarding digital images.Digital image forensics, which detects modification of digital images, has been actively researched for the last decade ,2. Forenetc. If a forged surveillance video is used as court evidence, it can cause severe problems, such as convicting an innocent person. Therefore, it is important to detect forgeries associated with surveillance videos.Within the last few decades, surveillance cameras have been installed in many areas to prevent crime. As a consequence, in many court cases, surveillance videos are used as court evidence. Unfortunately, surveillance videos can be easily forged by video editing tools, such as Premier, Vegas, A common form of manipulation, which is often perpetrated in surveillance video, is cropping a video after enlarging it to erase evidence of a crime in the outer part of the video. As surveillance videos are always recorded at regular resolution, magnifying to the original resolution is required for a cropped video. We refer to this type of forgery as upscale-crop forgery. An upscale-crop forgery can be attempted in the following scenario. Another type of forgery, in which splicing and compositing parts of a video frame by various image editing methods, such as intra- and inter-frame copy-move, splicing, and so on, can also be accomplished. We refer to this type of forgery as partial manipulation. For instance, the falsifier can generate By examining the forged videos of In this paper, we propose a forensic method for surveillance video based on sensor pattern noise (SPN). In order to detect manipulation of surveillance video with high accuracy, we first analyze the general characteristics of the surveillance camera and consider related studies from the literature in Section 2. From the analysis, an overview of SPN in Section 3 lays the foundation for its application to surveillance video forensics. Sections 4 and 5, respectively, explain the proposed upscale-crop and partial manipulation detectors based on SPN. Experimental results are then given in Section 6, and Section 7 concludes the paper.2.This section explains the general characteristics of surveillance video. We then review the forensic methods that have been studied so far in two separate categories: upscale-crop forgery and partial manipulation detectors. Finally, we discuss the contributions of the proposed method.2.1.In order to detect forgeries of surveillance video, first of all, the characteristics of a surveillance camera should be analyzed. Unlike general cameras, surveillance cameras can record not only RGB video, but also infrared video. They can also take both static-scene video from a fixed position and dynamic-scene video when the camera is installed on a moving object. Furthermore, the recorded video is compressed by video codec, such as H.264. Therefore, these characteristics of surveillance cameras should be considered for a forgery detector of surveillance video.2.2.Enlarging a video includes a resampling process of each frame in the video. Therefore, upscale-crop forgery can be detected by determining whether or not an investigated video was resampled. Gallagher first uncovered periodicity in the second derivative signal of interpolated images . Not onlAside from analyzing the n-th order derivative of the interpolated image, Popescu and Farid identified the correlation between neighboring pixels of the interpolated image by a local linear predictor that uses an expectation/maximization (EM) algorithm . The outThese methods were able to detect a trace of upscale-crop forgery accurately if an investigated video was uncompressed. However, these methods rarely detect forgery in surveillance videos, because the periodic properties of resampling artifacts mostly disappear during the video compression process.2.3.Methods to detect partially manipulated images or videos have been actively researched in the last decade. Detection of copy-move (CM) forgery is one of representative approaches to localizing partial manipulation. CM forgery copies parts of an image and inserts them into another part of the same image. This is usually done to conceal or emphasize detail. CM forgery was first proposed by Fridrich et al. . They leet al.'s approach is the same as the approach of Chen et al. [et al.'s method also had low accuracy when the SPN contained many high-frequency components. Hsu et al. developed a method based on the correlations of SPN between every two temporally neighboring video blocks [et al. described a geometric method to detect physically implausible trajectories of objects in video sequences [To overcome the drawbacks of CM forgery detectors, methods that analyze the statistical properties of both unforged and forged areas have been proposed. Chen et al. proposed the detection method of partial manipulation based on SPN . They ren et al. . Therefoo blocks . Simulato blocks ,17. Kobao blocks . They eso blocks , Kobayasequences . They ex2.4.In our previous work, we proposed a forgery detection method that could detect upscale-crop forgery and partial manipulation . UpscaleWe discuss three main contributions to solving the problems of surveillance camera forensics. To satisfy the inherent constraints of a surveillance camera as stated in Section 2.1, SPN is used as a statistical tool. SPN is extractable from both the RGB video and the infrared video. Moreover, the SPN survives under lossy compression, filtering, gamma correction and many other typical processing procedures. Therefore, the proposed method is robust against RGB/infrared mode and video compression (see Section 3 for the details of SPN). A second contribution lies in a novel upscale-crop forgery detector based on a minimum average correlation energy Mellin radial harmonic (MACE-MRH) correlation filter. To detect upscale-crop forgery, we designed two different MACE-MRH correlation filters from a reference SPN (see Section 4). Third, we propose the partial manipulation detector to accurately detect partial manipulation in static-scene video by eliminating high frequency components and adaptively choosing the size of a local search window (see Section 5).3.An image sensor, such as CCD or CMOS, in digital imaging devices is composed of an enormous number of photon detectors, commonly called pixels. Pixels have different sensitivities to light, due to the inhomogeneity of silicon wafers, and the variable sensitivity of each pixel to light generates uncorrelated pattern noise. Consequently, every sensor casts a unique sensor pattern noise (SPN) onto every image or video it takes. This SPN acts as a sensor fingerprint and exploits identifying imaging sources or verifying the image in the field of digital forensics –24.N frames, I1, I2, …, nI, the SPN of the video is computed as In a video clip, the SPN can be extracted as follows. Assuming that the video is composed of F is the wavelet denoising filter described in [ribed in .Using SPN extracted from The whole process of the proposed method, which is based on the characteristics of SPN, is depicted in 4.This section explains the details of upscale-crop forgery detection as the first step of the proposed method. In general, when a surveillance video is presented as legal evidence in court, the information of the camera, by which the video is recorded, becomes available publicly. Thus, prior knowledge of the recording device can be used to determine whether or not the investigated video is manipulated.To detect upscale-crop forgery of the surveillance video, we exploit reference SPN extracted from the source camera. More specifically, two MACE-MRH correlation filters, which have different scale-tolerance ranges, are designed from the corresponding reference SPN. The first filter is designed to have a very large correlation value when the suspicious video is not scaled. On the other hand, the second filter is designed to maintain a high correlation value even if the suspicious video is upscaled. By calculating two cross-correlation values between the different MACE-MRH correlation filters and the test SPN, we judge whether or not the test video is forged.In the following subsections, we first provide an overview of the MACE-MRH correlation filter . Afterwa4.1.x and h denote the 2D test pattern and the correlation filter generated from the reference pattern, respectively. Then, correlation output c can be expressed as the inverse 2D Fourier Transform (FT) of the conjugate product in the frequency domain as follows:X and H are the 2D FT of x and h, respectively. If the test pattern is similar to the reference pattern, the correlation output, c, has a high correlation peak. Thus, the similarity betweien two patterns is measured by calculating the following peak to correlation energy (PCE).Correlation is a natural metric for characterizing the similarity between a reference pattern and a test pattern. A correlation filter is designed to have a high correlation peak if the reference pattern, which was used to generate the filter, is similar to a test pattern. Let The correlation filter basically has a shift invariance property, since the convolution operation in mF(ϕ), is computed from reference SPN:F is the FT of the reference SPN in polar coordinates and mF(ϕ) is the m-th MRH function of F. R and r0 are selected as 768 and 14.07, respectively, which satisfy the relationship ln R – ln r0 = L ∈ Z+.To detect upscale-crop forgery, the proposed method exploits the MACE-MRH correlation filter designed from reference SPN. The MACE-MRH filter is designed as shown in c(β), and the coefficients, mC, represents the function of the scale factor, β, as below:mH(ϕ) is the m-th MRH function of the MACE-MRH correlation filter. ĉ(β) in Second, MRH function coefficients are computed according to the scale response. The relationship between the scale response, ĉ(β), and the coefficients, mC, is exactly the same as A(w) and ka of The relationship between the transformed scale response, mC as that of designing the FIR filter of A(w). Thus, by employing available FIR filter design algorithms, the coefficients, mC, of c(β) can be calculated. In this paper, we calculated mC by the fir1 function of Matlab 2012a.mH(ϕ), of mC as constraints. There are many mH(ϕ) candidates that satisfy the constraints. Thus, more constraints are needed to find a unique solution. Therefore, we selected mH(ϕ), which minimize the average correlation energy while satisfying the relationship in fP(ϕ) is the average power spectrum of the reference SPN obtained by computing the average of F2 along the radial axis. mH(ϕ) from mC and mF(ϕ) by After that, the MRH function, H, is found by applying the inverse MRH transforms of mH(ϕ) and applying a polar-to-Cartesian coordinate transform.Finally, the correlation filter, 4.2.In the previous section, we explained how the MACE-MRH correlation filter is designed. In this section, we show how we apply the MACE-MRH correlation filter to upscale-crop forgery detection.mC = 1 for all m, the scale response of β = 1. Therefore, by designing the first MACE-MRH correlation filter with mC = 1 for all m, we can generate a filter that has only a peak correlation value when the input pattern is not distorted by scaling.In our previous work, we proposed a camera identification method using a MACE-MRH correlation filter generated from SPN . The expT times. Then, the MACE-MRH correlation filter is generated from the magnified reference SPN and the scale response, c(β), is set as below.The second MACE-MRH correlation filter is designed to maintain a high correlation value even if the input pattern is enlarged. To design such a filter, the reference SPN is magnified by T times, it tolerates scaling in the following range.tβ value [tβ to detect forgery in the surveillance video compressed with low quality. In a real world scenario, attackers may magnify the video with a small scaling factor, because they do not want to expose their manipulation. Thus, it is unnecessary to consider a wide range of scaling factors that can be easily detected by the naked eye. scaling factor ≤ 1.44 by setting T = 1.2 and tβ = 0.2 in Because of the trade-off between the range of scale-tolerance and the performance, the MACE-MRH filter generally has a higher correlation value with a lower βt value . Thus, wχ1 and χ2, we extract test SPN ψ from the inspected video by After designing two filters, namely m1peak,n1peak) and  are the peak positions in c1 and c2, respectively, which represent the location of the maximum values from c1 and c2.PCE1 value is larger than the 2PCE value and vice versa.5.et al. detected doctored regions in an image [In this section, we explain how to detect partial manipulation of a video under investigation. If a video has been partially manipulated by clipping objects from an intra-or inter-frame and superimposing them, the doctored region will have weak SPN or not be synchronized with the reference SPN. Thus, the normalized correlation coefficient (NCC) between the reference and test SPN in the doctored region is very small. By using this property of SPN, Chen an image . HoweverLi proposed an approach to reduce the influence of high frequency components in their SPN . By applFrom the above observation, we propose a forgery detector with a small local searching window to accurately detect partial manipulation from a static-scene video. Specifically, the proposed method estimates a high frequency map (HFM) to determine whether or not each pixel of the SPN is contaminated by high frequency components. Afterwards, we remove the high frequency components from the SPN using the HFM and adaptively select the size of the local searching window according to the quantity of clean SPN in the window block. In the next subsection, we explain the details of estimating the HFM and forgery detection method.5.1.SPN is accurately estimated with smooth and bright scenes, such as a scene of blue sky . Thus, bα = 1.703e + 0.005, μ = 0, and σ = 0.000944.−5 with threshold spnτ, as high frequency components. In other words, a high frequency map (HFM) is determined from the investigated SPN as in the following equation.ψ is test SPN, spnτ is 0.003 and HFM indicates whether or not the corresponding SPN pixel is a high frequency component .HFM, we prune the erroneously detected part of the HFM. Since high frequency components are normally connected with their neighbors, connected HFM components, whose size is smaller than 10 × 10, are filtered out using the four-connected-component labeling algorithm [HFM of After estimating the lgorithm . Figure HFM calculated as above, the proposed method removes the parts of contaminated SPN by multiplying the HFM with the corresponding SPN and calculates the NCC from the filtered SPN. HFM. The size of the small block is 64 × 64, and that of the large block is 128 × 128. NCC values between each block of test SPN and the corresponding reference SPN were calculated as below.Using the ψ and χ represent the selected block of test SPN and the corresponding reference SPN, respectively. The test SPN of the proposed HFM and Li's method was filtered by HFM, which determines that the position of the time stamp is not SPN, as shown in The position of the time stamp in the video does not contain any sensor pattern noise, as the time stamp was digitally inserted after the capture. Thus, if a test video has a big time stamp, SPN estimated from that video will have many errors in the region of the time stamp. Therefore, the SPN errors by the time stamp should be filtered. The proposed method can filter them by 5.2.HFM and adaptively choosing the size of the local search window according to the quantity of clean SPN in the window block. The detection process of partial manipulation consists of three steps. In the first step, we generate clean SPN for the test video by removing contaminated SPN. To that purpose, the HFM estimated from the test SPN is multiplied by both the reference and test SPN.The proposed method detects partial manipulation in static-scene video by eliminating high frequency components using the δ and ψ represent the reference and test SPN, respectively.δ̂ and ψ̂ are calculated by sliding a searching window centered at each pixel. The size of the local searching window is adaptively determined by the quantity of clean SPN in the window block, as shown in In the second step, to determine whether or not any pixel of the test video is forged, NCC values between BS is the block size of the window centered on . Once the block size of the window is determined, each inspection block is extracted from δ̂ and ψ̂ as follows:T is BS/2, and NCC values between δblock and ψblock are calculated.x,y), is forged if ρ ≤ pixelτ.Z indicates whether each pixel is forged (one) or not (zero).video and vice versa.As a final step, the proposed method determines whether or not the inspected video is forged as follows:6.etc., were automatically set.This section contains extensive detection tests of both upscale-crop forgery and partial manipulation. We recorded 120 sample videos, 60 RGB and 60 infrared videos, from ten surveillance cameras, as summarized in 6.1.In order to measure the performance of the proposed upscale-crop detector, we first created 240 unforged videos by compressing 120 sample videos with the H.264 encoder with quality factors of 80 and 100. Then, 1,920 forged videos were created as follows: All frames of 120 sample videos were enlarged in increments of 0.05 from 1.05 to 1.4 by bi-cubic interpolation kernels. The outer part of the scaled videos was then cropped out to make the resolution 640 × 480. Finally, the forged videos were compressed with quality factors of 80 and 100. With the test videos, we measured the average detection accuracy of the proposed method, varying both scaling and quality factors. We further benchmarked two more detectors, which were, respectively, proposed by Mahdian [−2. After that, the forgery detection accuracy of each method was computed. The proposed method found non-doctored videos with 100% accuracy, i.e., without any false positive error. For measuring the forgery detection accuracy with a similar false positive condition, the decision thresholds of Mahdian's approach and Kirchner's approach were set to a false positive rate (FPR) of 106.2.In this section, we discuss the interesting case in which a video is forged by both upscale-crop and partial manipulation. If upscale-crop forgery occurs after partial manipulation, the proposed detector is not affected by partial manipulation at all, since all pixels in the investigated video frame have the trace of upscaling inherently. On the other hand, if partial manipulation occurs after upscale-crop forgery, some of the upscale traces in the partially manipulated region disappear. Consequently, the detection accuracy of upscale-crop forgery might be affected by the partial manipulation after the upscale-crop, especially when the size of the doctored region is big enough.To measure the performance of the proposed upscale-crop detector according to the size of the locally doctored region after upscale-crop forgery, 1,920 forged videos were created as follows. One-hundred twenty sample videos were enlarged with scaling factors of 1.15 and 1.3, followed by cropping to 640 × 480 at the center position. After that, the videos were forged by copying and pasting objects from other videos at random positions. The size of the doctored regions was varied from 50 × 50 to 200 × 200 in steps of 50 square pixels. Afterwards, the videos were compressed by an ffdshow H.264 encoder with quality factors of 80 and 100. With the forged videos, we measured the average detection accuracy of the proposed method. We also tested both the Mahdian [6.3.Sections 6.3 and 6.4 only consider the detection performance of the proposed method against forged videos with partial manipulation. In this section, we focus on how well the proposed method detects forged pixels in the locally doctored videos by evaluating the partial manipulation detection performance at the pixel level. For this purpose, 1,440 test videos were created as follows: 120 sample videos were forged by copying and pasting objects of other videos at random positions. The size of the doctored regions was varied from 100 × 100 to 150 × 150 in steps of 10 square pixels to examine the influence of the size of the doctored region. Afterwards, the videos were compressed by an ffdshow H.264 encoder with quality factors of 80 and 100. To analyze the performance according to the types of video scene, we classified the test videos into static-scene and dynamic-scene video.To evaluate the performance of the proposed partial manipulation detector, we conducted three types of experiments. First, we analyzed the distribution of the NCC values in doctored and non-doctored regions. The NCC values corresponding to each pixel of video were calculated by pixel) versus the false positive rate (FPRpixel) was calculated from the NCC values by changing the threshold. pixel < 10−2 with TPRpixel higher than 99%. However, Chen's method and Li's method with a 128 × 128 window detected forgery with lower TPRpixel than the other methods, because the size of the detection block was larger than that of the forged region for some test videos. From the analysis of pixel, of the proposed method for static scene and dynamic scene videos as 0.0092 and 0.0815, respectively.Second, from the above analysis, we compared the performance of each method by receiver-operating-characteristic (ROC) curves. The pixel level true positive rate (TPRθ(log(BS × BS)) by fast Fourier Transform. Therefore, the required time complexity is as below.Finally, we analyze the computational complexity of each method. Three detectors determine forged pixels by computing NCC values between local blocks of test SPN and the corresponding reference SPN blocks as M, N and BS are the height and width of an investigated video and the block size of the local searching window, respectively. 6.4.Z in pixel.After determining the forged region at a pixel level as depicted in Section 6.3, we finally determined whether or not the investigated videos were forged in this section. More specifically, we measured the performance of partial manipulation detection among three detectors  at the video level. For that purpose, 240 unforged videos were created by compressing 120 sample videos with H.264 with quality factors of 80 and 100. Then, 1,440 forged videos were created as explained in Section 6.3. For all test videos, we calculated the NCC values of each method and generated forgery map Z, we can determine whether the test video was forged or not by comparing the number of forged pixels with threshold τvideo in video, the investigated video is determined to be forged; otherwise, it is determined to not be forged. By choosing various τvideo, we generated video-level ROC curves of a true positive rate at the video level (TPRvideo) versus a false positive rate at the video level (FPRvideo).From the map, video while achieving higher accuracy than Chen's method and Li's method, especially for the static-scene.video as FPRvideo = 10−2 and calculated the forgery detection accuracy. video = 10−2. For static-scene videos, Chen's method and Li's method with a 64 × 64 window had low accuracy. Li's method with a 128×128 window detected forgery with over 90% accuracy, only if the size of the doctored region was bigger than 140 × 140. On the other hand, the proposed method detected forgeries with over 90% accuracy regardless of the size of the doctored region. In the dynamic-scene videos, the proposed method and Li's method with a 64 × 64 window detected forgery with an accuracy of 100% in all doctored region sizes.For a more detailed comparison with each method, we set the τ7.With the growth of the digital imaging industry, surveillance cameras are widely used throughout our society. As a result, in many court cases, surveillance videos are used as court evidence. At the same time, forgeries of surveillance videos are rapidly increasing. In this paper, we focused on a forensic technique to detect altered surveillance videos. Two types of forgeries, called upscale-crop forgery and partial manipulation, were identified by the proposed method based on sensor pattern noise (SPN). We exploited the scaling tolerance of a minimum average correlation energy Mellin radial harmonic (MACE-MRH) correlation filter to reliably unveil traces of upscale-crop forgery of videos. By excluding high-frequency components of the investigated video and adaptively selecting the size of the window block, the proposed method effectively detected partially manipulated regions in static-scene videos. Empirical evidence from a large database of test videos supported the superior performance of our techniques regardless of RGB/infrared video, dynamic-/static-scene video and compression.


Using participant ratings and computational measures, we demonstrated distinct patterns across measures of similarity and co-occurrence, and familiarity for each relational construct in two different item sets. In a standard lexical decision task (LDT) with various delays between prime and target presentation (SOAs), target RTs and priming magnitudes were consistent across the three relations for both item sets. However, across the SOAs, there were distinct patterns among the three relations on some of the underlying measures influencing target word recognition . These distinct patterns suggest different mechanisms of lexical priming and further demonstrate that integrative relations are distinct from thematic and taxonomic relations.Word pairs may be integrative (i.e., combination of two concepts into one meaningful entity; e.g.,  Semantic richness refers to the variability in the information associated with a word's meaning that can facilitate lexical priming of the target following a related prime . Integrative relations are included among the “forward phrasal associates” prime-target pairs in the Semantic Priming Project (SPP)  and external component  subtype relations. Notably, earlier relational taxonomies further subdivided such integrative relations into a small and finite number of general relations . They are classified by Santos et al. (barn—hay), and person-location  relations among other subtypes , coordinate , and subordinate . Within this study, we limit our taxonomic items to the category co-member or coordinate relations, which are denoted in the SPP as “category” relations . Integrative and thematic relations may overlap, particularly for the locative subtype of relation. For example, the concepts hospital and doctor can be integrated to denote a subclass of doctors that work in a hospital and are thematically related in that hospitals and doctors play complementary roles in a given event or situation. However, there are many other pairs that are thematic but not so integrative  or that are integrative but not necessarily thematic . Integrative and taxonomic relations may overlap depending on the similarity between the concepts and, to a lesser degree, on the extent to which the concepts belong to the same specific category. Highly similar items that belong to a specific (or sub-) category are less likely to be integrated than less similar ones  may also be considered as thematic in that they may play complementary roles in a given scenario or event (ice-cream and cake may be served together at a party). More typically though, pairs having both a thematic and taxonomic relation will be co-members of a broader category .Note that these relation types are not mutually exclusive. Indeed there is much overlap with concept pairs often representing two of the three or even all three relations  than for taxonomically related pairs , and attributed this result to a greater “salience” for the thematically related items. However, these studies did not control for word association strength, which has been shown to produce more robust lexical priming effects particularly at shorter and longer SOAs . Studies 3 and 4 consisted of a smaller set of prime-target pairs with the target held constant among the three relations . For both item sets, we minimized and equated association strength and assessed local co-occurrence or word pair frequency (Google hits), and global co-occurrence (LSA cosines).To the extent that integrative, thematic, and taxonomic relations are conceptually distinct, they should exhibit distinctive patterns across pair measures of semantic richness . Indeed, Maki and Buchanan  found a In Study 1, we assess the extent to which items taken from the SPP differed on two measures of global and local co-occurrence (described further in the subsequent sections) across our three relations. In Study 2, we sought to examine whether target RTs and priming magnitudes would differ across these three relations using the LDT target RTs taken from the 200 ms and 1200 ms SOAs in SPP.instruction book) appears in long-term memory, whereas global co-occurrence refers to the co-occurrence of the prime and target within a given text. In the current study, we assess local co-occurrence by the frequency of the word pair in Google and global co-occurrence using LSA cosines. In addition to influencing lexical priming, the extent and type of co-occurrence is predicted to vary among the three relations.Co-occurrence between primes and targets influence lexical priming. According to compound-cue theory . Moreover, in an exploratory factor analysis, Maki and Buchanan  is a statistical approach to language learning that is able to capture subtle semantic relationships between words even though it has no knowledge of word meaning or syntax . Though some thematic items can be combined into a plausible entity , the combined entity does not as effectively denote a subtype of the second concept . Thus, word pair frequencies (logGoogle hits) should be higher for the integrative pairs than for the thematic and taxonomic pairs. In contrast, both thematic and taxonomic pairs tend to have greater global or textual co-occurrence than the integrative items, due to the complementary roles the concepts share in a given event for the thematic items and the inclusion within the same category and high semantic similarity for the taxonomic items. Hence, global co-occurrence (LSA cosines) should be greater for the thematic and taxonomic pairs than for the integrative pairs.One critical difference between the integrative and the other two relations is that by definition the two concepts in integrative relations can combine into a plausible entity that denotes a subtype of the second concept  as well as target RTs and priming magnitudes from a LDT with a 200 ms SOA and a 1200 ms SOA. To investigate lexical priming across integrative, thematic, and taxonomic relations for only weakly associated items, we selected items having the following relations from the “Other Associates” tab in SPP: forward phrasal associates, script, and category. Next we eliminated all pairs having forward association strengths (FAS) greater than 0.10 so that only weakly associated items would be included. Results of a One-Way ANOVA confirmed equivalent and weak  FAS, F < 1, p = 0.63, and backward association strengths, F < 1, p = 0.83, across the three relations. Then we limited our items to only noun–noun prime-target pairs and removed any items having proper names for the prime or target  and morphemic repetition between prime and target . The final set of items used in Studies 1 and 2 consisted of 89 integrative items, 78 thematic items, and 85 taxonomic items as shown in Appendix A.The SPP, , F = 64.63, p < 0.001, and global co-occurrence (LSA cosines), F = 13.23, p < 0.001. As shown in Table p < 0.001, followed by the taxonomic items, which were in turn higher than the thematic items, p < 0.01. In contrast, the integrative pairs had reliably lower LSA cosines than the thematic and taxonomic pairs (ps < 0.01), which did not differ (p = 0.29). In sum, these results demonstrate distinct patterns of co-occurrence for the integrative items  in comparison to the thematic and taxonomic relations.We compared the word pair frequencies (logGoogle hits) and the global/textual co-occurrence (LSA cosines) among the three relations using a One-Way ANOVA with Tukey HSD car—garage) than for their associated taxonomic pairs (car—bus) in a standard LDT with a 200 ms SOA. Here we investigate whether such a difference would occur for our weakly associated thematic, taxonomic, and integrative items by comparing the RTs and priming effects (PEs) found in the 200 and 1200 ms SOAs of the SPP.The purpose of Study 2 was to determine whether the response times and priming effects would differ among the three relations. Recall that Sachs et al.  found mopost-hoc tests. Neither prime lengths, F = 1.10, p = 0.33, nor target lengths, F = 1.40, p = 0.25, differed across the three relations. However, prime frequencies differed, F = 14.98, p < 0.001, with reliably greater frequencies for the integrative primes  compared to the thematic , p < 0.001, and taxonomic primes , p < 0.001, which did not differ. Target frequencies also differed among the three relations, F = 12.57, p < 0.001. Integrative target frequencies  were greater than thematic , p < 0.01, which in turn were marginally greater than the taxonomic targets , p = 0.10. Baseline prime RTs differed among the three relations, F = 5.67, p < 0.01, with faster RTs for the integrative primes  than the thematic , p < 0.001, and taxonomic primes , which did not differ, p = 0.83. Baseline RTs for the integrative targets  did not differ from the thematic targets , p = 0.57, but were marginally faster than the taxonomic targets , p = 0.08. Baseline RTs did not differ between the thematic and taxonomic targets, p = 0.57. Given these differences, we next assessed whether prime frequencies, target frequencies, baseline prime RTs, and baseline target RTs were associated with our primed target RT at each SOA. Correlations with the primed target RTs at each SOA were reliable for only the target frequencies  and baseline target RTs , so we included these two variables as covariates in our analyses below. As discussed in the Introduction, we did not predict any differences among word recognition latencies or priming effects for our weakly associated items at either SOA.The same SPP materials from Study 1 were used. Differences in prime and target lengths, frequencies, and baseline RTs (RTs for the word presented in isolation) can influence priming effects  = 1.82, p = 0.17, and priming effects, F < 1, p = 0.82, across the three relations. The lack of difference among the relations was consistent across both SOAs, as evident by the lack of an interaction for the RTs, F < 1, p = 0.92, and PEs, F = 1.28, p = 0.28, nor was there an effect of SOA for either RTs, F < 1, p = 0.78, or PEs, F = 1.03, p = 0.31. Not surprisingly, the target frequencies and baseline target RTs had a reliable effect on RTs (ps < 0.001), but did not impact PEs (ps > 0.45). No other covariates or interactions were reliable.We conducted two separate 3  × 2  mixed ANCOVAs on the target RTs and PEs with target frequencies and baseline (ELP) target RTs as covariates. Adjusted mean RTs and PEs for each relation are shown in Table t-tests revealed reliable PEs (>0) for all relations at the 200 ms SOA (ps = 0.01). However, at the 1200 ms SOA, only the taxonomic items had reliable priming effects (p = 0.01), whereas the thematic and integrative items did not . The effects for the taxonomic items are consistent with prior studies . Such neutral primes tend to artificially inflate the RTs for the control condition at long SOAs, which in turn yield inflated priming effects  is paired with an integrative , thematic , and taxonomic  prime.Finally, the inclusion of different targets across the three relations in this study and in Sachs et al.  is less The primary purpose of Studies 3 and 4 was to replicate and extend the results found in Studies 1 and 2 using a more controlled set of items having the same target across each relation. We begin with an item analysis to further demonstrate distinct patterns on the co-occurrence measures of LSA and logGoogle across the three relations (Study 3). As mentioned in the Introduction, we extend this item analysis to also include BEAGLE cosines, feature similarity ratings, familiarity ratings. We also include our relation defining measures of relational integration, thematic relatedness relations, and category co-membership in order to verify our classification into relational categories. Next we investigate the extent to which these measures differentially predict lexical priming across the three relations using a standard LDT with 100, 500, and 800 ms SOAs (Study 4).As in Study 1, we minimized and equated association strength and assessed local co-occurrence or word pair frequency (Google hits), and global co-occurrence (LSA cosines and BEAGLE cosines). In addition to these database and computational measures, a total of 130 Wayne State University undergraduates provided ratings for categorical relatedness, thematic relatedness, integration, feature similarity, and familiarity. Each of these additional measures is described in detail below along with the relevance to semantic priming theories and the predicted differences across the three relations.nurse—doctor) are predicted to have higher BEAGLE cosines than those that are only associative  or only semantic . BEAGLE incorporates both “co-occurrence information”  and “transition information”  at a 250 ms SOA but not for the less similar pairs . Thematically related items are often based on the ability of the items to play complementary roles in the same scenario . However, many thematically related pairs  are based primarily on their complementary roles in the same event and are not dependent on the extent of overlapping features between items. Item pairs that share very few common features are possible candidates for integrative relations. Integrating two concepts into a single, modified concept requires very low overlap in features between items  between two concepts is partially determined by the distribution of common features among the items . Taxonomic categories are based on common features among category members  rated the feature similarity of each word pair on a scale from 1  to 7 (very similar). Feature similarity was emphasized in the instructions and differentiated via examples from association and co-occurrence. Instructions for this and all subsequent rating tasks are included in Appendix B. Based on the prior research described above, we predicted that feature similarity would be highest for the taxonomic pairs and lowest for the integrative pairs with the thematic pairs having a feature similarity intermediate between these two other relations.As in Estes and Jones , particiN = 21) rated the familiarity for each pair on a scale from 1 (unfamiliar) to 7 (very familiar). We also assessed the familiarity of our prime-target pairs. As previously mentioned, familiarity is moderately correlated with Google hits. In addition to highly frequent word pairs, familiarity is also likely to be high for words that seem to go together in a given event . Hence, we predict higher familiarity ratings for the integrative and thematic items than for the taxonomic pairs.As an additional measure of local co-occurrence or word pair frequency, participants  for the respective measure representing that relation . Additionally, each of the three measures should be reliably higher for the items in the represented relation than for the items in the other two relations . For each of the following three rating tasks, the 60 targets were presented with each of their prime-types and the presentation order of all 180 items was randomized across participants.N = 28) rated each pair from 1  to 7 (definitely co-members of the same specific category). Instructions distinguished taxonomic relatedness over thematic relatedness and relational integration by emphasizing co-membership in a specific category (see Appendix B).Because category membership is based on more than just feature similarity  rated the extent to which each pair of concepts was linked together in a common scenario, event, or function on a scale from 1  to 7 . Instructions emphasized that thematically related concepts were often not featurally similar (see Appendix B).Participants (r = 0.80). Participants (N = 29) rated the extent to which the word pair made sense as an object within a sentential context from 1  to 7 (completely sensible). The same sentence frame was used for each target across the three relations with the word pair shown in ALL CAPS as the object of each sentence . Note that in this integrative rating task, the integrative pairs  should have much higher ratings than the thematic pairs, which are not as readily integrative .To better distinguish integrative relations from thematic relations we used the sentential integrative rating task from Estes and Jones , which wBased on the results from the three relational verification rating tasks, we narrowed down the prior set of 180 items (60 per relation) to a final set of 132 items (44 per relation) in order to better minimize the degree to which items could represent more than one relation. This final set of items is shown in Appendix C.post-hoc tests .The means, SDs, minimums, and maximums on each of these measures  are shown for each relation in Table The inter-correlations among these measures for all 132 items are shown in Table ambulance siren, shower soap), we found no overall relationship between integrative and thematic ratings across our item set. The integrative ratings and category co-member  ratings were inversely related. Likewise, the inverse relationships between feature similarity and integrative ratings across all items are consistent with the dissociation between integrative  and taxonomic  pairs observed in lexical priming . These inverse correlations further underscore the difficulty (but not impossibility) of relationally integrating two highly similar items from the same category . Yet, as mentioned in the Introduction, there is also overlap between taxonomic and integrative relations. Despite our best efforts to tease apart the three relations in the creation of our item set, this overlap was reflected by a few items of our taxonomic and integrative pairs  that had high ratings across category co-membership, feature similarity, and integration. These items likely reduced the extent to which integrative ratings were inversely correlated with category co-membership and feature similarity. As shown in Table Despite the overlap between integrative and thematic relations in general and for some of our items  sometimes create more coherent categories than taxonomic relations . However, as demonstrated by the merely marginal correlation between thematic relatedness and feature similarity, members of thematic categories do not cohere around shared features. Rather, members of thematic categories are united by playing complementary roles in the same scenario or event  in comparison to feature similarity ratings (r = 0.26). This finding also corroborates the results of Maki and Buchanan's . Moreover, familiarity ratings were related to logGoogle, consistent with the findings of Wisniewski and Murphy (rs > 0.40) than these two measures were to each other indicate that BEAGLE cosines reflect both local and global co-occurrence. Indeed, this finding supports the BEAGLE model's incorporation of both “co-occurrence information”  and “transition information” , logGoogle was not related to feature similarity ratings. The three co-occurrence measures  were interrelated, though to a much lesser extent between logGoogle and LSA. The correlation between BEAGLE and LSA is consistent with that found by Jones and Mewhort  to their global integration model and to higher LSA cosines for their script-related items than their unrelated items. A similar study  to the integration of the prime concepts into a situation model . As with Chwilla and Kolk (deer—pony) used in Chiarello et al.  were particularly high for both the taxonomic and thematic pairs. For these items, we predict that the more global co-occurrence measures should facilitate priming effects by facilitating global integration  should predict lexical priming, particularly at short SOAs. The Embodied Conceptual Combination (ECCo) model  participated for partial course credit and were randomly assigned to the 100 ms SOA (N = 57), the 500 ms SOA (N = 105) or the 800 ms SOA (N = 61).Wayne State University undergraduates (http://elexicon.wustl.edu/) and compared across the three relations. A One-Way ANOVA found no reliable differences among the relations for prime length, F < 1, p = 0.78, or prime RTs, F = 1.05, p = 0.35. However, prime frequencies differed among the relations, F = 3.12, p < 0.05, with reliably greater frequencies for the integrative primes  and marginally greater frequencies for the thematic primes  in comparison to the taxonomic primes .Experimental items consisted of the final set of items from Study 3 (see Appendix C). As in Study 2, prime frequencies (logHAL), length, and RTs were taken from the ELP website . As in prior studies , thematic prime , taxonomic prime , or an unrelated prime . An additional 44 filler trials consisted of a real word prime followed by a non-word target  and there were no reliable main effects or interactions (p > 0.20).RTs from incorrect trials (1.4% of the data) were excluded from analyses in addition to RTs greater than 1500 ms and any remaining RTs greater than 2.5 SDs above or below each participant's condition mean . Mean response times and accuracies were analyzed using a 3  ×4  ANOVA across participants Fp  = 11.96, p < 0.001, η2p = 0.05, and Fi  = 10.28, p < 0.001, η2p = 0.19. There was no main effect of SOA by subjects, Fp  = 1.68, p = 0.19. Within the item analysis, RTs did not differ between the 500 ms and 800 ms SOAs (both Ms = 667), but were faster than in the 100 ms SOA (M = 701), Fi  = 50.69, p < 0.001. There was not an interaction between SOA and Relation, Fp  < 1, p = 0.51, and Fi  = 1.35, p = 0.24.Mean RTs and priming effects are shown in Table Fp  < 1, p = 0.56, and Fi  < 1, p = 0.54, or among the SOAs, Fp < 1, p = 0.86, and Fi  < 1, p = 0.88, nor was there a reliable interaction, Fp  = 1.28, p = 0.28, and Fi  = 1.96, p = 0.10. The consistent priming effects among all three relations across the SOAs replicates the pattern of results found in Study 2 and in our earlier study using neutral primes  × 3 (Relation) ANOVA with priming effects (unrelated RTs—related RTs) as the dependent measure. Priming effects did not differ among the three relations, p < 0.10) and reliable (p < 0.05) predictors found in the partial correlation analyses were then further examined in hierarchical stepwise regression analyses for the applicable SOA's target RTs with the same control variables  entered into the first block and the marginal and reliable correlates entered into the second block. Variables that had beta coefficients with significance levels greater than 0.05 were excluded from the best fitting model.Though priming effects were equivalent among the three relations within each SOA, different underlying measures were related to priming within each relation at each SOA  along with baseline target RTs  as the best fitting model, r = 0.63, R2 = 0.40, F = 13.28, p < 0.001. Moreover, the addition of logGoogle was reliably more predictive of target RTs in the 100 ms SOA than only the baseline target RTs in Model 1, Δ R2 = 0.17, F = 11.04, p < 0.01. Either compound-cue theory or the ECCo theory may explain these effects at this short 100 ms SOA. That is, the more familiar or frequently co-occurring the word pair, the easier it is to retrieve the representation of that entity from memory. The current results suggest a very rapid process of retrieval consistent with the ECCo model and compound-cue theories.Local co-occurrence (word pair frequencies) as measured by logGoogle was reliably related to the target RTs at the 100 ms SOA. Additionally, we found a marginal correlation between feature similarity ratings and target RTs at this short SOA. No other variables approached conventional levels of significance. These correlates (logGoogle and feature similarity ratings) and the criterion measure of target RTs for the 100 ms SOA were entered into a hierarchical stepwise regression model with only the control variables entered in the first block and the predictors added to the second block. Results demonstrated that the inclusion of logGoogle , baseline prime RTs , and logGoogle , r = 0.58, R2 = 0.33, F = 6.50, p = 0.001. The addition of logGoogle to the model explained more of the variance than just the two control variables alone, Δ R2 = 0.08, F = 4.69, p < 0.05. Within the 800 ms SOA, the best fitting model included only the baseline target RTs  and BEAGLE cosines , r = 0.54, R2 = 0.29, F = 8.30, p = 0.001. Moreover, the inclusion of BEAGLE cosines accounted for more of the variance than baseline target RTs alone, Δ R2 = 0.09, F = 5.11, p < 0.05.In contrast to the results for the integrative items, no predictors were reliably related to target RTs at the 100 ms SOA. Word pair frequencies (logGoogle) were related to target RTs at only the 500 ms SOA but did not approach significance at the shorter 100 ms or the longer 800 ms SOAs. Interestingly, the co-occurrence measures (LSA and BEAGLE) and feature similarity were related to word recognition target RTs at the 800 ms SOAs  but not at the 100 or 500 ms SOAs. As before, within the applicable SOAs, we included the marginal and reliable correlates along with the control variables in the hierarchical stepwise regression analyses to determine whether these co-occurrence variables explained the variance in target RTs above and beyond the control variables. Within the 500 ms SOA, the best fitting model included baseline target RTs . These primes were presented for 400 ms and the N400 effect occurred an additional 400–500 ms following target presentation for a total duration of approximately 800 ms following prime onset. Hence, our results are consistent with the global integration model proposed by Chwilla and Kolk . Most importantly, these results are the first to demonstrate a key difference in the underlying influences of lexical priming between integrative pairs  and thematic pairs .Our results for the 800 ms SOA corroborate those of prior studies  and logGoogle, , r = 0.67, R2 = 0.45, F = 16.09, p < 0.001. The addition of logGoogle accounted for additional variance in target RTs, Δ R2 = 0.08, F = 5.96, p < 0.05. Within the 800 ms SOA, the best fitting model included baseline target RTs and BEAGLE cosines, r = 0.43, R2 = 0.18, F = 4.47, p < 0.05. The addition of BEAGLE cosines accounted for additional variance in target RTs, Δ R2 = 0.08, F = 4.01, p = 0.05. Moreover, in this model the BEAGLE cosines  were a reliable predictor, whereas the baseline target RTs were not .The pattern of results for the taxonomic items across the three SOAs was somewhat similar to that of the thematic items. Within the 500 ms SOA, only word pair frequencies (logGoogle) were reliably correlated with target RTs. Yet in contrast to the thematic items, only the BEAGLE cosines were reliably related to target RTs within the 800 ms SOA. In the regression analyses, the pattern of results was identical to that for the thematic items. Within the 500 ms SOA, the best fitting model included baseline target RTs  and thematic pairs , with relatively less distinction between the thematic and taxonomic items. Integrative pairs were lower in global co-occurrence  and feature similarity (Study 3) in comparison to thematic and taxonomic pairs. We also found distinct patterns of correlations between each of the relational classification ratings  and the other measures, thereby further distinguishing among these relations . This distinction between integrative and thematic relations is an important finding for semantic relation researchers using both behavioral and neuroscience methods. For instance, would additional areas of brain activation result for pairs that are both integrative and thematic? On a related note, could the earlier activation obtained for thematic in comparison to taxonomic pairs in earlier studies , may exhibit distinct priming characteristics, time courses of activation, and/or underlying neural regions of activation in comparison to thematic relations that are less easily integrated .We demonstrated distinct patterns of underlying factors  among weakly associated integrative, thematic, and taxonomic pairs for a large item set with different targets taken from the SPP (Study 1) and for a smaller more controlled item set having the same target across the relations (Study 3). Most notably, our results were the first to demonstrate a distinction between integrative pairs (e.g., Despite the distinct pattern on these measures for each relation we found no differences in overall priming magnitudes among the relations in Studies 2 and 4. Recall that prior studies had previously shown such a dissociation between thematic and taxonomic relations in regards to time course and/or strength of activation (generally with earlier and/or more robust activation for thematic than taxonomic items Sachs et al., Association strength poses an additional variable that should be examined further. In our current research, we focused on only weakly associated integrative, thematic, and taxonomic pairs, because the associative boost found in prior studies with taxonomic pairs (Moss et al., The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Whether H2A.Z is involved in p21 activity in the absence of p53 is not known. The p21 gene is repressed in estrogen receptor (ER) negative cell lines that are p53−/− and hormone independent for their growth. Here we demonstrate that class I and II pan Histone deacetylase inhibitors (HDACi) induce p21 transcription and reduce cell proliferation of MDA-MB231, an ERα-negative mammary tumor cell line, in a H2A.Z dependent manner. H2A.Z is associated with the transcription start site (TSS) of the repressed p21 gene. Depleting H2A.Z did not lead to transcription of p21 but annihilated the stimulating effect of HDACi on this gene. Acetylation of H2A.Z but not of H3K9 at the p21 promoter correlated with p21 activation. We further show that HDACi treatment reduced the presence of the p400 chromatin remodeler at the p21 TSS. We propose a model in which association of p400 negatively affects p21 transcription by interfering with acetylation of H2A.Z.Differential positioning of the histone variant H2A.Z in a p53 dependent manner was shown to regulate  Much of research on HDAC inhibitors has focused on the upregulation of p21. Activation of p21 involves acetylation of promoter chromatin, but the mechanism remains poorly understood Estrogen receptor negative breast cancer types are generally more aggressive and prone to metastasize. The absence of Estrogen receptor-alpha (ERα) correlates with hormone-independent growth of these mammary tumor cells and causes uncontrolled proliferation and insensitivity to anti-hormonal treatments. In ERα-negative cell lines, a subset of genes is epigenetically silenced p21 at the p53 binding sites in p53+/+ cells (U2oS) p21 expression p21 promoter. Depleting p400 by siRNA increases p21 expression in a p53 dependent manner and induces premature senescence The histone variant H2A.Z has been shown to bind to the promoter of p21 in response to HDACi treatment of these ERα-negative cells requires H2A.Z acetylation and exchange at its transcription start site.In the ERα-negative breast cancer cell line MDA-MB231 p53 is mutated and non-functional. Here we show that activation of −8 or 5×10−9 M for the indicated times. 4×106 MDA-MB231 cells where mock-transfected (pcDNA3.1) or transfected with 2µg of pcDNA3.1/Tip60 (gifts from Dr. Didier Trouche) with Amaxa® Cell line Nucleofactor Kit V program X-013 according to the manufacturer’s protocol. MDA-MB231 cells were mock-transfected or transfected with H2A.Z siRNA ON-TARGET plus SMARTpool or scrambled (scr) siRNA (Dharmacon Thermo Scientific) with Interferine (Ozyme) according to the manufacturer’s protocol. Tip60 siRNA MDA-MB231, Hs-578T and HeLa cells were purchased from ATCC (used up to 15 passages). All cell lines were maintained in Dulbecco’s modified Eagle’s medium (DMEM) with Glutamax containing 50 mg/ml gentamicin, 1 mM sodium pyruvate and 10% heat-inactivated fetal calf serum (FCS) (Invitrogen). MDA-MB231 cells were treated with 50 or 100 ng/ml TSA (Sigma-Aldrich) and with LBH589 5×10realplex (Eppendorf) using the platinum SYBR Green q-PCR SuperMix (Invitrogen) according to the manufacturer’s instructions. Amplification conditions: 1 min at 50°C, 3 min at 95°C followed by 40 cycles . q-PCR for RPLP0 mRNA was used as an internal control. The primers used in q-PCR: CDKN1A : 5′-GGAAGACCATGTGGACCTGT-3′ and 5′-GGATTAGGGCTTCCTCTTGG-3′, H2AFZ: 5′-CCTTTTCTCTGCCTTGCTTG-3′ and 5′-CGGTGAGGTACTCCAGGATG-3′, RPLP0: 5′-TGGCAGCATCTACAACCCTGAA-3′ and 5′- CACTGGCAACATTGCGGACA-3′, TIP60:5′-CAGGACAGCTCTGATGGAATAC-3′ and 5′-AGAGGACAGGCAATGTGGTGAG-3′, p400: 5′-TGGCAGAGACTTGCTAAGGA-3′ and 5′-AGCGTCAACATCAGCTCACT-3′Total RNA was extracted using an RNeasy mini-kit (Qiagen) and eluted with 35 µl of RNAase-free water. First strand cDNA was generated using 1 or 2 µg of total RNA in a reaction containing random oligonucleotides as primers with the ThermoScript RT-PCR system (Invitrogen). Real-time PCR was performed on a Mastercycler® ep p21 gene. The primers used in q-PCR are listed here: Primers 1:5′-TCAATGCCACCACCTTAACA-3′ and 5′-AGAGAGGCATCCTCCAGACA-3′, Primers 2:5′-CTGTGGCTCTGATTGGCTTT-3′ and 5′-CTCCTACCATCCCCTTCCTC-3′, Primers 3:5′-GAAATGCCTGAAAGCAGAGG-3′ and 5′-GTCTGCACCTTCGCTCCTAT-3′, Primers 4 (TSS): 5′-ACTGGGGGAGGAGGGAAGT-3′ and 5′-AGCTGAGCCTGGCCGAGT-3′, Primers 5:5′-CCAGGAAGGGCGAGGAAA-3′ and 5′-GGGACCGATCCTAGACGAACTT-3′, Primers 6:5′-AGCCGGAGTGGAAGCAGA-3′ and 5′-AGTGATGAGTCAGTTTCCTGCAAG-3′, Primers 7: 5′-GCACCATCCTGGACTCAAGTAGT-3′ and 5′-CGGTTACTTGGGAGGCTGAA-3′.ChIP analyses were performed as described previously ueous One Solution Cell Proliferation Assay (Promega) according to the manufacturer’s instructions. For Trypan blue assay, 2×105 cells seeded in 35 mm dishes. Cells were harvested and counted by trypan blue staining at indicated times following the different treatments.MTT assay was performed using CellTiter 96® AQp21 gene and its regulatory pathway. As previously described for pan HDACi p21 transcription was greatly activated in cells exposed to TSA for 24 h in which we detected >3-fold increase in p21 mRNA levels  breast cancer cell lines is estrogen-independent. A priority in breast cancer treatment is the development of agents able to contain or reduce growth of these cell types, which are more aggressive and insensitive to antiestrogens used to control estrogen responsive tumors. ERα- cells, MDA-MB231, were grown in standard medium and treated with the histone deacetylase inhibitors (HDACi) Trichostatin A (TSA) or panobinostat (LBH589). Cell growth was arrested by 50 or 100 ng/ml TSA  and 50 nA levels  and a maA levels , S1d.p21 gene is mediated by dynamic binding of the histone variant H2A.Z to p53 binding sites within the p21 promoter region in p53 positive cells, such as ERα-positive MCF-7 (data not shown) or U2OS cells p21 promoter in these cells as was shown to be the case in the p53- osteosarcoma, SaOS cell line p21 gene. The amplified fragment  reduced growth of MG63 osteosarcoma, p53−/− cells and activated various p21 promoter constructs driving a luciferase reporter gene p21 gene is also activated by TSA or LBH589 in ERα- mammary tumor cells whose growth rate is insensitive to hormones and antihormones. In this study we provide a comprehensive analysis of the activation of the p21 gene in ERα- MDA-MB231 cells which provides a mechanistic link between histone acetylation, H2A.Z variant incorporation and p21 mediated growth arrest.Lack of regulation of the p21 gene, H2A.Z was present at the TSS in ERα- cells. H2A.Z binding to the TSS was frequently been observed in yeast TFF1, PGR or CCND1p21 expression in MDA-MB231 cells. This observation correlates with previous studies showing that a 50% reduction H2A.Z association was not sufficient to induce changes in gene regulation Unlike in p53 positive cells, U2OS osteosarcoma or MCF-7 cells, where the histone variant H2A.Z is associated with the p53 binding sites of the inactive et al. showed that p400 and H2A.Z associate with the repressed p21 gene in U2OS cells p21 activation et al., however, demonstrated that p400 inhibits TIP60 activity by direct binding to TIP60 via its SANT domain In 2007 Gevry p21. Under these conditions, binding of p400 and H2A.Z to the p21 promoter was reduced, but the concomitant increase in H2A.Z acetylation was independent of TIP60. Furthermore, depleting p400 also stimulated p21 expression independently of TIP60 suggesting that p400 exerts a repressive effect. In contrast, depleting H2A.Z was not sufficient to mediate p21 repression under normal conditions but it played a central role in p21 activation upon TSA treatment. We propose that acetylation of H2A.Z rather than H2A.Z per se is important to drive proper p21 gene expression. A ratio in favor of acetylated H2A.Z was associated with p21 activation upon TSA treatment. This observation corroborates findings by Valdes-Mora and colleagues who recently correlated aberrant gene expression in prostate cancer cells with H2A.Z acetylation at specific promoters p21 activation by catalysing H2A.Z eviction and allowing the recruitment of HATs such as p300.In ER-negative, p53 mutant breast cancer cell lines, TSA treatment activates p21 promoter at several Sp1 sites and independently of p53 as part of a multiprotein complex which also contains PR and Sp1 p21 promoter at levels proportional to transcriptional activity. Hence, the cofactors required for p21 activation are distinct in p53 negative compared to positive cells p21 does not obey to the classical pathways, open new avenues for growth control therapies.The histone-acetyltransferase CBP/p300 has been shown to act on the Hua et al. Figure S1p21 is activated in response to pan HDAC class I and II inhibitors. a) MTT assay to quantify proliferation rates in the presence of LBH589 of MDA-MB231 cells cultured in rich medium. Two different concentrations (5*10−9 M and 5*10−8 M) were used. b) q-PCR analysis of p21 mRNA expression levels. c) p21 mRNA expression level in MDA-MB231 treated or not with LBH589 (5*10−9 M) for 48 h and/or transfected with a smartpool siH2A.Z (72 h) as indicated. d) Western blot analysis of p21 protein levels after 24 h of TSA treatment at the indicated doses.(PDF)Click here for additional data file.Figure S2H2A.Z specifically regulates p21 in ERα-negative breast cancers following HDAC inhibitor treatment. a, b, c, d) q-PCR analysis of p21 and H2A.Z mRNA expression in Hela  and in Hs-578T  cells. Cells were treated with siH2A.Z or scramble siRNA and treated for 24 h with two different concentrations of TSA.(PDF)Click here for additional data file.


This study examines the association between cultural orientation and drinking behaviors among university students. Cultural orientation is the measure of how the cultural values of individuals living in their own society are influenced by cultural values introduced from the outside.In 2011, a cross-sectional survey collected data from 1279 university students from six universities in central China. Participants used a likert scale to rank a series of statements reflecting cultural values from the previously validated Chinese Cultural Orientation Scale and answered questions about their drinking behaviors and socio-demographic characteristics.OR = 1.80, P<0.05) and marginal orientation  increased the likelihood of the student being regular drinking, compared to students with traditional orientations. Males  had a higher likelihood of regular drinking than females, graduate students  had a higher likelihood of regular drinking than undergraduates, students from urban areas  had a higher likelihood of regular drinking than those from towns/rural areas, and students attending key universities  had a lower likelihood of regular drinking than those attending general universities.Statistically significant differences in cultural orientation were observed for gender, hometown and type of university attendance. Traditional-oriented students were more likely to be occasional drinkers or nondrinkers, while marginal-oriented students, bicultural-oriented students and western-oriented students were more likely to be regular drinkers. Bicultural orientation (Cultural orientation influences drinking behaviors. Traditional cultural orientation was associated with less drinking while western cultural orientation, marginal cultural orientation and bicultural orientation were associated with more drinking. The role of gender, hometown and university attendance is partially moderated through the influence of cultural orientation. The relationship between a traditional cultural orientation and alcohol drinking suggests that traditional Chinese cultural values should be examined for their role in possibly reducing alcohol-related risks through education and policy initiatives. Reducing alcohol use, and high risk drinking patterns are important public health challenges, especially in countries experiencing rapid change. To develop effective programs to reduce alcohol related risks there is a need to better understand psychosocial and cultural influences on drinking behavior. In societies where alcohol is an integral part of social life and is largely unregulated by law it is especially important to understand the psychological and cultural aspects of drinking behavior In China, historical records indicate that alcohol has been used for thousands of years and is today an accepted part of daily life. Drinking patterns are deeply rooted in Chinese culture and daily life. Nevertheless, some patterns of alcohol use have detrimental effects on health. WHO When individuals living in their own society absorb new and different cultural values and attitudes as a result of exposure to media, education, cross-cultural relationships and foreign individuals and products their traditional cultural values are challenged. The degree to which an individual accepts or rejects the new or imported values relative to retaining their traditional indigenous value system reflects his or her cultural orientation This study describes the cultural orientation of Chinese college students who are reconciling their traditional cultures with foreign cultures while remaining in their country of origin.In the last three decades, following China’s opening to the west, there have been significant social, ideological, and cultural changes. At the same time alcohol drinking patterns have changed and traditional values have been increasingly challenged by outside influences especially western influences. Drinking behaviors often change along with changes in cultural practices and socio-cultural environment. Eide and Acuda et al We conducted a questionnaire survey among university students in China to examine the relationship between cultural orientation and drinking behavior. Also we took into account possible moderating factors like gender, hometown, grade and type of university attended. We believe that a better understanding of the psychosocial and cultural influences that affect drinking behavior can be useful to both researchers and public health practitioners working for drinking behavioral intervention and the betterment of related policies.There are several reasons for choosing university students as our respondents. First, the college environment, at least in the west seems to support increased alcohol consumption This study was reviewed and approved by the ethical committee of School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. The participation of this study was voluntary and confidentiality of the information assured. All participants signed an informed consent form prior to the investigation.u&Bentler Cultural orientation was measured by using the CCOS instrument, which contained 67 items representing ten subscales reflecting either Western or traditional cultural values. This instrument was developed over several years by the University of Nebraska-Lincoln and the Chinese Health Education Center Second-order factor analysis confirmed the bi-dimensional model of separate higher-order factors of westernization and traditionality found in previous work Drinking status was assessed by measuring the drinking frequency within the last year and the last 30 days. Shell, Newman and Qian have used this measure to categorize drinkers and nondrinkers by drinking frequency in several studies Participants were a sample of 1279 students from six universities in Wuhan, China. Stratified cluster sampling was used to select the students. Strata were created based on gender. Student dormitory buildings were the secondary sampling units. In each university, one boy’s building was selected and one girl’s building was selected. From the six universities, twelve dormitory buildings were selected and each student of the buildings was asked to participate. Because of some no-response and some missing data, the total number of valid return was 1242 with a response rate of 97.11%. Of these, 634 (51.05%) were males and 608 (48.95%) were females. Mean age of the 1242 students was 21.22 years old (a range of 17–30 years old). Mean age was 21.57 years old (a range of 17–30 years old) for males and 20.85 years old (a range of 17–28 years old) for females; There were 365 (29.39%) freshmen, 91 (7.33%) sophomore, 402 (32.37%) junior, 220 (17.71%) senior and 164 (13.20%) graduate students; 902 (72.62%) students came from urban areas and 340 (27.38%) from towns or rural areas; 806 (64.90%) students came from key universities and 436 (35.10%) from general universities. In China, key universities are more prestigious, accepting students with higher entrance exam scores and receiving greater support from the central government.This cross-sectional survey took place in 2011. Data collectors were university counselors or student leaders who had previous experience with conducting epidemiological surveys. All data collectors completed two days of training. Survey questions included information on demographic characteristics, alcohol drinking behavior and cultural orientation. Data collectors administered the questionnaire under the supervision of one of co-authors in this study. Emphasis was placed on answering the self-rated questionnaire independently, honestly and accurately. The questionnaire took approximately 30 minutes to complete.P<0.05. We used SAS version 9.2 for all statistical analyses.Demographic differences and drinking behaviors in cultural orientations were examined using Chi-square test. Multinomial logistic regression analyses were performed to examine the relationship between cultural orientation and drinking behaviors, controlling for the socio-demographic characteristics of gender, grade, hometown and type of university. The significance set at Chi-square measures of association were calculated to assess variations in cultural orientation among different socio-demographic groups. Our findings indicate that cultural orientation is related to drinking behaviors among Chinese university students, similar to the findings of previous studies Although the mechanism for how cultural orientation may affect patterns of alcohol use is not fully understood, there are some possible explanations. Traditionally oriented students possible drink less because they value traditional Chinese values, which evolved over time to support low risk drinking behavior. Values that did not support low risk drinking would threaten the survival of the society.Counter intuitively and unlike some prior research It appears that the two mixed cultural orientations create the highest risk factors for problem drinking. In both orientations, individuals do not have a clear identity. Bicultural individuals who endorse values from both the receiving and traditional cultural contexts may find themselves without a clear value system and able to vary their position depending on the circumstances Our findings confirmed gender differences in alcohol use, that is, males tend to be higher frequent drinkers, similar to the findings of Shell and colleagues Graduate students were more likely to be regular drinkers than undergraduates. A scant amount of literature has shown the specific differences between the two populations. Our findings confirm the findings of Wang and Zhang’s study among university students in Beijing that graduate students were prone to be to drink more Students who came from an urban area tended to be higher frequent drinkers than those from town/rural area. Zhou’s study in Hunan Province in China showed that the drinking rates were higher in the urban area (45.9%) than in the rural area (39.6%) Key university attendance was associated with less drinking than general university attendance. Key universities refer to universities recognized as prestigious and which received a high level of support from the central government with different campus culture and model of teaching from general universities. Our findings suggest the type of university attended was associated with cultural orientation. Students in key university were more likely to be western-oriented. Despite this they drank less, possibly the result of the heavy time requirements for academic success that leave little time for recreational activities that might include alcohol use. It may be the case that key students, like students in Western colleges, drink fewer times but drink more each time they drink. This possibility clearly needs further study.In summary, culture orientation had an important impact on drinking behaviors. The role of gender, hometown and university type on drinking behaviors is partially mediated through the influences of culture orientation. The significance of our findings could be considered as the basis for alcohol policy and program development. These factors that differentially contribute to alcohol use deserve careful and detailed attention in efforts to reduce alcohol drinking. Reinforcing traditional beliefs and values may be beneficial for less drinking. In the meantime, significant changes in the formal policy environment at the university level seem to be indispensable. Specific strategies of preventive intervention would meet specific population, considering the role of gender, hometown, campus environment and graduate students/undergraduates.Several limitations of this study should be mentioned. First, it should be noted that this study only took place in a single city in China. Whether the findings would generalize to other parts of China is unknown. Second, the study is cross-sectional. Data on drinking patterns over time and cultural orientation changes over time may provide new insights into their relationship. Finally, the continued development of the CCOS is also needed to enhance reliability and validity. At the same time a more detailed analysis of the relationships of drinking and other variables could help in understanding problematic drinking pattern