Miracle-dz/UniFAR-FTUs huggingface dataset:
Review: elimination of bacteriophages in whey and whey products

As the cheese market faces strong international competition, the optimization of production processes becomes more important for the economic success of dairy companies. In dairy productions, whey from former cheese batches is frequently re-used to increase the yield, to improve the texture and to increase the nutrient value of the final product. Recycling of whey cream and particulated whey proteins is also routinely performed. Most bacteriophages, however, survive pasteurization and may re-enter the cheese manufacturing process. There is a risk that phages multiply to high numbers during the production. Contamination of whey samples with bacteriophages may cause problems in cheese factories because whey separation often leads to aerosol-borne phages and thus contamination of the factory environment. Furthermore, whey cream or whey proteins used for recycling into cheese matrices may contain thermo-resistant phages. Drained cheese whey can be contaminated with phages as high as 109 phages mL-1. When whey batches are concentrated, phage titers can increase significantly by a factor of 10 hindering a complete elimination of phages. To eliminate the risk of fermentation failure during recycling of whey, whey treatments assuring an efficient reduction of phages are indispensable. This review focuses on inactivation of phages in whey by thermal treatment, ultraviolet (UV) light irradiation, and membrane filtration. Inactivation by heat is the most common procedure. However, application of heat for inactivation of thermo-resistant phages in whey is restricted due to negative effects on the functional properties of native whey proteins. Therefore an alternative strategy applying combined treatments should be favored – rather than heating the dairy product at extreme temperature/time combinations. By using membrane filtration or UV treatment in combination with thermal treatment, phage numbers in whey can be reduced sufficiently to prevent subsequent phage accumulations.
A dual-band RF front-end for WCDMA and GSM applications

An RF front-end for dual-band, dual-mode operation is presented in this paper. The front-end consumes 22.5 mW from a 1.8 V supply and is designed to be used in direct conversion WCDMA and GSM receivers. The measured noise figure, gain, and IIP3 are 2.3 dB, 39.5 dB, and -19 dBm for GSM and 4.3 dB, 33 dB, and -14.5 dBm for WCDMA, respectively. The front-end has 27 dB gain control range in both systems.
Contact Resistance for “End-Contacted” Metal−Graphene and Metal−Nanotube Interfaces from Quantum Mechanics

In this paper, we predict the current−voltage (I−V) characteristics and contact resistance of “end-contacted” metal electrode−graphene and metal electrode−carbon nanotube (CNT) interfaces for five metals, Ti, Pd, Pt, Cu, and Au, based on the first-principles quantum mechanical (QM) density functional and matrix Green’s function methods. We find that the contact resistance (normalized to surface C atoms) is 107 kΩ for Ti, 142 kΩ for Pd, 149 kΩ for Pt, 253 kΩ for Cu, and 187 kΩ for Au. This can be compared with the contact resistance (per C) for “side-contacted” metal−graphene or metal−CNT interfaces of 8.6 MΩ for Pd, 34.7 MΩ for Pt, 630 MΩ for Cu, etc. Those are in good agreement with available experimental results, 40.5 MΩ for Pt, for example. Thus, compared to the values for side-contacted interfaces from QM, we find a decrease in contact resistance by factors ranging from 6751 for Au and 2488 for Cu, to 233 for Pt and 60 Pd, to 8.8 for Ti. This suggests a strong advantage for developing technology to ac.
On Posets and Hopf Algebras

Abstract We generalize the notion of the rank-generating function of a graded poset. Namely, by enumerating different chains in a poset, we can assign a quasi-symmetric function to the poset. This map is a Hopf algebra homomorphism between the reduced incidence Hopf algebra of posets and the Hopf algebra of quasi-symmetric functions. This work implies that the zeta polynomial of a poset may be viewed in terms Hopf algebras. In the last sections of the paper we generalize the reduced incidence Hopf algebra of posets to the Hopf algebra of hierarchical simplicial complexes.
Fluid-structure Interaction Within 3-layered Aortic Arch Model under Pulsatile Blood Flow

In cardiovascular biomechanics the fluid-structure interaction within large blood vessel is required to understand the aortic wall tear, aortic dissection and so on. A loosely coupled method was used to study the complex mechanical interaction under pulsatile flow in a three-layered aortic arch model. The results showed the variations of wall stress along arch portion, and wall stress distribution in three-layered wall. The study provide insight into the biomechanics of aortic dissection: at systolic acceleration phase, the highest normal stress in the media layer may be responsible for the tear and dissection extending into the media layer; at foot entrance flow, the shear stress might contribute to the dissection in the media near the adventitia layer.
The Deterministic Execution Hammer : How Well Does it Actually Pound Nails ?

This paper takes a critical look at the benefits provided by state-of-the-art deterministic execution techniques. Specifically, we look at four applications of deterministic execution: debugging, fault-tolerant replication, testing, and security. For each application, we discuss what an ideal system would provide, and then look at how deterministic systems compare to the ideal. Further, we discuss alternative approaches, not involving determinism, and we judge whether or not these alternatives are more suitable. Along the way, we identify open questions and suggest future work. Ultimately, we find that there are competitive alternatives to determinism for debugging and replicating multithreaded programs; that determinism has high, though unproven, potential to improve testing; and that determinism has distinct security benefits in eliminating some covert timing channels. Furthermore, determinism is a unified solution for all four applications: this confers a distinct advantage over point solutions that do not compose well with one another.
The Impact of Political Context on the Questions Asked and Answered

This chapter examines how the larger political context and policies enacted at different points in American history have affected the questions education researchers asked and answered. The authors argue that while education researchers are often quick to consider how their research should shape policy, they are less likely to contemplate the possible effect of policies on their scholarship. To examine whether the policy–research relationship is indeed bidirectional, the authors conducted a thorough content analysis of six of the most prominent education research journals, some of which date back to the late 19th and early 20th centuries. The goal was to consider how shifts in racial politics and educational policies may have influenced what was studied, particularly research that examined the role of race and ethnicity in education. The authors looked for shifts between education research examining race and education within a broader social context and research focused on the personal and familial deficits of individual students or families. They argue that if these shifts in research are somewhat synchronized with shifts in racial politics and policies in the United States, this is a potential indicator of the impact that the larger political milieu may have had on education research over the last 100 years. Consideration of this research−policy relationship may raise the awareness of education researchers in terms of the origins of the questions they will ask and answer in the American Educational Research Association’s second century.
Discovering and Explaining Mobility Patterns in Urban Spaces: A Study of Manhattan Taxi Data

Nowadays, human movement in urban spaces can be traced digitally in many cases. It can be observed that movement patterns are not constant, but vary across time and space. In this work, we characterize such spatio-temporal patterns with an innovative combination of two separate approaches that have been utilized for studying human mobility in the past. First, by using non-negative tensor factorization (NTF), we are able to cluster human behavior based on spatio-temporal dimensions. Second, for understanding these clusters, we propose to use HypTrails, a Bayesian approach for expressing and comparing hypotheses about human trails. To formalize hypotheses we utilize data that is publicly available on the Web, namely Foursquare data and census data provided by an open data platform. By applying this combination of approaches to taxi data in Manhattan, we can discover and explain different patterns in human mobility that cannot be identified in a collective analysis. As one example, we can find a group of taxi rides that end at locations with a high number of party venues (according to Foursquare) on weekend nights. Overall, our work demonstrates that human mobility is not one-dimensional but rather contains different facets both in time and space which we explain by utilizing online data. The findings of this paper argue for a more fine-grained analysis of human mobility in order to make more informed decisions for e.g., enhancing urban structures, tailored traffic control and location-based recommender systems.
Improved chemotherapeutic efficacy of injectable chrysin encapsulated by copolymer nanoparticles

Chrysin is a flavone that is found in several plants and in honeycomb and possesses various biological activities. However, its low solubility means it has poor bioavailability, which must be resolved to enable its pharmaceutical applications. In the present study, chrysin was incorporated into methoxy poly(ethylene glycol)-β-polycaprolactone nanoparticles (chrysin-NPs) using the oil-in-water technique in order to overcome problems associated with chrysin. The properties of chrysin-NPs were analyzed, and their anticancer effects were investigated in vitro and in vivo. Chrysin-NPs were 77 nm sized (as determined by dynamic laser light scattering) and showed a monodisperse distribution. The zeta potential of chrysin-NPs was −2.22 mV, and they were spherically shaped by cryo-transmission electron microscopy (cryo-TEM). The loading efficiency of chrysin-NPs was 46.96%. Chrysin-NPs retained the cytotoxicity of chrysin in A549 cells. The therapeutic efficacies of chrysin-NPs were compared with those of chrysin in an A549-derived xenograft mouse model. Chrysin-NPs were intravenously injected at a 10 times lower dosage than chrysin 3 times per week (q2d×3/week). However, free chrysin was orally administrated 5 times per week (q1d×5/week). Chrysin-NP-treated group showed significant tumor growth delay, which was similar to that of chrysin-treated group, despite the considerably lower total dosage. These results suggest that the injectable chrysin-NPs enhance therapeutic efficacy in vivo and offer a beneficial formulation for chemotherapy.
Human-Robot User Studies in Eldercare: Lessons Learned

This paper describes our experiences in collecting user data on humanrobot interaction in nursing homes for the elderly. Learnings from two experiments were used to develop guidelines to support human-robot user studies with elderly users, in particular for experiments in an eldercare institution. Our experiences show that this demands a very strict organization, full cooperation by nursing personnel and extreme attention to informing the participants both before and during the experiment. Furthermore, first analysis of data from the studies suggests that social abilities in a robotic interface contribute to feeling comfortable talking to it and invite elders to be more expressive.
An Image Steganographic Scheme Based on Support Vector Regression

This paper presents a novel image steganographic method that utilizes support vector regression (SVR) to predict the embedded pixel value such that secret data is also embedded into the pixel-value difference between the predicted pixel value and the original pixel value. Due to the significant learning ability in the correlations of training samples by support vector regression, the trained SVR function is obtained by neighboring pixels of the sample pixels to predict the embedded pixel values, and then the proposed scheme uses pixel-value differences to embed the secret data. In the data extraction phase, the proposed scheme uses trained SVR function to predict the embedded pixel value, and the secret data is extracted from pixel-value differences. Experimental results show that SVR is good at learning the correlations of neighboring pixel, and the proposed scheme also has reliable security, high embedding capacity and better image quality for the stego-image.
A Sustainable Approach for Carbon Dioxide Fixation

Carbon dioxide is a green house gas that exists in earth’s atmosphere. In recent decade’s due to increment of population and rapid industrialization, the amount of CO2 has increased significantly and has caused global warming and other problems. Different methods are used for reduction of CO2 concentration in air one method is storing CO2 gas below the ground, but this manner doesn’t provide a long time solution, so in depth researches was conducted in the past years to investigate different methods of CO2 treatment. A noble method is using microalgae to reduce CO2 either from the atmosphere or fuel gases from energy plants. CO2 is captured by microalgae through photosynthesis and is permanently stored in form of biomass. Microalgae can also be used for treating wastewater that contains some amounts of CO2 and other compounds. Combination of CO2 treatment, biofuel production and wastewater treatment may provide a very promising alternative to current CO2 treatment strategies. This paper attempts to review the present day technologies for CO2 removal with a special emphasis on employing microalgae.
Relational Algebra Algorithms and Data Structures for GPU

Relational databases remain an important application domain for organizing and analyzing the massive volume of data generated as sensor technology, retail and inventory transactions, social media, computer vision, and new fields continue to evolve. At the same time, processor architectures are beginning to shift towards hierarchical and parallel architectures employing throughput-optimized memory systems, lightweight multi-threading, and Single-Instruction Multiple-Data (SIMD) core organizations. Examples include general purpose graphics processing units (GPUs) such as NVIDIA’s Fermi, Intels Sandy Bridge, and AMD’s Fusion processors. This paper explores the mapping of primitive relational algebra operations onto GPUs. In particular, we focus on algorithms and data structure design identifying a fundamental conflict between the structure of algorithms with good computational complexity and that of algorithms with memory access patterns and instruction schedules that achieve peak machine utilization. To reconcile this conflict, our design space exploration converges on a hybrid multi-stage algorithm that devotes a small amount of the total runtime to prune input data sets using an irregular algorithm with good computational complexity. The partial results are then fed into a regular algorithm that achieves near peak machine utilization. The design process leading to the most efficient algorithm for each stage is described, detailing alternative implementations, their performance characteristics, and an explanation of why they were ultimately abandoned. The least efficient algorithm (JOIN) achieves 57% − 72% of peak machine performance depending on the density of the input. The most efficient algorithms (PRODUCT, PROJECT, and SELECT) achieve 86% − 92% of peak machine performance across all input data sets. To the best of our knowledge, these represent the best known published results to date for any implementations. This work lays the foundation for the development of a relational database system that achieves good scalability on a Multi-level BulkSynchronous-Parallel (Multi-BSP) processor architecture exemplified by modern GPUs.
One seed to find them all: mining opinion features via association

Feature-based opinion analysis has attracted extensive attention recently. Identifying features associated with opinions expressed in reviews is essential for fine-grained opinion mining. One approach is to exploit the dependency relations that occur naturally between features and opinion words, and among features (or opinion words) themselves. In this paper, we propose a generalized approach to opinion feature extraction by incorporating robust statistical association analysis in a bootstrapping framework. The new approach starts with a small set of feature seeds, on which it iteratively enlarges by mining feature-opinion, feature-feature, and opinion-opinion dependency relations. Two association model types, namely likelihood ratio tests (LRT) and latent semantic analysis (LSA), are proposed for computing the pair-wise associations between terms (features or opinions). We accordingly propose two robust bootstrapping approaches, LRTBOOT and LSABOOT, both of which need just a handful of initial feature seeds to bootstrap opinion feature extraction. We benchmarked LRTBOOT and LSABOOT against existing approaches on a large number of real-life reviews crawled from the cellphone and hotel domains. Experimental results using varying number of feature seeds show that the proposed association-based bootstrapping approach significantly outperforms the competitors. In fact, one seed feature is all that is needed for LRTBOOT to significantly outperform the other methods. This seed feature can simply be the domain feature, e.g., "cellphone" or "hotel". The consequence of our discovery is far reaching: starting with just one feature seed, typically just the domain concept word, LRTBOOT can automatically extract a large set of high-quality opinion features from the corpus without any supervision or labeled features. This means that the automatic creation of a set of domain features is no longer a pipe dream!
Mathematical aspects of decentralized control of formations in the plane

In formation control, an ensemble of autonomous agents is required to stabilize at a given configuration in the plane, doing so while agents are allowed to observe only a subset of the ensemble. As such, formation control provides a rich class of problems for decentralized control methods and techniques. Additionally, it can be used to model a wide variety of scenarios where decentralization is a main characteristic. We introduce here some mathematical background necessary to address questions of stability in decentralized control in general and formation control in particular. This background includes an extension of the notion of global stability to systems evolving on manifolds and a notion of robustness of feedback control for nonlinear systems. We then formally introduce the class of formation control problems, and summarize known results.
How to implement the future?

This paper sheds light on the realities of implementing spanking new ideas in existing software systems. Information is provided both on the advantages and drawbacks of starting from scratch and basing yourself on an existing software asset to implement your IT future. The paper touches upon the need for tool support to refactor existing software systems so that implementing their IT future is enabled. An idea of how such refactory tools look like is given and pointers to technical research contributions are provided. Those tools aid in overcoming the maintenance debt built up over the years. It is argued that implementing the future in IT amounts to dealing with the past to a large extent.
A Multi-criteria Class-based Job Scheduler for Large Computing Farms

In this paper we propose a new multi-criteria class-based job scheduler able to dynamically schedule a stream of batch jobs on large-scale computing farms. It is driven by several configuration parameters allowing the scheduler customization with respect to the goals of an installation. The proposed scheduling policies allow to maximize the resource usage and to guarantee the applications QoS requirements. The proposed solution has been evaluated by simulations using different streams of synthetically generated jobs. To analyze the quality of our solution we propose a new methodology to estimate whether at a given time the resources in the system are really sufficient to meet the service level requested by the submitted jobs. Moreover, the proposed solution was also evaluated comparing it with the Backfilling and Flexible backfilling algorithms. Our scheduler demonstrated to be able to carry out good scheduling choices.
Machupo Virus Glycoprotein Determinants for Human Transferrin Receptor 1 Binding and Cell Entry

Machupo virus (MACV) is a highly pathogenic New World arenavirus that causes hemorrhagic fever in humans. MACV, as well as other pathogenic New World arenaviruses, enter cells after their GP1 attachment glycoprotein binds to their cellular receptor, transferrin receptor 1 (TfR1). TfR1 residues essential for this interaction have been described, and a co-crystal of MACV GP1 bound to TfR1 suggests GP1 residues important for this association. We created MACV GP1 variants and tested their effect on TfR1 binding and virus entry to evaluate the functional significance of some of these and additional residues in human and simian cells. We found residues R111, D123, Y122, and F226 to be essential, D155, and P160 important, and D114, S116, D140, and K169 expendable for the GP1-TfR1 interaction and MACV entry. Several MACV GP1 residues that are critical for the interaction with TfR1 are conserved among other New World arenaviruses, indicating a common basis of receptor interaction. Our findings also open avenues for the rational development of viral entry inhibitors.
Financial Valuation and Risk Management Working Paper No . 431 Financial Market Equilibria with Cumulative Prospect Theory

The paper shows that financial market equilibria need not exist if agents possess cumulative prospect theory preferences with piecewise-power value functions. The reason is an infinite short-selling problem. But even when a short-sell constraint is added, non-existence can occur due to discontinuities in agents demand functions. Existence of equilibria is established when short-sales constraints are imposed and there is also a continuum of agents in the market.
Vector Space Model based on Semantic Attributes of Words.

従来, ベクトル空間法において, ベクトルの基底数を削減するため, ベクトルの基軸を変換する方法が提案されている. この方法の問題点として, 計算量が多く, 大規模なデータベースへの適用が困難であるこトが挙げられる. これに対して, 本論文では, 特性ベクトルの基底として, 単語の代わりに単語の意味属性 (「日本語語彙大系」で規定された約2, 710種類) を使用する方法を提案する. この方法は, 意味属性間の包含関係に基づいた汎化が可能で計算コストもきわめて少なく, 容易にベクトルの次元数を圧縮できることが期待される. また, 単語の表記上の揺らぎに影響されず, 同義語, 類義語も考慮されるため, 従来の単語を基底とする文書ベクトル空間法に比べて, 検索漏れを減少させることが期待される. BMIR-J2の新聞記事検索 (文書数約5,000件) に適用した実験結果によれば, 提案した方法は, 次元数の削減に強い方法であり, 検索精度をあまり落とすことなく, 文書ベクトルの基底数を300～600程度まで削減できることが分かった. また, 単語を基底とした文書ベクトルの方法と比べて高い再現率が得られることから, キーワード検索におけるKW拡張と同等の効果のあることが分かった.