cssi/SciSciGPT-SciSciNet huggingface dataset:
Establishing human factors criteria for space control systems

This paper describes the development of a human factors methodology and its application to the operational test and evaluation of space control systems. The method uses a correlational approach to link human factors measures to the mission effectiveness of space control systems. Experiment 1 describes an initial wide-spectrum attempt to identify human factors predictors of system performance. Based on the results of Experiment 1. the human factors measures and analysis method were refined and applied in the test of an operational satellite control system in Experiment 2. Experiment 3 applied the same methodology to a different satellite control system in order to determine the generalizability of the approach. The methodology worked with more than one system and was robust with respect to changes in personnel and location. The methodology was sensitive to changes in software, hardware, and procedures, and it yielded data that correctly reflected those changes.
Active Site Binding Is Not Sufficient for Reductive Deiodination by Iodotyrosine Deiodinase.

The minimal requirements for substrate recognition and turnover by iodotyrosine deiodinase were examined to learn the basis for its catalytic specificity. This enzyme is crucial for iodide homeostasis and the generation of thyroid hormone in chordates. 2-Iodophenol binds only very weakly to the human enzyme and is dehalogenated with a kcat/Km that is more than 4 orders of magnitude lower than that for iodotyrosine. This discrimination likely protects against a futile cycle of iodinating and deiodinating precursors of thyroid hormone biosynthesis. Surprisingly, a very similar catalytic selectivity was expressed by a bacterial homologue from Haliscomenobacter hydrossis. In this example, discrimination was not based on affinity since 4-cyano-2-iodophenol bound to the bacterial deiodinase with a Kd lower than that of iodotyrosine and yet was not detectably deiodinated. Other phenols including 2-iodophenol were deiodinated but only very inefficiently. Crystal structures of the bacterial enzyme with and without...
What's Next After Process Characterization

Semiconductor packaging industry has been intensively driven into miniaturizing and thinning of package with more functionality, in short, "getting more with less". With the increasing complexity in packaging, the process characterization has been pushed to the limit in order to maintain a stable and predictable process. This has led to great challenges in thorough process characterization using sequential design of experiments (DOEs) to ensure the most optimized process window is achieved. However, a well characterized process today may not behave in similar manner tomorrow. Any slight variation in raw material or machine inherent variation will drift the optimized process window. This will definitely affect the stability and predictability of the process. It has been observed that under certain situation, the process seems to be perfectly characterized and optimized during engineering run, but low ppm of defects will only be surfaced out during production run. The reason for this observation is that process characterization during engineering run is mostly performed under controlled environment using the best performed machine with one single batch of material. Additional process characterization through detailed Design of Experiments (DOEs) and further optimization through Response Surface Methodology (RSM) may not help to resolve the issue. Major portion of this issue can be attributed to machine-to-machine variation, time instability of the machine and material variation. In order to maintain machine-to-machine consistency and time stability, equipment characterization methodology has been developed based on Six Sigma DMAIC methodology. It covers 5 major phases, which are Define, Measure, Analyze, Improve and Control Phase. Within every phase, data analysis is performed using statistical tools in order to draw data-driven conclusion. This paper will discuss about how Six Sigma DMAIC approach is used to develop effective equipment characterization methodology in order to minimize machine-to-machine variation and maintain time stability. Statistical tools employed in every phase will be discussed as well. The focus of this paper is on the methodology developed and used in one case study. The equipment characterization methodology has been successfully used in the case study to achieve significant OEE improvement by more than 5%, which results in additional capacity without capital. Other advantages include better machine performance with more predictable process, better machine portability, reduction of non-screenable quality related issues and improvement in yield loss.
Adaptive Visual Servo Control of Robotic Harvesting Systems

Abstract: Harvesting efficiency is a critical factor in determining whether robotic harvesting can be economically superior to hand picking. One practical challenge in robotic harvesting is to grasp a moving fruit, where unsuccessful pick cycles may result in lower harvesting efficiency. The fruit motion can be due to exogenous disturbances such as wind gust, canopy unloading, and particularly, fruit detachment forces. In this paper, an adaptive visual servo control law is presented to estimate and subsequently compensate the unknown time-varying fruit motion. The fruit motion in the image plane and along the optical axis is modeled as a second-order spring-mass system. The unknown parameters of fruit motion are identified using an adaptive parameter update law, and a robust feedback term is included in the control law to account for modeling uncertainties. Lyapunov-based stability analysis guarantees uniformly ultimately bounded regulation of the robot to the fruit position. Simulation results are provided to verify the feasibility of the developed controller.
A fast algorithm for demixing signals with structured sparsity

Demixing, or source separation, involves disentangling a complicated signal into simpler, more informative components. Algorithms for signal demixing impact several applications, ranging from interference cancellation in communication signals, foreground-background separation in images and video, and outlier suppression in machine learning. Central to several modern demixing algorithms is an assumption of some form of low-dimensional structure in the signal components. However, the majority of these modern algorithms are based on convex optimization, and their computational complexity can be high (polynomial) in terms of the signal size. In this paper, we propose a new algorithmic approach for signal demixing based on structured sparsity models. Our approach leverages recent advances in constructing sparsity models via appropriately chosen graphs; this graphical approach can be shown to model a diverse variety of low-dimensional structures in signals. Despite being highly nonconvex, our algorithm exhibits a nearly-linear running time, and therefore is scalable to very high-dimensional signals. We supplement our proposed algorithm with a theoretical analysis, providing sufficient conditions for provably reconstruction of the underlying components. Finally, we demonstrate the validity of the method via numerical experiments on real 2D image data.
Optimum Extraction of an Exhaustible Resource: A Mathematical Analysis

In this paper, we discuss optimum extraction of an exhaustible resource. The problem is essentially the same as in (Ref. 1), but we shall study it in greater detail and in a somewhat more general context.
Language-agnostic simulation model management platform

Simulation models are expensive to design and run. Commercial modeling software made for specific industries are costly and do not allow for compatibility across languages. Free and open source languages allow for more control in model creation. However, models written using these languages require more time to develop and interpret. We present a platform compatible with open source languages that runs models in Monte Carlo and Design of Experiments sampling with the ability to randomly distribute inputs and interpret outputs. Supported languages include Java, Python, and R. The platform utilizes a parameter input configuration syntax which defines how model inputs are distributed, allowing for both deterministic and stochastic model creation. Models outputs are then interpreted by the platform using built-in customizable tools.
PREDICTING ACADEMICS VIA BEHAVIOR WITHIN AN ELEMENTARY SAMPLE: AN EVALUATION OF THE SOCIAL, ACADEMIC, AND EMOTIONAL BEHAVIOR RISK SCREENER (SAEBRS)

This study examined the extent to which teacher ratings of student behavior via the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) predicted academic achievement in math and reading. A secondary purpose was to compare the predictive capacity of three SAEBRS subscales corresponding to social, academic, or emotional domains of behavior. Universal screening was conducted to evaluate 1,058 elementary students’ performance in both reading and math, which were then combined to form a composite estimate of overall academic performance. Results indicated that the SAEBRS composite scale and all three subscales each individually predicted academic performance. Results further indicated that the SAEBRS Academic Behavior subscale was the best predictor of academic performance. Furthermore, the SAEBRS Social Behavior scale was found to function as a net suppressor variable, enhancing the capacity of Academic Behavior to predict academic performance via the suppression of variance irrelevant relative to academic performance. Follow-up path analyses suggested Academic Behavior also served as a mediating variable, as it partially accounted for the relationship between Social Behavior and academic performance. Implications for educators and limitations of this study are discussed.
GLP-1 receptor agonists in the treatment of polycystic ovary syndrome

Introduction: Polycystic ovarian syndrome (PCOS) affects many women of child-bearing age and is characterized by hyperandrogenism, ovulatory and metabolic dysfunction. A primary treatment goal is w...
Transfer of a skilled motor learning task between virtual and conventional environments

Immersive, head-mounted virtual reality (HMD-VR) can be a potentially useful tool for motor rehabilitation. However, it is unclear whether the motor skills learned in HMD-VR transfer to the non-virtual world and vice-versa. Here we used a well-established test of skilled motor learning, the Sequential Visual Isometric Pinch Task (SVIPT), to train individuals in either an HMD-VR or conventional training (CT) environment. Participants were then tested in both environments. Our results show that participants who train in the CT environment have an improvement in motor performance when they transfer to the HMD-VR environment. In contrast, participants who train in the HMD-VR environment show a decrease in skill level when transferring to the CT environment. This has implications for how training in HMD-VR and CT may affect performance in different environments.
Presynaptic Dopamine Synthesis Capacity in Schizophrenia and Striatal Blood Flow Change During Antipsychotic Treatment and Medication-Free Conditions

Standard-of-care biological treatment of schizophrenia remains dependent upon antipsychotic medications, which demonstrate D2 receptor affinity and elicit variable, partial clinical responses via neural mechanisms that are not entirely understood. In the striatum, where D2 receptors are abundant, antipsychotic medications may affect neural function in studies of animals, healthy volunteers, and patients, yet the relevance of this to pharmacotherapeutic actions remains unresolved. In this same brain region, some individuals with schizophrenia may demonstrate phenotypes consistent with exaggerated dopaminergic signaling, including alterations in dopamine synthesis capacity; however, the hypothesis that dopamine system characteristics underlie variance in medication-induced regional blood flow changes has not been directly tested. We therefore studied a cohort of 30 individuals with schizophrenia using longitudinal, multi-session [15O]-water and [18F]-FDOPA positron emission tomography to determine striatal blood flow during active atypical antipsychotic medication treatment and after at least 3 weeks of placebo treatment, along with presynaptic dopamine synthesis capacity (ie, DOPA decarboxylase activity). Regional striatal blood flow was significantly higher during active treatment than during the placebo condition. Furthermore, medication-related increases in ventral striatal blood flow were associated with more robust amelioration of excited factor symptoms during active medication and with higher dopamine synthesis capacity. These data indicate that atypical medications enact measureable physiological alterations in limbic striatal circuitry that vary as a function of dopaminergic tone and may have relevance to aspects of therapeutic responses.
Compañeros: High School Students Mentor Middle School Students to Address Obesity Among Hispanic Adolescents.

INTRODUCTION Promotoras, Hispanic community health workers, are frequently employed to promote health behavioral change with culturally bound Hispanic lifestyle behaviors. Peer health mentors have been used in schools to promote healthy nutrition and physical activity behaviors among students. This study investigates the efficacy of combining these 2 approaches by training high school health mentors, called companeros, to engage Hispanic middle school students in a school-based obesity intervention as a strategy to promote and sustain reductions in standardized body mass index (zBMI). METHODS High school companeros were trained to participate in a 6-month obesity program alongside middle school students in Houston, Texas. Middle school students were randomized to participate in the program either with companeros (n = 94) or without companeros (n = 95). The intervention was conducted from 2013 through 2016 in 3 cohorts of students, 1 each school year. Students were followed for 12 months. The primary outcome was zBMI, which was analyzed at baseline, 6 months, and 12 months. RESULTS Significant differences were found between conditions across time (F = 4.58, P = .01). After the 6-month intervention, students in the condition with companeros had a larger decrease in zBMI (F = 6.94, P = .01) than students in the condition without companeros. Furthermore, students who received the intervention with companeros showed greater sustained results at 12 months (F = 7.65, P = .01). CONCLUSION Using high school companeros in an obesity intervention for Hispanic middle school students could be effective in promoting and maintaining reductions in zBMI.
Hemoglobin Providence (β82 Lys > Asn, Asp) and lower-than-expected HbA1c in a nonadherent teenager with type 1 diabetes: a case report and literature review

Key Clinical Message Endocrinologists should have a high index of suspicion for a Hb variant when the HbA1c is not consistent with other indices of glycemic control.
Accelerating Alzheimer's disease drug innovations from the research pipeline to patients

Abstract In June 2017, a diverse group of experts in Alzheimer's disease convened to discuss how to accelerate getting new drugs to patients to both prevent and treat the disease. Participants concluded that we need a more robust, diversified drug development pipeline. Strategic policy measures can help keep new Alzheimer's disease therapies (whether to treat symptoms, prevent onset, or cure) affordable for patients while supporting innovation and facilitating greater information sharing among payers, providers, researchers, and the public, including a postmarket surveillance study system, disease registries, innovative payment approaches, harmonizing federal agency review requirements, allowing conditional coverage for promising therapeutics and technology while additional data are collected, and opening up channels for drug companies to communicate with payers (and each other) about data and outcomes. To combat reimbursement issues, policy makers should address the latency time between potential treatment—which may be costly and fall on private payers—and societal benefits that accrue elsewhere.
Whole-Plant Metabolic Allocation Under Water Stress.

Trade-offs between plant growth and defense depend on environmental resource availability. Plants are predicted to prioritize growth when environmental resources are abundant and defense when environmental resources are scarce. Nevertheless, such predictions lack a whole-plant perspective—they do not account for potential differences in plant allocation above- and belowground. Such accounting is important because leaves and roots, though both critical to plant survival and fitness, differ in their resource-uptake roles and, often, in their vulnerability to herbivores. Here we aimed to determine how water availability affects plant allocation to multiple metabolic components of growth and defense in both leaves and roots. To do this, we conducted a meta-analysis of data from experimental studies in the literature. We assessed plant metabolic responses to experimentally reduced water availability, including changes in growth, nutrients, physical defenses, primary metabolites, hormones, and other secondary metabolites. Both above- and belowground, reduced water availability reduced plant biomass but increased the concentrations of primary metabolites and hormones. Importantly, however, reduced water had opposite effects in different organs on the concentrations of other secondary metabolites: reduced water increased C-based secondary metabolites in leaves but reduced them in roots. In addition, plants suffering from co-occurring drought and herbivory stresses exhibited dampened metabolic responses, suggesting a metabolic cost of multiple stresses. Our study highlights the needs for additional empirical studies of whole-plant metabolic responses under multiple stresses and for refinement of existing plant growth-defense theory in the context of whole plants.
Fast Parallel Connected Components Algorithms on GPUs

We study parallel connected components algorithms on GPUs in comparison with CPUs. Although straightforward implementation of PRAM algorithms performs relatively better on GPUs than on CPUs, the GPU memory subsystem performance is poor due to non-coalesced random accesses. We argue that generic sort-based access coalescing is too costly on GPUs. We propose a new coalescing technique and a new meta algorithm to improve locality and performance. Our optimization achieves up to 2.7 times speedup over the straightforward implementation. Interestingly, our optimization also works well on CPUs. Comparing the best-performing algorithms on GPUs and CPUs, we find our new algorithm is the fastest on GPUs and the second fastest on CPUs, while the parallel Rem's algorithm is the fastest on CPUs but does not perform well on GPUs due to path divergence.
Primary spontaneous mesencephalic hemorrhage

The case histories of two patients with clinically diverse forms of the very rare entity primary, spontaneous mesencephalic hemorrhage are presented. Each exhibited characteristic mesencephalic signs and neuroimaging profiles. However, both patients differed markedly in their predisposing factors, state of arousal, memory, temporal course and functional residua. One patient was unique in displaying a normal level of alertness throughout his clinical course and an isolated retrograde amnesia. The latter sign suggests a role for mesencephalic reticular activation in long-term retrieval and illustrates the differential effects of a subtle activation deficit on memory and arousal. These findings broaden the distinctive clinico-anatomical profile of primary, spontaneous mesencephalic hemorrhage.
Answering Structured Queries on Unstructured Data.

There is growing number of applications that require access to both structured and unstructured data. Such collections of data have been referred to as dataspaces, and Dataspace Support Platforms (DSSPs) were proposed to offer several services over dataspaces, including search and query, source discovery and categorization, indexing and some forms of recovery. One of the key services of a DSSP is to provide seamless querying on the structured and unstructured data. Querying each kind of data in isolation has been the main subject of study for the fields of databases and information retrieval. Recently the database community has studied the problem of answering keyword queries on structured data such as relational data or XML data. The only combination that has not been fully explored is answering structured queries on unstructured data. This paper explores an approach in which we carefully construct a keyword query from a given structured query, and submit the query to the underlying engine (e.g., a web-search engine) for querying unstructured data. We take the first step towards extracting keywords from structured queries even without domain knowledge and propose several directions we can explore to improve keyword extraction when domain knowledge exists. The experimental results show that our algorithm works fairly well for a large number of datasets from various domains.
Impact of Segment Size and Parallel Streams on TCP BBR

TCP BBR has been recently proposed as a congestion control algorithm. BBR represents a disruption from the window-based loss-based congestion control used during the last 30 years. While BBR has been tested for trivial applications (e.g., browsing, YouTube), its use for moving big data has not been extensively studied yet. Features that largely impact the efficiency of transporting big flows are the use of parallel streams and the maximum segment size (MSS). This paper studies the impact of these two features on big flows, in the presence of packet losses and latency. Empirical results demonstrate that BBR reacts better than window-based loss-based algorithms (Cubic, Reno, HTCP) to large MSS. Similarly, as the number of parallel streams used in a data transfer increases, the performance gap between BBR and Cubic, Reno, and HTCP increases in favor of BBR. For example, in a 20-millisecond RTT, 10 Gbps network with high corruption rate (0.01%), BBR's average improvement factor from using multiple streams is almost 4. In contrast, HTCP's, Cubic's, and Reno's improvement factors are below 2. Using large MSS and parallel streams permit BBR to sustain high throughput, even in the presence of a significant corruption rate.
Unjust punishment in organizations

Abstract What causes leaders to punish subordinates unjustly? And why might leaders keep punishing subordinates unjustly, even when this increases workplace misconduct? In the current paper we address these questions by suggesting that power and status cause leaders to punish unjustly. We review evidence on the effects of power and status on punishment, review how unjust punishments foster misconduct, and highlight how this creates a self-perpetuating feedback loop—leaders are more likely to punish in an unjust manner when subordinates engage in misconduct, but subordinates’ misconduct is partly caused by unjust punishments. We also discuss how leader-subordinate distrust may be at the heart of this phenomenon and how organizations may counteract unjust punishments. We draw attention to research areas that have received little attention and draw up an agenda for future research. Taken together, we integrate the literatures on power, status, punishment and trust, review evidence on when unjust punishments become perpetuating, challenge research suggesting that leaders are cautious when punishing, and guide future research on the topic of punishment in organizations.
Abnormalities in gray matter microstructure in young adults with 22q11.2 deletion syndrome.

Abstract Background 22q11.2 Deletion Syndrome (22q11DS) is a genetic, neurodevelopmental disorder characterized by a chromosomal deletion and a distinct cognitive profile. Although abnormalities in the macrostructure of the cortex have been identified in individuals with 22q11DS, it is not known if there are additional microstructural changes in gray matter regions in this syndrome, and/or if such microstructural changes are associated with cognitive functioning. Methods This study employed a novel diffusion MRI measure, the Heterogeneity of Fractional Anisotropy (HFA), to examine variability in the microstructural organization of the cortex in healthy young adults (N = 30) and those with 22q11DS (N = 56). Diffusion MRI, structural MRI, clinical and cognitive data were acquired. Results Compared to controls, individuals with 22q11DS evinced increased HFA in cortical association (p = .003, d = 0.86) and paralimbic (p Conclusions These findings suggest that cortical microstructural disorganization may be a neural correlate of response inhibition in individuals with 22q11DS. Given that the migration pattern of neural crest cells is disrupted at the time of early brain development in 22q11DS, we hypothesize that these neural alterations may be neurodevelopmental in origin, and reflect cortical dysfunction associated with cognitive deficits.
Solving Nonlinear Parabolic Equations by a Strongly Implicit Finite Difference Scheme

We discuss the numerical solution of nonlinear parabolic partial differential equations , exhibiting finite speed of propagation, via a strongly implicit finite difference scheme with formal truncation error \(\mathcal {O}\left [(\Delta x)^2 + (\Delta t)^2 \right ]\). Our application of interest is the spreading of viscous gravity currents in the study of which these type of differential equations arise. Viscous gravity currents are low Reynolds number (viscous forces dominate inertial forces) flow phenomena in which a dense, viscous fluid displaces a lighter (usually immiscible ) fluid. The fluids may be confined by the sidewalls of a channel or propagate in an unconfined two-dimensional (or axisymmetric three-dimensional) geometry. Under the lubrication approximation, the mathematical description of the spreading of these fluids reduces to solving the so-called thin film equation for the current’s shape h(x, t). To solve such nonlinear parabolic equations we propose a finite difference scheme based on the Crank–Nicolson idea. We implement the scheme for problems involving a single spatial coordinate (i.e., two-dimensional, axisymmetric or spherically symmetric three-dimensional currents) on an equispaced but staggered grid. We benchmark the scheme against analytical solutions and highlight its strong numerical stability by specifically considering the spreading of non-Newtonian power law fluids in a variable width confined channel like geometry (a “Hele-Shaw cell”) subject to a given mass conservation/balance constraint. We show that this constraint can be implemented by reexpressing it as nonlinear flux boundary conditions on the domain’s endpoints. Then, we show numerically that the scheme achieves its full second order accuracy in space and time. We also highlight through numerical simulations how the proposed scheme accurately respects the mass conservation/balance constraint.
(213) IgG-Immune Complex Directly Activates Joint Sensory Neurons through Neuronal FcγRI to Induce Arthritis Pain

Joint pain in rheumatoid arthritis (RA) represents a significant health burden. Although RA pain is conventionally thought to result from inflammation, it often persists even after control of inflammation with available therapies, suggesting the additional involvements of non-inflammatory mechanisms. Yet, such mechanisms remain largely unexplored. Our in situ hybridization assays suggested that the immune complex receptor FcγRI was expressed in a subpopulation of joint sensory neurons. Consistent with this finding, the proportion of joint sensory neurons exhibiting a Ca2+ increase in response to IgG-immune complex (IgG-IC), assayed both in vitro and in vivo, was lower in global FcγRI−/− mice, compared with wildtype mice. Injection of IgG-IC but not monomeric IgG into one ankle of naive mice evoked joint pain-related behaviors without concurrent joint swelling. This effect was diminished in global FcγRI−/− mice. Ablation of T and B cells, mast cells or macrophages had no effect on IgG-IC evoked nocifensive behaviors. Under arthritic conditions, FcγRI mRNA expression and function were upregulated in dorsal root ganglion (DRG) in a mouse model of antigen-induced arthritis (AIA). In vivo extracellular electrophysiological recordings on intact DRG showed that genetic deletion of FcγRI reduced the incidence of abnormal activity and mechanical hypersensitivity of joint sensory neurons in the context of AIA. Acute blockade of FcγRI with neutralizing antibody and genetic knockout of FcγRI significantly attenuated pain-related behaviors in the AIA model. Conversely, no significant differences between treatments or genotypes were observed in the inflamed joint in the expression level of cytokines or in immune cell infiltration. These findings indicate that FcγRI may contribute to arthritis pain through a non-inflammatory mechanism that parallels inflammation and joint damage and point towards a promising therapeutic target to consider for RA pain that is resistant to current anti-inflammatory treatments. Supported by NIAMS 1R01AR072230 to L.Q.
A two-field semi-Lagrangian reproducing kernel model for impact and penetration simulation into geo-materials

In this paper, a displacement–pressure (u–p) semi-Lagrangian reproducing kernel (RK) is introduced to study the penetration depth of various projectile types into dry and fully saturated geo-materials. To describe the poromechanics of saturated materials, Biot theory is incorporated into the semi-Lagrangian formulation and a damage model is embedded into Drucker–Prager constitutive model to simulate the soil behavior and separation during the impact and penetration process. The stabilized nodal domain integration is developed in the two-field semi-Lagrangian RK formulation to ensure numerical stability, and the kernel contact algorithm is implemented to model the interaction between soil and projectile bodies. Several examples are studied to validate and assess the proposed method’s performance in predicting the final penetration depth, and the results are compared to those reported in the literature.
Distribution of iron in the liver predicts the response of chronic hepatitis C infection to interferon therapy

Recent evidence suggests that patients with chronic hepatitis C virus (CHCV) who respond to interferon-alpha (IFN) therapy have a lower hepatic iron concentration than those who do not. The object of this study was to assess the concentration and distribution of iron in liver biopsies from 15 patients with CHCV seen at the authors' medical center between June 1992 and March 1993. Patients with complete response to IFN were compared to those with non-complete response with respect to quantitative hepatic iron concentration, serum iron indices, and a detailed analysis of histologic features of hematoxylin-and-eosin and iron-stained pre-IFN biopsies. Patients with non-complete response had significantly higher scores for stainable iron in sinusoidal cells (P = .02) and portal tracts (P = .05) than did patients with complete response. Total hepatic iron scores, mean quantitative hepatic iron, and mean serum ferritin were higher in patients with noncomplete response, but the differences were not significant. In conclusion, iron deposition in sinusoidal cells and portal tracts is significantly less frequent in patients with complete response to IFN than in those with poor or no response, and may be a useful, objective predictor of response to IFN therapy.
General surgery chief residents' perspective on surgical education during the coronavirus disease 2019 (COVID-19) pandemic.

Abstract Background The coronavirus disease 2019 pandemic has negatively affected the training of general surgery chief residents during the last trimester of their residency. Our goal was to evaluate the educational concerns of graduating general surgery chief residents during the coronavirus disease 2019 pandemic. Methods An anonymous web-based survey was distributed between March 31 and April 7, 2020 to all current general surgery chief residents from 6 academic medical centers in Boston, Massachusetts. Interviews were also conducted with attending surgeons from participating institutions. Results A total of 24 of 39 general surgery chief residents participated in our survey (61.5% response rate). General surgery chief residents were most concerned about the potential delay in the date of board examinations, followed by not feeling adequately prepared for the board examinations and a possible delay in the graduation date. Whereas not having enough cases to feel ready for fellowship or job and not achieving a sufficient number of cases to meet the requirements for graduation were only moderately concerning to chief residents, attending surgeons stressed a greater importance on the loss of the operative experience as nearly all (93.3%) of them suggested a personalized approach for additional general surgery training during fellowship or job onboarding. Conclusion In addition to the dramatic impact on public health, the coronavirus disease 2019 outbreak has also caused unprecedented changes to surgical education. Therefore, creative interventions are needed to help general surgery chief residents successfully transition into the next phase of their surgical career.
Towards full cell potential utilization during water purification using Co/Bi/TiO2 nanotube electrodes

Abstract Here we report on a research effort towards full cell potential utilization during the elimination of organic pollutants under environmentally relevant conditions. Meropenem was selected as a representative recalcitrant antibiotic and a newly-developed Co and Bi co-doped TiO2 nanotube array (Co/Bi/TiO2 NTA) electrode was employed as both anode and cathode. While electrochemical reduction of Meropenem appeared to be much more energy efficient (0.042 kWh/m3) than electrochemical oxidation (0.813 kWh/m3) in synthetic electrolyte, the degradation was significantly inhibited in environmental matrices (secondary effluent/SE and RO concentrate) due to the competition and/or inhibition effects of other species present in the matrices as well as electrode fouling. Calcium carbonate and magnesium oxide were identified to be main mineral foulants. The elimination of Meropenem was then examined in coupled treatment schemes (e.g. sequential and simultaneous), taking advantages of the “self-regeneration” characteristic of TiO2 NTA based electrodes through cathodic polarization. While a simultaneous oxidation & reduction with regular polarity switching seems to be a preferred treatment scheme especially for challenging matrices such as RO concentrate, the bipolar stability of the nanostructured electrode may limit the electrode lifetime. A hybrid electrolysis system coupling anodic oxidation of organic pollutants and cathodic hydrogen generation as a renewable energy source was also tested in a flow-through reactor, where consistent and steady treatment performance was demonstrated for a period of 3 days. We think the results obtained from this study have underlined the importance of matrix characteristics on the design and selection of electrochemical treatment processes. It also provides insights into future development of coupled anodic and cathodic processes for water purification.
Моделирование экзоскелета с гибридным линейным гравитационным компенсатором

Purpose of research . Development of a mathematical model of an exoskeleton equipped with a hybrid linear gravity compensator (HLGC), dynamic analysis on the example of a typical exoskeleton application scenario (in the process of lifting a load), obtaining time patterns of changes in system parameters, including electric drive torques allowing assessment of power plan power consumption and energy efficiency. The article deals with the challenging issue of improving the efficiency of the exoskeletal suit by means of HLGC. The use of a hybrid approach makes it possible to increase the efficiency of assisting the exoskeletal suit when performing various technological operations, for example, when lifting a load, when tilting and holding. Methods. When developing a mathematical model, an original approach was used to form the motion trajectory of the exoskeleton sectors during operation, based on the use of seventh-order polynomials. The paper uses a mathematical model represented by a system of second-order differential equations that connects the moments acting on the operator and the exoskeleton, the angular accelerations of the operator's back and the exoskeleton. Results. During numerical simulation, time diagrams of changes in system parameters, angles of rotation of exoskeleton hinges, moments that occur in a hybrid LGC, as well as graphs of current consumption of engines when performing lift and tilt with a load are obtained. Conclusion. In the course of the research, a kinematic model of an exoskeleton suit equipped with a GLGC was developed, second-order differential equations describing the dynamic behavior of the electromechanical system were written, and numerical simulation was performed to estimate the forces and energy consumption in the exoskeleton hinges and the drive of the hybrid linear gravity compensator.
Translational Effect of Provider-Focused, Multi-State, Multi-Clinic Asthma Care Quality Improvement Program on Patient-Level Health Care Costs

Introduction/Objectives:Enhancing Care for Patients with Asthma (ECPA), a year-long provider-focused, multi-state, multi-clinic quality improvement program, decreased avoidable utilizations among p...
Introduction to novel developments in radio-imaging and radiotherapy

Radiation therapy has long been known to be a very effective form of therapy in relieving symptoms and prolonging the life of patients with brain metastases. Novel developments in this field have allowed oncologists to improve on older forms of radiation therapy; these recent advances in radiotherapeutic techniques (stereotactic radiosurgery and hippocampal-avoidant whole brain radiation therapy) allow sparing of the healthy brain from receiving unnecessary radiation while delivering effective treatment to the metastases, thus improving the quality of life for surviving patients. Furthermore, multiple clinical trials have documented the increased loco-regional control in the brain when radiosurgery is interdigitated with immune check point inhibitors for treatment of melanoma brain metastases. Mild hyperthermia has been used for decades as an adjuvant to radiotherapy in the treatment of radiation resistant cancers; lately, however, thermal therapies, such as hyperthermia, cryoablation, radiofrequency ablation and high intensity focused ultrasound are being investigated to provide a new ablative approach to cancer while thermoacoustic imaging and thermometry have recently been proposed as new techniques for monitoring tissue temperature in the breast during ablation treatment. In addition, other hybrid techniques have emerged that combine ultrasounds with other forms of energy such as light to provide a more accurate diagnosis and enhance the efficacy of therapy for early and late stage cancers.
Word-Final Disfluencies in a School-Age Child: Beneath the Tip of the Iceberg.

Purpose Disfluencies associated with stuttering generally occur in the initial position of words. This study reviews data from a school-age child with an atypical stuttering profile consisting pred...
Ontology and the Completeness of Sellars’s Two Images

Sellars claims completeness for both the “manifest” and the “scientific images” in a way that tempts one to assume that they are independent of each other, while, in fact, they must share at least one common element: the language of individual and community intentions. I argue that this significantly muddies the waters concerning his claim of ontological primacy for the scientific image, though not in favor of the ontological primacy of the manifest image. The lesson I draw is that we need to re-assess the aims of ontology.
Reporters and “Willing Propagandists”: AEF Correspondents Define Their Roles

Abstract World War I occurred at a pivotal time in the development of journalistic norms and press-military relations. Correspondents accredited to the American Expeditionary Force and the army officers who censored them entered the war in 1917 without clear guidelines on reporters' roles. Early clashes over censorship dissolved after a few months as reporters demonstrated they could be trusted with sensitive information and the army liberalized regulations. Still, correspondents grappled with whether they should report independently about all newsworthy events, regardless of whether they might be perceived as critical, or act as “propagandists” deliberately producing stories to support the war effort. This article, drawing from AEF correspondents' letters in the National Archives, argues that reporters sought to maximize access and minimize censorship in order to report freely stories that would be both accurate and patriotic. Among those who sought propagandistic roles were Westbrook Pegler and Heywood ...
An Ecosystems Approach to Human Service Database Design

ABSTRACT Early client-tracking databases were strongly influenced by the structure of previous paper-based systems. More recently, there has been evolution toward databases that attempt to represent the inter-connectedness of people in the human service environment. No consensus on best practices, however, has yet emerged. This paper presents a systems analysis technique and a data model based on one of the theoretical foundations of current social work practice: the ecosystems perspective. This approach facilitates a range of knowledge management and performance measurement capabilities that have so far been uncommon in client-tracking systems.
Kalman Filters for Dynamic and Secure Smart Grid State Estimation

Combining dynamic state estimation methods suchasKalmanfilterswithreal-timedatagenerated/collected by digital meters such as phasor measurement units (PMU) can lead to advanced techniques for improving the quality of monitoring and controllability in smart grids. Classic Kalman filters achieve optimal performance with ideal sys- tem models, which are usually hard to obtain in practice with unexpected disturbances, device failures, and malicious data attacks. In this work, we introduce and compare a novel method, viz. adaptive Kalman Filter with inflatable noise variances, against a variety of classic Kalman filters. Exten- sive simulation studies demonstrate the powerful ability of our proposed algorithm under suboptimal conditions such as wrong system modeling, sudden disturbance and bad data
Linear Response Theory and Spin Relaxation

Linear response theory is a powerful tool for interpreting and predicting the results of macroscopic experiments which measure transport and relaxation properties of non-equilibrium systems. The application of linear response theory proceeds in several steps, each of which yields more useful and detailed information concerning the time dependence of the non-equilibrium system.
The Death of Certainty

In the previous chapters we have attempted to illustrate the progress of a conceptual evolution, a search for certainty. This search began with a rather nebulous, poorly differentiated animistic or anthropomorphic way of viewing our world, through progressive differentiation via linguistic tools and other cultural instruments, to a religious conceptual frame in which man and his gods were differentiated from the world. With religion came ritual, dogma, and increased certainty. From the misty continuum of the beginning we became convinced of a standardized reality. Our certainty was bolstered by revelation and reified by a specialized social segment dominated by priests and shamen whose power rested heavily on words.
Willow: a user-programmable SSD

We explore the potential of making programmability a central feature of the SSD interface. Our prototype system, called Willow, allows programmers to augment and extend the semantics of an SSD with application-specific features without compromising file system protections. The SSD Apps running on Willow give applications low-latency, high-bandwidth access to the SSD's contents while reducing the load that IO processing places on the host processor. The programming model for SSD Apps provides great flexibility, supports the concurrent execution of multiple SSD Apps in Willow, and supports the execution of trusted code in Willow.We demonstrate the effectiveness and flexibility of Willow by implementing six SSD Apps and measuring their performance. We find that defining SSD semantics in software is easy and beneficial, and that Willow makes it feasible for a wide range of IO-intensive applications to benefit from a customized SSD interface.
Strain differences in behavioral and cellular responses to perinatal hypoxia and relationships to neural stem cell survival and self-renewal: Modeling the neurovascular niche.

Premature infants have chronic hypoxia, resulting in cognitive and motor neurodevelopmental handicaps caused by suboptimal neural stem cell (NSC) repair/recovery in neurogenic zones (including the subventricular and the subgranular zones). Understanding the variable central nervous system repair response is crucial to identifying “at risk” infants and to increasing survival and clinical improvement of affected infants. Using mouse strains found to span the range of responsiveness to chronic hypoxia, we correlated differential NSC survival and self-renewal with differences in behavior. We found that C57BL/6 (C57) pups displayed increased hyperactivity after hypoxic insult; CD-1 NSCs exhibited increased hypoxia-induced factor 1α (HIF-1α) mRNA and protein, increased HIF-1α, and decreased prolyl hydroxylase domain 2 in nuclear fractions, which denotes increased transcription/translation and decreased degradation of HIF-1α. C57 NSCs exhibited blunted stromal-derived factor 1-induced migratory responsiveness, decreased matrix metalloproteinase-9 activity, and increased neuronal differentiation. Adult C57 mice exposed to hypoxia from P3 to P11 exhibited learning impairment and increased anxiety. These findings support the concept that behavioral differences between C57 and CD-1 mice are a consequence of differential responsiveness to hypoxic insult, leading to differences in HIF-1α signaling and resulting in lower NSC proliferative/migratory and higher apoptosis rates in C57 mice. Information gained from these studies will aid in design and effective use of preventive therapies in the very low birth weight infant population.
VLSI architecture for video-assisted global positioning

We design and implement an efficient architecture for geometric computation of the global position of an airborne video camera from images of known landmarks. A solution based on this analysis, a robust Hough transform-like method facilitated by a class of CORDIC-structured computations is implemented within the framework of terrain navigation. It empowers aerial surveillance systems to navigate effectively when the global position and inertial navigation sensors are out of order. This is particularly useful when the GPS functionality is disrupted by jamming and other techniques. Our architecture exploits parallelism among independent operations and uses pipelining of critical components for superior performance. Double precision division being computationally expensive is performed minimally. Correlation between data is tapped to reduce complexity of flash ADCs, at the cost of few clock cycles once to initialize Hough voting