Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient training methods for conditional random fields

Many applications require predicting not a just a single variable, but multiple variables that depend on each other. Recent attention has therefore focused on structured prediction methods, which combine the modeling flexibility of graphical models with the ability to employ complex, dependent features typical of traditional classification methods. Especially popular have been conditional random fields (CRFs), which are graphical models of the conditional distribution over outputs given a set of observed features. Unfortunately, parameter estimation in CRFs requires repeated inference, which can be computationally expensive. Complex graphical structures are increasingly desired in practical applications, but then training time often becomes prohibitive. In this thesis, I investigate efficient training methods for conditional random fields with complex graphical structure, focusing on local methods which avoid propagating information globally along the graph. First, I investigate piecewise training, which trains each of a model's factors separately. I present three views of piecewise training: as maximizing the likelihood in a so-called "node-split graph", as maximizing the Bethe likelihood with uniform messages, and as generalizing the pseudo-moment matching estimator of Wainwright et al. [2003]. Second, I propose piecewise pseudolikelihood, a hybrid procedure which "pseudolikelihood-izes" the piecewise likelihood, and is therefore more efficient if the variables have large cardinality. Piecewise pseudolikelihood performs well even on applications in which standard pseudolikelihood performs poorly. Finally, motivated by the connection between piecewise training and BP, I explore training methods using beliefs arising from stopping BP before convergence. I propose a new schedule for message propagation that improves upon the dynamic schedule proposed recently by Elidan et al. [2006], and present suggestive results applying dynamic schedules to the system of equations that combine inference and learning. I also present two novel families of loopy CRFs, which appear as test cases throughout. First is the dynamic CRF, which combines the factorized state representation of dynamic Bayesian networks with the modeling flexibility of conditional models. The second of these is the skip-chain CRF, which models the fact that identical words are likely to have the same label, even if they occur far apart.
Magnetoelastic Sensors for the Detections of Pulse Waves

A novel sensor for noninvasive pulse wave detection has been developed using the magnetoelastic principle. The sensor can be used for noninvasive detection of the heart-generated blood-pressure waves which propagates along the arteries near the skin surface. The shape and velocity of the pulse wave traveling trough arteries is related to heart function and blood vessels health. The proposed work shows that magnetoelastisc principles can be successfully used to detect small oscillations such as the ones generated by the pulsation of the blood vessels using a simple device and extends the type of the pulse wave sensors.
Large-Scale Modeling of Grid-Connected Electric Vehicles

This paper presents a methodology for modeling the load behavior of electric vehicles. This information is needed to make a more accurate prediction of the technical potential of electric vehicles which might be used in the future as dispersed energy storages or controllable loads. For this purpose, a simplified stochastic model is established based on nonhomogeneous semi-Markov processes. This model is capable of describing the grid connectivity of electric vehicles over the period of one day. In addition, it provides information about the driven distance and the state of charge. This makes it possible to generate information about the load behavior of the vehicles at different times and locations. The fundamentals of the model are given in this paper as well as the basic results. As proof of validation, a comparison between the results and real data are presented. Finally, a synthetic load profile is generated based on the proposed model.
Demographic, clinical and microbiological characteristics of maternity patients: a Canadian clinical cohort study.

OBJECTIVE To determine the demographic, clinical and microbiological characteristics of a representative Canadian obstetrical population. DESIGN A one-year cohort study of all maternity patients who were followed to delivery, using detailed patient questionnaires containing more than 60 demographic and clinical variables, and three microbiological evaluations during gestation - first trimester, 26 to 30 weeks, and labour and delivery. Outcome measurements included birth weight and gestational age. SETTING Labour and delivery suites of all office obstetrical practices affiliated with a single hospital. POPULATION STUDIED A consecutive sample of pregnant women in the study practices during one year were eligible for enrolment; 2237 consecutive patients were approached for consent, 2047 enrolled and 1811 completed the study through delivery. RESULTS The average patient was white, married and 29 years of age. Slightly more than half of the patients had postsecondary education, but 10% fell below the national poverty line for income. Frequency of factors linked to adverse pregnancy outcomes included cigarette smoking (19%), alcohol ingestion (18%), previously having had a premature infant (7%), and maternal diabetes (2%). Overall prevalence of genital microbes variously implicated in prematurity was 37% for ureaplasma, 11% for group B streptococcus and 4% for Mycoplasma hominis. Prevalence of bacterial vaginosis was 14%. The median gestational age for the cohort was 39 weeks, with 7% of infants born less than 37 weeks' gestation. Mean birth weight was 3415 g. CONCLUSIONS The present clinical cohort represents demographic and medical characteristics of the Canadian obstetrical population. The birth outcomes are consistent with national data. This database provides valuable information about a general obstetrical population that is managed by a universal health care system.
Stub-loaded compact dual-band implantable antenna for biotelemetry

A compact dual-band planar implantable antenna is presented for biotelemetry at medical communications service (MICS) band (402-405 MHz) and industrial, scientific and medical (ISM) band (433.05-434.79 MHz, 2400-2480 MHz). With the use of loaded stub and meandered strip, a compact design is obtained for MICS and ISM band. The measured 10 dB return loss bandwidth is 378-452 MHz (17.8%) at the lower band and 2412-2524 MHz (4.5%) at the upper band, respectively. The antenna occupies a volume of only 671.83 mm3 (23 ×23×1.27 mm).
Characterizing the heterogeneity of tumor tissues from spatially resolved molecular measures

Background Tumor heterogeneity can manifest itself by sub-populations of cells having distinct phenotypic profiles expressed as diverse molecular, morphological and spatial distributions. This inherent heterogeneity poses challenges in terms of diagnosis, prognosis and efficient treatment. Consequently, tools and techniques are being developed to properly characterize and quantify tumor heterogeneity. Multiplexed immunofluorescence (MxIF) is one such technology that offers molecular insight into both inter-individual and intratumor heterogeneity. It enables the quantification of both the concentration and spatial distribution of 60+ proteins across a tissue section. Upon bioimage processing, protein expression data can be generated for each cell from a tissue field of view. Results The Multi-Omics Heterogeneity Analysis (MOHA) tool was developed to compute tissue heterogeneity metrics from MxIF spatially resolved tissue imaging data. This technique computes the molecular state of each cell in a sample based on a pathway or gene set. Spatial states are then computed based on the spatial arrangements of the cells as distinguished by their respective molecular states. MOHA computes tissue heterogeneity metrics from the distributions of these molecular and spatially defined states. A colorectal cancer cohort of approximately 700 subjects with MxIF data is presented to demonstrate the MOHA methodology. Within this dataset, statistically significant correlations were found between the intratumor AKT pathway state diversity and cancer stage and histological tumor grade. Furthermore, intratumor spatial diversity metrics were found to correlate with cancer recurrence. Conclusions MOHA provides a simple and robust approach to characterize molecular and spatial heterogeneity of tissues. Research projects that generate spatially resolved tissue imaging data can take full advantage of this useful technique. The MOHA algorithm is implemented as a freely available R script (see supplementary information).
Semiautomatic reconstruction of building height and footprints from single satellite images

Extraction of man-made structures from satellite images is one of the essential issues in remote sensing and many techniques were proposed for building extraction from high resolution satellite images. However, most of them rely stereo analysis or additional data sources such as LIDAR for retrieval of 3D building information. This paper proposes a semiautomatic approach that extracts 3D building information from single satellite images. In this approach, after measuring boundaries of a building roof we determine the building height by projecting building shadow onto the image space until the projected shadow matches the actual shadow. Then we extract building footprints by translating roof boundaries along the direction of vertical edges to the amount determined by the building height. To increase the level of automation, we devised a technique that adjusts the height so that the projected shadow matches the actual shadow and determine building height automatically. We also devised a technique to extract roof boundaries by clicking only two corner points. A panchromatic IKONOS image and Quickbird image over Deajeon area were used to test proposed algorithms and a IKONO stereo pair was used to get reference building heights. While building heights determined manually showed the accuracy of an RMS error of 1.66 m, the heights determined automatically showed an RMS error of 1.86 m. The results show that 3D building information can be extracted from single satellite images and that the automation approaches proposed in this paper worked.
Antioxidant and acetylcholinesterase inhibiting activity of several aqueous tea infusions in vitro.

Summary A study of antioxidant activity and acetylcholinesterase (AChE) inhibitory activity of aqueous tea infusions prepared from walnut (Juglans regia L.), peppermint (Menthapiperita L.), strawberry (Fragariaananassa L.), lemon balm (Melissa officinalis L.), sage (Salvia offici- nalis L.), and immortelle (Helichrysum arenarium (L.) Moench. ) is presented here. Chemical composition of selected aqueous tea infusions was determined by high-performance liquid chromatography with photodiode-array method (HPLC-PDA), and the following phenolic compounds were identified as dominant: rosmarinic acid, gallic acid (not identified in walnut and sage), caffeic acid (in sage and peppermint), neochlorogenic acid, 3-p-couma- roylquinic acid and quercetin 3-galactoside (in walnut) and luteolin 7-O-glucoside (in sage). Antioxidant activity of the selected aqueous tea infusions was measured using low-density lipoprotein (LDL) oxidation method, 2,2'-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging test, b-carotene bleaching method, and Rancimat method (induction pe- riod of lard oxidation). Strawberry and lemon balm aqueous infusions completely inhibi- ted LDL oxidation at the concentration of 0.005 g/L in the reacting system. Very long pro- longation of the lag phase was achieved with peppermint and sage aqueous infusions. All tested infusions in the concentration range of 0.05-2.85 g/L showed very pronounced ef- fect of DPPH scavenging activity (90-100 %) as well as the inhibition of b-carotene blea- ching (89-100 %). In pure lipid medium, used in Rancimat method, sage and immortelle at the concentration of 0.16 % (by mass) had the highest ability to inhibit lipid peroxidation process. Screening of the AChE inhibitory activity by Ellmans method showed that the strongest inhibition was obtained with walnut and strawberry aqueous infusions at the concentration of 1.36 g/L in the reacting system. The presented results suggest that natural antioxidants could be useful and merit further investigations in the treatment and preven- tion of Alzheimer's disease.
Intermodal Perception of Temporal Order and Motor Skills: Effects of Age

Employing visual, auditory, and tactile stimuli, intermodal differences in perceptual latency were inferred by means of perception of temporal order (PTO) and by varieties of serial reaction times (RT) to the same stimuli. Skill at reading, peg board, tapping, and tracking was also determined for the same Ss. Mean intermodal differences in latency inferred from PTO were significantly different from those obtained from mean RTs. A correlation matrix showed that individual differences in visual, auditory and tactile latencies inferred from PTO were relatively independent of latencies inferred from RT. Consonant with previous studies, PTO scores correlated with reading rate and also with peg board speed. Taking age of Ss into account, the latter correlations were seen to be due exclusively to the presence of older Ss, who did show a correlation between PTO and RT. It was hypothesized that aged Ss show a decrease in perceptual “channel capacity” and a resulting overloading of short-term memory when faced with a complex perceptual and motor task.
Rich club and reward network connectivity as endophenotypes for alcohol dependence: a diffusion tensor imaging study

We aimed to examine the whole‐brain white matter connectivity and local topology of reward system nodes in patients with alcohol use disorder (AUD) and unaffected siblings, relative to healthy comparison individuals. Diffusion‐weighted magnetic resonance imaging scans were acquired from 18 patients with AUD, 15 unaffected siblings of AUD patients and 15 healthy controls. Structural networks were examined using network‐based statistic and connectomic analysis. Connectomic analysis showed a significant ordered difference in normalized rich club organization (AUD < Siblings < Controls). We also found rank ordered differences (Control > Sibling > AUD) for both nodal clustering coefficient and nodal local efficiency in reward system nodes, particularly left caudate, right putamen and left hippocampus. Network‐based statistic analyses showed that AUD group had significantly weaker connectivity than controls in the right hemisphere, mostly in the edges connecting putamen and hippocampus with other brain regions. Our results suggest that reward system network abnormalities, especially in subcortical structures, and impairments in rich‐club organization might be related to the familial predisposition for AUD.
Heat generation by optically and thermally interacting aggregates of gold nanoparticles under illumination

The generation of heat by clusters and arrays of gold nanoparticles under illumination is investigated theoretically. The nanoparticles are embedded in a homogeneous dielectric medium, and the finite thermal resistance at the interface between the nanoparticle and the medium is taken into account. An analytic solution is derived for the case of a single nanoparticle. The T-matrix method is used to calculate the energy absorption efficiency of groups of nanoparticles, taking into account their optical interactions. Heat transfer equations are developed that take into account thermal interactions between nanoparticles. The equations are solved numerically using the finite element software COMSOL. Periodic boundary conditions are applied to treat the thermal interactions between the nanoparticles for arrays of nanoparticles. Results are presented for illumination by a standard xenon flash lamp. The thermal resistance at the nanoparticle–medium interface is found to strongly influence the nanoparticle temperature, but to have negligible influence on the temperature of the dielectric medium after a few tens of nanoseconds of exposure to the flash lamp pulse. Optical interactions are found to be important if particle centres are separated by about twice the particle diameter or less. Thermal interactions between nanoparticles via the medium are found to be the dominant factor in determining the temperature increase in the dielectric medium. The maximum temperature increase is proportional to the volume fraction of the nanoparticles in the medium.
Teratogen Use in Women of Childbearing Potential: An Intervention Study

Purpose: The purpose of this study was to quantify the number of women of childbearing potential who are prescribed angiotensin-converting enzyme inhibitor (ACE inhibitor), angiotensin receptor blocker (ARB), or HMG-coenzyme A reductase inhibitor (statin) and to determine the number of documented teratogenic risk discussions (risk documentation) before and after educational interventions. Methods: The institutional review board–approved retrospective chart review included female patients ages 15 to 45 years who were prescribed an ACE inhibitor, ARB, or statin between January 1, 2007, and March 1, 2009. Exclusion criteria were tubal ligation and hysterectomy. A survey determined physician knowledge of teratogenic risks and prescribing practices for targeted medications. Educational interventions were implemented. Data was reviewed and analyzed quarterly for 1 year. Results: Baseline analysis included 200 patients. A total of 129 (64.5%) patients were prescribed an ACE inhibitor, 29 (14.5%) were prescribed an ARB, and 88 (44.0%) were prescribed a statin. Risk documentation occurred for 40 (20%) patients. Analysis after intervention of 131 patients revealed that risk documentation was 2.4 times greater than before intervention (odds ratio, 2.4; 95% CI, 1.5–3.9). No significant difference identified in survey responses before and after intervention; however, resident physicians overestimated risk documentation. Conclusions: Physicians’ baseline awareness of ACE inhibitor, ARB, or statin teratogenic risks and risk documentation was lacking. Improvement in risk documentation was seen after intervention; however, continual improvement is essential.
Actigraphy scoring reliability in the study of osteoporotic fractures.

STUDY OBJECTIVES The editing and scoring of actigraphy data are important for calculating variables that describe sleep. Scoring is dependent on marking time points for when a participant got in and out of bed, plus time when the actigraph was removed. This placement of time points is subject to error. We examined interscorer reliability to determine if files scored by 2 different people were comparable. DESIGN Observational study. SETTING Community-based. PARTICIPANTS A subset of 36 women taken from the latest biannual visit of the Study of Osteoporotic Fractures. All women had actigraphy data scored by 1 scorer for the Study of Osteoporotic Fractures staff, plus a blinded rescoring by an expert scorer at a different site. INTERVENTIONS N/A. MEASUREMENTS AND RESULTS The outcomes of interest from actigraphy are duration of in-bed interval, total sleep time, sleep latency, sleep efficiency, wake after sleep onset, total nap time, and total daytime minutes of watch removal. Clearly documented actigraphy scoring procedures were used. There were no significant differences between the expert scorer and the study scorer in sleep outcomes (all P values >.16 from a paired t test). There was a small but statistically significant difference between scorers for watch removal times (mean absolute difference 3.4 minutes +/- 5.4, P=.02). The intraclass correlation coefficients showed a high level of agreement (range, 0.84-0.99). CONCLUSIONS Even in a large study with 2 scorers, it is possible to use actigraphy as a measure of sleep without introducing interscorer measurement error. Using well-documented scoring and data-gathering procedures are essential for data quality control.
Prevalence of building-related symptoms as an indicator of health and productivity.

BACKGROUND The prevalence of building-related symptoms (BRS) is commonly used to characterize the indoor air quality in office buildings. To analyze the costs of building renovation and the improvement of the indoor environment, it is useful to quantitatively relate the prevalence or intensity of BRS to productivity. The intent of this study is to summarize the links between the BRS and productivity, and demonstrate this linkage in two case buildings. MATERIAL AND METHODS A literature was surveyed for studies that measured simultaneously the prevalence or intensity of BRS and subjectively reported or objectively measured productivity. Case studies in two office environments were performed. An association between the prevalence of BRS and productivity of workers in a call center and in an insurance office were investigated. In the first case study, the productivity was expressed using the direct productivity metrics, namely the number of telephone contacts during active working hours while in the second case, the productivity was assessed by using the data concerning sick leave rates. RESULTS Employees who report more BRS also have more often absences which relate to indoor environment quality (IEQ). Their productivity is lower than those who have better IEQ in their offices. Despite uncertainties related to the data concerning recorded sick leave and self-reported productivity, the number of studies showing an association between BRS and productivity or sick leave suggests that such a relationship exists. The present case studies also demonstrated an association between the BRS and the direct productivity. Based on the data from the call center, a reduction of 10%-units in the prevalence of general symptoms (such as fatigue, headache, nausea, etc.) corresponded with a gain of 1.5% in performance. Based on the findings in the insurance company, a reduction of 10%-units in the prevalence of irritation symptoms corresponded with a decrease of 0.7% in the short-term absenteeism. CONCLUSIONS A review of 23 studies suggests that a linkage exists between typical BRS and productivity indicators such as task or work performance or absence from work. Quantitative associations between BRS and productivity were demonstrated in two office environments. Quantitative associations between BRS and economic metrics enable cost-benefits analysis.