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Abstract Background The timing of artificial insemination is critical to achieve acceptable results in cattle production systems. Over the past 60 years the length and expression of oestrus in dairy cattle has altered. Recent studies have indicated the optimal timing for insemination after the commencement of oestrus may now be earlier than traditional recommendations in beef cattle, as is the case in dairy cattle. The aim of the current study was to evaluate the effect of time from onset of oestrus [as determined by an automated activity monitoring system (AAMS)] to artificial insemination (AI) on pregnancy outcome in Norwegian beef cattle. Five commercial beef suckler herds participated in a cohort study by providing data on the time of AAMS alarm and time of AI. Blood sampling on the day of AI was performed and serum progesterone concentration measured. Pregnancy detection was performed by transrectal ultrasonography and aging of the fetus performed when necessary. A mixed logistic regression model was fitted to study the effect of time from AAMS alarm to AI on pregnancy outcome. Time categories used in the model were 24 h. Results AI periods (n = 229) with serum progesterone concentration

Copyright of Revista Biológico Agropecuaria Tuxpan is the property of Revista Biologico Agropecuaria Tuxpan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The timing of artificial insemination is critical to achieve acceptable results in cattle production systems. Over the past 60 years the length and expression of oestrus in dairy cattle has altered. Recent studies have indicated the optimal timing for insemination after the commencement of oestrus may now be earlier than traditional recommendations in beef cattle, as is the case in dairy cattle. The aim of the current study was to evaluate the effect of time from onset of oestrus [as determined by an automated activity monitoring system (AAMS)] to artificial insemination (AI) on pregnancy outcome in Norwegian beef cattle. Five commercial beef suckler herds participated in a cohort study by providing data on the time of AAMS alarm and time of AI. Blood sampling on the day of AI was performed and serum progesterone concentration measured. Pregnancy detection was performed by transrectal ultrasonography and aging of the fetus performed when necessary. A mixed logistic regression model was fitted to study the effect of time from AAMS alarm to AI on pregnancy outcome. Time categories used in the model were < 12 h, 12–24 h, and > 24 h. Results: AI periods (n = 229) with serum progesterone concentration < 1 ng/mL were available for analysis. Overall pregnancy risk per AI for the whole study period was 65.5%, with an inter-herd variation from 10 to 91%. Median time elapsed from AAMS alarm to AI was 17.75 h. Herd affected pregnancy outcome (P = 0.001), while breed and parity status (heifer/cow) did not. The time category closer to AAMS alarm 0–12 h showed a numerically lower pregnancy risk as compared to the baseline group which had AI 12–24 h after onset of oestrus. Conclusion: This study found no evidence to support a change in the recommended timing of AI in beef suckler cows. [ABSTRACT FROM AUTHOR]

The purpose of this paper is a social one, to present various experimental thermal analyses of sports footwear to identify the areas that ensure the best foot ventilation for comfort in movement. The mechanical properties of the analyzed footwear were determined on the Nano Indenter Agilent G200, with the help of which Young's modulus was determined according to ISO 14577. Thermography measurements were performed at the Oradea University Sports Club. The FLIR SC 640 thermal imaging camera was used, which is a portable thermographic scanning equipment. The measurements were performed on eight athletes (subjects) in a volleyball training session, wearing sports footwear (Asics and Mizuno). Thermographic recordings were made during training at five different times: moment zero (before the start of training), moment one (2 min of training), moment two (5 min of training), moment three (15 min of training), and moment four (at the end of the volleyball training session). For the other three subjects, although having different models of the same sports footwear, the analysis of the thermal distribution values shows they are within the minimum and maximum limits of the five subjects analyzed in the paper. Based on the thermographic recording values obtained, a mathematical model was determined using polynomial regression to predict temperature values outside the range of the experimental data. In the present paper, research was carried out in order to identify the thermal variations of indoor sports shoes used in volleyball training so as to detect the heat exchange between the foot and the outdoor environment. Whether we are talking about winter sports or sports that take place in other atmospheric conditions, the comfort given by the optimal temperature at the level of each body segment is certainly reflected in the level of performance achieved. [ABSTRACT FROM AUTHOR]

Simple Summary: Fertility a very important field for dairy farms and directly affects their economic success. Therefore, early and accurate estrus detection is crucial, particularly for farms using artificial insemination. During the last decades, several automated sensor-based technologies for estrus detection have been developed. Nevertheless, accurate estrus detection still remains a challenge. In this study, the capacity of electronic nose (EN) technology (MENT-EGAS prototype), which was based on 10 non-specified chemical metal-oxide sensors to detect estrus by the direct sampling of odor from the perineal headspace in Holstein dairy cows, was assessed. Principal component analyses (PCA) were applied and identified high discrimination between proestrus and estrus, and between estrus and metestrus in cycling cows. Additionally, high discrimination amongst estrus in cycling cows and pregnant cows was perceived. Based on these findings, we show for the first time that it is possible to recognize estrus accurately in dairy cattle by direct sampling on the perineal headspace using an EN device during milking. In the future, MENT-EGAS technology could be routinely used on dairy cattle farms as a non-invasive, accurate method for estrus detection. Estrus detection is very important for the profitability of dairy herds. Different automatic systems for estrus detection have been developed over the last decades. Our study aimed to assess the ability of the electronic nose (EN) MENT-EGAS prototype to detect estrus, based on odor release from the perineal headspace in dairy cattle by direct sampling. The study was performed in an Italian dairy farm using 35 multiparous Holstein–Friesian cows. The cows were divided into three groups: group I included 10 lactating 5-month pregnant cows, group II included 19 lactating cycling cows, and group III included 6 cows that were artificially inseminated 18 days before the trial. Odors from the perineal headspace were collected using the MENT-EGAS prototype. In group I, odors were collected once a day for 5 consecutive days. In group II, odors were collected twice daily from day 18 until day 1 of the reproductive cycle. In group III, odors were also collected twice daily from the presumable day 18 of gestation until day 22. Principal component analyses (PCA) of the perineal headspace samples were performed. PCA in group I revealed no significant discrimination. PCA in group II revealed clear discrimination between proestrus and estrus, and between estrus and metestrus but no significant discrimination was obtained between proestrus and metestrus. PCA in group III revealed that in four cows the results were similar to group I and in two cows the results were similar to group II. On day 40 of the presumable pregnancy, the ultrasound examination revealed that only the four cows were pregnant and the other two cows were regularly cycling. On the basis of our findings, we conclude that it is possible to accurately detect estrus in dairy cattle from directly collected odor samples using the MENT-EGAS prototype. This represents the first study of estrus detection using an EN detection by direct sampling. EN technologies, such as MENT-EGAS, could be applied in the future in dairy cattle farms as a precise, non-invasive method for estrus detection. [ABSTRACT FROM AUTHOR]

With the high thermal conductivity and breakdown voltage, silicon carbide (SiC) has been treated as a promising material to work in harsh environment especially high temperature. However, due to its chemical inertness and wide band-gap, it is difficult to achieve the ion implantation, etching and good ohmic contact. In this study, silicon carbide on insulator (4H-SiCOI) is applied to fabricate MEMS thermocouple sensor, which can simultaneously compatible with bulk silicon CMOS process. The stress and temperature distribution of the sensor was simulated by COMSOL. After optimized the process parameters, the sensor based on 4H-SiCOI was successfully fabricated. Preliminary test results demonstrated the sensor shows good sensitivity about 1.44 $\times 10^{-{8}}\,\,{V}{m}^{{{2}}}/{W}$ and response time of 3.24ms, which also keeps good linearity and repeatability. This sensor can satisfy the needs of fast and high precision heat detection and our work may have a meaningful reference value for other same type SiC-based MEMS thermocouple sensor design and preparation. [ABSTRACT FROM AUTHOR]

Estrus detection is very important for the profitability of dairy herds. Different automatic systems for estrus detection have been developed over the last decades. Our study aimed to assess the ability of the electronic nose (EN) MENT-EGAS prototype to detect estrus, based on odor release from the perineal headspace in dairy cattle by direct sampling. The study was performed in an Italian dairy farm using 35 multiparous Holstein–Friesian cows. The cows were divided into three groups: group I included 10 lactating 5-month pregnant cows, group II included 19 lactating cycling cows, and group III included 6 cows that were artificially inseminated 18 days before the trial. Odors from the perineal headspace were collected using the MENT-EGAS prototype. In group I, odors were collected once a day for 5 consecutive days. In group II, odors were collected twice daily from day 18 until day 1 of the reproductive cycle. In group III, odors were also collected twice daily from the presumable day 18 of gestation until day 22. Principal component analyses (PCA) of the perineal headspace samples were performed. PCA in group I revealed no significant discrimination. PCA in group II revealed clear discrimination between proestrus and estrus, and between estrus and metestrus but no significant discrimination was obtained between proestrus and metestrus. PCA in group III revealed that in four cows the results were similar to group I and in two cows the results were similar to group II. On day 40 of the presumable pregnancy, the ultrasound examination revealed that only the four cows were pregnant and the other two cows were regularly cycling. On the basis of our findings, we conclude that it is possible to accurately detect estrus in dairy cattle from directly collected odor samples using the MENT-EGAS prototype. This represents the first study of estrus detection using an EN detection by direct sampling. EN technologies, such as MENT-EGAS, could be applied in the future in dairy cattle farms as a precise, non-invasive method for estrus detection.

High-yielding cows may suffer from negative energy balance during early lactation, which can lead to ketosis and delayed ability of returning to cyclicity after calving. Fast recovery after calving is essential when breeding for improved fertility. Traditionally used fertility traits, such as the interval from calving to first insemination (CFI), have low heritabilities and are highly influenced by management decisions. Herd Navigator™ management program samples and analyses milk progesterone and β-hydroxybutyrate (BHB) automatically during milking. In this study, the genetic parameters of endocrine fertility traits (measured from milk progesterone) and hyperketonemia (measured from milk BHB) in early lactation were evaluated and compared with traditional fertility traits (CFI, interval from calving to the last insemination and interval from first to last insemination) and the milk yield in red dairy cattle herds in Finland. Data included observations from 14 farms from 2014 to 2017. Data were analyzed with linear animal models using DMU software and analyses were done for first parity cows. Heritability estimates for traditional fertility traits were low and varied between 0.03 and 0.07. Estimated heritabilities for endocrine fertility traits (interval from calving to the first heat (CFH) and commencement of luteal activity (C-LA)) were higher than for traditional fertility traits (0.19 to 0.33). Five slightly different hyperketonemia traits divided into two or three classes were studied. Linear model heritability estimates for hyperketonemia traits were low, however, when the threshold model was used for binary traits the estimates became slightly higher (0.07 to 0.15). Genetic correlation between CFH and C-LA for first parity cows was high (0.97) as expected since traits are quite similar. Moderate genetic correlations (0.47 to 0.52) were found between the endocrine fertility traits and early lactation milk yield. Results suggest that the data on endocrine fertility traits measured by automatic systems is a promising tool for improving fertility, specifically when more data is available. For hyperketonemia traits, dividing values into three classes instead of two seemed to work better. Based on the current study and previous studies, where higher heritabilities have been found for milk BHB traits than for clinical ketosis, milk BHB traits are a promising indicator trait for resistance to ketosis and should be studied more. It is important that this kind of data from automatic devices is made available to recording and breeding organizations in the future.

Fire detection systems in ships are based on smoke and heat detection in accordance with safety regulations. The rapid advancement of machine vision technology has led to the development of video smoke detection (VSD) systems. In this study, a VSD system is applied to smoke detection within the engine room of the ship. A dataset for a range of scenarios was created with a smoke generator. The method for smoke detection was based on motion detection and a support vector machine classifier, which was used to make candidate regions and perform classification. A local binary pattern descriptor was used to extract the feature vector. A training set was made from a variety of video frames, randomly. Experimental results seldom produced false positive windows in the non‐smoke region. However, if the greyscale value of difference image between background and the smoke is lower than the setting value for motion detection, the system could not detect smoke. Processing time is sufficiently fast for use in real‐time smoke detection systems. To install a VSD system on‐board a vessel, the authors recommend a performance standard of the system which must be met. [ABSTRACT FROM AUTHOR]

This study was conducted to investigate the optimal artificial insemination (AI) time with diagnostic kit at ovulation time. We already applied the patent about the protein in the cow heat mucose in external reproductive tract. And we would examine the accuracy for detection of cow heat by the kit produced with the protein. Evaluation of optimal heat detection was tried two time at 12 hrs and 24 hrs after the heat. And then, AI service also performed two times with no relation to the results of heat diagnosis by heat detection kit and pregnancy rates were checked with rectal palpation on 60th day after AI. Heat diagnostic results by kit in natural heat after 12 hrs in Hanwoo cows were showed 31.3~75.0% on positive in first heat detection and 33.3~100.0% on positve in second heat detection. In the 1st positive results were significant different (p

High-yielding cows may suffer from negative energy balance during early lactation, which can lead to ketosis and delayed ability of returning to cyclicity after calving. Fast recovery after calving is essential when breeding for improved fertility. Traditionally used fertility traits, such as the interval from calving to first insemination (CFI), have low heritabilities and are highly influenced by management decisions. Herd Navigator™ management program samples and analyses milk progesterone and β -hydroxybutyrate (BHB) automatically during milking. In this study, the genetic parameters of endocrine fertility traits (measured from milk progesterone) and hyperketonemia (measured from milk BHB) in early lactation were evaluated and compared with traditional fertility traits (CFI, interval from calving to the last insemination and interval from first to last insemination) and the milk yield in red dairy cattle herds in Finland. Data included observations from 14 farms from 2014 to 2017. Data were analyzed with linear animal models using DMU software and analyses were done for first parity cows. Heritability estimates for traditional fertility traits were low and varied between 0.03 and 0.07. Estimated heritabilities for endocrine fertility traits (interval from calving to the first heat (CFH) and commencement of luteal activity (C-LA)) were higher than for traditional fertility traits (0.19 to 0.33). Five slightly different hyperketonemia traits divided into two or three classes were studied. Linear model heritability estimates for hyperketonemia traits were low, however, when the threshold model was used for binary traits the estimates became slightly higher (0.07 to 0.15). Genetic correlation between CFH and C-LA for first parity cows was high (0.97) as expected since traits are quite similar. Moderate genetic correlations (0.47 to 0.52) were found between the endocrine fertility traits and early lactation milk yield. Results suggest that the data on endocrine fertility traits measured by automatic systems is a promising tool for improving fertility, specifically when more data is available. For hyperketonemia traits, dividing values into three classes instead of two seemed to work better. Based on the current study and previous studies, where higher heritabilities have been found for milk BHB traits than for clinical ketosis, milk BHB traits are a promising indicator trait for resistance to ketosis and should be studied more. It is important that this kind of data from automatic devices is made available to recording and breeding organizations in the future. [ABSTRACT FROM AUTHOR]

Aim: Timely estrus detection is one of the critical factors for increasing reproductive efficiency in buffaloes. In recent decades, saliva has become a more popular as a noninvasive source for determining physiological status of animals by various biochemical electrolytes. This study was designed to assess and correlate changes in different salivary minerals concentration (calcium, inorganic phosphorus, magnesium, sodium, potassium, and chloride) during different stages of the estrous cycle in Murrah buffaloes. Materials and Methods: The saliva samples were collected during the different phases of the estrous cycle from 20 Murrah buffaloes in early morning hours and were assayed using respective minerals assay kits. Results: The concentrations of calcium (8.76±0.08-12.11±0.11 mg/dl), inorganic phosphorus (6.56±0.13-14.72±4.50 mg/dl), magnesium (2.27±0.14-5.79±0.15 mg/dl), sodium (139.47±0.31-159.62±1.22 mmol/L), potassium (12.40±0.22-26.85±1.22 mmol/L), and chloride (109.28±0.41-137.07±0.68 mmol/L) varied during the different phases of estrous cycle. The concentration of calcium, inorganic phosphorus, magnesium, sodium, potassium, and chloride in saliva were significantly (p

The relationship of the estrous cycle to milk composition and milk physical properties was assessed on Holstein (n = 10,696), Brown Swiss (n = 20,501), Simmental (n = 17,837), and Alpine Grey (n = 8,595) cows reared in northeastern Italy. The first insemination after calving for each cow was chosen to be the day of estrus and insemination. Test days surrounding the insemination date (from 10 d before to 10 d after the day of the estrus) were selected and categorized in phases relative to estrus as diestrus high-progesterone, proestrus, estrus, metestrus, and diestrus increasing-progesterone phases. Milk components and physical properties were predicted on the basis of Fourier-transform infrared spectra of milk samples and were analyzed using a linear mixed model, which included the random effects of herd, the fixed classification effects of year-month, parity number, breed, estrous cycle phase, day nested within the estrous cycle phase, conception, partial regressions on linear and quadratic effects of days in milk nested within parity number, as well as the interactions between conception outcome with estrous cycle phase and breed with estrous cycle phase. Milk composition, particularly fat, protein, and lactose, showed clear differences among the estrous cycle phases. Fat increased by 0.14% from diestrus high-progesterone to estrous phase, whereas protein concomitantly decreased by 0.03%. Lactose appeared to remain relatively constant over diestrus high-progesterone, rising 1 d before the day of estrus followed by a gradual reduction over the subsequent phases. Specific fatty acids were also affected across the estrous cycle phases: C14:0 and C16:0 decreased (−0.34 and −0.48%) from proestrus to estrus with a concomitant increase in C18:0 and C18:1 cis-9 (0.40 and 0.73%). More general categories of fatty acids showed a similar behavior; that is, unsaturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, trans fatty acids, and long-chain fatty acids increased, whereas the saturated fatty acids, medium-chain fatty acids, and short-chain fatty acids decreased during the estrous phase. Finally, urea, somatic cell score, freezing point, pH, and homogenization index were also affected indicating variation associated with the hormonal and behavioral changes of cows in standing estrus. Hence, the variation in milk profiles of cows showing estrus should potentially be taken into account for precision dairy farming management. [ABSTRACT FROM AUTHOR]

This study was conducted to investigate the optimal artificial insemination (AI) time with diagnostic kit at ovulation time. We already applied the patent about the protein in the cow heat mucose in external reproductive tract. And we would examine the accuracy for detection of cow heat by the kit produced with the protein. Evaluation of optimal heat detection was tried two time at 12 hrs and 24 hrs after the heat. And then, AI service also performed two times with no relation to the results of heat diagnosis by heat detection kit and pregnancy rates were checked with rectal palpation on 60th day after AI. Heat diagnostic results by kit in natural heat after 12 hrs in Hanwoo cows were showed 31.3~75.0% on positive in first heat detection and 33.3~100.0% on positve in second heat detection. In the 1st positive results were significant different (p<0.05), but 2nd positive were not. The results of heat detection showed different result on regional influence and individual cow effects. The pregnancy rates of first trial of heat detection were showed 34.4~78.7% on positive and 21.3~68.8% on negative after the diagnosis by heat detection kit. And the pregnancy rates of next trial of heat detection were showed 33.3~85.7% on positive and 14.3~66.6% on negative after the heat diagnosis. Both positive results of first trial and next trial also were showed significant different (p<0.05), but negative results were not. In positive result, first trial of total pregnancy rates was higher than the next trial of pregnancy, but there showed opposite results on negative results. In conclusion, the optimal heat detection kit is suitable to ordinary Hanwoo cows and it suggested that we have to improve the kit's accuracy by detecting the materials like proteins related optimal AI time. [ABSTRACT FROM AUTHOR]

Proper heat detection to achieve appropriate timing of insemination is the biggest restriction in attaining high conception rate in dairy herd. The estrus detection is the key issue to be considered on priority basis. Inefficient heat detection reduces the fertility status of herd. Interventions in existing management practices in farm can manifest estrus with clarity. Manifestation of estrus is due to effect of estrogen on Central Nervous System (CNS). The standing to be ridden is the best reliable sign of estrus. Ovulation time is well estimated by standing heat. Different factors are responsible which affect estrous behavior, out of which feeding and management interventions are one of the most important factors. For improving efficiency of heat detection in animal visual observation is best method, if it is done thrice a day for 30 minutes every time. However heat detection aids, if used in combination give better results as compared to visual observation. The progesterone (P4) estimation in milk and ultrasound monitoring of ovary and reproductive tracts for estimation of ovulation time are other important methods. Ovulation is very important point in dairy reproduction management. The optimum time for insemination is before the actual ovulation. It is already established that, estrus detection alone contributes considerably to reproductive status of the herd, therefore the need of the hour is critical observation of dairy herd to reduce incidence of unnoticed estrus. [Vet World 2013; 6(6.000): 363-369]

The present study was designed to estimate changes in salivary pH, electrical conductivity (EC) and its various constituent biomolecules like total carbohydrates, total proteins, albumin, mucin 5 and total lipids, during different phases of estrous cycle. In present investigation, the levels of all biomolecules like total CHO, total proteins, albumin, mucin 5, total lipids and EC were observed to be significantly (P

Objectives The three objectives of this study were to determine the positive predictive value (PPV) of oestrus diagnosis (heat detection accuracy) by dairy farmers, calculate the diagnostic sensitivity and specificity of the P4 Rapid milk progesterone assay for detecting a corpus luteum and evaluate the economics of using a cow-side milk progesterone assay designed to aid oestrus diagnosis. Methods Milk samples were collected from 752 cows diagnosed in oestrus by farm personnel on 14 dairy farms. Samples were tested using the P4 Rapid milk progesterone assay to estimate the PPV of oestrus diagnosis at each farm and a crude pooled mean of PPV of oestrus diagnosis across all farms. A further 156 milk samples were collected from cows with luteal tissue status determined by transrectal ultrasound and tested by the P4 Rapid assay to enable calculation of the sensitivity and specificity of the P4 Rapid assay. Results For pooled farm samples, the PPV was 97.0%, with a range between farms of 88.9-100%. Sensitivity of the P4 Rapid milk progesterone assay for detecting a corpus luteum was 90.1% and specificity was 98.7%. Misclassification of oestrus in cows previously identified as pregnant was the most common cause of false-positive oestrus diagnoses by farm personnel. Conclusion Routine testing of milk progesterone in all cows diagnosed in oestrus is not economically justified and may even slightly reduce submission rates; conversely, strategic use of cow-side milk progesterone assays can improve herd reproductive performance by facilitating decisions on whether to rebreed cows previously diagnosed as pregnant. [ABSTRACT FROM AUTHOR]

Heat detection in ewe by acidity, elasticity of the cervical and vaginal mucus and by vaginal temperature measurement. Three simple methods were tested to predict oestrus in adult Texel ewes in conjonction with progesterone essays or the use of vasectomized ram. The pH of the vaginal mucus enables oestrus detection : more acid during oestrous and more alkaline during the luteal phase. The use of cervico-vaginal mucus elasticity as a predictor of oestrus was difficult due to its scarcity during some phases of the cycle and even the total lack of mucus by some ewes. The temperature measurement has been ineffective for heat detection.

Our aim was to investigate whether four fertility traits were different in herds using the activity tag Heatime for reproduction management compared within other herds. The genetic parameters were estimated using animal models. The fertility traits were number of inseminations (NINS), interval from first to last insemination (IFL), age at first insemination (AFI), and age at first calving (AFC) in Danish Holstein heifers. The means of the traits were all significantly different between the two groups of herds. Heritabilities for NINS and IFL were lower than 1%, while heritabilities for AFI and AFC were 12–29%. Heritabilities were all lower in Heatime herds than in reference herds. The genetic correlations between traits in different environments were high for NINS, AFI, and AFC (>0.88), while the correlation for IFL was 0.68 but with a higher SE (0.313). Thus, IFL seems not to be the same trait in Heatime and reference herds. [ABSTRACT FROM AUTHOR]

Rattlesnakes use their facial pit organs to sense external thermal fluctuations. A temperature decrease in the heat-sensing membrane of the pit organ has the potential to enhance heat flux between their endothermic prey and the thermal sensors, affect the optimal functioning of thermal sensors in the pit membrane and reduce the formation of thermal “afterimages”, improving thermal detection. We examined the potential for respiratory cooling to improve strike behaviour, capture, and consumption of endothermic prey in the South American rattlesnake, as behavioural indicators of thermal detection. Snakes with a higher degree of rostral cooling were more accurate during the strike, attacking warmer regions of their prey, and relocated and consumed their prey faster. These findings reveal that by cooling their pit organs, rattlesnakes increase their ability to detect endothermic prey; disabling the pit organs caused these differences to disappear. Rattlesnakes also modify the degree of rostral cooling by altering their breathing pattern in response to biologically relevant stimuli, such as a mouse odour. Our findings reveal that low humidity increases their ability to detect endothermic prey, suggesting that habitat and ambush site selection in the wild may be influenced by external humidity levels as well as temperature. [ABSTRACT FROM AUTHOR]

Between one and two school fires occur in Sweden every day. In most cases, arson is the cause of the fire. The most severe fires generally start outside the building and spread up along the façade and into the attic through ventilation openings in the eaves. Linear heat detectors can be placed on façades to detect these types of fires. Such devices detect fire when short-circuited at a specific temperature. In this article, an attempt to simulate linear heat detectors is presented. Data from small-scale and full-scale experiments are compared with these simulations. The small-scale experiments and simulations demonstrate that the cable failure model in Fire Dynamics Simulator can be used to predict detection in linear heat detectors that use short-circuiting as the means of signaling an overheated condition. The full-scale experiments provide a measure of the uncertainties involved, as well as the possibility of using simulations of linear heat detectors in a fire engineering design. [ABSTRACT FROM PUBLISHER]

Abstract: Background: Human experimental pain models help to understand the mechanism of the underlying clinical pain conditions and can be adopted to test analgesic efficacy of drugs used in the management of pain. In early phases, the clinical development of new analgesic agents is severely hindered due to lack of reliable sensitive tests for the experimental pain models. Objective: The aim of the present study was to standardize and validate a simple contact heat pain model that can be used for future screening of various analgesic agents. Methods: The method was standardized by recording heat detection and heat pain detection threshold in degrees centigrade in 24 healthy volunteers. Reproducibility of the test procedure was evaluated by recording the thermal threshold parameters by a single observer on 2 sessions (inter-day reproducibility) and a second observer on 1 session (inter-observer reproducibility) separately. Validity of model was further tested by evaluating the analgesic effect of tramadol on 12 healthy volunteers. Results: Thermal pain model using contact heat method was found to produce low variability with coefficient of variation <5%. Inter-observer and inter-day reproducibility was very good, as shown by Bland–Altman Plot; with most of the values within 2 SD. There was a significant difference in both heat detection threshold and heat pain detection threshold produced by tramadol, as compared with placebo (P < 0.05). Conclusions: The newly developed pain model produces a type of experimental pain that is responsive to analgesic effects of tramadol at clinically relevant doses. The model might be useful in early screening of new therapeutic agents before proceeding to expensive clinical trials in acute and chronic pain sufferers. [Copyright &y& Elsevier]

An introduction is presented in which the editor discusses various reports within the issue on topics including coding properties in invertebrate sensory systems, olfactory receptor neurons in cockroaches, and detection of moth sex pheromones in a rich background of plant volatile.

Abstract: This paper suggests a method for automatic detection of sows returning to oestrus in the gestation department. The detection is based on monitoring of sows’ visits to a boar, where the duration and frequency of visits are modelled separately and subsequently combined. The hypothesis is that it is possible to reduce the response time and the number of false alarms compared to previously published attempts. The duration of visits to a boar is defined as seconds per hour the sow is near the boar – logarithmically transformed. The duration is modelled with a multiprocess dynamic linear model with first order Markov probabilities. The indicator of oestrus is the probability of the model describing oestrus, , and it is monitored with a threshold value. The frequency of visits to a boar is defined as number of visits per 6h. A dynamic generalised linear model with two built-in diurnal periods is applied. The indicator of oestrus is the relative deviation from the forecasted frequency, which is monitored with a threshold value. The probability, , and the relative deviation from the forecasted frequency are combined by means of Bayes Theorem. The combined probability of oestrus is monitored with a threshold value as well. Results indicate that the specificity is superior compared to previously published attempts. The model describing duration alone yields the most satisfactory specificity – 99.4% per sow day, which is considerably greater than previously published studies. Furthermore, this model detects 87.4% of the sows entering oestrus, which is slightly lower than previous attempts. The response time of the models is 1h for the duration model and the combined model and 6h for the frequency model. This is better than previous attempts. Even though the specificity is greater, the proportion of false alarms on a day-to-day basis is still too high (91.0%), which is due to the very large proportion of the sow days defined as non-oestrus. In order to improve the specificity of the detection method, it is suggested to combine the detection method in the present study with other information sources about oestrus. [Copyright &y& Elsevier]