Miracle-dz/UniFAR-FTUs huggingface dataset:
Can crowdsourcing be a mechanism for decentralised governance? A case study in the conﬂict mineral supply chain in the Democratic Republic of Congo

Can crowdsourcing can be used as a mechanism for governance, so as to achieve more fairness in ecosystems in the real world? To answer this question, the present thesis focuses on a use case of an ecosystem in the mining sector of the Democratic Republic of Congo. The stakeholders, their interests and relationships are analysed for this ecosystem, using conceptual modeling and ontology engineering techniques, enriched and supplemented with data from interviews with domain experts. The analysis reveals the governance structures for this ecosystem and shows that power imbalances - despite the introduction of a crowdsourcing platform - still negatively impact the whole supply chain and disempower those who are at the bottom of the supply chain. This thesis also provides a number of observations on the usefulness of conceptual modeling and ontology methods for this case study in the DR Congo.
SERVICE QUALITY DYNIAMICS AND BANK CUSTOMER LOYALTY : STUDY OF PT BANK CENTRAL ASIA Tbk BINTARO

This research aims to prove that the quality of service activities, the more performance of a bank exists. This study uses qualitative and quantitative analysis, where analysis is to determine the performance of bank services, qualitative analysis is to determine service quality, the relationship with customer loyalty, while quantitative analysis aims to determine the effect of service quality, will form perceived value which then affects satisfaction and loyalty. BCA customers in the future. Through the questionnaire data source using AMOS software. Based on the results of research that has been carried out, that PT Bank BCA Tbk in Bintaro, namely the quality of services provided to customers has a very large influence in achieving customer loyalty. This does not just happen because of the model that has been studied. The variable of service quality in achieving loyalty, was influenced by other variables. Then the variables that influence are the value perception variable and the image variable. The need to build good relationships with customers in addition to providing good service quality, so that other variables can be created. this model are answers to the two basic problems of making scientific conclusions in the social and behavioral sciences. The first problem related to measurement problems can be answered with a measurement model, while the second problem related to causal relationships can be answered using a latent variable model. Unlike other analytical techniques that can only measure unidirectional causal relationships, SEM also allows analyzing two-way relationships. that
Debugging Transient Faults in Data Center Networks using Synchronized Network-wide Packet Histories

Data center network faults are hard to debug due to their scale and complexity. With the prevalence of hard-to-reproduce transient faults, root-cause analysis of network faults is extremely difﬁcult due to unavailability of historical data, and inability to correlate the distributed data across the network. Often, it is not possible to ﬁnd the root cause using only switch-local information. To ﬁnd the root cause of such transient faults, we need: 1) Visibility : ﬁne-grained, packet-level and network-wide observability, 2) Retrospection : ability to get historical information before the fault occurs, and 3) Correlation : ability to correlate the information across the network. In this work, we present the design and implementation of S yNDB, a tool with the aforementioned capabilities to enable root cause analysis of network faults. We implement and evaluate S yNDB with realistic topologies using large scale simulation and programmable switches. Our evaluations show that S yNDB can capture and correlate packet records over sufﬁciently large time windows ( ∼ 4 ms), thus facilitating the root cause analysis of various network faults.
Just-In-Time Composition of Reconfigurable Overlays (Invited Talk)

This paper describes a framework supporting the automatic composition of reconfigurable overlays laid on top of an FPGA to offload computing-intensive sections of a given application, from an embedded processor to a loosely coupled reconfigurable accelerator. Overlays provide an abstraction layer acting as an intermediate fabric between users’ applications and the FPGA fabric. Among the existing flavors, the overlay template proposed in this work is based on a coarse-grain reconfigurable architecture featuring word-level operators, reducing long place-and-route times associated with FPGA designs. The proposed overlays are composed at run-time using a tile-based approach, in which pre-synthesized processing elements are stitched together following a 2D grid pattern and using dynamic and partial reconfiguration. The proposed reconfigurable architecture is accompanied by an automated toolchain that, relying on an LLVM intermediate representation, automatically converts the source code to a data-flow graph that is afterward mapped onto the overlay. A mapping example is provided in this paper to show the possibilities enabled by the framework, including loop mapping and loop unrolling support, features originally described in this work.
Web-based Supplementary Materials for ‘Handling Missing Data in Matched Case-Control Studies using Multiple

Web Appendix A: Proof that equation (1) implies (2) and vice versa First, suppose that equation (1) holds for any function q(S). Then G(x 1 ,x con 1 , . . . ,x cat M+1,x con M+1) = P (D = 1 |X = x 1 ,X con = x 1 ,S) ∏M+1 k=2 P (D = 0 |X cat = x k ,X con = x k ,S) ∑M+1 j=1 P (D = 1 |X cat = x j ,X con = x j ,S) ∏ k 6=j P (D = 0 |X cat = x k ,X con = x k ,S) = exp(β catx cat 1 + β ⊤ conx con 1 ) ∑M+1 j=1 exp(β ⊤ catx cat j + β ⊤ conx con j ) Second, suppose that equation (2) holds. Then G(x,x, 0, 0, . . . , 0, 0) = exp(β catx cat + β conx ) exp(β catx cat + β⊤ conx con) + M . Therefore exp(β catx cat + β conx ) exp(β catx cat + β⊤ conx con) + M . = P (D = 1 |X = x,X = x,S)P (D = 0 |X = 0,X = 0,S)
ScrutinAI: A Visual Analytics Approach for the Semantic Analysis of Deep Neural Network Predictions

We present ScrutinAI, a Visual Analytics approach to exploit semantic understanding for deep neural network (DNN) predictions analysis, focusing on models for object detection and semantic segmentation. Typical fields of application for such models, e.g. autonomous driving or healthcare, have a high demand for detecting and mitigating data-and model-inherent shortcomings. Our approach aims to help analysts use their semantic understanding to identify and investigate potential weaknesses in DNN models. ScrutinAI therefore includes interactive visualizations of the model’s inputs and outputs, interactive plots with linked brushing, and data filtering with textual queries on descriptive meta data. The tool fosters hypothesis driven knowledge generation which aids in understanding the model’s inner reasoning. Insights gained during the analysis process mitigate the “black-box character” of the DNN and thus support model improvement and generation of a safety argumentation for AI applications. We present a case study on the investigation of DNN models for pedestrian detection from the automotive domain.
Tempol decreases the levels of reactive oxygen species in human neutrophils and impairs their response to Mycobacterium tuberculosis

Background and aims : Mycobacterium tuberculosis (Mtb), the main causative agent of human tuberculosis (TB), remains as a serious public health problem. The innate immune response following Mtb infection plays a crucial role in preventing the onset of active TB and limiting its spread. Since phagocytes-derived reactive oxygen/nitrogen species (ROS/RNS) during the oxidative burst can fight Mtb, we hypothesized that the use of antioxidants could increase the host’s susceptibility to Mtb/TB. In that way, we investigated the effects of the nitroxide Tempol, an antioxidant with superoxide dismutase-like activity, on the response of neutrophils against Mtb. Methods : Human blood-derived neutrophils were isolated from healthy volunteers and incubated with Mtb (H37Ra) at different multiplicities of infection (MOIs), in the absence or presence of Tempol. The levels of ROS in neutrophils were evaluated using the cytochrome C reduction assay (extracellular O 2•- ) and luminol-(total intracellular and extracellular ROS) and isoluminol-(extracellular ROS) amplified chemiluminescence assay. The killing assay (two-step protocol) checked the mycobactericidal capacity of neutro-124 phils, as calculated the phagocytosis ( K p ) and intracellular killing ( K k ) rates. Results : The levels of ROS and killing capacity in Mtb-stimulated neutrophils were significantly decreased by 450 µM Tempol ( p < 0.05). Interestingly, Tempol decreased the k k of neutrophils, but did not affect their k p , demonstrating that a putative diminution in ROS levels, ultimately, affected the intracellular killing of Mtb. Conclusion : This study provides insights regarding the role of antioxidants on the neutrophil response toward Mtb, so that our findings deserve to be considered regarding further studies and clinical implications. DPI: Diphenyleneiodonium chloride; ETs: Extracellular traps; fMLP: N-formyl-methionyl-leucyl-phenylalanine; gp91 phox : 91-kDa glycoprotein of phagocyte oxidase INH: Isoniazid; KRG: Krebs-Ringer phosphate buffer; MФ: Macrophage; MDR: Multi drug-resistant tuberculosis; MOI: Multiplicity of infection; Mtb: Mycobacterium tuberculosis ; NAC: N-acetylcysteine; NADPH oxidase: Nicotinamide adenine dinucleotide phosphate oxidase; NETs: Neutrophil extracellular traps; NOS: Nitric oxide synthase; Nox: neutrophil oxidase; OD: Optical density; OS: Oxidative stress; PAMPs: Pathogen-associated molecular patterns; PBS: Phosphate-buffered saline; PMA: Phorbol 12-myristate 13-acetate; PMN: Polymorphonuclear neutrophil; PRR: Pattern recognition receptors; RNS: Reactive nitrogen species, ROS: Reactive oxygen species; SOD: Superoxide dismutase; TB:
Operating System Support for Safe and Efficient Auxiliary Execution

Modern applications run various auxiliary tasks. These tasks gain high observability and control by executing in the application address space, but doing so causes safety and performance issues. Running them in a separate process offers strong isolation but poor observability and control. In this paper, we propose special OS support for auxiliary tasks to address this challenge with an abstraction called orbit . An orbit task offers strong isolation. At the same time, it conveniently observes the main program with an automatic state synchronization feature. We implement the abstraction in the Linux kernel. We use orbit to port 7 existing auxiliary tasks and add one new task in 6 large applications. The evaluation shows that the orbit-version tasks have strong isolation with comparable performance of the original unsafe tasks.
Supplementary for Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation

Virtual adversarial training (VAT) [1] aims to produce a gradient-oriented perturbation that maximises the divergence between the prediction distributions of the original and perturbed inputs. After maximising the divergence between the predictions of the original and its perturbed version, the classification boundary will move towards the classification boundary, producing a more challenging classification sample that can improve training generalization. During training, the teachers ensemble predictions yield more accurate performance than the student predictions, as shown in Fig. 3-(b). This demonstrates that the teachers ensemble results follow more closely the true classification boundary than the student predictions. Therefore, the adversarial samples provided by the teachers (i.e., T-VAT) can be more ”accurate” to alter the student model’s gradient than the adversarial samples provided by the student.
Supplementary: Semantic-Aware Domain Generalized Semantic Segmentation

Existing DG methods [3, 11–13, 20] only focus on three domain generalization settings, i.e. (1) G → C, B, M, & S; (2) S → C, B, M, & G and (3) C → G, S, B, & M while losing the sight of the other two DG settings: (4) B → G, S, C, & M and (5) M → G, S, C, & M. However, recently several studies [2, 6] stress the importance of the last two settings. Therefore, we consider a more comprehensive evaluation which performs generalization from each of them. Results on the last two settings are reported in Tab. 1, suggesting that our model consistently achieves the state-of-the-art results on all settings and backbones.
Group-housed pigs and their body parts detection with Cascade Faster R-CNN

: The detection of individual pigs and their parts is a key step to realizing automatic recognition of group-housed pigs’ behavior by video monitoring. However, it is still difficult to accurately locate each individual pig and their body parts from video images of groups-housed pigs. To solve this problem, a Cascade Faster R-CNN Pig Detector (C-FRPD) was designed to detect the individual pigs and different parts of their body. Firstly, the features were extracted by 101-layers Residual Networks (ResNet-101) from video images of group-housed pigs, and the features were input into the region proposal networks (RPN) to obtain the region proposals. Then classification and bounding box regression on region proposals were performed to get the location of each pig. Finally, the body parts of the pig were determined by using the Cascade structure to search on the feature map of the pig body area. These operations completed the detection of the whole body of each pig and its different parts of the body, and established the association between the whole and parts of the body in the end-to-end detection. In this study, 1500 pig pen images were trained and tested. The test results showed that the detection accuracy of C-FRPD reached 98.4%. Compared with the Faster R-CNN without cascade structure, the average detection accuracy was increased by 4.3 percentage points. The average detection time of a single image was 259 ms. The method in this study could accurately detect and correlate the individual pig with its head, back, and tail in the image. This method can provide a technical reference for recognizing the behavior of group-housed pigs. and with
ASSESSING IMAGE QUALITY IMPACT OF VIEW BYPASS IN CLOUD RENDERING

Author: Stamm, Alex. MS Institution: Purdue University Degree Received: May 2019 Title: Assessing Image Quality Impact of View Bypass in Cloud Rendering Committee Chair: Tim McGraw The accessibility and flexibility of mobile devices make them an advantageous platform for gaming, but there are hardware limitations that impede the rendering of high-quality graphics. Rendering complex graphics on a mobile device typically results in a delayed image, also known as latency, and is a great discomfort for users of any real-time rendering experience. This study tests the image stream optimization View Bypass within a cloud gaming architecture, surpassing this imposing limitation by processing the high-quality game render on a remote computational server. A two sample for means test is performed to determine significance between two treatments: the control group without the View Bypass algorithm and the experimental group rendering with the View Bypass algorithm. A SSIM index score is calculated comparing the disparity between the remote server image output and the final mobile device image output after optimizations have been performed. This score indicates the overall image structural integrity difference between the two treatments and determines the quality and effectiveness of the tested algorithm.
Restoration of anterior teeth with different types of post and core: A case series.

Restoration of endodontically treated or fractured teeth is often considered as challenging. Fabrication of post core not only increases the fracture toughness of the tooth but also increases the retention of the prosthesis. The purpose of this case series is to discuss three different procedures of post and core fabrication in the anterior teeth. Pre-fabricated metal post with composite core, custom made metal post core and glass fiber post with composite core are three different treatment options which can be utilized to save the fractured teeth.
Solving large scale linear multicommodity flow problems with an active set strategy and proximal-accpm

In this paper, we propose to solve the linear multicommodity flow problem using a partial Lagrangian relaxation. The relaxation is restricted to the set of arcs that are likely to be saturated at the optimum. This set is itself approximated by an active set strategy. The partial Lagrangian dual is solved with Proximal-ACCPM, a variant of the analytic center cutting plane method. The new approach makes it possible to solve huge problems when few arcs are saturated at the optimum, as it appears to be the case in many practical problems. Acknowledgments. The work was partially supported by the Fonds National Suisse de la Recherche Scientifique, grant # 12-57093.99.
Anthropogenic threats to evolutionary heritage of angiosperms in the Netherlands through an increase in high-competition environments

Present biodiversity comprises the evolutionary heritage of Earth’s epochs. Lineages from particular epochs are often found in particular habitats, but whether current habitat decline threatens the heritage from particular epochs is unknown. We hypothesized that within a given region, humans threaten specifically habitats that harbor lineages from a particular geological epoch. We expect so because humans threaten environments that dominated and lineages that diversified during these epochs. We devised a new approach to quantify, per habitat type, diversification of lineages from different epochs. For Netherlands, one of the floristically and ecologically best-studied regions, we quantified the decline of habitat types and species in the past century. We defined habitat types based on vegetation classification and used existing ranking of decline of vegetation classes and species. Our suggest a If within many
Biodynamic timber sheet pile – vegetation retaining structure

Timber sheet pile walls are widely used for the protection of stream banks in different parts of the world. However, there is tendency of creating more sustainable types of stream banks not only because exploitable wood is more difficult to obtain, but also because of disturbance to the natural habitat of plants and animals due to hard embankments. In The Netherlands alone, about 2500 km of engineered timber sheet pile wall embankments exist, primarily made with tropical hardwood, apart from an even much larger amount of ´non-engineered´ small size timber based embankments. As an alternative, the authors propose to use a mixed timber sheet pile-vegetation system, where locally available timber can be applied in combination with natural vegetation. Unlike the usual bioengineering scheme, vegetation is not seen as an element, which could replace the timber sheet piles. Instead a new perspective is tested, where the vegetation is included as a ´structural´ element which will reduce or even counteract the consequences time dependent biological degradation of the timber sheet pile. By doing so, both long term durability as well as reliability of the stream bank are improved. We have developed a comprehensive design model, based on well-established sub- models from the literature on plant growth as well as timber service life. The timber sheet pile wall-vegetation system is illustrated in an example case study. Preliminary analysis including only the mechanical reinforcement of vegetation shows that the durability of timber sheet piles is enhanced. Thus, using vegetation in combination with highly degradable timber could possibly negate the need for using hardwood timber, or more generally, save resources that are currently used for these structures.
Spatially Distributed Hydrological Model

This manuscript has been co-authored by employees of Oak Ridge National Laboratory, managed by UT Battelle, LLC, under contract DE20 AC05-00OR22725, and Pacific Northwest National Laboratory, managed by Battelle, under contract DE-AC05-76RL01830 with the U.S. 21 Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the 22 United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this 23 manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these 24 results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access25 plan). 26
The challenges of artificial intelligence for Moroccan companies?

From deep learning to cognitive technology, artificial intelligence is everywhere in digital communication. It allows us to react more accurately to customers and engage them in meaningful, personalized interactions. In other words, without artificial intelligence, there is no digital consumer experience! The design of interactive user interface systems is a growing field of study that requires a wide range of skills, including psychology, artificial intelligence, software engineering and marketing. After a theoretical analysis, the objective of this article is to study the challenges of implementing its practices in relation to a country like Morocco in the different sectors that make up its economy, especially those focused on customer relations and experience.
COVID-19 epidemic scenarios into 2021 based on observed key superspreading events

Key high transmission dates for the year 2020 are used to create scenarios of the evolution of the COVID-19 pandemic in several states of Mexico for 2021. These scenarios are obtained through the estimation of a time-dependent contact rate, where the main assumption is that disease behavior is heavily determined by the mobility and social activity of the population during holidays and other important calendar dates. First, changes in the eﬀective contact rate on predetermined dates of 2020 are estimated. Then, this information is used to propose diﬀerent scenarios for the number of cases and deaths for 2021. The fundamental assumptions behind this methodology are that the eﬀective contact rate incorporates the main superspreading transmission events during last year, that each region has an independent epidemic not explicitly interconnected with other regions and, ﬁnally, that there are no new highly transmissible SARS-CoV-2 vari-Mario ants active during the timeline of the forecasts. Also, several levels of vaccination are considered to analyze their impact on the projections of the epidemic curve. The objective is to generate a range of scenarios that could be useful to evaluate the possible evolution of the epidemic and its likely impact on incidence and mortality.
Do learned representations respect causal relationships? (Supplementary Material)

Datasets are divided into subsets. Causal consistency is the ratio of subsets whose causal relation between representations matches that of the labels, with higher values representing higher consistency. Further, we compute average causal consistency (and confidence intervals) across a small interval K (ten) of epochs after representation learning has converged. Overall, Causal consistency =