ABSTRACT: Our aim was to determine the effects of P intake on P balance, serum parathyroid hormone (PTH) levels, and bone resorption during the final 4 wk prepartum and the first 8 wk of lactation. Sixty pregnant multiparous Holstein Friesian dairy cows were assigned to a randomized block design with repeated measurements and dietary treatments arranged according to a 2 × 2 factorial design. The experimental diets contained 3.6 (high phosphorus [HP]) or 2.2 (low phosphorus [LP]) g P/kg DM during the dry period (Dry-HP and Dry-LP, respectively), and 3.8 or 2.9 g P/kg DM during 56 d after calving (Lac-HP and Lac-LP, respectively). The level of dietary P of Dry-LP, expressed as g/kg DM, was 18% greater than recommended by the Dutch Central Bureau for Livestock Feeding (The Hague, the Netherlands), whereas the P content of Lac-LP was, across the 8 wk of lactation, 24% lower than recommended. Both P intake and fecal P excretion decreased in the dry period to increase again in subsequent lactation. Cows fed high dietary P excreted more P in the feces than cows fed low dietary P pre- and postpartum. Cows in both Dry-HP and Dry-LP were in positive P balance in the dry period. Cows in both Lac-LP and Lac-HP were in negative P balance after calving, with the negative P balance being more pronounced in Lac-LP than in Lac-HP. Serum concentrations of PTH and apparent total-tract OM and NDF digestibility were neither affected by any 2-way or 3-way interaction between time of sampling and dietary treatments nor by the P concentration of the experimental diets during the pre- and postpartum period. Before calving, serum carboxy-terminal collagen crosslink (CTX) concentrations were basically similar between Dry-HP and Dry-LP. After calving, serum CTX concentrations increased, with a more pronounced increase when Lac-LP was fed compared with Lac-HP. The results suggest that when feeding diets containing low P (2.9 g/kg DM) postpartum, cows excreted less P in the feces than at recommended dietary P (3.8 g P/kg DM) without a negative impact on OM and NDF digestibility. The increase in serum CTX concentrations, without increasing serum PTH concentrations upon feeding low P, indicate a prominent role of bone resorption to meet P demands in the first 8 wk postpartum. The present trial focused on the final 4 wk of gestation and the subsequent 8 wk of lactation, but long-term effects of low dietary P during early lactation on serum PTH and on bone P dynamics in mid and late lactation need to be further investigated.
L. de Souza Ferreira, T. Showemimo, L.B. Juliano
et al.
For decades, conventional microbiological methods have been used to identify bacterial causes of bovine mastitis. Although these methods are relatively accurate for identification of important mastitis pathogens, all diagnostic tests are imperfect, and as testing technologies advance, widespread use of newer technologies may result in differences in the distribution of etiologies that are identified. As a result, historical research using conventional microbiological methods may not be comparable to results of current studies. The objective of this study was to compare agreement between the original identification of mastitis pathogens from cows enrolled in mastitis studies between 2003 and 2011 with identification of the same isolates using MALDI-TOF. Cryopreserved bacterial isolates (n = 308) that had been recovered from quarter milk samples and originally identified using conventional microbiological techniques were used. Bacterial identification was performed using MALDI-TOF. Among all isolates, 277 were able to be identified using MALDI-TOF, and the overall observed levels of agreement were 86% and 64% for identification at the genus level and genus-species level, respectively. The kappa statistic for agreement between methods at the genus level was substantial at 0.80 (95% CI: 0.78, 0.82) but dropped to 0.64 (95% CI: 0.62, 0.66) for agreement at both the genus and species level. For gram-positive isolates, agreement at both the genus level and the genus and species level was substantial. In contrast, for gram-negative isolates, the genus-level agreement was substantial, but agreement at both the genus and species levels was moderate. Our findings suggest substantial agreement between MALDI-TOF and conventional methods for determining genus-level identification, but some discrepancies occur at the species level. These results indicate that historical mastitis research using conventional microbiological methods are comparable at the genus level to current results using MALDI-TOF, but some caution should be applied when making species-level comparisons, especially for gram-negative pathogens.
ABSTRACT: Although improving the management of lactating cows to reduce health and reproductive issues can enhance cow longevity, the long-term effects of early-life management practices are less understood. The objectives of this study were to characterize dairy farms based on their early-life management practices and analyze their associations with herd longevity, productivity, and profitability. In this cross-sectional observational study, early-life management practices regarding colostrum feeding, milk feeding, solid feed and weaning, and housing were collected from 1,658 dairy farms in Québec, Canada, using a questionnaire between February 2020 and February 2021. Length of productive life and the percentage of cows in their third or greater lactation, estimated from DHI testing data, were used as herd longevity indicators, whereas lifetime cumulative ECM production and lifetime cumulative milk value, also derived from DHI records, served as indicators of productivity and profitability, respectively. Cluster analysis was performed to characterize farms based on their early-life management practices. Cluster stability assessment was used to determine the best clustering algorithm and number of clusters. Associations between herd longevity, productivity, profitability, and early-life management practices were assessed using multivariate linear regression models. Due to missing data (ranging from 0.1% to 15.4% across variables), multiple imputation was employed, and significant practices were identified by iteratively applying likelihood ratio tests (α < 0.05) across the imputed datasets. Two clusters were identified and denominated as traditionally or modernly managed farms. The traditionally managed farms cluster (n = 600; 36.2%) was characterized by feeding nonpasteurized or nonacidified milk (whole or waste) with individual buckets, not measuring the concentration of IgG in the colostrum, and housing calves individually. Modernly managed farms (n = 1,058; 63.8%) were characterized by feeding calves powdered milk replacer through automated systems and group housing calves both before and after weaning. Practices adopted by traditionally managed farms were associated with increased longevity but lower productivity and profitability, whereas practices adopted by modernly managed farms were associated with lower longevity but increased productivity and profitability. Our results highlight that early-life management practices are linked with herd longevity, productivity, and profitability, but further research is needed to understand the underlying factors contributing to these associations and to guide dairy farmers in making informed management decisions.
In the dairy industry, surplus calves have been reported to be especially prone to poor welfare on farms and to inappropriate killing of male calves for economic reasons. Therefore, this study aimed to examine calf carcasses for evidence of inappropriate killing and diseases that may have caused prolonged suffering and unnecessary pain in the course of their lives. Our study was conducted during March 2022 and from April to May 2023 in 2 animal byproduct processing plants, where we carried out external inspections of the carcasses to record the sex of the animals and check for the presence of identification marks. We paid particular attention to findings relevant to animal welfare that suggested improper killing or unnecessary suffering and pain in the animals. The examinations included observations on the skinned carcasses (in plant 1), as well as on carcasses in the blanket, the opening of the trachea, and the carpal and tarsal joints (i.e., partial necropsy). In total, 981 calves from dairy cattle and beef cattle herds were examined on 19 delivery days. This encompassed 450 calves at the first location and 531 at the second location. In total, 515 calves were male and 465 were female. The sex of one animal could not be determined because of the nutritional trace on the carcass. Ear tags were not inserted in 588 calves. Five of the 588 calves initially had ear tags. Ear tags were detected in 393 calves. At partial necropsy, 18 animals were diagnosed with profound emaciation. Additionally, arthritis existed in 9 animals. Chronic diseases other than arthritis were observed in 27 (2.8%) of 981 animals. Arthromyodysplastic syndrome was diagnosed in 26 animals. Fractures were found in 38 animals, of which only 3 cases occurred antemortem. The remaining 35 cases of fracture occurred postmortem as a result of transportation. No animal had signs of improper obstetric care. Amniotic fluid was detected in the lumen of the trachea of 122 stillborn calves (i.e., death sub natu). In contrast to the situation reported in pigs, no evidence existed in the 2 animal byproduct processing plants investigated for calf carcasses that inappropriate killing and diseases leading to prolonged suffering and unnecessary pain before death represented systemic problems. No fundamental need for routine testing of animal carcasses existed in either animal byproduct processing plant.
Reasoning has substantially improved the performance of large language models (LLMs) on complicated tasks. Central to the current reasoning studies, Process Reward Models (PRMs) offer a fine-grained evaluation of intermediate reasoning steps and guide the reasoning process. However, extending PRMs to multimodal large language models (MLLMs) introduces challenges. Since multimodal reasoning covers a wider range of tasks compared to text-only scenarios, the resulting distribution shift from the training to testing sets is more severe, leading to greater generalization difficulty. Training a reliable multimodal PRM, therefore, demands large and diverse datasets to ensure sufficient coverage. However, current multimodal reasoning datasets suffer from a marked quality imbalance, which degrades PRM performance and highlights the need for an effective data selection strategy. To address the issues, we introduce DreamPRM, a domain-reweighted training framework for multimodal PRMs which employs bi-level optimization. In the lower-level optimization, DreamPRM performs fine-tuning on multiple datasets with domain weights, allowing the PRM to prioritize high-quality reasoning signals and alleviating the impact of dataset quality imbalance. In the upper-level optimization, the PRM is evaluated on a separate meta-learning dataset; this feedback updates the domain weights through an aggregation loss function, thereby improving the generalization capability of trained PRM. Extensive experiments on multiple multimodal reasoning benchmarks covering both mathematical and general reasoning show that test-time scaling with DreamPRM consistently improves the performance of state-of-the-art MLLMs. Further comparisons reveal that DreamPRM's domain-reweighting strategy surpasses other data selection methods and yields higher accuracy gains than existing test-time scaling approaches.
Tom Bäckström, Mohammad Hassan Vali, My Nguyen
et al.
Speaker, author, and other biometric identification applications often compare a sample's similarity to a database of templates to determine the identity. Given that data may be noisy and similarity measures can be inaccurate, such a comparison may not reliably identify the true identity as the most similar. Still, even the similarity rank based on an inaccurate similarity measure can disclose private information about the true identity. We propose a methodology for quantifying the privacy disclosure of such a similarity rank by estimating its probability distribution. It is based on determining the histogram of the similarity rank of the true speaker, or when data is scarce, modeling the histogram with the beta-binomial distribution. We express the disclosure in terms of entropy (bits), such that the disclosure from independent features are additive. Our experiments demonstrate that all tested speaker and author characterizations contain personally identifying information (PII) that can aid in identification, with embeddings from speaker recognition algorithms containing the most information, followed by phone embeddings, linguistic embeddings, and fundamental frequency. Our initial experiments show that the disclosure of PII increases with the length of test samples, but it is bounded by the length of database templates. The provided metric, similarity rank disclosure, provides a way to compare the disclosure of PII between biometric features and merge them to aid identification. It can thus aid in the holistic evaluation of threats to privacy in speech and other biometric technologies.
Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix
et al.
Single-channel speech enhancement is utilized in various tasks to mitigate the effect of interfering signals. Conventionally, to ensure the speech enhancement performs optimally, the speech enhancement has needed to be tuned for each task. Thus, generalizing speech enhancement models to unknown downstream tasks has been challenging. This study aims to construct a generic speech enhancement front-end that can improve the performance of back-ends to solve multiple downstream tasks. To this end, we propose a novel training criterion that minimizes the distance between the enhanced and the ground truth clean signal in the feature representation domain of self-supervised learning models. Since self-supervised learning feature representations effectively express high-level speech information useful for solving various downstream tasks, the proposal is expected to make speech enhancement models preserve such information. Experimental validation demonstrates that the proposal improves the performance of multiple speech tasks while maintaining the perceptual quality of the enhanced signal.
Gabriel C. Medeiros, Jose Bento S. Ferraz, Victor B. Pedrosa
et al.
ABSTRACT: Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems has increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in an xyz plan, which can then be used to derive udder conformation traits. Because AMS generate a large amount of data for individual cows per milking visit, they can contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multitrait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 SNPs. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front–rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (± SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (± SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between FTD and RTD (0.54 ± 0.03), UD and DFR (−0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (−0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection subindexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (−0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms.
Short-chain fatty acids (SCFA) are essential to cattle as a source of energy and for other roles in metabolism. These molecules are formed during fermentation by microbes in the rumen, but even after decades of study, the biochemical pathways responsible for forming them are not always clear. Here we review recent advances in this area and their importance for improving animal productivity. Studies of bacterial genomes have pointed to unusual biochemical pathways in rumen organisms. One study found that 8% of rumen organisms forming acetate, a major SCFA, had genes for a pathway previously unknown in bacteria. The existence of this pathway was subsequently confirmed biochemically in propionibacteria. The pathway was shown to involve 2 enzymes that convert acetyl-coenzyme A to acetate. Similar studies have revealed new enzymatic steps for forming propionate and butyrate, other major SCFA. These new steps and pathways are significant for controlling fermentation. With more precise control over SCFA, cows can be fed more precisely and potentially reach higher productivity.
Luisa Cordeiro de Oliveira, Carolina Carvalho Ramos Viana, Júlia D'Almeida Francisquini
et al.
With the growth of the Brazilian sports nutrition market, whey protein, a supplement derived from whey, rich in proteins of high biological value, has great potential for expansion. Correct information on product labeling is essential to ensure consumer health. The aim of this study was to evaluate and compare nutritional tables in terms of constituent composition, with an emphasis on protein content, lists of ingredients and aminogram tables on product labels, in order to verify their compliance with current legislation. The labels of whey protein supplements of the following types were analyzed: concentrate, isolate and hydrolysate from 4 national brands, making a total of 12 samples. The isolated and hydrolyzed products did not differ statistically (p0.05) in terms of protein content. Whey protein concentrate, on the other hand, had significantly lower protein contents (p0.05) than those found for hydrolyzed and isolated food supplements. Despite complying with current legislation in terms of nutritional information, there was a lack of standardization in terms of product labelling, such as a lack of uniformity in the units of measurement used. This highlights the need for more specific legislation establishing criteria for standardizing the labelling of these products, in order to make it easier for consumers to read and better understand the nutritional information.
Giovanni Bittante, Nicolò Amalfitano, Alessandro Ferragina
et al.
ABSTRACT: Cheese presents extensive variability in physical, chemical, and sensory characteristics according to the variety of processing methods and conditions used to create it. Relationships between the many characteristics of cheeses are known for single cheese types or by comparing a few of them, but not for a large number of cheese types. This case study used the properties recorded on 1,050 different cheeses from 107 producers grouped into 37 categories to analyze and quantify the interrelationships among the chemical and physical properties of many cheese types. The 15 cheese traits considered were ripening length, weight, firmness, adhesiveness, 6 different chemical characteristics, and 5 different color traits. As the 105 correlations between the 15 cheese traits were highly variable, a multivariate analysis was carried out. Four latent explanatory factors were extracted, representing 86% of the covariance matrix: the first factor (38% of covariance) was named Solids because it is mainly linked positively to fat, protein, water-soluble nitrogen, ash, firmness, adhesiveness, and ripening length, and negatively to moisture and lightness; the second factor (24%) was named Hue because it is linked positively to redness/blueness, yellowness/greenness, and chroma, and negatively to hue; the third factor (17%) was named Size because it is linked positively to weight, ripening length, firmness, and protein; and the fourth factor (7%) was named Basicity because it is linked positively to pH. The 37 cheese categories were grouped into 8 clusters and described using the latent factors: the Grana Padano cluster (characterized mainly by high Size scores); hard mountain cheeses (mainly high Solids scores); very soft cheeses (low Solids scores); blue cheeses (high Basicity scores), yellowish cheeses (high Hue scores), and 3 other clusters (soft cheeses, pasta filata and treated rind, and firm mountain cheeses) according to specific combinations of intermediate latent factors and cheese traits. In this case study, the high variability and interdependence of 15 major cheese traits can be substantially explained by only 4 latent factors, allowing us to identify and characterize 8 cheese type clusters.
The primary objective of this study was to determine the antimicrobial resistance (AMR) profile of common mastitis pathogens on large Chinese dairy farms. A total of 673 isolates, including Staphylococcus aureus (14.41%, 97/673), coagulase-negative staphylococci (CNS, 52.30%, 352/673), Streptococcus agalactiae (5.64%, 38/673), non-agalactiae streptococci (7.42%, 50/673), Acinetobacter spp. (7.72%, 52/673), Escherichia spp. (6.39%, 43/673), and Klebsiella spp. (6.09%, 41/673), were collected from 15 large Chinese dairy farms in 12 provinces. The AMR profiles were measured using a microdilution method. Our results showed that more than 75% of Staph. aureus (87/97) and CNS (291/352) were resistant to penicillin (PEN). More than 30% of Escherichia spp. (15/43) showed resistance to ampicillin (AMP). However, less than 10% CNS and non-agalactiae streptococci showed resistance to amoxicillin/clavulanate (AMC; 1/352; 0/50), cephalexin (LEX; 1/352; 0/50), ceftiofur (EFT; 10/352; 0/50), and rifaximin (RIX; 21/352; 2/50); less than 10% Staph. aureus showed resistance to AMC (1/97), oxacillin (OX; 3/97), LEX (1/97), EFT (2/97), and RIX (2/97); less than 10% Strep. agalactiae showed resistance to PEN (3/38), AMC (0/38), LEX (0/38), EFT (0/38), and RIX (0/38); and less than 10% Escherichia spp. showed resistance to AMC (1/43) and EFT (4/43). These results suggested that most mastitis pathogens were susceptible to most antimicrobials with exceptions of Staph. aureus tested against penicillin or ampicillin and CNS against penicillin or oxacillin. To control the AMR threat in Chinese dairy farms, a nationwide surveillance program for AMR of bovine mastitis pathogens is needed.
Xiaohui Zhang, Yuanrong Zheng, Changyu Zhou
et al.
This work investigated the effects of the combined use of thermosonication-preconditioned lactic acid bacteria (LAB) with the addition of ultrasound-assisted pineapple peel extracts (UU group) on the post-acidification potential, physicochemical and functional qualities of yogurt products, aimed at achieving prolonged preservation and enhancing functional attributes. Accordingly, the physical–chemical features, adhesion properties, and sensory profiles, acidification kinetics, the contents of major organic acids, and antioxidant activities of the differentially processed yogurts during refrigeration were characterized. Following a 14-day chilled storage process, UU group exhibited acidity levels of 0.5–2 oT lower than the control group and a higher lactose content of 0.07 mg/ml as well as unmodified adhesion potential, indicating that the proposed combination method efficiently inhibited post-acidification and delayed lactose metabolism without leading to significant impairment of the probiotic properties. The results of physicochemical analysis showed no significant changes in viscosity, hardness, and color of yogurt. Furthermore, the total phenolic content of UU-treated samples was 98 μg/mL, 1.78 times higher than that of the control, corresponding with the significantly lower IC50 values of DPPH and ABTS radical scavenging activities of the UU group than those of the control group. Observations by fluorescence inverted microscopy demonstrated the obvious adhesion phenomenon with no significant difference found among differentially prepared yogurts. The results of targeted metabolomics indicated the proposed combination strategy significantly modified the microbial metabolism, leading to the delayed utilization of lactose and the inhibited conversion into glucose during post-fermentation, as well as the decreased lactic acid production and a notable shift towards the formation of relatively weak acids such as succinic acid and citric acid. This study confirmed the feasibility of thermosonication-preconditioned LAB inocula, in combination with the use of natural active components from fruit processing byproducts, to alleviate post-acidification in yogurt and to enhance its antioxidant activities as well as simultaneously maintaining sensory features.
ABSTRACT: The objective of this study was to quantify the farm gate nitrogen (N) offset potential of perennial ryegrass (Lolium perenne L.; PRG) white clover (Trifolium repens L.; WC) swards by comparing the herbage and milk production from dairy farmlets that were simulations of full farming systems. A study was established where 120 cows were randomly assigned to 4 farmlets of 10.9 ha (stocking rate: 2.75 cow/ha), composed of 20 paddocks each. Cows were fed 526 kg of DM of concentrate on average each year. The 4 grazing treatments were PRG-only at 150 or 250 kg of N/ha and PRG-WC at 150 or 250 kg of N/ha. Cows remained in their treatment group for an entire grazing season and were re-randomized as they calved across treatments each year. As cows calved in the spring as standard practice in Ireland, they were rotationally grazed from early February both day and night (weather permitting) to mid-November, to a target postgrazing sward height of 4.0 cm. Mean sward WC content was 18.1% and 15.4% for the 150 and 250 kg of N/ha PRG-WC treatments, respectively over the 3-yr period. When WC was included, lowering the N rate did not reduce pregrazing yield, pregrazing height, or herbage removed, but those factors decreased significantly when WC was absent. Total annual herbage DM production was 13,771, 15,242, 14,721, and 15,667 kg of DM/ha for PRG-only swards receiving 150 or 250 kg of N/ha and PRG-WC swards receiving 150 or 250 kg of N/ha, respectively. In addition, when WC was present, compressed postgrazing sward heights were lower (4.10 vs. 4.21 cm) and herbage allowance (approximately 17 kg/cow feed allocation per cow per day) higher than the high-N control (+ 0.7 kg of DM/cow per day). There was a significant increase in milk production, both per cow and per hectare, when WC was included in PRG swards. Over the 3-yr study, cows grazing PRG-WC had greater milk (+304 kg) and milk solids (+31 kg of fat + protein) yields than cows grazing PRG-only swards. This significant increase in milk production suggests that the inclusion of WC in grazing systems can be effectively used to increase milk production per cow and per hectare and help offset nitrogen use. This result shows the potential to increase farm gate N use efficiency and reduce the N surplus compared with PRG-dominant sward grazing systems receiving 250 kg of N/ha, without negatively affecting milk solids yield or herbage production, thus increasing farm profit by €478/ha.
S. Johanan Joysingh, P. Vijayalakshmi, T. Nagarajan
The onset of a musical note is the earliest time at which a note can be reliably detected. Detection of these musical onsets pose challenges in the presence of ornamentation such as vibrato, bending, and if the attack of the note transient is slower. The legacy systems such as spectral difference or flux and complex domain functions suffer from the addition of false positives due to ornamentation posing as viable onsets. We propose that this can be solved by appropriately improving the resolution of the onset strength signal (OSS) and smoothening it to increase true positives and decrease false positives, respectively. An appropriate peak picking algorithm that works well in unison with the OSS generated is also desired. Since onset detection is a low-level process upon which many other tasks are built, computational complexity must also be reduced. We propose an onset detection alogrithm that is a combination of short-time spectral average-based OSS estimation, chirp group delay-based smoothening, and valley-peak distance-based peak picking. This algorithm performs on par with the state-of-the-art, superflux and convolutional neural networks-based onset detection, with an average F1 score of 0.88, across three datasets. Subsets from the IDMT-SMT-Guitar, Guitarset, and Musicnet datasets that fit the scope of the work, are used for evaluation. It is also found that the proposed algorithm is computationally 300\% more efficient than superflux. The positive effects of smoothening an OSS, in determining the onset locations, is established by refining the OSS produced by legacy algorithms, where consistent improvement in onset detection performance is observed. To provide insights into the performance of the proposed algorithms when different ornamentation styles are present in the recording, three levels of results are computed, by selecting different subsets of the IDMT dataset.
Milk is a highly important consumer for Americans and the health of the cows' teats directly affects the quality of the milk. Traditionally, veterinarians manually assessed teat health by visually inspecting teat-end hyperkeratosis during the milking process which is limited in time, usually only tens of seconds, and weakens the accuracy of the health assessment of cows' teats. Convolutional neural networks (CNNs) have been used for cows' teat-end health assessment. However, there are challenges in using CNNs for cows' teat-end health assessment, such as complex environments, changing positions and postures of cows' teats, and difficulty in identifying cows' teats from images. To address these challenges, this paper proposes a cows' teats self-attention residual convolutional neural network (CTSAR-CNN) model that combines residual connectivity and self-attention mechanisms to assist commercial farms in the health assessment of cows' teats by classifying the magnitude of teat-end hyperkeratosis using digital images. The results showed that upon integrating residual connectivity and self-attention mechanisms, the accuracy of CTSAR-CNN has been improved. This research illustrates that CTSAR-CNN can be more adaptable and speedy to assist veterinarians in assessing the health of cows' teats and ultimately benefit the dairy industry.
Adrian Lutsch, Muhammad El-Hindi, Matthias Heinrich
et al.
Trusted Execution Environments (TEEs), such as Intel's Software Guard Extensions (SGX), are increasingly being adopted to address trust and compliance issues in the public cloud. Intel SGX's second generation (SGXv2) addresses many limitations of its predecessor (SGXv1), offering the potential for secure and efficient analytical cloud DBMSs. We assess this potential and conduct the first in-depth evaluation study of analytical query processing algorithms inside SGXv2. Our study reveals that, unlike SGXv1, state-of-the-art algorithms like radix joins and SIMD-based scans are a good starting point for achieving high-performance query processing inside SGXv2. However, subtle hardware and software differences still influence code execution inside SGX enclaves and cause substantial overheads. We investigate these differences and propose new optimizations to bring the performance inside enclaves on par with native code execution outside enclaves.
ABSTRACT: The productivity of smallholder dairy farms is very low in developing countries. Important genetic gains could be realized using genomic selection, but genetic evaluations need to be tailored for lack of pedigree information and very small farm sizes. To accommodate this situation, we propose a flexible Bayesian model for the genetic evaluation of milk yield, which allows us to simultaneously account for nongenetic random effects for farms and varying SNP variance (BayesR model). First, we used simulations based on real genotype data from Indian crossbred dairy cattle to demonstrate that the proposed model can separate the true genetic and nongenetic parameters even for small farm sizes (2 cows on average) although with high standard errors in scenarios with low heritability. The accuracy of genomic genetic evaluation increased until farm size was approximately 5. We then applied the model to real data from 4,655 crossbred cows with 106,109 monthly test day milk records and 689,750 autosomal SNPs. We estimated a heritability of 0.16 (0.04) for milk yield and using cross-validation, a genomic estimated breeding value (GEBV) accuracy of 0.45 and bias (regression of phenotype on GEBV) of 1.04 (0.26). Estimated genetic parameters were very similar using BayesR, BayesC, and genomic BLUP approaches. Candidate genes near the top variants, IMMP2L and ARHGEF2, have been previously associated with milk protein composition, mastitis resistance, and milk cholesterol content. The estimated heritability and GEBV accuracy for milk yield are much lower than those from intensive or pasture-based systems in many countries. Further increases in the number of phenotyped and genotyped animals in farms with at least 2 cows (preferably 3–5, to allow for dropout of cows) are needed to improve the estimation of genetic effects in these smallholder dairy farms.
A pregnancy loss or abortion can be assumed when a dairy cow that has been previously diagnosed pregnant shows signs of estrus. In herds using leg-based pedometers as a tool to detect cows in estrus, a sudden increase in walking activity (hereafter, activity peaks) relative to a certain threshold activity triggers an estrous alert that can be confused with a pregnancy loss. The objective of this study was to determine whether pregnant cows can show activity peaks as measured by pedometers. We used data from a dairy herd of 250 milking cows using pedometers as a means of measuring walking activity to detect cows in estrus. Two databases were used in this study, which included the walking activity of the entire herd recorded by the pedometers from January 1, 2018, to December 31, 2021 (database 1), and the calving dates, the insemination dates, the dates when a pregnancy diagnosis was declared pregnant, the dates when a pregnancy diagnosis was declared not pregnant or open, and the abortion dates (database 2). Activity peaks were identified within an experimental unit, which was defined as pregnant cows showing an insemination event followed by a confirmed pregnancy and subsequent calving. The activity peaks were identified using the peak searching algorithm that compares the step count on a given day with the step counts of its adjacent days. The candidate peaks were characterized for their magnitudes by the prominence metric. A chi-squared test was performed to test the specificity of the system. From the 4-yr database, 537 pregnancies or experimental units were identified, and 77 pregnancies showed 1 or more peaks, which means that 14.4% of the pregnancies showed activity peaks. Within the pregnancies showing peaks (n = 77), the median equaled 1 peak/pregnancy, the average equaled 1.53 peaks/pregnancy, and the maximum equaled 13 peaks/pregnancy. In conclusion, activity peaks can be observed for pregnant cows using pedometers. These peaks could generate false estrous alerts during the pregnancy period when using pedometers, and these false alerts should not be interpreted as pregnancy losses.