Miracle-dz/UniFAR-FTUs huggingface dataset:
Obstructive Sleep Apnea of Obese Adults: Pathophysiology and Perioperative Airway Management

Collapsible pharyngeal airway size is determined by interaction between structural properties of the pharyngeal airway and neural regulation of the pharyngeal dilating muscles. Obesity seems to have two distinct mechanical influences on the pharyngeal airway collapsibility. First, obesity increases soft tissue surrounding the pharyngeal airway within limited maxillomandible enclosure occupying and narrowing its space (pharyngeal anatomical imbalance). Second, obesity, particularly central obesity, increases visceral fat volume decreasing lung volume. Pharyngeal wall collapsibility is increased by the lung volume reduction, possibly through decreased longitudinal tracheal traction (lung volume hypothesis). Neural compensation for functioning structural abnormalities operating during wakefulness is lost during sleep, leading to pharyngeal obstruction. Instability of the negative feedback of the respiratory system may accelerate cycling of pharyngeal closure and opening. Improvement of the pharyngeal anatomical imbalance and maintenance of lung volume are the keys for safe perioperative airway managements of obese patients with obstructive sleep apnea.
Detecting defects in object-oriented designs: using reading techniques to increase software quality

Inspections can be used to identify defects in software artifacts. In this way, inspection methods help to improve software quality, especially when used early in software development. Inspections of software design may be especially crucial since design defects (problems of correctness and completeness with respect to the requirements, internal consistency, or other quality attributes) can directly affect the quality of, and effort required for, the implementation. We have created a set of “reading techniques” (so called because they help a reviewer to “read” a design artifact for the purpose of finding relevant information) that gives specific and practical guidance for identifying defects in Object-Oriented designs. Each reading technique in the family focuses the reviewer on some aspect of the design, with the goal that an inspection team applying the entire family should achieve a high degree of coverage of the design defects. In this paper, we present an overview of this new set of reading techniques. We discuss how some elements of these techniques are based on empirical results concerning an analogous set of reading techniques that supports defect detection in requirements documents. We present an initial empirical study that was run to assess the feasibility of these new techniques, and discuss the changes made to the latest version of the techniques based on the results of this study.
Sentiment Domain Adaptation with Multi-Level Contextual Sentiment Knowledge

Sentiment domain adaptation is widely studied to tackle the domain-dependence problem in sentiment analysis field. Existing domain adaptation methods usually train a sentiment classifier in a source domain and adapt it to the target domain using transfer learning techniques. However, when the sentiment feature distributions of the source and target domains are significantly different, the adaptation performance will heavily decline. In this paper, we propose a new sentiment domain adaptation approach by adapting the sentiment knowledge in general-purpose sentiment lexicons to a specific domain. Since the general sentiment words of general-purpose sentiment lexicons usually convey consistent sentiments in different domains, they have better generalization performance than the sentiment classifier trained in a source domain. In addition, we propose to extract various kinds of contextual sentiment knowledge from massive unlabeled samples in target domain and formulate them as sentiment relations among sentiment expressions. It can propagate the sentiment information in general sentiment words to massive domain-specific sentiment expressions. Besides, we propose a unified framework to incorporate these different kinds of sentiment knowledge and learn an accurate domain-specific sentiment classifier for target domain. Moreover, we propose an efficient optimization algorithm to solve the model of our approach. Extensive experiments on benchmark datasets validate the effectiveness and efficiency of our approach.
Normal thermoregulatory responses to 3‐iodothyronamine, trace amines and amphetamine‐like psychostimulants in trace amine associated receptor 1 knockout mice

3‐Iodothyronamine (T1AM) is a metabolite of thyroid hormone. It is an agonist at trace amine‐associated receptor 1 (TAAR1), a recently identified receptor involved in monoaminergic regulation and a potential novel therapeutic target. Here, T1AM was studied using rhesus monkey TAAR1 and/or human dopamine transporter (DAT) co‐transfected cells, and wild‐type (WT) and TAAR1 knock‐out (KO) mice. The IC50 of T1AM competition for binding of the DAT‐specific radio‐ligand [3H]CFT was highly similar in DAT cells, WT striatal synaptosomes and KO striatal synaptosomes (0.72–0.81 μM). T1AM inhibition of 10 nM [3H]dopamine uptake (IC50: WT, 1.4 ± 0.5 μM; KO, 1.2 ± 0.4 μM) or 50 nM [3H]serotonin uptake (IC50: WT, 4.5 ± 0.6 μM; KO, 4.7 ± 1.1 μM) in WT and KO synaptosomes was also highly similar. Unlike other TAAR1 agonists that are DAT substrates, TAAR1 signaling in response to T1AM was not enhanced in the presence of DAT as determined by CRE‐luciferase assay. In vivo, T1AM induced robust hypothermia in WT and KO mice equivalently and dose dependently (maximum change degrees Celsius: 50 mg/kg at 60 min: WT −6.0 ± 0.4, KO −5.6 ± 1.0; and 25 mg/kg at 30 min: WT −2.7 ± 0.4, KO −3.0 ± 0.2). Other TAAR1 agonists including beta–phenylethylamine (β‐PEA), MDMA (3,4‐methylenedioxymethamphetamine) and methamphetamine also induced significant, time‐dependent thermoregulatory responses that were alike in WT and KO mice. Therefore, TAAR1 co‐expression does not alter T1AM binding to DAT in vitro nor T1AM inhibition of [3H]monoamine uptake ex vivo, and TAAR1 agonist‐induced thermoregulatory responses are TAAR1‐independent. Accordingly, TAAR1‐directed compounds will likely not affect thermoregulation nor are they likely to be cryogens. © 2010 Wiley‐Liss, Inc.
Ice nucleation processes in upper tropospheric wave‐clouds observed during SUCCESS

We have compared in situ measurements near the leading‐edges of wave‐clouds observed during the SUCCESS experiment with numerical simulations. Observations of high supersaturations with respect to ice (>50%) near the leading edge of a very cold wave cloud (T <−60°C) are approximately consistent with recent theoretical and laboratory studies suggesting that large supersaturations are required to homogeneously freeze sulfate aerosols. Also, the peak ice crystal number densities observed in this cloud (about 4 cm−3) are consistent with the number densities calculated in our model. In the warmer wave‐cloud (T ≃−37°C) relatively large ice number densities were observed (20–40 cm−3). Our model calculations suggest that these large number densities are probably caused by activation of sulfate aerosols into liquid droplets followed by subsequent homogeneous freezing. If moderate numbers of effective heterogeneous freezing nuclei (0.5–1 cm−3) had been present in either of these clouds, then the number densities of ice crystals and the peak relative humidities should have been lower than the observed values.
Towards Reliable Reliability Estimates for Individual Regression Predictions Technical Report T-01 / 08

In machine learning, the reliability estimates for individual predictions provide more information about individual prediction error than the average accuracy of predictive model (such as relative mean squared error). Individual reliability estimates may represent a decisive information in risk-sensitive applications of machine learning (e.g. medicine, engineering, business), where they enable the users to distinguish between more or less reliable predictions. In the paper we compare the sensitivitybased reliability estimates, developed in our previous work, with four novel approaches, proposed or inspired by the ideas from the related work. The results, obtained using 8 regression models and 28 domains indicate the potential for the usage of a sensitivity-based estimate, as well as the approach to the local modeling of prediction error, with the regression trees. By combining pairs of individual estimates, we further designed a new estimate which performs better with neural networks and bagging. With various normalizations we succeeded to improve the interpretability and inter-comparability of estimates’ values without affecting their performance.
Ice volume changes (1936–1990–2007) and ground-penetrating radar studies of Ariebreen, Hornsund, Spitsbergen

Ariebreen is a small (0.37 km2)-valley glacier located in southern Spitsbergen. Our ground-penetrating radar surveys of the glacier show that it is less than 30 m thick on average, with a maximum thickness of 82 m, and it appears to be entirely cold. By analysing digital terrain models of the ice surface from different dates, we determine the area and volume changes during two periods, 1936–1990 and 1990–2007. The total ice volume of the glacier has decreased by 73% during the entire period 1936–2007, which is equivalent to a mean mass balance rate of −0.61±0.17 m y−1 w.eq. The glacier thinning rate has increased markedly between the first and second periods, from −0.50±0.22 to −0.95±0.17 m y−1 w.eq. To access the supplementary material for this article, please see Supplementary Files under Article Tools online.
A general framework for the manufacturing workstation design optimization: a combined ergonomic and operational approach

A general framework for the effective design, or re-design, of manufacturing workstations under a combined ergonomic and operational optimization approach is presented. This general framework must be regarded as a method for facilitating and supporting engineers and researchers in the design of manufacturing workstations. The three key elements forming this general framework are presented and discussed. Finally to provide evidence on the relevance of the proposed general framework, two original case studies, developed by the authors in cooperation with two real manufacturing systems (one located in Italy and one in Spain), are presented. This paper will provide useful insights and guidelines to engineers, researchers and practitioners involved in manufacturing workstations design.
Variability of chlorophyll associated with El Niño–Southern Oscillation and its possible biological feedback in the equatorial Pacific

[1] The relationship between oceanic phytoplankton and climate variability has been given increasing attention with the accumulation of satellite-derived chlorophyll data over the past decade. Here we examine the dominant variability of phytoplankton and its associated tropical climate systems; in particular, the El Nino–Southern Oscillation (ENSO). The analysis, using 148 months of chlorophyll data, reveals that the first two leading modes of tropical chlorophyll anomalies are linked to the mature phase and the decaying phase of the ENSO cycle. It is also found that when El Nino events occur, the reduced surface solar radiation (enhanced convective activity), as well as the insufficient nutrient supply (suppressed equatorial upwelling), can also play a significant role in reducing chlorophyll concentration. The effect of reduced surface solar radiation on chlorophyll is larger in the central Pacific than in the eastern and western Pacific, and this regional difference of the impact induces a distinctly asymmetric response of ocean chlorophyll to El Nino and La Nina in the central Pacific. A linear statistical analysis shows that the dominant variability of chlorophyll associated with ENSO contributes radiant feedback to the equatorial Pacific by altering the surface shortwave albedo. The decreased chlorophyll concentration during El Nino tends to induce radiant cooling at the ocean surface.
Data collection and restoration for heterogeneous process migration

This study presents a practical solution for data collection and restoration to migrate a process written in high level stack-based languages such as C and Fortran over a network of heterogeneous computers. We study a logical data model which recognizes complex data structures in process address space. Then, novel methods are developed to incorporate the model into a process and to collect and restore data efficiently. We have implemented a prototype software and performed experiments on different programs. Experimental and analytical results show that (I) a user-level process can be migrated across different computing platforms, (2) semantic information of data structures in the process's memory space can be correctly collected and restored, (3) the costs of data collection and restoration depend on the complexity of the logical model representing the process's data structures and the amount of data involved and (4) the implantation of the data collection and restoration mechanisms into the process is not a decisive factor of incurring execution overheads; with appropriate program analysis, we can achieve practically low overhead.
Standing wave modes observed in the South China Sea deep basin

This study deals with standing wave or seiche events using cruise observations, satellite altimeter data, and theoretical analysis. Cruise missions in summer 2007 and 2009 detected internal oscillation signals in the South China Sea (SCS) deep basin. The signals have average wavelengths of 320 and 390 km and the maximum amplitudes of 50–100 m at layers 500–700 m and 1500–1700 m. Satellite altimeter sea level anomaly (SLA) images and the second intrinsic mode function (IMF2) images derived from the empirical mode decomposition (EMD) analysis show that the observed internal oscillations are a portion of 2-D seiche modes, which lasted for at least 2 weeks. We recognize that the observed internal oscillation signals represent seiche modes H5,3 and H5,1 derived from a rectangular model ocean basin with a uniform depth, a west-east length of 1000 km and a north-south width of 800 km. Statistical analysis of standing wave modes H4,0, H5,1, and H5,3 with the average wavelength of 500, 390, and 320 km indicates that from 1993 to 2012 (1045 weeks), total 94 events with total temporal coverage of 218 weeks are affirmed. The total occurrence frequency is 20.9%. Histograms of annual distributions of seiche events and timespans show an interannual variability of about 9 years, with peak years 1993, 1994, 1998, 2001, and 2011. While monthly distributions show an intraseasonal variability double-peaked in May and October, transit periods of East Asia monsoon in the SCS.
Estimation of Radiofrequency Power Leakage from Microwave Ovens for Dosimetric Assessment at Nonionizing Radiation Exposure Levels

The electromagnetic field leakage levels of nonionizing radiation from a microwave oven have been estimated within a complex indoor scenario. By employing a hybrid simulation technique, based on coupling full wave simulation with an in-house developed deterministic 3D ray launching code, estimations of the observed electric field values can be obtained for the complete indoor scenario. The microwave oven can be modeled as a time- and frequency-dependent radiating source, in which leakage, basically from the microwave oven door, is propagated along the complete indoor scenario interacting with all of the elements present in it. This method can be of aid in order to assess the impact of such devices on expected exposure levels, allowing adequate minimization strategies such as optimal location to be applied.
Measuring the importance of morphological information for finnish speech synthesis

The basic assumption in intonation models and perhaps generally in prosody models is, that part-of-speech information is of paramount importance for predicting the actual values for the prosodic parameters; be they pitch, segmental duration or loudness. We have studied whether morphological knowledge, in addition to part-of-speech and functional information, is of any help in predicting prosody in a morphologically rich language such as Finnish. Our research concerns Finnish prosody with respect to pitch and segmental duration. The basic methodology we employ is based on artiﬁcial neural networks. It is a continuation of our earlier studies on prosody where we investigated the problem of generating values for prosodic parameters for text-to-speech synthesis. The basic methodology we employ is based on standard multi-layer feed-forward networks that are trained with backpropagation. The results we have obtained show that there are certain advantages in adding morphological knowledge to the network input. Apart from part-of-speech information, there are certain cases where morphological features seem to affect the outcome of both pitch and segmental durations. This behavior can be ex-pected in a morphologically rich language.
Nonaqueous phase liquid transport and cleanup: 1. Analysis of mechanisms

Groundwater contamination by nonaqueous liquids such as organic solvents and petroleum hydrocarbons frequently occurs as a result of surface spills, tank leaks, and improper disposal practices. This first of two papers examines the physics governing the emplacement and movement of a separate phase in porous media, the role of sorption, and the conditions necessary to mobilize a separate phase. The movement of the separate phase is controlled by capillary forces, and ganglia displacement by groundwater is not possible under reasonable hydraulic gradients. In addition, because of mass transfer limitations in liquid phase dissolution, groundwater extraction at contaminated sites is shown to be ineffective in removing the nonaqueous contaminant within a reasonable time frame. Therefore other means of mobilizing the trapped second phase are needed, steam displacement is proposed and steam front propagation through contaminated porous media is evaluated. The results of laboratory experiments supporting some of these analytical results are presented in the second paper (Hunt et al., this issue).
Matrix Metalloproteinases Increase Very Early during Experimental Focal Cerebral Ischemia

Microvascular integrity is lost during focal cerebral ischemia. The degradation of the basal lamina and extracellular matrix are, in part, responsible for the loss of vascular integrity. Matrix metalloproteinases (MMPs) may play a primary role in basal lamina degradation. By using a sensitive modification of gelatin zymography, the authors investigated the activity of MMP-2 and MMP-9 in frozen 10-µm sections of ischemic and nonischemic basal ganglia and plasma samples of 27 non-human primates after middle cerebral artery occlusion/reperfusion (MCAO/R) for various periods. The gelatinolytic activities were compared with parallel cell dUTP incorporation in the ischemic zones of adjacent sections. In the brain, the integrated density of MMP-2 increased significantly by 1 hour after MCAO and was persistently elevated thereafter. Matrix metalloproteinase-2 expression was highly correlated with the extent of neuron injury and the number of injured neurons (r = 0.9763, SE = 0.004, 2P < 0.0008). Matrix metalloproteinase-9 expression only was significantly increased in subjects with hemorrhagic transformation. In plasma, only MMP-9 increased transiently at 2 hours of MCAO. These findings highlight the early potential role of MMP-2 in the degradation of basal lamina leading to neuronal injury, and an association of MMP-9 with hemorrhagic transformation after focal cerebral ischemia.
Long-Term Fine Particulate Matter Exposure and Mortality From Diabetes in Canada

OBJECTIVE Recent studies suggest that chronic exposure to air pollution can promote the development of diabetes. However, whether this relationship actually translates into an increased risk of mortality attributable to diabetes is uncertain. RESEARCH DESIGN AND METHODS We evaluated the association between long-term exposure to ambient fine particulate matter (PM2.5) and diabetes-related mortality in a prospective cohort analysis of 2.1 million adults from the 1991 Canadian census mortality follow-up study. Mortality information, including ∼5,200 deaths coded as diabetes being the underlying cause, was ascertained by linkage to the Canadian Mortality Database from 1991 to 2001. Subject-level estimates of long-term exposure to PM2.5 were derived from satellite observations. The hazard ratios (HRs) for diabetes-related mortality were related to PM2.5 and adjusted for individual-level and contextual variables using Cox proportional hazards survival models. RESULTS Mean PM2.5 exposure levels for the entire population were low (8.7 µg/m3; SD, 3.9 µg/m3; interquartile range, 6.2 µg/m3). In fully adjusted models, a 10-µg/m3 elevation in PM2.5 exposure was associated with an increase in risk for diabetes-related mortality (HR, 1.49; 95% CI, 1.37–1.62). The monotonic change in risk to the population persisted to PM2.5 concentration <5 µg/m3. CONCLUSIONS Long-term exposure to PM2.5, even at low levels, is related to an increased risk of mortality attributable to diabetes. These findings have considerable public health importance given the billions of people exposed to air pollution and the worldwide growing epidemic of diabetes.
A model of tourism information service composition based on fuzzy Petri net

At present, because of users' fuzzy demand and the uncertain reliability of Web service itself, the general Petri network has been not able to meet the combination of indefinite information very well. The article was undertaken to set up a composite model of information services for tourists, according to travel time, destination and other information provided by users. Also in this model, the users can participate in the process of decision-making. It was verified that the model is effective by example.