Demand Prediction by Incorporating Internet-of-Things Data: A Case of Automobile Repair and Maintenance Service

While anecdotal evidence highlights the value of Internet-of-Things (IoT) data for business operations, rigorous empirical validation is still limited. The key challenge lies in integrating IoT analytics into business evaluation. To address the issues, we focus on the automotive industry and study the value of telematics data, an important IoT application in this domain, in terms of predicting maintenance, repair, and operations (MRO) service demands. Our approach involves building a prediction system with users’ driving behavior, MRO service records, and environmental data (weather and traffic). We show a substantial improvement in prediction performance upon incorporating user behavior information derived from IoT data. Specifically, we find that hard acceleration, hard braking, and speeding rank the third, fifth, and sixth, respectively, in terms of their contribution to the MRO prediction. Our results shed light on the design of product-service systems (PSS), an emerging trend to integrate product offerings with service offerings

Does My Dog ''Speak'' Like Me? The Acoustic Correlation between Pet Dogs and Their Human Owners

How hosts language influence their pets' vocalization is an interesting yet underexplored problem. This paper presents a preliminary investigation into the possible correlation between domestic dog vocal expressions and their human host's language environment. We first present a new dataset of Shiba Inu dog vocals from YouTube, which provides 7500 clean sound clips, including their contextual information of these vocals and their owner's speech clips with a carefully-designed data processing pipeline. The contextual information includes the scene category in which the vocal was recorded, the dog's location and activity. With a classification task and prominent factor analysis, we discover significant acoustic differences in the dog vocals from the two language environments. We further identify some acoustic features from dog vocalizations that are potentially correlated to their host language patterns

Towards Lexical Analysis of Dog Vocalizations via Online Videos

Deciphering the semantics of animal language has been a grand challenge. This study presents a data-driven investigation into the semantics of dog vocalizations via correlating different sound types with consistent semantics. We first present a new dataset of Shiba Inu sounds, along with contextual information such as location and activity, collected from YouTube with a well-constructed pipeline. The framework is also applicable to other animal species. Based on the analysis of conditioned probability between dog vocalizations and corresponding location and activity, we discover supporting evidence for previous heuristic research on the semantic meaning of various dog sounds. For instance, growls can signify interactions. Furthermore, our study yields new insights that existing word types can be subdivided into finer-grained subtypes and minimal semantic unit for Shiba Inu is word-related. For example, whimper can be subdivided into two types, attention-seeking and discomfort

Perfluoroalkyl substances in the environment and biota from the coasts of the South China Sea: profiles, sources, and potential risks

Perfluoroalkyl substances (PFAS) are an emerging class of contaminants that have been produced since the 1950s. The first report on PFAS to raise global concerns was published in 2001. Since then, many countries have implemented policies to control PFAS. In this study, PFAS in the water, sediment, and biota in coastal areas were surveyed to review their use since their earliest production by using chronological methods combined with previous policy restrictions imposed on PFAS. In the meantime, reports of existing PFAS were evaluated to assess the ecological and health risks of seafood consumption by coastal populations. Following the restrictions on PFAS, the concentrations of PFAS have been decreasing steadily. With regard to the current occurrences of PFAS in water and sediment, there is almost no ecological risk. However, different gender and age groups are still at risk of exposure to perfluorooctane sulfonate and require constant monitoring. It is expected that the negative impacts of PFAS on the environment and human health will continue to decrease with the implementation of the emerging pollution control policy by the Chinese government in 2023

Hypoxic acclimatization training improves the resistance to motion sickness

ObjectiveVestibular provocation is one of the main causes of flight illusions, and its occurrence is closely related to the susceptibility of motion sickness (MS). However, existing training programs have limited effect in improving the resistance to motion sickness. In this study, we investigated the effects of hypoxia acclimatization training (HAT) on the resistance to motion sickness.MethodsHealthy military college students were identified as subjects according to the criteria. MS model was induced by a rotary chair. Experimental groups included control, HAT, 3D roller training (3DRT), and combined training.ResultsThe Graybiel scores were decreased in the HAT group and the 3DRT group and further decreased in the combined training group in MS induced by the rotary chair. Participants had a significant increase in blood pressure after the rotary chair test and a significant increase in the heart rate during the rotary chair test, but these changes disappeared in all three training groups. Additionally, LFn was increased, HFn was decreased, and LF/HF was increased accordingly during the rotary chair test in the control group, but the changes of these three parameters were completely opposite in the three training groups during the rotary chair test. Compared with the control group, the decreasing changes in pupillary contraction velocity (PCV) and pupillary minimum diameter (PMD) of the three training groups were smaller. In particular, the binocular PCV changes were further attenuated in the combined training group.ConclusionOur research provides a possible candidate solution for training military pilots in the resistance to motion sickness

Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical-In silico Approach Combining In vitro Experiments and Machine Learning.

Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical-In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p < 0.001). Notably, the exposure of HS resulted in the induction of necroptosis by tumor necrosis factor α and receptor interaction protein 3 (p < 0.05; p < 0.01) and, hence, an increased level of necrotic cardiomyocytes. In conclusion, using this novel Medical-In silico approach, our data suggest (i) that HS induces necroptosis in cardiomyocytes by phosphorylation (activation) of receptor-interacting protein 3, (ii) that HS is a therapeutic target in trauma- or sepsis-associated cardiomyopathy, and (iii) indicate that this proof-of-concept is a first step toward simulating the extent of activated components in the pro-apoptotic pathway induced by HS with only a small data set gained from the in vitro experiments by using machine learning algorithms.This work was supported by an intramural grant to LM (START 46/16) and EZ (START 113/17). LM has received a grant by the Deutsche Forschungsgemeinschaft (DFG, MA 7082/1–1). We thank Dr Claycomb and his coworkers for providing the HL-1 cells and a detailed documentation. The Immunohistochemistry and Confocal Microscopy Unit, a core facility of the Interdisciplinary Center for Clinical Research (IZKF) Aachen, within the Faculty of Medicine at the RWTH Aachen University, supported this work

Comparing gene discovery from Affymetrix GeneChip microarrays and Clontech PCR-select cDNA subtraction: a case study

BACKGROUND: Several high throughput technologies have been employed to identify differentially regulated genes that may be molecular targets for drug discovery. Here we compared the sets of differentially regulated genes discovered using two experimental approaches: a subtracted suppressive hybridization (SSH) cDNA library methodology and Affymetrix GeneChip(® )technology. In this "case study" we explored the transcriptional pattern changes during the in vitro differentiation of human monocytes to myeloid dendritic cells (DC), and evaluated the potential for novel gene discovery using the SSH methodology. RESULTS: The same RNA samples isolated from peripheral blood monocyte precursors and immature DC (iDC) were used for GeneChip microarray probing and SSH cDNA library construction. 10,000 clones from each of the two-way SSH libraries (iDC-monocytes and monocytes-iDC) were picked for sequencing. About 2000 transcripts were identified for each library from 8000 successful sequences. Only 70% to 75% of these transcripts were represented on the U95 series GeneChip microarrays, implying that 25% to 30% of these transcripts might not have been identified in a study based only on GeneChip microarrays. In addition, about 10% of these transcripts appeared to be "novel", although these have not yet been closely examined. Among the transcripts that are also represented on the chips, about a third were concordantly discovered as differentially regulated between iDC and monocytes by GeneChip microarray transcript profiling. The remaining two thirds were either not inferred as differentially regulated from GeneChip microarray data, or were called differentially regulated but in the opposite direction. This underscores the importance both of generating reciprocal pairs of SSH libraries, and of real-time RT-PCR confirmation of the results. CONCLUSIONS: This study suggests that SSH could be used as an alternative and complementary transcript profiling tool to GeneChip microarrays, especially in identifying novel genes and transcripts of low abundance

Reversal of oncogene transformation and suppression of tumor growth by the novel IGF1R kinase inhibitor A-928605

BACKGROUND: The insulin-like growth factor (IGF) axis is an important signaling pathway in the growth and survival of many cell and tissue types. This pathway has also been implicated in many aspects of cancer progression from tumorigenesis to metastasis. The multiple roles of IGF signaling in cancer suggest that inhibition of the pathway might yield clinically effective therapeutics. METHODS: We describe A-928605, a novel pyrazolo [3,4-d]pyrimidine small molecule inhibitor of the receptor tyrosine kinases (IGF1R and IR) responsible for IGF signal transduction. This compound was first tested for its activity and selectivity via conventional in vitro kinome profiling and cellular IGF1R autophosphorylation. Additionally, cellular selectivity and efficacy of A-928605 were analyzed in an IGF1R oncogene-addicted cell line by proliferation, signaling and microarray studies. Finally, in vivo efficacy of A-928605 was assessed in the oncogene-addicted cell line and in a neuroblastoma model as a single agent as well as in combination with clinically approved therapeutics targeting EGFR in models of pancreatic and non-small cell lung cancers. RESULTS: A-928605 is a selective IGF1R inhibitor that is able to abrogate activation of the pathway both in vitro and in vivo. This novel compound dosed as a single agent is able to produce significant growth inhibition of neuroblastoma xenografts in vivo. A-928605 is also able to provide additive effects when used in combination with clinically approved agents directed against EGFR in non-small cell lung and human pancreatic tumor models. CONCLUSION: These results suggest that a selective IGF1R inhibitor such as A-928605 may provide a useful clinical therapeutic for IGF pathway affected tumors and warrants further investigation

Nodal s± pairing symmetry in an iron-based superconductor with only hole pockets

The origin of high-temperature superconductivity in iron-based superconductors is still not understood; determination of the pairing symmetry is essential for understanding the superconductivity mechanism. In the iron-based superconductors that have hole pockets around the Brillouin zone centre and electron pockets around the zone corners, the pairing symmetry is generally considered to be s±, which indicates a sign change in the superconducting gap between the hole and electron pockets. For the iron-based superconductors with only hole pockets, however, a couple of pairing scenarios have been proposed, but the exact symmetry is still controversial. Here we determine that the pairing symmetry in KFe2As2—which is a prototypical iron-based superconductor with hole pockets both around the zone centre and around the zone corners—is also of the s± type. Our laser-based angle-resolved photoemission measurements have determined the superconducting gap distribution and identified the locations of the gap nodes on all the Fermi surfaces around the zone centres and the zone corners. These results unify the pairing symmetry in hole-doped iron-based superconductors and point to spin fluctuation as the pairing glue in generating superconductivity