Miracle-dz/UniFAR-FTUs huggingface dataset:
A Review on the Resilient Response of Unsaturated Subgrade Soils

Considering the great contribution of subgrade modulus to the overall performance of roads or railways, it is crucial to provide the best prediction of resilient modulus for their foundations. Incorporating the seasonal variation of moisture content, the resilient modulus variation of unsaturated soils will be accurately predicted. This paper aims to introduce and discuss the knowledge about resilient response of unsaturated soils and emphasize the effects of humidity. A literature review on resilient response of unsaturated soils is presented based on the previous studies. The affecting factors (i.e., wetting and drying, moisture content, and matric suction) were discussed. The prediction model development of the resilient response of unsaturated soils was presented. The limitations and advantages of the model were analyzed and compared. It reveals that the current models were limited regarding stress conditions, moisture content, matric suction, and soil types, and further studies are still needed to achieve a better understanding of resilient response of unsaturated soils.
TRENDS AND GAPS IN DEVELOPMENT ASSISTANCE FOR HEALTH

After nearly a decade during which levels of external development assistance for health (DAH) stagnated, an encouraging rise has occurred in the volume of such assistance. Donors and developing countries are testing and implementing innovative approaches to the use of DAH, while simultaneously seeking ways to raise the effectiveness of existing streams of aid and more traditional financing mechanisms. In short, DAH has entered a dynamic phase that holds considerable promise. Nevertheless, it continues to suffer from a broad range of disappointments: misuse and inefficiency in the deployment of funds, gaps in essential areas that require financing support, and weaknesses in institutional and management arrangements. Substantial room for improvement exists. This chapter documents those recent trends, analyzes the effects and assesses the performance of DAH, and points to areas that require priority attention. In the first part, we present statistics on DAH, updating the World Development Report 1993 (World Bank 1993) and the report of the Commission on Macroeconomics and Health (CMH 2001). In the second part, we assess the performance of DAH. In the third part, we present recent innovations to underscore the current dynamic nature of such assistance. The chapter concludes with some suggestions on future directions.
Household Wealth Index, Nutritional Status And Dietary Practices Of Children Aged 6-59 Months In Mogadishu, Somalia

xv CHAPTER ONE: INTRODUCTION . 1 1.1 Background information . 1 1.2 Statement of the Problem . 2 1.3 Justification of the study . 3 1.4 Aim of the study . 3 1.5 Purpose of the Study . 4 1.6 Objectives . 4 1.6. 1 Overall Objectives . 4 1.7 Research questions . 4 CHAPTER TWO: LITERATURE REVIEW . 6 2.
Optimal Second Price Auctions with Positively Correlated Private Values and Limited Information

Closely related to the work of Athey and Haile (2002), we consider the problem of maximizing revenue in a second-price private-values auction with only limited data from previous auctions. We find that, when bidder values for the object being sold are not assumed to be distributed independently, the optimal levels of the reserve price and (when available) entry fee are not uniquely identified, and can vary over a significant range. Further, under two common representations of positively correlated values, the optimal values of these parameters tend to be lower than analysis assuming independence would have suggested. While this is written as a theory paper, the well-publicized use of auctions by the government (spectrum auctions, procurement auctions, and others) means that any work on how to best run an auction, and on the data requirements and difficulties in running an auction optimally, has clear policy implications.
SEMANTIC SEGMENTATION OF THE PROSTATE IN 3D MRI

Segmentation of the prostate in 3D MRI is of high clinical demand since it has high diagnostic value. However, there is a lack of accurate prostate segmentation methods. Semantic segmentation of the prostate in 3D MRI is a challenging task since there is a large variation of prostate shapes, there are different parameters used for acquisition of T2-weighted MRI of the prostate and the amount of provided training data is limited. The segmentation problem can be described as a pixel level boundary detection problem. In this paper we investigate different convolutional neural network architectures for segmentation of the prostate. First, we ﬁnd use of 3D context information necessary for high performance. We ﬁnd that use of dense connected fully covo-lutional neural networks has high segmentation performance. This is caused by the fact that dense convolutional neural networks has deep supervision properties, thus the architecture mitigates vanishing gradients. We show state of the art on the Promise-12 challenge with a dice coefﬁcient equal 0.898 on the validation set using 3D fully dense convolutional neural networks.
Modulation of the immune response byMiddle East respiratory syndrome coronavirus

Correspondence Fatemeh Farshadpour, Ph.D., The Persian Gulf Tropical Medicine Research Center, Bushehr University of Medical Sciences, Moallem Street, Bushehr 7514633341, Iran. Email: f.farshadpour@bpums.ac. ir; f.farshadpour@yahoo.com Abstract Coronavirus (CoV) infections are commonly associated with respiratory and enteric disease in humans and animals. In 2012, a new human disease called Middle East respiratory syndrome (MERS) emerged in the Middle East. MERS was caused by a virus that was originally called human coronavirus‐Erasmus Medical Center/2012 but was later renamed as Middle East respiratory syndrome coronavirus (MERS‐CoV). MERS‐CoV causes high fever, cough, acute respiratory tract infection, and multiorgan dysfunction that may eventually lead to the death of the infected individuals. The exact origin of MERS‐CoV remains unknown, but the transmission pattern and evidence from virological studies suggest that dromedary camels are the major reservoir host, from which human infections may sporadically occur through the zoonotic transmission. Human to human transmission also occurs in healthcare facilities and communities. Recent studies on Middle Eastern respiratory continue to highlight the need for further understanding the virus‐host interactions that govern disease severity and infection outcome. In this review, we have highlighted the major mechanisms of immune evasion strategies of MERS‐CoV. We have demonstrated that M, 4a, 4b proteins and Plppro of MERS‐CoV inhibit the type I interferon (IFN) and nuclear factor‐κB signaling pathways and therefore facilitate innate immune evasion. In addition, nonstructural protein 4a (NSP4a), NSP4b, and NSP15 inhibit double‐ stranded RNA sensors. Therefore, the mentioned proteins limit early induction of IFN and cause rapid apoptosis of macrophages. MERS‐CoV strongly inhibits the activation of T cells with downregulation of antigen presentation. In addition, uncontrolled secretion of interferon ɣ‐induced protein 10 and monocyte chemoattractant protein‐1 can suppress proliferation of human myeloid progenitor cells.
A Preliminary Study of an Emergency Department-based In-depth Injury Surveillance System of Preschool Children Injury

Purpose: To describe the use of an emergency department (ED)-based, in-depth injury surveillance system to determine the incidence and mechanism of preschool children injury. Methods: We prospectively studied and registered injured children under 7 years old, (n=5,921) whose injuries resulted in ED treatment from August 2006 to July 2008. We upgraded the checklist surveillance items, included place, accident mechanism, and agent factors. The ED physicians recorded the injury data on checklists in real time as they gave the ED orders. The recorded data were stored in computer networks and automatically coded, which enabled access to the raw data sources. The statistical data were calculated in detail by using relative frequency distribution from the raw data. Results: A total of 29,548 injured patients visited the ED from August 2006 to July 2008. Preschool children injuries, except those from traffic accidents, were 5,921(20.0%). The most common sources of injuries were from blunt trauma (37%), slips(17%), and falls(16%). Among those admitted to our hospital, fall injuries and inhalation of foreign body accidents accounted for 7.6% and 7.5%, respectively. The larger proportion of fall injuries occurred from a height of less than 1 meter(82.2%). The frequency of injury mechanism differed according to age: fall(35%), blunt(19%), and burn(14%) were noted under 1 year old, compared to blunt(34%), fall(14%), and slip(13%) from between 1 to under 3 years of age, and blunt(37%), slip(19%), and fall (11%) between 3 to under 7 years of age. Conclusion: The ED-based preschool children injury surveillance system could provide a useful and efficient method to determine injury incidence and injury-related factors.
An Investigation of the Relationship Between Schneiderian Membrane Thickness and Sinus Floor Cortication through Cone-beam Computed Tomography Schneiderian Membran Kalınlığı ile Sinüs Taban Kortikasyonu Arasındaki İlişkinin Konik Işınlı Bilgisayarlı Tomografi ile İncelenmesi

Seval Bayrak1, Gulbahar Ustaoglu2, Gozde Serindere3, Husniye Demirturk Kocasarac4 1 Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Bolu Abant İzzet Baysal University 2 Department of Periodontology, Faculty of Dentistry, Bolu Abant İzzet Baysal University 3 Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Hatay Mustafa Kemal University 4 Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Texas Health Science Center Abstract Aim: In this study, we aimed to investigate the relationship between sinus floor cortication (SFC) and Schneiderian membrane thickness (SMT) through cone-beam computed tomography (CBCT) images. Materials and Methods: A total of 292 maxillary sinuses of 146 patients (61 males, 85 females) who underwent a CBCT scan for dental implant treatment were evaluated. SFC was classified as follows: type-1: sinus floor exhibiting similar or higher density than the surrounding cortical areas, type-2: sinus floor exhibiting lower density than the surrounding cortical areas, type-3: sinus floor exhibiting no cortical bone, and type-4: sinus floor exhibiting fusion of sinus floor bone and native crestal bone. We also investigated the relationship between the SFC types and SMTs measured from the highest border of the membrane to the sinus floor on cross-sectional images. Results: Type-1, type-2, type-3, and type-4 SFC were seen in 114, 102, 48, and 28 cases, respectively. The Schneiderian membrane was found to be thinner in type-1 SFC than in type-2 SFC. No significant difference was found between type-3 and type-4 SFC in terms of SMT. Discussion and Conclusion: Evaluation of SFC and SMT using CBCT can provide information about implant stability and survival in treatment after sinus grafting. Although type-1 SFC is favorable for implant placement, it may also be associated with an increased risk of membrane perforation.
Keyphrase Extraction and Geospatial Characterizations for the Usage of Keyphrases

Keyphrase extraction is an important task in natural language processing. Keyphrases can, for instance, ease the process of summarizing a collection of documents by concisely describing each document. Furthermore, they facilitate the process of visualizing patterns that exist in textual documents, in addition to facilitating other tasks such as, categorization, clustering, indexing and searching. There are two main categories of automatic keyphrase extraction methods: the supervised approach that relies on training data, and the unsupervised method which tries to infer keyphrase relevance from statistics directly collected from a dataset. This project advances a proposal for a novel unsupervised method for keyphrase extraction, combining an approach based on centrality over a weighted graph with language modeling techniques. The new method will thus leverage an innovative combination of different approaches for estimating the importance of a keyphrase and the strength of the semantic relation between candidate keyphrases. Techniques used to estimate the degree of spatial auto-correlation in the usage of keyphrases were also incorporated into the new method, the goal being the capture of candidate keyphrase with interesting spatial distribution patterns (e.g., that are specific to a particular region). We tested the new methods on three different corpus commonly used for evaluating keyphrase extraction methods. The evaluation results indicate that this technique can approximate (and in some cases surpass) the results obtained by other state-of-the-art keyphrase extraction methods.
1 Historical Overview of Climate Change Science Coordinating Lead

Contributing Authors: M. Allen (UK), I. Auer (Austria), J. Biercamp (Germany), C. Covey (USA), J.R. Fleming (USA), R. García-Herrera (Spain), P. Gleckler (USA), J. Haigh (UK), G.C. Hegerl (USA, Germany), K. Isaksen (Norway), J. Jones (Germany, UK), J. Luterbacher (Switzerland), M. MacCracken (USA), J.E. Penner (USA), C. Pfister (Switzerland), E. Roeckner (Germany), B. Santer (USA), F. Schott (Germany), F. Sirocko (Germany), A. Staniforth (UK), T.F. Stocker (Switzerland), R.J. Stouffer (USA), K.E. Taylor (USA), K.E. Trenberth (USA), A. Weisheimer (ECMWF, Germany), M. Widmann (Germany, UK)
Foresighting Economic Spillovers Towards Transformative Change

This paper critically reviews the challenges and the opportunities that economic spillovers bring to different sectors. The purpose is to investigate how such spillover could be utilised for the benefit of slow-developing countries as Africa and the Middle East. The work of Karlsson et al. (2018) is used as the main reference for this study. The outcome of this study shows the importance of having the proper strategies, policies and the right clusters that support the positive exposure of the spillovers as per the country’s competitiveness advantage or needs. This work would have a further implication on the decision-makers and governments that are trying to re-invent their countries economic resources and boost its limited productivity.
Power Enhancement by PSO Regulatory Fuzzy Control of Inverter in Grid Tied Solar PV system

Solar energy available in large magnitude makes it a highly appealing source of electricity. Solar energy development is affordable and clean will have longer-term benefits. In this work we have first designed solar PV system in MATLAB/SIMULINK environment. The output DC is passed through DC/DC converter before its conversion to AC via a inverter. The inverter control is intended to be enhanced via AI techniques such that the power output is enhanced and improved so that this power can be further sent to the grid. The AI techniques chosen is PSO and fuzzy specifically designed for photovoltaic systems. The proposed system is also integrated with the wind energy system before its integration with grid to make the system more reliable. The system voltage is maintained constant to be 400 Volts. It was found that system designed with PSO regulatory FUZZY controller as seen considerable improvement in active power output from the system from approximately 3KW in conventional inverter to 8KW in the proposed scheme. IndexTerms Artificial Intelligence, Hysteresis, PSO, Fuzzy, HERS.
Sparsity-Based Robust Bistatic MIMO Radar Imaging in the Presence of Array Errors

A sparse recovery method for robust transmit-receive angle imaging in a bistatic MIMO radar is proposed to deal with the effect of array gain-phase errors. The impact of multiplicative array gain-phase errors is changed to be additive through model reformulation, and transmit-receive angle imaging is formulated to a sparse total least square signal problem. Then, an iterative algorithm is proposed to solve the optimization problem. Compared with existing methods, the proposed method can achieve a significant performance gain in the case that the number of snapshots is small. Simulation results verify the effectiveness of the proposed method.
DEPOSITION OF SIO2 NANOPARTICLES ON CELLULOSE FIBERS FOR DECREASING THEIR WATER ABSORPTION IN FIBER-CEMENT

One of the drawbacks in the use of cellulose fibers in fiber-cement products is their high water absorption, which leads to fiber mineralization in the Portland cement matrix. Thus, this study aimed to evaluate different reaction conditions for deposition of the SiO2 nanoparticles on the surface of cellulose pulp fibers, and their influence on the moisture adsorption of the hybrid organic-inorganic material formed. SiO2 nanoparticle deposition was done with the sol-gel process, testing four reaction times (2, 12, 18 and 24 h) and three contents (1.00, 2.25 and 4.50 mL) of the tetraethyl orthosilicate (TEOS) precursor. The modification time and TEOS precursor content directly influence the amount of Si deposited on the fiber surface, the nanoparticle diameter distribution, and the resistance to moisture adsorption. The moisture adsorption capacity of the modified cellulose fibers was reduced up to 50%. These results are interesting for ongoing research in the direction of fiber modification strategies for application of the cellulose fibers as durable reinforcement in cement based composites.
Applying a Modified Contingent Valuation Method (CVM) for the Preservation/Restoration of the Lake Kastoria in Northern Greece

The preservation/restoration of natural environment is frequently entailing excessive cost (paid by people through taxation) while it is a source of additional income for both, the State and the people, due to tourism. Since the evaluation of this good cannot be in market terms, we apply herein a modified version of the Contingent Valuation Method (CVM), which is used in Experimental Economics in order to investigate the significance that people put on this good and how much they might be willing to pay (WTP) for supporting activities concerning the preservation/restoration of Lake Kastoria. The WTP dependence on (i) external diseconomies, (ii) the expectations for property values’ rise as a result of the restoration, (iii) the proximity of interviewees’ residence to the lake, (iv) the opinion of the interviewee on the time and money spent to visit the lake, (v) the time and money the interviewees spent to visit the lake, as well as other dependencies (all taken as independent variables) are estimated by means of Logit, Probit, Logistic and Linear Regression Models.The preservation/restoration of natural environment is frequently entailing excessive cost (paid by people through taxation) while it is a source of additional income for both, the State and the people, due to tourism. Since the evaluation of this good cannot be in market terms, we apply herein a modified version of the Contingent Valuation Method (CVM), which is used in Experimental Economics in order to investigate the significance that people put on this good and how much they might be willing to pay (WTP) for supporting activities concerning the preservation/restoration of Lake Kastoria. The WTP dependence on (i) external diseconomies, (ii) the expectations for property values’ rise as a result of the restoration, (iii) the proximity of interviewees’ residence to the lake, (iv) the opinion of the interviewee on the time and money spent to visit the lake, (v) the time and money the interviewees spent to visit the lake, as well as other dependencies (all taken as independent variables) are estimated by .
Introducing Rack

Developing general web frameworks and frameworkless web applications is difficult because lots of different ways to connect to web servers need to be implemented. Since Ruby is popular for writing web applications, we try to address this problem by proposing a lightweight abstraction mapping HTTP requests onto a simple Ruby API. This makes it possible to combine all kinds of web servers with different web applications without further change. Furthermore, our solution enables new functionality by combining and composing web applications, as well as better testability.
THE EFFECT OF DIFFERENT DOSES OF GAMMA IRRADIATION ON THE ECHIS COLORATUS VENOM TOXICITY IN MICE

Snake venoms are complex mixtures of proteins and non proteins components. This study evaluated the toxicity effect of LD50 of native Echis coloratus venom and the LD50 of dry venom irradiated with different doses of gamma radiation (2, 5 & 10 KGy) on Swiss albino mice. Measurement of some biochemical parameters and histological alterations in liver and kidney was investigated. The biochemical parameters showed highly significant increase (P< 0.001) in levels of ALT, AST, urea and CK in all groups compared to control group. Levels of serum creatinine showed highly significant increase (P< 0.001) in groups treated with LD50 of crude venom and 5 times LD50 of irradiated venom at 2 and 10 KGy, But, showed significant (P< 0.05) with groups treated with 5 times LD50 of irradiated venom at 5KGy & LD50 of irradiated venomat 10 KGy showed non-significant in group treated with LD50 of 5KGy & 2KGy compared to control group. Histological examination showed alterations in liver, kidney in mice injected with crude venom compared to control group. Also, the group of mice which injected with different doses of irradiated venom showed no histopathological alteration in liver and kidney tissues, except the mice group injected with 5 times LD50 of irradiated venom at 2 KGy and the group which injected with 5 times LD50 of irradiated venom at 10 KGy which showed alterations in liver and kidney tissues.
Unit Visualizations for Visual Storytelling

This case study is conducted by Le Devoir, a French-Canadian independent daily newspaper based in Montreal. This newspaper gathers about 50~journalists and attracts around 1~million readers every week. In the last six months, we published several visual stories using uniform unit visualizations. This type of visualization represents each data item as a specific visual element of constant size (e.g. square, circle, etc.). This case study details why unit visualizations can be particularly efficient representations for data-based visual stories. We also highlight the challenges and perspectives of such practice.