Miracle-dz/UniFAR-FTUs huggingface dataset:
Space-time trellis codes for 4-PSK with three and four transmit antennas in quasi-static flat fading channels

It has been established that the appropriate design parameters for space-time trellis code (STTC) in quasi-static flat Rayleigh fading channels are the rank and determinant criteria or the Euclidean distance criterion, depending on the value of the overall diversity gain. We propose two groups of new STTCs with more than two transmit antennas based on these two design criteria, respectively. These new STTCs are shown to achieve large performance improvements over the ones with two transmit antennas.
Correlation hiding by independence masking

Extracting useful correlation from a dataset has been extensively studied. In this paper, we deal with the opposite, namely, a problem we call correlation hiding (CH), which is fundamental in numerous applications that need to disseminate data containing sensitive information. In this problem, we are given a relational table T whose attributes can be classified into three disjoint sets A, B, and C. The objective is to distort some values in T so that A becomes independent from B, and yet, their correlation with C is preserved as much as possible. CH is different from all the problems studied previously in the area of data privacy, in that CH demands complete elimination of the correlation between two sets of attributes, whereas the previous research focuses on partial elimination up to a certain level. A new operator called independence masking is proposed to solve the CH problem. Implementations of the operator with good worst case guarantees are described in the full version of this short note.
Reengineering Escherichia coli for Succinate Production in Mineral Salts Medium

ABSTRACT The fermentative metabolism of glucose was redirected to succinate as the primary product without mutating any genes encoding the native mixed-acid fermentation pathway or redox reactions. Two changes in peripheral pathways were together found to increase succinate yield fivefold: (i) increased expression of phosphoenolpyruvate carboxykinase and (ii) inactivation of the glucose phosphoenolpyruvate-dependent phosphotransferase system. These two changes increased net ATP production, increased the pool of phosphoenolpyruvate available for carboxylation, and increased succinate production. Modest further improvements in succinate yield were made by inactivating the pflB gene, encoding pyruvate formate lyase, resulting in an Escherichia coli pathway that is functionally similar to the native pathway in Actinobacillus succinogenes and other succinate-producing rumen bacteria.
Finite-difference numerical modelling of gravito-acoustic wave propagation in a windy and attenuating atmosphere

Acoustic and gravity waves propagating in planetary atmospheres have been studied intensively as markers of specific phenomena such as tectonic events or explosions or as contributors to atmosphere dynamics. To get a better understanding of the physics behind these dynamic processes, both acoustic and gravity waves propagation should be modelled in a 3D attenuating and windy atmosphere extending from the ground to the upper thermosphere. Thus, in order to provide an efficient numerical tool at the regional or global scale we introduce a finite difference in the time domain (FDTD) approach that relies on the linearized compressible Navier-Stokes equations with a background flow (wind). One significant benefit of such a method is its versatility because it handles both acoustic and gravity waves in the same simulation, which enables one to observe interactions between them. Simulations can be performed for 2D or 3D realistic cases such as tsunamis in a full MSISE- atmosphere or gravity-wave generation by atmospheric explosions. We validate the computations by comparing them to analytical solutions based on dispersion relations in specific benchmark cases: an atmospheric explosion, and a ground displacement forcing.
Very Fast Outlier Detection in Large Multidimensional Data Sets

Outliers are objects that do not comply with the general behavior of the data. Applications such as exploration in science databases need fast interactive tools for outlier detection in data sets that have unknown distributions, are large in size, and are in high dimensional space. Existing algorithms for outlier detection are too slow for such applications. We present an algorithm based on an innovative use of k-d trees that doesn’t assume any probability model and is linear in the number of objects and in the number of dimensions. We also provide experimental results that show that this is indeed a practical solution to the above problem.
Gender & High Frequency vs. Low Frequency tasks in a context of Joint-Liability Incentives

We study the impact of high and low frequency incentives in a joint-liability framework on six academic outcomes of undergraduate students using a randomized field experiment. As recently documented in health literature, incentives to exercise are effective in developing healthy habits. Therefore, we design groups of three students and provide a premium to the homework’s grade if all the members of the group (three) meet some requirements. We investigate how the frequency of these take home tests affect the students study habits and thus, the academic outcomes. We find that there are no differences in the student’s educational outcomes between the high and low frequency groups. We also explore if male and female students respond differently to a joint-liability incentives scheme. We find that this treatment improves the accumulated grade average of male students, but not for females. This finding is in line with previous research on joint-liability and gender behavior, but now we present it in a new context. Finally, the paper outlines the main evaluation challenges associated with a field experiment in the classroom and provide some lessons in order to improve evaluation designs and to foster future randomized controlled trials in this area.
Cyber space evolution

This article describes a high-speed technology for description and solving logical problems, using the Boolean graphs of associative tables, by means of hardware implementation of parallel synthesis and analysis of algebraic, graph and tabular structures of predicate relations for obtaining deterministic multivalued result in n-dimensional discrete space. The problems of creating a theory of brain-like calculations are considered in the form: a metric of associative relations, association description architecture, optimization of the logical data structures, predicate computing models of system-level, architecture and instruction set of logical associative multiprocessor, synthesis and analysis of adjectives [1–5].
Scheduling Computational Workflows on Failure-Prone Platforms

We study the scheduling of computational workflows on compute resources that experience exponentially distributed failures. When a failure occurs, rollback and recovery is used to resume the execution from the last check pointed state. The scheduling problem is to minimize the expected execution time by deciding in which order to execute the tasks in the workflow and whether to checkpoint or not checkpoint a task after it completes. We give a polynomial-time algorithm for fork graphs and show that the problem is NP-complete with join graphs. Our main result is a polynomial-time algorithm to compute the execution time of a workflow with specified to-be-check pointed tasks. Using this algorithm as a basis, we propose efficient heuristics for solving the scheduling problem. We evaluate these heuristics for representative workflow configurations.
The Class Initiatives of Intelligence Rhetoric: Implications of Racism for Scientific Inquiry.

In a society that is not totalitarian, class disparities are enabled institutionally by science. A capital driven nation that associates intelligence with class and race can determine overall quality of life. Thus, perception of intelligence is an extremely powerful tool for reinforcing class. Seldom have scientists been more controversial than in their attempts to quantify intelligence on the basis of race. Racial models of intelligence provide a paradigm for class and given the correlation reflects a vivid illustration of how classism pervades the scientific community. In order to be better informed, scientists who conduct intelligence research must resist bias. In the aftermath, science will remain subject to flaws but enabled in its attempt to gather an accurate set of facts.
A Rough Set Based Efficient l-diversity Algorithm

Most of the organizations publish micro data for a variety of purposes including demographic and public health research. To protect the anonymity of the entities, data holders often remove or encrypt explicit identifiers. But, released information often contains quasi identifiers, which leak valuable information. Samarati and Sweeney introduced the concept of k-anonymity to handle this problem and several algorithms have been introduced by different authors in recent times. Lin et al put forth a new clustering-based method known as OKA for k-anonymization. But, k-anonymity can create groups that leak information due to homogeneity attack. This problem is tackled by the notion of l- diversity introduced by Machanavajjhala et al. Recently, the OKA algorithm is improved by Tripathy et al by making some modifications in the adjustment stage and introducing distinct l-diversity into it. But, in most of the modern databases impreciseness has become a common characteristic, which is not handled by any of the above algorithms. The primary purpose of this paper is to use MMeR, an algorithm introduced by Tripathy et al, in developing a suitable anonymisation algorithm which is applicable to any database having precise or imprecise heterogeneous data and satisfies both k-anonymity as well as l-diversity properties.
A critical issue in model-based inference for studying trait-based community assembly and a solution

Statistical testing of trait-environment association from data is a challenge as there is no common unit of observation: the trait is observed on species, the environment on sites and the mediating abundance on species-site combinations. A number of correlation-based methods, such as the community weighted trait means method (CWM), the fourth-corner correlation method and the multivariate method RLQ, have been proposed to estimate such trait-environment associations. In these methods, valid statistical testing proceeds by performing two separate resampling tests, one site-based and the other species-based and by assessing significance by the largest of the two p-values (the pmax test). Recently, regression-based methods using generalized linear models (GLM) have been proposed as a promising alternative with statistical inference via site-based resampling. We investigated the performance of this new approach along with approaches that mimicked the pmax test using GLM instead of fourth-corner. By simulation using models with additional random variation in the species response to the environment, the site-based resampling tests using GLM are shown to have severely inflated type I error, of up to 90%, when the nominal level is set as 5%. In addition, predictive modelling of such data using site-based cross-validation very often identified trait-environment interactions that had no predictive value. The problem that we identify is not an “omitted variable bias” problem as it occurs even when the additional random variation is independent of the observed trait and environment data. Instead, it is a problem of ignoring a random effect. In the same simulations, the GLM-based pmax test controlled the type I error in all models proposed so far in this context, but still gave slightly inflated error in more complex models that included both missing (but important) traits and missing (but important) environmental variables. For screening the importance of single trait-environment combinations, the fourth-corner test is shown to give almost the same results as the GLM-based tests in far less computing time.
A novel glycoprotein of feline infectious peritonitis coronavirus contains a KDEL-like endoplasmic reticulum retention signal

A new protein of feline infectious peritonitis coronavirus (FIPV) was discovered in lysates of [35S]cysteine-labeled infected cells. Expression of open reading frame (ORF) 6b of FIPV in recombinant vaccinia virus-infected cells was used to identify it as the 6b protein. Further characterization revealed that it is a novel type of viral glycoprotein whose function is not clear. It is a soluble protein contained in microsomes; its slow export from the cell is caused by the presence of an endoplasmic reticulum (ER) retention signal at the C terminus. This amino acid sequence, KTEL, closely resembles the consensus KDEL signal of soluble resident ER proteins. A mutant 6b protein with the C-terminal sequence KTEV became resistant to digestion by endo-beta-N-acetylglucosaminidase H with a half-time that was reduced threefold. In contrast, a mutant with the sequence KDEL was completely retained in the ER. The FIPV 6b protein is the first example of a viral protein with a functional KDEL-like ER retention signal.
Regulation of Neuronal Survival by the Serine-Threonine Protein Kinase Akt

A signaling pathway was delineated by which insulin-like growth factor 1 (IGF-1) promotes the survival of cerebellar neurons. IGF-1 activation of phosphoinositide 3-kinase (PI3-K) triggered the activation of two protein kinases, the serine-threonine kinase Akt and the p70 ribosomal protein S6 kinase (p70S6K). Experiments with pharmacological inhibitors, as well as expression of wild-type and dominant-inhibitory forms of Akt, demonstrated that Akt but not p70S6K mediates PI3-K-dependent survival. These findings suggest that in the developing nervous system, Akt is a critical mediator of growth factor-induced neuronal survival.
Intermittent Administration of Parathyroid Hormone [1–34] Prevents Particle-Induced Periprosthetic Osteolysis in a Rat Model

We examined whether intermittent administration of parathyroid hormone [1–34] (PTH[1–34]; 60 μg/kg/day) can prevent the negative effects of titanium (Ti) particles on implant fixation and periprosthetic osteolysis in a rat model. Eighteen adult male rats (12 weeks old, bones still growing) received intramedullary Ti implants in their bilateral femurs; 6 rats from the blank group received vehicle injections, and 12 rats from the control group and PTH treatment group received Ti particle injections at the time of operation and intra-articular injections 2 and 4 weeks postoperatively. Six of the rats that received Ti particles from the PTH group also received PTH[1–34] treatment. Six weeks postoperatively, all specimens were collected for assessment by X-ray, micro-CT, biomechanical, scanning electron microscopy (SEM), and dynamic histomorphometry. A lower BMD, BV/TV, Tb.N, maximal fixation strength, and mineral apposition rate were observed in the control group compared to the blank group, demonstrating that a periprosthetic osteolysis model had been successfully established. Administration of PTH[1–34] significantly increased the bone mineral density of the distal femur, BV/TV, Tb.N, Tb.Th, Tb.Sp, Con.D, SMI, and maximal fixation strength in the PTH group compared to that in the control group. SEM revealed higher bone–implant contact, thicker lamellar bone, and larger trabecular bone area in the PTH group than in the control group. A higher mineral apposition rate was observed in the PTH group compared to both the blank and control groups. These findings imply that intermittent administration of PTH[1–34] prevents periprosthetic osteolysis by promoting bone formation. The effects of PTH[1–34] were evaluated at a suprapharmacological dosage to the human equivalent in rats; therefore, additional studies are required to demonstrate its therapeutic potential in periprosthetic osteolysis.
THE RELATIONSHIP BETWEEN ELEMENTARY TEACHERS' YEARS OF EXPERIENCE AND THEIR SELF-PERCEIVED PEDAGOGICAL COMPETENCE IN ALABAMA ELEMENTARY SCHOOLS

Years of teaching experience have been found to increase student achievement more than advanced degrees, formal training, and in-service professional development. Additionally, teachers with high pedagogical competence levels have achieved excellent academic results and have also taught and led students to be well-rounded. It has been competent teachers who have lain at the heart of the educational process, as a bridge between the curriculum and the learner. The purpose of this correlational study was to determine whether a statistically significant relationship exists between years of teaching experience and elementary teachers’ self-perceived effective pedagogical competence. A convenience sample of 159 elementary teachers from three school districts in northwest Alabama participated in the study. Pearson correlations were utilized to test three null hypotheses to describe the strength and direction of the relationship between years of teaching experience and three factors of teachers’ self-perceived pedagogical competence as measured with the Elementary Teachers Instructional Auto-perceived Competence Evaluation Scale. It was discovered that no significant relationships were found between years of teaching experience and the socio-emotional, communicative-relational, or instructional factors of the participants’ pedagogical competence. It was concluded that teachers need quality professional development opportunities to maintain and upgrade their pedagogical competence throughout their teaching career. Since professional development was considered the next logical step in the process of building teachers’ pedagogical competence, it would be helpful to conduct a study that seeks to determine the types of professional development opportunities teachers want and need.
Joint Resource Bidding and Tipping Strategies in Multi-Hop Cognitive Networks

In multi-hop secondary networks, bidding strategies for spectrum auction, route selection, and relaying incentives should be jointly considered to establish multi-hop communication. In this paper, a framework for joint resource bidding and tipping is developed where users iteratively revise their strategies, which include bidding and incentivizing relays, to achieve their quality of service requirements. A bidding language is designed to generalize secondary users' (SUs) heterogeneous demands for multiple resources and willingness to pay. Then, group partitioning-based auction mechanisms are presented to exploit the heterogeneity of SU demands in multi-hop secondary networks. These mechanisms include primary operator (PO) strategies based on static and dynamic partition schemes combined with new payment mechanisms to obtain high revenue and fairly allocate the resources. The proposed auction schemes stimulate the participation of SUs and provide high revenue for the PO while maximizing the social welfare. Besides, they satisfy the properties of truthfulness, individual rationality, and computational tractability. Simulation results have shown that for highly demanding users the static group scheme achieves 150% more winners and three times higher revenue for the PO compared to a scheme without grouping. For lowly demanding users, the PO may keep similar revenue with the dynamic scheme by lowering 50% the price per channel as the number of winners will increase proportionally.
Evaluation of pulmonary function using single-breath-hold dual-energy computed tomography with xenon

Abstract Xenon-enhanced dual-energy computed tomography (xenon-enhanced CT) can provide lung ventilation maps that may be useful for assessing structural and functional abnormalities of the lung. Xenon-enhanced CT has been performed using a multiple-breath-hold technique during xenon washout. We recently developed xenon-enhanced CT using a single-breath-hold technique to assess ventilation. We sought to evaluate whether xenon-enhanced CT using a single-breath-hold technique correlates with pulmonary function testing (PFT) results. Twenty-six patients, including 11 chronic obstructive pulmonary disease (COPD) patients, underwent xenon-enhanced CT and PFT. Three of the COPD patients underwent xenon-enhanced CT before and after bronchodilator treatment. Images from xenon-CT were obtained by dual-source CT during a breath-hold after a single vital-capacity inspiration of a xenon–oxygen gas mixture. Image postprocessing by 3-material decomposition generated conventional CT and xenon-enhanced images. Low-attenuation areas on xenon images matched low-attenuation areas on conventional CT in 21 cases but matched normal-attenuation areas in 5 cases. Volumes of Hounsfield unit (HU) histograms of xenon images correlated moderately and highly with vital capacity (VC) and total lung capacity (TLC), respectively (r = 0.68 and 0.85). Means and modes of histograms weakly correlated with VC (r = 0.39 and 0.38), moderately with forced expiratory volume in 1 second (FEV1) (r = 0.59 and 0.56), weakly with the ratio of FEV1 to FVC (r = 0.46 and 0.42), and moderately with the ratio of FEV1 to its predicted value (r = 0.64 and 0.60). Mode and volume of histograms increased in 2 COPD patients after the improvement of FEV1 with bronchodilators. Inhalation of xenon gas caused no adverse effects. Xenon-enhanced CT using a single-breath-hold technique depicted functional abnormalities not detectable on thin-slice CT. Mode, mean, and volume of HU histograms of xenon images reflected pulmonary function. Xenon images obtained with xenon-enhanced CT using a single-breath-hold technique can qualitatively depict pulmonary ventilation. A larger study comprising only COPD patients should be conducted, as xenon-enhanced CT is expected to be a promising technique for the management of COPD.
An exact stability analysis test for single-parameter polynomially-dependent linear systems

We provide a condition for testing the stability of a single-parameter, polynomially-dependent linear system of polynomial degree N of the form x/sup /spl dot// = A(/spl rho/)x, A(/spl rho/) = /spl Sigma/ /sub i=0//sup N//spl rho//sup i/A/sub i/ over a compact interval. The test is nonconservative and can be cast as a convex feasibility problem in terms of a pair of linear matrix inequalities (LMIs).
IL-10 and glucocorticoids inhibit Aβ(1–42)- and lipopolysaccharide-induced pro-inflammatory cytokine and chemokine induction in the central nervous system

Alzheimer's disease (AD) is characterized by neuropil threads composed of structurally abnormal neurites, neurons containing paired helical filaments of tau protein, and extracellular deposits of amyloid-beta (Abeta) peptide, a protein fragment having neurotoxic and glial immune response activating potential. In the present study, we demonstrate that an acute intracerebroventricular (icv) injection of Abeta(1-42) in the mouse induces a time- and dose-dependent production of IL-1alpha, IL-1beta, IL-6 and MCP-1 in the hippocampus and cortex as measured by ELISA. Cytokine and chemokine levels were maximal at 9 h, with MCP-1 and IL-1alpha remaining elevated over a 24 h period and IL-1beta remaining elevated over a 48 h period. The temporal profile of Abeta-induced cytokine induction differed from that observed for LPS. Following an icv injection of LPS, maximal levels of IL-1alpha, IL-1beta, IL-6 and MCP-1 were attained by 9 h and, except for MCP-1, returned to levels indistinguishable from control at 24 h. MCP-1 remained elevated at 24 h and returned to basal levels at 48 h. In contrast, little production of TNF-alpha was observed under either Abeta or LPS acute stimulus conditions. Treatment with anti-inflammatory agents such as prednisolone, dexamethasone, or IL-10 inhibited both Abeta- and LPS-induced cytokine and chemokine production in the brain. In summary, icv administration of Abeta and LPS induced elevated brain levels of pro-inflammatory cytokines that could be inhibited by immune suppressing drugs and anti-inflammatory proteins, thus providing support for the utility of anti-inflammatory therapeutics in modulating the immunopathology observed in brain inflammatory diseases such as AD.