LLukas22/scidocs huggingface dataset:
Static analysis of energy consumption for LLVM IR programs

Energy models can be constructed by characterizing the energy consumed when executing each instruction in a processor's instruction set. This can be used to determine how much energy is required to execute a sequence of assembly instructions, without the need to instrument or measure hardware.
 However, statically analyzing low-level program structures is hard, and the gap between the high-level program structure and the low-level energy models needs to be bridged. We have developed techniques for performing a static analysis on the intermediate compiler representations of a program. Specifically, we target LLVM IR, a representation used by modern compilers, including Clang. Using these techniques we can automatically infer an estimate of the energy consumed when running a function under different platforms and compilers.
 One of the challenges in doing so is that of determining the energy cost of executing LLVM IR program segments, for which we have developed two different approaches. When this information is used in conjunction with our analysis, we are able to infer energy formulae that characterize the energy consumption for a particular program. This approach can be applied to any languages targeting the LLVM toolchain, including C and XC or architectures such as ARM Cortex-M or XMOS xCORE, with a focus towards embedded platforms. Our techniques are validated on these platforms by comparing the static analysis results to the physical measurements taken from the hardware. Static energy consumption estimation enables energy-aware software development by providing instant feedback to the developer, without requiring simulations or hardware knowledge.
Relationship between epicardial adipose tissue, coronary artery disease and adiponectin in a Mexican population

BACKGROUND
The amount of epicardial adipose tissue (EAT) around the heart has been identified as an independent predictor of coronary artery disease (CAD), potentially through local release of inflammatory cytokines. Ethnic differences have been observed, but no studies have investigated this relationship in the Mexican population. The objective of the present study was to evaluate whether a relationship exist between EAT thickness assessed via echocardiography with CAD and adiponectin levels in a Mexican population.


METHODS
We studied 153 consecutive patients who underwent coronary angiography and transthoracic echocardiography (TTE). EAT thickness on the free wall of the right ventricle was measured at the end of systole from parasternal long and short axis views of three consecutive cardiac cycles. Coronary angiograms were analyzed for the presence, extent and severity of CAD. Serum adiponectin, lipids, glucose, C-reactive protein and fibrinogen were determined.


RESULTS
EAT thickness was greater in patients with CAD than in those without CAD from both parasternal long (5.39 ± 1.75 mm vs 4.00 ± 1.67 mm p<0.0001) and short-axis views (5.23 ± 1.67 vs 4.12 ± 1.77, p=0.001). EAT thickness measured from parasternal long and short-axis showed a statistically significant positive correlation with age (r=0.354, p<0.001; r=0.286, p<0.001 respectively), and waist circumference (r=0.189, p=0.019; r=0.217, p=0.007 respectively). A significant negative correlation between EAT thickness from the parasternal long axis with cholesterol-HDL was observed (r=-0.163, p=0.045). No significant correlation was found between epicardial fat thickness and serum adiponectin or with the severity of CAD.


CONCLUSIONS
EAT thickness was greater in patients with CAD. However, no correlation was observed with the severity of the disease or with serum adiponectin levels. EAT thickness measured by echocardiography might provide additional information for risk assessment and prediction of CAD.
Estimating the dielectric constant of the channel protein and pore

When modelling biological ion channels using Brownian dynamics (BD) or Poisson–Nernst–Planck theory, the force encountered by permeant ions is calculated by solving Poisson’s equation. Two free parameters needed to solve this equation are the dielectric constant of water in the pore and the dielectric constant of the protein forming the channel. Although these values can in theory be deduced by various methods, they do not give a reliable answer when applied to channel-like geometries that contain charged particles. To determine the appropriate values of the dielectric constants, here we solve the inverse problem. Given the structure of the MthK channel, we attempt to determine the values of the protein and pore dielectric constants that minimize the discrepancies between the experimentally-determined current–voltage curve and the curve obtained from BD simulations. Two different methods have been applied to determine these values. First, we use all possible pairs of the pore dielectric constant of water, ranging from 20 to 80 in steps of 10, and the protein dielectric constant of 2–10 in steps of 2, and compare the simulated results with the experimental values. We find that the best agreement is obtained with experiment when a protein dielectric constant of 2 and a pore water dielectric constant of 60 is used. Second, we employ a learning-based stochastic optimization algorithm to pick out the optimum combination of the two dielectric constants. From the algorithm we obtain an optimum value of 2 for the protein dielectric constant and 64 for the pore dielectric constant.
Urinary hepcidin-25 and risk of acute kidney injury following cardiopulmonary bypass.

BACKGROUND AND OBJECTIVES
Acute kidney injury (AKI) complicating cardiopulmonary bypass (CPB) results in increased morbidity and mortality. Urinary hepcidin-25 has been shown to be elevated in patients who do not develop AKI after CPB using semiquantitative mass spectrometry (SELDI TOF-MS). The goals of this study were to quantitatively validate these findings with ELISA and evaluate the diagnostic performance of hepcidin-25 for AKI.


DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS
A nested, case-control analysis of urinary hepcidin-25 in AKI (n = 22) and non-AKI (n = 22) patients was conducted to validate the SELDI TOF-MS data at the following times: preoperatively; the start of CPB; 1 hour on CPB; on arrival to the intensive care unit; and postoperative days (POD) 1 and 3 to 5. The diagnostic performance of hepcidin-25 was then evaluated in the entire prospective observational cohort (n = 338) at POD 1. AKI was defined as Cr >50% from baseline, within 72 hours postoperatively.


RESULTS
Urinary hepcidin-25/Cr ratio was significantly elevated in all patients at POD 1 compared with baseline (P < 0.0005) and was also significantly elevated in non-AKI versus AKI patients at POD 1 (P < 0.0005). Increased log(10) hepcidin-25/Cr ratio was strongly associated with avoidance of AKI on univariate analysis. On multivariate analysis, the log(10) hepcidin-25/Cr ratio (P < 0.0001) was associated with avoidance of AKI with an area under the curve of 0.80, sensitivity 0.68, specificity 0.68, and negative predictive value 0.96.


CONCLUSIONS
Elevated urinary hepcidin-25 on POD 1 is a strong predictor of avoidance of AKI beyond postoperative day 1.
Adding Intelligence to Mobile Asset Management in Hospitals: The True Value of RFID

RFID (Radio Frequency Identification) technology is expected to play a vital role in the healthcare arena, especially in times when cost containments are at the top of the priorities of healthcare management authorities. Medical equipment represents a significant share of yearly healthcare operational costs; hence, ensuring an effective and efficient management of such key assets is critical to promptly and reliably deliver a diversity of clinical services at the patient bedside. Empirical evidence from a phased-out RFID implementation in one European hospital demonstrates that RFID has the potential to transform asset management by improving inventory management, enhancing asset utilization, increasing staff productivity, improving care services, enhancing maintenance compliance, and increasing information visibility. Most importantly, RFID allows the emergence of intelligent asset management processes, which is, undoubtedly, the most important benefit that could be derived from the RFID system. Results show that the added intelligence can be rather basic (auto-status change) or a bit more advanced (personalized automatic triggers). More importantly, adding intelligence improves planning and decision-making processes.
Integrated computer-aided process engineering

Abstract This paper is a review of our multi-year experience in the formulation of support systems for the process engineering design office. It describes our own experiments, as well as evolving concepts inherited from the work of others that we think will ultimately underpin computer integrated process engineering.
Hypothermia for Intracranial Hypertension after Traumatic Brain Injury.

BACKGROUND
In patients with traumatic brain injury, hypothermia can reduce intracranial hypertension. The benefit of hypothermia on functional outcome is unclear.


METHODS
We randomly assigned adults with an intracranial pressure of more than 20 mm Hg despite stage 1 treatments (including mechanical ventilation and sedation management) to standard care (control group) or hypothermia (32 to 35°C) plus standard care. In the control group, stage 2 treatments (e.g., osmotherapy) were added as needed to control intracranial pressure. In the hypothermia group, stage 2 treatments were added only if hypothermia failed to control intracranial pressure. In both groups, stage 3 treatments (barbiturates and decompressive craniectomy) were used if all stage 2 treatments failed to control intracranial pressure. The primary outcome was the score on the Extended Glasgow Outcome Scale (GOS-E; range, 1 to 8, with lower scores indicating a worse functional outcome) at 6 months. The treatment effect was estimated with ordinal logistic regression adjusted for prespecified prognostic factors and expressed as a common odds ratio (with an odds ratio <1.0 favoring hypothermia).


RESULTS
We enrolled 387 patients at 47 centers in 18 countries from November 2009 through October 2014, at which time recruitment was suspended owing to safety concerns. Stage 3 treatments were required to control intracranial pressure in 54% of the patients in the control group and in 44% of the patients in the hypothermia group. The adjusted common odds ratio for the GOS-E score was 1.53 (95% confidence interval, 1.02 to 2.30; P=0.04), indicating a worse outcome in the hypothermia group than in the control group. A favorable outcome (GOS-E score of 5 to 8, indicating moderate disability or good recovery) occurred in 26% of the patients in the hypothermia group and in 37% of the patients in the control group (P=0.03).


CONCLUSIONS
In patients with an intracranial pressure of more than 20 mm Hg after traumatic brain injury, therapeutic hypothermia plus standard care to reduce intracranial pressure did not result in outcomes better than those with standard care alone. (Funded by the National Institute for Health Research Health Technology Assessment program; Current Controlled Trials number, ISRCTN34555414.).
On impulse noise and its models

This article gives a discussion on impulse noise, its models and how it affects communications systems. We discuss the different impulse noise models in the literature, looking at their similarities and differences in communications systems. The impulse noise models discussed are memoryless (Middleton Class A and Bernoulli-Gaussian), and with memory (Markov- Middleton and Markov-Gaussian). We then go further to give performance comparisons in terms of bit error rates for some of the variants of impulse noise models. We also compare the bit error rate performance of single-carrier (SC) and multi-carrier (MC) communications systems operating under impulse noise. It can be seen that MC is not always better than SC under impulse noise. Lastly, the known impulse noise mitigation schemes (clipping/nulling using thresholds, iterative based and error control coding methods) are discussed.
Volatility Information Trading in the Option Market

Investors can trade on positive or negative information about firms in either the stock or the option market, and a well-developed literature examines the use of options to make directional trades. Surprisingly, very little is known about option market trading on volatility information, despite the fact that options are uniquely suited for such trading. This paper investigates volatility trading in the equity option market. Two principal predictions of the hypothesis that investors bring volatility information to the option market are that net non-market maker demand for volatility is positively related to the future volatility of underlying stocks and that market makers protect themselves from informed volatility traders by raising (lowering) option prices in response to increases (decreases) in net volatility demand. Using a dataset that allows us to construct net non-market maker demand for volatility at the Chicago Board Options Exchange over the 1990 through 2001 period, we find strong empirical support for both of these predictions. We also present two additional results which each provide further confirmation for the proposition that investors bring volatility information to the option market. First, non-market maker net volatility demand constructed from transactions which open new option positions is a stronger predictor of the future volatility of underlying stocks than net volatility demand constructed from transactions which close existing option positions. Second, the impact on option prices from each unit of net non-market maker volatility demand significantly increases as informational asymmetry intensifies in the days leading up to earnings announcement dates. * Ni and Poteshman are at the University of Illinois at Urbana-Champaign, xni@uiuc.edu and poteshma@uiuc.edu. Pan is at the MIT Sloan School of Management and NBER, junpan@mit.edu. We thank Joe Levin, Eileen Smith, and Dick Thaler for assistance with the data used in his paper. We benefited from discussions with Joe Chen, Jun Liu, Josh Pollet, Dimitri Vayanos, Jiang Wang, and Josh White.
Methylphenidate in the management of asthenia in breast cancer patients treated with docetaxel: results of a pilot study

Background The objectives of this pilot study were to evaluate the safety and efficacy of the central nervous system stimulant methylphenidate in the management of asthenia in breast cancer patients treated with docetaxel. Patients and methods Patients with early breast cancer who presented asthenia >3 on the Visual Analogue Scale (VAS) after the first cycle of docetaxel-based chemotherapy were included. Patients received two additional cycles of chemotherapy, one with methylphenidate (10 mg bid) and the other without methylphenidate. Asthenia was evaluated using VAS and the Functional Assessment of Cancer Therapy-Fatigue (FACT-F) scale. Distress was assessed using the Hospital Anxiety and Depression Scale (HADS), and quality of life using FACT-F. Results Ten patients were included and evaluated for efficacy and safety. Overall, cycles with methylphenidate were better tolerated than those without methylphenidate in terms of asthenia (VAS, p = 0.004; FACT-F, p = 0.027) and quality of life (FACT-F, p = 0.047). No significant differences were observed in terms of distress (HADS, p = 0.297). Six (60%) patients continued with methylphenidate after study end. Main adverse events during study were palpitations and insomnia (30% of patients each). Conclusions This pilot study suggests that methylphenidate may reduce asthenia and improve quality of life in breast cancer patients treated with docetaxel.
Text Visualization for Visual Text Analytics

The term visual text analytics describes a class of information analysis techniques and processes that enable knowledge discovery via the use of interactive graphical representations of textual data. These techniques enable discovery and understanding via the recruitment of human visual pattern recognition and spatial reasoning capabilities. Visual text analytics is a subclass of visual data mining / visual analytics, which more generally encompasses analytical techniques that employ visualization of non-physically-based (or “abstract”) data of all types. Text visualization is a key component in visual text analytics. While the term “text visualization” has been used to describe a variety of methods for visualizing both structured and unstructured characteristics of text-based data, it is most closely associated with techniques for depicting the semantic characteristics of the free-text components of documents in large document collections. In contrast with text clustering techniques which serve only to partition text corpora into sets of related items, these so-called semantic mapping methods also typically strive to depict detailed interand intra-set similarity structure. Text analytics software typically couples semantic mapping techniques with additional visualization techniques to enable interactive comparison of semantic structure with other characteristics of the information, such as publication date or citation information. In this way, value can be derived from the material in the form of multidimensional relationship patterns existing among the discrete items in the collection. The ultimate goal of these techniques is to enable human understanding and reasoning about the contents of large and complexly related text collections.
Monitoring the macroscopic effect of DDoS flooding attacks

Creating defenses against flooding-based, distributed denial-of-service (DDoS) attacks requires real-time monitoring of network-wide traffic to obtain timely and significant information. Unfortunately, continuously monitoring network-wide traffic for suspicious activities presents difficult challenges because attacks may arise anywhere at any time and because attackers constantly modify attack dynamics to evade detection. In this paper, we propose a method for early attack detection. Using only a few observation points, our proposed method can monitor the macroscopic effect of DDoS flooding attacks. We show that such macroscopic-level monitoring might be used to capture shifts in spatial-temporal traffic patterns caused by various DDoS attacks and then to inform more detailed detection systems about where and when a DDoS attack possibly arises in transit or source networks. We also show that such monitoring enables DDoS attack detection without any traffic observation in the victim network.
A Re-evaluation of the Impact of Temperature Humidity Index ( THI ) and Black Globe Humidity Index ( BGHI ) on Milk Production in High Producing Dairy Cows

The temperature humidity index (THI) was originally developed for humans by Thom (1958) and extended to cattle by Berry et al (1964). It is currently used to estimate cooling requirements of dairy cattle in order to improve the efficiency of management strategies to alleviate heat stress. The Livestock Conservation Institute evaluated the biological responses to varying THI values and categorized them into mild, moderate and severe stress levels for cattle (Whittier, 1993; Armstrong, 1994). However, as pointed out by Berman (2005) the supporting data for these designations are not published. In addition, the index is based on a retrospective analysis of studies carried out at The University of Missouri in the 1950‘s and early 1960‘s on a total of 56 cows averaging 15.5 kg/d, (range 2.7-31.8 kg/d). In contrast, average production per cow in the United States is presently over 30 kg/d with many cows producing above 50 kg/d at peak lactation. The sensitivity of cattle to thermal stress is increased when milk production is increased thus reducing the ―threshold temperature‖ when milk loss begins to occur (Berman, 2005). This is due to the fact that metabolic heat output is increased as production levels of the animal increase. For example, the heat production of cows producing 18.5 and 31.6 kg/d of milk has been shown to be 27.3 and 48.5% higher than non-lactating cows (Purwanto et al., 1990). Research has shown that when milk production is increased to from 35 to 45 kg/d the threshold temperature for heat stress is reduced by 5°C (Berman, 2005). The physiological effects based on THI predictions on milk yield are currently underestimating the severity of heat stress on Holstein cattle. Radiant heat load and/or convection effects were not evaluated by Berry et al., (1964) and the majority of dairy cows care currently housed under a shade structure during heat stress months. Shade structures alleviate some of the radiant heat load there is still a conducive effect coming from the metal shade structure. In Israel, a typical shade structure is estimated to add 3°C to the effective ambient temperature surrounding the animals (Berman, 2005). The use of fans for cooling management systems causes varying convection levels under shade structures as well.
Differential privacy and robust statistics

We show by means of several examples that robust statistical estimators present an excellent starting point for differentially private estimators. Our algorithms use a new paradigm for differentially private mechanisms, which we call Propose-Test-Release (PTR), and for which we give a formal definition and general composition theorems.
Both hepatocyte growth factor (HGF) and stromal-derived factor-1 regulate the metastatic behavior of human rhabdomyosarcoma cells, but only HGF enhances their resistance to radiochemotherapy.

Rhabdomyosarcomas (RMSs) are frequently characterized by bone marrow involvement. Recently, we reported that human RMS cells express the CXC chemokine receptor-4 (CXCR4) and postulated a role for the CXCR4 stromal-derived factor (SDF)-1 axis in the metastasis of RMS cells to bone marrow. Because RMS cells also express the tyrosine kinase receptor c-MET, the specific ligand hepatocyte growth factor (HGF) that is secreted in bone marrow and lymph node stroma, we hypothesized that the c-MET-HGF axis modulates the metastatic behavior of RMS cells as well. Supporting this concept is our observation that conditioned media harvested from expanded ex vivo human bone marrow fibroblasts chemoattracted RMS cells in an HGF- and SDF-1-dependent manner. Six human alveolar and three embryonal RMS cell lines were examined. We found that although HGF, similar to SDF-1, did not affect the proliferation of RMS cells, it induced in several of them: (a) locomotion; (b) stress fiber formation; (c) chemotaxis; (d) adhesion to human umbilical vein endothelial cells; (e) trans-Matrigel invasion and matrix metalloproteinase secretion; and (f) phosphorylation of mitogen-activated protein kinase p42/44 and AKT. Moreover HGF, but not SDF-1, increased the survival of RMS cells exposed to radio- and chemotherapy. We also found that the more aggressive alveolar RMS cells express higher levels of c-MET than embryonal RMS cell lines and "home/seed" better into bone marrow after i.v. injection into immunocompromised mice. Because we could not find any activating mutations in the kinase region of c-MET or any evidence for HGF autocrine stimulation, we suggest that the increased response of RMS cell lines depends on overexpression of functional c-MET. We conclude that HGF regulates the metastatic behavior of c-MET-positive RMS cells, directing them to the bone marrow and lymph nodes. Signaling from the c-MET receptor may also contribute to the resistance of RMS cells to conventional treatment modalities.