Miracle-dz/UniFAR-FTUs huggingface dataset:
FROM BREAST PUMP TO BEST PUMP: A HUMAN-CENTERED EVALUATION

Mothers can experience breastfeeding challenges, and the breast pump is often at the center. Existing literature outlines the range of mothers’ negative experiences with breast pumps, though there is a gap in which breast pump characteristics are important to mothers. Identifying which breast pump characteristics (i.e., portability, ease of use, low-weight, fast milk extraction, comfortability, low-noise, discreet) are important to breast pumping mothers, and whether or not this importance varies between mothers who do or do not work outside of the home will help identify user needs. Collecting user needs informs future breast pump designs in a user-centered design process. A survey collected information on mothers’ experiences with breast pumps and which breast pump characteristics mothers considered important. Summary statistics were analyzed for mothers who did and did not work outside the home, and Latent Class Analysis (LCA) was used to determine whether there were possible groupings between the importance of these characteristics. Summary statistics indicated that mothers considered all seven breast pump characteristics important except for discreet. The only characteristic found as statistically significantly different between mothers of different work statuses was portability. LCA identified a twoclass model with mothers’ age as a significant covariate. Mothers’ work status was not a significant covariate but did predict class membership when considered as a grouping variable in conjunction with mothers’ age. Breast pumping mothers’ needs differ beyond their work status, and collecting and considering these different needs is vital to creating redesigns that improve mothers’ breast pumping experience.
Word senses in information retrieval

Information retrieval (IR) often ignores word senses in document relevance calculations. This is largely due to the fact that word sense disambiguation is not an easy task. However, in IR some of the strictest requirements of traditional approach to detailed disambiguation can be relaxed. This paper discusses a successfully implemented approach to using word senses in IR tasks, which can be combined with various IR methods. Mirva Salminen mirva.salminen@helsinki.fi University of Helsinki Department of Computer Science Research Seminar on Intelligent Systems, Autumn 2004 Organizer: Petri Myllymäki Helsinki 4th November 2004
Water temperature interacts with the insecticide imidacloprid to alter acute lethal and sublethal toxicity to mayfly larvae

ABSTRACT Increased temperatures and exposure to agricultural insecticides are increasingly threatening freshwater ecosystems worldwide. However, their combined effects are still poorly understood. We investigated the individual and interactive effects of water temperature and imidacloprid, the most widely used neonicotinoid insecticide, on larvae of two New Zealand mayflies, Deleatidium spp. and Coloburiscus humeralis. Ninety-six-hour bioassays with imidacloprid were performed at 9, 12, 15, 18, 21 and 24°C, in a full-factorial design. Mayfly survivorship and sub-lethal responses of impairment and moulting were recorded. We documented synergistically increased mayfly mortality and immobility with exposure to imidacloprid at higher temperatures, implying temperature-enhanced toxicity of imidacloprid. Survivorship of both mayflies was synergistically reduced by the combination of imidacloprid exposure and increasing temperatures. The same interaction also affected mobility of C. humeralis and moulting frequency of Deleatidium. Our findings suggest that developing a more thorough understanding of temperature-contaminant interactions may be important to allow better protection of aquatic ecosystems.
Robustness of Interdependent Cyber-Physical Systems Against Cascading Failures

Integrated cyber-physical systems, such as the smart-grid, are increasingly becoming the underpinning technology for major industries. A major concern regarding such systems are the seemingly unexpected large scale failures, which are often attributed to a small initial shock getting escalated due to intricate dependencies within and across the individual (e.g., cyber and physical) counterparts of the system. In this paper, we develop a novel interdependent system model to capture this phenomenon, also known as cascading failures. Our framework consists of two networks that have inherently different characteristics governing their intradependence: first, a cyber-network where a node is deemed to be functional as long as it belongs to the largest connected (i.e., giant) component; and, second, a physical network where nodes are given an initial flow and a capacity, and failure of a node results with redistribution of its flow to the remaining nodes, upon which further failures might take place due to overloading (i.e., the flow of a node exceeding its capacity). Furthermore, it is assumed that these two networks are interdependent. For simplicity, we consider a one-to-one interdependence model where every node in the cyber-network is dependent upon and supports a single node in the physical network, and vice versa. We provide a thorough analysis of the dynamics of cascading failures in this interdependent system initiated with a random attack. The system robustness is quantified as the surviving fraction of nodes at the end of cascading failures, and is derived in terms of all network parameters involved (e.g., degree distribution, load/capacity distribution, failure size, etc.). Analytic results are supported through an extensive numerical study. Among other things, these results demonstrate the ability of our model to capture the unexpected nature of large-scale failures, and provide insights on improving system robustness.
Early Enteral Nutrition in Patients Undergoing Sustained Neuromuscular Blockade: A Propensity-Matched Analysis Using a Nationwide Inpatient Database.

OBJECTIVES Whether enteral nutrition should be postponed in patients undergoing sustained treatment with neuromuscular blocking agents remains unclear. We evaluated the association between enteral nutrition initiated within 2 days of sustained neuromuscular blocking agent treatment and in-hospital mortality. DESIGN Retrospective administrative database study from July 2010 to March 2016. SETTING More than 1,200 acute care hospitals covering approximately 90% of all tertiary-care emergency hospitals in Japan. PATIENTS Mechanically ventilated patients, who had undergone sustained treatment with neuromuscular blocking agents in an ICU, were retrospectively reviewed. We defined patients who received sustained treatment with neuromuscular blocking agents as those who received either rocuronium at greater than or equal to 250 mg/d or vecuronium at greater than or equal to 50 mg/d for at least 2 consecutive days. INTERVENTIONS Enteral nutrition started within 2 days from the initiation of neuromuscular blocking agents (defined as early enteral nutrition). MEASUREMENTS AND MAIN RESULTS We identified 2,340 eligible patients during the 69-month study period. Of these, 378 patients (16%) had received early enteral nutrition. One-to-three propensity score matching created 374-1,122 pairs. The in-hospital mortality rate was significantly lower in the early than late enteral nutrition group (risk difference, -6.3%; 95% CI, -11.7% to -0.9%). There was no significant difference in the rate of hospital pneumonia between the two groups (risk difference, 2.8%; 95% CI, -2.7% to 8.3%). Length of hospital stay among survivors was significantly shorter in the early compared with the late enteral nutrition group (risk difference, -11.4 d; 95% CI, -19.1 to -3.7 d). There was no significant difference between the two groups in length of ICU stay or length of mechanical ventilation among survivors. CONCLUSIONS According to this retrospective database study, early enteral nutrition may be associated with lower in-hospital mortality with no increase in-hospital pneumonia in patients undergoing sustained treatment with neuromuscular blocking agents.
UMA EVIDÊNCIA EXPERIMENTAL DO CONCEITO DE REPRESENTAÇÃO PROFISSIONAL ATRAVÉS DO ESTUDO DA REPRESENTAÇÃO DO GRUPO IDEAL

Este artigo apresenta uma evidencia experimental da nocao de representacao profissional. Apos descrever essa categoria particular de representacoes sociais e os interesses que ela representa no dominio da educacao, descrevem-se dois protocolos experimentais inscritos no âmbito da teoria estrutural que permitem a identificacao de diferencas entre as representacoes sociais e representacoes profissionais. Estes protocolos sao baseados na tecnica de “por em questao”, e centram-se na representacao do grupo ideal. Eles foram submetidos a 1.001 alunos da licenciatura de Ciencias da Educacao da Universidade de Toulouse-Le Mirail (296 para o primeiro e 705 para o segundo). Os resultados mostram diferencas na composicao do sistema central da representacao no contexto em que o objeto e pensado (social versus profissional). Eles tambem salientaram o carater muito estavel ao longo do tempo no nucleo central das representacoes e a necessidade de uma contextualizacao dos objetos no estudo da insercao social e profissional.
Can no-lose targets contribute to a 2°C target?

The contribution that no-lose target schemes for non-Annex I (NAI) countries could make to achieve the 2°C target is explored by accounting for the incentives of 18 NAI countries’ participation in no-lose target schemes. Using various scenarios, it is shown that implementing uniform no-lose targets as part of the burden-sharing will not lead to global emissions levels compatible with the 2°C target, because uniform no-lose targets will only be beneficial to a few NAI countries. Employing more lenient uniform no-lose targets or individual no-lose targets for large emitters could increase participation by NAI countries and decrease global emissions, global compliance costs, rents by NAI countries, and compliance costs for Annex I (AI) countries. However, the resulting global emissions levels will not be compatible with attaining the 2°C target. Achieving this target will require more stringent emissions targets for AI countries and more lenient no-lose targets for NAI countries. As such, no-lose targets should account for 20% to 47% of global emissions reductions, while due to emissions trading around two-thirds of global emissions reductions should be realized in NAI countries. Indeed, an effective solution may only require no-lose targets for five to seven of the largest NAI countries. Policy relevance No-lose targets are one of a number of instruments discussed under the United Nations Framework Convention on Climate Change New Market Mechanism to integrate NAI countries in global emissions reduction efforts. In contrast to binding reduction targets, which apply penalties if a target is not met, no-lose targets provide incentives for meeting a target, e.g. in the form of excess emissions certificates that can be sold on the global carbon market. The presented simulations show that no-lose targets can result in contributions from NAI countries to global emissions reduction efforts. However, the simulations also show that the necessary incentives for no-lose targets need to be adjusted. AI countries require more ambitious targets and NAI countries require less ambitious no-lose targets than proposed by the Intergovernmental Panel on Climate Change report. Effective no-lose targets may only be required for five to seven of the largest NAI countries.
Inadequate health literacy on childhood immunization and its predictors among antenatal mothers

Introduction: Outbreak of vaccine preventable disease still persists despite good coverage of immunization in Malaysia. Health literacy on childhood immunization is one of essential factor for the outbreak to happen. Thus, this study determined the predictors of health literacy on childhood immunization among antenatal mother in Seremban, Negeri Sembilan. Methodology: A cross sectional study was conducted among 424 antenatal women using a cluster sampling approach. Antenatal women who were Malaysian and not illiterate were chosen in this study. A selfadministered, validated and pretested questionnaire was used to collect data on sociodemographic, socio economic, awareness on immunization, utilization of health care services and health literacy on childhood immunization. The data was analyzed using SPSS version 22.0. Chi Square test was used in bivariate analysis and multiple logistic regression was used to determine the predictors of inadequate health literacy on childhood immunization. Result: Out of 362 respondents, 81.2% were inadequate health literacy. The predictors were maternal education (AOR= 2.608, 95% CI 1.477-4.604), parity (AOR= 1.067, 95% CI 1.103-3.876), residential area (AOR= 2.344, 95% CI 1.184-4.641) and utilization of government hospital (AOR= 2.344, 95% CI 1.184-4.641). Conclusion: Accessibility of health education with regard to immunization need to be strengthen among primigravida, low education and those staying in rural area. In addition, health education also needs to emphasize on the individual that is employed and low economic status with underutilization of government hospital. A simplified education material with interesting pictures and using visual aids help illiterate people for better understanding.
Tidal Type Determination on Manokwari Shipping Chanel by Using Admiralty Method

Komponen pasang surut perairan sangat penting bagi kepentingan pelabuhan, transportasi laut, industri perikanan, rekayasa pantai dan mitigasi kawasan pesisir. Ketinggian pasang surut yang terbentuk merupakan superposisi dari amplitudo komponen pasang surut akibat gaya tarik gravitasi matahari, bulan dan bumi terhadap massa air lautan. Komponen pasang surut yaitu K1, O1, P1, S2, M2, K2, M4, MS4. Penelitian ini bertujuan menentukan komponen dan tipe pasang surut pada alur pelayaran Manokwari-Papua Barat menggunakan metode admiralty. Bilangan Formzahl yang diperoleh yaitu 0.732 yang berarti bahwa perairan memiliki pasang surut Campuran Condong ke Harian Ganda (mixed tide prevailing semidiurnal) yang berarti bahwa pasang surut yang terbentuk terjadi dua kali pasang dan dua kali surut dalam sehari dan antara pasang pertama dan pasang kedua memiliki ketinggian hampir sama dan kadang terjadi dua kali pasang dan satu kali surut atau sebaliknya dua kali surut satu kali pasang dalam sehari. Perubahan kedudukan air rata-rata MSL berbeda-beda disebabkan selain kondisi perairan baik garis pantai dan batimetri adalah akibat gaya gravitasi bulan dan matahari terhadap bumi. Tinggi muka laut rata-rata (Mean Sea Level) diperoleh 98 cm. Kisaran pasut besar terjadi pada kondisi purnama dan pasang surut rendah terjadi pada kondisi perbani. Level permukaan laut pada kondisi air pasang rata-rata (Mean High Water Level) amplitudo mencapai 279 cm dan pada kondisi air surut rata-rta (Mean Low Water Level) mencapai amplitudo -83 cm.
Framing overtourism: a critical news media analysis

ABSTRACT To better comprehend how the news media frames modern overtourism, content analysis was conducted on 202 news articles. Results suggest that root causes of overtourism are largely overlooked and the focus is on reporting tourist numbers and impacts on local. The growth agenda continues to be promoted in the backdrop of overtourism news, while responsibilities to mitigate negative impacts are attributed to cities, communities and tourists. There is a need to explore responsibilities of diverse tourism actors in addressing overtourism, along with discussions on alternatives to the pro-growth paradigm and the industrial work-home-travel model that fuel modern mass tourism.
Neural field modelling

The tools of dynamical systems theory are having an increasing impact on our understanding of patterns of neural activity. In these five lectures I will describe how to build tractable tissue level models that maintain a strong link with biophysical reality. These models typically take the form of nonlinear integro-differential equations. Their non-local nature has led to the development of a set of analytical and numerical tools for the study of spatio-temporal patterns, based around natural extensions of those used for local differential equation models. I present an overview of these techniques, covering Turing instability analysis, amplitude equations, and travelling waves in both homogeneous and heterogeneous models. The last lecture discusses the spiking Lighthouse model of Haken, and advocates this as a tractable model that may allow for the development of an exactly soluble neurodynamics that goes beyond the standard mean field approach. Lecture 1: Tissue level firing rate models with axo-dendritic connections I – Turing instability analysis Lecture 2: Tissue level firing rate models with axo-dendritic connections II – Amplitude equations – Brain wave equations Lecture 3: Travelling waves and localised states – Construction and stability (Evans functions) – Interface dynamics Lecture 4: Waves in random neural media Lecture 5: Tissue level spiking models: the dynamics of the continuum Lighthouse model
Measuring rice farmers’ risk perceptions and attitude: Evidence from Pakistan

Abstract The agriculture sector is confronting numerous types of risk. Like other crops’ farmers, rice growers are also facing multifarious challenges, including production and environmental risk. On the one hand, they are suffering from water shortage. On the other hand, if a flood occurs, there is no proper water reservation management, especially in developing countries. Global warming is another erotic topic for agriculture sustainability. To address the growers’ perceptions and their attitudes toward such types of risks, a farm base survey was carried out, and rice farmers were investigated in Pakistan. Methods of equally likely certainty equivalent and risk matrix were applied to investigate the farmers’ risk perceptions and attitude. A probit model was also used to estimate the factors that influence farmers’ perceptions and attitudes toward risks. The outcomes of the study show that flood, input high prices, increasing temperature, and crop diseases are the perceiving risks among rice farmers. Different types of socio-economic factors are influencing farmers’ risk perceptions and their attitudes, such as age, education level, a distance of farms from rivers, and non-farm income. This study provides valuable information to the policymakers and concerning authorities to apprehend agricultural risks among rice farmers and farming sustainability, especially in developing countries.
Perceptions of Educational Stakeholders Regarding the Effects of Financial Mismanagement on Physical Facilities in Secondary Schools In Gucha District, Kenya

The government of Kenya allocates between 35 to 40 percent of the total budget to education. It is essential that public funds be directed effectively and used for the purposes for which they are allocated for. This study was therefore set to establish the perceptions of stakeholders on the effect of financial mismanagement on physical facilities in public secondary schools in Gucha district. The study employed a descriptive survey design. The study population consisted of 126 headteachers, 126 heads of departments, 126 Board of governors‟ chairpersons, 126 bursars, 1011 teachers, and 10 quality assurance officers. Stratified random sampling technique was used to select 5 boarding schools, 37 day schools, 42 headteachers, 42 Bursars, 42 heads of departments, 42 BOG chairpersons, 337 teachers while purposive sampling was used to select 10 quality assurance and standards officers. Data was collected by the use of questionnaire, interviews schedule, Focus group discussions and observation forms. Data collected were analyzed using both Quantitative and qualitative methods. The study established that financial mismanagement had adversely affected physical facilities. From the study it was concluded that mismanagement had affected the quality of education negatively. Based on the findings of the study it therefore emerged the need for financial training for all stakeholders involved in financial management directly and indirectly.
Applications of Nanofluids for the Thermal Enhancement in Radiative and Dissipative Flow over a Wedge

The colloidal analysis for H2O and EG (Ethylene Glycol) by considering the influence of radiative heat flux and viscous dissipation is not performed so far. This study is performed to fill up this gap. Therefore, the flow of water and ethylene glycol functionalized magnetite nanoparticles over a moving wedge is examined. For thermal enhancement, two different magnetite nanoparticles, namely CoFe 2 O 4 (Cobalt ferrite) and Mn − ZnFe 2 O 4 ( Mn − Zn ferrite), diluted in the base fluids. Self-similar flow model of a nonlinear nature, containing the volume fraction of nanoparticles is obtained by using compatible similarity variables. For mathematical treatment of the model, the Runge-Kutta scheme is utilized, coupled with shooting techniques. The results for flow characteristics and significant physical parameters are graphically examined. A comprehensive comparative analysis has been made, which proved the reliability of the study.
Evolutionary Learning of Boosted Features for Visual Inspection Automation

Evolutionary Learning of Boosted Features for Visual Inspection Automation Meng Zhang Department of Electrical and Computer Engineering, BYU Doctor of Philosophy Feature extraction is one of the major challenges in object recognition. Features that are extracted from one type of objects cannot always be used directly for a different type of objects, therefore limiting the performance of feature extraction. Having an automatic feature learning algorithm could be a big advantage for an object recognition algorithm. This research first introduces several improvements on a fully automatic feature construction method called Evolution COnstructed Feature (ECO-Feature). These improvements are developed to construct more robust features and make the training process more efficient than the original version. The main weakness of the original ECO-Feature algorithm is that it is designed only for binary classification and cannot be directly applied to multi-class cases. We also observe that the recognition performance depends heavily on the size of the feature pool from which features can be selected and the ability of selecting the best features. For these reasons, we have developed an enhanced evolutionary learning method for multi-class object classification to address these challenges. Our method is called Evolutionary Learning of Boosted Features (ECO-Boost). ECO-Boost method is an efficient evolutionary learning algorithm developed to automatically construct highly discriminative image features from the training image for multi-class image classification. This unique method constructs image features that are often overlooked by humans, and is robust to minor image distortion and geometric transformations. We evaluate this algorithm with a few visual inspection datasets including specialty crops, fruits and road surface conditions. Results from extensive experiments confirm that ECO-Boost performs closely comparable to other methods and achieves a good balance between accuracy and simplicity for real-time multi-class object classification applications. It is a hardware-friendly algorithm that can be optimized for hardware implementation in an FPGA for real-time embedded visual inspection applications.