batterydata/paper-abstracts huggingface dataset:
The objective of the present study was to examine the relationship between cognitive performance, driver perceptions and self-reported driving restrictions. A cross-sectional analysis was conducted on baseline data from Candrive II, a five-year prospective cohort study of 928 older drivers aged 70–94 years from seven cities. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA) as well as the Trail Making Test, parts A and B. Driver perceptions were assessed using the Day and Night Driving Comfort Scales and the Perceived Driving Abilities scale, while driving practices were captured by the Situational Driving Frequency and Avoidance scales, as well as the Driving Habits and Intentions Questionnaire. The baseline data indicates this cohort is largely a cognitively intact group. Univariate regression analysis showed that longer Trails A and B completion times were significantly, but only modestly associated with reduced driving frequency and perceived driving abilities and comfort, as well as a significant tendency to avoid more difficult driving situations (all p <.05). Most of these associations persisted after adjusting for age and sex, as well as indicators of health, vision, mood and physical functioning. Exceptions were Trails A and B completion times and situational driving frequency, as well as time to complete Trails B and current driving restrictions. After adjusting for the confounding factors, the total MoCA score was not associated with any of the driving measure scores while the number of errors on Trails A was significantly associated only with situational driving frequency and number of errors on Trails B was significantly associated only with situational driving avoidance. Prospective follow-up will permit examination of whether baseline cognition or changes in cognition are associated with changes in driver perceptions, actual driving restrictions and on-road driving outcomes (e.g., crashes, violations) over time.
A typical state-of-the-art Li cathode is a composite material consisting of many (nano) phases so its overall kinetics can be extremely sophisticated. In this paper we first show how one can identify selected important kinetic steps that may crucially affect the overall electrode performance. Based on relatively simple concepts supported with selected model experiments, we also give several practical recipes that might be helpful for designing of cathodes with improved overall kinetics.
The envelope glycoprotein complex (Env) of human immunodeficiency virus-1 (HIV-1) can induce apoptosis by a cornucopia of distinct mechanisms. A soluble Env derivative, gp120, can kill cells through signals that are transmitted by chemokine receptors such as CXCR4. Cell surface-bound Env (gp120/gp41), as present on the plasma membrane of HIV-1-infected cells, can kill uninfected bystander cells expressing CD4 and CXCR4 (or similar chemokine receptors, depending on the Env variant) by at least three different mechanisms. First, a transient interaction involving the exchange of lipids between the two interacting cells (‘the kiss of death’) may lead to the selective death of single CD4-expressing target cells. Second, fusion of the interacting cells may lead to the formation of syncytia which then succumb to apoptosis in a complex pathway involving the activation of several kinases (cyclin-dependent kinase-1, Cdk1; checkpoint kinase-2, Chk2; mammalian target of rapamycin, mTOR; p38 mitogen-activated protein kinase, p38 MAPK; inhibitor of NF-κB kinase, IKK), as well as the activation of several transcription factors (NF-κB, p53), finally resulting in the activation of the mitochondrial pathway of apoptosis. Third, if the Env-expressing cell is at an early stage of imminent apoptosis, its fusion with a CD4-expressing target cell can precipitate the death of both cells, through a process that may be considered as contagious apoptosis and which does not involve Cdk1, mTOR, p38 nor p53, yet does involve mitochondria. Activation of some of the above- mentioned lethal signal transducers have been detected in patients’ tissues, suggesting that HIV-1 may indeed trigger apoptosis through molecules whose implication in Env-induced killing has initially been discovered in vitro.
Background The authors aimed to determine whether electrical dental devices would interfere with the function of cardiac pacemakers or implantable cardioverter defibrillators (ICDs) in humans. Methods The authors exposed asymptomatic nonpacemaker-dependent patients to commonly used electrical dental equipment (for example, battery-operated curing lights, ultrasonic baths, ultrasonic scalers, electric pulp testers, and electric toothbrushes) in an outpatient cardiology clinic. The authors operated dental devices at various distances and programmed cardiac devices to sense and pace. The authors obtained cardiac tracings using a cardiac programming unit and a cardiac provider who noted any interference interpreted the results in real time. Results The authors enrolled 32 consecutive patients and tested 12 pacemakers and 20 ICDs. They did not observe any significant clinical interference in sensing and pacing functions in any patient; however, they noted minor interference without clinical impact in the telemetry from the cardiac programming unit during use of the ultrasonic scaler and bath. Conclusions The findings of this prospective study suggest that electrical devices commonly used in dental practices do not interfere with the sensing and pacing of contemporary cardiac patients’ pacemakers or ICDs. However, they do interfere with the telemetry from the cardiac programming unit, without any clinical impact on patient safety. These findings should help in the development of clinical guidelines regarding dental management of patients with pacemakers or ICDs. Practical Implications Electrical dental devices (for example, ultrasonic baths, ultrasonic scalers) induced minor interference with programmers that interrogate cardiac devices implanted in patients; however, overall, dental devices do not appear to interfere with pacemakers’ and defibrillators’ pacing and sensing function.
Malnutrition has been linked to serious complications in patients undergoing elective total joint arthroplasty (TJA). This study prospectively evaluated 2,161 patients undergoing elective TJA for malnutrition as defined by either an abnormal serum albumin or transferrin. The overall incidence of malnutrition was 8.5% (184 of 2,161) and the rate of overall complications in the malnourished group was 12% as compared to 2.9% in patients with normal parameters (P <0.0001). Malnutrition predicted serious complications involving hematoma formation, infection, renal and cardiac complications. Obesity, defined by a body mass index (BMI) of 30kg/m2 was present in 42.9% of malnourished patients with a significantly higher complication rate in this cohort. Malnutrition remains prevalent in patients >55years-old undergoing TJA and is associated with a significant increase in post-operative complications.
Slippage of the wires over the opposite cortex from the endosteal side is frequent and can lead to insufficient stability. This in vitro biomechanical study was planned to investigate the angle of wire insertion that leads to trans cortex perforation.
An electrochemical impedance investigation is made on the first lithium intercalation kinetics of mesocarbon microbeads (MCMB) heat-treated at high temperature (2800°C) as the lithium intercalation electrode in a gel electrolyte. The gel electrolyte is synthesized from a mixture containing the reactive monomers in an organic solution. Once the charge of lithium ion proceeds, a solid electrolyte interface (SEI) is formed on the MCMB electrode, and its thickness increases during charging. The growth of SEI resistance is indicated by means of ac impedance measurements. Studies on a MCMB electrode stored in its fully intercalated state showed that part of the extra charge consumed during prolonged storage could be attributed to deintercalation of lithium from the MCMB bulk and its subsequent reaction with electrolyte.
A modified self-extinguishing time (SET) device which enhances the reproducibility of the results is presented. Pentafluoro(phenoxy)cyclotriphosphazene (FPPN) is investigated as flame retardant electrolyte additive for lithium ion batteries (LIBs) in terms of thermal stability and electrochemical performance. SET measurements and adiabatic reaction calorimetry are applied to determine the flammability and the reactivity of a standard LIB electrolyte containing 5% FPPN. The results reveal that the additive-containing electrolyte is nonflammable for 10 s whereas the commercially available reference electrolyte inflames instantaneously after 1 s of ignition. The onset temperature of the safety enhanced electrolyte is delayed by ≈ 21 °C. Compatibility tests in half cells show that the electrolyte is reductively stable while the cyclic voltammogram indicates oxidative decomposition during the first cycle. Cycling experiments in full cells show improved cycling performance and rate capability, which can be attributed to cathode passivation during the first cycle. Post-mortem analysis of the electrolyte by gas chromatography-mass spectrometry confirms the presence of the additive in high amounts after 501 cycles which ensures enhanced safety of the electrolyte. The investigations present FPPN as stable electrolyte additive that improves the intrinsic safety of the electrolyte and its cycling performance at the same time.
Deposition of Lithium metal on anodes contributes significantly to ageing of Li-ion cells. Lithium deposition is connected not only to a drastic limitation of life-time, but also to fast-charging capability and safety issues. Lithium deposition in commercial Li-ion cells is not limited to operation conditions at low temperatures. In recent publications various types of commercial cells were investigated using complimentary analysis methods. Five cell types studied in literature (18650, 26650, pouch) serve as a basis for comparison when and why Li deposition happens in commercial Li-ion cells. In the present paper, we reviewed literature on (i) causes, (ii) hints and evidences for Li deposition, (iii) macroscopic morphology of Li deposition/plating, (iv) ageing mechanisms and shapes of capacity fade curves involving Li deposition, and (v) influences of Li deposition on safety. Although often discussed, safety issues regarding Li deposition are not only limited to dendrite growth and internal short circuits, but also to exothermic reactions in the presence of Lithium metal. Furthermore, we tried to connect knowledge from different length scales including the macroscopic level (Li-ion cells, operating conditions, gradients in cells, electrochemical tests, safety tests), the microscopic level (electrodes, particles, microstructure), and the atomic level (atoms, ions, molecules, energy barriers).
Adolescence is a period of significant brain changes; however, the effects of age and sex on cortical development are yet to be fully characterized. Here, we utilized innovative intrinsic curvature (IC) analysis, along with the traditional cortical measures [cortical thickness (CT), local gyrification index (LGI), and surface area (SA)], to investigate how these indices (1) relate to each other and (2) depend on age and sex in adolescent cortical development. T1-weighted magnetic resonance images from 218 healthy volunteers (age range 8.3–29.2 years, M[SD] = 16.5[3.4]) were collected at two sites and processed with FreeSurfer and Caret software packages. Surface indices were extracted per cortex area (frontal, parietal, occipital, temporal, insula, and cingulate). Correlation analyses between the surface indices were conducted and age curves were modelled using generalized additive mixed-effect models. IC showed region-specific associations with LGI, SA, and CT, as did CT with LGI. SA was positively associated with LGI in all regions and CT in none. CT and LGI, but not SA, were inversely associated with age in all regions. IC was inversely associated with age in all but the occipital region. For all regions, males had larger cortical SA than females. Males also had larger LGI in all regions and larger IC of the frontal area; however, these effects were accounted for by sex differences in SA. There were no age-by-sex interactions. The study of IC adds a semi-independent, sensitive measure of cortical morphology that relates to the underlying cytoarchitecture and may aid understanding of normal brain development and deviations from it.
Composite solid electrolytes are attractive as they combine the high ionic conductivity of ceramic nanoparticles and the excellent mechanical properties of polymer electrolytes. Vertically aligned ceramic nanoparticles in the polymer matrix represent an ideal structure for maximizing ionic conductivity of composite electrolytes. The ice-templating method was used to build rechargeable solid-state lithium metal batteries with a vertically aligned ceramic/polymer composite electrolyte composed of high ionic conductivity Li1.5Al0.5Ge1.5(PO4)3 (LAGP) and polyethylene oxide (PEO) polymer. The vertical LAGP walls provide continuous channels for fast ionic transport, while the PEO matrix renders the composite electrolyte flexible. This solid-state composite electrolyte has a conductivity of 1.67 × 10−4 S cm−1 at room temperature and 1.11 × 10−3 S cm−1 at 60 °C. LiFePO4 (LFP)/vertically aligned LAGP- PEO/Li full cells were also developed with a high capacity retention of 93.3% after 300 cycles. This study demonstrates the successful application of vertically aligned ceramic/polymer composite electrolytes for solid-state batteries with high performance.
A series of carbon-coated layered structured Li[Cr x Li(1/3−x/3)Ti(2/3−2x/3)]O2 samples (0.3≤ x ≤0.45) were prepared. Among them, the sample of x =0.4 shows the highest initial reversible capacity of 207mAhg−1 at 30mAg−1 in 2.5–4.4V. The reversible Li-storage capacities for the samples with high x values (x =0.4, 0.45) faded slightly while the samples with low Cr content (x =0.3 and 0.35) showed a capacity increase upon cycling. It was found that the relative intensity ratio of (003) peak to (104) peak (R (003) = I (003)/I (104)) is influenced strongly by x value in as-prepared samples. The samples of x =0.35 and 0.4 turn to a similar structure with low R (003) value during cycling. These phenomena indicate that the cation mixing of Cr3+ in the lithium layer occurs in as-prepared samples and became more significant upon delithiation and lithiation. This is supposed being a necessary process for Cr-based layered structure materials possessing electrochemical reactivates. The occurrence of the cation mixing is beneficial from the local lattice distortion caused by the short-range ordering between Ti and Li. This is supposed to be helpful for the migration of Cr6+ and Cr3+ at tetrahedral and octahedral sites. Different from the case of LiNiO2, the cation mixing is essential for the transport and storage of lithium in the carbon-coated Li–Cr–Ti–O layered compounds.
Energy efficiency in wireless and cellular networks has become one of the most important concerns for both academia and industry due to battery dependence of mobile devices. In this regard, Wireless Network Interface Cards (WNICs) of mobile devices have to be taken into account carefully as they consume an important chunk of the system's total energy. In this paper, we propose a real-time network power consumption profiler and an energy-aware network/interface selection tool for Android-based smartphones. The tool has been freely released on the Android Play Store. The proposed solution reports the power consumption levels of different network interfaces (Wi-Fi and Cellular) by making use of actual packet measurements and precise computations, and enables the devices to handover horizontally/vertically in order to improve the energy efficiency. In this context, widespread analyses have been executed to show the accuracy of the proposed tool. The results demonstrate that the proposed tool is very accurate for any type of IEEE 802.11 wireless or cellular stations, regardless of having different amount of channel utilization, transmission rates, signal strengths or traffic types.
Abstract We analyse the different components that are part of the heating, domestic hot water (DHW) and air conditioning facilities. For each of these components we show the conventional equations of conservation of mass and energy and from them exergy balances, as well as the corresponding expressions to characterize their efficiency, both through conventional energy performance and with exergy. Later, we look at cogeneration facilities, undertaking a review of micro-cogeneration technologies and then presenting the energy and exergy parameters with which the behaviour of these technologies is characterized. We end the chapter looking at equipment, such as energy storage systems, that must be analysed as dynamic systems due to its inherent properties. After a conventional energy analysis in the three phases of loading, storage and discharge, we characterize its behaviour through exergy analysis, highlighting the usefulness of this analysis and the additional information that it provides.
Silicon nanowires with hydride, methyl and siloxane surfaces terminations were evaluated as anodes in lithium-ion half cells using LiPF6 in EC/DMC electrolytes. Voltammetry, FT-IR and XPS analyses show hydride-terminated nanowires react with the electrolyte and methyl termination tends to passivate silicon surfaces. Silicon anodes pretreated with trimethoxymethylsilane show decreased lithium capacities similar to methylated anodes; however, the addition of 5% trimethoxymethylsilane as an electrolyte additive resulted in the formation of significantly more OPFx compounds while improving capacity retention relative to hydride-terminated nanowires (2348mAhg−1 at 15 cycles at C/10 rates). FTIR analysis show trimethoxymethylsilane additives covalently bond silicon surfaces and other SEI components. AFM nano-indentation tests also suggest the alkoxy silane additives in the electrolyte function as a binder to improve silicon's ability to withstand the large reversible volume changes. The results indicate silicon surface terminations play a key role in chemical and mechanical behaviors that control reversibility.
Sensor data quality plays a vital role in Internet of Things (IoT) applications as they are rendered useless if the data quality is bad. This systematic review aims to provide an introduction and guide for researchers who are interested in quality-related issues of physical sensor data. The process and results of the systematic review are presented which aims to answer the following research questions: what are the different types of physical sensor data errors, how to quantify or detect those errors, how to correct them and what domains are the solutions in. Out of 6970 literatures obtained from three databases (ACM Digital Library, IEEE Xplore and ScienceDirect) using the search string refined via topic modelling, 57 publications were selected and examined. Results show that the different types of sensor data errors addressed by those papers are mostly missing data and faults e.g. outliers, bias and drift. The most common solutions for error detection are based on principal component analysis (PCA) and artificial neural network (ANN) which accounts for about 40% of all error detection papers found in the study. Similarly, for fault correction, PCA and ANN are among the most common, along with Bayesian Networks. Missing values on the other hand, are mostly imputed using Association Rule Mining. Other techniques include hybrid solutions that combine several data science methods to detect and correct the errors. Through this systematic review, it is found that the methods proposed to solve physical sensor data errors cannot be directly compared due to the non-uniform evaluation process and the high use of non-publicly available datasets. Bayesian data analysis done on the 57 selected publications also suggests that publications using publicly available datasets for method evaluation have higher citation rates.
Despite the large body of work on fingerprint identification systems, most of it focused on using specialized devices. Due to the high price of such devices, some researchers directed their attention to digital cameras as an alternative source for fingerprints images. However, such sources introduce new challenges related to image quality. Specifically, most digital cameras compress captured images before storing them leading to potential losses of information. This study comes to address the need to determine the optimum ratio of the fingerprint image compression to ensure the fingerprint identification system’s high accuracy. This study is conducted using a large in-house dataset of raw images. Therefore, all fingerprint information is stored in order to determine the compression ratio accurately. The results proved that the used software functioned perfectly until a compression ratio of (30–40%) of the raw images; any higher ratio would negatively affect the accuracy of the used system.
We produce the first systematic study of the determinants and implications of in-person banking. Using survey data from the U.S., we show that firms which are informationally opaque or operate in rural areas are liable to contact their primary bank in-person. This tendency extends to older, less educated, and female business owners. We find that a relationship based on face-to-face communication, on average, lasts 17.88 months longer, spans a wider range of financial services, and is more likely to be exclusive. The associated loans mature 3.37 months later and bear interest rates which are 11 basis points lower. For good quality firms, in-person communication also relates to less discouraged borrowing. These results are robust to multiple approaches for endogeneity, including recursive bivariate probits, treatment effect models, and instrumental variables regressions. Overall, our findings offer empirical grounding to soft information theory and a note of caution to banks against suppressing channels of interpersonal communication.
Abstract The fitting of impedance models to measured data is an essential step in impedance spectroscopy (IS). Due to often complicated, nonlinear models, big number of parameters, large search spaces and presence of noise, an automated determination of the unknown parameters is a challenging task. The stronger the nonlinear behavior of a model, the weaker is the convergence of the corresponding regression and the probability to trap into local minima increases during parameter extraction. For fast measurements or automatic measurement systems these problems became the limiting factors of use. We compared the usability of stochastic algorithms, evolution, simulated annealing and particle filter with the widely used tool LEVM for parameter extraction for IS. The comparison is based on one reference model by J.R. Macdonald and a battery model used with noisy measurement data. The results show different performances of the algorithms for these two problems depending on the search space and the model used for optimization. The obtained results by particle filter were the best for both models. This method delivers the most reliable result for both cases even for the ill posed battery model.