PocketCare: Tracking the Flu with Mobile Phones using Partial Observations of Proximity and Symptoms

Mobile phones provide a powerful sensing platform that researchers may adopt to understand proximity interactions among people and the diffusion, through these interactions, of diseases, behaviors, and opinions. However, it remains a challenge to track the proximity-based interactions of a whole community and then model the social diffusion of diseases and behaviors starting from the observations of a small fraction of the volunteer population. In this paper, we propose a novel approach that tries to connect together these sparse observations using a model of how individuals interact with each other and how social interactions happen in terms of a sequence of proximity interactions. We apply our approach to track the spreading of flu in the spatial-proximity network of a 3000-people university campus by mobilizing 300 volunteers from this population to monitor nearby mobile phones through Bluetooth scanning and to daily report flu symptoms about and around them. Our aim is to predict the likelihood for an individual to get flu based on how often her/his daily routine intersects with those of the volunteers. Thus, we use the daily routines of the volunteers to build a model of the volunteers as well as of the non-volunteers. Our results show that we can predict flu infection two weeks ahead of time with an average precision from 0.24 to 0.35 depending on the amount of information. This precision is six to nine times higher than with a random guess model. At the population level, we can predict infectious population in a two-week window with an r-squared value of 0.95 (a random-guess model obtains an r-squared value of 0.2). These results point to an innovative approach for tracking individuals who have interacted with people showing symptoms, allowing us to warn those in danger of infection and to inform health researchers about the progression of contact-induced diseases

Exploration on Intelligent Teaching of Probability and Statistics in Universities

Starting from the concept of Intelligent Teaching, this paper briefly introduces the meaning of intelligent classroom, then gives the description about tools of Intelligent teaching. Taking Probability and Statistics as an example, this paper explores the mild Intelligent teaching with Mosotech as the tool of Intelligent teaching which can be used before, during and after class under the Intelligent teaching mode. Keywords: Intelligent teaching, Intelligent teaching tools, Probability and statistics DOI: 10.7176/JEP/12-27-03 Publication date:September 30th 202

Stilbene Analogs and Methods of Treating Cancer

Stilbene analogs and pharmaceutical compositions that are useful for the treatment of various cancers, including without limitation, colorectal cancer (CRC) and breast cancer are disclosed. The halogenated stilbene analogs include nitrogen heteroaryl groups and/or amino groups on the stilbene ring

Stilbene Analogs and Methods of Treating Cancer

Stilbene analogs and pharmaceutical compositions that are useful for the treatment of various cancers, including without limitation, colorectal cancer (CRC) and breast cancer are disclosed. For the complete abstract, please download this patent

Halogenated Diarylacetylenes and Methods of Treating Cancer

Halogenated diarylacetylenes, e.g., diarylacetylenes having at least one halo substituent in one aryl ring and an amine in the opposing aryl ring, can inhibit the proliferation of LSI 74T colon cancer cells through the inhibition of c-myc and induction of the cyclin-dependent kinase inhibitor-I (i.e., p21(Wifl/Cipl)). Such compounds are useful as antineoplastic agents

Application of improved YOLOv7-based sugarcane stem node recognition algorithm in complex environments

IntroductionSugarcane stem node detection is one of the key functions of a small intelligent sugarcane harvesting robot, but the accuracy of sugarcane stem node detection is severely degraded in complex field environments when the sugarcane is in the shadow of confusing backgrounds and other objects.MethodsTo address the problem of low accuracy of sugarcane arise node detection in complex environments, this paper proposes an improved sugarcane stem node detection model based on YOLOv7. First, the SimAM (A Simple Parameter-Free Attention Module for Convolutional Neural Networks) attention mechanism is added to solve the problem of feature loss due to the loss of image global context information in the convolution process, which improves the detection accuracy of the model in the case of image blurring; Second, the Deformable convolution Network is used to replace some of the traditional convolution layers in the original YOLOv7. Finally, a new bounding box regression loss function WIoU Loss is introduced to solve the problem of unbalanced sample quality, improve the model robustness and generalization ability, and accelerate the convergence speed of the network.ResultsThe experimental results show that the mAP of the improved algorithm model is 94.53% and the F1 value is 92.41, which are 3.43% and 2.21 respectively compared with the YOLOv7 model, and compared with the mAP of the SOTA method which is 94.1%, an improvement of 0.43% is achieved, which effectively improves the detection performance of the target detection model.DiscussionThis study provides a theoretical basis and technical support for the development of a small intelligent sugarcane harvesting robot, and may also provide a reference for the detection of other types of crops in similar environments

Two new species of Hypodontolaiminae (Nematoda, Chromadorida, Chromadoridae) from the Yellow Sea with a phylogenetic analysis in the subfamily

Two new species of Hypodontolaiminae, Dichromadora media sp. nov. and Neochromadora parabilineata sp. nov., were isolated and described from the Yellow Sea, China. Dichromadora media sp. nov. is characterized by four long cephalic setae, the amphidial fovea transverse oval in the male and slit-shaped in the female, the pharynx with a single posterior bulb, spicules curved and distally bifurcated, gubernaculum jointed, four (1+3) precloacal supplements papilliform, and the tail conical elongated with a short spinneret. Neochromadora parabilineata sp. nov. is characterized by the buccal cavity with one large hollow dorsal tooth and two small subventral teeth, the pharynx with an obvious posterior bulb, spicules L-shaped and widened medially, gubernaculum boat-shaped, seven cup-shaped and equidistant precloacal supplements, and a long and gradually tapering tail. The phylogenetic analysis of maximum likelihood and Bayesian inference based on rDNA sequences confirmed the taxonomic positions of Neochromadora parabilineata sp. nov. and Dichromadora media sp. nov. within Hypodontolaiminae. Tree topology in Hypodontolaiminae shows the genera Neochromadora, Dichromadora, Ptycholaimellus, and Spilophorella as polyphyletic groups, and the genus Chromadorita as a paraphyletic group

Phenylethynyl-Substituted Benzenes and Heterocycles for the Treatment of Cancer

Halogenated phenylethynyl-substituted heterocycles that possess either an N-alkylamino or N,N-dialkylamino group attached to the heterocycle or halogenated phenylethynyl-substituted benzenes that a nitrogen-containing heterocycle attached to the benzene inhibit the proliferation cancer cells and are useful antineoplastic agents