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A Riemannian augmented Lagrangian method for the optimal power flow problem in radial distribution networks
Accepted manuscrip
Multiple memory systems in instrumental music learning
Playing a musical instrument involves the simultaneous expression or performance of several cognitive functions, including motor actions, visual and auditory processing, working temporal-spatial processing, and sensorimotor awareness. To explore relationships between discrete skills in music learning and how performance can all occur at the same time, this constructivist grounded theory (GT) study explored learning phenomena of beginner instrumental music students (n = 15) through the lens of the multiple memory systems theory and its two major memory class systems of explicit and implicit memory. In addition to the multiple memory system model, special focus was given to working memory, an explicit memory operant in which conscious processing and synthesis of information occurs, and automaticity, the immediate recall or action through the implicit memory system. Three major themes emerged in the analysis phase of the study, resulting in the synthesis of a new theory for instrumental music education: the multiple memory music learning (MMML) framework. The first theme central to MMML, automatic music learning, illustrates how automaticity appears to occur within the short-term memory paradigm when learning an instrument. This phenomenon challenges the current viewpoint in neuroscientific and psychological literature that automaticity only exists as a long-term memory function. The second theme, contextual music learning, relates to context-dependent learning outcomes,
and the third theme, music learning sequencing and attentional behavior, pertains to the
order in which learning events took place and how these orders influence performance
outcomes. Although further research is recommended, the results of the study suggest that MMML could be a valuable framework for understanding cognitive and memory functioning for instrumental music students
Navigating the dynamics of private security in Turkey: reflections from a field in flux
Any fieldwork is inherently filled with tension arising from two fundamental yet conflicting obligations: first, the need to treat the field as an already constituted research object, and second, the requirement to continuously reframe, remake, or essentially reconstitute this object during the fieldwork. This double bind places the fieldworker in a blurred position, navigating between the certainty of the former and the uncertainty of the latter. My fieldwork on Istanbul's private security market in Turkey was no exception. While approaching the market as an already constituted research object, I also had to cartographically unfold it as I explored it. My research specifically examined how security, as a peculiar good and service, was translated into a market object in Turkey's private security industry. Despite its relatively recent emergence in 2004, the industry has experienced tremendous growth. By 2019, 1.6 million people had completed private security training, 1.1 million had obtained licenses, and around 320,000 were actively employed in the industry. This translates to nearly 3 in every 100 working-age individuals being trained, almost 2 in 100 licensed, and 1 in 200 working as private security guards.Published versio
The health equity explorer: an open-source resource for distributed health equity visualization and research across common data models
Introduction:
There is an urgent need to address pervasive inequities in health and healthcare in the USA. Many areas of health inequity are well known, but there remain important unexplored areas, and for many populations in the USA, accessing data to visualize and monitor health equity is difficult.
Methods:
We describe the development and evaluation of an open-source, R-Shiny application, the “Health Equity Explorer (H2E),” designed to enable users to explore health equity data in a way that can be easily shared within and across common data models (CDMs).
Results:
We have developed a novel, scalable informatics tool to explore a wide variety of drivers of health, including patient-reported Social Determinants of Health (SDoH), using data in an OMOP CDM research data repository in a way that can be easily shared. We describe our development process, data schema, potential use cases, and pilot data for 705,686 people who attended our health system at least once since 2016. For this group, 996,382 unique observations for questions related to food and housing security were available for 324,630 patients (at least one answer for all 46% of patients) with 65,152 (20.1% of patients with at least one visit and answer) reporting food or housing insecurity at least once.
Conclusions:
H2E can be used to support dynamic and interactive explorations that include rich social and environmental data. The tool can support multiple CDMs and has the potential to support distributed health equity research and intervention on a national scale
In situ neighborhood sampling for large-scale GNN training
Graph Neural Network (GNN) training algorithms commonly perform neighborhood sampling to construct fixed-size mini-batches for weight aggregation on GPUs. State-of-the-art disk-based GNN frameworks compute sampling on the CPU, transferring edge partitions from disk to memory for every mini-batch. We argue that this design incurs significant waste of PCIe bandwidth, as entire neighborhoods are transferred to main memory only to be discarded after sampling. In this paper, we make the first step towards an inherently different approach that harnesses near-storage compute technology to achieve efficient large-scale GNN training. We target a single machine with one or more SmartSSD devices and develop a high-throughput, epoch-wide sampling FPGA kernel that enables pipelining across epochs. When compared to a baseline random-access sampling kernel, our solution achieves up to 4.26× lower sampling time per epoch
Characteristics of bloodstains on waterproof fabrics
Blood is a biological fluid frequently encountered at crime scenes and can be an important source of information regarding the events that occurred and individuals involved. Blood evidence can be the subject of bloodstain pattern analysis (BPA) to ascertain the details of a blood shedding event as well as deoxyribonucleic acid (DNA) analysis to identify potential individuals that were present at the event. BPA becomes more complicated when bloodstains are found on clothing items due to the wide range of fabrics and their inherent properties, along with a range of factors, including but not limited to, treatments, effects of laundering, and wear. The interaction between fabrics and bloodstains has not been wholly explored in the forensic literature. Additionally, most forensic research on bloodstain and fabric interactions have been conducted on laundered, absorbent fabrics. Waterproof fabrics are designed to repel water and protect underlying surfaces from the effects of weather such as rain and snow, often having very different properties from other fabrics.
In this research, the characteristics of bloodstains deposited on waterproof and absorbent fabrics were assessed, as well as the ability to chemically detect the presence of blood after physical alteration of the stains. Six unlaundered, waterproof fabrics with different waterproof coatings, fiber content, and other properties in addition to three different types of absorbent fabrics were cut into swatches and utilized for this study. Whole human blood was used to create a variety of bloodstain types that are often observed at a crime scene: drip stains at two different impact angles, spatter stains, and transfer stains. Ten replicates were completed for all nine fabrics and each bloodstain type, for a total of 360 bloodstains. The dried bloodstains were photographed with a handheld digital camera and a digital camera mounted on a stereo microscope to better visualize the interactions between the blood and fibers. The bloodstained fabric swatches were then physically manipulated to assess the persistence of the stains and the ability of a presumptive blood assay to detect the remaining traces.
Four mechanisms of blood deposition created bloodstains with different characteristics. Differences were observed among the variety of waterproof fabrics as well as the different absorbent fabrics. Bloodstains on the waterproof fabrics appeared to rest on the surface with very little wicking into the fabric. The largest drip stain diameters were observed on the cotton t-shirt, implying that the cotton t-shirt had the greatest wicking ability. Pearling of the blood droplets was observed on the waterproof fabrics used in this experiment, but appeared to occur irrespective of the type of waterproof finish applied. The drip stains on the nylon fabrics appeared flatter and frequently caved in at the center, even though the waterproof finishes were the same as two of the polyester fabrics, which produced more spherical drip stains. The contrasting appearances of the drip stains on cotton jersey and the cotton t-shirt is likely due to the presence of 5% spandex in the cotton jersey fabric. Bloodstain characteristics thus appeared to be influenced by fiber content, fabric structure and thickness, and the presence of waterproofing surface treatments, as well as the blood deposition mechanism.
The bloodstains on absorbent fabrics did not separate greatly from the fabric after alteration and appeared largely unchanged. The bloodstains were dislocated from the waterproof fabrics to varying extents, but all greater than the absorbent fabrics. Traces of the bloodstains were frequently observed under the stereo microscope when the pre-existing stains were not observed macroscopically, indicating that a microscopic examination may be a useful tool in the forensic laboratory. The altered drip stains at both impact angles were overwhelmingly detected by the presumptive Kastle-Meyer blood test, with only a single instance of a negative result. In contrast, test results were more evenly split among the spatter stains on waterproof fabrics and were less likely to produce positive test results. Positive test results were obtained for the majority of altered stains, including stains that were not visible to the naked eye, indicating that a presumptive blood test may be useful for detecting latent bloodstains on clothing items such as the ones analyzed in this research
Benchmarking learned and LSM indexes for data sortedness
Database systems use indexes on frequently accessed attributes to accelerate query and transaction processing. This requires paying the cost of maintaining and updating those indexes, which can be thought of as the process of adding structure (e.g., sort) to an otherwise unstructured data collection. The indexing cost is redundant when data arrives pre-sorted, even if only up to some degree. While recent work has studied how classical indexes like B+-trees cannot fully exploit the near-sortedness during ingestion, there is a lack of this exploration on other index designs like read-optimized learned indexes or write-optimized LSM-trees.
In this paper, we bridge this gap by conducting the first-ever study on the behavior of learned indexes and LSM-trees when varying the data sortedness in an ingestion workload. Specifically, we build on prior work on benchmarking data sortedness on B+-trees and we expand the scope to benchmark: (i) ALEX and LIPP, which are updatable learned index designs; and (ii) the LSM-tree engine offered by RocksDB. We present our evaluation framework and detail key insights on the performance of the index designs when varying data sortedness. Our observations indicate that learned indexes exhibit unpredictable performance when ingesting differently sorted data, while LSM-trees can benefit from sortedness-aware optimizations. We highlight the potential headroom for improvement and lay the groundwork for further research in this domain
The price of privacy: a performance study of confidential virtual machines for database systems
Confidential virtual machines (CVM) use trusted hardware to encrypt data being processed in memory to prevent unauthorized access. Applications can be migrated to CVM without changes, i.e., lift and shift, to handle sensitive workloads securely in public clouds. AMD Secure Encrypted Virtualization (SEV) is one of the prominent technologies that provides hardware support for CVM. In this paper, we investigate various system operations, including CPU, memory, and disk and network I/O, to understand the performance overheads of SEV-supported CVMs. Our findings indicate that memory and I/O-intensive workloads can incur significant overhead. We then study the performance implications of running unmodified database applications, specifically Cock-roachDB, on CVMs by examining typical data access patterns of OLTP and OLAP workloads. A notable performance overhead of up to 18% is observed for TPC-C workload running on multinode database clusters, and an overhead of up to 13% is observed for TPC-H workload running on single-node database instances. The non-negligible overhead suggests the potential and necessity for database optimizations with respect to CVM, particularly for time-sensitive workloads. We offer a glimpse of the effect that CVM overhead can have in query planning using a simple join query: the optimal join algorithm becomes suboptimal on CVM, along with discussion of potential optimizations for reducing CVM overhead in the realm of database applications
Development of induced pluripotent Stem cells from human blood mononuclear cells for skin organoid development
Mosquito-borne viruses (MBV) are the cause of significant health and economic concerns worldwide. However, the mechanisms by which these viruses are transmitted to humans remain elusive. This is due to the scarcity of animal models recapitulating mosquitoes to human MBV transmission. While transgenic mice defective in their immune responses are permissive to MBV infection, the partial immunodeficiency of these models and the lack of human skin preclude an accurate understanding of the molecular and cellular mechanisms driving effective MBV transmission. The goal of this project is to develop the first mouse model co-engrafted with a functional human immune system and syngeneic induced pluripotent stem cells (iPSC)-derived skin organoids.
This novel mouse model will illuminate critical mechanisms and host-pathogen interactions driving MBV transmission and provide a novel technology to model skin-related diseases.2026-10-31T00:00:00
Data and resources for the dissertation: HIV treatment engagement interventions for men in Malawi: a mixed-methods economic evaluation
This repository contains an excel spreadsheet with costing details for the study: Identifying efficient linkage strategies for men in Malawi (IDEaL): an individually randomised control trial