cssi/SciSciGPT-SciSciNet huggingface dataset:
Leveraging multi-modal smartphone sensors for ranging and estimating the intensity of explosion events

Abstract Our society, unfortunately, is increasingly becoming exposed to explosion events that could have serious consequences. While explosion events like intentionally triggered bombs cause obvious harm to life and property, other explosions intended for benign purposes in quarries and construction zones may also cause unintended harm as a result of emanating seismic vibrations. As of today, detecting explosions, ranging them, and estimating their intensities are all accomplished only by seismometers that sense the associated ground vibrations and pressure changes as a result of their triggering. Unfortunately, seismometers are bulky, expensive and unsuitable for the ubiquitous use. In this paper, our broad motivation is to demonstrate the feasibility of leveraging the pervasive sensing and processing capabilities of modern smartphones to analyze explosion events. Within this context, we specifically address the problem of ranging and estimating the intensity of an explosion by leveraging the accelerometer and pressure sensors in the smartphone. To do so, we emplaced a number of smartphones in the vicinity of real explosion blasts conducted at a university mining laboratory, where the material blasted was Dynamite with Ammonium Nitrate Fuel Oil (ANFO). We then collected the corresponding accelerometer and pressure readings sensed by the phone. We extracted a number of novel features, and designed a machine learning based algorithmic framework for ranging and estimating the intensity of the explosion event. After an extensive validation, we find that the average-case error in ranging (i.e., estimating the distance to the source of the explosion event) and estimating the intensity of explosive material (in terms of its charge weight) are 8.24% and 7.37%, respectively. We also present perspectives on encoding our algorithm as a smartphone app, identify several critical challenges that will be encountered in real-time data processing of smartphone accelerometers and pressure sensors in the context of pervasive sensing of explosions, and also identify other practical issues like the diversity of smartphones. To the best of our knowledge, our work is pioneering in demonstrating the feasibility of using smartphones to analyze explosion events. We believe there are significant societal benefits emanating from our work.
Molecular Imaging of Diffuse Low Grade Glioma

Beyond defining tumor extent and anatomic location, recent advances in MRI and PET allow for the non-invasive physiologic, metabolic and molecular imaging of diffuse low-grade glioma. How this information can be best combined with detailed molecular characterization of tumors, in order to produce applicable markers of prognosis and response to therapy, remains to be determined. The impact on imaging of molecular features of gliomas including 1p/19q loss of heterozygosity (LOH) and the IDH1 and IDH2 mutations is discussed. Newer MR sequences and data mining techniques including diffusion and perfusion MRI and textural analysis may better stratify tumor prognosis and grade. Additionally, measurement of the oncometabolite 2-HG with MR spectroscopy appears clinically feasible, although the relationship to outcomes is yet to be determined. Lastly PET with amino acid tracers including C11-MET, FET and FDOPA provide additional avenues of tumor characterization that are unfettered by the high background uptake of FDG. The future may be characterized by gains in predictive, rather than merely prognostic markers, that could help optimize patient outcomes. As more targeted therapies become available, it will also be critical to develop early response indicators that are acquired prior to change in tumor size. To date, many imaging biomarkers lack the rigorous validation necessary for clinical decision-making, but ongoing efforts could yield such data in the near future. As more is understood about the relationship between imaging and underlying molecular features of disease, we can continue to refine treatment strategies in a manner more precisely tailored to individual patients.
Congenital Spinal Anomalies

Congenital spinal anomalies can occur spontaneously, due to maternal exposures or genetic variances. They are often associated with systemic abnormalities with underlying syndromes. Scoliosis can occur due to failure of formation, failure of segmentation, or a combination with rapid progression. Treatment options include observation with bracing, spinal fusion with or without correction, vertebrectomy, or growing rod constructs. Complications include crankshaft phenomenon, neurologic injury (especially with kyphotic deformity), soft tissue injury, or short stature.
Using an opportunity-propensity framework to estimate individual-, classroom-, and school-level predictors of middle school science achievement

Abstract Using data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998–99 (N = 4447), this analysis employs an opportunity-propensity (O-P) framework (Byrnes, 2003; Byrnes & Miller, 2007; Byrnes & Wasik 2009) to examine the influence of multiple student, teacher, classroom, and school factors on eighth-grade science achievement. Sackes, Trundle, Bell, and O’Connell (2011) fit an O-P structural equation model (SEM) to the same database to explain science achievement growth from Kindergarten to third grade. We extend this work by fitting an O-P SEM to this database to predict science achievement growth from fifth to eighth grade. This middle school model includes an opportunity variable – science curriculum track placement – that operates only in middle and high school. This variable and the school’s poverty rate are significant predictors of several opportunity factors. We replicate previous findings that propensity factors are the strongest determinants of science achievement, notably prior achievement. However, we find more opportunity factors than previous studies that are also significant. Other things being equal, having a state-certified teacher is the second strongest predictor of achievement within the model. Placement in a science honors course and being enrolled in a low income school are also linked to small but significant impacts on science achievement.
Perceived Discrimination as a Risk Factor for Use of Emerging Tobacco Products: More Similarities Than Differences Across Demographic Groups and Attributions for Discrimination.

Background: Perceived discrimination has been associated with cigarette smoking and other substance use among members of disadvantaged minority groups. However, most studies have focused on a singl...
Biological Microelectromechanical Systems (BioMEMS) Devices

This chapter highlights the use of biological microelectromechanical systems (BioMEMS) to better understand the physical and chemical interactions that cells have with their surroundings. These tools have provided significant insights into the cues from a cell's microenvironment and how they affect cell function. This information is useful in the design and development of new biomaterials and tissue-engineered constructs. BioMEMS devices and techniques are tools that are well-suited for a researcher to examine cell cytoskeleton and traction forces. Additionally, many of the tools presented can also be used to transmit forces to the cell in examining biochemical or biomechanical response. Measurement tools include membrane wrinkling, traction force microscopy, elastomer micropost arrays, extracellular matrix patterning. Micromanipulation techniques include traction force microscopy, magnetic twisting cytometry, optical traps and stretchers, and traditional MEMs fabricated tools. This chapter also covers microfluidic systems to exert physiologically relevant forces such as hemodynamic or interstitial shear forces to better match cell environments in living tissue. Increasingly, researchers have discovered that mechanical forces influence cell behavior in profound ways, and a better understanding through BioMEMS devices is important for future technology and therapy development.
Characterization of Load Sensitive Fatigue Crack Initiation in Ti-Alloys Using Crystal Plasticity Based FE Simulations

Fatigue life in near \(\alpha \) Ti-alloys shows large variation with characteristics of applied load and is due to the microstructurally dependent deformation behavior in these alloys. In the present work, the load sensitive fatigue crack nucleation behavior is investigated using a physically motivated crack initiation law and cyclic crystal plasticity based finite element (CPFE) simulations of statistically equivalent image based microstructures. Since cyclic CPFE simulation for large number of cycles using conventional time integration schemes is computationally prohibitive, a wavelet transformation based multi-time scale (WATMUS) method developed in [1, 2] is used in the present work to perform accelerated simulations. To predict cycles to nucleation, a physically motivated crack nucleation model based on crystal plasticity variables developed in [3] has been used in this work. The nucleation model is calibrated and validated with experiments. The sensitivity of crack nucleation to the characteristics of the applied load is studied by performing WATMUS method based CPFE simulations for different cyclic load profiles on a statistically equivalent microstructure.
Improving system efficiency for a variable-capacity/variable-blower-speed residential heat-pump system with multizone ductwork

This article describes efficiency improvements resulting from incorporating zonal airflow control into a variable-capacity/variable-fan-speed residential air-conditioning system. The results descri...
The Impact of Culture in Multicultural Teams

Japan is widely recognized for its success as an economic power. Despite some of the challenges in the last few years, it remains one of the world’s largest economies. The chances are that most of us have used, seen, and heard of Japanese brands ranging from automobiles to consumer electronics. Lesser known to the outside world but equally impressive is Japan’s highly service-oriented society domestically. This national and global success has been intriguing the rest of the world. The last 20 years have seen the adapting of Japanese management and organizational practices in small manufacturing plants in Asia to the assembly lines of American automobile giants such as General Motors. Many observers directly attribute Japan’s success to Japanese cultural values and the emphasis on teamwork. At the same time, Japanese organizations have been open to adapting and embracing some Westernstyle managerial practices. A major consequence of these developments is that in many of these international settings multicultural teams are attempting to work effectively where Japanese and other cultures may be significantly impacting the teamwork. Cultural values can deeply affect organizational and team structure, rewards and motivation, interpersonal interactions, decision making, and effectiveness. Chapter 1 highlighted some of the broad ways in which culture impacts and manifests the working of teams at organizational, team, and individual levels. When an organization consists of individuals with the same value orientations, policies and procedures follow naturally and smoothly, and expectations are mutually understood. When an organization consists of individuals with different value orientations, three
Usage of scientific references in MMR vaccination debates on twitter

This research analyzes scientific information sharing behaviors on Twitter. Over an eleven-month period, we collected tweets related to the controversy over the supposed linkage between the MMR vaccine and autism. We examined the usage pattern of scientific information resources by both sides of the ongoing debate. Then, we explored how each side uses scientific evidence in the vaccine debate. To achieve this goal, we analyzed the usage of scientific and non-scientific URLs by both polarized opinions. A domain network, which connects domains shared by the same user, was generated based on the URLs "tweeted" by users engaging in the debate in order to understand the nature of different domains and how they relate to each other. Our results showed that people with anti-vaccine attitudes linked many times to the same URL while people with pro-vaccine attitudes linked to fewer overall sources but from a wider range of resources, and that they provided fewer total links compared to people with anti-vaccine attitudes. Moreover, our results showed that vocal journalists have a huge impact on users' opinions. This study has the potential to improve understanding about how health information is disseminated via social media by showing how scientific evidence is referenced in discussions about controversial health issues. Monitoring scientific evidence usage on social media can reveal concerns and misconceptions related to the usage of these types of evidence.
Type-guided worst-case input generation

This paper presents a novel technique for type-guided worst-case input generation for functional programs. The technique builds on automatic amortized resource analysis (AARA), a type-based technique for deriving symbolic bounds on the resource usage of functions. Worst-case input generation is performed by an algorithm that takes as input a function, its resource-annotated type derivation in AARA, and a skeleton that describes the shape and size of the input that is to be generated. If successful, the algorithm fills in integers, booleans, and data structures to produce a value of the shape given by the skeleton. The soundness theorem states that the generated value exhibits the highest cost among all arguments of the functions that have the shape of the skeleton. This cost corresponds exactly to the worst-case bound that is established by the type derivation. In this way, a successful completion of the algorithm proves that the bound is tight for inputs of the given shape. Correspondingly, a relative completeness theorem is proved to show that the algorithm succeeds if and only if the derived worst-case bound is tight. The theorem is relative because it depends on a decision procedure for constraint solving. The technical development is presented for a simple first-order language with linear resource bounds. However, the technique scales to and has been implemented for Resource Aware ML, an implementation of AARA for a fragment of OCaml with higher-order functions, user-defined data types, and types for polynomial bounds. Experiments demonstrate that the technique works effectively and can derive worst-case inputs with hundreds of integers for sorting algorithms, operations on search trees, and insertions into hash tables.
Manufacturing competitiveness analysis for hydrogen refueling stations

Abstract Fuel cell electric vehicles (FCEVs) have now entered the market as zero-emission vehicles. Original equipment manufacturers such as Toyota, Honda, and Hyundai have released commercial cars in parallel with efforts focusing on the development of hydrogen refueling infrastructure to support new FCEV fleets. Persistent challenges for FCEVs include high initial vehicle cost and the availability of hydrogen stations to support FCEV fleets. This study sheds light on the factors that drive manufacturing competitiveness of the principal systems in hydrogen refueling stations, including compressors, storage tanks, precoolers, and dispensers. To explore major cost drivers and investigate possible cost reduction areas, bottom-up manufacturing cost models were developed for these systems. Results from these manufacturing cost models show there is substantial room for cost reductions through economies of scale, as fixed costs can be spread over more units. Results also show that purchasing larger quantities of commodity and purchased parts can drive significant cost reductions. Intuitively, these cost reductions will be reflected in lower hydrogen fuel prices. A simple cost analysis shows there is some room for cost reduction in the manufacturing cost of the hydrogen refueling station systems, which could reach 35% or more when achieving production rates of more than 100 units per year. We estimated the potential cost reduction in hydrogen compression, storage and dispensing as a result of capital cost reduction to reach 5% or more when hydrogen refueling station systems are produced at scale.
Parental environments alter DNA methylation in offspring of the purple sea urchin, Strongylocentrotus purpuratus

Abstract Phenotypic plasticity , within and across generations, is a strategy by which organisms can respond rapidly to environmental change. Epigenetic modifications, such as DNA methylation , have been proposed to be involved in phenotypic plasticity. We examined the potential for the environment to mediate both transgenerational and intragenerational plasticity in DNA methylation and phenotypes in early stages of the purple sea urchin , Strongylocentrotus purpuratus , an ecologically important herbivore in kelp forest ecosystems. This approach involved a controlled laboratory experiment where adult urchins were acclimated during gametogenesis to upwelling (~1300 μatm pCO2 & 13 °C) or non-upwelling (~650 μatm pCO2 & 17 °C) conditions that are representative of their kelp forest habitat. Progeny from these adults were raised in either high (~1050 μatm) or low (~450 μatm) pCO2 treatments and sampled at three developmental stages. Differences in condition experienced by mothers were associated with differentially methylated genes in the offspring. However, differences in developmental conditions corresponded to little observable effects on gene methylation in the progeny. Variation in gene body methylation across treatments was correlated with body size of the embryos and larvae, illustrating a potential link between transgenerational phenotypic plasticity and DNA methylation. Overall, our results suggest that epigenetic factors such as DNA methylation have the potential to contribute to phenotypic plasticity in a transgenerational framework, and further, that epigenetic processes may act as a mechanism of rapid response to environmental change.
Deep Learning for the Design of Computational Microscopes

We use deep learning to optimize the end-to-end design of computational microscopes, jointly designing the hardware for data collection and processing software for object reconstruction. With this framework, we optimize the illumination pattern for high space-bandwidth product imaging and 3-dimensional imaging.
Alternative spin on phylogenetically inherited spatial reference frames.

Abstract People make use of different frames of reference (north-south; left-right) to talk about space. To explore the cognitive capacity that children bring to learning spatial language, Haun, Rapold, Call, Janzen, and Levinson (2006) examined children’s ability to notice and abstract invariant frames of references across instances. They found that 4-year-olds and non-human great apes often noticed environment-defined allocentric relations and not body-defined egocentric ones, leading them to conclude that preschoolers are ready to learn environment-defined terms (e.g. “uphill”), but not body-defined ones (e.g., “left”). However, such a conclusion may be premature. In four new experiments we demonstrate that the previous findings could be an artifact of specific task constraints. With minor experiment modifications, similar-aged children readily noticed egocentric relations. Reviewing additional research, we provide an account of what makes acquiring frames of reference easy or difficult, and why full mastery of terms like “left” and “right” may take many years under normal circumstances.
A Modified Sodium Metabisulfite Method to Distinguish Sickle Cell Disease from Sickle Cell Trait for Use in Underdeveloped Countries

The objective of this study was to develop a simple, inexpensive, and rapid confirmatory test using a sodium metabisulfite microscopic method to distinguish AS from SS genotype in patients testing positive for hemoglobin S. Equal volumes of de-identified EDTA blood and 2% sodium metabisulfite were mixed, placed on a microscope slide with coverslip, and observed for sickling at 30-minute intervals over 3 hours. Sickle cells were enumerated/200 RBCs under 100x oil immersion and placed into 4 Likert categories (1+-4+) based on degree of sickling. In AS samples, 2+ and 3+ sickle cells rose most rapidly while 4+ sickle cells showed the steepest rise in the SS samples. Based on these data the number of 4+ sickle cells were counted every 30-minutes over 3 hours in 5 AS and 28 SS samples at 37 degrees Celsius. Mean number of 4+ sickle cells in AS samples were 4.75/200 at 2 hours and 17.75/200 at 3 hours whereas SS samples yielded 78.29/200 at 2 hours and 115.43/200 at 3 hours. Two-hour incubation showed a statistical difference (P=0.00024) between groups in the shortest time and may be used to distinguish SS from AS genotypes. More testing is needed to determine cutpoints to distinguish genotype.
Skeletal Muscle Tissue Engineering: Biomaterials-Based Strategies for the Treatment of Volumetric Muscle Loss.

Millions of Americans suffer from skeletal muscle injuries annually that can result in volumetric muscle loss (VML), where extensive musculoskeletal damage and tissue loss result in permanent functional deficits. In the case of small-scale injury skeletal muscle is capable of endogenous regeneration through activation of resident satellite cells (SCs). However, this is greatly reduced in VML injuries, which remove native biophysical and biochemical signaling cues and hinder the damaged tissue’s ability to direct regeneration. The current clinical treatment for VML is autologous tissue transfer, but graft failure and scar tissue formation leave patients with limited functional recovery. Tissue engineering of instructive biomaterial scaffolds offers a promising approach for treating VML injuries. Herein, we review the strategic engineering of biophysical and biochemical cues in current scaffold designs that aid in restoring function to these preclinical VML injuries. We also discuss the successes and limitations of the three main biomaterial-based strategies to treat VML injuries: acellular scaffolds, cell-delivery scaffolds, and in vitro tissue engineered constructs. Finally, we examine several innovative approaches to enhancing the design of the next generation of engineered scaffolds to improve the functional regeneration of skeletal muscle following VML injuries.
Enough Sight to Fight? The history of military visual system requirements

Abstract Medicine has a six-fold role to play in war, 1) selection of suitable military personnel, 2) to protect against disease, 3) to give medical attention and treatment to those who are ill and injured, 4) to assist in the rehabilitation of the disabled, 5) research to improve etiology and treatments of disease, and 6) the unit surgeon serves as a special staff officer to the military commander at all levels of a battalion and above, along with the attorney and chaplain, and supplies medical input into all plans whether it be training or combat operations. This article focuses on the realization by soldiers, since antiquity, the importance of the visual system in battle, how this was measured, and how modern military visual requirements have evolved along with the science of ophthalmology. Necessity and natural selection were the driving forces for recruitment and assignment in ancient and medieval armies. Since the advent of mechanized warfare, more soldiers can perform more tasks, more uniformly, radically changing the way soldiers are selected. Modern military duty eligibility requirements and assignments are now the result of special tests and documentation procedures resulting from a mixture of medical knowledge, science, and potential legal consequences. Nowhere is this more evident in the stringent visual system requirements for military service.
COVID-19 and Its Impacts on Managing Information Systems

Organizations have encountered risks of all types dealing with information systems (IS) and information technology (IT). However, managing risks in the COVID-19 environment is not something organiz...
Characteristics of Medical School Applicants: A Single-Institution Study.

Background and objectives Medical schools aim to admit talented learners who are honest, patient centered, and caring, in addition to possessing the required cognitive skills. The Association of American Medical Colleges (AAMC) describes core competencies for entering medical students in three categories: science, preprofessional, and thinking and reasoning. The authors sought to determine desired characteristics of medical school applicants at a rural, community-based medical school in light of the published core competencies. Methods This qualitative study involved an analysis of data from discussion groups, all from a convenience sample of participants. The authors led the discussion groups, and large sticky note pads and pens were provided to scribe responses. Group members were given the prompt, "What do you see as traits or characteristics of your ideal doctor?" We used a content analysis approach to analyze the data. Results The total number of responses across groups was 243, representing 15 unique characteristics. The 15 characteristics, listed in decreasing order of frequency, included good communicator, knowledgeable, dedicated, compassionate, respectful, community oriented, well rounded, patient, team player, available, leader, positive attitude, equal treatment, prevention focused, and urgency when needed for patient care. Of the top characteristics with 20 or more responses, alignment with AAMC competencies was noted, but less so with being community oriented as defined by study participants. Conclusions This study demonstrates that there are unique characteristics that a rural community and its medical school consider when admitting applicants to their medical program. Further research is needed to explore the need for additional competencies for rural medical schools to consider for entering medical students.
A cluster randomized stepped-wedge trial to de-implement unnecessary post-operative antibiotics in children: the optimizing perioperative antibiotic in children (OPerAtiC) trial

Antibiotic-resistant infections have become a public health crisis that is driven by the inappropriate use of antibiotics. In the USA, antibiotic stewardship programs (ASP) have been established and are required by regulatory agencies to help combat the problem of antibiotic resistance. Post-operative antibiotic use in surgical cases deemed low-risk for infection is an area with significant overuse of antibiotics in children. Consensus among leading public health organizations has led to guidelines eliminating post-operative antibiotics in low-risk surgeries. However, the best strategies to de-implement these inappropriate antibiotics in this setting are unknown. A 3-year stepped wedge cluster randomized trial will be conducted at nine US Children’s Hospitals to assess the impact of two de-implementation strategies, order set change and facilitation training, on inappropriate post-operative antibiotic prescribing in low risk (i.e., clean and clean-contaminated) surgical cases. The facilitation training will amplify order set changes and will involve a 2-day workshop with antibiotic stewardship teams. This training will be led by an implementation scientist expert (VRM) and a pediatric infectious diseases physician with antibiotic stewardship expertise (JGN). The primary clinical outcome will be the percentage of surgical cases receiving unnecessary post-operative antibiotics. Secondary clinical outcomes will include the rate of surgical site infections and the rate of Clostridioides difficile infections, a common negative consequence of antibiotic use. Monthly semi-structured interviews at each hospital will assess the implementation process of the two strategies. The primary implementation outcome is penetration, which will be defined as the number of order sets changed or developed by each hospital during the study. Additional implementation outcomes will include the ASP team members’ assessment of the acceptability, appropriateness, and feasibility of each strategy while they are being implemented. This study will provide important information on the impact of two potential strategies to de-implement unnecessary post-operative antibiotic use in children while assessing important clinical outcomes. As more unnecessary medical practices are identified, de-implementation strategies, including facilitation, need to be rigorously evaluated. Along with this study, other rigorously designed studies evaluating additional strategies are needed to further advance the burgeoning field of de-implementation. NCT04366440. Registered April 28, 2020, https://clinicaltrials.gov/ct2/show/NCT04366440 .
Variable subject pronoun expression revisited: This is what the Paisas do

We explore subject pronoun expression (SPE) in Medellin, Colombia using 4,623 tokens to test eight predictors. The 28% overall pronominal rate found is significantly higher than those in other mainland communities. Grammatical person exerts the greatest conditioning effect, with uno ‘one’ strongly favoring overt subjects. Findings for verb class reveal that speech and cognitive verbs promote overt subjects. However, our in-depth analysis unveils opposing tendencies between different pronominal subject + verb collocations for the same verb. E.g., whereas (yo) soy ‘I am’ strongly favors overt subjects, (ellos) son ‘they are’ favors null subjects. These findings suggest that analyses focusing on infinitives do not constitute the most accurate way to explore verb effects on SPE. Moreover, the effect of age reveals a low pronominal rate among the youngest speakers, a finding that appears to have cognitive and acquisitional implications, as younger speakers would be expected to have higher pronominal rates. In general, this study contributes to expand our knowledge of SPE. Further, the findings regarding age and the lexical effect of the verb open promising research paths.
VEHiCLE: a Variationally Encoded Hi-C Loss Enhancement algorithm for improving and generating Hi-C data

Chromatin conformation plays an important role in a variety of genomic processes. Hi-C is one of the most popular assays for inspecting chromatin conformation. However, the utility of Hi-C contact maps is bottlenecked by resolution. Here we present VEHiCLE, a deep learning algorithm for resolution enhancement of Hi-C contact data. VEHiCLE utilises a variational autoencoder and adversarial training strategy equipped with four loss functions (adversarial loss, variational loss, chromosome topology-inspired insulation loss, and mean square error loss) to enhance contact maps, making them more viable for downstream analysis. VEHiCLE expands previous efforts at Hi-C super resolution by providing novel insight into the biologically meaningful and human interpretable feature extraction. Using a deep variational autoencoder, VEHiCLE provides a user tunable, full generative model for generating synthetic Hi-C data while also providing state-of-the-art results in enhancement of Hi-C data across multiple metrics.
Influence of estradiol on bovine trophectoderm and uterine gene transcripts around maternal recognition of pregnancy.

Embryo survival and pregnancy success is increased among animals that exhibit estrus prior to fixed time-artificial insemination, but there are no differences in conceptus survival to d16. The objective of this study was to determine effects of preovulatory estradiol on uterine transcriptomes, select trophectoderm (TE) transcripts, and uterine luminal fluid proteins. Beef cows/heifers were synchronized, artificially inseminated (d0), and grouped into either high (highE2) or low (lowE2) preovulatory estradiol. Uteri were flushed (d16); conceptuses and endometrial biopsies (n = 29) were collected. RNA sequencing was performed on endometrium. Real-time polymerase chain reaction (RT-PCR) was performed on TE (n = 21) RNA to measure relative abundance of IFNT, PTGS2, TM4SF1, C3, FGFR2, and GAPDH. Uterine fluid was analyzed using 2D Liquid Chromatography with tandem mass spectrometry-based Isobaric tags for relative and absolute quantitation (iTRAQ) method. RT-PCR data were analyzed using the MIXED procedure in SAS. There were no differences in messenger RNA (mRNA) abundances in TE, but there were 432 differentially expressed genes (253 downregulated, 179 upregulated) in highE2/conceptus versus lowE2/conceptus groups. There were also 48 differentially expressed proteins (19 upregulated, 29 downregulated); 6 of these were differentially expressed (FDR < 0.10) at the mRNA level. Similar pathways for mRNA and proteins included: calcium signaling, protein kinase A signaling, and corticotropin-releasing hormone signaling. These differences in uterine function may be preparing the conceptus for improved likelihood of survival after d16 among highE2 animals. Summary sentence Preovulatory estradiol did not impact conceptus survival to d16; however, it did influence uterine gene/protein expressions related to adhesion, endometrial remodeling, metabolism, and immune regulation, which may explain improved pregnancy success.
Evaluation of Low-Pressure-Sintered Multi-Layer Substrates for Medium-Voltage SiC Power Modules

Direct-bonded aluminum (DBA) multi-layer substrates have been fabricated using low-pressure silver sintering. These multi-layer substrates can be used to reduce the peak electric field strength inside power modules. This benefit is particularly important for medium-voltage silicon carbide (SiC) MOSFETs due to their higher operating voltages. The voiding content and defect density of the bond used to create the multi-layer substrate stack-up is critical to the thermal performance and reliability of the power module. This work evaluated two low-pressure-assisted sintering techniques; one using nano-silver preform and the other using nano-silver paste to bond 23 mm by 49 mm DBA substrates. C-mode Scanning Acoustic Microscopy (C-SAM) was used to evaluate the bond quality after sintering. To evaluate the reliability of the sintered multi-layer substrates, passive thermal cycling from –40 °C to 200 °C was performed. Cross-sections were cut at pre-determined intervals and imaged with Scanning Electron Microscopy (SEM). After 1,000 thermal cycles, minor cracking was observed, but no failures have occurred.
Advancing measurement infrastructure for cell and gene therapy product development

Abstract Analytical methods are critical in the characterization and testing of cell and gene therapy products. Analytical method development occurs in parallel to product development and is refined as knowledge is accumulated during the development program. Validated analytical methods are generally required for product licensure, and steps should be taken to build towards analytical method validation as product development progresses towards release. Here we consider approaches for streamlining analytical method development via well-coordinated product and analytical method development efforts. We further discuss the importance of establishing a robust measurement infrastructure, including key aspects, such as measurement assurance strategies, measurement platforms with well-understood capabilities and limitations, standards to support rapid validation of a given measurement platform, as well as enabling tools and technologies to streamline and integrate various processes and data.
Cardiopulmonary function and intestinal blood flow in anaesthetised, experimentally endotoxaemic horses given a constant rate infusion of dexmedetomidine

BACKGROUND Endotoxaemia causes untoward inflammatory-mediated effects that might be attenuated by dexmedetomidine. OBJECTIVES To evaluate the effects of a dexmedetomidine intravenous (IV) infusion on systemic and intestinal haemodynamics and arterial blood gas values in sevoflurane-anaesthetised horses administered Escherichia coli O55:B5 lipopolysaccharides (LPS). STUDY DESIGN Randomised controlled in vivo experiment. METHODS A total of 13 horses weighing 456 ± 86 kg (mean ± standard deviation) and aged 13.9 ± 9.0 years donated for euthanasia underwent ventral midline celiotomy using sevoflurane anaesthesia. Baseline physiological variables were recorded after a 90-minute equilibration period. All horses were given 0.1 mcg/kg bwt LPS IV. Horses were randomly assigned to no further treatment (group LPS; seven horses) or IV administration of dexmedetomidine (loading dose 1.75 mcg/kg bwt followed by 1.75 mcg/kg bwt/h; group LPS-Dex; six horses) with concurrent target sevoflurane dose reduction of 50%. Cardiac index (CI; thermodilution), intestinal blood flow, arterial blood parameters and plasma dexmedetomidine concentration measurements were recorded every 30 minutes until euthanasia at 390 minutes. Data were compared between and within groups to baseline using a mixed model analysis (significance P < .05). RESULTS In LPS-Dex horses, intestinal blood flow and CI were transiently decreased after the dexmedetomidine loading dose, but no significant differences were found compared with baseline during the infusion. Sevoflurane dose was reliably reduced by approximately 40%. Significant differences were identified in creatinine (115 umol/L LPS-Dex; 195 umol/L LPS), bicarbonate (29.7 mmol/L LPS-Dex; 23 mmol/L LPS) and base excess (2.0 mmol/L LPS-Dex; -5.3 mmol/L LPS). Dexmedetomidine plasma concentrations were highest after the loading dose and stable during infusion dosing. MAIN LIMITATIONS Experimental conditions are not reflective of clinical colic management. CONCLUSIONS A dexmedetomidine infusion with sevoflurane dose reduction attenuated some deleterious changes in anaesthetised horses administered LPS without sustained negative cardiovascular effects and may be beneficial during colic surgery.
Crystal Diffusion Variational Autoencoder for Periodic Material Generation

Generating the periodic structure of stable materials is a long-standing challenge for the material design community. This task is difficult because stable materials only exist in a low-dimensional subspace of all possible periodic arrangements of atoms: 1) the coordinates must lie in the local energy minimum defined by quantum mechanics, and 2) global stability also requires the structure to follow the complex, yet specific bonding preferences between different atom types. Existing methods fail to incorporate these factors and often lack proper invariances. We propose a Crystal Diffusion Variational Autoencoder (CDVAE) that captures the physical inductive bias of material stability. By learning from the data distribution of stable materials, the decoder generates materials in a diffusion process that moves atomic coordinates towards a lower energy state and updates atom types to satisfy bonding preferences between neighbors. Our model also explicitly encodes interactions across periodic boundaries and respects permutation, translation, rotation, and periodic invariances. We significantly outperform past methods in three tasks: 1) reconstructing the input structure, 2) generating valid, diverse, and realistic materials, and 3) generating materials that optimize a specific property. We also provide several standard datasets and evaluation metrics for the broader machine learning community.
Towards dynamic multi-modal phenotyping using chest radiographs and physiological data.

The healthcare domain is characterized by heterogeneous data modalities, such as imaging and physiological data. In practice, the variety of medical data assists clinicians in decision-making. However, most of the current state-of-the-art deep learning models solely rely upon carefully curated data of a single modality. In this paper, we propose a dynamic training approach to learn modality-specific data representations and to integrate auxiliary features, instead of solely relying on a single modality. Our preliminary experiments results for a patient phenotyping task using physiological data in MIMIC-IV & chest radiographs in the MIMIC- CXR dataset show that our proposed approach achieves the highest area under the receiver operating characteristic curve (AUROC) (0.764 AUROC) compared to the performance of the benchmark method in previous work, which only used physiological data (0.740 AUROC). For a set of five recurring or chronic diseases with periodic acute episodes, including cardiac dysrhythmia, conduction disorders, and congestive heart failure, the AUROC improves from 0.747 to 0.798. This illustrates the benefit of leveraging the chest imaging modality in the phenotyping task and highlights the potential of multi-modal learning in medical applications.
Determinants of the Timing of Social Policy Adoption

L'A. examine les conditions de la mise en place de politiques sociales dans les pays europeens a partir de la fin du 19 e siecle. Ils se demandent en quoi l'organisation de l'Etat, l'industrialisation, le developpement politique, les capacites de negociations de la classe ouvriere ont pu jouer un role en ce domaine. Ils presentent un certain nombre de donnees collectees en Europe entre 1871 et 1976. Ils analysent a quels moments des politiques sociales ont ete elaborees dans les differents pays du vieux continent
The Impact of Interviewees’ Demographics on Interviewers’ Perceptions of their Task Performance1

Age, sex, race, education and income are examined as possible determinants of interviewers’ perceptions of interviewees’ task performance. Race, education and income are found to have significant effects on the perceptions of white interviewers.
A Breeding Ground for Revenue Reliability? Cameroonian Veterinary Agents and Tax Officials in the Face of Reform

This chapter explores how reforms affect public administrative action on the ground and how officials negotiate interdepartmental tensions. It focuses on the Cameroonian tax administration, whose face began to change markedly in the 1990s. The chapter examines the effects of a recent program aimed at improving the efficiency of the state's revenue-raising efforts. It analyzes in detail the Program for Improved Revenue Reliability in the Animal Husbandry and Fisheries Sector (PSREP), one such relatively modest component of these reforms, and to place the scope of this program within a broader spectrum of administrative practice. Recent studies have demonstrated how a transnational epistemic community of tax experts has played a major part in the design of strategies to improve tax administration in developing countries. The chapter discusses the contour of the administrative reforms in Cameroon before delving, through a specific example, into the nature of the transformations that they have triggered. Keywords: administrative reforms; Cameroonian tax administration; PSREP; transnational epistemic community
Efficient and Mutually Authenticated Key Exchange for Low Power Computing Devices

In this paper, we consider the problem of mutually authenticated key exchanges between a low-power client and a powerful server. We show how the Jakobsson-Pointcheval scheme proposed recently [15] can be compromised using a variant of interleaving attacks. We also propose a new scheme for achieving mutually authenticated key exchanges. The protocol is proven correct within a variant of Bellare-Rogaway model [3,4]. This protocol gives the same scalability as other publickey based authenticated key exchange protocols but with much higher efficiency and fewer messages. It only takes 20 msec total computation time on a PalmPilot and has only three short messages exchanged during the protocol.
Fatigue crack growth in a unidirectional SCS-6/Ti-15-3 composite

An investigation was conducted to characterize and model the fatigue crack growth (FCG) behavior of a SCS-6/Ti-15-3 metal matrix composite. Part of the study was conducted using a fatigue loading stage mounted inside a scanning electron microscope (SEM). This unique facility allowed high magnification viewing of the composite fatigue processes and measurement of the near crack tip displacements. The unidirectional composite was tested in the (0)8 (i.e., longitudinal) and (90)8 (i.e., transverse) orientations. For comparison purposes unreinforced matrix material produced by the identical process as the reinforced material was also tested. The results of the study reveal that the fatigue crack growth behavior of the composite is a function of specimen geometry, fiber orientation and the interaction of local stress fields with the highly anisotropic composite. In the case of (0)8 oriented single edge notch (SEN) specimens and (90)8 oriented compact tension (CT) specimens, the crack growth was normal to the loading direction. However, for the (0)8 CT specimens the crack grew mostly parallel to the loading and the fiber direction. The unusual fatigue behavior of the (0)8 CT specimens was attributed to the specimen geometry and the associated high tensile bending stresses perpendicular to the fiber direction. These stresses resulted in preferential cracking in the weak interface region perpendicular to the fiber direction. The interface region, and in particular the carbon coating surrounding the fiber proved to be the composites weakest link. In the (0)8 SEN the crack growth was confined to the matrix leaving behind unbroken fibers which bridged the cracked surfaces. As the crack grew longer, more fibers bridged the crack resulting in a progressive decrease in the crack growth rates and eventual crack arrest. The actual near crack tip displacement measurements were used in a proposed formulation for a bridging-corrected effective crack driving force, delta K(sub eff). This parameter was able to account for most of the experienced bridging and correlated the (0)8 SEN fatigue crack growth data reasonably well.
Solubilization and Partial Purification of Tyrosine Hydroxylase from Bovine Adrenal Medulla

Abstract Tyrosine hydroxylase from bovine adrenal medulla has been solubilized and extensively purified. The catalytic properties of the solubilized, purified enzyme are similar to those of the particulate enzyme. The stoichiometry of the reaction catalyzed by the enzyme, as well as its regulatory properties, have been found to vary with different pterin cofactors. The enzyme, for example, is markedly inhibited by its substrate, tyrosine, in the presence of tetrahydrobiopterin, but not in the presence of 6,7-dimethyltetrahydropterin. Purified tyrosine hydroxylase is sensitive to H2O2 that is generated during the nonenzymatic oxidation of tetrahydropterin. The enzyme can be protected by catalase, peroxidase, or Fe2+ from H2O2-mediated inactivation. In the presence of catalase or peroxidase, Fe2+ does not stimulate the reaction. It is concluded that the previous reports that tyrosine hydroxylase is stimulated by Fe2+ can be explained by the known ability of Fe2+ to decompose H2O2
Effects of chloramphenicol and cycloheximide on the biosynthesis of mitochondrial ribosomes in Tetrahymena.

Abstract Effects of two antibiotics, chloramphenicol and cycloheximide, on the synthesis of mitochondrial and cytoplasmic ribosomes in Tetrahymena were studied. The results presented here show that mitochondrial ribosome synthesis was not completely inhibited by chloramphenicol (0.5 mm), but was abolished by cycloheximide (1 mm). Acrylamide gel electrophoresis analysis revealed that mitochondrial ribosomal proteins in a range of molecular weights from 13,000 to 25,000 were found particularly susceptible to chloramphenicol inhibition. Cytoplasmic ribosomal proteins did not appear to be differentially inhibited by chloramphenicol. The inhibition of mitochondrial ribosome synthesis in the presence of cycloheximide did not result from the loss of mitochondrial protein synthesis capacity as evidenced by in vitro [14C]leucine incorporation capacity of mitochondria isolated from whole cells treated with cycloheximide. However, cycloheximide greatly reduces the capacity to incorporate [3H]uridine into mitochondrial ribosomes as RNaseresistant radioactivity. These results suggest that some mitochondrial ribosomal proteins are synthesized in mitochondria and others by cytoplasmic ribosomes. The synthesis of those proteins that are produced by the mitochondrial ribosomes appears to be under the control of cytoplasmic protein synthesis. However, mitochondrial ribosome assembly can take place in the absence of cytoplasmic protein synthesis.