Miracle-dz/UniFAR-FTUs huggingface dataset:
Ascertaining the Religious Coping Strategies among Women Living with Cervical Cancer in the Greater Accra Region: A Case of Korle Bu Teaching Hospital

: The purpose of this study was to ascertain the religious coping strategies among women living with cervical cancer in the Greater Accra region of Ghana. The study employed quantitative research approach specifically descriptive survey research design. The population included all women diagnosed with cervical cancer, 18 years and above and receiving treatment at the National Radiotherapy Centre and Nuclear Medicine of the Korle-Bu Teaching Hospital, Accra. A sample size of 113 was arrived at given a population of 160 using Krejcie and Morgan (1970) sampling formulae. Quota sampling was used to select participants for this study. The instruments used for the study was Brief Religious Cope (Brief RCOPE) by Pargament, Koenig and Perez (2000). Also, descriptive statistics thus mean and standard deviation was used in analyzing research question 1 and 2 whiles One-Way Multivariate Analysis of Variance (MANOVA) was used in examining the difference in religious coping practices. The mean of means obtained on the various research questions indicated an endorsement for positive religious coping among women living with cervical cancer. On the other hand, respondents did not reappraise God for things happening to them. Also, it was found that there is a statistically significant difference in the religious coping practices of women living with cervical cancer with respect to religious background. It is recommended that there should be an integration of positive religious coping techniques by nurses, physicians, pharmacists, clinical psychologists/counsellors and spiritual leaders into psychotherapy and counselling of women living with cervical cancer to enhance their skills in cancer management so as to ensure a holistic care of cervical cancer survivors.
CiteSum: Citation Text-guided Scientific Extreme Summarization and Domain Adaptation with Limited Supervision

Scientific extreme summarization (TLDR) aims to form ultra-short summaries of scientific papers. Previous efforts on curating scientific TLDR datasets failed to scale up due to the heavy human annotation and domain expertise required. In this paper, we propose a simple yet effective approach to automatically extracting TLDR summaries for scientific papers from their citation texts. Based on the proposed approach, we create a new benchmark CiteSum without human annotation, which is around 30 times larger than the previous human-curated dataset SciTLDR. We conduct a comprehensive analysis of CiteSum, examining its data characteristics and establishing strong baselines. We further demonstrate the usefulness of CiteSum by adapting models pre-trained on CiteSum (named CITES) to new tasks and domains with limited supervision. For scientific extreme summarization, CITES outperforms most fully-supervised methods on SciTLDR without any fine-tuning and obtains state-of-the-art results with only 128 examples. For news extreme summarization, CITES achieves significant gains on XSum over its base model (not pre-trained on CiteSum), e.g., +7.2 ROUGE-1 zero-shot performance and state-of-the-art few-shot performance. For news headline generation, CITES performs the best among unsupervised and zero-shot methods on Gigaword.
A review of methods for identifying QTLs in experimental crosses

Identifying the genetic loci contributing to variation in traits which are quantitative in nature (such as the yield from an agricultural crop or the number of abdominal bristles on a fruit fly) is a problem of great importance to biologists. The number and effects of such loci (called quantitative trait loci or QTLs) help us to understand the biochemical basis of these traits, and of their evolution in populations over time. Moreover, knowledge of these loci can aid in designing selection experiments to improve the traits. There are a large number of different methods for identifying the QTLs segregating in an experimental cross. Little has been written critically comparing the methods, and there have been few studies comparing their performance; we make an attempt at this.
Modular and Parameter-Efficient Fine-Tuning for NLP Models

State-of-the-art language models in NLP perform best when fine-tuned even on small datasets, but due to their increasing size, fine-tuning and downstream usage have become extremely compute-intensive. Being able to efficiently and effectively fine-tune the largest pre-trained models is thus key in order to reap the benefits of the latest advances in NLP. In this tutorial, we provide a comprehensive overview of parameter-efficient fine-tuning methods. We highlight their similarities and differences by presenting them in a unified view. We explore the benefits and usage scenarios of a neglected property of such parameter-efficient models—modularity—such as composition of modules to deal with previously unseen data conditions. We finally highlight how both properties——parameter efficiency and modularity——can be useful in the real-world setting of adapting pre-trained models to under-represented languages and domains with scarce annotated data for several downstream applications.
Shared knowledge in natural conversations: can entropy metrics shed light on information transfers?

The mechanisms underlying human communication have been under investigation for decades, but the answer to how understanding between locutors emerges remains incomplete. Interaction theories suggest the development of a structural alignment between the speakers, allowing for the construction of a shared knowledge base (common ground). In this paper, we propose to apply metrics derived from information theory to quantify the amount of information exchanged between participants, the dynamics of information exchanges, to provide an objective way to measure the common ground instantiation. We focus on a corpus of free conversations augmented with prosodic segmentation and an expert annotation of thematic episodes. We show that during free conversations, the amount of information remains globally constant at the scale of the conversation, but varies depending on the thematic structuring, underlining the role of the speaker introducing the theme. We propose an original methodology applied to uncontrolled material.
NLP DI at NADI Shared Task Subtask-1: Sub-word Level Convolutional Neural Models and Pre-trained Binary Classifiers for Dialect Identification

In this paper, we describe our systems submitted to the NADI Subtask 1: country-wise dialect classifications. We designed two types of solutions. The first type is convolutional neural network CNN) classifiers trained on subword segments of optimized lengths. The second type is fine-tuned classifiers with BERT-based language specific pre-trained models. To deal with the missing dialects in one of the test sets, we experimented with binary classifiers, analyzing the predicted probability distribution patterns and comparing them with the development set patterns. The better performing approach on the development set was fine-tuning language specific pre-trained model (best F-score 26.59%). On the test set, on the other hand, we obtained the best performance with the CNN model trained on subword tokens obtained with a Unigram model (the best F-score 26.12%). Re-training models on samples of training data simulating missing dialects gave the maximum performance on the test set version with a number of dialects lesser than the training set (F-score 16.44%)
Trawl selectivity studies on Nephrops norvegicus (L.) in the eastern Mediterranean Sea

The trawl codend selectivity on Nephrops norvegicus was studied using diamond meshes of 16 mm, 20 mm, 24 mm and 26 mm nominal side mesh size. The cover codend method was applied for the sampling. The logistic function for the probability of retention by the codend was used for the estimation of selectivity parameters from all data combined. The results indicated that the 16 mm mesh size was not selective and that almost all individuals were retained. The 24 mm and 26 mm mesh size showed quite similar results and were a little more selective than the 20 mm mesh size. None of the experimental mesh sizes proved to be adequate for N. norvegicus , since all estimated values of length of 50% retention (L50) were lower than the length at first maturity and those of length of 25% retention (L25) were lower than the legislated minimum landing size. It is suggested that mesh size should be much larger than 20 mm, the size legislated by E.U. for the Mediterranean.
Extracting Negative Correlation Pattern from Gene Expression Microarray Data

Analysing the gene expression microarray data (i.e. cDNA chip or oligonucleotide chip) became a major field of bioinformatics and many algorithms have been introduced to this purpose including various clustering methods [1, 2]. But currently used clustering methods are usually suited to detect the co-expression pattern, i.e. the clusters of genes which are up-regulated or down-regulated simultaneously. So, the researchers could not detect the genes which show the negative correlation pattern easily, although they might have important biological context (Figure 1). We describes the new method to find the candidate gene pairs of which one gene is up-regulated when the other gene is down-regulated and vice versa.
Good old pap smear towers over the latest LBC for cervical screening: a study in a rural teaching institute of Tamil Nadu, India

Introduction: Cervical cancer is the second most common cancer among Indian women and the fourth most frequent cancer in women across the globe. Though effective screening programmes are available, its role in effective prevention in a developing country like ours still remains an unanswered question and the probable reason behind this could be the difficulty in adopting liquid-based cytology (LBC) as the main screening program ahead of conventional pap smear (CPS). Aims and Objectives: This study was performed with an objective to analyse and interpret the samples by both CPS and LBC and to compare the both so as to find out the possibility of implementing LBC in a rural teaching institute of Tamilnadu like ours. Materials and methods: This was a prospective observational study which includes sample of 100 women who have attended the gynaecological outpatient department (OPD) of Vinayaka Missions Kirupananda, Variyar Medical College and Hospitals, Salem, Tamil Nadu. The slides were interpreted by two independent cytopathologists based on The Bethesda System and the results were analysed statistically. Results: The youngest patient was 19 years and the oldest was 68 years old. The most common age group in the study is 4th decade. The commonest clinical presentation was discharge per vaginum (PV). Screening time was less with LBC which also showed cleaner background compared to CPS. Other parameters like organisms and epithelial cell abnormalities were detected in both CPS and LBC. Conclusion: Even though LBC was few steps above CPS while considering the smear background and time taken to screen the slides, CPS still remains the better among the two in our setup taking into consideration the cost efficacy it provides which is the main factor for the population in our rural setup.
Divergent selection of mice for high and low swim stress-induced analgesia alters polymorphism at microsatellite loci.

The objective of this study was to determine microsatellite polymorphism in mice lines, divergently selected over 60 generations for high (HA) or low (LA) swim stress-induced analgesia. The polymorphism analysis covered 40 microsatellite markers within two lines (20 and 19 individuals for HA and LA line, respectively. The selection breeding strategy was based on a heterogeneous, outbred population of Swiss-Webster mice. The lines were earlier found to differ in brain opioid receptor density and in the expression of opioid-mediated phenomena, such as analgesic sensitivity to opiates and reversibility of swim stress-induced analgesia (SSIA) by naloxone. Apart from nociception-related traits, the HA mice displayed, as compared to the LA animals, higher emotionality in various behavioural tests, and higher degree of hypothermia when subjected to a hypothermic challenge. The present study showed that selection for HA and LA phenotypes affects the frequency of microsatellite alleles. The number of alleles per locus varied from 1 to 6 with a mean value of 2.9 for HA and 2.7 for LA line. Thirty-seven alleles were identified as specific to HA and 30 as specific to LA line. The expected heterozygosity ranged from 0.324 to 0.797 (mean 0.618). Of the 40 examined markers loci five had relatively high PIC value (> 0.7). It is concluded that HA
COMET-22: Unbabel-IST 2022 Submission for the Metrics Shared Task

In this paper, we present the joint contribution of Unbabel and IST to the WMT 2022 Metrics Shared Task. Our primary submission – dubbed COMET-22 – is an ensemble between a COMET estimator model trained with Direct Assessments and a newly proposed multitask model trained to predict sentence-level scores along with OK/BAD word-level tags derived from Multidimensional Quality Metrics error annotations. These models are ensembled together using a hyper-parameter search that weights different features extracted from both evaluation models and combines them into a single score. For the reference-free evaluation, we present CometKiwi. Similarly to our primary submission, CometKiwi is an ensemble between two models. A traditional predictor-estimator model inspired by OpenKiwi and our new multitask model trained on Multidimensional Quality Metrics which can also be used without references. Both our submissions show improved correlations compared to state-of-the-art metrics from last year as well as increased robustness to critical errors.
Analysis of Hybrid Converter with Wide Voltage Range Operation

A soft switching converter with wide voltage range operation is investigated in this paper. A series resonant converter is implemented to achieve a high circuit efficiency with soft switching characteristics on power switches and rectifier diodes. To improve the weakness of the narrow voltage range in LLC converters, an alternating current (ac) power switch is used on the primary side to select a half-bridge or full-bridge resonant circuit to implement 4:1 voltage range operation. On the secondary-side, another ac power switch is adopted to select a full-wave rectifier or voltage-doubler rectifier to achiever an additional 2:1 output voltage range. Therefore, the proposed resonant converter has the capacity for 8:1 (320V~40V) wide output voltage operation. A single-stage hybrid resonant converter is employed in the study circuit instead of a two-stage dc converter to achiever wide voltage range operation. As a result, the study converter has better converter efficiency. The theoretical analysis and circuit characteristics are verified by experiments with a prototype circuit.
Dataset Discovery in Data Lakes

Data analytics stands to benefit from the increasing availability of datasets that are held without their conceptual relationships being explicitly known. When collected, these datasets form a data lake from which, by processes like data wrangling, specific target datasets can be constructed that enable value– adding analytics. Given the potential vastness of such data lakes, the issue arises of how to pull out of the lake those datasets that might contribute to wrangling out a given target. We refer to this as the problem of dataset discovery in data lakes and this paper contributes an effective and efficient solution to it. Our approach uses features of the values in a dataset to construct hash– based indexes that map those features into a uniform distance space. This makes it possible to define similarity distances between features and to take those distances as measurements of relatedness w.r. t. a target table. Given the latter (and exemplar tuples), our approach returns the most related tables in the lake. We provide a detailed description of the approach and report on empirical results for two forms of relatedness (unionability and joinability) comparing them with prior work, where pertinent, and showing significant improvements in all of precision, recall, target coverage, indexing and discovery times.
Effect of different brine concentrations and ripening period on some quality properties of Turkish white pickled cheese

The aim of this study was to determine the effects of different brine concentrations on some properties of Turkish white cheese. Cheeses made from pasteurized milk (65°C for 30 min) were ripened in 11, 14 and 17 g 100 ml NaCl for 90 days at 7±1°C. Some physicochemical and biochemical analyses were carried out during storage time. The effects of brine concentrations on total solids, protein, ash, salt, pH, and WSN values were found to be significant (P<0.05). On the contrary, fat, lipolysis, TCA-SN and PTA-SN values of the cheese samples were not significantly affected by the brine concentrations used. On the other hand, the values of protein, ash, salt, pH, lipolysis, WSN, TCA-SN and PTA-SN of the experimental cheeses were significantly (P<0.05, P<0.01) affected by storage time, while the effect of storage period on total solids and fat contents was found to be insignificant (P>0.05).
Effect of Different Concentration of Cytokinins, Carbon Source and Agar on in vitro Propagation of Dahlia sp. through One Single Node

An efficient in vitro protocol for mass production of shoot of Dahlia was developed by using node explant, various carbon sources such as sucrose, glucose, fructose and galactose. Agar concentrations and various growth regulators on in vitro shoot multiplication of Dahlia were studied in the present investigation. The nodal explant from the gardens grown plant were used as testing plant material to develop an efficient protocol for mass propagation of exotic Dahlia to enhance their production for growers and the local markets. This study determined the effect of different carbon sucrose concentrations and gelling agent on in vitro propagation of Dahlia, different carbon sources (sucrose, glucose, fructose and galactose) were investigated, each sugar was added individually to the MS culture medium at the concentrations of 15, 30 and 45 g·L -1 , respectively. Culture medium of each treatment was supplemented with 1.5 mg·L -1 BA + 1.5 mg·L -1 Kin + 7.0 g·L -1 agar. The highest number of shoots (7.00), number of leaves (11.50), number of node (6.75) and shoot length (8.24 cm) was obtained on MS medium supplemented with 30 g·L -1 glucose. The least number of shoots (3.38), number of leaves (5.00), number of node (3.13) and the least shoot length (2.96 cm) was obtained on 45 g·L -1 galactose and the least shoot length (2.29 cm) was observed on MS medium with free carbon sources. While the medium with 30 g·L -1 glucose and 8 g·L -1 agar gave the highest number of shoots (7.13), number of leaves (10.75), number of node (7.13) and shoot length (8.18 cm). However, the least number of shoots (1.50), number of leaves (1.88), number of node (1.63) and the least shoot length (1.26 cm) was obtained with 30 g·L -1 galactose and 12 g·L -1 agar. Rooting was readily achieved upon transferring the microshoots onto MS medium supplemented with 0.1 mg·L -1 IBA, IAA and NAA and 30 g·L -1 (w/v) different types of carbon sources. The percentage of rooting was less (71.88%) on MS medium containing IAA as compared with IBA or NAA. While the medium having 30 g·L -1 glucose with 0.1 IBA or NAA mg·L -1 , give the highest percentage of root (100%), and the highest number of root (3.88) and root length (3.56 cm) was obtained on MS medium containing 30 g·L -1 glucose with 0.1 mg·L -1 IBA. More than 98% of rooted plantlets were established in the greenhouse.
Understanding health inequalities in multimorbidity and functional limitation of the ageing population in England

The thesis explored the social and life course factors behind the prevalence and risk of multimorbidity and functional limitation as well as their unequal distribution in the ageing population of England. Multimorbidity is the co-occurrence of two or more diseases within a person. Functional limitations are restrictions in performing fundamental physical and mental actions used in daily life. The thesis identified previously unmeasured inequality in the population with multimorbidity and functional limitation. People aged 50-54 years with the least household wealth had the same prevalence of complex multimorbidity as those 20 years older in the most affluent category and the prevalence of functional limitations comparable to those 30 years older in the top wealth group. Further analysis included a range of material, psychosocial and behavioural determinants into the analysis. Household wealth, sense of control over personal life, physical activity and loneliness were associated with the risk of multimorbidity and functional limitation. Finally, the thesis developed a pathway model of how childhood circumstances – social class, adverse experiences and health – affect the risk of multimorbidity and functional limitation in old age. The material, psychosocial and behavioural pathways acted as magnifiers of inequalities from the early life period.
The NiuTrans Machine Translation Systems for WMT22

This paper describes the NiuTrans neural machine translation systems of the WMT22 General MT constrained task. We participate in four directions, including Chinese→English, English→Croatian, and Livonian↔English. Our models are based on several advanced Transformer variants, e.g., Transformer-ODE, Universal Multiscale Transformer (UMST). The main workflow consists of data filtering, large-scale data augmentation (i.e., iterative back-translation, iterative knowledge distillation), and specific-domain fine-tuning. Moreover, we try several multi-domain methods, such as a multi-domain model structure and a multi-domain data clustering method, to rise to this year’s newly proposed multi-domain test set challenge. For low-resource scenarios, we build a multi-language translation model to enhance the performance, and try to use the pre-trained language model (mBERT) to initialize the translation model.
Genetic factors that provide adult plant resistance against Puccinia striiformis f. sp. tritici to wheat cultivar 'Stephens' in a multilocation analysis.

approved: _____________________________________________________________________ C. James Peterson Stripe rust (Puccinia striiformis f. sp. tritici) has been receiving increased attention in the USA since the appearance of more virulent races detected in the past decade. These races caused yield losses even in areas where the disease previously was rarely detected. Host plant resistance is the most cost effective and environmentally friendly means of controlling stripe rust. Deployment of single, major genes for resistance has been compromised due to the genetic variability of the pathogen, emphasizing the need to breed for durable resistance. ‘Stephens’ wheat (Triticum aestivum L.) has been
An Ultra-Sensitive Step-Function Opsin for Minimally Invasive Optogenetic Stimulation in Mice and Macaques

Optogenetics is among the most widely employed techniques to manipulate neuronal activity. However, a major drawback is the need for invasive implantation of optical fibers. To develop a minimally invasive optogenetic method that overcomes this challenge, we engineered a new step-function opsin with ultra-high light sensitivity (SOUL). We show that SOUL can activate neurons located in deep mouse brain regions via transcranial optical stimulation and elicit behavioral changes in SOUL knock-in mice. Moreover, SOUL can be used to modulate neuronal spiking and induce oscillations reversibly in macaque cortex via optical stimulation from outside the dura. By enabling external light delivery, our new opsin offers a minimally invasive tool for manipulating neuronal activity in rodent and primate models with fewer limitations on the depth and size of target brain regions and may further facilitate the development of minimally invasive optogenetic tools for the treatment of neurological disorders.