High-Resolution, High-Contrast Optical Interface for Defect Qubits

Point defects in crystals provide important building blocks for quantum applications. Since we optically address these defect qubits, having an efficient optical interface is a highly important aspect. However, conventional confocal fluorescence microscopy of high-refractive-index crystals suffers from limited photon collection efficiency and spatial resolution. Here, we demonstrate high-resolution, high-contrast imaging of defects in diamonds using microsphere-assisted confocal microscopy. A microsphere provides an excellent optical interface for point defects with a magnified virtual image that increases the spatial resolution up to lambda/5, as well as the optical signal-to-noise ratio by four times. These features enable individual optical addressing of single photons and single spins of multiple defects that are spatially unresolved in conventional confocal microscopy, with improved signal contrast. Combined with optical tweezers, this system also demonstrates the possibility of positioning or scanning the microspheres. The approach does not require any complicated fabrication or additional optical systems, but uses simple, off-the-shelf micro-optics. From these distinctive advantages of microspheres, our approach provides an efficient way to image and address closely spaced defects with much better resolution and sensitivity

Guidelines for experimental design and statistical analyses in animal studies submitted for publication in the Asian-Australasian Journal of Animal Sciences

Animal experiments are essential to the study of animal nutrition. Because of the large variations among individual animals and ethical and economic constraints, experimental designs and statistical analyses are particularly important in animal experiments. To increase the scientific validity of the results and maximize the knowledge gained from animal experiments, each experiment should be appropriately designed, and the observations need to be correctly analyzed and transparently reported. There are many experimental designs and statistical methods. This editorial does not aim to review and present particular experimental designs and statistical methods. Instead, we discuss some essential elements when designing an animal experiment and conducting statistical analyses in animal nutritional studies and provide guidelines for submitting a manuscript to the Asian-Australasian Journal of Animal Sciences for consideration for publication

Evaluation of feed value of a by-product of pickled radish for ruminants: analyses of nutrient composition, storage stability, and in vitro ruminal fermentation

Abstract Background By-products of pickled radish (BPR) are considered food waste. Approximately 300 g/kg of the total mass of raw materials becomes BPR. Production of pickled radish has grown continuously and is presently about 40,000 metric tons annually in Korea. The objective of the present study was thus to explore the possibility of using BPR as a ruminant feed ingredient. Results BPR contained a large amount of moisture (more than 800 g/kg) and ash, and comprised mostly sodium (103 g/kg DM) and chloride (142 g/kg DM). On a dry matter basis, the crude protein (CP) and ether extract (EE) levels in BPR were 75 g/kg and 7 g/kg, respectively. The total digestible nutrient (TDN) level was 527 g/kg and the major portion of digestible nutrients was carbohydrate; 88 % organic matter (OM) was carbohydrate and 65 % of total carbohydrate was soluble or degradable fiber. The coefficient of variation (CV) of nutrient contents among production batches ranged from 4.65 to 33.83 %. The smallest CV was observed in OM, and the largest, in EE. The variation in CP content was relatively small (10.11 %). The storage stability test revealed that storage of BPR at 20 °C (room temperature) might not cause spoilage for 4 d, and possibly longer. If BPR is refrigerated, spoilage can be deferred for 21 d and longer. The in vitro ruminal fermentation study showed that substitution of annual ryegrass straw with BPR improved ruminal fermentation, as evidenced by an increase in VFA concentration, DM degradability, and total gas production. Conclusion The major portion of nutrients in BPR is soluble or degradable fiber that can be easily fermented in the rumen without adverse effects, to provide energy to ruminant animals. Although its high sodium chloride content needs to be considered when formulating a ration, BPR can be successfully used as a feed ingredient in a ruminant diet, particularly if it is one component of a total mixed ration

Evaluation of the Equations to Predict Net Energy Requirement for Lactation in the Cattle Feeding System: Based on the Literature Database

The net energy requirement for lactation (NEL) equals the milk energy, which is the sum of the energy content from the energy-yielding nutrients in milk. The specific nutrients and their calories, however, vary depending on the feeding system. The objective of this study was to evaluate NEL prediction equations used in cattle feeding systems. A total of 11 equations from 6 feeding systems were assessed. For evaluation, a database was constructed based on the literature, and data for three nutrients (lactose, fat, and protein) were used to evaluate the equations. The equations were classified into three tiers based on the variables: Tier 1 (all three nutrients), Tier 2 (fat and protein), and Tier 3 (fat). NEL predicted by the equations were comparatively evaluated based on a reference value computed using Tyrrell and Reid’s equation. All equations showed high predictivity (in order, Tier 1, 2, and 3). Tier 1 equations showed a nearly perfect fit; however, for accurately predicting NEL, at least Tier 2 equations are recommended. The predictivity of theoretically derived equations was as high, or higher, as the predictivity of empirical equations. Thus, empirical development of an accurate equation to predict NEL, which requires a large amount of data, can be avoided

Evaluation of the Equations to Predict Net Energy Requirement for Lactation in the Cattle Feeding System: Based on the Literature Database

The net energy requirement for lactation (NEL) equals the milk energy, which is the sum of the energy content from the energy-yielding nutrients in milk. The specific nutrients and their calories, however, vary depending on the feeding system. The objective of this study was to evaluate NEL prediction equations used in cattle feeding systems. A total of 11 equations from 6 feeding systems were assessed. For evaluation, a database was constructed based on the literature, and data for three nutrients (lactose, fat, and protein) were used to evaluate the equations. The equations were classified into three tiers based on the variables: Tier 1 (all three nutrients), Tier 2 (fat and protein), and Tier 3 (fat). NEL predicted by the equations were comparatively evaluated based on a reference value computed using Tyrrell and Reid’s equation. All equations showed high predictivity (in order, Tier 1, 2, and 3). Tier 1 equations showed a nearly perfect fit; however, for accurately predicting NEL, at least Tier 2 equations are recommended. The predictivity of theoretically derived equations was as high, or higher, as the predictivity of empirical equations. Thus, empirical development of an accurate equation to predict NEL, which requires a large amount of data, can be avoided

Sensitivity analysis of the INRA 2018 feeding system for ruminants by a one-at-a-time approach: Effects of dietary input variables on predictions of multiple responses of dairy cattle

ABSTRACT: In the feeding system for ruminants developed in 2018 by the French National Institute of Agricultural Research (INRA), the prediction of multiple animal responses is based on the integration of the characteristics of the animal and the available feedstuff characteristics, as well as the rationing objectives. In this framework, the characterization of feedstuffs in terms of net energy, digestible protein, and fill units requires information on their chemical composition, digestibility, and degradability. Despite the importance of these feed characteristics, a comprehensive assessment of their impact on the responses predicted by the INRA 2018 feeding system has not been carried out. Thus, our study investigated how variables predicted by the INRA feeding system (i.e., outputs) for dairy cows are affected by variation in feed characterization (i.e., inputs). We selected 5 input variables for the sensitivity analysis: CP, OM apparent digestibility (OMd), gross energy (GE), effective degradability of nitrogen assuming a passage rate of 6%/h (ED6_N), and true intestinal digestibility (dr_N) of nitrogen. A one-at-a-time sensitivity analysis was performed on predicted digestive, productive, and environmental output variables for dairy cows with 6 contrasted diets. These 6 diets were formulated to meet 95% of the potential daily milk production (37.5 kg) of a multiparous cow at wk 14 of lactation. The values of the 5 key input variables of each feedstuff were then randomly sampled around the INRA 2018 feed table values (reference point). The response of the output variable to the variation of the input variable was quantified and compared using the tangent value at the reference point and the normalized sensitivity coefficient. Among the major final output variables, CP and dr_N had the greatest impact on N excretion in urine (as a proportion of total fecal and urinary N excretion; UN/TN); OMd and GE had the greatest impact on N utilization efficiency (NUE; N in milk as proportion of intake N); and ED6_N had the greatest impact on milk protein yield (MPY). Additionally, CP, GE, and dr_N had the least effect on methane emission, OMd had the least effect on UN/TN, and ED6_N had the least effect on NUE. The responses of most output variables to ED6_N and dr_N variations were highly dependent on diet and were related to the ratio between protein truly digestible in the intestine (PDI; i.e., MP) and net energy for lactation (UFL; i.e., NEL) at the reference point of each diet. Overall, we were able to analyze the response of output variables to the variations of the input variables, using the tangent and its normalized value at the reference point. The predicted final outputs were more affected by variations in CP, GE, and OMd. The other 2 input variables, ED6_N and dr_N, had a smaller effect on the final output variables, but the responses varied between the diets according to their PDI/UFL ratio. Our present study was conducted using 6 representative diets for dairy cattle fed at their potential, but should be completed by the analysis of more diverse conditions

Analysis of the Factors Influencing Body Weight Variation in Hanwoo Steers Using an Automated Weighing System

This study aimed to determine the factors affecting the body weight (BW) of Hanwoo steers by collecting a large number of BW measurements using an automated weighing system (AWS). The BW of 12 Hanwoo steers was measured automatically using an AWS for seven days each month over three months. On the fourth day of the BW measurement each month, an additional BW measurement was conducted manually. After removing the outliers of BW records, the deviations between the AWS records (a) and manual weighing records (b) were analyzed. BW measurement deviations (a − b) were significantly (p < 0.05) affected by month, day and the time within a day as well as the individual animal factor; however, unexplained random variations had the greatest impact (70.4%). Excluding unexplained random variations, the difference between individual steers was the most influential (80.1%). During the day, the BW of Hanwoo steers increased before feed offerings and significantly decreased immediately after (p < 0.05), despite the constant availability of feeds in the feed bunk. These results suggest that there is a need to develop pattern recognition algorithms that consider variations in individual animals and their feeding patterns for the analysis of BW changes in animals

Polythiophene-based terpolymers with modulated aggregation behaviors for high-performance organic solar cells with 16.6% efficiency

Polythiophenes (PTs) are an attractive class of polymer donors (PDs) for organic solar cells (OSCs) owing to their relatively simple structures and scalable synthesis. Herein, a series of chlorinated thiazole-incorporated PT terpolymers are designed and high-performance OSCs with a power conversion efficiency (PCE) of 16.6% are demonstrated. By incorporating two different units, 3,3 & PRIME;-difluoro-2,2 & PRIME;-bithiophene (T2F2) and thieno[3,2-b] thiophene (TT), the aggregation properties of the terpolymers (PTz-FX; X = 0, 30, 50, 70, and 100, where X represents the mole percentage of T2F2 to total T2F2 +TT) are modulated. Among the PTz-FX series, PTz-F70 is found to be the optimal PD because its suitably tuned aggregation property leads to an optimized blend morphology with well-developed crystalline structures and donor-acceptor intermixed domains. The balanced morphology not only promotes charge generation/transport but also suppresses charge recombination in OSC devices. Thus, the PTz-F70-based OSCs achieve the highest PCE (16.6%), outperforming the OSCs based on PTz-FX with extremely strong (PTz-F100, PCE= 14.7%) or weak (PTz-F0, PCE = 12.0%) aggregation properties. The PCE of the PTz-F70-based OSCs is one of the highest performances among PT-based binary OSCs. This study highlights the importance of controlling the aggregation property of PTs for achieving high-performance PT-based OSCs

A Korean validation study of the Clinically Useful Anxiety Outcome Scale: Comorbidity and differentiation of anxiety and depressive disorders.

This study aimed to evaluate the psychometric properties of the Korean version of the Clinically Useful Anxiety Outcome Scale (CUXOS) and to examine the current diagnostic comorbidity and differential severity of anxiety symptoms between major depressive disorder (MDD) and anxiety disorders.In total, 838 psychiatric outpatients were analyzed at their intake appointment. Diagnostic characteristics were examined using the structured clinical interview from the DSM-IV because the DSM5 was not available at the start of the study. The CUXOS score was measured and compared with that of 3 clinician rating scales and 4 self-report scales.The CUXOS showed excellent results for internal consistency (Cronbach's α = 0.90), test-retest reliability (r = 0.74), and discriminant and convergent validity. The CUXOS significantly discriminated between different levels of anxiety severity, and the measure was sensitive to change after treatment. Approximately 45% of patients with MDD were additionally diagnosed with anxiety disorders while 55% of patients with anxiety disorders additionally reported an MDD. There was a significant difference in CUXOS scores between diagnostic categories (MDD only, anxiety only, both disorders, and no MDD or anxiety disorder). The CUXOS scores differed significantly between all categories of depression (major, minor, and non-depression) except for the comparison between minor depression and non-depression groups.The Korean version of the CUXOS is a reliable and valid measure of the severity of anxiety symptoms. The use of the CUXOS could broaden the understanding of coexisting and differentiating characteristics of anxiety and depression