Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-aware Service Allocation for Cloud Computing

Energy efficiency has become an important managerial variable of IT management. Whereas cloud computing promises significantly higher levels of energy efficiency, it is still not known, if and to what extent outsourcing of software applications to cloud service providers affects the overall energy effi- ciency. This research is concerned with the allocation of cloud services from providers to customers and addresses the problem of energy-aware service allo- cation. The distributed nature of the problem, i.e., the multiple loci of control, entails the failure of centralised solutions. Hence, we approach this problem from a multiagent system perspective, which preserves the distributed setting of multiple service providers and customers. The contribution of our research is a game-theoretic framework for analysing service provider and customer interac- tions and a novel distributed allocation mechanism based on this framework to approximate energy-efficient, optimal allocations. We demonstrate the useful- ness and efficacy of the proposed artifact in several simulation experiments.
Call-level and packet-level performance modeling in cellular CDMA networks

We present a queueing analytical model to evaluate call-level and packet-level performances for uplink transmission of data calls in a voice/data cellular CDMA network. In the call-level, call admission control (CAC) is used to ensure that the cell is not overloaded and also to prioritize the handoff calls over the new calls. We assume finite queueing at the mobile to buffer the data packets for uplink transmission. The transmission rates for data calls can be adjusted to accommodate more voice and/or data calls while satisfying a minimum signal-to-interference (SIR)/rate requirement for voice/data calls. Call-level performance measures (i.e., new call blocking and handoff call dropping probabilities) for both voice and data calls and packet-level performance measures (i.e., queue throughput, packet dropping probability and delay) specifically for data calls can be obtained from our model. Impacts of the call-level parameter settings on the packet-level performance measures are investigated and typical numerical results are presented
Forecasting Compositional Time Series with Exponential Smoothing Methods

Compositional time series are formed from measurements of proportions that sum to one in each period of time. We might be interested in forecasting the proportion of home loans that have adjustable rates, the proportion of nonagricultural jobs in manufacturing, the proportion of a rock's geochemical composition that is a specific oxide, or the proportion of an election betting market choosing a particular candidate. A problem may involve many related time series of proportions. There could be several categories of nonagricultural jobs or several oxides in the geochemical composition of a rock that are of interest. In this paper we provide a statistical framework for forecasting these special kinds of time series. We build on the innovations state space framework underpinning the widely used methods of exponential smoothing. We couple this with a generalized logistic transformation to convert the measurements from the unit interval to the entire real line. The approach is illustrated with two applications: the proportion of new home loans in the U.S. that have adjustable rates; and four probabilities for specified candidates winning the 2008 democratic presidential nomination.
Comparison of motor-based versus visual sensory representations in object recognition tasks

Comparison of Motor-based versus Visual Sensory Representations in Object Recognition Tasks. (August 2005) Navendu Misra, B.S., The University of Texas at Austin Chair of Advisory Committee: Dr. Yoonsuck Choe Various works have demonstrated the usage of action as a critical component in allowing autonomous agents to learn about objects in the environment. The importance of memory becomes evident when these agents try to learn about complex objects. This necessity primarily stems from the fact that simpler agents behave reactively to stimuli in their attempt to learn about the nature of the object. However, complex objects have the property of giving rise to temporally varying sensory data as the agent interacts with the object. Therefore, reactive behavior becomes a hindrance in learning these complex objects, thus, prompting the need for memory. A straight forward approach to memory, visual memory, is where sensory data is directly represented. Another mechanism is skill-based memory or habit formation. In the latter mechanism the sequence of actions performed for a task is retained. The main hypothesis of this thesis is that since action seems to play an important role in simple perceptual understanding it may also serve as a good memory representation. In order to test this hypothesis a series of comparative tests were carried out to determine the merits of each of these representations. It turns out that skill memory performs significantly better at recognition tasks than visual memory. Furthermore, it was demonstrated in a related experiment that action forms a good intermediate representation of the sensory data. This provides support to theories that propose that various sensory modalities can ideally be represented in terms of action. This thesis successfully extends action to the role of understanding of complex objects.
E-Business applications in Polish SME sector – condition and developmen

An active sector of small and medium enterprises (SME) in Poland is a prerequisite of a properly functioning market economy. This sector encompasses various companies. The ICT (Information and Communication Technology) can help even the odds. We have conducted a questionnaire-based survey to identify how polish SMEs perceive this phenomenon of eBusiness systems.
Distinct Effects of EGFR Ligands on Human Mammary Epithelial Cell Differentiation

Based on gene expression patterns, breast cancers can be divided into subtypes that closely resemble various developmental stages of normal mammary epithelial cells (MECs). Thus, understanding molecular mechanisms of MEC development is expected to provide critical insights into initiation and progression of breast cancer. Epidermal growth factor receptor (EGFR) and its ligands play essential roles in normal and pathological mammary gland. Signals through EGFR is required for normal mammary gland development. Ligands for EGFR are over-expressed in a significant proportion of breast cancers, and elevated expression of EGFR is associated with poorer clinical outcome. In the present study, we examined the effect of signals through EGFR on MEC differentiation using the human telomerase reverse transcriptase (hTERT)-immortalized human stem/progenitor MECs which express cytokeratin 5 but lack cytokeratin 19 (K5+K19- hMECs). As reported previously, these cells can be induced to differentiate into luminal and myoepithelial cells under appropriate culture conditions. K5+K19- hMECs acquired distinct cell fates in response to EGFR ligands epidermal growth factor (EGF), amphiregulin (AREG) and transforming growth factor alpha (TGFα) in differentiation-promoting MEGM medium. Specifically, presence of EGF during in vitro differentiation supported development into both luminal and myoepithelial lineages, whereas cells differentiated only towards luminal lineage when EGF was replaced with AREG. In contrast, substitution with TGFα led to differentiation only into myoepithelial lineage. Chemical inhibition of the MEK-Erk pathway, but not the phosphatidylinositol 3-kinase (PI3K)-AKT pathway, interfered with K5+K19- hMEC differentiation. The present data validate the utility of the K5+K19- hMEC cells for modeling key features of human MEC differentiation. This system should be useful in studying molecular/biochemical mechanisms of human MEC differentiation.
SoDA: Enabling CDN-ISP collaboration with software defined anycast

Content Delivery Networks (CDNs) carry an increasing traffic share due to the performance benefits enabled by a global deployment of proxy servers and a request-routing mechanism mapping clients to the closest CDN proxy. The standard approach to map clients/proxies is based on Over the Top (OTT) information such as delay measurements. As this approach is challenging with respect to finding the best network path, more recent Anycast CDN (A-CDN) architectures adopt Internet Protocol (IP) anycast routing. IP anycast gives the control of proxy selection completely to the network, while the standard approach gives the full control to the application. There is no middle ground enabling the use of both sets of information. Consequently, this work proposes Software Defined Anycast (SoDA) to fill the gap. SoDA enables anycast routing based on a thin layer of Software Defined Networking (SDN) functionality. Our approach allows CDN providers to take influence on anycast routing and enables collaborative load balancing at a constant SDN rule count. SoDA is shown to offer more fair resource usage at a better performance for Internet Service Providers (ISPs) and CDN providers by using a number of fine grained data sets from a large European tier-1 ISP for evaluation.
Signal‐sensing mechanisms of the putative osmosensor KdpD in Escherichia coli

The KdpD protein is a membrane‐located sensory kinase (or signal transducer) critically involved in the regulation of the kdpABC operon that is responsible for a high‐affinity transport system in Escherichia coli. In this study, a set of KdpD mutants, each resulting in a single amino acid substitution around the membrane‐spanning regions of KdpD, was isolated. Amino acid substitutions in these KdpD mutants were located non‐randomly, particularly within the C‐terminal half of the membrane‐spanning regions. This set of KdpD mutants exhibited altered transmembrane‐signalling properties in response to external K+ and other stimuli. In particular, these mutants were found to be insensitive, if not completely, to the K+ signal. However, they were able to respond to other stimuli such as high‐salt stress, as in the wild type. Therefore, in contrast to the wild type, the cells carrying these mutations exhibited high levels of the steady‐state expression of kdp, regardless of external K+, provided that high concentrations of ionic solutes were supplemented to the cultures. More interestingly, the set of KdpD mutants could also respond to high concentrations of external non‐ionic solutes such as sucrose and D‐arabinose, thereby increasing substantially the steady‐state expression of kdp in response to the medium osmolarity. Furthermore, it was found that certain chemicals, ethanol, chlorpromazine and procaine, could function as effectors for the KdpD mutants at relatively low concentrations in the media. Based on these findings, we have examined the primary signal(s) that regulates the function of KdpD. We propose here that KdpD can be considered to be an environmental sensor that exhibits sensing mechanisms in response to both the level of K+ and the physico‐chemical state of the cytoplasmic membrane.
An Improved Regression Test Selection Technique by Clustering Execution Profiles

In order to improve the efficiency of regression testing, many test selection techniques have been proposed to extract a small subset from a huge test suite, which can approximate the fault detection capability of the original test suite for the modified code. This paper presents a new regression test selection technique by clustering the execution profiles of modification-traversing test cases. Cluster analysis can group program executions that have similar features, so that program behaviors can be well understood and test cases can be selected in a proper way to reduce the test suite effectively. An experiment with some real programs is designed and implemented. The experiment results show that our approach can produce a smaller test suite with most fault-revealing test cases in comparison with existing selection techniques.
Calibrating Energy-based Generative Adversarial Networks

In this paper, we propose to equip Generative Adversarial Networks with the ability to produce direct energy estimates for samples. Specifically, we propose a flexible adversarial training framework, and prove this framework not only ensures the generator converges to the true data distribution, but also enables the discriminator to retain the density information at the global optimal. We derive the analytic form of the induced solution, and analyze the properties. In order to make the proposed framework trainable in practice, we introduce two effective approximation techniques. Empirically, the experiment results closely match our theoretical analysis, verifying the discriminator is able to recover the energy of data distribution.
NEFRL: A New Neuro-Fuzzy System for Episodic Reinforcement Learning Tasks

In this paper, we propose a new neuro-fuzzy system for episodic reinforcement learning tasks, NEFRL. While NEFRL has all benefits of a neuro-fuzzy architecture, it has the additional advantage that it can learn with a numerical evaluation of performance and there is no need for training input-output pairs. Also, we show that the learning algorithm of this system converges with probability one to a local maximum of the average numerical performance signal. Our experimental results for the pole-balancing task show the power of this system even without any prior domain knowledge.
Immigrants’ Access to Health Insurance: No Equality without Awareness

The Czech government has identified commercial health insurance as one of the major problems for migrants’ access to health care. Non-EU immigrants are eligible for public health insurance only if they have employee status or permanent residency. The present study examined migrants’ access to the public health insurance system in Czechia. A cross-sectional survey of 909 immigrants from Ukraine and Vietnam was conducted in March and May 2013, and binary logistic regression was applied in data analysis. Among immigrants entitled to Czech public health insurance due to permanent residency/asylum, 30% were out of the public health insurance system, and of those entitled by their employment status, 50% were out of the system. Migrants with a poor knowledge of the Czech language are more likely to remain excluded from the system of public health insurance. Instead, they either remain in the commercial health insurance system or they simultaneously pay for both commercial and public health insurance, which is highly disadvantageous. Since there are no reasonable grounds to stay outside the public health insurance, it is concluded that it is lack of awareness that keeps eligible immigrants from entering the system. It is suggested that no equal access to health care exists without sufficient awareness about health care system.
Global Interconnect Analysis and Optimization for Nanometer Scale VLSI

The width of an interconnect and its spacing to neighboring interconnects affect greatly the delay and power dissipation of the line. Increasing the line width simply can reduce the delay but increase the power dissipation for a single line. If the line spacing is also increased appropriately, the power dissipated due to increasing the line width can be offset, even the power dissipation decrease. However, this improvement in the delay and power dissipation will conflict to the bandwidth. Therefore, a novel and efficient delay-power-reciprocal bandwidth tradeoff formulation is developed to optimize the width and spacing of global interconnects with repeaters for various ITRS nodes
Filipino Domestic Workers and Their Capacity Development

This study explored the day-to-day experiences of female Filipino domestic workers in Singapore, including their working conditions, employee–employer relationships, and psychological health. In-depth interviews were conducted with 18 women. Using grounded theory, the emergent themes revealed high levels of variation, both within and between women, suggesting that the quality of domestic workers’ lives depends largely on the personal characteristics of their employers or the workers themselves, rather than on any system of protection. More importantly, participants displayed positive and resilient coping strategies which enabled them to thrive despite restrictive circumstances. Implications pertaining to capabilities and empowerment development were discussed.
Endothelial FoxO proteins impair insulin sensitivity and restrain muscle angiogenesis in response to a high‐fat diet

Skeletal muscle microvascular dysfunction contributes to disease severity in type 2 diabetes. Recent studies indicate a role for Forkhead box O (FoxO) transcription factors in modulating endothelial cell phenotype. We hypothesized that a high‐fat (HF) diet generates a dysfunctional vascular niche through an increased expression of endothelial FoxO. FoxO1 protein increased (+130%) in the skeletal muscle capillaries from HF compared to normal chow‐fed mice. FoxO1 protein was significantly elevated in cultured endothelial cells exposed to the saturated fatty acid palmitate or the proinflammatory cytokine TNF‐α. In HF‐fed mice, endothelium‐directed depletion of FoxO1/3/ 4(FoxOD) improved insulin sensitivity (+110%) compared to that of the controls (FoxOL/L). The number of skeletal muscle capillaries increased significantly in the HF‐FoxOD mice. Transcript profiling of skeletal muscle identified significant increases in genes associated with angiogenesis and lipid metabolism in HF‐FoxOD vs. HF‐FoxOL/L mice. HF‐FoxOD muscle also was characterized by a decrease in inflammation‐related genes and an enriched M2 macrophage signature. We conclude that endothelial FoxO proteins promote insulin resistance in HF diet, which may in part result from FoxO proteins establishing an antiangiogenic and proinflammatory microenvironment within skeletal muscle. These findings provide mechanistic insight into the development of microvascular dysfunction in the progression of type 2 diabetes. —Nwadozi, E. , Roudier, E. , Rullman, E. , Tharmalingam, S. , Liu, H. ‐Y. , Gustafsson, T. , Haas, T. L. Endothelial FoxO proteins impair insulin sensitivity and restrain muscle angiogenesis in response to a high‐fat diet. FASEB J. 30, 3039–3052 (2016). www.fasebj. org
Cloning, expression, and sequencing of a protease gene from Bacteroides forsythus ATCC 43037 in Escherichia coli

We have isolated and characterized an N-benzoyl-Val-Gly-Arg-p-nitroanilide-specific protease gene, designated prtH, from Bacteroides forsythus ATCC 43037. Nucleotide sequencing of the DNA insert from the clone (hereafter referred to as clone FST) revealed that the protease activity corresponded to an open reading frame consisting of 1,272 bp coding for a 47.8-kDa protein. When plasmid pFST was used as a probe in Southern hybridization, Sau3AI-digested chromosomal DNA of B. forsythus ATCC 43037 as well as the chromosomal DNAs of the isolated strains Ta4, TR5, and YG2 showed 0.6- and 0.8-kb hybridizing bands. The cell-free extracts of clone FST showed hemolytic activity on human blood cells. The hydrolytic activity of cell extracts of the pFST clone was inhibited by p-toluenesulfonyl-L-lysine chloromethyl ketone hydrochloride, leupeptin, N-ethylmaleimide, iodoacetic acid, iodoaceteamide, and EDTA.
The effects of multiple team membership on networking online and offline: using multilevel multiple membership modeling

ABSTRACT When organizations use multiple team membership (MTM) to enhance efficient use of resources, workers in multiple teams develop networks that expand across team boundaries and are linked to teams at a higher level. On such complexity in multilevel networked organizations, we investigate how MTM and team characteristics shape individual-level networks both online and offline. We explain and use the relatively new approach of multilevel multimember modeling (MMMM) to consider how the diversity of teams is related to individual behaviors and networks. Studying a large trans-Canadian network of scholars making and studying digital media, we find that MTM and diversity in teams have a positive impact on the development of diverse ego networks online (email) rather than offline (in person). We also discuss the broader implications of MMMM for understanding the ways in which networked organizations operate.
Multinational Ownership and Subsidiary Investment

This paper examines how foreign ownership affects the investment decisions of subsidiary firms using a new dataset of listed-parent âˆ’ listed-subsidiary pairs. We find that improvements in the investment opportunities of parent firms have a negative effect on the investment of their subsidiaries, after controlling for the investment opportunities of the subsidiary, which can be independently observed. This provides evidence of internal capital markets in multinationals that reallocate funds towards units with better investment opportunities. We also find that the negative effect of the parentâ€™s investment opportunities on subsidiary investment is greatest where the relationship is more arms-length, i.e. where parents have modest ownership stakes, are distant from their subsidiaries or when subsidiaries â€“ as well as parents â€“ operate in well developed financial markets.
Drug product development and pharmacological evaluation of a sparingly soluble novel camptothecin analog for peroral administration

This work focused on the developmental aspects, pharmacokinetic evaluation, and pharmacological assessment of a drug inclusion complex for a novel camptothecin analog (CA) and 2-hydroxypropyl-β-cyclodextrin (HP-β-CD). Camptothecins analog belong to topoisomerase-I inhibitor class of compounds with proven anti-tumor activity but exhibit poor solubility. To enhance solubility a drug inclusion complex with cyclodextrin was developed using a spray-drying process. The powder complex characterized using DSC, XRPD, FT-IR, and 1H NMR techniques confirmed interaction of cyclodextrin with the CA indicating formation of a true complex wherein the drug is encapsulated in the cyclodextrin cavity. The saturation solubility and dissolution kinetics of drug complex evaluated in a discriminating medium showed significantly higher solubility and faster dissolution as compared to a physical mixture or powder blend comprising of drug and cyclodextrin. Pharmacokinetic (PK) studies in Wistar rats indicated a significant increase in the rate and extent of absorption for the drug complex as compared to a nanoparticulate dispersion that was used as the positive control. Pharmacological activity following peroral administration of drug complex in athymic nude mice with implanted tumors revealed that the tumor inhibition activity was equivalent to commercially available intravenous (IV) formulation with comparable safety profile. These studies demonstrated for the first instance feasibility of developing a safe and efficacious peroral formulation for a sparingly soluble camptothecin analog that may provide another viable, patient compliant, and cost effective option for the treatment of solid tumors.
Systematic rewiring in associative neural networks with small-world architecture

It is a known fact that a small amount of randomly rewired connections greatly improves the performance of associative neural network with regular architecture, still preserving its attractive features such as local connectivity and small total connection length. In this paper we propose the systematic way of connection rewiring which further improves the associative properties of the network using the same amount of rewiring.