Miracle-dz/UniFAR-FTUs huggingface dataset:
Mind and choice in economics

This paper holds that the criteria of rational behavior, so far assumed in behavioral models, are not dufficiently realistic. The point of view here presented lies upon contemporary neurobiology that teaches how individual behavior responds to more complex and efficient criteria than the ones so far utilized in the decision making models. Following Simon's and Hayek's institutions, the paper takes the view that knowledge is the fruit of a process of "endogenous construction" and that perception represents the source of the unpredictability of behavior, and the cornerston of economic change. A relevant part of contemporary neurobiology has later confirmed these intuitions, and it can probably help us understand the role of emotions in the processes of choice. The development of this approach may have an influence on economic theory, especially with reference to economic behavior, theory of games, procedural rationality models, and pathdependent processes.
Research on the Hierarchy AAA Scheme for Interworking Authentication in Heterogeneous Networks

Facing the different wireless access networks, this paper has proposed several novel interworking AAA architectures among the 3GPP, WiMax and hotspot wireless LANs. In these architectures, a new entity named standby 3GPP AAA server is defined to cope with the single point failure. Moreover, based on the proposed interworking AAA architectures, a hierarchy AAA scheme is proposed. As a result, the simulation results show that the performance of proposed scheme is better than the existed ones, and the total cost of the authentication process is reduce drastically.
Comparison of in vivo intrinsic activity of cefepime and imipenem in a Pseudomonas aeruginosa rabbit endocarditis model: effect of combination with tobramycin simulating human serum pharmacokinetics.

OBJECTIVES The purpose of this experimental study was first to compare the in vivo intrinsic activity of imipenem and cefepime administered as a continuous infusion and to determine their lowest effective serum steady-state concentration (LESSC). Secondly, we studied the effect of combining therapy with tobramycin. METHODS In a Pseudomonas aeruginosa (ATCC 27853) rabbit endocarditis model, beta-lactam antibiotics were administered by continuous infusion over a 24 h treatment period at different doses until the LESSC was reached, i.e. able to achieve a 2-log drop of cfu/g of vegetations versus untreated animals. The effect of adding tobramycin (3 mg/kg once daily) was then studied. RESULTS The LESSC was between 3 x and 4 x MIC of cefepime for P. aeruginosa and about 0.2 5x MIC of imipenem. Combination of tobramycin with each of the two beta-lactams did not result in any further significant killing. CONCLUSION The optimal Css/MIC ratio might differ from one molecule to another. The LESSC of imipenem is lower than that of cefepime, giving a better intrinsic activity in vivo, despite a higher MIC in vitro.
TOWARDS A DVL-BASED NAVIGATION SYSTEM FOR AN UNDERWATER ROBOT

This paper represents a first step towards a navigation system based on a ARGONAUT DVL (Doppler Velocity Log) sensor for an underwater remotely operated vehicle (ROV). The sensor measures the water currents, the vehicle ground speed, the altitude, the depth and its attitude. The navigation system is formulated in a way that is able to deal with the future integration of new sensors like a DGPS. Hence, sensor fusion and filtering techniques are used to get a position estimate using data from all sensors. One of the widely applied strategies is the Kalman filter. In this paper an EKF-based navigation system using a DVL sensor and the nonlinear dynamic model of an underwater robot is proposed, implemented and evaluated through simulation.
Service-Learning through Marketing Research Class Projects.

Although academic organizations typically cite “teaching, research, and service” as their primary missions, the service component is often weighted less-heavily in the faculty promotion and tenure process compared with teaching and research. This is unfortunate for publically-funded colleges and universities, since in many disciplines community service can be more beneficial and visible to taxpayers, legislators, parents, and other constituency groups than academic scholarship will ever be. One goal for higher education that should be taken very seriously is the development of students who learn the value of being productive members of their communities by contributing pro bono expertise to those with a need, but without the expertise or resources necessary to accomplish the task(s) on their own. In an effort to enhance their images, many modern organizations reward employees for such community service. Since the public at large has increasingly come to perceive higher education - particularly faculty members - in a negative light, service-learning is arguably one of the best methods for addressing this problematic image. One very promising area for service-learning activity is through marketing research class projects. This manuscript first provides an overview of service-learning including a conceptual framework, and then supports that introduction with an example.
Analyzing the Performance of Acoustic Channel in Underwater Wireless Sensor Network (UWSN)

Underwater acoustic wireless sensor networks (UAWSN) consist of a variable number of sensors that communicated with each other using acoustic signal and the sensor are deployed to perform collaborative monitoring tasks over a given area in underwater environment. The exploration in underwater environment will become crucial task in the future especially in oil/gas exploration. Designing underwater channel modeling for this type of network is essential and turns out to be a great challenged because of constrain and limitation in underwater environment. The unique characteristic of the underwater acoustic network are large propagation delay, limited bandwidth and high bit error rate. The goal of this paper is to analyze the performance of the acoustic channel in a Matlab simulation in term of sound speed and transmission loss.
Non-Performing Assets of Indian Public, Private and Foreign Sector Banks: An Empirical Assessment

This paper explores an empirical approach to the analysis of Non-Performing Assets (NPAs) of public, private, and foreign sector banks in India. The NPAs are considered as an important parameter to judge the performance and financial health of banks. The level of NPAs is one of the drivers of financial stability and growth of the banking sector. This paper aims to find the fundamental factors which impact NPAs of banks. A model consisting of two types of factors, viz., macroeconomic factors and bank-specific parameters, is developed and the behavior of NPAs of the three categories of banks is observed. This model tries to extend the methodology of widely-known Altman model. The empirical analysis assesses how macroeconomic factors and bank-specific parameters affect NPAs of a particular category of banks. The macroeconomic factors of the model included are GDP growth rate and excise duty, and the bank-specific parameters are Credit Deposit Ratio (CDR), loan exposure to priority sector, Capital Adequacy Ratio (CAR), and liquidity risk. The results show that movement in NPAs over the years can be explained well by the factors considered in the model for the public and private sector banks. The collinearity between independent variables was measured by Durbin-Watson test and VIF characteristic and it was found to be a little for public and private banks. The factors included in the model explains 97.1% (adjusted R-square value of regression results) of variations in NPAs of public banks and 76.9% of the same of private banks. The other important results derived from the analysis include the finding that banks’ exposure to priority sector lending reduces NPAs.
A Packet-classification Algorithm for Arbitrary Bitmask Rules , with Automatic Time-space Tradeoffs

We present an algorithm for classifying packets according to arbitrary (including noncontiguous) bitmask rules. As its principal novelty, the algorithm is parameterized by the amount of memory available and can customize its data structures to optimize classification time without exceeding a given memory bound. The algorithm thus automatically trades time for space efficiency as needed. The two extremes of this time-space tradeoff (linear search through the rules versus a single table that maps every possible packet to its class number) are special cases of the general algorithm we present. Additional features of the algorithm include its simplicity, its open-source prototype implementation, its good performance even with worst-case rule sets, and its extendability to handle range rules and dynamic updates to rule sets. Keywords-computer networks; algorithms.
Multiple Walker Recognition with Wireless Distributed Pyroelectric Sensors

This paper presents a wireless distributed pyroelectric sensor system, whose sensing visibilities are modulated by Frensnel lens arrays and coded masks, for multiple human walker recognition. One goal of our research is to make wireless distributed pyroelectric sensor nodes an alternative to the centralized infrared video sensors, with lower cost, lower detectability, lower power consumption and computation, and less privacy infringement. In our previous study, we succeeded in identifying individuals walking along the same path, or just randomly inside a room, with an identification rate higher than 80% for around 10 subjects, only using one wireless sensor node. To improve the identification rate and the number of subjects that can be recognized, one-by-one or simultaneously, we employ multiple sensor nodes to leverage the performance of the distributed sensor system. The fusion of pyroelectric biometrics from multiple nodes is performed at four different levels: sample, feature, score, and decision. The experimental results show that the proposed pyroelectric sensor system has potential to be a reliable biometric system for the verification/identification of a small group of human objects. Its applications include security monitoring, human-machine interfaces, and virtual environments.
Carrying capacity of railway station by microscopic simulation method

This paper introduces a microscopic simulation method for analyzing and evaluating carrying capacity of railway station. Capacity of railway station is extremely dependent on infrastructure and operation scheme. For simulation purposes, a railway station Infrastructures Representing Model (IRM) for fixed equipment was present first. Based on IRM and train operations, the main algorithm and process of evaluating method for railway station capacity is discussed in detail. In addition, we implement an automatic computer-based tool to analyze the capacity of railway station. The experimental results show that this product can be used for general railway station capacity analyzing and is also beneficial to guiding design or expansion of station.
The New Economic History

T he 'new economic history', sometimes called econometric history or cliometrics, is not often practised in Europe. However, it is fair to say that efforts to apply statistical and mathematical models currently occupy the centre of the stage in American economic history. The influence of this type of research in the United States is illustrated by the proceedings of the twentyfifth annual meeting of the Economic History Association, published in the last number of the Journal of Economic History.2 Of the ten major papers included in the issue, three practise the new economic history and a fourth is devoted to a discussion of it. Moreover, if the dissertations presented to the annual meeting are an index of the intellectual direction of the youngest generation of economic historians, then it is worth noting that six of these seven studies are cast in the new mode, and the seventh is a computer analysis (of a large sample of commercial papers) aimed at revealing the motivation for the colonization of the Americas.3 Econometric history gained its present eminence with extraordinary rapidity. Perhaps the first definitely formulated expression of the new approach is contained in a pair of essays written by Alfred H. Conrad and John R. Meyer in 1957, less than a decade ago.4 It was not until three years later that work in cliometrics had gone far enough to warrant a conference devoted to it. In December of i96o Purdue University sponsored a Seminar on Quantitative Methods in Economic History. Although the organizers of the meeting had difficulty in finding a score of scholars interested enough to attend, the Purdue Seminar did much to stimulate further research in the application of the mathematical and statistical models of economics to the study of history. So successful was the first meeting that the Purdue Seminar has become an annual event. The sixth meeting was held last January. This time the problem was
GPER-mediated proliferation and estradiol production in breast cancer-associated fibroblasts

Cancer-associated fibroblasts (CAFs) are crucial co-mediators of breast cancer progression. Estrogen is the predominant driving force in the cyclic regulation of the mammary extracellular matrix, thus potentially affecting the tumor-associated stroma. Recently, a third estrogen receptor, estrogen (G-protein-coupled) receptor (GPER), has been reported to be expressed in breast CAFs. In this study, GPER was detected by immunohistochemical analysis in stromal fibroblasts of 41.8% (59/141) of the primary breast cancer samples. GPER expression in CAFs isolated from primary breast cancer tissues was confirmed by immunostaining and RT-PCR analyses. Tamoxifen (TAM) in addition to 17β-estradiol (E2) and the GPER agonist G1 activated GPER, resulting in transient increases in cell index, intracellular calcium, and ERK1/2 phosphorylation. Furthermore, TAM, E2, and G1 promoted CAF proliferation and cell-cycle progression, both of which were blocked by GPER interference, the selective GPER antagonist G15, the epidermal growth factor receptor (EGFR) inhibitor AG1478, and the ERK1/2 inhibitor U0126. Importantly, TAM as well as G1 increased E2 production in breast CAFs via GPER/EGFR/ERK signaling when the substrate of E2, testosterone, was added to the medium. GPER-induced aromatase upregulation was probably responsible for this phenomenon, as TAM- and G1-induced CYP19A1 gene expression was reduced by GPER knockdown and G15, AG1478, and U0126 administration. Accordingly, GPER-mediated CAF-dependent estrogenic effects on the tumor-associated stroma are conceivable, and CAF is likely to contribute to breast cancer progression, especially TAM resistance, via a positive feedback loop involving GPER/EGFR/ERK signaling and E2 production.
Manufacturable nanometer designs using standard cells with regular layout

In addition to performance considerations, designing VLSI circuits at nanometer-scale process technology nodes demands considerations related to manufacturability and cost. Regular layout patterns are known to enhance resilience to random as well as certain types of systematic variations. In this contribution we assess the implications of this layout regularity using design automation for Critical Feature Analysis (CFA) and raw metrics, such as via count. Using the ISCAS'89 benchmark suite, for each benchmark circuit we compare place-and-route implementations that are based on semi-regular and ultra-regular cell layouts. While the CFA counter-intuitively suggests that implementations using ultra-regular layouts have lower Design for Manufacturability (DFM) scores than those using semi-regular layouts, we find that ultra-regular layouts yield implementations with an average of 22% fewer vias at the cost of a small wire length increase.
Online activity graph for document importance and association

The way in which a user interacts with her desktop while performing some task generates an information trail that can be used to identify the task context and the user's interests. This new information can in turn be fed back into the system to increase the level of support available to the user for both current and future tasks. In this paper we present research which analyses user-activity log files to explore how a user's activities evolve with time. Resources fall in and out of a task based on the user's mental model for tackling that task. We assign time-varying, importance and association values to each resource, based on the dwell-time and the resource-switching patterns exhibited by the user while browsing. Furthermore, we propose a new dynamic graph algorithm called OnlineActivityGraph which leverages on these values to generate document clusters and short-term user models. We further present a discussion about the encouraging results obtained from our preliminary experiments.
Long-Term Effect of a Combined Exercise and Motivational Program on the Level of Disability of Patients With Chronic Low Back Pain

Study Design. A prospective clinical randomized controlled trial. Objectives. To determine the long-term effect of a combined exercise and motivational program on the level of disability of patients with chronic and recurrent low back pain (LBP). Summary of Background Data. There is agreement on the importance of exercise during the course of chronic LBP. However, it is well known that long-term adherence with exercises is particularly low. Methods. A total of 93 patients with LBP were randomly assigned to the control group (standard exercise program) or the motivational group (combined exercise and motivational program). Follow-up assessments were performed at 3.5 weeks, 4 months, 12 months, and 5 years. Main outcome measures were disability scores, pain intensity, and working ability. In addition to classic statistics, the sophisticated linear partial credit model was used to test the effects of treatment on disability scores. Results. In both groups, significant improvements in the disability scores were found at all points of follow-up assessment, however, the cumulative effect of the treatment in the motivational group was more than twice as much as in the control group. This result is in accordance with the increasing divergence in pain intensity between groups between 12 months and 5 years after intervention. A significant, positive long-term effect at the 5-year reassessment in working ability was only seen in the motivational group. All statistically significant results were confirmed by intention-to-treat analyses. Conclusions. Regarding long-term efficacy, the combined exercise and motivation program was superior to the standard exercise program. Five years after the supervised combined exercise and motivational program, patients had significant improvements in disability, pain intensity, and working ability.
Control of fair queueing: modeling, implementation, and experiences

Feedback control of QoS-aware servers has recently gained much popularity due to its robustness in the face of uncertainty and modeling errors. Performance of servers is characterized by the behavior of queues, which constitute the main elements of the control loop. The central role of queues in the loop motivates understanding their behavior in the context of feedback control schemes. A popular queueing policy in servers where different traffic classes must be allocated a different share of a common resource is fair queueing (FQ). This paper investigates the interactions between a FQ element and a feedback controller. It is shown that the FQ element introduces challenges that render simple feedback control ineffective and potentially unstable. These challenges are systematically exposed, explained, and resolved. An extended feedback control scheme for the FQ element is subsequently developed. The scheme is tested on an experimental prototype demonstrating higher predictability and an order of magnitude improvement in responsiveness over the initial design. The results of the paper apply in general to most systems that use a dynamic processor sharing approach for service differentiation.
Integrating Multiple Knowledge Sources by Genetic Programming

In this paper, we have proposed a GP-based knowledge-integration framework that automatically combines multiple rule sets into one integrated knowledge base. The proposed framework consists of three phases: knowledge collection and translation, knowledge integration, and knowledge output. Two new genetic operators, abridgement and compromise, are designed in the proposed approach. Experimental results from diagnosis of breast cancer also show the feasibility of the proposed algorithm.
Sociomaterial Capabilities in Integrated Oil and gas Operations - Implications for Design

Organisations must design and innovate capabilities in a symbiotic evolution between social and technical elements. Information Systems (IS) literature has successfully demonstrated the relationship between the material technology and the social organization, and how both influence each other. However, research has tilted in terms of favouring the explanatory power of either social or material agencies. To address this we suggest viewing the relationship as a sociomaterial capability addressing key organisational objectives. To understand the role of IS in such a capability, an approach addressing the bi-directional and flexible relationship is needed. We explore sociomateriality and draw empirically on a holistic case study in an international oil and gas company. The result shows how two sociomaterial capabilities, convergence and maintenance, are performed to contain tensions between global requirements and local contexts and between rigidity and flexibility. Second, bridging capability with the information infrastructure design theory, we derive seven principles for information system design to support organisations.
Impact of individual and joint optimizations in multi-user OFDM resource allocation by modified PSO

This paper deals with the sub-carrier and bit allocations for multi-user orthogonal frequency division multiplexing (OFDM) systems by a modified particle swarm optimization (MPSO) method for a specific bit error rate (BER). The resources (subcarriers and the number of bits per symbol per subcarrier) are allocated according to the instantaneous channel state information (CSI) which is assumed to be perfect and available with no latency and at no cost. To allocate the resources, we optimize total transmit power and throughput simultaneously with MPSO for a multi-user OFDM system. Simulation results show that for a large number of users, the MPSO performs better than existing algorithms, and that joint optimization (margin adaptive and rate adaptive) converges quickly.