cssi/SciSciGPT-SciSciNet huggingface dataset:
An Initial Investigation of Protocol Customization

Attacks exploiting design or implementation flaws of particular features in popular protocols are becoming prevalent and have led to severe security impacts on a majority of software systems. Protocol customization as a general approach to specialize a standard protocol holds significant promise in reducing such attack surfaces in common protocols. In this work, we perform an initial investigation of applying protocol customization practices to reduce the attack surface of standard protocols. Our characterization study on 20 medium or high-impact common vulnerability exposures (CVEs) published in recent years indicates that some forms of customization have been supported in existing protocol software, but were implemented with huge manual effort and in an ad-hoc manner. More systematic and automated ways of protocol customization are awaited to generalize common customization practices across protocols. To work towards this goal, we identify key research challenges for the support of systematic and sufficiently automated protocol customization through real-world case study on popular protocol software, and propose an access control framework as a principled solution to unify existing protocol customization practices. We also present a preliminary design of a protocol customization system based on this design principle. Preliminary evaluation results demonstrate that our proposed system supports common customization practices for a majority of real-world protocol vulnerabilities in a systematic way.
Improved gait recognition based on specialized deep convolutional neural network

Abstract Gait recognition is a biometric technique used in determining the identity of humans based on the style and the manner of their walk. Its performance is often degraded by covariate factors such as carrying condition changes, clothing condition changes, and viewing angle variations. Recently, machine learning based techniques have produced promising results for challenging classification problems. Since, a deep convolutional neural network (CNN) is one of the most advanced machine learning techniques with the ability to approximate complex non-linear functions, we develop a specialized deep CNN architecture for Gait Recognition. The proposed architecture is less sensitive to several cases of the common variations and occlusions that affect and degrade gait recognition performance. It can also handle relatively small data sets without using any augmentation or fine-tuning techniques. The majority of previous approaches to gait recognition have used subspace learning methods which have several shortcomings that we avoid. Our specialized deep CNN model can obtain competitive performance when tested on the CASIA-B large gait dataset.
Two Times: Being and Becoming in Jane Bennett and Matthew Scherer

In an era of exponentially increasing globalization, the experience of time has changed. Tasks that once took days or weeks, now take hours or seconds. This shrinking of time, or the speeding up of activities and processes that transpire within it, has also had profound effects on the experience of space, bringing personal and cultural identities into increasingly closer proximity. As a result, the public sphere has become a contested site in which a multiplicity of heterogenous identities vie for legitimacy and acknowledgment. In such an environment, the concept of identity has taken on a new and heightened significance. Citizens of the contemporary global village risk irreconcilable conflict by privileging rigid conceptions of identity based upon an understanding of time that privileges being over becoming; an understanding that excludes the reality of change, difference, and alterity. Although Jane Bennett’s The Enchantment of Modern Life and Matthew Scherer’s Beyond Church and State: Democracy, Secularism, and Conversion are addressing fundamentally different problems, they nevertheless agree on the ethical and political significance of the plasticity of identity, as well as the possibility and nature of change. This convergence is not entirely surprising, given the web of influences in which Bennett and Scherer are implicated; a web wherein Gilles Deleuze is influenced by Henri Bergson and Bennett and Scherer by both Bergson and Deleuze. In this paper, I argue that both Bennett and Scherer, drawing upon the writings of Deleuze and Bergson respectively, acknowledge two kinds of time: a closed, circular time that solidifies habits—what I will call the time of being—and an open, spiral time which allows for the possibility of change and the production of new habits, the time of becoming. Not only do both Scherer and Bennett acknowledge these different understandings of time, but they also stress the necessity of cultivating an appreciation of the fundamental reality of becoming, and the role that such a cultivation can play in navigating an increasingly heterogeneous political landscape.
Resection of a Giant-Cell Tumor of the Proximal Aspect of the Radius with Osteoarticular Allograft Reconstruction: A Case Report

CASE Giant-cell tumors are locally aggressive osteolytic benign tumors that are characterized by multinucleated giant cells. Recurrence rates are ≤30% after curettage and <5% after resection, but reconstruction can be difficult. We describe an osteoarticular allograft reconstruction of the proximal aspect of the radius in a 23-year-old man after resection of a giant-cell tumor. CONCLUSION Five months after surgery, the patient had satisfactory joint articulation, range of motion, and strength, with no signs of hardware or graft failure. By 17 months, there was complete osseous union. The joint remained stable at 54 months. We describe our surgical approach, which restores joint stability and minimizes recurrence.
The K-path entrance in cytochrome c oxidase is defined by mutation of E101 and controlled by an adjacent ligand binding domain.

Abstract Three mutant forms of Rhodobacter sphaeroides cytochrome c oxidase (RsCcO) were created to test for multiple K-path entry sites (E101W), the existence of an “upper ligand site” (M350 W), and the nature and binding specificity of the “lower ligand site” (P315W/E101A) in the region of a crystallographically-defined deoxycholate at the K-path entrance. The effects of inhibitory and stimulatory detergents (dodecyl maltoside and Tween20) on these mutants are presented, as well as competition with other ligands, including the potentially physiologically relevant ligands cholesterol and retinoic acid. Ligands are shown to be able to compete with natural lipids to affect the activity of membrane-bound RsCcO. Results point to a single K-path entrance site at E101, with a single ligand binding pocket proximal to the entrance. The affinity of this pocket for amphipathic ligands is enhanced by removal of the E101 carboxyl and blocked by substituting a tryptophan in this area. A new crystal structure of the E101A mutant of RsCcO is presented that illustrates the structural basis of these results, showing that the loss of the E101 carboxyl creates a more hydrophobic groove consistent with altered ligand affinities.
Variability in Weight Concern and Physical Activity Engagement Among African American Adolescent Girls.

Lower rates of recreational physical activity (PA) among African American (AA) adolescent girls relative to other US age/race/gender groups are assumed to reflect within-race similarity in PA attitudes and practices. However, variability in PA attitudes and practices among AA adolescent girls is not well studied. To address this, a class-diverse sample of 51 AA adolescent girls’ responses to survey items querying weight concern (WC) and PA was examined for sub-groupings using cluster analysis. Three clusters were identified [L/H—low WC, high PA; H/L—high WC, low PA; and L/L—low WC and PA]. Survey item response means were examined by cluster. L/L differed visibly, but not significantly, from L/H and H/L on items assessing PA engagement. The same was true for H/L with WC items. Cluster identification and trends in response differences by cluster have potential implications for targeted PA promotion efforts. Further investigation with larger, representative samples is warranted.
Mineralocorticoid Disorders and Endocrine Hypertension

The renin-angiotensin-aldosterone system regulates intravascular volume and the serum potassium concentration through its regulation of sodium and potassium handling in the distal nephron of the kidneys. Isolated disorders of this system in children are rare but when present can cause significant morbidity from either deficient or excess mineralocorticoid action. This chapter describes the physiology of mineralocorticoid action followed by the mechanisms responsible for disordered mineralocorticoid action. For each disorder, the appropriate diagnostic evaluation and treatment recommendations are presented.
Propagation Directions of Ocean Surface Waves inside Tropical Cyclones

AbstractSurface wave propagation inside tropical cyclones (TCs) is complicated and multiple wave systems are frequently observed. The directional wave spectra acquired by hurricane hunters are analyzed to quantify its azimuthal and radial variations. Referenced to the hurricane heading, the dominate feature in the front half of the TC coverage area is single wave systems propagating toward left and left-front. Multiple wave systems are generally observed in the back and right quarters outside the radius of maximum wind (RMW). The directional differences and locations of occurrences of multisystem spectra are Gaussian distributed. The directional differences of the secondary and tertiary wave systems from the primary system are centered around 60°–70°. The minor systems are more likely on the left-hand side of the primary system than on the right-hand side by a 3-to-1 ratio. The most likely azimuthal location of multisystem spectra is about 210° counterclockwise from the heading. In the right-front quarter...
Sovereignty and social justice: how the concepts affect federal American Indian policy and American Indian health

The health disparities that are prevalent among American Indian and Alaska Native (AI/AN) communities are connected to the ideology of sovereignty and often ignored in social work and public health literature. Therefore, the purpose of this paper is to examine the health outcomes of American Indians from the time of contact with European settlers to the present through the ideology of sovereignty and federal government AI health policy. The foundation for the health outcomes of AIs and the governmental policies affecting them lie in the ideology of tribal sovereignty. This ideology has greatly impacted how the government views and treats AIs and consequently, how it has impacted their health. From the earliest treaties between European settlers and AIs, this legal relationship has been and remains a perplexing issue. With the examination of tribal sovereignty comes the realization that colonization and governmental polices have greatly contributed to the many social and health problems that AIs suffer from today. Understanding that the health disparities that exist among AI/AN populations cannot only be attributed to individual behavior and choice but is driven by societal, economic and political factors may be used to inform social work education, practice, and research.
Attempted Validation of the CARE Carotid Stenting Risk Score (P06.261)

OBJECTIVE: To determine if CARE carotid stenting risk score predicts in-hospital complications from carotid artery stenting (CAS). BACKGROUND: In hospital complications of carotid artery stenting (CAS) remain a major concern. Recently, the CARE registry investigators presented an internally validated score to help predict in-hospital complications from CAS, with the greatest weightage to increasing age, followed by impending major surgery, previous stroke, symptomatic status, previous stroke and contralateral occlusion. We attempted to externally validate the CARE carotid stenting risk score in our CAS population. DESIGN/METHODS: We performed a retrospective review of CAS procedures between June 2009 and April 2012 at an urban medical center. We included all patients where every risk factor was documented. In-hospital outcomes of stroke/death and/or myocardial infarction (MI) were recorded. RESULTS: A total of 139 CAS procedures met the inclusion criteria. Most common risk factor was prior stroke (25.9%) followed by A fib (14.4%). Most patients were between 60-90 years (60-69: 35.3%; 70-79: 27.3%; 80-89: 25.9%). There were 10 (7.2%) post op complications (9 strokes, 1 MI and 0 death). Most patients had a CARE score between 4 and 9. However, the CARE carotid stenting risk score did not correlate well with in-hospital complications in this series. CONCLUSIONS: CARE carotid stenting risk score did not correlate with outcome in our population. External validation in a much larger dataset with sufficient number of outcome events is required. Disclosure: Dr. Khalid has nothing to disclose. Dr. Rayes has nothing to disclose. Dr. Bhattacharya has nothing to disclose. Dr. Chaturvedi has received personal compensation for activities with Genentech, Inc., Abbott Vascular, Boehringer Ingelheim Pharmaceuticals, Inc., and Thornhill Research.
Software information systems

A key obstacle to higher productivity in large software systems is invisibility: the difficulty of locating needed information about the system under development. In this thesis, we introduce software information systems that use a knowledge base represented in description logic to help programmers find useful information. We describe how the representational and inferential services provided by description logics help address different aspects of software invisibility, and illustrate this with examples from an SIS for a specific telephonics system, Definity$\sp{TM}.$ We present enhancements to the description logic substrate needed in order to represent plan information, which is essential in describing our kinds of software. We also describe a variety of tools that aid in acquiring knowledge for a software information system from external sources. These include query generators and a portable system for querying abstract syntax trees of programs, which has found practical applications in a variety of other environments.
Merkel Cells Activate Sensory Neural Pathways through Adrenergic Synapses

Epithelial-neuronal signaling is essential for sensory encoding in touch, itch, and nociception; however, little is known about the release mechanisms and neurotransmitter receptors through which skin cells govern neuronal excitability. Merkel cells are mechanosensory epidermal cells that have long been proposed to activate neuronal afferents through chemical synaptic transmission. We employed a set of classical criteria for chemical neurotransmission as a framework to test this hypothesis. RNA sequencing of adult mouse Merkel cells demonstrated that they express presynaptic molecules and biosynthetic machinery for adrenergic transmission. Moreover, live-cell imaging directly demonstrated that Merkel cells mediate activity- and VMAT-dependent release of fluorescent catecholamine neurotransmitter analogs. Touch-evoked firing in Merkel-cell afferents was inhibited either by pre-synaptic silencing of SNARE-mediated vesicle release from Merkel cells or by neuronal deletion of β2-adrenergic receptors. Together, these results identify both pre- and postsynaptic mechanisms through which Merkel cells excite mechanosensory afferents to encode gentle touch. VIDEO ABSTRACT.
Activity-dependent development of GABAergic synapses

In the brain, dendrites of pyramidal neurons contain intermingled excitatory and inhibitory synapses. Synaptic connections dynamically change during development and throughout our lifetime, yet the brain can properly maintain an optimal ratio of synaptic excitation to inhibition. Despite recent advances in our understanding of the formation and refinement of excitatory glutamatergic synapses, little is known about signals that regulate inhibitory GABAergic synapse development. In this review, we discuss previous and recent insights in the cellular and molecular mechanisms that underlie GABAergic synapse formation and plasticity, with a specific focus on the key roles of synaptic activity and postsynaptic membrane molecules.
Electronic Medical Record Context Signatures Improve Diagnostic Classification Using Medical Image Computing

Composite models that combine medical imaging with electronic medical records (EMR) improve predictive power when compared to traditional models that use imaging alone. The digitization of EMR provides potential access to a wealth of medical information, but presents new challenges in algorithm design and inference. Previous studies, such as Phenome Wide Association Study (PheWAS), have shown that EMR data can be used to investigate the relationship between genotypes and clinical conditions. Here, we introduce Phenome-Disease Association Study to extend the statistical capabilities of the PheWAS software through a custom Python package, which creates diagnostic EMR signatures to capture system-wide co-morbidities for a disease population within a given time interval. We investigate the effect of integrating these EMR signatures with radiological data to improve diagnostic classification in disease domains known to have confounding factors because of variable and complex clinical presentation. Specifically, we focus on two studies: First, a study of four major optic nerve related conditions; and second, a study of diabetes. Addition of EMR signature vectors to radiologically derived structural metrics improves the area under the curve (AUC) for diagnostic classification using elastic net regression, for diseases of the optic nerve. For glaucoma, the AUC improves from 0.71 to 0.83, for intrinsic optic nerve disease it increases from 0.72 to 0.91, for optic nerve edema it increases from 0.95 to 0.96, and for thyroid eye disease from 0.79 to 0.89. The EMR signatures recapitulate known comorbidities with diabetes, such as abnormal glucose, but do not significantly modulate image-derived features. In summary, EMR signatures present a scalable and readily applicable.
Mechanism of a Standalone β‐Lactone Synthetase: New Continuous Assay for a Widespread ANL Superfamily Enzyme

Enzyme-catalyzed β-lactone formation from β-hydroxy acids is a crucial step in bacterial biosynthesis of β-lactone natural products and membrane hydrocarbons. We developed a novel, continuous assay for β-lactone synthetase activity using synthetic β-hydroxy acid substrates with alkene or alkyne moieties. β-Lactone formation is followed by rapid decarboxylation to form a conjugated triene chromophore for real-time evaluation by UV/Vis spectroscopy. The assay was used to determine steady-state kinetics of a long-chain β-lactone synthetase, OleC, from the plant pathogen Xanthomonas campestris. Site-directed mutagenesis was used to test the involvement of conserved active site residues in Mg2+ and ATP binding. A previous report suggested OleC adenylated the substrate hydroxy group. Here we present several lines of evidence, including hydroxylamine trapping of the AMP intermediate, to demonstrate the substrate carboxyl group is adenylated prior to making the β-lactone final product. A panel of nine substrate analogues were used to investigate the substrate specificity of X. campestris OleC by HPLC and GC-MS. Stereoisomers of 2-hexyl-3hydroxyoctanoic acid were synthesized and OleC preferred the (2R,3S) diastereomer consistent with the stereo-preference of upstream and downstream pathway enzymes. This biochemical knowledge was used to guide phylogenetic analysis of the β-lactone synthetases to map their functional diversity within the acyl-CoA synthetase, NRPS adenylation domain, and luciferase superfamily.
Physical and biological drivers of zooplankton communities in the Chukchi Sea

The physical environments of high-latitude systems are rapidly changing. For example, the Chukchi Sea has experienced increased water temperatures, advection from the Bering Sea, declines in sea-ice concentration, earlier spring ice retreat, and delayed fall ice formation. This physical restructuring is expected to impact ecosystem structure and function. In this study, a series of bio-oceanographic research surveys were conducted in the summers of 2010, 2011, and 2012 to characterize the physical environment and to examine the influence of physical forcing on zooplankton community distribution and abundance. Results revealed yearly advection from the Bering Sea influenced zooplankton community structure, but this influence became less apparent in the northeastern Chukchi due to changes in current speeds and patterns. Decreased advection and later ice retreat in colder years resulted in zooplankton communities that exhibited more diversity, had higher abundances of the lipid-rich copepod Calanus glacialis, and were less closely related to water masses advected from the south. These findings suggest more localized processes are influencing zooplankton community structure in the Chukchi Sea. Increased inflow of water into the Chukchi is predicted with increased warming in the Arctic and changes in food-web structure and function are likely to result.
Sequential obstacle interactions with dislocations in a planar array

Abstract The strengthening of metals by nano-scale obstacles is mainly attributed to the impediment to glide dislocations offered by these obstacles. It is important to understand the mechanisms for dislocation bypass of obstacles having nano-scale dimension, including the atomic-scale structure changes sustained by both obstacles and dislocations after the bypass process. Recently, atomic-scale modeling has provided much insight into obstacle interactions involving a single dislocation. However, the more naturally occurring scenarios involving a sequence of encounters with arrays of moving dislocations are not as well understood owing to prohibitively large length scale requirements for atomistic models. In this study, we utilize a novel multiscale concurrent atomistic-continuum method to simulate a sequence of interactions between glide dislocations in an array with a spherical nano-obstacle (either a void or an impenetrable precipitate) in Al. In the case of a void, the bypassing array of dislocations progressively weakens the void until it splits the originally spherical void into two hemispheres. In the case of a large impenetrable precipitate, sequential dislocations in the array bypass via alternating mechanisms of Orowan looping and Hirsch looping. The residual dislocation loop created around the precipitate by the bypass of the first dislocation is completely removed by the passage of the subsequent dislocation. These mechanisms can benefit the design of materials that are reinforced with nanophase inhomogeneities to achieve ultra high strength.
Continuous Learning of Human Activity Models Using Deep Nets

Learning activity models continuously from streaming videos is an immensely important problem in video surveillance, video indexing, etc. Most of the research on human activity recognition has mainly focused on learning a static model considering that all the training instances are labeled and present in advance, while in streaming videos new instances continuously arrive and are not labeled. In this work, we propose a continuous human activity learning framework from streaming videos by intricately tying together deep networks and active learning. This allows us to automatically select the most suitable features and to take the advantage of incoming unlabeled instances to improve the existing model incrementally. Given the segmented activities from streaming videos, we learn features in an unsupervised manner using deep networks and use active learning to reduce the amount of manual labeling of classes. We conduct rigorous experiments on four challenging human activity datasets to demonstrate the effectiveness of our framework for learning human activity models continuously.
Hereditary predisposition to uveal melanoma

Abstract Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Known risk factors for the risk of UM development include white race, blue/green iris eye color, older age, and some environmental risk, in particular arc welding. UM represent 3%–5% of all melanomas but it is biologically and genetically different from cutaneous melanoma. Based on the rarity of familial UM (about 1%), characterized by more than one individual with UM in the family, the contribution of genetics to the etiology of UM has been considered minimal in the traditional ophthalmology literature. However, multiple lines of evidence suggest that genetics contribute much more to the etiology of UM tumor predisposition. In the following chapter, we summarize the evidence of a genetic contribution to UM predisposition and discuss current genes suspected to be associated with the disease.
Some Popular Algorithms for Distributing Points on \(S^2\)

From star-charts to golf-ball dipples to testing radar in aircraft, well-placed points on the two-dimensional sphere \(S^2\subset \mathbb {R}^{3}\) have a vast number of practical applications. In this chapter, we describe the properties (such as equidistribution, covering, separation, quasi-uniformity, etc.) of such point configurations generated by commonly used methods, namely zonal equal-area points, generalized spiral points, Fibonacci points, HEALPix nodes, octahedral points, icosahedral points, cubed sphere nodes, Hammersley nodes, minimizing Coulomb and logarithmic energy points, radial icosahedral points, equal-area icosahedral nodes, maximal determinant nodes, and random points.
Why I Think That Dark Matter Has Large Self-interactions

We describe a self-interacting dark matter (SIDM) model that can explain the diverse rotation curves of spiral galaxies while maintaining the success of the cold dark matter model on large scales. The explanation is economical in that it only requires one parameter, the self-interaction cross section, which is common to all galaxies. The existence of this solution is demonstrated through fits to a diverse set of 135 rotation curves from the SPARC sample. Despite the apparent diversity, the model exhibits a tight correlation between the accelerations due to the dark and luminous matter. The inferred stellar mass-to-light ratios, halo masses, and halo concentrations are consistent with independent expectations from astrophysics and cosmology.
Diagnosis of Neural Network via Backward Deduction

Although widely used in various areas, the Deep Neural Network suffers from the lack of interpretability. Existing works usually focus on one data instance and the found explanations are thus limited. We argue that a good understanding of a model should contain both systematic explanations of model behavior and effective detection of its vulnerability. Particularly we propose to use backward deduction to achieve these two goals. Given a constraint on the model output, the deduction backtracks the architecture to find corresponding data ranges in the input. In each layer, depending on the type, specific rules and/or algorithms are developed. The resulted ranges in the end can be interpreted by sampling exemplary data from them. In experiment we show that with different strategies in selecting the data ranges, the sampled fake data can either explain the model or reflect its vulnerability.
Electronic Structure of Multicomponent Organic Molecular Materials: Evaluation of Range-Separated Hybrid Functionals.

Range-separated hybrid (RSH) functionals have become a tool of choice to study the intra- and inter-molecular electronic states in organic materials. These functionals provide the most accurate des...
DeepDiseaseInsight: A Deep Learning & NLP based Novel Framework for generating useful Insights from Disease News Articles

We live in an era of information explosion where media for information communication and information sharing have proliferated due to the onset of a digital age. One such important source and medium of consolidated, comprehensive and reliable information, which has persisted through centuries, is news articles. News articles have been considered as a primary source of information, ranging from local to global scope, and encompassing a wide array of domains, by most of the human population. However, as the technology for dissemination of information attracts innovations, it becomes equally important that the consumption and utilization of this information becomes smart as well. If processed properly and treated in an intelligent manner, the information contained in news articles can reveal useful insights and hidden patterns that might prove to be of critical importance in certain decision making pertaining to the topics and domains in question. The paper puts forward a novel framework created by combining Natural Language Processing methodologies like Sentiment Analysis and Information Retrieval, which are performed on top of a Deep Learning based classification with aptly defined classes for generating useful insights from a news article dataset. The paper contains the details regarding the implementation of this system and also a presentation of results on a particular data set of news articles - articles on HIV-AIDS, which have been categorized into meaningful classes and have been processed using aforementioned NLP tasks. Through this paper, a curated dataset of 3,000 news articles related to HIV-AIDS has also been introduced, which will be open sourced so as to inspire further research and experimentation in this specific domain.
Power Grid Contingency Analysis with Machine Learning: A Brief Survey and Prospects

We briefly review previous applications of machine learning (ML) in power grid analyses and introduce our ongoing effort toward developing a generative-adversarial (GA) model for fast and reliable grid contingency analyses. According to our review, the persisting limitation of traditional ML techniques in grid analyses is the need for an exhaustive amount of training data for model generalization and accurate predictions. GA models overcome this limitation by first learning true data distribution from a small training set, from which new samples assimilating true data are generated with some variations. Subsequently, GA models can transfer learn or super-generalize with increased accuracy, that is, accurately predict n − (k + 2) contingencies from a small n − k training set and generated n − (k + 1) data. The joint effort between Idaho National Lab and Florida State University strives to develop a zero-shot and deep learning-based contingency analysis tool, named Smart Contingency Analysis Neural Network (SCANN), by leveraging the aforementioned advantages of GA models. The basic architecture of SCANN stems from the Latent Encoding of Atypical Perturbations network combined with an adversarial network, and it is designed to generate imbalanced power flow data from learned true data distributions for prediction purposes. Here we also introduce the abstract concept of resilience-chaos plots, a new resilience characterization tool proposed to complement SCANN by aiding in the assessment of large amounts of high-order contingency predictions.
Entre la imagen y el texto: ciudad moderna y trabajadores en San Pablo

Siguiendo las ideas Georg Simmel sobre la ciudad moderna, este trabajo analiza la figura del trabajador en San Pablo durante las decadas del 20 y el 30 relacionando el documental Sao Paulo: sinfonia da metropole de Rodolfo Lustig y Adalberto Kemeny y el cuento “Primero de Maio” de Mario de Andrade.. Por un lado, el documental presenta un trabajador mecanizado, funcional a la productividad estimulada por el estado y el sistema economico. Por otro, en el cuento, el trabajador intenta salir de esta logica pero no tolera la confusion y regresa a su espacio laboral- familiar de pertenencia. De este modo, el autor demuestra la existencia de vinculos sentimentales desarrollados en el espacio laboral, los cuales, a pesar de oponerse a la logica capitalista industrial urbana, permiten su funcionamiento.
Improving racial disparities in unmet palliative care needs among intensive care unit family members with a needs-targeted app intervention: The ICUconnect randomized clinical trial.

Abstract Introduction The technologies used to treat the millions who receive care in intensive care unit (ICUs) each year have steadily advanced. However, the quality of ICU-based communication has remained suboptimal, particularly concerning for Black patients and their family members. Therefore we developed a mobile app intervention for ICU clinicians and family members called ICUconnect that assists with delivering need-based care. Objective To describe the methods and early experiences of a clustered randomized clinical trial (RCT) being conducted to compare ICUconnect vs. usual care. Methods and analysis The goal of this two-arm, parallel group clustered RCT is to determine the clinical impact of the ICUconnect intervention in improving outcomes overall and for each racial subgroup on reducing racial disparities in core palliative care outcomes over a 3-month follow up period. ICU attending physicians are randomized to either ICUconnect or usual care, with outcomes obtained from family members of ICU patients. The primary outcome is change in unmet palliative care needs measured by the NEST instrument between baseline and 3 days post-randomization. Secondary outcomes include goal concordance of care and interpersonal processes of care at 3 days post-randomization; length of stay; as well as symptoms of depression, anxiety, and post-traumatic stress disorder at 3 months post-randomization. We will use hierarchical linear models to compare outcomes between the ICUconnect and usual care arms within all participants and assess for differential intervention effects in Blacks and Whites by adding a patient-race interaction term. We hypothesize that both compared to usual care as well as among Blacks compared to Whites, ICUconnect will reduce unmet palliative care needs, psychological distress and healthcare resource utilization while improving goal concordance and interpersonal processes of care. In this manuscript, we also describe steps taken to adapt the ICUconnect intervention to the COVID-19 pandemic healthcare setting. Enrollment status A total of 36 (90%) of 40 ICU physicians have been randomized and 83 (52%) of 160 patient-family dyads have been enrolled to date. Enrollment will continue until the end of 2021.
Hospital Pricing Following Integration with Physician Practices.

Abstract The past decade has witnessed a new wave of hospital-physician integration, with the fraction of hospitals owning any office-based physician practice increasing from 28% in 2009 to 53% in 2015 nationwide. We offer one of the first hospital-level longitudinal analyses in examining how hospital-physician integration affects hospital prices in the modern healthcare environment. We find a robust 3–5% increase in hospital prices following integration. There is little indication that hospital quality is commensurately higher or that patient mix has changed following integration. Our supplementary analyses point to stronger bargaining leverage and foreclosure of rival hospitals as potential mechanisms for the estimated price effects.
Video-based Concurrent Activity Recognition for Trauma Resuscitation

We introduce a video-based system for concurrent activity recognition during teamwork in a clinical setting. During system development, we preserved patient and provider privacy by pre-computing spatio-temporal features. We extended the inflated 3D ConvNet (i3D) model for concurrent activity recognition. For the model training, we tuned the weights of the final stages of i3D using back-propagated loss from the fully-connected layer. We applied filtering on the model predictions to remove noisy predictions. We evaluated the system on five activities performed during trauma resuscitation, the initial management of injured patients in the emergency department. Our system achieved an average value of 74% average precision (AP) for these five activities and outperformed previous systems designed for the same domain. We visualized feature maps from the model, showing that the system learned to focus on regions relevant to performance of each activity.
Controllable quantum point junction on the surface of an antiferromagnetic topological insulator.

Engineering and manipulation of unidirectional channels has been achieved in quantum Hall systems, leading to the construction of electron interferometers and proposals for low-power electronics and quantum information science applications. However, to fully control the mixing and interference of edge-state wave functions, one needs stable and tunable junctions. Encouraged by recent material candidates, here we propose to achieve this using an antiferromagnetic topological insulator that supports two distinct types of gapless unidirectional channels, one from antiferromagnetic domain walls and the other from single-height steps. Their distinct geometric nature allows them to intersect robustly to form quantum point junctions, which then enables their control by magnetic and electrostatic local probes. We show how the existence of stable and tunable junctions, the intrinsic magnetism and the potential for higher-temperature performance make antiferromagnetic topological insulators a promising platform for electron quantum optics and microelectronic applications. Recent advances in the identification and growth of antiferromagnetic topological insulators open the way to the manipulation of the chiral edge states that are topologically required at their step edges and domain walls. Here, the authors propose a quantum point junction formed by two types of edge states and discuss its applications in electron quantum optics.
An Archive of Interfaces: Exploring the Potential of Emulation for Software Research, Pedagogy, and Design

This paper explores the potential of distributed emulation networks to support research and pedagogy into historical and sociotechnical aspects of software. Emulation is a type of virtualization that re-creates the conditions for a piece of legacy software to operate on a modern system. The paper first offers a review of Computer-Supported Cooperative Work (CSCW), Human-Computer Interaction (HCI), and Science and Technology Studies (STS) literature engaging with software as historical and sociotechnical artifacts, and with emulation as a vehicle of scholarly inquiry. It then documents the novel use of software emulations as a pedagogical resource and research tool for legacy software systems analysis. This is accomplished through the integration of the Emulation as a Service Infrastructure (EaaSI) distributed emulation network into a university-level course focusing on computer-aided design (CAD). The paper offers a detailed case study of a pedagogical experience oriented to incorporate emulations into software research and learning. It shows how emulations allow for close, user-centered analyses of software systems that highlight both their historical evolution and core interaction concepts, and how they shape the work practices of their users.
Virtual learning experiences in population health nursing course during the COVID-19 pandemic.

Aim To discuss the virtual learning strategies used in population health nursing course during the coronavirus disease 2019 (COVID-19) pandemic. Background The School of Nursing faculty in a South Central University in the United States quickly combined innovation with digital resources and transitioned a course in population health during the COVID-19 pandemic. Nursing faculty were challenged to develop student nursing objectives in assessment, planning, intervention and evaluation of vulnerable populations in the community through a virtual environment. Reflections of population health nursing clinical education The experiences of five clinical groups are described, covering adults with disabilities, older people, patients with COVID-19 and youth populations. Discussion The course objectives were met through use of a digital environment. Collaborative interventions were designed and implemented with community stakeholders while maintaining social distancing policies. Successes included increased frequency of communication and learning opportunities for students and the community, and student satisfaction. Barriers to student learning were not related to the digital learning environment, although the older adults required modifications to use electronic devices. Conclusion Virtual classrooms are a viable platform to teach population health nursing and to benefit vulnerable populations. Implications for nursing practice Virtual learning offers benefits within academia and the community. Technology offers the possibility to improve mental health among older people and enhance knowledge among the general population. Students are better able to connect with clinical faculty and stakeholders through digital platforms. Implications for nursing policy Nurses play a vital role in improving population health and can collaborate with community stakeholders to implement innovative and sustainable solutions to nursing education, practices and policy. Digital platforms can enhance the involvement of students through these collaborations during and after the pandemic.
Steady Seepage toward Circle of Finite Radius

There are a number of practical examples in the theory of steady seepage through porous media in which boundary geometries can be modeled with a circle next to an infinitely long, straight line. The intention of this note is to compare the mathematically exact and approximate flow rates for these examples in order to determine when these flows can be modeled accurately with a line singularity.
Representing the National Landscape in Irish Romanticism

Ireland is a country which has come to be defined in part by an ideology which conflates nationalism with the land. From the Irish Revival's celebration of the Irish peasant farmer as the ideal Irishman to the fierce history of land claim battles between the Irish and their colonisers, notions of the land have become particularly bound up with conceptions of what Ireland is and what it is to be Irish. In this book, Wright considers this fraught relationship between land and national identity in Irish literature. In doing so, she presents a new vision of the Irish national landscape as one that is vitally connected to larger geographical spheres. By exploring issues of globalisation, international radicalism, trade routes, and the export of natural resources, Wright is at the cutting edge of modern global scholarly trends and concerns. In considering texts from the Romantic era such as Leslie's Killarney, Edgeworth's ""Limerick Gloves,"" and Moore's Irish Melodies, Wright undercuts the nationalist myth of a ""people of the soil"" using the very texts which helped to construct this myth. Reigniting the field of Irish Romanticism, Wright presents original readings which call into question politically motivated mythologies while energising nationalist conceptions that reflect transnational networks and mobility.
Representation and Inequality in Late Nineteenth-Century America: The Politics of Apportionment

Review of: "Representation and Inequality in Late Nineteenth-Century America: The Politics of Apportionment," by Peter H. Argersinger.
Decision-Analytic Intelligent Systems: Automated Explanation and Knowledge Acquisition

This book presents a framework for building intelligent systems based on the mathematical decision models of Decision Analysis. The author provides new techniques for automated explanation and knowledge acquisition in formally sound systems that reason about complex tradeoffs in decisions. Also included are specifications for implementing these techniques in computer programs, along with demonstration applications in marketing, process control, and medicine. Readers with an interest in artificial intelligence will gain a foundation for building formally justifiable, intelligible, modifiable systems for computing decisions involving multiple considerations, with applications across a variety of domains. Beyond decision models, the methodology of the work reported suggests a more general approach to employing formal mathematical models in transparent intelligent systems. Decision-analysis experts will find a collection of methods for explaining decision-analytic advice to clients in intuitive terms, for simplifying parameter assessment, and for managing changing preferences over time. The book provides sufficient background material to promote understanding by readers who may be unfamiliar with artificial intelligence, with decision analysis, or with both fields, and such material is labeled to increase the well-versed reader's efficiency in skipping particular sections.
Synthetic approach for unsaturated precursors for parahydrogen induced polarization of choline and its analogs

Reported here are (i) a new synthetic approach for preparation of (ii) a new compound class, of -OH, for example, an -OH group is replaced with acetyl protecting group, protected 1,2-dehydrocholine analogs and (iii) a new synthetic route for betaine aldehyde. The CC bond of 1,2-dehydrocholine moiety can be used for molecular addition of parahydrogen producing -OH protected hyperpolarized choline by parahydrogen-induced polarization (PHIP). The reported synthetic approach allows for incorporation of (15) N and deuterium labels, which are necessary for preparation of highly polarized PHIP contrast agents. Isotope labeling with (15) N and/or deuterium was conducted. Hyperpolarized (15) N-choline enabled by the reported synthetic approach can be potentially used as an imaging biomarker of cancer similar to choline positron emission tomography tracers.
New analytic solutions for the 2-D TE mode MT problem

SUMMARY A closed-form solution is given for a 2-D, transverse electric mode, magnetotelluric (MT) problem. The model system consists of a finite vertical thin conductor with variable integrated conductivity over a perfectly conducting base. A notable property of the solution is that the frequency response possesses a single pole in the complex plane. Systems with finitely many resonances play a central role in the 1-D MT inverse problem based on finite data sets, but until now, no 2-D system of this kind was known. The particular model is shown to be just one of a large class of thin conductors with same the property, and further examples are given. The solutions of the induction problem for members of this family can often be written in compact closed form, making them the simplest known solutions to the 2-D MT problem.