A systematic literature review on IoT-aware business process modeling views,requirements and notations

Software and Systems Modeling - The Internet of things has been adopted in several sectors both influencing how people work and enhancing organizations’ business processes. This resulted in...     

Service Discovery and Negotiation With COWS

To provide formal foundations to current (web) services technologies, we put forward using COWS, a process calculus for specifying, combining and analysing services, as a uniform formalism for modelling all the relevant phases of the life cycle of service-oriented applications, such as publication, discovery, negotiation, deployment and execution. In this paper, we show that constraints and operations on them can be smoothly incorporated in COWS, and propose a disciplined way to model multisets of constraints and to manipulate them through appropriate interaction protocols. Therefore, we demonstrate that also QoS requirement specifications and SLA achievements, and the phases of dynamic service discovery and negotiation can be comfortably modelled in COWS. We illustrate our approach through a scenario for a service-based web hosting provider.     

Potential effects of hormonal synchronized breeding on genetic evaluations of fertility traits in dairy cattle: A simulation study

About 30% of producers use hormone protocols to synchronize ovulation and perform timed artificial insemination (AI) in Canada. Days from calving to first service (CTFS) and first service to conception (FSTC) become masked phenotypes leading to biased genetic evaluations of cows for these fertility traits. The objectives of this study were to (1) demonstrate and quantify the potential amount of bias in genetic evaluations, and (2) find a procedure that could remove the bias. Simulation was used for both objectives. The proposed solution was to identify cows that have been treated by hormone protocols, make their CTFS and FSTC missing, and perform a multiple trait analysis including traits that have high genetic correlations with CTFS and FSTC, and which are not affected by the hormone protocols themselves. A total of 12 scenarios (S1–S12) were tested, changing the percentage of herds and cows that were randomly selected to be under timed AI. Cows that were given hormone protocols had CTFS of 86 d and FSTC of 0, which were used in genetic evaluation. Four criteria were used to indirectly measure the presence of bias: (1) the correlation between true (TBV) and estimated (EBV) breeding values (accuracy); (2) the differences in the mean EBV of top 25, 50, and 75 sires; (3) changes in correlation between TBV and EBV rankings; and (4) the changes in mean EBV over the simulated generations. All criteria changed unfavorably and proportionally to the increased use of timed AI. The accuracy within each class of animals (cows, dams, or sires) decreased proportionally with increased use of timed AI, varying from 0.32 (S12) to 0.52 (S1) for bull EBV for CTFS. The average EBV of the top sires (best 25, 50, 75, or 100 sires) approached population average EBV values when increasing the number of treated animals. The sire rank correlation between EBV and TBV within simulated scenarios was smaller for scenarios with more synchronized animals, going from 0.38 (S12) to 0.67 (S1). The long-term use of hormonal synchronized cows clearly decreased the mean EBV over generations in the population for CTFS and FSTC. The inclusion of genetically correlated traits in a multiple trait model was effective in removing the bias due to the presence of hormonal synchronized cows. However, given the constraints within the simulation, it is important that further investigation with real data is conducted to determine the true effect of including timed AI records within genetic evaluations of fertility traits in dairy cattle.     

Laboratory silo type and inoculation effects on nutritional composition,fermentation, and bacterial and fungal communities of oat silage

The objectives were to evaluate (1) the use of 2 types of experimental silos (S) to characterize whole-crop oat (Avena sativa L.) silage with or without addition of an inoculant (I), and (2) the effect of inoculation on the microbial community structure of oats ensiled using only plastic bucket silos (BKT). From each of 6 sections in a field, oats were harvested, treated (INO) or not (CON) with inoculant, packed into 19-L BKT or vacuum bags (BG), and ensiled for 217 d. The inoculant added contained Lactobacillus buchneri and Pediococcus pentosaceus (4 × 10⁵ and 1 × 10⁵ cfu/g of fresh oats, respectively). The experimental design was a complete randomized design replicated 6 times. Treatment design was the factorial combination of 2 S × 2 I. Some differences existed between BG versus BKT at silo opening (217 d), including a decreased CP (7.73 vs. 7.04 ± 0.247% of DM) and ethanol (1.93 vs. 1.55 ± 0.155) and increased lactic acid (4.28 vs. 3.65 ± 0.241), respectively. Also, WSC and mold counts were reduced in BG versus BKT for CON (1.78 vs. 2.70 ± 0.162% of DM and 0.8 vs. 2.82 ± 0.409 log cfu/fresh g) but not for INO (～1.53 and 1.55), respectively. Application of INO increased DM recovery (96.1 vs. 92.9 ± 0.63%), aerobic stability (565 vs. 133 ± 29.2 h), acetic acid (2.38 vs. 1.22 ± 0.116% of DM), and reduced NDF (65.0 vs. 67.0 ± 0.57), ADF (36.7 vs. 38.1 ± 0.60), ethanol (0.63 vs. 2.85 ± 0.155), and yeast counts (1.10 vs. 4.13 ± 0.484 log cfu/fresh g) in INO versus CON, respectively. At d 0, no differences were found for S and I on the nutritional composition and background microbial counts. Leuconostocaceae (82.9 ± 4.27%) and Enterobacteriaceae (15.2 ± 3.52) were the predominant bacterial families and unidentified sequences were predominant for fungi. A higher relative abundance of the Davidiellaceae fungal family (34.3 vs. 19.6 ± 4.47) was observed in INO versus CON. At opening (217 d), INO had a lower relative abundance of Leuconostocaceae (42.3 vs. 95.8 ± 4.64) and higher Lactobacillaceae (57.4 vs. 3.9 ± 4.65) versus CON. Despite several differences were found between BKT and BG, both techniques can be comparable for characterizing effects of INO on the most basic measures used in silage evaluation. The use of inoculant improved oat silage quality partially by a shift in the bacterial community composition during ensiling, which mainly consisted of an increased relative abundance of Lactobacillaceae and reduction of Leuconostocaceae relative to CON.     

Modeling of Viscoelastic Contacts and Evolution of Limit Surface for Robotic Contact Interface

Viscoelastic contact is a type of contact which includes, in addition to linear or nonlinear elastic response, time-dependent response due to relaxation or creep phenomena that govern the contact behavior. The characteristics of the time-dependent relaxation of such a viscoelastic contact are typically exponentially decaying functions, and exponentially growing functions for creep, respectively. Such contacts can be found in anthropomorphic robotic fingers, soft materials, viscoelastic skin with rigid core, and human fingers and feet. In this paper, the nature of viscoelastic contacts is investigated, and the evolution of their friction limit surfaces and of the pressure distributions at the contact interface are studied. Two cases commonly found in robotic grasping and manipulation are discussed. Based on the modeling formulation, it is found that the two important parameters of analysis and modeling for such contacts, i.e., the radius of contact area and the profile of pressure distribution, can be chosen using proposed coupling equations as the viscoelastic contact interface evolves with time. The new contribution of this paper includes a proposal of coupling equations between the two important parameters to describe the viscoelastic contact interface, and a study of the evolution of limit surfaces for viscoelastic contact interface due to temporal dependency, and the implication on grasp stability. It is found from the evolution of limit surfaces that when normal force is applied with typical viscoelastic contacts, grasp becomes more stable as time elapses. The modeling can be applied to the design of fingertips and the analysis of robotic grasping and manipulation involving viscoelastic fingers     

A multi-criteria assessment of six energy conversion processes for H2 production

The study of Very Large Complex systems (“VLCS”), of which modern energy conversion systems are an important subset, requires a holistic approach to analyze the system itself and all of its “external” and “internal” interactions. The view taken in this paper is that the VLCS should be considered as an “extended” (in a sense specified below) thermodynamic system. The evaluation of the flows of matter and energy sustaining a VLCS and the knowledge of the transformations therein can be used to describe the rate of exploitation of the available natural resources, to assess the efficiency of the conversion process, and to provide a quantitative estimate of the impact of the system on the environment. This kind of information is an important part of the essential database of any Decision Support System for both the internal and global policy planning and for resources management. Several assessment methods are in use at present, and each one of them provides a different insight in the “performance” of the conversion chain under examination.     

Isotopic Effect on the Kinetics of the Belousov-Zhabotinsky Reaction

In this work we present results about the deuterium isotope effect on the global kinetics of a Belousov-Zhabotinsky reaction in batch conditions. A nonlinear dependence of the Induction Period upon the percentage of deuterated reactants was found. The isotopic effect on the bromination reaction of malonic acid was evaluated.     

School-based health care for urban minority junior high school students

OBJECTIVE: To describe the use of school-based health clinics by urban minority junior high school students. DESIGN: Review of demographic and utilization data collected by service providers during clinic visits. SETTINGS AND PARTICIPANTS: Health clinics in four junior high schools that enrolled predominantly Hispanic students who were residing in an economically disadvantaged, medically underserved New York (NY) school district. RESULTS: Of 5757 students who were enrolled in the schools, 5296 (92%) obtained parental consent to use the clinics, and 3723 (65%) used the clinics during the 1991-1992 academic year. Clinic users were 11 to 15 years old, 50% male and 50% female, 81% Hispanic and 14% black, and 29% sixth graders, 33% seventh graders, and 38% eighth graders. Clinic users made 16,340 clinic visits during the 1991-1992 academic year. Presenting complaints were mental health problems (32%), illness (14%), injury (12%), physical examination (5%), immunization (3%), follow-up (21%), and other (13%). Referral sources were clinic outreach (48%), self (44%), and school personnel (8%). Disposition of visits was on-site treatment (92%), referral to an affiliated hospital (5%), and referral elsewhere (3%). Compared with a nationwide group of high school-based clinics that served predominantly black adolescents, these clinics provided more mental health care (31% vs 21%), similar illness/injury care (32% vs 30%), and less preventive (10% vs 24%) and reproductive/contraceptive (7% vs 12%) care. CONCLUSIONS: Junior high school-based clinics can provide a wide range of primary and preventive health care services for large numbers of medically underserved youths. The provision of mental health services may fill a critical need among inner-city adolescents. Clinic outreach may be necessary to maximize utilization, especially among high-risk students.     

Comparison of Bayesian regression models and partial least squares regression for the development of infrared prediction equations

The objective of this study was to compare the prediction accuracy of 92 infrared prediction equations obtained by different statistical approaches. The predicted traits included fatty acid composition (n = 1,040); detailed protein composition (n = 1,137); lactoferrin (n = 558); pH and coagulation properties (n = 1,296); curd yield and composition obtained by a micro-cheese making procedure (n = 1,177); and Ca, P, Mg, and K contents (n = 689). The statistical methods used to develop the prediction equations were partial least squares regression (PLSR), Bayesian ridge regression, Bayes A, Bayes B, Bayes C, and Bayesian least absolute shrinkage and selection operator. Model performances were assessed, for each trait and model, in training and validation sets over 10 replicates. In validation sets, Bayesian regression models performed significantly better than PLSR for the prediction of 33 out of 92 traits, especially fatty acids, whereas they yielded a significantly lower prediction accuracy than PLSR in the prediction of 8 traits: the percentage of C18:1n-7 trans-9 in fat; the content of unglycosylated κ-casein and its percentage in protein; the content of α-lactalbumin; the percentage of α_S2-casein in protein; and the contents of Ca, P, and Mg. Even though Bayesian methods produced a significant enhancement of model accuracy in many traits compared with PLSR, most variations in the coefficient of determination in validation sets were smaller than 1 percentage point. Over traits, the highest predictive ability was obtained by Bayes C even though most of the significant differences in accuracy between Bayesian regression models were negligible.