Miracle-dz/UniFAR-FTUs huggingface dataset:
Bronchiectasis in Primary Antibody Deficiencies: A Multidisciplinary Approach

Bronchiectasis, the presence of bronchial wall thickening with airway dilatation, is a particularly challenging complication of primary antibody deficiencies. While susceptibility to infections may be the primary factor leading to the development of bronchiectasis in these patients, the condition may develop in the absence of known infections. Once bronchiectasis is present, the lungs are subject to a progressive cycle involving both infectious and non-infectious factors. If bronchiectasis is not identified or not managed appropriately, the cycle proceeds unchecked and yields advanced and permanent lung damage. Severe symptoms may limit exercise tolerance, require frequent hospitalizations, profoundly impair quality of life (QOL), and lead to early death. This review article focuses on the appropriate identification and management of bronchiectasis in patients with primary antibody deficiencies. The underlying immune deficiency and the bronchiectasis need to be treated from combined immunology and pulmonary perspectives, reflected in this review by experts from both fields. An aggressive multidisciplinary approach may reduce exacerbations and slow the progression of permanent lung damage.
Development and Life History of Zelus tetracanthus Stål1: A Potential Predator of Diorhabda spp.2 in Tamarix spp. L.3

Abstract. The harpactorine assassin bug, Zelus tetracanthus (Stål) (Hemiptera: Reduviidae), is an insect predator frequently found in surveys of saltcedar (Tamarix spp.) in Oklahoma. Previous studies in a laboratory showed it could prey on Diorhabda carinulata (Desbrochers) (Coleoptera: Chrysomelidae), a recently introduced biological control agent for Tamarix. An F2 cohort of Z. tetracanthus was reared from egg to adult to measure stage-specific development rates and describe immature stages at 22 ± 1.0°C and 16:8 light:dark hours. The mean times for development of the five instars were 6.96 ± 0.13, 5.18 ± 0.13, 6.94 ± 0.29, 10.92 ± 0.43, and 17.93 ± 0.76 days, respectively. Several anatomical characters to distinguish instars, including body size, body color, and select morphological characters were described. Data from museum collections of Z. tetracanthus suggested the insect has a univoltine life cycle. The development data contrast with a previous description of Z. socius (= Z. tetracanthus) and illustrate the need to further study the variable morphology, natural history, and genetic makeup of the species.
Pharmacological Inhibition of HDAC6 Attenuates NLRP3 Inflammatory Response and Protects Dopaminergic Neurons in Experimental Models of Parkinson’s Disease

Aim To investigate the role of histone deacetylase 6 (HDAC6) deacetylation activity in nucleotide-binding oligomerization domain and leucine-rich repeat pyrin 3 domain (NLRP3) inflammatory response and explore the effects of pharmacological inhibition of HDAC6 with tubastatin A (TBA) on dopaminergic injury. Methods Using 6-OHDA-induced Parkinson’s disease (PD) models, we examined the effects of TBA on NLRP3 activation and cell injury in SH-SY5Y cells. We also investigated the effects of TBA on NLRP3 inflammatory responses and dopaminergic injury in the nigrostriatal system in mice and analyzed the acetylation levels of peroxiredoxin2 (Prx2) and oxidative stress. Results TBA inhibited 6-OHDA-induced NLRP3 activation, as demonstrated by decreased expressions of NLRP3 and matured caspase-1 and IL-1β, and also alleviated glial proliferation and dopaminergic neuronal degeneration. Notably, TBA recovered acetylation levels of Prx2 and reduced oxidative stress. Conclusion Our findings indicate that pharmacological inhibition of HDAC6 with TBA attenuates NLRP3 inflammation and protects dopaminergic neurons, probably through Prx2 acetylation. This study suggests that the deacetylase catalytic domain of HDAC6 is a potential target for PD treatment.
Editorial: HIV and Cancer Immunotherapy: Similar Challenges and Converging Approaches

Division of Microbiology and Immunology, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States, Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, United States, Department of Pediatrics, Emory University School of Medicine and Children’s Healthcare of Atlanta, Atlanta, GA, United States, Division of Experimental Medicine, University of California, San Francisco, San Francisco, CA, United States, 5 Emory Vaccine Center and Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, United States
The Relationship between the Saudi Cadets’ Learning Motivation and Their Vocabulary Knowledge

This paper is a report on the study of the relationship between foreign/second language (L2) motivation and vocabulary knowledge. The population of the study is the cadets of a military academy in Saudi Arabia who study English as a foreign language. The total number of participants is 195 Saudis. The author uses the L2 Motivational Self System to investigate the cadets’ L2 motivation and the vocabulary test “X-Lex” (Meara & Milton, 2003) to measure their vocabulary size (VS). The correlation analysis shows a positive moderate statistical correlation between the students’ L2 motivation and their VS because the Ideal L2 Self, the Language Learning Attitudes, and the Intended Learning Effort had a linear relationship with the VS. Nevertheless, the regression analysis reveals that none of these motivational scales is a predictor of the students’ VS. Finally, the correlation analysis and the regression analysis disclose a statistically significant correlation between the Saudi cadets’ self-perception as competent English users and their L2 motivation as well as their VS.
Patience goes a long way: Evidence from Spain

This study uses newly available data from the Survey of Financial Competences to investigate whether cross-region migrants in Spain are more patient than individuals who choose to remain in their birth region. The empirical model incorporates predicted probabilities of underreporting and overreporting of the migrant status. Less patient individuals appear to be less likely to be migrants. This result is robust to controlling for a variety of demographic and economic factors, as well as for cognitive ability.
Stakeholder Participation in Project Initiation: A Foundation to Completion of Urban Road Transport Infrastructure Projects, Kenya

Cost overrun and delays are major impediments to project completion in road construction industry globally. Stakeholder participation in construction cycle could present a solution to these challenges. The purpose of this study was therefore, to examine the influence of stakeholder participation in project initiation on completion of urban road transport infrastructure projects in Kenya. The unit of analysis was the road construction projects implemented by Kenya Urban Roads Authority (KURA). Pragmatic research paradigm was chosen for this study to facilitate mixed research methods. The study adopted descriptive survey and correlational research designs. The target population was 1593 and the sample size was 309 respondents. Purposive and simple random sampling procedures were utilized. A five-point Likert type scale questionnaire was used to collect quantitative data while interview guides were used to collect qualitative data. The study then applied both descriptive and inferential statistics for the data analysis. The study found that participation in project initiation had a positive and significant influence on the completion of urban road transport infrastructure projects in Kenya (r=0. 859, R2=0. 737, F (1, 212)=594.869, p<0.001<0.05). The study established that there was a positive influence of participation in project initiation on completion of urban road transport infrastructure projects in Kenya. The study recommends formulation of a policy framework to sensitize stakeholders on their participation in project initiation, project design and project construction to enhance effective project implementation and completion. The study recommends hiring of competent and experienced project managers to ensure effective implementation of urban road transport infrastructure.
Towards developing tools for Indian Languages using Deep Learning

Extensive research is being carried out in the field of Natural Language Processing (NLP) in the context of Indian languages. Spelling correction, word segmentation, and grammar checking are the fundamental problems in NLP. The aim of these problems is to identify noise in the data and correct it. These tools are important for many NLP applications like web search engines, text summarization, sentiment analysis, machine translation etc. Many methods have been developed for these problems for English, which usually exploit linguistic resources like parsers, large amounts of real world data etc. making it difficult to adapt them to other languages. For these problems, deep learning models have also been implemented for English. These models use parallel data of noisy and correct mappings from different sources as training data for automatic correction tasks. Indian languages are resource-scarce and do not have such parallel data due to low volume of queries and non-existence of such prior implementations. Spell correction is very crucial for applications like web search engines. In speech recognition and optical character recognition (OCR), word boundaries are not often comprehensible. Grammar checking is important to clean up the corpus before using it in any application. It is also useful as an aid for second language users and for applications like automatic essay grading. In applications like speech-to-text, handwritten text-to-text, and Machine Translation, applying spell checking, word segmentation, and grammar checking on the output will result in improved accuracy. Most of the existing language processing systems for Indian languages are rule-based and language specific. Majority of the works have a dictionary-based approach and check the errors against the dictionary. Due to lack of availability of training data for machine learning models, we create synthetic datasets using language rules. In this work, we present approaches to build automatic language correction systems for Hindi. We have proposed deep learning models for spelling correction, word segmentation, and grammar checking. The proposed approaches are applicable to any resource-scarce language. A comparative evaluation for each of these three problems shows that the proposed models are competitive with the existing correction techniques for Indian languages.
Adesão ao tratamento do diabetes mellitus e variáveis sociodemográficas, clinicas e de controle metabólico Adherence to diabetes mellitus treatment and sociodemographic, clinical and metabolic control variables

Abstract Objective: To investigate the association between adherence to type 2 diabetes mellitus treatment and sociodemographic, clinical and metabolic control variables.Methods: Cross-sectional study that included 417 diabetes mellitus patients. The research instrument was a questionnaire with the study variables; Treatment Adherence Measure; Food Consumption Frequency Questionnaire and International Physical Exercise Questionnaire. Fisher’s Exact Test was used to analyze the data.Results: About 98.3% showed non adherence to the diet, 41.9% to physical exercise and 15.8% to the medication treatment.Conclusion: No association was found between adherence to type 2 diabetes mellitus treatment and sex, age, years of education, length of diagnosis and metabolic control variables. Descritores Adesao a medicacao; Diabetes mellitus /enfermagem; Cuidados de enfermagem; Enfermagem de atencao primaria; Atencao primaria a saude Keywords Patient compliance; Diabetes mellitus /nursing; Nursing care; Primary care nursing; Primary health care
OAEs and Meniere Disease

Otoacoustic emissions (OAEs) are responses originating from the inner ear. Clinically they are evoked by different families of acoustic stimuli, such as transient acoustic clicks, tone pips, and pure tones. Upon stimulation, the acoustic energy is transformed in the middle ear at acoustic pressure acting upon the stapes footplate. The pressure wave inside the cochlea stimulates the OAE generators and a reverse acoustic energy (the OAE response) propagates from the inner ear, through the stapes and the middle ear structures, to the tympanic membrane. Considering that the acoustic energy has to cross the middle ear structures twice, the functional status of the middle ear can influence or attenuate considerably the OAE response. In this context, any vestibular alteration can influence the middle ear mechanics (mainly the middle ear impedance) and consequently the OAE response characteristics. The data in the literature indicate that OAEs are very sensitive to changes in the intracranial pressure. These pressure alterations during the Meniere’s hydrops phase are expressed as changes in the intralabyrinthine pressure. Other studies have presented data supporting the assumption that OAEs can adequately monitor middle ear changes induced by the presentation of the glycerol test. The data in the literature suggest that OAEs can monitor the progress of Meniere’s disease using reliable indices.
ANALYSIS OF PREGNANT WOMEN WITH PLACENTA ACCRETA IN HAJI ADAM MALIK MEDAN HOSPITAL, PERIOD 2017-2019

Placenta accreta is an abnormal form of placentation in which the chorion villi attaches or invades abnormally through a defect in the basal decidua causing a possible failure of placental detachment from the uterus followed by heavy post-partum hemorrhage. Lately, there has been an increase in the incidence of placenta accreta at Rumah Sakit Umum Pemerintah Haji Adam Malik Medan (RSUP HAM). However, up to now, there are no data on prevalence, patient characteristics, risk factors or management of placenta accreta events in the province of North Sumatra.The design of this study is a descriptive study with a case series design that is women diagnosed with placenta accreta. The research sample is a part of the population that fulfills the inclusion and exclusion criteria. The sample size in this study is 50 patients diagnosed with placenta accreta to be taken with the total sampling technique registered in the medical record of RSUP Haji Adam Malik Medan from May 2017 to June 2019. The total number of patients diagnosed with placenta accreta from May 2017 to June 2019 (2 years) was 50 patients (100%), with the most periods being June 2018-June 2019 totaling 40 patients (90%), then the period May 2017 May 2018 numbered 10 patients (10%). The total number of patients diagnosed with placenta accreta from May 2017 to June 2019 (2 years) was 50 patients, with the most period being June 2018-June 2019 totaling 40 patients, then the period May 2017-May 2018 amounted to 10 patients. Based on age, 29 samples were aged 20-35 years, with parity, the majority were multigravida by 42 people. Based on gestational age, as many as 31 samples were between 34-37 weeks of pregnancy. For the history of antenatal care (ANC) the majority of samples did in external hospitals as many as 44 people, based on the history of C-section it appears that the majority of 31 samples lived 2 times. 43 samples never experienced abortion. 37 samples underwent Total Abdominal Hysterectomy (TAH) and 13 samples underwent conservative measures. 50 samples gave birth to live infants, while the majority of babies born weighed between 2500-4000 grams as many as 38 babies. Based on the Placenta Accreta Index (PAI) Score, it appears that 22 samples had scores >4-<6. 48 samples underwent elective surgery while only 2 samples underwent emergency surgery. Based on anatomic pathology examination, it appears that 29 samples were placenta accreta, 18 samples were placenta increta and 3 samples were placenta percreta.
Stock Return Predictability and Model Uncertainty: A Frequentist Model Averaging Approach

The model uncertainty is a phenomenon where general consensus about the form of specific model is unclear. Stock returns perfectly meet this condition, as extensive literature offers diverse methods and potential drivers without a clear winner among them. Relatively recently, averaging techniques emerged as a possible solution to such scenarios. The two major averaging branches, Bayesian (BMA) and Frequentist (FMA) averaging, naturally deal with uncertainty by averaging over all model candidates rather than choosing the ”best” one of them. We focus on FMA, and apply this method to our data from U.S. market about S&P 500 index, that I help to explain with the set of eleven explanatory variables chosen in accordance with related literature. To preserve a real-world applicability, I use rolling window scheme to regularly update data in the fitting model for quarterly based re-estimation. Consequently, predictions are obtained with the use of most recent data. Firstly, we find out that simple historical average model can be beaten with a standard model selection approach based on AIC value, with variables as Dividend Yield, Earnings ratio, and Book-to-Market value proving consistently as most significant across quarterly models. With FMA techniques, I was not able to consistently beat the benchmark from model selection, as results are rather disappointing. I discuss impact of window size choice in the rolling scheme and eventually re-run analysis with single window shift and random split. Observed results are much more promising, as all FMA methods are outperforming benchmark. JEL Classification C58, C22, G12
Modified Reinforcement Learning-Hierarchical Neuro-Fuzzy Politree Model for Control of Autonomous Agents

Abstract: This work presents a new hybrid neuro-fuzzy model for automatic learning of actions taken by agents. The main objective of this new model is to provide an agent with intelligence, making it capable, by interacting with its environment, to acquire and retain knowledge for reasoning (infer an action). This new model, named Reinforcement Learning Hierarchical Neuro-Fuzzy Politree (RL-HNFP), and its improved version (RL-HNFP + ), descends from the Reinforcement Learning Hierarchical Neuro-Fuzzy BSP (RL-HNFB) that applies binary hierarchical partitioning methods, together with the Reinforcement Learning (RL) methodology. These two characteristics permit the autonomous agent to automatically learn its structure and its necessary action in each position in the environment. The RL-HNFP model and its extension (RL-HNFP + ) are evaluated in a well known benchmark application in the area of autonomous agents: the Mountain Car Problem. The results obtained demonstrate the potential of these models, which operate without any prior information, such as number of rules, rules specification, or number of partitions that the input space should have, providing good performance and demonstrating the agent’s autonomy.
Prevalence of Diabetes and Pre-Diabetes in a Cohort of High Risk Undiagnosed Patients

No specific data and statistics are available in Lebanon, to estimate the prevalence of T2D and PD in rural areas such as Bekaa. Therefore, we undertook the mission of conducting this cross sectional study of 200 individuals aged 18 to 65, randomly selected from different regions of the Bekaa. The objectives of our study were to determine the prevalence of T2D and PD in high-risk patients, not known diabetics, and correlate the incidence with the known risk factors and their effects on developing T2D and PD. The risk factors studied were age, hypertension, obesity, family history of diabetes, history of gestational diabetes, and sedentary lifestyle [5-7].
Predictive Value of Maternal Serum Level of Procalcitonin in Diagnosing Chorioamnionitis in Mothers with Preterm Premature Rupture of Membrane (PROM)

Background: Premature Rupture of Membrane (PROM) refers to the rupture of fetal membranes at least 1 hour before the onset of labor pain. The present study intended to determine the predictive value of maternal serum level of Procalcitonin in the early diagnosis of Chorioamnionitis in mothers with PPROM.Methods: In this prospective cohort study, a total of 48 patients with PPROM were selected as the intended sample size due limited financial resources and in accordance with previous articles in Kosar ward of Motahhari hospital of Urmia city, Iran. Inclusion Criteria were amniotic fluid leak, positive Nitrazine and Fern test, gestational age from 28 to 33 weeks and lack of fetal tachycardia. Exclusion Criteria were chronic and congenital heart disease as well as use of NSAIDs. Data were analyzed using SPSS 19 and descriptive statistics, independent t-test and Pearson test were performed.Results: The present study was conducted on 48 pregnant women and their neonates. About %39.6 of mothers was pathologically infected with Chorioamnionitis while %60.4 of the patients were not infected with the disease. Moreover, %68.8 of the neonates had a five-minute Apgar score of ≥7. There was a significant correlation between infection of mothers with histopathologic Chorioamnionitis and neonatal hospitalization in NICU (P<0.001). The sensitivity, specificity, positive and negative predictive values of PCT inflammatory index were %100, %79, %57.5 and %100 respectively for the diagnosis of histopathologic Chorioamnionitis.Conclusion: It was found that there was a significant correlation between PCT index at delivery time and histopathologic Chorioamnionitis.
Do males differ from females in the way they set and meet goals? An analysis of marathon runners

We examine strategies adopted by people completing a well-defined but difficult task: running a marathon. We find strong evidence that males relative to females focus on, and care more about, beating a round number time (e.g., 4:00 hours). Our evidence suggests that setting a round number goal helps males perform better in the race. We find that these males are more likely to run at constant pace (the optimal way to run a marathon) and have more energy to speed up (“kick”) towards the end of the race. In contrast, females are less likely to set round number times as goals, and run more conservatively at the start, pace themselves better throughout the race, and finish with a stronger kick, irrespective of whether their finish time is close to a round number. Our results also suggest that males benefit more from planning than do females, since we find that less experienced males are more likely to start the race too aggressively and slow down considerably (“bonk”) towards the end of the race. Our results have implications for organizations because they suggest that the sexes can subconsciously differ in the strategies they adopt to complete a task and the goals they use to evaluate their performance.