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Age of Information-Based Optimal Scheduling With Energy Cost Trade-Off for Smart Warehouse: A Deep Reinforcement Learning-Based Approach
No full textRecent advances in the integration of high-speed mobile networks and real-time IoT devices have facilitated in building of smart warehouses, where a set of beacons and Internet of Things (IoT) devices (or source nodes) can monitor the status of various physical processes in a time-critical way. In real-time status monitoring systems, like smart warehouses, quantifying the freshness of the Internet of Things (IoT) data based on the age of information (AoI) metrics becomes quite crucial. As source nodes are battery-constrained, a balanced trade-off between AoI minimization and preservation of source node battery energy is essential. In this paper, in a smart warehouse scenario, we address the problem of minimization of the average weighted sum of AoI subject to the available energy constraint of each source node. We focus on joint optimization of packet transmission and energy may not be suitable for finding a solution in a reasonable time. To address the issue, we develop a deep Q-network (DQN) algorithm that enables us to a simultaneous reduction of the state-space dimension with learning of the age-optimal policy in unknown environmental dynamics. Taking account into the limited energy constraints of the user nodes, the proposed DQN algorithm aims to minimize the long-term average weighted sum-AoI of the user-transmitted data. Finally, we produce multifaceted simulation results in terms of convergence, learning process, and change of average sum-AoI under different energy constraints that shows the effectiveness of the proposed DQN algorithm
Leading Beyond the School Walls: Understanding Principal Community Activism
No full textThe purpose of this study is to investigate the ways school leaders perceive and engage in community-focused, activist leadership in response to community needs. We rely on a critical qualitative research design that draws on critical urban theory. Sources of data include a pilot focus group, semi-structured in-depth interviews with activist leaders, and publicly available documents. Findings demonstrate the ways that leaders engaged in activism by developing understandings of the communities they served as a first step to activism, rooting their schools as a physical resource for communities, and responding to community needs via activist practices. Through their work, leaders intentionally countered the impact of white supremacist neoliberal policies that negatively impacted their school communities. Our research contributes to the growing scholarship of in-practice models of activist school leadership, highlighting the necessity for leadership practice that addresses the challenges of disinvestment and heightened resource competition in urban communities of color. Furthermore, this study advocates for an expanded concept of equitable school leadership that encompasses both in-school and community-focused justice work as to engage in wholistic school improvement
Inflammatory Mediators and the RAGE Pathway in Placental Tissues of Pregnancies Complicated by Severe Preeclampsia
No full textIntroduction: Preeclampsia (PE) is a complex multisystem disorder of pregnancy associated with abnormal placentation, vascular anomalies, and systemic inflammation and hypertension. Previous research assessing inflammatory triggers of the condition used plasma, amniotic fluid, or explant samples. Studies using placental tissue from either vaginal or cesarean deliveries are confined to semiquantitative analysis using subjective scoring methods and generally involve a small sample size.
Methods: In this study, we have quantified the expression of inflammatory mediators by immunohistochemical image analysis of archived placental tissues obtained from cesarean delivery of preeclamptic, chorioamnionitic, and normal pregnancies.
Results: Among the inflammatory mediators, we found a significant elevation in the expression of receptors of advanced glycation end products (RAGE) and two of its damage-associated molecular pattern proteins (DAMPs) and ligands, the high mobility group box protein HMGB1 and the calcium binding protein S100, in preeclamptic tissues as compared to normal placentas. In addition, we observed a significant increase in the master pro-inflammatory transcription factor, nuclear factor kappa B p65 subunit (NFκB), as well as non-significant increases in cyclooxygenase 2 (COX-2) and interleukin 8 (IL-8) in the PE group.
Conclusion: This study provides insight into the relationship of tissue inflammatory mediators with severe preeclampsia and the RAGE associated signaling complex, suggesting a pathogenic role for this pathway which has clinical implications for the understanding, diagnosis, and potential novel therapeutic approaches to the syndrome
Investigating Extracellualr Vesicles Role in the Pathogenesis of Acute Lung Injury
No full textBackground: Extracellular vesicles (EVs) are small lipid-bound particles containing proteins and RNAs, whose role in intercellular communication and signaling is critical for homeostasis or inflammatory responses. Patients with acute lung injury display changes in EVs number, cargo content and signature compared to healthy individuals.
Hypothesis: We have hypothesized that EVs may play a role in the pathogenesis of acute lung, by transferring harmful mediators of inflammation and disrupting recipient cells homeostasis.
Methods: C57BL/6j mice (8-10 weeks old, 25g BW) were intratracheally instilled with 50µL of 5*1010- 11 EVs isolated from Human Lung Microvascular Endothelial cells (HLMVEC) exposed to 1 µg LPS. Mice were monitored clinically for weight, S/F ratio and signs of distress. After 72 hours, parameters of lung function were measured via Flexivent (SICREQ), bronchoalveolar lavage fluid (BALF) collected and lungs harvested for molecular and histological analysis.
Results: Mice instilled with inflammatory-derived EVs display progressive weight loss, and a reduction in the S/F ratio 24 hours after EVs exposure. EVs dose dependently provoked histological signs of acute lung injury via H&E staining. Analysis of BALF indicated an increased cellularity for both EVs concentrations of neutrophils. Only the highest dose provoked a significant reduction in pressure volume relationships measured via Flexivent.
Conclusion: During inflammatory conditions, endothelial cells produce EVs that have a pathogenic potential toward the alveolar structures. These preliminary reports may open avenues for novel therapeutic measures targeting EVs release or internalization. The EVs-effects on the lung structures observed here, may similarly be involved in the pathogenesis of acute distress respiratory syndrome (ARDS) observed in indirect sepsis
Virginia Academy of Sleep Medicine Position Statement on School Start Times in Virginia
Full text linkThe VASM endorses the 2017 AASM position statement that middle and high schools should begin no earlier than 8:30 a.m. The existing and updated scientific literature repeatedly identifies the detrimental impact of early high school start times, and the benefits of delaying start times, on the safety and well-being of students in Virginia. The adverse effects of early school start times on Virginia’s students have been demonstrated, with regards to academic performance, mental health, and driving risks. Data published since the AASM position paper highlight these dangers further. Importantly, recent studies also demonstrate some of the benefits that can come from delaying school start times, including improved academic performance and attendance, reduced depression and suicidality, positive economic impact, and reduction of adolescent motor vehicle crashes.
Early middle and high school start times significantly contribute to the public health epidemic of sleep deprivation in adolescents and its attendant harmful consequences. Thus, addressing start times, a modifiable risk factor, can not only address the teen sleep loss epidemic but also lead to increased productivity, attention, vigilance/safety, performance, and improved health in this vulnerable population
Statewide Seismic-Induced Landslide Risk Assessment in Virginia: A probabilistic approach
No full textLandslide hazards, driven by triggers such as earthquakes and rainfall, pose significant risks to infrastructure and community resilience. However, the assessment of these hazards has been constrained by the limited resolution and qualitative-based evaluations of the existing map in Virginia. This paper addresses these limitations by adapting a novel probabilistic approach (Saygili and Rathje, 2009) to develop a seismic-triggered, high-resolution, quantitative statewide landslide hazard map for Virginia. The method used the rigid sliding block approach and the Newmark (1965) displacement model to evaluate seismic-triggered landslide susceptibility, which is defined by a yield acceleration ky, the minimum horizontal acceleration of earthquake shaking that initiates the block sliding, resulting in a landslide. The yield acceleration is calculated by topographic slopes, soil shear strength parameters (including cohesion, internal friction angle, and unit weight of the soil), and groundwater table. To create a high-resolution map, we derived a topographic slope map (with a 10 m spacing) for Virginia from high-resolution digital elevation models. The soil shear strength parameters were inferred from a statewide surface geological map. The groundwater table was interpolated from water wells data. Next, we used probabilistic seismic hazard analysis (Cornell, 1968) to evaluate the probabilistic occurrence of seismic triggers such that the resultant ground shaking exceeds ky. A series of probabilistic assessments of seismic triggers for different return periods (the duration that, on average, one exceedance event would occur), including 100, 475, 975, and 2475 years (the most commonly considered in seismic design), were produced. Within a shorter return period, fewer extreme seismic events would occur, which would trigger fewer landslides. Therefore, we expect landslide hazards to be weaker during a shorter return period than a longer return period. After convolving the map by probabilistic assessments of seismic triggers at different return periods, the corresponding landslide hazard maps at those return periods were generated. We observed that higher landslide hazards appeared in the western regions of Virginia, primarily mountainous areas with steeper slopes. The hazard maps are in 10-m spacing that can provide a very accurate risk assessment for statewide infrastructure (e.g., transportation roads). In our future research, we will extend the analyses to conduct multi-triggered landslide hazards assessment by including rainfall-triggered landslides
The Cytotoxic Effect of a Cu(II) Complex with Thiosemicarbazone Ligand on Triple Negative Breast Cancer
No full textAbstract
Breast cancer, characterized by the uncontrolled growth of abnormal cells in the breast, poses a significant health challenge. Triple negative breast cancer (TNBC) is a subtype of breast cancer and characterized by the absence of three receptors commonly found in breast cancer cells: estrogen, progesterone, and HER2 receptors. Therapeutic options for treating TNBC are limited, and the chemotherapeutic drug, cisplatin, reported various side effects. Copper-containing complexes with thiosemicarbazones (TSCs) ligands have shown great potential in anti-cancer properties when compared to cisplatin. The current research involved a study of the cytotoxic effects of copper(II) complex [Cu(chromoneTSC)Cl2]•0.5H2O•0.0625C2H5OH (where chromoneTSC = (E)-N-Ethyl-2-((4-oxo-4H-chromen-3-yl)methylene)-hydrazinecarbothioamideand) and its “free” ligand, chromoneTSC, as well as cisplatin as a positive control on a human breast cancer MDA-MB-231 VIM RFP cell line. The cytotoxicity study was carried out by using a WST-8 based Cell Counting Kit-8 (CCK-8) assay. The IC50 values with the use of the “free” ligand, chromoneTSC, were 40.7 ± 3.2, 35.8 ± 1.6, and 31.5 ± 1.4 mM, at 24, 48, and 72 h, respectively. With cisplatin, the IC50 values were 30.6 ± 3.5, 23.7 ± 2.6, and 21.6 ± 1.9 mM at 24, 48, and 72 h, respectively. Intriguingly, the Cu(II) complex demonstrated a significant cytotoxic effect, as evidenced by the low IC50 values of 21.3 ± 2.7, 19.2 ± 2.8, and 15.8 ± 3.1 mM at 24, 48, and 72 h of treatment, respectively. These findings indicated the potential anti-cancer activity of the Cu(II) complex when compared to the “free” ligand and cisplatin. Future studies will investigate the cytotoxic effect of these compounds on non-cancerous MCF-10A cells and to study the cell death mechanisms induced after treatment, viz., apoptosis, pyroptosis, and necroptosis. This holistic approach aims to deepen our understanding of the compounds\u27 therapeutic potential and to pave the way for more targeted and efficacious breast cancer treatments
Golden Spirals Everywhere?
No full textThe article explores different types of spirals, including Archimedean, hyperbolic, and logarithmic spirals, with a focus on the golden ratio and golden spirals. It discusses the misconception that golden rectangles and spirals can be found in various natural and man-made objects, emphasizing the importance of understanding the properties of logarithmic spirals. The text provides mathematical equations for logarithmic spirals and poses questions for readers to explore the concept further. The author, John Adam, invites readers to engage in Fermi Questions and submit ideas for consideration
Golden Spirals Everywhere? Solutions for Fermi Questions, January 2025
No full textThe article discusses different types of spirals, including Archimedean, hyperbolic, and logarithmic spirals, with a focus on the golden ratio and golden spirals. It addresses the misconception that golden rectangles and spirals can be found in various natural and man-made structures, emphasizing the importance of understanding the properties of logarithmic spirals. The article provides mathematical explanations and solutions for questions related to pitch angles and self-similarity in logarithmic spirals, using examples like the nautilus shell and an ammonite-like stone. It concludes by referencing additional sources for further exploration of the golden ratio and golden spiral myths
Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration
No full textIn Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing, a team of distinguished researchers delivers an incisive and practical discussion of reinforcement learning (RL) in cybersecurity that combines intelligence preparation for battle (IPB) concepts with multi-agent techniques. The authors explain how to conduct path analyses within networks, how to use sensor placement to increase the visibility of adversarial tactics and increase cyber defender efficacy, and how to improve your organization’s cyber posture with RL and illuminate the most probable adversarial attack paths in your networks.
Containing entirely original research, this book outlines findings and real-world scenarios that have been modeled and tested against custom generated networks, simulated networks, and data. [Amazon.com]https://digitalcommons.odu.edu/ece_books/1012/thumbnail.jp