Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploitation of Neisseria meningitidis Group B OMV Vaccines Against N. gonorrhoeae to Inform the Development and Deployment of Effective Gonorrhea Vaccines

Have potential clues to an effective gonorrhea vaccine been lurking in international disease surveillance data for decades? While no clinically effective vaccines against gonorrhea have been developed we present direct and indirect evidence that a vaccine is not only possible, but may already exist. Experience from Cuba, New Zealand, and Canada suggest that vaccines containing Group B Neisseria meningitides outer membrane vesicles (OMV) developed to control type-specific meningococcal disease may also prevent a significant proportion of gonorrhea. The mechanisms for this phenomenon have not yet been elucidated but we present some strategies for unraveling potential cross protective antigens and effector immune responses by exploiting stored sera from clinical trials and individuals primed with a meningococcal group B OMV vaccine (MeNZB). Elucidating these will contribute to the ongoing development of high efficacy vaccine options for gonorrhea. While the vaccine used in New Zealand, where the strongest empirical evidence has been gathered, is no longer available, the OMV has been included in the multi component recombinant meningococcal vaccine 4CMenB (Bexsero) which is now licensed and used in numerous countries. Several lines of evidence suggest it has the potential to affect gonorrhea prevalence. A vaccine to control gonorrhea does not need to be perfect and modeling supports that even a moderately efficacious vaccine could make a significant impact in disease prevalence. How might we use an off the shelf vaccine to reduce the burden of gonorrhea? What are some of the potential societal barriers in a world where vaccine hesitancy is growing? We summarize the evidence and consider some of the remaining questions.
DeltaVR: Achieving High-Performance Mobile VR Dynamics through Pixel Reuse

Virtual Reality (VR) improves the user's experience when interacting with the virtual world, and could revolutionarily transform the designs of many interactive systems. However, providing VR from untethered mobile devices is difficult due to their limited local capabilities. Existing VR solutions address this difficulty by rendering VR frames at remote computing facilities, but are limited to rendering every VR frame separately. A tremendous amount of VR frame data, hence, needs to be transmitted to mobile devices over low-bandwidth wireless links and seriously impairs VR performance. In this paper, we aim to remove this performance constraint on highly dynamic VR applications with complicated scenes and intensive user movement, by adaptively reusing the redundant VR pixels across multiple VR frames. We leverage the unique characteristics of image warping used in current VR applications, and fundamentally expand the scope of image warping to the entire VR lifespan to precisely capture the fluctuations of VR scene due to VR dynamics. We implemented our design over Android OS and Unity VR application engine, and demonstrated that our design can maximize the mobile VR performance over highly dynamic VR scenarios with 95% less amount of VR frame data being transmitted, by completely removing the pixel redundancy across VR frames.
Robust Weighted Keypoint Matching Algorithm for Image Retrieval

The important factor which controls the accuracy of image matching process is a keypoint extraction. This paper describes a new weighted keypoint matching algorithm for improving the performance of image retrieval. The basic concept is to use the edge information. First, we compute the Scale Invariant Feature Transform (SIFT) features as keypoints from an input image. Also, the edge image is obtained for updating the ranking of the extracted keypoints. With the obtained edge map, we assign weights to keypoints where they correspond on the edge map. Finally the ranking of keypoints is re-ordered and Top-32 keypoints are selected based on the RootSIFT to matching process. Through the experiments, we verify that the proposed algorithm achieves 2.4% of more accuracy than the original SIFT detector when various distortions exist.
Fostering User Acceptance and Trust in Fully Automated Vehicles: Evaluating the Potential of Augmented Reality

Abstract Lack of trust in or acceptance of technology are some of the fundamental problems that might prevent the dissemination of automated driving. Technological advances, such as augmented reality aids like full-sized windshield displays or AR contact lenses, could be of help to provide a better system understanding to the user. In this work, we picked up on the question of whether augmented reality assistance has the potential to increase user acceptance and trust by communicating system decisions (i.e., transparent system behavior). To prove our hypothesis, we conducted two driving simulator studies to investigate the benefit of scenario augmentation in fully automated driving—first in normal (N=26) and then in rearward viewing (N=18) direction. Quantitative results indicate that the augmentation of traffic objects/participants otherwise invisible (e.g., due to dense fog), or the presentation of upcoming driving maneuvers while sitting backwards, is a feasible approach to increase user acceptance and trust. Results are further backed by qualitative findings from semistructured interviews and UX curves (a method to retrospectively report experience over time). We conclude that the application of augmented reality, in particular with the emergence of more powerful, lightweight, or integrated devices, is a good opportunity with high potential for automated driving.
Energy-efficient offloading policy in D2D underlay communication integrated with MEC service

The offloading policy has attracted much attention in the study of Device-to-Device (D2D) Communication underlaying cellular network integrated with Mobile Edge Computing (MEC) service. D2D communication can improve energy efficiency and prolong the battery life of user equipment (UEs) by offloading computation tasks from a UE to a nearby UE via a D2D link. How to coordinate UEs to offload tasks in D2D underlay communication integrated with MEC Service for reducing interference and improving network energy efficiency is a very important subject. In this paper, we study a D2D underlay communication integrated with MEC service system that provides three offloading policies that are: (i) executing tasks in local device, (ii) offloading tasks to servers in local region, (iii) offloading tasks to a nearby UE. Furthermore, we formulate the computation offloading problem as a potential game and propose a D2D communication integrated with MEC service offloading computation algorithm for solving the computation offloading problem in a short period. The simulation results show that our proposed algorithm can reduce overall system energy consumption under time constraints.
Maternal Mortality and Maternal Health Care in Nigeria: Implications for Socio-Economic Development

BACKGROUND: Even though maternal mortality, which is a pregnancy-related death is preventable, it has continued to increase in many nations of the world, especially in the African countries of the sub-Saharan regions caused by factors which include a low level of socioeconomic development. AIM: This paper focuses on cogent issues affecting maternal mortality by unpacking its precipitating factors and examining the maternal health care system in Nigeria. METHODS: Contemporary works of literature were reviewed, and the functionalist perspective served as a theoretical guide to examine the interrelated functions of several sectors of the society to the outcome of maternal mortality. RESULTS: It was noted that apart from the medical related causes (direct and indirect) of maternal mortality, certain socio-cultural and socioeconomic factors influence the outcome of pregnancy. Also, a poor health care system, which is a consequent of weak social structure, is a contributing factor. CONCLUSION: As a result, maternal mortality has debilitating effects on the socioeconomic development of any nation. It is therefore pertinent for the government to improve maternal health and eradicate poverty to ensure sustainable development.
Two-phase bundling strategy with limited capacity

Bundling, as an effective marketing model, has been gradually applied in all fields since the 1970s. Although there has many researches on bundling, the two-phase bundling strategy is still rare. This study considers a retailer who has a limited capacity of products sells two types of independent products in two periods, which the retailer can choose to sell products separately (pure components, PC) or bundled (pure bundling, PB) in different period. So there are four strategies the retailer can choose, i.e., PC-PC, PB-PB, PC-PB, and PB-PC. The research compares them, and the results show that the best bundling strategy depends on the capacity of two products.
A New Multi-Camera Dataset with Surveillance, Mobile and Stereo Cameras for Tracking, Situation Analysis and Crime Scene Investigation Applications

Nowadays, cameras are ubiquitous. In the event of a crime or terrorist attack, plenty of video data can be collected from surveillance cameras or mobile phone cameras from witnesses. This paper presents a new dataset, "IOSB-4D," which includes data from multiple static and mobile cameras (from potential witnesses) that record a site. We provide several scenarios involving 10 actors that contain scenes of kidnapping, attack of a person by a group, loading a briefcase into a trunk, and more. In total, there are recordings from three perspectives from stereo cameras as well as two static surveillance cameras and up to six mobile cameras. For all cameras, we provide intrinsic parameters, and for the static cameras, we provide 6DOF pose parameters. Furthermore, high resolution images of all actors are available. This new dataset is valuable for object tracking and situation analysis, or research on innovative visualizations of combined camera and video footage, for example, to create a visualization in 3D/4D for a post analytic crime scene investigation.
Vestibulo-Ocular Responses and Dynamic Visual Acuity During Horizontal Rotation and Translation

Dynamic visual acuity (DVA) provides an overall functional measure of visual stabilization performance that depends on the vestibulo-ocular reflex (VOR), but also on other processes, including catch-up saccades and likely visual motion processing. Capturing the efficiency of gaze stabilization against head movement as a whole, it is potentially valuable in the clinical context where assessment of overall patient performance provides an important indication of factors impacting patient participation and quality of life. DVA during head rotation (rDVA) has been assessed previously, but to our knowledge, DVA during horizontal translation (tDVA) has not been measured. tDVA can provide a valuable measure of how otolith, rather than canal, function impacts visual acuity. In addition, comparison of DVA during rotation and translation can shed light on whether common factors are limiting DVA performance in both cases. We therefore measured and compared DVA during both passive head rotations (head impulse test) and translations in the same set of healthy subjects (n = 7). In addition to DVA, we computed average VOR gain and retinal slip within and across subjects. We observed that during translation, VOR gain was reduced (VOR during rotation, mean ± SD: position gain = 1.05 ± 0.04, velocity gain = 0.97 ± 0.07; VOR during translation, mean ± SD: position gain = 0.21 ± 0.08, velocity gain = 0.51 ± 0.16), retinal slip was increased, and tDVA was worse than during rotation (average rDVA = 0.32 ± 0.15 logMAR; average tDVA = 0.56 ± 0.09 logMAR, p = 0.02). This suggests that reduced VOR gain leads to worse tDVA, as expected. We conclude with speculation about non-oculomotor factors that could vary across individuals and affect performance similarly during both rotation and translation.
A Framework for Memory Oversubscription Management in Graphics Processing Units

Modern discrete GPUs support unified memory and demand paging. Automatic management of data movement between CPU memory and GPU memory dramatically reduces developer effort. However, when application working sets exceed physical memory capacity, the resulting data movement can cause great performance loss. This paper proposes a memory management framework, called ETC, that transparently improves GPU performance under memory oversubscription using new techniques to overlap eviction latency of GPU pages, reduce thrashing cost, and increase effective memory capacity. Eviction latency can be hidden by eagerly creating space for demand-paged data with proactive eviction (E). Thrashing costs can be ameliorated with memory-aware throttling (T), which dynamically reduces \reviithe GPU parallelism when page fault frequencies become high. Capacity compression (C) can enable larger working sets without increasing physical memory capacity. No single technique fits all workloads, and, thus, ETC integrates proactive eviction, memory-aware throttling and capacity compression into a principled framework that dynamically selects the most effective combination of techniques, transparently to the running software. To this end, ETC categorizes applications into three categories: regular applications without data sharing across kernels, regular applications with data sharing across kernels, and irregular applications. Our evaluation shows that ETC fully mitigates the oversubscription overhead for regular applications without data sharing and delivers performance similar to the ideal unlimited GPU memory baseline. We also show that ETC outperforms the state-of-the-art baseline by 60.4% and 270% for regular applications with data sharing and irregular applications, respectively.
Therapeutic Synergy Between Antibiotics and Pulmonary Toll-Like Receptor 5 Stimulation in Antibiotic-Sensitive or -Resistant Pneumonia

Bacterial infections of the respiratory tract constitute a major cause of death worldwide. Given the constant rise in bacterial resistance to antibiotics, treatment failure is increasingly frequent. In this context, innovative therapeutic strategies are urgently needed. Stimulation of innate immune cells in the respiratory tract [via activation of Toll-like receptors (TLRs)] is an attractive approach for rapidly activating the body's immune defenses against a broad spectrum of microorganisms. Previous studies of the TLR5 agonist flagellin in animal models showed that standalone TLR stimulation does not result in the effective treatment of pneumococcal respiratory infection but does significantly improve the therapeutic outcome of concomitant antibiotic treatment. Here, we investigated the antibacterial interaction between antibiotic and intranasal flagellin in a mouse model of pneumococcal respiratory infection. Using various doses of orally administered amoxicillin or systemically administered cotrimoxazole, we found that the intranasal instillation of flagellin (a dose that promotes maximal lung pro-inflammatory responses) induces synergistic rather than additive antibacterial effects against antibiotic–susceptible pneumococcus. We next set up a model of infection with pneumococcus that is resistant to multiple antibiotics in the context of influenza superinfection. Remarkably, the combination of amoxicillin and flagellin effectively treated superinfection with the amoxicillin-resistant pneumococcus since the bacterial clearance was increased by more than 100-fold compared to standalone treatments. Our results also showed that, in response to flagellin, the lung tissue generated an innate immune response even though it had been damaged by the influenza virus and pneumococcal infections. In conclusion, we demonstrated that the selective boosting of lung innate immunity is a conceptually advantageous approach for improving the effectiveness of antibiotic treatment and fighting antibiotic-resistant bacteria.
Mental health and historical trauma among social workers working with victims of violent crime in South Africa

ABSTRACT The social work profession has become critical in assisting victims of violent crime at social service agencies in South Africa. Social workers have been spearheading efforts to help trauma victims at the expense of their mental health. For Black South African social workers, the mental burden of working with victim collides with historical trauma to create new ways of experiencing mental health challenges. The study aimed to explore the experiences of social workers working with victims of violent crime at select social service agencies in Johannesburg. The study was qualitative in nature and a case study design was used. Data was collected using in-depth interviews. The researchers used purposive sampling and data was analyzed using thematic analysis. Results from the study showed that Black South African social workers working in the field of violent crime face challenges such as prolonged sadness, emotional exhaustion and vicarious trauma. All these psychological problems are amplified by the fact that social workers in South Africa work under strenuous conditions. This increases the impact of psychological problems on social workers. Therefore, this paper argues that when the psychological effects of working with victims of violent crime, intersect with historical trauma, it produces unique ways of experiencing trauma for Black South African social workers. This study has strong implications for research about the health and wellbeing of social work practitioners working with trauma victims. The study exposes the need to prioritize the wellbeing of social workers especially those working in contexts with a traumatic past.
The “Hyper-Presence” of Cultural Heritage in Shaping Collective Memory

Abstract Virtual reality (VR) uses sensorial mimetics to construct collective memory in virtual space. The regeneration of high-definition cultural heritage symbols transforms memory into an immediate experience that is constantly being renewed, strengthens the relationship between cultural heritage and contemporary society, and continually affects the persistent renewal of cultural traditions. Hyper-presence is a networked state of cognitive psychology that lies in links, interactions, and exchanges; it is the result of networked social minds and distributed cognition. In the contemporary moment, cultural heritage takes on three types of progressively developed presence: simulated restoration presence, informationally reproduced presence, and symbolically regenerated presence. Symbolic regeneration belongs to the realm of hyper-presence. Building databases with data collected on cultural heritage is the foundation of building a cognitive agent. As a platform, VR becomes an efficient mode of information dissemination, forming an independent presence for cultural heritage through the reproduction of media and information. In a network society, informatized cultural heritage becomes a source for the production of new cultural symbols, and presence is created through the continuous regeneration and dissemination of symbols. Symbols and regenerated symbols combine to constitute the hyper-presence of informatized cultural heritage; people's understanding of cultural heritage therefore exists in an ever-changing state. Intelligences with presence on the network form a complete system, and VR creates comprehensive cognition for the system through high-definition virtuality. Formed in the coordination between intelligences, collective memory creates its hyper-presence today.
DNA barcoding of commercially important snapper species (Lutjaniformes; Lutjanidae; Lutjanus) from Visakhapatnam, Central Eastern coast of India

Abstract Snappers are commercially important fishes in Indian waters, currently belonging to the order Lutjaniformes, family Lutjanidae. Generally, recognizing species of Lutjanus is a challenging task not only because of overlapping morphological characters, such as shapes, size groups, or colour patterns, but also based on the definition of the species concept or the definition of the threshold for speciation. In India there has not been any updated and accurate study of the genus so far. Besides, identification of the group based on ecological aspects and DNA barcoding tools were confined to limited laboratories. In the present study, ten species of snappers were identified from samples obtained from the major fish landing centres in the Visakhapatnam, Central Eastern coast of India. Snapper species were identified using COI (Cytochrome oxidase I) sequences for DNA barcoding. The validity of the conjecture species-level taxonomy based on COI is assisted with high equivalence search (98–100%) both in BOLD and BLAST, well-distributed genetic distance values.
Synergistic Antiproliferative Effects of Co-nanoencapsulated Curcumin and Chrysin on MDA-MB-231 Breast Cancer Cells Through Upregulating miR-132 and miR-502c

Abstract In this study, we explored whether co-nanoencapsulated Curcumin (Cur) and Chrysin (Chr), natural herbal compounds with antitumor activities, regulate miR-132 and miR-502c and their downstream targets, leading to the synergistic growth inhibition in MDA-MB-231 breast cancer cells. For this purpose, Cur and Chr were co-encapsulated into PLGA-PEG nanoparticles (NPs) and characterized through DLS, FTIR and FE-SEM. MTT assay and cell cycle arrest analysis revealed that CurChr-loaded NPs had a considerable synergistic cytotoxicity against MDA-MB-231 cells with more cell accumulation in G2/M phase compared to the other groups. In addition, highest percentage of cell apoptosis was acquired in cells treated with CurChr-loaded NPs according to apoptosis analysis. Real-time PCR findings revealed that co-encapsulated form of Cur and Chr than free combination could further upregulate miR-132 and miR-502c expression (P < 0.001). Also, the strong reduction was detected in the protein levels of HN1 and P65 at the cells co-nanodelivered with Cur and Chr. These findings demonstrated that the co-nanodelivery of Cur and Chr through targeting miR-132 and miR-205c might be a novel strategy for the treatment of breast cancer.
Additive Margin Softmax with Center Loss for Face Recognition

In this paper, we propose a Convolutional Neural Network(CNN) model by combining Additive Margin Softmax with Center Loss for face recognition, which is denoted as AMS-CL. AMS-CL adopts the CNN network structure of ResNet50, which is pretrained on the FaceScrub dataset. In particular, AMS-CL exploits the Additive Margin Softmax (i.e., AM-softmax) to increase inter-class distance, avoiding overconfidence on face classifications. Furthermore, a regularization term for center loss is introduced by AMS-CL to decrease the intra-class distance simultaneously. Therefore, AMS-CL keeps beneficial inter-class and intra-class relations to classification tasks jointly. Alternatively, we propose to use classifiers on the hidden data representation achieved by AMS-CL to make predictions. Extensive experiments conducted on the LFW dataset show the effectiveness of the proposed AMS-CL model.