Characterizing and Quantifying Frustration in Quantum Many-Body Systems

We present a general scheme for the study of frustration in quantum systems. We introduce a universal measure of frustration for arbitrary quantum systems and we relate it to a class of entanglement monotones via an exact inequality. If all the (pure) ground states of a given Hamiltonian saturate the inequality, then the system is said to be inequality saturating. We introduce sufficient conditions for a quantum spin system to be inequality saturating and confirm them with extensive numerical tests. These conditions provide a generalization to the quantum domain of the Toulouse criteria for classical frustration-free systems. The models satisfying these conditions can be reasonably identified as geometrically unfrustrated and subject to frustration of purely quantum origin. Our results therefore establish a unified framework for studying the intertwining of geometric and quantum contributions to frustration.Comment: 8 pages, 1 figur

Does Blood Flow Restriction Applied Post High-Load Exercise Augment Skeletal Muscle Growth Following Eight Weeks of Training?

The application of blood flow restriction during low load exercise has consistently been shown to augment muscle hypertrophy which has been attributed to metabolic accumulation. It remains unknown, however, whether metabolites can augment muscle growth independent of further mechanical tension, specifically when maintained post high-load training. Thirteen untrained individuals performed 24 training sessions. The control arm performed one set of elbow flexion (70% 1RM) exercise to volitional fatigue, while the experimental arm performed the same protocol immediately folloby 3 min of blood flow restriction (70% arterial occlusion). Both conditions completed the same volume (3687 vs. 3638 kg) of exercise. There was an interaction (p=0.031) demonstrating an attenuation of muscle growth at the 60% site in the experimental [pre: 3.1 (0.6), post: 3.1 (0.7) cm] vs. control [pre: 3.1 (0.7), post 3.3 (0.7) cm] condition. Muscle growth at the 50% site did not differ between the experimental [pre: 2.9 (0.6), post 2.9 (0.6) cm] and control [pre: 2.8 (0.7), post: 2.9 (0.6) cm] condition (p=0.31) nor did it differ at the 70% site [experimental pre: 3.3 (0.60), post 3.5 (0.7) cm; control pre: 3.4 (0.7), post 3.6 (0.7) cm]. Although there were no differences at the group level, there were attenuations at the individual level. The number of measured sites displaying growth at or outside the error of the measurement was greater in the control (21) vs. experimental (10) condition. The application of blood flow restriction post high-load exercise did not augment, but appeared to attenuate muscle growth at the group and individual level. With regard to one-repetition maximum strength, increases were observed in both the control [pre: 13.5 (3.8), post: 16.3 (4.5) kg] and experimental [pre: 13.7 (4.1), post: 16.3 (4.6) kg] conditions with no differences between conditions. No changes were observed for isometric or isokinetic strength for either the control or experimental conditions. These results unveil the possibilities that 1) metabolites do not have anabolic properties per se, and may be detrimental for muscle hypertrophy; 2) immediate post-exercise blood flow is important for muscle hypertrophy; and/or 3) metabolites have anabolic properties but this was masked by the restriction of blood flow

GATOR: Requirements capturing of telephony features

We are developing a natural language-based, requirements gathering system called GATOR (for the GATherer Of Requirements). GATOR assists in the development of more accurate and complete specifications of new telephony features. GATOR interacts with a feature designer who describes a new feature, set of features, or capability to be implemented. The system aids this individual in the specification process by asking for clarifications when potential ambiguities are present, by identifying potential conflicts with other existing features, and by presenting its understanding of the feature to the designer. Through user interaction with a model of the existing telephony feature set, GATOR constructs a formal representation of the new, 'to be implemented' feature. Ultimately GATOR will produce a requirements document and will maintain an internal representation of this feature to aid in future design and specification. This paper consists of three sections that describe (1) the structure of GATOR, (2) POND, GATOR's internal knowledge representation language, and (3) current research issues

Do Individual Responses to Resistance Exercise Exist to an Extent That Can be Detected Beyond That of Measurement Error/Random Biological Variability?

Millions of dollars are spent analyzing inter-individual differences in response to resistance exercise, but the lack of a non-exercise control group means they may simply be examining random error. The purpose of this study was to determine whether there are inter-individual differences in response to two distinct resistance exercise protocols. Participants (n=151) were randomly assigned to one of 3 groups as follows: (1) a traditional exercise group performing 4 sets to failure with a load that could be lifted 8-12 times; (2) a one-repetition maximum (1RM) training group performing a 1RM test each visit; and (3) a non-exercise control group. Both exercise groups performed 18 sessions of elbow flexion exercise over 6 weeks. Both 1RM training (2.3kg) and traditional training (2.4kg) increased 1RM strength to a similar extent. Only the 1RM group increased untrained arm 1RM strength (1.5kg) which was greater than both other groups (p\u3c0.05). The traditional exercise group also increased ultrasound measured muscle size at all sites (all\u3e0.22cm), each of which were greater than both the control and 1RM group (p\u3c0.05). The 1RM group did not increase muscle mass (p\u3e0.05). Across both training groups, the only individual responses were found in the change in 1RM strength of the trained arm in the traditional training group (Levene’s test p\u3c0.05) in which 10 individuals (25%) were classified as responding differently from the mean. The variability in the response to other outcomes did not exceed that of the control group indicating it could not be detected above random error. Other commonly used approaches of classifying differential responders such as clustering analyses, standard deviations above and below the mean, and upper/lower percentiles would produce different results but are not appropriate. These findings demonstrate the importance oftaking into consideration the magnitude of random error when classifying individual responders, and provide possible rationale as to why numerous analyses fail to find/replicate what genes may be responsible for producing more favorable exercise outcomes

SEC2MWD: A MATLAB toolbox for derivation of molecular weight distributions from size exclusion chromatography

Size exclusion chromatography (SEC) is a type of liquid chromatography used for separating molecules based on their size. The pipeline for converting a raw chromatogram to a molecular weight distribution involves multiple steps and require various parameters to be defined for each step. Commercial software lack transparency in terms of methods and algorithms, and it may be cumbersome to explore effects of different parameter settings. We have therefore developed a MATLAB toolbox that reproduces the main functionality of commercial software in a transparent and flexible manner. The toolbox consists of seven main functions, each representing a step in the calculation pipeline. The modular architecture makes it easy to modify or replace individual steps of the pipeline if necessary.publishedVersio

Can Blood Flow Restriction En hance the Effectiveness of Electrical Stimulations for Treating Muscle Damage?

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The neutral amino acid transporter SLC7A10 in adipose tissue, obesity and insulin resistance

Obesity, insulin resistance and type 2 diabetes represent major global health challenges, and a better mechanistic understanding of the altered metabolism in these conditions may give improved treatment strategies. SLC7A10, a member of the SLC7 subfamily of solute carriers, also named ASC-1 (alanine, serine, cysteine transporter-1), has recently been implicated as an important modulator of core processes in energy- and lipid metabolism, through its particularly high expression in adipocytes. In human cohorts, adipose SLC7A10 mRNA shows strong inverse correlations with insulin resistance, adipocyte size and components of the metabolic syndrome, strong heritability, and an association with type 2 diabetes risk alleles. SLC7A10 has been proposed as a marker of white as opposed to thermogenic beige and brown adipocytes, supported by increased formation of thermogenic beige adipocytes upon loss of Slc7a10 in mouse white preadipocytes. Overexpression of SLC7A10 in mature white adipocytes was found to lower the generation of reactive oxygen species (ROS) and stimulate mitochondrial respiratory capacity, while SLC7A10 inhibition had the opposite effect, indicating that SLC7A10 supports a beneficial increase in mitochondrial activity in white adipocytes. Consistent with these beneficial effects, inhibition of SLC7A10 was in mouse and human white adipocyte cultures found to increase lipid accumulation, likely explained by lowered serine uptake and glutathione production. Additionally, zebrafish with partial global Slc7a10b loss-of-function were found to have greater diet-induced body weight and larger visceral adipocytes compared to controls. However, challenging that SLC7A10 exerts metabolic benefits only in white adipocytes, suppression of SLC7A10 has been reported to decrease mitochondrial respiration and expression of thermogenic genes also in some beige and brown adipocyte cultures. Taken together, the data point to an important but complex role of SLC7A10 in metabolic regulation across different adipose tissue depots and adipocyte subtypes. Further research into SLC7A10 functions in specific adipocyte subtypes may lead to new precision therapeutics for mitigating the risk of insulin resistance and type 2 diabetes.publishedVersio