Miracle-dz/UniFAR-FTUs huggingface dataset:
Few-Shot Pidgin Text Adaptation via Contrastive Fine-Tuning

The surging demand for multilingual dialogue systems often requires a costly labeling process for each language addition. For low resource languages, human annotators are continuously tasked with the adaptation of resource-rich language utterances for each new domain. However, this prohibitive and impractical process can often be a bottleneck for low resource languages that are still without proper translation systems nor parallel corpus. In particular, it is difficult to obtain task-specific low resource language annotations for the English-derived creoles (e.g. Nigerian and Cameroonian Pidgin). To address this issue, we utilize the pretrained language models i.e. BART which has shown great potential in language generation/understanding – we propose to finetune the BART model to generate utterances in Pidgin by leveraging the proximity of the source and target languages, and utilizing positive and negative examples in constrastive training objectives. We collected and released the first parallel Pidgin-English conversation corpus in two dialogue domains and showed that this simple and effective technique is suffice to yield impressive results for English-to-Pidgin generation, which are two closely-related languages.
Excavata-Kinetoplastea Trypanosomatidae Parasites and the Interaction with their Hosts

Kinetoplastea Trypanosomatidae are unicellular flagellated parasites of different kind of hosts. They cause diseases in plants, animals and humans. These parasites are transmitted by insect vectors in a wide range of geographic areas. In this communication we review the interactions between trypanosomatid parasites, their hosts and thoughts about their impact on environmental health, especially in those regions where hosts are natural reserves of many species. The interactions of these parasites and their hosts in some cases have great economic and environmental impact. We also address the genetic mechanisms that determine variability in some specific taxa. Two cell fusion and recombination of nuclear genomes and mitochondrial introgression seems to be the mechanisms that produce the greatest variability. However, these organisms most frequently reproduce clonally. Finally the mechanisms of the trypanosomatids response to environmental changes in their host are also analyzed. Review ARticle
Unbalanced Three‐Phase Optimal Power Flow for the Optimization of MV and LV Distribution Grids

Smart distribution grids are developed around the concept of advanced distribution management systems (ADSM), whose features are summarized in this Chapter. Optimal power flow (OPF) techniques are a basic function of ADSM and can be applied effectively for controlling distribution grids at both MV and LV voltage levels. Specialized formulations of OPF need to be developed for defining control actions, such as move tap-ratio in on-load tap changers, switch capacitors or disconnectors, change reference signals or price signals to be sent to prosumers or active end-users. A methodology for controlling active and reactive resources in distribution systems, based on the solution of a three-phase unbalanced OPF, has been proposed and tested in this chapter. Particular attention is devoted to low voltage grids due to their importance. These grids are experiencing dramatic changes in power operations and show the potential to take full advantage of throughout metering and control. Test results showed the feasibility of the approach.
Taxonomic Status of Water Vole, (Arvicola Amphibius Linneaus, 1758) in Western Anatolia

A total of 116 specimens of the genus Arvicola were collected from western part of Turkey (Western part of Anatolia and Turkish Thrace) and examined based on geometric morphometrics and traditional morphometrics. Morphometrical analyses showed that A. amphibius populations in western part of Turkey are highly differentiated as Anatolian and Thrace populations. Depend on morphometrical differentiation, we conclude that these two populations, classified within two subspecies; Arvicola amphibius persicus and Arvicola amphibius cerncavskii respectively.
The CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue

The CODI-CRAC 2022 Shared Task on Anaphora Resolution in Dialogues is the second edition of an initiative focused on detecting different types of anaphoric relations in conversations of different kinds. Using five conversational datasets, four of which have been newly annotated with a wide range of anaphoric relations: identity, bridging references and discourse deixis, we defined multiple tasks focusing individually on these key relations. The second edition of the shared task maintained the focus on these relations and used the same datasets as in 2021, but new test data were annotated, the 2021 data were checked, and new subtasks were added. In this paper, we discuss the annotation schemes, the datasets, the evaluation scripts used to assess the system performance on these tasks, and provide a brief summary of the participating systems and the results obtained across 230 runs from three teams, with most submissions achieving significantly better results than our baseline methods.
Invariants of Frameshifted Variants

Frameshifts in protein coding sequences are widely perceived as resulting in either non-functional or even deleterious protein products. Indeed, frameshifts typically lead to markedly altered protein sequences and premature stop codons. By analyzing complete proteomes from all three domains of life, we demonstrate that, in contrast, several key physicochemical properties of protein sequences exhibit significant robustness against +1 and −1 frameshifts in their mRNA coding sequences. In particular, we show that hydrophobicity profiles of many protein sequences remain largely invariant upon frameshifting. For example, over 2900 human proteins exhibit a Pearson correlation coefficient between the hydrophobicity profiles of the original and the +1-frameshifted variants greater than 0.7, despite a median sequence identity between the two of only 6.5% in this group. We observe a similar effect for protein sequence profiles of affinity for certain nucleobases, their matching with the cognate mRNA nucleobase-density profiles as well as protein sequence profiles of intrinsic disorder. Finally, we show that frameshift invariance is directly embedded in the structure of the universal genetic code and may have contributed to shaping it. Our results suggest that frameshifting may be a powerful evolutionary mechanism for creating new proteins with vastly different sequences, yet similar physicochemical properties to the proteins they originate from. Significance Statement Genetic information stored in DNA is transcribed to messenger RNAs and then read in the process of translation to produce proteins. A frameshift in the reading frame at any stage of the process typically results in a significantly different protein sequence being produced and is generally assumed to be a source of detrimental errors that biological systems need to control. Here, we show that several essential properties of many protein sequences, such as their hydrophobicity profiles, remain largely unchanged upon frameshifts. This finding suggests that frameshifting could be an effective evolutionary strategy for generating novel protein sequences, which retain the functionally relevant physicochemical properties of the sequences they derive from.
Image classification using bag of visual words and novel COSFIRE descriptors

The main task of a keypoint descriptor is to describe an interesting patch(keypoint) in an image. This project proposes a new keypoint descriptor, based on the trainable COSFIRE filters that are used for keypoint detection and pattern recognition, to describe keypoints found in an image. A keypoint is a particular patch within an image that is deemed to be an interesting patch by a keypoint detector. A visual descriptor effectively describes the detected keypoints by being robust to changes in different image conditions while also being distinctive between different keypoints. We analyse the popular Bag of Visual Words (BOVW) image classification model, by examining each step of this model and choosing the best design configuration, starting from the extraction and description of the image keypoints to the classification of unseen image dataset. The proposed solution takes into consideration the configuration parameters found in the COSFIRE filters to effectively construct the novel keypoint descriptor. Different COSFIRE descriptor configurations were proposed in this project and their performance was assessed, along with other popular keypoint descriptors, on the popular procedure defined by [1], where different image conditions, such as variation of viewpoint or blur, are taken into account to test the descriptor’s effectiveness. The best COSFIRE descriptor was then chosen along with the state-of-the-art SIFT descriptor [2] to evaluate their accuracy rate using the BoVW model. We evaluated our COSFIRE descriptors along with other popular keypoint descriptors such as SIFT [2] and BRISK [3]. The performance of the COSFIRE-336 descriptor achieved the best performance results amongst the configurations proposed in this project, exceeding the SIFT and the BRISK descriptors’ performance in various image conditions. The COSFIRE-336 keypoint descriptor achieved an impressive accuracy rate when evaluated using the BoVW model, achieving a higher accuracy rate than SIFT on an unseen dataset of 15 different categories.
Combining ability and association studies on different yield contributing traits for enhanced green cob yield in sweet corn (Zea mays con var saccharata)

The present study was carried out to determine the combining ability of six sweet corn inbred lines and their hybrids and to ascertain the association between different biometrical and quality traits for increased green cob yield in sweet corn (Zea mays con var saccharata). Six sweet corn inbred lines were used as parental lines and they were crossed in full diallel fashion. The resultant sweet corn hybrids and their parents along with check hybrid were evaluated in randomized complete block design. The SCA variance was found to be greater than GCA variance indicating the predominance of non additive gene action for all the characters studied. Highly positive sca effects were noticed in the hybrid 45683x45508 for cob placement height, plant height, cob length, cob breadth, number of kernels per row. The cross 45684x45508 expressed highly significant and positive sca effect for the most important trait, green cob weight and quality traits viz., total sugar and non reducing sugar and possibility of commercial exploitation of this hybrid to be assessed based on its stability. The traits viz., cob length, cob breadth, number of kernels per row and plant height had positive association with green cob weight which indicates the possibility of green cob yield improvement through selection in favour of these correlated traits.
Linked Open Data Query Based on Natural Language

Linked open data (LOD) supports the SPARQL query strongly. A translation system from the natural language query to the SPARQL query based on the syntax rules is proposed. For a natural language query, a parsing method is proposed to represent the query intention and construct the corresponding query graph. The algorithms for obtaining and instantiating triple patterns are designed based on the rules. A mapping method for different types of graph nodes is lastly proposed to improve the recall. The experiments based on test data from QALD-4 are conducted. Compared with the other systems, our system is more easy and effective, and evaluation results are outstanding in the field of unsupervised learning.
Mining Health-related Cause-Effect Statements with High Precision at Large Scale

An efficient assessment of the health relatedness of text passages is important to mine the web at scale to conduct health sociological analyses or to develop a health search engine. We propose a new efficient and effective termhood score for predicting the health relatedness of phrases and sentences, which achieves 69% recall at over 90% precision on a web dataset with cause-effect statements. It is more effective than state-of-the-art medical entity linkers and as effective but much faster than BERT-based approaches. Using our method, we compile the Webis Medical CauseNet 2022, a new resource of 7.8 million health-related cause-effect statements such as “Studies show that stress induces insomnia” in which the cause (‘stress’) and effect (‘insomnia’) are labeled.
PARALEL GENETİK ALGORİTMALARDA FARKLILIK VE GEÇİRGENLİK

Paralel genetik algoritmalar (PGA’lar) farkli bireylere sahip birden fazla alt populasyon uzerinde genetik algoritma (GA) calistirarak arama yapan bir en iyileme algoritmasidir. PGA’larin basarili bir arama yapmasini etkileyen en onemli unsurlardan biri kullanilan goc yontemidir. Goc yontemleri, secilen bireylerin hangi alt populasyonlara gonderilecegini belirler. Goc eden birey, alt populasyondaki arama kalitesini ve buna bagli olarak algoritma basarisini etkiler. PGA’larin GA’lardan daha basarili sonuclar uretmesi, goc isleminin farkliliga olan katkisinin bir sonucudur. Bu nedenle, tercih edilen goc yonteminin farkliligi arttiracak bir etkisinin olmasi istenir. Bu calismada, farkli goc yontemleri icin performans sonuclari ve farklilik degerleri verilmis ve elde edilen sonuclar karsilastirilmistir. Bunun yaninda goc bireylerinin alt populasyonlar arasinda dogru ve etkin tasinmasi yeni bir kavram olarak gecirgenlik ile ifade edilmistir. Farkli goc yontemleri icin gecirgenlik degerlendirmesi yapilmis ve gecirgenligin algoritma performansina katkisi incelenmistir.
An Automatically Generated Lexical Knowledge Base with Soft Definitions

There is a need for methods that understand and represent the meaning of text for use in Artificial Intelligence (AI). This thesis demonstrates a method to automatically extract a lexical knowledge base from dictionaries for the purpose of improving machine reading. Machine reading refers to a process by which a computer processes natural language text into a representation that supports inference or inter-connection with existing knowledge (Clark and Harrison, 2010). There are a number of linguistic ideas associated with representing and applying the meaning of words which are unaddressed in current knowledge representations. This work draws heavily from the linguistic theory of frame semantics (Fillmore, 1976). A word is not a strictly defined construct; instead, it evokes our knowledge and experiences, and this information is adapted to a given context by human intelligence. This can often be seen in dictionaries, as a word may have many senses, but some are only subtle variations of the same theme or core idea. Further unaddressed issue is that sentences may have multiple reasonable and valid interpretations (or readings). This thesis postulates that there must be algorithms that work with symbolic representations which can model how words evoke knowledge and then contextualize that knowledge. I attempt to answer this previously unaddressed question, “How can a symbolic representation support multiple interpretations, evoked knowledge, soft word senses, and adaptation of meaning? ” Furthermore, I implement and evaluate the proposed solution. This thesis proposes the use of a knowledge representation called Multiple Interpretation Graphs (MIGs), and a lexical knowledge structure called auto-frames to support contextualization. MIG is used to store a single auto-frame, the representation of a sentence, or an entire text. MIGs and auto-frames are produced from dependency parse trees using an algorithm I call connection search. MIG supports representing multiple different interpretations of a text, while auto-frames combine multiple word senses and information related to the word into one representation. Connection search contextualizes MIGs and auto-frames, and reduces the number of interpretations that are considered valid. In this thesis, as proof of concept and evaluation, I extracted auto-frames from Longman Dictionary of Contemporary English (LDOCE ). I take the point of view that a word’s meaning depends on what it is connected to in its definition. I do not use a The term machine reading was coined by Etzioni et al. (2006).
Applications of diffusion-weighted imaging in diagnosis, evaluation, and treatment of acute ischemic stroke

Diffusion-weighted image (DWI) is widely used in acute care hospitals and provides diverse, valuable information about acute stroke. DWI is the gold standard for identifying the infarct core. The DWI infarct pattern is correlated with the pathogenic mechanisms underlying stroke and may predict stroke recurrence and outcome. Therefore, a deeper understanding of DWI is necessary for physicians treating patients with acute ischemic stroke. In this review, the application and interpretation of DWI for acute stroke and future perspectives are discussed.
EM-PERSONA: EMotion-assisted Deep Neural Framework for PERSONAlity Subtyping from Suicide Notes

The World Health Organization has emphasised the need of stepping up suicide prevention efforts to meet the United Nation’s Sustainable Development Goal target of 2030 (Goal 3: Good health and well-being). We address the challenging task of personality subtyping from suicide notes. Most research on personality subtyping has relied on statistical analysis and feature engineering. Moreover, state-of-the-art transformer models in the automated personality subtyping problem have received relatively less attention. We develop a novel EMotion-assisted PERSONAlity Detection Framework (EM-PERSONA). We annotate the benchmark CEASE-v2.0 suicide notes dataset with personality traits across four dichotomies: Introversion (I)-Extraversion (E), Intuition (N)-Sensing (S), Thinking (T)-Feeling (F), Judging (J)–Perceiving (P). Our proposed method outperforms all baselines on comprehensive evaluation using multiple state-of-the-art systems. Across the four dichotomies, EM-PERSONA improved accuracy by 2.04%, 3.69%, 4.52%, and 3.42%, respectively, over the highest-performing single-task systems.
Hybrid Sense Disambiguation in Web Queries

With the development of the web, search engines have played an important role in information retrieval. Traditional search engines are based on keywords and usually are not satisfactory due to the unrelated provided information. With the emergence of semantic web, semantic search engines are being built which works based in the keywords’ meanings. In this paper we propose a hybrid method for keyword sense disambiguation in web queries. We analyze the key parameters and present experimental results which show the high performance of the proposed method.
Nursing Interventions in Depression Management

Depression is not just a persistent feeling of sadness and low mood, it is more than that. The primary health care team shares different roles in managing depression. Nurses, in all care facilities take care of patients holistically (physically, mentally, emotionally, psychologically and spiritually). Nurses are on top of their profession tending the well and sick. Understanding nurses’ key roles in the management of illnesses is vital in the care process. The research is a literature review, which aims to identify the nursing interventions used widely in managing depression in the general population. Jean Watson’s Nursing Care Theory was used as a guide theoretical foundation for the research paper and search process uncovered 20 peer reviewed articles published from 2000-2018.
Dwarfing-canopy and rootstock cultivars for fruit trees

Abstract As fruit trees generally have a large size, the production of small or even dwarf trees is of great interest for most of fruit crops. In this review, some of the main tropical, subtropical and temperate fruit trees that have small or even dwarfing cultivars are approached. The causes of dwarfism, although the use of dwarfing rootstocks, is the main theme of this review. The factors that affect the size of the fruit trees are also approached, as well the dwarf cultivars of banana, papaya and cashew, and the dwarf rootstocks for guava, mango, anonaceae, loquat, citrus, apple and peach trees.
A Novel Mutation in the Desmin Gene with an Infantile Autosomal Recessive Myopathy

Recent studies in desmin knockout (_/_) mice have shown that the targeted ablation of desmin leads to pathological changes of the extrasarcomeric intermediate filament cytoskeleton, as well as structural and functional abnormalities of mitochondria in striated muscle. Here, we report on a novel homozygous deletion in exon 6 of desmin gene in patients from two families with recurrent episodes of syncope from infancy and an aggressive course of muscles wasting and death from cardiac failure at age 20 years. Molecular analysis identified a homozygous deletion resulting in loss of 22 bp (i.e. loss of seven amino acids, in addition to a frame shift and a truncated desmin protein). The homozygous deletion changed protein structure in a highly conserved region and compromised the ability of desmin to form an intermediate filament network in transiently transfected cells, providing a confirmation of high pathogenic potential. Muscle biopsy demonstrated signs of myofibrillar myopathy with prominent subsarcolemmal desmin-reactive aggregates. From results of the present study, It could be concluded that, this deletion mutation is the molecular event leading to the development of the infantile autosomal recessive desmin myopathy. Elucidation of the genetic basis of heritable desminopathy might provide insights into the pathogenetic mechanisms of the disease. The focus of the study was to analyze the desmin gene sequences for mutation and to study the impact of mutation, if any, on the intermediate filament networks formation.
Single Nucleotide Polymorphism in Protamine 1 and Protamine 2 genes in fertile and infertile for men of Al-Najaf City

Around 15% of the couples on the planet confront failure in the primary involvement in pregnancy. These issues in these couples can be explained as infertility. The objective of the study was to determination relationship among polymorphisms Protamin1 (G197T) and Protamine2 (C248T) were studied in three groups (Teratozoospermia n=37, infertile normozoospermia n=34 compare with fertile normozoospermia 17=0). Methods: Samples were collected at the Fertility Center Laboratories in Sadr Medical City. Analysis of SNPs was performed for PRM1 and PRM2 by using restriction fragment length polymorphism (PCR-RFLP). Results: The result showed Three types of polymorphism occur in both PRM1 (G197, G197T and G/T197) and PRM2 (C248, C248TandC/T248) genes found in all our patients. In conclusion the results are consistent with some previous studies and indicating that all our tested with SNPs was associated with teratospermia and normospermia as idiopatic male infertility in Iraqi population, which can find a genetically engineered solution in the future.