Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation and modi fi cation of HPLC method for monitoring acetaminophen plasma concentrations in patients with chronic pancreatitis

Background. Pancreatitis is the infl ammation of the pancreas. Th e infl ammation may occur suddenly and resolve in a few days with the treatment in case of acute pancreatitis (AP). Chronic pancreatitis (CP) is a persistent infl ammation of the pancreas that results in irreversible morphological changes and impairment of both exocrine and endocrine functions. Abdominal pain is a typical symptom in both acute and chronic pancreatitis. Th erefore, the application of analgesics to this group of patients is a part of complex pharmacotherapy. Material and methods. A simple, precise, specifi c, and accurate HPLC (High Performance Liquid Chromatography) method was developed for the determination of acetaminophen (AAP) in human plasma. Th e chromatography was set on XTerra® RP C18, 150×4.6 mm, 3.5 μm column. Th e UV detector was set at 254 nm for AAP and phenacetin (internal standard). Th e injection volume was 2 μL. Th e mobile phase comprised phosphate buff er pH 3.5 and methanol in the ratio of 80:20 with fl ow rate of 1 mL/min. Results. Th e calibration for AAP was linear in the range 1.0-30.0 μg/mL. Lower limit of quantifi cation (LLOQ) was 1.0 μg/mL. Th e results for quality control samples (QCs) at concentrations of 1, 6, 15, and 25 μg/mL were less than 15% indicating good intraand inter-day precision. Blood samples from patients with chronic pancreatitis were collected within 8 h aft er the drug intravenous administration (1000 mg). Pharmacokinetic (PK) parameters for AAP were estimated by non-compartmental method. Conclusion. Th e proposed HPLC-UV method is suitable for routine analysis in patients. (Farm Współ 2017; 10: 3-10)
A novel multi-channel SAR-GMTI algorithm based on raw data

This paper presents a novel SAR-GMTI algorithm based on the range-compressed raw data. FrFT is introduced to the classical three-channel DPCA system to realize the moving target detection, parameter estimation and SAR imaging, acquiring an exact GMTI image of accelerative moving targets. As a pretreatment, Keystone transform is firstly applied to process the echoes receiving from each sub-aperture respectively in order to remove the range migration. Our scheme is available even under a clutter-rich and low SNR environment. The simulation results indicate the efficiency of the method.
Persistence of Borrelia burgdorferi in experimentally infected dogs after antibiotic treatment

In specific-pathogen-free dogs experimentally infected with Borrelia burgdorferi by tick exposure, treatment with high doses of amoxicillin or doxycycline for 30 days diminished but failed to eliminate persistent infection. Although joint disease was prevented or cured in five of five amoxicillin- and five of six doxycycline-treated dogs, skin punch biopsies and multiple tissues from necropsy samples remained PCR positive and B. burgdorferi was isolated from one amoxicillin- and two doxycycline-treated dogs following antibiotic treatment. In contrast, B. burgdorferi was isolated from six of six untreated infected control dogs and joint lesions were found in four of these six dogs. Serum antibody levels to B. burgdorferi in all dogs declined after antibiotic treatment. Negative antibody levels were reached in four of six doxycycline- and four of six amoxicillin-treated dogs. However, in dogs that were kept in isolation for 6 months after antibiotic treatment was discontinued, antibody levels began to rise again, presumably in response to proliferation of the surviving pool of spirochetes. Antibody levels in untreated infected control dogs remained high.
Probabilistic analysis for a multiple depot vehicle routing problem

We give a probabilistic analysis of the Multiple Depot Vehicle Routing Problem (MDVRP) where k depots and n customers are given by i.i. d. random variables in [0,1]d, d ≥ 2. The tour length divided by n(d−1)/d tends to α∫ [0,1] df(x)(d−1)/d dx, where f is the density of the absolutely continuous part of the law of the random variables giving the depots and customers and where the constant α depends on the number of depots. If k = o(n), α is the constant of the TSP problem. For k = λn, λ > 0, we prove lower and upper bounds on α, which decrease as fast as (1 + λ)−1/d. © 2006 Wiley Periodicals, Inc. Random Struct. Alg. , 2007
Modified Hamming Codes to Enhance Short Burst Error Detection in Semiconductor Memories (Short Paper)

Error correction codes are used in semiconductor memories to protect information against errors. Simple error correction codes are preferred due to their low redundancy and encoding/decoding latency. Hamming codes are simple and can be easily built for any word length. They only allow single error correction, so a multiple error can lead to a wrong decoding. Multiple errors often manifest as burst errors, and they are becoming more frequent as integration scale increases. This paper proposes modified Hamming codes, with the same redundancy and coverage as the original versions, but adding short burst error detection. Three code examples, with different error correction and detection capabilities, are presented. They are especially well-suited for memories, where the length of the data word is commonly a power of 2, and low redundancy and fast and simple encoder and decoder circuits are required.
Increasing the Expressivity of Conditional Functional Dependencies without Extra Complexity

The paper proposes an extension of CFDs [1], referred to as extended Conditional Functional Dependencies (eCFDs). In contrast to CFDs, eCFDs specify patterns of semantically related values in terms of disjunction and inequality, and are capable of catching inconsistencies that arise in practice but cannot be detected by CFDs. The increase in expressive power does not incur extra complexity: we show that the satisfiability and implication analyses of eCFDs remain NP - complete and coNP -complete, respectively, the same as their CFDs counterparts. In light of the intractability, we present an algorithm that approximates the maximum number of eCFDs that are satisfiable. In addition, we revise SQL techniques for detecting CFD violations, and show that violations of multiple eCFDs can be captured via a single pair of SQL queries. We also introduce an incremental SQL technique for detecting eCFD violations in response to database updates. We experimentally verify the effectiveness and efficiency of our SQL -based detection methods.
Designed as the first phase of a larger project to explore the relationships between the possible impact of reminiscence on memory deterioration in elderly women confined to nursing home

Designed as the first phase of a larger project to explore the relationships between the possible impact of reminiscence on memory deterioration in elderly women confined to nursing home environments, a study demonstrated that reminiscence activity is positively correlated with increases in communication interactions. Women were chosen as the target sample population because they comprise the largest single grouping currently residing in nursing home facilities. The methodology chosen was a one-to-one reminiscence activity between the elderly subject and a trained facilitator who had 12 years of experience as an activities director in several large nursing homes. Participants (n=12) met with a trained facilitator on three occasions over a 5-week period. Session one encouraged discussion of a favorite vacation or travel experience; session two encouraged discussion of a favorite pet or experience with animals; session three encouraged discussion of favorite dances, parties or other kinds of entertainment. In general, there was an overall increase in the amount, frequency, and length of interactions both initiated and maintained by the subjects in the study. All subjects demonstrated an increase in their willingness to interact with each other, staff members, volunteers, and relatives. For example, five of the subjects were slower to initiate interaction; they represented the most cognitively impaired, two being in the beginning stages of Alzheimer's disease. In two other cases, the increase in social activity was remarkable. Previously unwilling to leave their rooms, they eagerly sought out others and insisted on participating in programmed activities. (Contains 38 references.) (TB) *********************************************************************** * Reproductions supplied by EDRS are the best that can be made from the original document. **********************************************************************
The Neural System of Postdecision Evaluation in Rostral Frontal Cortex during Problem-solving Tasks

Visual Abstract Little attention has been paid to the postdecision processing in fMRI studies with task paradigms in which there was no explicit feedback. Although late-onset BOLD responses were previously observed in the lateral frontopolar cortex after the familiar-novel decision on visually presented words, the nature of neural activations that caused the late-onset BOLD responses remained elusive. We here found, in human experts conducting complicated problem-solving tasks in their expertise domain, that the rostral frontal cortex, including the lateral frontopolar cortex, along with the anterior inferior parietal lobule, was activated only during the postdecision period, although there was no feedback. That is, these areas showed late-onset BOLD responses, and fitting of the BOLD responses with different models indicates that they were caused by neural activations that occurred after the decision. However, there was no response after performing a sensory-motor control task, and the magnitude of postdecision activations was correlated with the degree of uncertainty about the preceding decision, which suggests that the postdecision neural activations were associated with the preceding decision procedure. Furthermore, the same set of areas was more strongly activated when the subject explicitly rethought the preceding problem. These results suggest that the rostral frontal cortex, together with anterior inferior parietal lobule, comprises a network for uncertainty monitoring and exploration of alternative resolutions in postdecision evaluation. The present results thus introduce a new aspect of the functional gradient along the rostrocaudal axis in the frontal cortex.
An ocular artefacts correction method for discriminative EEG analysis based on logistic regression

Electrooculogram (EOG) contamination is a common critical issue in general EEG studies as well as in building highperformance brain computer interfaces (BCI). Existing regression or independent component analysis based artefacts correction methods are usually not applicable when EOG is not available or when there are very few EEG channels. In this paper, we propose a novel ocular artefacts correction method for processing EEG without using dedicated EOG channels. The method constructs estimate of ocular components through artefacts detection in EEG. Then, an optimization based on logistic regression is introduced to remove the components from EEG. Specifically, the optimization ensures that the discriminative information is maintained in the corrected EEG signals. The proposed method is offline evaluated with a large EEG data set containing 68 subjects. Experimental results show that, through the artefacts removal correction by the proposed method, EEG classification accuracy can be improved with statistical significance.
DISTRACTED DRIVER BEHAVIOUR MODELS

Distraction is detrimental to traffic safety. This thesis provides insights into distracted driving behaviours through two research objectives explored on naturalistic driving data: 1) distraction engagement behaviours and visual attention allocation as a function of varying environmental demands, and 2) engagement in multiple types of secondary tasks. For this purpose, Naturalistic Engagement in Secondary Tasks (NEST) dataset was utilized. Through inferential statistics, it was shown that higher visual difficulty in the driving environment is associated with a decreased likelihood of distraction engagement, and a decrease in non-forward glances with the likelihood of longer glances (> 2s) being reduced to a larger extent compared to shorter ones (> 1.6s). Drivers 35 and older have reduced rates of non-forward glances compared to younger drivers. Moreover, the results demonstrate that engagement in multiple secondary task types is prevalent, and is more likely to occur in safety-critical as opposed to non-safety critical situations (baselines).
Linking Arable Crop Occurrence with Site Conditions by the Use of Highly Resolved Spatial Data

Agricultural land use is influenced in different ways by local factors such as soil conditions, water supply, and socioeconomic structure. We investigated at regional and field scale how strong the relationship of arable crop patterns and specific local site conditions is. At field scale, a logistic regression analysis for the main crops and selected site variables detected, for each of the analyzed crops, its own specific character of crop–site relationship. Some crops have diverging site relations such as maize and wheat, while other crops show similar probabilities under comparable site conditions, e.g., oilseed rape and winter barley. At the regional scale, the spatial comparison of clustered variables and clustered crop pattern showed a slightly stronger relationship of crop combination and specific combinations of site variables compared to the view of the single crop–site relationship.
Fluctuations in exchange rate and aggregate exports in Ukraine

This paper examines the effect of Exchange Rate Volatility (ERV) on the aggregate exports of Ukraine during the period of 1990 to 2013 using quarterly data. In the literature, it is found that exchange rate volatility causes a reduction in the overall level of trade. The paper tests this finding for Ukrainian foreign trade in the aforementioned period using the Autoregressive Distributed Lags (ARDL) method to co-integration. Overall, our findings suggest that there is a negative effect of ERV on Ukrainian exports. From a policy prospective, this result is important because it suggests that policy makers should consider the negative effect of ERV on exports when exercising exchange rate policy for balance of payment purposes.
On Learning Researchers' Dynamic Information Needs: An Entropy-Based Query Expansion Approach

Literature survey is one of the most important steps in the process of academic research, allowing researchers to explore and understand topics. However, researchers without sufficient prior knowledge lack the skills to determine proper and accurate keywords for investigating the topics at hand. To tackle this problem, we proposed an entropy-based query expansion with a reweigh ting (E_QE) approach to revise queries during the iterative retrieval process. We designed a series of experiments that consider the researcher's changing information needs during task execution. Two topic change situations are considered in this work¡Xboth minor, and dramatic topic changes. The simulation-based pseudo-relevance feedback technique is applied during the search process to evaluate the effectiveness of the proposed approach without the intervention of human efforts. We measured the effectiveness of the TFIDF and E_QE approaches for different types of topic change situations. The preliminary results show that the proposed query expansion approach can achieve better results, helping researchers to revise queries.
How Remote Work Can Foster a More Inclusive Environment for Transgender Developers

In this position paper, we claim that remote work offers a mechanism of control for identity disclosure and empowerment of software developers from marginalized communities. By talking to several transgender software developers we identified three themes that resonate across the trans experience and intersect with the advantages to working in software development remotely: identity disclosure, high-impact technical work and the autonomy to disengage and re-engage. Based on these themes we identify several open questions that the research community should address.
Spectroscopy of GRB 051111 at z = 1.54948: Kinematics and Elemental Abundances of the GRB Environment and Host Galaxy

We present a high-resolution, high S/N optical spectrum of the afterglow of GRB 051111 obtained with the HIRES spectrograph on the Keck I 10 m telescope. The spectrum exhibits three redshifted absorption systems with the highest, at z = 1.54948, arising in the GRB host galaxy. While the Lyα feature is outside the range of our spectrum, the high column density of weakly depleted Zn suggests that the host is a damped Lyα system with N(H ) ≳ 1021(Z/Z☉)-1. The bulk of the gas (>80%) is confined to a narrow velocity range of |v| < 30 km s-1, exhibiting strong dust depletion of refractory elements such as Fe and Cr. The depletion pattern is similar to that observed in warm disk clouds of the Milky Way. We also detect absorption from all ground-level fine-structure states of Fe II, the first such example in a QSO-DLA system or GRB-absorption spectrum, which indicate conditions that are consistent with the "warm disk" depletion pattern. The absorption profiles of Fe II and Mg II extend over several hundred km s-1, with a depletion pattern that more closely resembles that of QSO-DLA systems, suggesting that the sight line to GRB 051111 probes the halo of the host galaxy in addition to the dense disk. Thus, detailed diagnostics of the interstellar medium of GRB host galaxies continue to provide insight into regions that are generally missed in quasar surveys.
Target-sheep Transform-Source U Target-flower Transform-Source vs U Shape transfer Target-sheep Transform-Source U Target-flower Transform-Source vs Φ

We aim at improving object recognition with few training data in the target domain by leveraging abundant auxiliary data in the source domain. The major issue obstructing knowledge transfer from source to target is the limited correlation between the two domains. Transferring irrelevant information from the source domain usually leads to performance degradation in the target domain. To address this issue, we propose a transfer learning framework with the two key components, discriminative source data reconstruction and dual-domain boosting. The former correlates the two domains via reconstructing source data by target data in a discriminative manner. The latter discovers and delivers only knowledge shared by the target data and the reconstructed source data. Hence, it facilitates recognition in the target. The promising experimental results on three benchmarks of object recognition demonstrate the effectiveness of our approach.
Buffer management problems

In recent years, there has been a lot of interest in Quality of Service (QoS) networks. In regular IP networks, packets are indistinguishable and in case of overload any packet may be dropped. In a commercial environment, it is much more preferable to allow better service to higher-paying customers or customers with critical requirements. The idea of Quality of Service guarantees is that packets are marked with values which indicate their importance. This naturally leads to decision problems at network switches when many packets arrive and overload occurs. In this paper, we give an overview of several models that have been studied in this area from an online perspective. These models differ by restrictions such as bounded delay, bounded size of queue etc. We first present results for a single buffer in Section 1 and then for multiple buffers in Section 2. This paper is not meant as a comprehensive survey of the work in this area. There are many more variations of these problems that have been studied, for instance, multiple output buffers [14]. Our goal was merely to give a taste of this problem area, and we hope you enjoy it.
The Effets of Payroll Tax Subsidies for Low Wage Workers on Firms Level Decisions

We study the effect of the large increase of payroll tax subsidies for low-wage workersthat occurred in France in 1995. We compute the ex ante changes in average labor costs in1994 solely due to the changes in the tax subsidies and consider it as a treatment variable.We extend the Rubin causal framework to the case of a continuous treatment, define theensuing parameters of interest and generalize the propensity score property. We find thatpayroll tax subsidies had a strong effects on employment and on other firms outcomes,stock of capital, share of unskilled workers and average labor cost.
X-ray flare candidates in short gamma-ray bursts

We present the first systematic study of X-ray flare candidates in short gamma-ray bursts (SGRBs) exploiting the large 6-year Swift data base with the aim to constrain the physical nature of such fluctuations. We find that flare candidates appear in different types of SGRB host galaxy environments and show no clear correlation with the X-ray afterglow lifetime; flare candidates are detected both in SGRBs with a bright extended emission in the soft γ -rays and in SGRBs which do not show such component. We furthermore show that SGRB X-ray flare candidates only partially share the set of observational properties of long GRB (LGRB) flares. In particular, the main parameter driving the duration evolution of X-ray variability episodes in both classes is found to be the elapsed time from the explosion, with very limited dependence on the different progenitors, environments, central engine lifetimes, prompt variability timescales and energy budgets. On the contrary, SGRB flare candidates significantly differ from LGRB flares in terms of peak luminosity, isotropic energy, flare-to-prompt luminosity ratio and relative variability flux. However, these differences disappear when the central engine time-scales and energy budget are accounted for, suggesting that (i) flare candidates and prompt pulses in SGRBs likely have a common origin; (ii) similar dissipation and/or emission mechanisms are responsible for the prompt and flare emission in LGRBs and SGRBs, with SGRBs being less energetic albeit faster evolving versions of the long class. Finally, we show that in strict analogy to the SGRB prompt emission, flares candidates fall off the lag–luminosity relation defined by LGRBs, thus strengthening the SGRB flare–prompt pulse connection.
A Method Based on Generation Models for Analyzing Sentiment-Topic in Texts

This paper proposes a method based on generation model for sentiment analysis and topic identification in texts. Firstly sentiment and topic of training texts are labeled by hand and sentiment models and topic models are established. Secondly Compute the Kullback-Leibler divergence between a testing text and sentiment models in order to determine sentiment of the text. Similarly, calculate the Kullback-Leibler divergence between the testing text and topic model, so the topic of text can be identified. The unigram and bigram of words are employed as the model parameters, and correspondingly maximum likelihood estimation and some smoothing techniques are used to estimate these parameters. Empirical experiments on product reviews corpus show that this language modeling approach performs better than SVM and obtains improvement on precision. Moreover this method is better than SVM in robustness.
The Modular Backward Evolution - Why to Use Outdated Technologies

In this paper we draw a picture that captures the increasing interest in the format of modular synthesizers today. We therefore provide a historical summary, which includes the origins, the fall and the rediscovery of that technology. Further an empirical analysis is performed based on statements given by artists and manufacturers taken from published interviews.These statements were aggregated, ob-jectiﬁed and later reviewed by an expert group consisting of modular synthesizer vendors. Their responses provide the basis for the discussion on how emerging trends in synthe-sizer interface design reveal challenges and opportunities for the NIME community.