*-Wars Episode I: The Phantom Anomaly

As pointed out, chiral non-commutative theories exist, and examples can be constructed via string theory. Gauge anomalies require the matter content of individual gauge group factors, including U(1) factors, to be non-chiral. All ``bad'' mixed gauge anomalies, and also all ``good'' (e.g. for $\pi ^0\to \gamma \gamma$) ABJ type flavor anomalies, automatically vanish in non-commutative gauge theories. We interpret this as being analogous to string theory, and an example of UV/IR mixing: non-commutative gauge theories automatically contain ``closed string,'' Green-Schwarz fields, which cancel these anomalies.Comment: 20 pages. Added references and minor typos correcte

Inhibition of prefrontal protein synthesis following recall does not disrupt memory for trace fear conditioning

BACKGROUND: The extent of similarity between consolidation and reconsolidation is not yet fully understood. One of the differences noted is that not every brain region involved in consolidation exhibits reconsolidation. In trace fear conditioning, the hippocampus and the medial prefrontal cortex (mPFC) are required for consolidation of long-term memory. We have previously demonstrated that trace fear memory is susceptible to infusion of the protein synthesis inhibitor anisomycin into the hippocampus following recall. In the present study, we examine whether protein synthesis inhibition in the mPFC following recall similarly results in the observation of reconsolidation of trace fear memory. RESULTS: Targeted intra-mPFC infusions of anisomycin or vehicle were performed immediately following recall of trace fear memory at 24 hours, or at 30 days, following training in a one-day or a two-day protocol. The present study demonstrates three key findings: 1) trace fear memory does not undergo protein synthesis dependent reconsolidation in the PFC, regardless of the intensity of the training, and 2) regardless of whether the memory is recent or remote, and 3) intra-mPFC inhibition of protein synthesis immediately following training impaired remote (30 days) memory. CONCLUSION: These results suggest that not all structures that participate in memory storage are involved in reconsolidation. Alternatively, certain types of memory-related information may reconsolidate, while other components of memory may not

Fucus distichus: Investigating Humidity and Temperature Between Tides

Environmental elements such as changing rapidly changing temperature, prolonged periods of low to no water exposure, desiccation, predation and increased wave action can influence the diversity of microhabitats that inhabit the littoral zones. When making observations of various shorelines, specifically the physical conditions of the surrounding marine vegetation (i.e. Fucus distichus), an inquiry is made as to the role of Fucus in the amelioration of stressors on the marine habitat during low tide (MLLW), however, due to time considerations, temperature and humidity are the focus of this study. Using temperature and humidity probes, monitoring data shows that Fucus provides relatively humid and cooler conditions for organisms residing beneath the canopy during low tide. Varied weather during the experimental trials allows for monitoring during cool, overcast, and sunny days, allowing for evaluation of Fucus distichus\u27 efficacy in innate conditions. Further investigation, requiring warmer conditions and additional replicates are needed to fully assess the ability of Fucus to moderate environmental conditions beneath its canopy

An in vitro versus in vivo toxicogenomics investigation of prenatal exposures to tobacco smoke

Approximately 1 million women smoke during pregnancy despite evidence demonstrating serious juvenile and/or adult diseases being linked to early-life exposure to cigarette smoke. Susceptibility could be determined by factors in previous generations, i.e. pre-natal or ‘maternal’ exposures to toxins. Pre-natal exposure to airborne pollutants such as mainstream cigarette smoke has been shown to induce early-life insults (i.e. gene changes) in Offspring that serve as biomarkers for disease later in life. In this investigation, we have evaluated genome-wide changes in the lungs of mouse Dams and their juvenile Offspring exposed pre-natally to mainstream cigarette smoke. An additional lung model was tested alongside the murine model, as a means to find an alternative in vitro, human tissue-based replacement for the use of animals in medical research. Our toxicogenomic and bioinformatic results indicated that in utero exposure altered the genetic patterns of the foetus that could put them at greater risk for developing a range of chronic illnesses in later-life. The genes altered in the in vitro, cell culture model were reflected in the murine model of pre-natal exposure to MCS. The use of alternative in vitro models derived from human medical waste tissues could be viable options to achieve human end-point data and to conduct research that meets the remits for scientists to undertake the 3Rs practises

Multivariate sensor signals collected by aquatic drones involved in water monitoring: A complete dataset

Sensor data generated by intelligent systems, such as autonomous robots, smart buildings and other systems based on artificial intelligence, represent valuable sources of knowledge in today\u2019s data-driven society, since they contain information about the situations these systems face during their operation. These data are usually multivariate time series since modern technologies enable the simultaneous acquisition of multiple signals during long periods of time. In this paper we present a dataset containing sensor traces of six data acquisition campaigns performed by autonomous aquatic drones involved in water monitoring. A total of 5.6 hours of navigation are available, with data coming from both lakes and rivers, and from different locations in Italy and Spain. The monitored variables concern both the internal state of the drone (e.g., battery voltage, GPS position and signals to propellers) and the state of the water (e.g., temperature, dissolved oxygen and electrical conductivity). Data were collected in the context of the EU-funded Horizon 2020 project INTCATCH (http://www.intcatch.eu) which aims to develop a new paradigm for monitoring water quality of catchments. The aquatic drones used for data acquisition are Platypus Lutra boats. Both autonomous and manual drive is used in different parts of the navigation. The dataset is analyzed in the paper \u201cTime series segmentation for state-model generation of autonomous aquatic drones: A systematic framework\u201d [1] by means of recent time series clustering/segmentation techniques to extract data-driven models of the situations faced by the drones in the data acquisition campaigns. These data have strong potential for reuse in other kinds of data analysis and evaluation of machine learning methods on real-world datasets [2]. Moreover, we consider this dataset valuable also for the variety of situations faced by the drone, from which machine learning techniques can learn behavioural patterns or detect anomalous activities. We also provide manual labeling for some known states of the drones, such as, drone inside/outside the water, upstream/downstream navigation, manual/autonomous drive, and drone turning, that represent a ground truth for validation purposes. Finally, the real-world nature of the dataset makes it more challenging for machine learning methods because it contains noisy samples collected while the drone was exposed to atmospheric agents and uncertain water flow conditions

Introduction to Philosophy : Philosophy of Mind

1. Substance Dualism in Descartes2. Materialism and Behaviorism3. Functionalism4. Property Dualism5. Qualia and Raw Feels6. Consciousness7. Concepts and Content8. Freedom of the WillIntroduction to Philosophy: Philosophy of Mind surveys the central themes in philosophy of mind and places them in a historical and contemporary context intended to engage first-time readers in the field. It focuses on debates about the status and character of the mind and its seemingly subjective nature in an apparently more objective world. Cover art by Heather Salazar; cover design by Jonathan Lashle

Subspace clustering for situation assessment in aquatic drones

We propose a novel methodology based on subspace clustering for detecting, modeling and interpreting aquatic drone states in the context of autonomous water monitoring. It enables both more informative and focused analysis of the large amounts of data collected by the drone, and enhanced situation awareness, which can be exploited by operators and drones to improve decision making and autonomy. The approach is completely data-driven and unsupervised. It takes unlabeled sensor traces from several water monitoring missions and returns both a set of sparse drone state models and a clustering of data samples according to these models. We tested the methodology on a real dataset containing data of six different missions, two rivers and four lakes in different countries, for about 5.5 hours of navigation. Results show that the methodology is able to recognize known states “in/out of the water”, “up- stream/downstream navigation” and “manual/autonomous drive”, and to discover meaningful unknown states from their data-based properties, enabling novelty detection

Coupling atmospheric mercury isotope ratios and meteorology to identify sources of mercury impacting a coastal urban‐industrial region near Pensacola, Florida, USA

Identifying the anthropogenic and natural sources of mercury (Hg) emissions contributing to atmospheric mercury on local, regional, and global scales continues to be a grand challenge. The relative importance of various direct anthropogenic emissions of mercury, in addition to natural geologic sources and reemission of previously released and deposited mercury, differs regionally and temporally. In this study, we used local‐scale, mesoscale, and synoptic‐scale meteorological analysis to couple the isotopic composition of ambient atmospheric mercury with potential sources of mercury contributing to a coastal urban‐industrial setting near a coal‐fired power plant in Pensacola, Florida, USA. We were able to broadly discern four influences on the isotopic composition of ambient atmospheric mercury impacting this coastal urban‐industrial region: (1) local to regional urban‐industrial anthropogenic emissions (mean δ202Hg = 0.44 ± 0.05‰, 1SD, n = 3), (2) marine‐influenced sources derived from the Gulf of Mexico (mean δ202Hg = 0.77 ± 0.15‰, 1SD, n = 4), (3) continental sources associated with north‐northwesterly flows from within the planetary boundary layer (mean δ202Hg = 0.65 ± 0.04‰, 1SD, n = 3), and (4) continental sources associated with north‐northeasterly flows at higher altitudes (i.e., 2000 m above ground level; mean δ202Hg = 1.10 ± 0.21‰, 1SD, n = 8). Overall, these data, in conjunction with previous studies, suggest that the background global atmospheric mercury pool is characterized by moderately positive δ202Hg values; that urban‐industrial emissions drive the isotopic composition of ambient atmospheric mercury toward lower δ202Hg values; and that air‐surface exchange dynamics across vegetation and soils of terrestrial ecosystems drive the isotopic composition of ambient atmospheric mercury toward higher positive δ202Hg values. The data further suggest that mass‐independent fractionation (MIF) of both even‐mass‐ and odd‐mass‐number isotopes, likely generated by photochemical reactions in the atmosphere or during reemission from terrestrial and aquatic ecosystems, can be obscured by mixing with anthropogenic emissions having different MIF signatures.Key PointsIsotopic composition of TGM differed among meteorologically identified sourcesBackground atmospheric TGM displayed moderately positive δ202Hg valuesAnthropogenic emissions drive TGM isotopic composition to lower δ202Hg valuesPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136364/1/gbc20349-sup-0001-Supplementary.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136364/2/gbc20349.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136364/3/gbc20349_am.pd

A century-long record of plant evolution reconstructed from a coastal marsh seed bank

Evidence is mounting that climate-driven shifts in environmental conditions can elicit organismal evolution, yet there are sparingly few long-term records that document the tempo and progression of responses, particularly for plants capable of transforming ecosystems. In this study, we “resurrected” cohorts of a foundational coastal marsh sedge (Schoenoplectus americanus) from a time-stratified seed bank to reconstruct a century-long record of heritable variation in response to salinity exposure. Common-garden experiments revealed that S. americanus exhibits heritable variation in phenotypic traits and biomass-based measures of salinity tolerance. We found that responses to salinity exposure differed among the revived cohorts, with plants from the early 20th century exhibiting greater salinity tolerance than those from the mid to late 20th century. Fluctuations in salinity tolerance could reflect stochastic variation but a congruent record of genotypic variation points to the alternative possibility that the loss and gain in functionality are driven by selection, with comparisons to historical rainfall and paleosalinity records suggesting that selective pressures vary according to shifting estuarine conditions. Because salinity tolerance in S. americanus is tightly coupled to primary productivity and other vital ecosystem attributes, these findings indicate that organismal evolution merits further consideration as a factor shaping coastal marsh responses to climate change