Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast multiplication of integer matrices Withdrawn paper

Erratum. Eric Schost discovered a bug in this paper: by construction, formula (7) does not hold, since the matrix Va,n is not invertible whenever l> 2. Unfortunately, we do not see how to repair this bug: not only Va,n is not invertible, but the rank of Va,n is actually very small (and equal to max {q1, , ql}). This makes the proof collapse. We have also tried a few other things, such as fixing a=2 and trying to take many qi for which a is a primitive root of unity of a small order. This also does not work, since the product of two operators in Z[X, Q]2 makes the coefficient sizes increase by n2 (and not merely n) bits. Going until “small order n”, we must have q1 ql P lcm(21 − 1, 22 − 1, , 2− 1). This lcm is of the same order as 2 2 , but strictly smaller than 2 2 .
Quadcopter Flight Dynamics

Angular maneuvering scheme along with standard flight operations such as taking-off, landing and hovering is proposed for a quadcopter with indoor or outdoor flying capabilities. This is achieved by simultaneously controlling the speed of the four rotors in order for the quadcopter to attain the correct orientation. The total thrust is determined using the inputs of altitude, pitch and roll angles. Then the thrust that the rotors must generate independently is obtained from the ratio of the angles and the calculated thrust for maintaining the input altitude. Voltage supply that is needed to spin the rotors at a certain RPM (Rotations per minute) is obtained to produce the thrust computed in the previous step. Moreover, the procedure on varying the thrust direction of rotors is also illustrated to perform the standard flight operations.
Resolving the HONO formation mechanism in the ionosphere via ab initio molecular dynamic simulations

Significance This contribution resolves a long-standing puzzle of the nitrous acid (HONO) formation mechanism from NO+ motif and water clusters in the ionosphere (key layer for radio signal transmission). From previous studies, massive different isomer structures have been identified. However, an explanation of how the low-lying isomers channel through the high-lying ones to form HONO species has been elusive. A clear understanding of the mechanism was only possible through molecular dynamics simulation. This work identifies the critical isomer that is key to linking the network of all the low-lying isomers together. This finding provides, to our knowledge, the first solid theoretical evidence for the formation of HONO in the ionosphere. Solar emission produces copious nitrosonium ions (NO+) in the D layer of the ionosphere, 60 to 90 km above the Earth’s surface. NO+ is believed to transfer its charge to water clusters in that region, leading to the formation of gaseous nitrous acid (HONO) and protonated water cluster. The dynamics of this reaction at the ionospheric temperature (200–220 K) and the associated mechanistic details are largely unknown. Using ab initio molecular dynamics (AIMD) simulations and transition-state search, key structures of the water hydrates—tetrahydrate NO+(H2O)4 and pentahydrate NO+(H2O)5—are identified and shown to be responsible for HONO formation in the ionosphere. The critical tetrahydrate NO+(H2O)4 exhibits a chain-like structure through which all of the lowest-energy isomers must go. However, most lowest-energy isomers of pentahydrate NO+(H2O)5 can be converted to the HONO-containing product, encountering very low barriers, via a chain-like or a three-armed, star-like structure. Although these structures are not the global minima, at 220 K, most lowest-energy NO+(H2O)4 and NO+(H2O)5 isomers tend to channel through these highly populated isomers toward HONO formation.
NK Dendritic Cells Are Innate Immune Responders to Listeria monocytogenes Infection1

NK dendritic cells (NKDC) are recently described immunologic cells that possess both lytic and Ag-presenting function and produce prolific quantities of IFN-γ. The role of NKDC in innate immunity to bacterial infection is unknown. Because IFN-γ is important in the immune response to Listeria monocytogenes (LM), we hypothesized that NKDC play a critical role during LM infection in mice. We found that LM increased the frequency and activation state of NKDC in vivo. Using in vivo intracellular cytokine analysis, we demonstrated that NKDC are a major source of early IFN-γ during infection with LM. Adoptive transfer of wild-type NKDC into IFN-γ-deficient recipients that were subsequently infected with LM decreased bacterial burden in the liver and spleen and prolonged survival. In contrast, NK cells were depleted early during LM infection, produced less IFN-γ, and conferred less protection upon adoptive transfer into IFN-γ-deficient mice. In vitro, LM induction of IFN-γ secretion by NKDC depended on TLR9, in addition to IL-18 and IL-12. Our study establishes NKDC as innate immune responders to bacterial infection by virtue of their ability to secrete IFN-γ.
A Code-Based Input Partitioning Method for Equivalence Class Testing

Equivalence class testing is traditionally a specification-based testing technique that derives test cases through partitioning the input domain of a program into different classes. This technique is widely used for testing all kinds of software systems. However, it is often difficult to cover all possible combinations of input conditions based on the available specification information. This paper proposes a novel input partitioning method based on the information extracted from the program source code to aid in the equivalence class testing. Based on the partition, two equivalence class testing techniques, white-box, and gray-box, are proposed. We have evaluated the proposed techniques through empirical studies on web-based database applications. Experiment results showed that the proposed techniques perform better than traditional equivalence class testing.
Digital materials for digital printing

Conventional three-dimensional printing processes are material-dependent, and are irreversible. We present an alternative approach based on three-dimensional assembly of mass-produced two-dimensional components of digital material. This significantly enlarges the available material set, allows reversible disassembly, and imposes constraints that reduce the accumulation of local positioning errors in constructing a global shape. Experimental work on material properties and dimensional scaling of the digital material will be presented, with application in assembling functional structures. We propose that assembling digital material will be the future of 3-dimensional free-form fabrication of functional materials. Most existing commercial free-form fabrication printers build by putting together small quantities of no more than a few expensive materials. In order to make high-resolution objects they need to be very precise and therefore cost between tens and hundreds of thousands of dollars and are operated by skilled technicians. On the other hand young children build 3-dimensional structures out of LEGO with their hands. LEGO structures are cheap, quick and easy to make, reversible and most importantly they are more precise than the kids who build them. However, they are big and are only made out of ABS plastic. We believe that digital materials bring reversibility, simplicity, low cost and speed to free form fabrication in addition to a larger material set. Previous research on structures built out of many discrete parts involved self assembly [1], error correction self assembly [2], programmable self-assembly [3] and folding[4]. We rely on a digital printer, as presented in [5] which will assemble the structure by picking and placing the bricks forming the digital material. We define a digital material as a discrete set of components that can be of any sizes and shape, made out of various materials and that can fit together in various ways (press fit, friction fit, snap fit, reflow binding, etc.).
Fast DCT based expression extraction and lifelike transferring for facial images

Facial expression details are important visual cues to interpret expressions, which are also hard to be synthesized. We propose a novel facial expression transferring method to synthesize realistic colorful facial expressions with source-specific expression details. First, we choose YUV color space to represent the expression images. In Y channel of the color space, the expression image of the source object is transformed into frequency domain through discrete cosine transform. Then, the expression details including micro-expressions of the source object are extracted through analyzing their frequency distribution. Finally, those expression details are stitched smoothly to the target object with Poisson image editing method. The transferred result is combined with U and V channels of the warped target expression to synthesize the colorful realistic expressions of the target object, which reduces the effect of illumination and skin color variations. Experiments on the Multi-PIE database show that our method has higher perceptual quality over the state-of-the-art methods.
Advanced Scheme for Data Transmission with Early Congestion Detection

We develop a distributed opportunistic routing scheme with early congestion detection for multi-hop wireless networks. The introduced scheme utilizes the functionality of opportunistic routing and considering an expected average per packet reward criterion, shortest path and so on. Congestion in network causes packet loss and delayed packet delivery. By detecting congestion earlier, the routing scheme which utilizes the opportunities in the network can increase the rate of performance and reliability of the network. We implement it in the NS2 simulator and experiment with AODV routing protocol. Index Terms—AODV protocol, Congestion Detection, Opportunistic Routing, r-Decider Algorithm
Labor Relations in Basketball: The Lockout of 1998-99

Indeed, the sport was often cited as an example of good labor-management relations. What made the record even more remarkable is that basketball is the quintessential big-money game. There are ample riches to divide up between owners and players. Ticket prices to NBA games are the highest in sports, and the league has enjoyed strong financial support from television. The minimum cost of staging an event is far smaller in basketball than in other team sports that have larger rosters. 2 The combination of high revenues and relatively low overhead costs brought NBA salaries to the lofty average of $2.6 million, the highest in sports. The tranquility ended when the 1998–99 season was truncated by a 202-day lockout. This article examines the background of basketball labor relations, why the lockout occurred, its key issues, the dynamics of the bargaining process, and the eventual settlement. The saga of the league and its union is particularly interesting in that what was generally regarded as a successful structure for dividing up revenues became unglued. Besides the structural model and contested issues, an important aspect of the dispute was the negotiators and their relationships, not only with each other, but also with the people they represented. The clash of personalities and attitudes, so familiar from other sports, came at last to haunt basketball negotiations.
THE EFFECT OF NOISE ON THE DUST TEMPERATURE–SPECTRAL INDEX CORRELATION

We investigate how uncertainties in flux measurements affect the results from modified blackbody spectral energy distribution (SED) fits. We show that an inverse correlation between the dust temperature T and spectral index β naturally arises from least-squares fits due to the uncertainties, even for sources with a single T and β. Fitting SEDs to noisy fluxes solely in the Rayleigh–Jeans regime produces unreliable T and β estimates. Thus, for long wavelength observations (λ ≳ 200 μm), or for warm sources (T ≳ 60 K), it becomes difficult to distinguish sources with different temperatures. We assess the role of noise in recent observational results that indicate an inverse and continuously varying T–β relation. Though an inverse and continuous T–β correlation may be a physical property of dust in the interstellar medium, we find that the observed inverse correlation may be primarily due to noise.
Host-Based P2P Flow Identification and Use in Real-Time

Data identification and classification is a key task for any Internet Service Provider (ISP) or network administrator. As port fluctuation and encryption become more common in P2P applications wishing to avoid identification, new strategies must be developed to detect and classify their flows. This article introduces a method of separating P2P and standard web traffic that can be applied as part of an offline data analysis process, based on the activity of the hosts on the network. Heuristics are analyzed and a classification system proposed that focuses on classifying those “long” flows that transfer most of the bytes across a network. The accuracy of the system is then tested using real network traffic from a core Internet router showing misclassification rates as low as 0.54% of flows in some cases. We expand on this proposed strategy to investigate its relevance to real-time, early classification problems. New proposals are made and the results of real-time experiments are compared to those obtained in the offline analysis. It is shown that classification accuracies in the real-time strategy are similar to those achieved in offline analysis with a large portion of the total web and P2P flows correctly identified.
Super-resolution images by support vector regression on edge pixels

Support vector machine (SVM) is a statistical learning algorithm that is capable of estimating high-dimensional functions. Recently, support vector regression (SVR) - the use of SVM for regression - has been used to generate super-resolution images. In this paper, we propose to apply the SVR algorithm on edge pixels only so as to reduce the emboss effect that would appear in the edge region of an enlarged image if the SVR is applied on the entire input image. Such a modification is naturally motivated by the principle that human perception is mainly focusing on edge regions. Doing so can also reduce the overall time consumed during the training process and makes the enlarged image looking more pleasant perceptually.
Genes and Molecules of Lactobacilli Supporting Probiotic Action

SUMMARY Lactobacilli have been crucial for the production of fermented products for centuries. They are also members of the mutualistic microbiota present in the human gastrointestinal and urogenital tract. Recently, increasing attention has been given to their probiotic, health-promoting capacities. Many human intervention studies demonstrating health effects have been published. However, as not all studies resulted in positive outcomes, scientific interest arose regarding the precise mechanisms of action of probiotics. Many reported mechanistic studies have addressed mainly the host responses, with less attention being focused on the specificities of the bacterial partners, notwithstanding the completion of Lactobacillus genome sequencing projects, and increasing possibilities of genomics-based and dedicated mutant analyses. In this emerging and highly interdisciplinary field, microbiologists are facing the challenge of molecular characterization of probiotic traits. This review addresses the advances in the understanding of the probiotic-host interaction with a focus on the molecular microbiology of lactobacilli. Insight into the molecules and genes involved should contribute to a more judicious application of probiotic lactobacilli and to improved screening of novel potential probiotics.
Essays on inference and strategic modeling

This dissertation presents three stand-alone contributions to econometric inference and the analysis of strategic behavior. Chapter 1 develops a structural econometric framework for first-price auctions that generalizes the assumption of Bayesian Nash Equilibrium within the context of a level-k behavioral model. The level-k model nests equilibrium by allowing bidders to best respond to heterogeneous beliefs about opponents' bidding strategies. I characterize conditions for identification of the distribution over valuations and bidder-types in populations with heterogeneous behavioral strategies. I propose a semi-nonparametric maximum likelihood estimator, establishing nonparametric consistency with an upper- semicontinuous population likelihood function, which I compute using a generalized expectation maximization algorithm. Presenting evidence from a pilot study of vintage computer auctions, I find a high level of bidder sophistication in the field. I also characterize expected revenues in first price auctions with level-k bidders, establishing a partial identification result for expected revenues in unidentified behavioral models. Empirical evidence suggests a misspecified equilibrium optimal reserve price could reduce expected revenues 30% relative to an unbinding reserve price. Chapter 2 introduces new Bayesian methods adapted to estimating a large-dimensional covariance matrix. I analyze the return generating process using an unrestricted factor model of covariance, imposing structure on the covariance matrix through prior beliefs on the parameters governing this process. I use these methods to provide an empirical Bayesian foundation for a general class of shrinkage estimators and use the shrinkage interpretation to characterize prior beliefs that optimize a posterior objective function. This estimation strategy delivers lower finite-sample loss than existing estimators in Monte Carlo simulations and performs well in minimum variance portfolio selection exercises. Chapter 3 analyzes conformist tendencies for a population in which individuals gain utility by mimicking the average behavior, characterizing norms by the mean behavior, thus introducing an endogenous mechanism for establishing social norms. Under this specification, social preferences generally give rise to more concentrated behavior and a conformist pool forms when social preferences are sufficiently prominent. In addition to illustrating the determinants of conformist behavior with an endogenous reference point, these findings support applied work inferring social norms from average behavior
Tissue pharmacokinetics of ertapenem at steady-state in diabetic patients with leg infections.

OBJECTIVES Ertapenem pharmacokinetics were determined in the interstitium of healthy tissue and of infected tissue of patients suffering from diabetic foot infections, to evaluate if antibiotic concentrations at the target site are sufficient to achieve bacterial killing. PATIENTS AND METHODS Nine patients with diabetic foot infections received 1 g of ertapenem per day intravenously. At steady-state, ertapenem concentrations were measured over 8 h in plasma and in the interstitium of healthy subcutaneous adipose tissue and of soft tissue adjacent to the foot infection using microdialysis. RESULTS The maximum total concentration (Cmax) of ertapenem in plasma was 59.4 ± 12.9 mg/L. Free interstitial Cmax in the infected leg (4.5 ± 2.7 mg/L) was significantly higher (P=0.01) than in healthy subcutaneous tissue (2.4 ± 1.6 mg/L). For bacterial pathogens with an MIC of 1 mg/L, the free mean 'time above MIC' (T>MIC) in the interstitium of infected tissue was calculated to be 38%± 25% of the 24 h dosing interval. Accordingly, bacteriostatic (T>MIC >20%) and maximal bactericidal (T>MIC >40%) effects would be reached in 8/9 and 4/9 diabetic feet, respectively. CONCLUSIONS Although total plasma concentrations of ertapenem were lower in diabetics than reported for healthy subjects, free interstitial tissue concentrations in diabetics were similar to those known from healthy volunteers. Penetration of ertapenem into the interstitium of inflamed tissue of diabetic feet was not impaired in spite of angiopathy. Daily doses of >1 g of ertapenem might be considered to optimize bactericidal effects in diabetic foot infections caused by moderately susceptible strains.
Comparison of Density Forecasting Methods for Wood Growth Ring

The survival and development of human being are seriously threatened by the decrease of nature forest in all over the world. As a result, it has been widely focused on the intensive farming of plantation and scientific utilization of wood resource. The characteristics of regression analysis method, time series method and neural network method commonly used in wood quality forecast were analyzed. The modeling process and result of these forecasting methods were presented in terms of the density forecast of wood growth ring in this paper. The forecasting precisions were compared, and results indicated neural network method is the best method for wood quality forecast.
FAS/FASL gene polymorphisms in Turkish patients with chronic myeloproliferative disorders

Introduction Chronic myeloproliferative disorders (CMPD) are chronic myeloid hematological disorders, characterized by increased myeloid cell proliferation and fibrosis. Impaired apoptotic mechanisms, increased cell proliferation, uncontrolled hematopoietic cell proliferation and myeloaccumulation may contribute to the pathogenesis of CMPD. The aim of our study was to show the possible role of FAS/FASL gene polymorphisms in CMPD pathogenesis and investigate the association with clinical parameters and susceptibility to disease. Material and methods We included 101 (34 polycythemia vera (PV), 23 primary myelofibrosis (PMF), 44 essential thrombocythemia (ET)) CMPD patients diagnosed according to the WHO classification criteria and 95 healthy controls in this study. All the patients and the controls were investigated for FAS/FASL gene expression, allele frequencies and phenotype features, and also FAS mRNA levels were analyzed. Results Chronic myeloproliferative disorders patients showed increased FAS-670AG + GG genotype distribution compared with the control group (p < 0.05). While the A allele was more frequent in both groups, AG genotype was more frequent in CMPD patients. There was no association between FAS-670A>G gene polymorphism and some clinical parameters such as splenomegaly and thrombosis (p > 0.05). No statistically significant difference in FASL+843C>T genotype or allele frequency was found between groups (p > 0.05). Moreover, no statistically significant difference was detected in FASL and JAK2V617F mutations (p > 0.05). FAS mRNA expression was 1.5-fold reduced in patients compared to healthy subjects. Conclusions According to our findings, FAS/FASL gene expression may contribute to the molecular and immunological pathogenesis of CMPD. More investigations are needed to support these data.
Investigation of the Causal Relationship between Academic Motivation and Academic Engagement with the Mediating Role of Achievement Emotions and Academic Hardiness in Students

The aim of this study was to test the causal relationship between academic motivation and academic engagement with mediating role of achievement emotions and academic hardiness. 280 first year female high school students of Dezful city were selected by multiple stage random sampling. The instruments used in this study was the Revised Academic Hardiness Scale (2005), Tinio's Academic Engagement Scale (2009), Academic Motivation Scale (1989) and Pekrun's Achievement Emotion Questionnaire (2002). The current study plan was descriptive-correlative and the fitness of the proposed model was examined through structural equation modeling. The indirect effects were tested by using bootstrap procedure. The findings indicated that model fitted the data and all the direct paths were significant except external motivation to negative emotions. Also, all the indirect paths were significant.