LLukas22/scidocs huggingface dataset:
Quantitation of and superficial surgical landmarks for the anterior interosseous nerve.

OBJECT
There are scant data regarding the anterior interosseous nerve (AIN) in the neurosurgical literature. In the current study the authors attempt to provide easily identifiable superficial osseous landmarks for the identification of the AIN.


METHODS
The AIN in 20 upper extremities obtained in adult cadaveric specimens was dissected and quantified. Measurements were obtained between the nerve and surrounding superficial osseous landmarks. The AIN originated from the median nerve at mean distances of 5.4 cm distal to the medial epicondyle of the humerus and 21 cm proximal to the ulnar styloid process. The distance from the origin of the AIN to its branch leading to the flexor pollicis longus muscle and to the point it travels deep to the pronator quadratus (PQ) muscle measured a mean 4 and 14.4 cm, respectively. The mean distance from the AIN branch leading to the flexor pollicis longus muscle to the proximal PQ muscle was 12.1 cm, and the mean distance between this branch and the ulnar styloid process was 7.2 cm. The mean diameter of the AIN was 1.6 mm at the midforearm.


CONCLUSIONS
Additional landmarks for identification of the AIN can aid the neurosurgeon in more precisely isolating this nerve and avoiding complications. Furthermore, after quantitation of this nerve, the AIN branches can be easily used for neurotization of the median and ulnar nerves, and with the aid of a transinterosseous membrane tunneling technique, passed to the posterior interosseous nerve.
Research on allocation efficiency of the redistributed pseudo inverse algorithm

Allocation efficiency is an important performance index to measure the quality of the allocation algorithm. In order to compute the efficiency, the volume of the subset of attainable moments must be solved. The efficiency of the redistributed pseudo inverse (RPI) algorithm depends on the choice of the pseudo-inverse matrix. The subset of attainable moments of RPI is a complex non-convex polyhedron. By analyzing two-dimensional and three-dimensional allocation problems with a “micro-element” method, here we propose an approximate calculation algorithm to compute the volume of the non-convex polyhedron. In order to improve the allocation efficiency of RPI, genetic algorithm is used to find the best pseudo-inverse matrix. The simulation results show that the best pseudo-inverse matrix can be easily chosen by the proposed method and the high allocation efficiency is achieved.
Evaluation of the Antioxidant Activity of Syzygium cumini Leaves

The antioxidant activity of Syzygium cumini leaf extracts was investigated using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical-scavenging and ferric-reducing antioxidant power (FRAP) assays. The methanolic extract and its four water, ethyl acetate, chloroform, and n-hexane fractions were prepared and subjected to antioxidant evaluation. The results showed that the ethyl acetate fraction had stronger antioxidant activity than the other ones. HPLC data indicated that S. cumini leaf extracts contained phenolic compounds, such as ferulic acid and catechin, responsible for their antioxidant activity. A significant linear relationship between antioxidant potency, free radical-scavenging ability and the content of phenolic compounds of leaf extracts supported this observation.
The Effect of DPT-1 Intravenous Insulin Infusion and Daily Subcutaneous Insulin on Endogenous Insulin Secretion and Postprandial Glucose Tolerance

OBJECTIVE
To investigate the effect of parenteral insulin therapy on endogenous insulin secretion in the Diabetes Prevention Trial-Type 1 (DPT-1).


RESEARCH DESIGN AND METHODS
In the parenteral insulin arm of DPT-1, subjects without diabetes at high risk of future type 1 diabetes randomized to active treatment received a yearly 4-day intravenous insulin infusion (IV-I) and daily subcutaneous insulin (SC-I). To examine the effects of these insulin therapies on endogenous insulin secretion, C-peptide and glucose levels were compared during oral glucose tolerance tests (OGTTs) performed on and off IV-I and SC-I. Forty-six paired OGTTs were performed in 30 subjects from DPT-1 to determine the effect of IV-I. Twenty paired OGTTs were performed in 15 subjects from DPT-1 to determine the effect of SC-I.


RESULTS
IV-I suppressed fasting and OGTT-stimulated C-peptide (62% and 40%, respectively), and it significantly lowered fasting glucose (67.4 ± 4.5 mg/dL during IV-I vs. 90.9 ± 1.8 mg/dL off insulin; P < 0.05). By contrast, post-OGTT glucose levels were significantly higher during IV-I: Glucose during IV-I versus off insulin at 120 min was 203.9 ± 15.1 vs. 151.6 ± 10.2 mg/dL, respectively (P < 0.05); 49% of OGTTs became transiently diabetic (>200 mg/dL at 120 min) when receiving IV-I. Fasting glucose was significantly lower when receiving SC-I versus when off insulin (85 ± 3 vs. 94 ± 2 mg/dL, respectively; P < 0.05), but SC-I did not significantly alter fasting or OGTT-stimulated C-peptide compared with being off insulin.


CONCLUSIONS
These data demonstrate that the IV-I used in the DPT-1 markedly suppressed endogenous insulin secretion, which was frequently associated with postprandial glucose intolerance. SC-I, however, did not.
Visualization of Bibliographic Networks with a Reshaped Landscape Metaphor

We describe a novel approach to visualize bibliographic networks that facilitates the simultaneous identification of clusters (e.g., topic areas) and prominent entities (e.g., surveys or landmark papers). While employing the landscape metaphor proposed in several earlier works, we introduce new means to determine relevant parameters of the landscape. Moreover, we are able to compute prominent entities, clustering of entities, and the landscape’s surface in a surprisingly simple and uniform way. The effectiveness of our network visualizations is illustrated on data from the graph drawing literature.
The effect of high-flux hemodialysis on hemoglobin concentrations in patients with CKD: results of the MINOXIS study.

BACKGROUND AND OBJECTIVES
Hemodialysis treatment induces markers of inflammation and oxidative stress, which could affect hemoglobin levels and the response to erythropoietin use. This study sought to determine whether high-flux dialysis would help improve markers of renal anemia, inflammation, and oxidative stress compared with low-flux dialysis.


DESIGN, SETTINGS, PARTICIPANTS, & MEASUREMENTS
In a prospective, controlled study, 221 patients undergoing maintenance hemodialysis and receiving darbepoetin-alfa treatment (mean age, 66 years; 55% male) from 19 centers were screened in a 20-week run-in period of low-flux hemodialysis with a synthetic dialysis membrane. Thereafter, 166 patients were enrolled and randomly assigned to receive a synthetic high-flux membrane or to continue on low-flux dialysis for 52 weeks. Data on myeloperoxidase, oxidized LDL, high-sensitivity C-reactive protein, and the Malnutrition Inflammation Score were collected at baseline and after 52 weeks; routine laboratory data, such as hemoglobin, ferritin, and albumin, and the use of darbepoetin-alfa, were also measured in the run-in period. Results After 52 weeks, the low-flux and the high-flux groups did not differ with respect to hemoglobin (mean ± SD, 11.7±0.9 g/dl versus 11.7±1.1 g/dl; P=0.62) or use of darbepoetin-alfa (mean dosage ± SD, 29.8±24.8 μg/wk versus 26.0±31.1 μg/wk; P=0.85). Markers of inflammation, oxidative stress, or nutritional status also did not differ between groups.


CONCLUSION
Over 1 year, high-flux dialysis had no superior effects on hemoglobin levels or markers of inflammation, oxidative stress, and nutritional status. These data do not support the hypothesis that enhanced convective toxin removal would improve patient outcome.
Radial force and torque ripple optimization for acoustic noise reduction of SRM drives via fuzzy logic control

This paper presents a simple procedure for acoustic noise reduction in switched reluctance motor (SRMs) drive. The main sources of acoustic noise in a SRM are the radial magnetic force and torque ripple. Investigations of a radial force require an analytical relationship between motor designs and drive parameters. Thus, in this method two mathematical methods for calculation of radial force and torque have been proposed. These non-linear relations appeared phase current is one of the important factors in the SRM drive parameters because radial force and torque is dependent on square of current, directly. In this paper, torque ripple and radial force reduction with optimization of current waveform by fuzzy logic control has been presented. In the regions that torque reduces and radial force be not maximized the FL inject additional current for each phase currents. This drive has been simulated with MATLAB/SIMULINK for nonlinear model of the SRM. The Simulation results show that proposed drive will decreases maximum radial force and torque ripple but will keep of the maximum torque. This drive has the advantages of simple implementation on the every SRM drive without extra hardware, low cost, high reliability and because of low vibration excellent performance at long term.
Walking away from the Desktop Computer: Distributed Collaboration and Mobility in a Product Design Team

A study of a spatially distributed product design team shows that most members are rarely at their individual desks. Mobility is essential for the use of shared resources and for communication. It facilitates informal interactions and awareness unavailable to colleagues at remote sites. Implications for technology design include portable and distributed computing resources, in particular, moving beyond individual workstation-centric CSCW applications.
The positive effects of negative work: increased muscle strength and decreased fall risk in a frail elderly population.

BACKGROUND
The objective of this study was to determine if a chronic eccentric training intervention, i.e., negative work, could limit or even reverse sarcopenia and its related impairments and functional limitations. Is high-force eccentric training tolerable by elderly people and will it result in improved muscle size, strength, balance, and fall risk?


METHODS
21 frail elderly subjects (mean age, 80 years) experienced 11 weeks of lower extremity resistance training. The experimental eccentric (ECC) group (n=11) performed negative work while exercising on a high-force eccentric ergometer. The active "controls" performed traditional (TRAD) (n=10) lower extremity resistance exercises (weight training). Muscle fiber cross-sectional area and strength, balance, stair descending abilities, and fall risk were assessed prior to and following this intervention.


RESULTS
All ECC subjects who started the negative work intervention completed the study and reported the training to be relatively effortless; they experienced minimal and transient muscle soreness. Both groups experienced a significant increase in muscle fiber cross-sectional area (ECC=60%, TRAD=41%). Only the ECC group experienced significant improvements in strength (60%), balance (7%), and stair descent (21%) abilities. The timed up and go task improved in both groups, but only the ECC group went from a high to a low fall risk.


CONCLUSIONS
These data demonstrate that lower extremity resistance exercise can improve muscle structure and function in those with limited exercise tolerance. The greater strength increase following negative work training resulted in improved balance, stair descent, and fall risk only in the ECC group. Because low energy cost is coupled to high force production with eccentric exercise, this intervention may be useful for a number of patients that are otherwise unable to achieve high muscle forces with traditional resistance exercise.
Importance of lymph node dissection in thymic carcinoma.

BACKGROUND
Lymph node dissection plays important role in oncologic surgery. We investigated outcomes of lymph node dissection in thymic carcinoma.


METHODS
We retrospectively reviewed 37 patients, who underwent complete resection for thymic carcinoma. Patients were divided into four groups: no node dissection (Nx), 8; pathologic N0 by limited dissection (N0a), 13; pathologic N0 by extensive dissection (N0b), 10; and node metastasis (N1), 6. Outcomes of lymph node dissection were investigated. Disease-free survival (DFS) and freedom from recurrence of the four groups were compared.


RESULTS
A total of 349 lymph nodes were dissected in 29 patients. Metastasis was confirmed in 19 nodes in 6 patients, with tumor invading adjacent organs. Anterior mediastinal lymph node metastasis was confirmed in 4 patients. Intrathoracic lymph node metastasis was confirmed in 3 patients at the right paratracheal lymph nodes. Recurrences were diagnosed in 11 patients (Nx, 2; N0a, 4; N0b, 1; N1, 4). The 5-year overall survival rate was 65.5%, DFS was 60.9%, and freedom from recurrence was 68.2%. DFS rates of the N0b subgroup were significantly better than in the N1 subgroup (90% vs 33.3%). DFS rates of the Nx and N0a subgroups were similar (75% vs 48.7%, p=0.98), and the prognoses of both groups were intermediate between the N0b and N1 groups. Analyses of freedom from recurrence proved identical results.


CONCLUSIONS
Extensive lymph node dissection, meaning dissection of more than 10 lymph nodes, is required to predict prognosis accurately. Anterior mediastinal and right paratracheal lymph nodes should be dissected in thymic carcinoma.
Unsupervised representation learning of structured radio communication signals

We explore unsupervised representation learning of radio communication signals in raw sampled time series representation. We demonstrate that we can learn modulation basis functions using convolutional autoencoders and visually recognize their relationship to the analytic bases used in digital communications. We also propose and evaluate quantitative metrics for quality of encoding using domain relevant performance metrics.
Toward movement-invariant automatic lip-reading and speech recognition

We present the development of a modular system for flexible human-computer interaction via speech. The speech recognition component integrates acoustic and visual information (automatic lip-rcading) improving overall recognition, especially in noisy en­ vironments. The image of the lips, constituting the visual input, is automatically extracted from the camera picture of the speaker's face by the lip locator module. Finally, the speaker's face is au­ tomatically acquired and followed by the face tracker sub-system. Integration of the three functions results in thc first bi-modal speech recognizer allowing the speaker reasonable freedom of movement within a possibly noisy room while continuing to communicate with the computer via voice. Compared to audio-alone recogni­ tion, the combined system achieves a 20 to 50 percent error rate reduction for various signaVnoise conditions.
Rapid deployment of an electronic disease surveillance system in the state of Utah for the 2002 Olympic Winter Games

The key to minimizing the effects of an intentionally caused disease outbreak is early detection of the attack and rapid identification of the affected individuals. The Bush administration's leadership in advocating for biosurveillance systems capable of monitoring for bioterrorism attacks suggests that we should move quickly to establish a nationwide early warning biosurveillance system as a defense against this threat. The spirit of collaboration and unity inspired by the events of 9-11 and the 2002 Olympic Winter Games in Salt Lake City provided the opportunity to demonstrate how a prototypic biosurveillance system could be rapidly deployed. In seven weeks we were able to implement an automated, real-time disease outbreak detection system in the State of Utah and monitored 80,684 acute care visits occurring during a 28-day period spanning the Olympics. No trends of immediate public health concern were identified.
An Adaptive Combination Query Tree Protocol for Tag Identification in RFID Systems

A reader must be able to identify tags as quickly as possible, so tag anti-collision is a significant issue for the RFID system. In this paper, we propose a novel tag anti-collision protocol (ACQT), which is suitable for a large mobile tags environment. Based on a 3-ary tree, it has the optimal capacity to identify for tree-based protocols. Using a combination query tree, it can solve the problem of not being able to generate a 3-ary tree when the length of a tag's ID is not a multiple of 3. The joining and leaving strategies can efficiently be applied for tag mobility. The simulation results show that the protocol we present can achieve better performance than previous protocols by decreasing identification delay, collision cycles and idle cycles.
Recognizing and measuring self-regulated learning in a mobile learning environment

With the realization that more research is needed to explore external factors (e.g., pedagogy, parental involvement in the context of K-12 learning) and internal factors (e.g., prior knowledge, motivation) underlying student-centered mobile learning, the present study conceptually and empirically explores how the theories and methodologies of self-regulated learning (SRL) can help us analyze and understand the processes of mobile learning. The empirical data collected from two elementary science classes in Singapore indicates that the analytical SRL model of mobile learning proposed in this study can illuminate the relationships between three aspects of mobile learning: students’ self-reports of psychological processes, patterns of online learning behavior in the mobile learning environment (MLE), and learning achievement. Statistical analyses produce three main findings. First, student motivation in this case can account for whether and to what degree the students can actively engage in mobile learning activities metacognitively, motivationally, and behaviorally. Second, the effect of students’ self-reported motivation on their learning achievement is mediated by their behavioral engagement in a pre-designed activity in the MLE. Third, students’ perception of parental autonomy support is not only associated with their motivation in school learning, but also associated with their actual behaviors in self-regulating their learning. ! 2011 Elsevier Ltd. All rights reserved.
Understanding Policy in the Great Recession: Some Unpleasant Fiscal Arithmetic

I use the valuation equation of government debt to understand fiscal and monetary policy in and following the great recession of 2008-2009. I also examine policy alternatives to avoid deflation, and how fiscal pressures might lead to inflation. I conclude that the central bank may be almost powerless to avoid deflation or inflation; that an eventual fiscal inflation can come well before large deficits or monetization are realized, and that it is likely to come with stagnation rather than a boom. ∗University of Chicago Booth School of Business and NBER. 5807 S. Woodlawn, Chicago, IL 60637. john.cochrane@chicagobooth.edu; http://faculty.chicagobooth.edu/john.cochrane/research/Papers/. I thank many conferece participants, an anonymous referee, and especially Michael Woodford for helpful comments. I thank Francisco Vaquez-Grande for the surplus plot. I acknowledge research support from CRSP.
Get Training or Wait? Long-Run Employment Effects of Training Programs for the Unemployed in West Germany

Long–term public sector sponsored training programs often show little or negative short–run employment effects and often it is not possible to assess whether positive long–run effects exist. Based on unique administrative data, this paper estimates the long–run differential employment effects of three different types of training programs in West Germany. We use inflows into unemployment for the years 1986/87 and 1993/94 and apply local linear matching based on the estimated propensity score to estimate the effects of training programs starting during 1 to 2, 3 to 4, and 5 to 8 quarters of unemployment. The results show a negative lock– in effect for the period right after the beginning of the programs and significantly positive treatment effects on employment rates in the medium and long run. The differential effects of the three programs compared to one another are mainly driven by differences in the length of the lock–in periods.
Improving information security awareness and behaviour through dialogue, participation and collective reflection. An intervention study

The paper discusses and evaluates the effects of an information security awareness programme. The programme emphasised employee participation, dialogue and collective reflection in groups. The intervention consisted of small-sized workshops aimed at improving information security awareness and behaviour. An experimental research design consisting of one survey before and two after the intervention was used to evaluate whether the intended changes occurred. Statistical analyses revealed that the intervention was powerful enough to significantly change a broad range of awareness and behaviour indicators among the intervention participants. In the control group, awareness and behaviour remained by and large unchanged during the period of the study. Unlike the approach taken by the intervention studied in this paper, mainstream information security awareness measures are typically top-down, and seek to bring about changes at the individual level by means of an expert-based approach directed at a large population, e.g. through formal presentations, e-mail messages, leaflets and posters. This study demonstrates that local employee participation, collective reflection and group processes produce changes in short-term information security awareness and behaviour. a 2009 Elsevier Ltd. All rights reserved.
Stratification bias in low signal microarray studies

When analysing microarray and other small sample size biological datasets, care is needed to avoid various biases. We analyse a form of bias, stratification bias, that can substantially affect analyses using sample-reuse validation techniques and lead to inaccurate results. This bias is due to imperfect stratification of samples in the training and test sets and the dependency between these stratification errors, i.e. the variations in class proportions in the training and test sets are negatively correlated. We show that when estimating the performance of classifiers on low signal datasets (i.e. those which are difficult to classify), which are typical of many prognostic microarray studies, commonly used performance measures can suffer from a substantial negative bias. For error rate this bias is only severe in quite restricted situations, but can be much larger and more frequent when using ranking measures such as the receiver operating characteristic (ROC) curve and area under the ROC (AUC). Substantial biases are shown in simulations and on the van 't Veer breast cancer dataset. The classification error rate can have large negative biases for balanced datasets, whereas the AUC shows substantial pessimistic biases even for imbalanced datasets. In simulation studies using 10-fold cross-validation, AUC values of less than 0.3 can be observed on random datasets rather than the expected 0.5. Further experiments on the van 't Veer breast cancer dataset show these biases exist in practice. Stratification bias can substantially affect several performance measures. In computing the AUC, the strategy of pooling the test samples from the various folds of cross-validation can lead to large biases; computing it as the average of per-fold estimates avoids this bias and is thus the recommended approach. As a more general solution applicable to other performance measures, we show that stratified repeated holdout and a modified version of k-fold cross-validation, balanced, stratified cross-validation and balanced leave-one-out cross-validation, avoids the bias. Therefore for model selection and evaluation of microarray and other small biological datasets, these methods should be used and unstratified versions avoided. In particular, the commonly used (unbalanced) leave-one-out cross-validation should not be used to estimate AUC for small datasets.