Preferences,Knowledge, and Citizen Probability Assessments of the Terrorism Risk of Nuclear Power

How does the American public assess risk when it comes to national security issues? This paper addresses this question by analyzing variation in citizen probability assessments of the terrorism risk of nuclear power plants. Drawing on the literature on how motivated reasoning, selective information processing, and domain‐specific knowledge influence public opinion, we argue that heterogeneous issue preferences and knowledge of nuclear energy and homeland security have important explanatory power. Using original data from a unique 2009 national survey in the United States, we show that Americans are divided in their probability assessments of the terrorism risk of nuclear power plants. Consistent with our theoretical expectations, individuals who support using nuclear power to meet rising energy demands, who are generally less concerned with terrorism, or who are more knowledgeable about terrorism and nuclear security tend to provide lower assessments of the likelihood that nuclear power plants increase terrorist attacks, and vice versa. The findings have implications for the literature on public opinion, risk assessment, energy policy and planning, and homeland security.     

Environment and Energy: The Baltic Sea Gas Pipeline

Germany and Russia have agreed to build the Nord Stream gas pipeline. The 1,200 kilometers-long structure will run from Vyborg, Russia to Greifswald, Germany traversing the Baltic Sea. The Baltic countries, Finland, Poland and Sweden, have expressed concerns about the project. At issue is the environmental impact of the project as well as the energy, political, and socioeconomic implications.     

我国合同能源管理法律关系探究

我国从国外引进的合同能源管理是一种推广节省能源新技术的模式,在实际运行中需要协调与整合技术、资金、设施建设与项目管理等多方面的关系,因而,我国对合同能源管理、能源管理合同属性的认识比较模糊,并存在多种看法。为此,必须厘清合同能源管理所涉及的法律关系,充分解析能源管理合同的法律属性,分析把握合同能源管理运营中资产等所有权归属问题,在我国现有法律体系框架范围内,正确、有效地调整合同能源管理关系,积极促进节能新技术在全社会的推广、普及。     

Comparison of feature selection and data fusion of Fourier transform infrared and Raman spectroscopy for identifying watercolor ink

The identification of different kinds of watercolor inks is an important work in the field of forensic science. Four different kinds of watercolor ink Spectroscopy data fusion strategies (Fourier Transform Infrared spectroscopy and Raman spectroscopy) combined with a non-linear classification model (Extreme Learning Machine) were used to identify the brand of watercolor inks. The study chose Competitive Adaptive Reweighted Sampling (CARS), Random Frog (RF), Variable Combination Population Analysis-Genetic Algorithm (VCPA-GA), and Variable Combination Population Analysis-Iteratively Retains Informative Variables (VCPA-IRIV) to extract characteristic variables for mid-level data fusion. The Cuckoo Search (CS) algorithm is used to optimize the extreme learning machine classification model. The results showed that the classification capacity of the mid-level fusion spectra model was more satisfactory than that of single Infrared spectroscopy or Raman spectroscopy. The CS-ELM models based on infrared spectroscopy used to recognize the watercolor ink according to brands (ZHENCAI, DELI, CHENGUANG, and STAEDTLER) obtained an accuracy of 66.67% in the test set using all spectral datasets. The accuracy of CS-ELM models based on Raman spectroscopy was 67.39%. The characteristic wavelength selection algorithms effectively improved the accuracy of the CS-ELM models. The classification accuracy of the mid-level spectroscopy fusion model combined with the VCPA-IRIV algorithm was 100%. The data fusion method increased effectively spectral information. The method could satisfactorily identify different brands of watercolor inks and support the preservation of artifacts, paintings, and forensic document examination.     

Detection of Denatonium Benzoate (Bitrex) Remnants in Noncommercial Alcoholic Beverages by Raman Spectroscopy

Illegal alcoholic beverages are often introduced into market using cheap technical alcohol, which is contaminated by denatonium benzoate (Bitrex) of very small concentration. Bitrex is the most bitter chemical compound and has to be removed before alcohol consumption. The home‐made methods utilize sodium hypochlorite to disintegrate particles of denatonium benzoate in alcohol and to remove bitter taste before trading. In this experimental studies, we propose a novel method that detects in a fast way the remnants of denatonium benzoate in dubious alcohol samples by Raman spectroscopy. This method applies a portable Raman spectrometer of excitation wavelength 785 nm and utilizes the effect of surface‐enhanced Raman spectroscopy (SERS) to recognize the suspected alcoholic beverages. High effectiveness (over 98%) of YES/NO classification of the investigated samples was observed when the nonlinear algorithm support vector machine (SVM) was exploited at carefully adjusted detection parameters. The method can identify illicit alcohol within minutes.     

Infrared Spectra of U.S. Automobile Original Finishes (Post – 1989). VIII: In Situ Identification of Bismuth Vanadate Using Extended Range FT‐IR Spectroscopy,Raman Spectroscopy,and X‐Ray Fluorescence Spectrometry

Chrome Yellow (PbCrO₄·xPbSO₄) was a common pigment in U.S. automobile OEM finishes for more than three decades, but in the early 1990s its use was discontinued. One of its main replacements was Bismuth Vanadate (BiVO₄·nBi₂MoO₆, n = 0–2), which was commercially introduced in 1985, as this inorganic pigment also produces a very bright hue and has excellent outdoor durability. This paper describes the in situ identification of Bismuth Vanadate in automotive finishes using FT‐IR and dispersive Raman spectroscopy and XRF spectrometry. Some differentiation of commercial formulations of this pigment is possible based on far‐infrared absorptions, Raman data, and elemental analysis. The spectral differences arise from the presence or absence of molybdenum, the use of two crystal polymorphs of BiVO₄, and differences in pigment stabilizers. Bismuth Vanadate is usually not used alone, and it is typically found with Isoindoline Yellow, hydrous ferric oxide, rutile, Isoindolinone Yellow 3R, or various combinations of these.     

Rapid and nondestructive analysis of lipstick on different substrates using ATR-FTIR spectroscopy and chemometrics

Lipstick can be an important piece of evidence in crimes like murders, rapes, and suicides. Due to its prevalence, it can be an important corroborative evidence in crime reconstruction. The analysis of such evidence can provide an evidentiary link between the suspect, the victim, object, or the crime scene. We report the use of nondestructive ATR-FTIR spectroscopy combined with chemometrics for the classification of 10 brands of lipsticks with nine samples each. Chemometric method of partial least square-discriminant analysis (PLS-DA) has been employed to interpret the data and classify the samples into their respective classes. The PLS-DA model provides an AUC figure above 0.99 in all brands except one; for which it is slightly less at 0.94. We have also tested the traces of these lipstick samples on different substrates treating them as unknowns in the already trained PLS-DA model. 100% of the samples on nine substrates viz. a cotton, nylon, plastic, dry tissue, denim (blue jeans), wet tissue, nitrile gloves, white paper, and polyester were correctly attributed to their source brand. In conclusion, the results suggest that ATR-FTIR combined with the chemometrics is a rapid, nondestructive, and accurate method for the discrimination and source attribution of lipstick. This study has potential for use in actual forensic casework conditions.     

Surface-enhanced Raman spectroscopy enables confirmatory detection of dyes on hair submerged in hypolimnion water for up to twelve weeks

Difficulties in the localization of bodies of homicidal or drowning victims in natural water result in their submergence for weeks if not months. Water insects and microbes drastically change the body's appearance, which significantly changes the determination of a victim's identity. DNA analysis is commonly used for identifying the decedent; however, this PCR-based approach is time-consuming and destructive of the evidence. Considering that nearly half of the people in the world dye their hair with a variety of permanent and semi-permanent dyes, one can expect that confirmatory identification of dyes on the body's hair can be used to shed light on the victim's identity. A growing body of evidence suggests that surface-enhanced Raman spectroscopy (SERS) can be used to detect and identify hair dyes. In this study, we investigated the extent to which SERS could be used to detect black and blue, permanent and semi-permanent dyes on hair submerged in hypolimnion water for up to twelve weeks. We found that SERS enabled 100% accurate identification of analyzed dyes on hair submerged in hypolimnion water for up to 8 weeks, whereas, on average, 87% accurate identification of the hair dyes could be achieved on hair exposed for 10 weeks and 50% for hair exposed 12 weeks in hypolimnion water. We also found that the aqueous environment caused progressive fading of some dyes, whereas other dyes showed substantial spectral transformations after prolonged submergence. Finally, we found that changes in the intensity of vibrational bands of dyes could be used to predict the duration of submergence of colored hair in hypolimnion water.     

Characterization of an odor permeable membrane device for the storage of explosives and use as canine training aids

The storage and use of explosives is regulated at the state and federal level, with a particular focus on physical security and rigorous accounting of the explosive inventory. For those working with explosives for the training and testing of explosive-detecting canines, cross-contamination is an important concern. Hence, explosives intended for use with canine teams must be placed into secondary storage containers that are new, clean, and airtight. A variety of containers meet these requirements and include screw-top glass jars (e.g., mason jars). However, an additional need from the explosive-detecting canine community is secondary containers that can also be used as training aids whereby the volatiles emitted by explosives are emitted in a predictable and stable manner. Currently, a generally accepted method for the storage of explosives and controlled emission of explosive vapor for canine detection does not exist. Ideally, such containers should allow odor to escape from the training aid but block external contaminates such as particulates or other volatiles. One method in use places the explosive inside a permeable cotton bag when in use for training and then stores the cotton bag inside an impermeable nylon bag for long-term storage. This paper describes the testing of an odor permeable membrane device (OPMD) as a new way to store and deploy training aids. We measured the evaporation rate and flux of various liquid explosives and volatile compounds that have been identified in the headspace of actual explosives. OPMDs were used in addition to traditional storage containers to monitor the contamination and degradation of 14 explosives used as canine training aids. Explosives were stored individually using traditional storage bags or inside an OPMD at two locations, one of which actively used the training aids. Samples from each storage type at both locations were collected at 0, 3, 6, and 9 months and analyzed using Fourier Transform Infrared (FTIR) Spectroscopy and Gas Chromatography–Mass Spectrometry (GC–MS) with Solid-Phase Microextraction (SPME). FTIR analyses showed no signs of degradation. GC–MS identified cross-contamination from ethylene glycol dinitrate (EGDN) and/or 2,3-dimethyl-2,3-dinitrobutane (DMNB) across almost all samples regardless of storage condition. The contamination was found to be higher among training aids that were stored in traditional ways and that were in active use by canine teams.     

Enhancing Precision and Clarity in the Study of Policy Narratives: An Analysis of Climate and Air Issues in Delhi,India

The study of policy narratives is challenged by inconsistencies and a need for more precise definitions and measurements. The goals of this article are to build precision and clarity in the study of policy narratives by developing a network‐based approach—the ego‐alter dyad—for coding characters and their interactions around a policy issue and then to illustrate this approach in the analysis of air and climate issues in Delhi, India. The empirical results show that (1) the same actors are often heroes and villains, (2) heroes and villains are associated with different actions but with similar victims or beneficiaries, (3) narrators differ in their propensity to tell hero‐heavy or villain‐heavy policy narratives, and (4) the proportion of hero‐heavy or villain‐heavy policy narratives changes over time and differs across subtopics. The article concludes with a research agenda for further theoretical and methodological advancement in studying policy narratives.