Miracle-dz/UniFAR-FTUs huggingface dataset:
Compact Leakage-Free Support for Integrity and Reliability

The memory system is vulnerable to a number of security breaches, e.g., an attacker can interfere with program execution by disrupting values stored in memory. Modern Intel® Software Guard Extension (SGX) systems already support integrity trees to detect such malicious behavior. However, in spite of recent innovations, the bandwidth overhead of integrity+replay protection is non-trivial; state-of-the-art solutions like Synergy introduce average slowdowns of $2.3 \times$ for memory-intensive benchmarks. Prior work also implements a tree that is shared by multiple applications, thus introducing a potential side channel. In this work, we build on the Synergy and SGX baselines, and introduce three new techniques. First, we isolate each application by implementing a separate integrity tree and metadata cache for each application; this improves metadata cache efficiency and improves performance by 39%, while eliminating the potential side channel. Second, we reduce the footprint of the metadata. Synergy uses a combination of integrity and error correction metadata to provide low-overhead support for both. We share error correction metadata across multiple blocks, thus lowering its footprint (by $16 \times$) while preventing error correction only in rare corner cases. However, we discover that shared error correction metadata, even with caching, does not improve performance. Third, we observe that thanks to its lower footprint, the error correction metadata can be embedded into the integrity tree. This reduces the metadata blocks that must be accessed to support both integrity verification and chipkill reliability. The proposed Isolated Tree with Embedded Shared Parity (ITESP) yields an overall performance improvement of 64%, relative to baseline Synergy.
An empirical analysis of macroeconomic forecasting with a univariate and a multivariate time series model

This paper evaluates macroeconomic forecasts from a univariate ARIMA model and an unrestricted VAR model. The univariate model considered is a fitted model, and an AR(1) model is used as a benchmark. The variables that are used are the US and the UK real GDP, GDP deflator and the unemployment rate, using data from 1971 to 2002. Conclusions are that a VAR model is better in forecasting the US unemployment rate than a univariate model, while an AR(1) model performs better for the UK unemployment rate at the one-quarter horizon. However, it also shows that a univariate model provides better forecasts for the GDP deflator. The results are ambiguous for the real GDP, where most of the results are not significant. Except the US series, where it is confirmed that an AR(1) model perform better at the one quarter ahead horizon.
The effect of shrub clearing and grazing on the composition of a Mediterranean plant community: functional groups versus species

Fuel-breaks to impede the spread of fires in Medi- terranean woody vegetation are created by clearing of shrubs, followed by very intensive cattle grazing before the fire season. The present research analysed the effects of these two distur- bance types on herbaceous community composition at the func- tional group and the species level, by using canonical discrimi- nant ordination analysis and by categorical modeling methods. Grazing caused an increase in the abundance of small species, geophytes, and species with an early flowering period that ends before the grazing period. The abundance of many different species increased as a result of clearing. However, no associa- tion was found between positive or negative response to clear- ing and any species attribute tested. Several a priori functional groups defined by life form and family showed responses to either grazing or clearing. Links between these responses and individual species attributes are discussed. The results empha- size the different nature of the two disturbances: grazing as a selective agent, and shrub clearing as a generalized one. It also stresses the importance of the plant architecture and the mor- phological and phenological niche in determining community composition under extremely intensive grazing conditions.
LANGUAGE MODELS FOR UNSUPERVISED ACQUISITION OF MEDICAL KNOWLEDGE FROM NATURAL LANGUAGE TEXTS : APPLICATION FOR DIAGNOSIS PREDICTION

Following recent success of neural language models in various downstream language understanding tasks, including common sense reasoning, we investigate possible utility of such models in domain specific reasoning task— proposing of preliminary diagnosis based on patient complains, presented as natural language text. We demonstrate that language model, trained on the texts collected from online medical forums posses significant accuracy in this task (73% at top 10 suggestions), when evaluated on dataset, constructed from clinical case reports, published in specialized medical journals. While preliminary, these findings indicate a possible new method that can be used to augment online symptoms checkers and clinical decision support systems.
A SEMANTIC QUESTION CLASSIFICATION FOR QUESTION ANSWERING SYSTEM USING LINKED OPEN DATA APPROACH

Semantic question answering (SQA) was the research study regarding the natural language processing. The purposes of this study were 1) to encourage the users to query via the computer with the semantic natural language, and 2) to obtain the concise, accurate, and relevant to the users’ needs. Recently, it was found that the research studies have encountered the problems with semantic communication, flexibility, and accuracy of processes, especially the process of question classification. It was considered the vital process of developing the semantic question answering system. Thus, this paper attempted to propose a semantic question classification for the question answering system using the linked open data approach. It proposed the problem-solving technique for question classification through semantic grammar rules derived from the questions based on principles of English grammar. Moreover, the linked open data, WordNet and DBpedia were implemented to solve the problems of words similarity and question classification through the question classification taxonomy consisting of six main classes and fifty subclasses as standards for question classification. Besides this, the dataset from the question sets of TREC with one thousand questions were also implemented. The evaluation indicated a high accuracy of question classification with the total scores of precision, recall, and F-measure, at 92.82%, 95.16%, and 93.97%, respectively.
DEVELOPING THE SECURITY THREAT DETECTION MODEL FOR THE WEB SERVICE USING DEEP NEURAL NETWORK

The co-evolution of broadband networks and intelligent information system development ushers present golden days of web service. However, cyber attackers find loopholes easily for security threats under the web service environment. Detection of web service attacks requires to develop a new security threat counter-measure differentiated from the existing either signature-based or anomaly-based algorithms. In this regard, this research introduces a state-of-the-art intrusion detection model specialized in cyber-attacks on the web-service using the combination of deep neural network algorithms. Then, we evaluate the intrusion detection performance of the proposed deep neural network models with the Big Data of real time network traffic. Our research helps improve the limitation of existing intrusion detection systems and to overcome web service vulnerability on cyber threats.
Polymorphic microsatellites in largemouth bronze gudgeon (Coreius guichenoti) developed from repeat-enriched libraries and cross-species amplifications

Largemouth bronze gudgeon (Coreius guichenoti) is a medium-sized fish endemic from the upper Yangtze River of China and its survival is threatened by the construction of the Three Gorges Dam. This study reports 20 new polymorphic microsatellites from a repeat-enriched genomic library with a mean number allele of 5.2, and observed and expected heterozygosities ranging from 0.035 to 1, and from 0.13 to 0.917, respectively. In a cross-species amplification test, nine of the 37 tested loci were found to be also polymorphic in a congeneric species, brass gudgeon (C. heterodon). In addition, other four loci from common carp (Cyprinus carpio) were also polymorphic in C. guichenoti. Out of these 24 polymorphic microsatellites, only three loci significantly deviated from Hardy-Weinberg equilibrium in the sampled population (P l 0.0025), and all pairwise tests for linkage disequilibrium among loci were nonsignificant after applying sequential Bonferroni correction (P g 0.0026). These novel microsatellites provide sufficient levels of polymorphism for studies on population genetics and conservation in C. guichenoti and its related species.
Deterioration of Islet β-Cell Function After Hemipancreatectomy in Dogs

The metabolic consequences of hemipancreatectomy in living pancreas donors were tested in a dog model in which a 50% lobe-specific pancreatectomy was performed. Removal of the dorsal lobe (analogous to a donor, n = 4) resulted in a progressive increase in fasting glucose during 12 mo from 5.32 ± 0.16 to 8.17 ± 0.28 mM and a decrease in fasting insulin from 54 ± 3 to 6.0 ± 2.4pM and glucose clearance (Kg) from 3.00 ± 0.22 to 1.00 ± 0.06 mM. Removal of the ventral lobe (analogous to a recipient, n = 5)did not result in a change in fasting glucose or Kg during 12 mo, although fasting insulin was reduced from 36.0 ± 1.8 to 18.00 ± 1.93 pM. In vitro perfusion of the remnants after 1 yr showed a deterioration in glucose-stimulated insulin secretion (5–11 mM) by the dorsal remnant (18 ± 11 vs., 232 ± 37%) and the ventral remnant (2.6 ± 19 vs. 87 ± 13%). The dorsal remnant had a higher response than the ventral remnant (46 ± 23 vs. −16 ± 10%, respectively) to severe hyperglucosuria (11–27.7 mM). Insulin content was unchanged in the dorsal remnant (224 ± 16 vs. 180 ± 14μg/g), but was reduced in the ventral remnant (65 ± 14 vs. 154 ± 15μg/g). Invitro insulin pulse intervals were reduced in both remnants (5.3 ± 0.2 min vs. control 7.00 ± 0.18 min). Because of the above effects on the donor when the dorsallobe is removed, the continued use of hemipancreatectomy as a source of transplantable tissue must be questioned.
Effect of Allergic Rhinitis on Eustachian Tube Function and Middle Ear Ventilation

Introduction: Allergic Rhinitis is considered to be one of the most common diseases affecting a wide range of people barring age. Approximately 20% of adults and children have seasonal or perennial allergic rhinitis. Allergic rhinitis patients often suffer from like asthma, sinusitis ,otitis media and decreased hearing. So we decided to do study of eustachian tube function and middle ear ventilation in patients of allergic rhinitis. Aims:The purpose of this study was to assess the effect of allergic rhinitis on Eustachian tube function (ETF) and middle ear ventilation. Methods:This prospective study involved 100 Patients so 200 ears were studied. All patients of allergic rhinitis were evaluated on their first visit and assess the impedance tympanometry and Eustachian tube function was done and noted.AllPatients were prescribed ant allergic medication antihistamine and steroids nasal spray as per their liking at first visit . On their second visit after six week of first visit the process was repeated and results were compared. Results:There was statically significance increase in the proportion of type-Atympangram cases at first visit was42ears[21%]when compared second visitwas176ears [88%](P<0.05). At first visit value of middle ear pressure ranged from -150 to 4 daPa, means was -123 and at second visit middle ear pressure was from -75 to 4 and means was -11, with a statically significant improvement in middle ear pressure(P<0.05). Those patients had allergic rhinitis and poor ETF, seen significant improvement ETF at 6 week after anti allergic treatment. (P<0.05) Conclusion: We find out that allergic rhinitis has a definite relationship with ETF. Antiallergic treatment has a favorable effect on the middle ear pressure and ETF.
DBPEDIA BASED INFORMATION EXTRACTION FROM UNSTRUCTURED DATA

and entities by linking it to its semantic description available in the linked formal description that is the ontology. The presented technique is related to knowledge representation and has vast scope to support the development of the Semantic Web. An ontology is a formal and explicit specification of a shared conceptualization. Conceptualization refers to an abstract model of some phenomenon occurring in the world by having identified the relevant concepts of that phenomenon. Explicit refers to the type of concepts used and the constraints on their handling are defined clearly and concisely. Formal refers to the notion that the ontology should be machine readable and understandable. Shared points to the constraint that the ontology captures consensual knowledge, that is it should be widely acceptable and procurable. To sum up, the nucleus of an ontology is a data model for expressing and clearly describing the entities in the world. The model essentially contains a set of types, properties and relationship types. DBpedia is one such ontological model derived from Wikipedia. The concepts from Wikipedia are collected using its structured counterpart-the DBpedia ontology for further mining and extracting the mentions of the named entities from the unstructured text data under experimentation. It is a common observation that the text in news articles is often abounded with names of persons, places, organizations, time, spatial information etc. In the experiment, the text is annotated with the structured content derived from DBpedia using the GATE developer environment [5] and rules written in JAPE language which is a JAVA based grammar for annotating text. GATE developer is an integrated development environment for language processing components. JAPE is a finite state transducer and brings in the capability to identify regular expressions in annotations on documents. A JAPE grammar rule comprises of a set of phases, each of which consists
AUTOMATED MALARIA DIAGNOSIS USING OBJECT DETECTION RETINA-NET BASED ON THIN BLOOD SMEAR IMAGE

Malaria diagnosis is decided based on index malaria value which calculated from the amount of normal and infected erythrocyte on thin blood smear using microscope by a clinical pathologist. This activity is done manually and wastes a lot of time. Object detection using Convolutional Neural Network (CNN) is one of approach for solving this problem. However, the traditional object detection using CNN shows inadequate classification performance in labelling classes object. This paper is focused on the implementation of RetinaNet object detection approach to diagnose malaria. First, ResNet101 and ResNet50 used as RetinaNet backend network architecture for detecting both normal and infected erythrocytes on thin blood smear image with 1000x microscope zoom. Next, count every label of detected-object and calculate malaria-index value. Finally, after malaria-index value obtained, malaria diagnosis is defined. The algorithm performance with ResNet101 backend shows average precision (AP) 0,94, average recall 0,74, and average accuracy 0,73. Then the usage of ResNet50 backend in RetinaNet algorithm show average precision (AP) 0,90, average recall 0,78 and average accuracy 0,71.
A Deeper Look at Web Content Availability and Consistency over HTTP/S

—Recent studies of HTTPS adoption have found rapid progress towards an HTTPS-by-default web. However, these studies make two (sometimes tacit) assumptions: (1) That server-side HTTPS support can be inferred by the landing page (“/”) alone, and (2) That a resource hosted over HTTP and HTTPS has the same content over both. In this paper, we empirically show that neither of these assumptions hold universally. We crawl beyond the landing page to better understand HTTPS content unavailability and inconsistency issues that remain in today’s popular HTTPS-supporting websites. Our analysis shows that 1.5% of the HTTPS-supporting websites from the Alexa top 110k have at least one page available via HTTP but not HTTPS. Surprisingly, we also ﬁnd 3.7% of websites with at least one URL where a server returns substantially different content over HTTP compared to HTTPS. We propose new heuristics for ﬁnding these unavailability and inconsistency issues, explore several root causes, and identify mitigation strategies. Taken together, our ﬁndings highlight that a low, but signiﬁcant fraction of HTTPS-supporting websites would not function properly if browsers use HTTPS-by-default, and motivate the need for more work on automating and auditing the process of migrating to HTTPS.
Elderberry (Sambucus nigra L.) seed proteins inhibit protein synthesis and display strong immunoreactivity with rabbit polyclonal antibodies raised against the type 2 ribosome-inactivating protein nigrin b

Affinity chromatography-purified elderberry (Sambu cus nigra L.) seed proteins strongly inhibited protein synthesis and displayed the 28S rRNA N-glycosidase activity characteristic of all types of ribosome inactivating proteins (RIPs). Western blot analysis revealed several proteins that reacted with antibodies raised against the novel non-toxic type 2 ribosome inactivating protein nigrin b isolated from elder bark, thus indicating the presence of a new type 2 RIP.
Application of quantum chemical calculations in modeling of the supramolecular nanomedicine constructed from host-guest complexes of cucurbit[7]uril with gemcitabine anticancer drug

Using a quantum mechanical approach, we have investigated the drug delivery efficiency of cucurbit[7]uril for gemcitabine anticancer drug in gas and solution phases. The eight noncovalent interactions of drug gemcitabine with cucurbit[7]uril have been considered and optimized at M06-2X/6-31G(d,p) level. The calculation of binding energies showed the energetic stability of the host-guest complexes and confirmed the physical nature of interactions. It was specified that the gas phase binding energies are more negative than those of solution phase. The host-guest complex in which the drug is encapsulated in cucurbit[7]uril, is the most stable configuration and has the major contribution in gemcitabine drug delivery. Also, the free energies of solvation and quantum molecular descriptors were calculated. The free energies of solvation show that gemcitabine solubility increases in the vicinity of cucurbit[7]uril. The values of gemcitabine quantum molecular descriptors such as global hardness and HOMO-LUMO energy gap are higher than those of cucurbit[7]uril, showing the reactivity of the gemcitabine increases. The AIM analysis demonstrated that the hydrogen bonding between OH and NH2 functional groups of gemcitabine and the carbonyl functional group of cucurbit[7]uril plays an important role in the gemcitabine drug delivery.
OVERFLOWING TESTS ON THE ROSTOCK DREDGDIKES RESEARCH DIKE

As a part of the South Baltic Program, within the project DredgDikes large scale overflowing experiments on landside slopes of the Rostock research dike were carried out in September 2013. The aim of these experiments was to determine the landside slopes resistance against erosion caused by water. The test setup was in accordance with ASTM D-6460, modified to meet the project requirements, and the method used in the US NTPEP testing programme for rolled erosion control products. Therefore, three parallel flumes with a width of 0.6 m have been installed on the landside slopes at each cross-section of the research dike. Both short-term and long-term tests were carried out. Within the shot-term experiments generally five stages of discharge were realized for 45 minutes each, with erosion measurements between each stage. Each “long-term experiment” had a duration of at least 6 hours and was performed using a medium-high discharge. This paper presents the test methods as well as first results and conclusions of the experiments. The most important findings are that overflowing experiments are feasible with the proposed test set-up. Furthermore, it can be shown that under the project and test given boundary conditions the erosion resistance of the landside slopes is given.
SYNTHESIS AND BIOLOGICAL ACTIVITY EVALUATION OF NEW NUCLEOSIDE ANALOGUES FROM THEOBROMINE LINKED TO SCHIFF BASE

Most of antiviral and antitumor drugs that have been world-wide used belong to the nucleoside analogues. For this reason, a series of new nucleoside analogues were synthesized, using theobromine as a nucleobase, for the first time, by conversion to it chloro acetyl derivative, which was treated with hydrazine hydrate to give the key intermediate. Condensation of compound with different aromatic aldehyde gave Schiff base then they were subjected to condens with 1-bromo tetraacetyl glucose [2] forming blocked nucleoside analogues. Deblocking of these nucleoside using methanolic sodium methoxide afforded our target the free nucleoside . The synthesized compounds were identified by FT-IR spectroscopy and some of them with H-NMR and C-NMR spectroscopy.
Characterization of microbial populations of the borden aquifer

The indigenous microbial population of the Borden aquifer (Canada Forces Base Borden, Ontario, Canada) is largely aerobic and heterotrophic in nature, although a potential capacity for anaerobic nitrate reduction is present. The population possesses oligotrophic and psychrotrophic components. Chemolithotrophic and sulfate‐reducing organisms are rare. The latter, at least, are present although not detected with the MPN procedure used in this study. The recoverable, viable population is normally rather sparse (<10 to 104 CFU/g dry weight), and microbial communities are localized. Distinct populations were observed, even from samples taken within a small area (<5.5 m2) at one depth. These displayed varying metabolic capabilities when provided with 0.1% yeast extract, dissolved creosote components, and/or inorganic nutrients. On the basis of biochemical tests, most aquifer isolates seemed to possess either very broad or very restricted metabolic capabilities. The diameter of populations from pristine and rece.
Subdivision‐Specialized Linear Algebra Kernels for Static and Dynamic Mesh Connectivity on the GPU

Subdivision surfaces have become an invaluable asset in production environments. While progress over the last years has allowed the use of graphics hardware to meet performance demands during animation and rendering, high‐performance is limited to immutable mesh connectivity scenarios. Motivated by recent progress in mesh data structures, we show how the complete Catmull‐Clark subdivision scheme can be abstracted in the language of linear algebra. While this high‐level formulation allows for a fully parallel implementation with significant performance gains, the underlying algebraic operations require further specialization for modern parallel hardware. Integrating domain knowledge about the mesh matrix data structure, we replace costly general linear algebra operations like matrix‐matrix multiplication by specialized kernels. By further considering innate properties of Catmull‐Clark subdivision, like the quad‐only structure after refinement, we achieve an additional order of magnitude in performance and significantly reduce memory footprints. Our approach can be adapted seamlessly for different use cases, such as regular subdivision of dynamic meshes, fast evaluation for immutable topology and feature‐adaptive subdivision for efficient rendering of animated models. In this way, patchwork solutions are avoided in favor of a streamlined solution with consistent performance gains throughout the production pipeline. The versatility of the sparse matrix linear algebra abstraction underlying our work is further demonstrated by extension to other schemes such as and Loop subdivision.