Miracle-dz/UniFAR-FTUs huggingface dataset:
Vineyard Yield Estimation, Prediction, and Forecasting: A Systematic Literature Review

Purpose—knowing in advance vineyard yield is a critical success factor so growers and winemakers can achieve the best balance between vegetative and reproductive growth. It is also essential for planning and regulatory purposes at the regional level. Estimation errors are mainly due to the high inter-annual and spatial variability and inadequate or poor performance sampling methods; therefore, improved applied methodologies are needed at different spatial scales. This paper aims to identify the alternatives to traditional estimation methods. Design/methodology/approach—this study consists of a systematic literature review of academic articles indexed on four databases collected based on multiple query strings conducted on title, abstract, and keywords. The articles were reviewed based on the research topic, methodology, data requirements, practical application, and scale using PRISMA as a guideline. Findings—the methodological approaches for yield estimation based on indirect methods are primarily applicable at a small scale and can provide better estimates than the traditional manual sampling. Nevertheless, most of these approaches are still in the research domain and lack practical applicability in real vineyards by the actual farmers. They mainly depend on computer vision and image processing algorithms, data-driven models based on vegetation indices and pollen data, and on relating climate, soil, vegetation, and crop management variables that can support dynamic crop simulation models. Research limitations—this work is based on academic articles published before June 2021. Therefore, scientific outputs published after this date are not included. Originality/value—this study contributes to perceiving the approaches for estimating vineyard yield and identifying research gaps for future developments, and supporting a future research agenda on this topic. To the best of the authors’ knowledge, it is the first systematic literature review fully dedicated to vineyard yield estimation, prediction, and forecasting methods.
Assessment of Environmental Radioactivity in Soil Samples from Kathmandu Valley, Nepal

This study was conducted to determine the amount of naturally occurring radioactivity in the soil of Nepal's Kathmandu valley. The activity of naturally occurring radionuclides was determined in these soil samples using a sodium iodide detector. Activity concentrations of 238U, 232Th, and 40K were found in the range: 32.00-111.38 Bq kg-1, 33.52-130.04 Bq kg-1, and 342.50-897.71 Bq kg-1, respectively. These values are well within the permissible range as recommended by UNSCEAR. The soil samples with the highest activity concentrations were primarily found in the valley's northern region. The activity concentrations were also used to calculate the radiation hazard indices: the mean value obtained were 96.63 nGy hr-1 for Absorbed Gamma Dose Rate in Air, 200.04 Bq kg-1 for Radium Equivalent Activity, the 0.12 mSv yr-1 for Annual Effective Dose, and 0.55 for External Hazard Index. These calculated hazard indices were used to estimate the potential radiological health risk from the soil, and the dose rates associated with it were significantly less than their permissible limit. The overall findings indicate no radiological threat to the population's health in the study area. Additionally, the findings of this study provide baseline information on potential radionuclides that contribute mostly for radiation exposure from natural sources.
Vascular Endothelial Growth Factor Levels Difference among Hepatocellular Cancer Patients Based on Barcelona Clinic Liver Cancer Staging

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. It depends on angiogenesis for growth and metastasis. Vascular endothelial growth factor (VEGF), a growth factor for angiogenesis, is hoped to be a biomarker for the diagnosis of HCC and its development. AIM: The objective of the study is to determine the difference of VEGF levels among HCC patients based on barcelona clinic liver cancer (BCLC) staging. METHODS: A cross-sectional study was conducted at Haji Adam Malik General Hospital Medan, Indonesia between January and December 2018. Patients aged 18 years or older with HCC were enrolled using consecutive sampling method. Patients with cholangiocarcinoma, hemangioma, and liver metastasis were excluded from the study. The diagnosis of HCC was confirmed by triphasic computed tomography-scanning. Circulating VEGF levels were determined from serum specimen using Quantikine Human VEGF-enzyme-linked immunosorbent assay. All patients were grouped based on BCLC staging. Kruskal Wallis-H test was applied at 95% confidence interval. p < 0.05 was considered significant. RESULTS: Of 60 patients, 47 (78.3%) were male. Mean age of patients was 61.4 (SD11.7) years. Hepatitis B was the most common etiology (70.0%) of HCC. Based on BCLC staging, 25 (41.7%) patients were in stage C. Median VEGF level was 951.25 pg/mL. There was a statistically significant difference in VEGF levels (p = 0.006) where patients in Stage C (1,009.6 pg/mL) and D (1,189.7 pg/mL) had higher VEGF levels compared to those in Stage A (578 pg/mL). CONCLUSION: There was a statistically significant difference of VEGF levels among HCC patients based on BCLC staging.
On Minimal Second-order IIR Bandpass Filters with Constrained Poles and Zeros

In this paper, several forms of infinite impulse response (IIR) bandpass filters with constrained poles and zeros are presented and compared. The comparison includes the filter structure, the frequency ranges and a number of controlled parameters that affect computational efforts. Using the relationship between bandpass and notch filters, the two presented filters were originally developed for notch filters. This paper also proposes a second-order IIR bandpass filter structure that constrains poles and zeros and can be used as a minimal parameter adaptive digital second-order filter. The proposed filter has a wider frequency range and more flexibility in the range values of the adaptation parameters.
Association Analysis of MBL1 Gene SNPs, Genotype and Haplotypes with Clinical Mastitis in Murrah Buffaloes

Mannose-binding lectins (MBL1) gene a most important constituent of immune response system of an organism, the primary role of this gene in the classical and lectin-activation pathways is to provide protection against various dieases or bacterial pathogens. In this study, eight novel SNPs identified in the promoter region of MBL1 gene were 154C>T, 235G>A, 252A>T, 265C>A, 268T>C, 282G>A, 431G>A and 551C>G, when compared to reference sequence of Bubalus bubalis (NCBI accession number KC415281). Genomic DNA isolated from 200 lactating Murrah buffaloes was amplified for the targeted sequence of MBL1. PCR products were custom sequenced, edited and used for further analysis. The results indicated that only 551C>G polymorphism locus met Hardy–Weinberg equilibrium (c2 (2df) = 4.4: P=0.11). Pair linkage disequilibrium analysis and haplotype construction of MBL1 gene were performed using SHEsis software. Pair linkage disequilibrium analysis revealed moderate to strong linkage disequilibrium between the eight SNPs loci A total of 17 haplotypes were generated from eight SNPs in promoter region of MBL1 gene. Association between eight SNPs of MBL1 gene in Murrah buffalo has been analyzed and relative risks of the alleles for clinical mastitis were estimated with an odds ratio. Allelic association analysis showed that T allele of 154C>T, A allele of 235G>A, A allele of 252A>T, A allele of 265C>A , T allele of 268T>C, A allele of 282G>A , A allele of 431G>A and G allele of 551C>G had significant association with increased risk of clinical mastitis (P< 0.01). Haplotype analysis showed that Hap15 (CAAATAAG) and Hap16 (TAAATAAG) i.e. the haplotypes containing all 8 “at-risk” alleles, were significantly associated with clinical mastitis (P< 0.01). Hap6 (CGAATAAC) and Hap8 (CGTCCGGC) were significantly associated with a lower risk of clinical mastitis in Murrah buffaloes (P< 0.01). On the other hand, the Hap6 (CGAATAAC) and Hap8 (CGTCCGGC) which are unrepresented in affected group and without “at-risk” alleles were significantly associated with a lower risk for clinical mastitis (P<0.01). These findings indicated a MBL1 gene polymorphism could be used as genetic marker for mastitis resistance in Murrah buffaloes.
Mental distress evaluation and intervention for cancer patients*

Mental distress is prevalent among cancer patients. Many measurements have been developed to screen and evaluate such distress. About one-third of the persons with cancer will experience significant levels of distress, requiring targeted psychosocial intervention. Mental distress has been endorsed as the sixth vital sign by the International Psycho-Oncology Society (IPOS) in 2009. The need for effective screening and psychological interventions is well recognized as a necessary, integral part of oncology care. This systematic review examines the psychometric properties of the existing tools used to screen patients for emotional distress and the applicable intervention methods.
Brand Review Prediction using User Sentiments

- As the speed of innovation increases at an accelerating rate, Individuals' ways of sharing their views on different websites is also expanding. On social media sites like Facebook, Twitter, and Yelp, there are various reviews and opinions. Scores are normally provided on a range of 1 to 5 stars. Assessment of opinions through textual data analysis has played a critical role in analytics research because it offers useful options to sentiment mining. A review is an evaluation of a product or service by someone who has used the product or service or has experience with it. The ranking of any ecommerce site is heavily influenced by the opinions of its users. The goal of this paper is to describe how a Machine Learning (ML) algorithm works on Yelp's database to evaluate, anticipate, and recommend brands. With the sentimental analysis algorithm, we implemented Naive Bayes, Random Forest, Decision Tree, Support Vector Machines, K-Nearest Neighbour, and Multilayer Perceptron classifiers. The best result of the multilayer perceptron classifier is 93.40 percent.
DET ECT : A Deep Discriminative Clustering Baseline for Unsupervised and Universal Domain Adaptation

Given a set of labeled instances on a source domain, unsupervised domain adaptation (UDA) aims to learn a prediction function to classify instances in a shifted, target domain. Depending on the degrees of overlap between the label spaces of the two domains, the problem variants of UDA range from the classical, closed set setting to the most general — arguably the most challenging — setting of universal domain adaptation. In this work, we argue that no matter what the degree of label space overlap, the problem nature of UDA remains unchanged when it comes to learning the intrinsic discrimination of target data in an unsupervised manner, regularized by the labeled discrimination of source data in an unknown but shared label space, and we argue that this regularization should not overwhelm the learning of a target prediction function. To this end, we propose a simple but strong baseline of neighborhooD-prEserved deep discriminaTivE ClusTering ( DETECT ) for UDA, whose design complies with the above learning principles. We conduct thorough experiments that verify the efﬁcacy of constituent components in DETECT across a range of label space overlaps. Such a simple baseline also outperforms all existing methods on four UDA benchmarks.
Generalized adaptive refinement for grid-based hexahedral meshing

Due to their nice numerical properties, conforming hexahedral meshes are considered a prominent computational domain for simulation tasks. However, the automatic decomposition of a general 3D volume into a small number of hexahedral elements is very challenging. Methods that create an adaptive Cartesian grid and convert it into a conforming mesh offer superior robustness and are the only ones concretely used in the industry. Topological schemes that permit this conversion can be applied only if precise compatibility conditions among grid elements are observed. Some of these conditions are local, hence easy to formulate; others are not and are much harder to satisfy. State-of-the-art approaches fulfill these conditions by prescribing additional refinement based on special building rules for octrees. These methods operate in a restricted space of solutions and are prone to severely over-refine the input grids, creating a bottleneck in the simulation pipeline. In this article, we introduce a novel approach to transform a general adaptive grid into a new grid meeting hexmeshing criteria, without resorting to tree rules. Our key insight is that we can formulate all compatibility conditions as linear constraints in an integer programming problem by choosing the proper set of unknowns. Since we operate in a broader solution space, we are able to meet topological hexmeshing criteria at a much coarser scale than methods using octrees, also supporting generalized grids of any shape or topology. We demonstrate the superiority of our approach for both traditional grid-based hexmeshing and adaptive polycube-based hexmeshing. In all our experiments, our method never prescribed more refinement than the prior art and, in the average case, it introduced close to half the number of extra cells.
Histological Evaluation of Brain Tissue in Dyslipidemic Rats Treated with Dietary Supplements Based on Amazonian Fruits

Aims: By using histological analysis, the study aims to evaluate the effect of a nutraceutical based on the Amazonian fruits of camu-camu (Myrciaria dubia (Kunth) Mc Vaugh), acai (Euterpe precatoria Mart.) and guarana (Paullinia cupana) on the brain tissue (hippocampus) of dyslipidemic rats. Methodology: Preclinical trials were conducted using male and female rats (n=30) of the Wistar strain (Rattus norvegicus) that were randomly divided into five groups (G) (n=6). G1 was control, G2 was induced to obesity with consumption of experimental feed (hypercaloric and hyperlipidic), G3 was induced to obesity with consumption of experimental feed and treated with simvastatin (50 mg/kg/day), and G4 and G5, which were induced to obesity with the consumption of experimental feed and supplemented with 100 mg/kg/day and 200 mg/kg/day of the formulation, respectively. The study period was 72 days, and, for 37 days, induction to obesity was performed with the experimental feed (hypercaloric and hyperlipidic). During the following weeks, for 35 days, after division of the groups, certain groups received, in parallel, treatment with simvastatin (G3) or supplementation with the nutraceutical (G4 and G5). Subsequently, histological slides of the brain tissue stained with violet cresyl were elaborated, photographed and analyzed. Results: No significant differences were observed between the mean of intact neurons among the experimental groups induced to obesity. The neurotoxic effect, evidenced by the significant difference between the mean of intact neurons between the control group and obesity-induced groups, corroborates the findings of neuronal damage and degenerative processes reported in the literature. Conclusion: The nutraceutical based on Amazonian fruits was not able to prevent the neurotoxic effect arising from the hyperlipidic and hypercaloric diet, and therefore did not present a neuroprotective effect in Wistar rats under the conditions established in the experiment.
Analysing Educational Campaign’s Outcome in Donation-Based Crowdfunding: Social Capital as a Determinant Factor

A new financing alternative, known as crowdfunding, has expanded rapidly. Not all crowdfunding projects or campaigns can successfully reach the desired funding amount. Many studies have shown that social capital is a determinant of crowdfunding success, and some of it could be applied to the education domain. This study investigates the influence of the multidimensional social capital on the donation-based crowdfunding within the scope of educational campaigns belonging to higher education institutions students. This study uses the primary data extracted from the Skolafund crowdfunding site, a specialised third-party platform for higher education. This study, using the theory of multidimensional social capital as the theoretical foundation, develops a logit model linking all three social capital dimensions. The findings imply that only two social capital dimensions, namely structural and relational, are significant factors influencing the crowdfunding success likelihood. This study also finds that campaigns with lower funding targets are more likely to succeed. The practical implications of this study suggest the students should leverage their social capital to increase the fundraising amount. Higher education institutions also should consider to set up their crowdfunding platforms quickly or encourage students to utilise a third-party platform, such as Skolafund.
AI Based Proctoring System

— Massive open online courses (MOOCs) and other forms of remote education continue to increase in popularity and reach. The ability to efficiently proctor remote online examinations is an important limiting factor to the scalability of this next stage in education. Presently, human proctoring is the most common approach of evaluation, by either requiring the test taker to visit an examination center, or by monitoring them visually and acoustically during exams via a webcam. However, such methods are labor-intensive and costly. In this paper, we present a multimedia analytics system that performs automatic online exam proctoring. The system hardware includes one webcam and a microphone, for the purpose of monitoring the visual and acoustic environment of the testing location. The system some basic components that continuously estimate the key behavior cues: user verification using eye detection, text detection, voice detection, mouth opening detection, head pose estimation, no person detection, multiple face detection and phone detection. By combining the continuous estimation components, and applying a temporal sliding window, we design higher-level features to classify whether the test taker is cheating at any moment during the exam. To evaluate our proposed system, we collect multimedia (audio and visual) data from 24 subjects performing various types of cheating while taking online exams. Extensive experimental results demonstrate the accuracy, robustness, and efficiency of our online exam proctoring system.
Genotypes by environment effect on flowering and seed set in cassava, Manihot esculenta Crantz in Uganda

Cassava (Manihot esculenta Crantz) production has been constrained by biotic and abiotic factors, which could be solved by conventional breeding. However, cassava hybridization is difficult because many genotypes do not flower or set seeds and yet cassava sexual reproduction is essential for breeding programs. Consequently, this study was undertaken to identify agro ecologies in Uganda that best promote cassava flowering and seed set in order to facilitate breeding. Field evaluation of eight genotypes in randomized complete block design with three replications at three agro-ecologies of Uganda for two cropping seasons was conducted. Weather data were monitored and cassava flowering/seed set-related traits were collected at one-month interval commencing from 1.5 Months after planting. Results indicated that varieties previously categorized as high flowering and seed set performed differently than those identified as poor flowering and seed set, although with varying genotypic differences in each environment. Genotypes mean performances, additive main effect and multiplicative interaction and genotype main effect and genotype by environment interaction bi-plots model’ results indicated Rwebitaba in Western savannah grassland agro-ecology and Namulonge-NaCRRI in Lake Victoria Crescent agro-ecology as the most favorable environments for the performance of all the evaluated traits, and season one as the most favorable season. However, the most stable environment for all the evaluated traits was Abi-ZARDI. Conclusively, the high proportion of variation which occurred between genotypes and environments was explained by the genotypic variances. Dry months had poorer cassava flower initiation and development than wet months of the cropping season. Therefore, Abi-ZARDI in North-western savannah grassland agro-ecology and season one could be recommended for the establishment and timing of cassava breeding nursery.
Autonomic, hormonal, and subjective responses to a modified version of the TSST: a pilot study

El objetivo de esta investigación fue estudiar las respuestas hormonales, autonómicas y afectivas a una versión modificada del estresor TSST en una muestra de jóvenes universitarios compuesta de treinta y ocho sujetos (11 hombres y veintisiete mujeres, 11 en la fase lútea del ciclo menstrual, 16 mujeres en la fase folicular). La respuesta hormonal se evaluó con niveles de cortisol. La frecuencia cardíaca y la actividad electrodérmica se registraron durante toda la sesión experimental y la ansiedad rasgo y estado se evaluaron antes y después de la tarea. La fase de discurso provocó la frecuencia cardíaca más alta, la mayor frecuencia de respuestas inespecíficas y el mayor nivel de conductancia de la piel, mostrando diferencias significativas con la fase de habituación. Sin embargo, la respuesta de cortisol salival no fue significativa con respecto al factor estresante. En relación con las diferencias de sexo, independientemente del factor estresante,los hombres mostraron una mayor frecuencia de respuesta inespecífica, un mayor nivel de conductancia de la piel que las mujeres y mayores niveles de cortisol en comparación con las mujeres en la fase lútea. La ansiedad estado fue similar pre y postarea y no reveló ninguna diferencia asociada con el sexo o la fase del ciclo menstrual. Nuestros resultados sugieren que el eje HHA no responde al TSST sentado y proporcionó evidencia de que el TSST provoca diferentes patrones de respuesta psicofisiológica dependiendo de algunas variaciones del protocolo. The aim of this research was to study hormonal, autonomic and affective responses to a modified version of the stressor TSST in a sample of young university students composed for thirty-eight subjects (11 men and twenty seven women, 11 in the luteal phase of the menstrual cycle, 16 women in the follicular phase). The hormonal response was evaluated with levels of cortisol. Heart rate and Electrodermal Activity were recorded during all the experimental session and trait-state anxiety was evaluated before and after the task. The speech phase elicited the highest heart rate, frequency of non-specific response and skin conductance level, showing significant differences mainly with the habituation phase. However, the salivary cortisol response was not significant with respect to stressor. In relation with sex differences, regardless of the stressor, menshowed higher frequency of non-specific response, greater skin conductance level than women and higher cortisol levels in comparison with women in the luteal phase. State-anxiety was similar pre-/post task and did not reveal any difference associated to sex or menstrual cycle phase. Our results suggest that the HPA axis not response to sitting TSST and provided evidence that TSST elicits different pattern of psychophysiological response depending on some protocol variations.