Miracle-dz/UniFAR-FTUs huggingface dataset:
A Two-Layer Model for Taxi Customer Searching Behaviors Using GPS Trajectory Data

This paper proposes a two-layer decision framework to model taxi drivers' customer-search behaviors within urban areas. The first layer models taxi drivers' pickup location choice decisions, and a Huff model is used to describe the attractiveness of pickup locations. Then, a path size logit (PSL) model is used in the second layer to analyze route choice behaviors considering information such as path size, path distance, travel time, and intersection delay. Global Positioning System data are collected from more than 36 000 taxis in Beijing, China, at the interval of 30 s during six months. The Xidan district with a large shopping center is selected to validate the proposed model. Path travel time is estimated based on probe taxi vehicles on the network. The validation results show that the proposed Huff model achieved high accuracy to estimate drivers' pickup location choices. The PSL outperforms traditional multinomial logit in modeling drivers' route choice behaviors. The findings of this paper can help understand taxi drivers' customer searching decisions and provide strategies to improve the system services.
Application of the Method of Dynamic Decomposition for Recognition of Multiple Faults in the Large Scale Systems

The problem of the on-line multiple fault isolatio n in diagnostics of large scale systems has been presented in this paper. Considerations about possibilities of recognition of multiple faults mak ing use from the knowledge about signatures of single f aults have been made. Distinction between simultaneous faults and series of faults has been i ntroduced. The necessary condition of diagnostic reasoning assuming occurrence of multiple faults h as been formulated. It has been shown that multiple faults appearing simultaneously or within short tim e intervals may be correctly isolated under assumpt ion of single faults if the subsets of faults suitable for their isolation are disjunctive. An industrial example of reasoning about multiple faults has been presented.
Conversation and Language Acquisition: A Pragmatic Approach

ABSTRACT Children acquire language in conversation. This is where they are exposed to the community language by more expert speakers. This exposure is effectively governed by adult reliance on pragmatic principles in conversation: Cooperation, Conventionality, and Contrast. All three play a central role in speakers’ use of language for communication in conversation. Exposure to language alone, however, is not enough for learning. Children need to practice what they hear, and take account of feedback on their usage. Research shows that adults offer feedback with considerable frequency when young children make errors, whether in pronunciation (phonology), in word-from (morphology), in word choice (lexicon), or in constructions (syntax). Adults also offer children new words for objects, actions, and relations. And, along with new labels for such categories, they also provide supplementary information about the referents of new words—information about parts, properties, characteristic sounds, motion, and function, as well as about related neighboring objects, actions, and relations. All this helps children build up and organize semantic domains as they learn more words and more language.
The Impact of Social Media on ESL Students’ Learning Performance

In recent years, social media has become a common technology-supported learning tool for public and academic use. Students can use social networks to supplement their learning through the discussion and sharing of academic materials. The purpose of this study was to identify the English as a Second Language (ESL) students’ experience in the classroom facilitated by using a social media platform. Specifically, a quasiexperimental quantitative research design was used to determine the impact of social media on ESL students’ learning performance. Participants consisted of ESL students’ at an adult school in Central California aged 18 and older (n = 37). In order to assess the learning performance of ESL students, a Student Perception Toward Social Media in Education survey (SPSME) was used to measure students’ feelings about the impact of using social media on academic performance. Independent and paired samples t-tests were conducted to determine if there were statistically significant differences between the means of both groups on the SPSME. Data analysis revealed a statistically significant difference between the mean scores on the post-tests between the two groups (i.e., treatment and control). Meaning that the students in the treatment group demonstrated greater perception of engagement and improved upon their learning performance more than the students who did not receive the social media intervention.
UC Office of the President Recent Work Title Litter dominates surface fluxes of carbonyl sulfide in a Californian oak woodland Permalink

Carbonyl sulfide (COS) is a promising tracer for partitioning terrestrial photosynthesis and respiration from net carbon fluxes, based on its daytime co-uptake alongside CO2 through leaf stomata. Because ecosystem COS fluxes are the sum of plant and soil fluxes, using COS as a photosynthesis tracer requires accurate knowledge of soil COS fluxes. At an oak woodland in Southern California, we monitored below-canopy surface (soil + litter) COS and CO2 fluxes for 40 days using chambers and laser spectroscopy. We also measured litter fluxes separately and used a depth-resolved diffusion-reaction model to quantify the role of litter uptake in surface COS fluxes. Soil and litter were primarily COS sinks, and mean surface COS uptake was small (∼1 pmol m−2 s−1). After rainfall, uptake rates were higher (6–8 pmol m−2 s−1), and litter contributed a significant fraction (up to 90%) to surface fluxes. We observed rapid concurrent increases in COS uptake and CO2 efflux following the onset of rain. The patterns were similar to the Birch effect widely documented for soils; however, both COS and CO2 flux increases originated mainly in the litter. The synchronous COS-CO2 litter Birch effect indicates that it results from a rapid increase in litter microbial activity after rainfall. We expect that the drying-rewetting cycles typical for mediterranean and other semiarid ecosystems create a pronounced seasonality in surface COS fluxes. Our results highlight that litter uptake is an important component of surface COS exchange that needs to be taken into account in ecosystem COS budgets and model simulations.
Relevance assessment: are judges exchangeable and does it matter

We investigate to what extent people making relevance judgements for a reusable IR test collection are exchangeable. We consider three classes of judge: "gold standard" judges, who are topic originators and are experts in a particular information seeking task; "silver standard" judges, who are task experts but did not create topics; and "bronze standard" judges, who are those who did not define topics and are not experts in the task. Analysis shows low levels of agreement in relevance judgements between these three groups. We report on experiments to determine if this is sufficient to invalidate the use of a test collection for measuring system performance when relevance assessments have been created by silver standard or bronze standard judges. We find that both system scores and system rankings are subject to consistent but small differences across the three assessment sets. It appears that test collections are not completely robust to changes of judge when these judges vary widely in task and topic expertise. Bronze standard judges may not be able to substitute for topic and task experts, due to changes in the relative performance of assessed systems, and gold standard judges are preferred.
Reducing IRS-1 Activation Cause Mutation of Tyrosine Kinase Domain hINSR Gene on Type-2 Diabetes Mellitus Patients

The purpose of this study is to examine the effect of mutation on tyrosine kinase hINSR gene of DM Type 2 patients reduce the IRS- 1 activation by in silico analysis. Blood DNA of DM Type 2 patients from Saeful Anwar Hospital Malang were amplified and sequenced by specific primers of tyrosine kinase domain of hINSR gene. These gene sequences were converted to protein sequence by BLAST and the IRS-1 protein sequence is retrieved from NCBI database. Both of the protein sequence was aligned by using Bio edit version 5.0. 6. The model of three dimension protein was predicted by SWISS MODEL webserver, and visualized the structure alteration by using Pymol 0.99rc6 and Hex 5.0, and then superimpose of the hINSR and IRS-1 interaction were examined by docking using Hex 5.0. The results showed that one substitution and one deletion of 8-3F patient exon-22 hINSR gene tyrosine kinase domain cause loss of four helixes and three coils structures on tyrosine kinase hINSR protein. Six-deletions and six-substitutions on same gene domain of DMK9 patient changed the two helixes became coil structure. The binding energy of hINSR tyrosine kinase with IRS-1 of normal is E= -494.67 kJ/mol, DMK9 patient is E= -458.4 kJ/mol, and 8-3F patient is E=-544.20 kJ/mol. The DMK9 patient prognosis has better physiological condition than 8-3F patient. Interaction between 8-3F of hINSR tyrosine kinase domain mutation and PTB domain IRS-1 is more spontaneous than DMK9, but both of them were reduced on IRS-1 activation respectively.
Fabry disease: progression of nephropathy, and prevalence of cardiac and cerebrovascular events before enzyme replacement therapy

Background. In Fabry disease, progressive glycolipid accumulation leads to organ damage and early demise, but the incidence of renal, cardiac and cerebrovascular events has not been well characterized. Methods. We conducted a retrospective chart review of 279 affected males and 168 females from 27 sites (USA, Canada, Europe). The pre-defined study endpoints included progression of renal, cardiac and cerebrovascular involvement and/or death before the initiation of enzyme replacement therapy. Results. The mean rate of estimated glomerular filtration rate (eGFR) decline for patients was −2.93 for males, and −1.02 ml/min/1.73 m2/year for females. Prevalence and severity of proteinuria, baseline eGFR <60 ml/min/1.73 m2 and hypertension were associated with more rapid loss of eGFR. Advanced Fabry nephropathy was more prevalent and occurred earlier among males than females. Cardiac events (mainly arrhythmias), strokes and transient ischaemic attacks occurred in 49, 11, 6% of males, and in 35, 8, 4% of females, respectively. The mean age at death for 20 male patients was 49.9 years. Conclusions. Baseline proteinuria, reduced baseline eGFR, hypertension and male gender were associated with more rapid progression of Fabry nephropathy. The eGFR progression rate may increase with advancing nephropathy, and may differ between subgroups of patients with Fabry disease.
Photometric stereo with near point lighting: A solution by mesh deformation

We tackle the problem of photometric stereo under near point lighting in this paper. Different from the conventional formulation of photometric stereo that assumes parallel lighting, photometric stereo under the near point lighting condition is a nonlinear problem as the local surface normals are coupled with its distance to the camera as well as the light sources. To solve this non-linear problem of PS with near point lighting, a local/global mesh deformation approach is developed in our work to determine the position and the orientation of a facet simultaneously, where each facet is corresponding to a pixel in the image captured by the camera. Unlike nonlinear optimization schemes, the mesh deformation in our approach is decoupled into an iteration of interlaced steps of local projection and global blending. Experimental results verify that our method can generate accurate estimation of surface shape under near point lighting in a few iterations. Besides, this approach is robust to errors on the positions of light sources and is easy to be implemented.
Generational Patterns of Stress: Help From Our Microbes?

Exposure to adverse events affects the development of stress and threat response systems, and emerging evidence suggests that these effects are transmitted to future generations. How such effects are transmitted, and, similarly, how they can be ameliorated, is the topic of this article. Recent evidence demonstrates generational transmission of traits acquired following environmental exposures such as stress (e.g., parental deprivation) and dietary change (e.g., famine, high-fat diet). These diverse environmental exposures often affect both mental and physical health and appear to be transmitted through similar epigenetic and behavioral mechanisms. This convergence suggests an interesting possibility—dietary/gut-directed manipulations may work to prevent the transgenerational transmission of adversity. Although future research is required, gastrointestinal treatments show early promise in the treatment of generational mental health and are both economic and globally accessible.
Harvester: Influence Optimization in Symmetric Interaction Networks

The problem of optimizing influence diffusion ina network has applications in areas such as marketing, diseasecontrol, social media analytics, and more. In all cases, an initial setof influencers are chosen so as to optimize influence propagation.While a lot of research has been devoted to the influencemaximization problem, most solutions proposed to date applyon directed networks, considering the undirected case to besolvable as a special case. In this paper, we propose a novelalgorithm, Harvester, that achieves results of higher quality thanthe state of the art on symmetric interaction networks, leveragingthe particular characteristics of such networks. Harvester isbased on the aggregation of instances of live-edge graphs, fromwhich we compute the influence potential of each node. Weshow that this technique can be applied for both influencemaximization under a known seed size and also for the dualproblem of seed minimization under a target influence spread.Our experimental study with real data sets demonstrates that:(a) Harvester outperforms the state-of-the-art method, IMM,in terms of both influence spread and seed size; and (b) itsvariant for the seed minimization problem yields good seed sizeestimates, reducing the number of required trial influence spreadestimations by a factor of two; and (c) it is scalable with growinggraph size and robust to variant edge influence probabilities.
β Edge strands in protein structure prediction and aggregation

It is well established that recognition between exposed edges of β‐sheets is an important mode of protein–protein interaction and can have pathological consequences; for instance, it has been linked to the aggregation of proteins into a fibrillar structure, which is associated with a number of predominantly neurodegenerative disorders. A number of protective mechanisms have evolved in the edge strands of β‐sheets, preventing the aggregation and insolubility of most natural β‐sheet proteins. Such mechanisms are unfavorable in the interior of a β‐sheet. The problem of distinguishing edge strands from central strands based on sequence information alone is important in predicting residues and mutations likely to be involved in aggregation, and is also a first step in predicting folding topology. Here we report support vector machine (SVM) and decision tree methods developed to classify edge strands from central strands in a representative set of protein domains. Interestingly, rules generated by the decision tree method are in close agreement with our knowledge of protein structure and are potentially useful in a number of different biological applications. When trained on strands from proteins of known structure, using structure‐based (Dictionary of Secondary Structure in Proteins) strand assignments, both methods achieved mean cross‐validated, prediction accuracies of ∼78%. These accuracies were reduced when strand assignments from secondary structure prediction were used. Further investigation of this effect revealed that it could be explained by a significant reduction in the accuracy of standard secondary structure prediction methods for edge strands, in comparison with central strands.
Planar building facade segmentation and mapping using appearance and geometric constraints

Segmentation and mapping of planar building facades (PBFs) can increase a robot's ability of scene understanding and localization in urban environments which are often quasi-rectilinear and GPS-challenged. PBFs are basic components of the quasi-rectilinear environment. We propose a passive vision-based PBF segmentation and mapping algorithm by combining both appearance and geometric constraints. We propose a rectilinear index which allows us to segment out planar regions using appearance data. Then we combine geometric constraints such as reprojection errors, orientation constraints, and coplanarity constraints in an optimization process to improve the mapping of PBFs. We have implemented the algorithm and tested it in comparison with state-of-the-art. The results show that our method can reduce the angular error of scene structure by an average of 82.82%.
Pulmonary arterial compliance and exercise capacity after pulmonary endarterectomy

Patients with chronic thromboembolic pulmonary hypertension (CTEPH), despite successful pulmonary endarterectomy (PEA), can continue to suffer from a limitation in exercise capacity. The objective of this study was to assess whether pulmonary arterial compliance is a predictor of exercise capacity after PEA. Right heart haemodynamics, treadmill incremental exercise test, spirometry, carbon monoxide transfer factor, arterial blood gas and echocardiographic examinations were retrospectively analysed in a population of CTEPH patients who underwent PEA at a single centre. Baseline and 3-month haemodynamic data were available in 296 patients; 5-year follow-up data were available in 68 patients. In a multivariable model the following parameters were found to be independent predictors of exercise capacity after surgery: age, sex, pulmonary arterial compliance, tricuspid annular plane excursion, arterial oxygen tension and carbon monoxide transfer factor (p<0.0001); the model showed good discrimination (Harrell’s c=0.84) and calibration (shrinkage coefficient=0.91). Poor exercise capacity at 3 months was loosely associated with higher death rate during subsequent survival (Harrell’s c=0.61). In conclusion, after successful PEA, reduced pulmonary arterial compliance is an important determinant of exercise capacity in association with the age and sex of the patients, and the extent of recovery of both cardiac and respiratory function. However, exercise capacity does not explain a large proportion of the effect of surgery on subsequent survival. Pulmonary arterial compliance is an important determinant of exercise capacity after pulmonary endarterectomy http://ow.ly/rDj1B
Exploiting phonetic and phonological similarities as a first step for robust speech recognition

This paper presents two speech recognition systems which use the notion of phonetic and phonological similarity to improve the robustness of phoneme recognition. The first recognition system, YASPER, uses phonetic feature extraction engines to identify phonemes based on overlap relations between phonetic features. The second system uses the CMU Sphinx 3.7 decoder based on statistical context-dependent phone models. Experiments have been carried out on the TIMIT corpus which show improvements in phoneme error rate when a projection set constructed with respect to phonetic and phonological similarity is used. It is envisaged that in future, the two systems will provide alternative parallel streams of hypotheses for each interval of the speech signal and will work together as experts in the phoneme recognition process.
Versatile Bayesian classifier for moving object detection by non-parametric background-foreground modeling

Along the recent years, several moving object detection strategies by non-parametric background-foreground modeling have been proposed. To combine both models and to obtain the probability of a pixel to belong to the foreground, these strategies make use of Bayesian classifiers. However, these classifiers do not allow to take advantage of additional prior information at different pixels. So, we propose a novel and efficient alternative Bayesian classifier that is suitable for this kind of strategies and that allows the use of whatever prior information. Additionally, we present an effective method to dynamically estimate prior probability from the result of a particle filter-based tracking strategy.
Deciphering the cellular source of tumor relapse identifies CD44 as a major therapeutic target in pancreatic adenocarcinoma

It has been commonly found that in patients presenting Pancreatic Ductal Adenocarcinoma (PDAC), after a period of satisfactory response to standard treatments, the tumor becomes non-responsive and patient death quickly follows. This phenomenon is mainly due to the rapid and uncontrolled development of the residual tumor. The origin and biological characteristics of residual tumor cells in PDAC still remain unclear. In this work, using PDACs from patients, preserved as xenografts in nude mice, we demonstrated that a residual PDAC tumor originated from a small number of CD44+ cells present in the tumor. During PDAC relapse, proliferating CD44+ cells decrease expression of ZEB1, while overexpressing the MUC1 protein, and gain morphological and biological characteristics of differentiation. Also, we report that CD44+ cells, in primary and residual PDAC tumors, are part of a heterogeneous population, which includes variable numbers of CD133+ and EpCAM+ cells. We confirmed the propagation of CD44+ cells in samples from cases of human relapse, following standard PDAC treatment. Finally, using systemic administration of anti-CD44 antibodies in vivo, we demonstrated that CD44 is an efficient therapeutic target for treating tumor relapse, but not primary PDAC tumors. We conclude that CD44+ cells generate the relapsing tumor and, as such, are themselves promising therapeutic targets for treating patients with recurrent PDAC.
Send Orders of Reprints at Reprints@benthamscience.org Objective versus Subjective Cognitive Functioning in Patients with Obstructive Sleep Apnea

Study objectives: Previous studies have found that patients' neurocognitive functions were affected by OSA symptoms. However, no study has focused on the subjective awareness of cognitive impairments. This study used a subjective rating scale to evaluate OSA patient perceptions of their cognitive impairments, and explore the relationship between subjective and objective cognitive functions. Methods: An independent-group design was used to compare objective and subjective cognitive performance in both the OSA and control groups. An experimental group of 19 male OSA patients and a control group of 19 normal subjects matched in age and education participated in the study. A neurocognitive test battery that measures attention, memory and executive functions, and the SCIRS (Subjective Cognitive Impairment Rating Scale) that measures subjective perception of cognitive impairments were used. Results: On the neurocognitive test measures, OSA patients demonstrated decreased performance on memory and executive function. On the subjective measures, OSA patients reported a mild to moderately negative impact on attention, memory, and emotional control due to OSA. Conclusions: The results show that OSA patients may not be fully aware of their cognitive impairments, especially with regard to their executive functions. The inconsistency suggests that including neurocognitive tests in the evaluation of sleep-related breathing disorders may provide useful information that cannot be obtained through clinical interviews.