LLukas22/scidocs huggingface dataset:
Neurodevelopmental care in the NICU.

Neurodevelopmental care, which is any NICU intervention undertaken to improve neurodevelopmental outcome, includes NICU design, nursing routines, nursing care plans, management of pain, feeding methods and, most importantly, encouraging parental involvement with their NICU infant. Recognition that sensory stimulation can overwhelm preterm infants and increase physiologic signs of stress led to attempts to reduce sensory input. More recent approaches judiciously add back soothing sensory input (e.g., therapeutic touch, soft music). Circadian light/dark cycles and physical activity improve preterm growth. Attention to infant positioning and handling affects physiologic variables and joint mobility, if not functional motor abilities. A highly organized system of care for NICU infants is Als' NIDCAP (i.e., Neonatal Individualized Developmental Care and Assessment Program). Although NIDCAP may reduce need for respiratory support and hospital length of stay, it does not significantly influence neurodevelopmental outcome at 2-3 years. Pain management includes benign interventions (e.g., nonnutritive sucking, oral glucose), but the prolonged use of narcotics must be balanced against the consequences of sedation and dependency. The foremost challenge for NICUs remains parent disenfranchisement. Kangaroo care, which involves parent/infant skin-to-skin contact, improves preterm growth, decreases nosocomial infections and may shorten hospital length of stay. A great deal of work needs to be done to identify and demonstrate efficacy of specific interventions and changes that humanize the NICU, encourage parental involvement, support infant development and optimize preterm neurodevelopmental outcomes.
Aggregating Large Sets of Probabilistic Forecasts by Weighted Coherent Adjustment

P forecasts in complex environments can benefit from combining the estimates of large groups of forecasters (“judges”). But aggregating multiple opinions raises several challenges. First, human judges are notoriously incoherent when their forecasts involve logically complex events. Second, individual judges may have specialized knowledge, so different judges may produce forecasts for different events. Third, the credibility of individual judges might vary, and one would like to pay greater attention to more trustworthy forecasts. These considerations limit the value of simple aggregation methods like unweighted linear averaging. In this paper, a new algorithm is proposed for combining probabilistic assessments from a large pool of judges, with the goal of efficiently implementing the coherent approximation principle (CAP) while weighing judges by their credibility. Two measures of a judge’s likely credibility are introduced and used in the algorithm to determine the judge’s weight in aggregation. As a test of efficiency, the algorithm was applied to a data set of nearly half a million probability estimates of events related to the 2008 U.S. presidential election (∼16,000 judges). Compared with unweighted scalable CAP algorithms, the proposed weighting schemes significantly improved the stochastic accuracy with a comparable run time, demonstrating the efficiency and effectiveness of the weighting methods for aggregating large numbers and varieties of forecasts.
Comparison of whole-body cooling and selective head cooling on changes in urinary 8-hydroxy-2-deoxyguanosine levels in patients with global brain ischemia undergoing mild hypothermia therapy

BACKGROUND
We evaluated changes in the levels of urinary 8-hydroxy-2-deoxyguanosine (8-OHdG) in patients undergoing mild hypothermia therapy and compared 8-OHdG expressions in those receiving whole-body cooling or selective head cooling.


MATERIAL/METHODS
The subjects were 15 patients undergoing mild hypothermia therapy following resuscitation after cardiac arrest in our intensive care unit. We divided the patients into 2 groups receiving either whole-body cooling or selective head cooling, according to their circulatory stability. We examined urinary 8-OHdG level for 1 week and neurological outcomes 28 days after admission.


RESULTS
We observed significant decreases in urinary 8-OHdG levels on days 6 and 7 compared with that on day 1 in the whole-body cooling group. Furthermore, we noted significantly lower urinary 8-OHdG levels after days 5, 6 and 7 in the whole-body cooling group than in the selective head-cooling group. Neurological outcomes were similar in both groups.


CONCLUSIONS
Mild hypothermia therapy with whole-body cooling had a greater effect on the suppression of free radical production than selective head cooling. However, selective head cooling might be an appropriate indication for patients with circulatory instability after resuscitation, because it provides neuroprotection similar to that of whole-body cooling.
A Simpler Approach to Matrix Completion

This paper provides the best bounds to date on the number of randomly sampled entries required to reconstruct an unknown low rank matrix. These results improve on prior work by Candès and Recht [4], Candès and Tao [7], and Keshavan, Montanari, and Oh [18]. The reconstruction is accomplished by minimizing the nuclear norm, or sum of the singular values, of the hidden matrix subject to agreement with the provided entries. If the underlying matrix satisfies a certain incoherence condition, then the number of entries required is equal to a quadratic logarithmic factor times the number of parameters in the singular value decomposition. The proof of this assertion is short, self contained, and uses very elementary analysis. The novel techniques herein are based on recent work in quantum information theory.
Mragyati : A System for Keyword-based Searching in Databases

The web, through many search engine sites, has popularized the keyword-based search paradigm, where a user can specify a string of keywords and expect to retrieve relevant documents, possibly ranked by their relevance to the query. Since a lot of information is stored in databases (and not as HTML documents), it is important to provide a similar search paradigm for databases, where users can query a database without knowing the database schema and database query languages such as SQL. In this paper, we propose such a database search system, which accepts a free-form query as a collection of keywords, translates it into queries on the database using the database metadata, and presents query results in a well-structured and browsable form. The system maps keywords onto the database schema and uses inter-relationships (i.e., data semantics) among the referred tables to generate meaningful query results. We also describe our prototype for database search, called Mragyati. The approach proposed here is scalable, as it does not build an in-memory graph of the entire database for searching for relationships among the objects selected by the users query. Index Terms : database search, keyword search, metadata, relevance ranking, web-based search
Fractional, Circular, and Defective Coloring of Series-Parallel Graphs

In this note we consider colorings of series-parallel graphs. Specifically, we provide bounds on their fractional and circular chromatic numbers and the defective version of these parameters. The main result is that the fractional chromatic number of any series-parallel graph of odd girth k is exactly 2k/(k − 1).
Effect size estimation: methods and examples.

BACKGROUND
While the p-value will tell the reader a study's results are statistically significant, it does not provide any information about the practical or clinical importance of the findings. Furthermore, p-values are influenced by sample size. They are more likely to be significant when sample size is large and less likely if the sample is small. Effect size estimates, on the other hand, are not sensitive to sample size and provide information about the direction and strength of the relationship between variables (e.g., a treatment and an outcome). In addition to providing valuable clinical information about study findings, effect size estimates can provide a common metric to compare results across studies. Despite their usefulness, effect size estimates are often not reported as part of the research results. Consequently, effect sizes often have to be calculated based on summary and test statistics reported in research articles.


RESULTS
This article provides the formulas utilized to directly calculate common effective size estimates using summary statistics reported in research studies, as well as methods to more indirectly estimate these effect sizes when basis summary statistics are not reported. In addition we present formulas to compute the corresponding confidence interval for each effect size.
Birth sex ratios in sheep over nine lambing seasons: years 7–9 and the effects of ageing

The birth sex ratio of a commercial flock of Suffolk cross sheep, Ovis aries, was studied over nine consecutive lambing seasons. In all data from 2704 lambs were recorded and analysed. The overall (1985–1993) birth sex ratio was 49.96% male lambs. Ewes with single lambs produced significantly more males (53.04%) than ewes with triplets (45.54% male). A significant positive correlation was found between the flock age and the birth sex ratio (1985–1992). As the flock aged the birth sex ratio changed from female biased to male biased, remained male biased for a number of years, and then became female biased again. This pattern is evident first in single, then in twin and later in triplet births. Among like sex twins (males and females) (1985–1993) more males (53.88%) were born in the first half and more females (45.57% males) in the second half of the lambing season. The difference between the two halves is significant.
A diffusion-neural-network for learning from small samples

Neural information processing models largely assume that the patterns for training a neural network are sufficient. Otherwise, there must exist a non-negligible error between the real function and the estimated function from a trained network. To reduce the error, in this paper, we suggest a diffusion-neural-network (DNN) to learn from a small sample consisting of only a few patterns. A DNN with more nodes in the input and layers is trained by using the deriving patterns instead of original patterns. In this paper, we give an example to show how to construct a DNN for recognizing a non-linear function. In our case, the DNN’s error is less than the error of the conventional BP network, about 48%. To substantiate the special case arguments, we also study other two non-linear functions with simulation technology. The results show that the DNN model is very effective in the case where the target function has a strong non-linearity or a given sample is very small. 2003 Elsevier Inc. All rights reserved.
Progress and prospects: gene therapy for inherited immunodeficiencies

Haematopoietic stem cell transplantation (HSCT) is now widely used to treat primary immunodeficiencies (PID). For patients with specific disorders (severe combined immunodeficiency (SCID)-X1, adenosine deaminase deficiency (ADA)–SCID, X-chronic granulomatous disease (CGD) and Wiskott–Aldrich Syndrome (WAS)) who lack a suitable human leukocyte antigen (HLA)-matched donor, gene therapy has offered an important alternative treatment option. The success of gene therapy can be attributed, in part, to the selective advantage offered to gene-corrected cells, the avoidance of graft-versus-host disease and to the use of pre-conditioning in patients with chemotherapy to facilitate engraftment of corrected cells. Adverse events have been encountered and this has led to detailed characterization of retroviral vector integration profiles. A new generation of self-inactivating retroviral and lentiviral vectors have been designed to address these safety concerns, and are at an advanced stage of preparation for the next phase of clinical testing.
Theoretical Model for the Structural Phase Transition and the Metal–Insulator Transition in Polymerized KC60

Abstract The recently discovered structural phase transition in polymerized KC60 at about 50 K leads to a doubling of the unit cell volume and is accompanied by a metal–insulator transition. Here, we show that the superstructure results from orientational charge density waves along the polymer chains and correlated displacements of the K+ ions. The presented model can also account for the metal–insulator transition. The effect is specific for the space group Pmnn of KC60 and is absent in both Rb‐ and CsC60 (space group I2/m), in agreement with the present experimental knowledge of these compounds.
Aid, Public Expenditure and Dutch Disease

Contemporary policy debates on the macroeconomics of aid often concentrate on short-run Dutch disease effects, ignoring the possible supply side impact of aid— financed public expenditure. We develop a simple model of aid and public expenditure in which public infrastructure capital generates an inter-temporal productivity spillover for both tradable and non-tradable sectors, where these productivity effects may display sector-specific biases. The model also allows for non-homothetic demands. We then use an extended version of this model, calibrated to contemporary conditions in Uganda, to simulate the effect of a step increase in net aid flows. Our simulations show that beyond the short-run, where Dutch disease effects are present, the relationship between enhanced aid flows, real exchange rates and welfare is less straightforward than simple models of aid suggest. We show that public infrastructure which generates a productivity bias in favour of non-tradable production delivers the largest aggregate return to aid, with the real exchange rate appreciation reduced or reversed and enhanced export performance, but it does so at the cost of a deterioration in the income distribution. Income gains accrue predominantly to urban skilled and unskilled households, leaving the rural poor relatively worse off. Under plausible parameterizations of the model the rural poor may also be worse off in absolute terms.
Pollinator Community of Onion (Allium cepa L.) and its Role in Crop Reproductive Success

Investigations to identify the pollinator community of insects and its role in onion (Allium cepa L.) pollination were carried out at the research farm of University College of Agriculture, Bahauddin Zakariya University, Multan, Pakistan. The community of pollinators was composed of two bees (Order: Hymenoptera) and eight true flies (Order Diptera). Among bees, Apis dorsata proved to be an abundant pollinator (2.85±1.57 individuals/25 plants) while among true flies Episyrphus balteatus (Syrphidae) had the maximum abundance of 14.00±4.61 individuals/25 plants. All the insect pollinator species reached peak activity during 10:00 to 12:00 h. Eupeodes corollae (Syrphidae) exhibited the most efficient foraging behavior by visiting 17.14±1.38 flowers in 147.5±8.14 seconds on an umbel. A. dorsata was revealed as the most effective pollinator, however, based on seed setting results for visits by single species over 20 minutes and which produced 506 seeds/umbel/20 minute visit.
Kernelized Temporal Cut for Online Temporal Segmentation and Recognition

We address the problem of unsupervised online segmenting human motion sequences into different actions. Kernelized Temporal Cut (KTC), is proposed to sequentially cut the structured sequential data into different regimes. KTC extends previous works on online change-point detection by incorporating Hilbert space embedding of distributions to handle the nonparametric and high dimensionality issues. Based on KTC, a realtime online algorithm and a hierarchical extension are proposed for detecting both action transitions and cyclic motions at the same time. We evaluate and compare the approach to state-of-theart methods on motion capture data, depth sensor data and videos. Experimental results demonstrate the effectiveness of our approach, which yields realtime segmentation, and produces higher action segmentation accuracy. Furthermore, by combining with sequence matching algorithms, we can online recognize actions of an arbitrary person from an arbitrary viewpoint, given realtime depth sensor input.
Construction of coherent states for physical algebraic systems

We construct a general state which is an eigenvector of the annihilation operator of the generalized Heisenberg algebra. We show, for several systems characterized by different energy spectra, that this general state satisfies the minimal set of conditions required to obtain Klauder's minimal coherent states.
Exploitation of rocky intertidal grazers: population status and potential impacts on community structure and functioning

A wide range of anthropogenic activities are impacting the ecology of coastal areas. Exploitation of marine resources is one such activity, which, through cascading trophic effects, can have influences well beyond that of the target species. We investigated the mid-rocky-shore community structure of the Azores archipelago, a seldom-studied habitat, where there is a local tradition of exploiting limpets, the main intertidal grazers. The limpet population structure differed among islands, and there was an inverse relationship between the abundance of larger limpets and the human population per coastal perimeter, but not the associated catch data. At small scales of resolution (quadrats), there was a negative relationship between the cover of algae and limpets and a positive relationship between barnacles and limpets. These relationships were also apparent at the larger scale of islands as a function of the gradient of exploitation. Our results show how natural habitat fragmentation may be useful where the experimental testing of a hypothesis is not possible, and provide evidence for the trophic cascading effects of limpet exploitation at landscape scales.
Web-based tools can be used reliably to detect patients with major depressive disorder and subsyndromal depressive symptoms

BACKGROUND
Although depression has been regarded as a major public health problem, many individuals with depression still remain undetected or untreated. Despite the potential for Internet-based tools to greatly improve the success rate of screening for depression, their reliability and validity has not been well studied. Therefore the aim of this study was to evaluate the test-retest reliability and criterion validity of a Web-based system, the Internet-based Self-assessment Program for Depression (ISP-D).


METHODS
The ISP-D to screen for major depressive disorder (MDD), minor depressive disorder (MinD), and subsyndromal depressive symptoms (SSD) was developed in traditional Chinese. Volunteers, 18 years and older, were recruited via the Internet and then assessed twice on the online ISP-D system to investigate the test-retest reliability of the test. They were subsequently prompted to schedule face-to-face interviews. The interviews were performed by the research psychiatrists using the Mini-International Neuropsychiatric Interview and the diagnoses made according to DSM-IV diagnostic criteria were used for the statistics of criterion validity. Kappa (kappa) values were calculated to assess test-retest reliability.


RESULTS
A total of 579 volunteer subjects were administered the test. Most of the subjects were young (mean age: 26.2 +/- 6.6 years), female (77.7%), single (81.6%), and well educated (61.9% college or higher). The distributions of MDD, MinD, SSD and no depression specified were 30.9%, 7.4%, 15.2%, and 46.5%, respectively. The mean time to complete the ISP-D was 8.89 +/- 6.77 min. One hundred and eighty-four of the respondents completed the retest (response rate: 31.8%). Our analysis revealed that the 2-week test-retest reliability for ISP-D was excellent (weighted kappa = 0.801). Fifty-five participants completed the face-to-face interview for the validity study. The sensitivity, specificity, positive, and negative predictive values for major depressive disorder were 81.8% and 72.7%, 66.7%, and 85.7% respectively. The overall accuracy was 76.4%.


CONCLUSION
The evidence indicates the ISP-D is a reliable and valid online tool for assessing depression. Further studies should test the ISP-D in clinical settings to increase its applications in clinical environments with different populations and in a larger sample size.
Medium-term follow-up of plaque incision and porcine small intestinal submucosal grafting for Peyronie's disease

The best surgical option for the management of severe cases of Peyronie's disease is currently a matter of debate. To determine medium-term outcomes and complications after treatment of severe Peyronie's disease by porcine small intestinal submucosa (SIS) grafts, we retrospectively reviewed 33 consecutive plaque incisions followed by 4-ply SIS grafting in 28 patients (2002–2009). Postoperative complications, penile length preservation, de novo ED, penile curvature correction and curvature recurrence rates were recorded. Median patient age was 54 years (38–69 years). Median preoperative curvature was 90° (30–90°) (stable for at least 6 months). Six patients (21%) had preoperative ED. There were few postoperative complications (no cases of infection, haematoma (n=2), penile hypoesthesia (n=1), patch rejection and migration (n=1)). Subjective penile shortening and de novo ED were observed in 7 (25%) and 3 (11%) patients, respectively. The success rate for the procedure (straight penis or curvature ⩽20° and ability to have intercourse) was 67% (22/33). Four patients achieved curvature correction after a repeat procedure with a new SIS graft. Eleven patients experienced recurrence within 3 months of surgery. After a median follow-up of 9 months (3–94), 22 patients (79%) had a satisfactory curvature correction.
Effect of a mixed reality-based intervention on arm, hand, and finger function on chronic stroke

Virtual and mixed reality systems have been suggested to promote motor recovery after stroke. Basing on the existing evidence on motor learning, we have developed a portable and low-cost mixed reality tabletop system that transforms a conventional table in a virtual environment for upper limb rehabilitation. The system allows intensive and customized training of a wide range of arm, hand, and finger movements and enables interaction with tangible objects, while providing audiovisual feedback of the participants’ performance in gamified tasks. This study evaluates the clinical effectiveness and the acceptance of an experimental intervention with the system in chronic stroke survivors. Thirty individuals with stroke were included in a reversal (A-B-A) study. Phase A consisted of 30 sessions of conventional physical therapy. Phase B consisted of 30 training sessions with the experimental system. Both interventions involved flexion and extension of the elbow, wrist, and fingers, and grasping of different objects. Sessions were 45-min long and were administered three to five days a week. The body structures (Modified Ashworth Scale), functions (Motricity Index, Fugl-Meyer Assessment Scale), activities (Manual Function Test, Wolf Motor Function Test, Box and Blocks Test, Nine Hole Peg Test), and participation (Motor Activity Log) were assessed before and after each phase. Acceptance of the system was also assessed after phase B (System Usability Scale, Intrinsic Motivation Inventory). Significant improvement was detected after the intervention with the system in the activity, both in arm function measured by the Wolf Motor Function Test (p < 0.01) and finger dexterity measured by the Box and Blocks Test (p < 0.01) and the Nine Hole Peg Test (p < 0.01); and participation (p < 0.01), which was maintained to the end of the study. The experimental system was reported as highly usable, enjoyable, and motivating. Our results support the clinical effectiveness of mixed reality interventions that satisfy the motor learning principles for upper limb rehabilitation in chronic stroke survivors. This characteristic, together with the low cost of the system, its portability, and its acceptance could promote the integration of these systems in the clinical practice as an alternative to more expensive systems, such as robotic instruments.