Miracle-dz/UniFAR-FTUs huggingface dataset:
PHARMACISTS’ VIEW OF DRUG PROMOTION BY SALES REPRESENTATIVES: A SURVEY FROM INDONESIA

Interactions between pharmaceutical representatives and pharmacists are increasing. This study aimed to evaluate pharmacists’ views towards the drug promotion conducted by sales representatives in Indonesia. Adopting a cross-sectional survey study design, pharmacists completed questionnaires (n=120) to examine attitudes toward drug promotion by sales representatives, perception of the impact of drug promotion on attitudes and knowledge, and their experience in training in dealing with sales representatives and drug promotion. A total of 120 pharmacists participated in the study, of these; the majority of the respondents were females (80.83%) and aged 30-45 years (45.00%). Most respondents (55.83%) had experience in practice collaboration with doctors. However, only a small number of respondents (25.83%) were trained in drug promotion ethics. Approximately 71.67% of pharmacists do not agree with pharmaceutical company support of conferences and speakers, and the majority of respondents (73.33%) do not agree on the appropriateness of gifts provided by pharmaceutical companies. The majority of respondents believe that discussions with sales representatives impact prescribing (76.67%) and receiving gifts influences prescribing (72.50%). We found that majority of pharmacists accept promotion as a source of drug promotion and promotion as a source of information for the introduction of new medicines. Teaching the ethics or effects of drug company promotion has been never taught in pharmacy education. It is recommended that the structured curriculum of pharmacy education include courses/discussion groups on the ethical relationship between pharmacists and pharmaceutical companies.
Computational Investigations of Traditional Chinese Medicinal Compounds against the Omicron Variant of SARS-CoV-2 to Rescue the Host Immune System

Macrodomain-I of the NSP3 (non-structural protein 3) is responsible for immune response hijacking in the SARS-CoV-2 infection known as COVID-19. In the omicron variant (B.1.1.529), this domain harbors a new mutation, V1069I, which may increase the binding of ADPr and consequently the infection severity. This macrodomain-I, due to its significant role in infection, is deemed to be an important drug target. Hence, using structural bioinformatics and molecular simulation approaches, we performed a virtual screening of the traditional Chinese medicines (TCM) database for potential anti-viral drugs. The screening of 57,000 compounds yielded the 10 best compounds with docking scores better than the control ADPr. Among the top ten, the best three hits—TCM42798, with a docking score of −13.70 kcal/mol, TCM47007 of −13.25 kcal/mol, and TCM30675 of −12.49 kcal/mol—were chosen as the best hits. Structural dynamic features were explored including stability, compactness, flexibility, and hydrogen bonding, further demonstrating the anti-viral potential of these hits. Using the MM/GBSA approach, the total binding free energy for each complex was reported to be −69.78 kcal/mol, −50.11 kcal/mol, and −47.64 kcal/mol, respectively, which consequently reflect the stronger binding and inhibitory potential of these compounds. These agents might suppress NSP3 directly, allowing the host immune system to recuperate. The current study lays the groundwork for the development of new drugs to combat SARS-CoV-2 and its variants.
Industry Clusters and Food Value Chains: Can the Literature on Local Collective Failure be used as a Guide for Assessing and Overcoming Value Chain Failure?

In this paper the literature on industry clusters as a response to local collective failure is reviewed as a way of enhancing knowledge about how failure of food value chains to perform efficiently can be analysed and overcome. The conclusion is that there is much in the local collective failure literature that assists in an understanding of, and is consistent with, the concepts of value chain failure, value chain externalities and value chain goods. Four potential areas for enhancing the analysis of value chains by accessing this literature are noted: defining the boundary between chain failure and local collective failure; improving joint action among parties interested in overcoming chain failure; augmenting the processes of knowledge creation and application in value chains; and improving the governance of value chains. The key point is that the ability of local collective or value chain partners to produce chain goods and internalise positive chain externalities depends directly on the nature and intent of the joint action by the partners: will they cooperate or not, and, if they do cooperate, how and to what extent will they do so? These issues of coordination of economic activity and the nature of the relationships between partners go to the heart of governance within both local communities and value chains.
An Algorithm to Generate a Weighted Network Voronoi Diagram Based on Improved PCNN

The network Voronoi diagram has been extensively applied in many fields, such as influence area construction, location selection and urban planning, owing to its high accuracy and validity in space division. Taking advantage of parallel processing and auto-wave division of the pulse coupled neural network (PCNN), an algorithm for generating a weighted network Voronoi diagram is proposed in this paper. First, in order to better accommodate the scenes of urban facility points and road networks, the PCNN is improved. Second, the speed of the auto-wave in the improved PCNN is calculated by the weights of the facility points and the attributes of the related road network. Third, the nodes in the road network are considered as neurons, the facility points are projected onto the nearest road segments and the projected points are treated as initial neurons. The initial neurons generate auto-waves simultaneously, and the auto-waves transmit along the shortest path from neurons to other neurons with the calculated speed until all the neurons are fired. During this procedure, the road network and the corresponding space are assigned to the initial neurons and the weighted network Voronoi diagram is constructed. The experiments on the specific region with the real POIs present the feasibility, applicability and efficiency of the algorithm.
Strategies for Degrowth Computing

More energy is typically expended on a computer's manufacture than during its working life. This paper looks at 1) the concept of resource reduction and scarcity in the economy, degrowth, applied to the rendering of computing and information services, “degrowth computing” and identifies some strategies. It 2) explores some degrowth concepts around energy autarky with a Raspberry Pi, with some further thoughts about consumption within the research frames of the Limits community. When is the most sustainable computer not a new one? When might people not need consume this most useful of tools?
Robust H 2-control for discrete-time Markovian jump linear systems

This paper deals with the robust H2-control of discrete-time Markovian jump linear systems. It is assumed that both the state and jump variables are available to the controller. Uncertainties satisfying some norm bounded conditions are considered on the parameters of the system. An upper bound for the H2-control problem is derived in terms of a linear matrix inequality (LMI) optimization problem. For the case in which there are no uncertainties, we show that the convex formulation is equivalent to the existence of the mean square stabilizing solution for the set of coupled algebraic Riccati equations arising on the quadratic optimal control problem of discrete-time Markovian jump linear systems. Therefore, for the case with no uncertainties, the convex formulation considered in this paper imposes no extra conditions than those in the usual dynamic programming approach. Finally some numerical examples are presented to illustrate the technique.
Face mask detection using GoogLeNet CNN-based SVM classifiers

The COVID-19 pandemic that broke out in 2019 has affected the whole world, and in late 2021 the number of cases is still increasing rapidly. In addition, due to this pandemic, all people must follow the mask and cleaning rules. Herein, it is now mandatory to wear a mask in places where millions of people working in many workplaces work. For this reason, artificial intelligence-based systems that can detect face masks are becoming very popular today. In this study, a system that can automatically detect whether people are masked or not is proposed. In the dataset used in the study, there are a total of 440 images, 220 with masks and 220 without masks. Here, we extract image features from each image using the GoogLeNet deep learning architecture. Using the loss3-classifier layer of the GoogLeNet deep learning architecture, we obtain 1000 deep image features for each image. With the help of these image features, we train GoogLeNet based Linear Support Vector Machine (SVM), Quadratic SVM, and Coarse Gaussian SVM classifiers. Afterward, we develop a Graphical User Interface (GUI) application of the proposed system and a system that can detect masks from snapshots by saving the trained models. Thus, an application that is based on artificial intelligence and can automatically detect the mask has been developed. From the results, it appears that the accuracy (%), sensitivity (%), specificity (%) precision (%), F1 score (%), and Matthews Correlation Coefficient (MCC) values of GoogLeNet based Linear SVM, Quadratic SVM, and Coarse Gaussian SVM classifiers are equal to 99.55-99.55-99.55-99.55-99.55-0.9909, 99.55-99.55-99.55-99.55-99.55-0.9909, and 99.55-99.09-100-100-99.54-0.9910, respectively. When the results are examined, it is seen that not all classifiers are superior to each other in terms of accuracy. However, while Linear SVM and Quadratic SVM classifiers are more successful in terms of sensitivity and F1 score, it is seen that the Coarse Gaussian SVM classifier is better in terms of specificity, precision, and MCC.
Examining the adaptability and validity of interRAI acute care quality indicators in a surgical context

Background: Currently, the use of quality indicators in the surgical setting may be challenged by diverse patient needs, clinical complexity, and health trajectories. Therefore, the objective of this study was to examine the adaptability of existing quality indicators to a surgical context and propose new time points. Methods: A multi-method approach included an environmental scan of the literature, consultation with multinational experts, and analysis of surgical patient data. Quality indicators from the nurse-administered interRAI Acute Care instrument were examined within a surgical context using secondary data from a hospital in Brisbane, Australia (N = 1006 surgical cases). Results: A lack of relevancy of existing time points can preclude meaningful quality indicator measurement. Definitions of some quality indicators were adapted to ensure relevancy for the surgical population. As well, a surgical baseline (measured preoperative and post-injury) and a 48-h postoperative time point were added to the existing measurement timeline. Conclusion: Distinct measurement timelines were created for elective and non-elective surgical patients. The use of surgery-specific time points that can be embedded into an existing Acute Care measurement framework supports consistent quality indicator reporting. This study represents the first steps towards standardized quality reporting for health information systems across different care settings.
Intestinal Epithelial Cells Modulate the Production of Enterotoxins by Porcine Enterotoxigenic E. coli Strains

Enterotoxigenic Escherichia coli (ETEC) strains are one of the most common etiological agents of diarrhea in both human and farm animals. In addition to encoding toxins that cause diarrhea, ETEC have evolved numerous strategies to interfere with host defenses. These strategies most likely depend on the sensing of host factors, such as molecules secreted by gut epithelial cells. The present study tested whether the exposure of ETEC to factors secreted by polarized IPEC-J2 cells resulted in transcriptional changes of ETEC-derived virulence factors. Following the addition of host-derived epithelial factors, genes encoding enterotoxins, secretion-system-associated proteins, and the key regulatory molecule cyclic AMP (cAMP) receptor protein (CRP) were substantially modulated, suggesting that ETEC recognize and respond to factors produced by gut epithelial cells. To determine whether these factors were heat sensitive, the IEC-conditioned medium was incubated at 56 °C for 30 min. In most ETEC strains, heat treatment of the IEC-conditioned medium resulted in a loss of transcriptional modulation. Taken together, these data suggest that secreted epithelial factors play a role in bacterial pathogenesis by modulating the transcription of genes encoding key ETEC virulence factors. Further research is warranted to identify these secreted epithelial factors and how ETEC sense these molecules to gain a competitive advantage in the early engagement of the gut epithelium.
Premenstrual Syndrome and Its Association with Perceived Stress: The Experience of Medical Students in Jordan

Objective To assess the prevalence of premenstrual and menstrual symptoms and to investigate premenstrual severity’s association with perceived stress of premenstrual syndrome among medical students. Methods This is a cross-sectional study. Data were collected between March and April 2021, a self-administered online questionnaire (Supplementary Material) was distributed to a sample of female medical students in Jordan (n=594). Results The mean age was 21.6 ±2.2 years, and the mean body mass index (BMI) was 22.8 ±4.1 kg/m2. Most students were in their 5th and 6th university year, where 75.4% reported having dysmenorrhea, 45.8% used pharmacological agents for pain relief, while 54.2% used non-pharmacological means, and 58.1% occasionally skipped lectures. Most participants reported a constellation of physical and psychological symptoms. The mean for the premenstrual severity scale score was 29.3, and the mean for the perceived stress scale scores was 21.6. There was a statistically significant correlation between the premenstrual severity scale score and the perceived stress scale, between the premenstrual severity scale and absenteeism, between premenstrual severity scale and year of study, and between dysmenorrhea and the perceived stress scale, but not between the severity of symptoms and method of pain relief. Conclusion Premenstrual and menstrual symptoms have a negative impact on students that affects their academic participation. More support should be given from universities to address the menstruation-related struggles of female students.
Bootstrap Methods in Statistics Resampling

Several areas of science have 'bootstrap methods' They arise, for example, as techniques for numerical solution of differential equations. Often the name conveys the impression of getting something for nothing, like pulling oneself up by one's bootstraps. Thus, a bootstrap method attempts to solve a problem without, on the surface, appearing to bring adequate information or expertise to bear on it.
Income polarization in European countries and Europe wide, Cambridge

Polarization is an interesting additional social indicator for analyzing income distribution across countries, as it captures the phenomenon of ‘clustering around extreme poles’. Income polarization can be closely linked to social exclusion, which is relevant for EU social policy, because combatting social exclusion is a central element of the Lisbon Agenda and the Europe 2020 Strategy. Rising income polarization has been observed outside Europe, but within the EU, polarization is relatively unexplored. This paper provides theoretical insights into this relatively new dimension of income distribution and analyzes trends in income polarization in 28 EU countries and 3 non-EU countries, using micro-data from EU-SILC over the period 2004-2012. Income polarization is rather stable over this period in European countries, and Europe-wide. It was rising among the old EU15 countries in the sub-period 2004-2008, but declining afterwards. The opposite development is witnessed for New Member States. Despite the Great Recession we find quite stable income polarization in Europe.
The Role of Business Analytics for Competitive Advantage of Small and Medium Enterprises

Small and Medium Enterprises (SMEs) are locomotives of economic development. They constitute an important proportion of enterprises globally, including in Australia. Hence, the Australian government recognises the importance of enabling the competitiveness of SMEs as a driving force of the economy of Australia. In recent years, there has been a rapid expansion of technological resources which are essential in enabling competitive advantage for SMEs. One type of technical resource that has gained increasing importance over the last decade is Business Analytics (BA). Research into BA, predominantly in the context of large organisations, has shown how BA contributes to business value and business performance. However, there’s a lack of understanding of the role BA resources can play in obtaining competitive advantage in the SME context. By employing Resource-Based View (RBV) as theoretical underpinning, this research explores this gap and aims to provide a richer understanding of the role of BA capabilities and BA assets in enabling SMEs to create competitive advantage as well as an insight into how SMEs utilise BA resources to that end.
The implications of highly associated face and object recognition impairments for the cognitive architecture

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Explicit Import Revisited: A Critical Appraisal of Explicatures

The main goal of this paper is to argue that the way explicitly communicated content is approached in leading pragmatic theories is flawed, since it is posited that explicature generation involves pragmatic enrichment of the decoded logical form of the utterance to full propositionality. This kind of enhancement postulated to underlie explicature generation appears to be theoretically inadequate and not to correspond to the psychological reality of utterance interpretation. Drawing on earlier critique of extant pragmatic positions on explicatures, mainly by Borg (2016) and Jary (2016), I add further arguments against modelling explicitly communicated import in the way leading verbal communication frameworks do. It is emphasized that the cognitively plausible theory of communicated meaning is compromised at the cost of theory-internal concerns.
Routine cognitive screening in older patients admitted to acute medicine: abbreviated mental test score (AMTS) and subjective memory complaint versus Montreal Cognitive Assessment and IQCODE

Introduction: routine cognitive screening for in-patients aged ≥75 years is recommended, but there is uncertainty around how this should be operationalised. We therefore determined the feasibility and reliability of the Abbreviated mental test score (AMTS/10) and its relationship to subjective memory complaint, Montreal Cognitive Assessment (MoCA/30) and informant report in unselected older admissions. Methods: consecutive acute general medicine patients aged ≥75 years admitted over 10 weeks (March–May 2013) had AMTS and a question regarding subjective memory complaint (if no known dementia/delirium). At ≥72 h, the 30-point Montreal Cognitive Assessment (MoCA) and Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) were done. Cognitive impairment was defined as AMTS < 9 or MoCA < 26 (mild impairment) and MoCA < 20 (moderate/severe impairment) or IQCODE≥ 3.6. Results: among 264 patients (mean age/SD = 84.3/5.6 years, 117 (44%) male), 228 (86%) were testable with AMTS. 49/50 (98%) testable patients with dementia/delirium had low AMTS compared with 79/199 (44%) of those without (P < 0.001). Subjective memory complaint agreed poorly with objective cognitive deficit (39% denying a memory problem had AMTS < 9 (kappa = 0.134, P= 0.086)) as did informant report (kappa = 0.18, P = 0.15). In contrast, correlation between AMTS and MoCAwas strong (R = 0.59, P< 0.001) with good agreement between AMTS < 9 and MoCA < 20 (kappa = 0.50, P < 0.01), although 85% of patients with normal AMTS had MoCA < 26. Conclusions: the AMTS was feasible and valid in older acute medicine patients agreeing well with the MoCA albeit with a ceiling effect. Objective cognitive deficits were prevalent in patients without known dementia or delirium but were not reliably identified by subjective cognitive complaint or informant report.
Resonances hindering of low frequency phonons in nanophononic metamaterials with ultra-low thermal conductivity

Understanding the design rules to obtain materials that enable a tight control of phonon transport over a broad range of frequencies would aid major developments in thermoelectric energy harvesting, heat management in microelectronics and information and communication technology. Using atomistic simulations we show that the metamaterials approach relying on localized resonances is very promising to engineer heat transport at the nanoscale. Combining designed resonant structures to alloying can lead to extremely low thermal conductivity in silicon nanowires. The hybridization between resonant phonons and propagating modes greatly reduces the group velocities and the phonon mean free paths in the low frequency acoustic range below 4 THz. Concurrently alloy scattering hinders the propagation of high frequency thermal phonons. Our calculations establish a rationale between the size, shape and period of the resonant structures, and the thermal conductivity of the nanowire, and demonstrate that this approach is even e ↵ ective to block phonon transport in wavelengths much longer than the size and period of the surface resonant structures. A further consequence of using resonant structures is that they are not expected to scatter electrons, which is beneﬁcial for thermoelectric applications.
ReviewGenome Maintenance by DNA Helicase BLindsey Hazeslip 1

DNA Helicase B (HELB) is a conserved helicase in higher eukaryotes with roles in the initiation of DNA replication and in the DNA damage and replication stress responses. HELB is a predominately nuclear protein in G1 phase where it is involved in initiation of DNA replication through interactions with DNA topoisomerase 2-binding protein 1 (TOPBP1), cell division control protein 45 (CDC45), and DNA polymerase α-primase. HELB also inhibits homologous recombination by reducing long-range end resection. After phosphorylation by cyclin-dependent kinase 2 (CDK2) at the G1 to S transition, HELB is predominately localized to the cytosol. However, this cytosolic localization in S phase is not exclusive. HELB has been reported to localize to chromatin in response to replication stress and to localize to the common fragile sites 16D (FRA16D) and 3B (FRA3B) and the rare fragile site XA (FRAXA) in S phase. In addition, HELB is phosphorylated in response to ionizing radiation and has been shown to localize to chromatin in response to various types of DNA damage, suggesting it has a role in the DNA damage response.