Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Bioethanol Production from Ulva lactuca By Saccharomyces cerevisiae

Ulva lactuca acts a vital potential marine energy crop. Reducing sugars from U. lactuca were obtained and evaluated for the bioethanol production by Saccharomyces cerevisiae. The optimization process was investigated by Plackett-Burman experimental design followed by immobilization technique on supported solid materials. Results show that the sugar concentration, pH level and the inoculums size have a significant effect on the bioethanol production by S. cerevisiae to give concentration (12 ± 0.5 g/g of sugar/l) with conversion efficiency (47.1%). The immobilization of yeast cells upon luffa pulp shows the highest bioethanol productivity (13.3 g/g of sugar/l) with conversion efficiency (52%). Therefore, the immobilized yeast upon luffa pulp was recommended in the current work. Moreover, the supportive luffa pulp was efficiently used and recycled for several times in the bioethanol production.
A hybrid recommender systems based on weighted tags

Social tags in web 2.0 are becoming another important information source to describe the content of items as well as to profile users’ topic preferences. However, as arbitrary words given by users, tags contains a lot of noise such as tag synonym and semantic ambiguity a large number personal tags that only used by one user, which brings challenges to effectively use tags to make item recommendations. To solve these problems, this paper proposes to use a set of related tags along with their weights to represent semantic meaning of each tag for each user individually. A hybrid recommendation generation approaches that based on the weighted tags are proposed. We have conducted experiments using the real world dataset obtained from Amazon.com. The experimental results show that the proposed approaches outperform the other state of the art approaches.
Public Expenditure for Education and Economic Growth

The study examines the dependence between education and economic growth. Based on the neoclassic model of growth a theoretic dependence between human capital and GDP is drawn. The effect of public expenditure for education on growth in EU countries is studied. The econometric analysis shows that higher rates of economic growth are associated with accelerated growth of state expenditure for education. For the old member-states there is also a positive dependence between research and development expenditure and the trend toward growth of the aggregate product.
HARDWARE AND SOFTWARE APPROACHES FOR DETERMINISTIC MULTI-PROCESSOR REPLAY OF CONCURRENT PROGRAMS

As multi-processors become mainstream, software developers must harness the parallelism available in programs to keep up with multi-core performance. Writing parallel programs, however, is notoriously diffi cult, even for the most advanced programmers. " e main reason for this lies in the nondeterministic nature of concurrent programs, which makes it very diffi cult to reproduce a program execution. As a result, reasoning about program behavior is challenging. For instance, debugging concurrent programs is known to be diffi cult because of the non-determinism of multi-threaded programs. Malicious code can hide behind non-determinism, making software vulnerabilities much more diffi cult to detect on multi-threaded programs. In this article, we explore hardware and software avenues for improving the programmability of Intel® multi-processors. In particular, we investigate techniques for reproducing a non-deterministic program execution that can effi ciently deal with the issues just mentioned. We identify the main challenges associated with these techniques, examine opportunities to overcome some of these challenges, and explore potential usage models of program execution reproducibility for debugging and fault tolerance of concurrent programs.
Research Statement 1 Impact of Targeted Attacks: Theoretic-driven Simulation

My research focuses on improving the security of the cyber-physical infrastructure of power grids against targeted attacks. Targeted attacks are malicious attacks that are initiated from the cyber domain but “target” the physical process of power grids by introducing safety violations. With many cyber-physical systems (CPSs), including power grids, using off-the-shelf computing and communication infrastructure, the targeted attacks can become a serious threat. As shown in Figure 1, my thesis work focuses on three aspects to improve the resilience of power grids:  Understanding the impact of targeted attacks. I established a theoretical basis to demonstrate the impact of targeted attacks. By mapping the physical changes caused by targeted attacks into the modification of mathematical models of power systems, I demonstrated how the attacks maliciously change the electrical state of power grids.  Detecting targeted attacks. To detect targeted attacks in power grids, I combined the knowledge of both the cyber and physical infrastructure. I developed a DNP3 analyzer in Bro (a real-time network traffic analyzer), which can now provide high visibility of the data carried by the proprietary network protocols used in power grids. On top of the network analyzers, I developed a semantic analysis framework, which intercepts control commands and proactively estimates their execution consequences. To reduce detection latency while preserving detection accuracy, I proposed a new adaptive power flow analysis algorithm, which dynamically adapts its parameters (e.g., the iteration number) based on the semantics of the observed control commands.  Responding to targeted attacks. I proposed an example intrusion response mechanism for attacks that compromise phasor measurement units (PMU). Specifically, I designed a new routing algorithm to recover the measurements that are lost due to compromised PMUs. The algorithm considers the constraints in both network and physical infrastructure, to jointly reduce the network performance overhead and increase the coverage of PMU measurements.
Evaluating Value-at-Risk Models via Quantile Regression

This article is concerned with evaluating Value-at-Risk estimates. It is well known that using only binary variables, such as whether or not there was an exception, sacrifices too much information. However, most of the specification tests (also called backtests) available in the literature, such as Christoffersen (1998) and Engle and Manganelli (2004) are based on such variables. In this article we propose a new backtest that does not rely solely on binary variables. It is shown that the new backtest provides a sufficient condition to assess the finite sample performance of a quantile model whereas the existing ones do not. The proposed methodology allows us to identify periods of an increased risk exposure based on a quantile regression model (Koenker and Xiao 2002). Our theoretical findings are corroborated through a Monte Carlo simulation and an empirical exercise with daily S&P500 time series.
THE EFFECTS OF GOAL ORIENTATIONS ON KNOWLEDGE SOURCING , KNOWLEDGE MANAGEMENT SYSTEM USAGE , AND LEARNING OUTCOME

This research investigates individual differences in the context of knowledge management system (KMS) usage, knowledge sourcing and learning outcome. Individual differences are measured for mastery, performance and avoidance goal orientations. Individuals with high mastery goal orientations prefer to master and develop new skills and knowledge. Those with high performance goal orientations prefer to compare their performances with others. Lastly, those with high avoidance goal orientations prefer to avoid a new task if they feel incompetent. User posting and reading activities in a KMS are examined over a 3month period. Consistent with goal orientation theory, the results show that mastery goal orientation has an effect on reading, knowledge sourcing and learning outcome. In contrast, performance goal orientation has an effect only on posting, but not on reading. To a lesser degree than mastery goal orientation, avoidance goal orientation has an effect on reading, but not posting. These findings have important implications for both knowledge management researchers and practitioners.
Design of wideband antenna for RF energy harvesting system

This paper studies a wideband antenna of ice-cream cone structure and it is integrated with a rectifying circuit which has the potential to be used for RF energy harvesting system. The antenna is designed by using CST Studio Suite 2011 and fabricated on a double sided FR-4 printed circuit board using an etching technique. A single stage rectifying circuit is designed, simulated, fabricated and measured in this work. The design and simulation process was done by using Agilent Advanced Design System (ADS) 2011. Simulation and measurement were carried out for various input power levels at the specified frequency band. An experimental test has been conducted by varying the load, R of the rectifying circuit. For an equivalent incident signal of 20 dB, the system managed to produce 0.09V with load of 20kΩ. This voltage can be used to power low power sensors in sensor networks ultimately in place of batteries.
Distinct pools of cAMP centre on different isoforms of adenylyl cyclase in pituitary-derived GH3B6 cells

Microdomains have been proposed to explain specificity in the myriad of possible cellular targets of cAMP. Local differences in cAMP levels can be generated by phosphodiesterases, which control the diffusion of cAMP. Here, we address the possibility that adenylyl cyclases, the source of cAMP, can be primary architects of such microdomains. Distinctly regulated adenylyl cyclases often contribute to total cAMP levels in endogenous cellular settings, making it virtually impossible to determine the contribution of a specific isoform. To investigate cAMP dynamics with high precision at the single-isoform level, we developed a targeted version of Epac2-camps, a cAMP sensor, in which the sensor was tagged to a catalytically inactive version of the Ca2+-stimulable adenylyl cyclase 8 (AC8). This sensor, and less stringently targeted versions of Epac2-camps, revealed opposite regulation of cAMP synthesis in response to Ca2+ in GH3B6 pituitary cells. Ca2+ release triggered by thyrotropin-releasing hormone stimulated the minor endogenous AC8 species. cAMP levels were decreased by inhibition of AC5 and AC6, and simultaneous activation of phosphodiesterases, in different compartments of the same cell. These findings demonstrate the existence of distinct adenylyl-cyclase-centered cAMP microdomains in live cells and open the door to their molecular micro-dissection.
A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally.
Media Audiences: Effects, Users, Institutions, and Power

1. History and Concept of the Audience PART I. AUDIENCES AS OBJECTS 2. Effects of Media Messages PART II. AUDIENCES AS INSTITUTIONAL CONSTRUCTIONS 3. Public Opinion and Audience Citizenship 4. Media Ratings and Target Marketing PART III. AUDIENCES AS ACTIVE USERS OF MEDIA 5. Uses and Gratifications 6. Interpreting and Decoding Mass Media Texts 7. Reception Contexts & Media Rituals PART IV. AUDIENCES AS PRODUCERS AND SUBCULTURES 8. Media Fandom and Audience Subcultures 9. Online, Interactive Audiences in a Digital Media World 10. Conclusion: Audience Agency in New Contexts
Can a Single Brain Region Predict a Disorder?

We perform prediction of diverse disorders (cocaine use, schizophrenia and Alzheimer's disease) in unseen subjects from brain functional magnetic resonance imaging. First, we show that for multisubject prediction of simple cognitive states (e.g., motor versus calculation and reading), voxels-as-features methods produce clusters that are similar for different leave-one-subject-out folds; while for group classification (e.g., cocaine addicted versus control subjects), voxels are scattered and less stable. Therefore, we chose to use a single region per experimental condition and a majority vote classifier. Interestingly, our method outperforms state-of-the-art techniques. Our method can integrate multiple experimental conditions and successfully predict disorders in unseen subjects (leave-one-subject-out generalization accuracy: 89.3% and 90.9% for cocaine use, 96.4% for schizophrenia and 81.5% for Alzheimer's disease). Our experimental results not only span diverse disorders, but also different experimental designs (block design and event related tasks), facilities, magnetic fields (1.5T, 3T, 4T) and speed of acquisition (interscan interval from 1600 to 3500 ms). We further argue that our method produces a meaningful low-dimensional representation that retains discriminability.
Context-sensitive Referencing for Ontology Mapping Disambiguation

Ontologies can be used for e-business integration, for example by describing existing e-business standards as ontologies. If cooperating parties use different ontologies, ontology mappings are needed, which can be ambiguous, thus making ontology mapping disambiguation necessary. Different disambiguation strategies exist, such as community-driven or context-sensitive referencing of ontologies, where the latter is what we developed in our project. In this paper, we show that community-driven referencing can be realized using a context-sensitive referencing service in a way that the user administration is transparent to the referencing system.
Reliability Improvement Using Receive Mode Selection in the Device-to-Device Uplink Period Underlaying Cellular Networks

A new interference management scheme is proposed to improve the reliability of a device-to-device (D2D) communication in the uplink (UL) period without reducing the power of cellular user equipment (UE). To improve the reliability of the D2D receiver, two conventional receive techniques and one proposed method are introduced. One of the conventional methods is demodulating the desired signal first (MODE1), while the other is demodulating an interference first (MODE2), and the proposed method is exploiting a retransmission of the interference from the base station (BS) (MODE3). We derive their outage probabilities in closed forms and explain the mechanism of receive mode selection which selects the mode guaranteeing the minimum outage probability among three modes. Numerical results show that by applying the receive mode selection, the D2D receiver achieves a remarkable enhancement of outage probability in the middle interference regime from the usage of MODE3 compared to the conventional ways of using only MODE1 or MODE2.
Modeling Volatility of Islamic Stock Indexes: Empirical Evidence and Comparative Analysis

This paper aims to investigate the volatility behavior of Islamic stock indexes compared to their conventional counterparts. Four major Islamic stock indexes have been the subject of our paper namely the Standard and Poor’s Shariah index (S&P Shariah), the Dow Jones Islamic Market (DJIM) index, the FTSE Islamic index, the MSCI Islamic World as well as their conventional counterparts, respectively, the S&P 500, the Dow Jones Industrial Average (DJIA), the FTSE All world, and the MSCI World Indexes. GARCH models (Generalized Autoregressive Conditional Heteroscedastic) are used to estimate the conditional variance, particularly the Exponential GARCH model due to its ability to capture the leverage effect and leptokurtosis as the main stylized facts usually observed in financial times series. GARCH models are used also with Gaussian and non-Gaussian distribution in order to take into account the thick tails of daily data distribution. The results reveal that Islamic stock indexes were significantly affected by the financial crisis but they were less volatile than their conventional counterparts. This finding confirms the relative resilience of Islamic indexes to the global financial crisis, which has affected the Islamic finance as soon as the crisis has affected the real sector of the economy.
Serum Uric Acid and Chronic Kidney Disease: The Role of Hypertension

Background There are inconsistent findings on the role of hyperuricemia as an independent risk factor for chronic kidney disease (CKD). Hypertension has been implicated as a factor influencing the association between serum uric acid and CKD. In this population-based study we investigated the association between serum uric acid and decline in renal function and tested whether hypertension moderates this association. Methods We included 2601 subjects aged 55 years and over from the Rotterdam Study. Serum uric acid and estimated glomerular filtration rate (eGFR) were assessed at baseline. After average 6.5 years of follow-up, second eGFR was assessed. CKD was defined as eGFR<60 ml/min/1.73 m2. All associations were corrected for socio-demographic and cardiovascular factors. Results Each unit (mg/dL) increase in serum uric acid was associated with 0.19 ml/min per 1.73 m2 faster annual decline in eGFR. While the association between serum uric acid and incidence of CKD was not significant in our study population (Hazard Ratio: 1.12, 95% confidence interval [CI]: 0.98–1.28), incorporating our results in a meta-analysis with eleven published studies revealed a significant association (Relative Risk: 1.18, 95%CI: 1.15–1.22). In the stratified analyses, we observed that the associations of serum uric acid with eGFR decline and incident CKD were stronger in hypertensive subjects (P for interaction = 0.046 and 0.024, respectively). Conclusions Our findings suggest that hyperuricemia is independently associated with a decline in renal function. Stronger association in hypertensive individuals may indicate that hypertension mediates the association between serum uric acid and CKD.
Parametric analysis of dynamically equivalent reaction network models

Using the results related to dynamically equivalent realizations of reaction kinetic systems, we analyze the dynamical properties of mass action reaction networks on which the well known structure based theorems of reaction kinetics are not directly applicable with respect to given range of certain rate coefficients. We introduce a transformation matrix to describe parametric changes, and show that if the appropriate transformation matrix has been found, parameter ranges for which certain dynamical properties can be ensured may be determined via the solution of a linear programming problem. The method is illustrated by numerical examples.
Peroxisome Proliferator-Activated Receptor-γ Is a Potent Target for Prevention and Treatment in Human Prostate and Testicular Cancer

Peroxisome proliferator-activated receptor-γ (PPAR)-γ is a ligand-activated transcriptional factor belonging to steroid receptor superfamily. PPAR-γ plays a role in both adipocyte differentiation and tumorigenesis. Up to date, PPAR-γ is expressed in various cancer tissues, and PPAR-γ ligand induces growth arrest of these cancer cells. In this study, we examined the expression of PPAR-γ in prostate cancer (PC) and testicular cancer (TC) by RT-PCR and immunohistochemistry, and we also examined the effect of PPAR-γ ligand in these cells by MTT assay, hoechest staining, and flow cytometry. PPAR-γ expression was significantly more extensive and intense in malignant tissues than in normal tissues. PPAR-γ ligand induced the reduction of malignant cell viability through apoptosis. These results demonstrated that the generated PPAR-γ in PC and TC cells might play an important role in the tumorigenesis. PPAR-γ may become a new target in the treatment of PC and TC.
Party systems and public goods: the dynamics of good governance in the Indian states

ABSTRACT We argue that two key party system characteristics – the effective number of parties and electoral volatility – have a curvilinear, inverted-U shaped, influence on public goods provision. Rejecting the linear pattern generally assumed in the literature, we contend that optimal governance outcomes will be observed at intermediate levels of party system size and stability. Only under these conditions will the benefits of competition be balanced against the risks of fragmentation. We find support for our arguments by employing new data and estimating panel models of public goods provision in 29 Indian states and territories. We hope that our findings will contribute to understanding how party systems function, particularly those at the subnational level, and will better inform how they can be leveraged for development and good governance. We also hope that they will provide some guidance about the future trajectory of public policy in the Indian states.
Socio-economic assessment of the SAFESPOT cooperative systems - Methodology, final assessment results and deployment conclusions

This paper reports the methodology and the results of the socio-economic impact assessment of the SAFESPOT cooperative systems. Two application bundles, based on communication between vehicles or between vehicles and the infrastructure, which address the same problem areas of road safety (intersections, hazardous road and weather conditions, speed and inappropriate distance), are compared concerning their socio-economic benefits and system costs for the target year 2020. The results show that the infrastructure based bundle is slightly more effective in avoiding casualties, thus leading to higher safety benefits. The system costs are dominated by the infrastructure costs so that the lower invehicle costs of the infrastructure based system are outweighed by far. In terms of benefit-cost ratio the system based on vehicle-vehicle communication proves its efficiency whereas the vehicle-infrastructure based system is too expensive under the assumptions introduced for the assessment. In general it can be concluded that cooperative systems, especially when infrastructure comes into play, should aim towards leaner and smarter equipment at lower unit costs. Concerning deployment, it is argued that the system based on vehicle-vehicle communication looks more promising from the socio-economic perspective. The equipment of infrastructure on a limited scale, concentrating on black spots, would help to overcome the critical mass threshold of the vehicle-vehicle applications in early deployment phase.
Consensus Control of a Class of Lipschitz Nonlinear Systems With Input Delay

This paper deals with the consensus control design for Lipschitz nonlinear multi-agent systems with input delay. The Artstein-Kwon-Pearson reduction method is employed to deal with the input delay and the integral term that remains in the transformed system is analyzed by using Krasovskii functional. Upon exploring certain features of the Laplacian matrix, sufficient conditions for global stability of the consensus control are identified using Lyapunov method in the time domain. The proposed control only uses relative state information of the agents. The effectiveness of the proposed control design is demonstrated through a simulation study.