Miracle-dz/UniFAR-FTUs huggingface dataset:
A tool for the second generation vertical sounders radiance simulation: the GEISA/IASI spectroscopic database system

The development of the GEISA/IASI spectroscopic database is ongoing within the ISSWG (IASI-Infrared Atmospheric Sounding Interferometer- Sounding Science Working Group), in the frame of the CNES (Centre National d'Etudes Spatiales, France)/EUMETSAT (European organization for the exploitation of METeorological SATellites) Polar System (EPS) and the European Commission Environment and Climate Programme. The content, as well as the access and management facilities, of the version-2000 of the GEISA/IASI database system is described. It is developed and maintained at Laboratoire de Meteorologie Dynamique (LMD), France and EUMETSAT is planning to implement it within the EPS ground segment.
Evaluation of Tuberculosis Treatment Response With Serial C-Reactive Protein Measurements

Background Novel biomarkers are needed to assess response to antituberculosis therapy in smear-negative patients. Methods To evaluate the utility of CRP in monitoring response to antituberculosis therapy we conducted a post-hoc analysis on a cohort of adults with symptoms of tuberculosis and negative sputum smears in a high tuberculosis and HIV prevalence setting in KwaZulu-Natal, South Africa. Serial changes in CRP, weight, and haemoglobin were evaluated over 8 weeks. Results 421 participants with suspected smear-negative tuberculosis were enrolled and 33 excluded. 295 were treated for tuberculosis (137 confirmed, 158 possible), and 93 did not have tuberculosis. 185 of 215 (86%) participants who agreed to HIV testing were HIV-positive. At week 8, the on-treatment median CRP reduction in the tuberculosis group was 79.5% (IQR 25.4; 91.7), median weight gain 2.3% (IQR −1.0; 5.6), and median haemoglobin increase 7.0% (IQR 0.8; 18.9) (p-value <0.0001 for baseline to week 8 comparison of absolute median values). Only CRP changed significantly at week 2 (median reduction of 75.1% (IQR 46.9; 89.2) in the group with confirmed tuberculosis and 49.0% (IQR −0.4; 80.9) in the possible tuberculosis group. Failure of CRP to reduce to ≤55% of the baseline value at week 2 predicted hospitalization or death in both tuberculosis groups, with 99% negative predictive value. Conclusion Change in CRP may have utility in early evaluation of response to antituberculosis treatment and to identify those at increased risk of adverse outcomes. Key points C-reactive protein (CRP) falls by 80% after eight weeks of antituberculosis treatment. At two weeks sustained CRP elevation is associated with death or hospitalization.
Changes in Cortical Thickness in Patients With Early Parkinson’s Disease at Different Hoehn and Yahr Stages

Objectives: This study was designed to explore changes in cortical thickness in patients with early Parkinson’s disease (PD) at different Hoehn and Yahr (H-Y) stages and to demonstrate the association of abnormally altered brain regions with part III of the Unified Parkinson’s Disease Rating Scale (UPDRS-III). Materials and Methods: Sixty early PD patients and 29 age- and gender-matched healthy controls (HCs) were enrolled in this study. All PD patients underwent comprehensive clinical and neuropsychological evaluations and 3.0 T magnetic resonance scanning. Patients with H-Y stage ≤1.5 were included in the mild group, and all other patients were included in the moderate group. FreeSurfer software was used to calculate cortical thickness. We assessed the relationship between UPDRS-III and regional changes in cortical thinning, including the bilateral fusiform and the temporal lobe. Results: The average cortical thickness of the temporal pole, fusiform gyrus, insula of the left hemisphere and fusiform gyrus, isthmus cingulate cortex, inferior temporal gyrus, middle temporal cortex and posterior cingulate cortex of the right hemisphere exhibited significant decreasing trends in HCs group and PD groups (i.e., the mild group and moderate group). After controlling for the effects of age, gender, and disease duration, the UPDRS-III scores in patients with early PD were correlated with the cortical thickness of the left and right fusiform gyrus and the left temporal pole (p < 0.05). Conclusion: The average cortical thickness of specific brain regions reduced with increasing disease severity in early PD patients at different H-Y stages, and the UPDRS-III scores of early PD patients were correlated with cortical thickness of the bilateral fusiform gyrus and the left temporal pole.
High precision osmium stable isotope measurements by double spike MC-ICP-MS and N-TIMS

Osmium stable isotopes provide a new, potentially powerful tool with which to investigate a diverse range of geological processes including planetary formation, ore-genesis and weathering. In this paper, we present a new technique for high precision measurement of osmium (Os) stable isotope ratios by both Multiple-Collector Inductively Coupled Plasma Mass Spectrometry (MC-ICP-MS) and Negative ion Thermal Ionisation Mass Spectrometry (N-TIMS). We use a 188Os–190Os double spike, composed of 61% 188Os and 39% 190Os, to correct for mass dependent fractionation resulting from sample preparation and isotope measurement, with the ideal spike to sample ratio being 55 : 45. Isotope ratios are expressed as δ190Os which is the per mil deviation in the measured 190Os/188Os ratio relative to isotope reference material DROsS. Repeated analyses of double spiked DROsS for both MC-ICP-MS (n = 80 cycles) and N-TIMS (n = 280 cycles) show that an internal precision of 0.01–0.02‰ on δ190Os (2 se) can be attained, with a long-term reproducibility of 0.016‰ and 0.029‰ (2 sd; n = 91 and 83, respectively). The better reproducibility on MC-ICP-MS than on N-TIMS is, predominantly, due to measurement at higher beam intensities (11–18 V with consumption of ∼200 ng natural Os vs. 2–18 V with consumption of 2.3–45 ng natural Os, respectively). In addition to stable isotope compositions, our method allows for simultaneous measurement of 187Os/188Os and 186Os/188Os ratios with a precision of <40 ppm (2 se; 80 cycles for MC-ICP-MS and 280 cycles for N-TIMS) and an external reproducibility of 123–268 ppm and 234–361 ppm (2 sd; n = 91 for MC-ICP-MS and n = 83 for N-TIMS), respectively. We demonstrate that a similar precision and reproducibility can be obtained for other pure Os solutions as well as for geological materials. Furthermore, with a range of of analytical tests we evaluate and demonstrate the robustness of our method with regards to residual matrix effects and interference correction, signal intensity and on-peak zero on MC-ICP-MS, and the effect of oxygen corrections and isobaric interference on N-TIMS. Finally, we report the first Os stable isotope compositions for geological reference materials, including mantle peridotites and chromitites, and one ordinary chondrite.
Ultraviolet B radiation modifies circadian time in epidermal skin and in subcutaneous adipose tissue

Recent findings suggest that circadian time regulates cellular functions in the skin and may affect protection against ultraviolet radiation (UVR). It is not known, however, whether UVR through skin directly affects the expression of circadian genes. We investigated the effect of ultraviolet B (UVB) exposure on cryptochrome circadian clock 1 (CRY1), cryptochrome circadian clock 2 (CRY2), and circadian associated repressor of transcription (CIART) genes.
Metaheuristics in Telecommunication Systems: Network Design, Routing, and Allocation Problems

Recent advances in the telecommunication industry offer great opportunities to citizens and organizations in a globally connected world, but they also arise a vast number of complex challenges that decision makers must face. Some of these challenges can be modeled as combinatorial optimization problems (COPs). Frequently, these COPs are large-size, NP-hard, and must be solved in “real time,” which makes necessary the use of metaheuristics. The first goal of this paper is to provide a review on how metaheuristics have been used so far to deal with COPs associated with telecommunication systems, detecting the main trends and challenges. Particularly, the analysis focuses on the network design, routing, and allocation problems. In addition, due to the nature of these challenges, the paper discusses how the hybridization of metaheuristics with methodologies such as simulation and machine learning can be employed to extend the capabilities of metaheuristics when solving stochastic and dynamic COPs in the telecommunication industry.
Artificial Intelligence Defined 5G Radio Access Networks

Massive multiple-input multiple-output antenna systems, millimeter-wave communications, and ultra-dense networks have been widely perceived as the three key enablers that facilitate the development and deployment of 5G systems. This article discusses the intelligent agent that combines sensing, learning, and optimizing to facilitate these enablers. We present a flexible, rapidly deployable, and cross-layer artificial intelligence (AI)-based framework to enable the imminent and future demands on 5G and beyond. We present example AI-enabled 5G use cases that accommodate important 5G-specific capabilities and discuss the value of AI for enabling network evolution.
An Overview of Data-Driven Techniques for IT-Service-Management

High availability of information technology (IT)-applications and –infrastructure components is a significant factor for the success of organizations because more and more business processes depend entirely on IT-services. The result is that the complexity of IT-environments is permanently increasing and therefore cost intensive maintenance processes become more difficult. Several frameworks for IT-service-management like IT Infrastructure Library bundle established best practices to support the task of IT-service operating. This paper provides an overview of data-driven techniques, which can be used in addition to the standards of best practice frameworks to improve reactive and proactive maintenance tasks. We present a selection of different machine learning and statistical methods from a theoretical and practical perspective, which enable detailed insights into the IT-environment status. Furthermore, we present different approaches for the analysis of IT-service tickets, which are the primary communication path between the customer and service provider in case of issues. These methods enhance the resolution-finding process by a higher automatization level or by improvement of the situational understanding in case of root cause analysis and problem determination. Moreover, prediction of the future status allows the initiation of proactive actions to possibly prevent critical situations before their occurrence; existing methods, their potentials, and shortcomings as well are in the center of this paper. We close our overview with a systematic guide for practitioners to select the proper method for their setting, based on a series of questions about the application at hand.
Global dimension of tiled orders over commutative noetherian domains

Let R be a commutative noetherian domain and A = (A. ) C M (R ) be a tiled /? -order. The main result of this paper is the following Theorem. Let gl dim R = d < oo and A a triangular tiled R-order (i.e., A ■ R whenever i s /). Then the following three conditions are equivalent:
Sparsity-induced dynamic guided filtering approach for sparse-view data toward low-dose x-ray computed tomography

Iterative reconstruction (IR) methods that can incorporate filtering or regularization techniques have received widespread attention in many situations. Total variation (TV) regularization has proven to be a powerful tool to suppress streak artifacts and noise for sparse-view computed tomography (CT) reconstruction over 360°. However, with under-sampled projection data from limited-view (e.g. half-view) CT scanning, where the projections are further reduced, the edge structures are partly blurred, and some artifacts (such as blocky artifacts) are not effectively suppressed in TV-based results. To further improve the quality of the reconstructed image, a sparsity-induced dynamic guided image filtering reconstruction (SIDGIFR) method is proposed. Intermediate reconstruction results constrained by total difference (TD) minimization are taken as the guidance image to filter the results of projection onto convex sets (POCS) by guided image filtering (GIF). In the SIDGIFR algorithm, the guidance image is dynamically updated, which can transfer the important features (such as edge and small details) to the filtered image during the iterative process. To confirm the efficiency and feasibility of the SIDGIFR algorithm, simulated experiments and real data studies are performed. The quantitative evaluation shows that the proposed SIDGIFR method has better performance than other classical IR methods. What’s more, the proposed SIDGIFR algorithm can better preserve the edge structures, and suppress noise and artifacts, than the existing IR methods.
Ribosomal ambiguity (ram) mutations promote the open (off) to closed (on) transition and thereby increase miscoding

Abstract Decoding is thought to be governed by a conformational transition in the ribosome—open (off) to closed (on)—that occurs upon codon–anticodon pairing in the A site. Ribosomal ambiguity (ram) mutations increase miscoding and map to disparate regions, consistent with a role for ribosome dynamics in decoding, yet precisely how these mutations act has been unclear. Here, we solved crystal structures of 70S ribosomes harboring 16S ram mutations G299A and G347U in the absence A-site tRNA (A-tRNA) and in the presence of a near-cognate anticodon stem-loop (ASL). In the absence of an A-tRNA, each of the mutant ribosomes exhibits a partially closed (on) state. In the 70S-G347U structure, the 30S shoulder is rotated inward and intersubunit bridge B8 is disrupted. In the 70S-G299A structure, the 30S shoulder is rotated inward and decoding nucleotide G530 flips into the anti conformation. Both of these mutant ribosomes adopt the fully closed (on) conformation in the presence of near-cognate A-tRNA, just as they do with cognate A-tRNA. Thus, these ram mutations act by promoting the open (off) to closed (on) transition, albeit in somewhat distinct ways. This work reveals the functional importance of 30S shoulder rotation for productive aminoacylated-tRNA incorporation.
Impact of network protocols on data center applications

Data centers containing hundreds of thousands of servers have become the foundation of modern computing infrastructures. Enterprises are increasingly deploying new applications and moving existing applications to these large-scale data centers. These networked applications communicate via a set of conventional network protocols, which were originally designed for wide area networks. In this dissertation, we study the impact of different networking layer protocols on the performance of data center applications. At the transport layer, we observe that bandwidth sharing via TCP in commodity data center networks, which are organized in multi-rooted tree topologies, can lead to severe unfairness under many common traffic patterns. We term this phenomenon as the TCP Outcast problem. When a set of a large number of flows and another set of a small number of flows arrive at two input ports of a network switch and are destined to one common output port, the smaller set of flows loses out on its throughput share significantly. The Outcast problem occurs mainly in the taildrop queues that commodity switches use. Using careful analysis, we show that the taildrop queues exhibit a phenomenon known as port blackout, where a series of packets from one port are dropped. Port blackout affects the set of smaller number of flows more significantly, as these flows lose more consecutive packets leading to TCP timeouts. We show the existence of this TCP Outcast problem and its impact on MapReduce and file transfer applications. At the data link layer, we focus on a simple question: Should data center network operators turn on Ethernet jumbo frames? While prior work supports using jumbo frames for their throughput and CPU benefits, it is not clear whether these results are directly applica ble to modern data center networks. Most of the prior experiments were performed on older hardware, focusing mostly on TCP performance and not necessarily on the applicationlevel performance. In this dissertation, we evaluate the advantages of jumbo frames using modern hardware with features such as large send/receive offload, and with canonical data center applications such as MapReduce and tiered Web services. We find that the throughput and CPU utilization benefits still exist generally, although compared to prior studies, are significantly reduced. Based on these results, we conclude that data center network operators can safely turn jumbo frames on, despite a small side effect which we discovered.
Multimodality Fusion for Node Classification in D2D Communications

With the rapid development of 5G technology, D2D communications will be widely used in content distribution scenarios. An important prerequisite for realizing data transmission in D2D scenarios is to correctly classify each node in the network. However, most of existing node classification methods need huge computational overhead in large-scale networks. Inspired by network structure and attribute information, a multimodality fusion-based node classification scheme is proposed to obtain the tradeoff between classification accuracy and costs. First, in order to summarize label dependences to perform node classification, structure and information features are constructed. Structure features are obtained by embedding network data into a low-dimensional representation space, and information features are extracted from attribute information. Second, a multimodality fusion model is applied to integrate knowledge learned from different modalities, which can further improve the overall performance. Besides, the multilayer neural network based on softmax regression is used for multi-label classification. Finally, extensive experiments on two public datasets are conducted to verify the validity of the proposed scheme. Specifically, experimental results demonstrate the superior performance of our method over existing solutions in terms of accuracy and overhead.
A Study on Security Issues Caused by Ad Libraries in Smartphone Apps

—Many app developers would cooperate with ad networks by adding a procedural code (called ad library or ad lib) from ad providers into the app. The free apps will help them get into the market, and the ad will increase their income. To make ad more targeted at the needs of individual users, ad lib must collect personal information, including age, gender, income and something even more private, the habit of network use, and the location of users. It would automatically connect itself with the ad server to send out the personal information while receiving the ad reply from the ad server. Aside from pictures, it may include JavaScript for malicious acts and require the connection between the app and the third-party server to download malicious apps and automatically install and run them under the background. To make more profits from ads, many app developers embed more than one ad libs into an app, i.e., connecting to several ad providers, so as to make the security problem ever worse. Using the machine learning on the static program analysis, this paper developed an anti-ad app called Ad Pioneer . Users can adopt Ad Pioneer to check the security of an app’s ad, so as to prevent personal information leaking.
Modeling of ICPF (ionic conducting polymer film) actuator-modeling of electrical characteristics

The ionic conducting polymer film (ICPF) actuator is a filmy composite made of a perfluorosulfonic acid (PFS) membrane sandwiched between porous platinum layers. It can be driven by direct voltage input to its surfaces in wet condition. In this study, the electrical characteristics of the actuator were investigated. The electrical characteristics of the actuator were represented by the surface resistances of the porous platinum layers, resistance of the gel membrane permeated with water, and a series connection of resistance and capacitance. The model was composed of a distributed-constant system of the above elements. Moreover, the distributed current through the series connection of resistance and capacitance was possibly concerned with the generation of internal stresses causing the actuator to bend.
A Survey of IoT-Enabled Cyberattacks: Assessing Attack Paths to Critical Infrastructures and Services

As the deployment of Internet of Things (IoT) is experiencing an exponential growth, it is no surprise that many recent cyber attacks are IoT-enabled: the attacker initially exploits some vulnerable IoT technology as a first step toward compromising a critical system that is connected, in some way, with the IoT. For some sectors, like industry, smart grids, transportation, and medical services, the significance of such attacks is obvious, since IoT technologies are part of critical back-end systems. However, in sectors where IoT is usually at the end-user side, like smart homes, such attacks can be underestimated, since not all possible attack paths are examined. In this paper, we survey IoT-enabled cyber attacks, found in all application domains since 2010. For each sector, we emphasize on the latest, verified IoT-enabled attacks, based on known real-world incidents and published proof-of-concept attacks. We methodologically analyze representative attacks that demonstrate direct, indirect, and subliminal attack paths against critical targets. Our goal is threefold: 1) to assess IoT-enabled cyber attacks in a risk-like approach, in order to demonstrate their current threat landscape; 2) to identify hidden and subliminal IoT-enabled attack paths against critical infrastructures and services; and 3) to examine mitigation strategies for all application domains.
A progress preserving refinement

Designing correct parallel programs is a difficult challenge, because of the interleaving nature of the execution of processes. Event-B has improved on the situation by applying the techniques of refinement to the design of parallel algorithms in such a way that safety properties can be integrated into the design one gradually. Unfortunately, it does not cover the notion of progress, that is to say that nothing prevents a refinement in Event-B from introducing individual starvation. In UNITY, temporal properties (both safety and liveness) are part of a comprehensive program logic. However, the distinction that UNITY makes regarding specifications – sets of temporal properties –, and programs – action systems –, rules out the possibility of developing programs in a stepwise fashion. In this thesis, we provide a model for the UNITY logic and use it to define a refinement order and a set of refinement laws which will enable the symbols of our specifications to do the work in the process of refinement. By taking progress properties as a guideline for the development, the addition of new actions to an existing specification is motivated by a direct mapping to the requirement of progress rather than a vague understanding of what it might achieve. The result of our work is a modelling method called Unit-B, combining refinement and the reasoning about progress properties.
Nadelige gezondheidseffecten en ziekten veroorzaakt door chroom-6 : Indeling in categorieën van causaliteit in relatie tot chroom-6-blootstelling

Dit rapport maakt onderdeel uit van een serie van tien rapporten over het onderzoek naar chroom-6 bij tROM Tilburg. Dit rapport bevat geen afzonderlijke publiekssamenvatting. Een overkoepelende publiekssamenvatting van de tien rapporten is te vinden op de website van het RIVM: "Chroom-6 bij het re-integratieproject tROM: gezondheidsrisico's en verantwoordelijkheden - Bevindingen uit het onderzoek op hoofdlijnen (RIVM Rapport 2018-0164)"