Environmental science and pollution research international

Sensors (Basel, Switzerland)

Journal of the science of food and agriculture

aids care

personalized medicine

[1] Green is clean: the role of ICT in resource management.

[2] Can information and communication technology reduce CO emission? A quantile regression analysis.

[3] "Support for the supporters": a qualitative study of the use of WhatsApp by and for mentor mothers with HIV in the UK.

[4] Metrology for Agriculture and Forestry 2019

[5] International consortium for personalized medicine: an international survey about the future of personalized medicine.

[6] spazi urbani ibridi. dall'introduzione del digitale ai processi sociali nella città

[7] the problem of formation of communicative culture of individual in terms of computerization of society

[8] underdeveloped ict areas in sub-saharan africa

[9] rancang bangun perpustakaan digital politeknik negeri semarang berbasis web dengan flex framework

[10] you've got an e-message! improving healthcare professionals' communication and collaboration across the norwegian healthcare sector

[11] intelektualni kapital u digitalnoj ekonomiji / intellectual capital in digital economy

[12] funcionalidad de juegos de estrategia virtuales y del software cabri-géomètre ii en el aprendizaje de la simetría en secundaria

[13] comparison of gender relation to information and communication technologies at the to berg faculty

[14] quelle(s) considération(s) pour l’éthique dans l’usage des technologies d’information et de communication en relations publiques / which consideration(s) for ethics within the use of information and communication technologies by public relations

[15] the use of new technology in teaching geography in the ehea. the subjects of social and economic geography, cartography and photointerpretation, and gis

[16] knowledge organisations and high-tech regional innovation systems in developing countries: evidence from argentina

[17] utilization pattern of extension tools and methods by agricultural extension agents

[18] evaluating the influence of information and communications technology on food security

[19] differentiation in access to, and the use and sharing of (open) educational resources among students and lecturers at kenyan universities

[20] competencias tic en la formación inicial docente: estudio descriptivo para la toma de decisiones en el currículum

[21] ict and romania's development towards the knowledge economy

[22] research on geography teaching and teacher education in portugal

[23] the implementation of moodle platform through lecturer’s perspectives at english department

[24] farmers’ awareness level about ict tools and services in karnataka

[25] electronic support tools for identification and management of rice weeds in africa for better-informed agricultural change agents

[26] improving lives through integrated care in scotland

[27] information technology in enterprises of the food industry

[28] detecting the visible: the discursive construction of health threats in a syndromic surveillance system design

[29] Teacher and Context Factors Associated with the Educational Use of ICT: A Costa Rican Case Study

[30] Comparing Face-to-Face, Emergency Remote Teaching and Smart Classroom: A Qualitative Exploratory Research Based on Students’ Experience during the COVID-19 Pandemic

[31] Educational Experiences on Numeracy Education using Information and Communication Technology Tools, Remedial Education Programs, and Creative Teaching Methods: A Qualitative Inquiry in Rural Areas

[32] Prediction of Agro-Morphological and Nutritional Traits in Ethiopian Mustard Leaves ( A. Braun) by Visible-Near-Infrared Spectroscopy.

[33] Predictive framework for shape-selective separations in three-dimensional zeolites and metal-organic frameworks.

[34] Preferential molecular encapsulation of an ICT fluorescence probe in the supramolecular cage of cucurbit[7]uril and β-cyclodextrin: an experimental and theoretical approach.

[35] Histopathologic Predictors of Survival and Recurrence in Resected Ampullary Adenocarcinoma: International Multicenter Cohort Study.

[36] Predicting clinical outcomes in neuroblastoma with genomic data integration.

[37] Cult, conflict and conversion: Islam in Torgrim Eggen's Hilal (1995)

[38] Theoritical contrast for hilal visibility prediction at Pelabuhan Ratu

[39] Prediction of transcription factor binding sites using genetical genomics methods.

[40] Optimization the parameter of forecasting algorithm by using the genetical algorithm toward the information systems of geography for predicting the patient of dengue fever in district of sragen, Indonesia

[41] Multiple temperature effects on phenology and body size in wild butterflies predict a complex response to climate change.

[42] Development and validation of a Weibull–Arrhenius model to predict thermal inactivation of black mustard (Brassica nigra) seeds under fluctuating temperature regimens

[43] Pharmacophores modeling in terms of prediction of theoretical physico-chemical properties and verification by experimental correlations of Carbacylamidophosphates (CAPh) and Sulfanylamidophosphates (SAPh) Tested as New Carbonic Anhydrase Inhibitors.

[44] Predicting the future manufacturing cost of batteries for plug-in vehicles for the U.S. Environmental Protection Agency (EPA) 2017-2025 Light-Duty Greenhouse Gas Standards

[45] Environmental scarcities and violent conflict: evidence from cases

[46] Assessment of implementation of the health management information system at the district level in southern Malawi.

[47] [Predictive value of myoglobin and D-dimer on severe heat stroke: a clinical analysis of 38 patients with severe heat stroke].

[48] [Predictive value of myoglobin and D-dimer on severe heat stroke: a clinical analysis of 38 patients with severe heat stroke].

[49] Highly selective reaction based colorimetric and fluorometric chemosensors for cyanide detection via ICT off in aqueous solution

[50] Prediction of irinotecan toxicity in metastatic colorectal cancer patients based on machine learning models with pharmacokinetic parameters

[51] Comparative efficacy of machine-learning models in prediction of reducing uncertainties in biosurfactant production.

[52] Building CT Radiomics-Based Models for Preoperatively Predicting Malignant Potential and Mitotic Count of Gastrointestinal Stromal Tumors.

[53] Artificial Intelligence to Predict Maximum Surface Settlements Induced by Mechanized Tunnelling

[54] Predicting the outcome of granulation and tableting processes using different artificial intelligence methods

[55] Implementing Artificial Intelligence in Predicting Metrics for Characterizing Laser Propagation in Atmospheric Turbulence

[56] Distribución geográfica de Boa constrictor occidentalis Linnaeus, 1758 (Serpentes: Boidae)

[57] Schadenfreude, malicious and benign envy are associated with low body mass index in restrictive-type anorexia nervosa.

[58] Victims of Envy.

[59] RESEARCH ON THE POSITIONING OF PROTECTION AND UTILIZATION OF HISTORIC DISTRICTS UNDER BIG DATA ANALYSIS

[60] Expert predictions of changes in vegetation condition reveal perceived risks in biodiversity offsetting.

[61] Profiling of Polar Lipids in Marine Oleaginous Diatom Fistulifera solaris JPCC DA0580: Prediction of the Potential Mechanism for Eicosapentaenoic Acid-Incorporation into Triacylglycerol

[62] Hiseq Base Molecular Characterization of Soil Microbial Community, Diversity Structure, and Predictive Functional Profiling in Continuous Cucumber Planted Soil Affected by Diverse Cropping Systems in an Intensive Greenhouse Region of Northern China.

[63] Prediction of CH <inf>4</inf> adsorption on different activated carbons by developing an optimal multilayer perceptron artificial neural network

[64] Prediction of CO <inf>2</inf> adsorption on different activated carbons by hybrid group method of data-handling networks and LSSVM

[65] A comparative assessment of predicting CH <inf>4</inf> adsorption on different activated carbons using generalized regression neural network (GRNN), and adaptive network-based fuzzy inference system (ANFIS)

[66] Comparative study of predicting hospital solid waste generation using multiple linear regression and artificial intelligence.

[67] Machine Learning Model to Predict Osteoporotic Spine with Hounsfield Units on Lumbar Computed Tomography.

[68] Like Dissolves Like? A Comprehensive Evaluation of Partial Solubility Parameters to Predict Polymer-Drug Compatibility in Ultrahigh Drug-Loaded Polymer Micelles.

[69] The role of viscous and capillary forces in the prediction of critical conditions defining super-hydrophobic and hydrophilic characteristics

[70] Total antioxidant capacity; a potential biomarker for non-invasive sex prediction in culture medium of preimplantation human embryos

[71] Predictors of Clinical Reasoning Using the Reasoning 4 Change Instrument With Physical Therapist Students.

[72] Spliceman2: a computational web server that predicts defects in pre-mRNA splicing.

[73] miRWalk: An online resource for prediction of microRNA binding sites.

[74] Development of species specific putative miRNA and its target prediction tool in wheat (Triticum aestivum L.).

[75] Machine learning techniques in disease forecasting: a case study on rice blast prediction

[76] Searching algorithm for Type IV effector proteins (S4TE) 2.0: Improved tools for Type IV effector prediction, analysis and comparison in proteobacteria.

[77] Challenges and Contradictions of Metal Nano-Particle Applications for Radio-Sensitivity Enhancement in Cancer Therapy.

[78] Features that predict the acceptability of Java and Javascript answers on stack overflow

[79] Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions

[80] Prediction of nitrate accumulation and leaching beneath groundwater irrigated corn fields in the Upper Platte basin under a future climate scenario.

[81] The role of unsaturated zone in estimating groundwater recharge in arid and semiarid areas as depicted by geochemical tracers

[82] Using (cell-free) DNA to incriminate rejection as the cause of kidney allograft dysfunction: Do we have a verdict?

[83] Ict integration in Turkey: Evaluation of english language E-content of the FATİH project

[84] Determination of indoor radon concentrations at the elementary schools of Fatih district in Istanbul

[85] Reply to: Fatih Canan "The relationship between internet addiction and eating disorders"

[86] Reducing local vulnerabilities and risks by planning decisions: The case of fati˙h district in I˙stanbul

[87] Galectin-3: A Novel Biomarker Predicts Sudden Cardiac Death in Hypertrophic Cardiomyopathy.

[88] Galectin-3 correlates with arrhythmogenic right ventricular cardiomyopathy and predicts the risk of ventricular -arrhythmias in patients with implantable defibrillators.

[89] Does Metastatic Lymph Node SUVmax Predict Survival in Patients with Esophageal Cancer?

[90] Cardiotrophin-1: A new predictor of atrial fibrillation relapses after successful cardioversion.

[91] Conflicting demands on a modern healthcare service: Can Rawlsian justice provide a guiding philosophy for the NHS and other socialized health services?

[92] Pluralism and the roots of social conflict: Rethinking Rawls

[93] Food Addiction Is Associated with Irrational Beliefs via Trait Anxiety and Emotional Eating.

[94] Historioplastic metafiction: Tarantino, nolan, and the ⇜return to hegel⇝

[95] Predicting rank for scientific research papers using supervised learning

[96] Factors that influence the implementation of patient's safety culture by ward nurses in district general hospital.

[97] Understanding the spatial diversity of social uses, dynamics, and conflicts in marine spatial planning.

[98] Inhibition activity prediction for a dataset of candidates' drug by combining fuzzy logic with MLR/ANN QSAR models.

[99] Smartphone geospatial apps for dengue control, prevention, prediction, and education: MOSapp, DISapp, and the mosquito perception index (MPI).

[100] Analysis of parameters affecting blood oxygen saturation and modeling of fuzzy logic system for inspired oxygen prediction.

[101] A feature learning approach based on XGBoost for driving assessment and risk prediction.