Network Tomography: Identifiability and Fourier Domain Estimation

The statistical problem for network tomography is to infer the distribution of $\mathbf{X}$, with mutually independent components, from a measurement model $\mathbf{Y}=A\mathbf{X}$, where $A$ is a given binary matrix representing the routing topology of a network under consideration. The challenge is that the dimension of $\mathbf{X}$ is much larger than that of $\mathbf{Y}$ and thus the problem is often called ill-posed. This paper studies some statistical aspects of network tomography. We first address the identifiability issue and prove that the $\mathbf{X}$ distribution is identifiable up to a shift parameter under mild conditions. We then use a mixture model of characteristic functions to derive a fast algorithm for estimating the distribution of $\mathbf{X}$ based on the General method of Moments. Through extensive model simulation and real Internet trace driven simulation, the proposed approach is shown to be favorable comparing to previous methods using simple discretization for inferring link delays in a heterogeneous network.Comment: 21 page

Perturbations of bounce inflation scenario from f(T)f(T) modified gravity revisited

In this work, we revisit the perturbations that are generated in the bounce inflation scenario constructed within the framework of $f(T)$ theory. It has been well known that pure $f(T)$ theory cannot give rise to bounce inflation behavior, so aside from the gravity part, we also employ a canonical scalar field for minimal extension. We calculate the perturbations in $f(T)$ theory using the well-established ADM formalism, and find various conditions to avoid their pathologies. We find that it is indeed very difficult to obtain a healthy model without those pathologies, however, one may find a way out if a potential requirement, say, to keep every function continuous, is abandoned.Comment: 5 pages, 1 figures. Comments are welcom

Fabrication of CuOx thin-film photocathodes by magnetron reactive sputtering for photoelectrochemical water reduction

The CuOx thin film photocathodes were deposited on F-doped SnO2 (FTO) transparent conducting glasses by alternating current (AC) magnetron reactive sputtering under different Ar:O2 ratios. The advantage of this deposited method is that it can deposit a CuOx thin film uniformly and rapidly with large scale. From the photoelectrochemical (PEC) properties of these CuOx photocathodes, it can be found that the CuOx photocathode with Ar/O2 30:7 provide a photocurrent density of −3.2 mA cm−2 under a bias potential −0.5 V (vs. Ag/AgCl), which was found to be twice higher than that of Ar/O2 with 30:5. A detailed characterization on the structure, morphology and electrochemical properties of these CuOx thin film photocathodes was carried out, and it is found that the improved PEC performance of CuOx semiconductor photocathode with Ar/O2 30:7 attributed to the less defects in it, indicating that this Ar/O2 30:7 is an optimized condition for excellent CuOx semiconductor photocathode fabrication

Idiopathic desmoid-type fibromatosis of the pancreatic head: case report and literature review

Desmoid-type fibromatosis (DTF) is an uncommon nonmetastatic fibrous neoplasm. Sporadic intraperitoneal DTF is rarely described in current literature. We herein report a case of DTF of unknown cause involving the pancreatic head. A 41-year-old man presented with recurrent epigastric pain and weight loss. An abdominal computed tomography scan showed a well-delineated solid cystic mass inside the pancreatic head. Pylorus-preserving pancreaticoduodenectomy was performed due to the patient’s debilitating symptoms and suspected malignancy. The pathological examination revealed massive fibroblastic proliferation arising from the musculoaponeurotic tissues, consistent with a diagnosis of DTF. Immunohistochemical phenotyping determined positive immunoreactivity to vimentin and β-catenin, but negative immunoreactivity to smooth muscle actin, CD117, CD34, or S-100, confirming the diagnosis of DTF. No local recurrence or distant metastasis was found during a 24-month follow-up. Radical resection is recommended as first-line treatment for pancreatic DTF. Long-term follow-up studies are required to establish the prognosis of pancreatic DTF

Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model

Many crucial biological processes rely on networks of protein-protein interactions. Predicting the effect of amino acid mutations on protein-protein binding is vital in protein engineering and therapeutic discovery. However, the scarcity of annotated experimental data on binding energy poses a significant challenge for developing computational approaches, particularly deep learning-based methods. In this work, we propose SidechainDiff, a representation learning-based approach that leverages unlabelled experimental protein structures. SidechainDiff utilizes a Riemannian diffusion model to learn the generative process of side-chain conformations and can also give the structural context representations of mutations on the protein-protein interface. Leveraging the learned representations, we achieve state-of-the-art performance in predicting the mutational effects on protein-protein binding. Furthermore, SidechainDiff is the first diffusion-based generative model for side-chains, distinguishing it from prior efforts that have predominantly focused on generating protein backbone structures

Stereotypical Images of STEM Professionals and STEM Career Interests in Chinese Elementary School Students

This study investigated stereotypical images of STEM professions and STEM career interest in Chinese elementary school students. The relationships between stereotypical images of STEM professionals and STEM career interests were also determined. Data for this study was gathered from two elementary schools in China, forming a convenience sample of 318 students enrolled from 3rd to 6th grade. Quantitative data of stereotypes about STEM professionals’ social skills, positive images of STEM professionals, views on STEM implications for society, and STEM career interests were gathered by a questionnaire with Likert scale. Follow-up structured interviews were performed with 12 participants. Elementary school students had strong stereotypes about STEM professionals’ social skills, slightly deep positive image of STEM professionals, and very positive views on STEM implications for society. However, their STEM career interests were not very high. Besides, elementary school students’ stereotypes about STEM professionals’ social skills have minor negative effects on their STEM career interests. Their positive image of STEM professionals and views on STEM implications for society have significant correlation with their STEM career interests

Advanced Geological Prediction

Due to the particularity of the tunnel project, it is difficult to find out the exact geological conditions of the tunnel body during the survey stage. Once it encounters unfavorable geological bodies such as faults, fracture zones, and karst, it will bring great challenges to the construction and will easily cause major problems, economic losses, and casualties. Therefore, it is necessary to carry out geological forecast work in the tunnel construction process, which is of great significance for tunnel safety construction and avoiding major disaster accident losses. This lecture mainly introduces the commonly used methods of geological forecast in tunnel construction, the design principles, and contents of geological forecast and combines typical cases to show the implementation process of comprehensive geological forecast. Finally, the development direction of geological forecast theory, method, and technology is carried out. Prospects provide a useful reference for promoting the development of geological forecast of tunnels