Children’s rights and digital technologies

Digital technologies have reshaped children’s lives, resulting in new opportunities for and risks to their well-being and rights. This chapter investigates the impact of digital technologies on children’s rights through the lens of the United Nations Convention on the Rights of the Child. Up until now, not all rights have received the same level of attention in the digital context. Legal and policy discourse in the area of children and digital media predominantly focuses on ‘protection’ rights, albeit with a growing awareness of the tension between ‘protection’ and ‘participation’ rights. ‘Provision’ rights are not often emphasised, other than in the important domain of education. However, all children’s rights should be supported, valued and developed in both online and offline spheres of engagement. Governments, parents, educators, industry, civil society and children’s rights commissioners or ombudspersons should all take up their responsibility to enhance children’s rights in relation to digital technologies, while actively listening and taking account of children’s views when developing laws, policies, programmes and other measures in this field

Comparing proxy and model estimates of hydroclimate variability and change over the Common Era

Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy–model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations. We subsequently explore means of using proxy–model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy–model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections

Measuring the Capacity to Love: Development of the CTL-Inventory

Objective: The individual capacity to love (CTL) has been linked to various mental health parameters and is considered to be an important outcome parameter of psychotherapeutic treatment. However, empirical examinations of the concept have not been conducted up to now. The aim of this study was to develop a valid and reliable instrument for the assessment of CTL [Capacity to Love Inventory (CTL-I)] as a trait of personality, which is shown to be related to clinically relevant symptoms and conditions.Method: Four independent healthy samples in Austria (n = 547, n = 174, and n = 85) and Poland (n = 240) were assessed by a prototype of the CTL-I and its final shorter version in a confirmatory factor analysis (CFA). Internal consistency of the total questionnaire and each subscale was assessed by Cronbach alpha. External validity was measured against Beck Depression Inventory, Quality of Relationship Inventory, Sociosexual Orientation Inventory, Pathological Narcissism Inventory, and Narcissistic Personality Inventory according to the theoretical framework of the CTL concept. Further test–retest reliability was assessed.Results: The CFA confirmed 41 items in six dimensions: Interest in the life project of the other, Basic trust, Humility and gratitude, Common ego ideal, Permanence of sexual passion, and Acceptance of loss/jealousy/mourning. The Cronbach alphas of the total CTL-I and its subscales ranged between 0.67 and 0.90 in all samples, suggesting a valid construct. The CTL-I was moderately positively associated with quality of relationship (Support r = 0.63, Conflict r = -0.66, and Depth r = 0.66) and inversely associated with symptoms of depression (r = -0.37), pathological narcissism (r = -0.29) and promiscuity (r = -0.42). The test–retest reliability of the total CTL-I was high with r = 0.81, suggesting the stability of answers over time.Conclusion: The proposed 41-item version of the CTL-I is a psychometrically sound and validated instrument measuring six dimensions of the concept of the CTL. The reported negative associations with clinically relevant parameters such as depression, pathological narcissism and promiscuity as well as associations with relationship qualities such as conflicts, support, and depth warrant its future use in burdened populations including couples in clinical settings

Detection and Characterization of Ignitable Liquid Residues in Forensic Fire Debris Samples by Comprehensive Two-Dimensional Gas Chromatography

This study covers an extensive experimental design that was developed for creating simulated fire debris samples under controlled conditions for the detection and identification of ignitable liquids (IL) residues. This design included 19 different substrates, 45 substrate combinations with and without ignitable liquids, and 45 different ILs from three classes (i.e., white spirit, gasoline, and lamp oil). Chemical analysis was performed with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS) for improved separation and compound identification. The enhanced peak capacity offered by GC×GC-TOFMS allowed the use of a target compound list in combination with a simple binary decision model to arrive at quite acceptable results with respect to IL detection (89% true positive and 7% false positive rate) and classification (100% correct white spirit, 79% correct gasoline, and 77% correct lamp oil assignment). Although these results were obtained in a limited set of laboratory controlled fire experiments including only three IL classes, this study confirms the conclusions of other studies that GC×GC-TOFMS can be a powerful tool in the challenging task of forensic fire debris analysis

Local Ion Signatures (LIS) for the examination of comprehensive two-dimensional gas chromatography applied to fire debris analysis

Forensic examination of fire debris evidence is a notoriously difficult analytical task due to the complexity and variability of sample composition. The use of comprehensive two-dimensional gas chromatography with mass spectrometry detection (GC × GC–MS) allows the coupling of orthogonal retention mechanisms and therefore a high peak capacity. We demonstrate recent innovations in combining chemometric techniques for data reduction and feature selection, with evaluation of the evidence for forensic questions pertaining to the detection and subsequent classification of ignitable liquid residue (ILR) in fire debris samples. Chromatograms are divided into non-overlapping spatially delimited regions; for each of these regions a Local Ion Signature (LIS) is computed by summing the intensities, per nominal mass/charge over all points contained within each region. This yields a reduced feature space representing the original data as a set of consolidated ion traces. Subsequent feature selection is performed by evaluating the individual efficacy of each feature using a univariate score-based likelihood ratio (LR) approach for discriminating between pairs of same or different type samples. The retained features are used to model each ILR class using linear discriminant analysis (LDA). Results are demonstrated for 155 arson samples containing a diversity of substrate compounds and several known ignitable liquids. ILR detection is performed at 84% accuracy with fewer than 1% false positives followed by subsequent classification. Likelihood ratio distributions are presented referring to both detection and classification tasks