Composition and Dominance of Edible and Inedible Phytoplankton Predict Responses of Baltic Sea Summer Communities to Elevated Temperature and CO2

Previous studies with Baltic Sea phytoplankton combining elevated seawater temperature with CO2 revealed the importance of size trait-based analyses, in particular dividing the plankton into edible (>5 and <100 µm) and inedible (<5 and >100 µm) size classes for mesozoopankton grazers. While the edible phytoplankton responded predominantly negative to warming and the inedible group stayed unaffected or increased, independent from edibility most phytoplankton groups gained from CO2. Because the ratio between edible and inedible taxa changes profoundly over seasons, we investigated if community responses can be predicted according to the prevailing composition of edible and inedible groups. We experimentally explored the combined effects of elevated temperatures and CO2 concentrations on a late-summer Baltic Sea community. Total phytoplankton significantly increased in response to elevated CO2 in particular in combination with temperature, driven by a significant gain of the inedible <5 µm fraction and large filamentous cyanobacteria. Large flagellates disappeared. The edible group was low as usual in summer and decreased with both factors due to enhanced copepod grazing and overall decline of small flagellates. Our results emphasize that the responses of summer communities are complex, but can be predicted by the composition and dominance of size classes and groups.

Mirror descent algorithm on the indefinite control horizon

We consider the problem of optimal control in a random environment in a minimax setting as applied to data processing. It is assumed that the random environment provides two methods of data processing, the effectiveness of which is not known in advance. The goal of the control in this case is to find the optimal strategy for the application of processing methods and to minimize losses. To solve this problem, the mirror descent algorithm is used, including its modifications for batch processing. The use of algorithms for batch processing allows us to get a significant gain in speed due to the parallel processing of batches. In the classical statement, the search for the optimal strategy is considered on a fixed control horizon but this article considers an indefinite control horizon. With an indefinite horizon, the control algorithm cannot use information about the value of the horizon when searching for an optimal strategy. Using numerical modeling, the operation of the mirror descent algorithm and its modifications on an indefinite control horizon is studied and obtained results are presented.

P.232 Motor Recovery after Early Surgical Decompression in Cervical ASIA A Spinal Cord Injury Patients

Background: Despite growing evidence for early surgical decompression for traumatic cervical spinal cord injury(tCSCI) patients, controversy surrounds the efficacy of early surgical decompression on patients with a complete (ASIA A) cervical injury. Methods: Patients with ASIA A cervical tCSCI were isolated from 4 prospective, multi-center datasets. Patients who had a Glasgow coma scale of less than 13, were over the age of 70 or under 16 were excluded. Significant gain was defined to include those that recovered more than two muscle groups (greater than 3/5 power) below their level of injury. Analysis of variance (ANOVA) was then done to compare significant gain over the 1 year follow-up period for patients with and without early decompressive surgery (<24hrs). Results: We identified 420 cervical ASIA A tCSCI patients. The mean number of muscle groups gained was 2.69 (SD 2.3.12) for those who had early surgery compared to 2.37 (SD 3.38) for those with late surgery. Of those patients who had early surgery 39.67% had a significant improvement vs. 28.76% of those who did not have early surgery (P = 0.030). Conclusions: For the first time, we have shown a clear therapeutic benefit of early surgical decompression within 24 hrs in ASIA A tCSCI patients.

Newly learned novel cues to location are combined with familiar cues but not always with each other

Mature perceptual systems can learn new arbitrary sensory signals (novel cues) to properties of the environment, but little is known about the extent to which novel cues are integrated into normal perception. In normal perception, multiple uncertain familiar cues are combined, often near-optimally (reliability-weighted averaging), to increase perceptual precision. We trained observers to use abstract novel cues to estimate horizontal locations of hidden objects on a monitor. In Experiment 1, four groups of observers each learned to use a different novel cue. All groups benefitted from a suboptimal but significant gain in precision using novel and familiar cues together after short-term training (3 x ~1.5 hour sessions), extending previous reports of novel-familiar cue combination. In Experiment 2, we tested whether two novel cues may also be combined with each other. One pair of novel cues could be combined to improve precision but the other could not, at least not after three sessions of repeated training. Overall, our results provide extensive evidence that novel cues can be learned and combined with familiar cues to enhance perception, but mixed evidence for whether perceptual and decision-making systems can extend this ability to the combination of multiple novel cues with only short-term training.

Hepatocyte-Specific Phgdh-Deficient Mice Culminate in Mild Obesity, Insulin Resistance, and Enhanced Vulnerability to Protein Starvation

L-Serine (Ser) is synthesized de novo from 3-phosphoglycerate via the phosphorylated pathway committed by phosphoglycerate dehydrogenase (Phgdh). A previous study reported that feeding a protein-free diet increased the enzymatic activity of Phgdh in the liver and enhanced Ser synthesis in the rat liver. However, the nutritional and physiological functions of Ser synthesis in the liver remain unclear. To clarify the physiological significance of de novo Ser synthesis in the liver, we generated liver hepatocyte-specific Phgdh KO (LKO) mice using an albumin-Cre driver. The LKO mice exhibited a significant gain in body weight compared to Floxed controls at 23 weeks of age and impaired systemic glucose metabolism, which was accompanied by diminished insulin/IGF signaling. Although LKO mice had no apparent defects in steatosis, the molecular signatures of inflammation and stress responses were evident in the liver of LKO mice. Moreover, LKO mice were more vulnerable to protein starvation than the Floxed mice. These observations demonstrate that Phgdh-dependent de novo Ser synthesis in liver hepatocytes contributes to the maintenance of systemic glucose tolerance, suppression of inflammatory response, and resistance to protein starvation.

Management of an endo-perio lesion: A multidisciplinary approach

The presence of pulpal pathosis and inflammatory periodontal disease concomitantly can complicate diagnosis and treatment planning of any tooth. It requires a combined treatment approach involving endodontic, periodontic and prosthodontic intervention. Often, the periodontal and prosthodontic aspects are neglected by the clinicians after successful endodontic treatment resulting in failure. The present case report describes a multidisciplinary approach for the treatment of a tooth that presented with an endo-perio lesion; using non-surgical root canal treatment and periodontal regenerative surgery (non-incised papillae surgical approach, {NIPSA} long with GTR membrane and an alloplastic bone graft) which were then followed by the placement of a conservative tooth coverage restoration (endocrown). A significant gain in clinical attachment level was seen 6 months postoperatively. Radiographically also a significant amount of bone fill was observed.

Convolutional Neural Networks for Challenges in Automated Nuclide Identification

Improvements in Radio-Isotope IDentification (RIID) algorithms have seen a resurgence in interest with the increased accessibility of machine learning models. Convolutional Neural Network (CNN)-based models have been developed to identify arbitrary mixtures of unstable nuclides from gamma spectra. In service of this, methods for the simulation and pre-processing of training data were also developed. The implementation of 1D multi-class, multi-label CNNs demonstrated good generalisation to real spectra with poor statistics and significant gain shifts. It is also shown that even basic CNN architectures prove reliable for RIID under the challenging conditions of heavy shielding and close source geometries, and may be extended to generalised solutions for pragmatic RIID.

The development of interlanguage pragmatic markers in alignment with role relationships

Studies on the development of interlanguage pragmatic markers (PMs) have attracted increasing interest recently. However, little research is available on the PM dynamic development in alignment with English-as-a-foreign-language (EFL) classroom contexts. Given the lacuna, this article, based on the Complexity and the Alignment theories, investigates how PMs develop and how aligning with film-situated un/equal role relationships influences development. The study with eight data collection points tracks 28 EFL learners’ PM production over around 1.5 year. Results revealed: (1) the employed PM functions fluctuated but developed from singular to multiple, with the interpersonal function use being regressive and the structural and the cognitive, progressive; (2) the PM development manifested a significant gain in aligning with the equal role relationships; and (3) different proficiency learners had dissimilar PM development. These findings corroborate the view of context-dependent dynamic development and provide strong evidence for aligning EFL learning with various role relationships.

How to GAN Event Unweighting

Event generation with neural networks has seen significant progress recently. The big open question is still how such new methods will accelerate LHC simulations to the level required by upcoming LHC runs. We target a known bottleneck of standard simulations and show how their unweighting procedure can be improved by generative networks. This can, potentially, lead to a very significant gain in simulation speed.

Deployment mechanism for nanosatellite dipole antenna

The paper focuses on the design of the deployment mechanism for a nanosatellite with a fusible element. The main requirements for this mechanism were: relative simplicity of design, reliability, as well as simplification of the ground testing procedure. Using the principle of fixation on fusible elements, Rose’s alloy in particular, we designed a laboratory prototype of the antenna feed deployment mechanism for CubeSats. Furthermore, we developed a technology of flap deployment control by measuring the conductivity of the fusible element. We carried out a set of tests of the created laboratory prototype on a vibration stand and in a thermal vacuum chamber, as well as a series of functional tests. Comparison of the created prototype with the closest commercial analogs showed that a significant gain in the dimensions of the structure was achieved, as well as the number of elements of the mechanism itself was reduced, which positively affect reliability.