The Global Alliance for Infections in Surgery: Defining a Model for Antimicrobial Stewardship-Results From an International Cross-Sectional Survey

BACKGROUND: Antimicrobial Stewardship Programs (ASPs) have been promoted to optimize antimicrobial usage and patient outcomes, and to reduce the emergence of antimicrobial-resistant organisms. However, the best strategies for an ASP are not definitively established and are likely to vary based on local culture, policy, and routine clinical practice, and probably limited resources in middle-income countries. The aim of this study is to evaluate structures and resources of antimicrobial stewardship teams (ASTs) in surgical departments from different regions of the world. METHODS: A cross-sectional web-based survey was conducted in 2016 on 173 physicians who participated in the AGORA (Antimicrobials: A Global Alliance for Optimizing their Rational Use in Intra-Abdominal Infections) project and on 658 international experts in the fields of ASPs, infection control, and infections in surgery. RESULTS: The response rate was 19.4%. One hundred fifty-six (98.7%) participants stated their hospital had a multidisciplinary AST. The median number of physicians working inside the team was five [interquartile range 4-6]. An infectious disease specialist, a microbiologist and an infection control specialist were, respectively, present in 80.1, 76.3, and 67.9% of the ASTs. A surgeon was a component in 59.0% of cases and was significantly more likely to be present in university hospitals (89.5%, p \u3c 0.05) compared to community teaching (83.3%) and community hospitals (66.7%). Protocols for pre-operative prophylaxis and for antimicrobial treatment of surgical infections were respectively implemented in 96.2 and 82.3% of the hospitals. The majority of the surgical departments implemented both persuasive and restrictive interventions (72.8%). The most common types of interventions in surgical departments were dissemination of educational materials (62.5%), expert approval (61.0%), audit and feedback (55.1%), educational outreach (53.7%), and compulsory order forms (51.5%). CONCLUSION: The survey showed a heterogeneous organization of ASPs worldwide, demonstrating the necessity of a multidisciplinary and collaborative approach in the battle against antimicrobial resistance in surgical infections, and the importance of educational efforts towards this goal

Dynamic Wireless Information and Power Transfer Scheme for Nano-Empowered Vehicular Networks

In this paper, we investigate the wireless power transfer and energy-efficiency (EE) optimization problem for nano-centric vehicular networks operating over the terahertz band. The inbody nano-sensors harvest energy from a power station via radio-frequency signal and then use the harvested energy to transmit data to the sink node. By considering the properties of terahertz band (i.e., sensitivity to distance and frequency over the communication path), we adopt the Brownian motion model to develop a time-variant terahertz channel model and to describe the mobility of the nano-sensors. Thus, based on the channel model and energy resources, we further develop a long-term EE optimization problem. The EE optimization is further converted into a series of energy-efficient resource allocation problems over the time slots via equivalent transformation method. The resource allocation problem for each timeslot, which is formulated as a mixed integer nonlinear programming (MINLP), is solved based on the particle swarm optimization (PSO) method. In addition, a dynamic PSO-based EE optimization (DPEEO) algorithm is developed to obtain the sub-optimal solution for the EE optimization problem. By exploiting the special structure of the reformulated problem, an improved DPEEO algorithm, is presented which can handle the problem’s constraints quite well, decreases the research space, and greatly reduces the length of the convergence time. Simulation results validate the theoretical analysis of our system

Heuristic-based programable controller for efficient energy management under renewable energy sources and energy storage system in smart grid

An operative and versatile household energy management system is proposed to develop and implement demand response (DR) projects. These are under the hybrid generation of the energy storage system (ESS), photovoltaic (PV), and electric vehicles (EVs) in the smart grid (SG). Existing household energy management systems cannot offer its users a choice to ensure user comfort (UC) and not provide a sustainable solution in terms of reduced carbon emission. To tackle these problems, this research work proposes a heuristic-based programmable energy management controller (HPEMC) to manage the energy consumption in residential buildings to minimize electricity bills, reduce carbon emissions, maximize UC and reduce the peak-to-average ratio (PAR). We used our proposed hybrid genetic particle swarm optimization (HGPO) algorithm and existing algorithms like a genetic algorithm (GA), binary particle swarm optimization algorithm (BPSO), ant colony optimization (ACO), wind-driven optimization algorithm (WDO), bacterial foraging algorithm (BFA) to schedule smart appliances optimally to attain our desired objectives. In the proposed model, consumers use solar panels to produce their energy from microgrids. We also perform MATLAB simulations to validate our proposed HGPO-HPEMC (HHPEMC), and results confirm the efficiency and productivity of our proposed HPEMC based strategy. The proposed algorithm reduced the electricity cost by 25.55%, PAR by 36.98%, and carbon emission by 24.02% as compared to the case of without scheduling

Influence of proline priming on antioxidative potential and ionic distribution and its relationship with salt tolerance of wheat

Mechanisms involved in salt tolerance urge exploration and investigation of genotypic variation to assist future breeding programs. Comparative examination of ten wheat cultivars for salt tolerance and their response towards proline-seed-priming was performed. Exposure of wheat seedlings to salinity resulted in prominent reduction in root and shoot growth attributes of all cultivars. Furthermore, decrease in the chlorophyll contents was evident although this varied among cultivars. Wheat seedlings grown from proline pre-treated seeds exhibited improved photosynthetic pigments, besides this response was also cultivar and concentration dependent. Generally, salt stressed plants exhibited higher antioxidant enzyme activities. Proline priming significantly influenced antioxidant activities, however, its magnitude varied. The peroxidase activity varied among wheat cultivars that were evident from the analysis of POD activity on Native-PAGE gel. Salinity caused the accumulation of Na+ in the roots and the magnitude of Na+ translocation to the shoot was cultivar dependent. Similarly, K+ uptake and its distribution among root and shoot varied. Priming treatments affected ion distribution of Na+ and K+ but inter-cultivar variations were evident. Conclusively, all the cultivars investigated exhibited differential response to salinity and proline seed pre-treatments. However, the proline-priming mediated improvements in growth and antioxidant enzyme activities contributed to stress tolerance which partly relied on the ability of the plant to uptake sodium and its partitioning in the roots. Of the cultivars tested, Faisalabad-08 and Bhakhar-2002 were ranked as relatively salt tolerant and the cvs. AARI-10, MH-97 and Auqab-2000 as relatively salt sensitive

PENGARUH HARD FACTOR DAN SOFT FACTOR TERHADAP DISTRIBUSI SPASIAL EKONOMI KREATIF DI INDONESIA TAHUN 2016

Penelitian ini bertujuan untuk menganalisis tingkat konsentrasi distribusi spasial ekonomi kreatif dan pengaruh hard factor dan soft factor terhadap jumlah perusahaan atau usaha di sektor ekonomi kreatif di Indonesia. Variabel dependen pada penelitian ini adalah jumlah perusahaan atau usaha di subsektor industri kreatif sedangkan variabel independen yang digunakan terbagi ke dalam dua faktor yaitu hard factor dan soft factor. Hard factor terdiri dari jumlah penduduk dan Indeks Pembangunan Manusia (IPM) sedangkan soft factor terdiri dari Indeks Kota Toleran (IKT). Data yang digunakan adalah data sekunder yang didapat dari beberapa sumber. Berbeda dengan penelitian sebelumnya yang menggunakan data industri dari BPS pada tahun 2006, penelitian ini menggunakan data kolaborasi Bekraf-BPS dan data lain pada tahun 2016. Hasil analisis memberikan kesimpulan bahwa tingkat konsentrasi distribusi spasial industri kreatif di Indonesia cukup rendah atau dengan kata lain, tingkat kompetisi pasar industri kreatif cukup kompetitif. Sedangkan hasil regresi menunjukkan bahwa hard factor dan soft factor signifikan terhadap perubahan jumlah perusahaan maupun usaha di industri kreatif. Hard factor yang terdiri dari jumlah penduduk dan IPM memberikan hasil dengan pengaruh positif sedangkan soft factor yaitu IKT memberikan hasil dengan pengaruh negatif. Terdapat tujuh subsektor yang tidak signifikan pada variabel IKT. Penelitian ini menggunakan program STATA 13 untuk melakukan olah data. Hasil analisis menunjukkan bahwa persebaran ekonomi kreatif di Indonesia makin merata serta variabel jumlah penduduk, IPM dan IKT berpengaruh signifikan terhadap jumlah perusahaan atau usaha di sektor ekonomi kreatif di Indonesi

Bioactive Steroids and Saponins of the Genus Trillium

The species of the genus Trillium (Melanthiaceae alt. Trilliaceae) include perennial herbs with characteristic rhizomes mainly distributed in Asia and North America. Steroids and saponins are the main classes of phytochemicals present in these plants. This review summarizes and discusses the current knowledge on their chemistry, as well as the in vitro and in vivo studies carried out on the extracts, fractions and isolated pure compounds from the different species belonging to this genus, focusing on core biological properties, i.e., cytotoxic, antifungal and anti-inflammatory activities

Data mining of the essential causes of different types of fatal construction accidents

Accident analysis is used to discover the causes of workplace injuries and devise methods for preventing them in the future. There has been little discussion in the previous studies of the specific elements contributing to deadly construction accidents. In contrast to previous studies, this study focuses on the causes of fatal construction accidents based on management factors, unsafe site conditions, and workers' unsafe actions. The association rule mining technique identifies the hidden patterns or knowledge between the root causes of fatal construction accidents, and one hundred meaningful association rules were extracted from the two hundred and fifty-three rules generated. It was discovered that many fatal construction accidents were caused by management factors, unsafe site circumstances, and risky worker behaviors. These analyses can be used to demonstrate plausible cause-and-effect correlations, assisting in building a safer working environment in the construction sector. The study findings can be used more efficiently to design effective inspection procedures and occupational safety initiatives. Finally, the proposed method should be tested in a broader range of construction situations and scenarios to ensure that it is as accurate as possible

Breadwinners and Homemakers: Migration and Changing Conjugal Expectations in Rural Bangladesh

The literature on marriage norms and aspirations across societies largely sees the institution as static – a tool for the assertion of masculinities and subordination of women. The changing meanings of marriage and conjugality in the contemporary context of globalisation have received scant attention. Based on research in rural Bangladesh, this article questions the usefulness of notions of autonomy and dependence in understanding conjugal relations and expectations in a context of widespread migration for extended periods, especially to overseas destinations, where mutuality is crucial for social reproduction, though in clearly genderdemarcated domains

Deep learning approach for discovery of in silico drugs for combating COVID-19

Early diagnosis of pandemic diseases such as COVID-19 can prove beneficial in dealing with difficult situations and helping radiologists and other experts manage staffing more effectively. The application of deep learning techniques for genetics, microscopy, and drug discovery has created a global impact. It can enhance and speed up the process of medical research and development of vaccines, which is required for pandemics such as COVID-19. However, current drugs such as remdesivir and clinical trials of other chemical compounds have not shown many impressive results. Therefore, it can take more time to provide effective treatment or drugs. In this paper, a deep learning approach based on logistic regression, SVM, Random Forest, and QSAR modeling is suggested. QSAR modeling is done to find the drug targets with protein interaction along with the calculation of binding affinities. Then deep learning models were used for training the molecular descriptor dataset for the robust discovery of drugs and feature extraction for combating COVID-19. Results have shown more significant binding affinities (greater than -18) for many molecules that can be used to block the multiplication of SARS-CoV-2, responsible for COVID-19. [Abstract copyright: Copyright © 2021 Nishant Jha et al.

Financial crises and the attainment of the SDGs: an adjusted multidimensional poverty approach

This paper analyses the impact of financial crises on the Sustainable Development Goal of eradicating poverty. To do so, we develop an adjusted Multidimensional Poverty Framework (MPF) that includes 15 indicators that span across key poverty aspects related to income, basic needs, health, education and the environment. We then use an econometric model that allows us to examine the impact of financial crises on these indicators in 150 countries over the period 1980–2015. Our analysis produces new estimates on the impact of financial crises on poverty’s multiple social, economic and environmental aspects and equally important captures dynamic linkages between these aspects. Thus, we offer a better understanding of the potential impact of current debt dynamics on Multidimensional Poverty and demonstrate the need to move beyond the boundaries of SDG1, if we are to meet the target of eradicating poverty. Our results indicate that the current financial distress experienced by many low-income countries may reverse the progress that has been made hitherto in reducing poverty. We find that financial crises are associated with an approximately 10% increase of extreme poor in low-income countries. The impact is even stronger in some other poverty aspects. For instance, crises are associated with an average decrease of government spending in education by 17.72% in low-income countries. The dynamic linkages between most of the Multidimensional Poverty indicators, warn of a negative domino effect on a number of SDGs related to poverty, if there is a financial crisis shock. To pre-empt such a domino effect, the specific SDG target 17.4 on attaining long-term debt sustainability through coordinated policies plays a key role and requires urgent attention by the international community