Miracle-dz/UniFAR-FTUs huggingface dataset:
Melting at the Edge of a Slab in the Deepest Mantle

We analyzed new recordings of SPdKS seismic waveforms from a global set of broadband seismograms and horizontal tiltmeters from the Hi‐net array in Japan from 26 earthquakes in the Central American region. The anomalous waveforms are consistent with the presence of at least three ultralow‐velocity zones (ULVZs), on the core‐mantle boundary beneath northern Mexico and the southeastern United States. These ULVZs ring an area of high seismic wave speeds observed in tomographic models that has long been associated with past subduction. Waveform modeling using the PSVaxi method suggests that the ULVZs have S and P wave velocity decreases of 40% and 10%, respectively. These velocity decreases are likely best explained by a partially molten origin where the melt is generated through melting of mid‐ocean ridge basalt atop the subducted slab.
Unsupervised Alignment of Natural Language with Video

Today we encounter large amounts of video data, often accompanied with text descriptions (e.g., cooking videos and recipes, videos of wetlab experiments and protocols, movies and scripts). Extracting meaningful information from these multimodal sequences requires aligning the video frames with the corresponding sentences in the text. Previous methods for connecting language and videos relied on manual annotations, which are often tedious and expensive to collect. In this thesis, we focus on automatically aligning sentences with the corresponding video frames without any direct human supervision. We first propose two hierarchical generative alignment models, which jointly align each sentence with the corresponding video frames, and each noun in a sentence with the corresponding object in the video frames. Next, we propose several latent-variable discriminative alignment models, which incorporate rich features involving verbs and video actions, and outperform the generative models. Our alignment algorithms are primarily applied to align biological wetlab videos with text instructions. Furthermore, we extend our alignment models for automatically aligning movie scenes with associated scripts and learning word-level translations between language pairs for which bilingual training data is unavailable. Thesis: By exploiting the temporal ordering constraints between video and associated text, it is possible to automatically align the sentences in the text with the corresponding video frames without any direct human supervision.
Dynamic and Efficient Multicopy Provable Data Possession In Cloud Computing Systems

Cloud computing is a revolutionary computing paradigm which enables flexible, on-demand and low-cost usage of computing resources. Those advantages, ironically, are the causes of security and privacy problems, which emerge because the data owned by different users are stored in some cloud servers instead of under their own control. To deal with security problems, various schemes based on the Attribute-Based Encryption have been proposed recently. Data access control is an effective way to ensure the data security in the cloud. However, due to data outsourcing and untrusted cloud servers, the data access control becomes a challenging issue in cloud storage systems. Data security is the key concern in the distributed system. Various schemes based on the attribute-based encryption have been proposed to secure the cloud storage. However, most work focuses on the data contents privacy and the access control, while less attention is paid to the privilege control and the identity privacy. In this paper, we present a semianonymous privilege control scheme AnonyControl to address not only the data privacy, but also the user identity privacy in existing access control schemes. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semianonymity. Besides, it also generalizes the file access control to the privilege control, by which privileges of all operations on the cloud data can be managed in a fine-grained manner. Subsequently, we present the AnonyControl-F , which fully prevents the identity leakage and achieve the full anonymity. Our security analysis shows that both AnonyControl and AnonyControl-F are secure under the decisional bilinear Diffie–Hellman assumption, and our performance evaluation exhibits the feasibility of our schemes.
“This neighbourhood is killing us!” The impact of neighbourhood conditions on the health and wellbeing of people living in deprived neighbourhoods in Malta

A number of studies emphasise that the place of residence determines the health and wellbeing of its inhabitants. Although it is well known that similar to wealth, health varies across countries, few realise that the health and wellbeing of individuals also vary across local neighbourhoods. This qualitative study explores how the health and wellbeing of families living in deprived neighbourhood conditions in Malta are being affected due to the neighbourhood conditions. Participant parents and children narrate feelings of stigma experienced because of where they live and due to the physical conditions of their neighbourhood environment. Apart from the impact on the inhabitants’ self-esteem, the dilapidated neighbourhood environment reduces the possibility of enjoying social interaction with resourceful persons. This creates feelings of inequality and social exclusion which constrain these inhabitants from involving themselves in educational and cultural activities and thus inhibiting their wellbeing and the future success of their children. Moreover living in deprived neighbourhoods also puts the respondents at risk of ill-health and obesity due to the lack of adequately maintained open spaces for physical activity.
Data Security And Integrity Of Cloud StorageIn Cloud Computing

Cloud computing is the computing paradigm which enable obtaining resources like software, hardware, services over the internet. Most of user store their data on cloud for data security and integrity are prime related. In this article the problem of ensuring data integrity and security of data storage in cloud computing. For ensuring correctness of data, we assume the task of allowing a Third party auditor(TPA) used for exposing risk of cloud storage services on behalf of the cloud client to verify data integrity stored in the cloud. This paper focus on the data security, we proposed erasure correcting code in the file distribution to provide the redundancies and guarantee data dependability. By using homomorphic token with distributed verification of erasure coded data ,our scheme achieve storage correctness as well as error localization. Extensive security analysis show the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data alternation attack and even server colluding attacks.
Modeling and Designing of a Novel Lab-scale Passive Solar Still

The solar still is an emerging water distillation technology gaining popularity among the scientific community. Achieving a high throughput and/or performance in solar stills remains an unresolved challenge. In this study, the feasibility of utilizing solar distillation systems for large water production was investigated. A solar still was designed and tested with different brackish waters under solar insolation in Los Angeles from March to April. The inner surface area of the cell was about 12.7 cm 12.7 cm with a maximum volume of 322.6 cm 3 . The still performance was evaluated experimentally and modeled theoretically, showing a good agreement between theory and experiment. The maximum achieved efficiency was 20.54%, corresponding to a freshwater production of 384.4 mL/day·m 2 (6.2 mL/day). Lowering the feed amounts from 120 to 30 mL/day resulted in increasing the experimental performance from 6% to 18.3% due to the quick ramp in heat of vaporization; however, the production rates decreased from 446.4 to 341 mL/day·m 2 (7.2 to 5.5 mL/day). Polystyrene insulation and a blackened walls/basin can improve the performance by maintaining high temperature, decreasing heat loss, and enhancing solar absorption. It is concluded that still materials, insolation rate, and inclination angle are the most critical design factors.
İstatistiksel Veri Analizinde R Yazilimi ve Kullanimi* R Software and Its Use in Statistical Data Analysis*

The aim of this study is two old. It aims at introducing the R software at basic level as an analysis instrument which has been widespread in recent years and offers certain advantages in comparison to other statistical packages and identifying the frequency of the use of R and other packages in research in educational sciences published within the last 5 years in Turkey in 3 academic journals covered by the SSCI. Unlike the widely used statistical packages, R is an open-source software available free of charge with a dynamic structure constantly developed with the contributions of researchers from all over the world. Such a structure allows calculation of all kinds of statistical analysis which can be used by not only researchers in scientific research process but also teachers in school practices. The study was designed in descriptive survey model. It was found out that he R software was used in only one out of 1627 articles, while SPSS and Lisrel were the most frequently used statistical packages. It can be inferred from these findings that the R software has almost no use despite the significant advantages it offers. Hence, it is recommended to realize in-service training is held at universities in order to promote the use of the R software. SUMMARY
Modelling glacial abrupt climate changes and their impact on the Northern Hemisphere glacial ice sheets

During the last glacial period (LGP), the North Atlantic region experienced aseries of abrupt climate changes known as Dansgaard-Oeschger (D/O) eventswhich comprised rapid temperature excursions from cold to relatively mild climaticconditions and widespread impacts recurring on millennial time scales. Theprevailing paradigm to explain these glacial abrupt climate changes involves reorganisationsof the Atlantic meridional overturning circulation (AMOC). Coldclimatic conditions in the North Atlantic are thought to be associated to a weakAMOC regime in which the heat transport towards the North Atlantic is stronglydiminished, while relatively warm climatic conditions are thought to result froma reinvigoration of this northward heat transport. Freshwater uxes have beencommonly invoked to be responsible for perturbing the AMOC stability, thuspromoting these abrupt climate changes. However, there is still a high degreeof uncertainty regarding the origin and magnitude of these freshwater uxes, afactor that challenges the implication of this forcing in glacial abrupt climatechanges.
Tracking and managing non-point source pollution at Lake Herrick Watershed, Athens, Georgia

The Lake Allyn M. Herrick watershed is about 131 ha and covers portions of the University of Georgia’s East campus, the Oconee Forest and residential and commercial land use. Lake Herrick, a 6-ha water body established in 1982 on the University of Georgia campus, was closed in 2002 for recreation due to fecal contamination. Subsequent monitoring confirmed cyanobacterium blooms on the surface of the lake and elevated nutrient concentrations, especially phosphorus. Previous studies showed that phosphorus and fecal coliform were the main contaminants. In our study, two inflow tributaries (sites Birdsong and Armadillo) and the outlet stream (site Below Dam) were monitored for discharge, E. coli, forms of nitrogen and phosphorus, and other water quality parameters during baseflow and storm conditions from February 2016 to October 2017. Our results showed that total phosphorus was significantly higher during stormflow compared to baseflow and total nitrogen remained the same. E. coli results indicated that most of the bacteria entered the lake through the tributaries during stormflow. Microbial source tracking methods were used to detect the bacterial source in the samples specific to a dog, ruminant or human host. We found that dogs are a more likely source of this bacteria than humans or deer. The fact that human sources were uncommon in the Lake Herrick watershed indicated that there was reduced risk for human source contamination. Lake Herrick was reopened for limited recreation in October 2018. INDEX WORDS: water quality, nutrients, eutrophication, urban streams, fecal contamination, microbial source tracking TRACKING AND MANAGING NON-POINT SOURCE POLLUTION AT LAKE HERRICK WATERSHED, ATHENS, GEORGIA
Does rainfall variability matter for food security in developing countries ?

Abstract This paper contributes to the existing literature on rainfall variability and food security. It analyses the effect of rainfall variability on food security for 71 developing countries from 1960 to 2016. Results suggest that rainfall variability reduces food security in developing countries. Indeed, it reduces food availability per capita and increases the percentage of total undernourished population. Moreover, the negative effects of rainfall variability are exacerbated in the presence of civil conflicts and are high for the countries that are vulnerable to food price shocks.
Difficulties in explaining complex issues with maps.
Evaluating seismic hazard communication – the Swiss case

Abstract. 2.7 billion people live in areas where earthquakes causing at least slight damage have to be expected regularly. Providing information can potentially save lives and improve the resilience of a society. Maps are an established way to illustrate natural hazard. Despite of being mainly tailored to the requirements of professional users, they are often the only accessible information to help the public deciding about mitigation measures. There is evidence that hazard maps are frequently misconceived. Visual and textual characteristics as well as the manner of presentation have been shown to influence their comprehensibility. Using a real case, the material to communicate the updated seismic hazard model for Switzerland was analyzed in a representative online survey of the population (N = 491) and in two workshops involving architects and engineers not specializing in seismic retrofitting (N = 23). Although many best practice recommendations have been followed, the understanding of seismic hazard information remains challenging. Whereas most participants were able to distinguish hazardous from less hazardous areas, correctly interpreting detailed results and identifying the most suitable set of information for answering a given question proved demanding. We suggest scrutinizing current natural hazard communication strategies and empirically testing new products.
Image Source Identification Using Machine Learning Techniques

In digital forensics, identifying the model of the camera that was used to obtain a given digital image, presents an interesting problem. In a scene of a crime, it may help the forensic investigator to identify the camera that has taken the digital image used as evidence. The properties of the image given in the Exchangeable Image File Format are easy to modify and thus, cannot be authenticated. The exponential increase in digital image capturing devices in the past few years has further added to the problem. In this work, we aspire to provide experimental results and compare the accuracies generated by a number of two-class classifiers when fed with multiple features of images captured by two camera models, which help in the identification of the source camera model of the given image. Hence, to improve the efficiency of source identification, we strive to improve upon the classifiers in use.
Seasonal effect on biomarkers of exposure to petroleum hydrocarbons in the coasts of north western Suez Gulf, Egypt

Petroleum hydrocarbon profiles of surface water samples of the coasts of north western Suez Gulf, Egypt were assessed using standard analytical procedures. Water from surface levels) samples were collected from eight locations in the Gulf. Extraction of the petroleum hydrocarbons from the water samples collected and compounds were analytically determined with gas chromatography–flame ionization detector (GC‐FID) and quantified by integrating the areas of both the resolved and unresolved components. physical and chemical parameters of water such as PH values, conductivity, salinity, T.D. S, T.S. S, T.S, D.O. , BOD, COD, Cl-, SO4-, NO- and total alkalinity. Seasonal qualitative and quantitative studies have been carried out on the studied area. The concentration is relatively higher than recommended in the regulations of the Egyptian low of Environment of No.4/1994 of petroleum products especially crude oils at various locations dissolved petroleum hydrocarbons ranged from 5.639 up to 74.8 and 1.868 to 65.698 mg\ml for summer and winter seasons respectively. This probably indicates chronic oil pollution, in addition to hydrocarbon concentrations, the diagnostic indices used showed that the hydrocarbons in the area were from both biogenic, petrogenic and anthropogenic sources. On the other hand, FT-IR spectrometric analysis confirms the petrogenic nature of pollutants. More detailed studies are required to assess the changes in Suez Gulf water from different sources of pollution and monitoring should be conducted at least twice per year, serious commitment to application of environment low to the age of 1994 for the protection of water and beaches.
Controlled Consensus of Networked Delayed Multi-Agent Systems with Nonlinear Dyamics

This paper investigates the controlled consensus problem of Nonlinear Heterogeneous Networked Multi-Agent Systems (NHNMAS). The justified consensus criteria is obtained by means of the adaptive pinning control method and the proposed consensus criteria ensures all agent dynamics approach to the desired dynamic trajectories in the sense of estimable boundary. Compared with the case of linear ones discussed before, the results gotten here also reflect the nonlinear heterogeneous ones, and most of relevant results obtained via less complicated computation can be viewed as the special case of the present results. Finally, an numeric simulation is constructed to demonstrate the effectiveness of the proposed theoretical results.
Optimization techniques for arithmetic expressions

The increasing complexity of systems has spawned new directions in Design Automation research. System designers need the most sophisticated tools that can design applications of ever increasing complexity and meet the stringent requirements of performance and power consumption. Most of the popular embedded system applications perform some kind of continuous numeric processing which are computationally intensive. Examples of such computing can be found in multimedia applications such as 3-D computer graphics, audio and video processing and wireless communication applications. Traditionally system designers have often used hand written library routines for implementing these functions in software and custom Intellectual Property (IP) cores for hardware. Such an approach often does not give the best results since the results depend on the target architectures and the implementation constraints that are not taken into account in these libraries. Unfortunately, the currently available software compilers and high level synthesis frameworks have been designed for general purpose applications and do not do a good optimization of arithmetic expressions. As a result, there is an urgent need to come up with good tools that can take advantage of the flexibility of arithmetic expressions and provide the best solutions for their implementations. These methods then need to be integrated into the conventional optimization frameworks for software and/or hardware. This thesis highlights the opportunities available for the optimization of arithmetic expressions, and presents algebraic techniques for their optimization. The heart of these techniques is based on a novel canonical representation and methodology for eliminating redundant operations in arithmetic expressions. These techniques were applied for optimizing arithmetic functions in a number of popular applications, where significant performance, power and area savings were observed over the conventional techniques. This thesis also highlights the various factors that affect the delay and power consumption of these arithmetic expressions, and discusses some solutions that give the best result. Furthermore, the challenges of verifying the precision and range of these computations and their relationship with the various optimizations are studied.
Feasibility of Collaborative Learning with Robots Which Prompts Constructive Interaction

This paper reports feasibility of collaborative learning with educational-support robots between human. We designed a robot to prompt the constructive interaction. Constructive interaction has been regarded as a foundation of collaborative learning. Constructive interaction occurs when two students are solving the same question. Therefore, the robot is designed that alternately perform the speaker motion and listener motion to occur constructive interaction with human. In the speaker motion, the robot explains a solving method to the partner and solves a question. Moreover, the robot improves its accuracy rate as learning progress. In the listener motion, the robot does not solve a question and paying attention to a partner who is solving the questions. The robot learns while solving a question issued by learning system with a college student. The college students learned in the learning system with the robot for one month and were videoed during that time to see how they learned. This results of the study suggest that robot, which alternately solves the question with a human and improves its accuracy rate as learning progress, prompts learners to learning by constructive interaction with robot in collaborative learning. This constructive interaction indicates that learners alternately solve the question with robot and listen to robot’s speaking. However, learners interest in robot decrease when robot improves its accuracy rate at 100% and performs the same action. Additionally, the screen agent, which is designed same action as robot, does not prompt some learners to learning by constructive interaction because they feel lousy that screen agent could not solve the question correctly, so they ignore what the screen agent says. The same situation was occurred in some learners learning with robot.
Food Ontology Model for a Healthcare Service

유비쿼터스 정보기술이 의료서비스와 융합되면서 자가 건강관리에 필요한 다양한 형태의 콘텐츠에도 영향을 주고 있다. 특히 웹과 모바일 환경의 빠른 변화로 다량의 헬스케어 콘텐츠가 예상되기 때문에 검색의 효율성이 중요하다. 더구나 콘텐츠의 개인 맞춤형은 더 세밀하고 필요하며 단순한 키워드 중심의 검색방식에서도 환자 또는 사용자 요구와 특성에 맞도록 효율적인 검색방식이 필요하다. 따라서 콘텐츠의 의미를 시스템이 빠르게 이해할 수 있도록 정확한 시맨틱 검색이 필요하며 이를 위한 헬스케어 온톨로지를 모델링은 매우 의미 있다. 따라서 본 연구에서는 Protege 툴을 활용하여 헬스케어 콘텐츠 중 음식(Food) 클래스와 하위 클래스를 설계하고 각 클래스에 대한 제약조건 및 관계를 정의하여 실제 시스템에서 활용할 수 있는 시스템도 모델링하였다. 이렇게 모델링된 헬스케어 콘텐츠 온톨로지는 환자나 사용자들에게 원하는 정보를 신속하고 정확하게 검색할 수 있는 기반을 제공해준다.
Improved R-LKH Algorithm

Because some disadvantage of the R-LKH scheme which is one algorithm of the multicast rekeying, such as the inefficient rekeying andhigh computing spending of group controller and member, this paper proposes an improved R-LKH algorithm which increases the rekeyingefficiency and reduces the group traffic by adopting the efficient rekeying algorithm which combinies one-way function and random number.Itanalyses and compares the traffic of multicast and unicast when the members join or leave the group.The results show that the improved algorithmneeds less traffic and computing spending than the R-LKH.