Miracle-dz/UniFAR-FTUs huggingface dataset:
Discrete-Rate Adaptation and Selection in Energy Harvesting Wireless Systems

In a system with energy harvesting (EH) nodes, the design focus shifts from minimizing energy consumption by infrequently transmitting less information to making the best use of available energy to efficiently deliver data while adhering to the fundamental energy neutrality constraint. We address the problem of maximizing the throughput of a system consisting of rate-adaptive EH nodes that transmit to a destination. Unlike related literature, we focus on the practically important discrete-rate adaptation model. First, for a single EH node, we propose a discrete-rate adaptation rule and prove its optimality for a general class of stationary and ergodic EH and fading processes. We then study a general system with multiple EH nodes in which one is opportunistically selected to transmit. We first derive a novel and throughput-optimal joint selection and rate adaptation rule (TOJSRA) when the nodes are subject to a weaker average power constraint. We then propose a novel rule for a multi-EH node system that is based on TOJSRA, and we prove its optimality for stationary and ergodic EH and fading processes. We also model the various energy overheads of the EH nodes and characterize their effect on the adaptation policy and the system throughput.
Essays in macroeconomics with heterogeneous agents

This doctoral dissertation consists of the intersection of dynamic stochastic general equilibrium modeling, including heterogeneous agents, and the subjects of public finance and labor economics. The first chapter explains a puzzling empirical phenomenon regarding fertility rate in the United States. Over the last few decades, high-income females have demonstrated a tendency to have more children in the U.S. At the same time, household income structure has changed, becoming more unequal and more favorable to females. However, these changes appear contradictory to the predictions found in classical fertility literature, which suggest that high-income women exhibit low fertility due to the high opportunity cost of raising children. To account for this puzzling empirical phenomenon, we offer a fertility choice model with preference heterogeneity on having children, which allows for a comparative advantage between employment outside the home and child-rearing. We highlight the composition effect of females who desire children newly entering the high-income group, while females less desirous of children exit as the income structure changes. Our model accounts for 55% of the observed variation in the complete fertility rate, while the comparable model without composition effect fails to explain the observation. We also decompose various income shocks and find that changes in skill premium represent the major factor behind the phenomenon. The second chapter examines the quantitative effects of population aging driven by declining mortality and fertility rates. We also studies the macroeconomic effects of raising the mandatory retirement age in such an aging economy. When the mortality rate decreases, aggregate capital increases since individuals save more for a longer retirement. In contrast, an increase in aggregate labor input is negligible since lower mortality rates primarily affect those who are out of the labor force. When
An Algorithm for Merging Hyperellipsoidal Clusters

This report discusses an algorithm for merging hyperellipsoidal clusters The e ective merging radius between two clusters is introduced and this measure is used to determine the order in which clusters are combined We continue to merge clusters until a desired number of clusters is reached or until the minimum e ective merging radius is larger than some predetermined threshold
Analysis of serving discipline algorithms for cellular networks

As user requests arrive randomly in a wireless network, a good serving discipline scheme optimizes the trade-off between resource utilization and quality of service by effectively predicting future demands. In this paper, we analyze research outputs on serving discipline algorithms for cellular networks. The contribution of this paper is two-fold: first we review different serving discipline schemes and we choose the one which we believe is a good scheme. Then we propose an improvement on it and we validate our argument through simulation using the Network Simulator (NS-2).
Measuring the Success of Telecom Regulation: A Balanced Scorecard Approach

One of the most widely debated subjects in the field of telecom business is the role of regulation in the evolution of the fixed and mobile telecom industry. Strong arguments have been presented against too aggressive regulation [37, 39,40] but also in favor of an active role of the government in protecting the interests of consumers and business customers against potential misuse of monopoly power in the telecom markets. It is easy to see how different stakeholders (e.g., telecom network and service operators, various government bodies participating in the process of telecom regulation, consumers, and business customers) interpret the very same facts and figures in a very different – and sometimes even opposite – ways. Furthermore, even within a given stakeholder group, such as telecom operators or regulatory authorities, it is easy to detect strategic behavior depending on factors such as operators' market position or growth strategies, or political ambitions of various regulatory bodies. Against this background it is easy to understand how big a challenge it is for national regulatory authorities (NRAs) to find a balance between numerous and often contradictory interests and goals of various stakeholders. So what do we know about the role of telecom regulation. In their recent report " Regulation that's good for competition " , consulting company McKinsey described the goal of economic regulation in the following way: " The aim of economic regulation should be the same in all sectors: to facilitate fair competition among players or, where natural monopolies exist, to ensure fair pricing and service levels. Greater competition means stronger growth, which in turn means a faster-growing economy and more wealth to share. " [2] Despite these noble and widely accepted goals, the McKinsey article points out that governments everywhere " struggle to get regulation right " [2]. 3 Regulation costs are high Although regulation aims at providing us citizens with protection against large telecom operators and their evil plans to grab an increasing share of our wallets, this kind of service has its cost. The British " Better Regulation Task Force " (BRTF) emphasizes the fact that regulation " represents a significant cost for the economy " [26]. They point out that the cost of regulation " is borne by government, regulators and those being regulated. " Especially the last item on the list is somewhat peculiar; no wonder you can sometimes hear people from teleoperators making jokes about how …
Energy-efficient cluster-based protocol using an adaptive data aggregative window function (A-DAWF) for wireless sensor networks

We present an adaptive data aggregative window function (A-DAWF) for a distributed sensor network model in which nodes store data in their attribute window functions, and provide non-correlated data towards the base station (BS). Unlike previous works, namely data collection or data gathering management systems, we propose a novel approach that aims to process temporal redundant techniques in sensor nodes as well as providing spatial redundant filtration methods in cluster-head (CH) nodes. In this regard, preliminary results show that A-DAWF can suppress up to 90% of temporal redundant data among the considered sensor nodes by an optimal threshold of the window sizes, and their spatial correlations in CH node by a maximum error threshold compared to either periodic or a continuous data transmission system.
IMBALANCED DATASET CLASSIFICATION AND SOLUTIONS : A REVIEW

--- Imbalanced data set problem occurs in classification, where the number of instances of one class is much lower than the instances of the other classes. The main challenge in imbalance problem is that the small classes are often more useful, but standard classifiers tend to be weighed down by the huge classes and ignore the tiny ones. In machine learning the imbalanced datasets has become a critical problem and also usually found in many applications such as detection of fraudulent calls, bio-medical, engineering, remote-sensing, computer society and manufacturing industries. In order to overcome the problems several approaches have been proposed. In this paper a study on Imbalanced dataset problem and the solution is given.
Scaling-up Proven Education Interventions: Evidence from an RCT in Kenya (IGC Working Paper)

Contract teachers have been shown to significantly raise test scores for primary students in previous randomized trials in both Western Kenya (Duflo, Dupas and Kremer 2009) and various locations in India (Banerjee, Cole, Duflo and Linden 2007, Muralidharan and Sundararaman 2010). We report on the initial, randomized phase of a Kenyan government program to scale-up the contract teacher model by (a) expanding geographically across all eight Kenyan provinces, and (b) shifting implementation from NGOs to the Ministry of Education. Overall, we find a significant, positive e↵ect of 0.12 standard deviations on combined math and English scores across all treatment arms. Geographic heterogeneity in treatment e↵ects does not appear to pose a significant threat to the external validity of earlier studies; e↵ects are somewhat larger for schools with lower initial scores. However, overall e↵ects were entirely due to a 0.19 standard deviation increase in scores in the randomly assigned sub-group of treatment schools where the contract teacher program was administered by an international NGO. E↵ects were significantly smaller and indistinguishable from zero in schools where the program was administered by the Ministry of Education. Evidence suggests this performance gap may reflect challenges faced by the Ministry in centrally administering a program that involved local recruitment and monitoring of contract teachers. ⇤We are indebted to the sta↵ of the Ministry of Education, the National Examination Council, and World Vision Kenya who planned and executed this project, and in particular to Mukhtar Ogle and Salome Ong’ele for their leadership throughout the process. We acknowledge the financial support of the UK Department for International Development (DFID) as part of the “Improving Institutions for Pro-Poor Growth” (iiG) research consortium, the International Growth Centre (IGC), and the PEP-AUSAID Policy Impact Evaluation Research Initiative (PERI). The views expressed here are the authors’ alone. †Bold: Institute for International Economic Studies, Stockholm University, tessa.bold@iies.su. se. Kimenyi: Brookings Institution, Washington D.C., kimenyi@brookings.edu. Mwabu: Department of Economics, University of Nairobi, gmwabu@gmail.com. Ng’ang’a: Strathmore University, Nairobi, alicemnganga@yahoo.com. Sandefur: Center for Global Development, Washington D.C., jsandefur@cgdev.org. 1
Actin Fusion Proteins Alter the Dynamics of Mechanically Induced Cytoskeleton Rearrangement

Mechanical forces can regulate various functions in living cells. The cytoskeleton is a crucial element for the transduction of forces in cell-internal signals and subsequent biological responses. Accordingly, many studies in cellular biomechanics have been focused on the role of the contractile acto-myosin system in such processes. A widely used method to observe the dynamic actin network in living cells is the transgenic expression of fluorescent proteins fused to actin. However, adverse effects of GFP-actin fusion proteins on cell spreading, migration and cell adhesion strength have been reported. These shortcomings were shown to be partly overcome by fusions of actin binding peptides to fluorescent proteins. Nevertheless, it is not understood whether direct labeling by actin fusion proteins or indirect labeling via these chimaeras alters biomechanical responses of cells and the cytoskeleton to forces. We investigated the dynamic reorganization of actin stress fibers in cells under cyclic mechanical loading by transiently expressing either egfp-Lifeact or eyfp-actin in rat embryonic fibroblasts and observing them by means of live cell microscopy. Our results demonstrate that mechanically-induced actin stress fiber reorganization exhibits very different kinetics in EYFP-actin cells and EGFP-Lifeact cells, the latter showing a remarkable agreement with the reorganization kinetics of non-transfected cells under the same experimental conditions.
Anti-inflammatory effects of essential oil, aerial parts and hairy roots extracts of Nepeta pogonosperma on rat brain mixed cells

and objectives: Many Nepeta species have been commonly used in Iranian folk medicine as tranquilizer, relaxant, carminative and restorative tonic for nervous and respiratory disorders. Inflammation is a problem in many diseases and has an important role in brain function that can cause neurodegenerative disorders. Inflamed glial cells can exacerbate neurodegenerative diseases by producing neurotoxins. In the present study, the anti-inflammatory effects of essential oil, aerial parts and hairy roots extracts of Nepeta pogonosperma Jamzad & Assadi have been evaluated on rat brain mixed cells. Methods: Inflamed mixed glial cells from rats' brains were treated with different concentrations of essential oil and extracts from aerial parts and hairy roots of Nepeta pogonosperma to evaluate their anti-inflammatory effects. No level as the indicator for inflammation was measured. Results: The results revealed that 0.5 µL/mL of the essential oil reduced NO production significantly. In addition, some hairy root extract concentrations led to reduce it, although the extract of the aerial parts of the plant did not affect NO production. Conclusion: This research has confirmed the anti- inflammatory potential of essential oil and hairy root extract of Nepeta pogonosperma on rat brain mixed cells.
Functionally Suppressive CD8 T Regulatory Cells Are Increased in Patients with Multiple Myeloma: A Cause for Immune Impairment

Background Multiple myeloma (MM) is a plasma cell malignancy frequently associated with impaired immune cell numbers and functions. In MM, several studies have previously shown that CD4 regulatory T (Treg) cells hamper effector T cell functions and enhance immune dysfunction. In this study, we aimed to prove the presence of functionally suppressive Treg cells expressing CD8 phenotype (CD8 Treg cells) in MM. To the best of our knowledge, this has not been reported previously in MM. Methods We analyzed CD8 Treg cells and their transcription factor FoxP3 from 64 newly diagnosed MM patients using flow cytometry and real time-polymerase chain reaction (RT-PCR). RNA profile of cytokines in CD8 Treg cells was also assessed using RT-PCR. CD8 Treg cells from 5 MM patients and 5 healthy donors were functionally evaluated using proliferation assays. Results CD8 Treg cells (CD8+CD25hi+) were significantly elevated in MM patients (P<0.0001), and their transcription factor FoxP3 expression was also higher in MM (P<0.0001) compared to healthy donors which was evidenced by flow cytometry and RT-PCR analyses. CD8 Treg cells negatively correlated with total lymphocyte count (P = 0.016). Functional studies revealed that CD8 Treg cells isolated from MM patients and healthy donors inhibited proliferation of CD4 T cells in a concentration dependent manner. In the presence of CD8 Treg cells in proliferation assays, level of IFN-γ was decreased but not IL-10. CD4 T cells from MM patients secreted abnormal level of IL-10 compared to healthy donors (P = 0.01) in proliferation assays without CD8 Treg cells. RNA profile of cytokines from CD8 Treg cells did not differ significantly between MM patients and healthy donors. Conclusions These findings show the presence of increased number of functionally suppressive CD8 Treg cells in MM patients. We believe that these suppressive CD8 Treg cells might enhance immune impairment and disease progression in MM.
Defense against Routing Disruption Denial-of- Service Attacks in Mobile Ad Hoc Networks

Mobile Ad hoc NETworks (MANETs) are decentralized environments comprised of mobile computing devices that interact among each other via multi-hop wireless links. MANET nodes forward packets on behalf of other nodes in the network. Such routing decisions are made autonomously by individual nodes. MANET characteristics make them highly vulnerable to a myriad of physical and cyber attacks. Cryptographic solutions, while effective for maintaining confidentiality and authentication, cannot mitigate some critical attacks on MANET availability, in particular insider and protocol-compliant routing disruption Denial-of-Service (DoS) attacks. This paper proposes a novel secure routing architecture for MANET called ThroughpUt-Feedback (TUF) routing, which is designed to be resilient against most known forms of routing disruption DoS attacks. Our approach is to monitor the end-to-end "good" throughput (or "goodput") of closed-loop flows to detect attacks that are impossible to detect using existing methods operating at the network layer. A major advantage of the TUF architecture is that it can be readily integrated into on-demand source routing protocols. TUF provides mechanisms that monitor the goodput of the current route to detect abnormalities (e.g., node or link failures, DoS attacks, etc.), and then initiates a route rebuilding process once the route has been determined to be abnormal. TUF is agile in that it is designed in a way that allows it to limit control overhead by using low-overhead schemes until an attack condition requires the use of higher-overhead route management schemes. Using analysis and simulations, we show that the TUF architecture is resilient against a wide range of attacks, including protocol-compliant (also known as "JellyFish") attacks.
Evolving Small-World Networks based on the Modified BA Model

In order to mimic complex real-life systems, in this paper, we propose evolving small-world networks based on the modified BA model. In the process of network evolution, the links among the new nodes at each time step are involved, which is different from the classic BA model. The simulation results show our model exhibits the small-world property and the scale-free structure. Since most real networks are both scale-free and small-world networks, our model may provide a satisfactory description for empirical characteristics of real networks.
Wage Dispersion, Public Sector Wages and the Stagnating Danish Gender Wage Gap

The Gender wage gap in Denmark has virtually stagnated since the early 1970's. This study examines whether this stagnation is mainly due to a changing wage dispersion or to changing prices on observed and unobserved skills. Since about half of the female labour force is employed in the public sector, the impact of the changing wage structure between the public and private sectors is investigated. The analysis is based on the Juhn-Murphy-Pierce decomposition applied to a pooled wage regression model. The equivalence between the former and the Oaxaca-Ransom generalized wage decomposition is established. These techniques are applied to a sample of Danish wage earners in the period 1983-94. The decomposition results suggest different explanations bethind the stagnation of the gender wage gap in the public and private sectors. The development in average public sector wages is calculated assuming observed and unobserved private sector prices are in effect.
Illustrative Scientific Visualization Framework

Current scientific visualization techniques create complex images that may be difficult to interpret and do not have the expressiveness of illustrations. Incorporating traditional scientific illustration techniques into a visualization system enables artists and non-artists to harnesses the power of traditional illustration techniques when visually representing scientific data. In this paper we present an illustrative scientific visualization framework incorporating general illustration principles, as well as techniques and aesthetics of various styles. Such a framework provides a basic foundation for categorizing and communicating research and may stimulate future illustrative visualization systems.
Auditory training can improve working memory, attention, and communication in adverse conditions for adults with hearing loss

Auditory training (AT) helps compensate for degradation in the auditory signal. A series of three high-quality training studies are discussed, which include, (i) a randomized controlled trial (RCT) of phoneme discrimination in quiet that trained adults with mild hearing loss (n = 44), (ii) a repeated measures study that trained phoneme discrimination in noise in hearing aid (HA) users (n = 30), and (iii) a double-blind RCT that directly trained working memory (WM) in HA users (n = 57). AT resulted in generalized improvements in measures of self-reported hearing, competing speech, and complex cognitive tasks that all index executive functions. This suggests that for AT related benefits, the development of complex cognitive skills may be more important than the refinement of sensory processing. Furthermore, outcome measures should be sensitive to the functional benefits of AT. For WM training, lack of far-transfer to untrained outcomes suggests no generalized benefits to real-world listening abilities. We propose that combined auditory-cognitive training approaches, where cognitive enhancement is embedded within auditory tasks, are most likely to offer generalized benefits to the real-world listening abilities of adults with hearing loss.
Large-scale (512kbit) integration of multilayer-ready access-devices based on mixed-ionic-electronic-conduction (MIEC) at 100% yield

BEOL-friendly Access Devices (AD) based on Cu-containing MIEC materials [1-4] are integrated in large (512 × 1024) arrays at 100% yield, and are successfully co-integrated together with Phase Change Memory (PCM). Numerous desirable attributes are demonstrated: the large currents (>;200μA) needed for PCM, the bipolar operation required for high-performance RRAM, the single-target sputter deposition essential for high-volume manufacturing, and the ultra-low leakage ( 10 pA) and high voltage margin (1.5V) needed to enable large crosspoint arrays.
Link failure analysis in SDN datacenter using RipL-POX controller

In a SDN-based data center network, the controller used greatly affects the behavior of the network. In this paper, the observation is conducted to describe the effect of various link failure scenarios to data center network performance using the Ripl-POX controller. Results shown in this paper can be used as a consideration for both controller selection or building for managing the data center and switch replacement method selection. This paper shows the effect of one to three switches that is turned down simultaneously on overall bandwidth. The simulation is done on 4k-fat tree data center network on mininet environment with RipL-POX as controller.