Hasil untuk "Information resources (General)"

M. Sarter, J. Bruno

E. Nuwaysir, M. Bittner, J. Trent et al.

Anaylen Beatriz López Velasquez, Albino Goncalves de Sousa

The main objective of the study is to evaluate the impact of Artificial Intelligence (AI) Chatbots on the efficiency and quality of service management at Fundación Divino Niño. The study is qualitative and uses a field research design. It also focuses on describing the indicators of service management in this health institution, after having previously evaluated the AI Chatbots platforms and selected the one that best suits the needs of patient information requests considering the technical criteria. The results indicate that the implementation of AI Chatbots significantly improved efficiency in service management, response times were reduced by 40%, and user satisfaction increased by 25%. In addition, a decrease in operational costs was observed due to the automation of repetitive tasks by the people in charge of attending patients through WhatsApp and Social Media channels. User satisfaction increased notably and they provide a more satisfactory and personalized customer service experience, achieving a reduction in operating costs, freeing up resources that can be allocated to other critical areas of the Fundación Divino Niño. Finally, the impact has a significant impact by offering a sustainable and scalable solution for service management, which is especially beneficial for non-profit organizations.

Chuanhui Shan, Xinlong Geng, Chao Han

Extracting and detecting road network consistency from high-resolution remote sensing images has been a hot and difficult problem in the computer vision. Although it has made significant progress, there is still a phenomenon of high training accuracy but unsatisfactory actual extraction and detection results. The attention mechanism is one of the efficient and practical mechanisms in deep learning. It improves the performance of deep learning by selectively focusing on a portion of all information while ignoring other visible information, while effectively utilizing computing resources. Numerous experiments have also confirmed that the attention mechanism is resource-saving and effective. Its plug and play feature brings great convenience to programmers. In order to provide better road network detection results and solve the above problem, this paper combines the channel attention mechanism with ResNet and proposes SE-ResNet and ECA-ResNet for remote sensing image road network detection, making networks extract and learn road network features and ignore some non-road network features. The experimental results show that on the Massachusetts roads (MR) and CHN6-CUG roads datasets, ECA-ResNet and SE-ResNet based on channel attention mechanism perform similar to LeNet7 and ResNet in terms of accuracy, loss, accuracy convergence, and loss convergence, and even increase a certain computational burden. However, their final road network detection results (including road network detection pixel count, precision, recall, accuracy, IOU, F1 score, and actual road network detection result) of the former are significantly better than those of the latter. The channel attention mechanism makes the deep neural network pay more attention to the extraction and learning of road network features, while ignoring the extraction and learning of some non-road network features, which improves the accuracy of containing road network samples and reduces the accuracy of not containing road network samples. Therefore, the performance of ECA-ResNet and SE-ResNet is similar to that of LeNet7 and ResNet in the accuracy, loss, accuracy convergence and loss convergence, but the final road network detection results of ECA-ResNet and SE-ResNet are significantly better than those of LeNet7 and ResNet. Therefore, the proposed ECA-ResNet and SE-ResNet have broad application prospects in road network detection, especially ECA-ResNet.

Lesego Senjoba, Hajime Ikeda, Hisatoshi Toriya et al.

This study introduces a novel method for analyzing vibration data related to drill bit failure. Our approach combines explainable artificial intelligence (XAI) with convolutional neural networks (CNNs). Conventional signal analysis methods, such as fast Fourier transform (FFT) and wavelet transform (WT), require extensive knowledge of drilling equipment specifications, which limits their adaptability to different conditions. In contrast, our method leverages XAI algorithms applied to CNNs to directly identify fault signatures from vibration signals. The signals are transformed into their frequency components and then employed as inputs to a CNN model, which is trained to detect patterns indicative of drill bit failure. XAI algorithms are then employed to generate attention maps, highlighting regions of interest in the CNN. By scrutinizing these maps, engineers can identify critical frequencies associated with drill bit failure, providing valuable insights for maintenance and optimization. This method offers a transparent and interpretable framework for analyzing vibration data, enabling informed decision-making and proactive maintenance strategies to enhance drilling efficiency and minimize downtime. The integration of XAI with CNNs facilitates a deeper understanding of the root causes of drill bit failure and improves overall drilling performance.

Emilie Regina Algenio

Coaching Copyright is a welcome addition to the body of literature focusing on copyright educators who are, by extension, coaches. The book follows a logical order, starting with the title topic, offering a framework to address issues, and then positioning this framework within an instructional context. The next chapters cover ways to connect with your audience, succeeded by employing the framework for particular audiences and topics, and ending with a report about a Library Science course. This publication concentrates on the people who teach copyright within academic libraries in the United States. The target audience is wide, regardless of formal job positions, and its utility stretches far beyond the core subject. Keywords: copyright, instruction, coaching, education, teaching, copyright education, higher education

R. Zon, E. Kennedy, K. Adelson et al.

PURPOSE To provide standards and practice recommendations specific to telehealth in oncology. METHODS A systematic review of the literature on telehealth in oncology was performed, including the use of technologies and telecommunications systems, and other electronic methods of care delivery and sharing of information with patients. The evidence base was combined with the opinion of the ASCO Telehealth Expert Panel to develop telehealth standards and guidance. Public comments were solicited and considered in preparation of the final manuscript. RESULTS The Expert Panel determined that general guidance on implementing telehealth across general and specialty settings has been published previously and these resources are endorsed. A systematic search for studies on topics specific to oncology resulted in the inclusion of two clinical practice guidelines, 12 systematic reviews, and six primary studies. STANDARDS AND GUIDANCE Standards and guidance are provided for which patients in oncology can be seen via telehealth, establishment of the doctor-physician relationship, role of allied health professionals, role of advanced practice providers, multidisciplinary cancer conferences, and teletrials in oncology. Additional information is available at www.asco.org/standards.

P. Barrouillet, V. Camos

The time-based resource-sharing model considers working memory as the workspace in which mental representations are built, maintained, and transformed for completing goal-oriented tasks. Its main component is made of an episodic buffer and a procedural system that form an executive loop in which processing and storage share domain-general attentional resources on a temporal basis. Because working memory representations decay with time when attention is diverted, the cognitive load of a given activity is the proportion of time during which it occupies attention and prevents it from counteracting this decay through attentional refreshing. Consequently, recall in working memory tasks is an inverse function of the cognitive load of concurrent processing. Besides this system, an independent domain-specific maintenance system exists for verbal, but not visuospatial, information. Within this framework, working memory development mainly results from increasing processing speed that affects both the duration of the distraction of attention by concurrent tasks and refreshing efficiency.

Pardeep Sharma, Sandeep K. Sood, Sumeet Kaur

J. Rönnberg, M. Rudner, C. Foo et al.

Alexandru Vasile Rusu, Monica Trif, João Miguel Rocha

Food supplementation formulations refer to products that are designed to provide additional nutrients to the diet. Vitamins, dietary fibers, minerals and other functional compounds (such as antioxidants) are concentrated in dietary supplements. Specific amounts of dietary compounds are given to the body through food supplements, and these include as well so-called non-essential compounds such as secondary plant bioactive components or microbial natural products in addition to nutrients in the narrower sense. A significant social challenge represents how to moderately use the natural resources in light of the growing world population. In terms of economic production of (especially natural) bioactive molecules, ways of white biotechnology production with various microorganisms have recently been intensively explored. In the current review other relevant dietary supplements and natural substances (e.g., vitamins, amino acids, antioxidants) used in production of dietary supplements formulations and their microbial natural production via fermentative biotechnological approaches are briefly reviewed. Biotechnology plays a crucial role in optimizing fermentation conditions to maximize the yield and quality of the target compounds. Advantages of microbial production include the ability to use renewable feedstocks, high production yields, and the potential for cost-effective large-scale production. Additionally, it can be more environmentally friendly compared to chemical synthesis, as it reduces the reliance on petrochemicals and minimizes waste generation. Educating consumers about the benefits, safety, and production methods of microbial products in general is crucial. Providing clear and accurate information about the science behind microbial production can help address any concerns or misconceptions consumers may have.

M. Bacci, O.A. Idrissa, C. Zini et al.

The increasing frequency of extreme events in West Africa, such as droughts and floods, has made populations that base their subsistence mostly on rainfed agriculture even more vulnerable to climate threats. Climate Services (CS) are largely acknowledged as effective tools for tackling climate risks in agriculture, particularly in semi-arid developing countries but evidences of their effectiveness are still jeopardized. In Niger a climate service (CS) has been set up in the regions of Dosso and Tillabéri by the National Meteorological Service (NMS) to provide salient information for smallholder farmers. The CS was built on a robust collaboration among NMS, local extension services and authorities and farmers in 8 municipalities. The case study shows that a large share of farmers receives throughout the cropping season climatic information and advice via roving seminars and various media, including instant messaging services and radio broadcasts. Nevertheless, the results indicate that access to CS alone doesn’t imply relevant positive impacts on crop yields while the training of farmers in the use of the information results to be a significant factor. Indeed, in 2020, yields of trained farmers are significantly higher by around 17% compared to those of non-trained ones. Training and iterative interaction between farmers and NMS could also have indirect effects on information uptake, contributing to building reciprocal trust and therefore stronger action by trained farmers. The study confirms the importance of the social learning process in CS co-development. Since the study is limited by the small sample and the dataset covering only one cropping season, further research is needed to deepen cost-benefit analysis and disentangle the relative contribution of the CS components to yield increase. Indeed, evidences of the positive impact of CS could represent a leverage for local governments and international funders to support CS co-development and related capacity building activities. Practical implication: Climate variability and a strong increase in extreme hydro meteorological events are affecting agriculture production and exacerbating food insecurity in West Africa. In Niger, the vulnerability of agricultural production systems is coupled to ecosystem fragility and soil degradation. In this area, the rural population is the most vulnerable to climate threats because they have a reduced capability to implement effective risk reduction and climate change adaptation strategies and national government has limited resources to invest in climate policies. The CS implemented for the regions of Dosso and Tillabéri in Niger demonstrates that it is possible to set up an effective network for disseminating agrometeorological information for smallholder farmers at the municipal level with the aim of reducing the impact of climate threats on agriculture production. The information produced by the National Meteorological Service (NMS) is spread through extension services and rural radios to reach farmers. At the same time the agrometeorological field data are collected by local farmers and sent to the national service, ensuring the continuous monitoring of the cropping season. Subsequently, the agrometeorological information is coupled with setting up roving seminars in each municipality to spread tailored advice for farmers concerning seasonal climate forecasts and to build capacities in the use of agrometeorological advices during the season. During these seminars, rain gauges are also distributed to farmers and their use explained. In this way, farmers become able to autonomously take some tactical decisions, such as better timing the sowing of crops or performing farming activities, basing these choices on direct observations. The present case study demonstrates that the mere receipt of the climate information is not clearly related to an increase in yields; contrariwise, farmers who received training on how to properly use the information, have significantly higher yields. Repeated capacity building and information distribution over the years represent an element of trust building for end users who are more prone to use these CS in their agricultural choices, integrating their traditional knowledge. The next challenge is to guarantee the sustainability of these networks over time, because, even if technology advances could reduce the costs of the production and distribution of climate services, the training activities and maintaining the rural observation network are challenging. A possible way to make it sustainable is to reinforce institutional collaboration. Moreover, the use of a participatory approach in co-designing the CS could be a key element in pursuing the active involvement of the local population and administrations and could increase their motivation in the data exchange process. Basing on obtained results, the authors recommend to pursue the development of tailored CS for smallholder farmers in similar rural contexts, since these services constitute a real contribution to climate change adaptation at the local level in rural areas and future experiences could ensure the fine tuning of the climate information products, reducing delivery costs and increasing benefits for stakeholders. Finally, it is also recommended to further assess the cost/benefit ratio of CS in order to leverage funds and ensure scaling up and sustainability.

Sohni Siddiqui, Anjum Bano Kazmi, Mahwish Kamran

IntroductionA community cannot avoid the frustrating problem of antisocial behavior, which consists of actions that violate traditions or standards. To deal with the antisocial behavior and aggression in children, a variety of techniques and interventions have been proposed and applied throughout the world. Teachers can overcome antisocial behavior in educational institutions through professional development programs. In Pakistan, there are few studies that focus on teachers’ professional development in behavior management, which should be investigated.MethodsA qualitative research study examined teacher professional development courses aimed at improving classroom management skills and controlling antisocial behaviors by collecting information from instructors. This approach was taken because this study aims to identify teacher educators’ experiences related to antisocial and aggression control training in the school setting. In addition, the limitations and challenges associated with such development programs are revealed through semi-structured interviews.ResultsResearchers reported major challenges related to such trainings include resistance and unwillingness of school authorities and teachers to participate in such trainings, as well as lack of resources and finances.DiscussionTo ensure that teacher training is effective and leads to the development of teacher skills and improvement of student behavior, researchers recommend implementing evidence-based intervention programs with ongoing monitoring by a trained teacher specialist. It is also recommended that curricula be standardized and in-service training results be empirically verified.

ملوک السادات حسینی بهشتی, سهیلا خوئینی, الهام اسمعیل پونکی

هدف: این پژوهش با هدف تحلیل کتاب‌سنجی و شبکه هم‌نویسندگی و خوشه‌های موضوعی پژوهش‌های هستان‌شناسی در پایگاه اطلاعاتی اسکوپوس انجام شد.روش‌شناسی: پژوهش حاضر از نوع کاربردی است که با رویکرد علم‌سنجی و با روش‌های کتابخانه‌ای، تحلیل هم‌رخدادی واژگان و تکنیک تحلیل شبکه‌ای به انجام رسیده است. جامعه آماری پژوهش را تعداد 5226 مقاله علمی حوزه هستان‌شناسی تشکیل می‌دهند که از سال 1996 تا سال 2020  منتشر شده و در پایگاه اسکوپوس نمایه شده است. برای تحلیل داده‌ها به فراخور هدف از نرم‌افزارهای Excel، VOSviewer، Pajek و UCINet استفاده شد.                      یافته‌ها: یافته‌ها حاکی از آن است که بیشترین همکاری در تولید پژوهش‌های هستان‌شناسی توسط کشورهای چین، آمریکا و بریتانیا بوده است.  Rafael Valencia-Garciaو دانشگاه Zhejiang بیشترین تولیدات علمی را در بخش نویسندگان و دانشگاه‌ها به خود اختصاص داده‌اند. حوزه علوم کامپیوتر بیشترین سهم را در تولیدات علمی داشته است.                      نتیجه‌گیری: در مطالعه شبکه هم‌واژگانی حوزه هستان‌شناسی در پایگاه اسکوپوس 5 خوشه موضوعی شناسایی شد که خوشه وب معنایی بزرگ‌ترین خوشه است.

T. Ye, A. Krebs, M. Choukrallah et al.

In a single experiment, chromatin immunoprecipitation combined with high throughput sequencing (ChIP-seq) provides genome-wide information about a given covalent histone modification or transcription factor occupancy. However, time efficient bioinformatics resources for extracting biological meaning out of these gigabyte-scale datasets are often a limiting factor for data interpretation by biologists. We created an integrated portable ChIP-seq data interpretation platform called seqMINER, with optimized performances for efficient handling of multiple genome-wide datasets. seqMINER allows comparison and integration of multiple ChIP-seq datasets and extraction of qualitative as well as quantitative information. seqMINER can handle the biological complexity of most experimental situations and proposes methods to the user for data classification according to the analysed features. In addition, through multiple graphical representations, seqMINER allows visualization and modelling of general as well as specific patterns in a given dataset. To demonstrate the efficiency of seqMINER, we have carried out a comprehensive analysis of genome-wide chromatin modification data in mouse embryonic stem cells to understand the global epigenetic landscape and its change through cellular differentiation.

J. Snider, M. Kotlyar, Punit Saraon et al.

Studying protein interaction networks of all proteins in an organism (“interactomes”) remains one of the major challenges in modern biomedicine. Such information is crucial to understanding cellular pathways and developing effective therapies for the treatment of human diseases. Over the past two decades, diverse biochemical, genetic, and cell biological methods have been developed to map interactomes. In this review, we highlight basic principles of interactome mapping. Specifically, we discuss the strengths and weaknesses of individual assays, how to select a method appropriate for the problem being studied, and provide general guidelines for carrying out the necessary follow‐up analyses. In addition, we discuss computational methods to predict, map, and visualize interactomes, and provide a summary of some of the most important interactome resources. We hope that this review serves as both a useful overview of the field and a guide to help more scientists actively employ these powerful approaches in their research.

P. Gunz, P. Mitteroecker, Simon Neubauer et al.

Jo Hughson, J. Daly, R. Woodward‐Kron et al.

Background Pregnancy apps are a booming global industry, with most pregnant women in high-income countries now using them. From the perspective of health care and health information provision, this is both encouraging and unsettling; the demand indicates a clear direction for the development of future resources, but it also underscores the importance of processes ensuring access, reliability, and quality control. Objective This review provides an overview of current literature on pregnancy apps and aims at describing (1) the ways in which apps are used by women, in general, and by those of a culturally and linguistically diverse (CALD) background; (2) the utility and quality of information provided; and (3) areas where more research, development, and oversight are needed. Methods We chose a narrative review methodology for the study and performed a structured literature search including studies published between 2012 and 2017. Searches were performed using MEDLINE, EMBASE, and CINAHL databases. Studies were identified for inclusion using two separate search criteria and strategies: (1) studies on pregnancy apps and pregnant women’s use of these apps and (2) studies on CALD pregnant women and their use of technology for accessing information on and services for pregnancy. Overall, we selected 38 studies. Results We found that pregnancy apps were principally used to access pregnancy health and fetal development information. Data storage capability, Web-based features or personalized tools, and social media features were also popular app features sought by women. Lower rates of the pregnancy app uptake were indicated among lower-income and non-English-speaking women. Preliminary evidence indicates that a combination of technological, health literacy, and language issues may result in lower uptake of pregnancy apps by these groups; however, further investigation is required. A marked limitation of the health app industry is lack of regulation in a commercially dominated field, making it difficult for users to assess the reliability of the information being presented. Health professionals and users alike indicate that given the choice, they would prefer using pregnancy apps that are relevant to their local health care context and come from a trusted source. Evidence indicates a need for greater health professional and institutional engagement in the app development, as well as awareness of and guidance for women’s use of these resources. Conclusions This is the first review of pregnancy app use, types of information provided, and features preferred by pregnant women in general and by those of a CALD background in particular. It indicates the demand for access to accurate information that is relevant to users, their community, and their associated health services. Given the popularity of pregnancy apps, such apps have enormous potential to be used for the provision of accurate, evidence-based health information.

Hongbo Yang, Thomas Dietz, Yingjie Li et al.

The transformational potential of the United Nations’ 2030 Agenda for Sustainable Development Goals (SDGs) lies in effective efforts to reconcile the conflicts and maximize the synergies among the interrelated SDGs. Previous research on the interrelationships among SDGs often focused on depicting the degree to which different goals reinforce or hamper each other; however, drivers behind these interrelationships have rarely been evaluated. We developed a novel approach to unraveling the impact of human activities on the complex trade-offs and synergies among SDGs. We used the approach to assess the impacts of four globally common livelihoods, including cropping, local off-farm labor work, labor migration, and livestock husbandry, on the interrelationships among SDG 1 (no poverty), SDG 3 (enhance human well-being), and SDG 15 (protect life on land) in a demonstration site. The results show that our approach can be very useful in informing coherent governance and facilitating progress toward SDGs across social, economic, and environmental dimensions simultaneously.

Qiang Wu, Huan Liu, Yixin Shi et al.

<i>Ganoderma</i> (Ganodermaceae) is a genus of edible and medicinal mushrooms that create a diverse set of bioactive compounds. <i>Ganoderma lingzhi</i> has been famous in China for more than 2000 years for its medicinal properties. However, the genome information of <i>G. lingzhi</i> has not been characterized. Here, we characterized its 49.15-Mb genome, encoding 13,125 predicted genes which were sequenced by the Illumina and PacBio platform. A wide spectrum of carbohydrate-active enzymes, with a total number of 519 CAZymes were identified in <i>G. lingzhi</i>. Then, the genes involved in sexual recognition and ganoderic acid (GA, key bioactive metabolite) biosynthesis were characterized. In addition, we identified and deduced the possible structures of 20 main GA constituents by UPLC-ESI-MS/MS, including a new special ganochlearic acid A. Furthermore, 3996 novel transcripts were discovered, and 9276 genes were predicted to have the possibility of alternative splicing from RNA-Seq data. The alternative splicing genes were enriched for functional categories involved in protein processing, endocytosis, and metabolic activities by KEGG. These genomic, transcriptomic, and GA constituents’ resources would enrich the toolbox for biological, genetic, and secondary metabolic pathways studies in <i>G. lingzhi</i>.