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BackgroundOn June 23, 2022, the US Food and Drug Administration announced a JUUL ban policy, to ban all vaping and electronic cigarette products sold by Juul Labs. ObjectiveThis study aims to understand public perceptions and discussions of this policy using Twitter (subsequently rebranded as X) data. MethodsUsing the Twitter streaming application programming interface, 17,007 tweets potentially related to the JUUL ban policy were collected between June 22, 2022, and July 25, 2022. Based on 2600 hand-coded tweets, a deep learning model (RoBERTa) was trained to classify all tweets into propolicy, antipolicy, neutral, and irrelevant categories. A deep learning model (M3 model) was used to estimate basic demographics (such as age and gender) of Twitter users. Furthermore, major topics were identified using latent Dirichlet allocation modeling. A logistic regression model was used to examine the association of different Twitter users with their attitudes toward the policy. ResultsAmong 10,480 tweets related to the JUUL ban policy, there were similar proportions of propolicy and antipolicy tweets (n=2777, 26.5% vs n=2666, 25.44%). Major propolicy topics included “JUUL causes youth addition,” “market surge of JUUL,” and “health effects of JUUL.” In contrast, major antipolicy topics included “cigarette should be banned instead of JUUL,” “against the irrational policy,” and “emotional catharsis.” Twitter users older than 29 years were more likely to be propolicy (have a positive attitude toward the JUUL ban policy) than those younger than 29 years. ConclusionsOur study showed that the public showed different responses to the JUUL ban policy, which varies depending on the demographic characteristics of Twitter users. Our findings could provide valuable information to the Food and Drug Administration for future electronic cigarette and other tobacco product regulations.

High levels of intra-specific polymorphism and frequent hybridisation make it difficult to define species and correctly apply their scientific names. Populus L. is a challenging genus with plentiful natural and artificial hybrids. This study is a part of the project ‘Flora of Pan-Himalaya’ and aims to determine the taxonomic identity of P. gonggaensis N. Chao & J.R. He and to find out whether it is of hybrid origin. Whole-genome sequencing data were obtained from 57 samples. The SNP matrix was developed for phylogenetic reconstruction, ABBA-BABA statistics, PCA and ADMIXTURE analysis. The results indicate that P. gonggaensis is a spontaneous hybrid between P. lasiocarpa and P. cathayana. This study points out the importance of SNP data and comprehensive analyses for discovering the potential interspecific hybridisation and clarifies the usage of the name. In addition, the lectotype of P. gonggaensis was designated.

BackgroundOpen-system electronic cigarette (EC) product features, such as battery capacity, maximum output wattage, and so forth, are major components that drive product costs and may influence use patterns. Moreover, continued innovation and monitoring of product features and prices will provide critical information for designing appropriate taxation policies and product regulations. ObjectiveThis study will examine how product features are associated with the prices of devices sold in web-based vape shops. MethodsWe draw samples from 5 popular, US-based, web-based vape shops from April to August 2022 to examine starter kits, device-only products, and e-liquid container–only products. We implemented a linear regression model with a store-fixed effect to examine the association between device attributes and prices. ResultsEC starter kits or devices vary significantly by type, with mod prices being much higher than pod and vape pen prices. The prices of mod starter kits were even lower than those of mod devices, suggesting that mod starter kits are discounted in web-based vape shops. The price of mod kits, mod device–only products, and pod kits increased as the battery capacity and output wattage increased. For vape pens, the price was positively associated with the volume size of the e-liquid container. On the other hand, the price of pod kits was positively associated with the number of containers. ConclusionsA unit-based specific tax, therefore, will impose a higher tax burden on lower-priced devices such as vape pens or pod systems and a lower tax burden on mod devices. A volume- or capacity-based specific tax on devices will impose a higher tax burden on vape pens with a larger container size. Meanwhile, ad valorem taxes pegged to wholesale or retail prices would apply evenly across device types, meaning those with advanced features such as higher battery capacities and output wattage would face higher rates. Therefore, policy makers could manipulate tax rates by device type to discourage the use of certain device products.

Abstract The modern theory of quantized polarization has recently extended from 1D dipole moment to multipole moment, leading to the development from conventional topological insulators (TIs) to higher‐order TIs, i.e., from the bulk polarization as primary topological index, to the fractional corner charge as secondary topological index. The authors here extend this development by theoretically discovering a higher‐order end TI (HOETI) in a real projective lattice and experimentally verifying the prediction using topolectric circuits. A HOETI realizes a dipole‐symmetry‐protected phase in a higher‐dimensional space (conventionally in one dimension), which manifests as 0D topologically protected end states and a fractional end charge. The discovered bulk‐end correspondence reveals that the fractional end charge, which is proportional to the bulk topological invariant, can serve as a generic bulk probe of higher‐order topology. The authors identify the HOETI experimentally by the presence of localized end states and a fractional end charge. The results demonstrate the existence of fractional charges in non‐Euclidean manifolds and open new avenues for understanding the interplay between topological obstructions in real and momentum space.

BackgroundPrior studies have demonstrated that the e-cigarette market contains a large number of brands. Identifying these existing e-cigarette brands is a key element of market surveillance, which will further assist in policy making and compliance checks. ObjectiveTo facilitate the surveillance of the diverse product landscape in the e-cigarette market, we constructed a semantic database of e-cigarette brands that have appeared in the US market as of 2020-2022. MethodsIn order to build the brand database, we searched and compiled e-cigarette brands from a comprehensive list of retail channels and sources, including (1) e-liquid and disposable brands sold in web-based stores, (2) e-cigarette brands sold in brick-and-mortar stores and collected by the Nielsen Retail Scanner Data, (3) e-cigarette brands compiled by Wikipedia, (4) self-reported e-cigarette brands from the 2020 International Tobacco Control Four-Country Smoking and Vaping (ITC 4CV) US survey, and (5) e-cigarette brands on Twitter. We also estimated the top 5 e-cigarette brands by sales volume in brick-and-mortar stores, by the frequency and variety of offerings in web-based shops, and by the frequency of self-reported brands from the 2020 ITC 4CV US survey. ResultsAs of 2020-2022, a total of 912 e-cigarette brands have been sold by various retail channels. During 2020-2022, the top 5 brands are JUUL, vuse, njoy, blu, and logic in brick-and-mortar stores; blu, king, monster, twist, and air factory for e-liquids in web-based stores; hyde, pod mesh, suorin, vaporlax, and xtra for disposables sold in web-based stores; and smok, aspire, vaporesso, innokin, and eleaf based on self-reported survey data. ConclusionsAs the US Food and Drug Administration enforces the premarket tobacco market authorization, many e-cigarette brands may become illegal in the US market. In this context, how e-cigarette brands evolve and consolidate in different retail channels will be critical for understanding the regulatory impacts on product availability. Our semantic database of e-cigarette brands can serve as a useful tool to monitor product and marketplace development, conduct compliance checks, assess manufacturers’ marketing behaviors, and identify regulatory impacts.

BackgroundFrom 2016 to 2021, the volume of peer-reviewed publications related to tobacco has experienced a significant increase. This presents a considerable challenge in efficiently summarizing, synthesizing, and disseminating research findings, especially when it comes to addressing specific target populations, such as the LGBTQ+ (lesbian, gay, bisexual, transgender, queer, intersex, asexual, Two Spirit, and other persons who identify as part of this community) populations. ObjectiveIn order to expedite evidence synthesis and research gap discoveries, this pilot study has the following three aims: (1) to compile a specialized semantic database for tobacco policy research to extract information from journal article abstracts, (2) to develop natural language processing (NLP) algorithms that comprehend the literature on nicotine and tobacco product use among sexual and gender diverse populations, and (3) to compare the discoveries of the NLP algorithms with an ongoing systematic review of tobacco policy research among LGBTQ+ populations. MethodsWe built a tobacco research domain–specific semantic database using data from 2993 paper abstracts from 4 leading tobacco-specific journals, with enrichment from other publicly available sources. We then trained an NLP model to extract named entities after learning patterns and relationships between words and their context in text, which further enriched the semantic database. Using this iterative process, we extracted and assessed studies relevant to LGBTQ+ tobacco control issues, further comparing our findings with an ongoing systematic review that also focuses on evidence synthesis for this demographic group. ResultsIn total, 33 studies were identified as relevant to sexual and gender diverse individuals’ nicotine and tobacco product use. Consistent with the ongoing systematic review, the NLP results showed that there is a scarcity of studies assessing policy impact on this demographic using causal inference methods. In addition, the literature is dominated by US data. We found that the product drawing the most attention in the body of existing research is cigarettes or cigarette smoking and that the number of studies of various age groups is almost evenly distributed between youth or young adults and adults, consistent with the research needs identified by the US health agencies. ConclusionsOur pilot study serves as a compelling demonstration of the capabilities of NLP tools in expediting the processes of evidence synthesis and the identification of research gaps. While future research is needed to statistically test the NLP tool’s performance, there is potential for NLP tools to fundamentally transform the approach to evidence synthesis.

OBJECTIVES/GOALS: Cannabis laws may impact cannabis and tobacco use, given high prevalence of co-use of these products among young adults (YAs). The objective of this study was to examine trends in YA any cannabis, blunt, cigarette, and cigar use from 2002-2018 in states that passed adult and medical use (AMU) or medical use only (MUO) cannabis laws during that time (N=16). METHODS/STUDY POPULATION: Using data from the National Survey on Drug Use and Health, we conducted a segmented regression analysis to calculate absolute percent change (APC) in past 30-day cannabis and tobacco use between time points. The National Cancer Institute’s Joinpoint software was used to also estimate points of inflection (Joinpoints) when the slope of a trend significantly (p

Synthetic nicotine (relative to tobacco-derived, or “natural” nicotine) is an emerging feature of e-cigarettes including e-liquids in the online marketplace. This study investigated a total of 11,161 unique nicotine e-liquids sold in online stores in the US during 2021, using keyword matching approach to identify the feature of synthetic nicotine based on product description texts. We showed that in 2021, 2.13% of nicotine-containing e-liquids in our sample were marketed as synthetic nicotine e-liquids. About a quarter of the synthetic nicotine e-liquids that we identified were salt-based; the nicotine strength varied; and those synthetic nicotine e-liquids had a variety of flavor profiles. Synthetic nicotine containing e-cigarettes are likely to remain in the market and manufacturers might market those products as “tobacco-free,” to attract consumers who this feature as healthier or less addictive. It is important to monitor synthetic nicotine in the e-cigarette marketplace and assess how this feature influences consumer behaviors.

Given the increase in electronic cigarette use during the past decade, the objectives of this study are to obtain comprehensive product-level information from online vape shops, which are one of the most common outlets for e-cigarette users to purchase vaping products, especially e-liquid products, and to examine the appeal of various e-liquid product attributes to consumers. We used web scraping and estimation of generalized estimating equation (GEE) models to obtain and analyze data from five popular online vape shops that sell nationwide across the US. The outcome measures are e-liquid pricing for the following e-liquid product attributes: nicotine concentration (in mg/ml), nicotine form (nicotine-free, freebase, or salt), vegetable glycerin/propylene glycol (VG/PG) ratio, and a variety of flavors. We find that the pricing for freebase nicotine and nicotine salt products are 1% (p

Abstract Topological phases of matter are conventionally characterized by the bulk‐boundary correspondence in Hermitian systems. The topological invariant of the bulk in d dimensions corresponds to the number of (d − 1)‐dimensional boundary states. By extension, higher‐order topological insulators reveal a bulk‐edge‐corner correspondence, such that nth order topological phases feature (d − n)‐dimensional boundary states. The advent of non‐Hermitian topological systems sheds new light on the emergence of the non‐Hermitian skin effect (NHSE) with an extensive number of boundary modes under open boundary conditions. Still, the higher‐order NHSE remains largely unexplored, particularly in the experiment. An unsupervised approach—physics‐graph‐informed machine learning (PGIML)—to enhance the data mining ability of machine learning with limited domain knowledge is introduced. Through PGIML, the second‐order NHSE in a 2D non‐Hermitian topoelectrical circuit is experimentally demonstrated. The admittance spectra of the circuit exhibit an extensive number of corner skin modes and extreme sensitivity of the spectral flow to the boundary conditions. The violation of the conventional bulk‐boundary correspondence in the second‐order NHSE implies that modification of the topological band theory is inevitable in higher dimensional non‐Hermitian systems.

Bretschneidera sinensis is an endangered woody species found in East and South China. Comprehensive intraspecies chloroplast genome studies have demonstrated novel genetic resources to assess the genetic variation and diversity of this species. Using genome skimming method, we assembled the whole chloroplast genome of 12 genotypes of B. sinensis from different geographical locations, covering most wild populations. The B. sinensis chloroplast genome size ranged from 158,959 to 159,045 base pairs (bp) and displayed a typical circular quadripartite structure. Comparative analyses of 12 B. sinensis chloroplast genome revealed 33 polymorphic simple sequence repeats (SSRs), 105 polymorphic single nucleotide polymorphisms (SNPs), and 55 indels. Phylogenetic analysis showed that the 12 genotypes were grouped into 2 branches, which is consistent with the geographical distribution (Eastern clade and Western clade). Divergence time estimates showed that the two clades were divergent from 0.6 Ma in the late Pleistocene. Ex situ conservation is essential for this species. In this study, we identified SNPs, indels, and microsatellites of B. sinensis by comparative analyses of chloroplast genomes and determined genetic variation between populations using these genomic markers. Chloroplast genomic resources are also important for further domestication, population genetic, and phylogenetic analysis, possibly in combination with molecular markers of mitochondrial and/or nuclear genomes.

Populus not only has significant economic and ecological values, but also serves as a model tree that is widely used in the basic research of tree growth, physiology, and genetics. However, high levels of morphological variation and extensive interspecific hybridization of Populus pose an obstacle for taxonomy, and also to the understanding of phylogenetic interspecific relationships and biogeographical history. In this study, a total of 103 accessions representing almost all the wild species of Populus were collected and whole-genome re-sequenced to examine the phylogenetic relationships and biogeography history. On the basis of 12,916,788 nuclear single nucleotide polymorphisms (SNPs), we reconstructed backbone phylogenies using concatenate and coalescent methods, we highly disentangled the species relationships of Populus, and several problematic taxa were treated as species complexes. Furthermore, the phylogeny of the chloroplast genome showed extensive discordance with the trees from the nuclear genome data, and due to extensive chloroplast capture and hybridization of Populus species, plastomes could not accurately evaluate interspecies relationships. Ancient gene flow between clades and some hybridization events were also identified by ABBA–BABA analysis. The reconstruction of chronogram and ancestral distributions suggested that North America was the original region of this genus, and subsequent long dispersal and migration across land bridges were contributed to the modern range of Populus. The diversification of Populus mainly occurred in East Asia in recent 15 Ma, possibly promoted by the uplift of the Tibetan Plateau. This study provided comprehensive evidence on the phylogeny of Populus and proposed a four-subgeneric classification and a new status, subgenus Abaso. Meanwhile, ancestral distribution reconstruction with nuclear data advanced the understanding of the biogeographic history of Populus.

Abstract This review investigates the recent developments of heterogeneous objects modeling in additive manufacturing (AM), as well as general problems and widespread solutions to the modeling methods of heterogeneous objects. Prevalent heterogeneous object representations are generally categorized based on the different expression or data structure employed therein, and the state-of-the-art of process planning procedures for AM is reviewed via different vigorous solutions for part orientation, slicing methods, and path planning strategies. Finally, some evident problems and possible future directions of investigation are discussed.

The chloroplast genome sequences of Dianyuea turbinata (H.J. Dong & H. Peng) C. Shang, S. Liao & Z.X. Zhang, endemic to Yingjiang County, Yunnan Province, China, was presented in this study (Dong and Peng ; Shang et al. ). The chloroplast genome sequence was 154,045 bp in length, with a large single-copy (LSC) region of 82,247 bp, a small single-copy (SSC) region of 16,522 bp, separated by two inverted repeat (IR) regions of 27,638 bp each. The total GC content was 37.1%. The complete plastome sequence contained 134 genes, including 89 protein-coding, 37 tRNA and 8 rRNA genes. The phylogenetic status of genus Dianyuea has been clarified through a Maximum-likelihood tree based on the chloroplast genome of 17 species.

Macrophages have an affinity to developing tumors and have been shown to play a role in tumor combat and immune surveillance. However, the exact mechanism by which macrophages participate in the anti-tumor immune response remains unclear. Hence, the current study aimed to identify the effect of macrophages on gastric cancer (GC) cells via exosomes. Paired cancerous, tumor-adjacent, and non-cancerous stomach tissues were initially from 68 GC patients. T cells were isolated from peripheral blood mononuclear cells (PBMCs) obtained from both the GC patients as well as the healthy donors. Next, the exosomes were isolated from LPS and IFN-γ-induced PBMCs (M1 macrophages) and co-cultured with human GC cells. Another co-culture system comprised of CD3+ T cells and exosomes-treated GC cells was then performed. BALB/c mice and NOD/SCID nude mice were prepared for effects of exosomal miR-16-5p on tumor growth and anti-tumor immune response in GC in vivo. A relationship between M1 macrophages and the poor survival of GC patients was identified, while they secreted exosomes to inhibit GC development and activate a T cell-dependent immune response. Our results revealed that miR-16-5p was transferred intercellularly from M1 macrophages to GC cells via exosomes and targeted PD-L1. M1 macrophage-derived exosomes containing miR-16-5p were found to trigger a T cell immune response which inhibited tumor formation both in vitro and in vivo by decreasing the expression of PD-L1. Taken together, the key findings of the current study suggest that M1 macrophage-derived exosomes carrying miR-16-5p exert an inhibitory effect on GC progression through activation of T cell immune response via PD-L1. Our study highlights the promise of M1 macrophages as a potential cell-based therapy for GC treatment by increasing miR-16-5p in exosomes.

Injection molding is widely used in industries to produce polymeric products. At present, compound NURBS surfaces are commonly used to represent freeform surfaces in mold models. This work uses T-spline surface with extraordinary control points instead of NURBS to represent freeform surfaces in mold models. Compared with NURBS, T-splines’ higher-order continuity facilitates the mold quality control especially at the patch boundary. And, its patch layout information can be utilized for tool path planning. We propose an algorithm to determine the patch processing order and generate nonretraction tool path for T-spline surface models. The tool paths are generated patch by patch using isoparametric strategy. Actual machining and injection molding experiments have been conducted. The result shows the feasibility of the proposed method, and the final product is in good quality.

Abstract As a matter of fact, most natural structures are complex topology structures with intricate holes or irregular surface morphology. These structures can be used as lightweight infill, porous scaffold, energy absorber or micro-reactor. With the rapid advancement of 3D printing, the complex topology structures can now be efficiently and accurately fabricated by stacking layered materials. The novel manufacturing technology and application background put forward new demands and challenges to the current design methodologies of complex topology structures. In this paper, a brief review on the development of recent complex topology structure design methods was provided; meanwhile, the limitations of existing methods and future work are also discussed in the end.

The stochastic and intermittent nature of renewable energy resources (RERs) poses great challenges to the energy scheduling of microgrids. The hybrid energy storage system (HESS), such as a combination of the battery (BA) and ultracapacitor, is considered as an effective way to cope with such challenges. In this paper, a hierarchical energy scheduling framework is proposed for the microgrid with HESSs to optimize the operation under the uncertainty of RERs and loads. The framework consists of two stages of scheduling: hour-ahead scheduling and real-time scheduling. In hour-ahead scheduling, a deterministic optimization model is formulated to minimize the operation cost of microgrids, and to guarantee the operation safety. Subsequently, a decomposition-based method is presented to solve the proposed model. In real-time scheduling, a control strategy of HESSs is developed to accommodate the imbalanced power mainly due to the uncertainty of RERs and loads, while extending the lifetime of BAs. The methodology is tested on a seven-bus microgrid system. Simulation results validate the effectiveness of the formulated model and the developed strategy.

Background and Objectives: while existing research has demonstrated a positive association between exposure to point-of-sale (POS) tobacco advertising and youth smoking, there is limited evidence on the relationship between POS advertising restrictions and experimental smoking among youth. This study aims to fill this research gap by analyzing the association between POS advertising bans and youths' experimental smoking. Methods: Global Youth Tobacco Surveys from 130 countries during 2007-2011 were linked to the WHO “MPOWER” tobacco control policy measures to analyze the association between POS advertising bans (a dichotomous measure of the existence of such bans) and experimental smoking using weighted logistic regressions. All analyses were clustered at the country level and controlled for age, parents' smoking status, GDP per capita, and country-level tobacco control scores in monitoring tobacco use, protecting people from smoke, offering help to quit, warning about the dangers of tobacco, enforcing promotion/advertising bans, and raising taxes on tobacco. Results: The results suggest that a POS advertising ban is significantly associated with reduced experimental smoking among youth (OR = 0.63, p < 0.01), and that this association is seen for both genders (boys OR = 0.74, p < 0.1; girls OR = 0.52, p < 0.001). Conclusions: POS advertising bans are significantly associated with reduced experimental smoking among youth. Adopting POS advertising bans has the potential to reduce tobacco use among their youth in countries currently without such bans.

Background Since Iceland became the first country to impose a ban on point-of-sale (POS) displays in 2001, there have been 20 countries in total in the world implementing POS display bans as of 2016. Methods This study examined the effect that POS display bans have on smoking prevalence to provide evidence on their effectiveness in tobacco control.The data were sourced from Euromonitor International and WHO MPOWER package during 2007-2014 from 77 countries worldwide. Generalized Linear Model with country and year fixed effects was implemented to analyze the effect of POS display bans on smoking prevalence. Results Having a POS display ban decreased overall adult smoking, male smoking, and female smoking by about 7%, 6%, and 9%, respectively. Conclusions Having a POS display ban is likely to reduce smoking prevalence. Adopting such policies has the potential to generate public health benefits. Countries currently without a POS display ban are encouraged to implement such policies to curb the smoking epidemic.

Recent tobacco taxation research suggests that excise tax structure plays an important role in the effectiveness of increasing taxes in reducing consumption. However, evidence on excise tax structures of alcoholic beverages is scarce. We linked price variability measures for beer, wine, and liquor in the US derived using Economist Intelligence Unit city data from 2003 to 2016 with state-level excise tax structures from the Alcohol Policy Information System. Ordinary least squares (OLS) regressions were performed to assess the associations between excise tax structures and price variability, for beer, wine, and liquor (spirits), respectively. Results suggest that, compared with a specific excise beer tax structure based on volumes, a mixed structure with both specific and ad valorem components was associated with 38% (p≤0.01) greater beer price variability. In addition, a mixed excise tax structure for liquor was associated with 60-77% (p≤0.01) greater liquor price variability. However, these associations do not imply a causal link between tax structures and price variability. In summary, a mixed excise tax structure is associated with greater variability in beer and liquor prices, an indicator for tax avoidance opportunities. Future research is needed to identify the causal impact of tax structures on price variability.

ObjectivesThis study calculates cigarette affordability for 78 countries worldwide from 2001 to 2014 using the Relative Income Price (RIP) ratio defined as the percentage of per capita GDP required to purchase 100 packs of cigarettes using the lowest price from Economist Intelligence Unit (EIU) database, examine the association between cigarette affordability and cigarette consumption, and calculate the affordability elasticity of demand.Design and methodsRIP (2001-2014) was calculated for 16 low-income economies, 19 lower middle-income economies, 13 upper middle-income economies, and 30 high-income economies. Ordinary least square regressions were used to analyze the association between cigarette affordability and consumption.ResultsPer capita consumption continued to rise in low-income countries and decreased slightly in lower middle-income countries as the RIP of cigarette consistently declined in low- and lower middle-income economies from 2001 to 2014. The real cigarette prices continued to decline in low- and lower middle-income countries and continued to rise in upper middle- and high-income countries. Though cigarettes were more expensive in HICs than were in LMICs, cigarettes were more affordable in HICs than were in LMICs. The regression results show a 10% increase in the RIP of cigarettes led to a 2% decrease in per capita consumption. The affordability elasticity of demand differed significantly between HICs and LMICs. However, the effect of cigarette affordability on consumption has not changed over time.ConclusionsTo control the smoking epidemic, low- and lower middle-income countries should further increase cigarette prices. The rate of price increase should exceed the rate of economic growth and outpace the inflation rate to make cigarettes less affordable and thereby reducing tobacco use.

BACKGROUND:One of the major obstacles to the full implementation of the World Health Organization (WHO) Framework Convention of Tobacco Control (FCTC) tobacco control measures is the lack of sustainable financing resources. GOAL:To update and simulate country-specific indicators that are highly relevant to the costs and financial resources of the treaty policy implementation. We also developed an Excel tool for simulation and assessed the aggregated-level indicators by the 2016 World Bank income groups. APPROACHES:Using mostly 2016 data or 2014-15 data if 2016 one are not available, we updated five indicators relevant to the treaty implementation, which are the gap between current and desirable policy implementation, cigarette affordability, the costs of implementing best- buy tobacco control policies, the number of smoking-attributable deaths, and the simulated tax revenue resulting from a $1 tax increase. We also aggregated indicators and simulation results by the World Bank income groups, encompassing the five indicators and the reduction in smoking and in attributable deaths due to a hypothetical 1I$ tax increase. Finally, the policy implementation cost was compared with tax revenue and revenue increases. FINDINGS:As of 2016, smoking remains one of the leading causes of premature deaths worldwide while the implementation of best-buy tobacco control policies was below the recommended levels. Meanwhile, there was room to further increase cigarette taxes and prices, as cigarettes remained affordable in many countries. The total costs of implementing best-buy policies in the next 15 years merely account for 8.3% of the 2016 excise tax revenue, indicating that a small proportion of annual tax revenue could fund the implementation of tobacco control policies recommended by the WHO FCTC. CONCLUSIONS:Increasing taxes could have a multiplier impact on curbing tobacco use through aiding the implementation of the WHO FCTC.

Due to the compressibility of air, non-linear characteristics, and parameter uncertainties of pneumatic elements, the position control of a pneumatic cylinder or parallel platform is still very difficult while comparing with the systems driven by electric or hydraulic power. In this article, based on the basic dynamic model and descriptions of thermal processes, a controller integrated with online parameter estimation is proposed to improve the performance of a pneumatic cylinder controlled by a proportional valve. The trajectory tracking error is significantly decreased by applying this method. Moreover, the algorithm is expanded to the problem of posture trajectory tracking for the three-revolute prismatic spherical pneumatic parallel manipulator. Lyapunov’s method is used to give the proof of stability of the controller. Using NI-CompactRio, NI-PXI, and Veristand platform as the realistic controller hardware and data interactive environment, the adaptive robust control algorithm is applied to the physical system successfully. Experimental results and data analysis showed that the posture error of the platform could be about 0.5%–0.7% of the desired trajectory amplitude. By integrating this method to the mechatronic system, the pneumatic servo solutions can be much more competitive in the industrial market of position and posture control.

BackgroundIn the United States (U.S), cannabis policies have been increasingly liberalized whereas tobacco policies have been increasingly stringent. Given the high prevalence of cannabis and tobacco dual use, there are concerns that a policy regulating one substance may unintendedly influence the other. This study examined the responsiveness of the demand for cannabis joints and cigarettes when price varied.MethodsThe study included 338 adult participants (21+) who used both cannabis and tobacco and lived in one of the U.S. states with recreational cannabis legalized by the time of interview in 2019. They completed hypothetical purchase tasks to indicate the quantity desired of cannabis joints and cigarette packs 1) when only one substance was available with escalating prices and 2) when both substances were concurrently available with escalating prices of cannabis joints and a fixed price of cigarette packs. We estimated 1) the own-price elasticity of demand for each substance using nonlinear exponential demand model, and 2) the cross-price elasticity of demand at aggregate level using nonlinear exponential demand model and at individual level using log-linear demand model.ResultsThe estimates for the rate of change of own-price elasticity (α) were 0.0011 (SE = 0.000039, p  0.05) suggest an independent relationship between the two substances. At individual level, 78.70% of the participants treated the two substances as independent, 17.46% as complements, and 3.85% as substitutes.ConclusionsFor most adults who used both cannabis and tobacco in the U.S., cannabis joints and cigarettes had an independent relationship. Policies regulating the price of cannabis may not have large unintended consequences on cigarette use.