Why is Pan-Africanism, an intellectual idea which carried much political weight in the twentieth century, no longer of consequential interest to most Africans and Blacks in the world? Why is it that the ideas and individuals that tend to be popular about the African world do not often grapple with the complexity of said world? Even with the brilliance of Bessie Head’s revelations in Lesotho in the shadow of apartheid to the willfully imaginative poetic acts of Martinican Aimé Césaire, the astonishing military genius of revolutionary leader Amilcar Cabral of Guinea Bissau and the self-flagellating howling sounds of Fẹla Anikulapo-Kuti’s music on the streets of Nigeria and beyond, why do rich experiences of global Blackness still struggle for active engagement in the plain light of routine reckoning? The essays in Mandela in Havana, Maria in the Favela: Black Hosts are an attempt to reflect on these questions, and many others like them. Anchored in two catalytic moments in the period following the Second World War—the Pan-African Congress in Manchester in 1945 and the founding in 1947 of the journal Présence Africaine—as well as the impact on contemporary Black selfhoods of the events they set in motion, the essays frame the subsequent events as opportunities for Black people, intellectuals especially, to become hosts to the world, in a manner that was impossible for them to do in the previous decades. The chapters look closely at trends that animated that history and, through selected profiles, offer exemplary analyses of the attendant changes.
Recently, Yang, Yuan and Zhang (2024) [12] characterized when a self-similar measure satisfying the open set condition is doubling. In this paper, we study when a self-similar measure with overlaps is doubling. Let m≥2 and let β>1 be the Pisot number satisfying βm=∑j=0m−1βj. Let p=(p1,p2) be a probability weight and let μp be the self-similar measure associated to the IFS {S1(x)=x/β,S2(x)=x/β+(1−1/β)}. Yung (2007) [13] proved that when m=2, μp is doubling if and only if p=(1/2,1/2). We show that for m≥3, μp is always non-doubling.
Signaling theory explains how organizations convey credible information under conditions of information asymmetry. Yet, while recent work highlights that signals often interact—reinforcing or substituting—most studies have treated signals as independent and additive, and empirical evidence of configurational interaction patterns remains limited. This study addresses this limitation by examining how multiple institutional signals jointly shape evaluators’ judgments in peer-reviewed university research funding. Using fuzzy-set qualitative comparative analysis (fsQCA), we identify distinct configurations of capability, reputation, and status signals that lead to both high and low funding success. The findings reveal that no single signal ensures success; rather, outcomes emerge from specific portfolios of signals whose effects depend on their combinations. We extend signaling theory by demonstrating that signals can also suppress or neutralize one another, and by introducing a configurational perspective that captures synergy, substitution, and suppression within signal portfolios.
Head and neck squamous cell carcinoma (HNSCC) is a complex, aggressive and heterogeneous malignancy with trends rising rapidly worldwide. Tobacco use, alcohol consumption and human papillomavirus (HPV) infection are the leading risk factors associated with the occurrence of HNSCC. Standard treatments, including radiotherapy, chemotherapy, and surgical resection, are often associated with severe side effects and limited success, particularly in advanced, recurrent, or metastatic disease. Though the introduction of immune checkpoint inhibitors has reshaped the management of recurrent or metastatic disease, the clinical impact remains limited as a majority of patients do not achieve expected prognosis, attributed to a “cold” tumor microenvironment. Therefore, to enhance the clinical outcomes of HNSCC patients, it is priority to investigate more effective and well-tolerated targeted medicines. This review provides insights about the current treatment strategies, challenges associated with these traditional approaches along with shedding light on the state-of-the-art HNSCC treatment modalities such as advanced surgery, immunotherapy, epigenetics and cancer stem cell targeting, etc. Moreover, therapies involving varied sophisticated combinations of the abovementioned conventional approaches and these advanced treatment modalities have yielded better HNSCC prognosis in multiple preclinical and clinical settings. Continued multidisciplinary research targeting molecular pathways and innovative drug delivery systems hold the potential to remarkably enhance treatment efficacy while preserving patient’s quality of life.
Adaptive gradient methods are workhorses in deep learning. However, the convergence guarantees of adaptive gradient methods for nonconvex optimization have not been thoroughly studied. In this paper, we provide a fine-grained convergence analysis for a general class of adaptive gradient methods including AMSGrad, RMSProp and AdaGrad. For smooth nonconvex functions, we prove that adaptive gradient methods in expectation converge to a first-order stationary point. Our convergence rate is better than existing results for adaptive gradient methods in terms of dimension. In addition, we also prove high probability bounds on the convergence rates of AMSGrad, RMSProp as well as AdaGrad, which have not been established before. Our analyses shed light on better understanding the mechanism behind adaptive gradient methods in optimizing nonconvex objectives.
