Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of a rapid method for detection of M. tuberculosis resistance to isoniazid and rifampin in Lima, Peru.

SETTING Treatment of multidrug-resistant tuberculosis (MDR-TB) is often based on drug susceptibility testing (DST) results; for this reason, rapid, simple DST methods are sought which could be applied in resource-poor countries. One such method is a nitrate reductase colorimetric assay known as the Griess method. In Peru, where the incidence rate of TB is among the highest in South America, the National Institute of Health recently undertook the validation and implementation of the direct Griess method. OBJECTIVE To describe the process of validation and implemention of the direct Griess method at the Peruvian National Institute of Health. DESIGN Prospective study comparing the sensitivity and specificity of the direct Griess method with the Löwenstein-Jensen proportion method in determining resistance to isoniazid (INH) and rifampin (RMP) among clinical isolates. RESULTS Among 192 specimens, the sensitivity and specificity of the Griess method for detection of INH resistance was 99.1% and 100%, respectively. For identification of RMP resistance, the sensitivity and specificity was 93.5% and 100%, respectively. CONCLUSIONS In addition to its high sensitivity and specificity and rapid turn around time, the Griess method uses simple, inexpensive reagents and requires minimal laboratory space and technical expertise, thus providing an ideal screening tool for resource-poor settings with high rates of MDR-TB.
Speech enhancement using MMSE short time spectral estimation with gamma distributed speech priors

In this paper we consider optimal estimators for speech enhancement in the Discrete Fourier Transform (DFT) domain. We present an analytical solution for estimating complex DFT coefficients in the MMSE sense when the clean speech DFT coefficients are Gamma distributed and the DFT coefficients of the noise are Gaussian or Laplace distributed. Compared to the state-of-the-art Wiener or MMSE short time amplitude estimators the new estimators deliver improved signal-to-noise ratios. When the noise model is a Laplacian density the enhanced speech shows less annoying random fluctuations in the residual noise than for a Gaussian density.
A Systematic Study on Tooth Enamel Microstructures of Lambdopsalis bulla (Multituberculate, Mammalia) - Implications for Multituberculate Biology and Phylogeny

Tooth enamel microstructure is a reliable and widely used indicator of dietary interpretations and data for phylogenetic reconstruction, if all levels of variability are investigated. It is usually difficult to have a thorough examination at all levels of enamel structures for any mammals, especially for the early mammals, which are commonly represented by sparse specimens. Because of the random preservation of specimens, enamel microstructures from different teeth in various species are often compared. There are few examples that convincingly show intraspecific variation of tooth enamel microstructure in full dentition of a species, including multituberculates. Here we present a systematic survey of tooth enamel microstructures of Lambdopsalis bulla, a taeniolabidoid multituberculate from the Late Paleocene Nomogen Formation, Inner Mongolia. We examined enamel structures at all hierarchical levels. The samples are treated differently in section orientations and acid preparation and examined using different imaging methods. The results show that, except for preparation artifacts, the crystallites, enamel types, Schmelzmuster and dentition types of Lambdopsalis are relatively consistent in all permanent teeth, but the prism type, including the prism shape, size and density, may vary in different portions of a single tooth or among different teeth of an individual animal. The most common Schmelzmuster of the permanent teeth in Lambdopsalis is a combination of radial enamel in the inner and middle layers, aprismatic enamel in the outer layer, and irregular decussations in tooth crown area with great curvature. The prism seam is another comparably stable characteristic that may be a useful feature for multituberculate taxonomy. The systematic documentation of enamel structures in Lambdopsalis may be generalized for the enamel microstructure study, and thus for taxonomy and phylogenetic reconstruction, of multituberculates and even informative for the enamel study of other early mammals.
Association of XPD and XRCC1 genetic polymorphisms with hepatocellular carcinoma risk.

AIM XRCC1 and XPD are two major repair genes involved in nucleotide excision repair (NER), which is reported to be associated with risk of several cancers. We explored the association of XRCC1 and XPD polymorphisms with the risk of HCC. METHODS A total of 410 cases with HCC and 410 health controls were collected. XRCC1 Arg194Trp, XRCC1 Arg399Gln, XPD Lys751Gln and XPD Asp312Asn genotyping was performed by duplex polymerase-chain-reaction with the confronting-two-pair primer (PCR-CTPP) method. RESULTS XRCC1 194Trp/Trp was strongly significantly associated with an increased risk of HCC cancer when compared with the wide-type genotype (OR=2.26, 95% CI=(1.23-5.38). Individuals carrying the XRCC1 399Gln/ Gln showed increased risk of HCC (OR=1.74, 95%CI=1.06-2.74). The XPD 751Gln/Gln and Gln allele genotype were associated with strong elevated susceptibility to HCC (OR=3.51 and 1.42, respectively). CONCLUSION These results suggest that polymorphisms in XRCC1 and XPD may have functional significance in risk of HCC.
A General Digital Predistortion Architecture Using Constrained Feedback Bandwidth for Wideband Power Amplifiers

Digital predistortion (DPD) is one of the most effective techniques to mitigate the distortions caused by power amplifier (PA) nonlinearity and memory effects. As the input signal bandwidth increases, the required bandwidth on the DPD feedback channel becomes even larger, i.e., normally five times the signal bandwidth. However, the DPD feedback bandwidth is often restricted by the nonideal electronic components, e.g., the anti-aliasing filter and associated circuits, which therefore introduce bandwidth mismatch between the PA model basis functions and the feedback signal, and thus degrade the linearization performances of the DPD. This paper presents a general DPD architecture for wideband PA systems with constrained feedback bandwidth. By using linear operations to cancel the bandwidth mismatch between the proposed model and the PA feedback signal, the full-band PA model parameters can be estimated with bandwidth-limited observations. This estimated PA model is subsequently used with the PA input signal to extract the DPD function by applying the direct learning algorithms. The proposed DPD architecture reduces the feedback bandwidth to less than two times that of the input signal, while it maintains its linearization performance, as in the full-band case. Experiments are performed on the 20- and 100-MHz long-term evolution advanced signals to demonstrate the effectiveness of the proposed PA behavior modeling and DPD linearization performances with limited feedback bandwidth.
Hardware scale and performance evaluation of a compact subsystem modular optical cross connect that adopts tailored add/drop architecture

We propose novel highly scalable subsystem modular optical cross connect (OXC) architectures that use an efficient add/drop part to connect each transponder bank to a limited number of incoming/outgoing fibers. We investigate the performance and hardware scale of the proposed architectures in two add/drop configurations. Numerical evaluations prove that the proposed architectures attain almost the same routing performance as the equivalent conventional single large-scale OXC with an ideal colorless, directionless, and contentionless add/drop part, while enabling substantial hardware scale reduction.
Optimizing Quality for Collaborative Video Viewing

The increasing popularity of distance learning and online courses has highlighted the lack of collaborative tools for student groups. In addition, the introduction of lecture videos into the online curriculum has drawn attention to the disparity in the network resources used by the students. We present an architecture and adaptation model called AITV (Adaptive Internet Interactive Team Video), a system that allows geographically dispersed participants, possibly some or all disadvantaged in network resources, to collaboratively view a video in synchrony. AITV upholds the invariant that each participant will view semantically equivalent content at all times. Video player actions, like play, pause and stop, can be initiated by any of the participants and the results of those actions are seen by all the members. These features allow group members to review a lecture video in tandem to facilitate the learning process. We employ an autonomic (feedback loop) controller that monitors clients’ video status and adjusts the quality of the video according to the resources of each client. We show in experimental trials that our system can successfully synchronize video for distributed clients while, at the same time, optimizing the video quality given actual (fluctuating) bandwidth by adaptively adjusting the quality level for each participant.
On the.Inclusiveness. of India.s Consumption Expenditure Growth

This paper reviews the evidence on the `inclusiveness´ of the growth in consumption expenditure that has occurred in India over the last four decades or so. The notion of dynamic inclusiveness is framed in terms of imagined normative allocations of the inter-temporal product of growth, as dictated by notions of equity of varying orders of demandingness. There are analytical parallels between these exercises and those involved in the study of bankruptcy in `Talmudic estate problems´, as well as in the determination of optimal anti-poverty budgetary allocations. The issue of inclusive growth is reviewed in this paper with respect to inclusiveness across both income classes and social groups such as caste and occupation. The results of the investigation undertaken in the essay suggest distressingly little evidence of inclusiveness in India´s consumption growth experience.
Self-learning model-based segmentation of medical images

Interaction increases flexibility of segmentation but it leads to undesirable behaviour of an algorithm if knowledge being requested is inappropriate. In region growing, this is the case for defining the homogeneity criterion, as its specification depends also on image formation properties that are not known to the user. We developed a region growing algorithm that learns its homogeneity criterion automatically from characteristics of the region to be segmented. The method is based on a model that describes homogeneity and simple shape properties of the region. Parameters of the homogeneity criterion are estimated from sample locations in the region. These locations are selected sequentially in a random walk starting at the seed point, and the homogeneity criterion is updated continuously. In contrast to other adaptive region growing methods our approach produces results that are far less sensitive to the seed point location, and it allows a segmentation of individual structures. The model-based adaptive region growing approach was extended to a fully automatic and complete segmentation method by using the pixels with the smallest gradient length in the not yet segmented image region as a seed point. Both methods were tested for segmentation on test images and of structures in CT images. The performance of the semi-automatic method is compared with the adaptive moving mean value region growing method, and the automatic method is compared with the watershed segmentation. We found our method to work reliable if the model assumption on homogeneity and region characteristics were true. Furthermore, the model is simple but robust thus allowing for a certain amount of deviation from model constraints and still delivering the expected segmentation result.
Assessing Applicant "Fit" Within the Selection Process: Which Interviewer Perceptions Matter?

The research literature has noted that organizations are moving beyond simply hiring individuals with the necessary knowledge, sk ills , and abilities (KS As) that fulfill the requirements of the job employers are also looking for people who can fit in with a particular work group or even an entire organization. This study tested an exploratory model that predicted recruiter selection decisions from their evaluations of applicants’ person-job (P-J), person-group (P-G), and person-organization (P-O) fit. The model also postulated that P-G and P-O fit would be predicted by the perceived congruence (similarity) of work values between applicants and groups/organizations. Hypotheses were field-tested with 64 recruiters from 44 companies who conducted 262 initial interviews with job applicants. As expected, the combination of P-J, P-G, and P-O fit explained a significant amount of variance in recruiter selection decisions, such as the likelihood that applicants would be invited for a second interview or would be recommended for hiring. All three types of fit contributed to the recruiter selection decisions, but ceiling effects and high multicollinearity among the fit ratings complicated interpretation of their individual contributions. Applicant qualification match with job requirements strongly predicted P-J fit. Perceived similarity in the work values of achievement, fairness, honesty, and concern for others between applicants and organizations significantly predicted P-O fit. Value congruence between applicants and groups likewise predicted P-G fit. Among the study’s strengths was the use of Edwards’ polynomial regression and three-dimensional response surface techniques, which allowed for both the relaxation of traditional constraints on equations and the interpretation of the complex relationships between applicant values, organization/group values, and
Disease Diagnosis Using Pattern Matching Algorithm from DNA Sequencing: a Sequential and GPGPU based Approach

DNA sequencing is one of the most important areas of research today. DNA sequencing is used in a variety of areas like forensic science, agriculture, medical field etc. The disease diagnosis from DNA sequencing is one of them which are harmless method to find out chances of disease occurrence. Chemical as well as sequential change in DNA leads to diseases. DNA is a large database; an efficient algorithm is needed to carry out the disease diagnosis. The study proposed sequential as well as GPGPU based multi string pattern matching Aho-corasick algorithm to find out the chances of occurrence of certain nucleotide repeat diseases and some cancer types from different DNA sequences. The results demonstrate that the algorithm works better with GPGPU based parallel approach and gives better speed up when patterns increases. So, with the proposed way the algorithm is well worked for Bioinformatics applications.
Fast index assignment for balanced N-description scalar quantization

Summary form only given. We address the design of any number of balanced descriptions with multiple description scalar quantizers (MDSQ), using fast index assignment methods. Such systems proceed in two steps, scalar quantization and index assignment, that map the quantized value to an N-tuple of quantization indices, to be sent over N channels. We address the specific balanced scenario, where all descriptions have equal rates and where any subset of k out of N descriptions induces the same distortion. We propose two simple index assignment schemes for uniform sources, that are able to generate any number, N (greater than 2), of such balanced descriptions, at any coding rate. The case of Gaussian distributions is also addressed using companding.
Assessing the underlying pattern of human germline mutations: lessons from the factor IX gene

Germline mutations cause or predispose to most diseases. Hemophilia B is a useful model for studying the underlying pattern of recent germline mutations in humans because the observed pattern of mutation in factor IX more closely reflects the underlying pattern of mutation than the observed pattern for many other genes. In addition, it is possible to identify and correct for biases inherent in ascertaining only those mutations that cause hemophilia. Aspects of the pattern of germline mutation in the factor IX gene are becoming clear: 1) in the United States, two‐thirds of mutations causing mild disease arose from three founders whereas almost all the mutations resulting in either moderate or severe disease arose independently, generally within the past 150 years; 2) direct estimates of the rates of mutation in humans indicate that transitions are more frequent than transversions, which in turn are more frequent than deletions and insertions; 3) transitions at CpG are elevated approximately 24‐fold relative to transitions at non‐CpG dinucleotides; 4) transversions at CpG are elevated approximately eightfold relative to transversions at non‐CpG dinucleotides; 5) the sum total of the dinucleotide mutation rates produces a bias against G and C bases that would be sufficient to maintain the G+C content of the factor IX gene at its evolutionarily conserved level of 40%; and 6) the pattern of mutation is similar for Caucasians residing in the United States and for Asians residing in Asia. Two ideas emerge from this and from an analysis of the pattern of recent deleterious mutations compared with ancient neutral mutations that have been fixed during evolution into the factor IX gene. First, the bulk of germline mutations are likely to arise from endogenous processes rather than environmental mutagens. Second, the factor IX protein is composed mostly of two classes of amino acids: critical residues in which all single‐base missense changes will disrupt protein function, and “spacer” residues in which the precise nature of the residue is unimportant but the peptide bond is necessary to keep the critical residues in register. More work is necessary to assess the veracity and generality of these ideas. — Sommer, S. S. Assessing the underlying pattern of human germline mutations: lessons from the factor IX gene. FASEB J. 6: 2767‐2774; 1992.
Load Value Approximation

Approximate computing explores opportunities that emerge when applications can tolerate error or inexactness. These applications, which range from multimedia processing to machine learning, operate on inherently noisy and imprecise data. We can trade-off some loss in output value integrity for improved processor performance and energy-efficiency. As memory accesses consume substantial latency and energy, we explore load value approximation, a micro architectural technique to learn value patterns and generate approximations for the data. The processor uses these approximate data values to continue executing without incurring the high cost of accessing memory, removing load instructions from the critical path. Load value approximation can also inhibit approximated loads from accessing memory, resulting in energy savings. On a range of PARSEC workloads, we observe up to 28.6% speedup (8.5% on average) and 44.1% energy savings (12.6% on average), while maintaining low output error. By exploiting the approximate nature of applications, we draw closer to the ideal latency and energy of accessing memory.
Dynamics of proteasome distribution in living cells

Proteasomes are proteolytic complexes involved in non‐lysosomal degradation which are localized in both the cytoplasm and the nucleus. The dynamics of proteasomes in living cells is unclear, as is their targeting to proteins destined for degradation. To investigate the intracellular distribution and mobility of proteasomes in vivo, we generated a fusion protein of the proteasome subunit LMP2 and the green fluorescent protein (GFP). The LMP2–GFP chimera was quantitatively incorporated into catalytically active proteasomes. The GFP‐tagged proteasomes were located within both the cytoplasm and the nucleus. Within these two compartments, proteasomes diffused rapidly, and bleaching experiments demonstrated that proteasomes were transported slowly and unidirectionally from the cytoplasm into the nucleus. During mitosis, when the nuclear envelope has disintegrated, proteasomes diffused rapidly throughout the dividing cell without encountering a selective barrier. Immediately after cell division, the restored nuclear envelope formed a new barrier for the diffusing proteasomes. Thus, proteasomes can be transported unidirectionally over the nuclear membrane, but can also enter the nucleus upon reassembly during cell division. Since proteasomes diffuse rapidly in the cytoplasm and nucleus, they may perform quality control by continuous collision with intracellular proteins, and degrading those proteins that are properly tagged or misfolded.
PenguinOMeter: A New File-I/O Benchmark for Linux

PenguinoMeter is a new open-source benchmark for Linux that measures file-system data transfer rates. PenguinoMeter allows the user to specify the file-system workload to be used in the benchmark in a very flexible manner. The workload specification is patterned after that of the Intel® Iometer benchmark; the current version of PenguinoMeter can read configuration files produced by Iometer. A series of comparisons between Iometer and PenguinoMeter is used to demonstrate that the workloads generated by these two programs appear to be identical. As an example use of PenguinoMeter, we compare the file system performance of Microsoft® Windows® 2000 Professional and Linux 2.4. 9.
A Revised Probabilistic Estimate of the Maternal Methyl Mercury Intake Dose Corresponding to a Measured Cord Blood Mercury Concentration

In 2001, the U.S. Environmental Protection Agency (EPA) adopted a revised reference dose (RfD) for methyl mercury (MeHg) of 0.1 μg/kg/day. The RfD is based on neurologic developmental effects measured in children associated with exposure in utero to MeHg from the maternal diet. The RfD derivation proceeded from a point of departure based on measured concentration of mercury in fetal cord blood (micrograms per liter). The RfD, however, is a maternal dose (micrograms per kilogram per day). Reconstruction of the maternal dose corresponding to this cord blood concentration, including the variability around this estimate, is a critical step in the RfD derivation. The dose reconstruction employed by the U.S. EPA using the one-compartment pharmacokinetic model contains two areas of significant uncertainty: It does not directly account for the influence of the ratio of cord blood:maternal blood Hg concentration, and it does not resolve uncertainty regarding the most appropriate central tendency estimates for pregnancy and third-trimester–specific model parameters. A probabilistic reassessment of this dose reconstruction was undertaken to address these areas of uncertainty and generally to reconsider the specification of model input parameters. On the basis of a thorough review of the literature and recalculation of the one-compartment model including sensitivity analyses, I estimated that the 95th and 99th percentiles (i.e., the lower 5th and 1st percentiles) of the maternal intake dose corresponding to a fetal cord blood Hg concentration of 58 μg/L are 0.3 and 0.2 μg/kg/day, respectively. For the 99th percentile, this is half the value previously estimated by the U.S. EPA.