Electron dephasing in homogeneous and inhomogeneous indium tin oxide thin films

The electron dephasing processes in two-dimensional homogeneous and inhomogeneous indium tin oxide thin films have been investigated in a wide temperature range 0.3--90 K. We found that the small-energy-transfer electron-electron ($e$-$e$) scattering process dominated the dephasing from a few K to several tens K. At higher temperatures, a crossover to the large-energy-transfer $e$-$e$ scattering process was observed. Below about 1--2 K, the dephasing time $\tau_\varphi$ revealed a very weak temperature dependence, which intriguingly scaled approximately with the inverse of the electron diffusion constant $D$, i.e., $\tau_\varphi (T \approx 0.3 \, {\rm K}) \propto 1/D$. Theoretical implications of our results are discussed. The reason why the electron-phonon relaxation rate is negligibly weak in this low-carrier-concentration material is presented.Comment: 10 pages, 7 figure

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

A Round-Efficient Authenticated Key Agreement Scheme Based on Extended Chaotic Maps for Group Cloud Meeting

The security is a critical issue for business purposes. For example, the cloud meeting must consider strong security to maintain the communication privacy. Considering the scenario with cloud meeting, we apply extended chaotic map to present passwordless group authentication key agreement, termed as Passwordless Group Authentication Key Agreement (PL-GAKA). PL-GAKA improves the computation efficiency for the simple group password-based authenticated key agreement (SGPAKE) proposed by Lee et al. in terms of computing the session key. Since the extended chaotic map has equivalent security level to the Diffie–Hellman key exchange scheme applied by SGPAKE, the security of PL-GAKA is not sacrificed when improving the computation efficiency. Moreover, PL-GAKA is a passwordless scheme, so the password maintenance is not necessary. Short-term authentication is considered, hence the communication security is stronger than other protocols by dynamically generating session key in each cloud meeting. In our analysis, we first prove that each meeting member can get the correct information during the meeting. We analyze common security issues for the proposed PL-GAKA in terms of session key security, mutual authentication, perfect forward security, and data integrity. Moreover, we also demonstrate that communicating in PL-GAKA is secure when suffering replay attacks, impersonation attacks, privileged insider attacks, and stolen-verifier attacks. Eventually, an overall comparison is given to show the performance between PL-GAKA, SGPAKE and related solutions

The Evaluation of Short- and Long-Term Performance of Cold-Mix Asphalt Patching Materials

Potholes, one of the major types of distress on pavement surfaces, damage vehicles and are a safety hazard for the travelling public. In order to mitigate the effect of potholes, cold-mix asphalt (CMA) patching materials are commonly used for urgent repair of pavement surfaces before resurfacing can be undertaken. Therefore, the short-term (initial stability) and long-term (in-service durability) performance evaluation of CMA patching materials is necessary. This study conducted several curing conditions in the laboratory to investigate short-term, long-term, and moisture effects on pavement surfaces. Moreover, this study compared the Marshall stability of samples prepared under various compaction conditions. Marshall stability, Cantabro abrasion, and UK wheel tracking tests were conducted to evaluate the performance of CMA patching materials. The results indicated that the Marshall stability of dense-gradation (DG) CMA patching materials was higher than that of open-graded (OG) CMA patching materials and the Marshall stability of OG CMA patching materials was highly influenced by the coarse aggregate proportion. The DG and OG CMA patching materials exhibited comparable abrasion resistance, and the Cantabro abrasion ratio was highly correlated to the estimated asphalt film thickness for the OG CMA patching materials. A moisture indicator (MI) was proposed, and the effect of moisture damage on Marshall stability and Cantabro abrasion ratio was related to the proposed MI. The rutting resistance of the DG CMA patching materials was higher than that of the OG CMA patching materials, which is consistent with the Marshall stability result

Exploiting Common Patterns in Diverse Cancer Types via Multi-Task Learning

&lt;p&gt;Cancer, a leading global cause of death, requires a precise prognosis for selecting high-risk patients for appropriate treatment, potentially improving survival outcomes. Yet, the intricate interplay of genetic cancer biomarkers and diverse medical data challenge the capabilities of conventional statistical or machine learning approaches. In contrast, sophisticated deep learning techniques can simplify high-dimensional, heterogeneous medical data into manageable low-dimensional feature vectors and leverage shared knowledge across various cancer types through multi-task learning.&lt;/p&gt;&lt;p&gt;&nbsp;&lt;/p&gt;&lt;p&gt;This study integrates medical data from multiple cancer types and applies multi-task learning to exploit shared knowledge. We used a multi-task bimodal neural network to predict cancer prognoses using three datasets (breast, lung, and colon cancer) from The Cancer Genome Atlas (TCGA) project. Our model manages heterogeneous medical data, including RNA Sequencing (RNA-Seq) and clinical data.&lt;/p&gt;&lt;p&gt;&nbsp;&lt;/p&gt;&lt;p&gt;Our results showed significant improvements for our smallest dataset, Colon Adenocarcinoma, with increases up to 26% in the concordance index (c-index) and 41% in the area under the precision-recall curve (AUPRC). This work represents initial strides in using multi-task learning for prognosis prediction across cancer types, potentially revealing shared mechanisms among cancers and contributing to future applications in precision medicine.&lt;/p&gt;&lt;p&gt;&nbsp;&lt;/p&gt;&lt;p&gt;Important notice: This second version incorporates testing on an external dataset, as well as using Pytorch Lightning.&lt;/p&gt;For running this code, you will need to create en environment in Anaconda using the following command: conda env create --file environment.yaml Make sure you are using the same library versions as in the environment.yaml file so that you avoid any errors regarding version incompatibilities. Installing all the dependencies might take between 10 and 30 minutes

Homogenized Poly(3-hexylthiophene)/Methanofullerene Film by Addition of End-Functionalized Compatibilizer and Its Application to Polymer Solar Cells

A uniformed poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) blended film prepared by using spin-coating process is achieved by addition of 10% hydroxyl group end-functionalized P3HT (HOC-P3HT-COH) as a compatibilizer. Ratio of P3HT/PCBM on a spin-coated film has been improved from 1 : 1.22 on the edge and 1 : 0.85 in the center of substrate (substrate size, 2 cm × 3 cm) to 1 : 1.03 on the edge and 1 : 0.94 in the center for P3HT/HOC-P3HT-COH/PCBM film (1 : 0.1 : 1). Homogeneous and reproducible polymer solar cell with an average of 3.71% power conversion efficiency under AM1.5G irradiation is fabricated with 10% HOC-P3HT-COH in P3HT/PCBM layer

Human motion correction and representation method from motion camera

Motion estimation is a basic issue for many computer vision tasks, such as human–computer interaction, motion objection detection and intelligent robot. In many practical scenes, the object movement goes with camera motion. Generally, motion descriptors directly based on optical flow are inaccurate and have low discrimination power. To this end, a novel motion correction method is proposed and a novel motion feature descriptor called the motion difference histogram (MDH) for recognising human action is proposed in this study. Motion estimation results are corrected by background motion estimation and MDH encodes the motion difference between the background and the objects. Experimental results on video shot with camera motion show that the proposed motion correction method is effective and the recognition accuracy of MDH is better than that of the state-of-the-art motion descriptor