How Do Transformers Model Physics? Investigating the Simple Harmonic Oscillator.

How do transformers model physics? Do transformers model systems with interpretable analytical solutions or do they create an "alien physics" that is difficult for humans to decipher? We have taken a step towards demystifying this larger puzzle by investigating the simple harmonic oscillator (SHO), x¨+2γx˙+ω02x=0, one of the most fundamental systems in physics. Our goal was to identify the methods transformers use to model the SHO, and to do so we hypothesized and evaluated possible methods by analyzing the encoding of these methods' intermediates. We developed four criteria for the use of a method within the simple test bed of linear regression, where our method was y=wx and our intermediate was : (1) Can the intermediate be predicted from hidden states? (2) Is the intermediate's encoding quality correlated with the model performance? (3) Can the majority of variance in hidden states be explained by the intermediate? (4) Can we intervene on hidden states to produce predictable outcomes? Armed with these two correlational (1,2), weak causal (3), and strong causal (4) criteria, we determined that transformers use known numerical methods to model the trajectories of the simple harmonic oscillator, specifically, the matrix exponential method.

Vital lessons from struggling partnerships and potential partnerships: an international study with leaders across the health sector.

Background: Inter-organizational partnerships and collaborations, used here interchangeably, have growing prominence across the health sector. Successful partnerships have received extensive study. However, especially for partnerships including nonprofit partners, limited attention has been given to negative factors that contribute to struggling partnerships, including failed partnerships, and/or impede potential partnerships, including unexplored and undeveloped potential partnerships.

IMPDH inhibitors upregulate PD-L1 in cancer cells without impairing immune checkpoint inhibitor efficacy.

Tumor cells are characterized by rapid proliferation. In order to provide purines for DNA and RNA synthesis, inosine 5'-monophosphate dehydrogenase (IMPDH), a key enzyme in the de novo guanosine biosynthesis, is highly expressed in tumor cells. In this study we investigated whether IMPDH was involved in cancer immunoregulation.

Multivariate Pattern Analysis of EEG Reveals Neural Mechanism of Naturalistic Target Processing in Attentional Blink.

The human brain has inherent limitations in consciously processing visual information. When individuals monitor a rapid sequence of images for detecting two targets, they often miss the second target (T2) if it appears within a short time frame of 200-500 ms after the first target (T1), a phenomenon known as the attentional blink (AB). The neural mechanism behind the AB remains unclear, largely due to the use of simplistic visual items such as letters and digits in conventional AB experiments, which differ significantly from naturalistic vision.

Screening for severe coronary stenosis in patients with apparently normal electrocardiograms based on deep learning.

Background: Patients with severe coronary arterystenosis may present with apparently normal electrocardiograms (ECGs), making it difficult to detect adverse health conditions during routine screenings or physical examinations. Consequently, these patients might miss the optimal window for treatment.

Methods: We aimed to develop an effective model to distinguish severe coronary stenosis from no or mild coronary stenosis in patients with apparently normal ECGs.

Isorhapontigenin alleviates acetaminophen-induced liver injury by promoting fatty acid oxidation.

Acetaminophen (APAP) is a widely used analgesic and antipyretic medicine. It is frequently employed to alleviate pain and mitigate fever-related symptoms, but it can cause liver injury or even liver failure when overdosed. Isorhapontigenin, a compound derived from Chinese herbs and grapes, has been demonstrated to exhibit antioxidant and anti-inflammatory effects.

Network analysis of U.S. non-fatal opioid-involved overdose journeys, 2018-2023.

We present a nation-wide network analysis of non-fatal opioid-involved overdose journeys in the United States. Leveraging a unique proprietary dataset of Emergency Medical Services incidents, we construct a journey-to-overdose geospatial network capturing nearly half a million opioid-involved overdose events spanning 2018-2023. We analyze the structure and sociological profiles of the nodes, which are counties or their equivalents, characterize the distribution of overdose journey lengths, and investigate changes in the journey network between 2018 and 2023.

OncoSexome: the landscape of sex-based differences in oncologic diseases.

The NIH policy on sex as biological variable (SABV) emphasized the importance of sex-based differences in precision oncology. Over 50% of clinically actionable oncology genes are sex-biased, indicating differences in drug efficacy. Research has identified sex differences in non-reproductive cancers, highlighting the need for comprehensive sex-based cancer data.

Predicting Pancreatic Cancer in New-Onset Diabetes Cohort Using a Novel Model With Integrated Clinical and Genetic Indicators: A Large-Scale Prospective Cohort Study.

Introduction: Individuals who develop new-onset diabetes have been identified as a high-risk cohort for pancreatic cancer (PC), exhibiting an incidence rate nearly 8 times higher than the general population. Hence, the targeted screening of this specific cohort presents a promising opportunity for early pancreatic cancer detection. We aimed to develop and validate a novel model capable of identifying high-risk individuals among those with new-onset diabetes.

A mathematical model of glomerular fibrosis in diabetic kidney disease to predict therapeutic efficacy.

Background: Glomerular fibrosis is a tissue damage that occurs within the kidneys of chronic and diabetic kidney disease patients. Effective treatments are lacking, and the mechanism of glomerular damage reversal is poorly understood.

Methods: A mathematical model suitable for hypothesis-driven systems pharmacology of glomerular fibrosis in diabetes was developed from a previous model of interstitial fibrosis.

Accuracy and efficiency of drilling trajectories with augmented reality versus conventional navigation randomized crossover trial.

Conventional navigation systems (CNS) in surgery require strong spatial cognitive abilities and hand-eye coordination. Augmented Reality Navigation Systems (ARNS) provide 3D guidance and may overcome these challenges, but their accuracy and efficiency compared to CNS have not been systematically evaluated. In this randomized crossover study with 36 participants from different professional backgrounds (surgeons, students, engineers), drilling accuracy, time and perceived workload were evaluated using ARNS and CNS.

Carrier-free immobilized enzyme for ligand fishing of carbonic anhydrase inhibitors in Salvia miltiorrhiza.

The traditional method for natural products discovering could be time-consuming and labor-intensive, thus ligand fishing has attracted a lot of attention as a fast-screening method. Nevertheless, ligand fishing often relied on immobilized enzyme with solid carriers, which can be expensive and complicated to prepare. In this study, a carrier-free enzyme immobilization technology, cross-linked enzyme aggregates (CLEAs), was introduced by preparing carbonic anhydrase cross-linked enzyme aggregates (CA-CLEAs), aiming to develop a method for ligand fishing that is simpler, faster and more cost-effective.

Sorcin can trigger pancreatic cancer-associated new-onset diabetes through the secretion of inflammatory cytokines such as serpin E1 and CCL5.

A rise in blood glucose is an early warning sign of underlying pancreatic cancer (PC) and may be an indicator of genetic events in PC progression. However, there is still a lack of mechanistic research on pancreatic cancer-associated new-onset diabetes (PCAND). In the present study, we identified a gene SRI, which possesses a SNP with the potential to distinguish PCAND and Type 2 diabetes mellitus (T2DM), by machine learning on the basis of the UK Biobank database.

A Parrondo paradox in susceptible-infectious-susceptible dynamics over periodic temporal networks.

Many social and biological networks periodically change over time with daily, weekly, and other cycles. Thus motivated, we formulate and analyze susceptible-infectious-susceptible (SIS) epidemic models over temporal networks with periodic schedules. More specifically, we assume that the temporal network consists of a cycle of alternately used static networks, each with a given duration.

Genomic, Epigenomic, and Transcriptomic Inter- and Intratumor Heterogeneity in Desmoid Tumors.

Purpose: Desmoid tumors are bland fibroblastic tumors that do not metastasize but have a high rate of local recurrence. Previously published studies proposed two different transcriptomic signatures to predict relapse. Molecular heterogeneity has been well established in high-grade sarcomas, but little is known about molecular variability within locally aggressive tumors such as desmoids.

Performance Prediction of High-Entropy Perovskites LaSrMnCoFeO with Automated High-Throughput Characterization of Combinatorial Libraries and Machine Learning.

Perovskite oxides form a large family of materials with applications across various fields, owing to their structural and chemical flexibility. Efficient exploration of this extensive compositional space is now achievable through automated high-throughput experimentation combined with machine learning. In this study, we investigate the composition-structure-performance relationships of high-entropy LaSrMnCoFeO perovskite oxides (0 < x, y, z <1; x+y+z≈1) for application as oxygen electrodes in Solid Oxide Cells.