LLukas22/scidocs huggingface dataset:
Cancer mortality-to-incidence ratios in Georgia: describing racial cancer disparities and potential geographic determinants.

BACKGROUND
The objective of this study was to evaluate racial cancer disparities in Georgia by calculating and comparing mortality-to-incidence ratios (MIRs) by health district and in relation to geographic factors.


METHODS
Data sources included cancer incidence (Georgia Comprehensive Cancer Registry), cancer mortality (Georgia Vital Records), and health factor (County Health Rankings) data. Age-adjusted incidence and mortality rates were calculated by cancer site (all sites combined, lung, colorectal, prostate, breast, oral, and cervical) for 2003-2007. MIRs and 95% confidence intervals were calculated overall and by district for each cancer site, race, and sex. MIRs were mapped by district and compared with geographic health factors.


RESULTS
In total, 186,419 incident cases and 71,533 deaths were identified. Blacks had higher MIRs than whites for every cancer site evaluated, and especially large differentials were observed for prostate, cervical, and oral cancer in men. Large geographic disparities were detected, with larger MIRs, chiefly among blacks, in Georgia compared with national data. The highest MIRs were detected in west and east central Georgia, and the lowest MIRs were detected in and around Atlanta. Districts with better health behavior, clinical care, and social/economic factors had lower MIRs, especially among whites.


CONCLUSIONS
More fatal cancers, particularly prostate, cervical, and oral cancer in men were detected among blacks, especially in central Georgia, where health behavior and social/economic factors were worse. MIRs are an efficient indicator of survival and provide insight into racial cancer disparities. Additional examination of geographic determinants of cancer fatality in Georgia as indicated by MIRs is warranted.
Printed Arabic Character Recognition using Neural Network

Character recognition provides a solution for processing large volume of data automatically. The purpose of the present work is to recognize different forms of printed Arabic characters written in three different fonts (Times new roman, Arial and Tahoma) using back-propagation neural network. This work was tested on a sample of printed character and the correct average recognition rate was 97%.
Prediction of time of death after withdrawal of life-sustaining treatment in potential donors after cardiac death*.

OBJECTIVE
Organ donation after cardiac death increases the number of donor organs. In controlled donation after cardiac death donors, the period between withdrawal of life-sustaining treatment and cardiac arrest is one of the parameters used to assess whether organs are suitable for transplantation. The objective of this study was to identify donation after cardiac death donor characteristics that affect the interval between withdrawal of life-sustaining treatment and cardiac death.


DESIGN
Prospective multicenter study of observational data.


PATIENTS
All potential donation after cardiac death donors in The Netherlands between May 2007 and June 2009 were identified.


INTERVENTIONS
None.


MEASUREMENTS AND MAIN RESULTS
Of the 242 potential donation after cardiac death donors, 211 entered analysis, 76% of them died within 60 mins, and 83% died within 120 mins after withdrawal of life-sustaining treatment. The median time to death was 20 mins (range 1 min to 3.8 days). Controlled mechanical ventilation, use of norepinephrine, absence of reflexes, neurologic deficit as cause of death, and absence of cardiovascular comorbidity were associated with death within 60 and 120 mins. The use of analgesics, sedatives, or extubation did not significantly influence the moment of death. In the multivariable logistic regression analysis, controlled mechanical ventilation remained a risk factor for death within 60 mins, and norepinephrine administration and absence of cardiovascular comorbidity remained risk factors for death within 120 mins. The clinical judgment of the intensivist predicted death within 60 and 120 mins with a sensitivity of 73% and 89%, respectively, and a specificity of 56% and 25%, respectively.


CONCLUSION
Despite the identification of risk factors for early death and the additional value of the clinical judgment by the intensivist, it is not possible to reliably identify potential donation after cardiac death donors who will die within 1 or 2 hrs after life-sustaining treatment has been withdrawn. Consequently, a donation procedure should be initiated in every potential donor.
Syntactic N-grams as machine learning features for natural language processing

In this paper we introduce and discuss a concept of syntactic n-grams (sn-grams). Sn-grams differ from traditional n-grams in the manner how we construct them, i.e., what elements are considered neighbors. In case of sn-grams, the neighbors are taken by following syntactic relations in syntactic trees, and not by taking words as they appear in a text, i.e., sn-grams are constructed by following paths in syntactic trees. In this manner, sn-grams allow bringing syntactic knowledge into machine learning methods; still, previous parsing is necessary for their construction. Sn-grams can be applied in any natural language processing (NLP) task where traditional n-grams are used. We describe how sn-grams were applied to authorship attribution. We used as baseline traditional n-grams of words, part of speech (POS) tags and characters; three classifiers were applied: support vector machines (SVM), naive Bayes (NB), and tree classifier J48. Sn-grams give better results with SVM classifier. 2013 Elsevier Ltd. All rights reserved.
Quantitation of psilocin in human plasma by high-performance liquid chromatography and electrochemical detection: comparison of liquid-liquid extraction with automated on-line solid-phase extraction.

Two modifications of the HPLC-ED method with respect to extraction procedure used have been developed for psilocin, the active metabolite of psilocybin, in human plasma using either liquid-liquid extraction (LLE) or automated on-line solid-phase extraction (on-line SPE). Each type of the sample preparation required a different HPLC system followed by electrochemical detection at 650 to 675 mV. The limit of quantitation of both modifications was 10 ng/ml psilocin. There was no significant difference observable between the LLE and the on-line SPE in terms of method standard deviation (LLE 1.82%, on-line SPE 1.13%) and the analytical results. However, the advantages of on-line SPE in addition to different selectivity were less manual effort, smaller plasma volumes of 400 microl (LLE 2 ml) and a recovery of psilocin in human plasma of nearly 100% (LLE 88%). In contrast to a previous procedure both methods were rapid, simple and reliable and yielded high plasma recoveries. They were used successfully in the quantitation of psilocin in plasma samples obtained from healthy volunteers after p.o. administration of 0.2 mg psilocybin per kg body mass. Plasma concentration curves and pharmacokinetic parameters were calculated.
Toward a class-independent quantitative structure--activity relationship model for uncouplers of oxidative phosphorylation.

A mechanistically based quantitative structure-activity relationship (QSAR) for the uncoupling activity of weak organic acids has been derived. The analysis of earlier experimental studies suggested that the limiting step in the uncoupling process is the rate with which anions can cross the membrane and that this rate is determined by the height of the energy barrier encountered in the hydrophobic membrane core. We use this mechanistic understanding to develop a predictive model for uncoupling. The translocation rate constants of anions correlate well with the free energy difference between the energy well and the energy barrier, Delta G well-barrier,A (-) , in the membrane calculated by a novel approach to describe internal partitioning in the membrane. An existing data set of 21 phenols measured in an in vitro test system specific for uncouplers was extended by 14 highly diverse compounds. A simple regression model based on the experimental membrane-water partition coefficient and Delta G well-barrier,A (-) showed good predictive power and had meaningful regression coefficients. To establish uncoupler QSARs independent of chemical class, it is necessary to calculate the descriptors for the charged species, as the analogous descriptors of the neutral species showed almost no correlation with the translocation rate constants of anions. The substitution of experimental with calculated partition coefficients resulted in a decrease of the model fit. A particular strength of the current model is the accurate calculation of excess toxicity, which makes it a suitable tool for database screening. The applicability domain, limitations of the model, and ideas for future research are critically discussed.
Comparison of the Effects of Quetiapine XR and Lithium Monotherapy on Actigraphy-Measured Circadian Parameters in Patients With Bipolar II Depression.

PURPOSE/BACKGROUND
The aim of this study was to evaluate the effects of quetiapine XR and lithium on actigraphy-measured circadian parameters in patients with bipolar II depression.


METHODS/PROCEDURES
This was an 8-week, open-label, prospective, randomized comparative study. The assessments included the 17-item Hamilton Depression Rating Scale score and actigraphic measures concerning the previous 7 days, collected at each visit (weeks 0 [baseline], 1, 2, 4, 6, and 8); the actigraphic data were analyzed with a cosinor analysis.


FINDINGS/RESULTS
Medication, time, and the interaction between medication and time were significantly associated with acrophase for the entire group (Ps = 0.003, 0.020, and 0.042, respectively). More specifically, acrophase was significantly delayed at weeks 1 and 6 (Ps = 0.004 and 0.039, respectively) in the quetiapine XR group. The F statistics significantly increased over time for the entire group (P < 0.001), and there was a significant increase in F statistics on weeks 4 and 6 in the quetiapine XR group (Ps = 0.016 and 0.020, respectively) and on weeks 4 and 8 in the lithium group (Ps = 0.001 and 0.016, respectively). In addition, scores on the 17-item Hamilton Depression Rating Scale were significantly associated with the F statistics during 8 weeks for the entire group (P = 0.008).


IMPLICATIONS/CONCLUSIONS
Both quetiapine XR and lithium affected several circadian parameters, including peak activity time and robustness of circadian rhythm, but exerted different effects on acrophase in patients with bipolar II depression. In particular, clinical depressive symptoms were associated with robustness of circadian rhythm during the course of the 8-week treatment.
Ultrastaging of para-aortic lymph nodes in stage IIIC1 endometrial cancer: a preliminary report.

OBJECTIVE
The aim of this study was to determine the rate of occult metastasis, including isolated tumor cells, in para-aortic lymph nodes of patients with stage IIIC1 endometrial cancer who underwent pelvic and para-aortic lymphadenectomy.


METHODS
A series of 15 patients who had undergone combined pelvic and para-aortic lymphadenectomy during the period from 2004 to 2010 and who were diagnosed as being positive for pelvic node metastasis but negative for para-aortic node metastasis were included in this study. Ultra-staging by multiple slicing, staining with hematoxylin/eosin and cytokeratin, and microscopic inspection was performed on a total of 242 para-aortic lymph nodes.


RESULTS
Eleven (73.3%) of the 15 patients had occult para-aortic lymph node metastasis. Two patients (13.3%) had macrometastasis and nine patients (60.0%) had isolated tumor cells. Type 2 endometrial cancer tended to have a higher rate of occult metastasis than that of type 1 cancer (90% vs. 40%, P=0.07). The rate of occult para-aortic node metastasis was not related to the number of metastatic pelvic nodes. Five patients suffered recurrence in the lung or in the intraabdomen, but lymph node recurrence was not found in any case.


CONCLUSION
Patients with stage IIIC1 endometrial cancer have a potentially high rate of occult para-aortic node metastasis. Local treatment of the para-aortic region should be considered in patients with stage IIIC1 endometrial cancer until effective adjuvant therapy is established.
High-Frequency Current Source Inverter

The frequency range of the current source inverter (CSI) is limited by the slow commutation process in the inverter circuit. A method to reduce the commutation time and to limit the commutation capacitor voltage is proposed. A brief description of the conventional CSI and a detailed analysis of the commutation intervals of the proposed circuit are given. The experimental waveforms observed in the laboratory verify the validity of the analysis.
Millimeter-Wave Evolution for 5G Cellular Networks

Triggered by the explosion of mobile traffic, 5G cellular network requires evolution to increase the system rate 1000 times higher than the current systems in 10 years. Motivated by this common problem, this paper studies to integrate mm-wave access into current cellular networks as multi-band heterogeneous networks to exploit the ultrawideband aspect of the mm-wave band. This paper provides comprehensive architecture of 5G cellular networks with mm-wave access, where mmwave small cell basestations and a conventional macro basestation are connected to Centralized-RAN to effectively operate the system by enabling power efficient seamless handover as well as centralized resource control including dynamic cell structuring to match the limited coverage of mm-wave access with high traffic user locations via user-plane/controlplane splitting. To prove the effectiveness of the proposed 5G cellular networks with mm-wave access, system level simulation by using expected future traffic model and measurement based mm-wave propagation model is conducted. The numerical results show the effectiveness of the proposed network to realize 1000 times higher system rate than the current network in 10 years which is not achieved by the small cells using commonly considered 3.5 GHz band. Furthermore, the paper also gives latest status of mm-wave devices and regulations to show the feasibility of using mm-wave in the 5G systems. key words: Millimeter-wave, 5G cellular network, small cell, C-RAN, system rate gain
Body mass index and metabolic parameters in patients with schizophrenia during long-term treatment with paliperidone palmitate

BACKGROUND
There is a strong association between weight gain and metabolic events in patients with schizophrenia receiving many of the second-generation antipsychotic agents. We explored the relationship between body mass index (BMI) and metabolic events in patients with schizophrenia receiving long-acting injectable paliperidone palmitate (PP) in a long-term trial.


METHODS
We conducted a post hoc analysis of data from a PP study that included a 33-week open-label transition (TR) and maintenance phase; a variable duration, randomized, double-blind (DB), placebo-controlled phase and a 52-week open-label extension (OLE) phase. Overall, 644 patients received PP continuously from study entry through discontinuation or study completion and were grouped by baseline BMI (kg/m2): underweight (BMI <19; n = 29, 4.5%), normal-weight (BMI 19- < 25; n = 229, 35.6%), overweight (BMI 25- < 30; n = 232, 36.0%) and obese (BMI ≥ 30; n = 154, 23.9%). Metabolic treatment-emergent adverse events (TEAEs) and changes in related laboratory results from TR baseline were analyzed.


RESULTS
PP exposure was similar across BMI groups; overall mean (SD) dose/month was 70.3 (17.17) mg eq. [109.6 (26.78) mg]; median duration of exposure was 204 days (6 to 1009 days). Occurrences of metabolic TEAEs overall by group were 0% (underweight), 14.9% (normal-weight), 14.7% (overweight), and 24.0% (obese). The most common (≥ 2%) metabolic TEAE were weight gain and elevated blood levels of glucose, lipids, and insulin. Mean BMI and weight increased in normal-weight and overweight groups at DB endpoint, and in underweight, normal-weight and overweight groups at OLE endpoint (p ≤ 0.05). No consistent trend for increased metabolic-related laboratory values by baseline BMI group was observed. Homeostatic model assessments for insulin resistance indicated preexisting insulin resistance at baseline, with minimal changes at OLE endpoint across baseline BMI groups.


CONCLUSION
Occurrences of metabolic-related TEAEs trended with greater BMI status in patients with schizophrenia treated with PP; consistent trends in metabolic-related laboratory values were not observed.


TRIAL REGISTRATION
This study is registered at ClinicalTrials.gov (NCT 00518323).
Promoting an open research culture

Transparency, openness, and reproducibility are readily recognized as vital features of science (1, 2). When asked, most scientists embrace these features as disciplinary norms and values (3). Therefore, one might expect that these valued features would be routine in daily practice. Yet, a growing body of evidence suggests that this is not the case (4–6).
Combining Pattern Classifiers: Methods and Algorithms

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A Coherent understanding of solvable models for quantum measurement processes

By making use of Schwinger's oscillator model of angular momentum, we put forward an interesting connection among three solvable Hamiltonians, widely used for discussions on the quantum measurement problem. This connection implies that a particular macroscopic limit has to be taken for these models to be physically sensible.
MARKOV CHAIN MONTE CARLO FOR AUTOLOGISTIC REGRESSION MODELS WITH APPLICATION TO THE DISTRIBUTION OF PLANT SPECIES

SUMMARY In this paper, we explore using autologistic regression models for spatial binary data with covari-ates. Autologistic regression models can handle binary responses exhibiting both spatial correlation and dependence on covariates. We use Markov chain Monte Carlo (MCMC) to estimate the parameters in these models. The distributional behavior of the MCMC maximum likelihood estimates (MCMC MLEs) is studied via simulation. We nd that the MCMC MLEs are approximately normally distributed and that the MCMC estimates of Fisher information may be used to estimate the variance of the MCMC MLEs and to construct conndence intervals. Finally, we illustrate by example how our studies may be applied to model the distribution of plant species. In our simulations and data analysis, we have used the maximum pseudolikelihood estimates (MPLEs) as the \starting values" to generate the initial Monte Carlo sample. This seems to work well except when the degree of spatial correlation is very large.
Obstructions to convexity in neural codes

How does the brain encode spatial structure? One way is through hippocampal neurons called place cells, which become associated to convex regions of space known as their receptive fields: each place cell fires at a high rate precisely when the animal is in the receptive field. The firing patterns of multiple place cells form what is known as a convex neural code. How can we tell when a neural code is convex? To address this question, Giusti and Itskov identified a local obstruction, defined via the topology of a code’s simplicial complex, and proved that convex neural codes have no local obstructions. Curto et al. proved the converse for all neural codes on at most four neurons. Via a counterexample on five neurons, we show that this converse is false in general. Additionally, we classify all codes on five neurons with no local obstructions. This classification is enabled by our enumeration of connected simplicial complexes on 5 vertices up to isomorphism. Finally, we examine how local obstructions are related to maximal codewords (maximal sets of neurons that co-fire). Curto et al. proved that a code has no local obstructions if and only if it contains certain “mandatory” intersections of maximal codewords. We give a new criterion for an intersection of maximal codewords to be non-mandatory, and prove that it classifies all such non-mandatory codewords for codes on up to five neurons.
Ultrasonic Sensing For A Mobile Robot To Recognize An Environment - Measuring The Normal Direction Of Walls -

With a conventional ultrasonic sensor system for a mobile robot, the distance to an object can be obtained with a time-of-flight (TOF) method, in which a reflected point is regarded to be located directly on the transducer line-ofsight. However, in an indoor environment, flat walls have specular characteristics. So, the real reflected point is not located on the transducer’s lime-of-sight, because an echo from the normal incidence only returns to the transducer, since ultrasonic directivity is not so sharp in air. So, to accurately recognize the position of an object, it is important to detect the direction of the reflected point. One method to obtain the direction is to calculate it from the time difference between two parallel receivers. In this paper, an ultrasonic sensing method with a wide angle and high resolution in specular environment is proposed, and accurate environment recognition can be realized.
Without passport : the life and work of Paul Richard

Without Passport is the intimate portrait of a French intellectual whose memoirs span the period 1874 to 1919. The details of his childhood are followed by an account of his military service in Tunisia. Then seminary training and an active street ministry in Lille, lead him into conflict with the Church. With him we visit Devil's Island as it was in 1905, observe his brief career as an attorney in the Paris Court of Appeals, and follow him to India and Japan in the company of Mira Alfassa who later founded the largest spiritual community (Auroville) in India. Along the way we encounter other prominent figures in the colonial independence movement, including Abdul Baha, Aurobindo Ghose, Rabindranath Tagore, and Mitsuru Toyama. Then, a severe personal crisis followed by a new life in the United States, where his most influential book, entitled The Scourge of Christ, was published in 1929. It is a good counterpoint to the adventures described in Without Passport, because it enables us to share his spiritual voyage as well.
Rough Clustering Based Unsupervised Image Change Detection

This paper introduces an unsupervised technique to detect the changed region of multitemporal images on a same reference plane with the help of rough clustering. The proposed technique is a soft-computing approach, based on the concept of rough set with rough clustering and Pawlak’s accuracy. It is less noisy and avoids pre-deterministic knowledge about the distribution of the changed and unchanged regions. To show the effectiveness, the proposed technique is compared with some other approaches. Keywords—change detection; clustering; rough clustering; rough set