Coxiella burnetii (CB), is an emerging zoonotic health problem. The prevalence data from potential sources are valuable for assessing the risk to human and animal health. To estimate the prevalence of CB antibodies in Estonian ruminants, pooled milk and serum samples from cattle (Bos taurus) and pooled serum samples from sheep (Ovis aries) and goats (Capra hircus) were analyzed. Additionally, bulk tank milk samples  were analyzed for the presence of CB DNA. Questionnaires and herd-level datasets were used to identify the risk factors for exposure using binary logistic regression analysis. The prevalence of CB-positive dairy cattle herds (27.16%) was significantly higher than that in beef cattle herds (6.67%) and sheep flocks (2.35%). No CB antibodies were detected in the goat flocks. CB DNA was found in 11.36% of the BTM samples. The odds of seropositivity were higher in dairy cattle herds, with an increasing number of cattle in the herd, and with location in southwestern, northeastern and northwestern Estonia. Dairy cattle herds had higher odds of testing positive for CB in BTM if the dairy cows were kept loose and lower odds if the herd was located in northwestern Estonia.Q fever, a disease caused by  Coxiella burnetii (CB). The bacteria are considered to be globally distributed but may be overlooked in some countries due to the irregular or absence of investigations [CB are via the inhalation of spore-like stages transported in aerosols or via contact with excretions  from infected animals or contaminated materials [CB is transmitted through tick bites [CB [Q fever (QF) is a zoonosis caused by the intracellular bacterium igations ,2. The materials . In rareck bites . Humans ites [CB .In ruminants, cats, and dogs, the course of the infection is commonly asymptomatic but can, in some cases, affect reproduction, manifesting as stillbirths, infertility, retained placenta, abortions, and weak offspring . DomestiCB infection is 2 to 3 weeks, and the symptoms include flu-like illness, pneumonia, and hepatitis. Chronic QF is rare and generally manifests clinically as vascular infection and endocarditis [In humans, the average incubation period of CB infections were generally found near dairy goat farms with abortion waves induced by CB [In response to the rising concerns about health risks regarding a QF outbreak in the Netherlands, the European Food Safety Authority (EFSA) assembled a scientific opinion that called for the need for harmonized passive and active monitoring of QF . Followied by CB .CB infections in European ruminants range from 0.0% to 81.6% in cattle, 0.0% to 78.6% in sheep and 0.0% to 43.1% in goats [CB seropositivity. Breed, parity, use of windshield and use of artificial insemination were detected as animal-level risk factors [Herd-level seroprevalence estimates of in goats ,10. In p factors ,11.CB in domestic animals. Evidence of infection has previously been detected serologically in five cattle from three different farms [CB in other domestic animals, including sheep, goats, and pets.In Estonia, there are few data on the presence of nt farms . InformaCB in domestic ruminants in Estonia based on seroprevalence and identify potential associated risk factors.This study aimed to estimate the exposure to CB antibodies at the Estonian University of Life Sciences (EMU).The study population included cattle herds sampled for the official surveillance of enzootic bovine leukosis (EBL) in Estonia. Milk or serum samples from all cattle aged ≥ 24 months were collected from all cattle herds in Estonia by authorized veterinarians for EBL surveillance in 2012. Available aliquots of these samples were stored at the Estonian National Centre for Laboratory Research and Risk Assessment and tested for In 2012, 4665 cattle herds were registered in the Estonian national production animal register  The herd® [Herds with at least five adult animals were included. Using a random number generator EpiTools® , 504 catAssuming a 20% herd prevalence in the population, the sample size enabled the estimation of the prevalence at the country level in each herd category, with 95% confidence and 5% accepted error.CB antibody testing, unless ≤30 samples were collected, in which case all the samples were tested. The selected serum samples were pooled from 3 to 6 samples before testing for CB antibodies using 150 µL of each sample.From each beef herd, 30 serum samples were randomly selected for CB antibody testing. If the number of individual samples per herd was ≤50, all the samples were pooled and tested.Fifty individual milk samples were randomly selected from each dairy herd and pooled for The sampling scheme of included cattle herds is presented in A sample size of 30 animals per herd enabled the detection of a seropositive herd with 95% confidence if the within-herd seroprevalence was 12%, assuming a sensitivity of 82.6% and a specificity of 100% for testing antibodies in cattle blood serum , and a vIn Estonia, 1949 sheep flocks and 653 goat flocks were registered in the production animal register in 2012 .Brucella test were used for further investigation of CB antibodies at EMU.Flocks involved in the national breeding program and subjected to official surveillance for brucellosis were included. All herds sampled in 2012 and 2013 were included. Leftover serum samples from the Additional sheep and goat flocks not included in the brucellosis surveillance program were sampled to increase the herd sample size. Blood samples were collected from 30 randomly selected adult animals from each flock.The sampling procedure is summarized in The number of flocks tested enabled the detection of an infected flock with 95% confidence if the herd-level prevalence in the population was 2% in sheep and 20% in goats, assuming herd-level sensitivity and specificity of 95% and 100%, respectively. The number of samples collected from each flock (1–65) enabled the identification of an infected flock with 95% confidence, at least on a 20% prevalence level, assuming 88.8% sensitivity and 98.5% specificity of the test in sheep, and 91.6% sensitivity and 98.9% specificity in goats, respectively .CB infection in Estonian cattle herds.Two studies were performed to identify risk factors for In the first study (Risk Factor Study 1), herds and data from the seroprevalence study based on surveillance program samples were included. Data on the herds’ geographical locations, sizes , and breeds were retrieved from the National Animal Register database .CB antibodies and define the herd’s infection status (positive or negative), as specified in The second study (Risk Factor Study 2) included dairy cattle herds that volunteered to participate in the study in 2013. One tank milk sample (BTM) was submitted by farmers from each herd to test for Collected samples were stored at −20 °C in labelled plastic vials until analysis. All laboratory analyses were performed in 2012–2014.CB antibodies in milk and serum samples. Sample preparation, analyses, and interpretation of the results were performed according to the manufacturer’s instructions [An indirect enzyme-linked immunosorbent assay PrioCHECK Ruminant Q Fever Ab Plate Kit  was used to detect ructions .CB antibodies (n = 88) were tested for the presence of CB DNA using polymerase chain reaction. DNA was purified from milk samples using Chelex 100 Resin . Trans-1 (5′-TAT GTA TCC ACC GTA GCC AGT C-3′) and Trans-2 (5′-CCC AAC AAC ACC TCC TTA TTC-3′) primers were used to detect the presence of specific IS1111 repetitive elements in CB DNA. The use of these primers had been described by Berri et al. [All pooled milk samples that were positive for i et al. . Positivi et al.  and purii et al. .® epidemiological calculator ’Confidence limits for a proportion’ [Cattle herds were categorized as dairy herds (≥50% dairy breed cattle) and beef herds (<50% dairy breed cattle), and herd-level prevalence estimates were calculated for both subgroups as well as for sheep and goat herds. Wilson’s 95% confidence intervals (CI) were calculated using the EpiToolsportion’ .CB infection status based on antibodies and potential risk factors.Logistic regression analyses were used to estimate the association between herd Herd size was evaluated in the models as a continuous variable  and categorical variable (herd size). Prior analyses of cattle herds were categorized according to the number of animals as small , medium-sized , and large herds .The effects of specific cattle breeds  were evaluated using the number of animals of specific breeds registered in the herd.Cattle herds were grouped into regions based on Estonian counties (N = 15): southwest , southeast , northeast , and northwest  .The season of sample collection was determined as astronomical seasons: spring, summer, autumn, and winter, with the respective starting dates.The percentage of registered beef cattle was calculated from the total number of animals registered in the cattle herd.The keeping systems of lactating cows and pregnant heifers were categorized as tied, loose, or mixed (tied and loose).The grazing of adult animals was categorized as ’no grazing’, ‘grazing of dry cows’, or ‘grazing of all animals’.Participation in animal shows, pastures being in contact with the neighboring farms’ pastures, animals drinking from natural waterbodies, and employees keeping production animals at home were evaluated as binary variables (yes/no).CB seropositivity. Variables with p < 0.35  and herd size  were added to the model because of the different sizes of the beef and dairy cattle herds and the significant effect of herd size on CB seropositivity status of a herd among dairy cattle herds. The inclusion of variables  was used to monitor the fit of the models during construction. All variables with on 4.1.0 .The sample included 504 cattle herds, of which 324 were dairy and 180 were beef cattle herds. The average size of the herds was 278 for dairy herds (median 82) and 72 for beef herds (median 45). More than 90% of the dairy cattle were Estonian Holstein Friesian, Estonian Red, and/or Estonian Native cattle breeds. The beef cattle population consisted of more than 10 different breeds, of which Hereford, Aberdeen-Angus, and Limousine breeds were dominant.The small ruminant flocks consisted of 170 sheep and 18 goat flocks. The average flock size was 165 for sheep (median 110) and 52 for goats (median 16).CB-seropositive test result is presented in The prevalence of cattle herds, sheep, and goat flocks with at least one CB-positive herds was significantly higher in dairy cattle herds than in beef cattle herds and sheep flocks. The prevalence of CB-positive beef cattle herds and sheep flocks did not differ significantly.The apparent prevalence of CB was found in 11.36% (6.29–19.67 95% CI) of the CB-seropositive pooled milk samples (n/N = 10/88) from the EBL surveillance program.DNA of CB-positive in the univariable analysis were production type, region, number of animals, herd size, and season. The production type, number of animals, and region were included in the final multivariable model . However, the number of samples collected from small ruminant flocks might have been insufficient to detect all tuations .CB antibodies were found in herds from all regions of Estonia, where CB infections may already be endemic. The proportion of Estonian dairy cattle herds that tested positive for CB was lower than that observed in Danish, Dutch, and French dairy cattle herds [CB infections have spread in different regions of France and Denmark [CB infection is endemic in Western Europe and poses a threat to animal health. The study populations and laboratory methods used in the different studies varied, and comparisons between their results should be made with caution.le herds ,23,24, ble herds ,25. CB iCB antibodies found in cattle herds indicates that cattle, as hosts of an active infection, pose a risk of spreading zoonosis to humans, such as farmers and veterinarians [CB infection in cattle herds and the risk to people handling the animals.The presence of inarians ,27. Thisinarians . Since tCB DNA has been detected in the feces, vaginal mucus, milk, and abortion material of dairy cattle, indicating an active infection [CB DNA-positive pooled milk samples collected for surveillance indicated that more than one out of ten herds in Estonia had at least one animal with active infection at any given time. Older animals are at a higher risk of being antibody positive to CB likely because of a potentially longer exposure time [CB infection could not be determined in Estonian cattle herds. Parturition may or may not be associated with the secretion of CB, and the current state of knowledge suggests that control measures should focus on the whole herd, not only on infected or susceptible animals [nfection ,30. The ure time . In 2012ure time . Approxiure time . As we c animals ,33.CB transmission at the conventional milking parlor, which is commonly used in Estonian dairy cattle herds . The risk of detecting CB DNA in tank milk has been found to be lower in herds using automatic milking systems [DNA detection in pooled milk may indicate intermittent or persistent excretion of the pathogen ,33, whic systems , which i systems .CB-seropositive Estonian sheep flocks was relatively low, but it indicated that the infection occasionally occurs. Compared to Western and Central European sheep flocks, the proportion of CB seropositive Estonian sheep flocks was lower, similar to what has been observed in Northern Europe. A lower CB seroprevalence has been reported in sheep flocks in Norway and Sweden [CB has been detected in different areas of France and the Netherlands [CB infection is endemic in sheep in these countries. CB antibodies have been detected in both dairy and meat production systems [CB seroprevalence .The study results demonstrated that the prevalence of d Sweden ,25, and d Sweden ,24,36. Cherlands ,24 and c systems ,36. Kamp systems  suggeste systems . AdditioCB prevalence in sheep flocks may pose a public health risk [Because human QF outbreaks are often associated with small ruminants farming or contact with infected animals or their products, even a low lth risk .CB antibody-positive goat flocks were detected in Estonia. This finding is similar to those reported in Norway and Sweden [CB antibodies in the Netherlands and 61% in France [No d Sweden ,25. Howen France ,24. Kampn France  suggesteCB seroprevalence was observed in dairy cattle herds than in beef cattle herds. These results are in accordance with those reported in other countries [CB-positive herds has been associated with larger herds, higher herd density of the area, managemental differences including housing practices and herd size, and outdoor and indoor environmental conditions [A higher ountries ,31. A siountries ,24. A hinditions ,24. Ryannditions  identifiAlthough human QF outbreaks are mostly associated with small ruminants , outbreaCB infection is present in Estonian cattle herds, especially in dairy cattle, it is necessary to raise farmers’ awareness about the possible risks associated with CB infection in humans and animals. Schimmer et al. [CB-seropositive goats increased the odds of the farmer being seropositive as well, while no such relation was identified in dairy cattle farmers. Farmers should also be encouraged to contact veterinary authorities in case of animal health issues possibly related to QF, so that the spread of the infection can be promptly limited. Testing of imported animals originating from QF-endemic areas should be encouraged to restrict the purchase of CB-infected animals. In Estonia, 9.62% of veterinary professionals and 7.73% of dairy cattle farmers tested CB seropositive, which is higher than that in the general population (3.9%) [CB and should be informed of the risks associated with working or having contact with ruminants of unknown CB status.As this study revealed that r et al. ,40 foundn (3.9%) . FarmersCB in Estonia. Similarly, Spanish, Danish, and Irish cattle farms with more animals are more likely to be CB antibody positive [CB can easily spread. In these farms, dairy cattle are kept loose and interact more closely with each other than beef cattle on pastures. When using indoor housing, infectious pathogens might move more easily in the environment owing to the accumulation of dust, formation of aerosols, and transmission between animals. Moreover, larger dairy herds have a number of contacts with visitors, including veterinarians, inseminators, hoof trimers, and animal husbandry consultants, who can present a risk of introducing CB to the farm or between animals. However, a negative association in the univariable analysis of veterinary service was detected in Denmark, presumably due to adequate personal hygiene measures [Larger cattle herds had higher odds of being exposed to positive ,37,41. Tpositive . An incrpositive ,31,37. Omeasures .CB-seropositive cattle herds were found in all regions. Cattle from herds located in the southwestern part and dairy cattle from northwestern herds were less commonly CB seropositive than those from other regions of Estonia. Regional differences have been observed in other European countries. In Northern Ireland, CB seroprevalence in different regions ranges from 33% to 63% in cattle herds and from 3% to 10% in individual animals [CB in different regions [CB-seropositive herds are needed and can be used to conceptualize strategies for eradication programs.Estonian cattle herds were relatively evenly distributed between the counties  and CB-s animals . Signifi animals . Product regions ,42. In ECB seroprevalence has also been found in Danish loose housing systems than in cattle kept tied [CB bacteria and susceptible animals in the herd. Furthermore, limited movement has been suggested to reduce transmission within farms [The prevalence was lower in dairy cattle herds where animals were kept tied compared to herds, keeping the animals loose, or combining tied and free-range management in univariable analysis. A higher ept tied . Keepingept tied . The proin farms . HoweverCB for beef and dairy cattle and sheep, but not for goats in Estonia. Approximately one-tenth of the seropositive samples from cattle also contained CB DNA, indicating that a considerable proportion of exposed cattle may also shed the bacteria, and cattle may pose a risk for human infections. A larger herd size appears to be a risk factor for CB seropositivity in cattle herds, indicating that certain management practices may play a role in CB spread. Regional differences in CB seropositivity in cattle herds may reflect the effect of climatic conditions on CB spread in Estonia. The results of this study can be used to inform risk groups for zoonosis and to implement control strategies to limit the spread of CB in ruminant herds.This study established serological evidence of exposure to


As of 1 December 2018, all medically important antimicrobials (MIA) for veterinary use in Canada required a prescription from a veterinarian for purchase. Cow–calf herds, while numerous and an important component of the food supply chain, have not been included in Canadian national on-farm antimicrobial-use surveillance. Studies of antimicrobial-use practices on extensively managed cow–calf operations are limited, and prior to this study, the effects of the regulatory changes on antimicrobials in cow–calf herds had not been reported. The objectives of this study were to describe antimicrobial use practices on cow–calf operations and any changes associated with the imposed regulations. Overall, antimicrobial use patterns in 2020 remain relatively unchanged in cow–calf herds after the regulatory changes and compared to previous comparable data from 2014. While almost all herds used antimicrobials, the frequency of antimicrobial use within cow–calf operations was low. Antimicrobials were primarily used for the treatment of respiratory disease in calves, neonatal diarrhea, and lameness in adults; however, most herds treated less than 5% of animals for these reasons. The most frequently reported antimicrobials, tetracyclines and florfenicol, were not classified as either high or very high importance to human health.p = 0.05) to treat >5% of nursing calves for respiratory disease, suggesting the importance of vaccination programs for herds at risk. Overall, AMU was similar to previous Canadian studies; however, the percentage of herds using macrolides had increased from a comparable study in 2014.Despite growing concern surrounding antimicrobial use (AMU) and the importance of cow–calf herds to the Canadian livestock industry, surveillance of AMU in cow–calf herds to inform antimicrobial stewardship programs has been sporadic. Producers from the Canadian Cow–Calf Surveillance Network  provided data and almost all reported AMU in at least one animal  in 2019–2020. The most common reasons for AMU were treatment of respiratory disease in nursing calves in 78% of herds and neonatal diarrhea in 67% of herds, as well as for lameness in cows in 83% of herds. However, most herds treated <5% of animals for these reasons. Less than 2.5% of herds treated more than 30% of calves for either bovine respiratory disease or neonatal diarrhea and no herds treated more than 30% of cows for lameness. The most frequently reported antimicrobial was oxytetracycline in 81% of herds, followed by florfenicol in 73% of herds. Antimicrobials with very high importance to human health, such as ceftiofur, were used at least once by 20% of herds but were only used in >30% of nursing calves from one herd. Similarly, while 56% of herds used macrolides at least once, within-herd use was the highest in nursing calves where <4% of herds reported use in >30% of animals. Herds using artificial insemination and calving in the winter were more likely ( Antimicrobial use (AMU) and antimicrobial resistance (AMR) are sources of increasing concern for both human health and the livestock industry . In CanaThe second stream of AMU surveillance collects on-farm data but is limited to broiler chickens, grower-finisher pigs, turkeys, dairy, and feedlot cattle. In this stream, AMU is collected from sentinel farms that are enrolled in CIPARS farm surveillance providing qualitative and quantitative information on AMU as well as the reasons for use. Even with cow–calf operations being the most numerous livestock operations in Canada, with approximately 54,000 operations across the country, and despite cow–calf operations involving the most farm families of any commodity , this seThe Canadian government implemented regulations to enhance veterinary supervision over AMU in 2004, to automatically categorized newly approved antimicrobials as medically important (MIA), thereby making them available by prescription only. In December 2018, new regulations required all MIA antimicrobials, including those approved before 2004, to have a veterinary prescription for purchase by producers ,6. ThereThere are also no recently published data on AMU in cow–calf herds located in Eastern Canada with the last report published in 2008 . The lacThe primary objectives of this study were to determine the types of antimicrobials used on Canadian cow–calf operations and the reason for AMU in different animal groups , as well as any regional differences. The second objective was to compare these data to previously collected baseline data to determine if there have been any changes within the industry since the recent regulatory changes.This study was approved by the University of Saskatchewan’s Behavioural Research Ethics Board (Beh-REB#309).A paper-based survey to assess AMU was developed based on an AMU survey tool administered to Western Canadian producers in 2014 . The surThe survey consisted of two sections. The first section collected AMU information between 1 July 2019, and 30 June 2020, by production group, namely nursing calves, weaned calves, breeding females, and bulls. Questions for each of the production groups were described in separate tables. They included whether any animals from the group had been administered antimicrobials for a list of specific reasons. The lists of production group-specific reasons included whether animals were given antimicrobials for disease prevention or treatment for diarrhea, umbilical infection, respiratory disease, lameness, eye disease, mammary disease, reproductive diseases, and others as appropriate for each production stage. If AMU was reported, the next questions addressed which antimicrobial product or products were administered for the specified reason, the percentage of animals in the herd which received each product , the typical number of doses used, dose per animal, and route of administration.In June 2020, hard-copy surveys were distributed to the 168 participants in the Canadian Cow–Calf Surveillance Network (C3SN) which was established in 2018 . The C3SHerds were recruited through consultation with veterinarians, advertisements through research funding agencies such as the Beef Cattle Research Council (BCRC), provincial beef organizations, and word of mouth. Recruitment targeted herds larger than 40 breeding animals who reported pregnancy checking and had basic calving and production records. Network participants were provided with an honorarium for the completion of the surveys.Using a commercial database program  data from the 2020 AMU survey was merged with data from a 2019 general herd management, production, breeding, and weaning survey and data from a 2020 calving survey. These surveys were modified from a previous report . AntimicAntimicrobial use was also summarized based on its importance to human health. Health Canada’s Veterinary Drugs Directorate, a division of the Government of Canada, developed a system for categorizing antimicrobials based on their importance to human health : categorLogistic regression was used to examine the associations between herd and producer attributes and responses to questions regarding the three diseases most treated with antimicrobials: respiratory disease in nursing calves, diarrhea in nursing calves, and lameness in cows. The outcome was whether the herd reported treating more than 5% of calves or cows for the condition of interest with at least one antimicrobial.p-value < 0.20 were considered for inclusion in the final model. Multivariable models were created using manual backward selection. All factors with a p < 0.05 were retained in the final model and considered statistically significant. Potential confounders were retained in the model if inclusion changed the effect estimate by >25%. Two-way interactions were examined if more than two variables were retained as significant risk factors in the final model (p < 0.05) and the interaction was biologically plausible. Estimates were reported as odds ratios (OR) with 95% confidence intervals (95%CI). When intervening or highly correlated predictors were identified, competing models were assessed and the biologically appropriate model with the lowest Bayesian Information Criterion (BIC) was reported.Exploratory models were constructed in STATA 16  by first screening all unconditional associations that might be logically associated with the outcome to identify potential risk factors. Variables with a Risk factors explored included location of the herd (Western vs. Eastern Canada), herd size, number of animals purchased into the herd in 2020, whether a producer backgrounded calves, producer age, type of record-keeping system, season calving began, location of calving (pasture vs. any type of confinement system), use of community pasture, the use of breeding technologies including artificial insemination (AI), and herd type.The number of animals purchased by each herd during the first half of the year was categorized as above or below the median for all herds and was considered a relative indicator of biosecurity risk for AMU for calf diarrhea and respiratory disease. For evaluating risk factors for AMU for cow lameness, herds were classified depending on whether they purchased more cattle than the median value for all herds throughout the year. Potential risk factors were selected based on previous publications ,13 and eThe secondary objective of the study was to compare the data collected in this publication to the previously collected baseline data to determine if there have been any changes within the industry since the imposition of the new regulations . The relReturned surveys numbered 146 of 168 AMU, for a response rate of 87%: 30% of respondents were from Alberta, 20% from Saskatchewan, 17% from Ontario, 14% from Quebec, 12% from Manitoba, 5% from British Columbia, and 1% from both New Brunswick and Nova Scotia. Two-thirds of herds  were in Western Canada  and 33% (48/146) were in Eastern Canada . Out of the 56 who had previously participated in the WCCCSN [The median number of cows calving per herd was 124 (range: 14 to 1044) and the median number of heifers calving was 18 (range: 0 to 210). The median number of cows calving per herd in Western Canada was 131 (range: 23 to 1044) and heifers calving was 19 (range: 0 to 210). Eastern herds were typically smaller with a median number of cows calving of 67 per herd (range: 14 to 578) and heifers of 8 (range: 0 to 109). The median number of bulls was 7 per herd .p < 0.001), 64% (94/146) reported herd-level records of total numbers of animals treated  (p = 0.36), and 61% (89/146) reported maintaining both types of records  (p = 0.07). Twenty-four herd owners reported using multiple systems for recording individual animal treatments, with most being handwritten . Smartphone systems were the second-most-popular option with 27 users (18%); 22 (15%) reported using a computer-based record system.For the 2019/2020 production cycle, most herd owners  reported maintaining individual animal treatment records  (p = 0.44). Similarly, 98% (96/98) of western herds reported AMU in nursing calves compared to 88% (42/48) in the east (p = 0.02). Antimicrobial use was reported at least once in weaned calves in 66% (96/146) of operations and for bulls in 65% (95/146) of herds; 71% (70/98) in the west and 54% (26/48) in the east for weaned calves (p = 0.04), and 74% (73/98) in the west and 46% (22/48) in the east for bulls (p < 0.001).Antimicrobial use data were collected for nursing calves, weaned calves, cows and bulls . A greatp = 0.35). Category II antimicrobial use at least once was also not significantly different in the east  than in the west  (p = 0.62).Medically important antimicrobials were used at least once in 99% (145/146) of herds within the study, with most herds using more than one category of antimicrobials . Categorp = 0.21). Adult cows and weaned calves were most likely to receive in-feed category IV antimicrobials at least once. The proportion of animals within a herd treated with a category IV antimicrobial was not collected since this class of antimicrobial is provided in-feed for disease prevention and, therefore, typically given to all animals in a particular animal class.No MIAs or category I-III antimicrobials  were admForty-five percent of herds reported the use of at least one MIA in less than 5% of animals in either nursing calves or cows . Most hep = 0.13)  and enrofloxacin (2%) . Ceftiof = 0.13) .Category I drug use  in more p = 0.05) ) . Macroli = 0.05) .p = 0.09). Florfenicol was the second-most used at least once (p < 0.001). Sulfonamide boluses were the final product in this category and were used in 39% (57/146) of herds (p = 0.79).Tetracyclines were the category III product most likely to be reported to be used at least once across all age categories  and wereast once  and was of herds ; 40%  of herds reported the use of tetracyclines in more than 30% of nursing calves . TetracyLameness was the most common reason for the use of antimicrobials across all animal classes with 89% (130/146) of herds reporting that they treated for lameness at least once . RespiraNo producer reported using category I products for disease prevention . Categorp = 0.60). For weaned calves, 5% (8/146) of herds (Products considered as MIA were used for the prevention of diseases such as diarrhea and pneumonia in 18% (26/146) of herds and all animal classes except for bulls . AMU forof herds  and for of herds  reportedNo producer reported using more than two MIAs for disease prevention. The most common MIA used for disease prevention was oxytetracycline. Oxytetracycline was used for disease prevention in nursing calves, weaned calves, and cows in 8% (11/146), 2% (3/146), and 1% (2/146) of herds, respectively .p < 0.001). Most herds using dart guns  delivered less than 10% of total treatments using the dart gun. Nine producers reported using their dart gun to deliver greater than 50% of total treatments for sick animals.Sixty-two percent (90/146) of producers reported using remote delivery systems such as dart guns, crossbows, and pole syringes at least once to treat an animal. Remote delivery was more common in the west with 75% (73/98) of herds reporting use at least once compared to only 35% (17/48) of eastern herds reporting the use of a remote delivery system at least once. Dart guns were the most popular with 29% (42/146) of herds reporting use. Almost all dart gun use was in the west with 41% (41/98) of herds reporting dart gun use while only 2% (1/48) of herds used a dart gun in the east (p = 0.43). Pole syringes were used in 11% (11/98) of western herds and 4% (2/48) of eastern herds (p = 0.22). Roping and restraining of sick cattle for treatment when handling facilities were not available was also reported by 25% (36/146) of herds; 28% (28/98) of herds in the west and 17% (8/48) of herds in the east (p = 0.15).A similar but smaller number of herds reported the use of crossbows  and pole syringes . Crossbows were used in 10% (10/98) of herds in the west and 15% (7/48) in the east  of herds and for respiratory infections in 6% (8/146) of herds . DanofloThe category II drugs most likely to be used at least once in nursing calves were trimethoprim/sulfadoxine combinations, followed by penicillins and macrolides . TrimethThe category III antimicrobials that were most likely to be used at least once in nursing calves were florfenicol followed by oxytetracycline . Florfenp < 0.001), with 86% (84/98) and 63% (30/48) of western and eastern herds, reporting this use, respectively. The number of herds reporting AMU for diarrhea was similar in Eastern and Western Canada (p = 0.99), with both 67% of eastern (32/48) and western (66/98) herds reporting AMU for diarrhea.The number of herds reporting antimicrobial treatment for respiratory disease in calves before weaning varied by region  followed by diarrhea  . RespiraOxytetracyclines were the most common antimicrobials used for disease prevention in nursing calves  . Benzylpp = 0.99).The most common route of administration in nursing calves was subcutaneous (SQ) injection, followed by antimicrobial products being delivered orally (PO) . TreatmeAMU in weaned calves should be considered in the context that most herds weaned in October  or November . The median percentage of calves sold at weaning was 40%, and this did not differ between herds in the east (35%) and west (40%). Almost two-thirds of herds  also reported backgrounding some calves, and 14%  reported having a feedlot. Three herds did not retain any heifer calves as replacements.Ceftiofur, a category I antimicrobial, was used for treating weaned calves with arthritis and eye  infections in three herds . EnrofloSimilar to what was reported in nursing calves many of the farms using antimicrobials treated less than 5% of weaned calves . Three pOverall, respiratory disease was the most common reason for treatment in weaned calves  followed by treatment of arthritis  . FlorfenThe most common method of administering antimicrobials to weaned calves was by SQ injections followed by intramuscular (IM) injections , reflectParenteral ceftiofur was used to treat respiratory disease, reproductive disorders, and lameness in cows . Similarp < 0.001)  .Oxytetracycline, a category III antimicrobial, was by far the most used antimicrobial in cows and bulls and was administered for a variety of reasons . FlorfenNo farms treated more than 30% of their cows; however, 3% (4/146) of farms treated over 30% of their bulls ; howeverp = 0.10). Treatment of lameness in bulls was reported in 68% (66/98) of western herds compared to 35% (16/48) of eastern herds (p < 0.001).Lameness was the most common reason for AMU in adult cows and bulls . TreatmeLameness in adult animals was most frequently treated with oxytetracycline . OxytetrThe most popular route of administration in cows and bulls, as with weaned calves, was SQ injection followed by IM injection .Antimicrobial use by antimicrobial class and percentage of the herd treated was summarized for the three most-common treatment scenarios: preweaning respiratory disease and diarrhea, as well as cow lameness . The antp < 0.20 in the unconditional analysis. In the final multivariable model, which controlled for the calving season and the use of herd records, herds that used AI were more likely  to treat >5% of their calves for respiratory disease compared to herds that did not use AI. Herds that calved in the winter (Dec to Feb) were also more likely  to treat >5% of nursing calves for respiratory disease compared to herds that calved in the spring (March to May).Twenty-one percent (30/146) of herds reported treating >5% of nursing calves with at least one antimicrobial for respiratory disease. Based on unconditional analysis , herds cp < 0.20 in the unconditional analysis.Diarrhea in nursing calves was the second-most-common reason for at least one calf to be treated prior to weaning . Howeverp < 0.20). In the final multivariable model, no factors were shown to lead to an increased likelihood of treating >5% of cows for lameness.Lameness in adult cows was the most common reason for treatment at least once across all animal classes for all diseases in the study ; howeverA summary table was developed to allow for comparison between this study from 2020, and a similar baseline study in 2014 . The tabp = 0.02) (p = 0.03) (p = 0.002)  ( = 0.02) . Macroli = 0.03) . The num= 0.002) .p < 0.001) and the use of pole syringes increased from 1% (1/100) to 11% (11/98) (p = 0.002).The use of some remote delivery systems also increased in western herds between 2014 and 2020. Use of dart guns in herds from the west increased from 18% (18/100) to 41% (41/98)  by Health Canada . Use of Use of ceftiofur, a category I antimicrobial , was repTrends in the primary diseases identified and the approaches to treatment in nursing beef calves have remained stable between the 2014 and 2020 studies. Respiratory disease and diarrhea were the two most-common reasons for using an antimicrobial at least once in nursing calves in both 2020 and 2014. While trends across the years were similar, there was a difference across the country in the 2020 data with the respiratory disease being treated more frequently in herds from Western Canada than from Eastern Canada. In the current study, 78% and 67% of herds treated at least one calf with an antimicrobial for respiratory disease or diarrhea, respectively, with a higher proportion of herds treating respiratory disease in the west than in the east. The relative importance of these diseases was similar to what has been recently observed in the American cow–calf industry, although the percentage of herds reporting treatment in the current study was higher. In the 2017 USDA beef study, 36% of medium-sized herds 50–199 cows) and 50% of larger herds (>200 cows) reported treating at least one calf for respiratory disease and 31% of medium-sized herds and 55% of larger herds for diarrhea [9 cows anTop treatment choices for respiratory disease and diarrhea did not change between 2014  and 2020Macrolides are a category II drug considered of high importance to human health; however, macrolide use for treating respiratory disease in nursing calves was reported by a significantly higher proportion of herds in 2020 than in 2014. This change might be associated with the increasing availability of generic forms of one macrolide and the associated decrease in cost to producers, as well as the emergence of new macrolides. The use of macrolides for treating bovine respiratory disease (BRD) in nursing calves was also more common in 2020 in herds from the west than from the east.Oral administration of MIAs was almost exclusively limited to the treatment of diarrhea in nursing calves via bolus administration. The proportion of herds using an oral MIA for the treatment of diarrhea in calves prior to weaning was 52% in 2014  and 41% Lameness was the most reported reason for AMU in cows and bulls in 2020. Lameness was reported by relatively more western than eastern herds for both cows and bulls, with nearly double the herds treating bulls for lameness in the west as compared to the east. This difference is likely due to the relatively larger herd size and increased number of animals at risk in western herds. The 2017 USDA beef study  and the There are a number of reported differences in the proportion of herds treated for specific diseases between the American and Canadian studies. The reasons for the difference in the percentage of herds treated for respiratory disease, diarrhea, and lameness require further investigation. However, some possibilities could include climate differences in the primary cow/calf rearing areas, farm size, the season of calving, management intensity, recording keeping, and the approach to data collection and analysis.The use of MIAs in 18% of herds for disease prevention (19% from the west) was similar in the present study to the 2014 study (21%) . DiseaseIn the previous 2014 study, 23% of cow–calf producers had reported the use of dart guns 18%), crossbows (10%), and pole syringes (1%) to treat on pasture where handling facilities were not available . In the %, crossbThe main challenge with the use of remote delivery systems is that the total volume delivered by pneumatic darts is often less than 10 mL. This substantially limits the treatment options and typically results in the use of newer MIAs because often newer MIAs have a lower volume per unit of body weight dose . TulathrWhile several herd attribute and management variables were examined, only a very small number were associated with the likelihood that more than 5% of animals treated for any of the three most-common reasons. The only factor significantly associated with the risk of treating more than 5% of nursing calves for respiratory disease in the final multivariable model was the use of AI. The reason for this association could be that, typically, calves are separated from their mother and comingled with other calves while producers process the cows, temporarily increasing animal stress and density, thereby potentially increasing the risk of pathogen transmission. This finding is consistent with previous reports from other studies ,15,16 thThroughout the study, differences between Western and Eastern Canada were noted, including a higher frequency of western herds reporting AMU in nursing calves, weaned calves, and bulls. The variation in approaches to AMU could be due to differences in herd attributes and management practices. There were clear differences in herd size between eastern and western herds. Eastern herds reported a median of 75 bred cows and heifers whereas western herds had a median of 150 bred cows and heifers. Larger herds often require different management and could encounter different disease pressures than smaller herds. Herds from Western Canada were also more likely to maintain both individual-level records than herds located in Eastern Canada possibly due to less of an economic incentive for record maintenance in smaller operations . Less reOther studies have also reported differences between Western and Eastern Canadian cow–calf herds. In a recent summary of management practices, interventions near the time of birth were higher in eastern herds than in western herds . AdminisA limitation of this study and all survey studies is recall bias. In this study, most producers reported maintaining herd (64%) and/or individual animal-treatment records 79%). The utilization of receipts and other sources of information was also encouraged to assist in the completion of the survey. However, historically, the quality/extent of records maintained by cow–calf operations has been questioned 9%. The u. To addrSocial pressures including increased public scrutiny and stigmas in the beef industry around the use of antimicrobials in food production could have led to inaccurate data being provided by producers due to a perceived negative image or consequences related to what could be deemed “unnecessary use”. However, the impact of any hesitation to report use was expected to be minimal, given the need for a veterinary prescription for MIA, the commitment of the producers to completing surveys for this network over many years, the reporting of a range of antimicrobials, including very high importance category I products, and consistency of results across surveys, including surveys before AMU in the livestock industry was a target of public scrutiny.Since the herds enrolled in the study were participants in a longitudinal surveillance network, the sample population is potentially representative of relatively more progressive, intensively managed herds than might be observed in a random sample. While the study gives insight into AMU practices on Canadian cow–calf operations, the data reflects a segment of Canadian herds of similar size under comparable management.The percentage of herds and herd sizes enrolled from each province was, however, representative of all herds within Western and Eastern Canada. The herd sizes included in this study represent the cows from greater than 75% of all beef herds in Canada reported to the 2021 Agriculture Census [Opportunities exist for improvement in the use of antimicrobials in cow–calf operations. The proportion of herds that used any antimicrobial at least once in more than 30% of either cows or nursing calves was relatively small at only 12%. By better understanding the reasons for use in these herds, it might be possible to target intervention strategies to address some of the primary reasons for use. The most apparent target for use reduction is the 12% of herds that reported the use of MIA for disease prevention in nursing calves.The use of antimicrobials for the treatment of lameness was very common but is not necessary or beneficial in all cases. Noninfectious causes are generally responsible for most lameness in beef cattle . For exaFurthermore, the use of antimicrobials for the treatment of diarrhea in calves is another area where it might be possible to implement additional stewardship practices. Viruses can cause diarrhea in calves and viral causes of diarrhea will not respond to antimicrobials; however, it is challenging to differentiate viral and bacterial causes of diarrhea ,24. VeteIn summary, there were few changes between 2014 and the 2020 AMU data presented in the current study. While there was little use of category I antimicrobials of very-high importance to human health in cow–calf herds, macrolide use did increase slightly between 2014 and 2020 in Western Canadian herds for respiratory disease in nursing calves and lameness in cows and bulls. Other regional differences were identified in the frequency of AMU for respiratory disease in nursing calves, the types of products used for treatment, and the use of remote delivery systems. The relative importance of different reasons for treatment is similar to the most recent surveillance report from the United States. However, the proportion of herds reporting use in the current study was higher than that for similar medium-sized herds in the US report.


The consumption of whole grain cereal flour contributes to increased intake of dietary fibre and phenolic compounds beneficial to human health. However, whole grain flour also has some disadvantages, such as poor baking properties and lower technological quality. Applying ultrasonic and hydrothermal treatments can provide new opportunities to modify and improve the baking and biofunctionality of flour as well as the quality of baked goods.in vitro enzymatic digestibility protocol simulating the digestion process in the human gastrointestinal tract was applied to the untreated and treated whole grain flour samples. Total free phenolic compound content and total antioxidant capacity were also determined.The whole grain flour samples of six wheat varieties with different amylose content were studied. The original chemical composition and viscosity profiles of the flour were determined. The flour samples were subjected to ultrasonic treatment at a frequency of 30 kHz and temperature of 40 °C for 10 min and hydrothermal treatment on a magnetic stirrer with heating for 3 min after reaching the boiling point. The treatments were carried out to determine their influence on the studied digestible and antioxidant properties of the flour. A multistep Hydrothermal treatment had a positive effect on the digestibility of the whole grain flour, especially in waxy wheat genotypes compared to those with high amylose content, due to the formation of resistant starch. The hydrothermal treatment had an overall negative effect on the antioxidant capacity of the flour samples, while ultrasonic treatment generally increased the analytical values of total free phenolic compounds by enhancing their extractability. These findings can provide valuable information for the development of new whole wheat foods.To the best of our knowledge, this type of study of the effects of ultrasound and hydrothermal treatment on the digestibility and antioxidant properties has not yet been performed on whole wheat flour with different amylose content. Waxy and high-amylose wheat varieties are considered novel raw materials because of their unique properties in bread making, such as improved bread texture and increased dietary ﬁbre content. Triticum aestivum L.) is one of the most important cereals consumed as a staple in a broad range of foods worldwide  and α-(1→6) linkages that form branch points  and external factors  can affect the digestibility of a cereal-based food , bile extract porcine (B8631-100G), pancreatin from porcine pancreas (P1750-25G), protease from Streptomyces griseus (P5147-1G) and Viscozyme L cellulolytic enzyme mixture (V2010-50ML). Distilled water obtained in a laboratory distillation unit type D-8-SLO  was used for the analyses.All chemicals and enzymes used in this study were of analytical and high performance liquid chromatography (HPLC) grade. The chemicals used were: ethanol 95–96 %, p.a. , methanol 99.8 %, HPLC grade , Folin-Ciocalteu phenol reagent (F9252) of analytical grade (0.67 M), ABTS  diammonium salt (A1888-5G)  and sodium carbonate, anhydrous, 99.5 %, p.a. . The enzymes used for the Triticum aestivum L.): Zemunska rosa, Apche, Titan SBE I, Titan SBE II, W1 and Waxy1, with different amylose content (0–36.5 %), genetic background and geographical origin were used in this study. All investigated genotypes were grown in the experimental field of the Maize Research Institute Zemun Polje, Belgrade, Serbia , during the 2021/2022 growing season. Standard cultivation practices were followed to provide adequate nutrients to the plants and to keep the plots free from diseases and weeds. Whole wheat flour was obtained by milling in a laboratory mill  for fine sample preparation (mesh size 0.5 mm).Six genotypes of wheat (Whole wheat flour samples (10 g) were mixed with water in a mass ratio (hydromodulus) of 1:3, placed in glass flasks and subjected to ultrasonic treatment, which was performed in an ultrasonic water bath  at a frequency of 30 kHz and a temperature of 40 °C for 10 min. After ultrasonic treatment, the mixtures were transferred to Petri dishes and dried overnight in a forced-air oven  at 40 °C and then ground in a laboratory mill . The dry matter content of the samples was determined by the conventional drying method at 105 °C to a constant mass. The experiments were conducted in duplicate.t=200 °C) with magnetic stirrer  and subjected to hydrothermal treatment. The samples were boiled for 3 min after reaching the boiling point, while being continuously stirred manually with a glass stirring rod. The mixtures were transferred to Petri dishes and dried overnight in a forced-air oven  at 40 °C and then ground in a laboratory mill . The dry matter content of the samples was determined by the conventional drying method at 105 °C to a constant mass. The experiments were conducted in duplicate.Whole wheat flour samples (10 g) were mixed with water in a mass ratio (hydromodulus) of 1:6 in glass flasks. The magnet was added to the mixture and placed on a preheated hot plate , with total nitrogen multiplied by factor 5.7 used for wheat and wheat flour , the Van Soest detergent method modified by Mertens  were heated in a viscograph  from 25 to 95 °C at a rate of 1.5 °C/min. The suspensions were thermostatted at 95 °C for 30 min, then cooled to 50 °C and held for a further 10 min. The analyses were performed in two replicates according to the official method (φ(ethanol)=70 % for 30 min at room temperature on a horizontal shaker type Thys 2 . After centrifugation at 11 200×g for 5 min , the supernatant was used for the detection of total phenolic compounds. A volume of 5 mL of the extracts was evaporated to dryness under the N2 stream at 30 °C  and the final residues were dissolved in methanol (1.5 mL). Prior to analyses, the extracts were stored at -70 °C. All extractions were performed in duplicate.Extracts for the detection of total soluble free phenolic compounds were obtained by continuous shaking of 0.5 g of whole wheat flour sample in 10 mL of 2CO3 solution to the tubes, the samples were vortexed . The absorbances of the mixtures were measured  after 40 min at 750 nm. The analyses were performed in duplicate.Total soluble free phenolic content was determined by the Folin–Ciocalteu assay and expressed as mg of gallic acid equivalent (GAE) per kg of dry mass  mass of absolutely dry sample.where N=2). Statistical analyses were performed using Minitab statistical software, v. 19.2.0  to 16.23 % (Titan SBE II)  to 69.34 % (Apache). Based on the amylose mass fraction, the wheat genotype Apache (13.90 %) could be classified as normal, while Zemunska rosa with a typical amylose mass fraction of 19.00 % could be subcategorised as “partially waxy”. Previous studies have shown that partially waxy wheat (16-22 % amylose) is best suited for the production of noodles traditionally used in Asian cuisine ( SBE II) . These ri.e. w(NDF)=73.26 %, also had a very high mass fraction of hemicellulose (β-glucans and arabinoxylans) (66.94 %). On the other hand, the waxy wheat genotype W1 had the lowest mass fractions of all the dietary fibres analysed, which was not the case for the Waxy1 genotype, which had a significantly higher fibre mass fraction. Morita et al.  and Zemunska rosa (19.00 %) showed a similar trend in the development of peak and final viscosity. The high activity of α-amylase, which causes the enzymatic breakdown of starch molecules in the endosperm to simple sugars, may have resulted in low viscosity. This type of flour, usually produced by milling sprouted wheat, has a lower gas retention capacity and could affect the baking ability of bread , while Waxy1 amylopectin genotype showed a significant decrease in digestibility (about 9 %). Furthermore, there was no linear correlation between ultrasonic treatment and the  samples . Moreoveet al. , followed by standard wheat varieties (Zemunska rosa 1.9-fold and Apache 1.7-fold), while wheat genotypes with high amylose content showed the lowest increase in digestibility (Titans SBE II 1.4-fold and Titan SBE I 1.3-fold). The limited increase in digestibility of flour obtained from SBE genotypes can be explained by the formation of resistant starch, which occurs during cooling with retrogradation of starch  samples and the protein content. The ADF content showed a significant correlation with the antioxidant capacity especially in the untreated whole wheat flour samples, followed by the cooked and ultrasonically treated samples. A correlation between protein content and antioxidant capacity of the untreated and, to a lesser extent, the treated samples was also found.This study highlights some of the advantages and disadvantages of different treatments on the digestive and antioxidant properties of whole wheat flour. Hydrothermal treatment had a positive effect on the digestibility of the whole wheat flour types, especially in waxy genotypes compared to those with high amylose content, which can be explained by the formation of resistant starch. Hydrothermal treatment had an overall negative effect on the antioxidant capacity of the flour samples, while ultrasound generally had a positive effect on the total free phenolic compound content. The application of ultrasonic and hydrothermal treatments could provide new opportunities for the modification and improvement of the baking and biofunctionality of flour types as well as the quality of baked goods. Currently, further research is needed to fully understand how various pretreatments, components of a food's complex structure, interactions between macronutrient contents and digestibility affect the antioxidant properties of whole wheat flour. In this regard, the results obtained in this study may be useful for further studies focusing on the effects of pretreatments on the biofunctional properties of whole grain flour types.


Social media is a real-time social sensor to sense and collect diverse information, which can be combined with sentiment analysis to help IoT sensors provide user-demanded favorable data in smart systems. In the case of insufficient data labels, cross-domain sentiment analysis aims to transfer knowledge from the source domain with rich labels to the target domain that lacks labels. Most domain adaptation sentiment analysis methods achieve transfer learning by reducing the domain differences between the source and target domains, but little attention is paid to the negative transfer problem caused by invalid source domains. To address these problems, this paper proposes a cross-domain sentiment analysis method based on feature projection and multi-source attention (FPMA), which not only alleviates the effect of negative transfer through a multi-source selection strategy but also improves the classification performance in terms of feature representation. Specifically, two feature extractors and a domain discriminator are employed to extract shared and private features through adversarial training. The extracted features are optimized by orthogonal projection to help train the classification in multi-source domains. Finally, each text in the target domain is fed into the trained module. The sentiment tendency is predicted in the weighted form of the attention mechanism based on the classification results from the multi-source domains. The experimental results on two commonly used datasets showed that FPMA outperformed baseline models. The Internet of Things (IoT) has become a major focus in the IT industry. IoT connects physical objects to the online world, making them virtual intelligent objects based on sensors. To simulate real-world intelligence, millions of physical objects are interconnected through sensor devices. Today, IoT is using big data sentiment analysis to reshape, analyze, and improve integrated information processing systems based on sensors . SentimeData from social sensors have different types of themes, and they can be considered as different domains. Currently, the approach used for sentiment analysis in a single domain is usually supervised learning of annotated samples from that domain, but this process is labor-intensive and difficult to adapt to new domains. As shown in The fast development of IoT has significantly contributed to the promotion of sentiment analysis due to the integration of big data, cloud computing, and 5G . Cross-dFrom the second perspective, Chattopadhyay et al.  assignedWe propose a method for cross-domain sentiment analysis based on feature projection and multi-source attention (FPMA). The model optimizes the representation of the private and shared features through orthogonal projection, which enables the sentiment to be predicted based on the attention mechanism.We suggest a multi-source selection strategy based on the domain discriminator’s selection of the source domains that more closely resemble the text features of the target domain, effectively alleviating the negative transfer problem caused by source domains of low relevance.The experimental results of FPMA for both English and Chinese datasets show that the model outperforms the baseline models. We also validated the effectiveness of FPMA through ablation experiments.In this paper, we not only attempt to discard invalid source domains but also continuously optimize the feature representation to extract effective features. We propose a cross-domain sentiment analysis method based on feature projection and multi-source attention. In this method, we extract shared and private features using two feature extractors and a domain discriminator. We also use orthogonal projection to purify the private features and fuse the shared features. Next, we assign weights to the source domains based on the similarity of the private features. Finally, we predict the sentiment tendency of the target domain with an attention mechanism. Furthermore, in the case of too many source domains, we exploit the probability estimates from the domain discriminator to select the source domains that more closely match the target domain. The main contributions of this paper are as follows:Domain adaptation is an important part of transfer learning , which aIn multi-source domain adaptation, more consideration should be given to how multiple source domains can be combined. Guo et al.  combinedAttention mechanisms were first developed in the field of computer vision and were introduced into the field of natural language processing through machine translation  tasks. TGenerative adversarial networks were proposed by Goodfellow et al. , who useThe dataset is divided into different domains based on the topic of the texts. Suppose there are labeled text data from We propose a method for cross-domain sentiment analysis based on feature projection and multi-source attention. The overall structure is shown in The network structures of the feature extractors, domain discriminator, and sentiment classifier are shown in The feature processing step is divided into two main processes: (1) feature extraction and (2) feature purification and refusion. The former extracts the important features, while the latter further optimizes the extracted features to maximize their effectiveness for text classification.The feature extraction process has a domain discriminator, a shared feature extractor, and After adversarial training, the shared feature extractor extracts purer shared features, and the domain discriminator learns which domain the input features come from, enabling an improved separation between private features and shared features. It should be stressed that the discriminator plays a crucial role in the multi-source selection strategy to filter out ineffective source domains.Although the shared features obtained by the adversarial training are purer, certain shared features may still be intermingled with the private features of each source domain, degrading the sentiment classification. Inspired by Qin et al. , this woThe process of two-dimensional orthogonal projection is shown in In addition, the shared features mixed in with the private features may be redundant or may not be extracted by the shared feature extractor. The orthogonal projection shown in The formulas for the above process are:To simplify the depiction of the processes, we designate the fusion process of shared features The input to the source domain sentiment classifier is the concatenation of the purified private features and the fused shared features described above. If The training process for FPMA is divided into two parts. After initializing all the network parameters, the first step is the training of the domain discriminator, which enhances its discrimination ability by minimizing adversarial losses. The second step is the training of the feature extractors and the sentiment classifier, updating the parameters through adversarial loss and sentiment classification loss. The weight coefficient Algorithm 1. Module training processInput:     samples with sentiment label      samples for the target domain      samples with domain label Output:     Optimized parameter set 1:Initialize parameter set 2:repeat3:  for 4:    5:    for 6:      Take 7:      Extract shared features 8:      Calculate adversarial loss 9:      if 10:        Extract private features 11:        Calculate private loss 12:      Calculate loss 13:      Update parameters of the domain discriminator by minimizing 14:    end for15:  end for16:  17:  for 18:    Take 19:    Calculate two orthogonal projections to purify private features and fuse shared features using Equations (4)–(8)20:    Calculate sentiment classification loss 21:  end for22:  for 23:    Calculate adversarial loss 24:  end for25:  26:   Update parameters of the shared feature extractor, private feature extractor, and sentiment classifier by minimizing 27:return optimized parameter set According to the practice commonly adopted for generative adversarial networks, the domain discriminator is trained first, and then its parameters are fixed before training others. The specific process is shown in Algorithm 1.The text data in the source domain can provide rich feature information to the target domain, but certain source domain samples may make negative contributions to the domain adaptation; this is called negative transfer. In response, this paper proposes a multi-source selection strategy, as shown in A text vector from the target domain is sequentially fed into the trained private feature extractors and domain discriminator, and the probability distribution estimates The multi-source selection is performed only when the standard deviation exceeds a certain threshold, and the source domains with a probability higher than the average probability The key to weighted prediction is to find the correlation between the source domains and each text in the target domain. First, all the texts in each source domain are assigned private features through the corresponding domain private feature extractor. Averaging these private features  captures a large amount of feature information from the domain. Thus, the average private feature can be regarded as a typical feature of each domain. Second, when a text from the target domain passes through the trained private feature extractors, The attention mechanism is divided into two main steps: (1) calculating the weight coefficients based on the query and key vectors, and (2) weighting the value vectors according to the weight coefficients and summing them. The first step can be subdivided into two stages: (1) calculating the similarity or correlation between the query and key vectors, and (2) normalizing the original scores from the first stage. Therefore, let The Amazon review dataset  is one oThe online_shopping_10_cats dataset is a commonly used Chinese sentiment classification dataset. It is divided into 10 categories. The number of positive and negative reviews is about 30,000 each, as shown in BERT consisted of 12 layers, 768 hidden units, and 12 attention heads. All the networks used the Adam optimizer in the parameter optimization process, with an initial learning rate of 0.0001 and a batch size of 64. The weight coefficient, In order to verify the effectiveness of FPMA, experiments were conducted to compare it with several baseline models. The amount of data in the dataset is relatively balanced; thus, we used classification accuracy to evaluate the performance of the various methods. We used a multi-source selection strategy on the online_shopping_10_cats dataset but not on the Amazon review dataset for its limited number of domains.mSDA : marginaDANN : extractMDAN(Hard-Max), MDAN(Soft-Max) : two advMAN : learns MDAJL : employsHM-LTS : combineSDA : uses a The baseline models for the Amazon review dataset included:BTDNNs : transfeMDAN : uses doWS-UDA : an unsu2ST-UDA : furtherAdEA : utilizeThe baseline models for the online_shopping_10_cats dataset included:To further validate the effectiveness of FPMA, we conducted ablation experiments on two datasets. This paper proposes a cross-domain sentiment analysis method based on feature projection and multi-source attention, aiming to empower the IoT industry to leverage big data sentiment analysis with improved classification accuracy. The model extracted shared and private features using a domain discriminator. For improved classification, it also employed feature projection to further fuse and purify the shared and private features. To alleviate the effect of negative transfer caused by invalid domains, this study also offered a multi-source selection strategy. This strategy selected the source domains with greater correlation to each text in the target domain for classification prediction. FPMA outperformed previous baseline models in terms of average accuracy for both the Amazon review and the online_shopping_10_cats datasets. Moreover, the effectiveness of the feature processing and the multi-source selection strategy was verified through ablation experiments. This framework can benefit the IoT community through more effective sentiment analysis using big data. Performing sentiment analysis on data from social sensors can better drive IoT sensors to obtain valuable data that meet user demands, enabling the realization of various intelligent systems such as smart homes.In future work, we will further explore applications for datasets with richer sentiment labels. Furthermore, we intend to enable FPMA to perform multi-modal analysis, which considers the fusion of different types of data from multiple sensors. In terms of method application transfer, it is also challenging to collect sufficient data for a newly launched system to train an unsupervised log anomaly detection model. Similar to cross-domain sentiment analysis, a new system often requires log data from other systems for log anomaly prediction. We will continuously improve FPMA and apply it to log anomaly detection.


Gossypium hirsutum, Gohir.A03G0737001.1, was studied using sequence and bioinformatic tools. The encoded protein (referred to here as GhCPP1-A0A1U8HKT6) was predicted to function as a Chaperone-like protein of protochlorophyllide oxidoreductase (CPP1), which is involved with initiation of photochemical reactions of chlorophyll biosynthesis. Sequence analysis indicates it is embedded in the chloroplast envelope membrane through four transmembrane regions and contains a J-like domain that is structurally similar to the J domain of DnaJ/Hsp40 “holdase” chaperone proteins.A gene of unknown function identified in IntroductionGossypium hirsutum,Gossypium barbadense,Gossypium mustelinum,Gossypium tomentosum,Gossypium darwinii) were sequencedCotton plays a significant role in the United States economy as it is estimated to generate over 200,000 jobs and $25 billion dollars in annual revenueGossypium hirsutum gene Gohir.A03G073700 (CottonGen: mRNA ‘Gohir.A03G073700.1_UTX-TM1_v2.1"https://www.cottongen.org/bio_data/5920329), and associated protein  here referred to as GhCPP1-A0A1U8HKT6, is a chaperone-like protein of POR1 (CPP1). Angiosperms, such asG. hirsutum, require light for the biosynthesis of the green pigment chlorophyll. In one of the later steps of the biosynthetic pathway, protochlorophyllide is reduced to chlorophyllide with facilitation and catalysis by protochlorophyllide oxidoreductase (POR), a light-dependent enzymeG. hirsutum due to its structural and sequence features depicting similarity to already identified CPP1 proteins in angiosperms and related species.We predict that one of these genes of unknown function, theSequence Features). Interestingly,Arabidopsis thalianaandNicotiana benthamianaCPP1 proteins are indicated to contain three, not four, TM regionsArabidopsis CPP1, At2g20920, has been identified to also contain four TM regionsThe InterPro webserverHomologyArabidopsisproteins was assessed using the TAIR databaseOstreococcus tauriandChlamydomonas reinhardtii. AtCPP1 promoter activity is low in the globular stage ofArabidopsis embryogenesis but increases throughout the heart and linear stages and persists through the mature embryo stagein vitroimport ofArabidopsisPORA and PORB isoforms into isolated etioplastsHomology of GhCPP1-A0A1U8HKT6 toN. benthamiana  andA. thaliana, the bryophytePhyscomitrella patens, and a cyanobacteriumBrasilonema angustatum were aligned with GhCPP1-A0A1U8HKT6 , with highly-conserved residues in GhCPP1-A0A1U8HKT6 identified by ConSurfThe “holdase” activity of the molecular co-chaperone DnaJ has been attributed to a J domain which is an approximately 70 amino-acid sequence containing four helices with a loop region between the second and third helixStructural Featuresdepicts two high-confidence modeled regions between amino acids 56-119 and 150-254 and a low-confidence modeled region between them from amino acids 119-150. The structure is oriented vertically to show the cytoplasmic domain at the lower part of the image and the four transmembrane helices at the upper part of the image. The transmembrane domains exhibit expected high hydrophobicity as visualized by the ChimeraX surface calculation tool (same orientation as1C). A structural overlay of the J-like domain (amino acids 63-119) of GhCPP1-A0A1U8HKT6 with the J domain of the human DnaJ family member Tid1 (PDB ID: 2DN9) displays a similar anti-parallel hairpin between the horizontally-displayed alpha helices II and III, although GhCPP1-A0A1U8HKT6 lacks the fourth helix of human Tid1 and has a shorter loop  were used to predict and visualize the model structure of GhCPP1-A0A1U8HKT6.of the GhCPP1-A0A1U8HKT6 J-like domain (transparent ConSurf colored surface) with the J-like domain of TIM16  that shows a highly conserved surface in GhCPP1-A0A1U8HKT6 at the modeled protein-protein interaction site with the TIM14 protein (dark blue ribbon).When the DALI databaseConclusionGossypium hirsutum. GhCPP1-A0A1U8HKT6 is predicted to be anchored in the plastid membrane of the chloroplast where it could interact with POR and support its entry into the chloroplast where photochemical reactions of chlorophyll biosynthesis occur, similar to Arabidopsis CPP1 to which it has high sequence similarity. The molecular function of the J-like domain is still unclear. Similarity in structure to the J domain suggests a similar protein-protein interaction domain function as in the “holdase” activity of molecular chaperones, although the lack of a HPD motif indicates different binding partners. This is supported by the J-like domain in mitochondrial TIM16 being part of a heterodimer complex. It would be interesting for further studies to explore potential binding partners of GhCPP1-A0A1U8HKT6.Evidence from protein sequence, homology, and structure support that GhCPP1-A0A1U8HKT6 is likely a chaperone-like protein of POR1 in10.22002/a9fcw-h5n51Description: ConSurf sequence conservation results. Resource Type: Dataset. DOI:


The flour functionality and particle size distribution of wheat flour obtained on roller milling are dependent on the type of wheat, tempering conditions, and milling conditions. In this study, the impact of the tempering conditions (moisture and time) on the chemical and rheological properties of flour from blends of hard red wheat were analyzed. The wheat blends B1-25:75 (hard red spring (HRS)/hard red winter (HRW)), B2-50:50, and B3-75:25, which were tempered to 14%, 16%, and 18% for 16, 20, and 24 h, respectively, were milled using a laboratory-scale roller mill (Buhler MLU-202). Protein, damaged starch, and particle characteristics were influenced by blending, tempering, and milling streams. For all the blends, the protein content varied significantly among the break flour streams; the damaged starch content varied greatly in the reduction streams. The increased damaged starch content of the reduction streams proportionally increased water absorption (WA). Higher proportions of HRS in the blends significantly decreased the pasting temperature of the dough, as measured using Mixolab. Principal component analysis proved that the protein content was the key determinant in particle characteristics, WA, and pasting properties of the flour, especially in blends with a higher proportion of HRS. Nearly 20% of humans’ calorie intake worldwide is dependent on wheat . Grain iAccording to Campbell , the twoIn general, the quality of wheat is determined to a great extent by the environment and management practices ,12,13,14Although there have been numerous studies on the impact of tempering on flour quality and biochemical variations in milling streams, studies on the impact of blending on the composition and rheological parameters of milling streams are limited. Additionally, the published literature on blending focuses on blending wheat varieties of the same cultivars. For instance, the authors of  detailedThe hard red winter (HRW) and hard red spring (HRS) wheat grains used in the study were procured from Montana Flour and Grain . The moisture contents of the grains were measured following ASABE Standard S352.2 for whole kernels using the oven method ; proteinInitially, the wheat samples (HRW and HRS) were tempered under the studied conditions . Thereafter, the tempered HRW and HRS wheat samples were mixed in different ratios to obtain blends (2000 g) of varying protein content. These blends were milled using a laboratory mill  according to AACC 26-21.02 [6H8O7), and 1 drop of sodium thiosulphate (Na2O3S2). After the solution in the reaction bowl reached 35 °C, 1 g of flour was dispersed into the solution. The absorption of iodine by starch varied with the intensity of the damage and was measured.The chemical composition of the flour streams and straight-grade flour was determined according to standard protocols: crude protein (AACC 46-30.01), ash (AACC 08-01.01), moisture content (AACC 44-15.02), and damaged starch (AACC 76-33.01) . The amp3)was transferred to the dispersion chamber of the particle size analyzer, where it was dispersed as a thin layer on the glass slide [d10, d50, and d90. The values designated as d10, d50, and d90 indicate that 10, 50, and 90% of the measured particles are smaller than their respective value. It should be noted that all these diameters were calculated based on the assumption that the particles are spherical.The particle analyzer Malvern Morphology G3  was used to determine the size distribution of the flour samples. The flour sample  . MoreoveThe effect of tempering time, moisture, samples, and fraction was assessed with a fixed-effect model, as described by  using SAp > 0.05). However, in commercial milling, profitability is largely dependent on extraction. Thus, while not statistically significant, depending on the capacity of mills, even a 0.5% increase or decrease in the flour yield over time can influence the commercial value. Furthermore, varying the tempering moisture content from 14% to 18% resulted in an increase in flour yield from 71.7% to 73.1%. On the other hand, longer tempering time significantly (p < 0.05) reduced the flour yield. For instance, a yield as high as 73.7% was obtained by tempering the grains for 16 h, while it was reduced to 70.6% at 24 h  than HRS (68.4%). Additionally, the incorporation of greater percentages of HRS in the blend decreased the milling yield. For instance, B1, B2, and B3 had flour yields of 74.3%, 73.3%, and 72.9%, respectively . It shou at 24 h .p < 0.05) with successive passages in the break stream. It varied from 13.41% in 1 BK to 16.75% in 3 BK. Tempering conditions also significantly (p < 0.05) affected the protein content of the milling streams (p < 0.05). Similar increases in the ash content of reduction streams were reported by [The protein, ash, and damaged starch content of the flour samples varied with respect to the milling stream and tempering conditions. The influence of blending was more prominent on the protein content of the flour  than on  streams . Similarorted by . Apart fp < 0.05) in the milling streams (p > 0.05). ANOVA results showed that the interaction between moisture content and time had a significant impact on the damaged starch content of the flours (p > 0.05). Moreover, ANOVA results showed that milling streams (fraction) and tempering conditions significantly contributed to the variation in damaged starch, rather than blending.The degree of starch damage varied significantly  changes in the d10 value with respect to tempering moisture (d50 and d90 were not significantly (p > 0.05) affected by tempering conditions. Apart from blending and moisture content, the interactions between wheat × tempering time and moisture content × tempering time also contributed to the variations in particle characteristics such as d10, d50, and d90 .The rheological behavior of wheat dough is influenced by water, starch, and protein. In addition to its major components, other minor constituents such as pentosans and enzymes contribute to the complex rheological characteristics of the flour. When wheat flour is mixed with sufficient water, solubilization and unfolding of the protein occur, and it forms a continuous network. The starch molecules are embedded into this protein network to form a viscoelastic dough. The viscoelastic characteristics of dough undergo changes during mixing and heating. Mixolab measures the changes in the dough system pertaining to simultaneous heating and mixing. Water absorption (WA) is the amount of water required for the samples to reach an initial torque of 1.1 Nm (at 30 °C) for dough development. In the analysis, WA varied with respect to samples and milling stream. HRS samples had the highest WA of 68.8%. WA increased from 58.3% to 72.2% as the samples varied from 1 BK to 3 M. Even though grain moistening to 18% and longer tempering duration (24 h) increased the WA, the changes were statistically not significant (p > 0.05). T1 is the time required by the equipment to reach the required consistency of 1.1 Nm. T1 for the flour was higher (155.29 s) when the grains were tempered to 14% moisture content compared with 18% (135.75 s) (p < 0.05) with the milling stream. For instance, DS decreased from 10.1 min (1 BK) to 8.2 min for 3 M. Although there was an increase in dough stability with grain moistening and tempering time, the increase was statistically insignificant (p > 0.05).The C1 scores of the Mixolab analysis (corresponding to dough development at 30 °C) were statistically similar with respect to tempering conditions, sample, and milling streams. Although there was a gradual increase in the values with an increase in the protein content of the flour for the blends, the increase was statistically insignificant (35.75 s) . StabiliIncreasing the temperature of the system to 60 °C weakened the proteins and initiated the gelatinization of the dough. The low-energy hydrogen bonds in the glutenin network were easily broken with an increase in temperature . Thus, ip > 0.05) influence the starch gelatinization and pasting characteristics . The flour from the reduction streams had significantly lower C3 than the break streams. Additionally, for the break streams, C3 values were as high as 1.5 Nm, whereas it was successively reduced to 1.3, 1.1, and 0.8 Nm with the passage from 1 M to 3 M. The rate of gelatinization (β) was statistically different among the samples  decreased with blending. The decrease was proportional to the increase in HRS content. Among the samples, the lowest C3 value was observed for the HRS wheat (0.9 Nm). Tempering conditions did not significantly ( samples . For exap > 0.05), C4 varied with respect to the wheat samples (ranging from 1.4 to 1.7 Nm). Additionally, C4 values varied greatly among the milling streams. C4 was 1.8 Nm for 1 BK, whereas it was reduced to 1.2 Nm for 3 M. The cooking stability rate (γ) of the analyzed samples was not influenced by blending and tempering conditions. The torque obtained at the end of the test (C5) varied significantly (p < 0.05) with respect to the samples. The final torque was 2.6 Nm for B1 and decreased to 1.9 Nm for HRS samples. The flour samples exhibited a decrease in the final torque with an increase in protein content. Even though the break streams had higher torque than the reduction streams, there was a significant reduction in C5 torque with successive milling streams.In the last stage of analysis, using Mixolab, we measured gel stability (C4), i.e., the soundness of the starch fraction of the flour. It also corresponds to the presence of amylases in the samples. Although the variation was not significant (p < 0.05) influence on the pasting temperature range (D3–D2), which is the difference between the protein weakening temperature and the temperature at C3. For instance, it increased from 14.71 °C for the samples tempered to 14% (w.b) to 17.84 °C for those tempered to 18% (w.b). Increasing the proportion of the HRS content significantly (p < 0.05) narrowed the pasting temperature range . This enables the identification of similarities and differences based on the correlation of variables and pattern recognition. In the analysis, 92.29% of the variability in the data was explained by the first two PCs, where 77.5% of the variability was explained by PC1 and 14.8% by PC2 . In PCA In the analysis, there was an increase in the protein and damaged starch content of the flour with the milling stream and blends. It was observed that the increase in the protein content was prominent in the break stream, while the damaged starch content varied greatly in the reduction streams. This can be associated with the differences in the protein distribution inside the wheat kernels. In a typical wheat grain, the proportion of protein in the mature endosperm increases radially towards the outward direction . This diMechanical damage in starch is inevitable during the milling of grains . Shear fd10 values, as the studied time (greater than 16 h) was significant enough to ensure the moisture migration inside the kernels. Moreover, there was an increase in the mean particle size of the flour with an increasse in the proportion of HRS in the blend. With a higher proportion of HRS, the overall hardness of the wheat kernels increased, resulting in larger flour particles [The particle size distributiosn of flour depends on factors such as tempering, roll adjustments, and wheat characteristics . As expearticles . The pararticles .w/w) for every 1% increase in protein content [The WA of the flour depends on the quality and content of proteins, the native starch, the damaged starch content, and the fiber (pentosans) content . In the  content . Additio content , and the content , thus inDuring the mixing stage, the hydration of proteins leads to their expansion. This increases the interaction between the thiol groups of the protein, and disulfide bonds are created, which plays a significant role in the formation of the gluten network. Furthermore, the starch granules are embedded in the gluten network forming the dough. Thus, the behavior of the dough is also dependent on the starch content. Increasing the temperature from 30 to 90 °C during the analysis weakened the protein network and gelatinized the starch. Unlike in batter, where the complete gelatinization of the starch occurs upon heating, in dough systems, the gelatinization of the starch is incomplete due to the limited availability of water. This leads to the transfer of moisture from proteins to starch during cooking  and protThe distribution of lipids , fatty aPCA results revealed a negative correlation between particle characteristics and damaged starch. This inverse relationship implies that a reduction in particle size was associated with an increase in starch damage, which in turn was positively correlated with WA. Moreover, a reduction in particle size promotes the redox conversion of sulfhydryl (-SH) groups to disulfide groups . This leBy blending HRS and HRW, the protein content was intentionally varied, contributing to a change in the quality of protein among the samples. Subsequent changes in the starch granule type and distribution also occurred in the blends . These dIn summary, tempering and blending affected the composition and particle characteristics of flour. These variables had a significant influence on particle size, damaged starch content, and protein content; subsequent differences were observed in rheological properties. The flour from break and reduction streams differed in composition and rheological properties, contributing to the differences in functionality. Variations in the properties were also exhibited with successive milling streams in both break and reduction streams. An increased proportion of HRS in the blends varied the pasting characteristics and cooking stability of the flour. The experiments illustrated that blending not only affects the protein content and composition but also the starch quality and thus rheological properties. Therefore, tempering and blending can effectively modify the rheological and functional properties of flour.