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1. ABAQUS models for chiral TIM systems

   https://doi.org/10.4231/6AT6-RW35  

   Kim, Dong; Siegmund, Thomas; Siegmund, Thomas (January 2024, Purdue University Research Repository)

   Topologically Interlocked Material systems are a class of architectured materials. TIM systems are assembled from individual building blocks and are confined by an external frame. In particular, 2D, plate-type assemblies are considered. This publication contains files for the numerical analysis of the mechanical behavior of TIM systems through the use of finite element analysis. ABAQUS model files (inp format) for the study of the chiral/achiral response are provided. Files chirality_s1_in.inp are for type I square assemblies. n=3,5,7,9 Files chirality_s2_in.inp are for type II square assemblies. n=4,6,8,10 Files chirality_h1_in.inp are for type I hexagon assemblies. n=2,3,4,5 Files chirality_h2_in.inp are for type II hexagon assemblies. n=2,3,4,5 File chirality_s1i5_center_dissection.inp is for an assembly with a dissection of the central tile of type I square assembly with n=5. File chirality_s2i6_center_dissection.inp is for an assembly with a dissection of the central tile of type II square assembly with n=6. File chirality_s1i5_center_surrounding_dissection.inp is for an assembly with dissections of the tiles surrounding the center tile of type I square assembly with n=5. File chirality_h1i3_center_dissection.inp is for an assembly with a dissection of the central tile of type I hexagon assembly with n=3. File chirality_h2i3_center_dissection.inp is for an assembly with a dissection of the central tile of type II hexagon assembly with n=3. File chirality_h1i3_center_surrounding_dissection.inp is for an assembly with dissections of the tiles surrounding the center tile of type I hexagon assembly with n=3. 

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2. Role of Regularization in the Prediction of Valence from Speech

   https://doi.org/10.21437/Interspeech.2018-2508  

   Sridhar, Kusha; Parthasarathy, Srinivas; Busso, Carlos (September 2018, Interspeech 2018)

   Regularization plays a key role in improving the prediction of emotions using attributes such as arousal, valence and dominance. Regularization is particularly important with deep neural networks (DNNs), which have millions of parameters. While previous studies have reported competitive performance for arousal and dominance, the prediction results for valence using acoustic features are significantly lower. We hypothesize that higher regularization can lead to better results for valence. This study focuses on exploring the role of dropout as a form of regularization for valence, suggesting the need for higher regularization. We analyze the performance of regression models for valence, arousal and dominance as a function of the dropout probability. We observe that the optimum dropout rates are consistent for arousal and dominance. However, the optimum dropout rate for valence is higher. To understand the need for higher regularization for valence, we perform an empirical analysis to explore the nature of emotional cues conveyed in speech. We compare regression models with speakerdependent and speaker-independent partitions for training and testing. The experimental evaluation suggests stronger speaker dependent traits for valence. We conclude that higher regularization is needed for valence to force the network to learn global patterns that generalize across speakers. 

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3. Faster Linear Algebra for Distance Matrices

   Indyk, Piotr; Silwal, Sandeep (January 2022, Conference on Neural Information Processing Systems)

   The distance matrix of a dataset X of n points with respect to a distance function f represents all pairwise distances between points in X induced by f. Due to their wide applicability, distance matrices and related families of matrices have been the focus of many recent algorithmic works. We continue this line of research and take a broad view of algorithm design for distance matrices with the goal of designing fast algorithms, which are specifically tailored for distance matrices, for fundamental linear algebraic primitives. Our results include efficient algorithms for computing matrix-vector products for a wide class of distance matrices, such as the l1 metric for which we get a linear runtime, as well as a quadratic lower bound for any algorithm which computes a matrix-vector product for the l_infty case. Our upper bound results have many further downstream applications, including the fastest algorithm for computing a relative error low-rank approximation for the distance matrix induced by l1 and l2 functions and the fastest algorithm for computing an additive error lowrank approximation for the l2 metric, in addition to applications for fast matrix multiplication among others. We also give algorithms for constructing distance matrices and show that one can construct an approximate l2 distance matrix in time faster than the bound implied by the Johnson-Lindenstrauss lemma. 

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4. Excess mortality in Belarus during the COVID-19 pandemic as the case study of a country with limited non-pharmaceutical interventions and limited reporting

   https://doi.org/10.1038/s41598-022-09345-z  

   Kirpich, Alexander; Shishkin, Aleksandr; Weppelmann, Thomas A.; Tchernov, Alexander Perez; Skums, Pavel; Gankin, Yuriy (December 2022, Scientific Reports)

   Abstract Public health intervention to contain the ongoing COVID-19 pandemic significantly differed by country since the SARS-CoV-2 spread varied regionally in time and in scale. Since vaccinations were not available until the end of 2020 non-pharmaceutical interventions (NPIs) remained the only strategies to mitigate the pandemic spread at that time. Belarus in Europe is one of a few countries with a high Human Development Index where no lockdowns have ever been implemented and only limited NPIs have taken place for a period of time. Therefore, the Belarusian case was evaluated and compared in terms of the mortality burden. Since the COVID-19 mortality was low, the excess overall mortality was studied for Belarus. Since no overall mortality data have been reported past June 2020 the analysis was complemented by the study of Google Trends funeral-related search queries up until August 2021. Depending on the model, the Belarusian mortality for June of 2020 was 29 to 39% higher than otherwise expected with the corresponding estimated excess death was from 2953 to 3690 while the reported COVID-19 mortality for June 2020 was only 157 cases. The Belarusian excess mortality for June 2020 was higher than for all neighboring countries with an excess of 5% for Poland, 5% for Ukraine, 8% for Russia, 11% for Lithuania and 11% for Latvia. The relationship between Google Trends and mortality time series was studied using Granger’s test and the results were statistically significant. The results for Google Trends searches did vary by key phrase with the largest excess of 138% for April 2020 and 148% for September 2020 was observed for a key phrase “coffin”, while the largest excess of 218% for January 2021 was observed for “funeral services”. In summary, there are indications of the excess overall mortality in Belarus, which is larger than the reported COVID-19-related mortality. 

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5. Fostering inclusion and diversity through research, teaching, mentoring, and outreach

   https://doi.org/10.1091/mbc.E19-07-0379  

   Torres, Jorge Z. (November 2019, Molecular Biology of the Cell)

   I am deeply humbled and honored to receive the American Society for Cell Biology (ASCB) Prize for Excellence in Inclusivity. Thank you to the ASCB for recognizing the contributions of faculty to inclusion and diversity in STEM and the importance of this for the advancement of science. Thank you to the Howard Hughes Medical Institute (HHMI) for your generous support of inclusivity. The prize money will be used to fund outreach activities aimed at increasing inclusion in science and to create research opportunities for students from underrepresented groups in the sciences. In this essay, I share bits of my life’s story that I hope will resonate with a broad audience, especially students from underrepresented groups in STEM, and that drive my passion for inclusion and diversity. I provide points of consideration for students to enhance their preparation for science careers and for faculty to improve the current landscape of inclusion and diversity in STEM. 

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