The 2nd Place Solution for 2023 Waymo Open Sim Agents Challenge

In this technical report, we present the 2nd place solution of 2023 Waymo Open Sim Agents Challenge (WOSAC)[4]. We propose a simple yet effective autoregressive method for simulating multi-agent behaviors, which is built upon a well-known multimodal motion forecasting framework called Motion Transformer (MTR)[5] with postprocessing algorithms applied. Our submission named MTR+++ achieves 0.4697 on the Realism Meta metric in 2023 WOSAC. Besides, a modified model based on MTR named MTR_E is proposed after the challenge, which has a better score 0.4911 and is ranked the 3rd on the leaderboard of WOSAC as of June 25, 2023

Porous amorphous Ge/C composites with excellent electrochemical properties

Porous amorphous germanium/carbon (Ge/C) composites, which were synthesized through the reduction/carbonization of germanium oxide/oleic acid precursors, could exhibit a high-capacity, high-rate and long-life performance due to the synergistic effect of the porous structure and carbon

Dibromido{2-hydr­oxy-N′-[phen­yl(2-pyrid­yl)methyl­ene]benzohydrazide}copper(II)

In the title complex, [CuBr2(C19H15N3O2)], the metal ion is coordinated by the N,N′,O-tridentate 2-hydr­oxy-N′-[phen­yl(2-pyrid­yl)methyl­ene]benzohydrazide ligand and two bromide ions, resulting in a distorted CuN2OBr2 square-based pyramidal coordination geometry with one bromide ion in the apical site. An intra­molecular N—H⋯O hydrogen bond occurs in the ligand. In the crystal, mol­ecules are connected by inter­molecular C—H⋯O, C—H⋯Br and O—H⋯Br inter­actions

Inhibitory Effect of Phthalic Acid on Tyrosinase: The Mixed-Type Inhibition and Docking Simulations

Tyrosinase inhibition studies are needed due to the medicinal applications such as hyperpigmentation. For probing effective inhibitors of tyrosinase, a combination of computational prediction and enzymatic assay via kinetics was important. We predicted the 3D structure of tyrosinase, used a docking algorithm to simulate binding between tyrosinase and phthalic acid (PA), and studied the reversible inhibition of tyrosinase by PA. PA inhibited tyrosinase in a mixed-type manner with a Ki = 65.84 ± 1.10 mM. Measurements of intrinsic and ANS-binding fluorescences showed that PA induced changes in the active site structure via indirect binding. Simulation was successful (binding energies for Dock6.3 = −27.22 and AutoDock4.2 = −0.97 kcal/mol), suggesting that PA interacts with LEU73 residue that is predicted commonly by both programs. The present study suggested that the strategy of predicting tyrosinase inhibition based on hydroxyl groups and orientation may prove useful for screening of potential tyrosinase inhibitors

Bis(dicyanamido-κN 1)bis­[2-(2-hydroxy­ethyl)pyridine-κ2 N,O]nickel(II)

In the title complex, [Ni{N(CN)2}2(C7H9NO)2], the NiII ion (site symmetry ) adopts a distorted trans-NiO2N4 octa­hedral geometry. In the crystal, inter­molecular O—H⋯N hydrogen bonds link the mol­ecules, forming a chain along the c axis

Marbofloxacin

In the title compound, [systematic name: 9-fluoro-2,3-dihydro-3-methyl-10-(4-methyl­piperazin-1-yl)-7-oxo-7H-pyrido[1,2,3-ij][1,2,4]benzoxadiazine-6-carb­oxy­lic acid], C17H19FN4O4, the carbonyl and carboxyl groups are coplanar with the quinoline ring, making a dihedral angle of 2.39 (2)°. The piperazine ring adopts a chair conformation and the oxadiazinane ring displays an envelope conformation with the CH2 group at the flap displaced by 0.650 (2) Å from the plane through the other five atoms. The mol­ecular structure exhibits an S(6) ring motif, owing to an intra­molecular O—H⋯O hydrogen bond. In the crystal, weak C—H⋯F hydrogen bonds link mol­ecules into layers parallel to the ab plane

DiffNAS: Bootstrapping Diffusion Models by Prompting for Better Architectures

Diffusion models have recently exhibited remarkable performance on synthetic data. After a diffusion path is selected, a base model, such as UNet, operates as a denoising autoencoder, primarily predicting noises that need to be eliminated step by step. Consequently, it is crucial to employ a model that aligns with the expected budgets to facilitate superior synthetic performance. In this paper, we meticulously analyze the diffusion model and engineer a base model search approach, denoted "DiffNAS". Specifically, we leverage GPT-4 as a supernet to expedite the search, supplemented with a search memory to enhance the results. Moreover, we employ RFID as a proxy to promptly rank the experimental outcomes produced by GPT-4. We also adopt a rapid-convergence training strategy to boost search efficiency. Rigorous experimentation corroborates that our algorithm can augment the search efficiency by 2 times under GPT-based scenarios, while also attaining a performance of 2.82 with 0.37 improvement in FID on CIFAR10 relative to the benchmark IDDPM algorithm