Applying machine learning methods to geographic data provides insights into spatial patterns in the data as well as assists in interpreting and describing environments. This paper investigates the results of k-means clustering applied to 51 geospatial layers, selected and scaled for a model of outdoor acoustic environments, in the continental United States. Silhouette and elbow analyses were performed to identify an appropriate number of clusters (eight). Cluster maps are shown and the clusters are described, using correlations between the geospatial layers and clusters to identify distinguishing characteristics for each cluster. A subclustering analysis is presented in which each of the original eight clusters is further divided into two clusters. Because the clustering analysis used geospatial layers relevant to modeling outdoor acoustics, the geospatially distinct environments corresponding to the clusters may aid in characterizing acoustically distinct environments. Therefore, the clustering analysis can guide data collection for the problem of modeling outdoor acoustic environments by identifying poorly sampled regions of the feature space (i.e., clusters which are not well-represented in the training data).

Separating crowd responses from raw acoustic signals at sporting events is challenging because recordings contain complex combinations of acoustic sources, including crowd noise, music, individual voices, and public address (PA) systems. This paper presents a data-driven decomposition of recordings of 30 collegiate sporting events. The decomposition uses machine-learning methods to find three principal spectral shapes that separate various acoustic sources. First, the distributions of recorded one-half-second equivalent continuous sound levels from men's and women's basketball and volleyball games are analyzed with regard to crowd size and venue. Using 24 one-third-octave bands between 50 Hz and 10 kHz, spectrograms from each type of game are then analyzed. Based on principal component analysis, 87.5% of the spectral variation in the signals can be represented with three principal components, regardless of sport, venue, or crowd composition. Using the resulting three-dimensional component coefficient representation, a Gaussian mixture model clustering analysis finds nine different clusters. These clusters separate audibly distinct signals and represent various combinations of acoustic sources, including crowd noise, music, individual voices, and the PA system.

Chromosome 3p (chr3p) is frequently deleted in multiple cancers, indicating the presence of shared tumor suppressors. Analysis of genomic alterations in 33 different cancer types implicates the deletion or deleterious mutations of SET-domain-containing 2 ( SETD2 ) at chr3p21 in significantly facilitating the formation of isochromosomes, consisting of two identical mirror-imaged arms, thereby promoting genomic instability conducive to large-scale chromosomal rearrangements and rapid cancer genome evolution. Fracturing of dicentric isochromosomes during cell division is pervasive and follows the dynamic fragmentation pattern of solids under impulse. Across cancers, isochromosomes form most frequently on chr8 to amplify the MYC -containing q-arm and chr17 to delete the TP53 -containing p-arm. In the most aggressive uveal melanoma (UVM) subtype, chr3 deletion also includes MITF , a critical melanocyte differentiation and survival factor, and co-occurs with chr8q amplification. We demonstrate that MITF is a master transcriptional regulator of GNAQ / GNA11 , mutated in 90% of UVM patients, and the associated synthetic-lethal genes identified by recent CRISPR screening studies. MITF maintains MAPK and calcium homeostasis in UVM, and its deletion is thus accidental, creating an early crisis during oncogenesis. We further show that MITF, MYC, and GNAQ/GNA11 form coupled regulatory feedback loops in the melanocyte lineage, and MITF deletion in UVM creates acute dependency on MYC-mediated rescue via chr8q amplification, often as a consequence of isochromosome formation. The discovered feedback loops predict both overall and relapse-free patient survival within the most aggressive UVM subtype, explain sensitivity to therapeutic gene perturbations, and inform effective combinatorial therapies.

Background: Chromosome 3p (chr3p) is frequently deleted in multiple cancers, indicating the presence of shared tumor suppressors. In aggressive uveal melanomas (UVM), this deletion often co-occurs with chr8q amplification (8q+), suggesting strong selection pressure during UVM evolution. Methods: To understand the pattern of genomic alterations mediated by chr3p deletion, we have developed an algorithm for detecting isochromosomes in 10,632 TCGA cancer patients. We further perform integrative genomics analysis to investigate how chr3p deletion could affect subsequent cancer genome evolution and synthetic lethality in UVM. Results: Analysis of genomic alterations in 33 different cancer types implicates the deletion or deleterious mutations of SET-domain-containing 2 (SETD2) at chr3p21 in significantly facilitating the formation of isochromosomes, thereby promoting genomic instability conducive to rapid cancer genome evolution. Fracturing of dicentric isochromosomes during cell division is pervasive and follows the dynamic fragmentation pattern of solids under impulse. In the most aggressive UVM subtype, chr3 deletion includes MITF, a master regulator of melanocyte survival and differentiation, and co-occurs with 8q+. We demonstrate that MITF is a master transcriptional regulator of GNAQ/GNA11 and associated synthetic-lethal genes in UVM. MITF maintains MAPK and calcium homeostasis in UVM, and its hemizygous deletion is thus accidental, likely creating an early crisis during oncogenesis. We further show that MITF, MYC, and GNAQ/GNA11 form coupled regulatory feedback loops in the melanocyte lineage, and MITF deletion in UVM creates acute dependency on MYC-mediated rescue via 8q+. The discovered feedback loops predict both overall and relapse-free patient survival within the most aggressive UVM subtype, explain sensitivity to therapeutic gene perturbations, and inform effective combinatorial therapies. Conclusions: SETD2 deletion potentiates isochromosome formation across diverse cancers. Combinatorial targeting of MITF together with a previously identified synthetic lethal gene may benefit UVM patients harboring both chr3 deletion and 8q+.

Crowds at collegiate basketball games react acoustically to events on the court in many ways, including applauding, chanting, cheering, and making distracting noises. Acoustic features can be extracted from recordings of crowds at basketball games to train machine learning models to classify crowd reactions. Such models may help identify crowd mood, which could help players secure fair contracts, venues refine fan experience, and safety personnel improve emergency response services or to minimize conflict in policing. By exposing the key features in these models, feature selection highlights physical insights about crowd noise, reduces computational costs, and often improves model performance. Feature selection is performed using random forests and least absolute shrinkage and selection operator logistic regression to identify the most useful acoustic features for identifying and classifying crowd reactions. The importance of including short-term feature temporal histories in the feature vector is also evaluated. Features related to specific 1/3-octave band shapes, sound level, and tonality are highly relevant for classifying crowd reactions. Additionally, the inclusion of feature temporal histories can increase classifier accuracies by up to 12%. Interestingly, some features are better predictors of future crowd reactions than current reactions. Reduced feature sets are human-interpretable on a case-by-case basis for the crowd reactions they predict.