Investigating DNA Barcoding Potentials and Genetic Structure in Ozobranchus spp. from Atlantic and Pacific Ocean Sea Turtles

The Ozobranchidae family is the smallest and least studied hirudinean taxon. Our research includes the largest molecular dataset yet reported for marine ozobranchids (Ozobranchus margoi and Ozobranchus branchiatus) with the most number of documented turtle hosts (57) from the Atlantic and Pacific Oceans to date of any marine turtle epibiont study. Turtle species sampled in this study include loggerheads (Caretta caretta), hawksbill (Eretmochelys imbricata), olive ridley (Lepidochelys olivacea), and green turtles (Chelonia mydas). Phylogenetic analyses of mitochondrial (COI) and nuclear ribosomal (18S and 28S) genes all support the monophyly of marine Ozobranchidae leeches with speciation occurring over an extensive period of time, likely prior to the Isthmus of Panama. Histone H3 data suggests at least three histone H3 genes for O. margoi. In addition, mtDNA analyses show higher genetic structure in the Atlantic for O. branchiatus existing in both ocean basins. The small tropical family of turtle annelids was also used to examine the limitations of DNA barcoding on taxa with incomplete taxonomic sampling and to assess whether these issues can be adequately resolved using the character-based approach. The ability to assign ocean basin origin of leech specimens using character-based DNA barcoding suggests the potential for this tool to be integrated with other applications besides species identification

ROBUST DYNAMIC ID-BASED REMOTE MUTUAL AUTHENTICATION SCHEME

Dynamic ID based authentication scheme is more and more important in insecure wireless environment and system. Two of kinds of attack that authentication schemes must resist are stealing identity and reflection attack which is a potential way of attacking a challenge- response authentication system using the same protocol in both direc­tions. It must be guaranteed to prevent attackers from reusing informa­tion from authentication phase and the scheme of Yoon and Yoo satisfies those requirements. However, their scheme can not resist insider and impersonation attack by using lost or stolen smart card. In this paper, we demonstrate that Yoon and Yoo’s scheme is still vulnerable to those attacks. Then, we present an improvement to their scheme in order to isolate such problems

Beyond Domain Adaptation: Unseen Domain Encapsulation via Universal Non-volume Preserving Models

Recognition across domains has recently become an active topic in the research community. However, it has been largely overlooked in the problem of recognition in new unseen domains. Under this condition, the delivered deep network models are unable to be updated, adapted or fine-tuned. Therefore, recent deep learning techniques, such as: domain adaptation, feature transferring, and fine-tuning, cannot be applied. This paper presents a novel Universal Non-volume Preserving approach to the problem of domain generalization in the context of deep learning. The proposed method can be easily incorporated with any other ConvNet framework within an end-to-end deep network design to improve the performance. On digit recognition, we benchmark on four popular digit recognition databases, i.e. MNIST, USPS, SVHN and MNIST-M. The proposed method is also experimented on face recognition on Extended Yale-B, CMU-PIE and CMU-MPIE databases and compared against other the state-of-the-art methods. In the problem of pedestrian detection, we empirically observe that the proposed method learns models that improve performance across a priori unknown data distributions

New Primers Reveal the Presence of a Duplicate Histone H3 in the Marine Turtle Leech Ozobranchus branchiatus

Marine leeches, specific to sea turtles, have been implicated as potential vector organisms in the spread of fibropapillomatosis (FP), a pandemic neoplastic disease with green turtles (Chelonia mydas) having the highest affliction rate. Polymerase chain reaction identified two independent, seemingly functional histone H3 loci for marine turtle leeches Ozobranchus branchiatus collected from C. mydas in Florida and Hawaii. Primers were developed to amplify each product separately. These novel markers will be useful in identifying ectoparasites in FP research, evaluating other histone variants, and chromatin dynamics regulation studies. This poster was created and presented by Triet M. Truong at the Wright State University Chemistry Department posters in the hall event on June 1, 2012 and the results were published in Conservation Genetics Resources (2012), 4, 487-490

An investigation of online teaching and lecturers' online teaching competence in Vietnam: A case study at universities of technology and education

The rapid digital transformation and the widespread influence of the COVID-19 pandemic have impacted higher education in Vietnam. This social setting fosters online teaching and lecturers’ online teaching competencies.  The aim of this study is to investigate online teaching competence at two universities of technology and education in Vietnam through a survey. Based on a review of the literature, an online teaching competence scale for lecturers was developed and its validity and reliability were evaluated using exploratory component analysis and Cronbach's alpha coefficients with data from 311 lecturers at two public universities of technology and education. The online teaching competency scale for lecturers consists of 25 items organized into five component competencies: “Understanding student learning”, “online session administration”, “digital content development and learning facilitation”, “technology” and “online learning outcomes assessment”. With the exception of “technology”, the remaining component competencies were identified as good. Not only online teaching modes but also online teaching activities and productions were also deployed to maintain learning activities especially during the COVID-19 pandemic at two universities. Recommendations for developing lecturers' online teaching competence were also considered

DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking

Multi-Camera Multiple Object Tracking (MC-MOT) is a significant computer vision problem due to its emerging applicability in several real-world applications. Despite a large number of existing works, solving the data association problem in any MC-MOT pipeline is arguably one of the most challenging tasks. Developing a robust MC-MOT system, however, is still highly challenging due to many practical issues such as inconsistent lighting conditions, varying object movement patterns, or the trajectory occlusions of the objects between the cameras. To address these problems, this work, therefore, proposes a new Dynamic Graph Model with Link Prediction (DyGLIP) approach to solve the data association task. Compared to existing methods, our new model offers several advantages, including better feature representations and the ability to recover from lost tracks during camera transitions. Moreover, our model works gracefully regardless of the overlapping ratios between the cameras. Experimental results show that we outperform existing MC-MOT algorithms by a large margin on several practical datasets. Notably, our model works favorably on online settings but can be extended to an incremental approach for large-scale datasets.Comment: accepted at CVPR 202

QUÁ TRÌNH CHUYỂN PHA PHI CÂN BẰNG CỦA VẬT LIỆU HAI CHIỀU PENTA-GRAPHENE

Graphene has received enormous attention in the semiconductor industry during the last two decades. However, since graphene is a gapless semiconductor, it has critical challenges to be engineered into semiconductor devices. Recent reports have shown that penta-graphene stands out as a promising semiconductor candidate with an electronic bandgap between 2.2 and 4.3 eV; thus, it can surmount graphene’s obstacles. However, when being heated, penta-graphene can transform its configurations from pentagonal lattices to hexagonal graphene-like heterostructures, resulting in a significant electronic modification. In this paper, we investigate the effect of heating rates on the non-equilibrium phase transition of a two-dimensional penta-graphene by using molecular dynamic simulations. We have shown that, with a fast-heating process, penta-graphene naturally transforms to graphene without a clear phase separation point. Nevertheless, with a sufficiently slow heating protocol, this transition is a first-order phase transition from a pentagonal to a more stable hexagonal configuration. These results provide the possibility to implement penta-graphene in future optoelectronic devices.Graphene đã được chứng minh là vật liệu mang tính đột phá cho ngành vật liệu bán dẫn. Tuy nhiên, với độ rộng vùng cấm gần như bằng không, graphene có những hạn chế nhất định khi được ứng dụng để chế tạo linh kiện điện tử. Các nghiên cứu gần đây cho thấy penta-graphene với độ rộng vùng cấm 2,2–4,3 eV và độ bền cơ – nhiệt cao có thể dung hòa nhược điểm của graphene. Tuy nhiên, khi bị nung nóng, penta-graphene có thể chuyển từ cấu trúc vòng 5 điển hình sang cấu trúc vòng 6 của graphene, nhưng điều kiện cụ thể để quá trình chuyển pha này hình thành vẫn chưa được nghiên cứu chi tiết. Trong bài báo này, chúng tôi nghiên cứu sự ảnh hưởng của tốc độ nung đến tính chất nhiệt động phi cân bằng của penta-graphene bằng phương pháp mô phỏng động học phân tử. Ở tốc độ nung lớn, penta-graphene sẽ dần chuyển sang graphene mà không có điểm chuyển pha rõ nét. Tuy nhiên, nếu penta-graphene được nung rất chậm, quá trình chuyển pha từ penta-graphene sang graphene là quá trình chuyển pha loại I với sự gián đoạn của thông số nhiệt động tại điểm chuyển pha. Kết quả này sẽ góp phần bổ sung các thông số kỹ thuật quan trọng trong việc ứng dụng vật liệu penta-graphene để chế tạo các linh kiện quang – điện tử trong tương lai