Participative Budgeting and Participant Motivation: A Review of the Literature

In their discussion - Participative Budgeting and Participant Motivation: A Review of the Literature - by Frederick J. Demicco, Assistant Professor, School of Hotel, Restaurant and Institutional Management, The Pennsylvania State University and Steven J. Dempsey, Fulton F. Galer, Martin Baker, Graduate Assistants, College of Business at Virginia Polytechnic Institute and State University, the authors initially observe: “In recent years behavioral literature has stressed the importance of participation In goal-setting by those most directly affected by those goals. The common postulate is that greater participation by employees in the various management functions, especially the planning function, will lead to improved motivation, performance, coordination, and functional behavior. The authors analyze this postulate as it relates to the budgeting process and discuss whether or not participative budgeting has a significant positive impact on the motivations of budget participants.” In defining the concept of budgeting, the authors offer: “Budgeting is usually viewed as encompassing the preparation and adoption of a detailed financial operating plan…” In furthering that statement they also furnish that budgeting’s focus is to influence, in a positive way, how managers plan and coordinate the activities of a property in a way that will enhance their own performance. In essence, framing an organization within its described boundaries, and realizing its established goals. The authors will have you know, to control budget is to control operations. What kind of parallels can be drawn between the technical methods and procedures of budgeting, and managerial behavior? “In an effort to answer this question, Ronen and Livingstone have suggested that a fourth objective of budgeting exists, that of motivation,” say the authors with attribution. “The managerial function of motivation is manipulative in nature.” Demicco, Dempsey, Galer, and Baker attempt to quantify motivation as a psychological premise using the expectancy theory, which encompasses empirical support, intuitive appeal, and ease of application to the budgetary process. They also present you with House's Path-Goal model; essentially a mathematics type formula designed to gauge motivation. You really need to see this. The views of Argyris are also explored in particular detail. Although, the Argyris study was primarily aimed at manufacturing firms, and the effects on line-supervisors of the manufacturing budgets which were used to control and evaluate their performance, its application is relevant to the hospitality industry. As the title suggests, other notables in the field of behavioral motivation theory, and participation are also referenced. “Behavioral theory has been moving away from models of purported general applicability toward contingency models that are suited for particular situations,” say the authors in closing. “It is conceivable that some time in the future, contingency models will make possible the tailoring of budget strategies to individual budget holder personalities.”

Application of a PERT-Type System and "Crashing" in a Food Service Operation

A pert-type system, a combination of the program evaluation and review technique (PERT) and the critical path method (CPM), might be used by the hospitality industry to improve planning and control of complex functions. The author discusses this management science technique and how it can assist.

Forecasting future prevalence of type 2 diabetes mellitus in Syria

Background Type 2 diabetes mellitus (T2DM) is increasingly becoming a major public health problem worldwide. Estimating the future burden of diabetes is instrumental to guide the public health response to the epidemic. This study aims to project the prevalence of T2DM among adults in Syria over the period 2003–2022 by applying a modelling approach to the country’s own data. Methods Future prevalence of T2DM in Syria was estimated among adults aged 25 years and older for the period 2003–2022 using the IMPACT Diabetes Model (a discrete-state Markov model). Results According to our model, the prevalence of T2DM in Syria is projected to double in the period between 2003 and 2022 (from 10% to 21%). The projected increase in T2DM prevalence is higher in men (148%) than in women (93%). The increase in prevalence of T2DM is expected to be most marked in people younger than 55 years especially the 25–34 years age group. Conclusions The future projections of T2DM in Syria put it amongst countries with the highest levels of T2DM worldwide. It is estimated that by 2022 approximately a fifth of the Syrian population aged 25 years and older will have T2DM.

Fixed vs. variable noise in 2AFC contrast discrimination: lessons from psychometric functions.

Recent discussion regarding whether the noise that limits 2AFC discrimination performance is fixed or variable has focused either on describing experimental methods that presumably dissociate the effects of response mean and variance or on reanalyzing a published data set with the aim of determining how to solve the question through goodness-of-fit statistics. This paper illustrates that the question cannot be solved by fitting models to data and assessing goodness-of-fit because data on detection and discrimination performance can be indistinguishably fitted by models that assume either type of noise when each is coupled with a convenient form for the transducer function. Thus, success or failure at fitting a transducer model merely illustrates the capability (or lack thereof) of some particular combination of transducer function and variance function to account for the data, but it cannot disclose the nature of the noise. We also comment on some of the issues that have been raised in recent exchange on the topic, namely, the existence of additional constraints for the models, the presence of asymmetric asymptotes, the likelihood of history-dependent noise, and the potential of certain experimental methods to dissociate the effects of response mean and variance.

A heavy metal P-type ATPase OsHMA4 prevents copper accumulation in rice grain

Acknowledgements We thank B. Lahner, E. Yakubova and S. Rikiishi for ICP-MS analysis, N. Komiyama, Iowa State University Plant Transformation Facility and Prashant Hosmani for generation of transgenic rice, K. Wang for providing pTF101.1 vector and N. Verbruggen for providing pYES2 and pYEC2/CT-GFP vectors. We also thank Rice T-DNA Insertion Sequence Database center for providing the T-DNA insertion line and X. Wang, T. Zheng and Z. Li for accessing 3 K rice genome sequence, and Graeme Paton for helpful discussions on Cu bioavailability in water-logged soils. This research was supported by a Grant-in-Aid for Specially promoted Research (JSPS KAKENHI Grant Number 16H06296 to J.F.M), and the US National Science Foundation, Plant Genome Research Program (Grant #IOS 0701119 to D.E.S., M.L.G. and S.R.M.P.).

Type 2 diabetes, but not obesity, prevalence is positively associated with ambient temperature

Acknowledgements This study was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13030000), the National Science foundation of China (microevolution program NSFC91431102) and the 1000 talents program. We are grateful to members of the Molecular Energetics group in Beijing and the Energetics group in Aberdeen, UK for valuable discussion of the data and analysis. All data analysed in this paper are already available in the public domain.

Setting type on a linotype machine

Inscriptions: Verso: [stamped] Photograph by Freda Leinwand. [463 West Street, Studio 229G, New York, NY 10014].

Cutting type

Inscriptions: Verso: [stamped] Credit must be given to Leinwand from Monkmeyer Press Photo Service].

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Functional expression of a novel Kunitz type protease inhibitor from the human blood fluke Schistosoma mansoni

BACKGROUND: Schistosomes are able to survive for prolonged periods in the blood system, despite continuous contact with coagulatory factors and mediators of the host immune system. Protease inhibitors likely play a critical role in host immune modulation thereby promoting parasite survival in this extremely hostile environment. Even though Kunitz type serine protease inhibitors have been shown to play important physiological functions in a range of organisms these proteins are less well characterised in parasitic helminths.

METHODS: We have cloned one gene sequence from S. mansoni, Smp_147730 (SmKI-1) which is coded for single domain Kunitz type protease inhibitor, E. coli-expressed and purified. Immunolocalisation and western blotting was carried out using affinity purified polyclonal anti-SmKI-1 murine antibodies to determine SmKI-1 expression in the parasite. Protease inhibitor assays and coagulation assays were performed to evaluate the functional roles of SmKI-1.

RESULTS: SmKI-1 is localised in the tegument of adult worms and the sub-shell region of eggs. Furthermore, this Kunitz protein is secreted into the host in the ES products of the adult worm. Recombinant SmKI-1 inhibited mammalian trypsin, chymotrypsin, neutrophil elastase, FXa and plasma kallikrein with IC50 values of 35 nM, 61 nM, 56 nM, 142 nM and 112 nM, respectively. However, no inhibition was detected for pancreatic elastase or cathepsin G. SmKI-1 (4 μM) delayed blood clot formation, reflected in an approximately three fold increase in activated partial thromboplastin time and prothrombin time.

CONCLUSIONS: We have functionally characterised the first Kunitz type protease inhibitor (SmKI-1) from S. mansoni and show that it has anti-inflammatory and anti-coagulant properties. SmKI-1 is one of a number of putative Kunitz proteins in schistosomes that have presumably evolved as an adaptation to protect these parasites from the defence mechanisms of their mammalian hosts. As such they may represent novel vaccine candidates and/or drug targets for schistosomiasis control.

Functions of the SLC36 transporter Pathetic in growth control of Drosophila sensory neurons

Thesis (Ph.D.)--University of Washington, 2016-08

Big bang bifurcations in von Bertalanffy’s dynamics with strong and weak Allee effects

The main purpose of this work was to study population dynamic discrete models in which the growth of the population is described by generalized von Bertalanffy's functions, with an adjustment or correction factor of polynomial type. The consideration of this correction factor is made with the aim to introduce the Allee effect. To the class of generalized von Bertalanffy's functions is identified and characterized subclasses of strong and weak Allee's functions and functions with no Allee effect. This classification is founded on the concepts of strong and weak Allee's effects to population growth rates associated. A complete description of the dynamic behavior is given, where we provide necessary conditions for the occurrence of unconditional and essential extinction types. The bifurcation structures of the parameter plane are analyzed regarding the evolution of the Allee limit with the aim to understand how the transition from strong Allee effect to no Allee effect, passing through the weak Allee effect, is realized. To generalized von Bertalanffy's functions with strong and weak Allee effects is identified an Allee's effect region, to which is associated the concepts of chaotic semistability curve and Allee's bifurcation point. We verified that under some sufficient conditions, generalized von Bertalanffy's functions have a particular bifurcation structure: the big bang bifurcations of the so-called box-within-a-box type. To this family of maps, the Allee bifurcation points and the big bang bifurcation points are characterized by the symmetric of Allee's limit and by a null intrinsic growth rate. The present paper is also a significant contribution in the framework of the big bang bifurcation analysis for continuous 1D maps and unveil their relationship with the explosion birth and the extinction phenomena.

Neurorehabilitation of hand functions using brain computer interface

Introduction: Brain computer interface (BCI) is a promising new technology with possible application in neurorehabilitation after spinal cord injury. Movement imagination or attempted movement-based BCI coupled with functional electrical stimulation (FES) enables the simultaneous activation of the motor cortices and the muscles they control. When using the BCI- coupled with FES (known as BCI-FES), the subject activates the motor cortex using attempted movement or movement imagination of a limb. The BCI system detects the motor cortex activation and activates the FES attached to the muscles of the limb the subject is attempting or imaging to move. In this way the afferent and the efferent pathways of the nervous system are simultaneously activated. This simultaneous activation encourages Hebbian type learning which could be beneficial in functional rehabilitation after spinal cord injury (SCI). The FES is already in use in several SCI rehabilitation units but there is currently not enough clinical evidence to support the use of BCI-FES for rehabilitation. Aims: The main aim of this thesis is to assess outcomes in sub-acute tetraplegic patients using BCI-FES for functional hand rehabilitation. In addition, the thesis explores different methods for assessing neurological rehabilitation especially after BCI-FES therapy. The thesis also investigated mental rotation as a possible rehabilitation method in SCI. Methods: Following investigation into applicable methods that can be used to implement rehabilitative BCI, a BCI based on attempted movement was built. Further, the BCI was used to build a BCI-FES system. The BCI-FES system was used to deliver therapy to seven sub-acute tetraplegic patients who were scheduled to receive the therapy over a total period of 20 working days. These seven patients are in a 'BCI-FES' group. Five more patients were also recruited and offered equivalent FES quantity without the BCI. These further five patients are in a 'FES-only' group. Neurological and functional measures were investigated and used to assess both patient groups before and after therapy. Results: The results of the two groups of patients were compared. The patients in the BCI-FES group had better improvements. These improvements were found with outcome measures assessing neurological changes. The neurological changes following the use of the BCI-FES showed that during movement attempt, the activation of the motor cortex areas of the SCI patients became closer to the activation found in healthy individuals. The intensity of the activation and its spatial localisation both improved suggesting desirable cortical reorganisation. Furthermore, the responses of the somatosensory cortex during sensory stimulation were of clear evidence of better improvement in patients who used the BCI-FES. Missing somatosensory evoked potential peaks returned more for the BCI-FES group while there was no overall change in the FES-only group. Although the BCI-FES group had better neurological improvement, they did not show better functional improvement than the FES-only group. This was attributed mainly to the short duration of the study where therapies were only delivered for 20 working days. Conclusions: The results obtained from this study have shown that BCI-FES may induce cortical changes in the desired direction at least faster than FES alone. The observation of better improvement in the patients who used the BCI-FES is a good result in neurorehabilitation and it shows the potential of thought-controlled FES as a neurorehabilitation tool. These results back other studies that have shown the potential of BCI-FES in rehabilitation following neurological injuries that lead to movement impairment. Although the results are promising, further studies are necessary given the small number of subjects in the current study.

Decoherence models for discrete-time quantum walks and their application to neutral atom experiments

We discuss decoherence in discrete-time quantum walks in terms of a phenomenological model that distinguishes spin and spatial decoherence. We identify the dominating mechanisms that affect quantum-walk experiments realized with neutral atoms walking in an optical lattice. From the measured spatial distributions, we determine with good precision the amount of decoherence per step, which provides a quantitative indication of the quality of our quantum walks. In particular, we find that spin decoherence is the main mechanism responsible for the loss of coherence in our experiment. We also find that the sole observation of ballistic-instead of diffusive-expansion in position space is not a good indicator of the range of coherent delocalization. We provide further physical insight by distinguishing the effects of short- and long-time spin dephasing mechanisms. We introduce the concept of coherence length in the discrete-time quantum walk, which quantifies the range of spatial coherences. Unexpectedly, we find that quasi-stationary dephasing does not modify the local properties of the quantum walk, but instead affects spatial coherences. For a visual representation of decoherence phenomena in phase space, we have developed a formalism based on a discrete analogue of the Wigner function. We show that the effects of spin and spatial decoherence differ dramatically in momentum space.