Non-stationary Stochastic Optimization

We consider a non-stationary variant of a sequential stochastic optimization problem, in which the underlying cost functions may change along the horizon. We propose a measure, termed variation budget, that controls the extent of said change, and study how restrictions on this budget impact achievable performance. We identify sharp conditions under which it is possible to achieve long-run-average optimality and more refined performance measures such as rate optimality that fully characterize the complexity of such problems. In doing so, we also establish a strong connection between two rather disparate strands of literature: adversarial online convex optimization; and the more traditional stochastic approximation paradigm (couched in a non-stationary setting). This connection is the key to deriving well performing policies in the latter, by leveraging structure of optimal policies in the former. Finally, tight bounds on the minimax regret allow us to quantify the "price of non-stationarity," which mathematically captures the added complexity embedded in a temporally changing environment versus a stationary one

Social welfare and profit maximization from revealed preferences

Consider the seller's problem of finding optimal prices for her $n$ (divisible) goods when faced with a set of $m$ consumers, given that she can only observe their purchased bundles at posted prices, i.e., revealed preferences. We study both social welfare and profit maximization with revealed preferences. Although social welfare maximization is a seemingly non-convex optimization problem in prices, we show that (i) it can be reduced to a dual convex optimization problem in prices, and (ii) the revealed preferences can be interpreted as supergradients of the concave conjugate of valuation, with which subgradients of the dual function can be computed. We thereby obtain a simple subgradient-based algorithm for strongly concave valuations and convex cost, with query complexity $O(m^2/\epsilon^2)$, where $\epsilon$ is the additive difference between the social welfare induced by our algorithm and the optimum social welfare. We also study social welfare maximization under the online setting, specifically the random permutation model, where consumers arrive one-by-one in a random order. For the case where consumer valuations can be arbitrary continuous functions, we propose a price posting mechanism that achieves an expected social welfare up to an additive factor of $O(\sqrt{mn})$ from the maximum social welfare. Finally, for profit maximization (which may be non-convex in simple cases), we give nearly matching upper and lower bounds on the query complexity for separable valuations and cost (i.e., each good can be treated independently)

MIDA boronates are hydrolysed fast and slow by two different mechanisms

MIDA boronates (N-methylimidodiacetic boronic acid esters) serve as an increasingly general platform for small-molecule construction based on building blocks, largely because of the dramatic and general rate differences with which they are hydrolysed under various basic conditions. Yet the mechanistic underpinnings of these rate differences have remained unclear, which has hindered efforts to address the current limitations of this chemistry. Here we show that there are two distinct mechanisms for this hydrolysis: one is base mediated and the other neutral. The former can proceed more than three orders of magnitude faster than the latter, and involves a rate-limiting attack by a hydroxide at a MIDA carbonyl carbon. The alternative 'neutral' hydrolysis does not require an exogenous acid or base and involves rate-limiting B-N bond cleavage by a small water cluster, (H2O)n. The two mechanisms can operate in parallel, and their relative rates are readily quantified by (18)O incorporation. Whether hydrolysis is 'fast' or 'slow' is dictated by the pH, the water activity and the mass-transfer rates between phases. These findings stand to enable, in a rational way, an even more effective and widespread utilization of MIDA boronates in synthesis

The role for high flow nasal cannula as a respiratory support strategy in adults: a clinical practice guideline

Purpose: High flow nasal cannula (HFNC) is a relatively recent respiratory support technique which delivers high flow, heated and humidified controlled concentration of oxygen via the nasal route. Recently, its use has increased for a variety of clinical indications. To guide clinical practice, we developed evidence-based recommendations regarding use of HFNC in various clinical settings. Methods: We formed a guideline panel composed of clinicians, methodologists and experts in respiratory medicine. Using GRADE, the panel developed recommendations for four actionable questions. Results: The guideline panel made a strong recommendation for HFNC in hypoxemic respiratory failure compared to conventional oxygen therapy (COT) (moderate certainty), a conditional recommendation for HFNC following extubation (moderate certainty), no recommendation regarding HFNC in the peri-intubation period (moderate certainty), and a conditional recommendation for postoperative HFNC in high risk and/or obese patients following cardiac or thoracic surgery (moderate certainty). Conclusions: This clinical practice guideline synthesizes current best-evidence into four recommendations for HFNC use in patients with hypoxemic respiratory failure, following extubation, in the peri-intubation period, and postoperatively for bedside clinicians

Rhaponticum acaule (L) DC essential oil: chemical composition, in vitro antioxidant and enzyme inhibition properties

Background: α-glucosidase is a therapeutic target for diabetes mellitus (DM) and α-glucosidase inhibitors play a vital role in the treatments for the disease. Furthermore, xanthine oxidase (XO) is a key enzyme that catalyzes hypoxanthine and xanthine to uric acid which at high levels can lead to hyperuricemia which is an important cause of gout. Pancreatic lipase (PL) secreted into the duodenum plays a key role in the digestion and absorption of fats. For its importance in lipid digestion, PL represents an attractive target for obesity prevention. Methods: The flowers essential oil of Rhaponticum acaule (L) DC (R. acaule) was characterized using gas chromatography-mass spectrometry (GC-MS). The antioxidant activities of R. acaule essential oil (RaEO) were also determined using 2,2’-azinobis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS), reducing power, phosphomolybdenum, and DNA nicking assays. The inhibitory power of RaEO against α-glucosidase, xanthine oxidase and pancreatic lipase was evaluated. Enzyme kinetic studies using Michaelis-Menten and the derived Lineweaver-Burk (LB) plots were performed to understand the possible mechanism of inhibition exercised by the components of this essential oil. Results: The result revealed the presence of 26 compounds (97.4%). The main constituents include germacrene D (49.2%), methyl eugenol (8.3%), (E)-β-ionone (6.2%), β-caryophyllene (5.7%), (E,E)-α-farnesene (4.2%), bicyclogermacrene (4.1%) and (Z)-α-bisabolene (3.7%). The kinetic inhibition study showed that the essential oil demonstrated a strong α-glucosidase inhibiton and it was a mixed inhibitor. On the other hand, our results evidenced that this oil exhibited important xanthine oxidase inhibitory effect, behaving as a non-competitive inhibitor. The essential oil inhibited the turkey pancreatic lipase, with maximum inhibition of 80% achieved at 2 mg/mL. Furthermore, the inhibition of turkey pancreatic lipase by RaEO was an irreversible one. Conclusion: The results revealed that the RaEO is a new promising potential source of antioxidant compounds, endowed with good practical applications for human health. Keywords: α-glucosidase, Antioxidant activity, Chemical composition, Pancreatic lipase inhibition, Rhaponticum acaule essential oil, Xanthine oxidase

A Genome-Wide SNP Scan Reveals Novel Loci for Egg Production and Quality Traits in White Leghorn and Brown-Egg Dwarf Layers

Availability of the complete genome sequence as well as high-density SNP genotyping platforms allows genome-wide association studies (GWAS) in chickens. A high-density SNP array containing 57,636 markers was employed herein to identify associated variants underlying egg production and quality traits within two lines of chickens, i.e., White Leghorn and brown-egg dwarf layers. For each individual, age at first egg (AFE), first egg weight (FEW), and number of eggs (EN) from 21 to 56 weeks of age were recorded, and egg quality traits including egg weight (EW), eggshell weight (ESW), yolk weight (YW), eggshell thickness (EST), eggshell strength (ESS), albumen height(AH) and Haugh unit(HU) were measured at 40 and 60 weeks of age. A total of 385 White Leghorn females and 361 brown-egg dwarf dams were selected to be genotyped. The genome-wide scan revealed 8 SNPs showing genome-wise significant (P<1.51E-06, Bonferroni correction) association with egg production and quality traits under the Fisher's combined probability method. Some significant SNPs are located in known genes including GRB14 and GALNT1 that can impact development and function of ovary, but more are located in genes with unclear functions in layers, and need to be studied further. Many chromosome-wise significant SNPs were also detected in this study and some of them are located in previously reported QTL regions. Most of loci detected in this study are novel and the follow-up replication studies may be needed to further confirm the functional significance for these newly identified SNPs