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Education as a protective factor for mental health risks among youth living in highly dangerous regions in Afghanistan
No full textAbstractBackgroundChildren in Afghanistan live in dangerous areas, and have been exposed to traumatic events and chaotic education. Progress has been made on access to education for girls who were the most affected by traditional attitudes against engagement in education.ObjectivesThe objectives were to evaluate the mental health of Afghan children living in regions of conflict and the association of mental health with school attendance for girls and boys.MethodThe study included 2707 school aged children in eight regions of Afghanistan (16 provinces) residing in households recruited through a multi-stage stratified cluster sampling strategy in 2017. The level of terrorist threat was evaluated by the intensity of terrorist attacks recorded that year in each province. Child mental health was assessed with the parental report Strengths and Difficulties Questionnaire (SDQ) along with information on school attendance, sociodemographic characteristics and geographic location.ResultsA total of 52.75% of children had scores above threshold for the SDQ total difficulties score, 39.19% for emotional difficulties, 51.98% for conduct challenges, and 15.37% for hyperactivity/inattention. Peer relationship problems were high (82.86%) and 12.38% reported that these problems impacted daily life. The level of terrorist threat was associated with SDQ total difficulties (Adjusted Odds Ratio [AOR] = 4.08, P < 0.0001), with youth in regions with high levels of terrorist threat more likely to have problems than youth in regions with low or medium levels of danger, independent of region and ethnicity. School attendance was negatively associated with emotional symptoms (AOR = 0.65, P < 0.0001) and mental health difficulties with impairment (AOR = 0.67, P = 0.007), but positively associated with peer relationships difficulties (AOR = 1.96, P > 0.0001). Conduct (AOR = 1.66, P < .0001) and SDQ total difficulties (AOR = 1.22, P = 0.019) were higher among boys. Overall, gender did not modify the relationship between school attendance and child mental health.ConclusionAttending school is essential for children’s mental health, across gender, and should be supported as a priority in Afghanistan despite the return of the Taliban.</jats:sec
Geodesic complexity of a tetrahedron
No full textWe prove that the geodesic complexity of a regular tetrahedron exceeds its
topological complexity by 1 or 2. The proof involves a careful analysis of
minimal geodesics on the tetrahedron
An Untargeted Survey of the Rotational Properties of Main-belt Asteroids using the Transiting Exoplanet Survey Satellite (TESS)
No full textAbstract
We present photometric data for minor planets observed by the Transiting Exoplanet Survey Satellite during its Cycle 1 operations. In total, we extracted usable detections for 37,965 objects. We present an examination of the reliability of the rotation period and light-curve amplitudes derived from each object based upon the number of detections and the normalized Lomb–Scargle power of our period fitting and compare and contrast our results with previous similar works. We show that for objects with 200 or more photometric detections and a derived normalized, generalized Lomb–Scargle power greater than 0.2, we have an 85% confidence in that period; this encompasses 3492 rotation periods we consider to be highly reliable. We independently examine a series of periods first reported by Pál et al.; periods derived in both works found to have similar results should be considered reliable. Additionally, we demonstrate the need to properly account for the true proportion of slow rotators (P > 100 hr) when inferring shape distributions from sparse photometry.</jats:p
Cry me a Pele’s tear: new insights on the internal structures of Pele’s tears
No full textIn this paper we present novel observations of internal structures of Pele’s tears and spheres revealed from SEM studies of particles formed within Kilauean lava fountains. Partially weathered Pele’s tears from eruption episodes in 1969 include a crust, or rind, of material that is smooth on the external surface. However, once this crust is peeled away, it reveals a sub-crustal surface within the tear that is morphologically complex. This surface is characterized by a network of ridges and valleys that warp around radial structures with pores at their centers. The ridges and valleys are interpreted to represent the differential cooling and shrinkage of the external surface of the spheres and tears relative to the interior upon exiting the lava fountain and chilling in ambient air. The radial structures are interpreted to be formed as result of chemical zonation within the cooling at locations where a vesicle contacts the external crust. An additional feature is observed on the underside of crust that is peeled off each tear. This surface has a roughly polygonal network of tubes that surround pores at the center of many of the polygons. The tubes are hollow and some contain solid material within, possibly the remains of the crushed top of the tube where the SEM can peer inside. The origin of this tube network is a puzzle remaining to be solved.</jats:p
Beam energy dependence of the linear and mode-coupled flow harmonics in Au+Au collisions
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Analysis of Nonlinear Control Systems: From Lifting Operators to Learning Interaction Laws in Networks
No full textThis dissertation explores a diverse set of problems in dynamical systems, control, estimation, and learning theory. Part I studies nonlinear systems using operator theory, specifically Carleman Linearization. Chapter one delves into the convergence of Carleman Linearization over a characterizable time horizon. The findings show that the Carleman Linearization converges to the original solution for general time-varying nonlinear systems with an analytic right-hand side over a finite time horizon. The third chapter introduces a new method to solve the Hamilton-Jacobi-Bellman Equation using the tools from Carleman Linearization. The analysis demonstrates the convergence of the method and proves that the control input obtained stabilizes the nonlinear dynamics after a certain truncation length. The second part of this dissertation is focused on examining the learning of dynamical systems under the presence of uncertainties. Chapter three explores techniques to enhance the robustness of recurrent neural networks by employing concepts from control and estimation theories. Initially, the chapter outlines how to measure the robustness of the recurrent neural networks and then introduces a novel algorithm to estimate the output covariance and biases for RNNs. We then utilized the gradient descent algorithm to minimize covariances along biases to obtain a robust RNN model. In Chapter four, we analyze the learning of nonlinear couplings in a network of interacting agents in a non-parametric set-up, where only a single sample trajectory is available. The study demonstrates that for geometrically ergodic networks, assuming the compactness of the hypothesis space, learning algorithms converge even when only a single sample trajectory is available. Additionally, we reveal that if the hypothesis space is convex and coercive, the empirical estimator converges uniquely. Part III of this dissertation is dedicated to developing and analyzing a systematic framework to study the risk of undesired events in the network of interconnected agents. In Chapter six, we explore the inherent risk associated with non-minimum phase systems. Using the systematic risk framework, we then investigate the trade-offs between collision risk, network topology, control cost, and non-minimum phase zeros of the system. In the last Chapter, we propose a framework to evaluate the risk of misperception resulting from noisy environmental observations. We employ the Expected Shortfall (Average Value-at-Risk) measure to evaluate the risk of collision between pairs of vehicles and the risk of violating traffic laws for each vehicle under possible misperceptions. Obtaining an explicit expression for the risk measure allows us to investigate potential trade-offs between overall misperception-induced risks and network architecture
Single-Cell Sensing Using Non-Specific Intracellular Targets: Leveraging Automation for Complex Diagnoses
No full textDiagnosis of disease is traditionally dependent on identifying specific markers that can alert to the presence of physical abnormalities causing the symptoms within the patient. However, this model poses a problem for diagnosis of more complex states, limiting the ability to diagnose before significant symptoms present or to address some diseases where understanding is limited. Although specific markers help us ensure that an appropriate diagnosis is given, new techniques in data analysis like machine learning can help us solve more complex relationships to improve quantitative diagnosis. The main qualities emphasized in diagnostic techniques are reliability, speed, and cost effectiveness because these all impact the ability of the diagnostic to bring quality care to patients regardless of financial status or global location.While limitations in most diagnostic methods exist, electrical diagnostic methods are widely considered one of the most accessible options in terms of saving time and resources. With electronics, there are typically less required consumables and the need for skilled laboratory technicians supporting in the clinical setting. These low-cost and low-resource options make electrical diagnostic methods highly translatable for both rural and urban locations. In single-cell applications, lab-on-a-chip style diagnostics consolidate cell manipulation and measurement onto small footprint systems that give rapid electrical readings. Electrical impedance can also collect multiple frequencies quickly, leading to more features per cell to develop a more complete picture of distinct levels of cellular organization. Multi-frequency impedance can measure many single cells to represent an entire population and capture both unique properties of individuals and statistically relevant population changes.In the work described here, a microfluidic system integrated with broadband impedance measurement capabilities for single cell analysis is used to examine the way disease-related changes can be both measured and modelled electrically. As a cornerstone, device performance was improved through a systemic approach to integration between the physical and software components of the electronic and microfluidic system. Through these process improvements, optimization occurred in a data-driven manner to improve individual cell speed and location, the integration of control systems, and automated data processing. By taking an interdisciplinary approach and incorporating both hardware and software processes, the throughput was improved to enable study of larger populations than initially possible.As these system integrations improved the capability for measurement of single cells, two cell types were analyzed to look at potential impedance diagnostic markers to identify two different diseases. In one, a lymphoma cell line was treated to change the nucleus size to imitate changes associated with both cancer and apoptosis. In this project, feature selection and a classification learning model was used to identify the frequencies most relevant to alterations in nucleus size and show the ability to predict individual cell nucleus changed within a population based on an electrical signature. Alternatively, skeletal muscle cells were altered to induce a state of oxidative stress and calcium increase, ionic conditions associated with myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS). The characterization of these ionic changes was used to speculate on measurements of clinically sourced patient skeletal muscle cells from a patient with ME/CFS and an age and sex matched healthy person
Evaluation of Load Models for Fatigue of Steel Highway Bridges and Orthotropic Steel Decks
No full textThe load models used in the US to design and evaluate fatigue details in steel highway bridges and orthotropic steel decks are standard truck models. However, vehicles passing over bridges have various weights and types. This research evaluates the standard fatigue load models used in the US, considering how well these load models represent the effects of traffic loading, and the reliability of various steel highway bridges and orthotropic steel decks designed using the standard fatigue load models. In this research, weigh-in-motion (WIM data) from 28 WIM sites nationwide in the US are analyzed and the variation in truck traffic loading is observed. The finite life and infinite life AASHTO fatigue load models, which are standard in the US, are evaluated by comparing them with the effects of truck traffic that is modeled using the WIM truck data. To perform this evaluation, a computational program was developed to generate the fatigue stress response of a steel highway bridge (or orthotropic steel deck) fatigue detail using a simulation approach. Steel girder highway bridges with seven bridge span lengths, i.e., 20 ft, 40 ft, 60 ft, 80 ft, 100 ft, 150 ft, and 200 ft, are considered. For each bridge span length, three cases are considered, where each case focuses on a specific fatigue detail in a specific location in a steel highway bridge with a specific bridge type. Simply-supported and continuous-span bridge types are considered. Simple orthotropic steel deck bridges with five independent floor beams and 11 ribs are considered. The reliability of steel girder bridge fatigue details and orthotropic steel deck rib-to-floor beam connection details designed for the finite life fatigue limit state and infinite life fatigue limit state using the current AASHTO fatigue load models is assessed. The results showed that the finite life fatigue reliability and the infinite life fatigue reliability are not uniform with bridge location, in addition, the finite life fatigue reliability is not uniform with bridge span length. Alternative finite life and infinite life site-specific or highway-specific fatigue load models which provide improved fatigue reliability are proposed for steel highway bridges and orthotropic steel decks. Revisions to the finite life and infinite life AASHTO fatigue load models for steel highway bridges and orthotropic steel decks are suggested