Software testing is an important factor of the software development process. Integration testing is an important and expensive level of the software testing process. Unfortunately, since the developers have limited time to perform integration testing and debugging and integration testing becomes very hard as the combinations grow in size, the chain of calls from one module to another grow in number, length, and complexity. This research is about providing new methodology for integration testing to reduce the number of test cases needed to a significant degree while returning as much of its effectiveness as possible. The proposed approach shows the best order in which to integrate the classes currently available for integration and the external method calls that should be tested and in their order for maximum effectiveness. Our approach limits the number of integration test cases. The integration test cases number depends mainly on the dependency among modules and on the number of the integrated classes in the application. The dependency among modules is determined by using an information retrieval technique called Latent Semantic Indexing (LSI). In addition, this research extends the mutation testing for use in integration testing as a method to evaluate the effectiveness of the integration testing process. We have developed a set of integration mutation operators to support development of integration mutation testing. We have conducted experiments based on ten Java applications. To evaluate the proposed methodology, we have created mutants using new mutation operators that exercise the integration testing. Our experiments show that the test cases killed more than 60% of the created mutants.

The thesis deals with latent criminality as a dynamic criminality phenomenon. The first chapter is dedicated to the scientific discipline of criminology, which examines criminality as a whole, criminality itself and terms which define criminality, such as scope, level, structure and dynamic. The second chapter deals directly with latent criminality. It lists all that is included in latent criminality and its relation to registered criminality. The chapter describes the possible causes and brings closer all the methods for examining it. The most common of those are victimization method and self-reporting investigation. One of the main causes of crime latency is the victim's failure to report. The third chapter is therefore dedicated to crime victims. It lists the differences between a victim and an injured party and describes the relation between victim and perpetrator. This chapter also ties to the victim's consent with prosecution, which can be influenced by the aforementioned relation to the perpetrator. In the fourth chapter, criminality is divided into individual types. Apart from definitions of the different criminality types, such as property offences, violent, moral and economic criminality, the thesis here details the statistical indicators of these criminality types (number of crimes...

TOPICAL ANALYSIS OF FAKE NEWS 4 Abstract Since the 2016 US presidential campaign of Donald Trump, the term "fake news" has permeated mainstream discourse. The proliferation of disinformation and false narratives on social media platforms has caused concern in security circles in both the United States and European Union. Combining latent Dirichlet allocation, a machine learning method for text mining, with themes on topical analysis, ideology and social identity drawn from Critical Discourse theory, this thesis examines the elaborate fake news environments of two well-known English language websites: InfoWars and Sputnik News. Through the exploration of the ideologies and social representations at play in the larger thematic structure of these websites, a picture of two very different platforms emerges. One, a white dominant, somewhat isolationist counterculture mindset that promotes a racist and bigoted view of the world. Another, a more subtle world order-making perspective intent on reaching people in the realm of the mundane. Keywords: fake news, Sputnik, InfoWars, topical analysis, latent Dirichlet allocation Od americké prezidentské kampaně Donalda Trumpa z roku 2016, termín "fake news" (doslovně falešné zprávy) pronikl do mainstreamového diskurzu. Šíření dezinformací a falešných zpráv na platformách...

Latent prints can be used as evidence in crime scenes to connect individuals to the location of a potential crime. In some cases, perpetrators may handle partially eaten fruits at the scene of a crime and leave latent fingerprints on the surface of the fruit. Plant leaves of common household ornamental plants and regional shrubs may also be a potential source of latent prints. Fruits, vegetables, and plant leaves have not been extensively studied as substrates for fingerprint development. In order to assess the feasibility of developing and visualizing latent prints on fruits, vegetable, and plant leaf surfaces, black and white fingerprint powder, bi-chromatic magnetic powder, and LumicyanoTM superglue fuming were utilized on tomato, zucchini, cucumber, acorn squash, carrot, mango, plum, pear, orange, pepper, banana, watermelon, Rhododendron leaf, Philodendron leaf, and Jasmine leaf. An aging study up to sixteen days was also conducted on eight of the fifteen substrates to determine the effects of aging on latent fingerprint impression development. Latent prints were recovered from all surfaces with the three techniques. Using a scoring system of 0-2, in which 2 represents the presence of six or more minutiae and 0 represents the lack of minutiae, impressions developed with fingerprint powder scored the highest average across all substrates. The aging study revealed a general decline in the quality of the latent prints over time with LumicyanoTM fuming performing the best.

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Obsessive-compulsive disorder (OCD) is relatively common (Ruscio, Stein, Chiu, & Kessler, 2010) and leads to significant functional impairment (World Health Organization, 2001). Research suggests that exposure and response prevention (EX/RP) is efficacious for reducing OCD symptoms (NICE, 2006); however, standard outpatient EX/RP does not effectively alleviate symptom severity among a substantial proportion of OCD patients (Abramowitz, 2006). Intensive EX/RP programs have been developed to address the needs of treatment-refractory OCD patients (Veale et al., 2016). While evidence from effectiveness studies suggests that intensive EX/RP programs lead to significant reductions in OCD symptom severity, a portion of patients do not demonstrate improvement in response to intensive treatment (e.g., Björgvinsson, Hart, et al., 2013; Boschen, Drummond, & Pillay, 2008). These findings underscore the need to identify reliable predictors of OCD patient response to intensive EX/RP to help target clinical and research efforts toward improving treatment outcomes for those least likely to respond to current treatment modalities. Therefore, the proposed study evaluated distinct trajectories of OCD symptom change across six-weeks of intensive treatment and examined factors that predict membership in those trajectory groups. Results suggested that three latent subgroups of OCD patients emerged with one demonstrating symptom relapse during intensive treatment. Further, OCD symptom severity was the only baseline factor that predicted latent-class membership. Implications and future directions of research are discussed.

Most psychoneuroimmunology research examines individual proteins; however, some studies have used summed score composites of all available inflammatory markers without evaluating the appropriateness of this decision. Using three different samples (MIDUS-2: N = 1,255 adults, MIDUS-R: N =863 adults, and ACE: N = 315 adolescents), this study investigates the dimensionality of eight inflammatory proteins (C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-α (TNF-α), fibrinogen, E-selectin, and intercellular adhesion molecule (ICAM)-1) and compares the resulting factor structure to a) an “a priori” factor structure in which all inflammatory proteins equally load onto a single dimension (a technique that has been used previously) and b) proteins modeled individually (i.e., no latent variable) in terms of model fit, replicability, reliability, temporal stability, and their associations with medical history and depression symptoms. A hierarchical factor structure with two first-order factors (Factor 1A: CRP, IL-6, fibrinogen; Factor 2A: TNF-α, IL-8, IL-10, ICAM-1, IL-6) and a second-order general inflammation factor was identified in MIDUS-2 and replicated in MIDUS-R and partially replicated in ACE (which unfortunately only had CRP, IL-6, IL-8, IL-10, and TNF-α but, unlike the other two, has longitudinal data). Both the empirically-identified structure and modeling proteins individually fit the data better compared to the one-dimensional “a priori” structure. Results did not clearly indicate whether the empirically-identified factor structure or the individual proteins modeled without a latent variable had superior model fit. Modeling the empirically-identified factors and individual proteins (without a latent factor) as outcomes of medical diagnoses resulted in comparable conclusions, but modeling empirically-identified factors resulted in fewer results “lost” to correction for multiple comparisons. Importantly, when the factor scores were recreated in a longitudinal dataset, none of the individual proteins, the “a priori” factor, or the empirically-identified general inflammation factor significantly predicted concurrent depression symptoms in multilevel models. However, both empirically-identified first-order factors were significantly associated with depression, in opposite directions. Measurement properties are reported for the different aggregates and individual proteins as appropriate, which can be used in the design and interpretation of future studies. These results indicate that modeling inflammation as a unidimensional construct equally associated with all available proteins does not fit the data well. Instead, empirically-supported aggregates of inflammation, or individual inflammatory markers, should be used in accordance with theory. Further, the aggregation of shared variance achieved by constructing empirically-supported aggregates might increase predictive validity compared to other modeling choices, maximizing statistical power. / Psychology

Early identification of emotional and behavioral disorders is critical in ensuring that students receive the interventions and supports necessary for school success. While externalizing and internalizing behaviors often occur comorbidly, more research is needed to understand how different subtypes of these behaviors may manifest, especially in the early elementary school years. Further, as schools increase their emphasis on universal, evidence-based interventions as tools for preventing the development of later social-emotional and behavior challenges, it is important to understand how different groups of students respond to such interventions. In the present study, I explored the behavioral and emotional profiles of 470 second-grade students using latent profile analysis. I also examined how students transitioned between profiles over the course of one school year (i.e., fall to spring) within the context of a social-emotional intervention (Social Skills Improvement System-Classwide Intervention Program, SSIS-CIP; Elliott & Gresham, 2007). Additionally, I used multinomial logistic regression analyses to examine if child race, gender, teacher-student relationship, and treatment condition (intervention vs. control) predicted profile membership and transition over the course of a school year. I used five behavioral composites from the Social Skills Improvement System Rating Scales-Teacher Form (SSIS-RST; Gresham & Elliott, 2008) to create the student profiles. Three profiles of students emerged in the present study. The first profile (normative) was characterized by the lowest levels of all five externalizing and internalizing behaviors. The second profile (at-risk) demonstrated elevated levels of impulsive behaviors, conduct problems, and emotion dysregulation, with less elevated levels of bullying. The third profile (comorbid) demonstrated elevated levels of all five externalizing and internalizing behaviors. From fall to spring, students in the normative profile exhibited a 93% probability of remaining in the normative profile. Students in the at-risk profile demonstrated a similarly high likelihood of remaining in the at-risk profile over time (72%), while students in the comorbid profile experienced a 57% chance of remaining in the comorbid profile over time. Teachers’ observed emotional support, child race, child gender, and participation in the SSIS-CIP intervention were all predictors of profile movement, however, the associations varied across the different profiles. Results of the present study suggest the SSIS-CIP may function as a preventative tool for students identified within the normative group as well as an effective intervention for those students with the most severe behavioral presentations. Consistent with previous research, teachers rated males and students of color higher on measures of externalizing behaviors. Notably, while female students were less likely to be identified in the comorbid profile in the fall, they were more likely to remain in that profile over time compared to male students who were identified in the comorbid profile in the fall. Surprisingly, teacher emotional support was negatively associated with movement from the at-risk group to the normative group. Future research should continue to explore the ways in which externalizing and internalizing behaviors manifest in young children as well as the intersection between gender and race as it relates to teachers’ ratings of students’ behaviors. / School Psychology

An analysis to determine physical and spatial patterns of the surface latent heat flux (LHF) and near surface (5m) salinity (NSS) beneath tropical cyclones (TCs) in the North Atlantic and eastern North Pacific basins during the first 24 hours of rapid intensification (RI) was conducted using empirical orthogonal function (EOF) analysis. To determine if these patterns were unique to RI, TC RI cases were compared to three non-RI intensification thresholds, 10 kt, 15 kt and 20 kt, for both LHF and NSS. Though similarities exist between non-RI and RI cases physical and spatial patterns unique to the RI cases did exist. Sea surface temperatures associated with statistically identified TC groups were assessed for their potential influence on RI. While inconclusive in the eastern North Pacific, NSS in the Atlantic may play a role for RI TCs in areas affected by river discharge from South America.

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