Conditional cooperation is the tendency to cooperate if and only if others do so as well. It is the most common behavior in social dilemmas. We study how the incidence of conditional cooperation in the public goods game, the most widely studied social dilemma in experimental economics, varies with group size. In a laboratory experiment, we apply the strategy method to elicit how participants’ willingness to contribute to a public good depends on other group members’ decisions. A within-subject design allows us to evaluate and compare an individual participant's contribution behavior in different-sized groups. Two main findings emerge. First, the share of players who are conditional cooperators is consistent across group sizes. Second, the strategies chosen imply that conditional cooperators hold a (correct) belief that others are more cooperative in a larger than in a smaller group.

Jicha is a Bronze Age settlement located next to the upper Mekong River in the Hengduan Mountains of Yunnan, south-west China. Recent excavations have revealed details of successive occupation and copper-base industrial activity. The site's position and chronology provide evidence of north–south demographic movement and technological transmission along the eastern Qinghai-Tibet Plateau corridor.

Data-driven generative design (DDGD) methods utilize deep neural networks to create novel designs based on existing data. The structure-aware DDGD method can handle complex geometries and automate the assembly of separate components into systems, showing promise in facilitating creative designs. However, determining the appropriate vectorized design representation (VDR) to evaluate 3D shapes generated from the structure-aware DDGD model remains largely unexplored. To that end, we conducted a comparative analysis of surrogate models’ performance in predicting the engineering performance of 3D shapes using VDRs from two sources: the trained latent space of structure-aware DDGD models encoding structural and geometric information and an embedding method encoding only geometric information. We conducted two case studies: one involving 3D car models focusing on drag coefficients and the other involving 3D aircraft models considering both drag and lift coefficients. Our results demonstrate that using latent vectors as VDRs can significantly deteriorate surrogate models’ predictions. Moreover, increasing the dimensionality of the VDRs in the embedding method may not necessarily improve the prediction, especially when the VDRs contain more information irrelevant to the engineering performance. Therefore, when selecting VDRs for surrogate modeling, the latent vectors obtained from training structure-aware DDGD models must be used with caution, although they are more accessible once training is complete. The underlying physics associated with the engineering performance should be paid attention. This paper provides empirical evidence for the effectiveness of different types of VDRs of structure-aware DDGD for surrogate modeling, thus facilitating the construction of better surrogate models for AI-generated designs.

Risk of bias assessment is a critical step of any meta-analysis or systematic review. Given the low sample count of many microbiome studies, especially observational or cohort studies involving human subjects, many microbiome studies have low power. This increases the importance of performing meta-analysis and systematic review for microbiome research in order to enhance the relevance and applicability of microbiome results. This work proposes a method based on the ROBINS-I tool to systematically consider sources of bias in microbiome research seeking to perform meta-analysis or systematic review for microbiome studies.

Site-specific weed management (on the scale of a few meters or less) has the potential to greatly reduce pesticide use and its associated environmental and economic costs. A prerequisite for site-specific weed management is the availability of accurate maps of the weed population that can be generated quickly and cheaply. Improvements and cost reductions in unmanned aerial vehicles (UAVs) and camera technology mean these tools are now readily available for agricultural use. We used UAVs to collect aerial images captured in both RGB and multispectral formats of 12 cereal fields (wheat [Triticum aestivum L.] and barley [Hordeum vulgare L.]) across eastern England. These data were used to train machine learning models to generate prediction maps of locations of black-grass (Alopecurus myosuroides Huds.), a prolific weed in UK cereal fields. We tested machine learning and data set resampling methods to obtain the most accurate system for predicting the presence and absence of weeds in new out-of-sample fields. The accuracy of the system in predicting the absence of A. myosuroides is 69% and its presence above 5 g in weight with 77% accuracy in new out-of-sample fields. This system generates prediction maps that can be used by either agricultural machinery or autonomous robotic platforms for precision weed management. Improvements to the accuracy can be made by increasing the number of fields and samples in the data set and the length of time over which data are collected to gather data across the entire growing season.

We analyze whether industry competition influences analyst coverage decisions and whether analysts benefit from covering product market competitors. We find that analysts are more likely to cover a firm when this firm competes with more firms already covered by the analyst. We also find that the intensity of competition among these competitors is additionally important to the coverage decision. Moreover, we find that analysts who cover product market competitors are more likely to obtain analyst star status. These results are consistent with the importance to analysts of industry competition and product market knowledge accumulated through covering product market competitors.

This study presents a cross-temporal comparison of managerial ethics in China and the US. Although it is well established that cross-cultural differences exist in business ethics and that culture and values in a society may evolve over time, little attention has been paid to the longitudinal changes in such cross-cultural differences that might have occurred over time. Building on three different perspectives on values evolution, namely, convergence, divergence, and crossvergence, we investigate whether and how cross-cultural differences in managerial ethical decision-making and the associated moral philosophy have changed in China and the US over the decade between the mid-1990s and the mid-2000s. Our analysis reveals that the difference in Chinese and American managers' ethical decision-making evolved in many different directions over the decade, lending support to the crossvergence perspective. Interestingly, however, we discover that the divergence outlook prevails when it comes to the moral philosophies behind their decision-making. These findings provide critical insights into cross-cultural as well cross-temporal evolution in business ethics in a world of increasing cross-cultural and multicultural interactions.

Having upended the traditional software development, which historically was centred exclusively on proprietary, copyright-protected code, open-source has now entered the physical artefact world. In doing so, it has started to change not only how physical products are designed and developed, but also the commercialisation process. In recent years, authors have witnessed entrepreneurs intentionally choosing not to patent their product design and technologies but instead licencing the designs and technologies under open-source licences. The entrepreneurs share their product designs online with their community – people who congregated due to the shared interests in products’ technology or project’s social objectives. Founding a startup firm without excluding others from using their own invention is not a common practice. Therefore, there is reason to ask if this choice a strategic decision or irrational action due to short-sightedness or extreme altruism? Conducting interviews with 65 founders, we grounded a framework explaining that the driver of going open is a result of both intrinsic and extrinsic factors. In addition, we observed the change of identities over time among the entrepreneurs. We hope to use this paper as a pilot study of this emerging socio-technological phenomenon, which is understudied relative to the proprietary product commercialisation process.

Heterogeneity in the number of secondary tuberculosis (TB) cases per source case, the effective reproductive number, R, is important in modelling prevention strategies' impact on incidence.

We estimated mean R (Rm) and calculate the dispersion parameter of this distribution, k, using surveillance and genotyping data for U.S. cases during 2009–2018. We modelled transmission assuming cases in a cluster have matching genotypes and share characteristics related to geography, temporal proximity (i.e. serial interval) and time since U.S. arrival among non-U.S.-born persons.

Complete data were available for 55 330/85 958 cases. Varying the serial interval and geographic proximity used to derive clusters, we consistently estimated Rm<1.0 and k < 0.08; the low value of k indicates a small number of source cases produce a disproportionate number of secondary cases.

U.S. TB reproductive number has a highly skewed distribution, indicating a minority of source cases disproportionately contribute to transmission.

There are three approaches to studying designers – through their cognitive profile, design behaviors, and design artifacts (e.g., quality). However, past work has rarely considered all three data domains together. Here we introduce and describe a framework for a comprehensive approach to engineering design, and discuss how the insights may benefit engineering design research and education. To demonstrate the proposed framework, we conducted an empirical study with a solar energy system design problem. Forty-six engineering students engaged in a week-long computer-aided design challenge that assessed their design behavior and artifacts, and completed a set of psychological tests to measure cognitive competencies. Using a machine learning approach consisting of k-means, hierarchical, and spectral clustering, designers were grouped by similarities on the psychological tests. Significant differences were revealed between designer groups in their sequential design behavior, suggesting that a designer's cognitive profile is related to how they engage in the design process.

The prevention, treatment and control of Haemonchus contortus have been increasingly problematic due to its widespread occurrence and anthelmintic resistance. There are very few descriptions of recombinant antigens being protective for H. contortus, despite the success of various native antigen preparations, including Barbervax. We recently identified an H. contortus excretory–secretory antigen, H. contortus adhesion-regulating molecule 1 (HcADRM1), that served as an immunomodulator to impair host T-cell functions. Given the prophylactic potential of HcADRM1 protein as a vaccine candidate, we hereby assessed the efficacies of HcADRM1 preparations against H. contortus infection. Parasitological and immunological parameters were evaluated throughout all time points of the trials, including fecal egg counts (FEC), abomasal worm burdens, complete blood counts, cytokine production profiles and antibody responses. Active vaccination with recombinant HcADRM1 (rHcADRM1) protein induced protective immunity in inoculated goats, resulting in reductions of 48.9 and 58.6% in cumulative FEC and worm burdens. Simultaneously, passive administration of anti-HcADRM1 antibodies generated encouraging levels of protection with 46.7 and 56.2% reductions in cumulative FEC and worm burdens in challenged goats. In addition, HcADRM1 preparations-immunized goats showed significant differences in mucosal and serum antigen-specific immunoglobulin G (IgG) levels, total mucosal IgA levels, haemoglobin values and circulating interferon-γ, interleukin (IL)-4 and IL-17A production compared to control goats in both trials. The preliminary data of these laboratory trials validated the immunoprophylactic effects of rHcADRM1 protein. It can be pursued as a potential vaccine antigen to develop an effective recombinant subunit vaccine against H. contortus under field conditions.

ABSTRACT IMPACT: Triple negative breast cancer (TNBC) affects 10-20% of women with breast cancer and is biologically more aggressive than other subtypes. The novel compound we have developed, DL7076, would give clinicians a vital strategy to improve the commonly used cyclophosphamide (CPA) and doxorubicin (DOX) regimen in the treatment of TNBC. OBJECTIVES/GOALS: The objective of this research project is to develop a novel compound which can activate both 1) the constitutive androstane receptor (CAR) and subsequently enhance the CYP2B6-mediated activation of CPA, and 2) the nuclear factor erythroid- related factor-2 (Nrf2) leading to the cardiomyocyte protection from DOX-associated cardiotoxicity. METHODS/STUDY POPULATION: Following the identification of the compound candidate, DL7076 was evaluated for tissue specific induction of CAR and Nrf2 using qPCR, western blot analysis, and luciferase reporter assays.

Further, we have developed a multicellular coculture model incorporating human primary hepatocytes for metabolism, TNBC spheroids as the target, and cardiomyocytes as a side target of DOX. We have investigated the anticancer effects of CPA/DOX on TNBC cells and the toxic effects on cardiomyocytes with/without a CAR-Nrf2 activator, in a multicellular environment where hepatic metabolism is well-retained. RESULTS/ANTICIPATED RESULTS: We found that our dual activator of CAR and Nrf2, DL7076, exhibits tissue specific induction of CAR and Nrf2. Inclusion of DL7076 in combination with the CPA/DOX regimen improves anticancer efficacy, through the subsequent increase in the formation of the active CPA metabolite. With the addition of DL7076, DOX-mediated off-target cardiotoxicity was markedly reduced.

Lastly, utilizing the novel coculture system with human primary hepatocytes, TNBC spheroids, and cardiomyocytes, the inclusion of DL7076 to the CPA/DOX regimen shows decreased spheroid viability and improved cardiomyocyte viability and function. DISCUSSION/SIGNIFICANCE OF FINDINGS: Our findings suggest that DL7076 can facilitate DOX/CPA containing regimens by increasing CAR-mediated metabolism and subsequent CPA bioactivation while selectively protecting cardiomyocytes from DOX-induced toxicity. This research is expected to translate our basic scientific findings into therapeutic interventions for women with TNBC.

ABSTRACT IMPACT: This study advances our understanding of potentially key drivers in the early formation of pancreatic cancer, a disease with few treatment options and poor patient outcomes. OBJECTIVES/GOALS: Patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) have a 5-year survival rate of ˜9%. A key driver of poor patient outcomes is late-stage diagnosis. A better understanding of PDAC onset is needed. This study was developed to understand how extracellular vesicles may be involved in the early formation of PDAC. METHODS/STUDY POPULATION: Extracellular vesicles (EVs) were isolated from several human PDAC and normal pancreatic cell lines, using ultracentrifugation with filtration or size exclusion chromatography. We next treated normal pancreatic cell lines with cancer cell EVs (cEVs). Next generation sequencing was used to measure global gene expression changes after treatment. Validations were performed using qPCR and luciferase activity assays. Multi-omics characterization of EVs was accomplished using mass spectrometry based proteomics, metabolomics and lipidomics analysis. RESULTS/ANTICIPATED RESULTS: We found that normal cells upregulated a variety of stress response pathways in response to cEVs. Lipid synthesis was also severely downregulated in these cells. We further validated activation of the unfolded protein response (UPR) in normal cells treated with cEVs. Multi-omics characterization of cEVs identified several enriched proteins, lipids and metabolites which may play a role in the activation of the UPR. DISCUSSION/SIGNIFICANCE OF FINDINGS: Our results indicate that cEVs induce stress, and in particular the UPR, in normal pancreatic cells. Long-term UPR can impact a variety of cancer hallmarks. The UPR can mediate progression of pancreatic intraepithelial neoplasia (PanIN) to PDAC. Our results highlight a potential role for cEVs to alter the function of normal cells, aiding disease onset.