Expanding an abridged life table

A question of interest in the demographic and actuarial fields is the estimation of the age-specific mortality pattern when data are given in age groups. Data can be provided in such a form usually because of systematic fluctuations caused by age heaping. This is a phenomenon usual to vital registrations related to age misstatements, usually preferences of ages ending in multiples five. Several techniques for expanding an abridged life table to a complete one are proposed in the literature. Although many of these techniques are considered accurate and are more or less extensively used, they have never been simultaneously evaluated. This work provides a critical presentation, an evaluation and a comparison of the performance of these techniques. For that purpose, we consider empirical data sets for several populations with reliable analytical documentation. Departing from the complete sets of qx-values, we form the abridged ones. Then we apply each one of the expanding techniques considered to these abridged data sets and finally we compare the results with the corresponding complete empirical values.abridged life table, age-specific mortality pattern, complete life table, expanding method, interpolation, life tables, parametric models, probability of dying, splines

Dairy calf pneumonia: Effective treatment depends on early and accurate diagnosis

Dairy calf pneumonia is one of the most economically important diseases of calves. A delayed diagnosis could result endemic herd problem, prolonged use of antibiotics, high recurrence rate, pulmonary abscessation and ear infections. The key for effective control is the early detection of pneumonia and the accurate diagnosis of the etiologic factor. For the early detection, a respiratory disease score was assigned based on rectal temperature, character of nasal discharge, eye discharge or ear appearance, and presence of a cough. Each clinical sign has a point scale from 0 (normal) to 4 (severe). The respiratory disease score is the sum of points from the 4 categories of clinical signs, with increasing values representing progressive severity. The scoring system results in a minimum score of 0 and a maximum score of 12. Calves with score 5 or higher, having at least 2 clinical signs of respiratory disease, are considered sick and have to be treated. For the accurate diagnosis of the etiological agent the best tool in a live calf is bronchoalveolar lavage (BAL) fluid collection. Sampling of severely affected animals should be avoided. New acute cases are ideal. BAL is performed in sedated calves using a sterilized, flexible catheter with a 5-cc balloon cuff. The fresh BAL fluid sample is processed within 2 hours of collection or refrigerated until analysis. Part of the sample is used for microbiology and the remaining is submitted for cytology. BAL fluid that yields homogenous (>106 CFU/ml) bacterial or positive Mycoplasma bovis culture is considered abnormal. A disproportionate lowering of macrophages (<61%) or elevation of neutrophils (>39%) provides evidence of an inflammatory response with or without a positive culture. The ideal antibiotic selection would be based on the antibiotic susceptibility pattern of lung pathogens after BAL fluid culture

Quantifying RFID-enabled Traceability For The Food Industry: A Case Study

With the competitive differentiators of supply chain operation’s efficiency, food differentiation with credence attributes, quality enhancement and food safety, the concept of “traceability as strategy and mandatory initiative” has replaced that of “traceability as a cost of a business or as a voluntary responsibility”. This implies that the introduction of a traceability system should be perceived and positioned as a catalyst for better business practices in terms of legal compliance, safety and quality assurance, risk prevention, efficient recalls/withdrawals and consumer’s trust. However, despite these benefits, a traceability system is also investment worthy. Hence, the value of investment in a traceability system constitutes a matter of considerable concern and debate for both practitioners and academics alike; meaning that it is essential to recognize the extent to which the potential benefits gained by a traceability system outweigh the value of investment in such an initiative. As a result, this paper presents a cost-benefit evaluation applied in a frozen food company regarding the pilot deployment of a RFID-based traceability system

Sparse Linear Concept Discovery Models

The recent mass adoption of DNNs, even in safety-critical scenarios, has shifted the focus of the research community towards the creation of inherently intrepretable models. Concept Bottleneck Models (CBMs) constitute a popular approach where hidden layers are tied to human understandable concepts allowing for investigation and correction of the network's decisions. However, CBMs usually suffer from: (i) performance degradation and (ii) lower interpretability than intended due to the sheer amount of concepts contributing to each decision. In this work, we propose a simple yet highly intuitive interpretable framework based on Contrastive Language Image models and a single sparse linear layer. In stark contrast to related approaches, the sparsity in our framework is achieved via principled Bayesian arguments by inferring concept presence via a data-driven Bernoulli distribution. As we experimentally show, our framework not only outperforms recent CBM approaches accuracy-wise, but it also yields high per example concept sparsity, facilitating the individual investigation of the emerging concepts.Comment: Accepted @ ICCVW CLVL 202