1,416 research outputs found

    Evaluation of the utility and performance of an autonomous surface vehicle for mobile monitoring of waterborne biochemical agents

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    Real-time water quality monitoring is crucial due to land utilization increases which can negatively impact aquatic ecosystems from surface water runoff. Conventional monitoring methodologies are laborious, expensive, and spatio-temporally limited. Autonomous surface vehicles (ASVs), equipped with sensors/instrumentation, serve as mobile sampling stations that reduce labor and enhance data resolution. However, ASV autopilot navigational accuracy is affected by environmental forces (wind, current, and waves) that can alter trajectories of planned paths and negatively affect spatio-temporal resolution of water quality data. This study demonstrated a commercially available solar powered ASV equipped with a multi-sensor payload ability to operate autonomously to accurately and repeatedly maintain established A-B line transects under varying environmental conditions, where lateral deviation from a planned linear route was measured and expressed as cross-track error (XTE). This work provides a framework for development of spatial/temporal resolution limitations of ASVs for real-time monitoring campaigns and future development of in-situ sampling technologies

    Ewert v. Canada: Shining Light on Corrections and Indigenous People

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    In Ewert v. Canada, the Supreme Court considered an Indigenous federal inmate’s claim that the continued use of actuarial tools to assess his risk was contrary to the Corrections and Conditional Release Act and sections 7 and 15 of the Charter. The case offers an important opportunity to consider issues of substantive equality; access to justice; and how Correctional Service Canada’s (CSC) current practices contribute to the larger problem of Indigenous alienation from the criminal justice system. Given the opaque nature of the correctional system, it is only through cases like Ewert that we get a glimpse into this type of decision-making

    Social Connectedness in Schizotypy: The Role of Cognitive and Affective Empathy

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    Social connectedness is increasingly understood to be a resilience factor that moderates vulnerability to poor physical and mental health. This study examines cognitive and affective processes that support normal socialization and social connectedness, and the impact of schizotypy, in well-functioning college students. In this study, a total of 824 college students completed a series of self-report questionnaires, and structural equation modeling was then employed to identify relationships between cognitive and affective empathy, alexithymia, distress tolerance, social connectedness, and schizotypy. Schizotypy is a trait-like condition, presumed to be genetic in origin, associated with the risk for schizophrenia. Like schizophrenia, schizotypy is thought to have three distinct dimensions or categories, termed positive, negative, and disorganized. Results indicate that the respective dimensions of schizotypy have different pathways to social connectedness, through both direct and indirect effects. Positive schizotypy exerts a counterintuitive positive influence on social connectedness, mediated by positive effects on cognitive empathy, but this is obscured by the high correlations between the schizotypal dimensions and the strong negative influences on empathy and social connectedness of the negative and disorganized dimensions, unless all those intercorrelations are taken into account. Overall, the pathways identified by structural equation modeling strongly support the role of empathy in mediating the impact of schizotypy on social connectedness. Implications for the etiology of social impairments in schizotypy, and for interventions to enhance social connectedness to improve quality of life and reduce health disparities in people at risk for severe mental illness, are discussed

    Rethinking Retail in Indy: Reconnecting East 10th Street, Reinventing Small Town Shopping, Reevaluating 1970s Shopping Malls, and Revitalizing Fountain Square

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    poster abstractThe dawn of 21st century brought about significant advances in technology that affected all aspects of social life. These advances, specifically the interstate system and the automobile, revolutionized the institution of retail and the way we as consumers shop. In the 1970s, the strip center, the enclosed mall and big box stores drew business from local retail, leaving many urban neighborhood retail strips abandoned. In present day, we see yet another shift in retail trends as the presence of “dead malls” becomes more common and authentic urban shopping strips re-emerge. The gap between these two eras of retail has not been completely bridged, though. In this presentation, we will explore different perspectives on the future of urban retail throughout Greater Indianapolis through the use of ethnographic and descriptive research methods. We will look at possibilities for the re-use of the largely abandoned Lafayette Square Mall; evaluate different perspectives on how East 10th Street can reconnect retail with a struggling residential community; analyze the impact of downtown and highway oriented retail nodes on the struggling revitalization of suburban Greenfield; and examine whether the unique and independently owned eateries and pubs are truly serving as engines in spurring the economic revival of the older neighborhood of Fountain Square

    New Chairs in a World of Hurt: Using Trauma-Informed Leadership to Guide Communication, Compassion, and Flexibility for Five New Chairs.

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    Presenters will discuss their challenges as first-year Chairs facing the multiple academic fires generated by an unprecedented global pandemic. The presenters will detail how using Trauma-Informed Leadership styles allowed them to adjust for the unpredictability of communication from system-level administration, establish relationships with internal stakeholders, and develop trust with faculty as new leaders within the institution

    Ranked Set Sampling for a Population Proportion:Allocation of Sample Units to Each Judgment Order Statistic

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2 Accent 6" /> <w:LsdException Locked="false" Priority="67" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 1 Accent 6" /> <w:LsdException Locked="false" Priority="68" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 2 Accent 6" /> <w:LsdException Locked="false" Priority="69" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 3 Accent 6" /> <w:LsdException Locked="false" Priority="70" SemiHidden="false" UnhideWhenUsed="false" Name="Dark List Accent 6" /> <w:LsdException Locked="false" Priority="71" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Shading Accent 6" /> <w:LsdException Locked="false" Priority="72" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful List Accent 6" /> <w:LsdException Locked="false" Priority="73" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Grid Accent 6" /> <w:LsdException Locked="false" Priority="19" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Subtle Emphasis" /> <w:LsdException Locked="false" Priority="21" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Intense Emphasis" /> <w:LsdException Locked="false" Priority="31" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Subtle Reference" /> <w:LsdException Locked="false" Priority="32" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Intense Reference" /> <w:LsdException Locked="false" Priority="33" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Book Title" /> <w:LsdException Locked="false" Priority="37" Name="Bibliography" /> <w:LsdException Locked="false" Priority="39" QFormat="true" Name="TOC Heading" /> </w:LatentStyles> </xml><![endif]--><!--[if gte mso 10]> <style>\ud /* Style Definitions */\ud table.MsoNormalTable\ud {mso-style-name:"Table Normal";\ud mso-tstyle-rowband-size:0;\ud mso-tstyle-colband-size:0;\ud mso-style-noshow:yes;\ud mso-style-priority:99;\ud mso-style-parent:"";\ud mso-padding-alt:0in 5.4pt 0in 5.4pt;\ud mso-para-margin:0in;\ud mso-para-margin-bottom:.0001pt;\ud mso-pagination:widow-orphan;\ud font-size:10.0pt;\ud font-family:"Times New Roman","serif";}\ud </style> <![endif]--> <p class="MsoNormal" style="text-align: justify;"><span style="font-size: 10pt;">Ranked set sampling is an alternative to simple random sampling that has been shown to outperform simple random sampling in many situations by reducing the variance of an estimator, thereby providing the same accuracy with a smaller sample size than is needed in simple random sampling. Ranked set sampling involves preliminary ranking of potential sample units on the variable of interest using judgment or an auxiliary variable to aid in sample selection. Ranked set sampling prescribes the number of units from each rank order to be measured.</span></p> <p class="MsoNormal" style="text-align: justify;"><span style="font-size: 10pt;">&nbsp;</span></p> <p class="MsoNormal" style="text-align: justify;"><span style="font-size: 10pt;">Balanced ranked set sampling assigns equal numbers of sample units to each rank order. Unbalanced ranked set sampling allows unequal allocation to the various ranks, but this allocation may be sensitive to the quality of information available to do the allocation.<span>&nbsp; </span>In this paper we use a simulation study to conduct a sensitivity analysis of optimal allocation of sample units to each of the order statistics in unbalanced ranked set sampling. Our motivating example comes from the National Survey of Families and Households.</span></p

    Non-invasive Drug Monitoring of β-Lactam Antibiotics Using Sweat Analysis-A Pilot Study

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    Background: Antimicrobial resistance is a major challenge in treating infectious diseases. Therapeutic drug monitoring (TDM) can optimize and personalize antibiotic treatment. Previously, antibiotic concentrations in tissues were extrapolated from skin blister studies, but sweat analyses for TDM have not been conducted. Objective: To investigate the potential of sweat analysis as a non-invasive, rapid, and potential bedside TDM method. Methods: We analyzed sweat and blood samples from 13 in-house patients treated with intravenous cefepime, imipenem, or flucloxacillin. For cefepime treatment, full pharmacokinetic sampling was performed (five subsequent sweat samples every 2 h) using ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry. The ClinicalTrials.gov registration number is NCT03678142. Results: In this study, we demonstrated for the first time that flucloxacillin, imipenem, and cefepime are detectable in sweat. Antibiotic concentration changes over time demonstrated comparable (age-adjusted) dynamics in the blood and sweat of patients treated with cefepime. Patients treated with standard flucloxacillin dosage showed the highest mean antibiotic concentration in sweat. Conclusions: Our results provide a proof-of-concept that sweat analysis could potentially serve as a non-invasive, rapid, and reliable method to measure antibiotic concentration and as a surrogate marker for tissue penetration. If combined with smart biosensors, sweat analysis may potentially serve as the first lab-independent, non-invasive antibiotic TDM method

    Artificial Stupidity

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    Public debate about AI is dominated by Frankenstein Syndrome, the fear that AI will become superhuman and escape human control. Although superintelligence is certainly a possibility, the interest it excites can distract the public from a more imminent concern: the rise of Artificial Stupidity (AS). This article discusses the roots of Frankenstein Syndrome in Mary Shelley’s famous novel of 1818. It then provides a philosophical framework for analysing the stupidity of artificial agents, demonstrating that modern intelligent systems can be seen to suffer from ‘stupidity of judgement’. Finally it identifies an alternative literary tradition that exposes the perils and benefits of AS. In the writings of Edmund Spenser, Jonathan Swift and E.T.A. Hoffmann, ASs replace, enslave or delude their human users. More optimistically, Joseph Furphy and Laurence Sterne imagine ASs that can serve human intellect as maps or as pipes. These writers provide a strong counternarrative to the myths that currently drive the AI debate. They identify ways in which even stupid artificial agents can evade human control, for instance by appealing to stereotypes or distancing us from reality. And they underscore the continuing importance of the literary imagination in an increasingly automated society
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