Herbal medicine IMOD suppresses LPS-induced production of proinflammatory cytokines in human dendritic cells

Traditional medicines that stimulate or modulate the immune system can be used as innovative approaches to treat immunological diseases. The herbal medicine IMOD has been shown to strongly modulate immune responses in several animal studies as well as in clinical trials. However, little is known about the mechanisms of IMOD to modulate immunity. Here we have investigated whether IMOD modulates the immunological function of human dendritic cells (DCs). IMOD alone did not induce DC maturation nor production of cytokines. Notably, IMOD decreased the production of pro-inflammatory cytokines IL-6, IL-12 p70 and TNFα by LPS-activated DCs at both mRNA and protein levels in a dose dependent manner. In contrast, treatment with IMOD did not affect LPS induced-production of the anti-inflammatory cytokine IL-10. Furthermore, IMOD inhibited T cell activation/proliferation by LPS-treated DCs and skewed T-cells responses towards the T helper type 2 polarization. These data strongly indicate that IMOD has a potent immunomodulatory ability that affects TLR signaling and thereby modulates DC function. Insight into the immunomodulatory effect of herbal medicine IMOD may provide innovative strategies to affect the immune system and to help combat various disease

Is Topical Zinc Effective in the Treatment of Melasma? A Double-Blind Randomized Comparative Study

Background and ObjectivesZinc plays a role in skin health, and preliminary data have shown its beneficial effects for melasma. We compared the effect of topical zinc with that of hydroquinone as the standard treatment on severity of melasma. Patients and MethodsNinety-three women with melasma were randomized to receive zinc sulfate 10% or hydroquinone 4% solutions once daily for 2months. They were followed for an additional 3months while using sunscreen. The severity of melasma was assessed at baseline and at 2 and 5months using the Melasma Area and Severity Index (MASI). ResultsEighty-two patients completed the study. The MASI score fell significantly in both groups, but a greater decrease was seen in those who received hydroquinone (43.515.5% vs 18.6 +/- 20.8%, p<.001). Postinflammatory pigmentation occurred in 5.2% of the zinc group and irritation in 30.9% of the hydroquinone group. ConclusionTopical zinc therapy is not highly effective in reducing the severity of melasma, but further trials are needed to determine whether adding zinc to current topical treatments could improve treatment response

Coordinated Sensor-Based Area Coverage and Cooperative Localization of a Heterogeneous Fleet of Autonomous Surface Vessels (ASVs)

Sensor coverage with fleets of robots is a complex task requiring solutions to localization, communication, navigation and basic sensor coverage. Sensor coverage of large areas is a problem that occurs in a variety of different environments from terrestrial to aerial to aquatic. In this thesis we consider the aquatic version of the problem. Given a known aquatic environment and collection of aquatic surface vehicles with known kinematic and dynamic constraints, how can a fleet of vehicles be deployed to provide sensor coverage of the surface of the body of water? Rather than considering this problem in general, in this work we consider the problem given a specific fleet consisting of one very well equipped robot aided by a number of smaller, less well equipped devices that must operate in close proximity to the main robot. A boustrophedon decomposition algorithm is developed that incorporates the motion, sensing and communication constraints imposed by the autonomous fleet. Solving the coverage problem leads to a localization/communication problem. A critical problem for a group of autonomous vehicles is ensuring that the collection operates within a common reference frame. Here we consider the problem of localizing a heterogenous collection of aquatic surface vessels within a global reference frame. We assume that one vessel -- the mother robot -- has access to global position data of high accuracy, while the other vessels -- the child robots -- utilize limited onboard sensors and sophisticated sensors on board the mother robot to localize themselves. This thesis provides details of the design of the elements of the heterogeneous fleet including the sensors and sensing algorithms along with the communication strategy used to localize all elements of the fleet within a global reference frame. Details of the robot platforms to be used in implementing a solution are also described. Simulation of the approach is used to demonstrate the effectiveness of the algorithm, and the algorithm and its components are evaluated using a fleet of ASVs

Semi-Deterministic Single Interaction MIMO Channel Model

In this chapter a mathematical model to characterize wireless communication channel is developed which falls into semi-deterministic channel models. This model is based on electromagnetic scattering and reflecting and fundamental physics however it has been kept simple through appropriate assumptions

Uncertainty, Investment and Firm Dynamics

Chapter 1: Unpacking Economic Uncertainty: Measuring the Firm, Sector and Aggregate Components Existing measures of uncertainty are typically estimated in a preliminary step using market data (Bloom, Bond and Van Reenen, 2007), media sources (Baker, Bloom and Davis, 2016), or macroeconomic indicators (Jurado, Ludvigson and Ng, 2015), and then treated as if they were observable data series (Carriero, Clark and Marcellino, 2018). These measures often fail to capture the complexity and heterogeneity of firms’ salient uncertainty. While efforts have been made to create disaggregated uncertainty measures, much of the economic literature on the impact of uncertainty on firms’ decisions has focused on aggregated uncertainty, assuming a uniform uncertainty process across firms. To address this issue, this chapter raises two questions: “How is firm uncertainty decomposed into firm, sector, and aggregate sources? To what extent does heterogeneity of uncertainty exist across firms?” This chapter introduces a novel method to measure firms’ uncertainty, proxied by their sales volatility, and decomposes a multi-layered system of indices: commonalities among all firms (potentially driven by macro-level developments such as economic policy and aggregate demand shocks), sectoral commonalities (such as supply chain disruptions, technological shocks, and input price variations), and firm-specific factors. The approach used to measure uncertainty involves disaggregated firm-level data to construct different measures of uncertainty at aggregate, sectoral, and firm levels by decomposing the volatility of firms’ sales, termed “Overall Uncertainty” (OU). The chapter also contributes to the literature by introducing the concept of uncertainty heterogeneity and emphasises the differences in firms’ perceptions of uncertainty and its origins, as well as the varying impacts of uncertainty on different firms and sectors. The chapter validates this approach by demonstrating that the computed aggregate-level uncertainty for the U.S. economy aligns with existing measures of macroeconomic uncertainty, such as those by Baker, Bloom and Davis (2016) and Jurado, Ludvigson and Ng (2015). Using data from the Quarterly Compustat database, our results reveal significant heterogeneity in uncertainty across firms based on their characteristics and sectors. For example, larger firms tend to experience lower uncertainty than smaller firms. Moreover, high uncertainty episodes are more pronounced in the manufacturing sector compared to the services and mining sectors, corroborating findings on the sectoral heterogeneity of uncertainty by Born and Pfeifer (2021) and Parast and Subramanian (2021). These findings have significant implications for policymakers, particularly in understanding the vulnerability of smaller firms to macroeconomic conditions. The results underscore the need for fiscal and monetary policies that consider the differential impacts on firms’ uncertainty, which in turn affects their performance, investment decisions, and hiring choices. This understanding can empower policymakers to make informed decisions, aligning with empirical evidence on the stagnation of U.S. investments and industrial production over recent decades, especially in the manufacturing sector.Chapter 2: Firms’ Investment &amp; Capacity Utilisation: The Role of Uncertainty and Financial Constraints The second chapter in this thesis examines the role of capacity utilisation in firms’ investments. Previous research has identified a trigger point in capacity utilisation at which firms typically invest and expand (Brown and Mawson, 2013; Coad et al., 2021). In essence, once firms reach a “capacity target”, some of them invest in new production capacity to prepare for periods of high demand. However, the previous efforts in the literature studying the relationship between capacity utilisation and investments of growth have not studied the role of uncertainty and financial constraints. Our empirical analysis uses the INVIND survey data from the Bank of Italy for the period 2002- 2023 and documents a structural break in the capacity utilisation of Italian manufacturing firms following the Great Recession and the European debt crisis. This shift is accompanied by a simultaneous decline in investments as documented previously by Bond, Rodano and Serrano-Velarde (2015); Busetti, Giordano and Zevi (2015), alongside heightened uncertainty and tighter financial constraints. Consequently, low capacity utilisation, coupled with high uncertainty and constrained financing, may have contributed to the infrequent expansion of Italian firms during the last two decades. We pose the following research questions: “Does the probability of investing in production capacity depend on firms’ capacity targets and the extent to which they exceed their capacity utilisation target?” and “How do financial constraints and demand uncertainty influence the relationship between capacity utilisation and investment?” The empirical analysis in this chapter includes applying an instrument variable analysis to solve for the endogeneity between financial constraints and investments. Additionally, by constructing investment spikes following Grazzi, Jacoby and Treibich (2016); Arata (2019), we isolate the expansion investments, which represent the firm growth from other types of investments, such as replacement for wear and tear. The impact of capacity utilisation on investment is measured via the difference between the observed capacity and the target, which is measured as the sectoral average conditional on the business cycle. Furthermore, we construct a dummy for observations with capacity utilisation higher than the target and call these observations interchangeably at the growth window and operating overcapacity. By using this dummy, we document the non-linearity in the relationship between capacity utilisation and investment. Briefly, the extent of operations above the target is less important than reaching the target. Our findings confirm that firms with high capacity utilisation are more inclined to invest compared to those with lower capacity utilisation. This chapter sheds light on the heterogeneous impact of uncertainty on firms. The results suggest that firms operating at high capacity are not affected by uncertainty, whereas those at lower capacity levels exhibit increased investments during uncertain times. This chapter contributes to the literature on firm-level heterogeneity by introducing a new dimension based on capacity utilisation and uncertainty. The results have significant implications for industrial policy, suggesting that identifying and understanding these trigger points can aid in designing cost-effective strategies to encourage investment during critical growth periods.Chapter 3: Data, Uncertainty and R&amp;D Investments The third chapter explores the effect of higher investments in data on firms’ Research and Development (R&amp;D) activities. We hypothesise that investing in data results in lower uncertainty, thereby motivating firms to engage more in innovative activities like R&amp;D. It then moves on to studying the multiplier effect of these investments on improving firms’ productivity to establish the complementarity among these investments. Therefore, this chapter hypothesises that investing more in data leads to more innovation via a reduction in uncertainty of the firm. Furthermore, the chapter examines whether the combination of these two investments increases firms’ labour productivity through more data-driven decision-making that leads to more efficiency. Ultimately, the chapter poses the questions: “Does investing in data affect R&amp;D investments?” and “Is there a cumulative effect on productivity from sole investments in data, sole investments in R&amp;D, and joint investments in data and R&amp;D? Is there a multiplier effect?” Investing in data results in lower uncertainty, which reduces marginal production costs. Lower costs yield larger market concentration and firm size, which allows the firm to boost its R&amp;D investments (Eeckhout and Veldkamp, 2022; Brynjolfsson, Jin and Wang, 2023). Using an instrumental variable (IV) approach with data from the INVIND survey of the Bank of Italy between 2002-2023, this chapter identifies a causal impact of data investments on R&amp;D. The econometric framework in this chapter uses the introduction of the General Data Protection Regulation (GDPR) as an instrument for data to address the endogeneity between data and R&amp;D. By treating data and analytics as information, the study demonstrates that reducing uncertainty is a primary benefit of these investments, which can facilitate firms’ innovative activities. The results show a causal relationship between investments in data and software and the tendency to invest in innovative activities, highlighting the potential for a virtuous cycle between investments in intangible assets and innovation. Importantly and to measure firms have gained efficiency-related gains, we test whether the combination of these investments contributes to higher labour productivity in both short and long terms, building on the previous literature on the role of intangibles in improving productivity, such as Corrado et al. (2021); Añón Higón, Gómez and Vargas (2017); Goodridge and Haskel (2023). The results in this chapter indeed confirm the conjecture that investing in these intangible assets and their combination positively impacts productivity. Therefore, not only does investing more in data lead to more innovation, but their usage and combination positively affects labour productivity. These findings have important implications for academic research and policy and suggest that data and analytics investments can reduce uncertainty and enhance firm performance, ultimately encouraging a more innovative and productive business environment

The Community Ecology of Herbivore Regulation in an Agroecosystem: Lessons from Complex Systems

AbstractWhether an ecological community is controlled from above or below remains a popular framework that continues generating interesting research questions and takes on especially important meaning in agroecosystems. We describe the regulation from above of three coffee herbivores, a leaf herbivore (the green coffee scale, Coccus viridis), a seed predator (the coffee berry borer, Hypothenemus hampei), and a plant pathogen (the coffee rust disease, caused by Hemelia vastatrix) by various natural enemies, emphasizing the remarkable complexity involved. We emphasize the intersection of this classical question of ecology with the burgeoning field of complex systems, including references to chaos, critical transitions, hysteresis, basin or boundary collision, and spatial self-organization, all aimed at the applied question of pest control in the coffee agroecosystem

Addressing fault tolerance in 4-PAM signaling by using block codes for on/off-chip communication

The AWGN channel is characterized and verified for 4-PAM signaling. Based on that, three fault tolerant on/off-chip communication architectures using block codes alongside 4-PAM modulation have been evaluated. The results display decent improvement in BER performance while keeping complexity as low as possible

Insights from excrement: invasive gastropods shift diet to consume the coffee leaf rust and its mycoparasite

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154946/1/ecy2966.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154946/2/ecy2966_am.pd