Perilaku Petani Terhadap Adopsi Teknologi M-Bio untuk Pengembangan Usahatani Agroforestri

This study aims to determine the behavior of farmers in adopting M-Bio technology for the development of agroforestry farming. The research method is a survey with data collection techniques: observation and in-depth interviews with respondents. Research variables include farmer behavior towards the implementation of counseling and training as well as farmer behavior towards the adoption of M-Bio Technology. The research was conducted in Setiawaras Village in the Cipigan Insan Mandiri and Dadap Sari farmer groups from July to October 2020. The data analysis used was descriptive analysis with a Likert scale with scores of 1, 2, 3, 4, and 5 then measured by weighted values. The data distribution was converted into a ratio scale with a score between 0–100. Furthermore, the scores are grouped into: (1) Very Low: 0–20; (2) Low: 21 - 40; (3) Moderate: 41–60; (4) Height: 61–80; and (5) Very High: 81-100. The results showed that the behavior of farmers towards the implementation of counseling and training on M-Bio technology with all its indicators (presentation and practice, attention, comprehensiveness, results and retention) had a score between 80 - 100 so all of them were categorized as very high. Likewise, the behavior of farmers towards the adoption of M-Bio technology for the development of agroforestry farming along with all its indicators concerning cognitive, apective, and conative aspects has a score between 80 - 100 so that all of them are also categorized as very high. Abstrak Penelitian bertujuan untuk mengetahui perilaku petani dalam adopsi teknologi M-Bio untuk pengembangan usahatani agroforestri. Metode penelitian adalah survey dengan teknik pengumpulan data : observasi dan wawancara mendalam dengan responden. Varibel penelitian mencakup perilaku petani terhadap pelaksanaan penyuluhan dan pelatihan serta perilaku petani terhadap adopsi Teknologi M-Bio. Penelitian dilaksanakan di Desa Setiawaras pada kelompok tani Cipigan Insan Mandiri dan Dadap Sari dari bulan Juli sampai Oktober 2020. Analisis data yang digunakan adalah analisis deskriptif dengan skala likert skor 1, 2, 3, 4, dan 5 kemudian diukur dengan nilai tertimbang. Sebaran data diubah menjadi skala rasio dengan skor antara 0–100. Selanjutnya, skor dikelompokkan menjadi : (1) Sangat Rendah:0–20; (2) Rendah:21 – 40; (3) Sedang:41–60; (4) Tinggi:61–80; dan (5) Sangat Tinggi: 81-100. Hasil penelitian menunjukkan bahwa perilaku petani terhadap pelaksanaan penyuluhan dan pelatihan teknologi M-Bio dengan seluruh indikatornya (presentasi dan praktek, atensi, komprehensif, hasil dan retensi) memiliki skor antara 80 – 100 sehingga semuanya terkategori sangat tinggi. Demikian juga dengan perilaku petani terhadap adopsi teknologi M-Bio untuk pengembangan usahatani agroforestri beserta seluruh indikatornya yang menyangkut aspek kognitif, apektif, dan konatif memiliki skor antara 80 – 100 sehingga semuanya juga terkategori sangat tinggi.

Specimen Mammography for Intraoperative Margin Assessment in Breast Conserving Surgery: A Meta-Analysis

Specimen mammography is one of the widely used intraoperative methods assessing margin status in breast conserving surgery. We performed a meta-analysis to evaluate the diagnostic accuracy of specimen mammography. Literature databases including Pubmed, Cochrane Library, Web of Science and EMBASE were searched prior to May 2020. 18 studies with a total of 1142 patients were included. Data was extracted to perform pooled analysis, heterogeneity testing, threshold effect testing, sensitivity analysis, publication bias analysis and subgroup analyses. The pooled weighted values were a sensitivity of 0.55 (95% CI, 0.45–0.64), a specificity of 0.85 (95% CI, 0.77–0.90), a DOR of 7 (95% CI, 4–11) and a pooled positive likelihood ratio of 3.6 (95% CI 2.4-5.3). The area under the receiver operator characteristic curve was 0.75 (95% CI 0.71-0.78). In the subgroup analysis, the pooled specificity in the positive margin defined as tumor at margin subgroup was lower than the other positive margin definition subgroup (0.79 [95% CI: 0.66, 0.91] vs. 0.88 [95% CI: 0.81, 0.95], p = 0.01). Our findings indicated specimen mammography to be an accurate and intraoperative imaging technique for margin assessment in breast conserving surgery.

Predicting Fluid Intelligence via Naturalistic Functional Connectivity Using Weighted Ensemble Model and Network Analysis

Objectives: Functional connectivity triggered by naturalistic stimuli (e.g., movie clips), coupled with machine learning techniques provide great insight in exploring brain functions such as fluid intelligence. However, functional connectivity is multi-layered while traditional machine learning is based on individual model, which is not only limited in performance, but also fails to extract multi-dimensional and multi-layered information from the brain network. Methods: In this study, inspired by multi-layer brain network structure, we propose a new method, namely weighted ensemble model and network analysis, which combines machine learning and graph theory for improved fluid intelligence prediction. Firstly, functional connectivity analysis and graphical theory were jointly employed. The functional connectivity and graphical indices computed using the preprocessed fMRI data were then all fed into an auto-encoder parallelly for automatic feature extraction to predict the fluid intelligence. In order to improve the performance, tree regression and ridge regression models were stacked and fused automatically with weighted values. Finally, layers of auto-encoder were visualized to better illustrate the connectome patterns, followed by the evaluation of the performance to justify the mechanism of brain functions. Results: Our proposed method achieved the best performance with a 3.85 mean absolute deviation, 0.66 correlation coefficient and 0.42 R-squared coefficient; this model outperformed other state-of-the-art methods. It is also worth noting that the optimization of the biological pattern extraction was automated though the auto-encoder algorithm. Conclusion: The proposed method outperforms the state-of-the-art reports, also is able to effectively capture the biological patterns of functional connectivity during a naturalistic movie state for potential clinical explorations.

NIMG-03. TUMOR HABITAT ANALYSIS BY MAGNETIC RESONANCE IMAGING DISTINGUISHES TUMOR PROGRESSION FROM RADIATION NECROSIS IN BRAIN METASTASES AFTER STEREOTACTIC RADIOSURGERY

OBJECTIVES Identification of viable tumor after stereotactic radiosurgery (SRS) is important for future targeted therapy. This study aimed to determine whether tumor habitat on structural and physiologic MRI can distinguish viable tumor from radiation necrosis of brain metastases after SRS. METHOD Multiparametric contrast-enhanced T1-and T2-weighted imaging, apparent diffusion coefficient (ADC), and cerebral blood volume (CBV) were obtained from 52 patients with 69 metastases, showing enlarging enhancing masses after SRS. Voxel-wise clustering identified three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable). Habitat-based predictors for viable tumor or radiation necrosis were identified by logistic regression. Performance was validated using the area under the curve (AUC) of the receiver-operating-characteristics curve in an independent dataset with 24 patients. RESULTS None of the physiologic MRI habitats were indicative of viable tumor. Viable tumor was predicted by a high-volume fraction of solid low-enhancing habitat (low T2-weighted and low CE-T1-weighted values; odds ratio [OR] 1.74, P< .001) and a low-volume fraction of nonviable tissue habitat (high T2-weighted and low CE-T1-weighted values; OR, 0.55, P< .001). Combined structural MRI habitats yielded good discriminatory ability in both development (AUC 0.85, 95% confidence interval [CI]: 0.77–0.94) and validation sets (AUC 0.86, 95% CI:0.70–0.99), outperforming single ADC (AUC 0.64) and CBV (AUC 0.58) values. The site of progression matched with the solid low-enhancing habitat (72%, 8/11). CONCLUSION Solid low-enhancing and nonviable tissue habitats on structural MRI can help to localize viable tumor in patients with brain metastases after SRS.

Formulation of a novel drinking water quality index equation with the application of multi-criteria decision making techniques

Water Quality Index elucidates the complexity in assessing water quality by converting the results of various parameters into a single number for a precise interpretation of the condition of concerning water. The present study focuses on implementing Multi-Criteria decision-making techniques, namely, Analytical Hierarchy Process and Analytical Networking Process, in estimating the relative weighted significance values of the water quality parameters based on three novel criteria like Cost, Potability, and Taste. The suggested Water Quality Index technique utilizes these weighted values of the water quality parameters in depicting and expressing the water quality level in the form of an index value. Dissolved Oxygen has emerged as the most persuasive factor in evaluating water quality for drinking purposes in this study. This paper has also suggested modifying the standard weighted arithmetic water quality index for higher accuracy in results. Furthermore, Sensitivity analysis is performed to corroborate the Multi-Criteria Decision Making approach in index assessment. The accuracy of the Water Quality Index analysis shall improve if a fixed set of criteria and their preference are asserted and justified based on which the water quality parameters are ranked. Their weighted significance values will be estimated accordingly.

Análisis del modelo multicausal sobre el nivel de la anemia en niños de 6 a 35 meses en Perú

severa. Objetivo: Determinar la prevalencia del nivel de anemia y sus factores asociados en niños menores de tres años utilizando un modelo multicausal en la población peruana. Materiales y métodos: Se realizó un estudio de nivel explicativo a través de un análisis secundario con los datos de la base de datos de la Encuesta Demográfica y de Salud Familiar del 2019. La variable principal fue el nivel de anemia utilizando el Hemocue® para su medición. Se consideraron valores ponderados; frecuencias, porcentajes, bondad de ajuste y un modelo de regresión ordinal. Resultados: Un 40.20% de niños menores de tres años presentaron anemia. Los factores como presencia de diarrea (OR=1,30), 12 meses de vida (OR: 3,33), no iniciar el control prenatal (OR:1,19), sexo masculino (OR: 1.25), madre con anemia (OR: 1.75), madre de 15 a 24 años (OR: 1.94), pozo de tierra como fuente de agua (OR: 1,53), lengua materna aymara (OR: 2,31) se asociaron al nivel de anemia. Conclusiones: Entre los factores de riesgo asociados a la anemia según el modelo multicausal resultan la diarrea en las últimas dos semanas como factor inmediato, entre los subyacentes son edad del niño, fuente de agua potable, control prenatal, anemia y edad de la mujer. Asimismo, los factores protectores corresponden al amamantamiento por alguna vez y quintil de riqueza superior. Introduction: Iron deficiency anemia in children from 6 to 35 months is a severe public health issue.Objective: to determine the prevalence of anemia level and related factors in children under three years applying multicausal model in Peruvian population.Materials and methods: To explanatory level research was carried out applying a secondary analysis with data found in the database of the 2019 Demographic and Family Health Survey. The main variable was the level of anemia in which Hemocue® test was used. Weighted values, frequencies, percentages, goodness-of- fit, and an ordinal regression model were taken into consideration.Results: 40.20% of children under three years old presented anemia. Factors as presence of diarrhea (OR = 1.30), 12 months of life (OR: 3.33), not starting prenatal control (OR: 1.19), male gender (OR: 1.25), mother with anemia (OR: 1.75), mothers who are 15 to 24 (OR: 1.94), water well as a source of water (OR: 1.53), Aymara as mother tongue (OR: 2.31) were associated with anemia level. Conclusions: Among the risk factors associated with anemia according to the multicausal model, diarrhea in the last two weeks is a determinant factor, among the underlying factors are the child's age, source of drinking water, prenatal care, anemia and the woman's age. In addition, the protective factors correspond to breastfeeding for some time and the highest wealth quintile. Introdução: a anemia ferropriva em crianças de 6 a 35 meses é um grave problema de Saúde Pública. Objetivo: determinar a prevalência do nível de anemia e seus fatores associados em crianças menores de três anos por meio de um modelo multicausal na população peruana. Materiais e métodos: foi realizado um estudo de nível explicativo por meio de uma análise secundária com os dados do banco de dados da Pesquisa Demográfica e de Saúde da Família 2019. A variável principal foi o grau de anemia utilizando o Hemocue® para sua mensuração. Valores ponderados foram considerados; frequências, porcentagens, qualidade de ajuste e um modelo de regressão ordinal. Resultados: 40,20% das crianças menores de três anos apresentavam anemia. Fatores como presença de diarreia (OR = 1,30), 12 meses de vida (OR: 3,33), não início do controle pré-natal (OR: 1,19), sexo masculino (OR: 1,25), mãe com anemia (OR: 1,75), mãe de 15 a 24 anos (OR: 1,94), terra como fonte de água (OR: 1,53), língua materna aimará (OR: 2,31) foram associados ao nível de anemia. Conclusões: entre os fatores de risco associados à anemia segundo o modelo multicausal, a diarreia nas últimas duas semanas é um fator imediato, entre os fatores subjacentes estão a idade da criança, fonte de água potável, acompanhamento pré-natal, anemia e idade da mulher. Da mesma forma, os fatores de proteção correspondem à amamentação por algum tempo e ao quintil de maior riqueza.

Ultra-Short-term Power Prediction of the Wind Farm Based on Multivariate Data Combination

Accurate wind power prediction is an important way to promote large-scale wind power grid connection. First, to address the abnormal wind farm actual measurement data caused by wind abandonment and power limitation, the DBSCAN method is used to pre-process the wind farm actual measurement data and eliminate the abnormal data. Then, a short-term wind power prediction model with a combination of GA-LSSVM and ARIMA weights is established, and the Lagrange multiplier algorithm is used to obtain the weighted values of each single model in the combined model to further obtain the wind power prediction results. Finally, the effectiveness of the proposed method is verified by arithmetic examples, and the results show that the proposed model and method can effectively improve the prediction accuracy of short-term wind power.

Is Gadoxetic Acid Disodium (Gd-EOB-DTPA)-Enhanced Magnetic Resonance Imaging an accurate diagnostic method for Hepatocellular Carcinoma? a systematic review with meta-analysis

Background: Gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) has become a widely used liver-specific contrast agent worldwide, but its value and limitations as a diagnostic technique with hepatocellular carcinoma (HCC), have not been assessed. Introduction: A review of the latest evidence available on the diagnostic value of Gd-EOB-DTPA-enhanced MRI for the evaluation of HCC is reported. Methods: A systematic, comprehensive literature search was conducted with PubMed, Scopus, EMBASE, the Web of Science, the Cochrane Library, CNKI, vip, wanfangdata and CBM from inception to June 31, 2020. The QUADAS-2 tool was used to evaluate the quality of the included studies. Pooled sensitivity (SEN), pooled specificity (SPE), pooled positive likelihood ratio (PLR), pooled negative likelihood ratio (NLR), pooled diagnostic odds ratio (dOR) and summary receiver operating characteristic (SROC) curves were calculated to assess the diagnostic value of the individual diagnostic tests. Results: A total of 47 articles were included, involving a total of 6362 nodules in 37 studies based on per-lesion studies. There were 13 per-patient studies, including a total of 1816 patients. The results of the meta-analysis showed that the per-lesion studies pooled weighted values were SEN 0.90 [95% confidence interval (CI): 0.87-0.92], SPE 0.92 (95%CI: 0.90-0.94), PLR 11.6 (95%CI: 8.8-15.2), NLR 0.11 (95%CI: 0.09-0.14) and dOR 107.0 (95%CI: 74.0-155.0). The AUC of the SROC curve was 0.96. The per-patient studies pooled weighted values were SEN 0.84 [95% confidence interval (CI): 0.78-0.89], SPE 0.92 (95%CI: 0.88-0.94), PLR 10.4 (95%CI: 7.4-14.6), NLR 0.17 (95%CI: 0.12-0.24) and dOR 61.0 (95%CI: 42.0-87.0). The AUC of the SROC curve was 0.95 and subgroup analyses were performed. Conclusions: The diagnostic value of Gd-EOB-DTPA for HCC was quantitatively evaluated in a per-lesion study and a per-patient study using a systematic review of the literature. A positive conclusion was drawn: Gd-EOB-DTPA-enhanced imaging is a valuable diagnostic technique for HCC. The size of the nodules and the selection of the imaging diagnostic criteria may affect the diagnostic sensitivity.

The Effect of Teaching–Learning Environments on Student’s Engagement with Lean Mindset

Lean thinking is a methodology employed initially by manufacturing organizations such as Toyota and New Balance that aims to increase customer value whilst also maintaining a low level of waste. The Lean thinking tools and techniques employed in the manufacturing sector can also be transferred to other sectors and significantly improve the service or product, such as public sector organizations or Higher Education Institutions (HEI). In the current education climate, due to the pandemic (SARS-CoV-2, COVID-19), the majority of HEIs have moved to an online or hybrid teaching and learning environment. This has developed the principle that Lean thinking can be deployed in educational methods and techniques to greatly increase the level of student engagement and the efficiency of learning. The following study outlines the key waste sources found in three types of teaching–learning environments (face to face, online and hybrid) and provides practical implications to counter the non-value-added issues. The data for this study were gathered through a questionnaire from final year undergraduate engineering students. The results indicate that online teaching had the greatest effect on student engagement, based on the identification and weighted values of non-value-added issues. The study highlights the key Lean wastes within online, hybrid and face to face teaching, and provides key examples within the stated Lean waste to provide solutions to improve student engagement.

Associations between biomarkers of multimorbidity burden and mortality risk among patients with acute dyspnea

The patients’ burden of comorbidities is a cornerstone in risk assessment, clinical management and follow-up. The aim of this study was to evaluate if biomarkers associated with comorbidity burden can predict outcome in acute dyspnea patients. We included 774 patients with dyspnea admitted to an emergency department and measured 80 cardiovascular protein biomarkers in serum collected at admission. The number of comorbidities for each patient were added, and a multimorbidity score was created. Eleven of the 80 biomarkers were independently associated with the multimorbidity score and their standardized and weighted values were summed into a biomarker score of multimorbidities. The biomarker score and the multimorbidity score, expressed per standard deviation increment, respectively, were related to all-cause mortality using Cox Proportional Hazards Model. During long-term follow-up (2.4 ± 1.5 years) 45% of the patients died and during short-term follow-up (90 days) 12% died. Through long-term follow-up, in fully adjusted models, the HR (95% CI) for mortality concerning the biomarker score was 1.59 (95% CI 1348–1871) and 1.18 (95% CI 1035–1346) for the multimorbidity score. For short-term follow-up, in the fully adjusted model, the biomarker score was strongly related to 90-day mortality (HR 1.98, 95% CI 1428–2743), whereas the multimorbidity score was not significant. Our main findings suggest that the biomarker score is superior to the multimorbidity score in predicting long and short-term mortality. Measurement of the biomarker score may serve as a biological fingerprint of the multimorbidity score at the emergency department and, therefore, be helpful for risk prediction, treatment decisions and need of follow-up both in hospital and after discharge from the emergency department.