Diagnosing weakly first-order phase transitions by coupling to order parameters

The hunt for exotic quantum phase transitions described by emergent fractionalized degrees of freedom coupled to gauge fields requires a precise determination of the fixed point structure from the field theoretical side, and an extreme sensitivity to weak first-order transitions from the numerical side. Addressing the latter, we revive the classic definition of the order parameter in the limit of a vanishing external field at the transition. We demonstrate that this widely understood, yet so far unused approach provides a diagnostic test for first-order versus continuous behavior that is distinctly more sensitive than current methods. We first apply it to the family of $Q$-state Potts models, where the nature of the transition is continuous for $Q\leq4$ and turns (weakly) first order for $Q>4$, using an infinite system matrix product state implementation. We then employ this new approach to address the unsettled question of deconfined quantum criticality in the $S=1/2$ N\'eel to valence bond solid transition in two dimensions, focusing on the square lattice $J$-$Q$ model. Our quantum Monte Carlo simulations reveal that both order parameters remain finite at the transition, directly confirming a first-order scenario with wide reaching implications in condensed matter and quantum field theory.Comment: Published versio

Asynchronous Silent Programmable Matter Achieves Leader Election and Compaction

We study models and algorithms for Programmable Matter (PM), that is matter with the ability to change its physical properties (e.g., shape or optical properties) in a programmable fashion. PM can be implemented by assembling a system of weak self-organizing computational elements, called particles, that can be programmed via distributed algorithms to collectively achieve some global task. Recent advances in the production of nanotechnologies have rendered such systems increasingly possible in practice, thus triggering research interests from many areas of computer science. The most established models for PM assume that particles: are modeled as finite state automata; are all identical, executing the same algorithm based on local observation of the surroundings; live and operate in the cells of a hexagonal grid; can move from one cell to another by repeatedly alternating between a contracted state (a particle occupies one cell) and an expanded state (a particle occupies two neighboring cells). Given these elementary features, it is rather hard to design distributed algorithms even for basic tasks and, in fact, all existing solutions to solve fundamental problems via PM have resorted to endowing PM systems with various capabilities to overcome such hardness, thus assuming quite unrealistic features. In this paper, we move toward more realistic computational models for PM. Specifically, we first introduce, a new modeling approach that relaxes several assumptions used in previous ones. Second, we present a distributed algorithm to solve, in the model, a foundational primitive for PM, namely Leader Election. This algorithm works in O(n) rounds for all initial configurations of n particles that are both connected (i.e. particles induce a connected graph) and compact (i.e. without holes, that is no empty cells surrounded by particles occur). As usual in asynchronous contexts, a round is intended as the time within which all particles have been activated at least once. Third, we show that, if the initial configuration admits holes, it is impossible to achieve leader election while preserving connectivity. Finally, by slightly empowering the robots, we design an algorithm to handle initial configurations admitting holes that in O(n2) rounds solves the leader election problem while obtaining also compaction

Testosterone decreases adiponectin levels in female to male transsexuals

Aim: To evaluate the effect of testosterone (T) on adiponectin serum levels in transsexual female patients. Methods: We measured adiponectin, leptin, luteinizing hormone and follicle stimulating hormone, T, estradiol, lipid profile, biochemical parameters and body composition in 16 transsexual female patients at baseline and after 6 months of T treatment (100 mg Testoviron Depot /10 days, i.m.). Results: Adiponectin levels were 16.9 ± 7.3 mg/mL at baseline and 13.5 ± 7.4 mg/mL at month 6 of T treatment (P < 0.05). Leptin and high-density lipoprotein cholesterol decreased significantly, whereas body mass index, waist circumference and lean body mass increased significantly after 6 months of T treatment. No changes in insulin or Homeostasis Model Assessment were detected. Conclusion: T can significantly reduce adiponectin serum levels in transsexual female patients

Antenatal automatic diagnosis of cleft lip via unsupervised clustering method relying on 3D facial soft tissue landmarks

Objectives Ultrasound (US) is the first-choice device to detect different types of facial dysmorphisms. Anyway, at present no standard protocol has been defined for automatic nor semi-automatic diagnosis. Even though the practitioner's contribution is core, steps towards automatism are to be undertaken. We propose a methodology for diagnosing cleft lip on 3D US scans. Methods A bounded Depth Minimum Steiner Trees (D-MST) clustering algorithm is proposed for discriminating groups of 3D US faces relying on the presence/absence of a cleft lip. The analysis of 3D facial surfaces via Differential Geometry is adopted to extract landmarks. Thus, the extracted geometrical information is elaborated to feed the unsupervised clustering algorithm and produce the classification. The clustering returns the probability of being affected by the pathology, allowing physicians to focus their attention on risky individuals for further analysis. Results The feasibility is tested upon the available 3D US scans data and then deeply investigated for a large dataset of adult individuals. 3D facial Bosphorus database is chosen for the testing, which seven cleft lip-affected individuals are added to, by artificially creating the defect. The algorithm correctly separates left and right-sided cleft lips, while healthy individuals create a unique cluster; thus, the method shows accurate diagnosis results. Conclusions Even if further testing is to be performed on tailored datasets made exclusively of fetal images, this techniques gives hefty hints for a future tailored algorithm. This method also fosters the investigation of the scientific formalisation of the "normotype", which is the representative face of a class of individuals, collecting all the principal anthropometric facial measurements, in order to recognise a normal or syndromic fetus

Second-line chemotherapy for patients with advanced gastric cancer: who may benefit?

No established second-line chemotherapy is available for patients with advanced gastric cancer failing to respond or progressing to first-line chemotherapy. However, 20–40% of these patients commonly receive second-line chemotherapy. We evaluated the influence of clinico-pathologic factors on the survival of 175 advanced gastric cancer patients, who received second-line chemotherapy at three oncology departments. Univariate and multivariate analyses found five factors which were independently associated with poor overall survival: performance status 2 (hazard ratio (HR), 1.79; 95% CI, 1.16–2.77; P=0.008), haemoglobin ⩽11.5 g l−1 (HR, 1.48; 95% CI, 1.06–2.05; P=0.019), CEA level >50 ng ml−1 (HR, 1.86; 95% CI, 1.21–2.88; P=0.004), the presence of greater than or equal to three metastatic sites of disease (HR, 1.72; 95% CI, 1.16–2.53; P=0.006), and time-to-progression under first-line chemotherapy ⩽6 months (HR, 1.97; 95% CI, 1.39–2.80; P<0.0001). A prognostic index was constructed dividing patients into low- (no risk factor), intermediate- (one to two risk factors), or high- (three to five risk factors) risk groups, and median survival times for each group were 12.7 months, 7.1 months, and 3.3 months, respectively (P<0.001). In the absence of data deriving from randomised trials, this analysis suggests that some easily available clinical factors may help to select patients with advanced gastric cancer who could derive more benefit from second-line chemotherapy

Mucinous histology predicts for poor response rate and overall survival of patients with colorectal cancer and treated with first-line oxaliplatin- and/or irinotecan-based chemotherapy

The objective of this study was to investigate the efficacy of first-line chemotherapy containing irinotecan and/or oxaliplatin in patients with advanced mucinous colorectal cancer. Prognostic factors associated with response rate and survival were identified using univariate and multivariate logistic and/or Cox proportional hazards analyses. The population included 255 patients, of whom 49 (19%) had mucinous and 206 (81%) had non-mucinous colorectal cancer. The overall response rates for mucinous and non-mucinous tumours were 18.4 (95% CI, 7.5–29.2%) and 49% (95% CI, 42.2–55.8%), respectively (P=0.0002). After a median follow-up of 45 months, median overall survival for the mucinous patients was 14.0 months compared with 23.4 months for the non-mucinous group (hazard ratio (HR), 1.74; CI 95%, 1.27–3.31; P=0.0034). After adjustment for significant features by multivariate Cox regression analysis, mucinous histology was associated with poor overall survival (HR, 1.593, 95% CI, 1.05–2.40; P=0.0267), together with performance status ECOG 2, number of metastatic sites ⩾2, and peritoneal metastases. This retrospective analysis shows that patients with mucinous colorectal cancer have poor responsiveness to oxaliplatin/irinotecan-based first-line combination chemotherapy and an unfavourable prognosis compared with non-mucinous colorectal cancer patients

Leader election and compaction for asynchronous silent programmable matter

We study models and algorithms for Programmable Matter (PM, shortly), that is matter with the ability to change its physical properties (e.g., shape or optical properties) in a programmable fashion. PM can be implemented by assembling a system of weak self-organizing computational elements, called particles, that can be programmed via distributed algorithms to collectively achieve some global task. We first introduce SILBOT, a new and weak modeling approach that, unlike previous ones, does not require: i) any synchronization mechanism nor explicit communication between particles; ii) atomicity for the performed actions; iii) activation of one particle at the time within a finite neighborhood. Second, we present a distributed algorithm to solve, in the SILBOT model, a foundational primitive for PM, namely Leader Election. This algorithm manages initial configurations that are both connected (i.e. particles induce a connected graph) and compact (i.e. without holes). Third, we show that, if the initial configuration contains holes, it is impossible to achieve leader election while preserving connectivity. Finally, we design an algorithm to handle configurations admitting holes. Specifically, the algorithm achieves compaction, i.e. stabilizes the system into a compact connected configuration, while at the same time accomplishing leader election, provided that particles are able to sense holes

Biogeophysical Classifìcation of Seafìoor Seeps at a Carbonate-Hydrate Mound, Northern Gulf of Mexico

Located on the continental slope in 900m of water, Woolsey Mound dominates seafloor morphology at Mississippi Canyon 118. The carbonate-hydrate mound is the site of the Gulf of Mexico Hydrates Research Consortium’s seafloor observatory to investigate and monitor hydrographic, geophysical, geological, geochemical and biological processes of the hydrocarbon system, northern Gulf of Mexico. Spatial and temporal variability of processes that produced the mound - venting fluids, formation/dissociation of hydrates, formation of authigenic carbonate and of micro and macrofaunal communities - are unknown and form the basis of several investigations at the site. Innovative survey and monitoring systems, sensors, and tools have been developed to extract samples and data to unravel the history, character and composition of the site. This study represents an attempt to integrate results of extensive geophysical studies with recent studies of the macrofauna thriving at the site, and to use the results to develop a system of vent classification for use in evaluating the subseafloor hydrocarbon system. Seafloor morphology and geology have been characterized integrating high resolution swath bathymetry, acoustic imagery, seafloor video and sediment, water column, and pore-water samples. AUV bathymetric surveys were completed in 2005 and 2009; video images, photographs, core samples and water samples were collected during cruises from 2002 - 2010. Seismo-acoustic data have been directed at maximizing definition at various depths. Deep data show a salt body underlying Woolsey Mound; crestal faults emanating from the salt body infrequently but notably intersect the seafloor. High frequency chirp and surface-source-deep-receiver data reveal many intersections of antithetical faults with the seafloor. These have been mapped over seafloor bathymetry determined from multibeam surveys. Outcropping hydrates, fluid-migration features and seafloor communities- identified and described from numerous types of imagery - have been mapped. These maps have been combined/overlain on the bathymetry/fault maps to produce a biotypes-seep map from which we have identified and differentiated types of seeps. Community complexity is used as a proxy for seep duration/age while specific community components are believed to reflect composition of seep fluids. Although preliminary, this approach represents a novel classification system for seafloor hydrocarbon seeps