Miracle-dz/UniFAR-FTUs huggingface dataset:
Intercomparison of near real time monitors of PM2.5 nitrate and sulfate at the U.S. Environmental Protection Agency Atlanta Supersite

[1] Five new instruments for semicontinuous measurements of fine particle (PM2.5) nitrate and sulfate were deployed in the Atlanta Supersite Experiment during an intensive study in August 1999. The instruments measured bulk aerosol chemical composition at rates ranging from every 5 min to once per hour. The techniques included a filter sampling system with automated water extraction and online ion chromatographic (IC) analysis, two systems that directly collected particles into water for IC analysis, and two techniques that converted aerosol nitrate or sulfate either catalytically or by flash vaporization to gaseous products that were measured with gas analyzers. During the one-month study, 15-min integrated nitrate concentrations were low, ranging from about 0.1 to 3.5 μg m -3 with a mean value of 0.5 μg m -3 . Ten-minute integrated sulfate concentrations varied between 0.3 and 40 μg m -3 with a mean of 14 μg m -3 . By the end of the one-month study most instruments were in close agreement, with r-squared values between instrument pairs typically ranging from 0.7 to 0.94. Based on comparison between individual semicontinuous devices and 24-hour integrated filter measurements, most instruments were within 20-30% for nitrate (∼0.1-0.2 μg m -3 ) and 10-15% for sulfate (1-2 leg m -3 ). Within 95% confidence intervals, linear regression fits suggest that no biases existed between the semicontinuous techniques and the 24-hour integrated filter measurements of nitrate and sulfate;, however, for nitrate, the semicontinuous intercomparisons showed significantly less variability than intercomparisons amongst the 24-hour integrated filters.
A feasibility assessment of wold reintroduction to the Cape Breton Highlands

This thesis reports an assessment of the feasibility of establishing a viable population of Wolves (Canis sp.) on Cape Breton Island, Nova Scotia as a means of determining if Wolves can limit Moose (Alces alces) abundance in Cape Breton Highlands National Park (CBHNP) to densities desired by Parks Canada ecologists (e.g., 0.5 Moose/km2). As apex carnivores, Wolves are effective in preventing ungulate populations from reaching hyperabundant levels. It is uncertain which Canis species was present in the region prior to preEuropean settlement and therefore, I used ArcGIS and Marxan to estimate the amount of available habitat for both Gray (Canis lupus) and Eastern Wolf (C. lycaon) to form territorial packs on Cape Breton Island. The population viability analysis programme VORTEX was used to predict the population size of a viable population, as well as the size needed to limit Moose (A. a. andersoni) abundance to levels less likely to impact vegetation. VORTEX simulated the population by evaluating the annual life cycle and tracking mate selection, reproduction, mortality, increment of age by one year of individuals, as well as migration among populations, removals, and supplementation. Based on the VORTEX model simulations of the long-term viability of both Wolf species, the optimal and suboptimal habitat within the National Park and adjacent highland areas could support 30 C. lupus (16 inside the Park and 14 outside of the Park), or 33 (17 inside the Park, and 16 outside of the Park) C. lycaon, respectfully. Results identified several factors important to the long-term viability of Wolf populations: 1) the percentage of adult females breeding; 2) carrying capacity; and: 3) mortality rates. If the percentage of female breeders (C. lupus) remains 55% or higher, and Wolves are not subject to immediate and long-term anthropogenic mortality risk (modelled as 30% inn mortality pups, 10% in adults), the population maintains a carrying capacity of n = 36 with a low probability of extinction (<0.25). However, based on mainly negative public attitudes to Eastern Coyote in the region, it is presumed that mortality rates will be high outside of the National Park; a Park-only population size of 16 Gray Wolves would not be viable, nor reduce Moose density to desired levels. Even if mortality rates outside
The value of cytological diagnosis of small cell lung carcinoma.

INTRODUCTION Small cell lung carcinoma (SCLC) is a very aggressive neoplasm. Accurate and quick diagnosis is crucial to initiate proper treatment. The aim of this study was to establish the value of initial cytological diagnosis and to present typical cytological features of SCLC. MATERIAL AND METHODS We reviewed 116 cases of SCLC confirmed by cytology in: bronchial brushings, pleural fluids, and fine needle aspiration biopsies (FNAB). RESULTS In 77% of SCLC cases, the diagnosis was established only by cytology; in 23% of cases, both cytological and histological recognition was possible. Cytology of SCLC was initially uncertain in 12%, and histology was uncertain in 30% of the cases. The morphology of SCLC cells was not uniform, and often a mixture of non-small atypical cells and bronchial epithelial cells with signs of metaplasia was observed. There were four cases of combined cell type with large cell carcinoma and two with adenocarcinoma. The main diagnostic problem was to distinguish small cell lung carcinoma from lymphomas, and from cancer consisting of small cells with the cytological features of non-small cell carcinoma. CONCLUSION Diagnosis of SCLC in cytological smears is accurate, and final diagnosis is based on light microscopy. In the differential diagnosis, other tumours of small cells have to be taken into account.
Chronic Illness with Complexities: Mental Illness and Substance Use Among Veteran Clinic Users with Diabetes

Objective: Create a taxonomy and examine the predictors of the often co-occurring conditions of substance use disorders and mental illness in veterans with diabetes. Design: Merged Veteran Health Administration and Medicare fee-for-service claims data (N = 485,893). Results: Thirty-one percent of patients with diabetes were diagnosed with either mental illness or substance use and had higher rates of diabetes-related complications. Women were more likely to have serious mental illness; African Americans and Latinos more likely to have drug and/or alcohol use. Conclusion: Prevalence of substance use disorder and mental illness differed by socio-demographics, suggesting the need for tailored diabetes management interventions.
Nonlinear Intrinsic Dimensionality Computations

In pattern recognition, the raw data and dimensionality of the measurement space is usually very large. Therefore, some form of dimensionality reduction has been commonly considered as a practical preprocessing method for feature selection. Based on a method that increases the variance while maintaining local structure, a technique is developed to determine intrinsic dimensionality. A cost function is introduced to guide the maintenance of the rank order and therefore local structure. Two criteria of using the cost function to increase the variance have been introduced. Several methods of defining the local regions are suggested. A program is implemented and tested to find the intrinsic dimensionality of a variety of experimental data.
Mixed continuous/binary quantum-inspired learning system with non-negative least square optimisation for automated design of regularised ensemble extreme learning machines

In this paper, a hybrid quantum-inspired evolutionary algorithm (QIEA) is proposed to automatically design regularised ensemble extreme learning machines (EELMs). Quantum evolutionary computing is a relatively recent spot-lighted concept which takes advantage from both the evolutionary and quantum computing laws. In general, QIEAs have been proven to be really powerful for optimising complex engineering tasks. The fascinating trait of observation operator in QIEA enables us to transform the quantum bits to both the binary and continuous spaces. Here, the authors present a mix continuous/binary version of QIEA, to find out whether it is suited for designing regularised EELMs. Indeed, the design process of EELM is conducted at two different levels, i.e. hyper and low levels. At the low level, some novel criteria are presented in the form of penalty functions to enable the optimiser searching for parsimonious, compact and accurate regularised extreme learning machines, as individual components of the ensemble. At the hyper-level, the non-negative least square error optimisation technique is utilised to deterministically find the most eligible components for designing the ensemble. Through extensive numerical experiments, the authors demonstrate that the proposed method is really efficient for the automated design of EELM identifiers.
Live Semantic Sport Highlight Detection Based on Analyzing Tweets of Twitter

Microblogging as a new form of communication on Internet, has attracted the attention from researchers recently. Relying the real-time and conversational properties of microblogging, its users update their statuses and share experience within their the social network. Those characteristics also make microblogging an important tool for users to share or discuss real world events such as earth quake or sport game. In this paper, we propose a novel and flexible solution to detect and recognize real-time events from sport games based on analyzing the messages posted on microblogging services. We take Twitter as the experiment platform and collect a large-scale dataset of Twitter messages that are called tweets for 18 prominent sport games covering four types of sports in 2011. We also collect corresponding sport videos for those games. The proposed solution applies moving-threshold burst detection on the volume of tweets to detect highlights in sport games. A tf-idf-based weighting method is applied on the tweets within detected highlights for semantic extraction. According to the experiments we perform on the tweet and video datasets, we find that the proposed methods can achieve competent performance in sport event detection and recognition. Besides, our method can find non pre-defined tidbits that are difficult to detect in previous works.
Stabilization of thalamo‐cortical long‐term potentiation by the amygdala: cholinergic and transcription‐dependent mechanisms

Synaptic potentiation allows neurons to enhance excitability and store information for extended time periods. We examined the role of the amygdaloid complex, known to facilitate long‐term memory encoding, to influence synaptic strength at thalamo‐cortical synapses. In urethane‐anaesthetized rats, theta‐burst stimulation of the dorsal lateral geniculate nucleus of the thalamus induced early phase (1–2 h) long‐term potentiation (LTP) of the field postsynaptic potential (fPSP) recorded in the ipsilateral primary visual cortex. Electrical stimulation (100 Hz) of the amygdala 5 min after thalamic stimulation converted early phase LTP to stable late‐phase (> 4 h) LTP. This effect was not correlated with the degree of electrocorticographic activation of V1 induced by amygdala stimulation. Amygdala stimulation without thalamic theta‐burst stimulation did not change thalamo‐cortical fPSPs. The centrally acting cholinergic‐muscarinic receptor antagonist scopolamine (1 mg/kg, i.p.), but not peripherally acting methyl‐scopolamine, completely blocked the amygdala‐induced conversion of early to late‐phase thalamo‐cortical LTP. Further, ventricular application of the transcription inhibitor anisomycin (250 µg) reduced amygdala‐induced late‐phase LTP induction. These results demonstrate that the amygdaloid complex transforms time‐limited synaptic enhancement of thalamo‐cortical transmission into long lasting increases in synaptic strength. These processes are mediated, at least in part, by cholinergic and transcription‐dependent mechanisms. These amygdaloid‐induced effects provide a potential mechanism underlying long‐term enhancement of sensory transmission and information encoding in thalamo‐cortical networks.
Intestinal Stem Cells in GI Physiology and Disease Mitochondrial DNA polymerase editing mutation , PolgD 257 A , disturbs stem-progenitor cell cycling in the small intestine and restricts excess fat absorption

Raymond G. Fox, Scott Magness, Gregory C. Kujoth, Tomas A. Prolla, and Nobuyo Maeda Curriculum in Genetics and Molecular Biology, Department of Pathology and Laboratory Medicine, Department of Medicine, Division of Gastroenterology and Hepatology, University of North Carolina, Chapel Hill, North Carolina; and Departments of Genetics and Medical Genetics and Neurological Surgery, University of Wisconsin, Madison, Wisconsin
A novel method for transient detection in high-cadence optical surveys - Its application for a systematic search for novae in M 31

Context. In the present era of large-scale surveys in the time domain, the processing of data, from procurement up to the detection of sources, is generally automated. One of the main challenges in the astrophysical analysis of their output is contamination by artifacts, especially in the regions of high surface brightness of unresolved emission. Aims. We present a novel method for identifying candidates for variable and transient sources from the outputs of optical time-domain survey data pipelines. We use the method to conduct a systematic search for novae in the intermediate Palomar Transient Factory (iPTF) observations of the bulge part of M 31 during the second half of 2013. Methods. We demonstrate that a significant fraction of artifacts produced by the iPTF pipeline form a locally uniform background of false detections approximately obeying Poissonian statistics, whereas genuine variable and transient sources, as well as artifacts associated with bright stars, result in clusters of detections whose spread is determined by the source localization accuracy. This makes the problem analogous to source detection on images produced by grazing incidence X-ray telescopes, enabling one to utilize the arsenal of powerful tools developed in X-ray astronomy. In particular, we use a wavelet-based source detection algorithm from the Chandra data analysis package CIAO. Results. Starting from ~2.5 × 10^5 raw detections made by the iPTF data pipeline, we obtain approximately 4000 unique source candidates. Cross-matching these candidates with the source-catalog of a deep reference image of the same field, we find counterparts for ~90% of the candidates. These sources are either artifacts due to imperfect PSF matching or genuine variable sources. The remaining approximately 400 detections are transient sources. We identify novae among these candidates by applying selection cuts to their lightcurves based on the expected properties of novae. Thus, we recovered all 12 known novae (not counting one that erupted toward the end of the survey) registered during the time span of the survey and discovered three nova candidates. Our method is generic and can be applied to mining any target out of the artifacts in optical time-domain data. As it is fully automated, its incompleteness can be accurately computed and corrected for.
Adaptive online learning for human tracking

In this work, we present a multiple classifiers system cascades an on-line learning RGB-D appearance model framework in which detection, recognition, and tracking are highly coupled for a wheelchair robot equipped with a Kinect sensor to improve the efficiency of the care assistance and quality of accompanying service. The on-line trained classifiers use the surrounding background as negative examples in the updating which allows the algorithm to choose the most discriminative features between the target and the background, incrementally adjust to the changes in specific tracking environment. Meanwhile, a depth clustering based human detection is proposed to extract human candidates. Accordantly, an on-line learning RGB-D appearance model is cascaded to strengthen the human tracking function by dealing with color, depth and position information from the identified caregiver. Consequently, several experiments have been conducted to demonstrate the effectiveness and feasibility in real world environments.
Hybrid functional calculations on the Na and K impurities in substitutional and interstitial positions in Cu2ZnSnSe4

We studied the energetics, atomic and electronic structure of Na and K extrinsic defects in Cu2ZnSnSe4 by ab initio calculations using the HSE06 hybrid functional. Our results show that (i) among all substitutional positions, the Cu-site is the most favorable position for both Na and K. (ii) The tetrahedrally coordinated interstitial site has a lower formation energy than the octahedrally coordinated interstitial site. (iii) Based on the band structure calculations we can conclude, Se-related defects lead to the formation of defect states within the band gap.
Thymic stromal lymphopoietin is present in human breast milk

Macfarlane TV, Seager AL, Moller M, Morgan G, Thornton CA. Thymic stromal lymphopoietin (TSLP) is present in human breast milk. Pediatr Allergy Immunol 2010: 21: e454–e456. © 2010 The Authors Journal compilation © 2010 Blackwell Munksgaard
Title Improving the generalisation ability of genetic programmingwith semantic similarity based crossover

This paper examines the impact of semantic control on the abi lity of Genetic Programming (GP) to generalise via a semantic based crossover operator (Semantic Similarity based Crossover SSC). The use of vali dation sets is also investigated for both standard crossover and SSC. All GP sys tems are tested on a number of real-valued symbolic regression problems. The e xp rimental results show that while using validation sets barely improve genera lisation ability of GP, by using semantics, the performance of Genetic Programming is enhanced both on training and testing data. Further recorded statistics s how that the size of the evolved solutions by using SSC are often smaller than ones ob tained from GP systems that do not use semantics. This can be seen as one of th e reasons for the success of SSC in improving the generalisation ability of GP .
Mining Frequent Temporal Patterns in Interval Sequences

Recently a new type of data source came into the focus of knowledge discovery from temporal data: interval sequences. In contrast to event sequences, interval sequences contain labeled events with a temporal extension. However, existing algorithms for mining patterns from interval sequences proved to be far from satisfying our needs. In brief, we missed an approach that, at the same time, defines support as the number of pattern instances, allows input data that consists of more than one sequence, implements time constraints on a pattern instance, and counts multiple instances of a pattern within one interval sequence. In this paper we propose a new support definition which incorporates these properties. We also describe FSMSet, an algorithm that employs the new support definition, and demonstrate its performance on field data from the automotive business.
Modeling the Decline in English Passivization

Evidence from the Hansard corpus shows that the passive voice in British English has declined in relative frequency over the last two centuries. We investigate which factors are predictive of whether transitive verb phrases are passivized. We show the increasing im-portance of the person-hierarchy effects observed by Bresnan et al. (2001), with increasing strength of the constraint against passiviz-ing clauses with local agents, as well as the rising prevalence of such agents. Moreover, our ablation experiments on the Wall Street Journal and Hansard corpora provide support for the unmarked information structure of ‘given’ before ‘new’ noted by Halliday (1967).
In vitro degradation and erosion of degradable, segmented polyurethanes containing an amino acid-based chain extender

In vitro degradation and erosion of novel, degradable segmented polyurethanes containing a phenylalanine diester chain extender were investigated by exposing the polymers to buffer, chymotrypsin, and trypsin solutions for up to 28 days. Polyurethane degradation and erosion were monitored by gravimetry, scanning electron microscopy (SEM), and gel permeation chromatography (GPC) and compared to a control polyurethane. Polyurethanes were synthesized using two different soft segments (polycaprolactone diol and polyethylene oxide) of variable molecular weight. Inclusion of the phenylalanine-based chain extender resulted in an increased susceptibility to enzyme-mediated, but not buffer-mediated, erosion in comparison to the control polyurethane. SEM analysis indicated that enzyme-mediated erosion proceeded via a surface-limited mechanism resulting in a progressive removal of material from the surface inwards with time. The magnitude of degradation and erosion was highly variable and was dependent on soft segment type and molecular weight. The range of degradation rates, as well as physicochemical properties, makes these polyurethanes potentially useful for a wide range of biomedical applications.
FACTORS FOR SUCCESSFUL IMPLEMENTATION OF ERP SYSTEMS

Original scientific paper This meticulous research presents methodological aspects of key factors influencing the implementation and introduction of modern information systems, with special emphasis on the implementation of integrated comprehensive ERP system in enterprises in the region. The aim of the work stems directly from the research subject itself and the presentation of the analysis of the ERP systems implementation, through the study of relevant scientific literature and conducted research examples in practice on a representative sample of enterprises, varying in type of activity and ownership structure. The results of this study can serve as material for everyone involved in this current topic, and for those who decide to implement modern integrated ERP solutions to their business, and who want to expand their knowledge respectively.
Preliminary Results on the Daily and Seasonal Rhythms of Cuttlefish Sepia officinalis (Linnaeus, 1758) Locomotor Activity in Captivity

This research was aimed at characterizing the daily rhythms of locomotor activity of cuttlefish Sepia officinalis (Linnaeus, 1758), a promising aquaculture species, in a captive environment. Cuttlefish were distributed within two tanks equipped with infrared photocells, allowing the monitoring of locomotor activity continuously from August to February. Results showed a preference of cuttlefish for being active during the night in summer (24.2 ± 1.3 °C) and in autumn (18.4 ± 3.4 °C), with maximum activity peaks observed, respectively, at 01:09 h and 21:47 h, in close relation with sunset time. In winter (12.7 ± 1.4 °C), this preference changed, with higher levels of activity observed during the afternoon in December (15:20 h) and in January (18:13 h), thus suggesting this species as possessing a dualistic behaviour. Levels of activity progressively decreased during autumn and winter, likely related to low temperatures. The present study offers new insights on the behaviour of Sepia officinalis, presenting a variability of patterns across seasons, regulated by environmental synchronizers; photoperiod determining the activity periods, and temperature modulating the levels of activity. Such information may be a valuable tool for the improvement of cuttlefish culture protocols in aquaculture, and consequently its welfare.