bluuebunny/crossref_metadata_2025 huggingface dataset:
Foundations of radiological protection in space: the integrated multidisciplinary approach for next manned missions in deep space
Authors: Rizzo Alessandro , Borra Enrico Maria , Ciciani Luca , Di Fino Luca , Romoli Giulia , Santi Amantini Giorgia , Sperandio Luciano , Vilardi Ignazio , Narici Livio
Published: November 2023

Future manned missions in deep space toward Moon and Mars represent one of the greatest challenges for radiological protection, which task is to mitigate risks for human life raised by the hostile space radiation environment. The prolonged exposure of astronauts to cosmic rays, mainly ion fields of galactic or solar origin, with a large dynamical behavior in time and space with a wide range of kinetic energies, may result in an unacceptable life risk for the next deep space manned missions. Indeed, these ions can deliver significant doses to astronauts by directly hitting human tissues as well as exposing them to secondary particles (neutron and high-LET nuclear fragments) produced by their interaction with space habitat materials. This radiation environment is very different from work environments on Earth, for example, in nuclear power plants or nuclear medicine departments, for which radioprotection was historically developed. Workers on Earth are mainly exposed to photons ($$\textrm{X}$$
X
-rays and $$\gamma$$
γ
-rays), to $$\alpha$$
α
- and $$\beta$$
β
-particles and neutrons, with lower energies than those in space. This difference marks a significant change in the methodological approach of the radioprotection in space compared to that on ground. The review presents the basic principles of radiation protection in space compared to that on ground and the strategies that must be implemented to mitigate risks in manned missions. In particular, the principles of the integrated multidisciplinary approach proposed by NASA and other space agencies for human space exploration are also discussed, with emphasis on the synergies among the various countermeasures proposed.
A Pre-Silicon Detection Based on Deep Learning Model for Hardware Trojans
Authors: Ma Pengcheng , Wang Zhen , Wang Yong
Published: November 2023

Several hardware Trojan (HT) detection techniques are available today to ensure the security of hardware systems. However, the existing pre-silicon HT detection techniques have problems such as difficulties in capturing HT path features and poor applicability. To address these challenges, this paper proposes a gate-level HT detection scheme based on a deep learning model. We parse the circuit gate-level netlist and develop an algorithm to extract circuit path sentences based on the signal propagation rule. Path sentences consisting of gate names are extracted as experimental datasets. We apply the theory of natural language processing (NLP) to the task of HT detection and use three neural networks to filter the length of path sentences. Then, based on the deep learning model text convolutional neural network (TextCNN), we propose PS-TextCNN for HT detection. Our approach is verified on seven benchmark circuits of the RS232-series and eight benchmark circuits of the s-series. We achieve an average true positive rate (TPR) of 88.9%. The TPR of the RS232-series reaches a high score of 99.5%. The TPR of the s-series is 79.5%, which is significantly higher than that of the existing gate-level HT detection techniques.
The photography method: Solving pentagon equation
Authors: Manturov Vassily Olegovich , Wan Zheyan
Published: November 2023

In this paper, we consider two applications of the pentagon equation. The first deals with actions of flips on edges of triangulations labeled by rational functions in some variables. The second can be formulated as a system of linear equations with variables corresponding to triangles of a triangulation. The general method says that if there is some general data (say, edge lengths or areas) associated with states (say, triangulations) and a general data transformation rule (say, how lengths or areas are changed under flips) then after returning to the initial state we recover the initial data.
Preservation of NATP
Authors: Ahn Jinhoo , Kim Joonhee , Lee Hyoyoon , Lee Junguk
Published: November 2023

We prove the preservation theorems for NATP; many of them extend the previously established preservation results for other model-theoretic tree properties. Using them, we also furnish proper examples of NATP theories which are simultaneously TP2 and SOP.

First, we show that NATP is preserved by the parametrization and sum of the theories of Fraïssé limits of Fraïssé classes satisfying strong amalgamation property.

Second, the preservation of NATP for two kinds of dense/co-dense expansions, i.e. the theories of lovely pairs and of [Formula: see text]-structures for geometric theories, and dense/co-dense expansion on vector spaces is proved.

Next, we prove the preservation of NATP for the generic predicate expansion and the pair of an algebraically closed field and its distinguished subfield; for the latter, not only NATP, but also the preservation of NTP1 and NTP2 is considered.

Finally, we present some proper examples of NATP theories using the results proved in this paper, including the parametrization of DLO and the expansion of an algebraically closed field by adding a generic linear order. In particular, we show that the model companion of the theory of algebraically closed fields with circular orders (ACFO) is NATP.
Influence Line Identification Method Based on VMD Combined with Improved Wavelet Threshold Denoising
Authors: Zhu Jinsong , Zhou Shuai
Published: November 2023

The influence line of bridge can reflect the performance of the bridge under the moving vehicle load. It has a wide range of applications in structural damage detection, performance evaluation, model correction and bridge weigh-in-motion. Fast moving vehicles will cause the dynamic effect of the bridge, resulting in the change of the bridge response curve and the difficulty of identifying the influence line. In this paper, an influence line identification method based on variational mode decomposition (VMD) combined with improved wavelet threshold denoising is proposed. Firstly, the mathematical model of influence line identification is established based on vehicle load matrix and bridge response. Then, VMD combined with improved wavelet threshold denoising method is used to eliminate dynamic fluctuation effect and noise. Finally, the elastic net penalty term is introduced in the influence line identification problem, and the B-spline basis function is used to reconstruct the influence line. In order to verify the effectiveness of the proposed method, a vehicle-bridge coupling model is established for numerical calculation, and the identification of bridge displacement influence lines under different conditions such as vehicle speed, noise level, road roughness and vehicle weight is investigated. The results show that the proposed method can effectively eliminate the dynamic fluctuation components and noise of the bridge response. In the case of good road roughness, the influence line can still be accurately identified when the vehicle speed reaches 15 m/s.
Three-dimensional stochastic Navier–Stokes equations with Markov switching
Authors: Hsu Po-Han , Sundar Padmanabhan
Published: November 2023

A finite-state Markov chain is introduced in the noise terms of the three-dimensional stochastic Navier–Stokes equations in order to allow for transitions between two types of multiplicative noises. We call such systems as stochastic Navier–Stokes equations with Markov switching. To solve such a system, a family of regularized stochastic systems is introduced. For each such regularized system, the existence of a unique strong solution (in the sense of stochastic analysis) is established by the method of martingale problems and pathwise uniqueness. The regularization is removed in the limit by obtaining a weakly convergent sequence from the family of regularized solutions, and identifying the limit as a solution of the three-dimensional stochastic Navier–Stokes equation with Markov switching.
Toward Development of a Plate Discrete Element Method: Geometry and Kinematics
Authors: Chen Jian , Krengel Dominik , Matuttis Hans-Georg
Published: November 2023

Shapes of constituent particles have a prominent effect on the macroscopic responses of granular assemblies. Clayey minerals often possess a plate-shaped geometry with a large surface-to-volume ratio. It is difficult to model such a geometry with spheres or clusters of spheres in a conventional discrete element method (DEM). In this study, we present a new DEM for plate-shaped particles with a focus on particle geometry and kinematics. The moment of inertia for a general convex plate is given and unit quaternions are adopted to represent the angular degrees of freedom. In addition, the equation of motion for rotation is proposed to be solved in a body-fixed rather than in a space-fixed reference frame. We present simulations of the rotation of a system of plate-shaped particles under the conservation of angular momentum without external torque. The results demonstrate the necessity and importance of enforcing the unity constraint on the quaternions numerically solved from the equation of motion for rotation.
An Abstract Context to Lattice-Based Ideals (Filters) with Multi-Fuzzy Soft Settings
Authors: Vimala J. , Begam S. Sabeena , Saeed Muhammad , Khan Khuram Ali , Ur Rahman Atiqe
Published: November 2023

In this study, multi-fuzzy soft ideals (filters) are introduced over the lattice-ordered multi-fuzzy soft set ([Formula: see text]) and their results are shown. The ideas of lattice-ordered multi-fuzzy soft homomorphism ([Formula: see text]) between two [Formula: see text]s are then introduced, along with those of lattice-ordered multi-fuzzy soft isotone map [Formula: see text], lattice-ordered multi-fuzzy soft isomorphism ([Formula: see text]), and kernel of [Formula: see text]. We also look at the principal ideal and soft prime ideal of [Formula: see text].
A finite presentation for the balanced superelliptic handlebody group
Authors: Omori Genki , Yoshida Yuya
Published: November 2023

The balanced superelliptic handlebody group is the normalizer of the transformation group of the balanced superelliptic covering space in the handlebody group of the total space. We give a finite presentation for the balanced superelliptic handlebody group. To give this presentation, we construct a finite presentation for the liftable Hilden group.
Preparation and photocatalytic degradation performance of AgI/4A molecular sieves
Authors: Duan Yaqian , Gao Jianping
Published: November 2023

AgI/4A molecular sieves photocatalysts with different mass ratios were prepared by depositing the silver iodide on the 4A molecular sieve by ion exchange method. When the mass ratio of silver iodide and 4A molecular sieve was 2:1, AgI/4A molecular sieves exhibited enhancing photocatalytic activity than pure AgI and 4A molecular sieves. The degradation rate of methyl orange (MO) dye reached 96.4% at 20 min. The possible mechanism of photodegradation by AgI/4A molecular sieves was proposed.
Studies on ZrO2 nanoparticles for gas sensing application
Authors: Rathod Urjitsinh , Hajra Sumana , Nasit Manas , Zala Vikramsinh , Vachhani Niravkumar , Jethva Sadaf , Savaliya Chirag , Ravalia Ashish , Katba Savan , Solanki Vanaraj
Published: November 2023

Zirconium dioxide (ZrO2) nanoparticles were synthesized using co-precipitation technique and their structural, particle size, UV-Visible (UV–vis), and gas sensing properties were studied. In this paper, the particle size-dependent properties of ZrO2 have been investigated. XRD analysis indicated that the crystal structure of ZrO2 nanoparticles varies with sintering temperature, while crystallite size decreases with an increase in sintering temperature. A small variation in the optical energy band gap is observed in UV–vis spectroscopy. Resistance versus time data was carried out for the gas sensing application, and it was observed that the particle size and nature of the gas play a key role in the sensing of the gases. In the present case, ZrO2 nanoparticles possess more sensitivity to acetone than methanol.
Total chromatic number for certain classes of product graphs
Authors: Sandhiya T. P. , Geetha J. , Somasundaram K.
Published: November 2023

Total coloring is a function that assigns colors to the vertices and edges of the graph such that the adjacent and the incident elements receive different colors. The minimum number of colors required for a proper total coloring of a graph [Formula: see text] is called the total chromatic number of [Formula: see text] and is denoted by [Formula: see text]. Behzad–Vizing conjecture (Total Coloring Conjecture) states that for any graph [Formula: see text], [Formula: see text], where [Formula: see text] is the maximum degree of [Formula: see text]. In this paper, we verify the Behzad–Vizing conjecture for some product graphs.
Superior energy storage performance of BNT-based ferroelectric ceramics based on maintaining high polarization and breakdown strength
Authors: Jiang Mingjia , Peng Zhanhui , Zhou Qiyuan , Wu Di , Wei Lingling , Liang Pengfei , Chao Xiaolian , Yang Zupei
Published: November 2023

Bi[Formula: see text]Na[Formula: see text]TiO3 (BNT)-based lead-free ceramics with superior ferroelectric properties are considered to be extremely advantageous in energy storage capacitors for future green technologies. Here, we demonstrate an approach to achieve both ultrahigh energy density [Formula: see text] and efficiency [Formula: see text] by regulating the multiscale electropolar structures and microstructure. A satisfactory energy storage performance of a high [Formula: see text] of [Formula: see text], and a decent [Formula: see text] of 80% under [Formula: see text] are attained in the 0.5(BNT-CS)-0.5SB[Formula: see text]T ceramic (abbreviated as BNT-0.2SBT). Moreover, BNT-0.2SBT exhibits superior power density ([Formula: see text]), ultrafast discharge time ([Formula: see text][Formula: see text]ns) at [Formula: see text], and good temperature stability. The findings in this work not only demonstrate that a valid candidate, but also provide a new idea of how to achieve both high-energy storage density and efficiency in lead-free ferroelectric materials.
Efficient Maximum k-Defective Clique Computation with Improved Time Complexity
Authors: Chang Lijun
Published: November 2023

k-defective cliques relax cliques by allowing up-to k missing edges from being a complete graph. This relaxation enables us to find larger near-cliques and has applications in link prediction, cluster detection, social network analysis and transportation science. The problem of finding the largest k-defective clique has been recently studied with several algorithms being proposed in the literature. However, the currently fastest algorithm KDBB does not improve its time complexity from being the trivial O(2n), and also, KDBB's practical performance is still not satisfactory. In this paper, we advance the state of the art for exact maximum k-defective clique computation, in terms of both time complexity and practical performance. Moreover, we separate the techniques required for achieving the time complexity from others purely used for practical performance consideration; this design choice may facilitate the research community to further improve the practical efficiency while not sacrificing the worst case time complexity. In specific, we first develop a general framework kDC that beats the trivial time complexity of O(2n) and achieves a better time complexity than all existing algorithms. The time complexity of kDC is solely achieved by our newly designed non-fully-adjacent-first branching rule, excess-removal reduction rule and high-degree reduction rule. Then, to make kDC practically efficient, we further propose a new upper bound, two new reduction rules, and an algorithm for efficiently computing a large initial solution. Extensive empirical studies on three benchmark graph collections with 290 graphs in total demonstrate that kDC outperforms the currently fastest algorithm KDBB by several orders of magnitude.
BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach
Authors: Zheng Zhen , Pan Zaifeng , Wang Dalin , Zhu Kai , Zhao Wenyi , Guo Tianyou , Qiu Xiafei , Sun Minmin , Bai Junjie , Zhang Feng , Du Xiaoyong , Zhai Jidong , Lin Wei
Published: November 2023

Compiler optimization plays an increasingly important role to boost the performance of machine learning models for data processing and management. With increasingly complex data, the dynamic tensor shape phenomenon emerges for ML models. However, existing ML compilers either can only handle static shape models or expose a series of performance problems for both operator fusion optimization and code generation in dynamic shape scenes. This paper tackles the main challenges of dynamic shape optimization: the fusion optimization without shape value, and code generation supporting arbitrary shapes. To tackle the fundamental challenge of the absence of shape values, it systematically abstracts and excavates the shape information and designs a cross-level symbolic shape representation. With the insight that what fusion optimization relies upon is tensor shape relationships between adjacent operators rather than exact shape values, it proposes the dynamic shape fusion approach based on shape information propagation. To generate code that adapts to arbitrary shapes efficiently, it proposes a compile-time and runtime combined code generation approach. Finally, it presents a complete optimization pipeline for dynamic shape models and implements an industrial-grade ML compiler, named BladeDISC. The extensive evaluation demonstrates that BladeDISC outperforms PyTorch, TorchScript, TVM, ONNX Runtime, XLA, Torch Inductor (dynamic shape), and TensorRT by up to 6.95×, 6.25×, 4.08×, 2.04×, 2.06×, 7.92×, and 4.16× (3.54×, 3.12×, 1.95×, 1.47×, 1.24×, 2.93×, and 1.46× on average) in terms of end-to-end inference speedup on the A10 and T4 GPU, respectively. BladeDISC's source code is publicly available at https://github.com/alibaba/BladeDISC.
Efficient Core Maintenance in Large Bipartite Graphs
Authors: Luo Wensheng , Yang Qiaoyuan , Fang Yixiang , Zhou Xu
Published: November 2023

As an important cohesive subgraph model in bipartite graphs, the (α, β)-core (a.k.a. bi-core) has found a wide spectrum of real-world applications, such as product recommendation, fraudster detection, and community search. In these applications, the bipartite graphs are often large and dynamic, where vertices and edges are inserted and deleted frequently, so it is costly to recompute (α, β)-cores from scratch when the graph has changed. Recently, a few works have attempted to study how to maintain (α, β)-cores in the dynamic bipartite graph, but their performance is still far from perfect, due to the huge size of graphs and their frequent changes. To alleviate this issue, in this paper we present efficient (α, β)-core maintenance algorithms over bipartite graphs. We first introduce a novel concept, called bi-core numbers, for the vertices of bipartite graphs. Based on this concept, we theoretically analyze the effect of inserting and deleting edges on the changes of vertices' bi-core numbers, which can be further used to narrow down the scope of the updates, thereby reducing the computational redundancy. We then propose efficient (α, β)-core maintenance algorithms for handling the edge insertion and edge deletion respectively, by exploiting the above theoretical analysis results. Finally, extensive experimental evaluations are performed on both real and synthetic datasets, and the results show that our proposed algorithms are up to two orders of magnitude faster than the state-of-the-art approaches.
Enriching Recommendation Models with Logic Conditions
Authors: Fan Lihang , Fan Wenfei , Lu Ping , Tian Chao , Yin Qiang
Published: November 2023

This paper proposes RecLogic, a framework for improving the accuracy of machine learning (ML) models for recommendation. It aims to enhance existing ML models with logic conditions to reduce false positives and false negatives, without training a new model. Underlying RecLogic are (a) a class of prediction rules on graphs, denoted by TIEs, (b) a new approach to learning TIEs, and (c) a new paradigm for recommendation with TIEs. TIEs may embed ML recommendation models as predicates; as opposed to prior graph rules, it is tractable to decide whether a graph satisfies a set of TIEs. To enrich ML models, RecLogic iteratively trains a generator with feedback from each round, to learn TIEs with a probabilistic bound. RecLogic also provides a PTIME parallel algorithm for making recommendations with the learned TIEs. Using real-life data, we empirically verify that RecLogic improves the accuracy of ML predictions by 22.89% on average in an area where the prediction strength is neither sufficiently large nor sufficiently small, up to 33.10%.
Secure Sampling for Approximate Multi-party Query Processing
Authors: Luo Qiyao , Wang Yilei , Yi Ke , Wang Sheng , Li Feifei
Published: November 2023

We study the problem of random sampling in the secure multi-party computation (MPC) model. In MPC, taking a sample securely must have a cost Ω(n) irrespective to the sample size s. This is in stark contrast with the plaintext setting, where a sample can be taken in O(s) time trivially. Thus, the goal of approximate query processing (AQP) with sublinear costs seems unachievable under MPC. To get around this inherent barrier, in this paper we take a two-stage approach: In the offline stage, we generate a batch of n/s samples with (n) total cost, which can then be consumed to answer queries as they arrive online. Such an approach allows us to achieve an Õ(s) amortized cost per query, similar to the plaintext setting. Based on our secure batch sampling algorithms, we build MASQUE, an MPC-AQP system that achieves sublinear online query costs by running an MPC protocol to evaluate the queries on pre-generated samples. MASQUE achieves the strong security guarantee of the MPC model, i.e., nothing is revealed beyond the query result, which itself can be further protected by (amplified) differential privacy
TeraHAC: Hierarchical Agglomerative Clustering of Trillion-Edge Graphs
Authors: Dhulipala Laxman , Łącki Jakub , Lee Jason , Mirrokni Vahab
Published: November 2023

We introduce TeraHAC, a (1+ε)-approximate hierarchical agglomerative clustering (HAC) algorithm which scales to trillion-edge graphs. Our algorithm is based on a new approach to computing (1+ε)-approximate HAC, which is a novel combination of the nearest-neighbor chain algorithm and the notion of (1+ε)-approximate HAC. Our approach allows us to partition the graph among multiple machines and make significant progress in computing the clustering within each partition before any communication with other partitions is needed.

We evaluate TeraHAC on a number of real-world and synthetic graphs of up to 8 trillion edges. We show that TeraHAC requires over 100x fewer rounds compared to previously known approaches for computing HAC. It is up to 8.3x faster than SCC, the state-of-the-art distributed algorithm for hierarchical clustering, while achieving 1.16x higher quality. In fact, TeraHAC essentially retains the quality of the celebrated HAC algorithm while significantly improving the running time.
An Extractive-and-Abstractive Framework for Source Code Summarization
Authors: Sun Weisong , Fang Chunrong , Chen Yuchen , Zhang Quanjun , Tao Guanhong , You Yudu , Han Tingxu , Ge Yifei , Hu Yuling , Luo Bin , Chen Zhenyu
Published: November 2023

(Source) Code summarization aims to automatically generate summaries/comments for given code snippets in the form of natural language. Such summaries play a key role in helping developers understand and maintain source code. Existing code summarization techniques can be categorized into
extractive methods
and
abstractive methods
. The
extractive methods
extract a subset of important statements and keywords from the code snippet using retrieval techniques and generate a summary that preserves factual details in important statements and keywords. However, such a subset may miss identifier or entity naming, and consequently, the naturalness of the generated summary is usually poor. The
abstractive methods
can generate human-written-like summaries leveraging encoder-decoder models. However, the generated summaries often miss important factual details.

To generate human-written-like summaries with preserved factual details, we propose a novel extractive-and-abstractive framework. The extractive module in the framework performs the task of extractive code summarization, which takes in the code snippet and predicts important statements containing key factual details. The abstractive module in the framework performs the task of abstractive code summarization, which takes in the code snippet and important statements in parallel and generates a succinct and human-written-like natural language summary. We evaluate the effectiveness of our technique, called EACS, by conducting extensive experiments on three datasets involving six programming languages. Experimental results show that EACS significantly outperforms state-of-the-art techniques for all three widely used metrics, including BLEU, METEOR, and ROUGH-L. In addition, the human evaluation demonstrates that the summaries generated by EACS have higher naturalness and informativeness and are more relevant to given code snippets.
(Un)likelihood Training for Interpretable Embedding
Authors: Wu Jiaxin , Ngo Chong-Wah , Chan Wing-Kwong , Hou Zhijian
Published: November 2023

Cross-modal representation learning has become a new normal for bridging the semantic gap between text and visual data. Learning modality agnostic representations in a continuous latent space, however, is often treated as a black-box data-driven training process. It is well known that the effectiveness of representation learning depends heavily on the quality and scale of training data. For video representation learning, having a complete set of labels that annotate the full spectrum of video content for training is highly difficult, if not impossible. These issues, black-box training and dataset bias, make representation learning practically challenging to be deployed for video understanding due to unexplainable and unpredictable results. In this article, we propose two novel training objectives, likelihood and unlikelihood functions, to unroll the semantics behind embeddings while addressing the label sparsity problem in training. The likelihood training aims to interpret semantics of embeddings beyond training labels, while the unlikelihood training leverages prior knowledge for regularization to ensure semantically coherent interpretation. With both training objectives, a new encoder-decoder network, which learns interpretable cross-modal representation, is proposed for ad-hoc video search. Extensive experiments on TRECVid and MSR-VTT datasets show that the proposed network outperforms several state-of-the-art retrieval models with a statistically significant performance margin.
Plastics and the Environment
Authors: Napper I.E. , Thompson R.C.
Published: November 2023

Plastics are persistent and pervasive throughout the environment and have now been reported from the deepest parts of the ocean to the tops of the highest and most remote mountains. There is a body of information on the sources, degradation, and transport of plastics as well as a variety of research investigating the ecotoxicological and wider ecological consequences of plastic ingestion and accumulation. Such knowledge has been obtained with developments in field and laboratory methods for plastic identification and then well-publicized in the media and wider public communications. However, although there has been a large focus on plastic pollution within the past decade, there is plenty that we do not yet know. Even within the past five years, sources of microplastics (1 μm–5 mm) to the environment have been confirmed that had not previously been considered, for example, road paints and tire wear particles. Initial research focused on plastic in the marine environment, but understanding on the accumulation and impacts in terrestrial and freshwater environments is growing. There is a substantial lack of basic science focused on the efficiency of solutions aimed at mitigating plastic pollution. This review highlights some recent (past five years) research on plastics in the environment, including investigations in accumulation, sources, distribution, impacts, solutions and provides directions for future work.
Metrics for Decision-Making in Energy Justice
Authors: Baker Erin , Carley Sanya , Castellanos Sergio , Nock Destenie , Bozeman Joe F. , Konisky David , Monyei Chukwuka G. , Shah Monisha , Sovacool Benjamin
Published: November 2023

Energy equity and justice have become priority considerations for policymakers, practitioners, and scholars alike. To ensure that energy equity is incorporated into actual decisions and analysis, it is necessary to design, use, and continually improve energy equity metrics. In this article, we review the literature and practices surrounding such metrics. We present a working definition for energy justice and equity, and connect them to both criteria for and frameworks of metrics. We then present a large sampling of energy equity metrics, including those focused on vulnerability, wealth creation, energy poverty, life cycle, and comparative country-level dynamics.We conclude with a discussion of the limitations, gaps, and trade-offs associated with these various metrics and their interactions thereof.
Brine: Genesis and Sustainable Resource Recovery Worldwide
Authors: Liu Chenglin , Lowenstein Tim K. , Wang Anjian , Zheng Chunmiao , Yu Jianguo
Published: November 2023

Brine contains cations such as K+, Ca2+, Na+, Mg2+, Li+, B3+, Rb2+, and Cs2+, as well as anions such as SO42−, Cl−, HCO3−, CO32−, NO3−, Br−, and I−, which are valuable elements. Brines are widely distributed in salt lakes in the world's three enormous plateaus and beyond and are classified into three types: sulfate-, chloride-, and carbonate-type brines. Sulfate-type brine forms in salt lakes, whereas carbonate-type brine results from magmatic and hydrothermal activity. Chloride-type brine forms in deep basins due to the reduction and transformation of buried brine. Li in brine plays a critical role in clean energy transitions, and K in brine is important for potash production. Recently, new techniques for extracting Li from brine have been developed, and the large-scale, comprehensive development pattern of brines has formed the basis for a recycling economic model, which contributes to the efficient use of brines for potash and Li2CO3 development and CO2 emission reduction. This article reviews the genesis of brines and highlights new utilization techniques, trends, and sustainable development.
Insight on Surface Changes Post Chemical Mechanical Polishing (CMP) of the Silicon Substrate by Adding Polyoxyethylene Ether
Authors: Wang Xuejie , Wang Chenwei , Zhu Mengya , Zhou Jianwei , Luo Chong , Chen Zhibo , Yang Xiao , Wang Haiying , Zhang Xinying
Published: November 2023

In this study, fatty alcohol polyoxyethylene ether (AEO-9) and isomeric decyl polyoxyethylene ether (XP-70, XP-90) are tested as additives to slurries, aiming to improve the surface quality during Si fine chemical mechanical polishing (CMP) in 14 nm ultra-large-scale integration. Large particle count, contact angle and polishing data reveal that, XP-90 exhibits improved dispersibility and hydrophilicity, reducing the roughness and defects. Various analytical results on silicon surfaces including X-ray photoelectron spectrometry, Fourier transform infrared spectrometry, and scanning electron microscopy data shed new light on the mechanism of the effects of polyoxyethylene ether on silicon CMP. And the surface roughness of Si is also optimized.
A critical discussion on the relationship between E3 ubiquitin ligases, protein degradation, and skeletal muscle wasting: it’s not that simple
Authors: Hughes David C. , Goodman Craig A. , Baehr Leslie M. , Gregorevic Paul , Bodine Sue C.
Published: November 2023

Ubiquitination is an important post-translational modification (PTM) for protein substrates, whereby ubiquitin is added to proteins through the coordinated activity of activating (E1), ubiquitin-conjugating (E2), and ubiquitin ligase (E3) enzymes. The E3s provide key functions in the recognition of specific protein substrates to be ubiquitinated and aid in determining their proteolytic or nonproteolytic fates, which has led to their study as indicators of altered cellular processes. MuRF1 and MAFbx/Atrogin-1 were two of the first E3 ubiquitin ligases identified as being upregulated in a range of different skeletal muscle atrophy models. Since their discovery, the expression of these E3 ubiquitin ligases has often been studied as a surrogate measure of changes to bulk protein degradation rates. However, emerging evidence has highlighted the dynamic and complex regulation of the ubiquitin proteasome system (UPS) in skeletal muscle and demonstrated that protein ubiquitination is not necessarily equivalent to protein degradation. These observations highlight the potential challenges of quantifying E3 ubiquitin ligases as markers of protein degradation rates or ubiquitin proteasome system (UPS) activation. This perspective examines the usefulness of monitoring E3 ubiquitin ligases for determining specific or bulk protein degradation rates in the settings of skeletal muscle atrophy. Specific questions that remain unanswered within the skeletal muscle atrophy field are also identified, to encourage the pursuit of new research that will be critical in moving forward our understanding of the molecular mechanisms that govern protein function and degradation in muscle.
Assessment of Climate Change Impacts and Water Restrictions on Solar Tower Plants
Authors: Marugán-Cruz C. , Fernández-Torrijos M. , Sobrino C. , Santana D.
Published: November 2023

Climate projections under the high-emission representative concentration pathway “RCP-8.5” scenario are used to show the effects of global warming on the energy production of two similar concentrated solar tower power plants in Spain and Chile from 2025 to 2060. Results show a reduction of the annual energy production of almost 1.8% for Chile and an increase of almost 6% in the Spanish plant, but an increase of 10% water consumption due to both the increase in dry- and wet-bulb temperatures and changes in the direct normal irradiation caused by climate change. When the effect of water restrictions is included in the model caused by the foreseen reduction in water availability in Spain, the increase of the annual energy production is only 2%. Finally, the levelized cost of energy (LCOE) calculated during the whole power plant lifetime (35 years) with respect to the LCOE obtained at the beginning of the project is increased by 1.1% in the Chilean plant, whereas in the Spanish plant, it can be reduced more than 2.5% if there are no water restrictions, while a reduction of 0.4% is expected in a scenario with water restrictions. Results show that careful consideration of climate projections should be considered to properly estimate the economic viability of solar tower plants.
Evaluation of the Effects of Different Types of Resin Cement Systems on the Push-Out Bond Strength of the Fiber Post to Intracanal Dentin in Anterior Primary Teeth
Authors: Nozari Ali , Rasoolzade Boshra , Jowkar Zahra , Hamidi Seyed Ahmadreza , Jowkar Mohammad
Published: November 2023

Background. This study aimed to evaluate the effects of using three different resin cements on push-out bond strength (PBS) of fiber posts to root canal dentin of primary teeth. Methods. Fifty primary canines were randomly divided into five experimental groups according to the type of the luting agent used for fiber post cementation after endodontic treatment and post space preparation as the following: Group 1: glass ionomer cement (GIC), Group 2: flowable resin composite, Group 3: etch and rinse (E&R) resin cement, Group 4: self-etch (SE) resin cement, Group 5: self-adhesive (SA) resin cement. The PBS values of the cemented fiber posts to root canals were measured. The data were statistically analyzed using a one-way analysis of variance, followed by Tukey’s post hoc test. Results. The highest mean PBS value was observed in Group 4 (SE resin cement), followed by Group 3 (E&R resin cement), and the lowest PBS value belonged to Group 1 (GIC), followed by Group 5 (p-values < 0.05). The mean PBS of Group 3 (E&R resin cement) was significantly higher than those of Groups 1 (GIC), 2 (flowable resin composite), and 5 (SA resin cement) (p-values < 0.05). However, no significant difference was found between the mean PBS of GIC and SA resin cement (p-value >0/05). Conclusion. Using SE resin cement for fiber post cementation in primary anterior teeth showed the best results, followed by E&R resin cement. The lowest PBS was observed for GIC, followed by SA resin cement.
Bayesian Estimation of the Stress-Strength Reliability Based on Generalized Order Statistics for Pareto Distribution
Authors: Ezmareh Zahra Karimi , Yari Gholamhossein
Published: November 2023

The aim of this paper is to obtain a Bayesian estimator of stress-strength reliability based on generalized order statistics for Pareto distribution. The dependence of the Pareto distribution support on the parameter complicates the calculations. Hence, in literature, one of the parameters is assumed to be known. In this paper, for the first time, two parameters of Pareto distribution are considered unknown. In computing the Bayesian confidence interval for reliability based on generalized order statistics, the posterior distribution has a complex form that cannot be sampled by conventional methods. To solve this problem, we propose an acceptance-rejection algorithm to generate a sample of the posterior distribution. We also propose a particular case of this model and obtain the classical and Bayesian estimators for this particular case. In this case, to obtain the Bayesian estimator of stress-strength reliability, we propose a variable change method. Then, these confidence intervals are compared by simulation. Finally, a practical example of this study is provided.
Islanding Event Detection in Grid-Connected Distributed Generation Systems Using Unscented Kalman Filter
Authors: Singh Nivedita , Ansari M. A. , Tripathy Manoj , Gupta Pratiksha , Ali Ikbal , Alward Yahya , Rawea Adel
Published: November 2023

A pressing concern in modern smart grid systems revolves around islanding, leading to unpredictable system parameters and a decline in power quality. In response to this concern, we introduce a novel passive method for identifying islanding in grid-connected distributed generation units. This method utilizes the unscented Kalman filter (UKF) to assess the voltage signal captured at the DG position. The triphase voltage signal observed at the point of common coupling (PCC) is used as the test signal. The UKF extracts and filters the harmonic content of the voltage signal to produce a residual signal, which detects changes in the power system. The estimation of total harmonic distortion (THD) follows, and its fluctuations help discern between islanding and typical events. This suggested approach undergoes assessment through a test system simulated in MATLAB/Simulink across different situations. Outcome findings underscore the efficacy of the suggested approach in distinguishing between islanding and regular occurrences, ensuring enhanced reliability and resilience against incorrect operations by removing the zone of nondetection. In our detailed experiments, we found that the proposed unscented Kalman filter (UKF) technique improved islanding detection accuracy by approximately 90% over traditional methods, under varied conditions. Specifically, the nondetection zone (NDZ) was reduced by 95% when compared to the most commonly used passive methods. Furthermore, in scenarios with high harmonic content and noise, the UKF showcased a 90% improvement in reliability over conventional techniques.
Calorie Labeling Impact on Consumers Who Understand Their Calorie Needs: A Cross-Sectional Study
Authors: Albugmi Mutlaq , Alsaheil Nouf , Alahmed Zahra
Published: November 2023

Introduction: Saudi Arabia has an obesity prevalence of 38.96%, ranking 15th globally. The increasing prevalence of obesity has motivated Saudi Arabian health policymakers to develop national strategies to prevent or reduce the anticipated increase in cases. Therefore, the Food and Drug Authority has recently enacted compulsory calorie labeling on the menus of all food industry providers who provide food and drinks to consumers outside their homes. This study aimed to determine whether calorie labeling on fast-food restaurant menus helps consumers make informed decisions about their food consumption. Methods: This cross-sectional study conducted in Saudi Arabia between April and October 2022 employed a self-reported online survey to investigate the influence of caloric labeling on residents’ food-ordering decisions and to determine the effects of the independent variables on calorie requirement knowledge. Participants included Arabic- and English-speaking adults residing in different regions of Saudi Arabia. Data collection utilized a river sampling technique, employing social media platforms for survey distribution. The inclusion criteria encompassed adult Saudi residents exposed to calorie labels, while those who did not encounter such labels were excluded. Results: This study aimed to examine the factors influencing individuals’ food choices and their knowledge of daily calorie requirements. A social media advertisement was used to recruit 935 participants, with 760 included in the final analysis. Descriptive statistics revealed that the mean age of participants was 37.5 years, with 61.1% being female. Moreover, 59.3% reported having a college degree, and the mean monthly income was SAR 7,725. Logistic regression analysis demonstrated that knowing the daily calorie requirements significantly influenced food choices, with individuals who knew their calorie needs being four times more likely to use calorie labels when selecting food. However, other independent variables were found to be statistically insignificant. Additionally, age and citizenship status were significantly associated with knowledge of calorie requirements, with the 18–29 age group and Saudi Arabian citizens showing higher knowledge levels. Discussion: The findings of this study may catalyze further research aimed at measuring and understanding other variables that may impact consumer choices, such as pictures and font sizes, and understanding consumer knowledge and awareness of daily calorie requirements.
Humoral immunity is not altered in overweight pregnant Crioulo mares
Authors: Mousquer Mariana Andrade , Moraes Bruna dos Santos Suñe , Santos Alice Corrêa , Souza Rafaela Pinto de , Lima Marcelo de , Rodrigues Paulo Ricardo Centeno , Curcio Bruna da Rosa , Nogueira Carlos Eduardo Wayne
Published: November 2023

Both pregnancy and obesity can influence significant changes in the immune system. On this basis, the present study proposes to evaluate the humoral immune response of overweight pregnant mares in response to a commercial vaccine. Thirty pregnant Crioulo mares were separated according to body condition score (BCS) into overweight (BCS≥7/9) or lean-control (BCS= 5-6/9). In each group, the animals were subdivided into vaccinated and controls. The mares were vaccinated against EHV-1 in two doses spaced 21 days apart and had their blood collected monthly, for five months, for antibody evaluation. Both vaccinated groups had an increase in specific neutralizing antibodies after the vaccine. However, after the second dose, there was no increase in antibodies in any of the groups. Vaccinated overweight and lean-control mares did not differ at any time point. Therefore, this study demonstrated that obesity does not influence the humoral immune response in pregnant Crioulo mares.
O Protocolo de Madri para o registro internacional de marcas
Authors: Silveira Newton , Santos Jr. Walter Godoy dos
Published: November 2023

O presente artigo trata do percurso histórico do Acordo de Madri, desde o seu surgimento, passando pela adesão e pela denúncia promovidas pelo Brasil, até se chegar ao ano de 2019, em que novamente o país passa a participar efetivamente do sistema administrado pela Organização Mundial da Propriedade Intelectual para o registro internacional de marcas. A análise do percurso histórico em apreço é secundada pela constatação de que se trata de um diploma internacional que cuida de um fluxo unificado para o depósito simultâneo de marcas em diversos países, sem prejuízo da aplicação da legislação interna sobre a matéria de cada Estado-Membro. Nesse sentido, eventuais antinomias são resolvidas em favor da Lei Brasileira de Propriedade Industrial (Lei n. 9.279/1996), sobretudo quanto à necessidade de se manter no país um advogado com poderes para receber citação. Por fim, segue um exame geral da aplicação do Protocolo no Brasil por meio da Resolução INPI/PR n. 247/2019 e a conclusão no sentido de que a adoção pelo Brasil do Acordo, do Protocolo e do Regulamento de Madri para o registro de marcas, bem como a elaboração de atos normativos que permitam colocar essas regras procedimentais internacionais em movimento no Brasil, representam importantes balizas para que se possa atingir os ideais do legislador constitucional originário e fazer da Propriedade Industrial um vetor do desenvolvimento social, tecnológico e econômico do Brasil, consoante o disposto no art. 5º, XXIX, da Carta da República.
Direito Internacional entre voluntarismo e jus cogens: os acordos bilaterais de imunidade e a jurisdição do Tribunal Penal Internacional
Authors: Casella Paulo Borba
Published: November 2023

O Direito Internacional, entendido quer como expressão da vontade dos estados – voluntarismo –, quer como conjunto de princípios e normas vinculantes – jus cogens – é questão crucial para determinar seu conteúdo e alcance. O Estatuto de Roma, que criou o Tribunal Penal Internacional (TPI) constitui passo relevante no sentido de fortalecer o conteúdo institucional; enquanto os Acordos bilaterais de imunidade de jurisdição, para excluir a jurisdição do TPI tentam retornar a visão obsoleta de Direito Internacional voluntarista, regido pelas principais potências, como no passado – antes jogo político e de equilíbrio de poder do que conjunto de princípios e normas gerais de Direito Internacional, vinculantes para toda a sociedade internacional.
Por um direito universal da humanidade
Authors: Lima Sérgio Eduardo Moreira
Published: November 2023

O artigo é uma homenagem a Antônio Cançado Trindade, jurista, professor e magistrado brasileiro, como parte da reflexão sobre a importância de seu pensamento e de seu legado. Ao situá-lo dentro das tradições e da doutrina latino-americana e no direito internacional contemporâneo, busca-se estabelecer diferenças e explicar o reconhecimento internacional de sua obra, considerada original e inovadora. Inspirado em concepções jusnaturalistas, dedicou sua vida à humanização e à universalização do Direito Internacional, colocando a pessoa humana em lugar antes ocupado apenas pelo Estado. Sua crítica ao positivismo justifica-se ainda mais diante do reiterado abuso da força em conflitos, como o da invasão do Iraque, em 2003, ou a guerra da Rússia na Ucrânia, em 2022, com a anexação de territórios, ao arrepio da lei. As ameaças de Moscou de uso de armas de destruição em massa mostram a atualidade do voto dissidente do jurista na Corte Internacional de Justiça e sua brilhante defesa da Obrigação Universal do Desarmamento Nuclear. Foi o único internacionalista latino-americano a ser consagrado pela prestigiosa coleção Doctrine(s), em 2012, com edição sobre a importância de seu pensamento. Ficou ali reconhecido de forma eloquente o que Cançado Trindade representa: a defesa da ideia de que o direito internacional não é aquele baseado na vontade dos estados soberanos, ao qual se quis tantas vezes e por tanto tempo reduzir, mas o que se está tornando de forma irresistível, no que ele deveria ter sido sempre: um direito universal da humanidade, no qual a pessoa humana deve ser o beneficiário último (JOUANNET, 2012).