Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification and Characterization of a Dextranase Gene of Streptococcus criceti

The dextranase gene, dex, was identified in Streptococcus criceti strain E49 by degenerate PCR and sequenced completely by the gene‐walking method. A sequence of 3,960 nucleotides was determined. The dex gene encodes a 1,200‐amino acid protein, which has a calculated molecular mass of 128,129.91 and pI of 4.15 and is predicted to be a cell‐surface protein. The deduced amino acid sequence of dex showed homology to S. downei dextranase (63.9% identity). Phylogenetic analysis revealed the similarity of the deduced amino acid sequence of dextranases in S. criceti, S. sobrinus, and S. downei. A recombinant form of the protein with six histidine residues tagged in the C‐terminus was partially purified and showed dextranase activity on blue‐dextran sodium dodecyl sulfate‐polyacrylamide gel electrophoresis (BD‐SDS‐PAGE) followed by renaturation. We also detected dextranase activity in S. criceti cell extracts and culture supernatant by renatured BD‐SDS‐PAGE, whereas no dextranase activity of the cells was observed on blue‐dextran brain heart infusion (BD‐BHI) agar plates. Furthermore, PCR‐based mutations of dextranase indicated that a deletion mutant of the C‐terminal region could hydrolyze blue dextrans and that the D453E mutation, W793L mutation, and double mutations (W793L and deletion of the C‐terminal region) resulted in a loss of dextranase activity. These findings suggest that Asp‐453 and Trp‐793 residues of S. criceti dextranase are critical to the enzyme's activity.
A model of fluid and solute exchange in the human: validation and implications.

In order to understand better the complex, dynamic behaviour of the redistribution and exchange of fluid and solutes administered to normal individuals or to those with acute hypovolemia, mathematical models are used in addition to direct experimental investigation. Initial validation of a model developed by our group involved data from animal experiments (Gyenge, C.C., Bowen, B.D., Reed, R.K. & Bert, J.L. 1999b. Am J Physiol 277 (Heart Circ Physiol 46), H1228-H1240). For a first validation involving humans, we compare the results of simulations with a wide range of different types of data from two experimental studies. These studies involved administration of normal saline or hypertonic saline with Dextran to both normal and 10% haemorrhaged subjects. We compared simulations with data including the dynamic changes in plasma and interstitial fluid volumes VPL and VIT respectively, plasma and interstitial colloid osmotic pressures PiPL and PiIT respectively, haematocrit (Hct), plasma solute concentrations and transcapillary flow rates. The model predictions were overall in very good agreement with the wide range of experimental results considered. Based on the conditions investigated, the model was also validated for humans. We used the model both to investigate mechanisms associated with the redistribution and transport of fluid and solutes administered following a mild haemorrhage and to speculate on the relationship between the timing and amount of fluid infusions and subsequent blood volume expansion.
Evaluating Effects of User Experience and System Transparency on Trust in Automation

Existing research assessing human operators' trust in automation and robots has primarily examined trust as a steady-state variable, with little emphasis on the evolution of trust over time. With the goal of addressing this research gap, we present a study exploring the dynamic nature of trust. We defined trust of entirety as a measure that accounts for trust across a human's entire interactive experience with automation, and first identified alternatives to quantify it using real-time measurements of trust. Second, we provided a novel model that attempts to explain how trust of entirety evolves as a user interacts repeatedly with automation. Lastly, we investigated the effects of automation transparency on momentary changes of trust. Our results indicated that trust of entirety is better quantified by the average measure of “area under the trust curve” than the traditional post-experiment trust measure. In addition, we found that trust of entirety evolves and eventually stabilizes as an operator repeatedly interacts with a technology. Finally, we observed that a higher level of automation transparency may mitigate the “cry wolf’ effect - wherein human operators begin to reject an automated system due to repeated false alarms.
Active Learning with Cross-Class Similarity Transfer

How to save labeling efforts for training supervised classifiers is an important research topic in machine learning community. Active learning (AL) and transfer learning (TL) are two useful tools to achieve this goal, and their combination, i.e., transfer active learning (T-AL) has also attracted considerable research interest. However, existing T-AL approaches consider to transfer knowledge from a source/auxiliary domain which has the same class labels as the target domain, but ignore the relationship among classes. In this paper, we investigate a more practical setting where the classes in source domain are related/similar to but different from the target domain classes. Specifically, we propose a novel cross-class T-AL approach to simultaneously transfer knowledge from source domain and actively annotate the most informative samples in target domain so that we can train satisfactory classifiers with as few labeled samples as possible. In particular, based on the class-class similarity and sample-sample similarity, we adopt a similarity propagation to find the source domain samples that can well capture the characteristics of a target class and then transfer the similar samples as the (pseudo) labeled data for the target class. In turn, the labeled and transferred samples are used to train classifiers and actively select new samples for annotation. Extensive experiments on three datasets demonstrate that the proposed approach outperforms significantly the state-of-the-art related approaches.
Projective identification and suicide contagion

The effect of suggestion on suicide is well established. However, the intrapsychic mechanisms of the contagion of suicides are poorly understood. In this article I first present the literature about suicide clustering and about projective identification. In the following clinical vignette I try to understand a patient's suicidal behaviour, referring to William Goldstein's clarifying model of projective identification. I aim to illustrate that his model has heuristic value in the treatment of suicidal patients when the effect of suggestion or identification is suspected.
Non-invasive Trigger-free Fault Injection Method Based on Intentional Electromagnetic Interference

This paper presents a new type of fault injection method based on intentional electromagnetic interference (IEMI), which causes information leakage from cryptographic devices without disrupting their operations or damaging their physical structures. The basic principle is to transmit a sinusoidal EM wave via a power/communication cable or an antenna. The IEMI-based fault injection method is performed at a distance from the target module through many filtering components, such as a voltage regulator, without leaving any hard evidence of the attack. It can also be applied under the condition that there is no trigger signal synchronized with the cryptographic operation. We demonstrate the potential capability of the IEMI-based fault injection attacks through an experiment using an Advanced Encryption Standard (AES) module implemented on a standard FPGA board. The experimental result shows that generating effective faults is feasible and such IEMI-based fault injection is available for a typical differential fault analysis on AES. Keywords-fault injection attacks; intentional electromagnetic interference; AES; non-invasive fault injection
Portable Computerized Assessments of Sleepy Drivers in Operational Environments

Excessive daytime sleepiness underpins a large number of the reported motor vehicle crashes. Fair and accurate field measures are needed to identify at-risk drivers who have been identified as potentially driving in a speed deprived state on the basis of erratic driving behavior. The purpose of this research study was to evaluate a set of cognitive tests that can assist Motor Vehicle Enforcement Officers on duty in identifying drivers who may be engaged in sleep impaired driving. Currently no gold standard test exists to judge sleepiness in the field. Previous research has shown that Psychomotor Vigilance Task (PVT) is sensitive to sleep deprivation. The first goal of the current study was to evaluate whether computerized tests of attention and memory, more brief than PVT, would be as sensitive to sleepiness effects. The second goal of the study was to evaluate whether objective and subjective indices of acute and cumulative sleepiness predicted cognitive performance. Findings showed that sleepiness effects were detected in three out of six tasks. Furthermore, PVT was the only task that showed a consistent slowing of both 'best', i.e., minimum, and 'typical' responses, median Reaction Time (RT) due to sleepiness. However, PVT failed to show significant associations with objective measures of sleep deprivation (number of hours awake). The findings indicate that sleepiness tests in the field have significant limitations. The findings clearly show that it will not be possible to set absolute performance thresholds to identify sleep-impaired drivers based on cognitive performance on any test. Cooperation with industry to adjust work and rest cycles, and incentives to comply with those regulations will be critical components of a broad policy to prevent sleepy truck drivers from getting on the road.
A Survey of Multi-Agent Trust Management Systems

In open and dynamic multiagent systems (MASs), agents often need to rely on resources or services provided by other agents to accomplish their goals. During this process, agents are exposed to the risk of being exploited by others. These risks, if not mitigated, can cause serious breakdowns in the operation of MASs and threaten their long-term wellbeing. To protect agents from the uncertainty in the behavior of their interaction partners, the age-old mechanism of trust between human beings is re-contexted into MASs. The basic idea is to let agents self-police the MAS by rating each other on the basis of their observed behavior and basing future interaction decisions on such information. Over the past decade, a large number of trust management models were proposed. However, there is a lack of research effort in several key areas, which are critical to the success of trust management in MASs where human beings and agents coexist. The purpose of this paper is to give an overview of existing research in trust management in MASs. We analyze existing trust models from a game theoretic perspective to highlight the special implications of including human beings in an MAS, and propose a possible research agenda to advance the state of the art in this field.
KLF2 Is a Novel Transcriptional Regulator of Endothelial Proinflammatory Activation

The vascular endothelium is a critical regulator of vascular function. Diverse stimuli such as proinflammatory cytokines and hemodynamic forces modulate endothelial phenotype and thereby impact on the development of vascular disease states. Therefore, identification of the regulatory factors that mediate the effects of these stimuli on endothelial function is of considerable interest. Transcriptional profiling studies identified the Kruppel-like factor (KLF)2 as being inhibited by the inflammatory cytokine interleukin-1β and induced by laminar shear stress in cultured human umbilical vein endothelial cells. Overexpression of KLF2 in umbilical vein endothelial cells robustly induced endothelial nitric oxide synthase expression and total enzymatic activity. In addition, KLF2 overexpression potently inhibited the induction of vascular cell adhesion molecule-1 and endothelial adhesion molecule E-selectin in response to various proinflammatory cytokines. Consistent with these observations, in vitro flow assays demonstrate that T cell attachment and rolling are markedly attenuated in endothelial monolayers transduced with KLF2. Finally, our studies implicate recruitment by KLF2 of the transcriptional coactivator cyclic AMP response element–binding protein (CBP/p300) as a unifying mechanism for these various effects. These data implicate KLF2 as a novel regulator of endothelial activation in response to proinflammatory stimuli.
A new algorithm for detecting low-complexity regions in protein sequences

MOTIVATION Pair-wise alignment of protein sequences and local similarity searches produce many false positives because of compositionally biased regions, also called low-complexity regions (LCRs), of amino acid residues. Masking and filtering such regions significantly improves the reliability of homology searches and, consequently, functional predictions. Most of the available algorithms are based on a statistical approach. We wished to investigate the structural properties of LCRs in biological sequences and develop an algorithm for filtering them. RESULTS We present an algorithm for detecting and masking LCRs in protein sequences to improve the quality of database searches. We developed the algorithm based on the complexity analysis of subsequences delimited by a pair of identical, repeating subsequences. Given a protein sequence, the algorithm first computes the suffix tree of the sequence. It then collects repeating subsequences from the tree. Finally, the algorithm iteratively tests whether each subsequence delimited by a pair of repeating subsequences meets a given criteria. Test results with 1000 proteins from 20 families in Pfam show that the repeating subsequences are a good indicator for the low-complexity regions, and the algorithm based on such structural information strongly compete with others. AVAILABILITY http://bioinfo.knu. ac.kr/research/CARD/ CONTACT: swshin@bioinfo.knu. ac.kr
FPGA-based detailed EMTP

More powerful simulation hardware is always preferred when it comes to accurate, efficient and economical simulation of large complex power systems. This paper proposes a FPGA-based EMT simulator which considers the detailed EMT model of synchronous generator, excitation system and transmission lines. The well-known two-area four-machine system is taken as an example to validate the proposed simulator and for this particular system, the simulation time-step as low as 10μs can be easily achieved. To validate the proposed simulator, comparison is made between simulation results from the proposed simulator and from MATLAB Simulink, and excellent accuracy has been achieved.
Finance and Economics Discussion Series Is Corporate Governance Ineffective in Emerging Markets? Is Corporate Governance Ineffective in Emerging Markets? Is Corporate Governance Ineffective in Emerging Markets?

NOTE: Staff working papers in the Finance and Economics Discussion Series (FEDS) are preliminary materials circulated to stimulate discussion and critical comment. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by other members of the research staff or the Board of Governors. References in publications to the Finance and Economics Discussion Series (other than acknowledgment) should be cleared with the author(s) to protect the tentative character of these papers.5296. I thank Paul Kim for diligent research assistance and an anonymous referee and participants in the WFA 2000 meetings, the Tuck School conference on International Corporate Governance, and a seminar at the World Bank for helpful comments. The author is a staff economist in the Division of Research and Statistics. The views in this paper are solely the responsibility of the author and should not be interpreted as reflecting the views of the Board of Governors of the Federal Reserve System or of any other person associated with the Federal Reserve System. Abstract I test whether corporate governance is ineffective in emerging markets by estimating the link between CEO turnover and firm performance for over 1,200 firms in eight emerging markets. I find two main results. First, CEOs of emerging market firms are more likely to lose their jobs when their firm's performance is poor, suggesting that corporate governance is not ineffective in emerging markets. Second, for the subset of firms with a large domestic shareholder, there is no link between CEO turnover and firm performance. For this subset of emerging market firms, corporate governance appears to be ineffective. 1 Examples include pension fund CalPERS (Engardio 2002) and mutual fund group Franklin-Templeton (Mobius 2001). 2 A survey of emerging market investors by the consulting firm McKinsey came to these conclusions. See Coombes and Watson (2001). 1 In recent years, investors have been loudly calling for corporate governance reforms in emerging markets. These calls intensified with the Asian financial crisis of 1997-98, which many blamed on poor corporate governance (Johnson et al. 2000). Some institutional investors have identified corporate governance as a key factor affecting their willingness to invest in an emerging market. 1 These calls for corporate governance reform are based on the premise that corporate governance in emerging markets is in need of improvement. There are good reasons to think that the effectiveness of corporate governance might be quite different in developed …
Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City

Abstract. The goal of this research is to quantify diesel- and gasoline-powered motor vehicle emissions within the Mexico City Metropolitan Area (MCMA) using on-road measurements captured by a mobile laboratory combined with positive matrix factorization (PMF) receptor modeling. During the MCMA-2006 ground-based component of the MILAGRO field campaign, the Aerodyne Mobile Laboratory (AML) measured many gaseous and particulate pollutants, including carbon dioxide, carbon monoxide (CO), nitrogen oxides (NOx), benzene, toluene, alkylated aromatics, formaldehyde, acetaldehyde, acetone, ammonia, particle number, fine particulate mass (PM2.5), and black carbon (BC). These serve as inputs to the receptor model, which is able to resolve three factors corresponding to gasoline engine exhaust, diesel engine exhaust, and the urban background. Using the source profiles, we calculate fuel-based emission factors for each type of exhaust. The MCMA's gasoline-powered vehicles are considerably dirtier, on average, than those in the US with respect to CO and aldehydes. Its diesel-powered vehicles have similar emission factors of NOx and higher emission factors of aldehydes, particle number, and BC. In the fleet sampled during AML driving, gasoline-powered vehicles are found to be responsible for 97% of total vehicular emissions of CO, 22% of NOx, 95–97% of each aromatic species, 72–85% of each carbonyl species, 74% of ammonia, negligible amounts of particle number, 26% of PM2.5, and 2% of BC; diesel-powered vehicles account for the balance. Because the mobile lab spent 17% of its time waiting at stoplights, the results may overemphasize idling conditions, possibly resulting in an underestimate of NOx and overestimate of CO emissions. On the other hand, estimates of the inventory that do not correctly account for emissions during idling are likely to produce bias in the opposite direction.The resulting fuel-based estimates of emissions are lower than in the official inventory for CO and NOx and higher for VOCs. For NOx, the fuel-based estimates are lower for gasoline-powered vehicles but higher for diesel-powered ones compared to the official inventory. While conclusions regarding the inventory should be interpreted with care because of the small sample size, 3.5 h of driving, the discrepancies with the official inventory agree with those reported in other studies.
Delay-Concerned Opportunistic Scheduling Algorithm in Wireless Communication Networks

In this paper we examine the packets’ delay performance under the temporal fairness opportunistic scheduling (TFOS) algorithm which is first introduced in [1]. We also simulate the earliest deadline-first (EDF) scheduling algorithm in the wireless environment. We find that the opportunistic scheduling algorithm biases the users who always experience the good channel condition in packets’ delay to improve system performance and the EDF which works well in wireline networks on delay performance [2] does not perform well in wireless communication networks. So we propose a new scheme which considers both users channel condition and packets’ delay. The simulation results show that the new scheme works well with respect to both system performance improvement and the balance of packet delay distribution.
The Effects of Intermittent Fasting during the Month of Ramadan in Chronic Haemodialysis Patients in a Tropical Climate Country

Background Chronic kidney disease is an emerging problem in the majority Muslim countries. Despite the uncertainties of the risks involved, some Muslim patients undergoing chronic haemodialysis choose to observe intermittent fasting during the month of Ramadan. This study aims to investigate the effect of Ramadan fasting in haemodialysis patients residing in a tropical climate country. Methods This prospective cross sectional study recruited Muslim patients on regular haemodialysis from three haemodialysis centres in Kuala Lumpur from 15th July 2011 to 29th August 2011. Patients who fasted for any number of days were included (n = 35, 54% female, age 54±11 years). 89% of patients fasted for more than 15 days and 49% were diabetics. Dialysis parameters and blood samples were obtained one week prior to Ramadan and during the last week of Ramadan. The differences in dialysis parameters and biochemical values pre- and end-Ramadan were examined using paired t-test. Results Both pre- and post-dialysis weight were significantly decreased during Ramadan fasting compared to the month prior (p = <0.001). There was a significant decrease in the amount of ultrafiltration (p = 0.002). There were no significant differences in dry weight, inter-dialytic weight gain, mean urea reduction ratio or blood pressure measurements comparing pre- and end of Ramadan fasting. There was a significant increase in serum albumin level (p = 0.006) and decrease in serum phosphate level (p = 0.02) at the end of Ramadan. Conclusion Ramadan fasting is associated with reduced weight, improved serum albumin and phosphate level in our population of haemodialysis patients. A larger multi-centre study will allow us to understand more about the effects of fasting in this population.
AN APPROACH FOR RECOGNIZING STEM-END/CALYX REGIONS IN APPLE QUALITY SORTING

In this paper we introduce a cascaded-classifier approach to localize stem-ends and calyxes of ‘Jonagold’ apples. First classifier (artificial neural network) extracts candidate objects, whereas the second one (nearest neighbor) discriminates stem-ends and calyxes from others. Overall system is tested by 616 fruits from which first classifier found 414 candidate objects. Several features are extracted from these objects and these features are then selected by forward selection method. With these selected features the second classifier reached to 80% recognition rate. Classification errors of each feature is also introduced for comparison.
Improving Similarity Measures for Short Segments of Text

In this paper we improve previous work on measuring the similarity of short segments of text in two ways. First, we introduce a Web-relevance similarity measure and demonstrate its effectiveness. This measure extends the Web-kernel similarity function introduced by Sahami and Heilman (2006) by using relevance weighted inner-product of term occurrences rather than TF×IDF. Second, we show that one can further improve the accuracy of similarity measures by using a machine learning approach. Our methods outperform other state-of-the-art methods in a general query suggestion task for multiple evaluation metrics.