AIDing Contraception: HIV and Recent Trends in Abortion Rates

Since the onset of HIV/AIDS awareness in the early 1980s, much attention has centered around the substantial negative effects of the disease throughout the world. This paper provides evidence of a secondary effect the disease has had on sexual behavior in the United States. Using a difference-in-differences estimation framework and state level data, we show that the perceived threat of HIV resulted in a drop in unwanted pregnancies, as demonstrated by a lower incidence of abortions. Our results suggest that each additional reported case of HIV per 1,000 individuals resulted in 85.5 fewer abortions per 1,000 live births.

Bio-AKA: An efficient fingerprint based two factor user authentication and key agreement scheme

The fingerprint has long been used as one of the most important biological features in the field of biometrics. It is person-specific and remain identical though out one’s lifetime. Physically uncloneable functions (PUFs) have been used in authentication protocols due to the unique physical feature of it. In this paper, we take full advantage of the inherent security features of user’s fingerprint biometrics and PUFs to design a new user authentication and key agreement scheme, namely Bio-AKA, which meets the desired security characteristics. To protect the privacy and strengthen the security of biometric data and to improve the robustness of the proposed scheme, the fuzzy extractor is employed. The scheme proposed in the paper can protect user’s anonymity without the use of password and allow mutual authentication with key agreement. The experimental results show superior robustness and the simplicity of our proposed scheme has been validated via our performance and security analysis. The scheme can be an ideal candidate for real life applications that requires remote user authentication

Priming effects on labile and stable soil organic carbon decomposition: Pulse dynamics over two years

Soil organic carbon (SOC) is a major component in the global carbon cycle. Yet how input of plant litter may influence the loss of SOC through a phenomenon called priming effect remains highly uncertain. Most published results about the priming effect came from short-term investigations for a few weeks or at the most for a few months in duration. The priming effect has not been studied at the annual time scale. In this study for 815 days, we investigated the priming effect of added maize leaves on SOC decomposition of two soil types and two treatments (bare fallow for 23 years, and adjacent old-field, represent stable and relatively labile SOC, respectively) of SOC stabilities within each soil type, using a natural 13C-isotope method. Results showed that the variation of the priming effect through time had three distinctive phases for all soils: (1) a strong negative priming phase during the first period (≈0-90 days); (2) a pulse of positive priming phase in the middle (≈70-160 and 140-350 days for soils from Hailun and Shenyang stations, respectively); and (3) a relatively stabilized phase of priming during the last stage of the incubation (>160 days and >350 days for soils from Hailun and Shenyang stations, respectively). Because of major differences in soil properties, the two soil types produced different cumulative priming effects at the end of the experiment, a positive priming effect of 3-7% for the Mollisol and a negative priming effect of 4-8% for the Alfisol. Although soil types and measurement times modulated most of the variability of the priming effect, relative SOC stabilities also influenced the priming effect for a particular soil type and at a particular dynamic phase. The stable SOC from the bare fallow treatment tended to produce a narrower variability during the first phase of negative priming and also during the second phase of positive priming. Averaged over the entire experiment, the stable SOC (i.e., the bare fallow) was at least as responsive to priming as the relatively labile SOC (i.e., the old-field) if not more responsive. The annual time scale of our experiment allowed us to demonstrate the three distinctive phases of the priming effect. Our results highlight the importance of studying the priming effect by investigating the temporal dynamics over longer time scales

School climate’s effect on hospitality department students’ aesthetic experience, professional identity and innovative behavior

This study investigated the effects of school climate and students’ aesthetic experience on their professional identity and innovative behavior. A survey was conducted with 385 students from hospitality-related departments of colleges and universities in Hainan, China, and the data were analyzed using a hierarchical linear model (HLM). Using the criteria constituting the students’ aesthetic experience scale proposed by Chang, it was found that teacher support can improve students’ professional identity; school climate and students’ understanding of beauty and full experience contribute to the development of students’ innovative behavior; students’ understanding of beauty and full experience have mediating effects between teacher support and professional cognition; students’ understanding of beauty and full experience have mediating effects between student support and innovative behavior; student support positively moderates the relationships between full experience with professional cognition and students’ appraisal of the hospitality industry; and teacher support positively moderates the relationship between students’ full experience and professional emotion. Therefore, teacher support under school climate and students’ understanding of beauty and full experience under aesthetic experience were the most important factors in enhancing hospitality department students’ professional identity and innovative behavior

Local keypoint-based Faster R-CNN

Region-based Convolutional Neural Network (R-CNN) detectors have achieved state-of-the-art results on various challenging benchmarks. Although R-CNN has achieved high detection performance, the research of local information in producing candidates is insufficient. In this paper, we design a Keypoint-based Faster R-CNN (K-Faster) method for object detection. K-Faster incorporates local keypoints in Faster R-CNN to improve the detection performance. In detail, a sparse descriptor, which first detects the points of interest in a given image and then samples a local patch and describes its invariant features, is first employed to produce keypoints. All 2-combinations of the produced keypoints are second selected to generate keypoint anchors, which are helpful for object detection. The heterogeneously distributed anchors are then encoded in feature maps based on their areas and center coordinates. Finally, the keypoint anchors are coupled with the anchors produced by Faster R-CNN, and the coupled anchors are used for Region Proposal Network (RPN) training. Comparison experiments are implemented on PASCAL VOC 07/12 and MS COCO. The experimental results show that our K-Faster approach not only increases the mean Average Precision (mAP) performance but also improves the positioning precision of the detected boxes

A Survey of the methods on fingerprint orientation field estimation

Fingerprint orientation field (FOF) estimation plays a key role in enhancing the performance of the automated fingerprint identification system (AFIS): Accurate estimation of FOF can evidently improve the performance of AFIS. However, despite the enormous attention on the FOF estimation research in the past decades, the accurate estimation of FOFs, especially for poor-quality fingerprints, still remains a challenging task. In this paper, we devote to review and categorization of the large number of FOF estimation methods proposed in the specialized literature, with particular attention to the most recent work in this area. Broadly speaking, the existing FOF estimation methods can be grouped into three categories: gradient-based methods, mathematical models-based methods, and learning-based methods. Identifying and explaining the advantages and limitations of these FOF estimation methods is of fundamental importance for fingerprint identification, because only a full understanding of the nature of these methods can shed light on the most essential issues for FOF estimation. In this paper, we make a comprehensive discussion and analysis of these methods concerning their advantages and limitations. We have also conducted experiments using publically available competition dataset to effectively compare the performance of the most relevant algorithms and methods

Quantitative Analysis of Volatile Impurities in Diallyldimethylammonium Chloride Monomer Solution by Gas Chromatography Coupled with Liquid-Liquid Extraction

The quantitative analysis method for volatile impurities in diallyldimethylammonium chloride (DADMAC) monomer solution was established in this paper. The volatile impurities were quantitatively analyzed with trichloromethane as extraction solvent and n-hexane as internal standard by using gas chromatography (GC) coupled with solvent extraction, and the chromatographic conditions, quantitative methods, and extraction conditions were systematically investigated in detail. The results showed that excellent linear relationships of 5 volatile impurities (dimethylamine, allyldimethylamine, allyl chloride, allyl alcohol, and allyl aldehyde) were obtained in the range of 1–100 mg·L−1. The method also showed good specificity, recovery (95.0%–107.5%), and relative standard deviation (RSD, 1.40%–7.67%). This method could accurately detect the whole volatile impurities in DADMAC monomer solution quantitatively in one time with a low detection limit. Furthermore, this method is conducive to the preparation of highly pure DADMAC monomer and the development of national and international standards of the DADMAC monomer product quality, and the results could provide a strong foundation for the regulation and mechanism research of impurities on monomer reactivity in polymerization