Search results for: endogenous variable

Authors: Bin Zhou, Tongli Lu, Jianwu Zhang, Hongtao Hao

Abstract:

Dual clutch transmissions (DCT) offer a high comfort performance in terms of the gearshift. Hydraulic multi-disk clutches are the key components of DCT, its engagement determines the shifting comfort. The prefill of the clutches requests an initial engagement which the clutches just contact against each other but not transmit substantial torque from the engine, this initial clutch engagement point is called the touch point. Open-loop control is typically implemented for the clutch prefill, a lot of uncertainties, such as oil temperature and clutch wear, significantly affects the prefill, probably resulting in an inappropriate touch point. Underfill causes the engine flaring in gearshift while overfill arises clutch tying up, both deteriorating the shifting comfort of DCT. Therefore, it is important to enable an adaptive capacity for the clutch prefills regarding the uncertainties. In this paper, a dynamic model of the hydraulic actuator system is presented, including the variable force solenoid and clutch piston, and validated by a test. Subsequently, the open-loop clutch prefill is simulated based on the proposed model. Two control parameters of the prefill, fast fill time and stable fill pressure is analyzed with regard to the impact on the prefill. The former has great effects on the pressure transients, the latter directly influences the touch point. Finally, an adaptive method is proposed for the clutch prefill during gear shifting, in which clutch fill control parameters are adjusted adaptively and continually. The adaptive strategy is changing the stable fill pressure according to the current clutch slip during a gearshift, improving the next prefill process. The stable fill pressure is increased by means of the clutch slip while underfill and decreased with a constant value for overfill. The entire strategy is designed in the Simulink/Stateflow, and implemented in the transmission control unit with optimization. Road vehicle test results have shown the strategy realized its adaptive capability and proven it improves the shifting comfort.

Keywords: clutch prefill, clutch slip, dual clutch transmission, touch point, variable force solenoid

Procedia PDF Downloads 298

Authors: Muhammad Asim

Abstract:

Background: Less than half of women in South Asia (SA) use any modern contraceptive method which leads to a huge burden of unintended pregnancies, unsafe abortions, maternal deaths, and socioeconomic loss. Women empowerment plays a pivotal role in improving various health seeking behaviours, including contraceptive use. The objective of this study to explore the association between women's empowerment and modern contraceptive, among rich and poor segment of population in SA. Methods: We used the most recent, large-scale, demographic health survey data of five South Asian countries, namely Afghanistan, Pakistan, Bangladesh, India, and Nepal. The outcome variable was the current use of modern contraceptive methods. The main exposure variable was a combination (interaction) of socio-economic status (SES) and women’s level of empowerment (low, medium, and high), where SES was bifurcated into poor and rich; and women empowerment was divided into three categories: decision making, attitude to violence and social independence. Moreover, overall women empowerment indicator was also created by using three dimensions of women empowerment. We applied both descriptive statistics and multivariable logistic regression techniques for data analyses. Results: Most of the women possessed ‘medium’ level of empowerment across South Asian Countries. The lowest attitude to violence empowerment was found in Afghanistan, and the lowest social independence empowerment was observed in Bangladesh across SA. However, Pakistani women have the lowest decision-making empowerment in the region. The lowest modern contraceptive use (22.1%) was found in Afghanistan and the highest (53.2%) in Bangladesh. The multivariate results depict that the overall measure of women empowerment does not affect modern contraceptive use among poor and rich women in most of South Asian countries. However, the decision-making empowerment plays a significant role among both poor and rich women to use modern contraceptive methods across South Asian countries. Conclusions: The effect of women’s empowerment on modern contraceptive use is not consistent across countries, and among poor and rich segment of population. Of the three dimensions of women’s empowerment, the autonomy of decision making in household affairs emerged as a stronger determinant of mCPR as compared with social independence and attitude towards violence against women.

Keywords: women empowerment, contraceptive use, South Asia, women autonomy

Procedia PDF Downloads 65

Authors: Abdulatif Abdulsalam Mohamed Shaban

Abstract:

A.C motors, in general, have superior performance characteristics to their d.c. counterparts. However, despite these advantage a.c. motors lack the controllability and simplicity and so d.c. motors retain a competitive edge where precise control is required. As part of an overall project to develop an improved cycloconverter control strategy for induction motors. Simulation and modelling techniques have been developed. This contribution describes a method used to simulate an induction motor drive using the SIMULINK toolbox within MATLAB software. The cycloconverter fed induction motor is principally modelled using the d-q axis equations. Results of the simulation for a given set of induction motor parameters are also presented.

Keywords: simulation, converter, motor, cycloconverter

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Authors: Subir S. Rao

Abstract:

Existing warehouse configurations use non-traditional aisle designs with a central P/D point in their models, which is mathematically simple but less practical. Many warehouses use multiple P/D points to avoid congestion for pickers, and different warehouses have different flow policies and infrastructure for using the P/D points. Many warehouses use multiple P/D points with non-traditional aisle designs in their analytical models. Standard warehouse models introduce one-sided multiple P/D points in a flying-V warehouse and minimize pick distance for a one-way travel between an active P/D point and a pick location with P/D points, assuming uniform flow rates. A simulation of the mathematical model generally uses four fixed configurations of P/D points which are on two different sides of the warehouse. It can be easily proved that if the source and destination P/D points are both chosen randomly, in a uniform way, then minimizing the one-way travel is the same as minimizing the two-way travel. Another warehouse configuration analytically models the warehouse for multiple one-sided P/D points while keeping the angle of the cross-aisles and picking aisles as a decision variable. The minimization of the one-way pick travel distance from the P/D point to the pick location by finding the optimal position/angle of the cross-aisle and picking aisle for warehouses having different numbers of multiple P/D points with variable flow rates is also one of the objectives. Most models of warehouses with multiple P/D points are one-way travel models and we extend these analytical models to minimize the two-way pick travel distance wherein the destination P/D is chosen optimally for the return route, which is not similar to minimizing the one-way travel. In most warehouse models, the return P/D is chosen randomly, but in our research, the return route P/D point is chosen optimally. Such warehouses are common in practice, where the flow rates at the P/D points are flexible and depend totally on the position of the picks. A good warehouse management system is efficient in consolidating orders over multiple P/D points in warehouses where the P/D is flexible in function. In the latter arrangement, pickers and shrink-wrap processes are not assigned to particular P/D points, which ultimately makes the P/D points more flexible and easy to use interchangeably for picking and deposits. The number of P/D points considered in this research uniformly increases from a single-central one to a maximum of each aisle symmetrically having a P/D point below it.

Keywords: non-traditional warehouse, V cross-aisle, multiple P/D point, pick travel distance

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Authors: Monika Sogani, Zainab Syed, Adrian C. Fisher

Abstract:

Pollution of estrogenic compounds has caught the attention of researchers as the slight increase of estrogens in the water bodies has a significant impact on the aquatic system. They belong to a class of endocrine disrupting compounds (EDCs) and are able to mimic hormones or interfere with the action of endogenous hormones. The microbial electrochemical remediation system (MERS) is employed here for exploiting an electrophototrophic bacterium for evaluating the capacity of biodegradation of ethinylestradiol hormone (EE2) under anaerobic conditions with power generation. MERS using electro-phototrophic bacterium offers a tailored solution of wastewater treatment in a developing country like India which has a huge solar potential. It is a clean energy generating technology as they require only sunlight, water, nutrients, and carbon dioxide to operate. Its main feature that makes it superior over other technologies is that the main fuel for this MERS is sunlight which is indefinitely present. When grown in light with organic compounds, these photosynthetic bacteria generate ATP by cyclic photophosphorylation and use carbon compounds to make cell biomass (photoheterotrophic growth). These cells showed EE2 degradation and were able to generate hydrogen as part of the process of nitrogen fixation. The two designs of MERS were studied, and a maximum of 88.45% decrease in EE2 was seen in a total period of 14 days in the better design. This research provides a better insight into microbial electricity generation and self-sustaining wastewater treatment facilities. Such new models of waste treatment aiming waste to energy generation needs to be followed and implemented for building a resource efficient and sustainable economy.

Keywords: endocrine disrupting compounds, ethinylestradiol, microbial electrochemical remediation systems, wastewater treatment

Procedia PDF Downloads 103

Authors: Muhammad Asim

Abstract:

Background: Less than half of women in South Asia (SA) use any modern contraceptive method which leads to a huge burden of unintended pregnancies, unsafe abortions, maternal deaths, and socioeconomic loss. Women empowerment plays a pivotal role in improving various health seeking behaviours, including contraceptive use. The objective of this study to explore the association between women's empowerment and modern contraceptive, among rich and poor segment of population in SA. Methods: We used the most recent, large-scale, demographic health survey data of five South Asian countries, namely Afghanistan, Pakistan, Bangladesh, India, and Nepal. The outcome variable was the current use of modern contraceptive methods. The main exposure variable was a combination (interaction) of socio-economic status (SES) and women’s level of empowerment (low, medium, and high), where SES was bifurcated into poor and rich; and women empowerment was divided into three categories: decision making, attitude to violence and social independence. Moreover, overall women empowerment indicator was also created by using three dimensions of women empowerment. We applied both descriptive statistics and multivariable logistic regression techniques for data analyses. Results: Most of the women possessed ‘medium’ level of empowerment across South Asian Countries. The lowest attitude to violence empowerment was found in Afghanistan, and the lowest social independence empowerment was observed in Bangladesh across SA. However, Pakistani women have the lowest decision-making empowerment in the region. The lowest modern contraceptive use (22.1%) was found in Afghanistan and the highest (53.2%) in Bangladesh. The multivariate results depict that the overall measure of women empowerment does not affect modern contraceptive use among poor and rich women in most of South Asian countries. However, the decision-making empowerment plays a significant role among both poor and rich women to use modern contraceptive methods across South Asian countries. Conclusions: The effect of women’s empowerment on modern contraceptive use is not consistent across countries, and among poor and rich segment of population. Of the three dimensions of women’s empowerment, the autonomy of decision making in household affairs emerged as a stronger determinant of mCPR as compared with social independence and attitude towards violence against women.

Keywords: women empowerment, modern contraceptive use, South Asia, women autonomy

Procedia PDF Downloads 64

Authors: A. Mohammadi, M. Moghimi, S. Mohammadi

Abstract:

Engineers need computational methods which could provide solutions less sensitive to the environmental effects, so the techniques should be used which take the uncertainty to account to control and minimize the risk associated with design and operation. In order to consider uncertainty in engineering problem, the optimization problem should be solved for a suitable range of the each uncertain input variable instead of just one estimated point. Using deterministic optimization problem, a large computational burden is required to consider every possible and probable combination of uncertain input variables. Several methods have been reported in the literature to deal with problems under uncertainty. In this paper, different methods presented and analyzed.

Keywords: uncertainty, Monte Carlo simulated, stochastic programming, scenario method

Procedia PDF Downloads 390

Authors: Ebenezer Amoquandoh, Daniel Bruce Sarpong, Godfred K. Ofosu-Budu, Andreas Fliessbach

Abstract:

Soil quality is at stake globally, but under tropical conditions, the loss of soil fertility may be existential. The current rates of soil nutrient depletion, erosion and environmental degradation in most of Africa’s farmland urgently require methods for soil fertility restoration through affordable agricultural management techniques. The study assessed the effects of locally available organic resources to improve soil fertility, crop yield and profitability compared to business as usual on farms in the Eastern and Greater Accra regions of Ghana. Apart from this, we analyzed the change of farmers’ perceptions and knowledge upon the experience with the new techniques; the effect of using locally available organic resource on farmers’ yield and determined the factors influencing the profitability of farming. Using the Difference in Mean Score and Proportion to estimate the extent to which farmers’ perceptions, knowledge and practices have changed, the study showed that farmers’ perception, knowledge and practice on the use of locally available organic resources have changed significantly. This paves way for the sustainable use of locally available organic resource for soil fertility improvement. The Propensity Score Matching technique and Endogenous Switching Regression model used showed that using locally available organic resources have the potential to increase crop yield. It was also observed that using the Profit Margin, Net Farm Income and Return on Investment analysis, it is more profitable to use locally available organic resources than other soil fertility amendments techniques studied. The results further showed that socioeconomic, farm characteristics and institutional factors are significant in influencing farmers’ decision to use locally available organic resources and profitability.

Keywords: soil fertility, locally available organic resources, perception, profitability, sustainability

Procedia PDF Downloads 128

Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

Abstract:

In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

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Authors: Anjan Hazra, Nirjhar Dasgupta, Chandan Sengupta, Sauren Das

Abstract:

Tea (Camellia sinensis) has received substantial attention from the scientific world time to time, not only for its commercial importance, but also for its demand to the health-conscious people across the world for its extensive use as potential sources of antioxidant supplement. These health-benefit traits primarily rely on some regulatory networks of different metabolic pathways. Development of microsatellite markers from the conserved genomic regions is being worthwhile for studying the genetic diversity of closely related species or self-pollinated species. Although several SSR markers have been reported, in tea the trait-specific Simple Sequence Repeats (SSRs) are yet to be identified, which can be used for marker assisted breeding technique. MicroRNAs are endogenous, noncoding, short RNAs directly involved in regulating gene expressions at the post-transcriptional level. It has been found that diversity in miRNA gene interferes the formation of its characteristic hair pin structure and the subsequent function. In the present study, the precursors of small regulatory RNAs (microRNAs) has been fished out from tea Expressed Sequence Tag (EST) database. Furthermore, the simple sequence repeat motifs within the putative miRNA precursor genes are also identified in order to experimentally validate their existence and function. It is already known that genic-SSR markers are very adept and breeder-friendly source for genetic diversity analysis. So, the potential outcome of this in-silico study would provide some novel clues in understanding the miRNA-triggered polymorphic genic expression controlling specific metabolic pathways, accountable for tea quality.

Keywords: micro RNA, simple sequence repeats, tea quality, trait specific marker

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Authors: Muhammad Usman, Munir Ahmed

Abstract:

The demand of high-rise buildings has grown fast during the past decades. The design of these buildings by using RC core wall have been widespread nowadays in many countries. The RC core wall (RCCW) buildings encompasses central core wall and boundary columns joined through post tension slab at different floor levels. The core wall often provides greater stiffness as compared to the collective stiffness of the boundary columns. Hence, the core wall dominantly resists lateral loading i.e. wind or earthquake load. Non-linear response history analysis (NLRHA) procedure is the finest seismic design procedure of the times for designing high-rise buildings. The modern design tools for nonlinear response history analysis and performance based design has provided more confidence to design these structures for high-rise buildings. NLRHA requires selection and scaling of ground motions to match design spectrum for site specific conditions. Designers use several techniques for scaling ground motion records (time series). Time domain and frequency domain scaling are most commonly used which comprises their own benefits and drawbacks. Due to lengthy process of NLRHA, application of only one technique is conceivable. To the best of author’s knowledge, no consensus on the best procedures for the selection and scaling of the ground motions is available in literature. This research aims to provide the finest ground motion scaling technique specifically for designing 40 story high-rise RCCW buildings. Seismic response of 40 story RCCW building is checked by applying both the frequency domain and time domain scaling. Variable sites are selected in three critical seismic zones of Pakistan. The results indicates that there is extensive variation in seismic response of building for these scaling. There is still a need to build a consensus on the subjected research by investigating variable sites and buildings heights.

Keywords: 40-storied RC core wall building, nonlinear response history analysis, ground motions, time domain scaling, frequency domain scaling

Procedia PDF Downloads 118

Authors: Christina Williams, Mehari Weldemariam, Ann M. Farese, Thomas J. MacVittie, Maureen A. Kane

Abstract:

Radiation exposure results in dose-dependent and time-dependent multi-organ damage. Drug development of medical countermeasures (MCM) for radiation-induced injury occurs under the FDA Animal Rule because human efficacy studies are not ethical or feasible. The FDA Animal Rule requires the representation of both sexes and describes several uses for biomarkers in MCM drug development studies. Currently, MCMs are limited and there is no FDA-approved biomarker for any radiation injury. Sex as a variable is essential to identifying biomarkers and developing effective MCMs for acute radiation exposure (ARS) and delayed effects of acute radiation exposure (DEARE). These studies aim to address the death of information on sex differences that have not been determined by studies that included only male, single-sex cohorts. Studies have reported differences in radiosensitivity according to sex. As such, biomarker discovery for radiation-induced damage must consider sex as a variable. This study evaluated the plasma proteomic profile of Rhesus macaque non-human primates after different exposures and doses, as well as time points after radiation. Exposures and doses included total body irradiation between 5-7.5 Gy and partial body irradiation with 5% bone marrow sparing at 9, 9.5 and 10 Gy. Timepoints after irradiation included days 1, 3, 60, and 180, which encompassed both acute radiation syndromes and delayed effects of acute radiation exposure. Bottom-up proteomic analyses of plasma included equal numbers of males and females. In the control animals, few proteomic differences are observed between the sexes. In the irradiated animals, there are a few sex differences, with changes mostly consisting of proteins upregulated in the female animals. Multiple canonical pathways were upregulated in irradiated animals relative to the control animals when subjected to pathway analysis, but differential responses between the sexes are limited. These data provide critical baseline differences according to sex and establish sex differences in non-human primate models relevant to drug development of MCM under the FDA Animal Rule.

Keywords: ionizing radiation, sex differences, plasma proteomics, biomarker discovery

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Authors: Hongquan Zhang

Abstract:

Inspired by endogenous protein motors, researchers have constructed various synthetic DNA motors based on the specificity and predictability of Watson-Crick base pairing. However, the application of DNA motors to signal amplification and biosensing is limited because of low mobility and difficulty in real-time monitoring of the walking process. The objective of our work was to construct a new type of DNA motor termed target-triggered DNA motors that can walk for hundreds of steps in response to a single target binding event. To improve the mobility and processivity of DNA motors, we used gold nanoparticles (AuNPs) as scaffolds to build high-density, three-dimensional tracks. Hundreds of track strands are conjugated to a single AuNP. To enable DNA motors to respond to specific protein and nucleic acid targets, we adapted the binding-induced DNA assembly into the design of the target-triggered DNA motors. In response to the binding of specific target molecules, DNA motors are activated to autonomously walk along AuNP, which is powered by a nicking endonuclease or DNAzyme-catalyzed cleavage of track strands. Each moving step restores the fluorescence of a dye molecule, enabling monitoring of the operation of DNA motors in real time. The motors can translate a single binding event into the generation of hundreds of oligonucleotides from a single nanoparticle. The motors have been applied to amplify the detection of proteins and nucleic acids in test tubes and live cells. The motors were able to detect low pM concentrations of specific protein and nucleic acid targets in homogeneous solutions without the need for separation. Target-triggered DNA motors are significant for broadening applications of DNA motors to molecular sensing, cell imagining, molecular interaction monitoring, and controlled delivery and release of therapeutics.

Keywords: biosensing, DNA motors, gold nanoparticles, signal amplification

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Authors: David Polcari, Samuel C. Perry, Loredano Pollegioni, Matthias Geissler, Janine Mauzeroll

Abstract:

ᴅ-serine acts as an endogenous co-agonist for N-methyl-ᴅ-aspartate receptors in neuronal synapses. This makes it a key component in the development and function of a healthy brain, especially given its role in several neurodegenerative diseases such as Alzheimer’s disease and dementia. Despite such clear research motivations, the primary site and mechanism of ᴅ-serine release is still currently unclear. For this reason, we are developing a biosensor for the detection of ᴅ-serine utilizing a microelectrode in combination with a ᴅ-amino acid oxidase enzyme, which produces stoichiometric quantities of hydrogen peroxide in response to ᴅ-serine. For the fabrication of a biosensor with good selectivity, we use a permselective poly(meta-phenylenediamine) film to ensure only the target molecule is reacted, according to the size exclusion principle. In this work, we investigated the effect of the electrodeposition conditions used on the biosensor’s response time and selectivity. Careful optimization of the fabrication process allowed for enhanced biosensor response time. This allowed for the real time sensing of ᴅ-serine in a bulk solution, and also provided in means to map the efflux of ᴅ-serine in real time. This was done using scanning electrochemical microscopy (SECM) with the optimized biosensor to measure localized release of ᴅ-serine from an agar filled glass capillary sealed in an epoxy puck, which acted as a model system. The SECM area scan simultaneously provided information regarding the rate of ᴅ-serine flux from the model substrate, as well as the size of the substrate itself. This SECM methodology, which provides high spatial and temporal resolution, could be useful to investigate the primary site and mechanism of ᴅ-serine release in other biological samples.

Keywords: ᴅ-serine, enzymatic biosensor, microelectrode, scanning electrochemical microscopy

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Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

Abstract:

Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

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Authors: Amira ben Hassine, A. Valverde, V. Serafín, C. Muñoz-San Martín, M. Garranzo-Asensio, M. Gamella, R. Barderas, M. Pedrero, N. Raouafi, S. Campuzano, P. Yáñez-Sedeño, J. M. Pingarrón

Abstract:

This work describes the development of a dual electrochemical immunosensing platform for accurate determination of two target proteins, IL-13 Receptor α2 (IL-13Rα2) and E-cadherin (E-cad). The proposed methodology is based on the use of sandwich immunosensing approaches (involving horseradish peroxidase-labeled detector antibodies) implemented onto magnetic microbeads (MBs) and amperometric transduction at screen-printed dual carbon electrodes (SPdCEs). The magnetic bioconjugates were captured onto SPdCEs and the amperometric transduction was performed using the H2O2/hydroquinone (HQ) system. Under optimal experimental conditions, the developed bio platform demonstrates linear concentration ranges of 1.0–25 and 5.0-100 ng mL-1, detection limits of 0.28 and 1.04 ng mL-1 for E-cad and IL-13Rα2, respectively, and excellent selectivity against other non-target proteins. The developed immuno-platform also offers a good reproducibility among amperometric responses provided by nine different sensors constructed in the same manner (Relative Standard Deviation values of 3.1% for E-cad and 4.3% for IL-13Rα2). Moreover, obtained results confirm the practical applicability of this bio-platform for the accurate determination of the endogenous levels of both extracellular receptors in colon cancer cells (both intact and lysed) with different metastatic potential and serum and tissues from patients diagnosed with colorectal cancer at different grades. Interesting features in terms of, simplicity, speed, portability and sample amount required to provide quantitative results, make this immuno-platform more compatible than conventional methodologies with the clinical diagnosis and prognosis at the point of care.

Keywords: electrochemistry, mmunosensors, biosensors, E-cadherin, IL-13 receptor α2, cancer colorectal

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Authors: Iveta Ludviga, Agita Kalvina

Abstract:

This paper aims to link together the concepts of job satisfaction, work engagement, trust, job meaningfulness and loyalty to the organisation focusing on specific type of employment–academic jobs. The research investigates the relationships between job satisfaction, work engagement and loyalty as well as the impact of trust and job meaningfulness on the work engagement and loyalty. The survey was conducted in one of the largest Latvian higher education institutions and the sample was drawn from academic staff (n=326). Structured questionnaire with 44 reflective type questions was developed to measure toe constructs. Data was analysed using SPSS and Smart-PLS software. Variance based structural equation modelling (PLS-SEM) technique was used to test the model and to predict the most important factors relevant to employee engagement and loyalty. The first order model included two endogenous constructs (loyalty and intention to stay and recommend, and employee engagement), as well as six exogenous constructs (feeling of fair treatment and trust in management; career growth opportunities; compensation, pay and benefits; management; colleagues; teamwork; and finally job meaningfulness). Job satisfaction was developed as second order construct and both: first and second order models were designed for data analysis. It was found that academics are more engaged than satisfied with their work and main reason for that was found to be job meaningfulness, which is significant predictor for work engagement, but not for job satisfaction. Compensation is not significantly related to work engagement, but only to job satisfaction. Trust was not significantly related neither to engagement, nor to satisfaction, however, it appeared to be significant predictor of loyalty and intentions to stay with the University. This paper revealed academic jobs as specific kind of employment where employees can be more engaged than satisfied and highlighted the specific role of job meaningfulness in the University settings.

Keywords: job satisfaction, job meaningfulness, higher education, work engagement

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Authors: Guettal Djaouida, Ziadi Abdelkader

Abstract:

In this paper, we study a coupling of the Alienor method with the algorithm of Piyavskii-Shubert. The classical multidimensional global optimization methods involves great difficulties for their implementation to high dimensions. The Alienor method allows to transform a multivariable function into a function of a single variable for which it is possible to use efficient and rapid method for calculating the the global optimum. This simplification is based on the using of a reducing transformation called Alienor.

Keywords: global optimization, reducing transformation, α-dense curves, Alienor method, Piyavskii-Shubert algorithm

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Authors: Janne Engblom, Elias Oikarinen

Abstract:

The understanding of housing price dynamics is of importance to a great number of agents: to portfolio investors, banks, real estate brokers and construction companies as well as to policy makers and households. A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models is dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Common Correlated Effects estimator (CCE) of dynamic panel data which also accounts for cross-sectional dependence which is caused by common structures of the economy. In presence of cross-sectional dependence standard OLS gives biased estimates. In this study, U.S housing price dynamics were examined empirically using the dynamic CCE estimator with first-difference of housing price as the dependent and first-differences of per capita income, interest rate, housing stock and lagged price together with deviation of housing prices from their long-run equilibrium level as independents. These deviations were also estimated from the data. The aim of the analysis was to provide estimates with comparisons of estimates between 1980-1999 and 2000-2012. Based on data of 50 U.S cities over 1980-2012 differences of short-run housing price dynamics estimates were mostly significant when two time periods were compared. Significance tests of differences were provided by the model containing interaction terms of independents and time dummy variable. Residual analysis showed very low cross-sectional correlation of the model residuals compared with the standard OLS approach. This means a good fit of CCE estimator model. Estimates of the dynamic panel data model were in line with the theory of housing price dynamics. Results also suggest that dynamics of a housing market is evolving over time.

Keywords: dynamic model, panel data, cross-sectional dependence, interaction model

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Authors: Yi Fung Lin, Pei Chen Tsai

Abstract:

Purpose: Many breast cancer survivors actively seek information about diet, exercise, and nutritional supplements to expedite recovery, reduce the risk of recurrence, and enhance their quality of life. While weight loss is not a primary concern for overweight or obese patients during the active treatment phase, they continue to face the additional burden and risks associated with excess weight post-treatment. This group has complex views on weight loss: they are concerned that exercise or dietary control might exacerbate symptoms, yet they also believe that obesity could negatively impact health. These perceptions can have both positive and negative effects on weight management. Therefore, this qualitative study aimed to explore the factors that influence overweight or obese breast cancer survivors' ability to manage their weight. Method: Eight women participated in in-depth interviews in 2022. Data was extracted based on the verbatim transcripts of the audio files, and the analysis was conducted through careful reading of the text. This qualitative research collected data until data saturation was reached. Results: A total of 22 codes were identified and subsequently integrated into three main themes: (1) Facilitators, including support systems, others' successful weight loss experiences, education, responsibility to others, and motivation; (2) Barriers, encompassing physical limitations, the stigma associated with weight loss, the cost of weight loss, antiestrogen medication, and cancer symptoms; (3) Variable Factors, which comprise perspectives on cancer, perspectives on obesity, and past experiences with weight loss. Conclusions: These findings are similar to previous research on barriers and motivators, highlighting variable factors that exist and can lead to either positive or negative effects on weight loss. The results can inform the development of weight management programs tailored to the needs of overweight or obese breast cancer survivors. Additionally, the identified factors represent vital variables for future studies, serving as valuable references for further research in this area.

Keywords: weight management, breast cancer, overweight, obese, cancer survivors

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Authors: Yuanxiaoyue Yang

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Emissions trading, or ‘cap-and-trade', has been long promoted by economists as a more cost-effective pollution control approach than traditional performance standard approaches. While there is a large body of empirical evidence for the overall effectiveness of emissions trading, relatively little attention has been paid to other unintended consequences brought by emissions trading. One important consequence is that cap-and-trade could introduce the risk of creating high-level emission concentrations in areas where emitting facilities purchase a large number of emission allowances, which may cause an unequal distribution of environmental benefits. This study will contribute to the current environmental policy literature by linking trading activity with environmental injustice concerns and empirically analyzing the causal relationship between trading activity and emissions reduction under a cap-and-trade program for the first time. To investigate the potential environmental injustice concern in cap-and-trade, this paper uses a differences-in-differences (DID) with instrumental variable method to identify the causal effect of allowance trading behaviors on emission reduction levels under the clean air interstate rule (CAIR), a cap-and-trade program targeting on the power sector in the eastern US. The major data source is the facility-year level emissions and allowance transaction data collected from US EPA air market databases. While polluting facilities from CAIR are the treatment group under our DID identification, we use non-CAIR facilities from the Acid Rain Program - another NOx control program without a trading scheme – as the control group. To isolate the causal effects of trading behaviors on emissions reduction, we also use eligibility for CAIR participation as the instrumental variable. The DID results indicate that the CAIR program was able to reduce NOx emissions from affected facilities by about 10% more than facilities who did not participate in the CAIR program. Therefore, CAIR achieves excellent overall performance in emissions reduction. The IV regression results also indicate that compared with non-CAIR facilities, purchasing emission permits still decreases a CAIR participating facility’s emissions level significantly. This result implies that even buyers under the cap-and-trade program have achieved a great amount of emissions reduction. Therefore, we conclude little evidence of environmental injustice from the CAIR program.

Keywords: air pollution, cap-and-trade, emissions trading, environmental justice

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Authors: Päärn Paiste, Margit Kõiv, Riho Mõtlep, Kalle Kirsimäe

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For small-scale wastewater management, the treatment wetlands (TWs) as a low cost alternative to conventional treatment facilities, can be used. However, P removal capacity of TW systems is usually problematic. P removal in TWs is mainly dependent on the physico–chemical and hydrological properties of the filter material. Highest P removal efficiency has been shown trough Ca-phosphate precipitation (i.e. active filtration) in Ca-rich alkaline filter materials, e.g. industrial by-products like hydrated oil shale ash (HOSA), metallurgical slags. In this contribution we report preliminary results of a full-scale TW system using HOSA material for P removal for a municipal wastewater at Nõo site, Estonia. The main goals of this ongoing project are to evaluate: a) the long-term P removal efficiency of HOSA using real waste water; b) the effect of high organic loading rate; c) variable P-loading effects on the P removal mechanism (adsorption/direct precipitation); and d) the form and composition of phosphate precipitates. Onsite full-scale experiment with two concurrent filter systems for treatment of municipal wastewater was established in September 2013. System’s pretreatment steps include septic tank (2 m2) and vertical down-flow LECA filters (3 m2 each), followed by horizontal subsurface HOSA filters (effective volume 8 m3 each). Overall organic and hydraulic loading rates of both systems are the same. However, the first system is operated in a stable hydraulic loading regime and the second in variable loading regime that imitates the wastewater production in an average household. Piezometers for water and perforated sample containers for filter material sampling were incorporated inside the filter beds to allow for continuous in-situ monitoring. During the 18 months of operation the median removal efficiency (inflow to outflow) of both systems were over 99% for TP, 93% for COD and 57% for TN. However, we observed significant differences in the samples collected in different points inside the filter systems. In both systems, we observed development of preferred flow paths and zones with high and low loadings. The filters show formation and a gradual advance of a “dead” zone along the flow path (zone with saturated filter material characterized by ineffective removal rates), which develops more rapidly in the system working under variable loading regime. The formation of the “dead” zone is accompanied by the growth of organic substances on the filter material particles that evidently inhibit the P removal. Phase analysis of used filter materials using X-ray diffraction method reveals formation of minor amounts of amorphous Ca-phosphate precipitates. This finding is supported by ATR-FTIR and SEM-EDS measurements, which also reveal Ca-phosphate and authigenic carbonate precipitation. Our first experimental results demonstrate that organic pollution and loading regime significantly affect the performance of hydrated ash filters. The material analyses also show that P is incorporated into a carbonate substituted hydroxyapatite phase.

Keywords: active filtration, apatite, hydrated oil shale ash, organic pollution, phosphorus

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Authors: F. Keller, G. Reinhart

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The efficient and economic allocation of resources is one main goal in the field of production planning and control. Nowadays, a new variable gains in importance throughout the planning process: Energy. Energy-efficiency has already been widely discussed in literature, but with a strong focus on reducing the overall amount of energy used in production. This paper provides a brief systematic approach, how energy-supply-orientation can be used for an energy-cost-efficient production planning and thus combining the idea of energy-efficiency and energy-flexibility.

Keywords: production planning, production control, energy-efficiency, energy-flexibility, energy-supply

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Authors: Susana P. Dias, Andrea Gomes, Fernanda M. Ferreira, Marta F. Henriques

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Thymus mastichina L. is an endogenous medicinal and aromatic plant of the Mediterranean flora. It has been used empirically over the years as a natural preservative in food. Nowadays, the antimicrobial activity of its bioactive compounds, such as essential oils and extracts, has been well recognized. The main purpose of this study was to evaluate the antimicrobial effect of Thymus mastichina ethanolic and aqueous extracts on pathogens and spoilage microorganisms present in cheese during ripening. The effect that the extract type and its concentration has on the development of Staphylococcus aureus, Escherichia coli, and Yarrowia lipolytica populations during 24 hours, was studied 'in vitro' using appropriate culture media. The results achieved evidenced the antimicrobial activity of T. mastichina extracts against the studied strains, and the concentration of 2 mg/mL (w/v) was selected and used directly on the cheese surface during ripening. In addition to the microbiological evaluation in terms of total aerobic bacteria, Enterobacteriaceae, yeasts (particularly Y. lipolytica) and molds, the treated cheeses physicochemical evaluation (humidity, aw, pH, colour, and texture) was also performed. The results were compared with cheeses with natamicyn (positive control) and without any treatment (negative control). The physicochemical evaluation showed that the cheeses treated with ethanolic extract of Thymus mastichina, except the fact that they lead to a faster water loss during ripening, did not present considerable differences when compared to controls. The study revealed an evident antimicrobial power of the extracts, although less effective than the one shown by the use of natamycin. For this reason, the improvement of the extraction methods and the adjustment of the extract concentrations will contribute to the use of T. mastichina as a healthier and eco-friendly alternative to natamycin, that is also more attractive from an economic point of view.

Keywords: antimicrobial activity, cheese, ethanolic extract, Thymus mastichina

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Authors: F. Argurio, F. G. Vaccaro

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In a global environment defined by ever-increasing health issues, in spite of the progress made by modern medicine, this paper seeks to readdress the question of global health in an international relations perspective. The research hypothesis is: the lower the security environment, the higher the spread of communicable diseases. This question will be channeled by re-scaling the connotation of 'global' and 'international' dimension through the theoretical lens of glocalization, a theory by Bauman that starts its analysis from simple systems to get to the most complex ones. Glocalization theory will be operationalized by analyzing health in an armed-conflict context. In this respect, the independent variable 'low security environment' translates into the cases of Syria and Yemen, which provide a clear example of the all-encompassing nature of conflict on national health and the effects on regional development. In fact, Syria and Yemen have been affected by poliomyelitis and cholera outbreaks respectively. The dependent variable will be constructed on said communicable diseases which belong to the families of sanitation-related and vaccine-preventable diseases. The research will be both qualitative and quantitative, based on primary (interviews) and secondary (WHO and other NGO’s reports) sources. The methodology is based on the assessment of the vaccine coverage and case-analysis in time and space using epidemiological data. Moreover, local health facilities’ functioning and efficiency will be studied. The article posits that the intervention and cooperation of international organizations with the local authorities becomes crucial to provide the local populations with their primary health needs. In Yemen, the majority of fatal cholera cases were in the regions controlled by the Houthi rebels, not officially accredited by the International Community. Similarly, the polio outbreak in Syria primarily affected the areas not controlled by the Syrian Arab Republic forces, recognized as the leading interlocutor by the WHO. The jeopardized possibilities to access these countries have been pivotal to the determining the problem in controlling sanitation-related and vaccine preventable diseases. This represents a potential threat to global health.

Keywords: health in conflict-affected areas, cholera, polio, Yemen, Syria, glocalization

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Authors: Faiz Khan Mohammad, Saumya Ray Chaudhari, Raghunathan Rengaswamy, Swagatika Sahoo

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Cholera caused by pathogenic gut bacteria Vibrio Cholerae (VC), is a major health problem in developing countries. Different strains of VC exhibit variable responses subject to different extracellular medium (Nag et al, Infect Immun, 2018). In this study, we present a new approach to model the variable VC responses in mono- and co-cultures, subject to continuously changing growth medium, which is otherwise difficult via simple FBA model. Nine VC strain and seven E. coli (EC) models were assembled and considered. A continuously changing medium is modelled using a new iterative-based controlled medium technique (ITC). The medium is appropriately prefixed with the VC model secretome. As the flux through the bacteria biomass increases secretes certain by-products. These products shall add-on to the medium, either deviating the nutrient potential or block certain metabolic components of the model, effectively forming a controlled feed-back loop. Different VC models were setup as monoculture of VC in glucose enriched medium, and in co-culture with VC strains and EC. Constrained to glucose enriched medium, (i) VC_Classical model resulted in higher flux through acidic secretome suggesting a pH change of the medium, leading to lowering of its biomass. This is in consonance with the literature reports. (ii) When compared for neutral secretome, flux through acetoin exchange was higher in VC_El tor than the classical models, suggesting El tor requires an acidic partner to lower its biomass. (iii) Seven of nine VC models predicted 3-methyl-2-Oxovaleric acid, mysirtic acid, folic acid, and acetate significantly affect corresponding biomass reactions. (iv) V. parhemolyticus and vulnificus were found to be phenotypically similar to VC Classical strain, across the nine VC strains. The work addresses the advantage of the ITC over regular flux balance analysis for modelling varying growth medium. Future expansion to co-cultures, potentiates the identification of novel interacting partners as effective cholera therapeutics.

Keywords: cholera, vibrio cholera El. tor, vibrio cholera classical, acetate

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Authors: Muhammad Asim, Mehvish Amjad

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Background: Less than half of women in South Asia (SA) use any modern contraceptive method which leads to a huge burden of unintended pregnancies, unsafe abortions, maternal deaths, and socioeconomic loss. Women empowerment plays a pivotal role in improving various health seeking behaviours, including contraceptive use. The objective of this study to explore the association between women's empowerment and modern contraceptive, among rich and poor segment of population in SA. Methods: We used the most recent, large-scale, demographic health survey data of five South Asian countries, namely Afghanistan, Pakistan, Bangladesh, India, and Nepal. The outcome variable was the current use of modern contraceptive methods. The main exposure variable was a combination (interaction) of socio-economic status (SES) and women’s level of empowerment (low, medium, and high), where SES was bifurcated into poor and rich; and women empowerment was divided into three categories: decision making, attitude to violence and social independence. Moreover, overall women empowerment indicator was also created by using three dimensions of women empowerment. We applied both descriptive statistics and multivariable logistic regression techniques for data analyses. Results: Most of the women possessed ‘medium’ level of empowerment across South Asian Countries. The lowest attitude to violence empowerment was found in Afghanistan, and the lowest social independence empowerment was observed in Bangladesh across SA. However, Pakistani women have the lowest decision-making empowerment in the region. The lowest modern contraceptive use (22.1%) was found in Afghanistan and the highest (53.2%) in Bangladesh. The multivariate results depict that the overall measure of women empowerment does not affect modern contraceptive use among poor and rich women in most of South Asian countries. However, the decision-making empowerment plays a significant role among both poor and rich women to use modern contraceptive methods across South Asian countries. Conclusions: The effect of women’s empowerment on modern contraceptive use is not consistent across countries, and among poor and rich segment of population. Of the three dimensions of women’s empowerment, the autonomy of decision making in household affairs emerged as a stronger determinant of mCPR as compared with social independence and attitude towards violence against women.

Keywords: women empowerment, modern contraceptive use, South Asia, socio economic status

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Authors: Svitlana Antonenko, Gennady Telegeev

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Introductive statement: The development of chronic myeloid leukemia (CML) is caused by Bcr-Abl oncoprotein. Modern treatments with tyrosine kinase inhibitors are greatly complicated by the mutational variability of the Bcr-Abl oncoprotein, which causes drug resistance. Therefore, there is an urgent need to develop new approaches to the treatment of the disease, which will allow modeling the level of Bcr-Abl oncoprotein in the cell. Promising in this direction is the identification of proteases that can selectively promote cellular proteolysis of oncoproteins. The aim of the study was to study the effect of the interaction of Bcr-Abl with deubiquitinase USP1 on the level of oncoprotein in CML cells. Methodology: K562 cells were selected for the experiment. Сells were incubated with ML323 inhibitor for 24 hours. Precipitation of endogenous proteins from K562 cell lysate was performed using anti-Bcr-Abl antibodies. Cell lysates and precipitation results were studied by Western blot. Subcellular localization of proteins was studied by immunofluorescence analysis followed by confocal microscopy. The results were analyzed quantitatively and statistically. Major findings: The Bcr-Abl/USP1 protein complex was detected in CML cells, and it was found that inhibition of USP1 deubiquitinating activity by the compound ML323 leads to disruption of this protein complex and a decrease in the level of Bcr-Abl oncoprotein in cells. The interaction of Bcr-Abl with USP1 may result in deubiquitination of the oncoprotein, which disrupts its proteasomal degradation and leads to the accumulation of CML in cells. Conclusion: We believe that the interaction of oncoprotein with USP1 may be one of the prerequisites that contribute to malignant cell transformation due to the deubiquitination of oncoprotein, which leads to its accumulation and disease progression. A correlation was found between the deubiquitinating activity of USP1 and the level of oncoprotein in CML cells. Thus, we identify deubiquitinase USP1 as a promising therapeutic target for the development of a new strategy for the treatment of CML by modulating the level of Bcr-Abl in the cell.

Keywords: chronic myeloid leukemia, Bcr-Abl, USP1, deubiquitination Bcr-Abl, K562 cell

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Authors: Mohammed Abdullah Alshahrani

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The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

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Authors: Man Ying Kang, Joshua Kin Man Nan

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The prolonged pandemic has posed alarming public health challenges to various parts of the world, and face-to-face mental health treatment is largely discounted for the control of virus transmission, online psychological services and self-help mental health kits have become essential. Online self-help mindfulness-based interventions have proved their effects on fostering mental health for different populations over the globe. This paper was to test the effectiveness of an online short-term audio-based mindfulness (SAM) program in enhancing wellbeing, dispositional mindfulness, and reducing stress and negative affect in community settings in China, and to explore possible mechanisms of how dispositional mindfulness, stress, and negative affect influenced the intervention effects on wellbeing. Community-dwelling adults were recruited via online social networking sites (e.g., QQ, WeChat, and Weibo). Participants (n=100) were randomized into the mindfulness group (n=50) and a waitlist control group (n=50). In the mindfulness group, participants were advised to spend 10–20 minutes listening to the audio content, including mindful-form practices (e.g., eating, sitting, walking, or breathing). Then practice daily mindfulness exercises for 3 weeks (a total of 21 sessions), whereas those in the control group received the same intervention after data collection in the mindfulness group. Participants in the mindfulness group needed to fill in the World Health Organization Five Well-Being Index (WHO), Positive and Negative Affect Schedule (PANAS), Perceived Stress Scale (PSS), and Freiburg Mindfulness Inventory (FMI) four times: at baseline (T0) and at 1 (T1), 2 (T2), and 3 (T3) weeks while those in the waitlist control group only needed to fill in the same scales at pre- and post-interventions. Repeated-measure analysis of variance, paired sample t-test, and independent sample t-test was used to analyze the variable outcomes of the two groups. The parallel process latent growth curve modeling analysis was used to explore the longitudinal moderated mediation effects. The dependent variable was WHO slope from T0 to T3, the independent variable was Group (1=SAM, 2=Control), the mediator was FMI slope from T0 to T3, and the moderator was T0NA and T0PSS separately. The different levels of moderator effects on WHO slope was explored, including low T0NA or T0PSS (Mean-SD), medium T0NA or T0PSS (Mean), and high T0NA or T0PSS (Mean+SD). The results found that SAM significantly improved and predicted higher levels of WHO slope and FMI slope, as well as significantly reduced NA and PSS. FMI slope positively predict WHO slope. FMI slope partially mediated the relationship between SAM and WHO slope. Baseline NA and PSS as the moderators were found to be significant between SAM and WHO slope and between SAM and FMI slope, respectively. The conclusion was that SAM was effective in promoting levels of mental wellbeing, positive affect, and dispositional mindfulness as well as reducing negative affect and stress in community settings in China. SAM improved wellbeing faster through the faster enhancement of dispositional mindfulness. Participants with medium-to-high negative affect and stress buffered the therapy effects of SAM on wellbeing improvement speed.

Keywords: mindfulness, negative affect, stress, wellbeing, randomized control trial

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