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Three penetrating captive bolt (PCB) placements were tested on cadaver heads from swine with estimated body weight (BW) >200 kg (sows = 232.9 ± 4.1 kg; boars = 229.3 ± 2.6 kg). The objectives were to determine tissue depth, cross-sectional brain area, visible brain damage (BD), regions of BD, and bolt-brain contact; and determine relationships between external head dimensions and tissue depth at each placement. A Jarvis PAS-Type P 0.25R PCB with a Long Stunning Rod Nosepiece Assembly and 3.5 g power loads was used at the following placements on heads from 111 sows and 46 boars after storage at 2 to 4 °C for ~62 h before treatment: FRONTAL (F)-3.5 cm superior to the optic orbits at midline, TEMPORAL (T)-at the depression posterior to the lateral canthus of the eye within the plane between the lateral canthus and the base of the ear, or BEHIND EAR (BE)-directly caudal to the pinna of the ear on the same plane as the eyes and targeting the middle of the opposite eye. For sows, the bolt path was in the plane of the brain for 42/42 (100%, 95% confidence interval [CI]: 91.6% to 100.0%) F heads, 39/40 (97.5%, 95% CI: 86.8% to 99.9%) T heads, and 34/39 (87.5%, 95% CI: 72.6% to 95.7%) BE heads; for the heads that could reliably be assessed for BD damage was detected in 25/26 (96.2%, 95% CI: 80.4% to 99.9%) F heads, 24/35 (68.6%, 95% CI: 50.7% to 83.2%) T heads, and 5/40 (12.5%, 95% CI: 4.2% to 26.8%) BE heads. For boars, the bolt path was in the plane of the brain for 17/17 (100.0%, 95% CI: 80.5% to 100.0%) F heads, 18/18 (100.0%, 95% CI: 81.5% to 100.0%) T heads, and 14/14 (100.0%, 95% CI: 76.8% to 100.0%) BE heads; damage was detected in 11/12 (91.7%, 95% CI: 61.5% to 99.8%) F heads, 2/15 (13.3%, 95% CI: 1.7% to 40.5%) T heads, and 7/14 (50.0%, 95% CI: 23.0% to 77.0%) BE heads. Tissue depth was reported as mean ± standard error followed by 95% one-sided upper reference limit (URL). For sows, total tissue thickness was different (P < 0.05) between placements (F: 52.7 ± 1.0 mm, URL: 64.1 mm; T: 69.8 ± 1.4 mm, URL: 83.9 mm; BE: 89.3 ± 1.5 mm, URL: 103.4 mm). In boars, total tissue thickness was different (P < 0.05) between placements (F: 41.2 ± 2.1 mm, URL: 56.3 mm; T: 73.2 ± 1.5 mm, URL: 83.4 mm; BE: 90.9 ± 3.5 mm, URL: 113.5 mm). For swine > 200 kg BW, F placement may be more effective than T or BE due to less soft tissue thickness, which may reduce concussive force. The brain was within the plane of bolt travel for 100% of F heads with BD for 96.2% and 91.7% of F sow and boar heads, respectively.

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The burgeoning research and applications of technological advances are launching the development of precision livestock farming. Through sensors (cameras, microphones and accelerometers), images, sounds and movements are combined with algorithms to non-invasively monitor animals to detect their welfare and predict productivity. In turn, this remote monitoring of livestock can provide quantitative and early alerts to situations of poor welfare requiring the stockperson's attention. While swine practitioners' skills include translation of pig data entry into pig health and well-being indices, many do not yet have enough familiarity to advise their clients on the adoption of precision livestock farming practices. This review, intended for swine veterinarians and specialists, (1) includes an introduction to algorithms and machine learning, (2) summarizes current literature on relevant sensors and sensor network systems, and drawing from industry pig welfare audit criteria, (3) explains how these applications can be used to improve swine welfare and meet current pork production stakeholder expectations. Swine practitioners, by virtue of their animal and client advocacy roles, interpretation of benchmarking data, and stewardship in regulatory and traceability programs, can play a broader role as advisors in the transfer of precision livestock farming technology, and its implications to their clients.

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Acute outbreaks of respiratory disease in swine at agricultural fairs in Michigan, USA, in 2015 raised concern for potential human exposure to influenza A virus. Testing ruled out influenza A virus and identified porcine hemagglutinating encephalomyelitis virus as the cause of influenza-like illness in the affected swine.

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Data from the Food Safety Division, Alberta Agriculture, Food and Rural Development were analyzed to determine the frequency of diagnosis of porcine proliferative enteropathy (PPE) relative to the diagnosis of other porcine enteric infections between 1993 and 1997. Next to colibacillosis, PPE was the most commonly diagnosed enteric disease among those reported.

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