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Purpose – The study is interested in knowing “the role of the organizational structure as a mediating variable of the relationship between the information technology and organizational communication”. Design/methodology/approach – The study was conducted in several service companies, and the study adopted the questionnaire as a basic tool for the data collection on the practical side, as 267 opinions were surveyed, in addition to conducting personal interviews, and the normal distribution of data was tested, analyzing, describing and diagnosing study variables, testing correlations and determining direct effects. Findings – Findings show that there is no direct and significant statistical impact of information technology on organizational communications. Whereas there was a positive, direct and statistically significant impact of information technology on the organizational structure. There was also a positive, direct and statistically significant effect of the organizational structure on organizational communication. Research limitations/implications – This paper is restricted to the role of the organizational structure as a mediating variable of the relationship between the influence of information technology on organizational communication. Practical implications – As part of the practical implication, the paper suggests the need to increase support and attention to the importance of information technology in service organizations in order to increase coordination and organizational communication and achieve a high ability to explore and exploit ideas. Originality/value – Apart from the fact that several companies were engaged, the organizational structures of these companies were engaged too to examine the impacts of Information technology (ICT) on organizational communication.

Infertility is estimated to affect more than 50 million couples around the world, with the male factor accounting for half of these cases, yet there is a notable absence of effective treatment options for men, other than in-vitro fertilisation (IVF) or intracytoplasmic sperm injection (ICSI). This review considers unlicensed and empirical treatments used for male subfertility, including hormonal therapy, phosphodiesterase inhibitors, and antioxidants. Compounds generally demonstrate variable improvements in sperm function, but benefits for fertility are less clear. There is a pressing need for effective treatment options for subfertile men; however, our knowledge of sperm function is limited, restricting the identification of precise treatment targets. The traditional drug discovery pathway is also notorious for its extensive resource and time requirements, often extending over decades and demanding significant financial investment. Unfortunately, a substantial number of potential therapies fail before reaching the marketplace. Furthermore, reliance on mammalian models is not possible in the drug development process for male subfertility, due to significant variability between animals and man. We review recent breakthroughs and highlight novel methods aimed at improving the effectiveness and efficiency of drug discovery for male subfertility. High-throughput screening, combinatorial chemistry, and the repurposing of established medications have great potential. These strategies offer the promise of accelerating the pace of drug development, curbing the extensive demand for resources, and, in the case of drug repurposing, diminishing the demand for comprehensive pharmacokinetic and pharmacodynamic studies. As these innovative approaches are adopted, the feasibility of addressing male subfertility through scientific advancements appears to be increasingly attainable. Lay summary Globally, millions of men suffer from infertility, but with very few exceptions, there is no effective treatment or cure other than complex fertility treatments such as in vitro fertilisation. This review article considers various approaches to treat men, or sperm, which have been largely unsuccessful to date. A significant issue is that we lack a detailed understanding of how sperm work and why treatments do not work. Another issue is that drug discovery is slow and costly because many potential treatments fail early on. However, we discuss recent technical and technological advancements that offer hope, such as high-throughput and phenotypic screening, which allow for the rapid testing of thousands of chemicals to observe their effects on sperm, and combinatorial chemistry, which involves generating large numbers of compounds to find those with beneficial properties. Finding relevant new uses for prescription drugs could also significantly speed up the drug discovery process and result in much-needed new treatments for male infertility.

The influence of transition metals (Zn, Cd and Ni) on bismuth magnesium niobate (Bi3.5Mg1.8Nb2.7O13.8, BMN) pyrochlores was investigated. Considering the difference in their ionic radii, Cd was postulated to substitute Mg at the eight-fold coordinated A-site whereas Zn and Ni were to replace Mg at the six-fold coordinated B-sites of the host structure. Solubility limits in these substitutional pyrochlore solid solutions were determined to be 0.4, 0.1 and 0.3 for Zn, Ni and Cd, respectively. Upon introducing these divalent cation dopants, notable changes in the lattice parameters and grain sizes were observed with increasing dopant concentration. The high dielectric constants, ε′ of Zn, Cd and Ni doped BMN pyrochlores were discernible with their bulk values of 195-216, 173-195 and 153-195, respectively. The highest ε′ of 216 was recorded for the composition with Zn = 0.1 in contrast to the lowest value of 153 found in the composition with Ni = 0.1. Meanwhile, these highly insulating divalent cation doped BMN pyrochlores also exhibit low dielectric losses, tan _ whose values are in the order of 10−3. The excellent dielectric properties allow these novel pyrochlore phases to be potentially applied for the energy storage applications.

In the dynamic field of Customer Retention Prediction (CRP), strategic marketing and promotion efforts targeting specific customers are crucial. Understanding customer behavior and identifying churn indicators are vital for devising effective retention strategies. However, identifying customers likely to terminate services presents a challenge, leading to data imbalance issues. Existing CRP studies using Machine Learning (ML) techniques and data imbalance methods face problems such as overfitting and computational complexity. Similarly, recent CRP studies employing Deep Learning (DL) approaches rely on data sampling techniques, which can result in overfitting and a lack of cost sensitivity. Additionally, DL approaches struggle with slow convergence and get stuck in local minima. This paper introduces an effective hybrid of Deep Learning (DL) classifiers focusing on cost-metric integration to address data imbalance issues and period-shift Cosine Annealing Learning Rate (ps-CALR) to accelerate model training, ultimately enhancing performance. Three Telecom datasets, namely IBM, Iranian, and Orange, were used to assess the model performance. Empirical findings show that the hybrid DL classifiers significantly improved CRP over conventional ML. This paper contributes methodological advancements and practical insights for effective customer retention in the telecom industry.

Abstract Background General mental health inpatient units hold a valuable place in the stepped system of care, and for identification and treatment of people with eating disorders (EDs) or disordered eating behaviours (DEBs). This study aimed to pragmatically evaluate an evidence-informed screening and care pathway, alongside a staff education program, implemented to improve identification and treatment access for consumers with EDs and DEBs, with co-occurring psychiatric conditions, on a general mental health ward. Methods A mixed methodology design was mapped to the RE-AIM implementation framework. It encompassed medical record audits across two 3-month time points pre and post implementation of the pathway, and key informant consumer and health professional interviews. Results Process and implementation data were compared for three-month periods pre (2019, n = 348) and post-implementation (2021, n = 284). Post-implementation, intake SCOFF screening occurred in 94.7% of admissions. People with ED/DEBs diagnoses were 35 times more likely to have a SCOFF score ≥ 2 (OR = 35.2, p

Abstract Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP–SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP–SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP–SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a hub SNP with a significant main effect and a large minor allele frequency (MAF) tended to have a higher false-positive rate. In addition, peripheral null SNPs in a cluster with a small MAF tended to enhance false positivity. We also demonstrated that using the modified significance criterion based on the 3 p-value rules and the bootstrap approach (3pRule + bootstrap) can reduce false positivity and maintain high true positivity. In addition, our results also showed that a pair without a significant main effect tends to have weak or no interaction. This study identified the cluster effect and suggested using the 3pRule + bootstrap approach to enhance SNP–SNP interaction detection accuracy.

Background: Community-based doula support for women and gender-diverse birthing people has a range of benefits in improving maternal outcomes and experiences. However, there is limited research on how doula services operate in Australia. Birth for Humankind is an Australian community-based volunteer doula service, which provides free doula support for women and gender diverse birthing people experiencing social discrimination and financial disadvantage. The aim of this study was to understand facilitators and barriers to implementation and sustainability of a community-based doula service delivered to clients concurrently receiving care at a major maternity hospital in Melbourne, Australia. Methods: We conducted a qualitative study consisting of 30 in-depth interviews with doulas and managers of the community-based doula service Birth for Humankind, and midwives, doctors and social workers from a maternity hospital. Data were inductively thematically analysed, and themes were then deductively categorised using the Capability, Opportunity, and Motivation (COM-B) model and Theoretical Domains Framework (TDF) to understand behavioural influences and facilitators and barriers to implementing and sustaining the doula service within a hospital setting. Results: Facilitators to implementation of the doula service included: collaborative relationships; having sound knowledge of referral processes; and being a valued professional doula service with dedicated volunteers. Barriers to implementation included: limited knowledge of the doula service from hospital staff; difficulty in retaining volunteer doulas; being a small non-profit doula service; and limited capacity of hospitals to financially support the doula service. Advocacy for renumerating doulas may be one means to strengthen and sustain existing doula-provider service relationships. Conclusion: Consideration of establishing strategic partnerships between the doula service and hospitals may create financially-sustainable pathways to enable provision of high-quality, community-based doula support for women and gender diverse birthing people to continue.

The effect of different coal bottom ash (CBA) gradings on ground granulated blast furnace slag (GGBS) binary blended cement mortar is not well-documented in current literature. Therefore, previous studies have reported inconsistent and contradictory effects of using various CBA gradings as a fine aggregate replacement in mortar and concrete. Hence, the present work aimed to establish the influence of different coal bottom ash (CBA) gradings, which is crucial for reducing coal power plant waste by utilising larger fractions of CBA in mortar and concrete without compromising its hardened properties. Specifically, this study investigated the optimal grading of coal bottom ash (CBA) for natural sand replacement in ground granulated blast furnace slag (GGBS) binary blended cement mortar. The research examines three CBA gradings: passing 10 mm sieve (R-CBA), passing 4.75 mm sieve (S-CBA), and grading according to BS EN12620 (Gr-CBA) at 20 %, 40 %, and 60 % sand replacement levels for comparison. Resultant mortar specimens were tested at 7, 28, and 91 days for mechanical strength, fluid transport, and drying shrinkage. Results show that all CBA gradings performed better than the control mix (with river sand only). The Gr-CBA mix outperformed the S-CBA mix by up to 29 % in strength due to highly consistent grading. R-CBA mix exhibited optimal performance compared to the other two CBA mix up to 30 % in strength. The coarser grading of the R-CBA mix enhances the interfacial transition zone and aggregate-binder bond and, hence, exhibited a better performance. This study highlights the potential use of R-CBA grading to increase the CBA reuse rate in mortar or concrete while maintaining desirable performance.

Abstract A third of patients with non‐Hodgkin's lymphoma (NHL) develop pleural effusion during the disease course for various reasons. In most cases, lymphoma‐related pleural effusion is a manifestation of widespread systemic disease, signifying a high tumour burden and therefore, a poorer prognosis. On the other hand, primary pleural lymphomas (PPLs) exhibit exclusive or dominant involvement of serous cavities, without detectable solid tumour masses. PPL is an uncommon disease and is of two types: primary effusion lymphoma (PEL) and diffuse large B‐cell lymphoma associated with chronic inflammation (DLBCL‐CI). PPLs not related to PELs and DLBCL‐CIs are exceedingly rare. Herein, we describe four patients with biopsy proven B‐cell NHL. One had no extra‐pleural involvement at the time of diagnosis, indicating PPL. In all cases, histopathological examination of pleural biopsies obtained via medical thoracoscopy (MT) were crucial in clinching the final diagnosis. Clinicians are alerted to the potential relationship between exudative effusion and NHL as well as the role of MT in the diagnosis of B‐cell NHL.

Dengue fever is an arthropod-borne viral disease that is widespread throughout the world. Herein, we report a case of dengue cardiomyopathy that was detected and treated to best effect using point-of-care ultrasound (POCUS) and the VExUS score. A 75-year-old lady with no known comorbidities presented with a 10-day history of fever, vomiting, loose stool, and poor appetite. Upon arrival, she was febrile and hypotensive. Bedside POCUS showed poor left ventricular systolic function, inferior vena cava measuring 2.27cm and VExUS grading of 2 to 3. Dengue serology IgM and IgG were positive and NT-proBNP raised at 12500pg/ml. Instead of fluid resuscitation, diuretic and inotropes were initiated along the line of cardiogenic shock secondary to dengue cardiomyopathy. Serial normal cardiac enzymes and electrocardiogram excluded acute coronary syndrome. She was discharged well, and repeated echocardiography one-month post discharge showed normal left ventricular systolic function with no clinical signs or symptoms of heart failure.

The digital transformation process of power systems towards smart grids is resulting in improved reliability, efficiency and situational awareness at the expense of increased cybersecurity vulnerabilities. Given the availability of large volumes of smart grid data, machine learning-based methods are considered an effective way to improve cybersecurity posture. Despite the unquestionable merits of machine learning approaches for cybersecurity enhancement, they represent a component of the cyberattack surface that is vulnerable, in particular, to adversarial attacks. In this paper, we examine the robustness of autoencoder-based cyberattack detection systems in smart grids to adversarial attacks. A novel iterative-based method is first proposed to craft adversarial attack samples. Then, it is demonstrated that an attacker with white-box access to the autoencoder-based cyberattack detection systems can successfully craft evasive samples using the proposed method. The results indicate that naive initial adversarial seeds cannot be employed to craft successful adversarial attacks shedding insight on the complexity of designing adversarial attacks against autoencoder-based cyberattack detection systems in smart grids.