Miracle-dz/UniFAR-FTUs huggingface dataset:
Is There Discretion in Wage Setting? a Test Using Takeover Legislation

Anecdotal evidence suggests that uncontrolled managers let wages rise above competitive levels. To test this belief, we examine the wage impact of antitakeover legislation passed throughout the 1980s in many states. Since many view hostile takeovers as an important disciplining device, these laws, by reducing takeover threats, potentially raised managerial discretion. If uncontrolled managers pay higher wages, we expect wages to rise following these laws. Using firm-level data, we find that these laws raised annual wages by 1% to 2%, or about $500 per year. The findings are robust to a battery of specification checks and do not appear to be contaminated by the political economy of the laws or other sources of bias. These results challenge standard theories of wage determination that ignore the role of managerial preferences.
The Buffer-Stock Model and the Aggregate Propensity to Consume: A Panel-Data Study of the Us States

We simulate a buffer-stock model of consumption, explicitly aggregate over consumers, and estimate aggregate marginal propensities to consume out of current and lagged income using simulated data generated by the model. We calculate the predicted marginal effects of changing persistence of income shocks, aggregate-level uncertainty, and individual-level risk. Next, we estimate marginal propensities for US states using panel-data methods. We find effects of persistence that clearly correspond to the predictions of the model and while the effect of aggregate uncertainty cannot be determined precisely, indicators of individual level uncertainty have strong effects consistent with the model. Overall, the buffer-stock model clearly helps explain differences in consumer behaviour across states.
Law and Behaviors in Social Dilemmas: Testing the Effect of Obligations on Cooperation

Laws consist of two components: the 'obligations' they express and the 'incentives' designed to enforce them.In this paper we run a public good experiment to test whether or not obligations have any independent effect on cooperation in social dilemmas.The results show that, for given marginal incentives, different levels of minimum contribution required by obligation determine significantly different levels of average contributions.Moreover, unexpected changes in the minimum contribution set up by obligation have asymmetric dynamic effects on the levels of cooperation: a reduction does not alter the descending trend of cooperation, whereas an increase induces a temporary re-start in the average level of cooperation.Nonetheless, obligations per se cannot sustain cooperation over time.
Inventive Process as a Recombinant Search over Complex Landscape: Evidence from the Disk Drive Industry

The inventive process has been often modeled as a bounded iterative trial-and-error recombinant search over complex landscape. Our main research question is whether such approximation is empirically valid. To investigate it, we develop a single-industry measure of invention interdependence and provide a relatively direct test of the canonical NK model. Our findings indicate that the NK model correctly predicts most of the empirical patterns. We also find that the consistency between the empirical estimates and the model predictions deteriorates with expanded definition of industry boundaries. Our results suggest that models representing iterative trial-and-error recombinant search are applicable as approximations of the inventive process when one looks at single mature industries where most of the knowledge originates from within the same technological domain. When inventors draw from a broad knowledge base and fundamentally new knowledge is created then applicability of simple models of recombinant search may be limited.
Queue-Length based Algorithms for Optimal End-to-End Throughput Allocation and Stability in Multi-hop Random Access Networks

We consider a model of wireless network with random (slotted-Aloha-type) access and with multi-hop flow routes. The goal is to devise distributed strategies for optimal utility-based end-to-end throughput allocation and queueing stability. We consider a class ofqueue back-pressure randomaccess algorithms (QBRA), where actual queue lengths of the flows (in each node’s close neighborhood) are used to determine nodes’ channel access probabilities. This is in contrast to previously proposed algorithms, which are purely optimizationbased and oblivious of actual queues. QBRA is also substantially different from much studied “MaxWeight” type scheduling algorithms, also using back-pressure. For the model with infinite backlog at each flow source, we show that QBRA, combined with simple congestion control local to each source, leads to optimal end-to-end throughput allocation, within the network saturation throughput region achievable by a random access. (No end-to-end message passing is required.) This scheme generalizes for the case of additional, minimum flow rate constraints. For the model with stochastic exogenous arrivals, we show that QBRA ensures stability of the queues as long as nominal loads of the nodes are within the saturation throughput region. Simulation comparison of QBRA and (queue oblivious) optimization-based random access algorithms, shows that QBRA performs better in terms of endto-end delays.
CHARACTERIZATION OF THE FMT-2 DISCHARGE CATHODE PLUME

Laser-induced fluorescence and emission spectroscopy were used to interrogate the plasma downstream of the discharge cathode in the FMT-2 ion engine. Ion velocities consistent with a potential hill approximately 0.75 cm downstream of the unkeepered orifice were observed at higher powers. The high energy tail, discharge voltage oscillations, and the concentration of Xe III may collectively contribute to the erosion observed in NSTAR wear tests.
Office Rent Determinants During Market Decline and Recovery

This article empirically examines office rent determinants in distinct periods of a market cycle. The study uses a dataset of office properties located in a large metropolitan area and spanning a six-year period. During this period, office rents experienced a significant decline and recovery. A time-varying parameter rent index identifies three distinct periods of the cycle: decline, trough and recovery. Tests of structural change conclude that market participants value the determinants of office rents differently during the periods. A microexamination of each rent determinant over the periods of the market cycle provides a greater understanding of how rents vary over time and the factors that influence them.
Innovations in Government: Research, Recognition, and Replication

The Innovations in American Government Awards Program began in 1985 with a grant from the Ford Foundation to the Kennedy School of Government at Harvard to conduct a program of awards for innovations in state and local government. The foundation's objective was ambitious and, in an era of "government is the problem" rhetoric, determinedly proactive. It sought to counter declining public confidence in government by highlighting innovative and effective programs. Over twenty years later, research, recognition, and replication are the source of the program's continuing influence and its vitality. What is the future of government innovation? How can innovation enhance the quality of life for citizens and strengthen democratic governance? Innovations in Government: Research, Recognition, and Replication answers these questions by presenting a comprehensive approach to advancing the practice and study of innovation in government. The authors discuss new research on innovation, explore the impact of several programs that recognize innovation, and consider challenges to the replication of innovations. Contributors include Eugene Bardach (University of California- Berkeley), Robert Behn (Harvard University), John D. Donahue (Harvard University), Marta Ferreira Santos Farah (Center for Public Administration and Government, Fundacao Getulio Vargas), Archon Fung (Harvard University), Jean Hartley (University of Warwick), Steven Kelman (Harvard University), Gowher Rizvi (Ash Institute for Democratic Governance and Innovation, Harvard University), Peter Spink (Center for Public Administration and Government, Fundacao Getulio Vargas), and Jonathan Walters (Governing).
Glycan Specificity of P[19] Rotavirus and Comparison with Those of Related P Genotypes

ABSTRACT The P[19] genotype belongs to the P[II] genogroup of group A rotaviruses (RVs). However, unlike the other P[II] RVs, which mainly infect humans, P[19] RVs commonly infect animals (pigs), making P[19] unique for the study of RV diversity and host ranges. Through in vitro binding assays and saturation transfer difference (STD) nuclear magnetic resonance (NMR), we found that P[19] could bind mucin cores 2, 4, and 6, as well as type 1 histo-blood group antigens (HBGAs). The common sequences of these glycans serve as minimal binding units, while additional residues, such as the A, B, H, and Lewis epitopes of the type 1 HBGAs, can further define the binding outcomes and therefore likely the host ranges for P[19] RVs. This complex binding property of P[19] is shared with the other three P[II] RVs (P[4], P[6], and P[8]) in that all of them recognized the type 1 HBGA precursor, although P[4] and P[8], but not P[6], also bind to mucin cores. Moreover, while essential for P[4] and P[8] binding, the addition of the Lewis epitope blocked P[6] and P[19] binding to type 1 HBGAs. Chemical-shift NMR of P[19] VP8* identified a ligand binding interface that has shifted away from the known RV P-genotype binding sites but is conserved among all P[II] RVs and two P[I] RVs (P[10] and P[12]), suggesting an evolutionary connection among these human and animal RVs. Taken together, these data are important for hypotheses on potential mechanisms for RV diversity, host ranges, and cross-species transmission. IMPORTANCE In this study, we found that our P[19] strain and other P[II] RVs recognize mucin cores and the type 1 HBGA precursors as the minimal functional units and that additional saccharides adjacent to these units can alter binding outcomes and thereby possibly host ranges. These data may help to explain why some P[II] RVs, such as P[6] and P[19], commonly infect animals but rarely humans, while others, such as the P[4] and P[8] RVs, mainly infect humans and are predominant over other P genotypes. Elucidation of the molecular bases for strain-specific host ranges and cross-species transmission of these human and animal RVs is important to understand RV epidemiology and disease burden, which may impact development of control and prevention strategies against RV gastroenteritis.
The Dark Matter, Gas and Galaxy Distributions in Abell 2218: A Weak Gravitational Lensing and X-ray Analysis

We report on the detection of dark matter in the cluster Abell 2218 using the weak gravitational distortion of background galaxies. We find a highly significant, coherent detection of the distortion in the images of the background galaxies. The inferred 2D mass distribution has a peak that is coincident with the optical and X-ray centroid. The qualitative distributions of the cluster light, the X-ray emission and the dark matter are similar and the projected total mass, gas, and light surface densities are consistent with a $r^{-1}$ profile at distance of $r > 180^{\prime\prime}$ from the cluster cD galaxy. Using the weak lensing technique, we determine a lower bound for the total mass in A2218 of $(3.9 \pm 0.7) \times 10^{14}$~h$^{-1}$~M$_\odot$ within a fiducial aperture of radius 0.4~h$^{-1}$Mpc. The associated cluster mass-to-light ratio is $(440 \pm 80)$~h~$M_\odot/L_{\odot B}$. The mass estimated by the weak lensing method is consistent with that inferred from the X-ray data under the assumption of hydrostatic equilibrium and we derive an upper bound for the gas-to-total mass ratio at 400~h$^{-1}$kpc of $M_{gas}/M_{tot} = (0.04 \pm 0.02)$h$^{-3/2}$.
Ambient Noise Tomography of Northeastern China , the Korean Peninsula , and the Sea of Japan

This study lays the foundation for a high-resolution 3-D model of the crust and uppermost mantle to a depth of about 80 km beneath northeastern China and surrounding regions. Such a model is motivated to produce new constraints on the massive volcanism, crustal extension, cratonic rejuvenation, and lithospheric thinning that are hypothesized for northeastern China. Ambient noise tomography is particularly needed to constrain the structure of the crust, and complements information from other types of data. Ambient noise tomography is applied here to data from more than 300 broad-band seismic stations from Chinese Provincial networks, the Japanese F-Net, and the IRIS Global Seismic Network, producing more than 50,000 inter-station paths across the region. Two years of continuous data from 2007 into 2009 are used to produce group and phase velocity maps from 12 sec to 45 sec period across northeastern China, the Korean Peninsula, and the Sea of Japan. To generate the Rayleigh wave dispersion maps, the effects of the persistent localized Kyushu microseism were eliminated in the dispersion measurements. In doing so, the location of the microseism by Zeng and Ni (2010) is confirmed. Average resolution across the study region is estimated to be about 100 km. The dispersion maps are geologically coherent, displaying the signatures of a variety of crustal structures, including sedimentary basins, mountain roots, ocean-continent variations, and anomalies due to continental rifting and volcanism. The maps at different periods and between phase and group velocities are consistent with one another, and vertically relatively smooth Vs models are shown fit the observations well.
The environmental dependence of the chemical properties of star-forming galaxies

We use a 0.040 < z < 0.085 sample of 37 866 star-forming galaxies from the Fourth Data Release of the Sloan Digital Sky Survey to investigate the dependence of gas-phase chemical properties on stellar mass and environment. The local density, determined from the projected distances to the fourth and fifth nearest neighbours, is used as an environment indicator. Considering environments ranging from voids, i.e. log Σ ≤ -0.8, to the periphery of galaxy clusters, i.e. log E ≈ 0.8, we find no dependence of the relationship between galaxy stellar mass and gas-phase oxygen abundance, along with its associated scatter, on local galaxy density. However, the star-forming gas in galaxies shows a marginal increase in the chemical enrichment level at a fixed stellar mass in denser environments. Compared with galaxies of similar stellar mass in low-density environments, they are enhanced by a few per cent for massive galaxies to about 20 per cent for galaxies with stellar masses ≤10 9.5 M ⊙ . These results imply that the evolution of star-forming galaxies is driven primarily by their intrinsic properties and is largely independent of their environment over a large range of local galaxy density.
Detection of Various Vehicles Using Wireless Seismic Sensor Network

The Detection of vehicles, whether wheeled or tracked can be achieved using seismic sensors as all vehicles when they move create vibrations which travel as waves through the earth and based on the type of vibrations generated by the movement of vehicles; classification of the vehicles can be carried out. This can also be achieved by using acoustic sensors but this approach inherits the problem of Doppler shift which is also associated with detection of signals through Radars. This paper is devoted to seismic detection of vehicles by using unpowered geophones sensors. The event triggering is captured in real time in different terrain scenarios like loose earth or concrete approaches. The geophones are connected through wires with the event detection and data analyzing system. However, the complexity of the seismic waves and its dependency on the underlying geological characteristics throws the challenges in the vehicle detection and recognition and extraction of robust feature vector which can explicitly correspond to a specific type of vehicle or target. This paper has emerged from the series of field experiments carried out and performance evaluation conducted to derive the optimal relationship of the different parameters. It proposes a new feature extraction algorithm- spectral statistics and wavelet coefficients characterization (SSWCC). SSWCC extracts a feature vector from both the frequency and the time frequency domain analysis of the seismic signals, including the spectrum, the power spectral density (PSD) and the wavelet coefficients. The SSWCC algorithm is designed for real-time applications, and a series of experiments shown its robustness and effectiveness.
Optimal dynamic pricing of inventories with stochastic demand over finite horizons

In many industries, managers face the problem of selling a given stock of items by a deadline. We investigate the problem of dynamically pricing such inventories when demand is price sensitive and stochastic and the firm's objective is to maximize expected revenues. Examples that fit this framework include retailers selling fashion and seasonal goods and the travel and leisure industry, which markets space such as seats on airline flights, cabins on vacation cruises, and rooms in hotels that become worthless if not sold by a specific time. We formulate this problem using intensity control and obtain structural monotonicity results for the optimal intensity resp. , price as a function of the stock level and the length of the horizon. For a particular exponential family of demand functions, we find the optimal pricing policy in closed form. For general demand functions, we find an upper bound on the expected revenue based on analyzing the deterministic version of the problem and use this bound to prove that simple, fixed price policies are asymptotically optimal as the volume of expected sales tends to infinity. Finally, we extend our results to the case where demand is compound Poisson; only a finite number of prices is allowed; the demand rate is time varying; holding costs are incurred and cash flows are discounted; the initial stock is a decision variable; and reordering, overbooking, and random cancellations are allowed.
A Multivariate Artificial Neural Network Approach for Rainfall Forecasting: Case Study of Victoria, Australia

El Nino southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) have enormous effects on the precipitations around the world. Australian rainfall is also affected by these key modes of complex climate variables. Many studies have tried to establish the relationships of these large-scale climate indices among the rainfalls of different parts of Australia, particularly Western Australia, New South Wales, Queensland and Victoria. Unlike the other regions, no clear relationship can be found between each individual large-scale climate mode and Victorian rainfall. Past studies considering southeast Australian rainfall predictability could achieve a maximum of 30% correlation. This study looks into the lagged-time relationships of these modes on Victorian spring rainfall. On the other hand, few attempts have been made to establish the combined effect of these indices on rainfall in order to develop a better understanding and forecasting system. Since rainfall is a complicated atmospheric phenomenon, linear techniques might not be sufficient enough to capture its characteristics. This research attempts to find a nonlinear relationship between the Victorian rainfall and the lagged-indices affecting the region using Artificial Neural Networks (ANN). It was discovered that ANN modelling is able to provide higher correlations using the lagged-indices to forecast spring rainfall in compared to linear methods. Using these indices in an ANN model increased the model correlation up to 99%, 98% and 43% for the three case study stations of Horsham, Melbourne and Orbost in Victoria, Australia respectively. it seems that IOD has a higher effect on the centre and west of Victoria more than the ENSO, while ENSO seems to have a stronger effect on the east side. This method can be used for other parts of the world where a relationship exists between rainfall and large scale climate modes which could not be established by linear methods. Index Terms—Rainfall, ENSO, IOD, forecasting, ANN
Toxic Effect of Colchicine on Hippocampal Cortical Area

Background and Objectives: Study of deleterious effect of neurotoxins on the animals' brain is a fascinating research plan. In this project, the damage effect of colchicine on the hippocampal cornu ammonis 1 (CA1) was examined by the studying of the hippocampal tissue. Materials and Methods: Injections of colchicine (5,25 μg/rat, intrahippocampal CA1) were performed in cannulated male Wistar rats while being settled in the stereotaxic apparatus. Control group was solely injected saline (1 μl/rat, intra-CA1). Other groups of rats were trained in the conditioning device to receive the colchicine (5 and 25 µg/rat, intra- CA1) prior to the testing; the control group was given saline (1 µl/rat, intra-CA1). At the end of the experiments, the rats were decapitated and their brains were removed for histological studies. Results: The number of the small pyramidal cells of hippocampal CA1 showed a decrease in the colchicine-received rats than the control group. The novelty behavioral assessment showed a significant difference between the colchicine given rats versus control (p<0.05). Conclusion: Hippocampal CA1 layer plays an important role in the memory and learning processes. Lesion of this region by the aid of neurotoxins (e.g. colchicine) may lead us to provide a proper animal model to study the learning dysfunctions in the future. This research may appropriately validate the lesion effect of the toxin in the hippocampal CA1. It may also propose an incidence of the novelty seeking behavior due to the lesion in the hippocampus.
Components of the plasma membrane of growing axons. I. Size and distribution of intramembrane particles

The plasmalemma of mature and growing olfactory axons of the bullfrog has been studied by freeze-fracture. Intramembrane particles (IMPs) of mature olfactory axons are found to be uniformly distributed along the shaft. However, during growth, a decreasing gradient of IMP density is evident along the somatofugal axis. The size histograms of axolemmal IMPs from different segments of growing nerve reveal regional differences in the particle composition. The distribution of each individual size class of particles along the growing nerve forms a decreasing gradient in the somatofugal direction; the slope of these gradients varies directly with particle diameter. These size-dependent density gradients are consistent with a process of lateral diffusion of membrane components that are inserted proximally into the plasma membrane. The membrane composition of the growth cone, however, appears to be independent of these diffusion gradients; it displays a mosaic pattern of discrete domains of high and low particle densities. The relative IMP profiles of these growth cone regions are similar to one another but contain higher densities of large IMPs than the neighboring axonal shaft. The shifting distributions of intramembrane particles that characterize the sprouting neuron give new insights into cellular processes that may underlie the establishment of the functional polarity of the neuron and into the dynamics of axolemmal maturation.