Research Tool Research Articles

The moderating role of emotional skills between jealousy and mate retention tactics

BackgroundThe purpose of this study was to investigate the moderating role of emotional skills – emotion regulation, emotion under-standing and emotional intelligence – between jealousy in a close relationship and employing mate retention tactics.Participants and procedureThe study involved a group of 196 Polish nationals (111 women and 85 men) aged between 19 and 62, who were involved in romantic relationships of the following types: dating relationship, cohabitating, engaged or married. The following research tools were used: the Emotion Regulation Questionnaire (ERQ), the Emotion Understanding Test, INTE questionnaire, the Mate Retention Inventory – Short Form (MRI-SF) and the Multidimensional Jealousy Scale.ResultsEmotion suppression was identified as a modifier between jealousy and the use of acts linked to the direct guarding tactic, and between jealousy and acts associated with the public signals of possession tactic. The ability to suppress emotion con-tributes to an increased readiness to employ direct guarding at the time of a high jealousy level.ConclusionsThe results showed that the moderators of the relationship between jealousy and mate retention tactics were emotional suppression and emotion understanding. Emotional functioning is important for the well-being of relationships, especially for dealing with jealousy.

Single-Molecule Maps of Membrane Insertion by Amyloid-β Oligomers Predict Their Toxicity.

The interaction of small Amyloid-β (Aβ) oligomers with the lipid membrane is an important component of the pathomechanism of Alzheimer's disease (AD). However, oligomers are heterogeneous in size. How each type of oligomer incorporates into the membrane, and how that relates to their toxicity, is unknown. Here, we employ a single molecule technique called Q-SLIP (Quencher-induced Step Length Increase in Photobleaching) to measure the membrane insertion of each monomeric unit of individual oligomers of Aβ42, Aβ40, and Aβ40-F19-Cyclohexyl alanine (Aβ40-F19Cha), and correlate it with their toxicity. We observe that the N-terminus of Aβ42 inserts close to the center of the bilayer, the less toxic Aβ40 inserts to a shallower depth, and the least toxic Aβ40-F19Cha has no specific distribution. This oligomer-specific map provides a mechanistic representation of membrane-mediated Aβ toxicity and should be a valuable tool for AD research.

Engineering viral vectors for acoustically targeted gene delivery

Targeted gene delivery to the brain is a critical tool for neuroscience research and has significant potential to treat human disease. However, the site-specific delivery of common gene vectors such as adeno-associated viruses (AAVs) is typically performed via invasive injections, which limit its applicable scope of research and clinical applications. Alternatively, focused ultrasound blood-brain-barrier opening (FUS-BBBO), performed noninvasively, enables the site-specific entry of AAVs into the brain from systemic circulation. However, when used in conjunction with natural AAV serotypes, this approach has limited transduction efficiency and results in substantial undesirable transduction of peripheral organs. Here, we use high throughput in vivo selection to engineer new AAV vectors specifically designed for local neuronal transduction at the site of FUS-BBBO. The resulting vectors substantially enhance ultrasound-targeted gene delivery and neuronal tropism while reducing peripheral transduction, providing a more than ten-fold improvement in targeting specificity in two tested mouse strains. In addition to enhancing the only known approach to noninvasively target gene delivery to specific brain regions, these results establish the ability of AAV vectors to be evolved for specific physical delivery mechanisms.

RADAR-Pipeline: Scalable Feature Generation for Mobile Health Data

Introduction & BackgroundRADAR-Pipeline is an open-source Python framework designed to simplify and enhance mobile health data analysis. It has been designed to efficiently read and process the large amount of data generated through the RADAR-Base platform. RADAR-base is a scalable, real-time streaming and analytics open-source platform to facilitate research access and customisation requirements. Studies using the Radar-base platform have collected fine-grained longitudinal data from wearables and phones. The data can potentially create multitudes of digital biomarkers, which can be used to inform us greatly about the disease condition. Due to the sheer size of the data, it can be difficult for researchers to read and process those data -- a common task is identifying useful features and common data processing/analysis steps previously used by the community. Up to now, these have been hand-crafted by individual data scientists, often lacking the capability to be easily reused by the community without author-specific knowledge. Furthermore, generating variables based on already established research on a larger scale can be challenging and could hinder replication. Hence, we have designed RADAR-Pipeline to help researchers overcome these challenges. It empowers them to create and share their data analysis and visualisation pipelines, fostering collaboration and knowledge sharing within the research community. Objectives & ApproachThe primary objective of RADAR-Pipeline is to offer researchers a user-friendly and powerful platform to develop and share their research. Researchers can build reusable analysis and visualisation pipelines to ensure consistent and reliable results. It simplifies big data analysis by leveraging Apache Spark to handle large and complex mobile health datasets efficiently. Researchers can also save time and effort by reusing and extending existing pipelines built by others. Finally, the RADAR-Pipeline promotes collaboration and recognition by allowing researchers to share their work through the RADAR-base Analytics Catalogue, making their pipelines citable and accessible to the wider research community. Whilst Radar-pipeline has been designed to read data from Radar-base, it can also be used to read data from any dataset which uses Hadoop Distributed File System (HDFS) file system namespace. Relevance to Digital FootprintsMobile health data is rich and valuable for understanding human behaviour and health. RADAR-Pipeline addresses the challenges associated with analysing large and complex mobile health datasets, enabling researchers to extract valuable insights that can be used to (1) Improve public health: By enabling efficient analysis of large-scale mobile health data, RADAR-Pipeline can contribute to research efforts aimed at improving population health outcomes and developing effective interventions; (2) Personalised healthcare: By facilitating the extraction of individual-level features from mobile health data, RADAR-Pipeline can seamlessly be integrated with Kafka data streams and machine learning pipelines to process the data in real-time, which can then be utilised to create more effective and targeted real-time interventions. (3) Promote reproducible research: The framework's emphasis on transparency and reproducibility in research aligns with the conference's focus on the responsible use of digital mobile health data. Conclusions & ImplicationsRADAR-Pipeline is a valuable tool for researchers, offering them the means to harness the potential of mobile health data. By adopting this framework, researchers can achieve efficient and scalable data analysis, thereby streamlining the extracting insights from digital footprints. This efficiency enables researchers to delve deeper into the data and uncover valuable patterns and trends. Furthermore, RADAR-Pipeline promotes collaboration and knowledge sharing within the research community. By providing a standardised framework for data analysis, RADAR-Pipeline facilitates collaboration among researchers, leading to the sharing of best practices and the dissemination of knowledge.

Profiling expression strategies for a type III polyketide synthase in a lysate-based, cell-free system

Some of the most metabolically diverse species of bacteria (e.g., Actinobacteria) have higher GC content in their DNA, differ substantially in codon usage, and have distinct protein folding environments compared to tractable expression hosts like Escherichia coli. Consequentially, expressing biosynthetic gene clusters (BGCs) from these bacteria in E. coli often results in a myriad of unpredictable issues with regard to protein expression and folding, delaying the biochemical characterization of new natural products. Current strategies to achieve soluble, active expression of these enzymes in tractable hosts can be a lengthy trial-and-error process. Cell-free expression (CFE) has emerged as a valuable expression platform as a testbed for rapid prototyping expression parameters. Here, we use a type III polyketide synthase from Streptomyces griseus, RppA, which catalyzes the formation of the red pigment flaviolin, as a reporter to investigate BGC refactoring techniques. We applied a library of constructs with different combinations of promoters and rppA coding sequences to investigate the synergies between promoter and codon usage. Subsequently, we assess the utility of cell-free systems for prototyping these refactoring tactics prior to their implementation in cells. Overall, codon harmonization improves natural product synthesis more than traditional codon optimization across cell-free and cellular environments. More importantly, the choice of coding sequences and promoters impact protein expression synergistically, which should be considered for future efforts to use CFE for high-yield protein expression. The promoter strategy when applied to RppA was not completely correlated with that observed with GFP, indicating that different promoter strategies should be applied for different proteins. In vivo experiments suggest that there is correlation, but not complete alignment between expressing in cell free and in vivo. Refactoring promoters and/or coding sequences via CFE can be a valuable strategy to rapidly screen for catalytically functional production of enzymes from BCGs, which advances CFE as a tool for natural product research.

The role of internet addiction and academic resilience in predicting the mental health of high school students in Tehran

BackgroundThe World Health Organization defines mental health as a combination of two dimensions: the negative dimension, or negative mental health, which indicates the presence of mental disorders, symptoms, and problems, and the positive dimension, or positive mental health, which includes emotions and positive personal characteristics such as self-esteem, resilience against environmental challenges, a sense of integrity, and self-efficacy. The aim of the present study was to investigate the role of internet addiction and academic resilience in predicting the mental health of high school students in Tehran, Iran.MethodThe research method employed was a survey. 758 people participated in the study, and the samples consisted of high school students in Tehran during the academic year 2022–2023. The process of collecting information was carried out by distributing the questionnaire link through virtual networks and schools. The research utilized Young’s Internet Addiction Test, Samuels’ Academic Resilience Inventory, and Goldberg’s Mental Health Questionnaire as the research tools. Statistical tests, including Pearson’s correlation and multiple regression analysis, were employed to investigate the relationships between variables.ResultThe effect of internet addiction on mental health (ß=0.39) is negative and significant at the 0.001 level, while the effect of academic resilience on mental health (ß=0.66) is positive and significant at the 0.001 level. These two variables collectively predict 53% of the variance in students’ mental health. This indicates that as internet addiction increases among students, their mental health significantly decreases, whereas higher levels of academic resilience correspond to higher mental health.ConclusionsThis study has elucidated the role of internet addiction and academic resilience in predicting the mental health of high school students in Tehran. Given the significance of adolescent mental health, it is imperative for healthcare professionals and other stakeholders to develop intervention and prevention models to address mental health crises and plan for the enhancement of adolescent mental health.

Embracing the Versatility of Botulinum Neurotoxins in Conventional and New Therapeutic Applications.

Botulinum neurotoxins (BoNTs) have been used for almost half a century in the treatment of excessive muscle contractility. BoNTs are routinely used to treat movement disorders such as cervical dystonia, spastic conditions, blepharospasm, and hyperhidrosis, as well as for cosmetic purposes. In addition to the conventional indications, the use of BoNTs to reduce pain has gained increased recognition, giving rise to an increasing number of indications in disorders associated with chronic pain. Furthermore, BoNT-derived formulations are benefiting a much wider range of patients suffering from overactive bladder, erectile dysfunction, arthropathy, neuropathic pain, and cancer. BoNTs are categorised into seven toxinotypes, two of which are in clinical use, and each toxinotype is divided into multiple subtypes. With the development of bioinformatic tools, new BoNT-like toxins have been identified in non-Clostridial organisms. In addition to the expanding indications of existing formulations, the rich variety of toxinotypes or subtypes in the wild-type BoNTs associated with new BoNT-like toxins expand the BoNT superfamily, forming the basis on which to develop new BoNT-based therapeutics as well as research tools. An overview of the diversity of the BoNT family along with their conventional therapeutic uses is presented in this review followed by the engineering and formulation opportunities opening avenues in therapy.

Applications of machine learning in urodynamics: A narrative review.

Machine learning algorithms as a research tool, including traditional machine learning and deep learning, are increasingly applied to the field of urodynamics. However, no studies have evaluated how to select appropriate algorithm models for different urodynamic research tasks. We undertook a narrative review evaluating how the published literature reports the applications of machine learning in urodynamics. We searched PubMed up to December 2023, limited to the English language. We selected the following search terms: artificial intelligence, machine learning, deep learning, urodynamics, and lower urinary tract symptoms. We identified three domains for assessment in advance of commencing the review. These were the applications of urodynamic studies examination, applications of diagnoses of dysfunction related to urodynamics, and applications of prognosis prediction. The machine learning algorithm applied in the field of urodynamics can be mainly divided into three aspects, which are urodynamic examination, diagnosis of urinary tract dysfunction and prediction of the efficacy of various treatment methods. Most of these studies were single-center retrospective studies, lacking external validation, requiring further validation of model generalization ability, and insufficient sample size. The relevant research in this field is still in the preliminary exploration stage; there are few high-quality multi-center clinical studies, and the performance of various models still needs to be further optimized, and there is still a distance from clinical application. At present, there is no research to summarize and analyze the machine learning algorithms applied in the field of urodynamics. The purpose of this review is to summarize and classify the machine learning algorithms applied in this field and to guide researchers to select the appropriate algorithm model for different task requirements to achieve the best results.

Dementia Ideal Care: Ecosystem Map of Best Practices and Care Pathways Enhancedby Technology and Community.

Globally, much work has been done by nonprofit, private, and academic groups to develop best practices for the care of people living with dementia (PLWD), including Alzheimer's disease. However, these best practices reside in disparate repositories and tend to focus on one phase of the patient journey or one relevant group. To fill this gap, we developed a Dementia Ideal Care Map that everyone in the dementia ecosystem can use as an actionable tool for awareness, policy development, funding, research, training, service delivery, and technology design. The intended audience includes (and not limited to) policymakers, academia, industry, technology developers, health system leaders, clinicians, social service providers, patient advocates, PLWD, their families, and communities at large. A search was conducted for published dementia care best practices and quality measures, which were then summarized in a visual diagram. The draft diagram was analyzed to identify barriers to ideal care. Then, additional processes, services, technologies, and quality measures to overcome those challenges were brainstormed. Feedback was then obtained from experts. The Dementia Ideal Care Map summarizes the ecosystem of over 200 best practices, nearly 100 technology enablers, other infrastructure, and enhanced care pathways in one comprehensive diagram. It includes psychosocial interventions, care partner support, community-based organizations; awareness, risk reduction; initial detection, diagnosis, ongoing medical care; governments, payers, health systems, businesses, data, research, and training. Dementia Ideal Care Map is a practical tool for planning and coordinating dementia care. This visualized ecosystem approach can be applied to other conditions.

Design and Psychometric Properties of the Student Perception of Teacher Care Scale in University Students

Teacher care in the university setting is crucial for the academic, emotional, and social development of students, encompassing moral virtues such as compassion and professional competence. The students’ perception of teacher care directly relates to their well-being and active participation in learning. Despite the recognized importance of teacher care, there is a lack of adequate instruments to measure it, especially in specific cultural and educational contexts like Peru. The aim of this research is to develop and assess the psychometric properties of a scale measuring student perception of teacher care in the Peruvian university context, to provide a valid and reliable tool for future research and educational practices. An instrumental study was conducted with 910 university students aged between 18 and 50 years (M = 20.2, SD = 3.45). The Student Perception of Teacher Care Scale (SPTCS) was used, divided into five dimensions (Compassion, Competence, Confidentiality, Trust, and Awareness). Exploratory (EFA) and confirmatory (CFA) factor analyses were conducted to evaluate the scale’s internal structure, along with reliability analyses and measurement invariance across genders. The EFA identified a four-factor structure reflecting the dimensions of Confidentiality and Trust, Competence, Awareness, and Compassion. The CFA confirmed this structure with good fit indices for four-factor models, which was then adjusted to a five-factor model, one of which is a second-order factor (χ2 = 720.727, df = 369, CFI = 0.951, TLI = 0.946, RMSEA = 0.046, and SRMR = 0.032). Internal reliability was high (α and ω > 0.9 for all factors). Measurement invariance was established across genders, allowing for valid comparisons between men and women. It is concluded that the Student Perception of Teacher Care Scale proves to be a valid and reliable instrument for measuring teacher care in the Peruvian university context. The results emphasize the multidimensionality of teacher care and its significance for the educational environment and student experience. This study contributes to educational research and teaching practice, offering a means to assess and improve caring relationships in higher education.

Visualizing Anthocyanins: Colorimertic Analysis of Blue Maize

Anthocyanin, vibrant pigments found in a wide range of plants, including maize, contribute to the red, blue, and purple hues observed in fruits, vegetables, and grains. The inherent color variations in maize, including natural shades of purple, red, blue, and even rainbow colors, pose a significant challenge in accurately assessing maize maturity. This study recognizes the importance of visualizing the distinct blue purplish anthocyanin coloration to determine the optimal harvest time for blue maize, particularly among small-scale producers. To address this crucial need, this research project presents the development of the MaizeMeter, an advanced colorimeter specifically designed to analyze maize color based on anthocyanin pigmentation. Leveraging the power of Internet of Things (IoT) implementation, the MaizeMeter provides real-time monitoring and interpretation of anthocyanin color values. The proposed methodology encompasses the calibration of the color sensor and the prototyping of the MaizeMeter, culminating in the establishment of a comprehensive database of anthocyanin color profiles in blue maize. The generated anthocyanin color database by the MaizeMeter will serve as a vital tool for small-scale farmers and researchers, enabling more efficient and accurate assessment of maize maturity in the future.

Assessment of Service Quality Perception Gap between Service Seekers and Service Providers of Land Services in Rwanda

Purpose: This study aimed to assess the determinants of customer satisfaction from the perspective of service seekers and service providers using SERVQUAL. Methodology: the study employed both quantitative and qualitative research approaches. The survey method was used to collect primary quantitative data. Probability sampling was employed to select both service seekers and service providers. 422 service seekers were randomly selected from a list of 53,158 people. 45 service providers were also randomly selected from 416 land officers. A data collection tool was developed for service seekers and customized for service providers. The validity of the research tool was tested and the results showed a P-value of 0.00. Cronbach’s Alpha calculation was employed to test reliability and resulted in an output of 0.932 > 0.7 which shows excellent reliability. Key informant interviews were also conducted with purposively selected respondents to collect their opinions on service quality to complement the quantitative data. Findings: From the perspective of service seekers, the findings showed that the five service quality dimensions are positive and significant predictors of satisfaction. The data from the service providers show that only empathy is a positive and significant predictor of satisfaction whereas, the other four dimensions are positive but less significant predictors of satisfaction. The study results revealed a discrepancy between service seekers and service providers in the dimensions that predict the satisfaction of customers with land services more than others. Contribution to Theory, Policy, and Practice: Understanding the perception gap allows service providers to adjust their approaches to service delivery design to be more customer-focused. The study also informs policymakers where to focus efforts to enhance the quality of services. The unique aspect that this research puts forward is the comparison of the data from both service seekers and service providers to show similarities or differences in their understanding of which dimensions predict the satisfaction of customers more than others. The study recommends continuous collection of feedback from service seekers to help bridge the perception gap in what predicts satisfaction of service seekers.

Raman scattering owing to magneto-polaron states in monolayer transition metal dichalcogenides

Magneto-optical measurements are fundamental research tools that allow for studying the hitherto unexplored optical transitions and the related applications of topological two-dimensional (2D) transition metal dichalcogenides (TMDs). A theoretical model is developed for the first-order magneto-resonant Raman scattering in a monolayer of TMD. A significant number of avoided crossing points involving optical phonons in the magneto-polaron (MP) spectrum, a superposition of the electron and hole states in the excitation branches, and their manifestations in optical transitions at various light scattering configurations are unique features for these 2D structures. The Raman intensity reveals three resonant splittings of double avoided-crossing levels. The three excitation branches are present in the MP spectrum provoked by the coupling of the Landau levels in the conduction and valence bands via an out-of-plane A1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$A_1$$\\end{document}-optical phonon mode. The energy gaps at the anticrossing points in the MP scattering spectrum are revealed as a function of the electron and hole optical deformation potential constants. The resonant MP Raman scattering efficiency profile allows for quantifying the relative contribution of the conduction and valence bands in the formation of MPs. The results obtained are a guideline for controlling MP effects on the magneto-optical properties of TMD semiconductors, which open pathways to novel optoelectronic devices based on 2D TMDs.

The Uses of X/Twitter by Members of the TESOL Community

A lack of dialogue and collaboration between researchers and practitioners has been recognized in the field of second language education. Social media platforms such as X/Twitter have potential for connecting professionals in the teaching of English to speakers of other languages (TESOL) community and supporting professional learning and research; however, studies of TESOL professionals’ uses of X/Twitter have only examined posts/tweets from a limited number of communities marked by hashtags/ keywords. This study identifies 23 hashtags relevant to TESOL instruction for adults in the Canadian context and used them as search parameters to extract a data set of 4,833 posts/tweets. Eighty-two North American university professors who had published in the field of TESOL, were selected and searched for on X/Twitter. Upon locating 15 X/Twitter professor accounts, all 272 posts/tweets posted over the one-year period, were extracted. Two content analyses were conducted to infer the purpose of the posts/ tweets and identify the hashtags used by the professors. Results reveal considerable variation in the professors’ and other TESOL community members’ uses of X/Twitter and suggest that the two groups participate in rather separate X/Twitter communities. Recommendations for maximizing X/Twitter as a tool for professional learning and research and fostering the research-practice link are provided.

Decoding AI in Contemporary Art: A Five-Trope Classification for Understanding and Categorization

Abstract The article presents a historical overview of the classification of contemporary artworks that either have utilized artificial intelligence as a tool in their creation or focus on AI as their central theme or subject matter. The authors analyze artworks and descriptions, focusing on artists’ motivations and AI’s role in their practice, identifying five distinct tropes in AI art. The authors compare artworks with respect to key questions, creating a useful tool for art historians, curators, researchers, and artists. This historical classification provides a structured approach to understanding AI art’s creative significance and attributes as it has developed over time.

Preparation of Light‐responsive Unnatural RNA Bases via a Chromogenic Morita‐Baylis‐Hillman Adduct Path

AbstractRNA‐based tools for biological and pharmacological research are raising an increasing interest. Among these, RNA aptamers whose biological activity can be controlled via illumination with specific wavelengths represent an important target. Here, we report on a proof‐of‐principle study supporting the viability of a systematic use of Morita‐Baylis‐Hillman adducts (MBHAs) for the synthesis of light‐responsive RNA building blocks. Accordingly, a specific acetylated MBHA derivative was employed in the functionalization of the four natural RNA bases as well as two unnatural bases (5‐aminomethyl uracil and 5‐methylaminomethyl uracil). The results reveal a highly selective functionalization for both unnatural bases. The conjugation products were then investigated spectroscopically, photochemically and computationally. It is shown that when a single light‐responsive unit is present (i. e. when using 5‐methylaminomethyl uracil), the generated unnatural uracil behaves like a cinnamic‐framework‐based photochemical switch that isomerizes upon illumination through a biomimetic light‐induced intramolecular charge transfer mechanism driving a barrierless and, therefore, ultrafast reaction path.

Deciphering the Role of Virus Receptors in Plant–Virus–Vector Interactions

Insect-transmitted plant viruses are a major threat to global agricultural crop production. Receptors play a prominent role in the interplay between host-pathogen and vector interaction. The virus–vector relationship involves both viral and vector receptors. Receptors-like kinases (RLKs) and receptor-like proteins play a crucial role in plant immunity, which acts as a basal defense. Pathogens can evade or block host recognition by their effector proteins to inhibit pathogen recognition receptor (PRR)-mediated signaling. Intriguingly, RLKs are also known to interact with viral proteins and impact plant susceptibility against viruses, while the endocytic receptors in vectors assist in the binding of the virus to the vectors. Unlike other receptors of fungi and bacteria which have three different domains located from extracellular or intracellular to perceive a multitude of molecular patterns, the characterization of viral receptors is quite complex and limited since the virus is directly injected into plant cells by insect vectors. Little is known about these receptors. Unraveling the receptors involved in virus entry and transmission within the vector will provide vital information in virus–vector interactions. This review focuses on efforts undertaken in the identification and characterization of receptors of plant viruses within the host and vector. This will lead to a better understanding of the cellular mechanism of virus transmission and spread, and further suggests new alternative tools for researchers to develop an integrated approach for the management of viral diseases and associated vectors.

Generation of nanobodies from transgenic ‘LamaMice’ lacking an endogenous immunoglobulin repertoire

Due to their exceptional solubility and stability, nanobodies have emerged as powerful building blocks for research tools and therapeutics. However, their generation in llamas is cumbersome and costly. Here, by inserting an engineered llama immunoglobulin heavy chain (IgH) locus into IgH-deficient mice, we generate a transgenic mouse line, which we refer to as ‘LamaMouse’. We demonstrate that LamaMice solely express llama IgH molecules without association to Igκ or λ light chains. Immunization of LamaMice with AAV8, the receptor-binding domain of the SARS-CoV-2 spike protein, IgE, IgG2c, and CLEC9A enabled us to readily select respective target-specific nanobodies using classical hybridoma and phage display technologies, single B cell screening, and direct cloning of the nanobody-repertoire into a mammalian expression vector. Our work shows that the LamaMouse represents a flexible and broadly applicable platform for a facilitated selection of target-specific nanobodies.

The effect of educational intervention according to mindfulness on the psychological well-being of female heads of households.

The low level of psychological well-being is one of the most common problems of the women who are the heads of households, and various educational programs have been conducted to improve the psychological well-being of such a group. The present study was conducted to outline the effectiveness of mindfulness-based educational intervention in the psychological well-being of women as the heads of households. This research as a semi-experimental study was done by pretest-posttest design and control group. The study statistical population included all women as the heads of households in Shiraz, who had a file in the Shiraz based welfare office and at the same time their children were studying in schools covered by the 2nddistrict educational department of Shiraz in 2022-2023. Out of the female heads of the households in the statistical community, 30 women were selected as Purposive sampling and then randomly divided into two 15-individual groups, including experimental group (training on mindfulness-based therapy) and control group. The research tool included Ryff's psychological well-being scale (Ryff, 1989). The experimental group was subjected to training on mindfulness-based therapy (Baer et al., 2006) during eight 90-min sessions. However, the control group did not receive any intervention. After running the intervention, a significant difference was seen between the components of autonomy, personal growth, purpose in life, self-acceptance, positive relationship with others, and psychological well-being after running the educational intervention between the experimental and control groups (P < 0.05), while no meaningful difference popped up between the experimental and control groups in terms of environmental mastery as one of the aspects measured in psychological well-being scale after the educational intervention (P = 0.602). According to the results, it seems that psychologists can benefit from the method of training on mindfulness-based therapy in order to increase the psychological well-being of women as the heads of households.

Water and Sanitation Practices and performance of Bomet Water and Sanitation Company in Bomet County, Kenya

Water and sanitation provision practices are established with the intention to enhance performance, provision on clean water and enhanced sanitation services. However, globally, not all Water &amp; Sanitation Companies are able to achieve their core mandate of provision of adequate clean water and sanitation services. All Water and Sanitation Companies adopt water and sanitation practices however the extent to which they affect performance of water and sanitation companies is has attracted divergent views while other scholar found a negative affect others found a positive effect and hence a dilemma exist as to what is the exact effect of water and sanitation practices on the performance of water and sanitation companies. At Bomet Water and Sanitation Company in Bomet County, very few studies exist that have been conducted on the subject matter and yet its performance is not optimal and the hence the reason as to why this study was conducted at the Water and Sanitation Company. The purpose of this study was to determine the effect of water and sanitation practices on performance of Bomet Water and Sanitation Company in Bomet County, Kenya. Specific objectives of the study were to establish how resources influences performance of Bomet Water and Sanitation Company, to find out the extent to which stakeholder engagement effects performance of Bomet Water and Sanitation Company, to determine the effects of governance on the performance of Bomet Water and Sanitation Company and to examine the influence of information communication technology on the performance of Bomet Water and Sanitation Company. Theories adopted were; Resource Based View Theory, Stakeholder Theory, Stewardship Theory, Systems Theory and Balance scorecard Theory. The study adopted a descriptive research design and targeted 170 respondents drawn from commercial, technical and administration department. The sample size was 34 staffs selected using stratified random sampling technique. A pilot study was conducted to test the effectiveness and reliability of the research tool. The study used both primary and secondary data sources. Data was analyzed using quantitative approach which involved the use of descriptive statistics that entailed percentages, frequency, mean and standard deviation. Inferential statistic adopted was regression analysis was used to establish existing relationships between water and sanitation provision practices and performance of Bomet Water and Sanitation Company. Results were as follows; resources had a positive and significant effect on performance of BOMWASCO of (β=-0.229, p &lt; 0.05). Stakeholder engagement had a positive and significant effect on performance of BOMWASCO (β=0.231, p &lt; 0.05). Governance had a positive and significant effect on performance of BOMWASCO (β=0.451, p &lt; 0.05). ICT had a positive and significant effect on performance of BOMWASCO (β=0.343, p &lt; 0.05). The study concluded that resources, stakeholder engagement, governance and ICT have a positive and significant effect on performance of BOMWASCO. The study recommended that physical resources should used sufficiently and correctly to enhance equitable water supply all residents. The community should continue to be engaged in all water supply and solid waste collection practices in the County. BOMWASCO board structure should effectively represent diverse stakeholder interests. Current software solutions should continue being used in a manner that effectively meets organizational needs and requirements. The study recommends further studies should be conducted on Water and sanitation practices and performance of other water and sanitation companies in Kenya.