Miracle-dz/UniFAR-FTUs huggingface dataset:
Bone, microbiological and intestinal characteristics of piglets fed diets containing Lithothamnium calcareum

The aim of this study was to assess the effect of calcitic seaweed (CS), calcitic limestone (CL) and monodicalcium phosphate (DP) fed to piglets in various combinations on their gastrointestinal tract and bones. A total of 128 piglets (21 days old, 5.50 ± 0.49 kg bodyweight (BW) were assigned to treatments in a randomized complete block design and eight replications to one of four diets: D1: with CL + DP, D2: with CL, CS + DP, D3, similar to D2, but with 30% less calcium from CS and DP, and D4: with CS + DP. Treatments affected the metatarsal bones, mineral concentration in the heart and liver, and pH in the cecum and colon.Piglets fed D4 tended to have a greater Enterobacteriaceae count in the jejunum and ileum compared withD1 (4.82 vs 4.79 CFU/g). Piglets fed D1 and D3 had a greater Enterobacteriaceae count in their cecum than D4 (4.79 and 4.80 vs 4.76). The D2 and D1 treatments produced greater crypt depth (CD) in the duodenum and ileum compared with D3 and D4, respectively. Feeding D3 resulted in a greater villus height (VH) to CD ratio in the duodenum compared with D2 and showed a 24.5% increase in heart weight compared with fed D1. In conclusion, CS could be an alternative source of calcium source for piglets. The inconsistent findings of the present study suggest the need for further studies to better understand the interplay of effects of Ca2+ source and level on its metabolism.
Judgment Bias During Gestation in Domestic Pigs

In humans and rats, changes in affect are known to occur during pregnancy, however it is unknown how gestation may influence mood in other non-human mammals. This study assessed changes in pigs' judgment bias as a measure of affective state throughout gestation. Pigs were trained to complete a spatial judgment bias task with reference to positive and negative locations. We tested gilts before mating, and during early and late gestation, by assessing their responses to ambiguous probe locations. Pigs responded increasingly negatively to ambiguous probes as gestation progressed and there were consistent inter-individual differences in baseline optimism. This suggests that the pigs' affective state may be altered during gestation, although as a non-pregnant control group was not tested, an effect of learning cannot be ruled out. These results suggest that judgment bias is altered during gestation in domestic pigs, consequently raising novel welfare considerations for captive multiparous species.
Organizational learning and network adaptation in multi-agent systems

In both real and artificial societies, successful organizations are highly dependent upon a structure that fosters effective and efficient behavior at both the individual and the organizational levels. In multi-agent systems, groups of agents must coordinate effectively in order to solve problems, allocate tasks across a distributed organization, collectively distribute knowledge and information, and achieve collective goals. The organizational structure of a multi-agent system dictates the interactions among the agents, and can play a significant role in the overall performance of a society of agents. Given the importance of organizational network structures for multi-agent systems, distributed network adaptation is a promising approach for organizational learning. After reviewing related work in multi-agent learning, the structure and dynamics of networks, and organizational learning in multi-agent systems, I present the concept of agent-organized networks as an approach for organizational learning by distributed network adaptation. Supported by theoretical evidence of the complexity of organizational network design, a general learning-based agent-organized network framework is proposed and applied to two general environments: multi-agent team formation and a production and exchange economy. In addition, the general framework is used to develop distributed network adaptation strategies for specific applications in supply network formation and wireless sensor networks. Experimental results for both the general and specific multi-agent environments support the hypothesis that distributed management and adaptation of organizational network structure leads to improved collective performance in nulti-agent systems. Analyses of the structural characteristics of the networks as they evolve are used to aid in understanding the behavior of agent-organized networks and further support the utility of distributed network adaptation for organizational learning in multi-agent systems.
Social support to mitigate perceived risk: moderating effect of trust

ABSTRACT During a crisis period, the transmission of travel information is faster than ever via social media (Wut, T. M., Xu, J. B., & Wong, S.-m. (2021). Crisis management research (1985–2020) in the hospitality and tourism industry: A review and research agenda. Tourism Management, 85, 104307). Social media influencers provide opportunities to mitigate perceived risk and rebuild travel confidence. Based on both customer socialization theory and dual-process theory of cognitive reasoning, we propose that trust would moderate the relationship between social support from social media influencers and perceived risk. The research model was tested using 738 questionnaires collected from Chinese social media users. Findings from statistical analyses have shown significant relationships among the research variables, and the moderating role of cognitive and affective trust was supported. Our findings could provide implications regarding how to utilize social media influencers wisely to mitigate perceived risk in the post-COVID-19 period.
Crowdsourcing for the spatialization and signaling of Covid-19 transmission predictors: an approach based on risk perception

Popular participation in public health actions is essential for fighting Covid-19, especially in vulnerable urban communities where the lack of geographical data at fine resolution scale hinders appropriate spatial responses. This work proposes a crowdsourcing-based solution that captures georeferenced data regarding the population's perception of risk in relation to transmission predictors of Coronavirus. The proposed solution allows for mapping and sending real-time alerts regarding the presence of such transmission predictors. A validation study involving 20 people from a community in the city of Salvador revealed that the proposed solution is highly acceptable as user-centred alert tool, especially among young people.
An Investigation of Antecedents for Data Governance Adoption in the Rail Industry—Findings From a Case Study at Thales

The role of data governance is experiencing a paradigm shift as organizations increasingly incorporate data governance to encourage the strategic utilization of data and, therefore, promote data-driven innovation. However, the opportunities arising from technological advancements and novel value propositions based on data come with implications that often stem from external and internal contingent factors, e.g., industry characteristics or organizational structures. In combination with inadequate practices regarding the conduct of data, difficulties in the adoption of data governance can increase. This article draws upon established practices from information technology governance and organizational theory, specifically contingency theory, to examine occurring antecedents in the adoption of data governance at Thales Ground Transportation Systems, a manufacturer of solutions for the railway infrastructure. By investigating the nomological link between antecedents, adoption, and consequences, associated implications for data governance can be taken into account in early phases of adoption to promote data-driven innovation. The article proposes new antecedents evolving from interorganizational dynamics such as data collaborations in the respective ecosystem.
The Modified Shields Classification and 12 Families with Defined DSPP Mutations

Mutations in Dentin Sialophosphoprotein (DSPP) are known to cause, in order of increasing severity, dentin dysplasia type-II (DD-II), dentinogenesis imperfecta type-II (DGI-II), and dentinogenesis imperfecta type-III (DGI-III). DSPP mutations fall into two groups: a 5′-group that affects protein targeting and a 3′-group that shifts translation into the −1 reading frame. Using whole-exome sequence (WES) analyses and Single Molecule Real-Time (SMRT) sequencing, we identified disease-causing DSPP mutations in 12 families. Three of the mutations are novel: c.53T>C/p.(Val18Ala); c.3461delG/p.(Ser1154Metfs*160); and c.3700delA/p.(Ser1234Alafs*80). We propose genetic analysis start with WES analysis of proband DNA to identify mutations in COL1A1 and COL1A2 causing dominant forms of osteogenesis imperfecta, 5′-DSPP mutations, and 3′-DSPP frameshifts near the margins of the DSPP repeat region, and SMRT sequencing when the disease-causing mutation is not identified. After reviewing the literature and incorporating new information showing distinct differences in the cell pathology observed between knockin mice with 5′-Dspp or 3′-Dspp mutations, we propose a modified Shields Classification based upon the causative mutation rather than phenotypic severity such that patients identified with 5′-DSPP defects be diagnosed as DGI-III, while those with 3′-DSPP defects be diagnosed as DGI-II.
Microfluidics for High Pressure: Integration on GaAs Acoustic Biosensors with a Leakage-Free PDMS Based on Bonding Technology

Microfluidics integration of acoustic biosensors is an actively developing field. Despite significant progress in “passive” microfluidic technology, integration with microacoustic devices is still in its research state. The major challenge is bonding polymers with monocrystalline piezoelectrics to seal microfluidic biosensors. In this contribution, we specifically address the challenge of microfluidics integration on gallium arsenide (GaAs) acoustic biosensors. We have developed a robust plasma-assisted bonding technology, allowing strong connections between PDMS microfluidic chip and GaAs/SiO2 at low temperatures (70 °C). Mechanical and fluidic performances of fabricated device were studied. The bonding surfaces were characterized by water contact angle measurement and ATR-FTIR, AFM, and SEM analysis. The bonding strength was characterized using a tensile machine and pressure/leakage tests. The study showed that the sealed chips were able to achieve a limit of high bonding strength of 2.01 MPa. The adhesion of PDMS to GaAs was significantly improved by use of SiO2 intermediate layer, permitting the bonded chip to withstand at least 8.5 bar of burst pressure. The developed bonding approach can be a valuable solution for microfluidics integration in several types of MEMS devices.
The Digital Divide in Online Learning: A Case Study of University Students in Nepal

This article analyses the online teaching-learning experience of university teachers and students during the COVID-19 pandemic in Nepal. The purpose of this study is to explore the challenges of online teaching-learning such as the availability of ICT infrastructure, technological skills and management for online classes by the higher education institutions. The researcher collected and studied some of the related academic and policy documents to understand the procedure of online teaching and learning in and around the country during the pandemic. This study was based on qualitative research utilizing semi-structured interviews with 15 participant students and five teachers from Prithvi Narayan Campus, Pokhara, Nepal. Only the students of the Faculty of Humanities and Social Sciences, and the Faculty of Management were selected for data collection. This study took the non-participant observation of various online classes and personal involvement and experiences as references to support and strengthen the data collected through interviews. The purpose was to find and discover the situation of online modes of teaching learning. The findings of the study indicated that the digital use in teaching and learning is the best alternative as it creates opportunities in an adverse situation. However, it causes many divisions among students. It is suggested that the government and university authorities should create a strong-learning atmosphere among the students so that the lines of division among students would be erased gradually.
Fault tolerance techniques for embedded telemetry system: case study

This paper presents software methods of improving fault tolerance in embedded systems. These methods have been adapted to a telemetry system dedicated to tracking vehicles for logistics purposes. The developed telemetry system allows us to monitor vehicle position and some technical parameters via GSM communication. It comprises the capability of remote software reconfiguration. To evaluate dependability of the system we use a fault injection technique based on simulating bit-flip errors within memory cells. For this purpose an original testbed has been developed. It provides not only the capability of disturbing internal state of the tested system (via JTAG interface) but also the possibility of controlling system input states and observing its behavior (in particular output signals) according to specified test scenarios. The whole test process is automatized. The paper presents a case study related to a commercial product but the described methodology and techniques can be extended for other embedded systems.
A Digital Self-Sustained Phase Shift Modulation Control Strategy for Full-Bridge LLC Resonant Converters

A digital self-sustained phase shift modulation (DSSPSM) strategy that allows for good soft switching and dynamic response performance in the presence of step variations is presented in this paper. The working principle, soft switching characteristics, and voltage gain formulae of a LLC converter with DSSPSM have been provided separately. Furthermore, the method for realizing DSSPSM is proposed. Specifically, some key components of the proposed DSSPSM are carefully investigated, including a parameter variation analysis, the start-up process, and the zero-crossing capture of the resonant current. The simulation and experiment results verify the feasibility of the proposed control method. It is observed that the zero voltage switching of the switches and the zero current switching of the rectifier diodes can be easily realized in presence of step load variations.
Architectural Implications of Locator/ID Separation

Recent work on Locator/ID Separation has focused primarily on the control plane protocols concerned with finding Identifier-to-Locator mappings. However, experience gained with a trial deployment of a system designed to implement Locator/ID Separation has revealed two general classes of problems which must be resolved after the mapping is found: The Locator Path Liveness Problem and the State Synchronization Problem. These problems have implications for the data plane as well as the control plane.
Evolving Machine Learning Methods for Density Estimation of Liquid Alkali Metals over the Wide Ranges

Alkali metals are widely used as industrial materials in products such as electrochemical cells because of their properties that make them suited to high temperatures. In this study, three computational approaches including gene expression programming (GEP), least squares support vector machine (LSSVM), and adaptive neuro fuzzy inference system (ANFIS) have been suggested to estimate density of different liquid alkali metals in extensive ranges of pressure and temperature. An experimental databank involving 595 experimental alkali metals’ densities has been gathered to prepare and test the models. The mathematical and visual comparisons of these models’ outputs and real density values are used to assess capacities of GEP, LSSVM, and ANFIS models in prediction of alkali metals’ density. The determined R-squared values for GEP, LSSVM, and ANFIS are 0.9999, 1, and 1, respectively. The MSE values are estimated to be 0.9184, 0.815, and 0.154 for GEP, ANFIS, and LSSVM, respectively. According to these results, these models can be suggested as simple and accurate ways for determining alkali metals’ properties. Results showed that LSSVM has the best performance in comparison with GEP and ANFIS. Moreover, the parametric analysis of input parameters is carried out to show the impact of them on alkali metals’ density. According to this analysis, the amount of lithium can be the most effective parameter on the mixture density.
Effectiveness and Safety of Antibiotic Prophylaxis for Persons Exposed to Cases of Invasive Group A Streptococcal Disease: A Systematic Review

Abstract Among close contacts of patients with invasive group A streptococcal (iGAS) infection, the benefits and harms of chemoprophylaxis are uncertain. We conducted a systematic review of studies that reported on persons who, after being exposed to a case of laboratory-confirmed or probable iGAS, received any antibiotic prophylaxis for the prevention of GAS infection or carriage. Thirty-seven studies including 26 outbreak investigations and 11 case series or reports were included with predominantly descriptive information that suggested that antibiotic prophylaxis may be effective in preventing GAS infection or GAS carriage, with very few serious adverse events. However, current available evidence is scant (with limited information on contacts of iGAS cases) and largely based on studies with weak design and small sample size. Therefore, definitive conclusions on effectiveness of antibiotic prophylaxis cannot be drawn. Well designed prospective studies are required to establish the benefit-harm profile of antibiotic prophylaxis for secondary prevention of GAS disease among close contacts of iGAS cases.
Cloud computing and its impact on service level: a multi-agent simulation model

Supply chains are increasingly becoming more complex, making collaboration progressively difficult to establish and maintain. It is imperative to understand not only the consequences, but also the drivers of effective and efficient collaboration. In this study, we attempt to show how varying levels of collaboration impact service level and how cloud computing fosters these levels of collaboration. We introduce a framework detailing how cloud computing impacts three levels of collaboration: (1) information centralisation, (2) vendor managed inventory and continuous replenishment programmes and (3) business intelligence (BI) collaborative planning, forecasting and replenishment. In addition, we use multi-agent-based simulation to analyse how each level of collaboration (enhanced through cloud computing) impacts service level as measured by fill rate. Obtained results show that cloud computing can enhance all three levels of collaboration. Further, our results demonstrate that BI collaborative planning, forecasting and replenishment have significantly greater service level benefits in comparison to other collaboration levels.
The Effects of Dietary Crude Protein Level on Ammonia Emissions from Slurry from Lactating Holstein-Friesian Cows as Measured in Open-Circuit Respiration Chambers

Simple Summary Farmed livestock, particularly dairy cows, are the largest source of ammonia (NH3) emissions to the atmosphere in Europe and other parts of the developed world. Generally, more than 80% of the total agricultural NH3 emissions in Europe come from manure slurries (mixtures of urine and faeces) with hydrolysis of urea nitrogen (N) in urine, and ammonification of the organic N fraction in faeces as the two main sources of the NH3. It is also worth noting that the concentration of these two main sources of NH3 emissions from manure slurries (particularly urea N in urine) is positively associated with dietary protein content. Abstract The effect of dietary crude protein (CP) level on ammonia (NH3) emissions from slurry from lactating Holstein-Friesian cows was studied. Twenty-four-hour total collections of faeces and urine were made from 24 lactating Holstein-Friesian cows fed four total mixed rations containing 141, 151, 177, and 201 g CP/kg DM (6 cows/diet). The collected urine and faeces from each cow were combined to form 2 kg duplicate slurry samples (weight/weight; fresh basis) according to the proportions in which they were excreted. NH3 emissions from the slurry samples were measured, during 0–24 and 24–48 h intervals in six open-circuit respiration chambers maintained at two temperatures (8 or 18 °C). NH3 emissions for the 0–24 and 0–48 h intervals, as well as the average daily emissions, increased linearly with increasing dietary CP level. Increasing the temperature from 8 to 18 °C positively affected NH3 emissions, but only for the 0–24 h interval. In situations where direct measurements are impossible, NH3 emissions from slurry can be predicted accurately using equations based on dietary CP level supported by either urinary nitrogen, faeces nitrogen, or both. In summary, increasing dietary CP level linearly increased average daily NH3 emissions from slurry, with a 5.4 g increase for each 10 g increase in dietary CP.
The pertinence and feasibility of implementing a plurilingual approach in Quebec, Canada: the beliefs of pre-service ESL teachers

ABSTRACT The field of language pedagogy has increasingly advocated for the implementation of plurilingual approaches which promote learners’ ability to mobilize all linguistic resources at their disposal in order to communicate in different situations with various interlocutors [Cabré Rocafort 2019. “The Development of Plurilingual Education Through Multimodal Narrative Reflection in Teacher Education: A Case Study of a Pre-Service Teacher’s Beliefs About Language Education. ” Canadian Modern Language Review 75 (1): 40–64; Coste, Moore, and Zarate 2009. Plurilingual and Pluricultural Competence. ]. The implementation of such approaches, however, relies greatly on teachers’ openness and ability to help their learners explore their linguistic and cultural repertoires. To date, the beliefs of pre-service teachers (PSTs) in Quebec regarding the implementation of plurilingual approaches remain under-researched. This exploratory study aimed at examining the beliefs of future teachers regarding the pertinence and feasibility of implementing a plurilingual approach, as well as the impact of teacher education and previous language learning experiences on these beliefs. An online questionnaire was shared with undergraduate ESL teacher education programs across the province of Quebec and answers from 52 PSTs were collected and analyzed. Results suggest that future teachers were reluctant to implement a plurilingual approach, despite holding positive beliefs towards certain underlying principles of plurilingualism. Findings also indicate that PSTs are heavily encouraged, during teacher education, to maintain a monolingual class policy. Pedagogical implications are discussed in light of research on plurilingualism and PSTs’ beliefs.