Evorus: A Crowd-powered Conversational Assistant Built to Automate Itself Over Time

Crowd-powered conversational assistants have been shown to be more robust than automated systems, but do so at the cost of higher response latency and monetary costs. A promising direction is to combine the two approaches for high quality, low latency, and low cost solutions. In this paper, we introduce Evorus, a crowd-powered conversational assistant built to automate itself over time by (i) allowing new chatbots to be easily integrated to automate more scenarios, (ii) reusing prior crowd answers, and (iii) learning to automatically approve response candidates. Our 5-month-long deployment with 80 participants and 281 conversations shows that Evorus can automate itself without compromising conversation quality. Crowd-AI architectures have long been proposed as a way to reduce cost and latency for crowd-powered systems; Evorus demonstrates how automation can be introduced successfully in a deployed system. Its architecture allows future researchers to make further innovation on the underlying automated components in the context of a deployed open domain dialog system.Comment: 10 pages. To appear in the Proceedings of the Conference on Human Factors in Computing Systems 2018 (CHI'18

PaLM: Scaling Language Modeling with Pathways

Large language models have been shown to achieve remarkable performance across a variety of natural language tasks using few-shot learning, which drastically reduces the number of task-specific training examples needed to adapt the model to a particular application. To further our understanding of the impact of scale on few-shot learning, we trained a 540-billion parameter, densely activated, Transformer language model, which we call Pathways Language Model PaLM. We trained PaLM on 6144 TPU v4 chips using Pathways, a new ML system which enables highly efficient training across multiple TPU Pods. We demonstrate continued benefits of scaling by achieving state-of-the-art few-shot learning results on hundreds of language understanding and generation benchmarks. On a number of these tasks, PaLM 540B achieves breakthrough performance, outperforming the finetuned state-of-the-art on a suite of multi-step reasoning tasks, and outperforming average human performance on the recently released BIG-bench benchmark. A significant number of BIG-bench tasks showed discontinuous improvements from model scale, meaning that performance steeply increased as we scaled to our largest model. PaLM also has strong capabilities in multilingual tasks and source code generation, which we demonstrate on a wide array of benchmarks. We additionally provide a comprehensive analysis on bias and toxicity, and study the extent of training data memorization with respect to model scale. Finally, we discuss the ethical considerations related to large language models and discuss potential mitigation strategies

Bond strength of different endodontic sealers to dentin: push-out test

OBJECTIVE: The aim of this in vitro study was to evaluate the bond strength of different root canal sealers to dentin. MATERIAL AND METHODS: Forty extracted single-rooted human teeth were examined and the coronal and middle thirds of the canals were prepared with a 1.50 mm post drill (FibreKor Post System, Pentron). The teeth were allocated in two experimental groups, irrigated with 2.5% NaOCl+17% EDTA or saline solution (control group) and instrumented using Race rotary files (FKG) to a size #40 at the working length. Then, the groups were divided into four subgroups and filled with Epiphany sealer (Group 1), EndoREZ (Group 2), AH26 (Group 3) and Grossman's Sealer (Group 4). After 2 weeks of storage in 100% humidity at 37ºC, all teeth were sectioned transversally into 2-mm-thick discs. Push-out tests were performed at a cross-head speed of 1 mm/min using a universal testing machine. The maximum load at failure was recorded and expressed in MPa. RESULTS: Means (±SD) in root canals irrigated with 2.5% NaOCl and 17% EDTA were: G1 (21.6±6.0), G2 (15.2±3.7), G3 (14.6±4.5) and G4 (11.7±4.1).Two-way ANOVA and Tukey's test showed the highest bond strength for the Epiphany's group (p< 0.01) when compared to the other tested sealers. Saline solution decreased the values of bond-strength (p<0.05) for all sealers. CONCLUSION: Epiphany sealer presented higher bond strength values to dentin in both irrigating protocols, and the use of 2.5% NaOCl and 17% EDTA increased the bond strength values for all sealers

PaLM 2 Technical Report

We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is a Transformer-based model trained using a mixture of objectives. Through extensive evaluations on English and multilingual language, and reasoning tasks, we demonstrate that PaLM 2 has significantly improved quality on downstream tasks across different model sizes, while simultaneously exhibiting faster and more efficient inference compared to PaLM. This improved efficiency enables broader deployment while also allowing the model to respond faster, for a more natural pace of interaction. PaLM 2 demonstrates robust reasoning capabilities exemplified by large improvements over PaLM on BIG-Bench and other reasoning tasks. PaLM 2 exhibits stable performance on a suite of responsible AI evaluations, and enables inference-time control over toxicity without additional overhead or impact on other capabilities. Overall, PaLM 2 achieves state-of-the-art performance across a diverse set of tasks and capabilities. When discussing the PaLM 2 family, it is important to distinguish between pre-trained models (of various sizes), fine-tuned variants of these models, and the user-facing products that use these models. In particular, user-facing products typically include additional pre- and post-processing steps. Additionally, the underlying models may evolve over time. Therefore, one should not expect the performance of user-facing products to exactly match the results reported in this report

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

A scoping review of nurse-led advance care planning.

BACKGROUND: Advance care planning (ACP) supports persons at any age or health status to determine their values, goals, and preferences regarding future medical care. The American Nurses Association endorses nurses to facilitate ACP to promote patient- and family-centered care. PURPOSE: This project reviewed and synthesized literature on nurse-led ACP training models. METHODS: A scoping review used the Arksey and O\u27Malley Framework to identify: (a) ACP training model type, (b) nurse-led ACP recipients, (c) ACP in special populations, (d) ACP outcomes. FINDINGS: Of 33 articles reviewed, 19 included 11 established models; however, the primary finding was lack of a clearly identified evidence-based nurse-led ACP training model. DISCUSSION: Nurses are integral team members, well positioned to be a bridge of communication between patients and care providers. This is a call to action for nurse leaders, researchers, educators to collaborate to identify and implement an evidence-based, effective nurse-led ACP training model

Mutated in colorectal cancer (Mcc), a candidate tumor suppressor, is dynamically expressed during mouse embryogenesis

10.1002/dvdy.22712Developmental Dynamics24092166-2174DEDY

A Cross-Sectional Study of Bone Nanomechanics in Hip Fracture and Aging

Bone mechanics is well understood at every length scale except the nano-level. We aimed to investigate the relationship between bone nanoscale and tissue-level mechanics experimentally. We tested two hypotheses: (1) nanoscale strains were lower in hip fracture patients versus controls, and (2) nanoscale mineral and fibril strains were inversely correlated with aging and fracture. A cross-sectional sample of trabecular bone sections was prepared from the proximal femora of two human donor groups (aged 44–94 years): an aging non-fracture control group (n = 17) and a hip-fracture group (n = 20). Tissue, fibril, and mineral strain were measured simultaneously using synchrotron X-ray diffraction during tensile load to failure, then compared between groups using unpaired t-tests and correlated with age using Pearson’s correlation. Controls exhibited significantly greater peak tissue, mineral, and fibril strains than the hip fracture (all p p = 0.099) and mineral (p = 0.004) strain, but not fibril strain (p = 0.260). Overall, hip fracture and aging were associated with changes in the nanoscale strain that are reflected at the tissue level. Data must be interpreted within the limitations of the observational cross-sectional study design, so we propose two new hypotheses on the importance of nanomechanics. (1) Hip fracture risk is increased by low tissue strain, which can be caused by low collagen or mineral strain. (2) Age-related loss of tissue strain is dependent on the loss of mineral but not fibril strain. Novel insights into bone nano- and tissue-level mechanics could provide a platform for the development of bone health diagnostics and interventions based on failure mechanisms from the nanoscale up