Miracle-dz/UniFAR-FTUs huggingface dataset:
Hard Times: Leadership in America

Leadership has never played a more prominent role in America's national discourse, and yet our opinions of leaders are at all-time lows. Private sector leaders are widely seen as greedy to the point of being corrupt. Public sector leaders are viewed as incompetent to the point of being inept. And, levels of trust in government have plummeted. As the title of this book conveys, leaders in America are experiencing hard times.Barbara Kellerman argues that we focus on leaders, and even on followers, while ignoring an essential element of leadership: context. This book is a corrective. It enables leaders to track the terrain that they must navigate in order to create change. Rather than a handy-dandy manual on what to do and how to do it, Hard Times is structured as a checklist. Twenty-four brief sections cover key aspects of the American landscape. They trace evolutions and revolutions that have revised our norms, transformed our populations and institutions, and shifted our culture.Kellerman's crash course on context reveals how significant it is to leadership. Clearer still is the fact that leadership is more difficult than it has ever been. It is context that explains why leadership is so fraught with frustration. And, it is context that makes evident why leadership will be better exercised if it is better understood. Calling out patterns that emerge from the checklist, Kellerman challenges leaders to do better. This fascinating read will change the way that all of us think about leadership, while compelling us to consider what it means for our future.
Maximizing Spectrum Utilization of Cognitive Radio Networks Using Channel Allocation and Power Control

We consider a cognitive radio network in which a set of base stations make opportunistic unlicensed spectrum access to transmit data to their subscribers. As the spectrum of interest is licensed to another (primary) network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to any primary user. We are interested in spectrum-allocation/power-control schemes that maximize the spectrum utilization of the cognitive network while appropriately protecting primary users. While doing so, the control schemes must also meet the required signal to interference plus noise ratio (SINR) of each subscriber of the cognitive network. This problem can be formulated as a linear mixed (0-1) integer programming. Due to the high complexity in obtaining optimal spectrum-allocation/power-control schemes, we propose a suboptimal scheme that can be obtained at lower complexity while still achieving good spectrum utilization. This suboptimal scheme is constructed based on the idea of a dynamic interference graph that captures the interfering effects. Numerical studies of our control scheme are presented.
Co-Evolving Better Strategies in Oligopolistic Price Wars

Using empirical market data from brand rivalry in a retail ground-coffee market, we model each idiosyncratic brand’s pricing behavior using the restriction that marketing strategies depend only on profit-relevant state variables, and use the genetic algorithm to search for coevolved equilibria, where each profit-maximizing brand manager is a stimulus-response automaton, responding to past prices in the asymmetric oligopolistic market. This chapter is part of a growing study of repeated interactions and oligopolistic behavior using the GA.
ON INTERCEPT ESTIMATION IN THE SAMPLE SELECTION MODEL

We provide a proof of the consistency and asymptotic normality of the estimator suggested by Heckman (1990, American Economic Review 80, 313–318) for the intercept of a semiparametrically estimated sample selection model. The estimator is based on “identification at infinity,” which leads to nonstandard convergence rate.
Beyond the Pipeline: Discrete Optimization in NLP

We present a discrete optimization model based on a linear programming formulation as an alternative to the cascade of classifiers implemented in many language processing systems. Since NLP tasks are correlated with one another, sequential processing does not guarantee optimal solutions. We apply our model in an NLG application and show that it performs better than a pipeline-based system.
Integrated Physiological, Biochemical, and Molecular Analysis Identifies Important Traits and Mechanisms Associated with Differential Response of Rice Genotypes to Elevated Temperature

In changing climatic conditions, heat stress caused by high temperature poses a serious threat to rice cultivation. A multiple organizational analysis at physiological, biochemical, and molecular levels is required to fully understand the impact of elevated temperature in rice. This study was aimed at deciphering the elevated temperature response in 11 popular and mega rice cultivars widely grown in India. Physiological and biochemical traits specifically membrane thermostability (MTS), antioxidants, and photosynthesis were studied at vegetative and reproductive phases, which were used to establish a correlation with grain yield under stress. Several useful traits in different genotypes were identified, which will be an important resource to develop high temperature-tolerant rice cultivars. Interestingly, Nagina22 emerged as the best performer in terms of yield as well as expression of physiological and biochemical traits at elevated temperature. It showed lesser relative injury, lesser reduction in chlorophyll content, increased super oxide dismutase, catalase and peroxidase activities, lesser reduction in net photosynthetic rate (PN), high transpiration rate (E), and other photosynthetic/fluorescence parameters contributing to least reduction in spikelet fertility and grain yield at elevated temperature. Furthermore, expression of 14 genes including heat shock transcription factors and heat shock proteins was analyzed in Nagina22 (tolerant) and Vandana (susceptible) at flowering phase, strengthening the fact that N22 performed better at molecular level also during elevated temperature. This study shows that elevated temperature response is complex and involves multiple biological processes that are needed to be characterized to address the challenges of extreme conditions of future climate.
Identification of a Highly Conserved Epitope on Avian Influenza Virus Non-Structural Protein 1 Using a Peptide Microarray

Avian influenza virus (AIV) non-structural protein 1 (NS1) is a multifunctional protein. It is present at high levels in infected cells and can be used for AIV detection and diagnosis. In this study, we generated monoclonal antibody (MAb) D7 against AIV NS1 protein by immunization of BALB/c mice with purified recombinant NS1 protein expressed in Escherichia coli. Isotype determination revealed that the MAb was IgG1/κ-type subclass. To identify the epitope of the MAb D7, the NS1 protein was truncated into a total of 225 15-mer peptides with 14 amino acid overlaps, which were spotted for a peptide microarray. The results revealed that the MAb D7 recognized the consensus DAPF motif. Furthermore, the AIV NS1 protein with the DAPF motif deletion was transiently expressed in 293T cells and failed to react with MAb D7. Subsequently, the DAPF motif was synthesized with an elongated GSGS linker at both the C- and N-termini. The MAb D7 reacted with the synthesized peptide both in enzyme-linked immunosorbent assay (ELISA) and dot-blot assays. From these results, we concluded that DAPF motif is the epitope of MAb D7. To our knowledge, this is the first report of a 4-mer epitope on the NS1 protein of AIV that can be recognized by MAb using a peptide microarray, which is able to simplify epitope identification, and that could serve as the basis for immune responses against avian influenza.
Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach

A maximum likelihood estimator based on the coalescent for unequal migration rates and different subpopulation sizes is developed. The method uses a Markov chain Monte Carlo approach to investigate possible genealogies with branch lengths and with migration events. Properties of the new method are shown by using simulated data from a four-population n-island model and a source–sink population model. Our estimation method as coded in migrate is tested against genetree; both programs deliver a very similar likelihood surface. The algorithm converges to the estimates fairly quickly, even when the Markov chain is started from unfavorable parameters. The method was used to estimate gene flow in the Nile valley by using mtDNA data from three human populations.
Generic Programming of Reusable, High Performance Container Types using Automatic Type Hierarchy Inference and Bidirectional Antichain Typing

We introduce a new compile-time notion of type subsumption based on type simulation. We show how to apply this static subsumption relation to support a more intuitive, object oriented approach to generic programming of reusable, high performance container types. As a first step towards an efficient implementation of the resulting type system in a compiler we present a novel algorithm for bidirectional type inference over arbitrary syntax graphs. The algorithm uses the new static type subsumption relation to compress the data that has to be stored for each node in the typeflow graph. During typeflow analysis this means that the set of types for a given node can be symbolically represented using antichains instead of using bitvectors or some other explicit set representation. This results in a typing algorithm that is both flexible and precise and shows good performance on representative instances.
Carotid Arterial Stiffness and Its Relationship to Exercise Intolerance in Older Patients With Heart Failure and Preserved Ejection Fraction

Heart failure with a preserved ejection fraction (HFpEF) is the dominant form of heart failure in the older population. The primary chronic symptom in HFpEF is severe exercise intolerance; however, its pathophysiology and therapy are not well understood. We tested the hypothesis that older patients with HFpEF have increased arterial stiffness beyond what occurs with normal aging and that this contributes to their severe exercise intolerance. Sixty-nine patients ≥60 years of age with HFpEF and 62 healthy volunteers (24 young healthy subjects ⩽30 years and 38 older healthy subjects ≥60 years old) were examined. Carotid arterial stiffness was assessed using high-resolution ultrasound, and peak exercise oxygen consumption was measured using expired gas analysis. Peak exercise oxygen consumption was severely reduced in the HFpEF patients compared with older healthy subjects (14.1±2.9 versus 19.7±3.7 mL/kg per minute; P<0.001) and in both was reduced compared with young healthy subjects (32.0±7.2 mL/kg per minute; both P<0.001). In HFpEF compared with older healthy subjects, carotid arterial distensibility was reduced (0.97±0.45 versus 1.33±0.55×10–3 mm Hg−1; P=0.008) and Young’s elastic modulus was increased (1320±884 versus 925±530 kPa; P<0.02). Carotid arterial distensibility was directly (0.28; P=0.02) and Young’s elastic modulus was inversely (–0.32; P=0.01) related to peak exercise oxygen consumption. Carotid arterial distensibility is decreased in HFpEF beyond the changes attributed to normal aging and is related to peak exercise oxygen consumption. This supports the hypothesis that increased arterial stiffness contributes to exercise intolerance in HFpEF and is a potential therapeutic target.
ROBUST COUNTERPART OPTIMIZATION : UNCERTAINTY SETS , FORMULATIONS AND PROBABILISTIC GUARANTEES

Robust counterpart optimization techniques are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. Robust counterpart optimization formulations induced by those different uncertainty sets are derived. For those robust formulations, their corresponding probability bounds on constraint violation are derived based on the distributional information of the uncertainty (i.e., bounded or unbounded uncertainty, with or without known probability distribution function). The tightness of the different probability bounds and the conservatism of different robust counterpart optimization formulations are illustrated through a case study.
Behavioral Banking: A Theory of the Banking Firm with Time-Inconsistent Depositors

Our equilibrium model determines the liquidity premium offered by a monopolistic bank to a pool of depositors made up of time-consistent and time-inconsistent agents. Time-consistent depositors demand compensation for illiquidity, whereas time-inconsistent ones are willing to forgo interest on illiquid savings accounts to discipline their future selves. We show that formal financial markets can reward time-inconsistent clients for illiquidity, even though these agents would agree to pay for it. The explanation combines two factors: the existence of reserve requirements making the bank keen to reward illiquid accounts more than liquid ones, and the presence of time-consistent agents who view illiquidity as a burden and therefore demand compensation for holding illiquid accounts.
Automatic Phonetic Segmentation for a Speech Corpus of Hebrew

This paper presents our study on different phonetic segmentation methods based on hidden Markov models evaluated against a Hebrew speech corpus. We investigated methods for fully automatic phonetic segmentation using only the corpus which should be segmented and automatically generated phonetic transcriptions. A new method for phonetic boundary correction based on spectral variation of the speech signal is proposed. The proposed method increased the boundary correctness of the baseline HMM segmentation system from 30.2%, 59.5% and 86.2% of automatic boundary marks with error smaller than 5, 10 and 20 ms respectively, to 52.3%, 76.3% and 90.7%.
The family Goneplacidae MacLeay, 1838 (Crustacea: Decapoda: Brachyura): systematics, phylogeny, and fossil records

A phylogenetic analysis of 14 genera of the family Goneplacidae MacLeay (Decapoda: Brachyura: Xanthoidea) is presented based upon 45 adult morphological characters. Two most-parsimonious trees were obtained (length = 87, CI = 0.6667, RI = 0.8242, RC = 0.5495). The present analysis suggests that the Goneplacidae is divided into six subfamilies: Carinocarcinoidinae subfam. nov., Chasmocarcininae Serene, Euryplacinae Stimpson, Goneplacinae MacLeay, Mathildellinae subfam. nov., and Trogloplacinae Guinot. The Carcinoplacinae H. Milne Edwards is synonymised with the Goneplacinae. The family and six subfamilies are defined or redefined based upon the phylogenetic analysis. Within the Goneplacidae, the Trogloplacinae and Chasmocarcininae are sister groups nested as the most derived clade, followed by the Carinocarcinoidinae, Goneplacinae, Euryplacinae, and the most basal Mathildellinae. Our analysis supports recognition of the family Pseudoziidae Alcock by Ng and Liao and suggests that it is the sister to the Eriphiidae MacLeay. A reexamination of fossil records of the Goneplacidae shows that 62 species, 20 genera, and five subfamilies are recognized as fossils. A new monotypic genus Viaplax (Euryplacinae) is erected for Pilumnoplax urpiniana Via. Chlinocephalus Ristori and Gillcarcinus Collins and Morris are moved to the Goneplacidae. Paleopsopheticus Hu and Tao is synonymised with Psopheticus Wood-Mason. Glaessneria Takeda and Miyake is here the junior synonym of Goneplax. Eleven extinct genera previously assigned to the Goneplacidae are not referred to any subfamilies and are transferred out of the Goneplacidae. New combinations include: Carcinoplax proavita (Glaessner), Goneplax arenicola (Glaessner), Euphylax zariquieri (Via) (Portunidae Rafinesque), and Psopheticus shujienae (Hu and Tao).
Endogenous capacity utilization and the asymmetric effects of monetary policy

This paper investigates the role of variable capacity utilization as a source of asymmetries in the relationship between monetary policy and economic activity within a dynamic stochastic general equilibrium framework. The source of the asymmetry is directly linked to the bottlenecks and stock-outs that emerge from the existence of capacity constraints in the real side of the economy. Money has real effects due to the presence of rigidities in households' portfolio decisions in the form of a Luces-Fuerst 'limited participation' constraint. The model features variable capacity utilization rates across firms due to demand uncertainty. A monopolistic competitive structure provides additional effects through optimal mark-up changes. The overall message of this paper for monetary policy is that the same actions may have different effects depending on the capacity utilization rate of the economy.
High rate puncturing of LDPC codes

High-rate LDPC codes are increasingly used in transmission systems. Puncturing is a common scheme which produces a code with higher code rate starting from a base code with lower rate. This paper discusses a new method to derive a puncturing pattern, given the parity matrix of the base code. The method allows the extraction of a puncturing pattern which is optimized in terms of error floor performance and satisfies some constraints which results in a significant reduction of HW complexity with respect to other solutions. Simulation and HW measurements results on a punctured 19/20 code derived from a rate 15/16 LDPC code are reported.
Maestro: Balancing Fairness, Latency and Throughput in the OpenFlow Control Plane

The fundamental feature of an OpenFlow network is that the controller is responsible for the configuration of switches for every traffic flow. This feature brings programmability and flexibility, but also puts the controller in a critical role in the performance of an OpenFlow network. To fairly service requests from different switches, to achieve low request-handling latency, and to scale effectively on multi-core processors are fundamental controller design requirements. With these requirements in mind, we explore multiple workload distribution designs within our system called Maestro. These designs are evaluated against the requirements, together with the static partitioning and static batching design found in other available multi-threaded controllers, NOX and Beacon. We find that a Maestro design based on the abstraction that each individual thread services switches in a round-robin manner can achieve excellent throughput scalability (second only to another Maestro design) while maintaining far superior and near optimal maxmin fairness. At the same time, low latency even at high throughput is achieved thanks to Maestro’s workloadadaptive request batching.
Varying spring preloads to select grasp strategies in an adaptive hand

We describe an underactuated hand mechanism that is able to adopt a wide range of grasp types by varying the internal forces in its fingers. The adjustment is accomplished by varying the preloads of springs, which affect the grasp stability and stiffness for large and small objects. Preload adjustment can be accomplished with low power, non-backdrivable actuators in the fingers. The analysis is presented first for a planar, two-fingered hand to illustrate the trends and tradeoffs associated with variations in preload. The results are then applied numerically to a three fingered hand with three phalanges per finger. This design is a prototype for a hand to be used in an underwater oil drilling platform under conditions of low friction and uncertain object locations.
Typing XHTML Web Applications in SMLserver

In this paper, we present a type system for typing Web applications in SMLserver, an ecient multi-threaded Web server platform for Standard ML programs. The type system guarantees that only conforming XHTML documents are sent to clients and that the target scriptlets of client-submitted forms use form data consistently and in a type-safe way. The type system is encoded in the type system of Standard ML using so-called phantom types, which are used both to guarantee conformity of XHTML documents and to guarantee form consistency.
The Proposal in Qualitative Research

The purpose of "qualitative" or "naturalistic" research varies according to the research paradigm, methods, and assumptions. Generally speaking, qualitative researchers attempt to describe and interpret some human phenomenon, often in the words of selected individuals (the informants). These researchers try to be clear about their biases, presuppositions, and interpretations so that others (the stakeholders) can decide what they think about it all. Unlike conventional, positivist research, there is no single accepted outline for a qualitative research proposal or report (Morse, 1991). The generic outline that follows is suggested as a point of departure for qualitative research proposals, and it applies specifically to the research paradigm and methods that seem most applicable to the study of families and family therapy (e.g., post-positivist, phenomenological clinical observation and long interviews). The outline is intended to serve as a point of departure for researchers, who must decide how to organize their proposals (a) to best communicate their ideas to their intended audiences and (b) to satisfy the demands of the context. Acknowledgements This proposal was produced in collaboration with Brent J. Atkinson, Ph.D. This article is available in The Qualitative Report: http://nsuworks.nova. edu/tqr/vol3/iss1/1 The Proposal in Qualitative Research by Anthony W. Heath The Qualitative Report, Volume 3, Number 1, March, 1997 The purpose of "qualitative" or "naturalistic" research varies according to the research paradigm, methods, and assumptions. Generally speaking, qualitative researchers attempt to describe and interpret some human phenomenon, often in the words of selected individuals (the informants). These researchers try to be clear about their biases, presuppositions, and interpretations so that others (the stakeholders) can decide what they think about it all. Unlike conventional, positivist research, there is no single accepted outline for a qualitative research proposal or report (Morse, 1991). The generic outline that follows is suggested as a point of departure for qualitative research proposals, and it applies specifically to the research paradigm and methods that seem most applicable to the study of families and family therapy (e.g., post-positivist, phenomenological clinical observation and long interviews). The outline is intended to serve as a point of departure for researchers, who must decide how to organize their proposals (a) to best communicate their ideas to their intended audiences and (b) to satisfy the demands of the context.
Pulse Coupled Neural Network Algorithm for Object Detection in Infrared Image

This paper describes an object detection algorithm based on pulse coupled neural networks (PCNN). To implement real time fusion of infrared surveillance object with an augmented background, the objects must be detected effectively, but the precision are not required. The simple frame difference method is adopted. We use an improved pulse coupled neural network to segment the frame difference image. The iteration times can be automatically estimated. This algorithm does not need model training and parameter learning, and it is applied to segment images with noise effectively. Object detection on several types of image is implemented with the proposed method and the experimental results demonstrate its validity.