Your search

The Life and Times of Chinua Achebe introduces readers to the life, literary works, and times of arguably the most widely-read African novelist of recent times, an icon, both in continental Africa and abroad. The book weaves together the story of Chinua Achebe, a young Igboman whose novel Things Fall Apart opened the eyes of the world to a more realistic image of Africa that was warped by generations of European travelers, colonists, and writers. Whilst continuing to write further influential novels and essays, Achebe also taught other African writers to use their skills to help their national leaders to fight for their freedoms in the post-colonial era, as internal warfare compounded the damage caused by European powers during the colonial era. In this book Kalu Ogbaa, an esteemed expert on Achebe and his works, draws on extensive research and personal interviews with the great man and his colleagues and friends, to tell the story of Achebe and his work. This intimate and powerful new biography will be essential reading for students and scholars of Chinua Achebe, and to anyone with an interest in the literature and post-colonial politics of Africa. © 2022 Kalu Ogbaa.

The purpose of this paper is to advance breakthrough research that further extends, as well as enrichens, our understanding of organizations. This is a companion article to “CEO Archetype Identity Drives Organization Culture” previously published in this journal. Archetypes are merely a special case of metaphors. In this paper, we generalize the concept of leadership archetypes to organization metaphors, adding original dimensions to existing concepts and theories of organizational diagnosis. Thus, the present research brings a new enlightening perspective to this field. Data from the past organization studies featured in this article involve the Zaltman Metaphorical Elicitation Technique (ZMET) embedded in qualitative in-depth personal interviews. These studies explore the impact of management styles on organization structure and functions. In each study metaphors were elicited from leaders and followers, and generated insights and action-oriented strategies to meet organizational challenges © 2021. American Psychological Association

Reentrance, the return of a system from an ordered phase to a previously encountered less-ordered one as a controlled parameter is continuously varied, is a recurring theme found in disparate physical systems, yet its microscopic cause is often not investigated thoroughly. Here, through detailed characterization and theoretical modeling, we uncover the microscopic mechanism behind reentrance in the strongly frustrated pyrochlore antiferromagnet Er2Sn2O7. We use single crystal heat capacity measurements to expose that Er2Sn2O7 exhibits multiple instances of reentrance in its magnetic field B vs temperature T phase diagram for magnetic fields along three cubic high symmetry directions. Through classical Monte Carlo simulations, mean field theory, and classical linear spin-wave expansions, we argue that the origins of the multiple occurrences of reentrance observed in Er2Sn2O7 are linked to soft modes. These soft modes arise from phase competition and enhance thermal fluctuations that entropically stabilize a specific ordered phase, resulting in an increased transition temperature for certain field values and thus the reentrant behavior. Our work represents a detailed examination into the mechanisms responsible for reentrance in a frustrated magnet and may serve as a template for the interpretation of reentrant phenomena in other physical systems. © 2021 American Physical Society.

"This exciting volume brings to life the food culture of Mexico, detailing the development of the cuisine and providing practical information about ingredients and cooking techniques so that readers can replicate some of Mexico's most important traditional dishes"--

This is the third and final book in the series Transformative Pedagogies in Teacher Education. Like the first two books in the series it is geared towards practitioners in the field of teacher education. This third book focuses on transformative leadership in teacher education. In other words, the kind of leadership and practices that will be important and necessary to bring about the kind of changes that both teachers and students seek to improve educational outcomes for all students, but in particular Black, Indigenous and racialized students who have been traditionally underserved by the education system. Teacher leadership plays an important role in transformative educational change that challenges all forms of oppression and white supremacy. This book features chapters by a collection of scholars, teacher educators, researchers, teacher advocates and practitioners drawing on their research and experiences to explore critical issues in teacher education. The book will be useful to teacher educators working with teacher candidates in different contexts, experienced teachers and school leaders. Given demographic shifts and the need for educators to respond to growing diversity in schools, educators will find valuable strategies in Transformative Pedagogies in Teacher Education: Re-Imagining Transformative Leadership in Teacher Education they can employ in their own practice. In addition to valuable strategies, authors explore different approaches and perspectives critical in these changing and challenging times. Critical notions of education are posited from different perspectives and contexts. This book will be useful for teacher education programs, principal preparation programs, in-service teachers, school boards and districts engaging in ongoing professional development of teachers and school leaders.

Building from an interactionist view of ethics, this study sought to integrate individual and contextual factors for understanding ethical perceptions in teams. Given the proximal nature of team members, this study specifically explored how individuals comparatively evaluate their own ethical behaviors and team members’ ethical behaviors to arrive at a perception of ethical person–group (P–G) fit within a team. Grounding our theoretical arguments in relational schemas theory (Baldwin, Psychological Bulletin 112:461–484, 1992), we demonstrate that interpersonal ethical perceptions can have distal impacts on perceptions of team functioning. The results support the hypotheses that a perceived ethical incongruence between the self and other team members (i.e., lack of ethical P–G fit) negatively influenced perceptions of relationship conflict and ultimately information sharing. By exploring individual and team level aspects of ethics concurrently, we contribute to a deeper understanding of contextual forces in ethics through an interactionist approach.

The organic component of the molluscan shell allows for orderly biomineralization and ensures structural integrity that is crucial to survival. This organic contribution to the shell typically composes 2-5% of the total adult shell by weight. Because macro- and microstructure of the shell is known to vary with ontogeny and across taxa, we examined if the organic to mineral ratio components in shell also varied with growth across taxa. To assess intraspecific differences in the organic to mineral ratio of the shell during growth, we examined ratios in three marine [Crepidula fornicata (Linnaeus, 1758), Littorina littorea (Linnaeus, 1758), and Littorina saxatilis (Olivi, 1792)] and two freshwater [Corbicula fluminea (Müller, 1774) and Bellamya chinensis (Gray, 1834)] mollusks across size ranges. In the marine gastropods, the average organic component by weight of the small size class was significantly larger than the average organic proportions of the medium and large size classes. The smallest size class of L. saxatilis had an average shell organic proportion of 11.12%, while the smallest size classes of C. fornicata (3.53%) and L. littorea (2.60%) had percentages below 5%. The smallest size class of C. fluminea had a greater average shell organic proportion than the largest size class (6.19% vs 2.68% organics). Adult specimens of B. chinensis had an average shell organic proportion of 3.93%, while in utero shelled juveniles had an average of 10.05%. In both freshwater and marine species, the smallest size class had a greater organic proportion. As the organic matrix is energetically more expensive than the calcified shell portion, we hypothesize that energy expended in these smaller (usually pre-reproductive maturity) stages of growth allows for a more rapid production of shell and that this “expense” is a valuable trade-off for the protection the shell offers young mollusks.

Drawing on Wales, Monsen, and McKelvie's (2011, Entrepreneurship Theory and Practice, 35(5), 895–923) model of entrepreneurial orientation pervasiveness and the strong culture hypothesis (Denison, 1984, Organization Dynamics, 13, 4–22), this study investigates how entrepreneurial orientation (EO) strength, defined as the level of agreement in the shared perceptions of EO, serves as a boundary condition of the EO–firm performance relationship. Four field studies provide evidence for a valid and reliable 10-item multidimensional measure of entrepreneurial orientation, the EO-10, which in turn, may be used to assess EO strength. We establish content and construct validity of the EO-10 (study 1; n = 447 employees), criterion-related validity with revenue growth and sales growth (study 2; n = 412 employees in 43 profit centers), and convergent validity with Covin and Slevin's (1989, Strategic Management Journal, 10, 75–87) 9-item measure (study 3; n = 291 employees). Finally, in study 4 (n = 853 employees nested in 22 organizations), we demonstrate the interactive effects of EO and EO strength on profit growth and revenue growth. In sum, this study provides conceptual and empirical evidence for the importance of EO strength as a moderator of the EO–firm performance relationship.

The students’ performance prediction (SPP) problem is a challenging problem that managers face at any institution. Collecting educational quantitative and qualitative data from many resources such as exam centers, virtual courses, e-learning educational systems, and other resources is not a simple task. Even after collecting data, we might face imbalanced data, missing data, biased data, and different data types such as strings, numbers, and letters. One of the most common challenges in this area is the large number of attributes (features). Determining the highly valuable features is needed to improve the overall students’ performance. This paper proposes an evolutionary-based SPP model utilizing an enhanced form of the Whale Optimization Algorithm (EWOA) as a wrapper feature selection to keep the most informative features and enhance the prediction quality. The proposed EWOA combines the Whale Optimization Algorithm (WOA) with Sine Cosine Algorithm (SCA) and Logistic Chaotic Map (LCM) to improve the overall performance of WOA. The SCA will empower the exploitation process inside WOA and minimize the probability of being stuck in local optima. The main idea is to enhance the worst half of the population in WOA using SCA. Besides, LCM strategy is employed to control the population diversity and improve the exploration process. As such, we handled the imbalanced data using the Adaptive Synthetic (ADASYN) sampling technique and converting WOA to binary variant employing transfer functions (TFs) that belong to different families (S-shaped and V-shaped). Two real educational datasets are used, and five different classifiers are employed: the Decision Trees (DT), k-Nearest Neighbors (k-NN), Naive Bayes (NB), Linear Discriminant Analysis (LDA), and LogitBoost (LB). The obtained results show that the LDA classifier is the most reliable classifier with both datasets. In addition, the proposed EWOA outperforms other methods in the literature as wrapper feature selection with selected transfer functions.

We report high-precision measurements of the longitudinal double-spin asymmetry, ALL, for midrapidity inclusive jet and dijet production in polarized pp collisions at a center-of-mass energy of √s=200 GeV. The new inclusive jet data are sensitive to the gluon helicity distribution, Δg(x,Q2), for gluon momentum fractions in the range from x≃0.05 to x≃0.5, while the new dijet data provide further constraints on the x dependence of Δg(x,Q2). The results are in good agreement with previous measurements at √s=200 GeV and with recent theoretical evaluations of prior world data. Our new results have better precision and thus strengthen the evidence that Δg(x,Q2) is positive for x>0.05.

We present the first inclusive measurements of the invariant and softdrop jet mass in proton-proton collisions at √s=200 GeV at STAR. The measurements are fully corrected for detector effects, and reported differentially in both the jet transverse momentum and jet radius parameter. We compare the measurements to established leading-order Monte Carlo event generators and find that STAR-tuned pythia-6 reproduces the data, while LHC tunes of pythia-8 and herwig-7 do not agree with the data, providing further constraints on parameter tuning. Finally, we observe that softdrop grooming, for which the contribution of wide-angle nonperturbative radiation is suppressed, shifts the jet mass distributions into closer agreement with the partonic jet mass as determined by both pythia-8 and a next-to-leading-logarithmic accuracy perturbative QCD calculation. These measurements complement recent LHC measurements in a different kinematic region, as well as establish a baseline for future jet mass measurements in heavy-ion collisions at RHIC.

The beam energy scan (BES) program at the BNL Relativistic Heavy Ion Collider (RHIC) was extended to energies below √sNN=7.7 GeV in 2015 by successful implementation of the fixed-target mode of operation in the STAR (Solenoidal Tracker At RHIC) experiment. In this mode, ions circulate in one ring of the collider and interact with a stationary target at the entrance of the STAR time projection chamber. The first results for Au+Au collisions at √sNN=4.5 GeV are presented, demonstrating good performance of all the relevant detector subsystems in fixed-target mode. Results presented here include directed and elliptic flow of identified hadrons, and radii from pion femtoscopy. The latter, together with recent HADES results, reveal a long-sought peak structure that may be caused by the system evolving through a first-order phase transition from quark-gluon plasma to the hadronic phase. Directed and elliptic flow for pions are presented for the first time at this beam energy. Pion and proton elliptic flow show behavior which hints at constituent quark scaling, and demonstrate that a definitive conclusion will be achievable using the full statistics of the ongoing second phase of BES (BES-II). In particular, BES-II to date has recorded fixed-target data sets with two orders of magnitude more events at each of nine energies between √sNN=3.0 and 7.7 GeV.

We report a systematic measurement of cumulants, Cn, for net-proton, proton, and antiproton multiplicity distributions, and correlation functions, κn, for proton and antiproton multiplicity distributions up to the fourth order in Au+Au collisions at √sNN=7.7, 11.5, 14.5, 19.6, 27, 39, 54.4, 62.4, and 200 GeV. The Cn and κn are presented as a function of collision energy, centrality and kinematic acceptance in rapidity, y, and transverse momentum, pT. The data were taken during the first phase of the Beam Energy Scan (BES) program (2010–2017) at the BNL Relativistic Heavy Ion Collider (RHIC) facility. The measurements are carried out at midrapidity (|y|< 0.5) and transverse momentum 0.4<pT<2.0GeV/c, using the STAR detector at RHIC. We observe a nonmonotonic energy dependence (√sNN = 7.7–62.4 GeV) of the net-proton C4/C2 with the significance of 3.1σ for the 0–5% central Au+Au collisions. This is consistent with the expectations of critical fluctuations in a QCD-inspired model. Thermal and transport model calculations show a monotonic variation with √sNN. For the multiparticle correlation functions, we observe significant negative values for a two-particle correlation function, κ2, of protons and antiprotons, which are mainly due to the effects of baryon number conservation. Furthermore, it is found that the four-particle correlation function, κ4, of protons plays a role in determining the energy dependence of proton C4/C1 below 19.6 GeV, which cannot be understood by the effect of baryon number conservation.

We present systematic measurements of azimuthal anisotropy for strange and multistrange hadrons (K0s, Λ, Ξ, and Ω) and ϕ mesons at midrapidity (|y|< 1.0) in collisions of U+U nuclei at √sNN=193 GeV, recorded by the STAR detector at the Relativistic Heavy Ion Collider. Transverse momentum (pT) dependence of flow coefficients (v2, v3, and v4) is presented for minimum bias collisions and three different centrality intervals. Number of constituent quark scaling of the measured flow coefficients in U+U collisions is discussed. We also present the ratio of vn scaled by the participant eccentricity (ɛn{2}) to explore system size dependence and collectivity in U+U collisions. The magnitude of v2/ɛ2 is found to be smaller in U+U collisions than that in central Au+Au collisions contradicting naive eccentricity scaling. Furthermore, the ratios between various flow harmonics (v3/v3/22, v4/v4/22) are studied and compared with hydrodynamic and transport model calculations.

Purpose The value of the events industry is increasing worldwide. An essential component for successful events is creating a unique experience by offering gamification. A conceptual model is proposed, exploring pre-event game communication and its effect on attendees' value perceptions, willingness to participate, word of mouth intentions and emotional commitment during gameplay at conference events. Design/methodology/approach Analysis of variance and structural equation modeling were employed to test the model using data collected from 177 attendees recruited from hospitality and tourism association network listservs and online research company. Findings Results reveal that perceptions of event gamification increase word of mouth intentions, willingness to participate and emotional commitment. Practical implications The study contributes to the knowledge of conference events with recommendations for incorporation of game elements for meeting planners to enhance attendee behaviors at the event. Originality/value This study is among the first to examine positive behavioral outcomes of using games at conference events.

Quadrotor UAVs are one of the most preferred types of small unmanned aerial vehicles, due to their modest mechanical structure and propulsion precept. However, the complex non-linear dynamic behavior of the Proportional Integral Derivative (PID) controller in these vehicles requires advanced stabilizing control of their movement. Additionally, locating the appropriate gain for a model-based controller is relatively complex and demands a significant amount of time, as it relies on external perturbations and the dynamic modeling of plants. Therefore, developing a method for the tuning of quadcopter PID parameters may save effort and time, and better control performance can be realized. Traditional methods, such as Ziegler–Nichols (ZN), for tuning quadcopter PID do not provide optimal control and might leave the system with potential instability and cause significant damage. One possible approach that alleviates the tough task of nonlinear control design is the use of meta-heuristics that permit appropriate control actions. This study presents PID controller tuning using meta-heuristic algorithms, such as Genetic Algorithms (GAs), the Crow Search Algorithm (CSA) and Particle Swarm Optimization (PSO) to stabilize quadcopter movements. These meta-heuristics were used to control the position and orientation of a PID controller based on a fitness function proposed to reduce overshooting by predicting future paths. The obtained results confirmed the efficacy of the proposed controller in felicitously and reliably controlling the flight of a quadcopter based on GA, CSA and PSO. Finally, the simulation results related to quadcopter movement control using PSO presented impressive control results, compared to GA and CSA.

Obstructive sleep apnea (OSA) is a well-known sleep ailment. OSA mostly occurs due to the shortage of oxygen for the human body, which causes several symptoms (i.e., low concentration, daytime sleepiness, and irritability). Discovering the existence of OSA at an early stage can save lives and reduce the cost of treatment. The computer-aided diagnosis (CAD) system can quickly detect OSA by examining the electrocardiogram (ECG) signals. Over-serving ECG using a visual procedure is challenging for physicians, time-consuming, expensive, and subjective. In general, automated detection of the ECG signal’s arrhythmia is a complex task due to the complexity of the data quantity and clinical content. Moreover, ECG signals are usually affected by noise (i.e., patient movement and disturbances generated by electric devices or infrastructure), which reduces the quality of the collected data. Machine learning (ML) and Deep Learning (DL) gain a higher interest in health care systems due to its ability of achieving an excellent performance compared to traditional classifiers. We propose a CAD system to diagnose apnea events based on ECG in an automated way in this work. The proposed system follows the following steps: (1) remove noise from the ECG signal using a Notch filter. (2) extract nine features from the ECG signal (3) use thirteen ML and four types of DL models for the diagnosis of sleep apnea. The experimental results show that our proposed approach offers a good performance of DL classifiers to detect OSA. The proposed model achieves an accuracy of 86.25% in the validation stage.

Two new imaging instruments, ‘Alopeke and Zorro, were designed, built, and commissioned at the Gemini-North and Gemini-South telescopes in 2018 and 2019, respectively. Here we describe them and present the results from over a year of operation. The two identical instruments are based on the legacy of the DSSI (Differential Speckle Survey Instrument) instrument, successfully used for years at the WIYN and the Gemini telescopes in Hawaii and Chile. ‘Alopeke and Zorro are dual-channel imagers having both speckle (6.7″) and “wide-field” (∼1 arcminute) field-of-view options. They were built to primarily perform speckle interferometry providing diffraction-limited imagery at optical wavebands, yielding pixel scale uncertainties of ±0.21 mas, position angle uncertainties of ±0.7◦, and photometric uncertainties of Δm ± 0.02–0.04 magnitudes (for the blue and red channels, respectively) when run through the standard data reduction pipeline. One of their main scientific roles is the validation and characterization of exoplanets and their host stars as discovered by transit surveys such as the NASA Kepler, K2, and TESS missions. The limiting magnitude for speckle observations at Gemini can be quite faint (r ∼18 in good observing conditions) but typically the observed targets are brighter. The instruments can also function as conventional CCD imagers providing a 1 arc-minute field of view and allowing simultaneous two-color, high-speed time-series operation. These resident visitor instruments are remotely operable and are available for use by the community via the peer-reviewed proposal process.

The purpose of this study is to investigate secondary teacher candidates’ experience of mathematical modeling task design. In the study, 54 teacher candidates in a university-based teacher education program created modeling tasks and scoring rubrics. Next, the participants pilot-tested the tasks with students and had the opportunity to revise the original tasks and rubrics based on student responses. The data included participants’ statements, in which they described and reflected on the design and revision process of modeling tasks. The study describes six didactic revision strategies in revising modeling tasks and identifies five emerging pedagogical ideas from revising tasks and rubrics. The study also discusses the way modeling task design activities have the potential to support teacher candidates’ learning through a bottom-up modeling curriculum in teacher education.