Search

The coordinated optimization of energy conservation, efficiency improvement, and pollution reduction in the sintering production process is vital for the efficient and sustainable development of the sintering department. However, previous studies have shown shortcomings in the multi-objective collaborative optimization of sintering systems and the quantification of pollutant impacts. To address these, this paper proposes a multi-objective optimization method integrated with the NSGA-III algorithm and establishes an integrated system optimization model for sintered ore production and high-temperature waste heat recovery. The results demonstrate significant improvements: energy utilization efficiency increased by 0.67%, energy consumption decreased by 17.3 MJ/t, production costs were reduced by 11.45 CNY/t, and the emissions of CO2, SO2, and NOx were reduced by 0.464 kg/t, 0.034 kg/t, and 0.008 kg/t, respectively. Additionally, the study identified optimal configuration parameters and analyzed the quantitative impact of several key factors on multiple indicators. The results also show that reducing the water content of the mixture, decreasing the middling coal content in the fuel, and increasing the thickness of the material layer are effective strategies to reduce energy consumption and pollutant emissions in the sintering process. Overall, implementing these optimizations can bring significant economic and environmental benefits to the steel industry. [ABSTRACT FROM AUTHOR]

Background: Esketamine, the first Food and Drug Administration-approved fast-acting antidepressant, has limited use because of its addictive properties. Although the combination of dextromethorphan and bupropion partially addresses the limitations of esketamine, concerns remain regarding neurologic side effects related to dextromethorphan metabolites, and seizure risks associated with high-dose bupropion. SAL0114, a novel formulation combining deuterated dextromethorphan (in which hydrogen atoms are replaced with deuterium) with bupropion, seeks to enhance dextromethorphan stability through deuteration of its metabolic sites. This approach is expected to increase antidepressant efficacy, reduce metabolite-induced safety issues, and allow for lower bupropion dosages. Methods: Radioligand competition binding assays were used to evaluate the impact of deuterium substitution on the in vitro activity of dextromethorphan and its metabolite, dextrorphan. In vitro hepatic microsomal stability and in vivo mouse pharmacokinetic assays were performed to assess the effects of deuteration on dextromethorphan stability. Two mouse models of behavioral despair were used to determine the antidepressant and synergistic effects of deuterated dextromethorphan and bupropion. Additionally, a reserpine-induced hypothermia rat model and an ammonia-induced cough mouse model were used to assess the in vivo effects from a pathological perspective. Results: Deuterated dextromethorphan maintained the same in vitro activity as dextromethorphan while exhibiting twice the metabolic stability both in vitro and in vivo. Combination with bupropion further improved its in vivo stability, increasing the exposure by 2.4 times. The combination demonstrated efficacy and synergistic effects in all tested animal models, showing superior efficacy compared with the dextromethorphan-bupropion combination. Conclusion: Deuteration improved dextromethorphan metabolic stability without altering its in vitro activity. Bupropion enhanced this stability and synergistically boosted the antidepressant effect by increasing deuterated dextromethorphan exposure in vivo. This enhanced metabolic stability suggests a reduction in dextromethorphan metabolites associated with clinical neurological side effects. Consequently, SAL0114 is hypothesized to offer improved efficacy and safety compared with the non-deuterated combination, potentially allowing for lower bupropion dosages. Further clinical studies are required to confirm these preclinical findings. [ABSTRACT FROM AUTHOR]

To meet the carbon–neutral goal in 2050, an accelerated transition of decarbonization is needed in the iron and steel industry. Lots of decarbonization path models are recently being used to analyze the technology pathways, industrial structure adjustments, and short- or long-term policies for greenhouse gas emission reduction. Thus, systematic insight is required for better making sense of the status quo and differences in low-carbon transition pathways at different levels. This paper reviews the carbon emission reduction of steel production routes and summarizes the decarbonization models from micro-, meso-, and macro-level perspectives, respectively. First, we systematically analyze the capacity and potential of both available and emerging technologies in the iron and steel production process. Additionally, we conduct a theoretical analysis of the bottom-up models currently used as effective tools to assess decarbonization technology pathways. Subsequently, pathways and models in terms of industrial synergy are elaborated. Policy guidance and market support are explored to overcome the challenges of collaborative carbon reduction faced by global steel producers. The characteristics of top-down models for supporting carbon reduction are also discussed. Finally, gaps in the literature and future research agendas are identified. Advancing this research could enrich discussions on steel industry decarbonization and provide clearer assessments of modeling approaches. The results indicate that existing energy-saving technologies in the iron and steel industry have limited carbon reduction capacity. Significant reduction requires coordinated efforts with upstream and downstream industries, particularly in hydrogen and power sectors, along with financial support and favorable policies. [ABSTRACT FROM AUTHOR]

To analyze the influence of diabetes mellitus on the clinical outcomes of moderately severe acute pancreatitis (MSAP) and severe acute pancreatitis (SAP). Methods: This retrospective study included patients diagnosed with MSAP and SAP at Shanxi Bethune Hospital from January 1, 2017, to December 31, 2021. Clinical data were collected, including patient demographics, 24-hour laboratory indicators, and inflammation indices. Propensity score matching (PSM) was used to compare outcomes before and after matching. Patients were randomized into training and validation sets (7:3) to develop and validate a clinical prediction model for infected pancreatic necrosis (IPN). Results: Among 421 patients, 79 had diabetes at admission. Before PSM, diabetic patients had higher incidences of peripancreatic fluid (71% vs 47%, p< 0.001) and IPN (48% vs 10%, p< 0.001), higher surgical intervention rates (24% vs 12%, p=0.008), and significant differences in abdominocentesis (22% vs 11%, p=0.014). After PSM, 174 patients were matched, and the diabetes group still showed higher incidences of peripancreatic fluid (69% vs 47%, p=0.008), IPN (48% vs 11%, p< 0.001), and surgical intervention rates (27% vs 13%, p=0.037). Diabetes, modified CT severity index (MCTSI), serum calcium, and HDL-c were identified as independent risk factors for IPN. The prediction model demonstrated good predictive value. Conclusion: In MSAP and SAP patients, diabetes mellitus can exert an influence on their clinical outcome and is an independent risk factor for IPN. The alignment diagram and web calculator constructed on the basis of diabetes mellitus, modified CT severity index (MCTSI), serum calcium and high-density lipoprotein cholesterol (HDL-c) have good predictive value and clinical guidance for the occurrence of IPN in MSAP and SAP. [ABSTRACT FROM AUTHOR]

Exploring theoretical energy consumption introduces a fresh perspective for energy-saving research within the iron and steel industry, with a primary focus on the energy expended during material transformation. Building upon the theory of theoretical energy consumption, this study meticulously investigates the theoretical energy consumption associated with each stage of the iron and steel making process, including coking, sintering, pelletizing, ironmaking, steelmaking, and hot rolling. The findings reveal that, under specific conditions, the theoretical energy consumption for each process is as follows: coking (2.59 GJ), sintering (1.36 GJ), pelletizing (1.02 GJ), ironmaking (8.81 GJ), steelmaking (−0.16 GJ), and hot rolling (0.76 GJ). Additionally, this study delves into the analysis of influencing factors on theoretical energy consumption. Using the coking process as an illustrative example, it is observed that the theoretical energy consumption in coking decreases with a reduction in both moisture and volatile content in coal. Under the specified conditions, the minimum theoretical energy consumption for each process is as follows: coking (2.51 GJ), sintering (0.98 GJ), pelletizing (0.67 GJ), ironmaking (8.38 GJ), steelmaking (−0.58 GJ), and hot rolling (0.07 GJ), respectively. This comprehensive analysis serves as a valuable resource for advancing sustainable practices in the iron and steel industry. [ABSTRACT FROM AUTHOR]

The surface subsidence under ultra-thick weakly cemented overburden exhibits the abnormal characteristics of being seriously small, which brings serious safety hazard to the efficient mining. A comprehensive analysis of the causes behind the abnormal surface deformation characteristics under ultra-thick weakly cemented overburden was undertaken through theoretical analysis and numerical simulation. The results indicated that when the mining degree exceeded the critical value (900 m), the fracture of the super-thick and weakly consolidated overburden occurred. At this point, the energy was rapidly dissipated, and the surface subsidence suddenly increased. Against this backdrop, a novel regional strata movement control method for the high-intensity and safe mining of super-thick and weakly consolidated overburden is proposed. It could provide technical support for the high-intensity and safe mining of the super-thick and weakly consolidated overburden. [ABSTRACT FROM AUTHOR]

Purpose: Acute pancreatitis is a common gastrointestinal emergency. Approximately 20% of patients with acute pancreatitis develop organ failure, which is significantly associated with adverse outcomes. This study aimed to establish an early prediction model for persistent organ failure in acute pancreatitis patients using 24-hour admission indicators. Patients and Methods: Clinical data and 24-h laboratory indicators of patients diagnosed with acute pancreatitis from January 1, 2017 to January 1, 2022 in Shanxi Bethune Hospital were collected. Patients from 2017 to 2021 were used as the training cohort to establish the prediction model, and patients from 2021 to 2022 were used as the validation cohort. Univariate logistic regression and LASSO regression were used to establish prediction models. The performance of the model was evaluated using area under the curve (AUC), calibration curves, and decision curve analysis (DCA), and subsequently validated in the validation group. Results: A total of 1166 patients with acute pancreatitis were included, a total of 145 patients suffered from persistent organ failure from 2017 to 2021. Data were initially selected for 100 variables, and after inclusion and exclusion, 46 variables were used for further analysis. Two prediction models were established and nomogram was drawn respectively. After comparison, the prediction values of the two models were similar (The univariate model AUC was 0.867, 95% CI (0.834– 0.9). The LASSO model AUC was 0.864, 95% CI (0.828– 0.895)), and the model established by LASSO regression was more parsimonious. A web calculator was developed using the model established by LASSO. Conclusion: Predictive model including 6 risk indicators can be used to predict the risk of persistent organ failure in patients with acute pancreatitis. [ABSTRACT FROM AUTHOR]

Liver cancer is one of the most common malignant tumors in the world, and its incidence and mortality are increasing year by year. The prognosis of liver cancer depends on the stage of liver cancer, the treatment method, the liver function, and individual differences. The prognosis of liver cancer mainly worsens with the progression of the stage. The prediction and staging system of liver cancer prognosis plays a very important role in the outcome of liver cancer prognosis, providing some guidance for clinical practice and bringing benefits for patients. This article reports on the prediction models and staging systems that have been applied in the field of liver cancer in the past 5 years, objectively analyzes the advantages and disadvantages, applicable population of each model and staging system, and searches for other patient and clinical characteristics that need to be considered for successfully establishing a prediction model, aiming to improve the specificity, sensitivity, and accuracy of liver cancer prediction and increase the overall survival rate of liver cancer. [ABSTRACT FROM AUTHOR]

Heterogeneous N-heterocyclic carbene materials have attracted increasing interest in the fields of materials science and catalysis due to their unique properties and potential applications. However, current heterogeneous systems primarily focus on a single class of carbene. In this work, we simultaneously introduce two classes of typical five-membered carbenes into a graphene lattice, forming a series of novel two-dimensional heterogeneous N-heterocyclic carbene nanomaterials (2D-NCMs) composed of multiple carbenes. First-principles calculations demonstrate the thermodynamic stability of the designed 2D-NCMs, as well as their diverse electronic properties ranging from metallic to semiconducting. The incorporation of carbenes in the 2D-NCMs enables them to adsorb both acidic BCl3 and basic CO molecules, thus exhibiting unique amphoteric properties. Furthermore, the 2D-NCMs exhibit remarkable adsorption capacities for ten transition metals, highlighting their promising potential for future catalytic applications. By adjusting the proportions of the two classes of carbenes, we can effectively regulate the electronic properties and adsorption capacities of small molecules and transition metals in the 2D-NCMs. This study presents a novel strategy for designing and regulating the properties of heterogeneous N-heterocyclic carbenes, offering significant implications in the fields of catalysis and materials science. [ABSTRACT FROM AUTHOR]

Allisartan isoproxil (AI) is an angiotensin II type 1 receptor blocker and be converted into the active substance EXP3174 in vivo. We evaluated the drug–drug interactions of AI and an indapamide sustained‐release (Ind SR) preparation, as well as the pharmacokinetic characteristics and safety of AI and Ind SR in healthy subjects. The trial was set up in 6 sequences and 3 cycles, and each cycle contained a 7‐day washout period. Subjects received 3 different trial drugs (A, AI; B, Ind SR; C, AI + Ind SR) during 3 different cycles. Twenty‐four subjects were enrolled in the clinical trial. Of these, 22 completed the study, 2 subjects dropped out due to adverse events (AEs). For subjects given AI alone or combined with Ind SR, the pharmacogenetic parameters Cmax and the geometric mean ratio of steady state (combined/single) of EXP3174 was 130%. The geometric mean ratio of area under the concentration–time curve over the dosing interval at steady state (combined/single use) was 144.5%. Therefore, the combination of Ind SR had an impact on the pharmacokinetics of AI. Then, the results indicated that the AI combination had no effect on the pharmacokinetics of Ind SR. Serious AEs did not occur. The AEs in this clinical trial were the same as those for AI and Ind SR. Combined administration resulted in 2 cases (2 subjects) of Grade 3 hypotension and 1 case of Grade 3 hypotension with AI alone. Considering that this trial included healthy volunteers, the risk of hypotension was expected to be manageable. [ABSTRACT FROM AUTHOR]

We introduce a new family of probability distributions that we call the Modified-Half-Normal distributions. It is supported on the positive part of the real line with its probability density proportional to the function x ↦ x α − 1 exp (− β x 2 + γ x) I (x > 0) , α > 0 , β > 0 , γ ∈ R. We explore a number of its properties including showing the fact that the normalizing constant and moments of the distribution can be represented in terms of the Fox-Wright function. We demonstrate its relevance by showing its connection to a number of Bayesian statistical methods appearing from multiple areas of research such as Bayesian Binary regression, Analysis of Directional data, and Bayesian graphical model. The availability of its efficient sampling scheme is important to the success of such Bayesian procedures. Therefore, a major focus of this article is the development of methods for generating random samples from the Modified-Half-Normal distribution. To ensure efficiency, we prove that the constructed accept reject algorithms are "uniformly efficient" with high acceptance probability irrespective of the choice of the parameter specifications. Finally, we provide basic inference procedure for its parameters when analyzing data assuming the Modified-Half-Normal probability model. [ABSTRACT FROM AUTHOR]

To solve the unreasonable energy distribution and excessive energy waste in the steam system of iron and steel (I&S) industry, a mixed integer linear programming model based on the theory of exergy and energy level is developed in this study to optimize the steam system. After optimization, the utilization potential of waste energy is found. Then, several waste energy recovery technologies are compared according to their application results. The results show that the exergy efficiency of steam system is 74.065%. After optimization, the exergy efficiency of steam system is increased by 10.568%, the energy input of the I&S enterprise is reduced by 84.30 MJ t−1‐CS−1, and waste energy potential is found at hot rolling, sintering, and converter. Herein, flue gas waste heat from hot rolling and sintering is recovered using series two‐stage Organic Rankine Cycle with cyclopentane as the working fluid, and steam waste energy from converter is recovered using saturated steam power generation. These waste energy technologies increase the electricity generation of I&S enterprise by 15.25 kWh t−1‐CS−1. Overall, combining the optimization model with the use of waste energy recovery technologies is necessary and effective for I&S enterprise to increase their energy efficiency. [ABSTRACT FROM AUTHOR]

Background: The assembly of metagenomes decomposes members of complex microbe communities and allows the characterization of these genomes without laborious cultivation or single-cell metagenomics. Metagenome assembly is a process that is memory intensive and time consuming. Multi-terabyte sequences can become too large to be assembled on a single computer node, and there is no reliable method to predict the memory requirement due to data-specific memory consumption pattern. Currently, out-of-memory (OOM) is one of the most prevalent factors that causes metagenome assembly failures. Results: In this study, we explored the possibility of using Persistent Memory (PMem) as a less expensive substitute for dynamic random access memory (DRAM) to reduce OOM and increase the scalability of metagenome assemblers. We evaluated the execution time and memory usage of three popular metagenome assemblers (MetaSPAdes, MEGAHIT, and MetaHipMer2) in datasets up to one terabase. We found that PMem can enable metagenome assemblers on terabyte-sized datasets by partially or fully substituting DRAM. Depending on the configured DRAM/PMEM ratio, running metagenome assemblies with PMem can achieve a similar speed as DRAM, while in the worst case it showed a roughly two-fold slowdown. In addition, different assemblers displayed distinct memory/speed trade-offs in the same hardware/software environment. Conclusions: We demonstrated that PMem is capable of expanding the capacity of DRAM to allow larger metagenome assembly with a potential tradeoff in speed. Because PMem can be used directly without any application-specific code modification, these findings are likely to be generalized to other memory-intensive bioinformatics applications. [ABSTRACT FROM AUTHOR]

Background Little is known about the distribution of antibiotic use in individual children over time. The amoxicillin index is a recently proposed metric to assess first-line antibiotic prescribing to children. Methods We constructed a cohort of continuously enrolled Medicaid children using enrollment claims from 2012 to 2017. Pharmacy claims were used to identify antibiotic prescription data. Results Among 169 724 children with 6 years of Medicaid enrollment, 10 804 (6.4%) had no antibiotic prescription claims during the study period; 43 473 (25.6%) had 1-3 antibiotics; 34 318 (20.2%) had 4-6 antibiotics; 30 994 (18.3%) had 7-10; 35 018 (20.6%) had 11-20; and 15 117 (8.9%) children had more than 20 antibiotic prescriptions. Overall, the population had a median total of 6 antibiotic prescriptions during the study period, but use was higher in certain patient groups: younger age (8 antibiotic fills over the 6-year period, [IQR 4-14]), White children (7 [IQR 3-13], compared to 3 [IQR 1-6] in Black children), rural settings (9 [IQR 4-15]) and chronic conditions (8 [IQR 4-15]). Higher-use groups also had lower rates of amoxicillin fills, reported as amoxicillin indices. Conclusions Antibiotic use is common among most children insured by Kentucky Medicaid. A number of fills over time were higher in younger children, and in White children, children living in rural settings and children with chronic conditions. Patients with higher recurrent antibiotic use are important targets for designing high-impact antibiotic stewardship efforts. [ABSTRACT FROM AUTHOR]

To demonstrate the effect of body posture on the occupant dynamic response under a spacecraft high-level re-entry acceleration overload, seat-dummy system models with typical body positions, including supine and lying positions, are established in this study using Pro-E and HyperWorks software. A Human Model for Safety (HUMOS version II) dummy was used in the model. Seat-dummy system models were calibrated and validated according to actual centrifugal test data. The effect of body posture on the overload response of key body organs, including the heart, lung, diaphragm, liver, and abdominal viscera are demonstrated and analyzed under a high-level acceleration overload (a peak value of 6.4 g as input). Simulation results show that the displacement and deformation of the diaphragm are the most important factors affecting human tolerance to re-entry overload. The acting force of the diaphragm from other organs' inertial reaction in supine position is larger than that in the lying position. Therefore, spacecraft designers should focus more on the mechanical status of human internal organs and provide a body posture for better protection of the crew during spacecraft re-entry. [ABSTRACT FROM AUTHOR]

Allisartan isoproxil (AI) is a blocker of the angiotensin II type 1 receptor. We evaluated the safety and pharmacokinetics of single‐ and multiple‐dose AI in healthy Chinese individuals. Participants were assigned to receive AI or placebo. Plasma concentration of EXP3174 (carboxylic acid derivative) was measured using liquid chromatography‐tandem mass spectrometry. Pharmacokinetic parameters were determined by noncompartmental methods. Twelve subjects were enrolled, and the ratio of men to women was 5:1. Main pharmacokinetic parameters of EXP3174 after single and multiple doses of AI were a mean maximum concentration in plasma (Cmax) of 2242 ± 1037 ng/mL and median time to reach Cmax (Tmax) of 3.5 hours (2.5‐8 hours). The median Tmax, at steady state was 4.0 hours (1.5‐8 hours). The mean Cmax at steady state (Cmax, SS) was 2047 ± 1050 ng/mL. In terms of EXP3174, there was no significant difference in the Cmax, SS, area under the curve from time zero to 24 hours of quantifiable concentration at steady state (AUC0–24 SS), and AUC0‐72 after multiple doses of AI. Serious adverse events did not occur. These data suggest that AI is safe and well tolerated in healthy Chinese individuals at a single dose of 480 or 480 mg once daily for 7 days. [ABSTRACT FROM AUTHOR]

Brain tumors are one of the most serious brain diseases, which often result in a short life. However, in developing areas, medical resources are in shortage, which affect the diagnosis of brain tumors. With the development of computer science, many diseases can be diagnosed by telemedicine systems, which help physicians save much time and improve diagnostic accuracy. Therefore, we propose a semantic segmentation method for brain tumors based on nested residual attention networks. It can be deployed in social mx'edia environment to work as a remote diagnosis system. The proposed method uses an improved residual attention block (RAB) as the basic unit. Based on the improved RAB, a nested RAB is designed to build the proposed method, which has better generalization. The proposed method includes an encoder part, a decoder part and skip connections. The encoder part learns multiple feature representations from inputs and the decoder part utilizes the learnt features to make segmentation predictions. In addition, high-level attention feature maps are exploited to induce low-level feature maps in skip connections to discard useless information. The proposed method is mainly validated on the dataset of Brain Tumor Segmentation challenge (BraTS) 2015. The proposed method achieves an average dice score of 0.87 (0.80, 0.72) for the whole tumor (core tumor, enhancing tumor) regions on BraTS 2015 dataset. [ABSTRACT FROM AUTHOR]

Application of energy saving and consumption reduction technologies in the iron and steel industry (ISI) is an effective way to achieve sustainable development. As the highly energy‐consuming ironmaking system is an important part of steel production, reducing its exergy loss is of great significance for overall energy saving in ISI. The optimization model of the ironmaking system is established in this study based on the law of conservation of mass and the second law of thermodynamics. For the target of minimum exergy loss, material and energy systems of ironmaking are optimized and analyzed. Factors that influence the ironmaking system are further discussed. The results show that the minimum exergy loss of the ironmaking system is 4605.80 MJ t‐HM−1 by improving operation conditions. Among them, 51.15% of the total exergy loss is contributed by the blast furnace ironmaking process. [ABSTRACT FROM AUTHOR]

Background: Kentucky has among the highest rate of attention deficit/hyperactivity disorder (ADHD) and stimulant use in the United States. Little is known about this use by race/ethnicity and geography. This article describes patterns of diagnosis of ADHD and receipt of stimulants and psychosocial interventions for children aged 6-17 years receiving Kentucky Medicaid in 2017 and identifies factors associated with diagnosis and treatment.Methods: Using Medicaid claims, children with and without ADHD (ICD-10 codes F90.0, F90.1, F90.2, F90.8, and F90.9) were compared and predictors of diagnosis and treatment type were examined. Psychosocial interventions were defined as having at least one relevant CPT code. Chi-squared tests and logistic regression models were used for univariate and multivariable analysis, respectively.Results: The rates of ADHD, stimulant use, and psychosocial interventions in our study population exceeded the national average (14% vs 9%; 75% vs 65.5%; and 51% vs 46.5%, respectively). The distributions varied by sex, race/ethnicity, sex among race/ethnicities, and population density. In general, race/ethnicity predicted ADHD diagnosis, stimulant use, and receipt of psychosocial interventions with non-Hispanic White children being more likely to receive diagnosis and medication, but less likely to receive psychosocial therapy than other children. Differences were also shown for rural compared with urban residence, sex, and sex within racial/ethnic groups.Conclusions: Diagnosis and treatment modalities differed for children by race/ethnicity, population density, and sex. More data are needed to better understand whether differences are due to provider bias, child characteristics, or cultural variations impacting the utilization of different treatment options. [ABSTRACT FROM AUTHOR]

Evaluating the energy efficiency of the iron and steel smelting route is of vital significance to achieve energy saving and consumption reduction. By establishing an input‐use‐end model, a new index is put forward herein to evaluate the energy utilization of the iron and steel smelting route—energy utilization efficiency. Furthermore, energy utilization efficiency of a typical iron and steel smelting route is analyzed based on the established network diagram. The results show that 1) the cleaned coal is the largest energy input in the whole route, which is 14 460.4 MJ, followed by injected coal. 2) About 57.6% of primary energy is converted into byproduct gases and 31.7% of that is converted into various waste heats. 3) The energy loss of the whole route is 9583.8 MJ, of which the direct loss, indirect loss, and internal loss are 2630.8, 5366.9, and 1586.1 MJ, respectively, accounting for 14.5%, 29.5%, and 8.7% of the total purchased energy. 4) The energy utilization efficiency of the whole process is 47.6%. 5) Improving energy recovery is the most effective measure to improve energy utilization efficiency instead of degrading energy input and changing product structure. [ABSTRACT FROM AUTHOR]

Summary: To promote the sustainable development of the iron and steel industry (ISI), evaluation methods and influencing factors of energy efficiency have been studied in the past decades. A systematic review of these methodologies and influencing factors is presented in this paper. Initially, this paper states the development, current situation, and energy consumption of the world's ISI. Then, the definition of energy efficiency is described. After that, the evaluation methods are categorized as single‐factor methods (including these indicators of thermodynamic, thermos‐physical, thermo‐economic, and economic) and multifactor methods (including parametric and nonparametric methods). Furthermore, typical evaluation methods are highlighted. Thermal analysis method and exergy analysis method are routinely combined to optimize the energy utilization. Data envelopment analysis (DEA) and stochastic frontier analysis (SFA) are widely concerned and well developed to gain a better economic benefit. Malmquist index method is often associated with DEA to analyze the technical process and return to scale. Some emerging methods are proposed, for example, the three‐stage DEA method together with DEA and SFA. Finally, the influencing factors of energy efficiency in the ISI are discussed, including industrial structure, technological level, energy consumption structure, price, and so on. It is suggested that optimizing energy structure and improving technology level are effective measures to improve the energy efficiency in the ISI. [ABSTRACT FROM AUTHOR]

Dynamic spectrum access (DSA) is the key to solving worldwide spectrum shortage. The open wireless medium subjects DSA systems to unauthorized spectrum use by illegitimate users. Secondary-user authentication is thus critical to ensure the proper operations of DSA systems. This paper presents SpecGuard, the first crowdsourced spectrum misuse detection framework for DSA systems. In SpecGuard, a transmitter is required to embed a spectrum permit into its physical-layer signals, which can be decoded and verified by ubiquitous mobile users. We propose three novel schemes for embedding and detecting a spectrum permit at the physical layer. The first scheme relies on a higher transmission power to embed the spectrum permit. To alleviate the assumptions on the additional transmission power, the second scheme is proposed with a limited negative impact on the normal data transmission. The third scheme takes a different approach by adopting a novel constellation design and exploiting the trust between the transmitter and the receiver. Crowdsourced spectrum misuse detection eliminates the need for the deployment of dedicated sensors and thus greatly reduces the deployment and maintenance cost. Detailed theoretical analyses, MATLAB simulations, and USRP experiments confirm that our schemes can achieve correct, low-intrusive, and fast spectrum misuse detection. [ABSTRACT FROM AUTHOR]

Online Analytical Processing, or OLAP, is an approach to answering multidimensional analytical (MDA) queries in an interactive way. However, the traditional OLAP approaches can only deal with structured data, but not unstructured textual data like tweets. To address this problem, we propose a Latent Dirichlet Allocation (LDA)-based model, called Multilayered Semantic LDA (MS-LDA), which detects the hidden layered interests from Twitter data based on LDA. The layered dimension of interests can be further used to apply OLAP techniques to Twitter data. Furthermore, MS-LDA employs the semantic similarity among words of tweets based on word2vec, and also the social relationship among twitters, to improve its effectiveness. The extensive experiments demonstrate that MS-LDA can effectively extract the dimension hierarchy of tweeters' interests for OLAP. [ABSTRACT FROM AUTHOR]

In order to demonstrate the influence of gender differences on occupant dynamic response during spacecraft high-level landing impact, this study established a seat-dummy system model using Pro-E and HyperWorks software. The 50th Hybrid III male dummy and the 5th Hybrid III female dummy were used in the model. The seat-dummy system model was calibrated and validated according to the actual impact condition and impact test data of the simulated spacecraft landing. The gender differences on the impact response of key body segments were demonstrated and analysed under high-level landing impact (at a peak value of 26g). The simulation results show that the peak acceleration value of the female is larger than the male by 43.7% on the shoulder and by about 33% on the chest and pelvis, while the female is smaller than the male by 40.0% on the head in the chest-back (anterior–posterior, Gx) direction. In the head-foot (superior–inferior, Gz) direction, the peak acceleration value of the female is larger than the male by about 45.2% on the head, 120% on the shoulder, 9.0% on the chest and 37.3% on the pelvis. Therefore, it is recommended that spacecraft designers should pay more attention to gender differences on the head-neck and pelvis, and provide better protection for females during landing impact. [ABSTRACT FROM PUBLISHER]

The plummeting cost of Bluetooth tags and the ubiquity of mobile devices are revolutionizing the traditional lost-and-found service. This paper presents SecureFind, a secure and privacy-preserving object-finding system via mobile crowdsourcing. In SecureFind, a unique Bluetooth tag is attached to every valuable object, and the owner of a lost object submits an object-finding request to many mobile users via the SecureFind service provider. Each mobile user involved searches his vicinity for the lost object on behalf of the object owner who can infer the location of his lost object based on the responses from mobile users. SecureFind is designed to ensure strong object security such that only the object owner can discover the location of his lost object as well as offering location privacy to mobile users involved. The high efficacy and efficiency of SecureFind are confirmed by extensive simulations. [ABSTRACT FROM PUBLISHER]

Secure neighbor discovery is fundamental to mobile ad hoc networks (MANETs) deployed in hostile environments and refers to the process in which two neighboring nodes exchange messages to discover and authenticate each other. It is vulnerable to the jamming attack in which the adversary intentionally transmits radio signals to prevent neighboring nodes from exchanging messages. Anti-jamming communications often rely on spread-spectrum techniques, which depend on a spreading code common to the communicating parties but unknown to the jammer. The spread code, however, is impossible to establish before the communicating parties successfully discover each other. While several elegant approaches have been recently proposed to break this circular dependence, the unique features of neighbor discovery in MANETs make them not directly applicable. In this paper, we propose JR-SND, a jamming-resilient secure neighbor discovery scheme for MANETs based on direct-sequence spread spectrum and random spread-code predistribution. JR-SND enables neighboring nodes to securely discover each other with overwhelming probability despite the presence of omnipresent jammers. Detailed theoretical and simulation results confirm the efficacy and efficiency of JR-SND. [ABSTRACT FROM PUBLISHER]

This paper considers a novel distributed system for collaborative location-based information generation and sharing which become increasingly popular due to the explosive growth of Internet-capable and location-aware mobile devices. The system consists of a data collector, data contributors, location-based service providers (LBSPs), and system users. The data collector gathers reviews about points-of-interest (POIs) from data contributors, while LBSPs purchase POI data sets from the data collector and allow users to perform spatial top- k queries which ask for the POIs in a certain region and with the highest k ratings for an interested POI attribute. In practice, LBSPs are untrusted and may return fake query results for various bad motives, e.g., in favor of POIs willing to pay. This paper presents three novel schemes for users to detect fake spatial snapshot and moving top-k query results as an effort to foster the practical deployment and use of the proposed system. The efficacy and efficiency of our schemes are thoroughly analyzed and evaluated. [ABSTRACT FROM AUTHOR]

This paper presents TIGHT, a geographic routing protocol for cognitive radio mobile ad hoc networks. TIGHT offers three routing modes and allows secondary users to fully explore the transmission opportunities over a primary channel without affecting primary users (PUs). The greedy mode routes a packet via greedy geographic forwarding until a PU region is encountered and then further routes the packet around the PU region to where greedy forwarding can resume. It works best when the PUs are only occasionally active. In contrast, the optimal and suboptimal modes route a packet along optimal and suboptimal trajectories to the destination, respectively. They work best when the PUs are active most of the time. The suboptimal mode is computationally more efficient than the optimal mode at the cost of using suboptimal trajectories in rare cases. The efficacy of TIGHT is confirmed by extensive simulations. [ABSTRACT FROM PUBLISHER]

Objective: With 16 percent of the total road user fatalities, motorcyclists represent the second highest rate of road fatalities in France after car occupants. Regarding road accidents, a large proportion of trauma was on the lower cervical spine. According to different clinical studies, it is postulated that the cervical spine fragility areas are located on the upper and lower cervical spine. In motorcycle crashes, impact conditions occur on the head segment with various orientations and impact directions, leading to a combination of rotations and compression. Hence, motorcyclist vulnerability was investigated considering many impact conditions. Method: Using the human model for safety (HUMOS), a finite element model, this work aims to provide an evaluation of the cervical spine weaknesses based on an evaluation of injury mechanisms. This evaluation consisted of defining 2 injury risk factors (joint injury and bone fracture) using a design of experiment including various velocities, impact directions, and impact orientations. Results: The results confirmed previously reported clinical and epidemiological work on the fragility of the lower cervical spine and the upper cervical spine segments. Joint injuries appeared before bone fractures on both the upper and lower cervical spine. Bone fracture risk was greater on the lower cervical spine than on the upper cervical spine. The compression induced by a high impact angle was identified as an important injury severity factor. It significantly increased the injury incidence for both joint injuries and bone fractures. It also induced a shift in injury location from the lower to the upper cervical spine. The impact velocity exhibited a linear relationship with injury risks and severity. It also shifted the bone fracture risk from the lower to upper spinal segments. [ABSTRACT FROM PUBLISHER]