cssi/SciSciGPT-SciSciNet huggingface dataset:
A Study on Performance and Power Efficiency of Dense Non-Volatile Caches in Multi-Core Systems

This paper presents a novel cache design based on Multi-Level Cell Spin-Transfer Torque RAM (MLC STT-RAM).Our design exploits the asymmetric nature of the MLC STT-RAM to build cache lines featuring heterogeneous performances, that is, half of the cache lines are read-friendly,while the other half are write-friendly--this asymmetry in read/write latencies are then used by a migration policy in order to overcome the high latency of the baseline MLC cache. Furthermore, in order to enhance the device lifetime, we propose to dynamically deactivate ways of a set in underutilized sets to convert MLC to Single-Level Cell (SLC)mode.Our experiments show that our design gives an average improvement of 12% in system performance and 26% in last-level cache(L3) access energy for various workloads.
The murine catecholamine methyltransferase mTOMT is essential for mechanotransduction by cochlear hair cells

Hair cells of the cochlea are mechanosensors for the perception of sound. Mutations in the LRTOMT gene, which encodes a protein with homology to the catecholamine methyltransferase COMT that is linked to schizophrenia, cause deafness. Here, we show that Tomt/Comt2, the murine ortholog of LRTOMT, has an unexpected function in the regulation of mechanotransduction by hair cells. The role of mTOMT in hair cells is independent of mTOMT methyltransferase function and mCOMT cannot substitute for mTOMT function. Instead, mTOMT binds to putative components of the mechanotransduction channel in hair cells and is essential for the transport of some of these components into the mechanically sensitive stereocilia of hair cells. Our studies thus suggest functional diversification between mCOMT and mTOMT, where mTOMT is critical for the assembly of the mechanotransduction machinery of hair cells. Defects in this process are likely mechanistically linked to deafness caused by mutations in LRTOMT/Tomt.
Ubiquitin- and ATP-dependent unfoldase activity of P97/VCP•NPLOC4•UFD1L is enhanced by a mutation that causes multisystem proteinopathy

p97 is a “segregase” that plays a key role in numerous ubiquitin (Ub)-dependent pathways such as ER-associated degradation. It has been hypothesized that p97 extracts proteins from membranes or macromolecular complexes to enable their proteasomal degradation; however, the complex nature of p97 substrates has made it difficult to directly observe the fundamental basis for this activity. To address this issue, we developed a soluble p97 substrate—Ub-GFP modified with K48-linked ubiquitin chains—for in vitro p97 activity assays. We demonstrate that WT p97 can unfold proteins and that this activity is dependent on the p97 adaptor NPLOC4-UFD1L, ATP hydrolysis, and substrate ubiquitination, with branched chains providing maximal stimulation. Furthermore, we show that a p97 mutant that causes inclusion body myopathy, Paget’s disease of bone, and frontotemporal dementia in humans unfolds substrate faster, suggesting that excess activity may underlie pathogenesis. This work overcomes a significant barrier in the study of p97 and will allow the future dissection of p97 mechanism at a level of detail previously unattainable.
On the Complexity of Bribery and Manipulation in Tournaments with Uncertain Information

We study the computational complexity of optimal bribery and manipulation schemes for sports tournaments with uncertain information: cup; challenge or caterpillar; and round robin. Our results carry over to the equivalent voting rules: sequential pair-wise elections, cup, and Copeland, when the set of candidates is exactly the set of voters. This restriction creates new difficulties for most existing algorithms. The complexity of bribery and manipulation are well studied, almost always assuming deterministic information about votes and results. We assume that for candidates i and j the probability that i beats j and the costs of lowering each probability by fixed increments are known to the manipulators. We provide complexity analyses for cup, challenge, and round robin competitions ranging from polynomial time to NP^PP. This shows that the introduction of uncertainty into the reasoning process drastically increases the complexity of bribery problems in some instances.
Exploring Factors Influencing Self-Efficacy in Information Security: An Empirical Analysis by Integrating Multiple Theoretical Perspectives in the Context of Using Protective Information Technologies

Self-efficacy in information security (SEIS) is one of the most researched predictors of end user security behavior that hinges on end user acceptance and use of the protective technologies such as anti-virus and anti-spyware. SEIS is also modeled as a mediator between factors affecting SEIS and the end user cybersecurity behavior. However, it is not clearly established in past literature on whether SEIS is better modeled as a predictor or as a mediator. It is stressed in literature that we should find new ways to improve SEIS. Accordingly, the purpose of this research is to empirically investigate what factors influence SEIS, and to examine the relative effect of each theorized factor (including self-efficacy) in increasing information security.
Saving face: How exit in response to negative press and star analyst downgrades reflects reputation maintenance by directors

This paper explores the extrinsic and intrinsic motivations driving individual-level responses to reputational threats in the context of the director labor market. Integrating work on reputation wi...
Ureteropelvic Junction Obstruction Presenting With Recurrent Abdominal Pain: Diagnosis by Ultrasound

Three cases of ureteropelvic junction obstruction are presented in which the only symptom was recurrent abdominal pain. Results of physical examination and urinalysis were normal. Ultrasound established the correct diagnosis in the two patients in whom it was performed. Because it is safe, involves no radiation exposure, and is useful in evaluating the gallbladder, pancrease, and liver, as well as both kidneys, abdominal ultrasound should be performed prior to contrast radiography in the evaluation of children with recurrent abdominal pain.
Evaluation of Recurrent Glomerulonephritis in Kidney Allografts

Abstract The clinical records and biopsy and nephrectomy specimens from 320 patients treated at the Duke University Medical Center between 1965 and 1977 were examined to determine the type and incidence of recurrent glomerulonephritis in the allograft. The diagnosis of recurrent disease required that the histopathologic features of the transplanted kidney resemble those of the diseased native kidney by immunofluorescence and light and electron microscopy. Of 204 patients with tissue available for evaluation from both the native and the transplanted kidney, 117 had some form of chronic glomerulonephritis. Of the 117, there were 61 whose disease could be subclassified further. Idiopathic membranous glomerulonephritis was documented in seven patients, IgA nephropathy in five, focal glomerular sclerosis in 20, type 1 membranoproliferative glomerulonephritis in 16, type 2 membranoproliferative glomerulonephritis in two, proliferative glomerulonephritis in five, crescentic proliferative glomerulonephritis in four and anti-glomerular basement membrane disease in two. In this group of 61, there were 19 patients with 21 allografts in which there was evidence of recurrent glomerulonephritis including four each with idiopathic membranous glomerulonephritis and focal glomerular sclerosis, seven with type 1 membranoproliferative glomerulonephritis, two each with type 2 membranoproliferative glomerulonephritis and anti-glomerular basement membrane disease and one each with IgA nephropathy and crescentic proliferative glomerulonephritis. There were 104 living related donor kidneys grafted into patients with chronic glomerulonephritis, and 78 had tissue available for evaluation. In this group, 15 patients had 16 grafts with recurrent glomerulonephritis. There were 55 cadaveric donor kidneys transplanted into patients with chronic glomerulonephritis, and 39 had tissue available for evaluation. In this group, there were five examples of recurrent glomerulonephritis. Thus, recurrent glomerulonephritis can occur in a variety of histologic subtypes, and in this study population, recurrent glomerulonephritis was more common in allografts from living related donors.
Property and Sovereignty Imbricated: Why Religion Is Not an Excuse to Discriminate in Public Accommodations

May a hotel owner that objects to same-sex marriage on religious grounds refuse to host a same-sex wedding in its ballroom or deny the couple the right to book the honeymoon suite? Do public accommodation laws oppress religious dissidents by forcing them to act contrary to their religious beliefs or does discriminatory exclusion threaten equal access to the market economy and deny equal citizenship to LGBTQ persons? Answering these questions requires explaining why one property claim should prevail over another and why one liberty should prevail when it clashes with another. And answering those questions requires analysis of the relationship between property and sovereignty. Sovereign power both creates and regulates the types of property rights that can be tolerated in a free and democratic society that values each person equally. Should we view sovereignty as a threat to property or property as a threat to sovereignty? Libertarians choose the first and liberals the second. But this is the wrong way to understand the relation between property and sovereignty. Property and sovereignty are not separate and independent concepts or spheres of social life that can be brought into relationship with each other. Rather, they are imbricated; they overlap like roof tiles. Our aspiration to live in a free and democratic society places certain constraints on both property and sovereignty. Such societies do not recognize absolute power, whether public or private. Free and democratic societies are committed to a substantive vision of both social relations and politics. We have fruitful debates about property and sovereignty and, in the end, must construct a legal system that effects an acceptable compromise between access and exclusion in the property regime. Our historic practices regarding racial and other forms of discrimination and our evolving norms suggest that p ublic accommodation laws enable access to the marketplace without regard to invidious discrimination. Religious freedom cannot operate to deny equal citizenship or opportunity. For that reason, a same-sex couple should not have to call ahead to see if they are welcome to book the honeymoon suite. Public accommodation laws do not infringe on legitimate property rights or religious freedoms; rather, they define the legitimate contours of liberty and property in a society that treats each person with equal concern and respect.
Investigating a learning progression for energy ideas from upper elementary through high school

This study tests a hypothesized learning progression for the concept of energy. It looks at 14 specific ideas under the categories of (i) Energy Forms and Transformations; (ii) Energy Transfer; (iii) Energy Dissipation and Degradation; and (iv) Energy Conservation. It then examines students’ growth of understanding within each of these ideas at three levels of increasing conceptual complexity. The basic level of the model focuses on simple energy relationships and easily observable effects of energy processes; the intermediate level focuses on more complex energy concepts and applications; and the advanced level focuses on still more complex energy concepts, often requiring an atomic/molecular model to explain phenomena. The study includes results from 359 distractor-driven, multiple-choice test items administered to over 20,000 students in grades 4 through 12 from across the U.S. Rasch analysis provided linear measures of student performance and item difficulty on the same scale. Results largely supported a model of students’ growth of understanding that progresses from an understanding of forms and transformations of energy to energy transfer to conservation while also progressing along a separate dimension of cognitive complexity. An analysis of the current state of students’ understanding with respect to the knowledge identified in the learning progression showed that elementary level students perform well in comparison to expectations but that middle and high school students’ performance does not meet expectations. © 2017 Wiley Periodicals, Inc. J Res Sci Teach 9999:XX–XX, 2017
A Controlled Study of the Nephrotoxicity of Mezlocillin and Amikacin in the Neonate

• The nephrotoxicity of the aminoglycoside amikacin sulfate was evaluated in an open, controlled study of newborns with presumed neonatal sepsis. One hundred twelve neonates were randomly allocated to receive either amikacin-ampicillin or mezlocillin, a semisynthetic penicillin. Neonates receiving amikacin, in contrast to those receiving mezlocillin, showed significant nephrotoxicity as evidenced by a delayed postnatal fall in mean serum creatinine level (82 to 80 μmol/L [0.93 to 0.90 mg/dL] vs 84 to 72 μmol/L [0.95 to 0.82 mg/dL]) and a delayed postnatal rise in mean creatinine clearance per kilogram of body weight (12% vs 38%). Furthermore, 40% of neonates receiving amikacin-ampicillin compared with 19% of neonates receiving mezlocillin had a decline in creatinine clearance (>25%). There was no relationship between amikacin nephrotoxicity and either peak or trough amikacin levels. In summary, in a controlled study of the use of amikacin and mazlocillin in neonates, the combination of amikacin and ampicillin proved more nephrotoxic to the newborn kidney. ( AJDC 1987;141:1175-1178)
Strength of functional signature correlates with effect size in autism.

Disagreements over genetic signatures associated with disease have been particularly prominent in the field of psychiatric genetics, creating a sharp divide between disease burdens attributed to common and rare variation, with study designs independently targeting each. Meta-analysis within each of these study designs is routine, whether using raw data or summary statistics, but combining results across study designs is atypical. However, tests of functional convergence are used across all study designs, where candidate gene sets are assessed for overlaps with previously known properties. This suggests one possible avenue for combining not study data, but the functional conclusions that they reach. In this work, we test for functional convergence in autism spectrum disorder (ASD) across different study types, and specifically whether the degree to which a gene is implicated in autism is correlated with the degree to which it drives functional convergence. Because different study designs are distinguishable by their differences in effect size, this also provides a unified means of incorporating the impact of study design into the analysis of convergence. We detected remarkably significant positive trends in aggregate (p < 2.2e-16) with 14 individually significant properties (false discovery rate <0.01), many in areas researchers have targeted based on different reasoning, such as the fragile X mental retardation protein (FMRP) interactor enrichment (false discovery rate 0.003). We are also able to detect novel technical effects and we see that network enrichment from protein–protein interaction data is heavily confounded with study design, arising readily in control data. We see a convergent functional signal for a subset of known and novel functions in ASD from all sources of genetic variation. Meta-analytic approaches explicitly accounting for different study designs can be adapted to other diseases to discover novel functional associations and increase statistical power.
O-GlcNAc regulation of autophagy and α-synuclein homeostasis; implications for Parkinson’s disease

Post-translational modification on protein Ser/Thr residues by O-linked attachment of s-N-acetyl-glucosamine (O-GlcNAcylation) is a key mechanism integrating redox signaling, metabolism and stress responses. One of the most common neurodegenerative diseases that exhibit aberrant redox signaling, metabolism and stress response is Parkinson’s disease, suggesting a potential role for O-GlcNAcylation in its pathology. To determine whether abnormal O-GlcNAcylation occurs in Parkinson’s disease, we analyzed lysates from the postmortem temporal cortex of Parkinson’s disease patients and compared them to age matched controls and found increased protein O-GlcNAcylation levels. To determine whether increased O-GlcNAcylation affects neuronal function and survival, we exposed rat primary cortical neurons to thiamet G, a highly selective inhibitor of the enzyme which removes the O-GlcNAc modification from target proteins, O-GlcNAcase (OGA). We found that inhibition of OGA by thiamet G at nanomolar concentrations significantly increased protein O-GlcNAcylation, activated MTOR, decreased autophagic flux, and increased α-synuclein accumulation, while sparing proteasomal activities. Inhibition of MTOR by rapamycin decreased basal levels of protein O-GlcNAcylation, decreased AKT activation and partially reversed the effect of thiamet G on α-synuclein monomer accumulation. Taken together we have provided evidence that excessive O-GlcNAcylation is detrimental to neurons by inhibition of autophagy and by increasing α-synuclein accumulation.
Formation of lithospheric shear zones: Effect of temperature on two-phase grain damage

Abstract Shear localization in the lithosphere is a characteristic feature of plate tectonic boundaries, and is evident in the presence of small grain mylonites. Localization and mylonitization in the ductile portion of the lithosphere can arise when its polymineralic material deforms by a grain-size sensitive rheology in combination with Zener pinning, which can impede, or possibly even reverse, grain growth and thus promotes a self-softening feedback mechanism. However, the efficacy of this mechanism is not ubiquitous and depends on lithospheric conditions such as temperature and stress. Therefore, we explore the conditions under which self-weakening takes place, and, in particular, the effect of temperature and deformation state (stress or strain-rate) on these conditions. In our model, the lithosphere-like polymineralic material is deformed in a two-dimensional simple shear driven by constant stress or strain rate. The mineral grains evolve to a stable size, which is obtained when the rate of coarsening by normal grain growth and the rate of grain size reduction by damage are in balance. Damage involves processes by which some of the deformational energy gets transferred into surface energy. This can happen by (i) dynamic recrystallization (grain damage) and (ii) stretching, deforming and stirring the material interface (interface damage). The influence of temperature enters through rheological laws (which govern the rate of work and damage), grain growth kinetics, and the damage partitioning fraction, which is the fraction of deformational work that goes into creating new surface energy. We demonstrate that a two-phase damage model, in which the partitioning fraction depends on both temperature and roughness of the interface between the phases, can successfully match the field data, including the reported correlation of grain size and temperature, the increasing dominance of dislocation creep at higher temperatures and a large range of grain sizes observed across the depth of a single shear zone.
Synchrotron Infrared Microspectroscopy for Assessment of Mutagenicity of Metal Implants

A major concern in the development and implementation of metal implants for the clinical use is the assessment of material-induced mutagenesis. In this study we used synchrotron microspectroscopy in the mid-infrared region (4000-400 cm1 ) to non-invasively assess the in situ human cell responses to metal surfaces. Specifically we examined the subtle genetic aberrations of cells as they responded to a range of metals commonly used in metal prosthetic devices. Relative band intensities and band intensity ratios for functional groups of biomolecules that are inherent to the experimental system were examined. The molecular components of the biomolecules as they were perturbed by the interactions with metals were investigated. These results demonstrate the potential use of synchrotron FTIR microspectroscopy to screen the mutagenicity of metal implants.
ON-LINE FAULT DETECTION VIA TRAJECTORY ENCODING

Abstract Trajectory encoding is a method for on-line monitoring of manufacturing processes with complex discrete and continuous dynamics and infrequent, uncertain observations. Using a behavioral model specification of the acceptable process behavior, an evolution graph is constructed and updated iteratively as observations are received from the system. The evolution graph efficiently represents the (possibly infinite) set of valid system trajectories which are consistent with the observations. I his paper focuses on the formal definition of the trajectory encoding method and the analytical results on the encoding as it relates to fault monitoring. The concluding section briefly describes applications of the method and directions for extensions to aid in fault diagnosis as well as detection.
Face Module for Realizable Z-matroids

In this work, we define the face ring for a matroid over Z. Its Hilbert series is, indeed, the expected specialization of the Grothendieck-Tutte polynomial defined by Fink and Moci in [10].
E-Pain Reporter: A Digital Pain and Analgesic Diary for Home Hospice Care.

Informal hospice caregivers play a key role in managing patients’ pain at home, but lack of adherence to doctor-prescribed analgesic regimens and medication errors are significant barriers to truly...
A Meta-Analysis to Determine the Impact of Restaurant Menu Labeling on Calories and Nutrients (Ordered or Consumed) in U.S. Adults

A systematic review and meta-analysis determined the effect of restaurant menu labeling on calories and nutrients chosen in laboratory and away-from-home settings in U.S. adults. Cochrane-based criteria adherent, peer-reviewed study designs conducted and published in the English language from 1950 to 2014 were collected in 2015, analyzed in 2016, and used to evaluate the effect of nutrition labeling on calories and nutrients ordered or consumed. Before and after menu labeling outcomes were used to determine weighted mean differences in calories, saturated fat, total fat, carbohydrate, and sodium ordered/consumed which were pooled across studies using random effects modeling. Stratified analysis for laboratory and away-from-home settings were also completed. Menu labeling resulted in no significant change in reported calories ordered/consumed in studies with full criteria adherence, nor the 14 studies analyzed with ≤1 unmet criteria, nor for change in total ordered carbohydrate, fat, and saturated fat (three studies) or ordered or consumed sodium (four studies). A significant reduction of 115.2 calories ordered/consumed in laboratory settings was determined when analyses were stratified by study setting. Menu labeling away-from-home did not result in change in quantity or quality, specifically for carbohydrates, total fat, saturated fat, or sodium, of calories consumed among U.S. adults.
Forecasting biodiversity in breeding birds using best practices

Biodiversity forecasts are important for conservation, management, and evaluating how well current models characterize natural systems. While the number of forecasts for biodiversity is increasing, there is little information available on how well these forecasts work. Most biodiversity forecasts are not evaluated to determine how well they predict future diversity, fail to account for uncertainty, and do not use time-series data that captures the actual dynamics being studied. We addressed these limitations by using best practices to explore our ability to forecast the species richness of breeding birds in North America. We used hindcasting to evaluate six different modeling approaches for predicting richness. Hindcasts for each method were evaluated annually for a decade at 1,237 sites distributed throughout the continental United States. All models explained more than 50% of the variance in richness, but none of them consistently outperformed a baseline model that predicted constant richness at each site. The best practices implemented in this study directly influenced the forecasts and evaluations. Stacked species distribution models and "naive" forecasts produced poor estimates of uncertainty and accounting for this resulted in these models dropping in the relative performance compared to other models. Accounting for observer effects improved model performance overall, but also changed the rank ordering of models because it did not improve the accuracy of the "naive" model. Considering the forecast horizon revealed that the prediction accuracy decreased across all models as the time horizon of the forecast increased. To facilitate the rapid improvement of biodiversity forecasts, we emphasize the value of specific best practices in making forecasts and evaluating forecasting methods.
Mimicking Intermolecular Interactions of Tight Protein-Protein Complexes for Small-Molecule Antagonists.

Tight protein-protein interactions (Kd 1000 A2 ) are highly challenging to disrupt with small molecules. Historically, the design of small molecules to inhibit protein-protein interactions has focused on mimicking the position of interface protein ligand side chains. Here, we explore mimicry of the pairwise intermolecular interactions of the native protein ligand with residues of the protein receptor to enrich commercial libraries for small-molecule inhibitors of tight protein-protein interactions. We use the high-affinity interaction (Kd =1 nm) between the urokinase receptor (uPAR) and its ligand urokinase (uPA) to test our methods. We introduce three methods for rank-ordering small molecules docked to uPAR: 1) a new fingerprint approach that represents uPA's pairwise interaction energies with uPAR residues; 2) a pharmacophore approach to identify small molecules that mimic the position of uPA interface residues; and 3) a combined fingerprint and pharmacophore approach. Our work led to small molecules with novel chemotypes that inhibited a tight uPAR⋅uPA protein-protein interaction with single-digit micromolar IC50 values. We also report the extensive work that identified several of the hits as either lacking stability, thiol reactive, or redox active. This work suggests that mimicking the binding profile of the native ligand and the position of interface residues can be an effective strategy to enrich commercial libraries for small-molecule inhibitors of tight protein-protein interactions.
Comparative Process-oriented Research Using Social Media and Historical Text:

This article evaluates whether we can use process-oriented theory to conduct comparative, historical social media research. There is a lack of theoretically informed approaches to studying recently...
Empirically derived pain-patient MMPI subgroups: prediction of treatment outcome.

Fifty-seven male chronic pain patients admitted to an inpatient multimodal pain treatment program at a Midwestern Veterans Administration hospital completed the MMPI, Profile of Mood States (POMS), Tennessee Self-Concept Scale (TSCS), Rathus Assertiveness Schedule (RAS), activity diaries, and an extensive pain questionnaire. All patients were assessed both before and after treatment, and most also were assessed 2–5 months prior to treatment. No significant changes occurred during the baseline period, but significant improvements were evident at posttreatment on most variables: MMPI, POMS, TSCS, RAS, pain severity, sexual functioning, and activity diaries. MMPI subgroup membership, based on a hierarchical cluster analysis in a larger sample, was not predictive of differential treatment outcome. Possible reasons for comparable treatment gains among these subgroups, which previously have been shown to differ on many psychological and behavioral factors, are discussed.
Alcohol Drinking and Blood Alcohol Concentration Revisited.

BACKGROUND It is widely assumed that the amount of alcohol in the blood reflects the amount of alcohol consumed. However, several factors in addition to amount of alcohol consumed can influence blood alcohol concentration (BAC). This study examines the effect of alcohol dose, concentration, and volume on BAC in rats with a high-alcohol-drinking (HAD) phenotype. METHODS Study 1 examined the relationship between the amount of alcohol consumed and BAC. Alcohol-naive, male, HAD rats (N = 7) were given access to alcohol for 2 h/d for 9 consecutive days with food and water ad libitum. Alcohol intake and BAC were measured at 30, 60, and 90 minutes after onset of access. Study 2 examined the effects of altering alcohol dose, concentration, and volume on BAC (as measured by area under the curve). Alcohol-naive, male, HAD rats (N = 39) were infused, via an intragastric cannulus, with 1.16, 2.44, or 3.38 g alcohol/kg body weight (BW), produced by varying alcohol volume while holding concentration constant or by holding volume constant while varying concentration. Other rats were infused with 10, 15, or 20% v/v alcohol solutions while holding dose constant. RESULTS BAC was more strongly correlated with the ratio of alcohol intake (g/kg BW) to total fluid intake (mls) (R = 0.85 to 0.97, p < 0.05 to p < 0.001) than it was with the amount of alcohol consumed (g/kg BW) (R = 0.70 to 0.81, p < 0.05). No effect of alcohol dose was seen during the first hour following the onset of an alcohol infusion regardless of whether dose was achieved by altering alcohol volume or concentration. After 1 hour, higher alcohol doses were predictive of greater BACs. CONCLUSIONS The fact that a 3-fold difference in alcohol dose did not result in significant differences in BACs during the first 30 minutes after ingestion of alcohol has potentially important implications for interpretation of studies that measure alcohol-sensitive end points during this time.
The uncovered interest parity puzzle, exchange rate forecasting, and Taylor rules

Abstract Recent research has found that the Taylor-rule fundamentals have power to forecast changes in U.S. dollar exchange rates out of sample. Our work casts some doubt on that claim. However, we find strong evidence of a related in-sample anomaly. When we include U.S. inflation in the well-known uncovered interest parity regression of the change in the exchange rate on the interest-rate differential, we find that the inflation variable is highly significant and the interest-rate differential is not. Specifically, high U.S. inflation in one month forecasts dollar appreciation in the subsequent month. We introduce a model in which a Taylor rule determines monetary policy, but in which not only monetary shocks but also liquidity shocks drive nominal interest rates. This model can potentially account for the empirical findings.
Microwave SQUID Multiplexer Demonstration for Cosmic Microwave Background Imagers.

Key performance characteristics are demonstrated for the microwave superconducting quantum interference device (SQUID) multiplexer (μmux) coupled to transition edge sensor (TES) bolometers that have been optimized for cosmic microwave background (CMB) observations. In a 64-channel demonstration, we show that the μmux produces a white, input referred current noise level of 29 pA/ Hz at a microwave probe tone power of −77 dB, which is well below the expected fundamental detector and photon noise sources for a ground-based CMB-optimized bolometer. Operated with negligible photon loading, we measure 98 pA/ Hz in the TES-coupled channels biased at 65% of the sensor normal resistance. This noise level is consistent with that predicted from bolometer thermal fluctuation (i.e., phonon) noise. Furthermore, the power spectral density is white over a range of frequencies down to ∼100 mHz, which enables CMB mapping on large angular scales that constrain the physics of inflation. Additionally, we report cross-talk measurements that indicate a level below 0.3%, which is less than the level of cross-talk from multiplexed readout systems in deployed CMB imagers. These measurements demonstrate the μmux as a viable readout technique for future CMB imaging instruments.
Yields versus Expected Returns of Corporate Bonds: Some Unexpected Results

We derive expected bond return equations for various structural credit valuation models with alternative stochastic processes and boundary conditions for default given in Merton [1974], Merton [1976], Black and Cox [1976], Heston [1993], Longstaff and Schwartz [1995], and Collin-Dufresne and Goldstein [2001]. We investigate the relationship between bond yields and expected returns under each of these models. We show that for the case of low leverage, bond yields are inversely related to expected returns for a range of maturities that lie beyond the hump of the term structure of bond yields. We also show that for the bonds of same maturity, the option characteristics of the bonds often lead to an inverse relation between bond yields and expected returns. For example, callable bonds have higher yields, but lower expected returns, than the corresponding yields and expected returns of the underlying straight bonds. Convertible bonds have higher yields but lower expected returns for the case of high leverage, and lower yields but higher expected returns for the case of low leverage, than the corresponding yields and expected returns of the underlying straight bonds.
Automated Detection of Whole-Cell Mitochondrial Motility and its Dependence on Cytoarchitectural Integrity

Current methodologies used for mitochondrial motility analysis tend to overlook either individual mitochondrial tracks or a cell-wide measure of motility. Furthermore, motility analysis of individual mitochondria is usually quantified by establishing an arbitrary threshold for “directed” motion. In this work, we created a custom, publicly available computational algorithm based on a previously published approach (Giedt et al, 2012) in order to characterize the distribution of mitochondrial movements at the whole-cell level, while still preserving information about individual mitochondria. The technique is easy to use, robust and computationally inexpensive. Images are first pre-processed for increased resolution, and then each mitochondrion is tracked based on object connectivity in space and time.When our method is applied to entire cells, we reveal that the mitochondrial net distances in fibroblasts follow a continuous lognormal distribution within a given cell or group of cells. This is in contrast to discrete categories used by others to bin mitochondria as either static or motile. Most mitochondria exhibit negligible movement, with the distribution center corresponding to a net distance of 132.3 nm. A few select mitochondria achieve net distances of several microns. The ability to model whole-cell mitochondrial motility as a lognormal distribution provides a new quantitative paradigm by which to compare mitochondrial motility in naive and treated cells. We further demonstrate that microtubule and microfilament depolymerization shift the lognormal distribution in directions which indicate decreased and increased mitochondrial movement, respectively. This shift occurs with distances of all magnitudes, even seemingly negligible ones. Our findings advance earlier work on neuronal axons (Morris and Hollenbeck, 1993) by relating them to a different cell type, applying them on a global scale, and automating measurement of mitochondrial motility in general.
Cryo-EM structure of Escherichia coli σ70 RNA polymerase and promoter DNA complex revealed a role of σ non-conserved region during the open complex formation

First step of gene expression is transcribing the genetic information stored in DNA to RNA by the transcription machinery including RNA polymerase (RNAP). In Escherichia coli, a primary σ70 factor forms the RNAP holoenzyme to express housekeeping genes. The σ70 contains a large insertion between the conserved regions 1.2 and 2.1, the σ non-conserved region (σNCR), but its function remains to be elucidated. In this study, we determined the cryo-EM structures of the E. coli RNAP σ70 holoenzyme and its complex with promoter DNA (open complex, RPo) at 4.2 and 5.75 A resolutions, respectively, to reveal native conformations of RNAP and DNA. The RPo structure presented here found an interaction between the σNCR and promoter DNA just upstream of the −10 element, which was not observed in a previously determined E. coli RNAP transcription initiation complex (RPo plus short RNA) structure by X-ray crystallography because of restraint of crystal packing effects. Disruption of the σNCR and DNA interaction by the amino acid substitutions (R157A/R157E) influences the DNA opening around the transcription start site and therefore decreases the transcription activity of RNAP. We propose that the σNCR and DNA interaction is conserved in proteobacteria, and RNAP in other bacteria replaces its role with a transcription factor.
WiFi-Enabled Smart Human Dynamics Monitoring

The rapid pace of urbanization and socioeconomic development encourage people to spend more time together and therefore monitoring of human dynamics is of great importance, especially for facilities of elder care and involving multiple activities. Traditional approaches are limited due to their high deployment costs and privacy concerns (e.g., camera-based surveillance or sensor-attachment-based solutions). In this work, we propose to provide a fine-grained comprehensive view of human dynamics using existing WiFi infrastructures often available in many indoor venues. Our approach is low-cost and device-free, which does not require any active human participation. Our system aims to provide smart human dynamics monitoring through participant number estimation, human density estimation and walking speed and direction derivation. A semi-supervised learning approach leveraging the non-linear regression model is developed to significantly reduce training efforts and accommodate different monitoring environments. We further derive participant number and density estimation based on the statistical distribution of Channel State Information (CSI) measurements. In addition, people's walking speed and direction are estimated by using a frequency-based mechanism. Extensive experiments over 12 months demonstrate that our system can perform fine-grained effective human dynamic monitoring with over 90% accuracy in estimating participants number, density, and walking speed and direction at various indoor environments.
Estimating Dynamic Models of Imperfect Competition

We describe a two-step algorithm for estimating dynamic games under the assumption that behavior is consistent with Markov perfect equilibrium. In the first step, the policy functions and the law of motion for the state variables are estimated. In the second step, the remaining structural parameters are estimated using the optimality conditions for equilibrium. The second step estimator is a simple simulated minimum distance estimator. The algorithm applies to a broad class of models, including industry competition models with both discrete and continuous controls such as the Ericson and Pakes (1995) model. We test the algorithm on a class of dynamic discrete choice models with normally distributed errors and a class of dynamic oligopoly models similar to that of Pakes and McGuire (1994).
PMAF: an algebraic framework for static analysis of probabilistic programs

Automatically establishing that a probabilistic program satisfies some property ϕ is a challenging problem. While a sampling-based approach—which involves running the program repeatedly—can suggest that ϕ holds, to establish that the program satisfies ϕ, analysis techniques must be used. Despite recent successes, probabilistic static analyses are still more difficult to design and implement than their deterministic counterparts. This paper presents a framework, called PMAF, for designing, implementing, and proving the correctness of static analyses of probabilistic programs with challenging features such as recursion, unstructured control-flow, divergence, nondeterminism, and continuous distributions. PMAF introduces pre-Markov algebras to factor out common parts of different analyses. To perform interprocedural analysis and to create procedure summaries, PMAF extends ideas from non-probabilistic interprocedural dataflow analysis to the probabilistic setting. One novelty is that PMAF is based on a semantics formulated in terms of a control-flow hyper-graph for each procedure, rather than a standard control-flow graph. To evaluate its effectiveness, PMAF has been used to reformulate and implement existing intraprocedural analyses for Bayesian-inference and the Markov decision problem, by creating corresponding interprocedural analyses. Additionally, PMAF has been used to implement a new interprocedural linear expectation-invariant analysis. Experiments with benchmark programs for the three analyses demonstrate that the approach is practical.
Robust multiclass queuing theory for wait time estimation in resource allocation systems

In this paper, we study systems that allocate different types of scarce resources to heterogeneous allocatees based on predetermined priority rules—the U.S. deceased-donor kidney allocation system or the public housing program. We tackle the problem of estimating the wait time of an allocatee who possesses incomplete system information with regard, for example, to his relative priority, other allocatees’ preferences, and resource availability. We model such systems as multiclass, multiserver queuing systems that are potentially unstable or in transient regime. We propose a novel robust optimization solution methodology that builds on the assignment problem. For first-come, first-served systems, our approach yields a mixed-integer programming formulation. For the important case where there is a hierarchy in the resource types, we strengthen our formulation through a drastic variable reduction and also propose a highly scalable heuristic, involving only the solution of a convex optimization problem (usually...
Borrower Risk and Housing Price Appreciation

Maintenance and improvements affect house values and thus the observed pecuniary return. Whether due to lack of liquidity or the presence of strategic incentives, some borrowers have a higher probability of default and this could lead to lower maintenance and investment in the property. We test this hypothesis using a sample of properties on which we have repeat sales and mortgage information. We find that the predicted probability of default at the time of the original purchase significantly reduces subsequent observed pecuniary return. For instance, an increase in the probability of default from 22% to 32% leads to an 0.5% reduction in appreciation per year. Because the future house price varies with borrower risk, we examine many simulated scenarios to analyze the implications of the findings. From these scenarios, we observe that the highest risk borrowers can experience approximately 3% less appreciation per year than the lowest risk borrowers.
Bimodal Network Architectures for Automatic Generation of Image Annotation from Text

Medical image analysis practitioners have embraced big data methodologies. This has created a need for large annotated datasets. The source of big data is typically large image collections and clinical reports recorded for these images. In many cases, however, building algorithms aimed at segmentation and detection of disease requires a training dataset with markings of the areas of interest on the image that match with the described anomalies. This process of annotation is expensive and needs the involvement of clinicians. In this work we propose two separate deep neural network architectures for automatic marking of a region of interest (ROI) on the image best representing a finding location, given a textual report or a set of keywords. One architecture consists of LSTM and CNN components and is trained end to end with images, matching text, and markings of ROIs for those images. The output layer estimates the coordinates of the vertices of a polygonal region. The second architecture uses a network pre-trained on a large dataset of the same image types for learning feature representations of the findings of interest. We show that for a variety of findings from chest X-ray images, both proposed architectures learn to estimate the ROI, as validated by clinical annotations. There is a clear advantage obtained from the architecture with pre-trained imaging network. The centroids of the ROIs marked by this network were on average at a distance equivalent to 5.1% of the image width from the centroids of the ground truth ROIs.
Predicting time to dementia using a quantitative template of disease progression.

Abstract Introduction Characterization of longitudinal trajectories of biomarkers implicated in sporadic Alzheimer's disease (AD) in decades before clinical diagnosis is important for disease prevention and monitoring. Methods We used a multivariate Bayesian model to temporally align 1369 Alzheimer's disease Neuroimaging Initiative participants based on the similarity of their longitudinal biomarker measures and estimated a quantitative template of the temporal evolution of cerebrospinal fluid A β 1 − 42 , p- ta u 181 p , and t-tau and hippocampal volume, brain glucose metabolism, and cognitive measurements. We computed biomarker trajectories as a function of time to AD dementia and predicted AD dementia onset age in a disjoint sample. Results Quantitative template showed early changes in verbal memory, cerebrospinal fluid Aβ1–42 and p-tau181p, and hippocampal volume. Mean error in predicted AD dementia onset age was 1.5 years. Discussion Our method provides a quantitative approach for characterizing the natural history of AD starting at preclinical stages despite the lack of individual-level longitudinal data spanning the entire disease timeline.
NKB signaling in the posterodorsal medial amygdala stimulates gonadotropin release in a kisspeptin-independent manner in female mice

Neurokinin B (NKB) signaling is critical for reproduction in all studied species. The existing consensus is that NKB induces GnRH release via kisspeptin (Kiss1) stimulation in the arcuate nucleus. However, the stimulatory action of NKB is dependent on circulating estrogen (E2) levels, without which, NKB inhibits luteinizing hormone (LH) release. Importantly, the evidence supporting the kisspeptin-dependent role of NKB, derives from models of persistent hypogonadal state [e.g. Kiss1r knock-out (KO) mice], with reduced E2 levels. Here, we demonstrate that in the presence of E2, NKB signaling induces LH release in a kisspeptin-independent manner through the activation of NK3R (NKB receptor) neurons in the posterodorsal medial amygdala (MePD). Importantly, we show that chemogenetic activation of MePD Kiss1 neurons induces LH release, however, the stimulatory action of NKB in this area is Kiss1 neuron-independent. These results document the existence of two independent neuronal circuitries within the MePD that regulate reproductive function in females.