Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Surgical Complications: A New Proposal With Evaluation in a Cohort of 6336 Patients and Results of a Survey

Objective:Although quality assessment is gaining increasing attention, there is still no consensus on how to define and grade postoperative complications. This shortcoming hampers comparison of outcome data among different centers and therapies and over time. Patients and Methods:A classification of complications published by one of the authors in 1992 was critically re-evaluated and modified to increase its accuracy and its acceptability in the surgical community. Modifications mainly focused on the manner of reporting life-threatening and permanently disabling complications. The new grading system still mostly relies on the therapy used to treat the complication. The classification was tested in a cohort of 6336 patients who underwent elective general surgery at our institution. The reproducibility and personal judgment of the classification were evaluated through an international survey with 2 questionnaires sent to 10 surgical centers worldwide. Results:The new ranking system significantly correlated with complexity of surgery (P < 0.0001) as well as with the length of the hospital stay (P < 0.0001). A total of 144 surgeons from 10 different centers around the world and at different levels of training returned the survey. Ninety percent of the case presentations were correctly graded. The classification was considered to be simple (92% of the respondents), reproducible (91%), logical (92%), useful (90%), and comprehensive (89%). The answers of both questionnaires were not dependent on the origin of the reply and the level of training of the surgeons. Conclusions:The new complication classification appears reliable and may represent a compelling tool for quality assessment in surgery in all parts of the world.
Tethered Swimming for the Evaluation and Prescription of Resistance Training in Young Swimmers

Abstract The aims of the present study were 1) to evaluate the effects of 11 weeks of a typical free-swimming training program on aerobic and stroke parameters determined in tethered swimming (Study 1; n=13) and 2) to investigate the responses of tethered swimming efforts, in addition to free-swimming sessions, through 7 weeks of training (Study 2; n=21). In both studies, subjects performed a graded exercise test in tethered swimming (GET) to determine anaerobic threshold (AnT), stroke rate at AnT (SRAnT), peak force at GET (PFGET) and peak blood lactate ([La-]GET). Participants also swam 100-, 200- and 400-m lengths to evaluate performance. In Study 2, swimmers were divided into control (i. e., only free-swimming; GC [n=11]) and tethered swimming group (i. e., 50% of the main session; GTS [n=10]). The results of Study 1 demonstrate that AnT, PFGET, [La-]GET and 200-m performance were improved with free-swimming training. The SRAnT decreased with training. In Study 2, free-swimming performance and most of the graded exercise test parameters were not altered in either group. However, [La-]GET improved only for GTS. These results demonstrate that aerobic parameters obtained in tethered swimming can be used to evaluate free-swimming training responses, and the addition of tethered efforts during training routine improves the lactate production capacity of swimmers.
Volcano-seismic signal detection and classification processing using hidden Markov models. Application to San Cristóbal volcano, Nicaragua

We present a method for automatic seismic event detection and classification, focusing on volcanic-seismic signals by means of the validity of the hidden Markov modeling (HMM) method in active volcanoes. Recordings of different seismic event types are studied at one active volcano; San Cristobal in Nicaragua. We use data from one field surveys carried out in February to March 2006. More than 600 hours of data in San Cristobal volcano were analyzed and 1098 seismic events were registered at short period stations. These events were manually labelled by a single expert technicians and identified three types classes of signals (S1, S2, S3) and tremor background seismic noise (NS). The method analyzes the seismograms comparing the characteristics of the data to a number of event classes defined beforehand. If a signal is present, the method detects its occurrence and produces a classification. From the application performed over our data set, we have demonstrated that in order to have a reliable result, a careful and adequate segmentation process is crucial. Also, each type of signals requires its own characterization. That is, each signal type must be represented by its own specific model, which would include the effects of source, path and sites. Once we have built this model, the success level of the system is high. Extensive performance evaluation is conducted to derive the optimal configuration of the different parameters Correct classification rates of up to 80% are achieved. The high success rates obtained imply that the method is fully able to detect, isolate, and identify seismic signals on raw seismic data. These results imply that, once an adequate training process has been used, the present method is particularly appropriate to work in real time, and in parallel to the data acquisition.
Novel Roles of Specific Isoforms of Protein Kinase C in Activation of the c-fos Serum Response Element

ABSTRACT Protein kinase C (PKC) is a multigene family of enzymes consisting of at least 11 isoforms. It has been implicated in the induction of c-fos and other immediate response genes by various mitogens. The serum response element (SRE) in the c-fospromoter is necessary and sufficient for induction of transcription of c-fos by serum, growth factors, and the phorbol ester 12-O-tetradecanoylphorbol-13-acetate (TPA). It forms a complex with the ternary complex factor (TCF) and with a dimer of the serum response factor (SRF). TCF is the target of several signal transduction pathways and SRF is the target of the rhoA pathway. In this study we generated dominant-negative and constitutively active mutants of PKC-α, PKC-δ, PKC-ɛ, and PKC-ζ to determine the roles of individual isoforms of PKC in activation of the SRE. Transient-transfection assays with NIH 3T3 cells, using an SRE-driven luciferase reporter plasmid, indicated that PKC-α and PKC-ɛ, but not PKC-δ or PKC-ζ, mediate SRE activation. TPA-induced activation of the SRE was partially inhibited by dominant negative c-Raf, ERK1, or ERK2, and constitutively active mutants of PKC-α and PKC-ɛ activated the transactivation domain of Elk-1. TPA-induced activation of the SRE was also partially inhibited by a dominant-negative MEKK1. Furthermore, TPA treatment of serum-starved NIH 3T3 cells led to phosphorylation of SEK1, and constitutively active mutants of PKC-α and PKC-ɛ activated the transactivation domain of c-Jun, a major substrate of JNK. Constitutively active mutants of PKC-α and PKC-ɛ could also induce a mutant c-fos promoter which lacks the TCF binding site, and they also induce transactivation activity of the SRF. Furthermore, rhoA-mediated SRE activation was blocked by dominant negative mutants of PKC-α or PKC-ɛ. Taken together, these findings indicate that PKC-α and PKC-ɛ can enhance the activities of at least three signaling pathways that converge on the SRE: c-Raf–MEK1–ERK–TCF, MEKK1-SEK1-JNK-TCF, and rhoA-SRF. Thus, specific isoforms of PKC may play a role in integrating networks of signal transduction pathways that control gene expression.
Computational Biology Modeling across Different Scales

One of the most formidable challenges in modern biology is to get a unified view of the various mechanisms governing the behavior and of the causal relationships among different parts of a living system. It is coming clearer nowadays that to get such comprehensive picture computational models embracing different observation levels in space and time have to be formulated to explain the enormous amount of data deriving from -omic high throughput measurements methods. In this article we aim at giving a meaning to the concept of multi-scale modeling in the framework of studies of biological systems with particular interest in understanding human physiology in disease conditions.
Event detection of underwater acoustic data from MACHO hydrophone

This paper presents an automated event detector of long time series of hydrophone data from Marine Cable Hosted Observatory (MACHO) system installed by the Central Weather Bureau in the offshore region of Taiwan's northeast coast. The detector includes time-varying ambient noise level estimation via SEL (Sound Exposure Level per second) and Leq (equivalent continuous sound level, averaged over 30 seconds), and an energy detector with the estimated ambient noise level as threshold. A user friendly UI (user interface) is written to enhance the utilization. A full year of data are analyzed with the detector, and the results are satisfactory in the robustness the detection rate and the efficiency of analysis of large amount of data.
Linguistically-motivated Tree-based Probabilistic Phrase Alignment

In this paper, we propose a probabilistic phrase alignment model based on dependency trees. This model is linguistically-motivated, using syntactic information during alignment process. The main advantage of this model is that the linguistic difference between source and target languages is successfully absorbed. It is composed of two models: Model1 is using content word translation probability and function word translation probability; Model2 uses dependency relation probability which is defined for a pair of positional relations on dependency trees. Relation probability acts as tree-based phrase reordering model. Since this model is directed, we combine two alignment results from bi-directional training by symmetrization heuristics to get definitive alignment. We conduct experiments on a Japanese-English corpus, and achieve reasonably high quality of alignment compared with word-based alignment model.
Paraveinal Mesophyll of Soybean Leaves in Relation to Assimilate Transfer and Compartmentation : III. Immunohistochemical Localization of Specific Glycopeptides in the Vacuole after Depodding.

Immunohistochemical staining was used to determine the cellular distribution of two glycosylated polypeptides (molecular weights of 27 and 29 kilodaltons) which are normally present at low levels in soybean (Glycine max var ;Wye') leaves but which markedly accumulate after depodding. These polypeptides, which comprise a substantial portion of the total leaf soluble protein of depodded plants, were exclusively located in the vacuoles of paraveinal mesophyll and associated bundle sheath cells. These results support the unique role of the soybean leaf paraveinal mesophyll in the transport and spatial compartmentation of nitrogen reserves in relation to seed filling.
Right place, right time, right peptide: DO keeps DM focused

Summary: Peptide loading of major histocompatibility class II molecules is catalyzed in late endosomal and lysosomal compartments of cells by the catalytic action of human leukocyte antigen (HLA)‐DM (H‐2M in mice). In B cells, dendritic cells and thymic epithelial cells, the peptide loading of class II molecules is modified by the expression of the non‐classical class II molecule, HLA‐DO (H‐2O in mice). Collectively, studies to date support that DO/H‐2O expression inhibits the presentation of antigens acquired by cells via fluid phase endocytosis. However, in B cells, the expression of H‐2O promotes the presentation of antigens internalized by the B‐cell receptor. In this review, we summarize the literature pertaining to DO assembly, transport, and function, with an emphasis on the function of DO/H‐2O.
An Effective Training Method For Deep Convolutional Neural Network

In this paper, we propose the nonlinearity generation method to speed up and stabilize the training of deep convolutional neural networks. The proposed method modifies a family of activation functions as nonlinearity generators (NGs). NGs make the activation functions linear symmetric for their inputs to lower model capacity, and automatically introduce nonlinearity to enhance the capacity of the model during training. The proposed method can be considered an unusual form of regularization: the model parameters are obtained by training a relatively low-capacity model, that is relatively easy to optimize at the beginning, with only a few iterations, and these parameters are reused for the initialization of a higher-capacity model. We derive the upper and lower bounds of variance of the weight variation, and show that the initial symmetric structure of NGs helps stabilize training. We evaluate the proposed method on different frameworks of convolutional neural networks over two object recognition benchmark tasks (CIFAR-10 and CIFAR-100). Experimental results showed that the proposed method allows us to (1) speed up the convergence of training, (2) allow for less careful weight initialization, (3) improve or at least maintain the performance of the model at negligible extra computational cost, and (4) easily train a very deep model.
Encoding and the rea for speech signals

A number of different possible explanations are distinguished for the findings on the right ear advantage (REA) for speech signals varied in their acoustic and phonetic properties. Two experiments are reported, using synthesized semivowels and vowels in monosyllable word frames. Both show REA. The detailed results of both experiments support the idea that a complicated “encoded” relationship between the acoustical stimulus and the response phoneme is a necessary condition for the REA, but that the encoding need only be signalled by an acoustical “trigger feature” in the stimulus; a task requiring a perceptual decoding is not necessary for REA to occur.
The Impact of Participant Characteristics on Use and Satisfaction of a Web-Based Computer-Tailored Chronic Obstructive Pulmonary Disease Self-Management Intervention: A Process Evaluation

Background A randomized controlled trial (RCT) showed that a Web-based computer-tailored self-management intervention for people with or at risk for chronic obstructive pulmonary disease (COPD) did not have a significant treatment effect. Process evaluation measures such as application use and satisfaction with the intervention can help understand these results. Objectives The aim of this paper is to uncover reasons for suboptimal application use, evaluate satisfaction with the intervention, and investigate which participant characteristics predict application use and user satisfaction. Methods Participants were recruited through 2 different channels: an online panel and general practice. The intervention group received the intervention, which consisted of 2 modules (smoking cessation and physical activity). The control group received no intervention. The study employed a mixed methods design. Quantitative and qualitative data were gathered assessing participant characteristics, application use, reasons for not using the application, and satisfaction with the intervention. Results The RCT included 1325 participants. The proportion of individuals who participated was significantly higher in the online group (4072/6844, 59.5%) compared to the general practice group (43/335, 12.8%) (P<.001). Application use was low. Of all participants in the intervention group, 52.9% (348/658) initiated use of one or both modules, 36.0% (237/658) completed an intervention component (prolonged use), and 16.6% (109/658) revisited one of the modules after completing an intervention component (sustained use). Older age, established diagnosis of COPD, or experiencing breathlessness predicted sustained use. Participant satisfaction with the 2 modules was 6.7 (SD 1.6) on a scale from 0 to 10. The interviews revealed that a computer application was believed not to be sufficient and the help of a health care professional was necessary. Participants with a greater intention to change were more satisfied with the application. Conclusions The application was not used sufficiently. Study materials should be further tailored to younger individuals, those at risk for COPD, and those who do not experience breathlessness in order to increase sustained use among them. Involvement of a health care professional could improve satisfaction with the intervention and potentially increase engagement with the intervention materials. However, to make this possible, recruitment in general practice needs to be improved. Recommendations are made for improving the study design, strengthening the intervention (eg, practice facilitation), and linking the computer application to interaction with a health care provider.
Isolation enhancement between two vertical monopole antennas using two printed strips

In this paper, two vertical metallic strips printed on a dielectric substrate are utilized to enhance the isolation between two monopoles. Each monopole is fed by a coplanar waveguide. The monopoles are placed in a close proximity of 10 mm, 0.08 λ<inf>o</inf>, where λ<inf>o</inf> is the wavelength at 2.4 GHz. The two-antenna array provides a bandwidth of 90 MHz (2.39 GHz–2.48 GHz) over which S<inf>11</inf> and S<inf>22</inf> are ≤ −10 dB and S<inf>21</inf> ≤ −17 dB and a bandwidth of 60 MHz in which S<inf>21</inf> is ≤ −20 dB. The isolation in terms of S<inf>12</inf> has been reduced by 14 dB from −9 dB when no decoupling structure is used. The array achieves a realized gain of 1.84 dB. The design represents a good candidate for modern wireless systems utilizing MIMO techniques including Wi-Fi, 4G LTE, as well as systems utilizing ISM spectrum.
Fuzzy Logic Approach to Forecast the Extendibility/Extensibility in Object Oriented Design using an Integrated Model

number of researchers have conducted various empirical studies on the software metrics for Object Oriented design. The research proved that some of these metrices are very useful for forcasting the quality attributes of the software like extendibility/extensibility, effectiveness, reliability and maintainability. In this paper a hybrid approach is proposed for investigating the extendibility/extensibility of classes in Object Oriented design.Tthe hybrid approach will comprised of subset of CK netric suite and mood netric suite. These days a great demand occur for finding software measurement so that quality of software can be forcasted. Therefore software engineering require various quality models that can be used for forcasting the characteristics for quality such as extendibility/extensibility, effectiveness, reliability and maintainability. The main objective of this work is to experimentally forecast the association between OOD metrics and extendibility/extensibility.
Cellular dynamics of epithelial clefting during branching morphogenesis of the mouse submandibular gland

We cultured the rudimental submandibular gland (SMG) of mice with a non–cell‐permeable fluorescent tracer, and observed cell behavior during epithelial branching morphogenesis using confocal time‐lapse microscopy. We traced movements of individual cells as shadowgraph movies. Individual epithelial cells migrated dynamically but erratically. The epithelial cleft extended by wiggling and separated a cluster of cells into two buds during branching. We examined the ultrastructure of the clefts in SMG rudiments treated with the laminin peptide A5G77f, which induces epithelial clefting. A short cytoplasmic shelf with a core of microfilaments was found at the deep end of the cleft. We propose that epithelial clefting involves a dynamic movement of cells at the base of the cleft, and the formation of a shelf within a cleft cell. The shelf might form a matrix attachment point at the base of the cleft with a core of microfilaments driving cleft elongation. Developmental Dynamics 239:1739–1747, 2010. © 2010 Wiley‐Liss, Inc.
Time synchronization and data fusion for RGB-Depth cameras and inertial sensors in AAL applications

Ambient Assisted Living applications often need to integrate data from multiple sensors, to provide consistent information on the observed phenomena. Data fusion based on samples from several sensors requires accurate time synchronization with sufficient resolution, depending on the sensor sampling frequency. This work presents a technical platform for the efficient and accurate synchronization of the data captured from RGB-Depth cameras and wearable inertial sensors, that can be integrated in AAL solutions. A case study of sensor data fusion for Timed Up and Go test is also presented and discussed.
DrinkSense: Characterizing Youth Drinking Behavior Using Smartphones

Alcohol consumption is the number one risk factor for morbidity and mortality among young people. In late adolescence and early adulthood, excessive drinking and intoxication are more common than in any other life period, increasing the risk of adverse physical and psychological health consequences. In this paper, we examine the feasibility of using smartphone sensor data and machine learning to automatically characterize and classify drinking behavior of young adults in an urban, ecologically valid nightlife setting. Our work has two contributions. First, we use previously unexplored data from a large-scale mobile crowdsensing study involving 241 young participants in two urban areas in a European country, which includes phone data (location. accelerometer, Wifi, Bluetooth, battery, screen, and app usage) along with self-reported, fine-grain data on individual alcoholic drinks consumed on Friday and Saturday nights over a three-month period. Second,we build a machine learning methodology to infer whether an individual consumed alcohol on a given weekend night, based on her/his smartphone data contributed between 8 PM and 4 AM. We found that accelerometer data is the most informative single cue, and that a combination of features results in an overall accuracy of 76.6 percent.
The Origins and Early Development of Mediterranean Maritime Activity

The Mediterranean is one of the world's two earliest foci of maritime activity. Recent discoveries shed new light on the times and places at which such activity began, and on the reasons why it did so. Lower and Middle Palaeolithic data continue to provide inconclusive evidence. Maritime activity remained modest for much of the Upper Palaeolithic (in contrast to Island Southeast Asia and the Pacific), and was perhaps linked to relocations due to adverse environmental conditions. The break-through, in the form of a shift from the use of a littoral resource to the development of longer maritime routes, is attested on Cyprus and in the Aegean, and seems to have taken place during the harsh climate of the Younger Dryas. Subsequently, seafaring in the eastern sub-basins of the Mediterranean became associated with the expansion dynamics of Neolithic groups, and may have been transferred with farming to the centre and west, where prior signs of comparable activity are generally less evident.