Strategy for Hydroxide Exclusion in Nanocrystalline Solid-State Metathesis Products

We demonstrate a simple strategy to either prevent or enhance hydroxide incorporation in nanocrystalline solid-state metathesis reaction products prepared in ambient environments. As an example, we show that ZnCO3 (smithsonite) or Zn5(CO3)2(OH)6 (hydrozincite) forms extremely rapidly, in less than two minutes, to form crystalline domains of 11 ± 2 nm and 6 ± 2 nm, respectively. The phase selectivity between these nanocrystalline products is dominated by the alkalinity of the hydrated precursor salts, which may in turn affect the availability of carbon dioxide during the reaction. Thus, unlike traditional aqueous precipitation reactions, our solid-state method offers a way to produce hydroxide-free, nanocrystalline products without active pH control

5G green cellular networks considering power allocation schemes

It is important to assess the effect of transmit power allocation schemes on the energy consumption on random cellular networks. The energy efficiency of 5G green cellular networks with average and water-filling power allocation schemes is studied in this paper. Based on the proposed interference and achievable rate model, an energy efficiency model is proposed for MIMO random cellular networks. Furthermore, the energy efficiency with average and water-filling power allocation schemes are presented, respectively. Numerical results indicate that the maximum limits of energy efficiency are always there for MIMO random cellular networks with different intensity ratios of mobile stations (MSs) to base stations (BSs) and channel conditions. Compared with the average power allocation scheme, the water-filling scheme is shown to improve the energy efficiency of MIMO random cellular networks when channel state information (CSI) is attainable for both transmitters and receivers.Comment: 14 pages, 7 figure

Massive Thirring Model: Inverse Scattering and Soliton Resolution

In this paper the long-time dynamics of the massive Thirring model is investigated. Firstly the nonlinear steepest descent method for Riemann-Hilbert problem is explored to obtain the soliton resolution of the solutions to the massive Thirring model whose initial data belong to some weighted-Sobolev spaces. Secondly, the asymptotic stability of multi-solitons follow as a corollary. The main difficulty in studying the massive Thirring model through inverse scattering is that the corresponding Lax pair has singularities at the origin and infinity. We overcome this difficulty by making use of two transforms that separate the singularities.Comment: arXiv admin note: text overlap with arXiv:2009.04260, arXiv:1907.0711

Analyze the Robustness of Classifiers under Label Noise

This study explores the robustness of label noise classifiers, aiming to enhance model resilience against noisy data in complex real-world scenarios. Label noise in supervised learning, characterized by erroneous or imprecise labels, significantly impairs model performance. This research focuses on the increasingly pertinent issue of label noise's impact on practical applications. Addressing the prevalent challenge of inaccurate training data labels, we integrate adversarial machine learning (AML) and importance reweighting techniques. Our approach involves employing convolutional neural networks (CNN) as the foundational model, with an emphasis on parameter adjustment for individual training samples. This strategy is designed to heighten the model's focus on samples critically influencing performance.Comment: 21 pages, 11 figure

Synthesis and surface reactivity of ZnO: application to gas and photon detection

This work employs different synthesis techniques to control the surface properties of polycrystalline ZnO for sensing device applications. ZnO micro-scale and nano-scale particles were made by various solid-state, solvothermal, and high temperature synthesis techniques that are designed for controlling crystal habit, surface polarity and surface area. The ZnO samples exhibited different degrees of degradation when exposed to ambient water and CO2, which were linked to ZnO surface dissolution and crystal growth conditions. In addition, a strategy for controlling the hydroxide in the products of the solid-state metathesis has been developed. Thin film gas sensors were assembled using the ZnO products. The capacitance responses of ZnO particles were evaluated after exposure to volatile organic compounds (ethanol and hexane) at various operation temperatures between 20 and 500⁰C. The results showed that gas sensing processes at low temperatures were mediated by the ambient humidity when detecting hydrophilic gases, and the responses from ZnO nanoparticles were greatly enhanced at high temperatures. Furthermore, a preliminary study for UV activated gas sensing was conducted to examine the effect of UV light radiation on the electrical properties of the ZnO samples, in which the AC frequency dependence of the photoresponse was revealed by electrical impedance spectroscopy

Transforming High School Counseling: Counselors\u27 Roles, Practices, and Expectations for Students\u27 Success

This study examined the current roles and practices of American high school counselors in relation to the ASCA National Model. Expectations for student success by high school counselors were also examined and compared to those of teachers\u27 and school administrators\u27. A nationally representative sample of 852 lead counselors from 944 high schools was surveyed as part of the High School Longitudinal Study: 2009-2012. Findings are examined in the light of the National Model and advocated practices

Efficiently Hardening SGX Enclaves against Memory Access Pattern Attacks via Dynamic Program Partitioning

Intel SGX is known to be vulnerable to a class of practical attacks exploiting memory access pattern side-channels, notably page-fault attacks and cache timing attacks. A promising hardening scheme is to wrap applications in hardware transactions, enabled by Intel TSX, that return control to the software upon unexpected cache misses and interruptions so that the existing side-channel attacks exploiting these micro-architectural events can be detected and mitigated. However, existing hardening schemes scale only to small-data computation, with a typical working set smaller than one or few times (e.g., $8$ times) of a CPU data cache. This work tackles the data scalability and performance efficiency of security hardening schemes of Intel SGX enclaves against memory-access pattern side channels. The key insight is that the size of TSX transactions in the target computation is critical, both performance- and security-wise. Unlike the existing designs, this work dynamically partitions target computations to enlarge transactions while avoiding aborts, leading to lower performance overhead and improved side-channel security. We materialize the dynamic partitioning scheme and build a C++ library to monitor and model cache utilization at runtime. We further build a data analytical system using the library and implement various external oblivious algorithms. Performance evaluation shows that our work can effectively increase transaction size and reduce the execution time by up to two orders of magnitude compared with the state-of-the-art solutions

Gender Difference in STEM Career Aspiration and Social-Cognitive Factors in Collectivist and Individualist Cultures

Gender equity in STEM demands that girls and women are provided with learning experiences, opportunities, and resources that meet their educational and vocational goals. This study examined gender difference in STEM learning experience, parental involvement, and self-efficacy to predict STEM career aspiration of different sociocultural groups. Two independent samples of high school students, one recruited from a collectivist culture (Taiwanese sample, N = 590) and the other recruited randomly from an individualist culture (American sample, N = 590), were used to examine the differences. Findings suggested a greater gender difference in STEM learning experience, parental involvement, and STEM self-efficacy of students from the collectivist culture than students from the individualist culture. Results of logistic analyses showed differential prediction of STEM career aspiration in two different cultural contexts. Findings were discussed in light of socio-cultural contexts

Multi-view Inverse Rendering for Large-scale Real-world Indoor Scenes

We present a multi-view inverse rendering method for large-scale real-world indoor scenes that reconstructs global illumination and physically-reasonable SVBRDFs. Unlike previous representations, where the global illumination of large scenes is simplified as multiple environment maps, we propose a compact representation called Texture-based Lighting (TBL). It consists of 3D meshs and HDR textures, and efficiently models direct and infinite-bounce indirect lighting of the entire large scene. Based on TBL, we further propose a hybrid lighting representation with precomputed irradiance, which significantly improves the efficiency and alleviate the rendering noise in the material optimization. To physically disentangle the ambiguity between materials, we propose a three-stage material optimization strategy based on the priors of semantic segmentation and room segmentation. Extensive experiments show that the proposed method outperforms the state-of-the-arts quantitatively and qualitatively, and enables physically-reasonable mixed-reality applications such as material editing, editable novel view synthesis and relighting. The project page is at https://lzleejean.github.io/TexIR.Comment: The project page is at: https://lzleejean.github.io/TexI