Exposure to strange adults does not cause pregnancy disruption or infanticide in the gray-tailed vole

A widely accepted paradigm in mammalian behavioral biology is that exposure to unfamiliar males causes pregnancy disruption in female rodents (commonly known as the Bruce effect). This behavioral phenomenon has been demonstrated in the laboratory with at least 12 species of rodents, primarily within the genus Microtus, and is supposedly an adaptation that provides male perpetrators with reproductive access to females, and functions, for females, as a counterstrategy to infanticide. However, neither the Bruce effect nor its adaptive significance have been tested experimentally in the field. In a controlled field study, we exposed reproducing female gray-tailed voles (Microtus canicaudus) to treatments in which males were removed and replaced by either unfamiliar males or females, and found no significant differences in intervals between parturitions, number of pregnancies, and juvenile recruitment among the treatment and control animals. Thus, we conclude that neither the Bruce effect nor infanticide occurred differentially as a consequence of the treatments in gray-tailed voles. Multimale mating to confuse paternity, and postpartum estrus resulting in simultaneous pregnancy and lactation may deter infanticide and functionally negate any benefits of pregnancy disruption in gray-tailed voles and perhaps other murid rodents with similar mating systems. In light of our results, we recommend field verification for other species of murid rodents that exhibit the Bruce effect in the laboratory before the results are applied to evolutionary theory. Received: 12 May 1998 / Accepted after revision: 6 September 1998     

Assessing of Environmental Quality in Six Areas in India,Sri Lanka and Bangladesh

Environmental quality for environmental health has been examined visually by describing general conditions and drinking water supply, sanitation and solid waste treatment conditions and practices in six South-East Asian villages with a dense population. The environmental review was supplemented by discussions with local people and political and administrative decision makers. Some drinking water analyses were done in order to show the water quality to the local people. The quality of the general conditions and the conditions and practices of drinking water supply, excreta disposal and solid waste treatment practices have been graded with the grading system presented below. The grading could be done in 1 or 2 days in each area by two persons, of which one was an environmental scientist and the other a social scientist, who also knew the local culture and worked as a translator.     

一种改进的多学习教与学优化算法

针对传统教与学算法在解决复杂多峰函数优化问题时,具有局部最优且搜索开发能力较差的缺点,提出了一种改进的多学习教与学优化算法,新算法为学员的每一维加入不同的教学因子,设计了基于学员均值比较的教师选择策略和向教师及学员学习的多学习策略。基于多个单峰和多峰函数的仿真结果表明,新算法跟传统的、改进的教与学算法相比,在稳定性、寻优精度和收敛速度方面更具优势。     

On-Scene Injury Severity Prediction (OSISP) Algorithm for Truck Occupants

Objective: The aim of this study is to develop an on-scene injury severity prediction (OSISP) algorithm for truck occupants using only accident characteristics that are feasible to assess at the scene of the accident. The purpose of developing this algorithm is to use it as a basis for a field triage tool used in traffic accidents involving trucks. In addition, the model can be valuable for recognizing important factors for improving triage protocols used in Sweden and possibly in other countries with similar traffic environments and prehospital procedures.

Methods: The scope is adult truck occupants involved in traffic accidents on Swedish public roads registered in the Swedish Traffic Accident Data Acquisition (STRADA) database for calendar years 2003 to 2013. STRADA contains information reported by the police and medical data on injured road users treated at emergency hospitals. Using data from STRADA, 2 OSISP multivariate logistic regression models for deriving the probability of severe injury (defined here as having an Injury Severity Score [ISS] > 15) were implemented for light and heavy trucks; that is, trucks with weight up to 3,500 kg and ??16,500 kg, respectively. A 10-fold cross-validation procedure was used to estimate the performance of the OSISP algorithm in terms of the area under the receiver operating characteristic curve (AUC).

Results: The rate of belt use was low, especially for heavy truck occupants. The OSISP models developed for light and heavy trucks achieved cross-validation AUC of 0.81 and 0.74, respectively. The AUC values obtained when the models were evaluated on all data without cross-validation were 0.87 for both light and heavy trucks. The difference in the AUC values with and without use of cross-validation indicates overfitting of the model, which may be a consequence of relatively small data sets. Belt use stands out as the most valuable predictor in both types of trucks; accident type and age are important predictors for light trucks.

Conclusions: The OSISP models achieve good discriminating capability for light truck occupants and a reasonable performance for heavy truck occupants. The prediction accuracy may be increased by acquiring more data. Belt use was the strongest predictor of severe injury for both light and heavy truck occupants. There is a need for behavior-based safety programs and/or other means to encourage truck occupants to always wear a seat belt.     

Fecal DDA as a biomarker of DDT exposure in chickens

Despite the largely theoretical risks for human morbidity from exposure to DDT (p, p′-dichlorodiphenyltrichloroethane), the reality that it is inexpensive and highly effective in reducing morbidity and mortality from malaria vectors has encouraged its continued use. Here we present data indicating that domestic fowl are potentially excellent sentinel species for detecting possible human exposures to DDT. In addition to measuring residues of DDT in chicken blood or eggs, a potential alternate analyte indicative of recent DDT exposure is the definitive metabolic product DDA (2,2-bis(4-chlorophenyl)acetic acid) in feces.