cssi/SciSciGPT-SciSciNet huggingface dataset:
Book Two of Radical Principia

By 1694 Newton had devised some quite radical plans for revising his 1687 Principia. “Newton came in the early 1690’s to conceive a grand scheme of revision of the published Principia,” writes white-side, in which not only its particular verbal and mathematical errors were to be corrected but, much more radically, the redundant in its logical and expository framework was to be cut out and the flimsier portions of the remaining structure were to be strengthened and supported and (where necessary) completely rebuilt. To David Gregory, during a visit by him to Cambridge in early May 1694, he proved unprecedentedly expansive regarding his intentions, elaborating for him a detailed overview of his plans for revision, and also showing him the manuscript papers in which he had already himself gone some way towards implementing them.♠
Repeated stimuli elicit diminished high-gamma electrocorticographic responses.

In the phenomenon of repetition suppression (RS), when a person views a stimulus, the neural activity involved in processing that item is relatively diminished if that stimulus had been previously viewed. Previous noninvasive imaging studies mapped the prevalence of RS for different stimulus types to identify brain regions involved in representing a range of cognitive information. However, these noninvasive findings are challenging to interpret because they do not provide information on how RS relates to the brain's electrophysiological activity. We examined the electrophysiological basis of RS directly using brain recordings from implanted electrocorticographic (ECoG) electrodes in neurosurgical patients. Patients performed a memory task during ECoG recording and we identified high-gamma signals (65–128 Hz) that distinguished the neuronal representation of specific memory items. We then compared the neural representation of each item between novel and repeated viewings. This revealed the presence of RS, in which the neuronal representation of a repeated item had a significantly decreased amplitude and duration compared with novel stimuli. Furthermore, the magnitude of RS was greatest for the stimuli that initially elicited the largest activation at each site. These results have implications for understanding the neural basis of RS and human memory by showing that individual cortical sites exhibit the largest RS for the stimuli that they most actively represent.
Energy analysis of four wireless sensor network MAC protocols

Using the MAC Layer Architecture framework, four power-aware MAC protocols were implemented in TinyOS on TelosB motes. Indoor energy measurements over a single-hop network topology were conducted using three wireless sensor network traffic patterns (broadcast, convergecast and local gossip). AS-MAC was the most energy-efficient for convergecast and local gossip traffic, while SCP-MAC was best for broadcast traffic. Over the three traffic patterns, BAS-MAC used slightly less energy than Crankshaft and BAS-MAC significantly outperformed AS-MAC in the broadcast traffic scenario.
Exploiting Resource Usage Patterns for Better Utilization Prediction

Understanding the resource utilization in computing clouds is critical for efficient resource planning and better operational performance. In this paper, we propose two ways, from microscopic and macroscopic perspectives, to predict the resource consumption for data centers by statistically characterizing resource usage patterns. The first approach focuses on the usage prediction for a specific node. Compared to the basic method of calibrating AR models for CPU usages separately, we find that using both CPU and memory usage data can improve the forecasting performance. The second approach is based on Principal Component Analysis (PCA) to identify resource usage patterns across different nodes. Using the identified patterns, we can reduce the number of parameters for predicting the resource usage on multiple nodes. In addition, using the principal components obtained from PCA, we propose an optimization framework to optimally consolidate VMs into a number of physical servers and in the meanwhile reduce the resource usage variability. The evaluation of the proposed approaches is based on traces collected from a production cloud environment.
Factors Associated with Uptake of Genetics Services for Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a common cardiovascular disorder with variable expressivity and incomplete penetrance. Clinical guidelines recommend consultation with a genetics professional as part of an initial assessment for HCM, yet there remains an underutilization of genetics services. We conducted a study to assess factors associated with this underutilization within the framework of the Health Belief Model (HBM). An online survey was completed by 306 affected individuals and at risk family members. Thirty-seven percent of individuals (113/306) had visited a genetics professional for reasons related to HCM. Genetic testing was performed on 53 % (162/306). Individuals who had undergone testing were more likely to have seen a genetics professional (p < 0.001), had relatives with an HCM diagnosis (p = 0.002), and have a known familial mutation (p < 0.001). They were also more likely to agree that genetic testing would satisfy their curiosity (p < 0.001), provide reassurance (p < 0.001), aid family members in making healthcare decisions (p < 0.001), and encourage them to engage in a healthier lifestyle (p = 0.002). The HBM components of cues to action and perceived benefits and barriers had the greatest impact on uptake of genetic testing. In order to ensure optimal counseling and care for individuals and families with HCM, awareness and education around HCM and genetic services should be promoted in both physicians and patients alike.
LQR-based optimal linear consensus algorithms

Laplacian matrices play an important role in linear consensus algorithms. This paper studies linear-quadratic regulator (LQR) based optimal linear consensus algorithms for multi-vehicle systems with single-integrator kinematics in a continuous-time setting. We propose two global cost functions, namely, interaction-free and interaction-related cost functions. With the interaction-free cost function, we derive the optimal (nonsymmetric) Laplacian matrix. It is shown that the optimal (nonsymmetric) Laplacian matrix corresponds to a complete directed graph. In addition, we show that any symmetric Laplacian matrix is inverse optimal with respect to a properly chosen cost function. With the interaction-related cost function, we derive the optimal scaling factor for a pre-specified symmetric Laplacian matrix associated with the interaction graph. Illustrative examples are given as a proof of concept.
Data and Modeling Issues Faced during the Efficiency Measurement of Road Maintenance Using Data Envelopment Analysis

Within the past two decades, the road maintenance concept has been gaining tremendous attention. This has brought about new institutional changes, predominant of which is the challenge for maintenance managers to achieve maximum performance from the existing road system. Such challenge makes it imperative to implement comprehensive systems that measure road maintenance performance. However, as pointed out by the Transportation Research Board, even though the road maintenance performance measurement systems developed and implemented by the state departments of transportation elaborate on the maintenance level of service (i.e., effectiveness of the road maintenance), the fundamental relationships between the maintenance level of service and the budget requirements (i.e., efficiency of road maintenance) need more investigation. This is mainly because not knowing how “efficient” state departments of transportation are in being “effective” can lead to excessive and unrealistic maintenance budget expectations. ...
"Rate My Therapist": Automated Detection of Empathy in Drug and Alcohol Counseling via Speech and Language Processing.

The technology for evaluating patient-provider interactions in psychotherapy–observational coding–has not changed in 70 years. It is labor-intensive, error prone, and expensive, limiting its use in evaluating psychotherapy in the real world. Engineering solutions from speech and language processing provide new methods for the automatic evaluation of provider ratings from session recordings. The primary data are 200 Motivational Interviewing (MI) sessions from a study on MI training methods with observer ratings of counselor empathy. Automatic Speech Recognition (ASR) was used to transcribe sessions, and the resulting words were used in a text-based predictive model of empathy. Two supporting datasets trained the speech processing tasks including ASR (1200 transcripts from heterogeneous psychotherapy sessions and 153 transcripts and session recordings from 5 MI clinical trials). The accuracy of computationally-derived empathy ratings were evaluated against human ratings for each provider. Computationally-derived empathy scores and classifications (high vs. low) were highly accurate against human-based codes and classifications, with a correlation of 0.65 and F-score (a weighted average of sensitivity and specificity) of 0.86, respectively. Empathy prediction using human transcription as input (as opposed to ASR) resulted in a slight increase in prediction accuracies, suggesting that the fully automatic system with ASR is relatively robust. Using speech and language processing methods, it is possible to generate accurate predictions of provider performance in psychotherapy from audio recordings alone. This technology can support large-scale evaluation of psychotherapy for dissemination and process studies.
Outlier Analysis: Advanced Concepts

Many scenarios for outlier analysis cannot be addressed with the use of the techniques discussed in the previous chapter. For example, the data type has a critical impact on the outlier detection algorithm. In order to use an outlier detection algorithm on categorical data, it may be necessary to change the distance function or the family of distributions used in expectation–maximization (EM) algorithms. In many cases, these changes are exactly analogous to those required in the context of the clustering problem.
Abstract IA-3: The regulation of p53 tumor suppressing activities

The p53 tumor suppressor is often altered in tumors via single nucleotide changes that alter critical amino acids in the DNA binding domain. These p53 mutants lose DNA binding activity and some mutants exhibit a gain‐of‐function phenotype that is manifested as metastasis in vivo . We have discovered that p53 mutants are normally unstable similar to wild type p53, and become stable in some tumors leading to the increased metastasis. Mdm2, a negative regulator of wild type p53 also negatively regulates mutant p53. Decreased Mdm2 gene dosage delays a cancer phenotype in tumor prone mouse models. In humans, an Mdm2 single nucleotide polymorphism (SNP) increases the levels of MDM2 and correlates with an earlier age of tumor onset. We have generated mice with the human MDM2 SNP and show that the SNP accelerates a tumor phenotype in mice. Citation Information: Cancer Res 2009;69(23 Suppl):IA-3.
Plasma prolactin, growth hormone, luteinizing hormone and glucocorticoids after prostaglandin F2alpha in heifers.

SummaryBlood plasma PRL, GH and glucocorticoids in heifers increased severalfold within 5-15 min after im injections of 15, 30, or 60 mg PGF2α or after a single 5 mg iv injection of PGF2α. Plasma LH increased at least twofold over basal estimates but not until 1.5-6 hr after im PGF2α. Constant iv infusion of PGF2α at the rate of 0.5 mg/min for 30 min produced greater plasma concentrations of PRL, GH, glucocorticoids and LH than those found after im injections. Plasma glucose increased 59-67% above pretreatment values between 30 and 60 min after iv administration of PGF2α. Plasma insulin increased more than twofold over basal estimates at 45 min after PGF2α administration, but these increases only approached significance (P ≃ 0.10). Free fatty acids did not change significantly (P > 0.05) after PGF2α administration. While exogenous PGF2α administration causes marked increases in several plasma hormones and glucose, the mechanism of action is unclear.
Global Optimization Under Uncertainty and Uncertainty Quantification Applied to Tractor-Trailer Base Flaps

Using a global optimization evolutionary algorithm (EA), propagating aleatory and epistemic uncertainty within the optimization loop, and using computational fluid dynamics (CFD), this study determines a design for a 3D tractor-trailer base (back-end) drag reduction device that reduces the wind-averaged drag coefficient by 41% at 57 mph (92 km/h). Because it is optimized under uncertainty, this design is relatively insensitive to uncertain wind speed and direction and uncertain deflection angles due to mounting accuracy and static aeroelastic loading. The model includes five design variables with generous constraints, and this study additionally includes the uncertain effects on drag prediction due to truck speed and elevation, steady Reynolds-averaged Navier–Stokes (RANS) approximation, and numerical approximation. This study uses the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) optimization and uncertainty quantification (UQ) framework to interface the RANS flow solver, grid generator, and optimization algorithm. The computational model is a simplified full-scale tractor-trailer with flow at highway speed. For the optimized design, the estimate of total predictive uncertainty is +15/−42%; 8–10% of this uncertainty comes from model form (computation versus experiment); 3–7% from model input (wind speed and direction, flap angle, and truck speed); and +0.0/−28.5% from numerical approximation (due to the relatively coarse, 6 × 106 cell grid). Relative comparison of designs to the no-flaps baseline should have considerably less uncertainty because numerical error and input variation are nearly eliminated and model form differences are reduced. The total predictive uncertainty is also presented in the form of a probability box, which may be used to decide how to improve the model and reduce uncertainty.
Development of a Coding Instrument to Assess the Quality and Content of Anti-Tobacco Video Games

Abstract Previous research has shown the use of electronic video games as an effective method for increasing content knowledge about the risks of drugs and alcohol use for adolescents. Although best practice suggests that theory, health communication strategies, and game appeal are important characteristics for developing games, no instruments are currently available to examine the quality and content of tobacco prevention and cessation electronic games. This study presents the systematic development of a coding instrument to measure the quality, use of theory, and health communication strategies of tobacco cessation and prevention electronic games. Using previous research and expert review, a content analysis coding instrument measuring 67 characteristics was developed with three overarching categories: type and quality of games, theory and approach, and type and format of messages. Two trained coders applied the instrument to 88 games on four platforms (personal computer, Nintendo DS, iPhone, and Androi...
CHAPTER 10 – Fractal Dimension and Hybridization

A single- and a dual-fractal analysis are presented in this chapter for solid- and liquid-phase DNA hybridization utilized for biosensor or immunoassay purposes. The fractal analysis provides a quantitative indication of the state of disorder and the binding-rate coefficient on the surface for the DNA–RNA binding systems analyzed. The fractal dimension value provides a quantitative measure of the degree of heterogeneity that exists on the biosensor or immunoassay surface. Initially, a single-fractal analysis was utilized to fit the DNA–RNA binding curve. This was indicated by the regression analysis provided by Sigma plot, where the error is the difference between the theoretical predicted value and the experimental value. Fractal dimensions for the dissociation step and dissociation-rate coefficients are presented in the chapter providing a more complete picture of the analyte–receptor reactions occurring on the surface than can be seen with an analysis of the binding step alone.
3-Dimensional numerical simulation of superadiabatic radiant porous burner with enhanced heat recirculation

Abstract A two-layer porous (fine and coarse) burner consisting of radiation corridors (finned rods) and an external preheater is numerically analyzed. The porous burner holds the flame and heats the finned rods effectively conducting heat to radiating disks downstream, while the sensible energy of the flue gas is recovered before exiting the burner by a preheater carrying a secondary air that mixes upstream with the fuel and primary air. Combination of inherent internal heat recirculation in the porous burner, external heat recovery and effective radiating pathways using the finned rods causes the exiting flue gas having a temperature lower than the radiating disks. The synchronized heat recirculation and preheating extend the lean flammability limit to 0.2 equivalence ratio and allow the radiating disk temperature higher than the exiting flue gas. The thermal nonequilibria (internal heat recirculation, local superadiabatic combustion and external preheating) and effective heat routing using radiation corridors are responsible for this reversed temperature leading to such a record thermal efficiency as high as 50%.
Multimodality Therapy of Localized Gastric Adenocarcinoma

Surgical resection is the primary method of obtaining a potential cure for patients with gastric adenocarcinoma. However, chemotherapy or chemoradiotherapy offer significant improvement in survival over surgery alone. Much of the difficulty in deciding the optimal treatment strategy is choosing between perioperative chemotherapy or adjuvant chemoradiotherapy. Adding to the complexity is the potential for incorporating treatment strategies based on clinical trials performed in Asia. There is likely a difference in tumor biology between Eastern and Western patients with gastric adenocarcinoma, in addition to the clear differences in screening, pathologic assessment, and surgical technique. Even among tumors in Western populations, heterogeneity of histology, anatomy, and staging among studies make cross-trial comparisons difficult. There is also active controversy surrounding the staging and management of gastroesophageal junction tumors. Lastly, the benefit of extended lymph node dissection is not clear based on the existing studies and has not been firmly established as a surgical standard of care for all patients. Future goals include better classification of gastric cancer, continued pursuit of randomized trials in Western populations, standardization of surgical technique, and incorporation of targeted therapies.
A novel robotic sound localization and separation using non-causal filtering and Bayesian fusion

Binaural localization and separation of two concurrent sound sources using a humanoid head is a challenging task, especially if the localization is done in the three dimensions using only the two ears of the humanoid. From a biological perspective, localization of sound sources, and the perceptual separation of sound mixtures by the human hearing organ are two closely interrelated processes. From a signal processing perspective, both localization and separation may be treated as two separate problems. This paper presents a novel method to localize and separate the sound sources, which are situated in high reverberation areas through the adaptation of a Multiple-Input-Multiple-Output system (MIMO) with a Bayesian network. It is shown that, taking account of connections between blind system identification and blind source separation, the sound sources are not only efficiently separated, they can also be accurately localized in the 3D space surrounding the humanoid head. This artificial head is equipped with two inner microphones and two outer microphones. The presented algorithm deploys a non-causal filter system using the known neural networks based principle of information propagation in combination with the machine learning based technique of Bayesian networks. Simulation results validated with experimental measurements showed that this method is outperforming in terms of localization accuracy and in solving the well-known front-back confusion problem.
MENINGKATKAN PEMAHAMAN MATEMATIKA SISWA MELALUI PENERAPAN PENDEKATAN MATEMATIKA REALISTIK PADA KELAS VI SD INPRES MALLENGKERI BERTINGKAT KOTA MAKASSAR

Penelitian ini merupakan penelitian tindakan kelas dengan teknik pengumpulan data menggunakan lembar observasi, tes hasil belajar, dan angket respons siswa. Pada penelitian ini telah dilaksanakan proses pembelajaran dengan menerapkan pendekatan realistik dan model pembelajaran kooperatif yang dilaksanakan sebanyak 2 (dua) siklus dengan masing-masing disajikan selama 4 kali tindakan dan 1 kali pemberian tes hasil belajar. Hasil penelitian ini menunjukkan bahwa penerapan pendekatan matematika realistik dapat meningkatkan pemahaman matematika siswa kelas VI SD Inpres Mallengkeri Bertingkat Kota Makassar dengan indikator sebagai berikut: (1) terjadi peningkatan rata-rata skor hasil belajar matematika yang dicapai 32 siswa dari sebelum pelaksanaan tindakan ke setelah pelaksanaan tindakan pada siklus I dan siklus II; (2) persentase siswa yang tuntas belajar sudah memenuhi target minimal ketuntasan klasikal 75% siswa mencapai KKM; (3) rata-rata aktivitas siswa pada setiap aspek yang diamati menunjukkan bahwa aktivitas siswa dikatakan memenuhi kriteria efektif; (3) aktivitas guru menunjukkan bahwa kemampuan guru mengelola pembelajarn sudah berada pada kategori “sangat tinggi”; (4) secara keseluruhan komponen yang direspons mendapat respons positif dari siswa dengan persentase di atas 70%. Kata kunci: Pemahaman Matematika, Pendekatan realistic
Mapping Interactions Between B2GPI and the Lipoprotein Receptors by Solution NMR Spectroscopy.

Abstract Antiphospholipid syndrome (APS) is an autoimmune disease characterized by venous or arterial thrombosis and recurrent pregnancy loss. Beta2 glycoprotein I (B2GPI) is the major target for these antibodies. Current evidence suggests that B2GPI acquires pathological properties leading to APS after association with antibodies. It was demonstrated that APS related antibodies induce activation of endothelial cells, monocytes and platelets, although the identity of a cell-surface receptors that transmit the antibody-induced signaling inside cells remain unclear. Biochemical studies have shown that the receptors of the low-density lipoprotein receptor (LDLR) family are all capable to bind B2GPI/antibody complexes. These receptors are abundantly expressed by many cell types. The ligand-binding activity of the lipoprotein receptors is confined primarily to structurally homologous LA modules, which are arranged in sequence to form a ligand-binding domain. We investigated at the atomic level the features of the ligand-binding LA modules required for interaction with B2GPI. We sought to determine whether the same residues that form the ligand-binding pocket on the LA modules in the crystal structure of a RAP/LA3-4 complex also recognize B2GPI. We demonstrated that the same residues that form the ligand-binding pocket on LA4 in the crystal structure of the RAP/LA3-4 complex comprise the contact site for B2GPI. The domain 5 from B2GPI (B2GPI-D5) was expressed and labeled for NMR studies. The residues of B2GPI-D5 that are perturbed when B2GPI-D5 was titrated with LA4 are located at the C-terminus of domain 5. Using NMR relaxation measurements, we determined that B2GPI-D5 binds LA4 with 1:1 stoichiometry. The estimated Kd of the B2GPI-D5/LA4 complex is about 30 uM. NMR experimental data was used to build a docking model of the complex.
Encountering Work: Intergenerational Informality, Child Labor, and Malnutrition in Urban Ecuador

This article examines the interconnections among informality, child labor, and child malnutrition in households at the bottom of the socioeconomic pyramid in urban Ecuador. Through qualitative interviews with 120 adult informal laborers, mostly street vendors, I elicited stories that not only revealed current labor conditions but also reflected upon whole lives engaged in informal work. Interviews uncovered lifelong structural conditions that perpetuate the social and economic inheritances of intergenerational work in the informal sector and intergenerational patterns of a broader, more inclusive form of child labor termed “encountering work.” Social, political, and economic factors related to informality and child labor maintain structural vulnerabilities that contribute to the emergence and exacerbation of syndemic health conditions, most notably through multiple forms of child malnutrition. The children of these 120 informal sector workers, especially those that encounter work in a variety of ways alongside their parents, demonstrate profound childhood nutritional failures that will likely impact them throughout their lives. The challenges related to intergenerational informality, child labor as encountering work, and child malnutrition can only be understood in the context of pervasive, intergenerational poverty. Encountering work is a survival strategy that allows families to subsist in an unequal society that can simultaneously perpetuate vulnerabilities and inequalities in health and opportunity.
Chew it over carefully

Temple cites that processed food has arguably helped us tackle hunger, cut waste and saved front-line troops from malnutrition. It helped free the 1950s housewife from the kitchen, provided more options for older people living independently and enabled space travel. We face big challenges in food security in an increasingly uncertain environment. We need to be capable of having rational conversations about the role processed food might have in helping us overcome these
The Genetics and Epigenetics of Life History and Reproduction: Fish

Abstract New methods in collecting genomic and epigenome data are allowing scientists new approaches to answer questions about the control of complex traits at the genome level. Fishes exhibit many complex phenotypes that are influenced by both the environment, genetics, as well as the interplay between these two factors (Genotype-by-Environment interactions). In the following article, I will detail how both genetic and epigenetic data have increased our understanding of three traits connected to life history development and reproduction in fishes: life history development in the salmonids, rapid adaptation to new environments in the Winter Skate, and the epigenetic control of sex-reversal in several species of fish. Although the majority of this article is dedicated to discussing the genetic and epigenetic basis of migration in salmonids, it is important to note that the development of these methods will allow similar datasets to be generated for many phenotypes connected to life history and reproduction in many species of fish.
Generalized Variance of Multivariate Omega Functions and Duality

The covariance of probabilistic variables and the geometry of cones in deterministic optimization traditionally belong in distinct domains of study. This paper aims to show a relationship between the generalized variance of multidimensional joint omega functions and the duality of certain linear programs. Omega distributions are ubiquitous, polymorphic, and multifunctional but have been overlooked, partly due to a lack of closed form. However, the covariance/correlation matrix of joint omega functions can be stated. The geometry that links distributional covariance and generalized variance to the volume of dual cones is an exquisitely simple one.
Exterior Intrusion Sensors

Intrusion detection systems consist of exterior and interior intrusion sensors, video alarm assessment, entry control, and alarm communication systems all working together. Exterior sensors are those used in an outdoor environment, and interior sensors are those used inside buildings. This chapter examines various aspects of exterior intrusion sensors, whose performance is described by three fundamental characteristics that include probability of detection, nuisance alarm rate, and vulnerability to defeat. It is important for the system designer to specify the detection criteria required or expected of a sensor or sensor system. This specification should be clear as to what will be detected, what actions are expected, and any other considerations such as weight or speed of movement. Nuisance alarm rate is a function of the number of nuisance alarms over a given time period. In an ideal sensor system, the nuisance alarm rate would be zero. It is found that passive sensors detect some type of energy that is emitted by the target of interest or detect the change of some natural field of energy caused by the target.
Seawater Dielectric Measurements at L-Band with Latest Improvements

Recently, the dielectric constant of seawater at L-band was determined by employing a resonant cavity technique. A dielectric model function has been developed based on the measurement data and the model function has been used for retrieving the ocean salinity. The results indicate that additional accuracy is still needed to resolve the bias correlated with sea surface temperature. This paper reports the improvements that have been made recently for the development of a more accurate seawater dielectric model function. The additional measurements for the open ocean will be addressed in the paper.
The Use of Stochastic Value Models to Create Technology Roadmaps

Since technology is rapidly advancing, systems engineers must now design for adaptability, such that the system can be updated with new components as they become available. Designing for adaptability typically requires analyzing and evaluating technologies at various stages of maturity to determine if they should be incorporated into the design. As such, technology roadmaps are a useful tool to identifying the change in a technology with time. Though traditional technology roadmaps are based on raw performance data, a technology roadmap based on value modeling would be more appropriate for system design. Value modeling is a technique used for evaluating different design decisions while focusing on the needs of the stakeholder. A qualitative model is built to determine what value measures are of concern to the stakeholder; a quantitative model is then built to convert raw performance data into a value score for evaluation. This process can be expanded to show the change in value score based on new technologies through the inclusion of uncertainty and the time domain. The SIPMath® Tool is Microsoft Excel provided a useful tool for building this model. A case study for different unmanned aerial vehicle batteries is presented to display this process.
Impact of incidental findings in preoperative CTA imaging for autologous breast reconstruction.

Abstract Background CT angiography (CTA) can be performed pre-operatively for perforator mapping in autologous breast reconstruction. The full impact of incidental CTA findings on breast reconstruction remains unclear. Methods CTAs were reviewed for all patients who underwent imaging prior to autologous breast reconstruction at Yale New Haven Hospital from 2013–2018. CTA findings and all resulting follow-up imaging, treatment, and change in management were catalogued. Our findings were compared to other published reports in the literature to better categorize the impact of CTA findings on patient care. Results Records from 341 patients were reviewed. One hundred fifty-four patients (45.2%) had incidental findings with 15.6% requiring further imaging or biopsy. Three patients (0.9%) underwent a change in management. One patient was diagnosed with metastatic disease prior to mastectomy. Another two patients required gynecologic procedures as a result of the CTA findings. Data was pooled with three other series in the literature for aggregate analysis of 959 operative planning CTAs. In total, incidental findings were present in 53.7% of patients. In the meta-analysis, 10.4% of patients required additional imaging or biopsy and 1.4% of screening CTAs impacted medical management. Conclusion Pre-operative autologous breast reconstruction planning reveals incidental findings in approximately half of all imaging studies. In an analysis of nearly 1000 CTAs, patient care was impacted in 1.4% of cases. If imaging is obtained for planning purposes, the reconstructive microsurgeon should carefully review the full imaging report given its potential impact on patient care.
Analysing Results from Research Using Traditional and Declarative Mapping Sentences

In this chapter I present brief details regarding the ways in which data that arises from the use of a mapping sentence in research is analysed. This is an important aspect of research that is often covered somewhat sparsely in the facet theory literature. I break the chapter into two parts. The first of these deals with the analysis of quantitative data that comes out of the use of a traditional mapping sentence in a research project. The second part of the chapter addresses how the declarative mapping sentence is employed in analysing narrative or other forms of qualitative information that comes from a project that has used a declarative mapping sentence in the design of its research. In my consideration of quantitative analyses, I present the statistical procedures that are employed (smallest space analysis and partial order scalogram analysis) and consider what each of these statistics is able to reveal in the data. Both of these approaches are graphical data analysis procedures, and I also address how the resultant graphical printouts are interpreted. Declarative mapping sentences are not analysed using statistical applications but rather are subject to a structured content analysis, and in this chapter, I offer suggestions regarding the use of such a technique.
Urban food–energy–water systems: past, current, and future research trajectories

With the majority of the world's population living in urban areas, cities now drive global flows of food, energy, and water, with unprecedented implications for the sustainability of the planet and its people. This focus issue presents research on the nexus between food, energy, and water (FEW), as it relates to urban areas, broadly conceived. The eight papers in this issue are interdisciplinary, multiscalar, and cross-sectoral as they consider the effects of FEW interactions on the health of cities, their inhabitants, and the distant peoples and places from resources originate. This editorial summarizes topical areas covered by the papers, which include: a review of existing research on urban FEW systems and promising approaches; urban agriculture and energy-water dynamics; conventional agriculture and FEW dynamics; and the energy 'foodprint' of the American diet. The editorial concludes by identifying four crucial areas for further research: 1) ecosystem services associated with urban agriculture; 2) resource recovery in the urban FEW nexus; 3) equity, social actors, and governance of the FEW nexus; and 4) the food-energy-water-health nexus.
Thermal History Characterization and Controlled Nucleation of Supercooled Gallium

Paraffin phase change materials are often used for thermal energy storage due to their high gravimetric latent heat values and low cost. However, they are not well suited for high heat transfer rat...
An aporia: calcinosis in juvenile dermatomyositis

As the hallmark sequelae of juvenile dermatomyositis (JDM), the calcinosis still bothers approximately one third of the patients, but it was considered a good prognostic sign.Today, however, it is universally acknow-ledged that the calcinosis is instead deemed a marker of the special state and inappropriate treatment for JDM.The treatment of based on disease process, including the biological agents and other immunomodulator, which have been not the radical therapy.However, it is a crucial to alleviate the calcinosis that controlling the long-term chronic inflammation for JDM. Key words: Juvenile dermatomyositis; Calcinosis; Mineral-associated proteins; Autoantibody; Chronic inflammation
Combination of Vancomycin or Daptomycin and Beta-lactam Antibiotics: A Meta-analysis.

Introduction: Observational and randomized controlled trials of the combination of vancomycin or daptomycin with a beta-lactam (BL) in patients with methicillin-resistant Staphylococcus aureus (MRSA) bacteremia have shown conflicting results on patient outcomes. Objectives: The primary purpose of this meta-analysis was to compare clinical failure with the combination of vancomycin or daptomycin with a BL versus vancomycin or daptomycin monotherapy in MRSA bacteremia or endocarditis. Methods: A systematic literature search of PubMed, Embase, CINAHL, and meeting proceedings was conducted from inception through February 11, 2020 to identify relevant studies. The primary outcome was clinical failure and secondary outcomes were mortality, nephrotoxicity, and bacteremia. The meta-analysis was preformed using Comprehensive Meta analysis® (Ver 3.0) with a random effects model. Outcomes were reported as odds ratios (OR) with corresponding 95% confidence intervals (CI). Results: Nine studies of 1,636 patients receiving vancomycin or daptomycin monotherapy versus the combination of vancomycin or daptomycin plus BL for MRSA bacteremia were included. Results showed combination therapy was associated with significantly lower clinical failure rates (OR 0.56 , 95% CI 0.39 - 0.79; I2 = 26.22%, p = 0.001). Improvement in clinical failure was driven by lower rates of bacteremia relapse and persistence. However, no difference was seen with mortality. Conclusion: Combination therapy with vancomycin or daptomycin plus BL for MRSA bacteremia showed lower clinical failure rates, however, no significant difference was seen in mortality.
The benefit of poor mixing: kinetics of coacervation

Complex coacervation has become a prominent area of research in the fields of food science, personal care, drug stabilization, and more. However, little has been reported on the kinetics of assembly of coacervation itself. Here, we describe a simple, low-cost way of looking at the kinetics of coacervation by creating poorly mixed samples. In particular, we examine how polymer chain length, the patterning and symmetry of charges on the oppositely charged polyelectrolytes, and the presence of salt and a zwitterionic buffer affect the kinetics of complex coacervation. Our results suggest an interesting relationship between the time for equilibration and the order of addition of polymers with asymmetric patterns of charge. Furthermore, we demonstrated that increasing polymer chain length resulted in a non-monotonic trend in the sample equilibration times as a result of opposing factors such as excluded volume and diffusion. We also observed differences in the rate of sample equilibration based on the presence of a neutral, zwitterionic buffer, as well as the presence and identity of added salt, consistent with previous reports of salt-specific effects on the rheology of complex coacervates. While not a replacement for more advanced characterization strategies, this turbidity-based method could serve as a screening tool to identify interesting and unique phenomena for further study.
Appliancizer: Transforming Web Pages into Electronic Gadgets

Making electronic gadgets that meet today's consumer standards has become a difficult task. Electronic gadgets are expected to have displays with visually appealing interfaces and, at the same time, be physically and screen-interactive, making the development process of these devices time-consuming and challenging. To address this problem, we have created Appliancizer, an online synthesis tool that can automatically generate sophisticated electronic devices from web pages. Appliancizer takes advantage of the similarities between software and physical interfaces to reduce development steps and allow the rapid development of electronic devices. By matching the interface of hardware components with the interface of graphical HTML elements found on web pages, our tool allows a designer to transform HTML elements from a digital to a tangible interface without changing the application source code. Finally, a modular design enables our tool to automatically combine the circuit design and low-level hardware code of selected hardware components into a complete design. Attendees can interact with our online tool and produce manufacturable PCBs from web pages.
Effects of prenatal synthetic cannabinoid exposure on the cerebellum of adolescent rat offspring

Cannabis is the most commonly used illicit drug worldwide. Recently, cannabis use among young pregnant women has greatly increased. However, prenatal cannabinoid exposure leads to long-lasting cognitive, motor, and behavioral deficits in the offspring and alterations in neural circuitry through various mechanisms. Although these effects have been studied in the hippocampus, the effects of prenatal cannabinoid exposure on the cerebellum are not well elucidated. The cerebellum plays an important role in balance and motor control, as well as cognitive functions such as attention, language, and procedural memories. The aim of this study was to investigate the effects of prenatal cannabinoid exposure on the cerebellum of adolescent offspring. Pregnant rats were treated with synthetic cannabinoid agonist WIN55,212-2, and the offspring were evaluated for various cerebellar markers of oxidative stress, mitochondrial function, and apoptosis. Additionally, signaling proteins associated with glutamate dependent synaptic plasticity were examined. Administration of WIN55,212-2 during pregnancy altered markers of oxidative stress by significantly reducing oxidative stress and nitrite content. Mitochondrial Complex I and Complex IV activities were also enhanced following prenatal cannabinoid exposure. With regard to apoptosis, pP38 levels were significantly increased, and proapoptotic factor caspase-3 activity, pERK, and pJNK levels were significantly decreased. CB1R and GluA1 levels remained unchanged; however, GluN2A was significantly reduced. There was a significant decrease in MAO activity although tyrosine hydroxylase activity was unaltered. Our study indicates that the effects of prenatal cannabinoid exposure on the cerebellum are unique compared to other brain regions by enhancing mitochondrial function and promoting neuronal survival. Further studies are required to evaluate the mechanisms by which prenatal cannabinoid exposure alters cerebellar processes and the impact of these alterations on behavior.
Metabolism and hepatotoxicity of pyrazinamide, an anti-tuberculosis drug.

Pyrazinamide (PZA) is an important component of a standard combination therapy against tuberculosis. However, PZA is hepatotoxic and the underlying mechanisms are poorly understood. Biotransformation of PZA in the liver was primarily suggested behind its hepatoxicity. This review summarizes the knowledge of the key enzymes involved in PZA metabolism and discusses their contributions to PZA hepatotoxicity. Significance Statement This review outlines the current understanding of PZA metabolism and hepatotoxicity. This work also highlights the gaps in this field, which can be used to guide the future studies on PZA-induced liver injury.
A Uniform Submersion Theorem

Given an n-dimensional, connected, analytic manifold M and analytic vector fields $$\{f_i\}_{i=0}^m$$ on M consider the affine control process 0.2 $$\begin{aligned} {\xi }' = f_0(\xi ) + \sum \limits _{i = 1}^mu_if_i(\xi )\,. \end{aligned}$$ Let $$t\rightarrow \xi _{x,\overline{u}}(t)$$ be the solution curve satisfying the above differential equation with initial condition $$\xi (0) = x$$ and $$\overline{u} = (u_1,u_2, \ldots ,u_m)\in W_T^m \equiv L^{\infty }([0,T],{\mathbb {R}}^m)$$ is a control function. For a fixed $$x\in M$$ and $$T>0$$ consider the evaluation map $$E^x : W_T^m \rightarrow M : E^x(\overline{u}) = \xi _{x,\overline{u}}(T)$$ . Given a compact, semi-analytic set $$K\subset M$$ , we prove that, (Theorem 1.6), if the system satisfies SAP (strong accessibility property), at each $$x\in K$$ , then the set of control functions $$\overline{u}\in C^{\infty }([0,T],{\mathbb {R}}^m)$$ at which the the map $$E^x$$ is a submersion, (uniformly as x varies over K), is dense in the set $$C^\infty ([0,T],{\mathbb {R}}^m)$$ of $$C^\infty $$ control functions with the $$C^\infty $$ topology. The proof of the uniform submersion theorem, uses a control theoretic notion of ‘detectability’ and is based on an important result, (Theorem 2.2), about existence and genericity of ‘universal detectors’.
Single Molecule Studies Reveal Regulatory Interactions between Master Kinases PDK1, AKT1 and PKCalpha

Leukocyte migration is controlled by a leading edge chemosensory pathway that generates the regulatory lipid PIP3, a growth signal, thereby driving leading edge expansion up attractant gradients toward sites of infection, inflammation, or tissue damage. PIP3 also serves as an important growth signal in growing cells and oncogenesis. The kinases PDK1, AKT1/PKB and PKC are key components of a plasma membrane-based PIP3 and Ca2+ signaling circuit that regulates these processes. PDK1 and AKT1 are recruited to the membrane by PIP3, while PKC is recruited to the membrane by Ca2+. All three of these master kinases phosphoregulate an array of protein targets. For example, PDK1 activates AKT1, PKC and other AGC kinases by phosphorylation at key sites. PDK1 is known to form PDK1:AKT1 and PDK1:PKC heterodimers stabilized by a PIF interaction between the PDK1 PIF pocket and the PIF motif of the AGC binding partner. Here we present the first, to our knowledge, single molecule studies of full length PDK1 and AKT1 on target membrane surfaces, as well as their interaction with full length PKC. The findings show that membrane-bound PDK1:AKT1 and PDK1:PKC heterodimers form under physiological conditions, and are stabilized by PIF interaction. PKC exhibits 8-fold higher PDK1 affinity than AKT1, thus PKC competitively displaces AKT1 from PDK1:AKT1 heterodimers. Ensemble activity measurements under matched conditions reveal that PDK1 activates AKT1 via a cis mechanism by phosphorylating an AKT1 molecule in the same PDK1:AKT1 heterodimer, while PKC acts as a competitive inhibitor of this phosphoactivation reaction by displacing AKT1 from PDK1. Overall, the findings provide new insights into molecular and regulatory interactions of the three master kinases on their target membrane, and suggest that the recently described tumor suppressor activity of PKC may arise from its ability to downregulate PDK1-AKT1 phosphoactivation in the PIP3-PDK1-AKT1-mTOR pathway linked to cell growth and oncogenesis. STATEMENT OF SIGNIFICANCEThis work investigates three master kinases that play central roles in guiding white blood cell migration to sites of infection, inflammation or tissue damage. More broadly, the same kinases help regulate production of a cell growth signal, and may trigger cancer when dysregulated. Using powerful single molecule methods, the work detects and analyzes the interactions between the three purified kinases on their target membrane surface. The findings reveal functionally important differences between pairwise binding affinities of different binding partners. Additional studies reveal that the highest affinity kinase can disrupt and inhibit the activated complex formed by association of the other two kinases. Such inhibition is proposed to help prevent cancer by limiting growth signal production by the activated complex.