Miracle-dz/UniFAR-FTUs huggingface dataset:
Fertility and Irrigation Effects on ‘Temple’ Orange. I. Yield and Leaf Analyses1

Six year’s data with so-called ‘Temple’ orange (Citrus hybrid) on ‘Cleopatra’ mandarin rootstock (Citrus reticulata Blanco), show that increased rates of N and K increased fruit yield. P also increased yield. Spring vs. fall irrigation resulted in a significant increase in fruit production in 1 of 6 years, although slightly higher fruit production was observed every year with spring irrigation. Increased N rates resulted in higher leaf N and Mg but lower leaf P, K, and Ca. Increased K rates raised leaf K but lowered leaf Mg. The addition of P in the fertilizer resulted in higher leaf P and Ca but lower K and Mg contents. Spring irrigation induced lower K but higher Mg in certain years.
Concordance between Different Criteria for Metabolic Syndrome in Peruvian Adults Undergoing Bariatric Surgery

Background: Metabolic Syndrome (MetS) is a clinical entity that has been linked to several non-communicable diseases. There are various consensuses to determine its presence, such as the IDF, ALAD, Harmonized, AHA/NHLBI, NCEP-ATP III or AACE criteria. However, there is currently no standardization to properly identify it. Objective: To assess the diagnostic concordance between different criteria for MetS in Peruvian adults undergoing bariatric surgery. Methods: We conducted a secondary analysis of the institutional database of a bariatric clinic located in Lima, Peru. We obtained data from adults between 18–59 years who underwent bariatric surgery (Roux-en-Y Gastric Bypass or Sleeve Gastrectomy). According to the Kappa coefficient, a heatplot was designed to analyze the concordance of the criteria. Results: An almost perfect concordance was found between all criteria except AACE. The highest kappa coefficient (κ = 0.980) was recorded between the IDF and ALAD criteria using all the sample. Similar results were obtained when we stratified by sex. Conclusions: This study shows that, excluding the AACE, different criteria for metabolic syndrome could be used in Latino adults undergoing bariatric surgery with similar results. Given the postoperative implications, we believe that IDF and ALAD would be the best options in our population.
The Use of Family Planning Methods (FPMs) in Ilala Municipality, Dar es Salaam, Tanzania

This paper examines the use of family planning methods in Ilala Municipality, Dar es Salaam, Tanzania. Atotal of 55 respondents were involved in the study. The study used both quantitative and qualitative techniquesin collecting and analysing data. A questionnaire, in-depth interviews and documentary review were used togather data. The findings indicated that the modern family planning methods, such as condoms and oralcontraceptives like postinor-2, the morning after pills, injection, and implant, were preferred over thetraditional family planning methods, such as withdrawals, calendar rhythm method and periodic abstinence.The factors influencing family planning methods were education, access to information, fear and unfoundedethical beliefs, number of siblings, children as an indicator of one’s high status, prestige, and childrenconfirming one’s virtue. Generally, the use of family planning methods was determined by socio-economicstatus of the users and environmental variables. Therefore, it is recommended that the stakeholders constructhealth centres and educate people on good family planning methods.
Challenges of Short Sentence Writing Encountered by First-Year Saudi EFL Undergraduate Students

This paper is set up to outline the most common challenges in writing short sentences encountered by the first-year students at the English language departments at Al-Baha University campuses. The study is considered necessary because it raises the awareness of both students and instructors to improve their sentence writing. A mixed approach (quantitative and qualitative) was used to collect the data using questionnaires and interviews. Approximately122 students who study English as a Foreign Language (EFL), (%50.4 females and %49.6 males), together with 30 EFL instructors (15 males and 15 females) who were randomly selected. The paper addresses three questions. They are: 1) What common challenges do students face when writing short sentences? , 2) What are the most frequent challenging short sentence components among the students? , and 3) What are the differences between male and female students regarding difficulties in writing short sentences? The study found significant challenges in constructing short sentences, distinguishing between active and passive voice, and using conjunctions, punctuation, quantifiers, and appropriate auxiliary verbs. Additionally, students encountered difficulties in building short sentences. Moreover, the study revealed that a high percentage of students have very low English writing skills practice. To overcome any obstacles and push students forward in their learning later, this study highly recommended that EFL instructors should pay more attention to the development of writing skills. Thus, extra written activities and peer assessment must be granted to students in writing short sentences. Moreover, more research should be done to explore and evaluate the most prevalent problems and barriers that first-year students encounter using written samples and paperwork.
Grassland farmers’ relationship with biodiversity: a case study from the northern Italian Alps

ABSTRACT To successfully understand and shape biodiversity conservation in Alpine grasslands, it is crucial to understand how farmers’ relationship to biodiversity influences their goals and associated practices. We explored how farmers perceive and value biodiversity, how this is related to agricultural and land use practices, and how they view their roles in affecting it. Semi-structured interviews were conducted with 22 farmers in the northern Italian Alps and with 6 experts in the fields of grassland management, agriculture, and environmental conservation in 2020. The farmers’ answers were analyzed using a mental model approach, relational thinking, and the literature on the ‘good farmer’. The experts’ responses were used to discuss and contextualize the farmer’s answers. We found that the farmers’ mental model of biodiversity is associated to different aspects of agricultural management practices and farmers’ roles in mountain agricultural landscapes. Instrumental values of biodiversity are negative and strongly perceived as such by farmers, while relational values associated with biodiversity are positive, but more weakly perceived. These differing perceptions and values seem to be associated with two roles that farmers have, as producers and landscape stewards, and how they value fodder quantity and quality. Most farmers don’t include considerations related to the conservation of biodiversity in their management decisions, and mostly do not envision any changes in biodiversity or management in the future. Effective biodiversity conservation in Alpine grasslands will therefore need to tap into these dual roles and the associated instrumental and relational values of biodiversity for a meaningful dialogue on conservation.
Correlation effects in strong-field ionization of heteronuclear diatomic molecules

We develop a time-dependent theory to investigate electron dynamics and photoionization processes of diatomic molecules interacting with strong laser fields including electron-electron correlation effects. We combine the recently formulated time-dependent generalized-active-space configuration interaction theory [D. Hochstuhl and M. Bonitz, Phys. Rev. A 86, 053424 (2012); S. Bauch et al., ibid. 90, 062508 (2014)] with a prolate spheroidal basis set including localized orbitals and continuum states to describe the bound electrons and the outgoing photoelectron. As an example, we study the strong-field ionization of the two-center four-electron lithium hydride molecule in different intensity regimes. By using single-cycle pulses, two orientations of the asymmetric heteronuclear molecule are investigated: Li-H, with the electrical field pointing from H to Li, and the opposite case of H-Li. The preferred orientation for ionization is determined and we find a transition from H-Li, for low intensity, to Li-H, for high intensity. The influence of electron correlations is studied at different levels of approximation, and we find a significant change in the preferred orientation. For certain intensity regimes, even an interchange of the preferred configuration is observed, relative to the uncorrelated simulations. Further insight is provided by detailed comparisons of photoelectron angular distributions with and without correlation effects taken into account.
The Microbiome in COPD: Emerging Potential for Microbiome-Targeted Interventions

Abstract The aim of interventions over the respiratory microbiome in COPD is to preserve the original microbial flora, focusing in taxa with a demonstrated impact on the prognosis of the disease. Inhaled therapy is the main treatment for COPD, and chronic corticosteroid use is recommended for patients with frequent exacerbations. This therapy, however, increases both the bronchial microbial load and the abundance of potentially pathogenic bacteria in patients with low peripheral eosinophil counts, and to minimize its use in patients without peripheral eosinophilia, when possible, may avoid increases in bacterial loads of microorganisms as Haemophilus influenzae and Streptococcus pneumoniae. In exacerbations antibiotics determine a decrease in the microbial diversity, a change that persists during stability periods in frequent exacerbators. High-diversity bronchial microbiomes are enriched in non-dominant genera and determine low exacerbation frequencies and survival improvement. Limiting the antibiotic use to the treatment of exacerbations which would clearly benefit would favor the diversity of the respiratory microbiome and may have a positive impact on quality of life and survival. Oral antiseptics have shown and effect on the bronchial microbiome that was associated with improvements in quality of life, and the gut microbiome may be also modified through the oral administration of probiotics or prebiotics, that potentially may determine decreases in lung inflammation and bronchial hyperreactivity. High fiber diets also favor the production of anti-inflammatory molecules by the digestive flora, which would reach the respiratory system through the bloodstream. Interventional approaches favoring the preservation of the respiratory microbiome in COPD need first to select accurately the patients who would benefit from long-term inhaled corticosteroids and antibiotic treatments during exacerbations, under the hypothesis that keeping a respiratory microbiome close to the healthy subject would favor the respiratory health. Additionally, high fiber diets may be able to modify the gut microbiome and influence the respiratory system through the gut-lung axis. Therapeutic approaches targeting the microbiome to improve COPD, however, still require clinical validation and the identification of patient subtypes who would benefit the most with their use.
High Strain Capacity Pipeline Qualification For the PNG LNG Project

The onshore pipeline portion of the Papua New Guinea Liquefied Natural Gas (PNG LNG) project traverses terrain with seismically active faults with potential soil displacements up to four meters. The resulting longitudinal strain demand exceeds 0.5% strain, thereby requiring use of the strain-based pipeline design method. This paper discusses the application of previously developed strain-based design methodologies to successfully qualify the PNG LNG pipeline system for a design tensile strain demand up to 3%, and flexibility to increase the design strain demand with additional restrictions on key variables impacting strain capacity at select locations. The qualification timeline, key engineering and project decisions, and lessons learned from this qualification effort are described.
Multivariate Techniques for Water Quality Analysis

The objective of this study was to demonstrate the application of multivariate statistical techniques towards the understanding of variables affecting water quality. One of the major problems confronting an investigator in the application of statistical techniques to water quality data is missing observations. A simultaneous multiple regression method is presented in this paper for estimating missing observations in a data matrix. The major goals of using multivariate analysis are to facilitate interpretation and to prove hypotheses concerning the data. The techniques considered in this paper include principal components, canonical correlation, partial correlation, multivariate analysis of variance (MANOVA), and discriminant analysis. Examples are presented demonstrating the application of these methods.
Asymptotic Inference for Nonstationary Fractionally Integrated Processes

This paper studies the asymptotics of nonstationary fractionally integrated (NFI) multivariate processes with memory parameter d > 0.5 . We provide conditions to establish a functional central limit theorem and weak convergence of stochastic integrals for NFI processes under the assumption that the innovations are linear processes. Several applications of these results are given. More specifically, we prove the rates of convergence of the OLS estimators of cointegrating vectors in triangular representations. When the regressors are strongly exogenous with respect to the corresponding parameters of the cointegrating vector, then the limiting OLS distribution is a mixture of normals from which standard inference can be implemented. On the other hand, we also extend Sims, Stock and Watson's (1990) study on estimation and hypothesis testing in vector autoregressions with integrated processes and deterministic components to the more general fractional framework. We show how their main conclusions remain valid when dealing with NFI processes, namely, that whenever a block of coefficients can be written as coefficients on zero mean I(0) regressors in a model that includes a constant term, they will have a joint asymptotic normal distribution, so that the corresponding restrictions can be tested using standard asymptotic chi-squared distribution theory. Otherwise, in general, the associated statistics will have nonstandard limiting distributions.
exus between being landlocked and living standards in Sub-Saharan African countries: A two-step System GMM analysis

The ultimate objective of the study was to investigate the effects of being landlocked on the living standards in Sub-Saharan African (SSA) countries from 1991 to 2019. Adopting the two-step estimation technique of System GMM (generalized method of moments), the study found that being landlocked has a negative and significant effect on the living standards in SSA countries when using GDP per capita as the living standard measure. Moreover, the historical living standard experiences of SSA countries have a positive and significant influence on the current living standard level. In addition, the population growth rate has a positive and significant effect on the living standards in SSA countries. On the other hand, the official exchange rate, broad money as a percentage of GDP, and inflation have a negative and significant effect on the living standards in SSA countries. Generally, the estimated result reveals the existence of a significant variation in the living standards in landlocked and coastal SSA countries. This study suggests that regional integration between landlocked and transit countries should be improved to minimize entry costs and increase access to global markets for landlocked countries. We argue that this study is of interest to landlocked and coastal countries to increase trade integration and promote the development of both groups, and it will contribute to the scarce empirical evidence.
Identifying the Perceived Severity of Patient-Generated Telemedical Queries Regarding COVID: Developing and Evaluating a Transfer Learning–Based Solution

Background Triage of textual telemedical queries is a safety-critical task for medical service providers with limited remote health resources. The prioritization of patient queries containing medically severe text is necessary to optimize resource usage and provide care to those with time-sensitive needs. Objective We aim to evaluate the effectiveness of transfer learning solutions on the task of telemedical triage and provide a thorough error analysis, identifying telemedical queries that challenge state-of-the-art natural language processing (NLP) systems. Additionally, we aim to provide a publicly available telemedical query data set with labels for severity classification for telemedical triage of respiratory issues. Methods We annotated 573 medical queries from 3 online health platforms: HealthTap, HealthcareMagic, and iCliniq. We then evaluated 6 transfer learning solutions utilizing various text-embedding strategies. Specifically, we first established a baseline using a lexical classification model with term frequency–inverse document frequency (TF-IDF) features. Next, we investigated the effectiveness of global vectors for text representation (GloVe), a pretrained word-embedding method. We evaluated the performance of GloVe embeddings in the context of support vector machines (SVMs), bidirectional long short-term memory (bi-LSTM) networks, and hierarchical attention networks (HANs). Finally, we evaluated the performance of contextual text embeddings using transformer-based architectures. Specifically, we evaluated bidirectional encoder representation from transformers (BERT), Bio+Clinical-BERT, and Sentence-BERT (SBERT) on the telemedical triage task. Results We found that a simple lexical model achieved a mean F1 score of 0.865 (SD 0.048) on the telemedical triage task. GloVe-based models using SVMs, HANs, and bi-LSTMs achieved a 0.8-, 1.5-, and 2.1-point increase in the F1 score, respectively. Transformer-based models, such as BERT, Bio+Clinical-BERT, and SBERT, achieved a mean F1 score of 0.914 (SD 0.034), 0.904 (SD 0.041), and 0.917 (SD 0.037), respectively. The highest-performing model, SBERT, provided a statistically significant improvement compared to all GloVe-based and lexical baselines. However, no statistical significance was found when comparing transformer-based models. Furthermore, our error analysis revealed highly challenging query types, including those with complex negations, temporal relationships, and patient intents. Conclusions We showed that state-of-the-art transfer learning techniques work well on the telemedical triage task, providing significant performance increase over lexical models. Additionally, we released a public telemedical triage data set using labeled questions from online medical question-and-answer (Q&A) platforms. Our analysis highlights various avenues for future works that explicitly model such query challenges.
Relative refractoriness of breast cancer cells to tumour necrosis factor‐α induced necroptosis

Necroptosis, a recently identified programmed cell death pathway, has attracted attention as an alternative route to target apoptosis‐resistant cancer cells. The status of the necroptosis pathway in different subtypes of breast cancer has not been well explored. Stimulating the cells by TNF‐α can trigger cell survival or death depending on the combination of downstream players involved. In this work, we attempted to induce necroptosis in them using a combination of TNF‐α and Z‐VAD‐FMK with and without chemotherapy. Cell viability, apoptosis, and necroptosis were assessed using MTT and Annexin‐V/PI assays, respectively. Gene and protein expression was analysed by qPCR and immunophenotyping. Both the cell lines were resistant to induction of cell death by necroptosis. There was no enhancement in cell death when chemotherapeutic drugs were combined with necroptosis induction. Expression studies showed reduced translational expression of key necroptosis molecules like RIP kinases and MLKL in breast cancer cells compared to positive control cell line L929. Also, cell survival molecules were expressed more in MDA‐MB‐231 in contrast to death pathway molecules which were expressed more in T47D cells. In this work, the two breast cancer cell lines were observed to be resistant to TNF‐α induced necroptosis with or without chemotherapy. Expression of key necroptosis players revealed relative insufficiency of the molecular machinery involved in the above pathway. In our opinion this may be the cause for resistance to necroptosis and novel strategies to upregulate these molecules need to be developed to sensitize the breast cancer cells towards cell death by necroptosis.
Two Time-Scale Learning for Beamforming and Phase Shift Design in RIS-aided Networks

In this work, we develop a two time-scale deep learning approach for beamforming and phase shift (BF-PS) design in time-varying RIS-aided networks. In contrast to most existing works that assume perfect CSI for BF-PS design, we take into account the cost of channel estimation and utilize Long Short-Term Memory (LSTM) networks to design BF-PS from limited samples of estimated channel CSI. An LSTM channel extrapolator is designed first to generate high resolution estimates of the cascaded BS-RIS-user channel from sampled signals acquired at a slow time scale. Subsequently, the outputs of the channel extrapolator are fed into an LSTM-based two stage neural network for the joint design of BF-PS at a fast time scale of per coherence time. To address the critical issue that training overhead increases linearly with the number of RIS elements, we consider various pilot structures and sampling patterns in time and space to evaluate the efficiency and sum-rate performance of the proposed two time-scale design. Our results show that the proposed two time-scale design can achieve good spectral efficiency when taking into account the pilot overhead required for training. The proposed design also outperforms a direct BF-PS design that does not employ a channel extrapolator. These demonstrate the feasibility of applying RIS in time-varying channels with reasonable pilot overhead.
The Sociodemographic-Professional Profile and Emotional Intelligence in Infant and Primary Education Teachers

Emotional intelligence is the key to students’ psychological-social well-being and academic performance, and teachers must provide socioemotional education in the classroom. To achieve this, teachers must display high levels of socioemotional skills that ensure their own personal, social, and career well-being and, as a result, that of their students. This study seeks to gain an insight into the levels of socioemotional skills of emotional perception, emotional understanding, and emotional regulation and how these are linked to the sociodemographic and career profile of teachers in infant and primary education. For this, we surveyed 351 teachers—310 female and 41 male—aged between 20 and 69. We used the Trait Meta-Mood Scale-24 (TMMS-24) together with a questionnaire (ad hoc) to determine the sociodemographic and career profile of participating teachers. Statistical analysis of the data showed that gender impacts on emotional regulation and emotional perception, while age and number of the children were also seen to have significant difference on emotional regulation and emotional perception. In contrast, professional qualifications were only seen to affect emotional perception. The variable reflecting the level at which staff teach showed significant difference on emotional perception and emotional understanding, while administrative posts held by teachers also demonstrated significant difference on their emotional understanding. The results confirm that sociodemographic and work-related variables impact the level of socioemotional skills of infant and primary education teachers. These aspects should be taken into account in the structure and planning of training aimed at developing socioemotional skills in order to ensure their success.