Workflow-Guided Response Generation for Task-Oriented Dialogue

Task-oriented dialogue (TOD) systems aim to achieve specific goals through interactive dialogue. Such tasks usually involve following specific workflows, i.e. executing a sequence of actions in a particular order. While prior work has focused on supervised learning methods to condition on past actions, they do not explicitly optimize for compliance to a desired workflow. In this paper, we propose a novel framework based on reinforcement learning (RL) to generate dialogue responses that are aligned with a given workflow. Our framework consists of ComplianceScorer, a metric designed to evaluate how well a generated response executes the specified action, combined with an RL opimization process that utilizes an interactive sampling technique. We evaluate our approach on two TOD datasets, Action-Based Conversations Dataset (ABCD) (Chen et al., 2021a) and MultiWOZ 2.2 (Zang et al., 2020) on a range of automated and human evaluation metrics. Our findings indicate that our RL-based framework outperforms baselines and is effective at enerating responses that both comply with the intended workflows while being expressed in a natural and fluent manner

VERVE: Template-based ReflectiVE Rewriting for MotiVational IntErviewing

Reflective listening is a fundamental skill that counselors must acquire to achieve proficiency in motivational interviewing (MI). It involves responding in a manner that acknowledges and explores the meaning of what the client has expressed in the conversation. In this work, we introduce the task of counseling response rewriting, which transforms non-reflective statements into reflective responses. We introduce VERVE, a template-based rewriting system with paraphrase-augmented training and adaptive template updating. VERVE first creates a template by identifying and filtering out tokens that are not relevant to reflections and constructs a reflective response using the template. Paraphrase-augmented training allows the model to learn less-strict fillings of masked spans, and adaptive template updating helps discover effective templates for rewriting without significantly removing the original content. Using both automatic and human evaluations, we compare our method against text rewriting baselines and show that our framework is effective in turning non-reflective statements into more reflective responses while achieving a good content preservation-reflection style trade-off

Adaptive Endpointing with Deep Contextual Multi-armed Bandits

Current endpointing (EP) solutions learn in a supervised framework, which does not allow the model to incorporate feedback and improve in an online setting. Also, it is a common practice to utilize costly grid-search to find the best configuration for an endpointing model. In this paper, we aim to provide a solution for adaptive endpointing by proposing an efficient method for choosing an optimal endpointing configuration given utterance-level audio features in an online setting, while avoiding hyperparameter grid-search. Our method does not require ground truth labels, and only uses online learning from reward signals without requiring annotated labels. Specifically, we propose a deep contextual multi-armed bandit-based approach, which combines the representational power of neural networks with the action exploration behavior of Thompson modeling algorithms. We compare our approach to several baselines, and show that our deep bandit models also succeed in reducing early cutoff errors while maintaining low latency

Valproic Acid Induces Hair Regeneration in Murine Model and Activates Alkaline Phosphatase Activity in Human Dermal Papilla Cells

Alopecia is the common hair loss problem that can affect many people. However, current therapies for treatment of alopecia are limited by low efficacy and potentially undesirable side effects. We have identified a new function for valproic acid (VPA), a GSK3β inhibitor that activates the Wnt/β-catenin pathway, to promote hair re-growth in vitro and in vivo.Topical application of VPA to male C3H mice critically stimulated hair re-growth and induced terminally differentiated epidermal markers such as filaggrin and loricrin, and the dermal papilla marker alkaline phosphatase (ALP). VPA induced ALP in human dermal papilla cells by up-regulating the Wnt/β-catenin pathway, whereas minoxidil (MNX), a drug commonly used to treat alopecia, did not significantly affect the Wnt/β-catenin pathway. VPA analogs and other GSK3β inhibitors that activate the Wnt/β-catenin pathway such as 4-phenyl butyric acid, LiCl, and BeCl(2) also exhibited hair growth-promoting activities in vivo. Importantly, VPA, but not MNX, successfully stimulate hair growth in the wounds of C3H mice.Our findings indicate that small molecules that activate the Wnt/β-catenin pathway, such as VPA, can potentially be developed as drugs to stimulate hair re-growth

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Fabrication of Molybdenum Alloy with Distributed High-Entropy Alloy Via Pressureless Sintering

In this study, a molybdenum alloy with dispersed high-entropy particles was fabricated using the powder metallurgy method. The high-entropy powder, composed of Nb, Ta, V, W, and Zr elements with a same atomic fraction, was prepared via high-energy ball milling. Using this powder, an ideal core-shell powder, composed of high-entropy powder as core and Mo powder as shell, was synthesized via the milling and reduction processes. These processes enabled the realization of an ideal microstructure with the high-entropy phase uniformly dispersed in the Mo matrix. The sintered body was successfully fabricated via uniaxial compaction followed by pressureless sintering. The sintered body was analyzed by X-ray diffraction and scanning electron microscope, and the high-entropy phase is uniformly dispersed in the Mo matrix

Effects of Adding Niobium and Vanadium to Fe-Based Oxide Dispersion Strengthened Alloy

In this study, the effects of adding niobium and vanadium to Fe-based oxide dispersion strengthened alloys are confirmed. The composition of alloys are Fe-20Cr-1Al-0.5Ti-0.5Y2 O3 and Fe-20Cr-1Al-0.5Ti-0.3V-0.2Nb-0.5Y2 O3. The alloy powders are manufactured by using a planetary mill, and these powders are molded by using a magnetic pulsed compaction. Thereafter, the powders are sintered in a tube furnace to obtain sintered specimens. The added elements exist in the form of a solid solution in the Fe matrix and suppress the grain growth. These results are confirmed via X-ray diffraction and scanning electron microscopy analyses of the phase and microstructure of alloys. In addition, it was confirmed that the addition of elements, improved the hardness property of Fe-based oxide dispersion strengthened alloys

Survey of Promising Technologies for 5G Networks

As an enhancement of cellular networks, the future-generation 5G network can be considered an ultra-high-speed technology. The proposed 5G network might include all types of advanced dominant technologies to provide remarkable services. Consequently, new architectures and service management schemes for different applications of the emerging technologies need to be recommended to solve issues related to data traffic capacity, high data rate, and reliability for ensuring QoS. Cloud computing, Internet of things (IoT), and software-defined networking (SDN) have become some of the core technologies for the 5G network. Cloud-based services provide flexible and efficient solutions for information and communications technology by reducing the cost of investing in and managing information technology infrastructure. In terms of functionality, SDN is a promising architecture that decouples control planes and data planes to support programmability, adaptability, and flexibility in ever-changing network architectures. However, IoT combines cloud computing and SDN to achieve greater productivity for evolving technologies in 5G by facilitating interaction between the physical and human world. The major objective of this study provides a lawless vision on comprehensive works related to enabling technologies for the next generation of mobile systems and networks, mainly focusing on 5G mobile communications