Heterogeneous Information and Appraisal Smoothing

This study examines the heterogeneous appraiser behavior and its implication on the traditional appraisal smoothing theory. We show that the partial adjustment model is consistent with the traditional appraisal smoothing argument only when all the appraisers choose the same smoothing technique. However, if appraiser behavior is heterogeneous and exhibits cross-sectional variation due to the difference in their access to, and interpretation of information, the model actually leads to a mixed outcome: The variance of the appraisal-based returns can be higher or lower than the variance of transaction-based return depending on the degree of such heterogeneity. Using data from the residential market, we find that, contrary to what the traditional appraisal smoothing theory would predict, appraisal-based indices may not suffer any “smoothing” bias. These findings suggest that the traditional appraisal smoothing theory, which fails to consider the heterogeneity of appraiser behaviors, exaggerates the effect of appraisal smoothing.

Ownership Restriction and Housing Value: Evidence from American Housing survey

Amendments to the Fair Lending Act have exempted an age restriction on ownership from fair housing prohibitions. This paper studies the economic impact of such ownership restriction on housing values. Using American Housing Survey data, we find that there is a significant premium attached to the restrictive covenant when other factors are controlled. In particular, we find that imposing age restriction on ownership increases the housing values by anywhere from 10.5% to 12.7%. At the average house value, this is equivalent to a dollar amount between $14,642 and$17,399. The estimates are robust to different specifications in hedonic equations.

Effect of Ambient Pressure on Equilibrium Moisture Content of Wood

The equilibrium moisture content (EMC) of Russian larch wood, Sugi wood, and Hinoki wood was measured under vacuum conditions at temperatures of 45, 50, and 60°C and ambient pressures of 13.3, 53.3, and 101.3 kPa. The results show that the EMC of each species increased with a decrease in ambient pressure. The effect of temperature and RH on EMC under vacuum conditions showed a similar tendency. Wet-bulb temperature needed to be controlled to measure EMC, even under vacuum, because pressure was not maintained only by water vapor pressure because of the presence of air in the vessel. There were obvious differences between the EMC values obtained in this experiment and previous experimental EMC values in which the wet-bulb temperature was not controlled

Challenges in cell culture platform development of mAb production with site-specific incorporation of non-natural amino acid for ADC generation

Ambrx’s mammalian expression platform (EuCODE) enables non-native amino acids (nnAAs) through an expanded genetic code to both generate novel bio-therapeutics and to optimize the performance of antibody drug conjugate (ADC), therapeutic proteins, monoclonal antibodies (mAbs), and, bi- and multi-specific medicines. While the ability to control the defined Drug-to-Antibody Ratio (DAR) and payload site can provide an advantage to an ADC, the site-specific incorporation of the NAAs into the antibody heavy chain introduces a unique challenge for antibody production. To enable higher performance benchmarks in time and resources for process development with stringent product quality requirements, a proprietary cell culture platform is being developed and demonstrated fast-track development of high-quality, high-titer processes for producing recombinant proteins from CHO cells. We successfully generated a CHO-K1 cell line, stably expressing engineered amber suppressor tRNA and its cognate tRNA synthetase specific for non-natural amino acid para-acetyl phenylalanine (pAF), to achieve high production of monoclonal antibodies (mAbs) containing nnAAs. The stable cell lines were further evolved using CRISPR/Cas9 genome editing technology to sequentially knock out selected genes in glutamine synthesis, and, apoptosis pathways to improve selection efficiency and prevent loss of viable cell mass in production cultures, respectively. Inhibition of apoptosis pathway leads to dramatic increase in viable cell mass and results in extended production time and increased productivity. In this presentation, we will discuss the challenges in cell culture platform development including cell line engineering, systematic DoE-based approaches on optimal chemically defined media and cell culture processes, and, strategies for scale up to clinical and commercial scales

CRISPR-Cas9 mediated cell line engineering of apoptosis pathways increases antibody expression with site-specific modifications for antibody drug conjugation

New generation of antibody drug conjugates (ADCs) have expanded the repertoire of antibody drugs in the clinic and the market for cancer and inflammation indications by using highly stable linkers to attach potent small-molecule drug to various targeting antibodies. The drug and site of drug linkage to the antibody can have profound impact on the physiochemical properties and pharmacological profile of the ADC. Ambrx has developed a technology, Eukaryotic Chemical Orthogonal Directed Engineering (EuCODE), which allows non-natural amino acids with diverse physicochemical and biological properties to be genetically encoded and site-specifically incorporated into proteins/antibodies in mammalian cells. The non-natural amino acid provides a handle for the attachment of a small-molecule drug to generate homogenous ADC with a defined Drug-to-Antibody Ratio (DAR). To establish a CHO expression system for high production of monoclonal antibodies (mAbs) containing non-natural amino acids, we successfully generated a EuCODE platform cell line stably expressing engineered amber suppressor tRNA and its cognate tRNA synthetase specific for non-natural amino acid para-acetyl phenylalanine (pAF). When transfected with antibody of interest engineered with amber nonsense codon (TAG) at selected sites suitable for drug conjugation, this EuCODE platform cell line generates stable cell lines producing pAF containing mAbs for site-specifically conjugated ADC. In order to improve production titers of pAF containing antibody and achieve a robust platform, the platform cell line and stable cell lines were further evolved using CRISPR/Cas9 genome editing technology to sequentially knock out selected genes in glutamine synthesis and apoptosis pathways to improve selection efficiency and prevent loss of viable cell mass in production cultures, respectively. Inhibition of apoptosis pathway leads to dramatic increase in viable cell mass and results in extended production time and increased productivity. Phenotypic and genetic properties of these CRISPR engineered cell lines and product quality of the antibody will be discussed in the context of using the platform to develop a commercial manufacturing cell line

Determination of 6 kinds of carbamate pesticides and 3 kinds of chloronicotinyl pesticides in Chinese Kushui rose by ultra high performance liquid chromatography-tandem mass spectrometry coupled with QuEChERS

Objective To establish a method for determination of 6 kinds of carbamate pesticides and 3 kinds of chloronicotinyl pesticides in Chinese Kushui rose by ultra high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) coupled with QuEChERS. Methods After extracted by acetonitrile, the Chinese Kushui rose was cleaned by QuEChERS. The target compounds were separated by C18 column (2.1 mm×100 mm, 1.7 μm) using 10 mmol/L ammonium acetate solution (0.1% formic acid) with acetonrtrile as mobile phase for gradient elution, and analyzed by MS/MS system with electrospray ionization (ESI+) under muti-reaction monitoring mode and quantified by external standard method. Results All the 9 kinds of pesticides showed good linear relationships in range of 0.01-0.50 μg/mL, and the correlation coefficients were above 0.990, the recoveries at different spiked levels for all target compounds in blank matrices were 76.3%-102%, and the relative standard deviation (RSD) were 1.3%-9.0% (n=6). The limits of detection and quantification of the method were 0.001 6-0.003 2 and 0.005 4-0.010 mg/kg. Conclusion The method was suitable for rapid screening and analysis of 9 pesticide residues in Chinese Kushui rose with the advantage of accuracy, rapidity, simplicity and high sensitivity

Flames: Benchmarking Value Alignment of Chinese Large Language Models

The widespread adoption of large language models (LLMs) across various regions underscores the urgent need to evaluate their alignment with human values. Current benchmarks, however, fall short of effectively uncovering safety vulnerabilities in LLMs. Despite numerous models achieving high scores and 'topping the chart' in these evaluations, there is still a significant gap in LLMs' deeper alignment with human values and achieving genuine harmlessness. To this end, this paper proposes the first highly adversarial benchmark named Flames, consisting of 2,251 manually crafted prompts, ~18.7K model responses with fine-grained annotations, and a specified scorer. Our framework encompasses both common harmlessness principles, such as fairness, safety, legality, and data protection, and a unique morality dimension that integrates specific Chinese values such as harmony. Based on the framework, we carefully design adversarial prompts that incorporate complex scenarios and jailbreaking methods, mostly with implicit malice. By prompting mainstream LLMs with such adversarially constructed prompts, we obtain model responses, which are then rigorously annotated for evaluation. Our findings indicate that all the evaluated LLMs demonstrate relatively poor performance on Flames, particularly in the safety and fairness dimensions. Claude emerges as the best-performing model overall, but with its harmless rate being only 63.08% while GPT-4 only scores 39.04%. The complexity of Flames has far exceeded existing benchmarks, setting a new challenge for contemporary LLMs and highlighting the need for further alignment of LLMs. To efficiently evaluate new models on the benchmark, we develop a specified scorer capable of scoring LLMs across multiple dimensions, achieving an accuracy of 77.4%. The Flames Benchmark is publicly available on https://github.com/AIFlames/Flames