Miracle-dz/UniFAR-FTUs huggingface dataset:
Recursive tree traversal dependence analysis

Weijiang, Yusheng M.S.E.C. E. , Purdue University, May 2015. Recursive Tree Traversal Dependence Analysis. Major Professor: Milind Kulkarni. While there has been much work done on analyzing and transforming regular programs that operate over linear arrays and dense matrices, comparatively little has been done to try to carry these optimizations over to programs that operate over heapbased data structures using pointers. Previous work has shown that point blocking, a technique similar to loop tiling in regular programs, can help increase the temporal locality of repeated tree traversals. Point blocking, however, has only been shown to work on tree traversals where each traversal is fully independent and would allow parallelization, greatly limiting the types of applications that this transformation could be applied to. The purpose of this study is to develop a new framework for analyzing recursive methods that perform traversals over trees, called tree dependence analysis. This analysis translates dependence analysis techniques for regular programs to the irregular space, identifying the structure of dependences within a recursive method that traverses trees. In this study, a dependence test that exploits the dependence structure of such programs is developed, and is shown to be able to prove the legality of several localityand parallelism-enhancing transformations, including point blocking. In addition, the analysis is extended with a novel path-dependent, conditional analysis to refine the dependence test and prove the legality of transformations for a wider range of algorithms. These analyses are then used to show that several common algorithms that manipulate trees recursively are amenable to several localityand parallelism-enhancing transformations. This work shows that classical dependence analysis techniques, which have largely been confined to nested loops over array data x structures, can be extended and translated to work for complex, recursive programs that operate over pointer-based data structures. 1
Strategies to control inbreeding in a pig breeding program: a simulation study

ABSTRACT: The objective of this study was to evaluate, through data simulation, the impact of restrictions on the maximum number of full- and half-sibs selected for males and females on the level of inbreeding and genetic gain of the herd. Data came from real populations A and B, composed of Pietrain and Landrace breed pigs, respectively. To generate the simulated populations, a Fortran-language simulator was developed using the (co)variances of the breeding values and the productive and reproductive rates obtained from populations A and B. Two data files were created. The first contained the pedigree of the previous 10 years, with 21,906 and 251,343 animals in populations A and B, respectively. The second included breeding values for age to reach 110 Kg body weight, backfat thickness, and feed conversion, for both populations; longissimus dorsi muscle depth, for population A only; and number of live piglets at the 5th day of life per farrowing, for population B only. Three scenarios were simulated with ten generations by varying the restrictions on the number of full- and half-sibs selected for males and females, with 30 replicates per generation and scenario. Regardless of the mating strategy used in a closed production unit, there is an increase in inbreeding levels. Inbreeding increases are larger in populations of smaller effective size. Restrictions on the number of full- and half-sibs selected are effective in reducing increments in inbreeding. Restriction to a maximum of two full-sibs and three half-sibs for males and three full sisters for females provided the highest genetic gains.
Language Branch Gated Multilingual Neural Machine Translation

Knowledge transfer across languages is crucial for multilingual neural machine translation. In this paper, we propose language branch (LB) gated multilingual neural machine translation that encourages knowledge transfer within the same language branch with a LB-gated module that is integrated into both the encoder and decoder. The LB-gated module distinguishes LB-specific parameters from global parameters shared by all languages and routes languages from the same LB to the corresponding LB-specific network. Comprehensive experiments on the OPUS-100 dataset show that the proposed approach substantially improves translation quality on both middle- and low-resource languages over previous methods. Further analysis demonstrates its ability in learning similarities between language branches.
Optimal Partial Transport Based Sentence Selection for Long-form Document Matching

One typical approach to long-form document matching is first conducting alignment between cross-document sentence pairs, and then aggregating all of the sentence-level matching signals. However, this approach could be problematic because the alignment between documents is partial — despite two documents as a whole are well-matched, most of the sentences could still be dissimilar. Those dissimilar sentences lead to spurious sentence-level matching signals which may overwhelm the real ones, increasing the difficulties of learning the matching function. Therefore, accurately selecting the key sentences for document matching is becoming a challenging issue. To address the issue, we propose a novel matching approach that equips existing document matching models with an Optimal Partial Transport (OPT) based component, namely OPT-Match, which selects the sentences that play a major role in matching. Enjoying the partial transport properties of OPT, the selected key sentences can not only effectively enhance the matching accuracy, but also be explained as the rationales for the matching results. Extensive experiments on four publicly available datasets demonstrated that existing methods equipped with OPT-Match consistently outperformed the corresponding underlying methods. Evaluations also showed that the key sentences selected by OPT-Match were consistent with human-provided rationales.
Reciprocal Learning of Knowledge Retriever and Response Ranker for Knowledge-Grounded Conversations

Grounding dialogue agents with knowledge documents has sparked increased attention in both academia and industry. Recently, a growing body of work is trying to build retrieval-based knowledge-grounded dialogue systems. While promising, these approaches require collecting pairs of dialogue context and the corresponding ground-truth knowledge sentences that contain the information regarding the dialogue context. Unfortunately, hand-labeling data to that end is time-consuming, and many datasets and applications lack such knowledge annotations. In this paper, we propose a reciprocal learning approach to jointly optimize a knowledge retriever and a response ranker for knowledge-grounded response retrieval without ground-truth knowledge labels. Specifically, the knowledge retriever uses the feedback from the response ranker as pseudo supervised signals of knowledge retrieval for updating its parameters, while the response ranker also receives the top-ranked knowledge sentences from knowledge retriever for optimization. Evaluation results on two public benchmarks show that our model can significantly outperform previous state-of-the-art methods.
Information flow tracking for JavaScript in Chromium

Data usage control is a concept that extends access control to also protect data after it has been released. Usage control enforcement relies on available information about the distribution of data in the monitored system. In this thesis we introduce an information flow tracking approach for JavaScript in order to enable usage control for dynamic content in web browsers. The proposed model is implemented as a prototype in the JavaScript engine V8 of the Chromium browser to evaluate the feasibility of the chosen approach.
Genetic research at the intersection of gender identity, sexual orientation, and mental health: community attitudes and recommendations for researchers

ABSTRACT The recent acceleration of research into sexual orientation, gender identity, and mental health has generally been conducted without sufficient understanding of the opinions of sexual and gender minorities (SGM) toward this research. We surveyed 768 individuals, with an enrichment of LGBTQ stakeholders, for their opinions regarding genetic research of SGM and mental health. We found that the key predictors of attitudes toward genetic research specifically on SGM are 1) general attitudes toward genetic and mental health research 2) tolerance of SGM and associated behaviors 3) non-cisgender stakeholder status and 4) age of the respondent. Non-heterosexual stakeholder status was significantly associated with increased willingness to participate in genetic research if a biological basis for gender identity were discovered. We also found that non-stakeholders with a low tolerance for SGM indicated their SGM views would be positively updated if science showed a biological basis for their behaviors and identities. These findings represent an important first step in understanding and engaging the LGBTQ stakeholder community in the context of genetic research.
A medical bioscience study of serum levels of paraoxonase 1 activity and total antioxidant capacity relationship with anti-mullerian hormone in polycystic ovary syndrome

The medical bioscience aims at training and developing scientists who will conduct research with a view to reduce the many lifestyle associated sicknesses. Polycystic ovary disease (PCOS) is a multifactorial disease and its prevalence rate increased significantly in the last few years. It is considered a cause of infertility and delayed reproduction, in addition to the many complications associated with the disease, which affect the lives of the patients in many aspects. During the study of the most important factors related to disease it is clear that the rise in AMH is indicative of degree of severity of disease, where it reflects the number of small follicles in the ovary. Hyperinsulinemia and insulin resistance with hyper- androgenemia conditions associated with PCOS enters the patients in vicious circle of factors where there is an increase in oxidative stress and decrease in antioxidants, including PON-1 and TAOC as the results showed, this in turn more increases the resistance of insulin and high level of testosterone followed by various complications on the heart and fertility and obesity and others. Serum AMH and PON-1was measured using enzyme linked immunosorbent kit [Elisa], while FSH, LH, testosterone, prolactin and estradiol were determined by VIDAS kit method (enzyme linked fluorescent assay) and TAOC measured by colorimetric method.
Information Hiding in Communication Networks: Fundamentals, Mechanisms, Applications, and Countermeasures

Describes Information Hiding in communication networks, and highlights their important issues, challenges, trends, and applications. Highlights development trends and potential future directions of Information Hiding Introduces a new classification and taxonomy for modern data hiding techniques Presents different types of network steganography mechanisms Introduces several example applications of information hiding in communication networks including some recent covert communication techniques in popular Internet services
Asymmetric Mutual Learning for Multi-source Unsupervised Sentiment Adaptation with Dynamic Feature Network

Recently, fine-tuning the pre-trained language model (PrLM) on labeled sentiment datasets demonstrates impressive performance. However, collecting labeled sentiment dataset is time-consuming, and fine-tuning the whole PrLM brings about much computation cost. To this end, we focus on multi-source unsupervised sentiment adaptation problem with the pre-trained features, which is more practical and challenging. We first design a dynamic feature network to fully exploit the extracted pre-trained features for efficient domain adaptation. Meanwhile, with the difference of the traditional source-target domain alignment methods, we propose a novel asymmetric mutual learning strategy, which can robustly estimate the pseudo-labels of the target domain with the knowledge from all the other source models. Experiments on multiple sentiment benchmarks show that our method outperforms the recent state-of-the-art approaches, and we also conduct extensive ablation studies to verify the effectiveness of each the proposed module.
Environmental Kuznets Curve in Croatia: panel data approach with Croatian counties

Concept of sustainable development has been in focus of researchers and policy makers in the last two decades. It is closely linked to the preservation of environment. This paper focuses on finding Environmental Kuznets Curve (EKC) relationship between economic development and pollution in Croatia. In order to empirically evaluate existence of this curve, data on 21 counties for different pollutants and income per capita has been obtained for the period 2008-2016. Different specifications of the relationship are observed: linear, quadratic and cubic, with addition of examining whether the Croatia’s accession to the EU has made a significant impact on lowering pollution. Results show that no EKC relationship is found for all pollutants (CO, CO2, NO2, SO2 and PM10) and that entering EU had a positive impact on diminishing pollution in Croatia.
Technology of automatic data discrimination based on CLIPS expert system

Considering the mass data and complex criterions of payload telemetry,we propose a technology of automatic discrimination for payload telemetry data based on C language integrated production system(CLIPS). This technology realizes not only the descriptions of complex discrimination rules by adopting the expert system language CLIPS but also the dynamic discrimination of telemetry data varying with the state of payloads by introducing finite state machine.Besides,we design the auxiliary learning algorithm of discrimination knowledge by mining rules from frequent patterns and improve the speed of discrimination by using reasoning mechanism of CLIPS.Thus this technology can meet the requirement of data discrimination for payload system test and flight control,and dramatically improves the efficiency and veracity of discrimination.It has been successfully applied to some satellite projects.
Correspondence Analysis of Breast Cancer Diagnosis Classification

There are five indicators used in the diagnosis of breast cancer classification. The indicators are a type of malignancy, location, topography, morphology, behavior, and grade. This study aimed to assess how the relationship between types of diagnostic classification was given to breast cancer patients. The research is a quantitative method and used the hospital medical records were collected in the form of anatomical pathology examination results for hospital patients in the year 2017. Data were obtained from 317 pathology examinations which included 282 breast cancer patients. Each patient is given a diagnosis according to the pathologist’s observations into various classifications according to location, topography, type, morphology, grade, and behavior. The result of the analysis showed a relationship between the location of cancer and the type of malignancy. Furthermore, there is a difference in the probability of a malignant or benign tumor-attacking the right or left breast. Correspondence analysis was carried out between the location of the tumor with topography, type of malignancy, morphology, grade, and behavior respectively. The results showed that there was a significant correspondence between topography with the type of malignancy, type of malignancy with morphology, morphology with grade, and grade with behavior. Each type of diagnosis of breast cancer diagnosis is entirely accurate and has a significant correspondence relationship with each other.
Stammzellfunktionen des Gens bällchen am Beispiel der Spermatogenese von Drosophila melanogaster

Gegenstand der vorliegenden Arbeit ist die Entwicklung der Keimbahnstammzellen im Testis von Drosophila melanogaster, die durch ihre Fahigkeit zur Selbsterneuerung und Differenzierung charakterisiert sind. Die Bildung von Tochterzellen mit unterschiedlichem Entwicklungspotential, das heist Erhalt des Stammzellpotentials bzw. Keimzellentwicklung, wird durch asymmetrische Teilungen der Stammzellen erreicht, ein Prozess, der von der unmittelbaren Stammzellumgebung, der sogenannten Stammzellnische, beeinflusst wird. Die Arbeit beschreibt die Funktion des Gens ballchen (ball) wahrend der fruhen Spermatogenese. Die molekulare Charakterisierung des Gens zeigt, dass es fur eine kernlokalisierte Serin/Threonin-Kinase codiert. Fur die Funktionsanalyse des Gens wurden spezifische Mutanten hergestellt. Diese weisen Allel-spezifische Defekte in der kontinuierlichen Produktion von Keimzellen auf. Die Defekte gehen sowohl bei hypomorphen als auch amorphen ball-Mutationen auf den Verlust der Keimbahnstammzellen zuruck. Eine Differenzierung der wenigen uberlebenden Keimzellen ist jedoch prinzipiell moglich. Keimzellautonome ball-Expression, die Transgen-abhangig in ball-Mutanten vermittelt wurde, zeigt, dass ball-Aktivitat in den Keimzellen fur den Erhalt der Keimbahn hinreichend ist. ball wird auch in den Stammzellpopulationen der weiblichen Keimbahn und des Nervensystems exprimiert. Bei amorphen ball-Mutanten werden in den entsprechenden Derivaten mutationsbedingte Phanotypen beobachtet, die wiederum auf Proliferationsdefekte schliesen lassen. Diese Beobachtungen lassen den Schluss zu, dass ball als intrinsischer Stammzellfaktor nicht nur in der mannlichen Keimbahn benotigt wird.
Soil mite communities (Acari: Gamasina) from different ecosystem types from Romania

The study aimed to characterize the distribution of soil mite populations (Acari: Gamasina) from several terrestrial ecosystems, some of them little studied in Romania as well as in Europe. We studied the Gamasina communities in seven ecosystem types from the Doftana Valley, Prahova County: Luzulo-Fagetum beech forest; Medio-European limestone beech forest of the Cephalanthero-Fagion; Pannonic woods with Quercus petraea and Carpinus betulus; Galio-carpinetum oak – hornbeam forests; Alpine rivers and their ligneous vegetation with Myricaria germanica; alluvial shrub, characteristic for a hilly-mountain area, with Salix purpurea; adjacent area to an inland cliff ecosystem. A total of 240 soil samples, 63 species and 475 individuals were analysed. The samples were taken from May 2006 till September 2010. The highest numerical abundance and species diversity was found in the area located nearby to an inland cliff, which is an early succession stage ecosystem. Considering the dominance and constancy indices quantified for mites from all investigated areas, the highest percent was recorded by the recedent-subrecedent and accessory-accidental species. Based on similarity index two different characteristic groups of gamasid populations were delimited: one for deciduous forests and one for shrubs. DCA ordination successfully handled the variation in soil mite species communities taking account of the soil type.
Adaptive Computing-Plus-Communication Optimization Framework for Multimedia Processing in Cloud Systems

A clear trend in the evolution of network-based services is the ever-increasing amount of multimedia data involved. This trend towards big-data multimedia processing finds its natural placement together with the adoption of the cloud computing paradigm, that seems the best solution to cope with the demands of a highly fluctuating workload that characterizes this type of services. However, as cloud data centers become more and more powerful, energy consumption becomes a major challenge both for environmental concerns and for economic reasons. An effective approach to improve energy efficiency in cloud data centers is to rely on traffic engineering techniques to dynamically adapt the number of active servers to the current workload. Towards this aim, we propose a joint computing-plus-communication optimization framework exploiting virtualization technologies, called MMGreen. Our proposal specifically addresses the typical scenario of multimedia data processing with computationally intensive tasks and exchange of a big volume of data. The proposed framework not only ensures users the Quality of Service (through Service Level Agreements), but also achieves maximum energy saving and attains green cloud computing goals in a fully distributed fashion by utilizing the DVFS-based CPU frequencies. To evaluate the actual effectiveness of the proposed framework, we conduct experiments with MMGreen under real-world and synthetic workload traces. The results of the experiments show that MMGreen may significantly reduce the energy cost for computing, communication and reconfiguration with respect to the previous resource provisioning strategies, respecting the SLA constraints.
A PRELIMINARY GEOMETRIC MORPHOMETRICS ASSESSMENT OF TWO FORENSICALLY IMPORTANT BLOW FLY LARVAE IN MALAYSIA, Chrysomya megacephala (Fabricius) AND Chrysomya rufifacies (Macquart) (DIPTERA: CALLIPHORIDAE)

In forensic entomology, the age of blow fly larvae (Diptera: Calliphoridae) that feed on decomposing human tissues can be used as reference in minimum post mortem interval (mPMI) estimation. To establish mPMI based on larval age, it is important to correctly identify larva species based on their morphological characteristics as larval developments from where they were collected are species-specific. Recently, landmark-based geometric morphometric analysis has been found useful to discriminate species and provide visual shape variations. The objective of this study was to assess the utilization of this technique on two forensically important blow fly species in Malaysia, i.e. the Chrysomya megacephala (Fabricius) and Chrysomya rufifacies (Macquart) based on the cephalopharyngeal skeletons of the larvae. A total of 10 landmarks on cephalopharyngeal skeleton were established and analyzed with geometric morphometric functions in MorphoJ™ software. Cephalopharyngeal skeleton centroid size, which represented the individual cephalopharyngeal skeleton shape profile, were statistically different between C. megacephala and C. rufifacies (p<0.001). Based on the landmark plot shifts, the two species could be differentiated based of parastomal bar, the clipeal arc, apical hook, upper margin of ventral cornu and lower margin of ventral cornu. These differences were well defined in visual presentation by using principal component analysis with 100% cross validation reassignment percentage. However, large scale study should be considered for a more complete cephalopharyngeal skeleton shapes profiles of forensically important Calliphoridae.