Nanoparticle Dynamics in Polymer Melts

The effect of small amounts of nanoparticles on the melt-state linear viscoelastic behaviour is investigated for different polymer-nanoparticles model systems characterized by poor polymer-particles interactions and low particle contents.contents. The drastic increase of the rheological properties with respect to the matrices is related to the formation of a filler network above a critical particles volume fraction. Once formed, the filler network exhibits an elastic feature that mixes with the intrinsic viscoelastic response of the polymer matrix, resulting in a complex Φ- and ω-dependent viscoelastic response of the nanocomposite. However, we show that the contributions of filler network and suspending medium can be decoupled due to the weak polymer-particle interactions and the differences in temporal relaxation scales. The adopted approach is validated through the building of a master curve of the moduli, which reflects the scaling of the elasticity of composites along the viscosity of the suspending medium. The two-phase model well works irrespective of the structure of the filler network, making evident the strict interrelationships between the structure, both on nano- and micro-scale, and the melt- state behaviour of the studied PNCs

Disease Progression Modeling and Prediction through Random Effect Gaussian Processes and Time Transformation

The development of statistical approaches for the joint modelling of the temporal changes of imaging, biochemical, and clinical biomarkers is of paramount importance for improving the understanding of neurodegenerative disorders, and for providing a reference for the prediction and quantification of the pathology in unseen individuals. Nonetheless, the use of disease progression models for probabilistic predictions still requires investigation, for example for accounting for missing observations in clinical data, and for accurate uncertainty quantification. We tackle this problem by proposing a novel Gaussian process-based method for the joint modeling of imaging and clinical biomarker progressions from time series of individual observations. The model is formulated to account for individual random effects and time reparameterization, allowing non-parametric estimates of the biomarker evolution, as well as high flexibility in specifying correlation structure, and time transformation models. Thanks to the Bayesian formulation, the model naturally accounts for missing data, and allows for uncertainty quantification in the estimate of evolutions, as well as for probabilistic prediction of disease staging in unseen patients. The experimental results show that the proposed model provides a biologically plausible description of the evolution of Alzheimer's pathology across the whole disease time-span as well as remarkable predictive performance when tested on a large clinical cohort with missing observations.Comment: 13 pages, 2 figure

Solid particle erosion and viscoelastic properties of thermoplastic polyurethanes

The wear resistance of several thermoplastic polyurethanes (TPUs) having different chemical nature and micronscale arrangement of the hard and soft segments has been investigated by means of erosion and abrasion tests. The goal was correlating the erosion performances of the materials to their macroscopic mechanical properties. Unlike conventional tests, such as hardness and tensile measurements, viscoelastic analysis proved to be a valuable tool to study the erosion resistance of TPUs. In particular, a strict correlation was found between the erosion rate and the high-frequency (~10^7 Hz) loss modulus. The latter reflects the actual ability of TPU to dissipate the impact energy of the erodent particles

Interfacially-Located Nanoparticles Anticipate the Onset of Co-Continuity in Immiscible Polymer Blends

The addition of nanoparticles has recently emerged as a clever tool to manipulate the microstructure and, through it, the macroscopic properties of immiscible polymer blends. Despite the huge number of studies in this field, the underlying mechanisms of most of the nanoparticle-induced effects on the blend microstructure remain poorly understood. Among others, the origin of effect of nanoparticles on the transition from distributed (drop-in-matrix) to co-continuous morphology is still controversial. Here we address this issue through a systematic study on a model blend of polystyrene (PS) and poly(methyl methacrylate) (PMMA) filled with small amounts of nanoparticles (organo-modified clay) selectively located at the polymer–polymer interface. Extraction experiments with selective solvents prove that the nanoparticles significantly anticipate the onset of co-continuity with respect to the unfilled blend. Morphological analyses reveal that such an effect is a consequence of the interconnection of nanoparticle-coated polymer domains. Such “ginger-like” clusters get into contact at low content due to their irregular shape, thus anticipating the onset of co-continuity

Fully Bio-Based Nanocomposite: Formulations For Packaging Application

The effect of a small amount of organoclay (OMMT) on mechanical, dynamic-mechanical, barrier and thermal properties of blown films based on blends of poly(lactic acid) (PLA) and polyamide 11 (PA11) was investigated. The addition of PA11 results in a decrease of elastic modulus (E) and tensile strength (σR) compared to neat PLA, which suggests poor interfacial adhesion between the polymer phases. Besides an enhancement of E and σR, the addition of 1 wt% of OMMT brings about a significant increase of the elongation at break. Neither blending with PA11 nor adding OMMT cause appreciable alterations of the barrier properties of the films, which remain essentially the same as those of pure PLA. Thermogravimetric analysis reveals that the onset of thermal degradation of the OMMT-filed blend is 15°C higher than of neat PLA. This improvement is probably due to the labyrinth effect of the PA11 phase. Finally, the OMMT brings about a slight enhancement of the glassy modulus compared to the unfilled blend, which suggests that the clay may exert some compatibilizing action. Such a beneficial effect of the OMMT endures up to the glass transition of PLA. he testing methods such as CCT, RCT, FCT, COBB, bursting etc. are supported by statistical technique and do not provide accurate results. The reason is the deviation of testing results. The same problem can be defined at the classification of different paper materials and qualities. This paper describes a new possible testing method to analyze the chemical and thermo-analytical nature of papers. This method can be used to specify effectively the limits of a given paper quality using in packaging industry and can help to ensure the exact traceability of paper identification. The results show that the this method on the one hand can be helpful to testing the paper during packaging producing process on the other hand after using as a packaging. To the testing a DSC measurement device was used as a thermo-analytical method to observe new specifics of paper based packaging

Role of polymer network and gelation kinetics on the mechanical properties and adsorption capacity of chitosan hydrogels for dye removal

Chitosan (CS) hydrogels are receiving growing attention as adsorbents for water purification purposes. The conditions of preparation of this class of materials play a crucial in the determination of their performances; however, this aspect is often neglected in the literature. In this study, we deal with this issue, focusing on the structure-property relationships of CS hydrogels obtained by phase inversion method. We show that the concentration of the starting solution determines the density and strength of intermolecular interactions, and that the gelation kinetics dictates the hydrogel structure at the microscale. Consequently, even subtle changes in the preparation protocol can cause significant differences in the performances of CS hydrogels in terms of mechanical properties and dye adsorption capacity. The observed trends are often neither trivial nor monotonic. Nonetheless, we demonstrate that they can be interpreted looking at the CS network structure, which can be inferred by rheological measurements

The Diverticular Disease Registry (DDR Trial) by the Advanced International Mini-Invasive Surgery Academy Clinical Research Network: Protocol for a Multicenter, Prospective Observational Study

Diverticular disease is an increasingly common issue, with a variety of clinical presentations and treatment options. However, very few prospective cohort studies explore outcomes between the different presentations and treatments. The Diverticular Disease Registry (DDR Trial) is a multicenter, prospective, observational cohort study on behalf of the Advanced International Mini-Invasive Surgery (AIMS) academy clinical research network. The DDR Trial aims to investigate the short-term postoperative and long-term quality of life outcomes in patients undergoing surgery or medical treatments for diverticular disease. DDR Trial is open to participation by all tertiary-care hospitals. DDR Trial has been registered at ClinicalTriats.gou (NCT 04907383). Data collection will be recorded on Research Electronic Data Capture (REDCap) starting on June 1 , 2021 and will end after 5 years of recruitment. All adult patients with imaging-proven colonic diverticular disease (i.e., symptomatic colonic diverticulosis including diverticular bleeding, diverticulitis, and Symptomatic Uncomplicated Diverticular Disease) will be included. The primary outcome of DDR Trial is quality of life assessment at 12-month according to the Gastrointestinal Quality of Life Index (GIQLI). The secondary outcome is 30-day postoperative outcomes according to the Clavien-Dindo classification. DDR Trial will significantly advance in identifying the optimal care for patients with diverticular disease by exploring outcomes of different presentations and treatments

Electric dipole moments and the search for new physics

Static electric dipole moments of nondegenerate systems probe mass scales for physics beyond the Standard Model well beyond those reached directly at high energy colliders. Discrimination between different physics models, however, requires complementary searches in atomic-molecular-and-optical, nuclear and particle physics. In this report, we discuss the current status and prospects in the near future for a compelling suite of such experiments, along with developments needed in the encompassing theoretical framework.Comment: Contribution to Snowmass 2021; updated with community edits and endorsement

Colorectal Cancer Stage at Diagnosis Before vs During the COVID-19 Pandemic in Italy

IMPORTANCE Delays in screening programs and the reluctance of patients to seek medical attention because of the outbreak of SARS-CoV-2 could be associated with the risk of more advanced colorectal cancers at diagnosis. OBJECTIVE To evaluate whether the SARS-CoV-2 pandemic was associated with more advanced oncologic stage and change in clinical presentation for patients with colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS This retrospective, multicenter cohort study included all 17 938 adult patients who underwent surgery for colorectal cancer from March 1, 2020, to December 31, 2021 (pandemic period), and from January 1, 2018, to February 29, 2020 (prepandemic period), in 81 participating centers in Italy, including tertiary centers and community hospitals. Follow-up was 30 days from surgery. EXPOSURES Any type of surgical procedure for colorectal cancer, including explorative surgery, palliative procedures, and atypical or segmental resections. MAIN OUTCOMES AND MEASURES The primary outcome was advanced stage of colorectal cancer at diagnosis. Secondary outcomes were distant metastasis, T4 stage, aggressive biology (defined as cancer with at least 1 of the following characteristics: signet ring cells, mucinous tumor, budding, lymphovascular invasion, perineural invasion, and lymphangitis), stenotic lesion, emergency surgery, and palliative surgery. The independent association between the pandemic period and the outcomes was assessed using multivariate random-effects logistic regression, with hospital as the cluster variable. RESULTS A total of 17 938 patients (10 007 men [55.8%]; mean [SD] age, 70.6 [12.2] years) underwent surgery for colorectal cancer: 7796 (43.5%) during the pandemic period and 10 142 (56.5%) during the prepandemic period. Logistic regression indicated that the pandemic period was significantly associated with an increased rate of advanced-stage colorectal cancer (odds ratio [OR], 1.07; 95%CI, 1.01-1.13; P = .03), aggressive biology (OR, 1.32; 95%CI, 1.15-1.53; P < .001), and stenotic lesions (OR, 1.15; 95%CI, 1.01-1.31; P = .03). CONCLUSIONS AND RELEVANCE This cohort study suggests a significant association between the SARS-CoV-2 pandemic and the risk of a more advanced oncologic stage at diagnosis among patients undergoing surgery for colorectal cancer and might indicate a potential reduction of survival for these patients