Clinical Assessment of Dairy Goats' Udder Health Using Infrared Thermography.

This study aimed to evaluate the capacity of infrared thermography (IRT) to be used for the in situ clinical assessment of udder health status across lactation in goats. Two epidemiological studies were designed, with 106 purebred Skopelos goats being prospectively monitored over one lactation in the first study and 132 goats of the same breed from a second farm being enrolled in the second, cross-sectional study. Goats were categorized based on the clinical status of each udder half (healthy, fibrotic, both fibrotic and asymmetric, asymmetric, swollen supra-mammary lymph nodes, and abscessed).

Single-molecule RNA sizing enables quantitative analysis of alternative transcription termination.

Transcription, a critical process in molecular biology, has found many applications in RNA synthesis, including mRNA vaccines and RNA therapeutics. However, current RNA characterization technologies suffer from amplification and enzymatic biases that lead to loss of native information. Here, we introduce a strategy to quantitatively study both transcription and RNA polymerase behaviour by sizing RNA with RNA nanotechnology and nanopores.

Mid-Infrared Variable Selection for Soil Organic Matter Fractions Based on Soil Model Systems and Permutation Importance Algorithm.

In this research, an attempt was made to classify soil samples according to the different fractions of soil organic matter (SOM) using model systems in which the ratio of the fractions of SOM is chemically mimicked. A mixture of starch and nicotinamide was used for the labile organic matter model, while a standard of humic acid was used for the stabile organic matter. Changing the threshold value in the selected ranges after a permutation importance algorithm is conducted using train models and test data set, a list of selected important wavelengths and their importance scores were obtained.

Mammalian Cell-Growth Monitoring Based on an Impedimetric Sensor and Image Processing within a Microfluidic Platform.

In recent years, advancements in microfluidic and sensor technologies have led to the development of new methods for monitoring cell growth both in macro- and micro-systems. In this paper, a microfluidic (MF) platform with a microbioreactor and integrated impedimetric sensor is proposed for cell growth monitoring during the cell cultivation process in a scaled-down simulator. The impedimetric sensor with an interdigitated electrode (IDE) design was realized with inkjet printing and integrated into the custom-made MF platform, i.

Explainable AI for unveiling deep learning pollen classification model based on fusion of scattered light patterns and fluorescence spectroscopy.

Pollen monitoring have become data-intensive in recent years as real-time detectors are deployed to classify airborne pollen grains. Machine learning models with a focus on deep learning, have an essential role in the pollen classification task. Within this study we developed an explainable framework to unveil a deep learning model for pollen classification.

Agrobot Lala-An Autonomous Robotic System for Real-Time, In-Field Soil Sampling, and Analysis of Nitrates.

This paper presents an autonomous robotic system, an unmanned ground vehicle (UGV), for in-field soil sampling and analysis of nitrates. Compared to standard methods of soil analysis it has several advantages: each sample is individually analyzed compared to average sample analysis in standard methods; each sample is georeferenced, providing a map for precision base fertilizing; the process is fully autonomous; samples are analyzed in real-time, approximately 30 min per sample; and lightweight for less soil compaction. The robotic system has several modules: commercial robotic platform, anchoring module, sampling module, sample preparation module, sample analysis module, and communication module.

Fundamental Study of the Optical and Vibrational Properties of Fx-AZB@MOF systems as Functions of Dye Substitution and the Loading Amount.

Controlling the switching efficiency of photoactive hybrid systems is an obligatory key prerequisite for systematically improving the design of functional materials. By modulating the degree of fluorination and the amount being embedded into porous hosts, the / ratios of fluorinated azobenzenes were adjusted as both functions of substitution and the degree of loading. Octafluoroazobenzene (F8-AZB) and perfluoroazobenzene (F10-AZB) were inserted into porous DMOF-1.

Why should we care about high temporal resolution monitoring of bioaerosols in ambient air?

This is the first time that atmospheric concentrations of individual pollen types have been recorded by an automatic sampler with 1-hour and sub-hourly resolution (i.e. 1-minute and 1-second data).

Predicting sensitivity of recently harvested tomatoes and tomato sepals to future fungal infections.

Tomato is an important commercial product which is perishable by nature and highly susceptible to fungal incidence once it is harvested. Not all tomatoes are equally vulnerable to pathogenic fungi, and an early detection of the vulnerable ones can help in taking timely preventive actions, ranging from isolating tomato batches to adjusting storage conditions, but also in making right business decisions like dynamic pricing based on quality or better shelf life estimate. More importantly, early detection of vulnerable produce can help in taking timely actions to minimize potential post-harvest losses.

MRI Reconstruction Using Markov Random Field and Total Variation as Composite Prior.

Reconstruction of magnetic resonance images (MRI) benefits from incorporating a priori knowledge about statistical dependencies among the representation coefficients. Recent results demonstrate that modeling intraband dependencies with Markov Random Field (MRF) models enable superior reconstructions compared to inter-scale models. In this paper, we develop a novel reconstruction method, which includes a composite prior based on an MRF model and Total Variation (TV).

Engineering Meteorological Features to Select Stress Tolerant Hybrids in Maize.

In this study we used meteorological parameters and predictive modelling interpreted by model explanation to develop stress metrics that indicate the presence of drought and heat stress at the specific environment. We started from the extreme temperature and precipitation indices, modified some of them and introduced additional drought indices relevant to the analysis. Based on maize's sensitivity to stress, the growing season was divided into four stages.

The balance between KIFC3 and EG5 tetrameric kinesins controls the onset of mitotic spindle assembly.

One of the first steps in mitotic spindle assembly is the dissolution of the centrosome linker followed by centrosome separation driven by EG5, a tetrameric plus-end-directed member of the kinesin-5 family. However, even in the absence of the centrosome linker, the two centrosomes are kept together by an ill-defined microtubule-dependent mechanism. Here we show that KIFC3, a minus-end-directed kinesin-14, provides microtubule-based centrosome cohesion.

STED nanoscopy of the centrosome linker reveals a CEP68-organized, periodic rootletin network anchored to a C-Nap1 ring at centrioles.

The centrosome linker proteins C-Nap1, rootletin, and CEP68 connect the two centrosomes of a cell during interphase into one microtubule-organizing center. This coupling is important for cell migration, cilia formation, and timing of mitotic spindle formation. Very little is known about the structure of the centrosome linker.

Portfolio optimization for seed selection in diverse weather scenarios.

The aim of this work was to develop a method for selection of optimal soybean varieties for the American Midwest using data analytics. We extracted the knowledge about 174 varieties from the dataset, which contained information about weather, soil, yield and regional statistical parameters. Next, we predicted the yield of each variety in each of 6,490 observed subregions of the Midwest.

Sparse Recovery in Magnetic Resonance Imaging With a Markov Random Field Prior.

Recent research in compressed sensing of magnetic resonance imaging (CS-MRI) emphasizes the importance of modeling structured sparsity, either in the acquisition or in the reconstruction stages. Subband coefficients of typical images show certain structural patterns, which can be viewed in terms of fixed groups (like wavelet trees) or statistically (certain configurations are more likely than others). Wavelet tree models have already demonstrated excellent performance in MRI recovery from partial data.

Human phosphatase CDC14A regulates actin organization through dephosphorylation of epithelial protein lost in neoplasm.

CDC14 is an essential dual-specificity phosphatase that counteracts CDK1 activity during anaphase to promote mitotic exit in Surprisingly, human CDC14A is not essential for cell cycle progression. Instead, it regulates cell migration and cell adhesion. Little is known about the substrates of hCDC14A and the counteracting kinases.

Genome editing through large insertion leads to the skipping of targeted exon.

Background: Highly efficient genome editing can be achieved through targeting an endonuclease to specific locus of interest. Engineered zinc-finger nuclease (ZFN) and CRISPR-associated protein-9 nuclease (Cas9) offer such an elegant approach for genome editing in vertebrate cells. In this study, we have utilized ZFN and Cas9-catalyzed double strand break followed by homologous recombination-mediated incorporation of premature stop codon and selection marker to target human cell division cycle 14A (hCDC14A) and cell division cycle 14B (hCDC14B) genes.

The centrosomal linker and microtubules provide dual levels of spatial coordination of centrosomes.

The centrosome is the principal microtubule organizing center in most animal cells. It consists of a pair of centrioles surrounded by pericentriolar material. The centrosome, like DNA, duplicates exactly once per cell cycle.