Miracle-dz/UniFAR-FTUs huggingface dataset:
Advancing Integrated Systems Modelling Framework for Life Cycle Sustainability Assessment

The need for integrated methodological framework for sustainability assessment has been widely discussed and is urgent due to increasingly complex environmental system problems. These problems have impacts on ecosystems and human well-being which represent a threat to economic performance of countries and corporations. Integrated assessment crosses issues; spans spatial and temporal scales; looks forward and backward; and incorporates multi-stakeholder inputs. This study aims to develop an integrated methodology by capitalizing the complementary strengths of different methods used by industrial ecologists and biophysical economists. The computational methodology proposed here is systems perspective, integrative, and holistic approach for sustainability assessment which attempts to link basic science and technology to policy formulation. The framework adopts life cycle thinking methods—LCA, LCC, and SLCA; stakeholders analysis supported by multi-criteria decision analysis (MCDA); and dynamic system modelling. Following Pareto principle, the critical sustainability criteria, indicators and metrics (i.e., hotspots) can be identified and further modelled using system dynamics or agent based modelling and improved by data envelopment analysis (DEA) and sustainability network theory (SNT). The framework is being applied to development of biofuel supply chain networks. The framework can provide new ways of integrating knowledge across the divides between social and natural sciences as well as between critical and problem-solving research.
The presence of two different target-site resistance mechanisms in individual plants of Alopecurus myosuroides Huds., identified using a quick molecular test for the characterisation of six ALS and seven ACCase SNPs.

BACKGROUND Target-site resistance to ALS- and ACCase-inhibiting herbicides in the grass weed Alopecurus myosuroides is associated with well-characterised allelic variants encoding ALS- and ACCase-based resistance. The potential for combined ALS and ACCase resistance presents a threat to future control, given the extent to which these herbicides are used. The authors present a primer extension method for rapid detection of known resistance-conferring substitutions. RESULTS Individuals showing combined resistance to field-rate mesosulfuron + iodosulfuron and cycloxydim were identified in four field-collected populations, with proportions ranging from 30 to 100%. Genotyping with the SNaPshot primer extension kit showed the T197 and L574 ALS and L1781 ACCase isoforms to be associated with ALS and ACCase resistance whenever they occurred. CONCLUSION Combined ALS and ACCase target-site resistance threatens future control of A. myosuroides. The SNaPshot extension assay provides a reliable new multiplexable method for characterising known allelic variants of the ALS and ACCase genes of A. myosuroides. The method offers significant advantages over both CAPS/dCAPS and PASA in that full genotyping can be accomplished at any nucleotide position using a single extension primer.
The Connectivity of the Creative Industries in North East England — The Problems of Physical and Relational Distance

The creative industries are seen as a key part of economic development policy for national and regional policymakers. This research adopts a relational approach to examine the spatialities and networks of connections that workers in the North East of England's creative industries forge and maintain over space. Based on a questionnaire survey and interviews, our findings reveal a set of industries that are isolated from the major hubs of creativity outside the region and display a regionally bounded set of working and engagement practices. Numerous reasons underpinning this isolation are outlined, which are generated, in part, by both physical and relational distance to other agents in similar sectors. We also examine a group of highly mobile creative workers whose working practices and previous experience outside the North East allows them to overcome barriers faced by their counterparts. The paper concludes by calling for further comparative research to better understand the connectivity of regional creative industries that also avoids privileging London as the only source of discursive and financial influence. A series of recommendations for policy makers tasked with fostering the creative industries is outlined.
Miniaturized Low-Cost Phased-Array Antenna Using SIW Slot Elements

In this letter, a miniaturized C-band phased-array antenna based on a novel series-fed network is introduced. The series-fed network, radiating elements, and phase shifters are the main parts of the proposed phased-array antenna. In order to use the identical phase shifters, quarter-wavelength transformers are used in the design of the series-fed network. Furthermore, by choosing the proper place of the quarter-wavelength transformers, the distance between adjacent radiating elements is significantly reduced to 0. 33λ0. To reduce mutual couplings between radiating elements, miniaturized negative-order substrate integrated waveguide (SIW) slot antennas are chosen as radiating elements. A low-cost and compact 4-bit composite right/left-handed (CRLH) phase shifter is used due to the capability of being placed in a series-fed network. The proposed low-cost phased-array antenna is fabricated on a single-layer printed circuit board (PCB), and good agreement between the simulation and measurement results is obtained. The beam scanning range is 38°, and the impedance bandwidth of the phased-array antenna is 25 MHz at the center frequency of 5 GHz.
Modeling the Electrophysiology of Suprachiasmatic Nucleus Neurons

Neurons in the SCN act as the central circadian (~24-h) pacemaker in mammals. Using measurements of the ionic currents in SCN neurons, the authors fit a Hodgkin-Huxley-type model that accurately reproduces slow (~2-8 Hz) neural firing as well as the contributions of ionic currents during an action potential. When inputs of other SCN neurons are considered, the model accurately predicts the fractal nature of firing rates and the appearance of random bursting. In agreement with experimental data, the molecular clock within these neurons modulates the firing rate through small changes in the concentration of internal calcium, calcium channels, or potassium channels. Predictions are made on how signals from other neurons can start, stop, speed up, or slow down firing. Only a slow sodium inactivation variable and voltage do not reach equilibrium during the interval between action potentials, and based on this finding, a reduced model is formulated.
Cell Phone Demand and Consumer Learning - an Empirical Analysis

A structural model is used in this paper to analyze the demand and learning behavior in cell phone market. We assume that the cell phone consumption can be divided into a high-value part and a low-value part. The consumers are assumed to be uncertain about the exogenous shock of the need for high-value usage and also their preferences over the low-value usage. Meanwhile, we assume that the consumers’ knowledge improves over time. As a result, the match between their plan choice and consumption pattern becomes better. Such a learning behavior is supported by the data set. Bayesian updating is used to represent the learning. The estimates of the parameters are obtained and compared to the benchmarks from previous research.
Poisson Random Fields for Dynamic Feature Models

We present the Wright-Fisher Indian buffet process (WF-IBP), a probabilistic model for time-dependent data assumed to have been generated by an unknown number of latent features. This model is suitable as a prior in Bayesian nonparametric feature allocation models in which the features underlying the observed data exhibit a dependency structure over time. More specifically, we establish a new framework for generating dependent Indian buffet processes, where the Poisson random field model from population genetics is used as a way of constructing dependent beta processes. Inference in the model is complex, and we describe a sophisticated Markov Chain Monte Carlo algorithm for exact posterior simulation. We apply our construction to develop a nonparametric focused topic model for collections of time-stamped text documents and test it on the full corpus of NIPS papers published from 1987 to 2015.
A Landholder‐Based Approach to the Design of Private‐Land Conservation Programs

Abstract: Many ecosystems exist primarily, or solely, on privately owned (freehold) or managed (leasehold) land. In rural and semirural areas, local and regional government agencies are commonly responsible for encouraging landholders to conserve native vegetation and species on these private properties. Yet these agencies often lack the capacity to design and implement conservation programs tailored to rural and semirural landholdings and instead offer one program to all landholders. Landholders may elect not to participate because the program is irrelevant to their property or personal needs; consequently, vegetation–retention objectives may not be achieved. We differentiated landholders in Queensland, Australia, according to whether they derived income from the land (production landholders) or not (nonproduction landholders). We compared these two groups to identify similarities and differences that may inform the use of policy instruments (e.g., voluntary, economic, and regulatory) in conservation program design. We interviewed 45 landholders participating in three different conservation agreement programs (price‐based rate [property tax] rebate; market‐based tender; and voluntary, permanent covenant). Production landholders were more likely to participate in short‐term programs that offered large financial incentives that applied to <25% of their property. Nonproduction landholders were more likely to participate in long‐term programs that were voluntary or offered small financial incentives that applied to >75% of their property. These results may be explained by significant differences in the personal circumstances of production and nonproduction landholders (income, education, health) and differences in their norms (beliefs about how an individual is expected to act) and attitudes. Knowledge of these differences may allow for development of conservation programs that better meet the needs of landholders and thus increase participation in conservation programs and retention of native vegetation.
A Nanowire Array for Reconfigurable Computing

A fine-grained reconfigurable array based on complementary, dual-gate, fully depleted, silicon on insulator (DGFD-SOI) nanowire transistors is proposed and analyzed. Both low power and reconfigurable operation may be achieved by altering the switching threshold of the array using the back-gate bias on the complementary double-gate transistors. Simulated performance figures are presented for the array when configured into representative circuits and compared with two similar self-assembled molecular arrays. It is shown that SOI nanowire arrays can achieve dense, low-power reconfigurable operation without the overheads of either level restoration or additional gain blocks that may be required by molecular-based systems.
Optimal execution with limit and market orders

We develop an optimal execution policy for an investor seeking to execute a large order using limit and market orders. The investor solves the optimal policy considering different restrictions on volume of both types of orders and depth at which limit orders are posted. We show how the execution policies perform when targeting the volume schedule of the Almgren–Chriss execution strategy. The different strategies considered by the investor outperform the Almgren–Chriss price with an average savings per share of about one to two and a half times the spread. This improvement over Almgren–Chriss is due to the strategies benefiting from the optimal mix of limit orders, which earn the spread and market orders, which keep the investor’s inventory schedule on target.
Performance analysis of fuzzy logic controllers optimized by using genetic algorithm

There are many different design parameters such as membership functions, scaling factors, inference and defuzzification methods in the structures of fuzzy logic controllers. Most of the time, it is difficult to determine the parameters accurately even with the help of experts. For this purpose, genetic algorithm one of the heuristic optimization techniques is used to facilitate the design of optimal fuzzy logic controller in this study. Fuzzy logic controllers used in the studies are designed with entirely user-defined software instead of toolboxes. Performances of the designed controllers have been analyzed through simulation studies performed on the permanent magnet synchronous motor. Results obtained from the simulation studies have showed that fuzzy logic controllers optimized based on ITAE performance indice have better performance.
Identification of SVAR Models by Combining Sign Restrictions With External Instruments

ABSTRACT We discuss combining sign restrictions with information in external instruments (proxy variables) to identify structural vector autoregressive (SVAR) models. In one setting, we assume the availability of valid external instruments. Sign restrictions may then be used to identify further orthogonal shocks, or as an additional piece of information to pin down the shocks identified by the external instruments more precisely. In a second setting, we assume that proxy variables are only “plausibly exogenous” and suggest various types of inequality restrictions to bound the relation between structural shocks and the external variable. This can be combined with conventional sign restrictions to further narrow down the set of admissible models. Within a proxy-augmented SVAR, we conduct Bayesian inference and discuss computation of Bayes factors. They can be useful to test either the sign- or IV restrictions as overidentifying. We illustrate the usefulness of our methodology in estimating the effects of oil supply and monetary policy shocks.
Who Bears the Lifetime Tax Burden

Debates about tax policy arise every year in Washington, and legislative changes occur almost as often. In just the past decade, corporate tax burdens were dramatically reduced and then subsequently increased. But who really bears the burden of taxation? Finding a satisfactory way to address this question remains one of the biggest challenges for economists. While much research has explored this issue using annual data on household incomes and expenditures, this book considers the multiple effects of taxes on individuals over their entire lifetimes. Since annual incomes typically vary from year to year, and change systematically over the course of a lifetime, annual income is not necessarily a good indicator of a person's relative well-being. Instead, Dianne Rogers and Don Fullerton categorize individuals into lifetime income groups, and re-estimate the pattern of earnings over the lifetime of each group. They utilize a general equilibrium model that encompasses household demands, work effort, and savings, and they calculate the distribution of each current tax. Because their model includes all major U.S. federal, state, and local taxes, it can be used to simulate the effects of changes in any of those taxes on investment, productivity, resource allocation, and the distribution of burdens. Don Fullerton is professor of economics at the University of Virginia and visiting professor of economics and public policy at Carnegie Mellon, School of Urban and Public Affairs. He served as Deputy Assistant Secretary of the Treasury for Tax Analysis from 1985 to 1987. Diane Lim Rogers is assistant professor of economics at Pennsylvania State University.
A Price Theoretic Approach to the Specification and Estimation of the Sales-Advertising Function

In spite of the great attention that marketing researchers have given to it, the determination of the sales-advertising function remains primarily an exercise in fitting statistical models to aggregate data sets. The approach of numerous studies to modeling the sales-advertising function has been to let the market data determine the "final" form of the model. ' Although such interesting phenomena as cumulative effects of advertising, the two-way causality between sales and advertising, and competitive advertising effects have been modeled in past studies, there has been little effort to explicitly link estimable salesadvertising functions to a theory of consumer behavior. Because the major use of the sales-advertising function is to set the firm's optimal level of advertising, it is necessary to obtain a model that adequately represents the true relationship between advertising and consumer demand for the This paper emphasizes the usefulness of modeling the salesadvertising function based explicitly on a theory of individual consumer choice. The proposed model of consumer choice rests on two assumptions: that the consumer maximizes utility net of information costs, and that advertising lowers these information costs. This model is used to generate the precise form of an estimable sales-advertising function. The function allows for the systematic measurement of own and competitive advertising effects. Also, the consumer choice model has implications that can be empirically tested. *Research supported in part by National Science Foundation under grant SOC 73-05547. I wish to thank Arnold Zellner for his invaluable help in the writing of this paper. Robert Blattberg, John Gould, Gregg Jarrell, Michael Jensen, John Long, Peter Pashigian, and Subrata Sen also provided helpful comments. Their help is gratefully acknowledged. I alone am responsible for any remaining errors. 1. Notable examples are the studies by Palda (1964), Bass (1969), Bass and Parsons (1969), Bass and Clarke (1972), Beckwith (1972), Schmalensee (1972), Clarke (1973), Wildt (1974), and Helmer and Johansson (1977).
Multiple Mixed Lineage Leukemia (MLL) Fusion Proteins Suppress p53-mediated Response to DNA Damage*

Chromosomal translocations involving the mixed lineage leukemia (MLL) gene are often observed in acute leukemias of both myeloid and lymphocytic origin. Expression of MLL fusion proteins is known to induce malignant transformation of normal blood progenitors; however, molecular mechanisms of this process are still poorly understood. In this study we investigated the effect of several frequently detected MLL fusion proteins on p53 transcriptional activity. Our data show that MLL-AF9, MLL-AF10, MLL-ENL, and MLL-ELL substantially down-regulate p53-mediated induction of p21, MDM2, and Bax in response to DNA damage. Furthermore, we identify the reduction in p53 acetylation by p300 as a major mechanism of the inhibitory effect of MLL leukemic fusions. Our data suggest that abrogation of p53 functional activity can be a common feature of MLL fusion-mediated leukemogenesis.
Heterogeneous Effects of International Migration and Remittances on Crop Income: Evidence from the Kyrgyz Republic

This paper uses a unique representative household budget survey from the Asian Development Bank to analyze the impact of international migration and remittances on crop income of rural farmers in the Kyrgyz Republic. Unlike other studies we allow the impact of remittances to be different for farmers with different land size and test whether reduced labor availability is more relevant for permanent than for seasonal migrants. We find that losing family members has a significant negative effect on crop income, but only for permanent migrants. Remittances partially compensate for this, but their positive impact decreases with farm size.
Micromotors Spontaneously Neutralize Gastric Acid for pH-Responsive Payload Release.

The highly acidic gastric environment creates a physiological barrier for using therapeutic drugs in the stomach. While proton pump inhibitors have been widely used for blocking acid-producing enzymes, this approach can cause various adverse effects. Reported herein is a new microdevice, consisting of magnesium-based micromotors which can autonomously and temporally neutralize gastric acid through efficient chemical propulsion in the gastric fluid by rapidly depleting the localized protons. Coating these micromotors with a cargo-containing pH-responsive polymer layer leads to autonomous release of the encapsulated payload upon gastric-acid neutralization by the motors. Testing in a mouse model demonstrate that these motors can safely and rapidly neutralize gastric acid and simultaneously release payload without causing noticeable acute toxicity or affecting the stomach function, and the normal stomach pH is restored within 24 h post motor administration.
Decision Making in Reference to Model of Marketing Predictive Analytics – Theory and Practice

Purpose: The objective of this paper is to describe concepts and assumptions of predictive marketing analytics in reference to decision making. In particular, we highlight issues pertaining to the importance of data and the modern approach to data analysis and processing with the purpose of solving real marketing problems that companies encounter in business. Methodology: In this paper authors provide two study cases showing how, and to what extent predictive marketing analytics work can be useful in practice e.g., investigation of the marketing environment. The two cases are based on organizations operating mainly on Web site domain. The fi rst part of this article, begins a discussion with the explanation of a general idea of predictive marketing analytics. The second part runs through opportunities it creates for companies in the process of building strong competitive advantage in the market. The paper article ends with a brief comparison of predictive analytics versus traditional marketing-mix analysis. Findings: Analytics play an extremely important role in the current process of business management based on planning, organizing, implementing and controlling marketing activities. Predictive analytics provides the actual and current picture of the external environment. They also explain what problems are faced with the company in business activities. Analytics tailor marketing solutions to the right time and place at minimum costs. In fact they control the effi ciency and simultaneously increases the effectiveness of the fi rm. Practical implications: Based on the study cases comparing two enterprises carrying business activities in different areas, one can say that predictive analytics has far more been embraces extensively than classical marketing-mix analyses. The predictive approach yields greater speed of data collection and analysis, stronger predictive accuracy, better obtained competitor data, and more transparent models where one can understand the inner working of the model. Originality: Authors describe the importance of analytics which enhance the decisions that the company makes as it executes strategies and plans, so that the company can be more effective and achieve better results. The key factor that enables to execute marketing strategies accurately and build competitive advantage in the future includes predictive modeling. The ability to predict probable futures allows us to shape the future, rather than merely survive whatever it brings.