LLukas22/scidocs huggingface dataset:
Systematic evaluation of supported liquid extraction in reducing matrix effect and improving extraction efficiency in LC-MS/MS based bioanalysis for 10 model pharmaceutical compounds.

In past a few years, there has been a large increase in the application of supported liquid extraction (SLE) for LC-MS/MS based bioanalysis due to its distinct practical advantage in reduced time cost, ease of operation and the feasibility for automation. The main purpose of this study was to systematically evaluate supported liquid extraction in reducing matrix effect and improving extraction efficiency/recovery under various extraction conditions with 10 model pharmaceutical compounds in liquid chromatography coupled to electrospray tandem mass spectrometry (LC-ESI-MS/MS) analysis. Selected compounds have diverse physicochemical properties where logP ranges from 0.1 to 6.24 and pK(a) ranges from 4.0 to 11.1. The factors that may have the impact on the recovery of analytes and phospholipids (PL) were assessed. Over 75% recovery was achieved for every analyte under its respectively optimized extraction conditions where the selection of the polarity of extraction solvent and buffered pH can be critical for efficient recovery. Furthermore, the matrix effect was assessed by postextraction spike and postcolumn infusion method. The matrix effect was considerably reduced for all analytes under most extraction conditions evaluated for SLE, compared with protein precipitation (PPT) method. The correlation between matrix effect and residual phospholipids in sample extract was clearly shown. Although analyte-dependent matrix effect was observed prominently in sample extract prepared by PPT, it was minimized by SLE sample preparation process that effectively removes the majority of phospholipids. Sample extracted by ethyl acetate contained more phospholipids and demonstrated stronger matrix effect than by other organic solvents. Water-miscible organic content, such as methanol and acetonitrile in samples prior to loading has significant impact on PL recovery when eluting with methyl tert-butyl ether. However, isopropanol does not enhance the recovery of PL when adding to dichloromethane for elution. In addition, the compromise between improved extraction efficiency by SLE and reduced matrix effect is sometimes necessary to yield clean extract with acceptable recovery. The effective removal of phospholipids and reduction of matrix effect, while achieving good recovery for all pharmaceutical compounds with diverse physicochemical properties, demonstrated that SLE is a valuable alternative technique to liquid-liquid extraction (LLE) in high throughput LC-MS/MS based bioanalysis.
Do race-specific definitions of short long bones improve the detection of down syndrome on second-trimester genetic sonograms?

OBJECTIVE
The purpose of this study was to determine whether the use of race-specific definitions of short femur and humerus lengths improves Down syndrome detection.


METHODS
This was a retrospective cohort study over 16 years. For each self-reported maternal race (white, African American, Hispanic, and Asian), we evaluated the efficiency of Down syndrome detection using published race-specific formulas compared with a standard formula for short femur and humerus lengths (observed versus expected lengths < or =0.91 and < or =0.89, respectively). The sensitivity, specificity, and 95% confidence intervals for each parameter were compared. Screening performance was compared by areas under the receiver operating characteristic curves.


RESULTS
Of 58,710 women, 209 (0.3%) had a diagnosis of a fetus with Down syndrome. Although the race-based formula increased sensitivity in each population, the increase was statistically significant only in the white population, whereas a decrease in specificity was statistically significant in all 4 populations, as denoted by nonoverlapping confidence intervals. The area under the receiver operating characteristic curve for the model using the race-specific definition of short femur length was 0.67 versus 0.65 compared with the standard definition, and for humerus length it was 0.70 versus 0.71.


CONCLUSIONS
The use of race-based formulas for the determination of short femur and humerus lengths did not significantly improve the detection rates for Down syndrome.
Brain–machine interfaces to restore motor function and probe neural circuits

Recent studies have shown that it is possible to create functional, bidirectional, real-time interfaces between living brain tissue and artificial devices. It is reasonable to predict that further research on brain–machine interfaces will lead to the development of a new generation of neuroprosthetic devices aimed at restoring motor functions in severely paralysed patients. In addition, I propose that such interfaces can become the core of a new experimental approach with which to investigate the operation of neural systems in behaving animals.
A finite difference model for air pollution simulation

A 3-D model for atmospheric pollutant transport is proposed considering a set of coupled convection–diffusion–reaction equations. The convective phenomenon is mainly produced by a wind field obtained from a 3-D mass consistent model. In particular, the modelling of oxidation and hydrolysis of sulphur and nitrogen oxides released to the surface layer is carried out by using a linear module of chemical reactions. The dry deposition process, represented by the so-called deposition velocity, is introduced as a boundary condition. Moreover, the wet deposition is included in the source term of the governing equations using the washout coefficient. Before obtaining a numerical solution, the problem is transformed using a terrain conformal coordinate system. This allows to work with a simpler domain in order to build a mesh that provides finite difference schemes with high spatial accuracy. The convection–diffusion–reaction equations are solved with a high order accurate time-stepping discretization scheme which is constructed following the technique of Lax and Wendroff. Finally, the model is tested with a numerical experiment in La Palma Island (Canary Islands). 2006 Elsevier Ltd. and Civil-Comp Ltd. All rights reserved.
Nonintrusive Biosignal Measurement System in a Vehicle

Measurement of driver's state is important in both daily healthcare and prevention of car accidents. Existing measurement methods, however, are too complex and uncomfortable to measure for everyday. A nonintrusive biosignal monitoring system is demanded for increasing the accessibility. In this paper, we proposed a nonintrusive measurement system integrated in a vehicle for recording electrocardiographic (ECG) signals and tested the performance of the system. The system consists of dry electrodes attached to the steering wheel and a wireless communication module using a Bluetooth device. ECG signals measured by our system were compared with those by a conventional system employing wet electrodes during real city road driving. Various parameters used for HRV analysis in time and frequency domain showed no significant differences between the two simultaneously measured ECG signals. The result implies the possibility that developed system could have a potential to monitor health information in a vehicle instead of commercial equipments.
An Unusual Association of Odontomas with Primary Teeth

Odontomas generally appear as small, solitary or multiple radio-opaque lesions found on routine radiographic examinations. Traditionally, odontomas have been classified as benign odontogenic tumors and are subdivided into complex or compound odontomas morphologically. Compound odontomas commonly occur in the incisor-canine region of the maxilla and complex odontomas are frequently located in the premolar and molar region of both jaws. Occasionally, odontoma may cause disturbances in the eruption of teeth such as impaction, delay eruption or retention of primary teeth. In general, odontomas occur more often in the permanent dentition and are very rarely associated with the primary teeth. In this report; two cases of compound odontoma associated with primary teeth is presented. (Eur J Dent 2007;1:45-49).
When true memory availability promotes false memory: Evidence from confabulating patients

We explored the extent to which confabulators are susceptible to false recall and false recognition, and whether false recognition is reduced when memory for studied items is experimentally enhanced. Five confabulating patients, nine non-confabulating amnesics--including patients with (F amnesics) and without frontal-lobe dysfunction (NF amnesics)--and 14 control subjects underwent the DRM paradigm [Roediger, H. L., & McDermott, K. B. (1995). Creating false memories: Remembering words not presented in lists. Journal of Experimental Psychology: Learning, Memory and Cognition, 21, 803-814.] in two experimental conditions. In both conditions participants studied eight lists of semantic associates, and free recall was tested after the presentation of each list. In the Standard condition recognition was tested after the presentation of all the lists, whereas in the Proximal condition patients were administered a six-item recognition task after the presentation of each list. Participants also provided remember or know judgements, and described the content of their recollections. All groups of patients recalled a lower proportion of targets and critical lures than did control subjects, but confabulators recalled more words unrelated to the studied lists than did NF amnesics and controls. All groups of participants improved true recognition across conditions. However, whereas normal controls suppressed false recognition to critical lures in the Proximal compared to the Standard condition, and non-confabulating amnesics showed comparable gist-based false recognition, confabulators showed increased levels of false recognition to critical lures across conditions. Furthermore, NF amnesics significantly reduced false recognition to unrelated lures in the Proximal compared to the Standard condition, whereas confabulators were unable to suppress false recognition to unrelated lures across conditions. Analysis of the phenomenological experience showed that, unlike non-confabulating amnesics, confabulators characterized true and false memories with irrelevant information related to test items. Results are interpreted in light of confabulators' monitoring deficits.
Pneumogastric (Vagus) Nerve Activity Indexed by Heart Rate Variability in Chronic Pain Patients Compared to Healthy Controls: A Systematic Review and Meta-Analysis.

BACKGROUND
A large body of scientific literature derived from experimental studies emphasizes the vital role of vagal-nociceptive networks in acute pain processing. However, research on vagal activity, indexed by vagally-mediated heart rate variability (vmHRV) in chronic pain patients (CPPs), has not yet been summarized.


OBJECTIVES
To systematically investigate differences in vagus nerve activity indexed by time- and frequency-domain measures of vmHRV in CPPs compared to healthy controls (HCs).


STUDY DESIGN
A systematic review and meta-analysis, including meta-regression on a variety of populations (i.e., clinical etiology) and study-level (i.e., length of HRV recording) covariates.


SETTING
Not applicable (variety of studies included in the meta-analysis).


METHODS
Eight computerized databases (PubMed via MEDLINE, PsycNET, PsycINFO, Embase, CINAHL, Web of Science, PSYNDEX, and the Cochrane Library) in addition to a hand search were systematically screened for eligible studies based on pre-defined inclusion criteria. A meta-analysis on all empirical investigations reporting short- and long-term recordings of continuous time- (root-mean-square of successive R-R-interval differences [RMSSD]) and frequency-domain measures (high-frequency [HF] HRV) of vmHRV in CPPs and HCs was performed. True effect estimates as adjusted standardized mean differences (SMD; Hedges g) combined with inverse variance weights using a random effects model were computed.


RESULTS
CPPs show lower vmHRV than HCs indexed by RMSSD (Z = 5.47, P < .0001; g = -0.24;95% CI [-0.33, -0.16]; k = 25) and HF (Z = 4.54, P < .0001; g = -0.30; 95% CI [-0.44, -0.17]; k = 61).Meta-regression on covariates revealed significant differences by clinical etiology, age, gender, and length of HRV recording.


LIMITATIONS
We did not control for other potential covariates (i.e., duration of chronic pain, medication intake) which may carry potential risk of bias.


CONCLUSION(S)
The present meta-analysis is the most extensive review of the current evidence on vagal activity indexed by vmHRV in CPPs. CPPs were shown to have lower vagal activity, indexed by vmHRV, compared to HCs. Several covariates in this relationship have been identified. Further research is needed to investigate vagal activity in CPPs, in particular prospective and longitudinal follow-up studies are encouraged.
Discrete choice methods and their applications to short-term travel decisions

Modeling travel behavior is a key aspect of demand analysis, where aggregate demand is the accumulation of individuals’ decisions. In this chapter, we focus on “short-term” travel decisions. The most important short-term travel decisions include choice of destination for a non-work trip, choice of travel mode, choice of departure time and choice of route. It is important to note that short-term decisions are conditional on long-term travel and mobility decisions such as car ownership and residential and work locations. The analysis of travel behavior is typically disaggregate, meaning that the models represent the choice behavior of individual travelers. Discrete choice analysis is the methodology used to analyze and predict travel decisions. Therefore, we begin this chapter with a review of the theoretical and practical aspects of discrete choice models. After a brief discussion of general assumptions, we introduce the random utility model, which is the most common theoretical basis of discrete choice models. We then present the alternative discrete choice model forms such as Logit, Nested Logit, Generalized Extreme Value and Probit, as well as more recent developments such as Hybrid Logit and the Latent Class choice model. Finally, we elaborate on the applications of these models to two specific short term travel decisions: route choice and departure time choice.
Software specification methods: an overview using a case study

Find the secret to improve the quality of life by reading this software specification methods an overview using a case study 1st edition. This is a kind of book that you need now. Besides, it can be your favorite book to read after having this book. Do you ask why? Well, this is a book that has different characteristic with others. You may not need to know who the author is, how well-known the work is. As wise word, never judge the words from who speaks, but make the words as your good value to your life.
Mental health promotion: guidance and strategies.

Public mental health incorporates a number of strategies from mental well-being promotion to primary prevention and other forms of prevention. There is considerable evidence in the literature to suggest that early interventions and public education can work well for reducing psychiatric morbidity and resulting burden of disease. Educational strategies need to focus on individual, societal and environmental aspects. Targeted interventions at individuals will also need to focus on the whole population. A nested approach with the individual at the heart of it surrounded by family surrounded by society at large is the most suitable way to approach this. This Guidance should be read along with the European Psychiatric Association (EPA) Guidance on Prevention. Those at risk of developing psychiatric disorders also require adequate interventions as well as those who may have already developed illness. However, on the model of triage, mental health and well-being promotion need to be prioritized to ensure that, with the limited resources available, these activities do not get forgotten. One possibility is to have separate programmes for addressing concerns of a particular population group, another that is relevant for the broader general population. Mental health promotion as a concept is important and this will allow prevention of some psychiatric disorders and, by improving coping strategies, is likely to reduce the burden and stress induced by mental illness.
A novel wavelet-SVM short-time passenger flow prediction in Beijing subway system

In order to effectively manage the use of existing infrastructures and prevent the emergency caused by the large gathered crowd, the short-term passenger flow forecasting technology becomes more and more significant in the field of intelligent transportation system. However, there are few studies discussing how to predict different kinds of passenger flows in the subway system. In this paper, a novel hybrid model Wavelet-SVM is proposed, and it combines the complementary advantages of Wavelet and SVM models, and meanwhile overcomes their shortcomings respectively. The Wavelet-SVM forecasting approach consists of three important stages. The first stage decomposes the passenger flow data into different high frequency and low frequency series by wavelet. During the prediction stage, the SVM method is applied to learn and predict the corresponding high frequency and low frequency series. In the last stage, the diverse predicted sequences are reconstructed by wavelet. The experimental results show that the approach not only has the best forecasting performance compared with the state-of-theart techniques but also appears to be the most promising and robust based on the historical passenger flow data in Beijing subway system and several standard evaluation measures. & 2015 Published by Elsevier B.V.
An Extreme Value Approach for Modeling Operational Risk Losses Depending on Covariates

A general methodology for modeling loss data depending on covariates is developed. The parameters of the frequency and severity distributions of the losses may depend on covariates. The loss frequency over time is modeled with a non-homogeneous Poisson process with rate function depending on the covariates. This corresponds to a generalized additive model which can be estimated with spline smoothing via penalized maximum likelihood estimation. The loss severity over time is modeled with a non-stationary generalized Pareto distribution (alternatively, a generalized extreme value distribution) depending on the covariates. Since spline smoothing can not directly be applied in this case, an efficient algorithm based on orthogonal parameters is suggested. The methodology is applied both to simulated loss data and a database of real operational risk losses. Estimates, including confidence intervals, for risk measures such as Valueat-Risk as required by the Basel II/III framework are computed. Furthermore, an implementation of the statistical methodology in R is provided.
Systolic and diastolic component of orthostatic hypotension and cardiovascular events in hypertensive patients: the Captopril Prevention Project.

OBJECTIVE
Impact of SBP vs. DBP decrement during orthostasis on cardiovascular events in hypertension is not clear.


METHODS
We assessed prospective association of orthostatic hypotension with mortality and major cardiovascular events [myocardial infarction (MI) and stroke] among 8788 treated hypertensive patients (52.2% men; mean age 52 years, mean BP 161/99  mmHg) without history of MI or stroke at baseline. Orthostatic hypotension was defined according to combined international consensus criteria, and as either systolic (decrease ≥20  mmHg) or diastolic orthostatic hypotension (decrease ≥10  mmHg). Final Cox regression model was adjusted for age, sex, supine SBP and DBP, diabetes, smoking, and total cholesterol.


RESULTS
A total of 1060 (12.1%) study participants fulfilled combined orthostatic hypotension criteria, of these 886 (10.1%) met systolic and 290 (3.3%) diastolic criterion. In the crude analysis, combined orthostatic hypotension criteria were predictive of the composite endpoint, major cardiovascular event, total mortality, and stroke but not MI. After full adjustment, combined orthostatic hypotension criteria and systolic orthostatic hypotension were independently associated with stroke only (hazard ratio: 1.48, 1.07-2.05, P = 0.019, and 1.53, 1.08-2.15, P = 0.015, respectively), whereas the composite endpoint tended in the same direction (hazard ratio: 1.21, 0.98-1.51, P = 0.075, and 1.24, 0.99-1.55, P = 0.066, respectively). In contrast, diastolic orthostatic hypotension was associated with increased risk of MI (hazard ratio: 2.04, 1.20-3.46, P = 0.008).


CONCLUSION
Orthostatic hypotension has a dual role in cardiovascular events among hypertensive patients: SBP fall indicates higher risk of stroke, whereas DBP fall confers higher risk of MI.
Using deep learning for Digital Soil Mapping

Digital soil mapping has been widely used as a cost-effective method for generating soil maps. However, current DSM data representation rarely incorporate contextual information of the landscape. DSM models are usually calibrated using point observations intersected with spatially corresponding point covariates. Here, we demonstrate the use of the convolutional neural network model that incorporates contextual information surrounding an observation to significantly improve the prediction accuracy over conventional DSM models. We describe a convolutional neural network (CNN) model that takes inputs 5 as images of covariates and explores spatial contextual information by finding non-linear local spatial relationships of neighbouring pixels. Unique features of the proposed model include: input represented as 3D stack of images, data augmentation to reduce overfitting, and simultaneously predicting multiple outputs. Using a soil mapping example in Chile, the CNN model was trained to simultaneously predict soil organic carbon at multiples depths across the country. The results showed the CNN model reduced the error by 30% compared with conventional techniques that only used point information of covariates. In the 10 example of country-wide mapping at 100 m resolution, the neighbourhood size from 3 to 9 pixels is more effective than at a point location and larger neighbourhood sizes. In addition, the CNN model produces less prediction uncertainty and it is able to predict soil carbon at deeper soil layers more accurately. Because the CNN model takes covariate represented as images, it offers a simple and effective framework for future DSM models. Copyright statement. Author(s) 2018. CC BY 4.0 License 15