Miracle-dz/UniFAR-FTUs huggingface dataset:
Posthepatectomy Portal Vein Pressure Predicts Liver Failure and Mortality after Major Liver Resection on Noncirrhotic Liver

Objectives:To evaluate the predictive value of portal vein pressure (PVP) after major liver resection for posthepatectomy liver failure (PLF) and 90-day mortality in patients without cirrhosis. Background:As elevated PVP is associated with liver failure after living donor liver transplantation, we hypothesized that the outcome after major hepatectomy may be influenced by posthepatectomy PVP. Patients and Methods:All patients without severe fibrosis or cirrhosis who underwent a major liver resection (≥3 segments) with an intraoperative measurement of PVP at the end of the procedure were included. Outcome was analyzed regarding 3 most widely used definitions of PLF: “50-50” criteria, peak of serum bilirubin greater than 120 &mgr;mol/L, and grade C PLF proposed by the International Study Group of Liver Surgery (ISGLS). Receiver operating characteristic curves and logistic regression model were used to determine the optimal cutoff of PVP and independent risk factors of PLF. Results:The study population consisted of 277 patients. Posthepatectomy PVP was gradually correlated with the PLF risk. Probability for PLF was nil when PVP was 10 mm Hg or less, ranges from 13% to 16%, depending on PLF definitions, when PVP was 20 mm Hg, and from 24% to 33% when PVP was 30 mm Hg. The optimal value of posthepatectomy PVP to predict PLF was 22 mm Hg when considering the “50-50” criteria and grade C PLF (proposed by the International Study Group of Liver Surgery). A value of 21 mm Hg best predicted PLF defined by peak of serum bilirubin greater than 120 &mgr;mol/L and 90-day mortality. At multivariate analysis, posthepatectomy PVP remained an independent predictor of PLF as well as the extent of resection, intraoperative transfusion, and the presence of diabetes. The 90-day mortality was associated with PVP greater than 21 mm Hg, older than 70 years, and intraoperative transfusion. Conclusions:Posthepatectomy PVP is an independent predictive factor of PLF and of 90-day mortality after major liver resection in patients without cirrhosis. Intraoperative modulation of PVP would be advisable when PVP exceeds 20 mm Hg.
Experimental investigation of water flow in smooth and rough silicon microchannels

Water flow in smooth rectangular cross-section microchannels and microchannels with discrete rectangle roughness elements was experimentally investigated. The microchannels were microfabricated on silicon wafers and the hydraulic diameter ranged from 153 µm to 191 µm. The rectangle roughness elements mounted on the sidewall of the microchannel were 50 µm high and 50 µm wide. The global pressure drop and velocity field were measured for Reynolds numbers between 100 and 2300. For the smooth rectangular microchannels, the friction factor of the laminar flow agreed with the value predicted by classical theory. The transition from laminar to turbulent flow occurred at about Re = 2100. For the microchannels with roughness elements, the friction factor approaches the conventional value for Re < 900 and is higher than the conventional value when Re > 900. It indicates that the presence of roughness elements leads to the early transition in the microchannels. The streamwise mean velocity profiles and turbulent intensities obtained from microscopic particle image velocimetry (micro-PIV) show that the transition from laminar flow to turbulent flow occurred for Reynolds numbers ranging between 900 and 1100. This result was consistent with the experimental data of the friction factor. The experimental results of flow fields also suggest that the flow became fully developed turbulence for Re > 1400 in the rough microchannel. In the microchannel with roughness elements, large scale coherence structures are observed in the flow fields for Re < 2000.
Monitoring high-ozone events in the US Intermountain West using TEMPO geostationary satellite observations

High-ozone events, approaching or exceeding the National Ambient Air Quality Standard (NAAQS), are fre- quently observed in the US Intermountain West in associa- tion with subsiding air from the free troposphere. Monitoring and attribution of these events is problematic because of the sparsity of the current network of surface measurements and lack of vertical information. We present an Observing Sys- tem Simulation Experiment (OSSE) to evaluate the ability of the future geostationary satellite instrument Tropospheric Emissions: Monitoring of Pollution (TEMPO), scheduled for launch in 2018-2019, to monitor and attribute high-ozone events in the Intermountain West through data assimilation. TEMPO will observe ozone in the ultraviolet (UV) and vis- ible (Vis) bands to provide sensitivity in the lower tropo- sphere. Our OSSE uses ozone data from the GFDL AM3 chemistry-climate model (CCM) as the "true" atmosphere and samples it for April-June 2010 with the current surface network (CASTNet -Clean Air Status and Trends Network- sites), a configuration designed to represent TEMPO, and a low Earth orbit (LEO) IR (infrared) satellite instrument. These synthetic data are then assimilated into the GEOS- Chem chemical transport model (CTM) using a Kalman fil- ter. Error correlation length scales (500 km in horizontal, 1.7 km in vertical) extend the range of influence of observa- tions. We show that assimilation of surface data alone does not adequately detect high-ozone events in the Intermoun- tain West. Assimilation of TEMPO data greatly improves the monitoring capability, with little information added from the LEO instrument. The vertical information from TEMPO fur- ther enables the attribution of NAAQS exceedances to back- ground ozone. This is illustrated with the case of a strato- spheric intrusion.
Longitudinal Changes in Poststroke Spatiotemporal Gait Asymmetry Over Inpatient Rehabilitation

Background. Little information exists about longitudinal changes in spatiotemporal gait asymmetry during rehabilitation, despite it being a common goal. Objectives. To describe longitudinal changes in spatiotemporal gait asymmetry over rehabilitation and examine relationships with changes in other poststroke impairments. Methods. Retrospective chart reviews were conducted for 71 stroke rehabilitation inpatients. Admission and discharge measures of spatiotemporal symmetry, velocity, motor impairment, mobility and balance were extracted and change scores were calculated. Relationships between changes in spatiotemporal symmetry and other change scores were investigated with Spearman correlations. Individuals were divided into four groups (worse, no change-symmetric, no change-asymmetric, improved) based on (1) symmetry/asymmetry at admission and (2) symmetry change scores >minimal detectable change. Differences in change scores between groups were investigated with analyses of covariance using the admission value as a covariate. Results. At admission, 59% and 49% of individuals were asymmetric in swing time and step length, respectively. Of these individuals, 21% and 14% improved swing symmetry or step symmetry, respectively. In contrast, 30% improved gait velocity, 62% improved functional balance and 73% improved functional mobility. Associations between change in swing symmetry and change in paretic limb weight bearing in standing and change in step symmetry and change in velocity were significant. There were no significant differences in change scores between the symmetry groups. Conclusions. The majority of asymmetric stroke patients did not improve spatiotemporal asymmetry during rehabilitation despite the fact that velocity, balance and functional mobility improved. Future work should investigate other factors associated with improved spatiotemporal symmetry and interventions to specifically improve it.
Risk factors influencing severity of attention deficit hyperactivity disorder in a sample of preparatory school students in Cairo

Background: Attention deficit hyperactivity disorder (ADHD) is one of the most common childhood psychiatric disorders. Severity of symptoms is associated with more behavioral problems, poor academic performance, and persistence of symptoms into adulthood. Methods: To examine the clinical and social correlates that may be identified as risk factors associated with ADHD severity in a sample of adolescent ADHD school students. A total of 925 students were recruited from two public and two private schools from eastern Cairo. They were interviewed using Conners-Wells Adolescent Self-Report—short version (CASS-S); students scoring more than 65 were further interviewed with Kiddie Schedule for Affective Disorders and Schizophrenia—present and lifetime version (K-SADS-PL) to confirm the diagnosis, then Conners-Wells Adolescent Self-Report—long version (CASS-L) to assess severity and Wechsler Intelligence Scale for Children (WISC) to ascertain intellectual ability. Results: About 10.3% of cases were severe, 5.7% were moderate, and 83.9% were mild. Severity was significantly associated with female gender, psychiatric comorbidity, family problems, conduct symptoms, and poor anger management. Diagnostic and Statistical Manual of Mental Disorders (4th ed.) (DSM-IV) hyperactive–impulsive type was the only predictive factor of ADHD severity. Conclusions: The diagnosis of hyperactive–impulsive subtype may predict the severity of ADHD symptoms.
Modified RSA Digital Signature Scheme for Data Confidentiality

As we know that digital signature is an authentication mechanism that enables the creator of a message to attach a code that acts as a signature. This signature guarantees the source authenticity and integrity of a message. Digital signature provides three types of services such as authentication, message integrity and non-repudiation, but does not provide the confidentiality of data which is most important during data transfer because the data is very sensitive. In this paper, we proposed a modified RSA digital signature scheme for data confidentiality. The main purpose of this approach is to provide the data confidentiality during the data transfer. To achieve this we are using the concept of public key encryption. General Terms Document Security
Influence of Impinging Ion Energy on the Bonding and Mechanical Characteristics of DLC Films Deposited by Microwave ECR Plasma CVD

DLC films were deposited on Si(111) substrates using CH 4 /Ar gas and microwave ECR plasma CVD processes. The energy of the ions impinging on the substrate during deposition was varied by changing the rf self bias voltage developed on the substrate. The bonding characteristics of the deposited films were investigated using FTIR and Raman spectroscopy, and mechanical properties were measured by nanoindentation and nanoscratch tests. The results obtained from different characterization techniques are correlated and explained on the basis of existing growth models for DLC films. Our studies indicate that the energy of the ions impinging on the substrates has a strong influence on the bonding characteristics and mechanical properties of the films.
Tow Collapse Model for Compression Strength of Textile Composites

The unidirectional composite compression strength model based on microbuckling of fibers embedded in a rigid-plastic matrix was extended to multiaxial laminates and textile composites. The resulting expression is a function of matrix yield strength under the fiber constraint, fiber tow inclination angle, fiber volume fraction, and the area fractions of various sets of inclined tows. The analysis was verified by experimentation. Compression tests were conducted on laminated, three-dimensional triaxially braided and orthogonally woven composites using the IITRI test specimen. The laminate specimens were made up of AS4/3501-6 graphite/epoxy composite with (0)24, (0/30/0/ - 30)35, and [(0/90)6/0)]s stacking sequence. Textile composites were made of BASF G30-500 graphite fiber tows (tow size is 6K) and Dow Chemicals Tactix 123 matrix. Fiber preform architecture of braided and woven composites before resin consolidation was 0/ + 17 and 0/90, respectively and after consolidation it was about (7/ + 20) and (5/90/90), respectively. The analysis agreed reasonably well with the test data for all cases considered. The axial fiber/tow misalignment angle for laminated, braided, and woven composites were about 4, 7, and 5 degrees, respectively. The compression strength was found to be strongly dependent on the percentage of axial tows and its misalignment angle. A small variation in the off-axis fiber/tow orientation had marginal effect on the compression strength. Hence, the off-axis tow misalignment angle can be assumed to be same as the initial laminate or the tow orientation angle.
Complications and Treatment of Mild Hypothermia

THE combination of anesthetic-induced impairment of thermoregulatory control and exposure to a cool operating room environment makes most surgical patients hypothermic. Several prospective, randomized trials have demonstrated various hypothermia-induced complications. There is no widely accepted definition for the term mild hypothermia. Furthermore, the term is not even used consistently in the literature. For the purpose of this review, mild hypothermia refers to core temperatures between 34 and 36°C.
Customized Medium Access Control (C-MAC) Protocol for Cooperative Wireless Network

Cooperation is always required in every filed of communication nowadays because neither a single layer, nor a single protocol is able to perform well in a network. In this work, cooperation has been performed using Medium Access Layer (MAC) using the concept of Rely Node. Although it has been claimed previously that cooperative scheme always promises a higher throughput and lower delay performances still here, a medium access control scheme known as C-MAC (Customize-Medium Access Control) has been proposed, where the neighbours, i.e. the relay node is selected not only assuming higher data rate, but also based on its reliability factor, power constraints, throughput, packet forwarding ratio, delay, which leads to motivate for better decision to deciding whom to co-operate with. The overall system has become reliable with an increased lifetime of the network.
Impact of metal ionic characteristics on adsorption potential of Ficus carica leaves using QSPR modeling

ABSTRACT The present study describes Quantitative Structure Property Relationship (QSPR) modeling to relate metal ions characteristics with adsorption potential of Ficus carica leaves for 13 selected metal ions (Ca+2, Cr+3, Co+2, Cu+2, Cd+2, K+1, Mg+2, Mn+2, Na+1, Ni+2, Pb+2, Zn+2, and Fe+2) to generate QSPR model. A set of 21 characteristic descriptors were selected and relationship of these metal characteristics with adsorptive behavior of metal ions was investigated. Stepwise Multiple Linear Regression (SMLR) analysis and Artificial Neural Network (ANN) were applied for descriptors selection and model generation. Langmuir and Freundlich isotherms were also applied on adsorption data to generate proper correlation for experimental findings. Model generated indicated covalent index as the most significant descriptor, which is responsible for more than 90% predictive adsorption (α = 0.05). Internal validation of model was performed by measuring (0.98). The results indicate that present model is a useful tool for prediction of adsorptive behavior of different metal ions based on their ionic characteristics.
Physician Obesity: The Tipping Point

As I bike through the early morning stxreets of Boston, my mind is awake, and my body feels strong. Ahead, I see the hospital where I work. Its pedestrian bridge spans a large urban street, and the brick of this building is deeply familiar to me as it has surrounded and greeted me on countless mornings and nights—first through my residency and now during my time as an attending physician. Already my mind has started to drift from the morning race of getting my three children to school to the dozens of chronically ill patients on my schedule, the medical students and residents with whom I have the good fortune to be teaching, and the multiple calls and meetings in the course of the day. All thoughts stop in the next moment when I feel a gale-like wind tipping my bike and with it, me, over. Fear washes over me. And then, as quickly as it had surged up, the gale force passes, and I am left unharmed. Looking up, I see a city bus filled with passengers (likely some are even my patients) unaware of their proxim.
Classification of Mental Tasks using EEG and Hierarchical Classifier employing Optimised Neural Networks

With recent advances in Electroencephalogram (EEG) signal processing and biomedical instrumentation, brain machine interfaces are used for rehabilitation of people suffering from neuromuscular disorders. This paper presents a novel method employing Hierarchical classifier using optimised Neural Networks to classify left-hand movement, right-hand movement and word generation using EEG signals. One of the most important components of brain computer interface (BCI) is feature extraction of EEG signals. Power spectral density (PSD) is used for feature extraction from EEG signals. The proposed pre-processing and reconfiguration of PSD samples make them more discriminative & yield appropriately organized feature vectors. The adaptation of network weights using Comprehensive Learning Particle Swarm Optimization (CLPSO) is proposed to improve the performance of Neural Network (NN). Further, the two level hierarchical neural network is used to enhance the discriminative property of the features and hence better classification accuracy is achieved. Results are verified on BCI benchmarking database as well as our own experimental database. Results obtained using the proposed methods are compared with other contemporary methods such as Linear Discrimination
Decision-feedback blind adaptive multiuser detector for synchronous CDMA system

We develop a blind adaptive multiuser detector for synchronous code-division multiple access (CDMA) with a noise-whitening filter. The triangular structure of the noise-whitened model ensures complete resolution of detection ambiguities. To further improve the symbol error probability performance, we introduce decision feedback in our detector similar to the decorrelating derision-feedback detector (DDFD), thus forming the decision-feedback blind adaptive multiuser detector (DFBD). Simulations indicate that the performance of the DFBD is very close to that of the DDFD in additive white Gaussian noise (AWGN) channels. In Rician fading channels, the DFBD can track the slowly varying channels well and has a symbol error probability performance approaching that of the DDFD, which requires the knowledge of users' energies. The blind adaptive and decision-feedback blind adaptive multiuser detectors proposed here do not, however, require that knowledge.
The Benefits of the Ka-Band as Evidenced from the SARAL/AltiKa Altimetric Mission: Quality Assessment and Unique Characteristics of AltiKa Data

The India-France SARAL/AltiKa mission is the first Ka-band altimetric mission dedicated to oceanography. The mission objectives are primarily the observation of the oceanic mesoscales but also include coastal oceanography, global and regional sea level monitoring, data assimilation, and operational oceanography. The mission ended its nominal phase after 3 years in orbit and began a new phase (drifting orbit) in July 2016. The objective of this paper is to provide a state of the art of the achievements of the SARAL/AltiKa mission in terms of quality assessment and unique characteristics of AltiKa data. It shows that the AltiKa data have similar accuracy at the centimeter level in term of absolute water level whatever the method (from local to global) and the type of water surfaces (ocean and lakes). It shows also that beyond the fact that AltiKa data quality meets the expectations and initial mission requirements, the unique characteristics of the altimeter and the Ka-band offer unique contributions in fields that were previously not fully foreseen.
Classifying movie genres by analyzing text reviews

This paper proposes a method for classifying movie genres by only looking at text reviews. The data used are from Large Movie Review Dataset v1.0 and IMDb. This paper compared a K-nearest neighbors (KNN) model and a multilayer perceptron (MLP) that uses tf-idf as input features. The paper also discusses different evaluation metrics used when doing multi-label classification. For the data used in this research, the KNN model performed the best with an accuracy of 55.4\% and a Hamming loss of 0.047.
Millimeter-wave beam-steering antenna array for 5G applications

In this paper, a modified uniplanar compact antenna array is designed at millimeter-wave (mm-wave) frequency bands for future 5G communications. The proposed antenna is composed of five mm-wave hexagonal antennas forming an array and printed on RO3003 flexible substrate. The proposed antenna covers the 24–30 GHz frequency range with a bandwidth of 6 GHz and exhibits a maximum gain of 10.7 dB. Moreover, the pattern can be steered at different desired angles by sweeping the frequency, similar to a leaky wave antenna. The simplicity of the design makes it suitable for 5G communications.
Ensembles of reference networks based on the rich–club structure for non–evolving networks

In networks the rich nodes are the subset of nodes with large numbers of links, or high degrees. The rich nodes and the connectivity between themselves (rich–club connectivity) tend to dominate the organisation of network structure. Recently there has been a considerable effort to characterise and model the rich–club connectivity in a variety of complex networks. In this paper we firstly clarify a number of terms: the rich-club coefficient quantifies the density of connectivity between a subset of rich nodes; the rich-club structure is the rich-club coefficient measured across the hierarchies of nodes; the rich-club phenomenon refers to the dynamic behaviour responsible for the formation of the rich–club connectivity in evolving networks; and the rich-club ordering discerns whether the connectivity between rich nodes in a nonevolving network (i.e. closed network or network snapshot) is higher than a reference network obtained by network randomisation. We then evaluate a recently proposed null model which is based on an ensemble of reference networks conserving the degree distribution of the original network. We remark that one should not confuse the rich-club structure of a network with the rich-club ordering detected by the null model. We also demonstrate that the null model cannot identify the dynamical mechanism that generates the rich–club connectivity. The main contribution of the paper is that we introduce two new ensembles of reference networks based on the rich-club structure for non–evolving networks. The first ensemble preserves the rich-club coefficient (as a function of the rank of a node) of the original network. Members of the ensemble exhibit similar degree distribution as the original network, and for assortative networks, similar assortative mixing as well. We propose that this ensemble can be used to study networks where assortativeness is a fundamental property, e.g. to detect the community structure in social networks. Analysis on the ensemble also provides a different way to interpret and model the evolution of social networks. The second ensemble preserves both the degree distribution and the rich–club coefficient (as a function of node degree). The reference networks in this ensemble have a similar structure as the original network. We use them to quantify the correlation profile between the rich nodes and pinpoint which links between the nodes are the backbone of network structure.
The Development of Microfluidic Systems within the Harrison Research Team

D. Jed Harrison is a full professor at the Department of Chemistry at the University of Alberta. Here he describes the development of microfluidic techniques in his lab from the initial demonstration of an integrated separation system for samples in liquids to the recent development of methods to fabricate crystalline packed beds with very low defect density.