Search results for: linear regression estimation

Authors: Pierre-Louis Lucas, Corinne Loutelier-Bourhis, Narimane Mati-Baouche, Philippe Chan Tchi-Song, Patrice Lerouge, Elodie Mathieu-Rivet, Muriel Bardor

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N-glycosylation is a post-translational modification taking place in the Endoplasmic Reticulum and the Golgi apparatus where defined glycan features are added on protein in a very specific sequence Asn-X-Thr/Ser/Cys were X can be any amino acid except proline. Because it is well-established that those N-glycans play a critical role in protein biological activity, protein half-life and that a different N-glycan structure may induce an immune response, they are very important in Biopharmaceuticals which are mainly glycoproteins bearing N-glycans. From now, most of the biopharmaceuticals are produced by mammalian cells like Chinese Hamster Ovary cells (CHO) for their N-glycosylation similar to the human, but due to the high production costs, several other species are investigated as the possible alternative system. In this purpose, the green microalgae Chlamydomonas reinhardtii was investigated as the potential production system for Biopharmaceuticals. This choice was influenced by the facts that C. reinhardtii is a well-study microalgae which is growing fast with a lot of molecular biology tools available. This organism is also producing N-glycan on its endogenous proteins. However, the analysis of the N-glycan structure of this microalgae has revealed some differences as compared to the human. Rather than in Human where the glycans are processed by key enzymes called N-acetylglucosaminyltransferase I and II (GnTI and GnTII) adding GlcNAc residue to form a GlcNAc₂Man₃GlcNAc₂ core N-glycan, C. reinhardtii lacks those two enzymes and possess a GnTI independent glycosylation pathway. Moreover, some enzymes like xylosyltransferases and methyltransferases not present in human are supposed to act on the glycans of C. reinhardtii. Furthermore, the recent structural study by mass spectrometry shows that the N-glycosylation precursor supposed to be conserved in almost all eukaryotic cells results in a linear Man₅GlcNAc₂ rather than a branched one in C. reinhardtii. In this work, we will discuss the new released MS information upon C. reinhardtii N-glycan structure and their impact on our attempt to modify the glycan in a Human manner. Two strategies will be discussed. The first one consisted in the study of Xylosyltransferase insertional mutants from the CLIP library in order to remove xyloses from the N-glycans. The second will go further in the humanization by transforming the microalgae with the exogenous gene from Toxoplasma gondii having an activity similar to GnTI and GnTII with the aim to synthesize GlcNAc₂Man₃GlcNAc₂ in C. reinhardtii.

Keywords: Chlamydomonas reinhardtii, N-glycosylation, glycosyltransferase, mass spectrometry, humanization

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Authors: Juan Cuesta

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Satellite observation is a fundamental component of air pollution monitoring systems, such as the large-scale Copernicus Programme. Next-generation satellite sensors, in orbit or programmed in the future, offer great potential to observe major air pollutants, such as tropospheric ozone, with unprecedented spatial and temporal coverage. However, satellite approaches developed for remote sensing of tropospheric ozone are based solely on measurements from a single instrument in a specific spectral range, either thermal infrared or ultraviolet. These methods offer sensitivity to tropospheric ozone located at the lowest at 3 or 4 km altitude above the surface, thus limiting their applications for ozone pollution analysis. Indeed, no current observation of a single spectral domain provides enough information to accurately measure ozone in the atmospheric boundary layer. To overcome this limitation, we have developed a multispectral synergism approach, called "IASI+GOME2", at the Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA) laboratory. This method is based on the synergy of thermal infrared and ultraviolet observations of respectively the Infrared Atmospheric Sounding Interferometer (IASI) and the Global Ozone Monitoring Experiment-2 (GOME-2) sensors embedded in MetOp satellites that have been in orbit since 2007. IASI+GOME2 allowed the first satellite observation of ozone plumes located between the surface and 3 km of altitude (what we call the lowermost troposphere), as it offers significant sensitivity in this layer. This represents a major advance for the observation of ozone in the lowermost troposphere and its application to air quality analysis. The ozone abundance derived by IASI+GOME2 shows a good agreement with respect to independent observations of ozone based on ozone sondes (a low mean bias, a linear correlation larger than 0.8 and a mean precision of about 16 %) around the world during all seasons. Using IASI+GOME2, lowermost tropospheric ozone pollution plumes are quantified both in terms of concentrations and also in the amounts of ozone photo-chemically produced along transport and also enabling the characterization of the ozone pollution, such as what occurred during the lockdowns linked to the COVID-19 pandemic. The current paper will show the IASI+GOME2 multispectral approach to observe the lowermost tropospheric ozone from space and an overview of several applications on different continents and at a global scale.

Keywords: ozone pollution, multispectral synergism, satellite, air quality

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Authors: Aline Woine, Moïra Mikolajczak, Virginie Dardier, Isabelle Roskam

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Background information: Becoming a parent is said to be the happiest event one can ever experience in one’s life. This popular (and almost absolute) truth–which no reasonable and decent human being would ever dare question on pain of being singled out as a bad parent–contrasts with the nuances that reality offers. Indeed, while many parents do thrive in their parenting role, some others falter and become progressively overwhelmed by their parenting role, ineluctably caught in a spiral of exhaustion. Parental burnout (henceforth PB) sets in when parental demands (stressors) exceed parental resources. While it is now generally acknowledged that PB affects the parent’s behavior in terms of neglect and violence toward their offspring, little is known about the impact that the syndrome might have on the children’s internalized (anxious and depressive symptoms, somatic complaints, etc.) and/or externalized (irritability, violence, aggressiveness, conduct disorder, oppositional disorder, etc.) behaviors. Furthermore, at the time of writing, to our best knowledge, no research has yet tested the reverse effect, namely, that of the child's internalized and/or externalized behaviors on the onset and/or maintenance of parental burnout symptoms. Goals and hypotheses: The present pioneering research proposes to fill an important gap in the existing literature related to PB by investigating the bidirectional effect between PB and the child’s internalized and/or externalized behaviors. Relying on a cross-lagged longitudinal study with three waves of data collection (4 months apart), our study tests a transactional model with bidirectional and recursive relations between observed variables and at the three waves, as well as autoregressive paths and cross-sectional correlations. Methods: As we write this, wave-two data are being collected via Qualtrics, and we expect a final sample of about 600 participants composed of French-speaking (snowball sample) and English-speaking (Prolific sample) parents. Structural equation modeling is employed using Stata version 17. In order to retain as much statistical power as possible, we use all available data and therefore apply the maximum likelihood with a missing value (mlmv) as the method of estimation to compute the parameter estimates. To limit (in so far is possible) the shared method variance bias in the evaluation of the child’s behavior, the study relies on a multi-informant evaluation approach. Expected results: We expect our three-wave longitudinal study to show that PB symptoms (measured at T1) raise the occurrence/intensity of the child’s externalized and/or internalized behaviors (measured at T2 and T3). We further expect the child’s occurrence/intensity of externalized and/or internalized behaviors (measured at T1) to augment the risk for PB (measured at T2 and T3). Conclusion: Should our hypotheses be confirmed, our results will make an important contribution to the understanding of both PB and children’s behavioral issues, thereby opening interesting theoretical and clinical avenues.

Keywords: exhaustion, structural equation modeling, cross-lagged longitudinal study, violence and neglect, child-parent relationship

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Authors: Nicholas McNamara, John Brookes, Michael Williams, Manish Mathew, Elizabeth Brookes, Tristan Yan, Paul Bannon

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Objective: Pericardial effusions are an uncommon but potentially fatal complication after cardiac surgery. The goal of this study was to describe the incidence and risk factors associated with the development of pericardial effusion requiring drainage after coronary artery bypass graft surgery (CABG). Methods: A retrospective analysis was undertaken using prospectively collected data. All adult patients who underwent CABG at our institution between 1st January 2017 and 31st December 2018 were included. Pericardial effusion was diagnosed using transthoracic echocardiography (TTE) performed for clinical suspicion of pre-tamponade or tamponade. Drainage was undertaken if considered clinically necessary and performed via a sub-xiphoid incision, pericardiocentesis, or via re-sternotomy at the discretion of the treating surgeon. Patient demographics, operative characteristics, anticoagulant exposure, and postoperative outcomes were examined to identify those variables associated with the development of pericardial effusion requiring drainage. Tests of association were performed using the Fischer exact test for dichotomous variables and the Student t-test for continuous variables. Logistic regression models were used to determine univariate predictors of pericardial effusion requiring drainage. Results: Between January 1st, 2017, and December 31st, 2018, a total of 408 patients underwent CABG at our institution, and eight (1.9%) required drainage of pericardial effusion. There was no difference in age, gender, or the proportion of patients on preoperative therapeutic heparin between the study and control groups. Univariate analysis identified preoperative atrial arrhythmia (37.5% vs 8.8%, p = 0.03), reduced left ventricular ejection fraction (47% vs 56%, p = 0.04), longer cardiopulmonary bypass (130 vs 84 min, p < 0.01) and cross-clamp (107 vs 62 min, p < 0.01) times, higher drain output in the first four postoperative hours (420 vs 213 mL, p <0.01), postoperative atrial fibrillation (100% vs 32%, p < 0.01), and pleural effusion requiring drainage (87.5% vs 12.5%, p < 0.01) to be associated with development of pericardial effusion requiring drainage. Conclusion: In this study, the incidence of pericardial effusion requiring drainage was 1.9%. Several factors, mainly related to preoperative or postoperative arrhythmia, length of surgery, and pleural effusion requiring drainage, were identified to be associated with developing clinically significant pericardial effusions. High clinical suspicion and low threshold for transthoracic echo are pertinent to ensure this potentially lethal condition is not missed.

Keywords: coronary artery bypass, pericardial effusion, pericardiocentesis, tamponade, sub-xiphoid drainage

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Authors: Keiko Yamauchi, Motoyuki Nakao, Yoko Ishihara

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The increase in the number of women with breast cancer in Japan has required hospitals to provide a higher quality of medicine so that patients are satisfied with the treatment they receive. However, patients’ satisfaction following breast cancer treatment has not been sufficiently studied. Hence, we investigated the factors influencing patient satisfaction following breast cancer treatment among Japanese women. These women underwent either breast-conserving surgery (BCS) (n = 380) or total mastectomy (TM) (n = 247). In March 2016, we conducted a cross-sectional internet survey of Japanese women with breast cancer in Japan. We assessed the following factors: socioeconomic status, cancer-related information, the role of medical decision-making, the degree of satisfaction regarding the treatments received, and the regret arising from the medical decision-making processes. We performed logistic regression analyses with the following dependent variables: extreme satisfaction with the treatments received, and regret regarding the medical decision-making process. For both types of surgery, the odds ratio (OR) of being extremely satisfied with the cancer treatment was significantly higher among patients who did not have any regrets compared to patients who had. Also, the OR tended to be higher among patients who chose to play a wanted role in the medical decision-making process, compared with patients who did not. In the BCS group, the OR of being extremely satisfied with the treatment was higher if, at diagnosis, the patient’s youngest child was older than 19 years, compared with patients with no children. The OR was also higher if patient considered the stage and characteristics of their cancer significant. The OR of being extremely satisfied with the treatments was lower among patients who were not employed on full-time basis, and among patients who considered the second medical opinions and medical expenses to be significant. These associations were not observed in the TM group. The OR of having regrets regarding the medical decision-making process was higher among patients who chose to play a role in the decision-making process as they preferred, and was also higher in patients who were employed on either a part-time or contractual basis. For both types of surgery, the OR was higher among patients who considered a second medical opinion to be significant. Regardless of surgical type, regret regarding the medical decision-making process decreases treatment satisfaction. Patients who received breast-conserving surgery were more likely to have regrets concerning the medical decision-making process if they could not play a role in the process as they preferred. In addition, factors associated with the satisfaction with treatment in BCS group but not TM group included the second medical opinion, medical expenses, employment status, and age of the youngest child at diagnosis.

Keywords: medical decision making, breast-conserving surgery, total mastectomy, Japanese

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Authors: Placide Poba-Nzaou, Anicet Tchibozo, Malatsi Galani, Ali Etkkali, Erwin Halim

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Artificial intelligence (AI) is a general-purpose technology that is transforming many industries, working life and society by stimulating economic growth and innovation. Despite the huge potential of benefits to be generated, the adoption of AI varies from one organization to another, from one region to another, and from one industry to another, due in part to obstacles that can inhibit an organization or organizations located in a specific geographic region or operating in a specific industry from adopting AI technology. In this context, these obstacles and their implications for AI adoption from the perspective of configurational theory is important for at least three reasons: (1) understanding these obstacles is the first step in enabling policymakers and providers to make an informed decision in stimulating AI adoption (2) most studies have investigating obstacles or challenges of AI adoption in isolation with linear assumptions while configurational theory offers a holistic and multifaceted way of investigating the intricate interactions between perceived obstacles and barriers helping to assess their synergetic combination while holding assumptions of non-linearity leading to insights that would otherwise be out of the scope of studies investigating these obstacles in isolation. This study aims to pursue two objectives: (1) characterize organizations by uncovering the typical profiles of combinations of 15 internal and external obstacles that may prevent organizations from adopting AI technology, (2) assess the variation in terms of intensity of AI adoption associated with each configuration. We used data from a survey of AI adoption by organizations conducted throughout the EU27, Norway, Iceland and the UK (N=7549). Cluster analysis and discriminant analysis help uncover configurations of organizations based on the 15 obstacles, including eight external and seven internal. Second, we compared the clusters according to AI adoption intensity using an analysis of variance (ANOVA) and a Tamhane T2 post hoc test. The study uncovers three strongly separated clusters of organizations based on perceived obstacles to AI adoption. The clusters are labeled according to their magnitude of perceived obstacles to AI adoption: (1) Cluster I – High Level of perceived obstacles (N = 2449, 32.4%)(2) Cluster II – Low Level of perceived obstacles (N =1879, 24.9%) (3) Cluster III – Moderate Level of perceived obstacles (N =3221, 42.7%). The proposed taxonomy goes beyond the normative understanding of perceived obstacles to AI adoption and associated implications: it provides a well-structured and parsimonious lens that is useful for policymakers, AI technology providers, and researchers. Surprisingly, the ANOVAs revealed a “high level of perceived obstacles” cluster associated with a significantly high intensity of AI adoption.

Keywords: Artificial intelligence (AI), obstacles, adoption, taxonomy.

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Authors: Arlene López-Sampson, Tony Page, Betsy Jackes

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Aquilaria genus produces a highly valuable fragrant oleoresin known as agarwood. Agarwood forms in a few trees in the wild as a response to injure or pathogen attack. The resin is used in perfume and incense industry and medicine. Cultivation of Aquilaria species as a sustainable source of the resin is now a common strategy. Physiological traits are frequently used as a proxy of crop and tree productivity. Aquilaria species growing in Queensland, Australia were studied to investigate relationship between leaf-productivity traits with tree growth. Specifically, 28 trees, representing 12 plus trees and 16 trees from yield plots, were selected to conduct carbon isotope analysis (δ13C) and monitor six leaf attributes. Trees were grouped on four diametric classes (diameter at 150 mm above ground level) ensuring the variability in growth of the whole population was sampled. Model averaging technique based on the Akaike’s information criterion (AIC) was computed to identify whether leaf traits could assist in diameter prediction. Carbon isotope values were correlated with height classes and leaf traits to determine any relationship. In average four leaves per shoot were recorded. Approximately one new leaf per week is produced by a shoot. Rate of leaf expansion was estimated in 1.45 mm day-1. There were no statistical differences between diametric classes and leaf expansion rate and number of new leaves per week (p > 0.05). Range of δ13C values in leaves of Aquilaria species was from -25.5 ‰ to -31 ‰ with an average of -28.4 ‰ (± 1.5 ‰). Only 39% of the variability in height can be explained by δ13C in leaf. Leaf δ13C and nitrogen content values were positively correlated. This relationship implies that leaves with higher photosynthetic capacities also had lower intercellular carbon dioxide concentrations (ci/ca) and less depleted values of 13C. Most of the predictor variables have a weak correlation with diameter (D). However, analysis of the 95% confidence of best-ranked regression models indicated that the predictors that could likely explain growth in Aquilaria species are petiole length (PeLen), values of δ13C (true13C) and δ15N (true15N), leaf area (LA), specific leaf area (SLA) and number of new leaf produced per week (NL.week). The model constructed with PeLen, true13C, true15N, LA, SLA and NL.week could explain 45% (R2 0.4573) of the variability in D. The leaf traits studied gave a better understanding of the leaf attributes that could assist in the selection of high-productivity trees in Aquilaria.

Keywords: 13C, petiole length, specific leaf area, tree growth

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Authors: Sonia Tamanna, Akramul Hassan, Mohammad Shakil Mahmood, Farzana Ansari, Gowhar Rashid, Mir Fahim Faisal, M. Zakir Hossain Howlader

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Background: Preeclampsia (PE), a pregnancy-specific hypertensive disorder, significantly impacts maternal and fetal health. It is particularly prevalent in underdeveloped countries and is linked to preterm delivery and fetal growth. The renin-angiotensin system (RAS) plays a crucial role in ensuring a successful pregnancy outcome, with Angiotensin-Converting Enzyme 2 (ACE2) being a key component. ACE2 converts ANG II to Ang-(1-7), offering protection against ANG II-induced stress and inflammation while regulating blood pressure and osmotic balance during pregnancy. The reduced maternal plasma angiotensin-converting enzyme 2 (ACE2) seen in preeclampsia might contribute to its pathogenesis. However, there has been a dearth of comprehensive research into the association between ACE2 gene polymorphism and preeclampsia. In the South Asian population, hypertension is strongly linked to two SNPs: rs2285666 and rs879922. This genotype was therefore considered, and the possible association of maternal and fetal ACE2 gene polymorphism with preeclampsia within the Bangladeshi population was evaluated. Method: DNA was extracted from peripheral white blood cells (WBCs) using the organic method, and SNP genotyping was done via PCR-RFLP. Odds ratios (OR) with 95% confidence intervals (95% CI) were calculated using logistic regression to determine relative risk. Result: A comprehensive case-control study was conducted on 51 PE patients and their infants, along with 56 control subjects and their infants. Maternal single nuvleotide polymorphisms (SNP) (rs2285666) analysis revealed a strong association between the TT genotype and preeclampsia, with a four-fold increased risk in mothers (P=0.024, OR=4.00, 95% CI=1.36-11.37) compared to their ancestral genotype CC. However, the CT genotype (rs2285666) showed no significant difference (P=0.46, OR=1.54, 95% CI=0.57-4.14). Notably, no significant correlation was found in infants, regardless of their gender. For rs879922, no significant association was observed in both mothers and infants. This pioneering study suggests that mothers carrying the ACE2 gene variant rs2285666 (TT allele) may be at higher risk for preeclampsia, potentially influencing hypertension characteristics, whereas rs879922 does not appear to be associated with developing preeclampsia. Conclusion: This study sheds light on the role of ACE2 gene polymorphism, particularly the rs2285666 TT allele, in maternal susceptibility to preeclampsia. However, rs879922 does not appear to be linked to the risk of PE. This research contributes to our understanding of the genetic underpinnings of preeclampsia, offering insights into potential avenues for prevention and management.

Keywords: ACE2, PCR-RFLP, preeclampsia, single nuvleotide polymorphisms (SNPs)

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Authors: Irene Kretchy, Frances Owusu-Daaku, Samuel Danquah

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Hypertension is the leading risk factor for cardiovascular diseases, and a major cause of death and disability worldwide. This study examined whether psychosocial variables influenced patients’ perception and experience of side effects of their medicines, how they coped with these experiences and the impact on mental health and medication adherence to conventional hypertension therapies. Methods: A hospital-based mixed methods study, using quantitative and qualitative approaches was conducted on hypertensive patients. Participants were asked about side effects, medication adherence, common psychological symptoms, and coping mechanisms with the aid of standard questionnaires. Information from the quantitative phase was analyzed with the Statistical Package for Social Sciences (SPSS) version 20. The interviews from the qualitative study were audio-taped with a digital audio recorder, manually transcribed and analyzed using thematic content analysis. The themes originated from participant interviews a posteriori. Results: The experiences of side effects – such as palpitations, frequent urination, recurrent bouts of hunger, erectile dysfunction, dizziness, cough, physical exhaustion - were categorized as no/low (39.75%), moderate (53.0%) and high (7.25%). Significant relationships between depression (x 2 = 24.21, P < 0.0001), anxiety (x 2 = 42.33, P < 0.0001), stress (x 2 = 39.73, P < 0.0001) and side effects were observed. A logistic regression model using the adjusted results for this association are reported – depression [OR = 1.9 (1.03 – 3.57), p = 0.04], anxiety [OR = 1.5 (1.22 – 1.77), p = < 0.001], and stress [OR = 1.3 (1.02 – 1.71), p = 0.04]. Side effects significantly increased the probability of individuals to be non-adherent [OR = 4.84 (95% CI 1.07 – 1.85), p = 0.04] with social factors, media influences and attitudes of primary caregivers further explaining this relationship. The personal adoption of medication modifying strategies, espousing the use of complementary and alternative treatments, and interventions made by clinicians were the main forms of coping with side effects. Conclusions: Results from this study show that contrary to a biomedical approach, the experience of side effects has biological, social and psychological interrelations. The result offers more support for the need for a multi-disciplinary approach to healthcare where all forms of expertise are incorporated into health provision and patient care. Additionally, medication side effects should be considered as a possible cause of non-adherence among hypertensive patients, thus addressing this problem from a Biopsychosocial perspective in any intervention may improve adherence and invariably control blood pressure.

Keywords: biopsychosocial, hypertension, medication adherence, psychological disorders

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Authors: Breno Barrreto Silva, Agnieszka Otwinowska, Katarzyna Kutylowska

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Research comparing lexical learning following the writing of sentences and longer texts with keywords is limited and contradictory. One possibility is that the recursivity of writing may enhance processing and increase lexical learning; another possibility is that the higher cognitive load of complex-text writing (e.g., essays), at least when timed, may hinder the learning of words. In our study, we selected 2 sets of 10 academic keywords matched for part of speech, length (number of characters), frequency (SUBTLEXus), and concreteness, and we asked 90 L1-Polish advanced-level English majors to use the keywords when writing sentences, timed (60 minutes) or untimed essays. First, all participants wrote a timed Control essay (60 minutes) without keywords. Then different groups produced Timed essays (60 minutes; n=33), Untimed essays (n=24), or Sentences (n=33) using the two sets of glossed keywords (counterbalanced). The comparability of the participants in the three groups was ensured by matching them for proficiency in English (LexTALE), and for few measures derived from the control essay: VocD (assessing productive lexical diversity), normed errors (assessing productive accuracy), words per minute (assessing productive written fluency), and holistic scores (assessing overall quality of production). We measured lexical learning (depth and breadth) via an adapted Vocabulary Knowledge Scale (VKS) and a free association test. Cognitive load was measured in the three essays (Control, Timed, Untimed) using normed number of errors and holistic scores (TOEFL criteria). The number of errors and essay scores were obtained from two raters (interrater reliability Pearson’s r=.78-91). Generalized linear mixed models showed no difference in the breadth and depth of keyword knowledge after writing Sentences, Timed essays, and Untimed essays. The task-based measurements found that Control and Timed essays had similar holistic scores, but that Untimed essay had better quality than Timed essay. Also, Untimed essay was the most accurate, and Timed essay the most error prone. Concluding, using keywords in Timed, but not Untimed, essays increased cognitive load, leading to more errors and lower quality. Still, writing sentences and essays yielded similar lexical learning, and differences in the cognitive load between Timed and Untimed essays did not affect lexical acquisition.

Keywords: learning academic words, writing essays, cognitive load, english as an L2

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Authors: Sukhvinder Kaur, Ashok Agarwal

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Background: For the first time in 2009, India was able to generate estimates of HIV incidence (the number of new HIV infections per year). Analysis of epidemic projections helped in revealing that the number of new annual HIV infections in India had declined by more than 50% during the last decade (GOI Ministry of Health and Family Welfare, 2010). Then, National AIDS Control Organisation (NACO) planned to scale up its efforts in generating projections through epidemiological analysis and modelling by taking recent available sources of evidence such as HIV Sentinel Surveillance (HSS), India Census data and other critical data sets. Recently, NACO generated current round of HIV estimates-2012 through globally recommended tool “Spectrum Software” and came out with the estimates for adult HIV prevalence, annual new infections, number of people living with HIV, AIDS-related deaths and treatment needs. State level prevalence and incidence projections produced were used to project consequences of the epidemic in spectrum. In presence of HIV estimates generated at state level in India by NACO, USIAD funded PIPPSE project under the leadership of NACO undertook the estimations and projections to district level using same Spectrum software. In 2011, adult HIV prevalence in one of the high prevalent States, Maharashtra was 0.42% ahead of the national average of 0.27%. Considering the heterogeneity of HIV epidemic between districts, two districts of Maharashtra – Thane and Mumbai were selected to estimate and project the number of People-Living-with-HIV/AIDS (PLHIV), HIV-prevalence among adults and annual new HIV infections till 2017. Methodology: Inputs in spectrum included demographic data from Census of India since 1980 and sample registration system, programmatic data on ‘Alive and on ART (adult and children)’,‘Mother-Baby pairs under PPTCT’ and ‘High Risk Group (HRG)-size mapping estimates’, surveillance data from various rounds of HSS, National Family Health Survey–III, Integrated Biological and Behavioural Assessment and Behavioural Sentinel Surveillance. Major Findings: Assuming current programmatic interventions in these districts, an estimated decrease of 12% points in Thane and 31% points in Mumbai among new infections in HRGs and migrants is observed from 2011 by 2017. Conclusions: Project also validated decrease in HIV new infection among one of the high risk groups-FSWs using program cohort data since 2012 to 2016. Though there is a decrease in HIV prevalence and new infections in Thane and Mumbai, further decrease is possible if appropriate programme response, strategies and interventions are envisaged for specific target groups based on this evidence. Moreover, evidence need to be validated by other estimation/modelling techniques; and evidence can be generated for other districts of the state, where HIV prevalence is high and reliable data sources are available, to understand the epidemic within the local context.

Keywords: HIV sentinel surveillance, high risk groups, projections, new infections

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Authors: Loreta Kaklauskiene, Arturas Kaklauskas

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The Integrated Human Resources and Work Environment Management (HOWE) System optimises employee productivity, improves the work environment, and, at the same time, meets the employer’s strategic goals. The HOWE system has been designed to ensure an organisation can successfully compete in the global market, thanks to the high performance of its employees. The HOWE system focuses on raising workforce productivity and improving work conditions to boost employee performance and motivation. The methods used in our research are linear correlation, INVAR multiple criteria analysis, digital twin, and affective computing. The HOWE system is based on two patents issued in Lithuania (LT 6866, LT 6841) and one European Patent application (No: EP 4 020 134 A1). Our research analyses ways to make human resource management more efficient and boost labour productivity by improving and adapting a personalised work environment. The efficiency of human capital and labour productivity can be increased by applying personalised workplace improvement systems that can optimise lighting colours and intensity, scents, data, information, knowledge, activities, media, games, videos, music, air pollution, humidity, temperature, vibrations, and other workplace aspects. HOWE generates and maintains a personalised workspace for an employee, taking into account the person’s affective, physiological and emotional (APSE) states. The purpose of this project was to create a HOWE for the customisation of quality control in smart workspaces taking into account the user’s APSE states in an integrated manner as a single unit. This customised management of quality control covers the levels of lighting and colour intensities, scents, media, information, activities, learning materials, games, music, videos, temperature, energy efficiency, the carbon footprint of a workspace, humidity, air pollution, vibrations and other aspects of smart spaces. The system is based on Digital Twins technology, seen as a logical extension of BIM.

Keywords: human resource management, health economics, work environment, organizational behaviour and employee productivity, prosperity in work, smart system

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Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

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Authors: Beatriz Garcia-Juan, Ana B. Escrig-Tena, Vicente Roca-Puig

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The aim of this article is to conduct a theoretical and empirical study in order to examine how the goal orientation (GO) of public employees affects the relationship between the structural and psychological empowerment that they experience at their workplaces. In doing so, we follow structural empowerment (SE) and psychological empowerment (PE) conceptualizations, and relate them to the public administration framework. Moreover, we review arguments from GO theories, and previous related contributions. Empowerment has emerged as an important issue in the public sector organization setting in the wake of mainstream New Public Management (NPM), the new orientation in the public sector that aims to provide a better service for citizens. It is closely linked to the drive to improve organizational effectiveness through the wise use of human resources. Nevertheless, it is necessary to combine structural (managerial) and psychological (individual) approaches in an integrative study of empowerment. SE refers to a set of initiatives that aim the transference of power from managerial positions to the rest of employees. PE is defined as psychological state of competence, self-determination, impact, and meaning that an employee feels at work. Linking these two perspectives will lead to arrive at a broader understanding of the empowerment process. Specifically in the public sector, empirical contributions on this relationship are therefore important, particularly as empowerment is a very useful tool with which to face the challenges of the new public context. There is also a need to examine the moderating variables involved in this relationship, as well as to extend research on work motivation in public management. It is proposed the study of the effect of individual orientations, such as GO. GO concept refers to the individual disposition toward developing or confirming one’s capacity in achievement situations. Employees’ GO may be a key factor at work and in workforce selection processes, since it explains the differences in personal work interests, and in receptiveness to and interpretations of professional development activities. SE practices could affect PE feelings in different ways, depending on employees’ GO, since they perceive and respond differently to such practices, which is likely to yield distinct PE results. The model is tested on a sample of 521 Spanish local authority employees. Hierarchical regression analysis was conducted to test the research hypotheses using SPSS 22 computer software. The results do not confirm the direct link between SE and PE, but show that learning goal orientation has considerable moderating power in this relationship, and its interaction with SE affects employees’ PE levels. Therefore, the combination of SE practices and employees’ high levels of LGO are important factors for creating psychologically empowered staff in public organizations.

Keywords: goal orientation, moderating effect, psychological empowerment, structural empowerment

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Authors: Dial Tassadit Rania, Figueiredo De Oliveira Gabriel

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In this paper, we investigate the relationship between ports and their hinterland and foreland environments and the competitive relationship between the ports themselves. These two environments are changing, evolving and introducing new challenges for commercial and economic development at the regional, national and international levels. Because of the rise of the containerization phenomenon, shipping costs and port handling costs have considerably decreased due to economies of scale. The volume of maritime trade has increased substantially and the markets served by the ports have expanded. On these bases, overlapping hinterlands can give rise to the phenomenon of competition between ports. Our main contribution comparing to the existing literature on this issue, is to build a set of hinterland, foreland and competition indicators. Using these indicators? we investigate the effect of hinterland accessibility, foreland connectivity and inter-ports competition on containerized traffic of Europeans ports. For this, we have a 10-year panel database from 2004 to 2014. Our hinterland indicators are given by two indicators of accessibility; they describe the market potential of a port and are calculated using information on population and wealth (GDP). We then calculate population and wealth for different neighborhoods within a distance from a port ranging from 100 to 1000km. For the foreland, we produce two indicators: port connectivity and number of partners for each port. Finally, we compute the two indicators of inter-port competition and a market concentration indicator (Hirshmann-Herfindhal) for different neighborhood-distances around the port. We then apply a fixed-effect model to test the relationship above. Again, with a fixed effects model, we do a sensitivity analysis for each of these indicators to support the results obtained. The econometric results of the general model given by the regression of the accessibility indicators, the LSCI for port i, and the inter-port competition indicator on the containerized traffic of European ports show a positive and significant effect for accessibility to wealth and not to the population. The results are positive and significant for the two indicators of connectivity and competition as well. One of the main results of this research is that the port development given here by the increase of its containerized traffic is strongly related to the development of its hinterland and foreland environment. In addition, it is the market potential, given by the wealth of the hinterland that has an impact on the containerized traffic of a port. However, accessibility to a large population pool is not important for understanding the dynamics of containerized port traffic. Furthermore, in order to continue to develop, a port must penetrate its hinterland at a deep level exceeding 100 km around the port and seek markets beyond this perimeter. The port authorities could focus their marketing efforts on the immediate hinterland, which can, as the results shows, not be captive and thus engage new approaches of port governance to make it more attractive.

Keywords: accessibility, connectivity, European containerization, European hinterland and foreland, inter-port competition

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Authors: Priyanka Mazumdar, Ananya Mukhopadhyay

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A lot of progress has been achieved in the research of turbidites during the last decades. However, their relationship to delta systems still deserves further attention. This paper addresses example of fine grained turbidite from a pro-deltaic deposit of a Proterozoic mixed energy delta system exposed along Chaossa-Baliana river section of the Chaossa Formation of the Simla Basin. Lithostratigraphic analysis of the Chaossa Formation reveals three major facies associations (prodelta deposit-FA1, delta slope deposit-FA2 and delta front deposit-FA3) based on lithofacies types, petrography and sedimentary structures. Detailed process-based facies and paleoenvironmental analysis of the study area have led to identification of more than150 m thick coarsening-upwards deltaic successions composed of fine grained turbidites overlain by delta slope deposits. Erosional features are locally common at the base of turbidite beds and still more widespread at the top. The complete sequence has eight sub-divisions that are here termed T1 to T8. The basal subdivision (T1) comprises a massive graded unit with a sharp, scoured base, internal parallel-lamination and cross-lamination. The overlying sequence shows textural and compositional grading through alternating silt and mud laminae (T2). T2 is overlying by T3 which is characterized by climbing ripple and cross lamination. Parallel laminae are the predominant facies attributes of T4 which caps the T3 unit. T5 has a loaded scour base and is mainly characterized laminated silt. The topmost three divisions, graded mud (T6), ungraded mud (T7) and laminated mud (T8). The proposed sequence is analogous to the Bouma (1962) structural scheme for sandy turbidites. Repetition of partial sequences represents deposition from different stages of evolution of a large, muddy, turbidity flow. Detailed facies analysis of the study area reveals that the sediments of the turbidites developed during normal regression at the stage of stable or marginally rising sea level. Thin-bedded turbidites were deposited predominantly by turbidity currents in the relatively shallower part of the Simla basin. The fine-grained turbidites are developed by resedimentation of delta-front sands and slumping of upper pro-delta muds.

Keywords: turbidites, prodelta, proterozoic, Simla Basin, Bouma sequence

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Authors: Keith T. S. Tung, Frederick K. Ho, Rosa S. Wong, Camilla K. M. Lo, Wilfred H. S. Wong, C. B. Chow, Patrick Ip

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Objectives: Underage drinking is an important public health problem both locally and globally. Conventional prevention/intervention relies on unidirectional knowledge transfer such as mail leaflets or health talks which showed mixed results in changing the target behaviour. Previously, we conducted a school internet-based intervention which was found to be effective in reducing alcohol use among adolescents, yet the underlying mechanisms have not been properly investigated. This study, therefore, examined the mechanisms that explain how the intervention produced a change in alcohol drinking behaviours among Chinese adolescent as observed in our previous clustered randomised controlled trial (RCT) study. Methods: This is a cluster randomised controlled trial with parallel group design. Participating schools were randomised to the Internet intervention or the conventional health education group (control) with a 1:1 allocation ratio. Secondary 1–3 students of the participating schools were enrolled in this study. The Internet intervention was a web-based quiz game competition, in which participating students would answer 1,000 alcohol-related multiple-choice quiz questions. Conventional health education group received a promotional package on equivalent alcohol-related knowledge. The participants’ alcohol-related attitude, knowledge, and perceived behavioural control were self-reported before the intervention (baseline) and one month and three months after the intervention. Results: Our RCT results showed that participants in the Internet group were less likely to drink (risk ratio [RR] 0.79, p < 0.01) as well as in lesser amount (β -0.06, p < 0.05) compared to those in the control group at both post-intervention follow-ups. Within the intervention group, regression analyses showed that high quiz scorer had greater improvement in alcohol-related knowledge (β 0.28, p < 0.01) and attitude (β -0.26, p < 0.01) at 1 month after intervention, which in turn increased their perceived behavioural control against alcohol use (β 0.10 and -0.26, both p < 0.01). Attitude, compared to knowledge, was found to be a stronger contributor to the intervention effect on perceived behavioural control. Conclusions: Our internet-based intervention has demonstrated effectiveness in reducing the risk of underage drinking when compared with conventional health education. Our study results further showed an attitude to be a more important factor than knowledge in changing health-related behaviour. This has an important implication for future prevention/intervention on an underage drinking problem.

Keywords: adolescents, internet-based intervention, randomized controlled trial, underage drinking

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Authors: Raja Umer Sajjad, Chang Hee Lee

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Stormwater runoff is the leading contributor to pollution of receiving waters. In response, an efficient stormwater monitoring program is required to quantify and eventually reduce stormwater pollution. The overall goals of stormwater monitoring programs primarily include the identification of high-risk dischargers and the development of total maximum daily loads (TMDLs). The challenge in developing better monitoring program is to reduce the variability in flux estimates due to sampling errors; however, the success of monitoring program mainly depends on the accuracy of the estimates. Apart from sampling errors, manpower and budgetary constraints also influence the quality of the estimates. This study attempted to develop optimum stormwater monitoring design considering both cost and the quality of the estimated pollutants flux. Three years stormwater monitoring data (2012 – 2014) from a mix land use located within Geumhak watershed South Korea was evaluated. The regional climate is humid and precipitation is usually well distributed through the year. The investigation of a large number of water quality parameters is time-consuming and resource intensive. In order to identify a suite of easy-to-measure parameters to act as a surrogate, Principal Component Analysis (PCA) was applied. Means, standard deviations, coefficient of variation (CV) and other simple statistics were performed using multivariate statistical analysis software SPSS 22.0. The implication of sampling time on monitoring results, number of samples required during the storm event and impact of seasonal first flush were also identified. Based on the observations derived from the PCA biplot and the correlation matrix, total suspended solids (TSS) was identified as a potential surrogate for turbidity, total phosphorus and for heavy metals like lead, chromium, and copper whereas, Chemical Oxygen Demand (COD) was identified as surrogate for organic matter. The CV among different monitored water quality parameters were found higher (ranged from 3.8 to 15.5). It suggests that use of grab sampling design to estimate the mass emission rates in the study area can lead to errors due to large variability. TSS discharge load calculation error was found only 2 % with two different sample size approaches; i.e. 17 samples per storm event and equally distributed 6 samples per storm event. Both seasonal first flush and event first flush phenomena for most water quality parameters were observed in the study area. Samples taken at the initial stage of storm event generally overestimate the mass emissions; however, it was found that collecting a grab sample after initial hour of storm event more closely approximates the mean concentration of the event. It was concluded that site and regional climate specific interventions can be made to optimize the stormwater monitoring program in order to make it more effective and economical.

Keywords: first flush, pollutant load, stormwater monitoring, surrogate parameters

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Authors: Xiaobo Rui, Zhoumo Zeng, Yibo Li

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A novel tri-cantilever energy harvester with magnetic oscillator was presented, which could convert the ambient vibration into electrical energy to power the low-power devices such as wireless sensor networks. The most common way to harvest vibration energy is based on the use of linear resonant devices such as cantilever beam, since this structure creates the highest strain for a given force. The highest efficiency will be achieved when the resonance frequency of the harvester matches the vibration frequency. The limitation of the structure is the narrow effective bandwidth. To overcome this limitation, this article introduces a broadband tri-cantilever harvester with nonlinear stiffness. This energy harvester typically consists of three thin cantilever beams vertically arranged with Neodymium Magnets ( NdFeB)magnetics at its free end and a fixed base at the other end. The three cantilevers have different resonant frequencies by designed in different thicknesses. It is obviously that a similar advantage of multiple resonant frequencies as piezoelectric cantilevers array structure is built. To achieve broadband energy harvesting, magnetic interaction is used to introduce the nonlinear system stiffness to tune the resonant frequency to match the excitation. Since the three cantilever tips are all free and the magnetic force is distance dependent, the resonant frequencies will be complexly changed with the vertical vibration of the free end. Both model and experiment are built. The electromechanically coupled lumped-parameter model is presented. An electromechanical formulation and analytical expressions for the coupled nonlinear vibration response and voltage response are given. The entire structure is fabricated and mechanically attached to a electromagnetic shaker as a vibrating body via the fixed base, in order to couple the vibrations to the cantilever. The cantilevers are bonded with piezoelectric macro-fiber composite (MFC) materials (Model: M8514P2). The size of the cantilevers is 120*20mm2 and the thicknesses are separately 1mm, 0.8mm, 0.6mm. The prototype generator has a measured performance of 160.98 mW effective electrical power and 7.93 DC output voltage via the excitation level of 10m/s2. The 130% increase in the operating bandwidth is achieved. This device is promising to support low-power devices, peer-to-peer wireless nodes, and small-scale wireless sensor networks in ambient vibration environment.

Keywords: tri-cantilever, ambient vibration, energy harvesting, magnetic oscillator

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Authors: N. F. Mikhailova, M. E. Fattakhova, M. A. Mironova, E. V. Vyacheslavova

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For the mental and social adaptation of the deaf and hard-of-hearing people, cultural and social aspects - the formation of identity (acculturation) and educational conditions – are highly significant. We studied 137 deaf and hard-of-hearing students in different educational situations. We used these methods: Big Five (Costa & McCrae, 1997), TRF (Becker, 1989), WCQ (Lazarus & Folkman, 1988), self-esteem, and coping strategies (Jambor & Elliott, 2005), self-stigma scale (Mikhailov, 2008). Type of self-identification of students depended on the degree of deafness, type of education, method of communication in the family: large hearing loss, education in schools for deaf, and gesture communication increased the likelihood of a 'deaf' acculturation. Less hearing loss, inclusive education in public school or school for the hearing-impaired, mixed communication in the family contributed to the formation of 'hearing' acculturation. The choice of specific coping depended on the degree of deafness: a large hearing loss increased coping 'withdrawal into the deaf world' and decreased 'bicultural skills' coping. People with mild hearing loss tended to cover-up it. In the context of ongoing discussion, we researched personality characteristics in deaf and hard on-hearing students, coping and other deafness associated factors depending on their acculturation type. Students who identified themselves with the 'hearing world' had a high self-esteem, a higher level of extraversion, self-awareness, personal resources, willingness to cooperate, better psychological health, emotional stability, higher ability to empathy, a greater satiety of life with feelings and sense and high sense of self-worth. They also actively used strategies, problem-solving, acceptance of responsibility, positive revaluation. Student who limited themselves within the culture of deaf people had more severe hearing loss and accordingly had more communication barriers. Lack of use or seldom use of coping strategies by these students point at decreased level of stress in their life. Their self-esteem have not been challenged in the specific social environment of the students with the same severity of defect, and thus this environment provided sense of comfort (we can assume that from the high scores on psychological health, personality resources, and emotional stability). Students with bicultural acculturation had higher level of psychological resources - they used Positive Reappraisal coping more often and had a higher level of psychological health. Lack of belonging to certain culture (marginality) leads to personality disintegration, social and psychological disadaptation: deaf and hard-of-hearing students with marginal identification had a lower self-estimation level, worse psychological health and personal resources, lower level of extroversion, self-confidence and life satisfaction. They, in fact, become 'risk group' (many of them dropped out of universities, divorced, and one even ended up in the ranks of ISIS). All these data argue the importance of cultural 'anchor' for people with hearing deprivation. Supported by the RFBR No 19-013-00406.

Keywords: acculturation, coping, deafness, marginality

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Authors: A.H.Y. Lai, C. Teyra

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In Taiwan, there are 16 official indigenous groups, accounting for 2.3% of the total population. Like other indigenous populations worldwide, indigenous peoples in Taiwan have poorer mental health because of their history of oppression and colonisation. Amid the negative narratives, the ethnic identity of cultural minorities is their unique psychological and cultural asset. Moreover, positive socialisation is found to be related to strong ethnic identity. Based on Phinney’s theory on ethnic identity development and social support theory, this study adopted a strength-based approach conceptualising ethnic identity as the central organising principle that linked perceived social support and mental health among indigenous adults in Taiwan. Aims. Overall aim is to examine the effect of ethnic identity and social support on mental health. Specific aims were to examine : (1) the association between ethnic identity and mental health; (2) the association between perceived social support and mental health ; (3) the indirect effect of ethnic identity linking perceived social support and mental health. Methods. Participants were indigenous adults in Taiwan (n=200; mean age=29.51; Female=31%, Male=61%, Others=8%). A cross-sectional quantitative design was implemented using data collected in the year 2020. Respondent-driven sampling was used. Standardised measurements were: Ethnic Identity Scale(6-item); Social Support Questionnaire-SF(6 items); Patient Health Questionnaire(9-item); and Generalised Anxiety Disorder(7-item). Covariates were age, gender and economic satisfaction. A four-stage structural equation modelling (SEM) with robust maximin likelihood estimation was employed using Mplus8.0. Step 1: A measurement model was built and tested using confirmatory factor analysis (CFA). Step 2: Factor covariates were re-specified as direct effects in the SEM. Covariates were added. The direct effects of (1) ethnic identity and social support on depression and anxiety and (2) social support on ethnic identity were tested. The indirect effect of ethnic identity was examined with the bootstrapping technique. Results. The CFA model showed satisfactory fit statistics: x^2(df)=869.69(608), p<.05; Comparative ft index (CFI)/ Tucker-Lewis fit index (TLI)=0.95/0.94; root mean square error of approximation (RMSEA)=0.05; Standardized Root Mean Squared Residual (SRMR)=0.05. Ethnic identity is represented by two latent factors: ethnic identity-commitment and ethnic identity-exploration. Depression, anxiety and social support are single-factor latent variables. For the SEM, model fit statistics were: x^2(df)=779.26(527), p<.05; CFI/TLI=0.94/0.93; RMSEA=0.05; SRMR=0.05. Ethnic identity-commitment (b=-0.30) and social support (b=-0.33) had direct negative effects on depression, but ethnic identity-exploration did not. Ethnic identity-commitment (b=-0.43) and social support (b=-0.31) had direct negative effects on anxiety, while identity-exploration (b=0.24) demonstrated a positive effect. Social support had direct positive effects on ethnic identity-exploration (b=0.26) and ethnic identity-commitment (b=0.31). Mediation analysis demonstrated the indirect effect of ethnic identity-commitment linking social support and depression (b=0.22). Implications: Results underscore the role of social support in preventing depression via ethnic identity commitment among indigenous adults in Taiwan. Adopting the strength-based approach, mental health practitioners can mobilise indigenous peoples’ commitment to their group to promote their well-being.

Keywords: ethnic identity, indigenous population, mental health, perceived social support

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Authors: Marlin Mubarak

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Background: Endometriosis is a complex disabling disease affecting young females in the reproductive period mainly. The aim of this project is to generate a diagnostic model to predict severity and stage of endometriosis prior to Laparoscopic surgery. This will help to improve the pre-operative diagnostic accuracy of stage 3 & 4 endometriosis and as a result, refer relevant women to a specialist centre for complex Laparoscopic surgery. The model is based on the British Society of Gynaecological Endoscopy (BSGE) pain questionnaire, clinical examination and ultrasound scan. Design: This is a prospective, observational, study, in which women completed the BSGE pain questionnaire, a BSGE requirement. Also, as part of the routine preoperative assessment patient had a routine ultrasound scan and when recto-vaginal and deep infiltrating endometriosis was suspected an MRI was performed. Setting: Luton & Dunstable University Hospital. Patients: Symptomatic women (n = 56) scheduled for laparoscopy due to pelvic pain. The age ranged between 17 – 52 years of age (mean 33.8 years, SD 8.7 years). Interventions: None outside the recognised and established endometriosis centre protocol set up by BSGE. Main Outcome Measure(s): Sensitivity and specificity of endometriosis diagnosis predicted by symptoms based on BSGE pain questionnaire, clinical examinations and imaging. Findings: The prevalence of diagnosed endometriosis was calculated to be 76.8% and the prevalence of advanced stage was 55.4%. Deep infiltrating endometriosis in various locations was diagnosed in 32/56 women (57.1%) and some had DIE involving several locations. Logistic regression analysis was performed on 36 clinical variables to create a simple clinical prediction model. After creating the scoring system using variables with P < 0.05, the model was applied to the whole dataset. The sensitivity was 83.87% and specificity 96%. The positive likelihood ratio was 20.97 and the negative likelihood ratio was 0.17, indicating that the model has a good predictive value and could be useful in predicting advanced stage endometriosis. Conclusions: This is a hypothesis-generating project with one operator, but future proposed research would provide validation of the model and establish its usefulness in the general setting. Predictive tools based on such model could help organise the appropriate investigation in clinical practice, reduce risks associated with surgery and improve outcome. It could be of value for future research to standardise the assessment of women presenting with pelvic pain. The model needs further testing in a general setting to assess if the initial results are reproducible.

Keywords: deep endometriosis, endometriosis, minimally invasive, MRI, ultrasound.

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Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Chia-Ching Sun, Li-Yin Chien, Chun-Ting Hsiao

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Background: Appropriate gestation weight gain benefits pregnant women and their children; however, excessive weight gain could raise the risk of adverse health outcomes and chronicle diseases. Nevertheless, there is currently limited evidence on the effect of physical activities on pregnant women’s gestational weight gain. Purpose: This study aimed to explore the correlation between the level of physical activity and gestation weight gain during the second and third trimester of pregnancy. Methods: This longitudinal study enrolled 800 healthy pregnant women aged over 20 from six hospitals in northern Taiwan. Structured questionnaires were used to collect data twice for each participant during 14-27 and 28-40 weeks of gestation. Variables included demographic data, maternal health history, and lifestyle. The International Physical Activity Questionnaire-short form was used to measure the level of physical activity from walking and of moderate-intensity and vigorous-intensity before and during pregnancy. Weight recorded at prenatal checkups were used to calculate average weight gain in each trimester of pregnancy. T-tests, ANOVA, chi-squared tests, and multivariable logistic regression models were applied to determine the predicting factors for weight gain during the second and third trimester. Result: Participants who had achieved recommended physical activity level (150 minutes of moderate physical activity or 75 minutes of vigorous physical activity a week) before pregnancy (aOR=1.85, 95% CI=1.27-2.67) or who achieved recommended walking level (150 minutes a week) during the second trimester of pregnancy (aOR=1.43, 95% CI= 1.00-2.04) gained significantly more weight during the second trimester. Compared with those who did not reach recommended level of moderate-intensity physical activity (150 minutes a week), women who had reached that during the second trimester were more likely to be in the less than recommended weight gain group than in the recommended weight gain group (aOR=2.06, CI=1.06-4.00). However, there was no significant correlation between physical activity level and weight gain in the third trimester. Other predicting factors of excessive weight gain included education level which showed a negative correlation (aOR=0.38, CI=0.17-0.88), whereas overweight and obesity before pregnancy showed a positive correlation (OR=3.97, CI=1.23-12.78). Conclusions/implications for practice: Participants who had achieved recommended physical activity level before pregnancy significantly reduced exercise during pregnancy and gained excessive weight during the second trimester. However, women who engaged in the practice of physical activity as recommended could effectively control weight gain in the third trimester. Healthcare professionals could suggest that pregnant women who exercise maintain their pre-pregnancy level of physical activity, given activities requiring physical contact or causing falls are avoided. For those who do not exercise, health professionals should encourage them to gradually increase the level of physical activity. Health promotion strategies related to weight control and physical activity level achievement should be given to women before pregnancy.

Keywords: pregnant woman, physical activity, gestation weight gain, obesity, overweight

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Authors: Gabriela Silva-Maceda, Silvia Romero-Contreras

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Spanish is a more transparent language than English given that it has more direct correspondences between sounds and letters. It has become important to understand how decoding and linguistic comprehension contribute to reading comprehension in the framework of the widely known Simple View Model. This study aimed to identify the level of prediction by these two components in a sample of 1st to 4th grade children attending two schools in central Mexico (one public and one private). Within each school, ten children were randomly selected in each grade level, and their parents were asked about reading habits and socioeconomic information. In total, 79 children completed three standardized tests measuring decoding (pseudo-word reading), linguistic comprehension (understanding of paragraphs) and reading comprehension using subtests from the Clinical Evaluation of Language Fundamentals-Spanish, Fourth Edition, and the Test de Lectura y Escritura en Español (LEE). The data were analyzed using hierarchical regression, with decoding as a first step and linguistic comprehension as a second step. Results showed that decoding accounted for 19.2% of the variance in reading comprehension, while linguistic comprehension accounted for an additional 10%, adding up to 29.2% of variance explained: F (2, 75)= 15.45, p <.001. Socioeconomic status derived from parental questionnaires showed a statistically significant association with the type of school attended, X2 (3, N= 79) = 14.33, p =.002. Nonetheless when analyzing the Simple View components, only decoding differences were statistically significant (t = -6.92, df = 76.81, p < .001, two-tailed); reading comprehension differences were also significant (t = -3.44, df = 76, p = .001, two-tailed). When socioeconomic status was included in the model, it predicted a 5.9% unique variance, even when already accounting for Simple View components, adding to a 35.1% total variance explained. This three-predictor model was also significant: F (3, 72)= 12.99, p <.001. In addition, socioeconomic status was significantly correlated with the amount of non-textbook books parents reported to have at home for both adults (rho = .61, p<.001) and children (rho= .47, p<.001). Results converge with a large body of literature finding socioeconomic differences in reading comprehension; in addition this study suggests that these differences were also present in decoding skills. Although linguistic comprehension differences between schools were expected, it is argued that the test used to collect this variable was not sensitive to linguistic differences, since it came from a test to diagnose clinical language disabilities. Even with this caveat, results show that the components of the Simple View Model can predict less than a third of the variance in reading comprehension in Spanish. However, the results also suggest that a fuller model of reading comprehension is obtained when considering the family’s socioeconomic status, given the potential differences shown by the socioeconomic status association with books at home, factors that are particularly important in countries where inequality gaps are relatively large.

Keywords: decoding, linguistic comprehension, reading comprehension, simple view model, socioeconomic status, Spanish

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Authors: Stephanie Watson, Fabrice Stephenson, Conrad Pilditch, Carolyn Lundquist

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Spatial data detailing both the distribution and density of functionally important marine species are needed to inform management decisions. Species distribution models (SDMs) have proven helpful in this regard; however, models often focus only on species occurrences derived from spatially expansive datasets and lack the resolution and detail required to inform regional management decisions. Boosted regression trees (BRT) were used to produce high-resolution SDMs (250 m) at two spatial scales predicting probability of occurrence, abundance (count per sample unit), density (count per km2) and uncertainty for seven coastal seafloor taxa that vary in habitat usage and distribution to examine prediction differences and implications for coastal management. We investigated if small scale regionally focussed models (82,000 km2) can provide improved predictions compared to data-rich national scale models (4.2 million km2). We explored the variability in predictions across model type (occurrence vs abundance) and model scale to determine if specific taxa models or model types are more robust to geographical variability. National scale occurrence models correlated well with broad-scale environmental predictors, resulting in higher AUC (Area under the receiver operating curve) and deviance explained scores; however, they tended to overpredict in the coastal environment and lacked spatially differentiated detail for some taxa. Regional models had lower overall performance, but for some taxa, spatial predictions were more differentiated at a localised ecological scale. National density models were often spatially refined and highlighted areas of ecological relevance producing more useful outputs than regional-scale models. The utility of a two-scale approach aids the selection of the most optimal combination of models to create a spatially informative density model, as results contrasted for specific taxa between model type and scale. However, it is vital that robust predictions of occurrence and abundance are generated as inputs for the combined density model as areas that do not spatially align between models can be discarded. This study demonstrates the variability in SDM outputs created over different geographical scales and highlights implications and opportunities for managers utilising these tools for regional conservation, particularly in data-limited environments.

Keywords: Benthic ecology, spatial modelling, multi-scalar modelling, marine conservation.

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Authors: Jožef Ritonja, Bojan Grčar, Boštjan Polajžer

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In recent years, electricity trade between neighboring countries has become increasingly intense. Increasing power transmission over long distances has resulted in an increase in the oscillations of the transmitted power. The damping of the oscillations can be carried out with the reconfiguration of the network or the replacement of generators, but such solution is not economically reasonable. The only cost-effective solution to improve the damping of power oscillations is to use power system stabilizers. Power system stabilizer represents a part of synchronous generator control system. It utilizes semiconductor’s excitation system connected to the rotor field excitation winding to increase the damping of the power system. The majority of the synchronous generators are equipped with the conventional power system stabilizers with fixed parameters. The control structure of the conventional power system stabilizers and the tuning procedure are based on the linear control theory. Conventional power system stabilizers are simple to realize, but they show non-sufficient damping improvement in the entire operating conditions. This is the reason that advanced control theories are used for development of better power system stabilizers. In this paper, the adaptive control theory for power system stabilizers design and synthesis is studied. The presented work is focused on the use of model reference adaptive control approach. Control signal, which assures that the controlled plant output will follow the reference model output, is generated by the adaptive algorithm. Adaptive gains are obtained as a combination of the "proportional" term and with the σ-term extended "integral" term. The σ-term is introduced to avoid divergence of the integral gains. The necessary condition for asymptotic tracking is derived by means of hyperstability theory. The benefits of the proposed model reference adaptive power system stabilizer were evaluated as objectively as possible by means of a theoretical analysis, numerical simulations and laboratory realizations. Damping of the synchronous generator oscillations in the entire operating range was investigated. Obtained results show the improved damping in the entire operating area and the increase of the power system stability. The results of the presented work will help by the development of the model reference power system stabilizer which should be able to replace the conventional stabilizers in power systems.

Keywords: power system, stability, oscillations, power system stabilizer, model reference adaptive control

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Authors: Abraham Castellanos, Christophe Durville, Sophie Echenim

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In this article, a portfolio optimization problem is performed in a Solvency II context: it illustrates how advanced optimization techniques can help to tackle complex operational pain points around the monitoring, control, and stability of Solvency Capital Requirement (SCR). The market SCR of a portfolio is calculated as a combination of SCR sub-modules. These sub-modules are the results of stress-tests on interest rate, equity, property, credit and FX factors, as well as concentration on counter-parties. The market SCR is non convex and non differentiable, which does not make it a natural optimization criteria candidate. In the SCR formulation, correlations between sub-modules are fixed, whereas risk-driven portfolio allocation is usually driven by the dynamics of the actual correlations. Implementing a portfolio construction approach that is efficient on both a regulatory and economic standpoint is not straightforward. Moreover, the challenge for insurance portfolio managers is not only to achieve a minimal SCR to reduce non-invested capital but also to ensure stability of the SCR. Some optimizations have already been performed in the literature, simplifying the standard formula into a quadratic function. But to our knowledge, it is the first time that the standard formula of the market SCR is used in an optimization problem. Two solvers are combined: a bundle algorithm for convex non- differentiable problems, and a BFGS (Broyden-Fletcher-Goldfarb- Shanno)-SQP (Sequential Quadratic Programming) algorithm, to cope with non-convex cases. A market SCR minimization is then performed with historical data. This approach results in significant reduction of the capital requirement, compared to a classical Markowitz approach based on the historical volatility. A comparative analysis of different optimization models (equi-risk-contribution portfolio, minimizing volatility portfolio and minimizing value-at-risk portfolio) is performed and the impact of these strategies on risk measures including market SCR and its sub-modules is evaluated. A lack of diversification of market SCR is observed, specially for equities. This was expected since the market SCR strongly penalizes this type of financial instrument. It was shown that this direct effect of the regulation can be attenuated by implementing constraints in the optimization process or minimizing the market SCR together with the historical volatility, proving the interest of having a portfolio construction approach that can incorporate such features. The present results are further explained by the Market SCR modelling.

Keywords: financial risk, numerical optimization, portfolio management, solvency capital requirement

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Authors: Shaine Mehta, Neelam Parmar, Patrick White, Mark Ashworth

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Patients with a history of substance have a high prevalence of comorbidities, including asthma and chronic obstructive pulmonary disease (COPD). Mortality rates are higher than that of the general population and the link to respiratory disease is reported. Randomised controlled trials (RCTs) support opioid substitution therapy as an effective means for harm reduction. However, whilst a high proportion of patients receiving opioid substitution therapy are smokers, to the author’s best knowledge there have been no studies of respiratory disease and smoking intensity in these patients. A cross sectional prevalence study was conducted using an anonymised patient-level database in primary care, Lambeth DataNet (LDN). We included patients aged 18 years and over who had records of ever having been prescribed methadone in primary care. Patients under 18 years old or prescribed buprenorphine (because of uncertainty about the prescribing indication) were excluded. Demographic, smoking, alcohol and asthma and COPD coding data were extracted. Differences between methadone and non-methadone users were explored with multivariable analysis. LDN contained data on 321, 395 patients ≥ 18 years; 676 (0.16%) had a record of methadone prescription. Patients prescribed methadone were more likely to be male (70.7% vs. 50.4%), older (48.9yrs vs. 41.5yrs) and less likely to be from an ethnic minority group (South Asian 2.1% vs. 7.8%; Black African 8.9% vs. 21.4%). Almost all those prescribed methadone were smokers or ex-smokers (97.3% vs. 40.9%); more were non-alcohol drinkers (41.3% vs. 24.3%). We found a high prevalence of COPD (12.4% vs 1.4%) and asthma (14.2% vs 4.4%). Smoking intensity data shows a high prevalence of ≥ 20 cigarettes per day (21.5% vs. 13.1%). Risk of COPD, adjusted for age, gender, ethnicity and deprivation, was raised in smokers: odds ratio 14.81 (95%CI 11.26, 19.47), and in the methadone group: OR 7.51 (95%CI: 5.78, 9.77). Furthermore, after adjustment for smoking intensity (number of cigarettes/day), the risk was raised in methadone group: OR 4.77 (95%CI: 3.13, 7.28). High burden of respiratory disease compounded by the high rates of smoking is a public health concern. This supports an integrated approach to health in patients treated for opiate dependence, with access to smoking cessation support. Further work may evaluate the current structure and commissioning of substance misuse services, including smoking cessation. Regression modelling highlights that methadone as a ‘risk factor’ was independently associated with COPD prevalence, even after adjustment for smoking intensity. This merits further exploration, as the association may be related to unexplored aspects of smoking (such as the number of years smoked) or may be related to other related exposures, such as smoking heroin or crack cocaine.

Keywords: methadone, respiratory disease, smoking cessation, substance misuse

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Authors: Tomola Obamuyi

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The banking system in Nigeria adopted innovative banking, with the aim of enhancing financial inclusion, and making financial services readily and cheaply available to majority of the people, and to contribute to the efficiency of the financial system. Some of the innovative services include: Automatic Teller Machines (ATMs), National Electronic Fund Transfer (NEFT), Point of Sale (PoS), internet (Web) banking, Mobile Money payment (MMO), Real-Time Gross Settlement (RTGS), agent banking, among others. The introduction of these payment systems is expected to increase bank efficiency and customers' satisfaction, culminating in better performance for the commercial banks. However, opinions differ on the possible effects of the various innovative payment systems on the performance of commercial banks in the country. Thus, this study empirically determines how commercial banks use innovation to gain competitive advantage in the specific context of Nigeria's finance and business. The study also analyses the effects of financial innovation on the performance of commercial banks, when different periods of analysis are considered. The study employed secondary data from 2009 to 2018, the period that witnessed aggressive innovation in the financial sector of the country. The Vector Autoregression (VAR) estimation technique forecasts the relative variance of each random innovation to the variables in the VAR, examine the effect of standard deviation shock to one of the innovations on current and future values of the impulse response and determine the causal relationship between the variables (VAR granger causality test). The study also employed the Multi-Criteria Decision Making (MCDM) to rank the innovations and the performance criteria of Return on Assets (ROA) and Return on Equity (ROE). The entropy method of MCDM was used to determine which of the performance criteria better reflect the contributions of the various innovations in the banking sector. On the other hand, the Range of Values (ROV) method was used to rank the contributions of the seven innovations to performance. The analysis was done based on medium term (five years) and long run (ten years) of innovations in the sector. The impulse response function derived from the VAR system indicated that the response of ROA to the values of cheques transaction, values of NEFT transactions, values of POS transactions was positive and significant in the periods of analysis. The paper also confirmed with entropy and range of value that, in the long run, both the CHEQUE and MMO performed best while NEFT was next in performance. The paper concluded that commercial banks would enhance their performance by continuously improving on the services provided through Cheques, National Electronic Fund Transfer and Point of Sale since these instruments have long run effects on their performance. This will increase the confidence of the populace and encourage more usage/patronage of these services. The banking sector will in turn experience better performance which will improve the economy of the country. Keywords: Bank performance, financial innovation, multi-criteria decision making, vector autoregression,

Keywords: Bank performance, financial innovation, multi-criteria decision making, vector autoregression

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