Effect of drinking water salinity on lactating cows' water and feed intake, milk yield, and rumen physiology.

Use of desalinated seawater in arid and semiarid regions for domestic, industrial, and agricultural purposes is on the rise. Consequently, in those regions, drinking water offered to lactating cows has lower salinity and mineral concentrations than in the past. Although water with total dissolved solids (TDSs) of up to 1 000 ppm is considered safe for drinking, lower salinity level may affect rumen physiology, feed and water intake, or milk yield.

Family Resilience in Families of Children With Autism Spectrum Disorders: Ecological Systems Theory Perspective.

Drawing on Bronfenbrenner's ecological systems theory (1992), we asked how certain resources contribute to family resilience in families of children with ASD: family quality of life (FQOL; family resources), sense of community and loneliness (informal resources), and family-centered support provided by the state (formal resources). One hundred and twenty-one Israeli parents of children with ASD completed an online survey. Path analysis using AMOS was conducted.

Bacterial defense and phage counterdefense lead to coexistence in a modeled ecosystem.

Bacteria have evolved many defenses against invading viruses (phage). Despite the many bacterial defenses and phage counterdefenses, in most environments, bacteria and phage coexist, with neither driving the other to extinction. How is coexistence realized in the context of the bacteria/phage arms race, and how are immune repertoire sizes determined in conditions of coexistence? Here we develop a simple mathematical model to consider the evolutionary and ecological dynamics of competing bacteria and phage with different immune/counterimmune repertoires.

Prediction of recurrent heart failure hospitalizations and mortality using the echocardiographic Killip score.

Aim: Examine the performance of a simple echocardiographic "Killip score" (eKillip) in predicting heart failure (HF) hospitalizations and mortality after index event of decompensated HF hospitalization.

Methods: HF patients hospitalized at our facility between 03/2019-03/2021 who underwent an echocardiography during their index admission were included in this retrospective analysis. The cohort was divided into 4 classes of eKillip according to: stroke volume index (SVI) < 35ml/m > and E/E' ratio < 15 > .

Lytic and temperate phage naturally coexist in a dynamic population model.

When phage infect their bacterial hosts, they may either lyse the cell and generate a burst of new phage, or lysogenize the bacterium, incorporating the phage genome into it. Phage lysis/lysogeny strategies are assumed to be highly optimized, with the optimal tradeoff depending on environmental conditions. However, in nature, phage of radically different lysis/lysogeny strategies coexist in the same environment, preying on the same bacteria.

Towards a universal mechanism for successful deep learning.

Recently, the underlying mechanism for successful deep learning (DL) was presented based on a quantitative method that measures the quality of a single filter in each layer of a DL model, particularly VGG-16 trained on CIFAR-10. This method exemplifies that each filter identifies small clusters of possible output labels, with additional noise selected as labels outside the clusters. This feature is progressively sharpened with each layer, resulting in an enhanced signal-to-noise ratio (SNR), which leads to an increase in the accuracy of the DL network.

The value of information gathering in phage-bacteria warfare.

Phages-viruses that infect bacteria-have evolved over billions of years to overcome bacterial defenses. Temperate phage, upon infection, can "choose" between two pathways: lysis-in which the phage create multiple new phage particles, which are then liberated by cell lysis, and lysogeny-where the phage's genetic material is added to the bacterial DNA and transmitted to the bacterial progeny. It was recently discovered that some phages can read information from the environment related to the density of bacteria or the number of nearby infection attempts.

Observing the universal screening of a Kondo impurity.

The Kondo effect, deriving from a local magnetic impurity mediating electron-electron interactions, constitutes a flourishing basis for understanding a large variety of intricate many-body problems. Its experimental implementation in tunable circuits has made possible important advances through well-controlled investigations. However, these have mostly concerned transport properties, whereas thermodynamic observations - notably the fundamental measurement of the spin of the Kondo impurity - remain elusive in test-bed circuits.

Erratum: Mechanical Frustration of Phase Separation in the Cell Nucleus by Chromatin [Phys. Rev. Lett. 126, 258102 (2021)].

This corrects the article DOI: 10.1103/PhysRevLett.126.

Identifying an Environment-Induced Localization Transition from Entropy and Conductance.

Environment-induced localization transitions (LT) occur when a small quantum system interacts with a bath of harmonic oscillators. At equilibrium, LTs are accompanied by an entropy change, signaling the loss of coherence. Despite extensive efforts, equilibrium LTs have yet to be observed.

Enhancing the accuracies by performing pooling decisions adjacent to the output layer.

Learning classification tasks of [Formula: see text] inputs typically consist of [Formula: see text]) max-pooling (MP) operators along the entire feedforward deep architecture. Here we show, using the CIFAR-10 database, that pooling decisions adjacent to the last convolutional layer significantly enhance accuracies. In particular, average accuracies of the advanced-VGG with [Formula: see text] layers (A-VGGm) architectures are 0.

Use of proximity loggers to Estimate Affiliative and Agonistic Relationships among Group-housed Holstein calves.

We used proximity loggers to map the social network of 15 group-housed suckling Holstein calves over a 70-day period divided into five trial periods. Tag ID, encountered tag ID, and encounter start time and length were collected from the proximity loggers. Use of 3D matrices and trendlines distinguished three encounter types: "rapid decline" (up to ~ 120 s), "moderate decline" (~120 to ~ 600 s), and "exponential decline" (longer than ~ 600 s).

YAP co-localizes with the mitotic spindle and midbody to safeguard mitotic division in lung-cancer cells.

YES-associated protein (YAP) is a part of the Hippo pathway, with pivotal roles in several developmental processes and dual functionality as both a tumor suppressor and an oncogene. In the present study, we identified YAP activity as a microtubular scaffold protein that maintains the stability of the mitotic spindle and midbody by physically interacting with α-tubulin during mitotic progression. The interaction of YAP and α-tubulin was evident in co-immunoprecipitation assays, as well as observing their co-localization in the microtubular structure of the mitotic spindle and midbody in immunostainings.

Peripheral ulcerative keratitis in a patient with granulomatous rosacea.

A 24-year-old woman visited our emergency department due to intermittent dull pain in the right eye, blurred vision, foreign body sensation for 3 weeks, and progressive facial rash with pustules for 3 months. She had a history of recurring skin rash on her face and extremities since early adolescence. Peripheral ulcerative keratitis (PUK) was diagnosed based on slit-lamp examination and corneal topography and then granulomatous rosacea (GR) based on clinical manifestations and skin pathology.

Using Brainwave Patterns Recorded from Plant Pathology Experts to Increase the Reliability of AI-Based Plant Disease Recognition System.

One of the most challenging problems associated with the development of accurate and reliable application of computer vision and artificial intelligence in agriculture is that, not only are massive amounts of training data usually required, but also, in most cases, the images have to be properly labeled before models can be trained. Such a labeling process tends to be time consuming, tiresome, and expensive, often making the creation of large labeled datasets impractical. This problem is largely associated with the many steps involved in the labeling process, requiring the human expert rater to perform different cognitive and motor tasks in order to correctly label each image, thus diverting brain resources that should be focused on pattern recognition itself.

Transcription Factor ATF3 Participates in DeltaNp63-Mediated Proliferation of Corneal Epithelial Cells.

Understanding the regulatory mechanisms underlying corneal epithelial cell (CEC) proliferation in vitro may provide the means to boost CEC production in cell therapy for ocular disorders. The transcription factor ΔNp63 plays a crucial role in the proliferation of CECs, but the underlying mechanisms is yet to be elucidated. TP63 and ΔNp63 are encoded by the gene via alternative promoters.

Efficient shallow learning as an alternative to deep learning.

The realization of complex classification tasks requires training of deep learning (DL) architectures consisting of tens or even hundreds of convolutional and fully connected hidden layers, which is far from the reality of the human brain. According to the DL rationale, the first convolutional layer reveals localized patterns in the input and large-scale patterns in the following layers, until it reliably characterizes a class of inputs. Here, we demonstrate that with a fixed ratio between the depths of the first and second convolutional layers, the error rates of the generalized shallow LeNet architecture, consisting of only five layers, decay as a power law with the number of filters in the first convolutional layer.

Realistic Protocol to Measure Entanglement at Finite Temperatures.

It is desirable to relate entanglement of many-body systems to measurable observables. In systems with a conserved charge, it was recently shown that the number entanglement entropy (NEE)-i.e.

Re-Evaluation of Genotyping Methodologies in Cattle: The Proficiency of Imputation.

In dairy cattle, identifying polymorphisms that contribute to complex economical traits such as residual feed intake (RFI) is challenging and demands accurate genotyping. In this study, we compared imputed genotypes ( = 192 cows) to those obtained using the TaqMan and high-resolution melting (HRM) methods ( = 114 cows), for mutations in the gene that had been suggested to have a large effect on RFI. Combining the whole genome sequence ( = 19 bulls) and the cows' BovineHD BeadChip allowed imputing genotypes for these mutations that were verified by Sanger sequencing, whereas, an error rate of 11.

Learning on tree architectures outperforms a convolutional feedforward network.

Advanced deep learning architectures consist of tens of fully connected and convolutional hidden layers, currently extended to hundreds, are far from their biological realization. Their implausible biological dynamics relies on changing a weight in a non-local manner, as the number of routes between an output unit and a weight is typically large, using the backpropagation technique. Here, a 3-layer tree architecture inspired by experimental-based dendritic tree adaptations is developed and applied to the offline and online learning of the CIFAR-10 database.

A Secure Base for Entrepreneurship: Attachment Orientations and Entrepreneurial Tendencies.

Entrepreneurship catalyzes economic growth; it generates jobs, advances the economy and solves global challenges. Hence, it is crucial to understand the factors contributing to entrepreneurship and entrepreneurs' development. While many studies have investigated intrapersonal factors for entrepreneurial tendencies, the present study focuses on a critical yet often overlooked interpersonal aspect: attachment orientations.

Entropy Measurement of a Strongly Coupled Quantum Dot.

The spin 1/2 entropy of electrons trapped in a quantum dot has previously been measured with great accuracy, but the protocol used for that measurement is valid only within a restrictive set of conditions. Here, we demonstrate a novel entropy measurement protocol that is universal for arbitrary mesoscopic circuits and apply this new approach to measure the entropy of a quantum dot hybridized with a reservoir. The experimental results match closely to numerical renormalization group (NRG) calculations for small and intermediate coupling.

Reducing dietary sodium of dairy cows fed a low-roughages diet affect intake and feed efficiency, but not yield.

Wastewater from dairy farms has become a major environmental and economical concern. Sodium residue in treated and untreated wastewater from dairy farms used for irrigation can lead to soil and groundwater salinization, with the risk of soil degradation. We examined the effect of reducing sodium fed to mid to late lactating cows from 0.

Brain inspired neuronal silencing mechanism to enable reliable sequence identification.

Real-time sequence identification is a core use-case of artificial neural networks (ANNs), ranging from recognizing temporal events to identifying verification codes. Existing methods apply recurrent neural networks, which suffer from training difficulties; however, performing this function without feedback loops remains a challenge. Here, we present an experimental neuronal long-term plasticity mechanism for high-precision feedforward sequence identification networks (ID-nets) without feedback loops, wherein input objects have a given order and timing.

Proteomic analysis of adipose tissue revealing differentially abundant proteins in highly efficient mid-lactating dairy cows.

The improvement of nutrient utilization efficiency in dairy cows represents an important task in view of the current rising demand for animal products and sustainable resource usage. In this perspective, the identification of appropriate markers to identify the most efficient animals for dairy production becomes a crucial factor. Residual feed intake (RFI), which represents the difference between predicted and actual intake, is used to define the efficiency of cows.