Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision Directed Channel Estimation Employing Projection Approximation Subspace Tracking

The attainable capacity and integrity of a state-of-the-art broadband multi-carrier communication system is highly sensitive to the accuracy of the information available concerning the channel conditions encountered. The majority of existing advanced channel estimation schemes assume knowledge of the channel's power delay profile (PDP) in order to estimate the corresponding instantaneous channel impulse response (CIR). It is evident however that in realistic mobile channels, where at least one of the communicating terminals is in motion, the power delay profile will also be time-variant and thus may not be known a priori at the receiver. In this paper we propose a decision directed channel estimation scheme employing the so-called projection approximation subspace tracking (PAST) algorithm. The PAST algorithm is utilised for the sake of achieving low-complexity recursive tracking of the channel's PDP. The achievable performance of the proposed method is documented in the context of an OFDM system communicating in realistic channel conditions characterized by a time-variant fractionally-spaced PDP.
Dichloridobis(4-chlorobenzyl)(4,4′-dimethyl-2,2′-bipyridine-κ2 N,N′)tin(IV)

The SnIV atom in the title compound, [Sn(C7H6Cl)2Cl2(C12H12N2)], is coordinated by the bidentate N-heterocycle molecule, two chlorobenzyl anions and two Cl− anions in a distorted trans-C2SnCl2N2 octahedral geometry [C—Sn—C = 178.4 (1)°]. In the molecular structure, the two benzene rings are oriented at a dihedral angle of 39.62 (17)°.
Intracellular Metabolism and In Vitro Activity of Tenofovir against Hepatitis B Virus

ABSTRACT Tenofovir is an acyclic nucleotide analog with activity against human immunodeficiency virus (HIV) and hepatitis B virus (HBV). Tenofovir disoproxil fumarate (tenofovir DF), a bis-alkoxyester prodrug of tenofovir, is approved for the treatment of HIV and is currently being developed to treat chronic hepatitis B. In this report, we further characterize the in vitro activity of tenofovir against HBV as well as its metabolism in hepatic cells. We show that tenofovir is efficiently phosphorylated to tenofovir diphosphate (TFV-DP) in both HepG2 cells and primary human hepatocytes. TFV-DP has a long intracellular half-life (95 h) and is a potent and competitive inhibitor of HBV polymerase (Ki = 0.18 μM). Tenofovir has a 50% effective concentration of 1.1 μM against HBV in cell-based assays, and potency is improved >50-fold by the addition of bis-isoproxil progroups. Tenofovir has previously demonstrated full activity against lamivudine-resistant HBV in vitro and clinically. Here we show that the major adefovir resistance mutation, rtN236T, confers three- to fourfold-reduced susceptibility to tenofovir in cell culture; the clinical significance of this susceptibility shift has not yet been determined. The rtA194T HBV polymerase mutation recently identified in tenofovir DF-treated HIV/HBV-coinfected patients did not confer in vitro resistance to tenofovir as a single mutation or in a lamivudine-resistant viral background. Overall, the antiviral and metabolic profile of tenofovir supports its development for the treatment of chronic hepatitis B.
Capacitated Facility Location Problem in random fuzzy environment: Using (α , β)-cost minimization model under the Hurwicz criterion

Capacitated Facility Location Problem CFLP as one of the most important problems in operations research is nowadays widely used in real life. Although many researchers have studied the CFLP in a deterministic environment, their proposed models cannot satisfactorily accommodate various customer demands in the real world. Thus, this paper focuses on the CFLP random fuzzy environment using α,β-cost minimization model under the Hurwicz criterion. Furthermore, it is proved that this model can deal with various CFLPs in random, fuzzy and random fuzzy environments. In order to solve this model, the simplex algorithm, fuzzy simulations and a firefly algorithm are integrated to produce a hybrid intelligent algorithm. Finally, some numerical examples are presented to illustrate the effectiveness of the proposed algorithm.
Vectorcardiographic Criteria for the Diagnosis of Anterior Myocardial Infarction

Frank lead vectorcardiograms (VCG) from four carefully selected patient subgroups (226 patients) were analyzed to develop optimal criteria for the diagnosis of anterior myocardial infarction. Specificity was evaluated using 100 healthy volunteers under age 30 and 80 patients with normal left ventriculogram and normal coronary arteriograms. Sensitivity was determined using 25 patients with evolutionary ST-T wave changes (V1 2), and LDH and CPK isoenzyme evidence of acute myocardial infarction; and 21 patients with anterior wall akinesia or dyskinesia and > 70% occlusion of the left anterior descending coronary artery. Patients with VCG evidence of bundle branch block, left or right ventricular hypertrophy were excluded.The criterion for the diagnosis of anterior myocardial infarction which was found to give the highest sensitivity with . 95% specificity was: initial anterior QRS forces must not exceed 0.1 mV in maximal anterior amplitude and also must not exceed 24 msec in duration. The performance of this proposed criterion was then tested using four similarly defined patient subgroups consisting of a total of 222 patients. The incidence of false positive diagnosis in these test subgroups was < 1% with a sensitivity of >95%. The overall performance of the proposed criterion was found to be significantly superior to both the widely accepted VCG and ECG criteria for anterior myocardial infarction. Thus, this quantitative criterion using both time and duration of initial anterior forces is both a highly specific and a sensitive indicator of anterior myocardial infarction.
Broader Perception for Local Community Identification

The local identification of communities in a network can be much more effective than partitioning the entire network when only a small portion of a large network is of interest. A local approach is also favored when it is difficult to obtain information about the entire network, the world wide web is a prime example. Such local identification algorithms typically evaluate nodes outside the local community that are directly connected to the local community as potential community members without the need for knowledge about the entire network. But while being a recognized and relevant technique in community identification, the quality of local community identification lags behind their global counterparts that use the entire network. In order to improve the evaluation of community candidates in local algorithms we propose the use of contextual information beyond direct neighbors. This will decrease the gap between relevant network knowledge of global and local methods while remaining a local approach. Benchmarks on synthetic networks show our approach increases the quality of locally identified communities in general and a decrease of the dependency on specific source nodes.
A Review on Performance Analysis of Cloud Computing Services for Scientific Computing

: Cloud computing has emerged as a very important commercial infrastructure that promises to reduce the need for maintaining costly computing facilities by organizations and institutes. Through the use of virtualization and time sharing of resources, clouds serve with a single set of physical resources as a large user base with altogether different needs. Thus, the clouds have the promise to provide to their owners the benefits of an economy of calibration and, at the same time, become a substitute for scientists to clusters, grids, and parallel production conditions. However, the present commercial clouds have been built to support web and small database workloads, which are very different from common scientific computing workloads. Furthermore, the use of virtualization and resource time sharing may introduce significant performance penalties for the demanding scientific computing workloads. In this paper, we analyze the performance of cloud computing services for scientific computing workloads. This paper evaluate the presence in real scientific computing workloads of Many-Task Computing users, that is, of users who employ loosely coupled applications comprising many tasks to achieve their scientific goals. Our effective method demonstrates to yield comparative and even better results than the more complex state-of-the-art techniques but has the advantage to be appropriate for real-time applications.
Agroecología y el diseño de sistemas agrícolas resilientes al cambio climático

Diverse, severe and location-specific impacts on agricultural production are anticipated with climate change.Temperature and water availability remain key factors in determining crop growth and productivity, predicted changes in these factors will lead to reduced crop yields. Climate induced changes in insect pest, pathogen and weed population dynamics and invasiveness could compound such effects. Undoubtedly climate and weather induced instability will affect levels of and access to food supply. Changes that will not radically modify the monoculture nature of dominant agroecosystems may temporarily moderate negative impacts. The biggest and most durable benefits will likely result from more radical agroecological measures that will strengthen the resilience of farmers and rural communities, such as diversification of agroecosytems in the form of polycultures, agroforestry systems and crop-livestock mixed systems accompanied by organic soil management, water conservation and harvesting and general enhancement of agrobiodiversity. Traditional farming systems are repositories of a wealth of principles and measures that can help modern agricultural systems become more resilient to climatic extremes. Many of these agroecological strategies that reduce vulnerabilities to climate variability include, crop diversification, maintaining local genetic diversity, animal integration, soil organic management, water conservation and harvesting, etc. Understanding the agroecological features that underlie the resilience of traditional agroecosystems is an urgent matter, as they can serve as the foundation for the design of adapted agricultural systems. Field surveys and results reported in the literature suggest that agroecosystems are more resilient when inserted in a complex landscape matrix, featuring adapted local germplasm deployed in diversified cropping systems managed with organic matter rich soils and water conservation-harvesting techniques. The identification of systems that have withstood climatic events recently or in the past and understanding the agroecological features of such systems that allowed them to resist and/or recover from extreme events is of increased urgency, as the derived resiliency principles and practices that underlie successful farms can be disseminated to thousands of farmers.
Optimal placement of training for frequency-selective block-fading channels

The problem of placing training symbols optimally for orthogonal frequency-division multiplexing (OFDM) and single-carrier systems is considered. The channel is assumed to be quasi-static with a finite impulse response of length (L + 1) samples. Under the assumptions that neither the transmitter nor the receiver knows the channel, and that the receiver forms a minimum mean square error (MMSE) channel estimate based on training symbols only, training is optimized by maximizing a tight lower bound on the ergodic training-based independent and identically distributed (i.i.d.) capacity. For OFDM systems, it is shown that the lower bound is maximized by placing the known symbols periodically in frequency. For single-carrier systems, under the assumption that the training symbols are placed in clusters of length /spl alpha/ /spl ges/ (2L + 1), it is shown that the lower bound is maximized by a family of placement schemes called QPP-/spl alpha/, where QPP stands for quasi-periodic placement. These placement schemes are formed by grouping the known symbols into as many clusters as possible and then placing these clusters periodically in the packet. For both OFDM and single-carrier systems, the optimum energy tradeoff between training and data is also obtained.
Tackling Obstacles for Gene Therapy Targeting Neurons: Disrupting Perineural Nets with Hyaluronidase Improves Transduction

Gene therapy has been proposed for many diseases in the nervous system. In most cases for successful treatment, therapeutic vectors must be able to transduce mature neurons. However, both in vivo, and in vitro, where preliminary characterisation of viral particles takes place, transduction of neurons is typically inefficient. One possible explanation is that the extracellular matrix (ECM), forming dense perineural nets (PNNs) around neurons, physically blocks access to the cell surface. We asked whether co-administration of lentiviral vectors with an enzyme that disrupts the ECM could improve transduction efficiency. Using hyaluronidase, an enzyme which degrades hyaluronic acid, a high molecular weight molecule of the ECM with mainly a scaffolding function, we show that in vitro in mixed primary cortical cultures, and also in vivo in rat cortex, hyaluronidase co-administration increased the percentage of transduced mature, NeuN-positive neurons. Moreover, hyaluronidase was effective at doses that showed no toxicity in vitro based on propidium iodide staining of treated cultures. Our data suggest that limited efficacy of neuronal transduction is partly due to PNNs surrounding neurons, and further that co-applying hyaluronidase may benefit applications where efficient transduction of neurons in vitro or in vivo is required.
Error Model and Compensation of Bell-Shaped Vibratory Gyro

A bell-shaped vibratory angular velocity gyro (BVG), inspired by the Chinese traditional bell, is a type of axisymmetric shell resonator gyroscope. This paper focuses on development of an error model and compensation of the BVG. A dynamic equation is firstly established, based on a study of the BVG working mechanism. This equation is then used to evaluate the relationship between the angular rate output signal and bell-shaped resonator character, analyze the influence of the main error sources and set up an error model for the BVG. The error sources are classified from the error propagation characteristics, and the compensation method is presented based on the error model. Finally, using the error model and compensation method, the BVG is calibrated experimentally including rough compensation, temperature and bias compensation, scale factor compensation and noise filter. The experimentally obtained bias instability is from 20.5°/h to 4.7°/h, the random walk is from 2.8°/h1/2 to 0.7°/h1/2 and the nonlinearity is from 0.2% to 0.03%. Based on the error compensation, it is shown that there is a good linear relationship between the sensing signal and the angular velocity, suggesting that the BVG is a good candidate for the field of low and medium rotational speed measurement.
Cycloheximide Protects HepG 2 Cells from Serum Withdrawal-Induced Apoptosis by Decreasing p 53 and Phosphorylated p 53 Levels

Cycloheximide (CHX), an inhibitor of protein synthesis, has been reported to prevent cell death in a wide variety of cell types and produced by different apoptotic stimuli. However, the mechanisms by which CHX protects cells from apoptosis are still unclear. In this study, we investigated whether p53 plays a role in the protection by CHX against serum withdrawalinduced apoptosis. Deprivation of serum from the culture medium causes apoptosis in HepG2 cells, and CHX dramatically protects cells from death. p53, p21, and Bax protein levels were elevated, and cell cycle arrest was produced after serum withdrawal. CHX abolished this elevation of p53, p21, and Bax as well as the cell cycle arrest induced by serum deprivation. The p53 inhibitor pifithrinprotects HepG2 cells against apoptosis induced by serum withdrawal. HepG2 cells expressing a dominant negative form of mutant p53 and Hep3B cells lacking p53 were resistant to serum withdrawal-induced apoptosis. Lowering of p53 by small interfering RNA protects HepG2 cells from serum withdrawal-induced apoptosis. p53 phosphorylation was induced by serum withdrawal and other chemotherapeutic reagents such as actinomycin D, doxorubicin, and etoposide. CHX decreases the levels of phosphorylated p53 (pp53) even in the presence of a proteasome inhibitor, which maintains the total p53 levels, whereas it does not affect the dephosphorylation of pp53. These results suggest the possibility that kinases that phosphorylate p53 might be affected by CHX administration. In summary, CHX protects HepG2 cells from serum withdrawal-induced apoptosis through inhibiting the synthesis of p53 and the phosphorylation of p53. Cycloheximide (CHX), a protein synthesis inhibitor, has been widely employed in studies of apoptosis. However, its effects on apoptosis vary from inhibition to enhancement depending on the apoptotic stimulators, e.g., CHX sensitizes cells to tumor necrosis factoror Fas-induced apoptosis (Fulda et al., 2000), but it prevents rat hepatocytes from apoptosis induced by transformation growth factor (Sâanchez et al., 1997) and protects rat thymocytes and mouse lymphoid cell lines against apoptosis induced by glucocorticoids and a calcium ionophore (Wyllie et al., 1984). The mechanisms by which CHX regulates apoptosis are not clear and still under investigation. The hypotheses whereby CHX sensitizes cells to CD95-induced apoptosis include down-regulating FLICE-inhibitory protein and receptor-interacting protein expression (Fulda et al., 2000) or inhibiting the synthesis of antiapoptotic proteins such as Bcl-2 or Bcl-xL. The standard view of the mechanism whereby CHX prevents cell death is that it inhibits the production of “killer proteins” by blocking protein synthesis. However, until now, such killer proteins have not been identified. Other mechanisms such as preventing cell death by activation of antiapoptotic signaling pathways have also been considered (Mattson and Fu-
Migration and social networks — An explanatory multi-evolutionary agent-based model

Sociodemographic studies on human migration phenomena are mostly based on surveys and censuses, which significantly increases the research costs. This scenario becomes even worse when the study involves migration and social networks, which often lacks on representative data and consensually accepted concepts by demographers and sociologists. In this paper we propose a new multi-evolutionary agent model dedicated to social simulations, mainly for those problems where higher order dynamic behaviors (e.g. secondary emergent phenomena) are important to the investigated phenomenon. Its usefulness lies on its multilevel evolutionary adaptability which enables it to capture multiple parallel phenomena. To verify our hypothesis we applied the model to Brazilian internal human migration phenomenon and to the influence of social networks on migration flows. This is followed by a comparative analysis against simulations carried out based on a non-evolutionary cognitive agent model. Results show that the proposed model was able to rise secondary migration-related phenomena such as countermigration flows. Experiments with the cognitive agent also produced the emergence of migration flows but no secondary phenomenon was observed which was the case with our approach. Furthermore, results also pointed out a significant influence exerted by information exchange inside social networks on migration flows.
Stage of readiness to control weight and adopt weight control behaviors in primary care

AbstractBACKGROUND: While the majority of adults are attempting weight loss at any given time, few engage in optimal diet and exercise. We examined factors associated with being in advanced stages of behavior change for weight loss, diet, and exercise. METHODS: We surveyed primary care patients about their health, health habits, and perception and advice about weight as health risk, and about stage of readiness to lose weight, improve diet (control food portions, limit fat intake, increase fruits and vegetables), and increase planned exercise using the Prochaska Stage of Behavior Change model. We conducted bivariable analyses to describe the association between being at the preparation (change in 1 month), action (changing now), and maintenance (maintaining change) stages of change for weight loss and being at 1 of these 3 advanced stages for improving diet and exercise. We also conducted multivariable analyses to examine factors associated with being at these advanced stages of readiness to concurrently lose weight, improve diet, and increase exercise. RESULTS: Of 365 patients (response rate of 60%), 33% were over-weight (body mass index [BMI], 25.0–29.9 kg/m2) and 27% were obese (BMI, 30.0+kg/m2). Of 199 respondents at the preparation, action, or maintenance stage of losing weight, 61% were also at an advanced stage for improving diet and exercise. Those perceiving weight as a health risk were more likely to be at advanced stages of readiness to concurrently lose weight, improve diet, and increase exercise (adjusted odds ratio [AOR], 5.6; 95% CI, 2.5 to 12.5) after adjustment for confounders; this perception was associated with BMI ([AOR, 1.2; 95% CI, 1.1 to 1.3 for each unit increment in BMI]) and being advised by a physician about weight as a health risk (AOR, 6.7; 95% CI, 3.0 to 15.1). Demographic factors, having obesity-related comorbidities, and mental and physical functioning did not appear important. CONCLUSIONS: A large proportion of primary care patients are at advanced stages of readiness to lose weight, improve diet, and increase exercise. Future studies should examine the effectiveness of primary care interventions to help patients optimize weight-related behavior.
Substitution of Formal and Informal Home Care Service Use and Nursing Home Service Use: Health Outcomes, Decision-Making Preferences, and Implications for a Public Health Policy

Objectives The purposes of this study are: (1) to empirically identify decision-making preferences of long-term health-care use, especially informal and formal home care (FHC) service use; (2) to evaluate outcomes vs. costs based on substitutability of informal and FHC service use; and (3) to investigate health outcome disparity based on substitutability. Methodology and data The methods of ordinary least squares, a logit model, and a bivariate probit model are used by controlling for socioeconomic, demographic, and physical/mental health factors to investigate outcomes and costs based substitutability of informal and formal health-care use. The data come from the 2013 Japanese Study of Aging and Retirement (JSTAR), which is designed by Keizai-Sangyo Kenkyu-jo, Hitotsubashi University, and the University of Tokyo. The JSTAR is a globally comparable data survey of the elderly. Results There exists a complement relationship between the informal home care (IHC) and community-based FHC services, and the elasticity’s ranges from 0.18 to 0.22. These are reasonable results, which show that unobservable factors are positively related to IHC and community-based FHC, but negatively related to nursing home (NH) services based on our bivariate probit model. Regarding health-care outcome efficiency issue, the IHC is the best one among three types of elderly care: IHC, community-based FHC, and NH services. Health improvement/outcome of elderly with the IHC is heavier concentrated on IHC services than the elderly care services by community-based FHC and NH care services. Conclusion Policy makers need to address a diversity of health outcomes and efficiency of services based on providing services to elderly through resource allocation to the different types of long-term care. A provision of partial or full compensation for elderly care at home is recommendable and a viable option to improve their quality of lives.