Neighborhood-based Hard Negative Mining for Sequential Recommendation

Negative sampling plays a crucial role in training successful sequential recommendation models. Instead of merely employing random negative sample selection, numerous strategies have been proposed to mine informative negative samples to enhance training and performance. However, few of these approaches utilize structural information. In this work, we observe that as training progresses, the distributions of node-pair similarities in different groups with varying degrees of neighborhood overlap change significantly, suggesting that item pairs in distinct groups may possess different negative relationships. Motivated by this observation, we propose a Graph-based Negative sampling approach based on Neighborhood Overlap (GNNO) to exploit structural information hidden in user behaviors for negative mining. GNNO first constructs a global weighted item transition graph using training sequences. Subsequently, it mines hard negative samples based on the degree of overlap with the target item on the graph. Furthermore, GNNO employs curriculum learning to control the hardness of negative samples, progressing from easy to difficult. Extensive experiments on three Amazon benchmarks demonstrate GNNO's effectiveness in consistently enhancing the performance of various state-of-the-art models and surpassing existing negative sampling strategies. The code will be released at \url{https://github.com/floatSDSDS/GNNO}

The Correlation between Thyrotropin and Dyslipidemia in a Population-based Study

This study investigated the relationship between serum thyrotrophin levels and dyslipidemia in subclinical hypothyroid and euthyroid subjects. A total of 110 subjects with subclinical hypothyroidism and 1,240 euthyroid subjects enrolled in this study. Patients with subclinical hypothyroidism had significantly lower high density lipoprotein cholesterol (HDL-C) levels than those who were euthyroid. The lipid profiles were each categorized and mean thyrotrophin levels were higher in subjects in the dyslipidemia subclasses than subjects in the normal subclasses. Thyrotrophin was positively associated with serum triglyceride and negatively associated with serum HDL-C in women. Thyrotrophin was also positively associated with total cholesterol (TC) in the overweight population along with TC and LDL-C in overweight women. In the euthyroid population, thyrotrophin was positively associated with TC in the overweight population. In conclusion, serum thyrotrophin was correlated with dyslipidemia in subclinical hypothyroid and euthyroid subjects; the correlation was independent of insulin sensitivity

Neutrino Physics with JUNO

The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purposeunderground liquid scintillator detector, was proposed with the determinationof the neutrino mass hierarchy as a primary physics goal. It is also capable ofobserving neutrinos from terrestrial and extra-terrestrial sources, includingsupernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos,atmospheric neutrinos, solar neutrinos, as well as exotic searches such asnucleon decays, dark matter, sterile neutrinos, etc. We present the physicsmotivations and the anticipated performance of the JUNO detector for variousproposed measurements. By detecting reactor antineutrinos from two power plantsat 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4sigma significance with six years of running. The measurement of antineutrinospectrum will also lead to the precise determination of three out of the sixoscillation parameters to an accuracy of better than 1\%. Neutrino burst from atypical core-collapse supernova at 10 kpc would lead to ~5000inverse-beta-decay events and ~2000 all-flavor neutrino-proton elasticscattering events in JUNO. Detection of DSNB would provide valuable informationon the cosmic star-formation rate and the average core-collapsed neutrinoenergy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400events per year, significantly improving the statistics of existing geoneutrinosamples. The JUNO detector is sensitive to several exotic searches, e.g. protondecay via the $p\to K^++\bar\nu$ decay channel. The JUNO detector will providea unique facility to address many outstanding crucial questions in particle andastrophysics. It holds the great potential for further advancing our quest tounderstanding the fundamental properties of neutrinos, one of the buildingblocks of our Universe

Pterostilbene–Nicotinamide Cocrystal: A Case Report of Single Cocrystals Grown from Melt Microdroplets

Screening and single-crystal growth of cocrystals is a time-consuming process, typically performed by solution crystallization. Here we reported a case that a single pterostilbene–nicotinamide cocrystal was efficiently cultivated from melt within 30 min, resulting in successful structure elucidation. This new cocrystal was discovered from melts and can be prepared on a gram scale within 10 min by simply seeding melts at 80 °C. This work demonstrates the possibility of growing single cocrystal from the melts and highlights the high efficiency of melt crystallization in research of pterostilbene–nicotinamide cocrystals

Method for detecting surface defects of underwater buildings: Binocular vision based on sinusoidal grating fringe assistance

In underwater building-surface defect detection, high pressure, cold and other underwater factors will cause harm to frogmen, sonar and other detection techniques contain limited information and accuracy is difficult to meet the demand. In view of the above disadvantages, a sine stripe-assisted visual detection method of underwater building surface-defects is proposed. By generating a fixed sine stripe by program and projected it on the surface of the underwater building, and then control a binocular CCD to acquire six frames of sinusoidal stripes with different phases in one sampling period. Experiment results show that the error of our method does not exceed 0.5 mm and the reconstruction efficiency is not less than 5 m2/s in the 3D dimensional measurement of the defects on the surface of the submerged building body