Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of anthropogenic disturbance on primate density at the landscape scale

Accurate estimations of the abundance of threatened animal populations are required for assessment of species’ status and vulnerability and conservation planning. However, density estimation is usually difficult and resource demanding, so researchers often collect data at local scales. However, anthropogenic pressures most often have landscape‐level effects, for example, through habitat loss and fragmentation. We applied hierarchical distance sampling (HDS) to transect count data to determine the effect of habitat and anthropogenic factors on the density of 3 arboreal primate species inhabiting 5 distinct tropical forests across a landscape of 19,000 km2 in the Udzungwa Mountains of Tanzania. We developed a novel, multiregion extension of HDS that allowed us to model density and detectability jointly across forests without losing site‐specific information. For all species, the effect of anthropogenic disturbance on density was overwhelmingly negative among metapopulations: −0.63 Angolan colobus (Colobus angolensis palliatus) (95% Bayesian CI −1.03 to −0.27), −0.54 Udzungwa red colobus (Procolobus gordonorum) (−0.89 to −0.22), and −0.33 Sykes' monkey (Cercopithecus mitis monoides) (−0.63 to −0.07). Some responses to habitat factors were shared, notably the negative effect of elevation and the positive effect of climber coverage. These results are important for conservation science and practice because: the among‐populations negative responses to anthropogenic disturbance provides a foundation for development of conservation plans that hold at the landscape scale, which is a comprehensive and cost‐efficient approach; the among‐species consistency in responses suggests conservation measures may be generalized at the guild level, which is especially relevant given the functional importance of primates in tropical rainforests; and the greater primate densities in areas at low elevation, which are closer to human settlements, point to specific management recommendations, such as the creation of buffer zones and prioritization of areas for protection.
Estimation of Perceptual Surface Property Using Deep Networks With Attention Models

How we perceive property of surfaces with distinct geometry and reflectance under various illumination conditions is not fully understood. One widely studied approach to understanding perceptual surface property is to derive statistics from images of surfaces with the goal of constructing models that can estimate surface property attributes. This paper presents machine-learning-based methods to estimate the lightness and glossiness of surfaces. Instead of deriving image statistics and building estimation models on top of them, we use deep networks to estimate the perceptual surface property directly from surface images. We adopt the attention models in our networks to allow the networks to estimate the surface property based on features in certain parts of images. This approach can rule out image variations due to geometry, reflectance, and illumination when making the estimations. The networks are trained with perceptual lightness and glossiness data obtained from psychophysical experiments. The trained deep networks provide accurate estimations of the surface property that correlate well with human perception. The network performances are compared with various image statistics derived for the estimation of perceptual surface property.
A Security Design for the Detecting of Buffer Overflow Attacks in IoT Device

At present, the IoT devices face many kinds of software and hardware attacks, especially buffer overflow attacks. This paper presents an architectural-enhanced security hardware design to detect buffer overflow attacks. One part of the design is instructions monitoring and verification used to trace the execution behavior of programs. Another one is secure tag validation used to monitor the attributes of every memory segment. The automated extraction tools extract the monitoring model and secure tag of each memory segment at the compile time. At run-time, the designed hardware observes its dynamic execution trace and checks whether the trace conforms to the permissible behavior, if not the appropriate response mechanisms will be triggered. The proposed schemes don’t change the compiler or the existing instruction set and imposes no restriction to the software developer. The architectural design is implemented on an actual OR1200-FPGA platform. The experimental analysis shows that the proposed techniques can detect a wide range of buffer overflow attacks. And it takes low performance penalties and minimal overheads.
Stunted scale-up of a performance-based financing program on HIV and maternal–child health services in Mozambique — a policy analysis

Objective: A performance-based financing (PBF) program was implemented for services for HIV, prevention of mother-to-child transmission (PMTCT) and maternal/child health (MCH) in two provinces of Mozambique. This study investigates the determinants of policy scale-up to help accelerate the expansion of PBF in Mozambique and globally from pilot projects to national policies. Methods: A retrospective policy programme analysis was carried out using in-depth key informant interviews. A total of 24 interviews were conducted with stakeholders from donor agencies, the implementing NGO, district and provincial health offices, and the Ministry of Health. Results: Stakeholders reported that the scale-up process of PBF was influenced by three key determinants: political power, financial sustainability, and available capacity and evidence. In Mozambique, PBF scaled-up provincially but not nationally due to these determinants. The adoption of PBF in Mozambique involved a restricted range of policy actors at the central level and was strongly driven by the donor and a PBF champion. Provincial scale-up was fostered by political support and increasing capacity over time. Conclusion: There was a generalised ambivalence and lack of incentive to scale-up PBF from the implementing NGO. Coupled with the lack of evidence of a positive effect, and of cost-effectiveness in comparison with other models to improve health service delivery and health system strengthening, it is difficult to argue for the need to scale up the PBF programme studied. Care needs to be taken to base the adoption of health policies, including PBF, on a situational analysis and on evidence of intervention effectiveness, cost-benefits and contextual fit.
Investigation of AC Loss in HTS Cross-Conductor Cables for Electrical Power Transmission

This paper presents the alternating current (ac) loss analysis on high-temperature superconductor (HTS) cross-conductor (CroCo) cables, in order to evaluate whether they can be utilized for electrical power transmission. The modeling of HTS CroCo cables was based on a cable assembled at the Karlsruhe Institute of Technology and the ac-loss calculation was based on the H-formulation model implemented in the finite-element method software package COMSOL Multiphysics. The ac-loss calculations have been carried out for isolated single-phase and three-phase CroCo cables. The ac-loss angular dependence of a particular phase of CroCo cables during three-phase operation has been studied. The current distributions of individual tapes within CroCo cables have been investigated.
Successful rapid oral desensitization for dual hypersensitivity to isoniazid and rifampin while treating central nervous system tuberculosis

ABSTRACT Tuberculosis of the central nervous system (CNS-TB) is a critical disease with poor prognosis if not diagnosed and treated early. A regimen of drugs with good CNS penetration is required for treatment. Treatment options are limited in case of hypersensitivity reaction of the recommended regimen. We are reporting a rare instance where a patient developed hypersensitivity to both first line agents (isoniazid and rifampin) for CNS-TB and was successfully desensitized against both these medications to complete the treatment course using the rapid desensitization process. There have been reported cases of desensitization to anti tuberculous medications in cases with pulmonary tuberculosis and hypersensitivity reaction. In this review article we discuss the prior used methods of slow and rapid desensitization in case on non-CNS tuberculosis infections. This is the first reported case to use similar method of rapid desensitization in treatment of central nervous system infection.
Bone and Joint Tissue Penetration of the Staphylococcus-Selective Antibiotic Afabicin in Patients Undergoing Elective Hip Replacement Surgery

Afabicin (formerly Debio 1450, AFN-1720) is a prodrug of afabicin desphosphono (Debio 1452, AFN-1252), a novel antibiotic in development which targets the staphylococcal enoyl-acyl carrier protein reductase (FabI) and exhibits selective potent antibacterial activity against staphylococcal species, including methicillin-resistant Staphylococcus aureus. As part of clinical development in bone and joint infections, a distribution study in bone was performed in 17 patients who underwent elective hip replacement surgery. ABSTRACT Afabicin (formerly Debio 1450, AFN-1720) is a prodrug of afabicin desphosphono (Debio 1452, AFN-1252), a novel antibiotic in development which targets the staphylococcal enoyl-acyl carrier protein reductase (FabI) and exhibits selective potent antibacterial activity against staphylococcal species, including methicillin-resistant Staphylococcus aureus. As part of clinical development in bone and joint infections, a distribution study in bone was performed in 17 patients who underwent elective hip replacement surgery. Patients received 3 doses of 240 mg afabicin orally (every 12 h) at various time points before surgery. Afabicin desphosphono concentrations were measured by liquid chromatography-tandem mass spectrometry in plasma, cortical bone, cancellous bone, bone marrow, soft tissue, and synovial fluid collected during surgery at 2, 4, 6, or 12 h after the third afabicin dose. The study showed good penetration of afabicin desphosphono into bone tissues, with mean area under the curve ratios for cortical bone-, cancellous bone-, bone marrow-, soft tissue-, and synovial fluid-to-total plasma concentrations of 0.21, 0.40, 0.32, 0.35, and 0.61, respectively. When accounting for the free fraction in plasma (2%) and synovial fluid (9.4%), the mean ratio was 2.88, which is indicative of excellent penetration and which showed that the afabicin desphosphono concentration was beyond the MIC90 of S. aureus over the complete dosing interval. These findings, along with preclinical efficacy data, clinical efficacy data for skin and soft tissue staphylococcal infection, the availability of both intravenous and oral formulations, and potential advantages over broad-spectrum antibiotics for the treatment of staphylococcal bone or joint infections, support the clinical development of afabicin for bone and joint infections. (This study has been registered at ClinicalTrials.gov under identifier NCT02726438.)
It’s about Time: Ossification Center Formation in C57BL/6 Mice from E12–E16

The establishment of precise, high-resolution temporal sequences for morphogenetic events in laboratory mice remains a vexing issue in developmental biology. Mouse embryos collected at the same period of gestation, even those from the same litter, show wide variation in individual levels of progress along their developmental trajectory. Therefore, age at harvest does not provide sufficient information about developmental progress to serve as the basis for forming samples for the study of rapidly or near-simultaneously occurring events such as the sequence of ossification center formation. Here, we generate two measures of individual developmental progress (developmental age) for a large sample of mouse embryos using crown–rump lengths that measures size, and limbstaging ages produced by the embryonic Mouse Ontogenetic Staging System (eMOSS) that measure shape. Using these measures, we establish fine-grained sequences of ossification center appearance for mouse embryos. The two measures of developmental progress generate slightly different sequences of ossification center formation demonstrating that despite their tight correlation throughout the developmental period, size and shape are aspects of form that are at least partially dissociated in development.
Sparklis over PEGASE knowledge graph: a new tool for pharmacovigilance

Pharmacovigilance is in charge of studying the adverse effects of pharmaceutical products. In this field, pharmacovigilance specialists experience several difficulties when searching and exploring their patient data despite the existence of standardized terminologies (MedDRA). In this paper, we present our approach to enhance the way pharmacovigilance specialists perform search and exploration on their data. First, we have developed a knowledge graph that relies on the OntoADR ontology to semantically enrich the MedDRA terminology with SNOMED CT concepts, and that includes anonymized patient data from FAERS 3. Second, we have chosen and extended a semantic search tool, Sparklis, according to the user requirements that we have identified in pharmacovigilance. We report the results of a usability evaluation that has been performed by human factors specialists to check the benefits of our proposal.
Intrusion Detection Based on Parallel Intelligent Optimization Feature Extraction and Distributed Fuzzy Clustering in WSNs

Aiming at large-scale, high dimensional data, and variable intrusion behavior in wireless sensor networks (WSNs), an intrusion detection algorithm based on parallel intelligent optimization feature extraction and distributed fuzzy clustering for WSNs is proposed. First, in order to effectively reduce the data dimensionality and improve the robustness of the feature extraction process, the parallel intelligent optimization feature extraction framework is constructed on the basis of defining the optimal feature evaluation index, for which the theoretical analysis shows that the index can eliminate feature redundancy and maintain the diversity of original data. Second, the spider cluster optimization algorithm evolution rule is redefined by introducing local search and adaptive multi strategy update method, and it proves that the improved social spider optimization (ISSO) algorithm has global convergence. The ISSO is used to solve the feature extraction framework, and through the parallel feature subset selection process, the best feature combination is extracted. Finally, WSNs intrusion detection is carried out by using the best feature subset and the distributed fuzzy clustering technology, and intelligent iterative evolution method and adaptive clustering strategy are introduced in order to improve the fuzzy clustering algorithm performance. Experimental results show that the intrusion detection algorithm can effectively give the results of intrusion detection, and moreover, compared with the other detection algorithms, the intrusion detection rate is improved by about 13.1%, and the false detection rate is decreased by about 8.5%.
Artificial Intelligence for Medical Image Analysis: A Guide for Authors and Reviewers.

OBJECTIVE The purpose of this article is to highlight best practices for writing and reviewing articles on artificial intelligence for medical image analysis. CONCLUSION Artificial intelligence is in the early phases of application to medical imaging, and patient safety demands a commitment to sound methods and avoidance of rhetorical and overly optimistic claims. Adherence to best practices should elevate the quality of articles submitted to and published by clinical journals.
Community Evolution Model for Network Flow Based Multiple Object Tracking

Multiple object tracking is a research hotspot in the artificial intelligent field, and tracking-by-detection is one of the most popular paradigms in recent years. Among these methods, the network flow based tracker is quite popular due to its computational efficiency and optimality, but it still has one main drawback: Object detection is the processing unit, so high-order information is hard to be taken into consideration directly, and it is usually processed hierarchically, which leads to error propagation. To address this problem, we propose community evolution model for network flow based trackers. We introduce a novel community, which maintains detections and tracklets dynamically. The community allows modeling the connectivities of detections and tracklets jointly, which adaptively incorporates all-level correlations among detections and tracklets, including low-level optical flow, mid-level color histogram, and high-level ranking model. We demonstrate the validity of our method on PETS09 dataset and the MOT17 benchmark, and our method achieves competitive results. Our results on the MOT17 benchmark are available on the website.
A Technology-Based Classification of Firms: Can We Learn Something Looking Beyond Industry Classifications? †

In this work we use clustering techniques to identify groups of firms competing in similar technological markets. Our clustering properly highlights technological similarities grouping together firms normally classified in different industrial sectors. Technological development leads to a continuous changing structure of industries and firms. For this reason, we propose a data driven approach to classify firms together allowing for fast adaptation of the classification to the changing technological landscape. In this respect we differentiate from previous taxonomic exercises of industries and innovation which are based on more general common features. In our empirical application, we use patent data as a proxy for the firms’ capabilities of developing new solutions in different technological fields. On this basis, we extract what we define a Technologically Driven Classification (TDC). In order to validate the result of our exercise we use information theory to look at the amount of information explained by our clustering and the amount of information shared with an industrial classification. All-in-all, our approach provides a good grouping of firms on the basis of their technological capabilities and represents an attractive option to compare firms in the technological space and better characterise competition in technological markets.
Tennison: A Distributed SDN Framework for Scalable Network Security

Despite the relative maturity of the Internet, the computer networks of today are still susceptible to attack. The necessary distributed nature of networks for wide area connectivity has traditionally led to high cost and complexity in designing and implementing secure networks. With the introduction of software-defined networks (SDNs) and network functions virtualization, there are opportunities for efficient network threat detection and protection. SDN’s global view provides a means of monitoring and defense across the entire network. However, current SDN-based security systems are limited by a centralized framework that introduces significant control plane overhead, leading to the saturation of vital control links. In this paper, we introduce TENNISON, a novel distributed SDN security framework that combines the efficiency of SDN control and monitoring with the resilience and scalability of a distributed system. TENNISON offers effective and proportionate monitoring and remediation, compatibility with widely available networking hardware, support for legacy networks, and a modular and extensible distributed design. We demonstrate the effectiveness and capabilities of the TENNISON framework through the use of four attack scenarios. These highlight multiple levels of monitoring, rapid detection, and remediation, and provide a unique insight into the impact of multiple controllers on network attack detection at scale.
On the Significance of Periodic Structures in Applied Electromagnetics

Periodic structures have played a key role in applied electromagnetics in different contexts such as frequency selective surfaces, phased arrays. Relative size of the lattice periodicity as compared to operating wavelength has a strong bearing on the functionality of these structures. In other words, the functionality constrains the lattice size (also referred to as periodicity or cell size). Different ranges of periodicity lead to fundamentally different types of operation on the part of the periodic structure. Three examples will be discussed in this paper to further illustrate the impact of cell size on the response of the periodic structure. The first example will address the realization of a volume hologram using artificial dielectric technology which necessitates a 3D lattice size much smaller than the operating wavelength. A multi-band hybrid reflector-reflectarray configuration with a dedicated radiation signature at each band will be discussed next as an illustration of a periodic structure with a cell size of the same order as the operating wavelength. Finally, realization of a beam combiner using a Talbot grating will be presented as an example of a periodic structure that utilizes periodicity in excess of the operating wavelength.
User-Centric Joint Access-Backhaul Design for Full-Duplex Self-Backhauled Wireless Networks

Full-duplex self-backhauling is promising to provide cost-effective and flexible backhaul connectivity for ultra-dense wireless networks, but also poses a great challenge to resource management between the access and backhaul links. In this paper, we propose a user-centric joint access-backhaul transmission framework for full-duplex self-backhauled wireless networks. In the access link, user-centric clustering is adopted so that each user is cooperatively served by multiple small base stations (SBSs). In the backhaul link, user-centric multicast transmission is proposed so that each user’s message is treated as a common message and multicast to its serving SBS cluster. We first formulate an optimization problem to maximize the network weighted sum rate through joint access-backhaul beamforming and SBS clustering when global channel state information (CSI) is available. This problem is efficiently solved via the successive lower-bound maximization approach with a novel approximate objective function and the iterative link removal technique. We then extend the study to the stochastic joint access-backhaul beamforming optimization with partial CSI. Simulation results demonstrate the effectiveness of the proposed algorithms for both full CSI and partial CSI scenarios. They also show that the transmission design with partial CSI can greatly reduce the CSI overhead with little performance degradation.
Adaptive Second-Order Sliding Mode Fuzzy Control Based on Linear Feedback Strategy for Three-Phase Active Power Filter

The increasing use of nonlinear loads entails serious electrical energy quality problems in power grids. Active power filter could lead to significant improvement in harmonic compensation performance. In this paper, an adaptive second-order sliding mode fuzzy control based on linear feedback strategy for a three-phase active power filter is proposed to eliminate harmonics. This scheme is constituted by adaptive controller, second-order sliding mode controller, fuzzy controller, and linear feedback controller. The linear feedback controller can compensate the system’s nonlinearities and make the new system have a linear behavior between the input and output. Moreover, the second-order sliding mode controller could transfer the discontinuities in the controller and reduce system chattering. Simulation results illustrate the proposed controller has better performance compared with fuzzy control and adaptive sliding mode fuzzy control.