Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemical Composition of Cattle Finished on Different Production Systems

(P< .05), suggesting that both hybrid and location may affect the relative digestibility of these grain sorghums. Large differences between hybrids, however, may account for a major portion of this interaction. These studies suggest that location as well as hybrid is important in determining the nutritive value of grain sorghum. This effect was especially pronounced for crude protein but was also observed to a lesser degree for IVDMD. The significant (P < .05) hybrid by location interactions indicate that both of these factors affect the nutritive characteristics of grain sorghum. Consequently, in order to predict the nutritive value of grain sorghum, these studies suggest that location, in addition to hybrid, must be considered.
Cadherin 13 Inhibits Pancreatic Cancer Progression and Epithelial-mesenchymal Transition by Wnt/β-Catenin Signaling

Cadherin 13 (CDH13) is an atypical cadherin that exerts tumor-suppressive effects on cancers derived from epithelial cells. Although the CDH13 promoter is frequently hypermethylated in pancreatic cancer (PC), the direct impact of CDH13 on PC is unknown. Accordingly, the expression of CDH13 in PC cell lines and paired PC tissues was examined by immunohistochemistry, quantitative real-time PCR and western blotting. Our findings showed that CDH13 was downregulated in PC tissues and cell lines. Moreover, cell proliferation, migration and invasion were detected by CCK-8 assay, transwell migration assay and transwell invasion assay, respectively. Xenograft tumor experiments were used to determine the biological function of CDH13 in vivo. As revealed by our data, CDH13 overexpression significantly inhibited the proliferation, migration and invasion of human PC cells in vitro. The inhibitory effect of CDH13 on PC was further confirmed in animal models. Mice subcutaneously or orthotopically transplanted with CDH13-overexpressing CFPAC-1 cells developed significantly smaller tumors with less liver metastases and mesenteric metastases than those of the control group. Next, transcriptomics and western blot analysis were used to identify the underlying mechanisms. Further molecular mechanism studies showed that CDH13 overexpression inhibited the activation of the Wnt/β-catenin signaling pathway and regulated the expression of epithelial-mesenchymal transition (EMT)-related markers. Our results indicated that CDH13 displayed an inhibitory effect on PC and suggested that CDH13 might be a potential biomarker and a new therapeutic target for PC.
Robust and steerable kronecker product differential beamforming With rectangular microphone arrays

Differential microphone arrays (DMAs), a class of welldesigned small-size arrays combined with differential beamforming, are very useful for processing broadband acoustic, audio, and speech signals in a wide range of applications. However, most efforts in the literature so far have been devoted to linear, circular, and spherical arrays. In this paper, we consider rectangular shapes of planar microphone arrays. Instead of adopting the traditional differential beamforming methods developed in the literature, we present a differential beamforming method based on the so-called Kronecker product. We first decompose the entire rectangular array into two virtual rectangular sub-arrays so that the steering vector of the entire array is the Kronecker product of the steering vectors of the two smaller virtual rectangular sub-arrays. We use the first virtual rectangular array, which is much smaller in size than the entire array but well satisfies the basic requirements for differential beamforming, to design a steerable differential beamformer. For the second virtual rectangular array, we can design either the delay-and-sum (DS) beamformer, which helps to improve the robustness of the global differential beamformer, or an adaptive beamformer, which makes the global differential beamformer adaptive. This method has many interesting properties, particularly the designed beamformer is fully steerable, and its robustness and the array gain can be easily controlled.
Computational and Applied

: Since criminals are getting more and more sophisticated in their act, it is quite unfortunate that Criminal and Civil Law together with the Law Enforcement Agencies are proven to be inefficient towards crime prevention and conviction of criminals in the law court. This research seeks to present a Forensic Crime Investigation System in a bid to curtain criminal activities and possibly bring crime perpetrator to justice. The system tracks and identifies the faces of individuals during surveillance, and should a crime occurs, it compares the images of the surveillance database against the standard database to uncover the identities of the faces found at the scene. This research use Gabor Based hybrid of Elastic Bunch Graph Matching (EBGM) and Principal Component Analysis (PCA) model for processing image forensics (facial recognition and identification). An Object Oriented Methodology was utilised to develop a software system using Java programming language. This system will be capable of generating real time recognition of faces during surveillance which will maintain and reveal the identities of people involved in or present at the crime scene. The system was test run using students’ data, and within the campus of Federal University of Agriculture Makurdi, surveillance was conducted at different locations, forensic analyses were carried out on the images captured, and the identities of these images were uncovered.
Telekine: Secure Computing with Cloud GPUs

GPUs have become ubiquitous in the cloud due to the dramatic performance gains they enable in domains such as machine learning and computer vision. However, offloading GPU computation to the cloud requires placing enormous trust in providers and administrators. Recent proposals for GPU trusted execution environments (TEEs) are promising but fail to address very real side-channel concerns. To illustrate the severity of the problem, we demonstrate a novel attack that enables an attacker to correctly classify images from ImageNet [17] by observing only the timing of GPU kernel execution, rather than the images themselves. Telekine enables applications to use GPU acceleration in the cloud securely, based on a novel GPU stream abstraction that ensures execution and interaction through untrusted components are independent of any secret data. Given a GPU with support for a TEE, Telekine employs a novel variant of API remoting to partition application-level software into components to ensure secret-dependent behaviors occur only on trusted components. Telekine can securely train modern image recognition models on MXNet [10] with 10%–22% performance penalty relative to an insecure baseline with a locally attached GPU. It runs graph algorithms using Galois [75] on one and two GPUs with 18%–41% overhead.
On the information structure sensitivity of projective content

This paper presents the findings of an experiment designed to investigate the information structure sensitivity of the projective contents associated with again, stop and manner adverbs. In contrast to the prejacent of manner adverbs, whose projectivity is expected to be sensitive to information structural focus (e.g., Abrusan, 2013a; Stevens et al., 2017), that of the prejacent of again is not (e.g., Beck, 2006; Abrusan, 2013b). We also investigated the pre-state content associated with stop because projection analyses differ in their predictions regarding the sensitivity of this projective content to information structural focus (e.g., Heim, 1983; van der Sandt, 1992; Kadmon, 2001; Simons, 2001; Abrusan, 2011, 2016; Romoli, 2011, 2015). We found that the projectivity of all three contents is sensitive to prosodically marked focus and discuss the implications of our findings for empirically adequate projection analyses.
NoJITsu: Locking Down JavaScript Engines

—Data-only attacks against dynamic scripting environments have become common. Web browsers and other modern applications embed scripting engines to support interactive content. The scripting engines optimize performance via just-in-time compilation. Since applications are increasingly hardened against code-reuse attacks, adversaries are looking to achieve code execution or elevate privileges by corrupting sensitive data like the intermediate representation of optimizing JIT compilers. This has inspired numerous defenses for just-in-time compilers. Our paper demonstrates that securing JIT compilation is not sufﬁcient. First, we present a proof-of-concept data-only attack against a recent version of Mozilla’s SpiderMonkey JIT in which the attacker only corrupts heap objects to successfully issue a system call from within bytecode execution at run time. Previous work assumed that bytecode execution is safe by construction since interpreters only allow a narrow set of benign instructions and bytecode is always checked for validity before execution. We show that this does not prevent malicious code execution in practice. Second, we design a novel defense, dubbed N O JIT SU to protect complex, real-world scripting engines from data-only attacks against interpreted code. The key idea behind our defense is to enable ﬁne-grained memory access control for individual memory regions based on their roles throughout the JavaScript lifecycle. For this we combine automated analysis, instrumentation, compartmentalization, and Intel’s Memory-Protection Keys to secure SpiderMonkey against existing and newly synthesized attacks. We implement and thoroughly test our implementation using a number of real-world scenarios as well as standard benchmarks. We show that N O JIT SU successfully thwarts code-reuse as well as data-only attacks against any part of the scripting engine while offering a modest run-time overhead of only 5%.
The energy production profile of a large number of residential co-generators: a statistical evaluation

Data obtained from an extensive experimentation, originally designed to evaluate the comfort and consumption performances of a micro-cog eneration system in a residential context, provide valuable information on the usage pattern o f these systems. Using these data, an on/off stochastic process of non-exponential holding times d pending on time varying covariates is estimated. The fitted model provides a building blo ck for the estimation (with uncertainty bounds) of the daily profile of the energy produced by a la rge number of micro-cogenerators. To this end, a special Monte Carlo simulation technique, based on dependent samples, is devised to describe the energy production in a typical winter day.
Into the Deep Web: Understanding E-commerce Fraud from Autonomous Chat with Cybercriminals

—E-commerce miscreants heavily rely on instant messaging (IM) to promote their illicit businesses and coordinate their operations. The threat intelligence provided by IM communication, therefore, becomes invaluable for understanding and mitigating the threats of e-commerce frauds. However, such information is hard to obtain since it is usually shared only through one-on-one conversations with the criminals. In this paper, we present the ﬁrst chatbot, called Aubrey , to actively collect such intelligence through autonomous chats with real-world e-commerce miscreants. Our approach leverages the question-driven conversation pattern of small-time workers, who seek jobs and/or attack resources from e-commerce fraudsters, to model the interaction process as a ﬁnite state machine, thereby enabling an autonomous conversation. Aubrey successfully chatted with 470 real-world e-commerce miscreants and gathered a large amount of fraud-related artifacts, including previously-unknown SIM gateways, account trading websites, and attack toolkits, etc. Further, the conversations revealed the supply chain of e-commerce fraudulent activities on the deep web and the complicated relations (e.g., complicity and reselling) among miscreants.
POST-TRAUMATIC STRESS RESPONSES AMONG REFUGEES FOLLOWING XENOPHOBIC ATTACKS IN DURBAN, SOUTH AFRICA

Following a spate of xenophobic attacks against foreign nationals in Durban, South Africa, displacement camps were set up to shelter predominantly Congolese and Burundian refugees. Embedded within the emergency program a prevalence study of symptoms of posttraumatic stress disorder (PTSD) was conducted among a convenience sample of this population. Twenty-seven participants included men and women who were screened for symptoms using the Harvard Trauma Questionnaire (HTQ). Results indicate a prevalence rate of 85% among this population. Limitations include the small sample size and potential self-reporting. The high prevalence rate of people who meet diagnostic criteria for PTSD has profound implications for psychosocial interventions and access to mental health services for this community – as well as significant broader legal and social justice implications.
The Intrusive Rendering: Dictation of Stereotypes and the Extra-Ordinary

It is no longer a surprise these days to see a photographic image of a building with a rather dubious existence: whether or not it has actually been built or still exists only as a project yet to be realised. A photo-realistic image of a building that has not yet been realised is conventionally known as the rendering, a practical and effective tool of representation of architectural projects. While contemporary practices heavily rely on a parallel industry of image production for these renderings, this phenomenon has been mostly treated, within the field of architecture, as subordinate to critical design discourses. The rendering comes after the design; it is an image-production akin to an advertisement, a commercial commodity aiming to sell the design, and a visualisation to seduce the eyes of the client and the general public audience. Out of the many examples of renderings produced for international architectural competition entries, it is often the case that a successful rendering exerts a tremendous power in winning the favour of the jury panel and the public audience. This is particular evident in the context of Taiwan, and at a even larger scale in China. This is the art of rendering that has had a phenomenal effect on the production, perception and valuation of architecture, which confronts the subordinate role of the rendering narrowly assumed within design practices in the West. This paper examines a lack of awareness of the implications of renderings upon the design development of a project, which is entangled with prejudices formed historically in the discourses on representation in relation to the idea of art and design in the West, going back to philosophical arguments formed in the Classical period. On the other hand, the potentially intrusive role that rendering plays in the design process is investigated in the particular context of Taiwan and China, where the issue of representation has been built upon an entirely different set of cultural criteria. This opens up questions on the condition of the hypothetical in rendering a vision, the co-existence of the truth and the lie, the stereotypical imageries appearing as dictations of meaning and framing the extraordinaries, and how all these factors of the rendering sets different judgement criteria on the refinement and manipulation of what is meant to be a ‘good’ design.
Frame-Level MMI as A Sequence Discriminative Training Criterion for LVCSR

In this work we present frame-level maximum mutual information (MMI) as a novel sequence discriminative training criterion for hybrid HMM-DNN acoustic models. Compared to the standard, sequence-level MMI criterion we show that frame-level MMI has increased robustness towards missing cross-entropy (CE) smoothing and can converge even without interpolation.Using model free optimization, we show that in the asymptotic case of an infinite amount of training data models trained using this criterion are equal to the true class posterior distribution, whereas training using the state-level minimum Bayes risk (sMBR) criterion leads to a distorted function of the true class posterior distribution. This analytical result is backed by experimental evidence.We further propose a generalized class of training criteria, that continuously interpolates between frame-level MMI and sMBR criterion.
Omani Students’ Perceptions of the Use and Applicability of Explicit Grammar Instruction in Communicative Language Teaching

7 Chapter One: Introduction.8 1.1. Research Background.8 1.2. The grammar debate in the Omani context.10 1.3. Statement of the problem.13 1.4. Research design.14 1.5. Significance of the study.14 1.6. Organization of the Paper.15 Chapter 2: Literature Review.16 2.1. Theoretical framework.16 2.2. Characteristics of traditional grammar instruction.17 2.3. The impact of modern linguistics on grammar instruction.18 2.4. Studies of explicit grammar instruction.24 2.5. The need to exploring the role of grammar teaching in CLT.27 Conclusion.32 Chapter 3: Methodology.33 3.1. Qualitative research.33 3.2. My role as a researcher.34 3.3. Participants.34 3.4. Data collection method.36
E-txt2db: Giving Structure to Unstructured Data (Extended Abstract)

A large amount of information handled in organizations is stored as unstructured or semi-structured documents (e.g., reports or e-mail messages). It is not easy, for a software tool, to use these type of documents, which means that much of this information is ignored. The Information Extraction area oﬀers a set of techniques that help extracting text segments from these documents in order to make them useful for a user in a given domain. Typically, to specify Information Extraction programs, a user can use: (i) procedural languages to develop the program from scratch; (ii) ETL (Extraction, Transformation and Loading) tools; (iii) Information Extraction frameworks or; (iv) declarative languages for Information Extraction. All these solutions have advantages and disadvantages. This work proposes a framework for Information Extraction called E-txt2db, that tries to combine the advantages of the existing solutions for the speciﬁcation of Information Extraction programs. E-txt2db oﬀers declarative operators based on the semantics of the following Information Extraction tasks: segmentation, classiﬁcation, association, normalization, coreference resolution. The work of this thesis focuses on the development of the classiﬁcation operator of E-txt2db, proposing its formalization, a Java API to create, execute and evaluate classiﬁcation models and an SQL-like syntax to specify classiﬁcation programs.
Aiming with → arrows ← at particles: Towards a conceptual analysis of directional meaning components in German particle verbs

This article presents a case study on the contributions of prepositional particles to the meanings of German particle verbs (such as anstrahlen ‘to beam/smile at’ and aufgeben ‘to give up’). Based on a set of 16 “concept images”, two-dimensional directional arrow pictographs, 60 experiment participants selected one or more concept images for a systematically composed set of 270 German particle verbs and their 30 base verbs. We formulate a series of hypotheses for the meanings of nine constituent particle types (ab, an, auf, aus, ein, mit, nach, vor, zu) and investigate them in the light of the concept image selections. Qualitative and quantitative analyses indicate that our hypotheses are largely confirmed, across three source domains varying in their abstractness (Machines & Tools, Force, Sound), as well as across well-known vs. unknown particle verbs. The particles exhibit individual concept image profiles, and they vary in their flexibility to provide predominant directions; for example, while auf is rather consistently perceived as contributing an upward/right direction to a particle verb meaning, an shows similarly strong preferences for a set of concept images; in both cases, these tendencies are observed across source domains.
Static Analysis of Python Programs

Python is an increasingly popular dynamic programming language, which is particularly used in the scientiﬁc community, and well-known for its powerful and permissive high-level syntax. The goal of this PhD is to develop static analyses for Python, i.e. to detect automatically uncaught exceptions in programs without running them. The current focus is to detect type and attribute errors using a type analysis
Biomedical Information Extraction for Complex Sentences

Biomedical literature is a challenging domain for information extraction due to the prevalence of long and complex sentences. A single sentence often includes multiple independent assertions that should all be in the extraction result. These assertions need to be extracted from the corpus and ﬁltered such that only the informative assertions remain. We seek to meet this need through a two-phase framework: in the ﬁrst phase, we use an extractor to generate nested extractions from the text; in the second phase we use a custom-built classiﬁer to obtain the desired set of independent simple assertions by ﬁltering out the non-informative assertions. The proposed system, Nested Bio Information Extraction (NBIE) generates short, informative assertions from biomedical text. Experimental results showed that our system was able to extract more than twice the number of assertions when compared to our baseline, while giving up around 10% in precision
STATUS OF THE PEREGRINE FALCON FALCO PEREGRINUS ON LUNDY: BREEDING ECOLOGY AND PREY SPECTRUM

Dense island sub-populations of Peregrine Falcons Falco peregrinus are common around the British Isles. Lundy offers a unique opportunity to study this specific area of Peregrine ecology. Manx Shearwaters Puffinus puffinus comprised a significant proportion of the prey spectrum; other important prey included: Herring Gulls Larus argentatus, Domestic Pigeons Columba livia and Rabbits Oryctolagus cuniculus. Preliminary data on breeding performance and nest cliff topography are presented. Further research is required to establish causality from the various limiting factors on the population; and inform how island populations of Peregrines are regulated in the United Kingdom.
Isolated Capital Cities, Accountability and Corruption: Evidence from Us States

We show that isolated capital cities are robustly associated with greater levels of corruption across US states, in line with the view that this isolation reduces accountability, and in contrast with the alternative hypothesis that it might forestall political capture. We then provide direct evidence that the spatial distribution of population relative to the capital affects different accountability mechanisms over state politics: newspaper coverage, voter knowledge and information, and turnout. We also find evidence against the capture hypothesis: isolated capitals are associated with more money in state-level campaigns. Finally, we show that isolation is linked with worse public good provision.
X-Classiﬁer A ﬂeXible Classiﬁer for the common user

Automatically managing collections of texts of considerable size is an important task because it allows the consultation of texts by topic or category, facilitating the individual search for a text, something that would be quite diﬃcult to achieve without any help. A popular way of managing text collections is through the task of text classiﬁcation, which allows the grouping of texts by category. However, currently there is still no solution to the classiﬁcation of any collection without the need of minor adjustments, which requires speciﬁc skills. In this paper we propose a solution for this problem, introducing a new approach to text classiﬁcation that adapts to any given problem without the need of any human intervention. Experimental results show that our solution can achieve a very similar performance to that of a supervised approach, without requiring the user to select or conﬁgure the algorithms to use in order to make the classiﬁcation.