nils-herrmann/clean_scirepeval huggingface dataset:
Identification and quantification of ageing mechanisms in Lithium ion batteries using the EIS technique
Venue: 2016 IEEE Transportation Electrification Conference and Expo (ITEC)

Ageing diagnosis in Lithium ion batteries is essential to ensure their reliability and optimum performance over time. The Battery Management System (BMS) usually monitors battery ageing with the aid of two metrics: capacity and power fade. However, these metrics do not identify the main root causes of battery ageing. Using the Electrochemical Impedance Spectroscopy technique, this work proposes a novel method to identify and quantify ageing mechanisms over time. The method is applied to four parallelised Lithium ion cells cycled with a constant driving profile for 500 cycles. As a result, Loss of Active Material (LAM) and Loss of Lithium Ions (LLI) were found to be the most pertinent ageing mechanisms over time for the four cells. Identification and quantification of ageing mechanisms will support novel battery lifetime control strategies within the BMS, so that potential failures during normal operation are prevented.
Variations and extension of the convex concave procedure

We investigate the convex concave procedure, a local heuristic that utilizes the tools of convex optimization to find local optima of difference of convex (DC) programming problems. The class of DC problems includes many difficult problems such as the traveling salesman problem. We extend the standard procedure in two major ways and describe several variations. First, we allow for the algorithm to be initialized without a feasible point. Second, we generalize the algorithm to include vector inequalities. We then present several examples to demonstrate these algorithms.
Demystifying the Secure Enclave Processor

The secure enclave processor (SEP) was introduced by Apple as part of the A7 SOC with the release of the iPhone 5S, most notably to support their fingerprint technology, Touch ID. SEP is designed as a security circuit configured to perform secure services for the rest of the SOC, with no direct access from the main processor. In fact, the secure enclave processor runs its own fully functional operating system dubbed SEPOS with its own kernel, drivers, services, and applications. This isolated hardware design prevents an attacker from easily recovering sensitive data (such as fingerprint information and cryptographic keys) from an otherwise fully compromised device. In this paper, we aim to shed some light the secure enclave processor and delve into the internals of SEPOS. In particular, we look at the SEPOS architecture itself and detail how the iOS kernel and the SEP exchange data using an elaborate mailbox mechanism. Furthermore, we show how this data is handled by SEPOS and relayed to its services and applications in order to allow iOS to interact with endpoints exposed by the SEP. Finally, we evaluate the SEP attack surface, its attack robustness, and highlight potential attack vectors.
Beginning Hybrid Mobile Application Development
Venue: Apress

With this hands on book, you'll learn how to create hybrid mobile apps using HTML 5, JQuery, and CSS3 that can be deployed on multiple platforms such as Android, iOS Windows Phone. Beginning Hybrid Mobile Application Development explains the top frameworks for hybrid app development along with the available APIs. You'll learn the internals of how hybrid apps work, why to choose JSON over XML, and how to access data in a hybrid app. And also you'll learn about the security issues in hybrid apps and secure coding guidelines.
Ascending Single Dose, Double Blind, Placebo Controlled Safety Study of Noribogaine in Opioid Dependent Patients
Venue: Clinical pharmacology in drug development

Ibogaine is a psychoactive substance that may reduce opioid withdrawal symptoms. This was the first clinical trial of noribogaine, ibogaine's active metabolite, in patients established on methadone opioid substitution therapy (OST) In this randomized, double blind, placebo controlled single ascending dose study, we evaluated the safety, tolerability, and pharmacokinetics of noribogaine in 27 patients seeking to discontinue methadone OST who had been switched to morphine during the previous week. Noribogaine doses were 60, 120, or 180 mg (n 6/dose level) or matching placebo (n 3/dose level) Noribogaine was well tolerated. The most frequent treatment emergent adverse events were noneuphoric changes in light perception ~1 hour postdose, headache, and nausea. Noribogaine had dose linear increases for AUC and Cmax and was slowly eliminated (mean t1/2 range, 24 30 hours) There was a concentration dependent increase in QTcI (0.17 ms/ng/mL) with the largest observed mean effect of ~16, 28, and 42 milliseconds in the 60 120 and 180 mg groups, respectively. Noribogaine showed a nonstatistically significant trend toward decreased total score in opioid withdrawal ratings, most notably at the 120 mg dose; however, the study design may have confounded evaluations of time to resumption of OST. Future exposure controlled multiple dose noribogaine studies are planned that will address these safety and design issues.
Oral noribogaine shows high brain uptake and anti withdrawal effects not associated with place preference in rodents
Venue: Journal of psychopharmacology

This study investigated the effects of noribogaine, the principal metabolite of the drug ibogaine, on substance related disorders. In the first experiment, mice chronically treated with morphine were subjected to naloxone precipitated withdrawal two hours after oral administration of noribogaine. Oral noribogaine dose dependently decreased the global opiate withdrawal score by up to 88% of vehicle control with an ED50 of 13 mg/kg. In the second experiment, blood and brain levels of noribogaine showed a high brain penetration and a brain/blood ratio of 7+ 1 across all doses tested. In a third experiment, rats given oral noribogaine up to 100 mg/kg were tested for abuse liability using a standard biased conditioned place paradigm. Noribogaine treated rats did not display place preference, suggesting that noribogaine is not perceived as a hedonic stimulus in rodents. Retrospective review of published studies assessing the efficacy of ibogaine on morphine withdrawal shows that the most likely cause of the discrepancies in the literature is the different routes of administration and time of testing following ibogaine administration. These results suggest that the metabolite noribogaine rather than the parent compound mediates the effects of ibogaine on blocking naloxone precipitated withdrawal. Noribogaine may hold promise as a non addicting alternative to standard opiate replacement therapies to transition patients to opiate abstinence.
Functional neurotoxicity evaluation of noribogaine using video EEG in cynomolgus monkeys.
Venue: Journal of pharmacological and toxicological methods

Continuous video electroencephalographic (EEG) monitoring remains the gold standard for seizure liability assessments in preclinical drug safety assessments. EEG monitored by telemetry was used to assess the behavioral and EEG effects of noribogaine hydrochloride (noribogaine) in cynomolgus monkeys. Noribogaine is an iboga alkaloid being studied for the treatment of opioid dependence.  Six cynomolgus monkeys (3 per gender) were instrumented with EEG telemetry transmitters. Noribogaine was administered to each monkey at both doses (i.e. 160 and 320mg/kg, PO) with an interval between dosing of at least 6days, and the resulting behavioral and EEG effects were evaluated. IV pentylenetetrazol (PTZ) served as a positive control for induced seizures.  The administration of noribogaine at either of the doses evaluated was not associated with EEG evidence of seizure or with EEG signals known to be premonitory signs of increased seizure risk (e.g. sharp waves, unusual synchrony, shifts to high frequency patterns) Noribogaine was associated with a mild reduction in activity levels, increased scratching, licking and chewing, and some degree of poor coordination and related clinical signs. A single monkey exhibited brief myoclonic movements that increased in frequency at the high dose, but which did not appear to generalize, cluster or to be linked with EEG abnormalities. Noribogaine was also associated with emesis and partial anorexia. In contrast, PTZ was associated with substantial pre ictal EEG patterns including large amplitude, repetitive sharp waves leading to generalized seizures and to typical post ictal EEG frequency attenuation.  EEG patterns were within normal limits following administration of noribogaine at doses up to 320mg/kg with concurrent clinical signs that correlated with plasma exposures and resolved by the end of the monitoring period. PTZ was invariably associated with EEG paroxysmal activity leading to ictal EEG. In the current study, a noribogaine dose of 320mg/kg was considered to be the EEG no observed adverse effect level (NOAEL) in conscious freely moving cynomolgus monkeys.
Flow Graph and Markovian Methods for Cyber Security Analysis
Venue: Int. J. Enterp. Inf. Syst.

A flow graph depicts the interrelationships among cyber security and security threats/incidents i.e. internal, external, and accidental. Using a flow graph, the manner in which security threats may affect systems can be investigated. This paper reports analytical approaches to analyze time to security threats and probability of security threat occurrence. Considering embedded threat detection functions in a safe guard unit, the proposed approaches use the flow graph concept, and Markovian method to calculate time to security threat occurrence and its probability. The threat detection functions are featured by incident detection and recovery mechanisms. The results of this study can be used by all parties public and private sector organizations, service providers, IT, and insurance companies to better deal with cyber security issues with respect to utilizing technology, investment, and insurance. An illustrative example is demonstrated to present the application of the approach.
Sampling for Bayesian Program Learning
Venue: NIPS

Towards learning programs from data, we introduce the problem of sampling programs from posterior distributions conditioned on that data. Within this setting, we propose an algorithm that uses a symbolic solver to efficiently sample programs. The proposal combines constraint based program synthesis with sampling via random parity constraints. We give theoretical guarantees on how well the samples approximate the true posterior, and have empirical results showing the algorithm is efficient in practice, evaluating our approach on 22 program learning problems in the domains of text editing and computer aided programming.
A comparative case study: Network agenda setting in crisis and non crisis news

In order to explore the Chinese traditional media role on social media platforms, this study examined the agenda setting effects between the networked attribute agendas of Chinese traditional media and various opinion leaders on Weibo in one crisis and non crisis news, respectively. The results showed that Chinese traditional media failed to lead the discussion on Weibo in both the crisis and non crisis cases. However, business elites tended to be the most influential opinion leaders in both circumstances. Furthermore, the news agendas of traditional media and the opinion leaders changed in both cases.
Gynecomastia in the Ancient Egypt limestone statue of Hemiunu, the architect of the Great Pyramid of Giza (fl. 2570 BC)
Venue: Journal of Endocrinological Investigation

is represented with marked signs of gynecomastia  The pathology is probably emphasized in an attempt to adhere to the androgynous model, regarded as attribute of divinity by Ancient Egyptian religion and philosophy  Interestingly, the endocrinological features are frequent in pictures and statues of the Ancient Egypt, such as "Seneb with his wife Senet and their children"  The present report follows previous publications appeared in this journal referring to ancient artistic representations of gynecomastia  The Roemerund Pelizaeus Museum Hildesheim of Hildesheim, Germany, hosts a large collection of Ancient Egyptian artworks, one of the most remarkable of which is the sculpture dedicated to Hemiunu (fl. 2570 BC) the architect of the Great Pyramid of Giza, Egypt. Nephew of the Pharaoh Kheops, as a member of the royal family, Hemiunu was a leading political figure of his time who served as vizier. In this limestone statue, discovered in 1912 in a monumental tomb in Giza, close to the royal pyramids, Hemiunu
Algorithmic Bias: From Discrimination Discovery to Fairness aware Data Mining
Venue: KDD

Algorithms and decision making based on Big Data have become pervasive in all aspects of our daily lives lives (offline and online) as they have become essential tools in personal finance, health care, hiring, housing, education, and policies. It is therefore of societal and ethical importance to ask whether these algorithms can be discriminative on grounds such as gender, ethnicity, or health status. It turns out that the answer is positive: for instance, recent studies in the context of online advertising show that ads for high income jobs are presented to men much more often than to women [Datta et al. 2015] and ads for arrest records are significantly more likely to show up on searches for distinctively black names [Sweeney, 2013] This algorithmic bias exists even when there is no discrimination intention in the developer of the algorithm. Sometimes it may be inherent to the data sources used (software making decisions based on data can reflect, or even amplify, the results of historical discrimination) but even when the sensitive attributes have been suppressed from the input, a well trained machine learning algorithm may still discriminate on the basis of such sensitive attributes because of correlations existing in the data. These considerations call for the development of data mining systems which are discrimination conscious by design. This is a novel and challenging research area for the data mining community. The aim of this tutorial is to survey algorithmic bias, presenting its most common variants, with an emphasis on the algorithmic techniques and key ideas developed to derive efficient solutions. The tutorial covers two main complementary approaches: algorithms for discrimination discovery and discrimination prevention by means of fairness aware data mining. We conclude by summarizing promising paths for future research.
Thermo compression molding of chitosan with a deep eutectic mixture for biofilms development

A eutectic mixture of choline chloride (ChCl) and citric acid (CA) was successfully used for the preparation of chitosan (Chit) bio films by thermo compression molding. Optimization of the film preparation conditions was carried out using response surface methodology and a Box Behnken design based on the best mechanical properties and lowest energetic requirements (lower compression load and time) The optimum film, made with chitosan and ChCl CA (eutectic mixture) was compared with films prepared using only CA in their formulation. Chit ChCl CA films presented higher elasticity, opacity and total color difference, and a lower tensile strength in relation to the Chit CA films. Films prepared with the eutectic mixture presented higher water vapor permeability values. These results were associated with the films microstructures. FTIR analysis confirms the occurrence of chemical changes in the processed films. The thermo compression process significantly affects the crystallinity of the pristine chitosan. The films thermal stability is depressed when compared to the stability of each component.
Acute Respiratory Distress Syndrome
Venue: Critical care nursing quarterly

Acute respiratory distress syndrome (ARDS) is a serious inflammatory disorder with high mortality. Its main pathologic mechanism seems to result from increased alveolar permeability. Its definition has also changed since first being described according to the Berlin definition, which now classifies ARDS on a severity scale based on PaO2 (partial pressure of oxygen, arterial)/FIO2 (fraction of inspired oxygen) ratio. The cornerstone of therapy was found to be a low tidal volume strategy featuring volumes of 6 to 8 mL per kg of ideal body weight that has been shown to have decreased mortality as proven by the ARDSnet trials. There are other areas of treatment right now that include extracorporeal membrane oxygenation, as well for severe refractory hypoxemia. Other methods that include prone positioning for ventilation have also shown improvements in oxygenation. Positive end expiratory pressure with lung recruitment maneuvers has also been found to be helpful. Other therapies that include vasodilators and neuromuscular agents are still being explored and need further studies to define their role in ARDS.
Towards Learning from Implicit Human Reward: (Extended Abstract)
Venue: AAMAS

The TAMER framework provides a way for agents to learn to solve tasks using human generated rewards. Previous research showed that humans give copious feedback early in training but very sparsely thereafter and that an agent's competitive feedback informing the trainer about its performance relative to other trainers can greatly affect the trainer's engagement and the agent's learning. In this paper, we present the first large scale study of TAMER, involving 561 subjects, which investigates the effect of the agent's competitive feedback in a new setting as well as the potential for learning from trainers' facial expressions. Our results show for the first time that a TAMER agent can successfully learn to play Infinite Mario, a challenging reinforcement learning benchmark problem. In addition, our study supports prior results demonstrating the importance of bi directional feedback and competitive elements in the training interface. Finally, our results shed light on the potential for using trainers' facial expressions as reward signals, as well as the role of age and gender in trainer behavior and agent performance.
Mass production of CNTs using CVD multi quartz tubes

Carbon nanotubes (CNTs) have become the backbone of modern industries, including lightweight and heavy duty industrial applications. Chemical vapor deposition (CVD) is considered as the most common method used to synthesize high yield CNTs. This work aims to develop the traditional CVD for the mass production of more economical CNTs, meeting the growing CNT demands among consumers by increasing the number of three particular reactors. All reactors housing is connected by small channels to provide the heat exchange possibility between the chambers, thereby decreasing synthesis time and reducing heat losses inside the ceramic body of the furnace. The novel design is simple and cheap with a lower reacting time and heat loss compared with the traditional CVD design. Methane, hydrogen, argon, and catalyzed iron nanoparticles were used as a carbon source and catalyst during the synthesis process. In addition, CNTs were produced using only a single quartz tube for comparison. The produced samples were examined using XRD, TEM, SEM, FTIR, and TGA. The results showed that the yield of CNTs increases by 287 compared with those synthesized with a single quartz tube. Moreover, the total synthesis time of CNTs decreases by 37 because of decreased heat leakage.
Optical investigation of reduced graphene oxide and reduced graphene oxide/CNTs grown via simple CVD method

Reduced graphene oxide carbon nanotube (rGO CNT) hybrid materials have been prepared via a simple CVD method. The photoluminescence (PL) properties of rGO CNTs were investigated and compared with reduced graphene oxide. The results suggest that unlike rGO, rGO CNTs possess a multicolor PL spectrum. Consequently, thanks to its unique optical properties, rGO CNT can be a potential candidate in the fields of photonic and electronic materials.
Fabrication of MnO@C CNTs composite by CVD for enhanced performance of lithium ion batteries

A novel MnO@Amorphous C Carbon nanotubes (MnO@C CNTs) composite is prepared by chemical vapor deposition (CVD) When used as an anode material for Li ion batteries, the MnO@C CNTs composite exhibits an initial discharge capacity of 1164 mA h g 1 at 100 mA g 1 and the discharge capacity gradually increased from 571.7 mA h g 1 to 654 mA h g 1 after 100 cycles at 1 A g 1 which shows an increase of the capacity rather than attenuation. Furthermore, the MnO@C CNTs electrode can deliver a capacity of up to 228 mA h g 1 at 5 A g 1 These results indicate that the three dimensional conductive network of the MnO@C CNTs composite could prevent the aggregation of MnO particles, and its open structure allows electrolyte penetration, and reduces the diffusion path of the lithium ions, hence maximizes utilization of the electrochemically active MnO particles, while enhances the conductivity of electrode material and Li transport. This work offers a universal approach to design various metal oxides@C CNTs composite.
CVD Grown CNTs on Basalt Fiber Surfaces for Multifunctional Composite Interphases

Chemical vapor deposition (CVD) is used as a method for the synthesis of carbon nanotubes (CNT) on substrates, most commonly pre treated by a metal catalyst. In this work, the capability of basalt fiber surfaces was investigated in order to stimulate catalyst free growth of carbon nanotubes. We have carried out CVD experiments on unsized, sized, and NaOH treated basalt fibers modified by growth temperature and a process gas mixture. Subsequently, we investigated the fiber surfaces by SEM, AFM, XPS and carried out single fiber tensile tests. Growth temperatures of 700 degC as well as 800 degC may induce CNT growth, but depending on the basalt fiber surface, the growth process was differently affected. The XPS results suggest surficial iron is not crucial for the CNT growth. We demonstrate that the formation of a corrosion shell is able to support CNT networks. However, our investigations do not expose distinctively the mechanisms by which unsized basalt fibers sometimes induce vertically aligned CNT carpets, isotropically arranged CNTs or no CNT growth. Considering data from the literature and our AFM results, it is assumed that the nano roughness of surfaces could be a critical parameter for CNT growth. These findings will motivate the design of future experiments to discover the role of surface roughness as well as surface defects on the formation of hierarchical interphases.