Quantum Tunneling of Thermal Protons Through Pristine Graphene

Atomically thin two-dimensional materials such as graphene and hexagonal boron nitride have recently been found to exhibit appreciable permeability to thermal protons, making these materials emerging candidates for separation technologies [S. Hu et al., Nature 516, 227 (2014); M. Lozada-Hidalgo et al., Science 351, 68 (2016).]. These remarkable findings remain unexplained by density-functional electronic structure calculations, which instead yield barriers that exceed by 1.0 eV those found in experiments. Here we resolve this puzzle by demonstrating that the proton transfer through pristine graphene is driven by quantum nuclear effects, which substantially reduce the transport barrier by up to 1.4 eV compared to the results of classical molecular dynamics (MD). Our Feynman-Kac path-integral MD simulations unambiguously reveal the quantum tunneling mechanism of strongly interacting hydrogen ions through two-dimensional materials. In addition, we predict a strong isotope effect of 1 eV on the transport barrier for graphene in vacuum and at room temperature. These findings not only shed light on the graphene permeability to protons and deuterons, but also offer new insights for controlling the underlying quantum ion transport mechanisms in nanostructured separation membranes

Content-Based Unsupervised Fake News Detection on Ukraine-Russia War

The Ukrainian-Russian war has garnered significant attention worldwide, with fake news obstructing the formation of public opinion and disseminating false information. This scholarly paper explores the use of unsupervised learning methods and the Bidirectional Encoder Representations from Transformers (BERT) to detect fake news in news articles from various sources. BERT topic modeling is applied to cluster news articles by their respective topics, followed by summarization to measure the similarity scores. The hypothesis posits that topics with larger variances are more likely to contain fake news. The proposed method was evaluated using a dataset of approximately 1000 labeled news articles related to the Syrian war. The study found that while unsupervised content clustering with topic similarity was insufficient to detect fake news, it demonstrated the prevalence of fake news content and its potential for clustering by topic

l-Peptide functionalized dual-responsive nanoparticles for controlled paclitaxel release and enhanced apoptosis in breast cancer cells

Nanoparticles and macromolecular carriers have been widely used to increase the efficacy of chemotherapeutics, largely through passive accumulation provided by their enhanced permeability and retention effect. However, the therapeutic efficacy of nanoscale anticancer drug delivery systems is severely truncated by their low tumor-targetability and inefficient drug release at the target site. Here, the design and development of novel l-peptide functionalized dual-responsive nanoparticles (l-CS-g-PNIPAM-PTX) for active targeting and effective treatment of GRP78-overexpressing human breast cancer in vitro and in vivo are reported. l-CS-g-PNIPAM-PTX NPs have a relative high drug loading (13.5%) and excellent encapsulation efficiency (74.3%) and an average diameter of 275 nm. The release of PTX is slow at pH 7.4 and 25 °C but greatly accelerated at pH 5.0 and 37 °C. MTT assays and confocal experiments showed that the l-CS-g-PNIPAM-PTX NPs possessed high targetability and antitumor activity toward GRP78 overexpressing MDA-MB-231 human breast cancer cells. As expected, l-CS-g-PNIPAM-PTX NPs could effectively treat mice bearing MDA-MB-231 human breast tumor xenografts with little side effects, resulting in complete inhibition of tumor growth and a high survival rate over an experimental period of 60 days. These results indicate that l-peptide-functionalized acid - and thermally activated - PTX prodrug NPs have a great potential for targeted chemotherapy in breast cancer.</p

BasicTAD: an Astounding RGB-Only Baseline for Temporal Action Detection

Temporal action detection (TAD) is extensively studied in the video understanding community by generally following the object detection pipeline in images. However, complex designs are not uncommon in TAD, such as two-stream feature extraction, multi-stage training, complex temporal modeling, and global context fusion. In this paper, we do not aim to introduce any novel technique for TAD. Instead, we study a simple, straightforward, yet must-known baseline given the current status of complex design and low detection efficiency in TAD. In our simple baseline (termed BasicTAD), we decompose the TAD pipeline into several essential components: data sampling, backbone design, neck construction, and detection head. We extensively investigate the existing techniques in each component for this baseline, and more importantly, perform end-to-end training over the entire pipeline thanks to the simplicity of design. As a result, this simple BasicTAD yields an astounding and real-time RGB-Only baseline very close to the state-of-the-art methods with two-stream inputs. In addition, we further improve the BasicTAD by preserving more temporal and spatial information in network representation (termed as PlusTAD). Empirical results demonstrate that our PlusTAD is very efficient and significantly outperforms the previous methods on the datasets of THUMOS14 and FineAction. Meanwhile, we also perform in-depth visualization and error analysis on our proposed method and try to provide more insights on the TAD problem. Our approach can serve as a strong baseline for future TAD research. The code and model will be released at https://github.com/MCG-NJU/BasicTAD.Comment: Accepted by CVI

Effect of institutional quality and foreign direct investment on economic growth and environmental quality: evidence from African countries

This study applies the method of the fully modified ordinary least squares (FMOLS) method and the vector error correction model (VECM) to explore whether institutional quality (IQ) and foreign direct investment (FDI) promoted economic growth (EG) and environmental quality (EQ) in oil-producing and non-oil-producing African countries from 1999 to 2017. The FMOLS findings demonstrate that IQ significantly promoted EG and improved EQ in the non-oil-producing countries, however it only improved EQ and showed no significant impact on EG in oil-producing countries. FDI significantly promoted EG to a higher extent in oil-producing countries than in non-oil-producing countries, but it presented no significant impact on EQ in both groups. The VECM results reveal that (i) two-way causation among IQ and EG, IQ and EQ, FDI and EG, and FDI and EQ was occurred in both groups, in the long-run. (ii) two-way causation among FDI and EQ and one-way causation from FDI to EG was observed in non-oil-producing countries in the short-run. Moreover, two-way causation among IQ and EG, and one-way causation from IQ to EQ were observed in non-oilproducing countries. To realize the sustainable development of economy and environment, a series of policy suggestions have been discussed

Bis(μ-1,2-bis­{[2-(2-pyrid­yl)-1H-imidazol-1-yl]meth­yl}benzene)bis­[bis­(thio­cyanato-κN)cadmium(II)]

The asymmetric unit of the binuclear title compound, [Cd2(NCS)4(C24H20N6)2], contains one half-mol­ecule, consisting of one Cd2+ cation, two half 1,2-bis­{[2-(2-pyrid­yl)-1H-imidazol-1-yl]meth­yl}benzene (L) ligands and two SCN− anions. The dimeric cyclic mol­ecule is completed by crystallographic inversion symmetry. The Cd2+ cation is coordinated by two N atoms from two SCN− anions and four N atoms from two symmetry-related L ligands, exhibiting a distorted octrahedral coordination. A two-dimensional supra­molecular network stacked parallel to [210] is finally formed by linking these dimers through weak π–π stacking inter­actions between the pyridine rings and benzene rings of adjacent dimers, with a plane-to-plane distance of 3.36 (6) Å and a centroid–centroid distance of 3.67 (2) Å. One of the thio­cyanate S atoms is equally disordered over two positions

Quantum tunneling of thermal protons through pristine graphene

Engineering of atomically thin membranes for hydrogen isotope separation is an actual challenge which has a broad range of applications. Recent experiments [M. Lozada-Hidalgo et al., Science 351, 68 (2016)] unambiguously demonstrate an order-of-magnitude difference in permeabilities of graphene-based membranes to protons and deuterons at ambient conditions, making such materials promising for novel separation technologies. Here we demonstrate that the permeability mechanism in such systems changes from quantum tunneling for protons to quasi-classical transport for heavier isotopes. Quantum nuclear effects exhibit large temperature and mass dependence, modifying the Arrhenius activation energy and Arrhenius prefactor for protons by more than 0.5 eV and by seven orders of magnitude correspondingly. Our findings not only shed light on the separation process for hydrogen isotope ions passing through pristine graphene but also offer new insights for controlling ion transport mechanisms in nanostructured separation membranes by manipulating the shape of the barrier and transport process conditions