Miracle-dz/UniFAR-FTUs huggingface dataset:
Negotiators at work: Three essays on employee negotiation skill development and exhibition

NEGOTIATORS AT WORK: THREE ESSAYS ON EMPLOYEE NEGOTIATION SKILL DEVELOPMENT AND EXHIBITION BY Elizabeth Foster Clenney March 29, 2013 Committee Chairs: Todd J. Maurer and Edward W. Miles Major Academic Unit: Managerial Sciences The need to negotiate is pervasive, but the ability to do so effectively is not so commonplace and is an often assumed or taken-for-granted skill. Despite the fact that people negotiate something nearly every day, be it in their personal or professional lives, very few people undergo formal negotiation skill training. In fact, most people overestimate their negotiating abilities, primarily because they never receive feedback on their skills. Consequently, this overestimation of negotiating ability often leads people to unknowingly negotiate suboptimal agreements. In other words, they can do better. In an organizational setting, many employees have to negotiate as a normal and customary part of their job; however, unlike other essential skills, such as technical skills or general communication skills, negotiation skills are not as widely taught and are frequently assumed to be mastered. Furthermore, organizations will place great emphasis on the outcomes of employee negotiations rather than the skills that lead to those outcomes. Similarly, scholarly research on negotiation seems to mimic this focus, where there are many studies related to negotiation outcomes and even general tactics (e.g., making the first offer, setting target and resistance points, etc.) prescribed to obtain outcomes. However, there is a large gap in understanding how people acquire and why they exhibit particular negotiation skills. Furthermore, the relationship between specific negotiation skills and specific negotiated outcomes has been inferred or tested indirectly in previous research. Studies in this dissertation directly examine if acquiring a particular negotiation skill set does lead to particular negotiated outcomes. This dissertation aims to set forth an initial framework for employee negotiation skill development and test key relationships to support the idea that not everyone acquires the same set of negotiation skills or are effective in every negotiation situation. This overall argument will be presented via three essays, the first proposes a theoretical framework and the second and third empirically test relationships set forth in the theory paper.
A Role for the Unfolded Protein Response (UPR) in Virulence and Antifungal Susceptibility in Aspergillus fumigatus

Filamentous fungi rely heavily on the secretory pathway, both for the delivery of cell wall components to the hyphal tip and the production and secretion of extracellular hydrolytic enzymes needed to support growth on polymeric substrates. Increased demand on the secretory system exerts stress on the endoplasmic reticulum (ER), which is countered by the activation of a coordinated stress response pathway termed the unfolded protein response (UPR). To determine the contribution of the UPR to the growth and virulence of the filamentous fungal pathogen Aspergillus fumigatus, we disrupted the hacA gene, encoding the major transcriptional regulator of the UPR. The ΔhacA mutant was unable to activate the UPR in response to ER stress and was hypersensitive to agents that disrupt ER homeostasis or the cell wall. Failure to induce the UPR did not affect radial growth on rich medium at 37°C, but cell wall integrity was disrupted at 45°C, resulting in a dramatic loss in viability. The ΔhacA mutant displayed a reduced capacity for protease secretion and was growth-impaired when challenged to assimilate nutrients from complex substrates. In addition, the ΔhacA mutant exhibited increased susceptibility to current antifungal agents that disrupt the membrane or cell wall and had attenuated virulence in multiple mouse models of invasive aspergillosis. These results demonstrate the importance of ER homeostasis to the growth and virulence of A. fumigatus and suggest that targeting the UPR, either alone or in combination with other antifungal drugs, would be an effective antifungal strategy.
Non-contiguous finished genome sequence of the opportunistic oral pathogen Prevotella multisaccharivorax type strain (PPPA20T)

Prevotella multisaccharivorax Sakamoto et al. 2005 is a species of the large genus Prevotella, which belongs to the family Prevotellaceae. The species is of medical interest because its members are able to cause diseases in the human oral cavity such as periodontitis, root caries and others. Although 77 Prevotella genomes have already been sequenced or are targeted for sequencing, this is only the second completed genome sequence of a type strain of a species within the genus Prevotella to be published. The 3,388,644 bp long genome is assembled in three non-contiguous contigs, harbors 2,876 protein-coding and 75 RNA genes and is a part of the GenomicEncyclopedia ofBacteria andArchaea project.
Source coding with a permutation-based reversible memory-binding transform for data compression in categorical data domains

A general purpose reversible memory-binding transform (MBT) is developed, which uses a permutation transform technique to bind memory information to a transformed signal alphabet. The algorithm performs well in conjunction with a Huffman coder for both ordered sources, such as pixel intensities, and categorical sources, such as vector quantized codebook indices.
Physiological adaptive indicators in fasted neonate broiler chicks in response to calcium gluconate injection.

Four hundred and eighty mixed-sex broiler chicks aged 3 h after hatching were allotted according to a completely random design in a 6 × 2 × 2 factorial schedule into two groups of 12 replications of 20 chicks each. The main experimental factors were fasting for 0, 6, 12, 24, 36 and 48 h after chick placement and calcium gluconate (Ca-glu) injection (0 and 0.6 ml). Live body weight (BW) of chicks decreased linearly (Y = 43.36-0.109BW0 h , r(2) = 0.876) as neonatal fasting extended. Injection of 0.6 ml Ca-glu at 3 h post-hatching did not affect weight loss of chicks. Yolk residuals (YR) utilized linearly (Y = 5.75-0.062YR, r(2) = 0.956) by 0.062 g/h in neonate fasted chicks up to 48 h, showing no effect of Ca-glu injection. Neonatal fasting periods longer than 12 h increased liver weight (p < 0.05). The mean absolute and proportional (% of BW0 h ) breast and leg weight were reduced linearly as neonatal fasting extended (p < 0.05). Serum glucose concentration increased up to 6 h and then reduced linearly to 150 mg/dl after 48-h fasting. The Ca-glu treatment influenced serum glucose level for a short period up to 6 h of fasting. Serum Ca concentration sharply increased up to threefolds in the birds received Ca-glu injection resulting in acute hypercalcemia, then decreased to the initial level after 24-h feed withdrawal (p < 0.05). The mean serum level for creatinine, uric acid, cholesterol, HDL, albumins and total proteins significantly increased during the fasting periods of 6 to 48 h and significantly elevated in the birds receiving 0.6-ml Ca-glu injection compared with the non-treated chicks (p < 0.05). It was concluded that subcutaneous administration of 0.6 ml Ca-glu in the chick's neck did not suitably support the increased metabolic demands for glucose and calcium in feed-deprived neonate chicks.
The Protein Information Resource

The Protein Information Resource (PIR) is an integrated public resource of protein informatics that supports genomic and proteomic research and scientific discovery. PIR maintains the Protein Sequence Database (PSD), an annotated protein database containing over 283 000 sequences covering the entire taxonomic range. Family classification is used for sensitive identification, consistent annotation, and detection of annotation errors. The superfamily curation defines signature domain architecture and categorizes memberships to improve automated classification. To increase the amount of experimental annotation, the PIR has developed a bibliography system for literature searching, mapping, and user submission, and has conducted retrospective attribution of citations for experimental features. PIR also maintains NREF, a non-redundant reference database, and iProClass, an integrated database of protein family, function, and structure information. PIR-NREF provides a timely and comprehensive collection of protein sequences, currently consisting of more than 1 000 000 entries from PIR-PSD, SWISS-PROT, TrEMBL, RefSeq, GenPept, and PDB. The PIR web site (http://pir.georgetown.edu) connects data analysis tools to underlying databases for information retrieval and knowledge discovery, with functionalities for interactive queries, combinations of sequence and text searches, and sorting and visual exploration of search results. The FTP site provides free download for PSD and NREF biweekly releases and auxiliary databases and files.
The Influence of Public Policy on Health, Wealth and Mortality

In this project we extend an augmented lifecycle model, incorporating a Grossman-style model of health capital, to enhance understanding of factors influencing consumption, wealth and health. We develop three primary results when using the model to explore the effects of stylized versions of Medicare and Social Security on wealth and longevity. First, our model calibration implies consumption and health are complements. As health depreciates with age, households will get less utility from consumption than would be in the case of a lifecycle model that does not endogenize health. Second, it appears that forward-looking households, when confronted by a substantially reduced safety net, will respond by reducing consumption and by reducing their health investment and therefore longevity. Third, there is a potentially important difference between short- and long- run responses to policy.
Categorical Models for a Semantically Linear Lambda-calculus

This paper is about a categorical approach to model a very simple Semantically Linear lambda calculus, named Sll-calculus. This is a core calculus underlying the programming language SlPCF. In particular, in this work, we introduce the notion of Sll-Category, which is able to describe a very large class of sound models of Sll-calculus. Sll-Category extends in the natural way Benton, Bierman, Hyland and de Paiva's Linear Category, in order to soundly interpret all the constructs of Sll-calculus. This category is general enough to catch interesting models in Scott Domains and Coherence Spaces.
Statistical Analysis on Large Scale Chinese Short Message Corpus and Automatic Short Message Error Correction

Analysis of short message corpus is an important foundation for research of automatic short message processing technology. Based on large scale short message corpus, this paper firstly presents statistical data and performs analysis in detail on basic information of short message corpus and special language phenomena in it. The distributions of the corpus parameters and special language phenomena are also given out. The statistical results presented in the paper are meaningful for research of robust short message understanding and implementation of short message based manmachine dialog system and short message based machine translation system. And we also build an automatic error correction system on mobile phone to correct the misapplication of Chinese character in short messages. The preliminary results show that our method is effective.
The Wyatt Sex History Questionnaire

The complexities of developing appropriate formats for obtaining sexual histories that include women's consensual and coercive sexual experiences are discussed in this paper. The Wyatt Sex History Questionnaire (WSHQ), used with a multi-ethnic sample of women, is described to obtain incidents of non-consensual sexual abuse. The advantages of using a face-to-face format to obtain incidents of child sexual victimization are highlighted. In order to assess a range of effects of women's consensual sexual functioning, items of the WSHQ, administered in telephone and face-to-face interviews, through self report measures and indirect questioning using randomized responses, were compared for their effectiveness in obtaining consensual sexual experiences. The advantages of using face-to-face interview techniques with multi-ethnic community sample to assess the affects of non-consensual sexual experiences in childhood on women's consensual sexual practices is discussed.
Large-Scale Testing of Bibliome Informatics Using Pfam Protein Families

Literature mining is expected to help not only with automatically sifting through huge biomedical literature and annotation databases, but also with linking bio-chemical entities to appropriate functional hypotheses. However, there has been very limited success in testing literature mining methods due to the lack of large, objectively validated test sets or "gold standards". To improve this situation we created a large-scale test of literature mining methods and resources. We report on a specific implementation of this test: how well can the Pfam protein family classification be replicated from independently mining different literature/annotation resources? We test and compare different keyterm sets as well as different algorithms for issuing protein family predictions. We find that protein families can indeed be automatically predicted from the literature. Using words from PubMed abstracts, of 3663 proteins tested, over 75% were correctly assigned to one of 618 Pfam families. For 90% of proteins the correct Pfam family was among the top 5 ranked families. We found that protein family prediction is far superior with keywords extracted from PubMed abstracts than with GO annotations or MeSH keyterms, suggesting that the text itself (in combination with the vector space model) is superior to GO and MeSH as a literature mining resources, at least for detecting protein family membership. Finally, we show that Shannon's entropy can be exploited to improve prediction by facilitating the integration of the different literature sources tested.
TAPIR: A software toolkit for approximating and adapting POMDP solutions online

One of the fundamental challenges in the design of autonomous robots is to reliably compute motion strategies in spite of significant uncertainty about sensor reliability, control errors, and unpredicatable events. The Partially Observable Markov Decision Process (POMDP) is a general and mathematically principled framework for this type of problem. Although exact solutions are computationally intractable, modern approximate POMDP solvers have made POMDP-based approaches practical for robotics tasks. However, almost all existing POMDP-based planning software suffers from at least two major issues. Firstly, most POMDP solvers require the model to be known a priori and remain constant during runtime, and secondly, quite a lot of the existing software is not very userfriendly. This paper presents the Toolkit for approximating and Adapting POMDP solutions In Real time (TAPIR), which tackles both problems. The need for a constant, fully known POMDP model is averted by implementing the recent Adaptive Belief Tree (ABT) algorithm, while user-friendliness is ensured by a welldocumented modular design, which also includes interfaces for the commonly-used Robotics Operating System (ROS) framework, and the high fidelity simulator V-REP. TAPIR can be downloaded from http://robotics.itee. uq. edu.au/~tapir. To the best of our knowledge, TAPIR is the first software toolkit that directly addresses the aforementioned problems.
Managing non-functional uncertainty via model-driven adaptivity

Modern software systems are often characterized by uncertainty and changes in the environment in which they are embedded. Hence, they must be designed as adaptive systems. We propose a framework that supports adaptation to non-functional manifestations of uncertainty. Our framework allows engineers to derive, from an initial model of the system, a finite state automaton augmented with probabilities. The system is then executed by an interpreter that navigates the automaton and invokes the component implementations associated to the states it traverses. The interpreter adapts the execution by choosing among alternative possible paths of the automaton in order to maximize the system's ability to meet its non-functional requirements. To demonstrate the adaptation capabilities of the proposed approach we implemented an adaptive application inspired by an existing worldwide distributed mobile application and we discussed several adaptation scenarios.
Square Root approximation to the Poisson Channel

Starting from the Poisson model we present a channel model for optical communications, called the Square Root (SR) Channel, in which the noise is additive Gaussian with constant variance. Initially, we prove that for large peak or average power, the transmission rate of a Poisson Channel when coding and decoding methods for the SR Channel are used, converges to the capacity of the Poisson Channel. Then, we derive bounds and asymptotic expressions for the capacity of the SR Channel, and compare them to those of other optical channel models. Finally, signal-independent noise sources are discussed.
Lifetime-Optimal Data Routing in Wireless Sensor Networks Without Flow Splitting

We consider two-tiered wireless sensor networks, and address the network lifetime problem for upper-tier aggregation and forwarding nodes (AFNs). Existing flow routing solutions proposed for maximizing network lifetime require AFNs to transmit flows to different nodes at the same time, which we call multi-session flow routing solutions. If an AFN is equipped with a single transmitter/receiver pair, a multi-session flow routing solution requires a packet-level power control at the AFN. In this paper, we show that it is possible to achieve the same optimal network lifetime by power control on a much larger timescale with the so-called single-session flow routing solutions. More importantly, we show how to perform optimal single-session flow routing when the bit-rate of composite flows generated by AFNs is time-varying, as long as the average bit-rate can be estimated. These results offer new understanding on energyconstrained flow routing in wireless sensor networks.
The use of extracted BSIM3v3 MOS parameters for fast design of circuits on weak inversion

This work describes a methodology for the extraction of DC parameters of MOS transistors on weak inversion from BSIM3v3 model. Once the optimum model for manual calculations has been defined, the parameters are obtained using the minimum square method. The results show that the proposed method improves the precision of the transistors 'dimensions' calculations, by giving a determination index r/sup 3/ to the I vs V relation, which is 99.31% of the worst case, when compared to the BSIM3v3.
Hoverfly mimicry deceives humans

It is believed that the resemblance of many hoverflies to stinging hymenopterans is a case of Batesian mimicry, though there is little experimental evidence that it is effective in protecting them from predators. In this study the effectiveness of hoverfly mimicry was investigated for humans by presenting groups of university students and schoolchildren with a questionnaire which included pictures of stinging hymenopterans, mimetic hoverflies and dipteran controls. More people thought that the mimics would sting than either of the control flies, though fewer than those who thought that the mimics' hymenopteran models would sting. This showed that the hoverflies' mimicry worked but was not 100% effective. More people thought that the good mimics would sting than poor mimics which were black and yellow, showing that the reaction was not just due to their warning coloration. Students' identification skills were poor; only 77%, 66% and 50% were able to correctly identify wasps, bumblebees and honeybees, respectively, but even knowledgeable students were confused by mimetic hoverflies. Significantly more of the students who had been stung thought that the Hymenoptera would sting and identified Hymenoptera correctly. Students who thought a hymenopteran would sting were in turn more likely to think that its mimic would sting. This suggests that the mimicry is partly mediated by experience. However, even students who had never been stung showed the same pattern of discrimination as those who had, suggesting that information is also passed on culturally. These results suggest that mimicry is effective and might help hoverflies avoid predation by birds but, as many of the subjects said they would kill a stinging insect, this would actually increase their chances of being killed by humans.
Multi-processor system design with ESPAM

For modern embedded systems, the complexity of embedded applications has reached a point where the performance requirements of these applications can no longer be supported by embedded system architectures based on a single processor. Thus, the emerging embedded System-on-Chip platforms are increasingly becoming multiprocessor architectures. As a consequence, two major problems emerge, i.e., how to design and how to program such multiprocessor platforms in a systematic and automated way in order to reduce the design time and to satisfy the performance needs of applications executed on these platforms. Unfortunately, most of the current design methodologies and tools are based on Register Transfer Level (RTL) descriptions, mostly created by hand. Such methodologies are inadequate, because creating RTL descriptions of complex multiprocessor systems is error-prone and time consuming. As an efficient solution to these two problems, in this paper we propose a methodology and techniques implemented in a tool called ESPAM for automated multiprocessor system design and implementation. ESPAM moves the design specification from RTL to a higher, so called system level of abstraction. We explain how starting from system level platform, application, and mapping specifications, a multiprocessor platform is synthesized and programmed in a systematic and automated way. Furthermore, we present some results obtained by applying our methodology and ESPAM tool to automatically generate multiprocessor systems that execute a real-life application, namely a Motion-JPEG encoder.
Efficient Parallel Community Detection in Large Edge-Intensive Networks

Community detection is a classic and very difficult task in social network analysis. A large number of methods have been developed for both efficient and effective community detection. However, much of the existing methods are heavily dependent on the number of links in the network, and thus they often suffer from the computational inefficiency when meeting large edge-intensive networks. In this paper, we present a novel SIMPLifying and Ensembling (SIMPLE) framework for parallel community detection. It employs the random link sampling to simplify the network and obtain basic partitionings on every sampled graphs. Then, the K-means-based Consensus Clustering is used to ensemble a number of basic partitionings to get high-quality community structures. Meanwhile, steps of random sampling and sampled graph partitioning are encapsulated into MapReduce to further improve the efficiency. Experiments on four real-world social networks analyze key parameters and factors inside SIMPLE, and demonstrate the effectiveness of the SIMPLE.