Miracle-dz/UniFAR-FTUs huggingface dataset:
PHYSICOCHEMICAL CHARACTERIZATION OF MOUSE MYELOMA PROTEINS: DEMONSTRATION OF HETEROGENEITY FOR EACH MYELOMA GLOBULIN

Physicochemical characterization of mouse myeloma proteins revealed the individuality of each myeloma protein. When the myeloma proteins are considered collectively a wide range of individual properties were represented, including electrophoretic mobilities varying from the gamma to alpha region, hexose contents from 1 to 4 per cent, and ultracentrifugal components from 6.5 to 13 S. The 20 myeloma proteins could be divided into groups, the gamma type and the beta type myeloma globulins, on the basis of physicochemical, as well as immunoelectrophoretic, studies. Two gamma type myeloma proteins (5563, MPC-11) resembled normal gamma globulins, sedimenting as a single 6.5 S peak in the ultracentrifuge, and having a relatively low hexose content (1 per cent). Eighteen beta type mouse myeloma proteins differed from gamma myeloma proteins and, typically, were found on ultracentrifugal analysis to have multiple components with sedimentation coefficients of 6.5, 9, 11, and 13 S, having a higher hexose content (2 to 4 per cent) as well as distinctive chromatographic and starch gel electrophoretic properties. All of the mouse myeloma proteins were heterogeneous and heterogeneity of two types was observed. Polymer formation was responsible for the 9, 11, and/or 13 S components seen on ultracentrifugation of the beta type myeloma proteins. Starch gel electrophoresis revealed this type of heterogeneity as relatively widely separated myeloma protein components, presumably owing to the retardation effect of starch gel on the electrophoretic migration of the larger polymers. Starch gel electrophoresis revealed a different type of heterogeneity for the two gamma type myeloma proteins, each of these being shown to contain 5 or more components differing only in electrophoretic properties. The physicochemical characteristics of the gamma-type and beta-type myeloma proteins in the mouse indicated the close similarity of these proteins to the gamma- and beta-(2A)-myeloma proteins in man.
In vivo mapping of tumor oxygen consumption using 19F MRI relaxometry

Recently, we have developed a new electron paramagnetic resonance (EPR) protocol in order to estimate tissue oxygen consumption in vivo. Because it is crucial to probe the heterogeneity of response in tumors, the aim of this study was to apply our protocol, together with 19F MRI relaxometry, to the mapping of the oxygen consumption in tumors. The protocol includes the continuous measurement of tumor pO2 during the following respiratory challenge: (i) basal values during air breathing; (ii) increasing pO2 values during carbogen breathing until saturation of tissue with oxygen; (iii) switching back to air breathing. We have demonstrated previously using EPR oximetry that the kinetics of return to the basal value after oxygen saturation are mainly governed by tissue oxygen consumption. This challenge was applied in hyperthyroid mice (generated by chronic treatment with L‐thyroxine) and control mice, as hyperthyroidism is known to dramatically affect the oxygen consumption rate of tumor cells. Our recently developed snapshot inversion recovery MRI fluorocarbon oximetry technique allowed the pO2 return kinetics to be measured with a high temporal resolution. The kinetic constants (i.e. oxygen consumption rates) were higher for tumors from hyperthyroid mice than from control mice, data that are consistent with our previous EPR study. The corresponding histograms of the 19F MRI data showed that the kinetic constants displayed a shift to the right for the hyperthyroid group, indicating a higher oxygen consumption in these tumors. The color maps showed a large heterogeneity in terms of oxygen consumption rate within a tumor. In conclusion, 19F MRI relaxometry allows the noninvasive mapping of the oxygen consumption in tumors. The ability to assess the heterogeneity of tumor response is critical in order to identify potential tumor regions that might be resistant to treatment and therefore produce a poor response to therapy. Copyright © 2010 John Wiley & Sons, Ltd.
Adverse feedback loop in the bank-based financial systems

This paper examines procyclicality of the financial system. The introduction describes the natural and regulatory sources of procyclicality, focusing on the potential procyclical effect of the current Basel II regulatory framework for banks. It also mentions the regulatory tools for mitigating procyclical behaviour by financial institutions currently being discussed in international forums. Under certain conditions, procyclical behaviour of the banking sector can lead to an adverse feedback loop whereby banks, in response to an economic downswing, engage in deleveraging and reduce their lending to the economy in order to maintain the required capital adequacy ratio. This then further negatively affects economic output and impacts back on banks in the form of, for example, increased loan losses. In the main empirical section of the paper, this effect was simulated on the example of the Czech banking sector. The simulation results suggest that under certain assumptions the feedback loop may play an important role.
Content validity and satisfaction with a stroke caregiver intervention program.

BACKGROUND AND PURPOSE Establishing evidence of content validity and satisfaction is an integral part of intervention research. The purpose of this article is to describe content validity and satisfaction relative to the Telephone Assessment and Skill-Building Kit (TASK), an 8-week follow-up program based on individualized assessment of stroke caregiver needs. DESIGN AND METHODS The TASK intervention enables caregivers to develop skills based on assessment of their own needs. During the development of the TASK program, 10 experts rated the validity of the TASK intervention components for accuracy, feasibility, acceptability, and problem relevance. After incorporating feedback from the experts, a randomized controlled clinical trial was instituted using a convenience sample of 40 stroke caregivers to determine satisfaction (usefulness, ease of use, and acceptability) with the TASK intervention (n=21) compared with an attention control group (n=19). Data collection occurred between March 2005 and June 2006. Data were analyzed using descriptive statistics, independent sample t tests, and content analysis. FINDINGS Expert ratings on a 1 to 5 scale, with 5 being strongly agree, provided evidence of content validity (accuracy 4.71, feasibility 4.46, acceptability 4.40, problem relevance 4.67). Caregivers in the TASK group scored significantly higher than the attention control group on all satisfaction measures (usefulness p=.02; ease of use p=.02; acceptability p=.05). Qualitative comments from caregivers provided further evidence of satisfaction. CONCLUSIONS Evidence of content validity and user satisfaction for the TASK intervention relative to an attention control group was found. CLINICAL RELEVANCE The TASK program may be a viable telephone-based program that can be implemented by nurses to support family caregivers during the first few months after stroke survivors are discharged home.
6.5L: Late‐News Paper: AMLCDs using Organic Thin‐Film Transistors on Polyester Substrates

We have fabricated and demonstrated active‐matrix liquid‐crystal displays using organic thin‐film transistors (OTFTs) on polyester substrates. This is the first reported demonstration of an OTFT active‐matrix liquid‐crystal display, and also the first demonstration of a TFT active‐matrix liquid‐crystal display of any type fabricated on a polyester substrate.
Encoding Distortion Modeling For DWT-Based Wireless EEG Monitoring System

Recent advances in wireless body area sensor net- works leverage wireless and mobile communication technologies to facilitate development of innovative medical applications that can significantly enhance healthcare services and improve quality of life. Specifically, Electroencephalography (EEG)-based applications lie at the heart of these promising technologies. However, the design and operation of such applications is challenging. Power consumption requirements of the sensor nodes may turn some of these applications impractical. Hence, implementing efficient encoding schemes are essential to reduce power consumption in such applications. In this paper, we propose an analytical distortion model for the EEG-based encoding systems. Using this model, the encoder can effectively reconfigure its complexity by adjusting its control parameters to satisfy application constraints while maintaining reconstruction accuracy at the receiver side. The simulation results illustrate that the main parameters that affect the distortion are compression ratio and filter length of the considered DWT-based encoder. Furthermore, it is found that the wireless channel variations have a significant influence on the estimated distortion at the receiver side.
A Digital Predictive Current Control With Improved Sampled Inductor Current for Cascaded Inverters

This paper proposes a current-control technique with a predictive control method for multilevel inverters. The proposed current-control method adopts a variable sampling point scheme for inductor current sensing. It is able to avoid the switching noise caused by the turn-on or turn-off of power devices. The measured value of the inductor current is used to estimate the inverter output voltage at the next switching period with a simple linear extrapolation to force the output current to follow the current reference. Compared to the conventional predictive current controllers, the proposed control features are as follows: (1) only the inductor current measurement is required, and it is able to achieve a cost-effective and less-complex circuit (the output voltage and current measurements are required for a conventional controller) and (2) the proposed variable sampling technique is designed to avoid the switching noise, thus a robust current-control system can be achieved. Finally, a seven-level cascaded inverter with three DC-AC converter modules was constructed and tested. Analysis, simulations, and experimental results are presented to demonstrate the superiority of the proposed system.
Nucleosome Positioning of Intronless Genes in the Human Genome

Nucleosomes, the basic units of chromatin, are involved in transcription regulation and DNA replication. Intronless genes, which constitute 3 percent of the human genome, differ from intron-containing genes in evolution and function. Our analysis reveals that nucleosome positioning shows a distinct pattern in intronless and intron-containing genes. The nucleosome occupancy upstream of transcription start sites of intronless genes is lower than that of intron-containing genes. In contrast, high occupancy and well positioned nucleosomes are observed along the gene body of intronless genes, which is perfectly consistent with the barrier nucleosome model. Intronless genes have a significantly lower expression level than intron-containing genes and most of them are not expressed in CD4+ T cell lines and GM12878 cell lines, which results from their tissue specificity. However, the highly expressed genes are at the same expression level between the two types of genes. The highly expressed intronless genes require a higher density of RNA Pol II in an elongating state to compensate for the lack of introns. Additionally, 5’ and 3’ nucleosome depleted regions of highly expressed intronless genes are deeper than those of highly expressed intron-containing genes.
eHealth Governance, A Key Factor for Better Health Care: Implementation of IT Governance to Ensure Better care through Better eHealth

In this chapter, a set of recommendations for aligning eHealth with healthcare strategies is developed. After introducing the key concepts IT governance as a key enabler of successful alignment is discussed and described. Taking outcomes from a study conducted in Scotland, this chapter compares & contrasts preliminary results with those from similar studies in other countries. This analysis forms the basis of the chapter’s recommendations, the most important of which are: (a) to employ a well-known and welldeveloped IT governance standard, (b) to ensure that the healthcare organisation has a high level of readiness for the transformation towards strategic alignment, and (c) to utilize experts to direct and monitor both the organisational change and the eHealth alignment. Importantly, the results presented in relation to perceived eHealth-NHS alignment are preliminary, but significant deviations compared with the results presented in advance on this chapter are not expected. DOI: 10.4018/978-1-60960-174-4.ch006
Determination of Mineral Constituents, Phytochemicals and Antioxidant Qualities of Cleome gynandra, Compared to Brassica oleracea and Beta vulgaris

The study compared mineral, chemical and antioxidant qualities of Cleome gynandra, a wild leafy vegetable, with two widely consumed commercial vegetables, Brassica oleracea and Beta vulgaris. Mineral nutrients were quantified with inductively coupled plasma mass spectrometry (ICP-MS), phenolic compounds using ultra-high performance liquid chromatography coupled to a mass spectrometer (UHPLC-MS) and β-carotene and vitamin C using high performance liquid chromatography with a photodiode array detector (HPLC-PDA). The antioxidant potential was evaluated using 2,2–diphenyl−1–picryl hydrazyl (DPPH) and oxygen radical absorbance capacity (ORAC) assays. Cleome gynandra had highest concentrations of phosphorus, potassium, calcium, iron, zinc, ascorbic acid, total phenolics, and flavonoids; whereas sodium, magnesium, manganese, copper and β-carotene were higher for B. vulgaris. The significantly higher antioxidant activity (P ≤ 0.05) exhibited by C. gynandra in comparison to the two commercial vegetables may be due to its significantly high levels of vitamin C and phenolic acids. These findings on the mineral, chemical and antioxidant properties of C. gynandra provide compelling scientific evidence of its potential in adding diversity to the diet and contributing toward the daily nutritional requirements of millions of people for food and nutritional security.
Use of a Robot Platoon to Implement Mobile Ad-hoc NETwork in Rescue Scenario - Preliminary Experimental Results

This paper proposes the use of a platoon of mobile robots to carry a number of repeater antennas in order to guarantee a constant communication between a rescue operator (human or robot) and a fixed base station. These mobile antennas suitably move to dynamically ensure a multi-hop communication link, handling the occurrence of obstacles, signal fading area and failures such as, e.g., the fault of one or more mobile robots. The control objective is achieved in the framework of a kind of behavioral control, namely the null-space-based behavioral control (NSB). The effectiveness of the proposed strategy is verified in preliminary experiments obtained using a platoon of Khepera II mobile robots.
Accumulation of cellobiose lipids under nitrogen-limiting conditions by two ustilaginomycetous yeasts, Pseudozyma aphidis and Pseudozyma hubeiensis.

Some basidiomycetous yeast strains extracellularly produce cellobiose lipids (CLs), glycolipid biosurfactants which have strong fungicidal activity. The representative CL producer Ustilago maydis produces CLs together with the other glycolipids, mannosylerythritol lipids (MELs); the preference of the two glycolipids is affected considerably by the nitrogen source. To develop new CL producers, 12 MEL producers were cultured under the nitrogen-limited conditions. Pseudozyma aphidis and Pseudozyma. hubeiensis were characterized as new CL producers. CL production was induced on three strains, P. aphidis, Pseudozyma graminicola, and P. hubeiensis under these conditions. The putative homologous genes of U. maydis cyp1, which encodes a P450 monooxygenase, essential for CL biosynthesis, were partially amplified from their genomic DNA. The nucleotide sequences of the gene fragments from P. hubeiensis and P. aphidis shared identities with U. maydis cyp1 of 99% and 78%, respectively. Furthermore, all of the deduced translation products are tightly clustered in the phylogenic tree of the monooxygenase. These results suggest that the genes involved with CL biosynthesis must be widely distributed in the basidiomycetous fungi as well as the MEL biosynthesis genes, and thus, the genus Pseudozyma has great potential as a biosurfactant producer.
Genetic Background and Environment Influence the Effects of Mutations in pykF and Help Reveal Mechanisms Underlying Their Benefit

Abstract : Resolving the relationship between genotypes and their effects remains a central challenge in the study of adaptation. Although parallel mutations, a signature of adaptation, have been observed a lot in natural and lab-evolved populations, it is unknown if they are equally adaptive, or even if they affect similar biological processes to cause phenotypic changes. Using eight independently occurring mutations in pykF identified from a long-term evolution experiment with Escherichia coli, I found the mutations confer similar benefits in the ancestral background, but variable effects in the background in which they were evolved. Differences in mutation background interactions were found to be driven by different suites of mutations in each genetic background, rather than by different pykF mutations. Through biochemical and physiological studies with the pykF mutations in the ancestor, I found that although the mutations affect enzymes in a range of different ways, the net effect of these changes is to lead to changes in the same biological pathways, and thus to confer similar fitness effects. An adaptive mutation may no longer be beneficial if the given genetic background or environment changes. Relatively few studies, however, have examined the combined effect of genetic and environmental context on fitness effects of a mutation. To do this, I measured fitness effect conferred by one pykF mutation in 23 divergent genetic backgrounds and five environments. I found the environment, genetic background, and interactions between them, all significantly affect fitness of the mutation, which makes it harder to predict evolutionary fate of new mutations. Nevertheless, I found that initial fitness of a progenitor strain can be used to predict contribution of a mutation: a mutation will contribute less when added to fitter progenitors.
Assessing the Effects of Depressed Mood and Cognitive Control Training on Memory Confidence and Accuracy Following Repeated Checking

Studies show that repeated checking leads to memory distrust in healthy controls. Additionally, the extent of this reduction in memory confidence has been associated with executive control. Utilizing a 2 × 2 design, we examine the role of mood and cognitive training targeting executive control on memory distrust following repeated checking. Participants were 69 individuals with depressed (n = 32) or euthymic (n = 37) mood. Memory distrust following a repeated checking task was assessed before and after 3 sessions of a computerized cognitive training program or a control task. Consistent with previous studies, participants reported reduced meta-memory following repeated checking. Although participants with depressed mood reported lower overall cognitive confidence at a trend level, the effect of repeated checking on memory distrust was not potentiated by depressed mood in our study. A reduction in memory distrust following repeated checking was found over time; however, this effect was not dependent on cog.
An efficient parallel graph clustering technique using Pregel

To represent complex structure, graph data is widely used in diverse applications. Among various techniques to extract meaningful information in graph data, graph clustering is an important task for the discovery of an underlying graph structure. However, the volume of graph data becomes large and increases fast recently as well as traditional clustering algorithms become computationally expensive as the size of data to be clustered increases. In this paper, we propose an efficient graph clustering algorithm running on Pregel which is one of prominent parallel processing models for large-scale graph data. Graph clustering technique merges the nodes into clusters such that the nodes in a cluster are strongly connected each other. To seek strongly connected nodes efficiently, we utilize Min-Hash which calculates similarity between vertices and/or clusters. In our experimental study, we demonstrate the efficiency and scalability of our parallel algorithm compared to existing algorithms.
Diagnosis of Breast Cancer using Decision Tree Models and SVM

Breast cancer represents the second important cause of cancer deaths in women today and it is the most common type of cancer in women. Disease diagnosis is one of the applications where data mining tools are proving successful results. Data mining with decision trees is popular and effective data mining classification approach. Decision trees have the ability to generate understandable classification rules, which are very efficient tool for transfer knowledge to physicians and medical specialists. In fundamental truth, they provide trails to find rules that could be evaluated for separating the input samples into one of several groups without having to state the functional relationship directly. The objective of this paper is to examine the performance of recent invented decision tree modeling algorithms and compared with one that achieved by radial basis function kernel support vector machine (RBFSVM) on the diagnosis of breast cancer using cytological proven tumor dataset. Four models have been evaluated in decision tree: Chi-squared Automatic Interaction Detection (CHAID), Classification and Regression tree (CR classification accuracy, sensitivity, and specificity. General Terms Breast cancer, Data mining
Games Counselor Trainees Play: Dealing with Trainee Resistance

Fear of personal change makes many beginning counselors resist the help and guidance offered them in the practicum setting, often leaving their supervisors perplexed and frustrated. Types of resistance used by counselors and examined in this article are submission, turning the tables, the “I'm no good” attitude, helplessness, and projection. Methods and techniques available to supervisors in dealing with such resistance and discussed here are interpretation, feedback, clarification, generalization, ignoring, role-playing, the alter-ego technique, and audiotaping.
Combined Bayesian and predictive techniques for rapid speaker adaptation of continuous density hidden Markov models

Abstract One problem faced by some model adaptation techniques is that only the parameters of those models which are observed in the adaptation data are updated. Hence, with small amounts of adaptation data most of the system parameters remain unchanged. In this paper, a technique called regression-based model prediction (RMP), which tries to overcome this problem, is presented. This technique tries to adapt the model parameters of a continuous density hidden Markov model set which has insufficient adaptation data when used with maximum a posteriori (MAP) estimation. The technique uses the parameters of better estimated models and a set of parameter relationships between the model parameters to update the parameters of models with insufficient adaptation data. The parameter relationships are found by applying linear regression to a number of speaker-specific model sets. Experiments using both MAP estimation and RMP are presented using the ARPA RM1 continuous speech database and RMP has been found to be useful in improving the system performance with as little as 3 s of adaptation speech. RMP has been shown to consistently improve the results obtained by MAP. When a very large number of adaptation sentences are used the error rates converge towards those of MAP. It is shown that RMP gives an improvement of 8·8% over the baseline error rate with a single adaptation sentence, and 27% with 40 adaptation sentences.