Higher-Order Components Dictate Higher-Order Contagion Dynamics in Hypergraphs.

The presence of the giant component is a necessary condition for the emergence of collective behavior in complex networked systems. Unlike networks, hypergraphs have an important native feature that components of hypergraphs might be of higher order, which could be defined in terms of the number of common nodes shared between hyperedges. Although the extensive higher-order component (HOC) could be witnessed ubiquitously in real-world hypergraphs, the role of the giant HOC in collective behavior on hypergraphs has yet to be elucidated. In this Letter, we demonstrate that the presence of the giant HOC fundamentally alters the outbreak patterns of higher-order contagion dynamics on real-world hypergraphs. Most crucially, the giant HOC is required for the higher-order contagion to invade globally from a single seed. We confirm it by using synthetic random hypergraphs containing adjustable and analytically calculable giant HOC.

A prospective study of incidence and outcome of acute kidney injury among hospitalised patients in Malaysia (My-AKI).

INTRODUCTION: The incidence of acute kidney injury (AKI) among hospitalised patients has not been well studied in Malaysia. MATERIALS AND METHODS: We conducted a prospective, multicentre study in seven hospitals in West Malaysia. All the adults admitted in March 2017 fulfilling Kidney Disease Improving Global Outcomes (KDIGO) criteria for AKI were included. RESULTS: Of the 34,204 patients screened, 2,457 developed AKI (7.18%), 13.1% of which occurred in intensive care unit (ICU). There were 60.2% males with a mean age of 57.8 (±17.5) years. The most common comorbidities were hypertension (55.0%), diabetes (46.6%), ischaemic heart disease (15.1%) and chronic kidney disease (12.0%). The commonest causes of AKI were sepsis (41.7%), pre-renal (24.2%) and cardiorenal syndrome (10.8%). Nephrotoxin exposure was reported in 31%. At diagnosis, the proportion of AKI stages 1, 2 and 3 were 79.1%, 9.7%, 11.2%, respectively. Referral to nephrologists was reported in 16.5%. Dialysis was required in 176 (7.2%) patients and 55.6% were performed in the ICU. Acidosis (46.2%), uraemia (31.6%) and electrolyte disturbance (11.1%) were the commonest indications. Continuous renal replacement therapy (CRRT) was required in 14%. The average length of hospital stay was 9.5 days. In-hospital mortality was 16.4%. Among survivors, full and partial renal recovery was seen in 74.7% and 16.4% respectively while 8.9% failed to recover. After a mean follow-up of 13.7 months, 593 (30.2%) of survivors died and 38 (1.9%) initiated chronic dialysis. Mortality was highest among those with malignancies (Hazard Ratio, HR 2.14), chronic liver disease (HR 2.13), neurological disease (HR 1.56) and cardiovascular disease (HR 1.17). CONCLUSION: AKI is common in hospitalised patients and is with associated high mortality during and after hospitalisation.

K-selective percolation: A simple model leading to a rich repertoire of phase transitions.

We propose a K-selective percolation process as a model for iterative removals of nodes with a specific intermediate degree in complex networks. In the model, a random node with degree K is deactivated one by one until no more nodes with degree K remain. The non-monotonic response of the giant component size on various synthetic and real-world networks implies a conclusion that a network can be more robust against such a selective attack by removing further edges. From a theoretical perspective, the K-selective percolation process exhibits a rich repertoire of phase transitions, including double transitions of hybrid and continuous, as well as reentrant transitions. Notably, we observe a tricritical-like point on Erdos-Rényi networks. We also examine a discontinuous transition with unusual order parameter fluctuation and distribution on simple cubic lattices, which does not appear in other percolation models with cascade processes. Finally, we perform finite-size scaling analysis to obtain critical exponents on various transition points, including those exotic ones.

No-exclaves percolation.

Network robustness has been a pivotal issue in the study of system failure in network science since its inception. To shed light on this subject, we introduce and study a new percolation process based on a new cluster called an 'exclave' cluster. The entities comprising exclave clusters in a network are the sets of connected unfailed nodes that are completely surrounded by the failed (i.e., nonfunctional) nodes. The exclave clusters are thus detached from other unfailed parts of the network, thereby becoming effectively nonfunctional. This process defines a new class of clusters of nonfunctional nodes. We call it the no-exclave percolation cluster (NExP cluster), formed by the connected union of failed clusters and the exclave clusters they enclose. Here we showcase the effect of NExP cluster, suggesting a wide and disruptive collapse in two empirical infrastructure networks. We also study on two-dimensional Euclidean lattice to analyze the phase transition behavior using finite-size scaling. The NExP model considering the collective failure clusters uncovers new aspects of network collapse as a percolation process, such as quantitative change of transition point and qualitative change of transition type. Our study discloses hidden indirect damage added to the damage directly from attacks, and thus suggests a new useful way for finding nonfunctioning areas in complex systems under external perturbations as well as internal partial closures.

Post-process optimization of 3D printed poly(lactic-co-glycolic acid) dental implant scaffold for enhanced structure and mechanical properties: effects of sonication duration and power.

We described a technique of a post-process stage to partially remove the poly(vinyl alcohol) (PVA) binder in Poly(lactic-co-glycolic acid) (PLGA) dental scaffolds. The scaffolds were exposed to ultrasonic waves while immersed in an ethanol/acetone solvent mixture that possessed both polar and nonpolar properties. A factorial experiment was conducted in which the scaffolds were treated to three levels of sonication power (pW): 0, 20% (22 W) and 40% (44 W), and soaking duration (t): 5, 15, and 30 min. The treated scaffolds were characterized by FT-IR, optical microscopy, and mechanical (compressive) testing. FT-IR revealed that the amount of PVA decreased with increasing pW and t. Two-way ANOVA revealed that increasing pW and t, respectively, resulted in increasing scaffold surface area to volume (SVR). Sonication and solvent caused structural damage (i.e., unevenness) on the scaffold surface, but the damage was minimal at 20% pW and 30 min. The optimal values of pW and t resulting in enhanced fracture strength, strain and toughness were 20% and 30 min, respectively, which corroborated the findings of minimal structural damage. However, sonication had no significant effects on the scaffold stiffness. Mechanistic analysis of the effects of sonication predicted that the ultrasonic energy absorbed by the scaffold was sufficient to disrupt the van Der Waals bonds between the PVA and PLGA but not high enough to disrupt the covalent bonds within the PLGA. This technique is promising as it can partially remove the PVA from the scaffold, and mitigate problematic issues down the line, such as thermal degradation during sterilization, and undue delay/variability in biodegradation.

Critical behaviors of high-degree adaptive and collective-influence percolation.

How the giant component of a network disappears under attacking nodes or links addresses a key aspect of network robustness, which can be framed into percolation problems. Various strategies to select the node to be deactivated have been studied in the literature, for instance, a simple random failure or high-degree adaptive (HDA) percolation. Recently, a new attack strategy based on a quantity called collective-influence (CI) has been proposed from the perspective of optimal percolation. By successively deactivating the node having the largest CI-centrality value, it was shown to be able to dismantle a network more quickly and abruptly than many of the existing methods. In this paper, we focus on the critical behaviors of the percolation processes following degree-based attack and CI-based attack on random networks. Through extensive Monte Carlo simulations assisted by numerical solutions, we estimate various critical exponents of the HDA percolation and those of the CI percolations. Our results show that these attack-type percolation processes, despite displaying apparently more abrupt collapse, nevertheless exhibit standard mean-field critical behaviors at the percolation transition point. We further discover an extensive degeneracy in top-centrality nodes in both processes, which may provide a hint for understanding the observed results.

Pattern of biopsy-proven renal disease in Sabah: A retrospective cross-sectional study over 3.5 years.

OBJECTIVES: To explore the epidemiological and histopathological patterns of glomerular diseases in Sabah. METHODS: A state-wide cross-sectional study was conducted. There were 336 native renal biopsies in 296 eligible patients from 1st January 2013 to 30th June 2016. All patients aged ≥12 years with sufficient sampling (≥8 glomeruli) for histopathological assessment were included. Graft kidney biopsies, protocol-based biopsies and patients with uncertain demographics were excluded. Demographics of patients, clinical data, laboratory parameters prior to biopsy, and histology findings of renal biopsies were collected from local unit database and recorded into a standardised data collection form. Descriptive statistical analyses were employed and factors associated with Lupus nephritis (LN) were explored using logistic regression. RESULTS: The mean age during biopsy was 34.53 years (Standard Deviation 0.759). Primary glomerulonephritis (PGN) accounted for 42.6% (126) of all native renal biopsies. The commonest cause of PGN was minimal change disease (38.9%, 49) followed by focal segmental glomerulosclerosis (33.3%, 42) and IgA nephropathy (14.3%, 18). LN is the leading cause for secondary glomerulonephritis (SGN) (87.2%, 136). Younger age (Odds Ratio, OR 0.978; 95% Confidence Interval, 95%CI 0.960, 0.996); female gender (OR 17.53; p<0.001); significant proteinuria (OR 132.0; p<0.001); creatinine level at biopsy (OR 11.26; p=0.004); positive antinuclear antibody (ANA) (OR 46.7; p<0.001); and ANA patterns (OR 8.038; p=0.018) were significant in predicting the odds of having LN. CONCLUSION: This is the first epidemiology study of glomerular diseases in Sabah. The predominance of LN suggests lower threshold for renal biopsy in patients with suspected glomerular disorders. We have identified significant predictors for early detection and treatment of LN.

The equilibrium and fixed-bed study of malachite green adsorption on chitosan hydrogels.

Chitosan hydrogel beads were prepared by a precipitation process, and were used to investigate the adsorption of malachite green (MG) oxalate under various conditions. It was found that adsorption equilibrium was most sensitive to the pH value at pH <8 while fixed bed breakthrough kinetics presented asymmetric S-shaped profiles which could not be adequately described by conventional models such as Adams-Bohart and Yoon-Nelson. The possible reasons were discussed and an improved Adams-Bohart model was proposed to better describe the changes in mass transfer mechanisms during adsorption.

Case series of haemothorax secondary to avulsed bullae vessel.

Haemothorax refer to the bleeding in the pleural space. It is commonly due to iatrogenic, blunt or penetrating chest trauma. Non-traumatic haemothorax is a rare entity that can potentially lead to life threatening complications. The initial management of both traumatic and non-traumatic haemothorax includes resuscitation and stabilisation of the patient. We would like to present two cases of non-traumatic haemothorax secondary to an avulsed bullae vessel.

Endometriosis - A rare cause of primary spontaneous pneumothorax.

Catamenial pneumothorax is a rare condition. We report a case of a 36-year-old female who presented with dyspnoea every time before she had her regular menses. Further investigation confirmed that she had catamenial pneumothorax. With this case we wish to highlight this rare diagnostic entity that every clinician should keep in mind.