Bullying, School Violence, and Climate in Evolving Contexts

2018 ◽  
Author(s):  
Ron Avi Astor ◽  
Rami Benbenisthty
Keyword(s):  
School Violence ◽  
School Safety ◽  
Media Coverage ◽  
Large Scale ◽  
Ecological Model ◽  
Empirical Studies ◽  
Practical Applications ◽  
Teacher Student ◽  
Area Of Interest ◽  
New Research

Since 2005, the bullying, school violence, and school safety literatures have expanded dramatically in content, disciplines, and empirical studies. However, with this massive expansion of research, there is also a surprising lack of theoretical and empirical direction to guide efforts on how to advance our basic science and practical applications of this growing scientific area of interest. Parallel to this surge in interest, cultural norms, media coverage, and policies to address school safety and bullying have evolved at a remarkably quick pace over the past 13 years. For example, behaviors and populations that just a decade ago were not included in the school violence, bullying, and school safety discourse are now accepted areas of inquiry. These include, for instance, cyberbullying, sexting, social media shaming, teacher–student and student–teacher bullying, sexual harassment and assault, homicide, and suicide. Populations in schools not previously explored, such as lesbian, gay, bisexual, transgender, and queer students and educators and military- and veteran-connected students, become the foci of new research, policies, and programs. As a result, all US states and most industrialized countries now have a complex quilt of new school safety and bullying legislation and policies. Large-scale research and intervention funding programs are often linked to these policies. This book suggests an empirically driven unifying model that brings together these previously distinct literatures. This book presents an ecological model of school violence, bullying, and safety in evolving contexts that integrates all we have learned in the 13 years, and suggests ways to move forward.

scholarly journals Domain-Adversarial Training of Self-Attention-Based Networks for Land Cover Classification Using Multi-Temporal Sentinel-2 Satellite Imagery

2021 ◽  
Vol 13 (13) ◽  
pp. 2564
Author(s):  
Mauro Martini ◽  
Vittorio Mazzia ◽  
Aleem Khaliq ◽  
Marcello Chiaberge
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Domain Adaptation ◽  
Learning Approaches ◽  
Atmospheric Conditions ◽  
Practical Applications ◽  
Area Of Interest ◽  
Multi Temporal ◽  
Significant Performance ◽  
Adversarial Training

The increasing availability of large-scale remote sensing labeled data has prompted researchers to develop increasingly precise and accurate data-driven models for land cover and crop classification (LC&CC). Moreover, with the introduction of self-attention and introspection mechanisms, deep learning approaches have shown promising results in processing long temporal sequences in the multi-spectral domain with a contained computational request. Nevertheless, most practical applications cannot rely on labeled data, and in the field, surveys are a time-consuming solution that pose strict limitations to the number of collected samples. Moreover, atmospheric conditions and specific geographical region characteristics constitute a relevant domain gap that does not allow direct applicability of a trained model on the available dataset to the area of interest. In this paper, we investigate adversarial training of deep neural networks to bridge the domain discrepancy between distinct geographical zones. In particular, we perform a thorough analysis of domain adaptation applied to challenging multi-spectral, multi-temporal data, accurately highlighting the advantages of adapting state-of-the-art self-attention-based models for LC&CC to different target zones where labeled data are not available. Extensive experimentation demonstrated significant performance and generalization gain in applying domain-adversarial training to source and target regions with marked dissimilarities between the distribution of extracted features.

“I Will Never Know the Person Who I Could Have Become”: Perceived Changes in Self-Identity Among Adult Survivors of Clergy-Perpetrated Sexual Abuse

2016 ◽  
Vol 34 (6) ◽  
pp. 1139-1162 ◽  
Author(s):  
Scott D. Easton ◽  
Danielle M. Leone-Sheehan ◽  
Patrick J. O’Leary
Keyword(s):  
Sexual Abuse ◽  
Media Coverage ◽  
Large Scale ◽  
Clinical Sample ◽  
Empirical Studies ◽  
Adult Survivors ◽  
Well Being ◽  
Future Research ◽  
Relational Self ◽  
Self Identity

Clergy-perpetrated sexual abuse (CPSA) during childhood represents a tragic betrayal of trust that inflicts damage on the survivor, the family, and the parish community. Survivors often report CPSA has a disturbing impact on their self-identity. Despite intense media coverage of clergy abuse globally in the Catholic Church (and other faith communities) over several decades, relatively few empirical studies have been conducted with survivors. Beyond clinical observations and advocacy group reports, very little is known about survivors’ perceptions of how the abuse impacted their long-term self-identity. Using data collected during the 2010 Health and Well-Being Survey, this qualitative analysis represents one of the first large-scale studies with a non-clinical sample of adult male survivors of CPSA from childhood ( N = 205). The negative effects of the sexual abuse on participants were expressed across six domains of self-identity: (a) total self, (b) psychological self, (c) relational self, (d) gendered self, (e) aspirational self, and (f) spiritual self. These findings highlight the range and depth of self-suffering inflicted by this pernicious form of sexual violence. The findings are useful for developing clinical services for survivors, shaping public and institutional policies to address clergy-perpetrated sexual abuse, and guiding future research with this population.

School Violence to School Safety: Reframing the Issue for School Psychologists

1994 ◽  
Vol 23 (2) ◽  
pp. 236-256 ◽  
Author(s):  
Gale M. Morrison ◽  
Michael J. Furlong ◽  
Richard L. Morrison
Keyword(s):  
School Violence ◽  
School Psychologists ◽  
School Safety

scholarly journals 2D Nanomaterials for Effective Energy Scavenging

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Md Al Mahadi Hasan ◽  
Yuanhao Wang ◽  
Chris R. Bowen ◽  
Ya Yang
Keyword(s):  
Large Scale ◽  
Waste Heat ◽  
Material Selection ◽  
Power Supplies ◽  
Small Scale ◽  
Energy Scavenging ◽  
Power Sources ◽  
Practical Applications ◽  
2D Nanomaterials ◽  
Self Powered

AbstractThe development of a nation is deeply related to its energy consumption. 2D nanomaterials have become a spotlight for energy harvesting applications from the small-scale of low-power electronics to a large-scale for industry-level applications, such as self-powered sensor devices, environmental monitoring, and large-scale power generation. Scientists from around the world are working to utilize their engrossing properties to overcome the challenges in material selection and fabrication technologies for compact energy scavenging devices to replace batteries and traditional power sources. In this review, the variety of techniques for scavenging energies from sustainable sources such as solar, air, waste heat, and surrounding mechanical forces are discussed that exploit the fascinating properties of 2D nanomaterials. In addition, practical applications of these fabricated power generating devices and their performance as an alternative to conventional power supplies are discussed with the future pertinence to solve the energy problems in various fields and applications.

scholarly journals Application of Novel Non-Thermal Physical Technologies to Degrade Mycotoxins

2021 ◽  
Vol 7 (5) ◽  
pp. 395
Author(s):  
Mohammad Yousefi ◽  
Masoud Aman Mohammadi ◽  
Maryam Zabihzadeh Khajavi ◽  
Ali Ehsani ◽  
Vladimír Scholtz
Keyword(s):  
Electron Beam ◽  
Food Systems ◽  
Large Scale ◽  
Plasma Electron ◽  
Pulsed Light ◽  
Beam Radiation ◽  
Practical Applications ◽  
Electron Beam Radiation ◽  
Non Thermal Plasma ◽  
Agriculture And Food

Mycotoxins cause adverse effects on human health. Therefore, it is of the utmost importance to confront them, particularly in agriculture and food systems. Non-thermal plasma, electron beam radiation, and pulsed light are possible novel non-thermal technologies offering promising results in degrading mycotoxins with potential for practical applications. In this paper, the available publications are reviewed—some of them report efficiency of more than 90%, sometimes almost 100%. The mechanisms of action, advantages, efficacy, limitations, and undesirable effects are reviewed and discussed. The first foretastes of plasma and electron beam application in the industry are in the developing stages, while pulsed light has not been employed in large-scale application yet.

scholarly journals A Short Review on Recent Advances of Hydrogel-Based Adsorbents for Heavy Metal Ions

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 864
Author(s):  
Suguna Perumal ◽  
Raji Atchudan ◽  
Thomas Nesakumar Jebakumar Immanuel Edison ◽  
Rajendran Suresh Babu ◽  
Petchimuthu Karpagavinayagam ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Metal Ions ◽  
Heavy Metal Ions ◽  
Large Scale ◽  
Water Bodies ◽  
Dimensional Structure ◽  
High Porosity ◽  
Adsorption Method ◽  
Toxic Heavy Metal ◽  
Practical Applications

The growth of industry fulfills our necessity and promotes economic development. However, pollutants from such industries pollute water bodies which pose a high risk for living organisms. Thus, researchers have been urged to develop an efficient method to remove toxic heavy metal ions from water bodies. The adsorption method shows promising results for the removal of heavy metal ions and is easy to operate on a large scale, thus can be applied to practical applications. Numerous adsorbents were developed and reported, among them hydrogels, which attract great attention because of the reusability, ease of preparation, and handling. Hydrogels are generally prepared by the cross-linking of polymers that result in a three-dimensional structure, showing high porosity and high functionality. They are hydrophilic in nature because of the functional groups, and are non-toxic. Thus, this review provides various methods of hydrogel adsorbents preparation and summarizes recent progress in the use of hydrogel adsorbents for the removal of heavy metal ions. Further, the mechanism involved in the removal of heavy metal ions is briefly discussed. The most recent studies about the adsorption method for the treatment of heavy metal ions contaminated water are presented.

scholarly journals Understanding racial differences of COPD patients with an ecological model: two large cohort studies in the US and Korea

2021 ◽  
Vol 12 ◽  
pp. 204062232098245
Author(s):  
Hye Yun Park ◽  
Hyun Lee ◽  
Danbee Kang ◽  
Hye Sook Choi ◽  
Yeong Ha Ryu ◽  
...  
Keyword(s):  
Racial Differences ◽  
Large Scale ◽  
Ecological Model ◽  
Prevalence Ratio ◽  
Poor Quality ◽  
Smoking History ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Copd Patients ◽  
The Us

Background: There are limited data about the racial difference in the characteristics of chronic obstructive pulmonary disease (COPD) patients who are treated at clinics. We aimed to compare sociodemographic and clinical characteristics between US and Korean COPD patients using large-scale nationwide COPD cohorts. Methods: We used the baseline demographic and clinical data of COPD patients aged 45 years or older with at least a 10 pack-per year smoking history from the Korean COPD Subtype Study (KOCOSS, n = 1686) cohort (2012–2018) and phase I (2008–2011) of the US Genetic Epidemiology of COPD (COPDGene) study ( n = 4477, 3461 were non-Hispanic whites [NHW], and 1016 were African Americans [AA]). Results: Compared to NHW, AA had a significantly lower adjusted prevalence ratio (aPR) of cough >3 months (aPR: 0.67; 95% CI [confidence interval]: 0.60–0.75) and phlegm >3 months (aPR: 0.78, 95% CI: 0.70–0.86), but higher aPR of dyspnea (modified Medical Round Council scale ⩾2) (aPR: 1.22; 95% CI: 1.15–1.29), short six-minute walk distance (<350 m) (aPR: 1.98; 95% CI: 1.81–2.14), and poor quality of life (aPR: 1.10; 95% CI: 1.05–1.15). Compared to NHW, Koreans had a significantly lower aPR of cough >3 months (aPR: 0.53; 95% CI: 0.47–0.59), phlegm >3 months (aPR: 0.75; 95% CI: 0.67–0.82), dyspnea (aPR: 0.72; 95% CI: 0.66–0.79), and moderate-to-severe acute exacerbation in the previous year (aPR: 0.73; 95% CI: 0.65–0.82). NHW had the highest burden related to chronic bronchitis symptoms and cardiovascular diseases related to comorbidities. Conclusion: There are substantial differences in sociodemographic characteristics, clinical presentation, and comorbidities between COPD patients from the KOCOSS and COPDGene, which might be caused by interactions between various intrapersonal, interpersonal, and environmental factors of the ecological model. Thus, a broader and more comprehensive approach would be necessary to understand the racial differences of COPD patients.

Curvature Variability Study for Small- and Large-Scale Linear Fresnel Solar Fields: A Step Toward Optimization

2017 ◽  
Vol 139 (5) ◽  
Author(s):  
Sara Benyakhlef ◽  
Ahmed Al Mers ◽  
Ossama Merroun ◽  
Abdelfattah Bouatem ◽  
Hamid Ajdad ◽  
...  
Keyword(s):  
Cost Reduction ◽  
Large Scale ◽  
Small Scale ◽  
Optimization Approach ◽  
Market Penetration ◽  
Concentrated Solar Power ◽  
Sustainable Technologies ◽  
Low Efficiency ◽  
New Research ◽  
Variability Study

Reducing levelized electricity costs of concentrated solar power (CSP) plants can be of great potential in accelerating the market penetration of these sustainable technologies. Linear Fresnel reflectors (LFRs) are one of these CSP technologies that may potentially contribute to such cost reduction. However, due to very little previous research, LFRs are considered as a low efficiency technology. In this type of solar collectors, there is a variety of design approaches when it comes to optimizing such systems. The present paper aims to tackle a new research axis based on variability study of heliostat curvature as an approach for optimizing small and large-scale LFRs. Numerical investigations based on a ray tracing model have demonstrated that LFR constructors should adopt a uniform curvature for small-scale LFRs and a variable curvature per row for large-scale LFRs. Better optical performances were obtained for LFRs regarding these adopted curvature types. An optimization approach based on the use of uniform heliostat curvature for small-scale LFRs has led to a system cost reduction by means of reducing its receiver surface and height.

scholarly journals Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods

2020 ◽  
Vol 34 (01) ◽  
pp. 630-637 ◽  
Author(s):  
Ferdinando Fioretto ◽  
Terrence W.K. Mak ◽  
Pascal Van Hentenryck
Keyword(s):  
Deep Learning ◽  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Electrical Power ◽  
Practical Applications ◽  
Fundamental Building Block ◽  
Optimal Power

The Optimal Power Flow (OPF) problem is a fundamental building block for the optimization of electrical power systems. It is nonlinear and nonconvex and computes the generator setpoints for power and voltage, given a set of load demands. It is often solved repeatedly under various conditions, either in real-time or in large-scale studies. This need is further exacerbated by the increasing stochasticity of power systems due to renewable energy sources in front and behind the meter. To address these challenges, this paper presents a deep learning approach to the OPF. The learning model exploits the information available in the similar states of the system (which is commonly available in practical applications), as well as a dual Lagrangian method to satisfy the physical and engineering constraints present in the OPF. The proposed model is evaluated on a large collection of realistic medium-sized power systems. The experimental results show that its predictions are highly accurate with average errors as low as 0.2%. Additionally, the proposed approach is shown to improve the accuracy of the widely adopted linear DC approximation by at least two orders of magnitude.

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