Deep Neural Newsvendor

We consider a data-driven newsvendor problem, where one has access to past demand data and the associated feature information. We solve the problem by estimating the target quantile function using a deep neural network (DNN). The remarkable representational power of DNN allows our framework to incorporate or approximate various extant data-driven models. We provide theoretical guarantees in terms of excess risk bounds for the DNN solution characterized by the network structure and sample size in a non-asymptotic manner, which justify the applicability of DNNs in the relevant contexts. Specifically, the convergence rate of the excess risk bound with respect to the sample size increases in the smoothness of the target quantile function but decreases in the dimension of feature variables. This rate can be further accelerated when the target function possesses a composite structure. Compared to other typical models, the nonparametric DNN method can effectively avoid or significantly reduce the model misspecification error. In particular, our theoretical framework can be extended to accommodate the data-dependent scenarios, where the data-generating process is time-dependent but not necessarily identical over time. Finally, we apply the DNN method to a real-world dataset obtained from a food supermarket. Our numerical experiments demonstrate that (1) the DNN method consistently outperforms other alternatives across a wide range of cost parameters, and (2) it also exhibits good performance when the sample size is either very large or relatively limited

Industry-finance integration activities is beneficial to the improvement of business performance of fishery companies—Based on DEA-CCR Model and DEA-Malmquist Model

Fisheries are an essential component of the national economy. The evaluation of fishery enterprises' business performance helps reveal the fishery industry's operating efficiency and serve the fishery economy's sustainable and high-quality development. This study used the data of fishery companies with industry-finance integration on the stock market from 2012-2021 and conducted a comparative study on the business performance of fishery companies with industry-finance integration on the stock market based on the DEA-CCR model and DEA- Malmquist index method. Two main results were revealed (i) the integration of industry and finance was an effective means to improve business performance, and the financial gains from the integration of industry and finance by listed fishery companies improve the overall efficiency and total factor productivity (TFP) of enterprises. (ii) The average TFP of listed fishery companies in China is declining, and technological decline is the main reason for the decline in TFP

High Sensitivity Sol-Gel Silica Coated Optical Fiber Sensor for Detection of Ammonia in Water

A high sensitivity ammonia sensor based on a tapered small core singlemode fiber (SCSMF) structure for measurement of ammonia concentration in water is reported. Two tapered SCSMF fiber structures with different waist diameters of 23 µm and 13.5 µm are fabricated by using a customized microheater brushing technique. The silica based material prepared by the sol-gel method is used as a coating applied to the surface of the tapered fiber structures. To investigate the influence of the coating thickness on the sensitivity to ammonia in water, silica coatings with different thicknesses (2-pass and 8-pass coatings) are deposited on the surface of the fiber sensor with a waist diameter of 23 µm. Experiments demonstrate that the sensor with a thicker (8-pass) silica coating shows better sensitivity of 0.131 nm/ppm to ammonia compared to that of 0.069 nm/ppm for the thinner silica coating (2-pass). To further improve the sensor sensitivity, the taper waist diameter is reduced. For an 8-pass coating (249nm at the taper waist section) applied to a tapered SCSMF structure based fiber sensor with a reduced waist diameter of 13.5 µm. Experimental results show that the sensitivity to ammonia is significantly improved to 2.47nm/ppm. The best measurement resolution for ammonia concentration in water is estimated to be 4 ppb while the response and recovery times are less than 2 and 5 minutes respectively. The proposed sensor also offers good performance in terms of repeatability and good selectivity for sensing ammonia compared to that of other common ions and organic molecules in water

High Sensitivity Sol-Gel Silica Coated Optical Fiber Sensor for Detection of Ammonia in Water

A high sensitivity ammonia sensor based on a tapered small core singlemode fiber (SCSMF) structure for measurement of ammonia concentration in water is reported. Two tapered SCSMF fiber structures with different waist diameters of 23 µm and 13.5 µm are fabricated by using a customized microheater brushing technique. The silica based material prepared by the sol-gel method is used as a coating applied to the surface of the tapered fiber structures. To investigate the influence of the coating thickness on the sensitivity to ammonia in water, silica coatings with different thicknesses (2-pass and 8-pass coatings) are deposited on the surface of the fiber sensor with a waist diameter of 23 µm. Experiments demonstrate that the sensor with a thicker (8-pass) silica coating shows better sensitivity of 0.131 nm/ppm to ammonia compared to that of 0.069 nm/ppm for the thinner silica coating (2-pass). To further improve the sensor sensitivity, the taper waist diameter is reduced. For an 8-pass coating (249nm at the taper waist section) applied to a tapered SCSMF structure based fiber sensor with a reduced waist diameter of 13.5 µm. Experimental results show that the sensitivity to ammonia is significantly improved to 2.47nm/ppm. The best measurement resolution for ammonia concentration in water is estimated to be 4 ppb while the response and recovery times are less than 2 and 5 minutes respectively. The proposed sensor also offers good performance in terms of repeatability and good selectivity for sensing ammonia compared to that of other common ions and organic molecules in water

Small RNA zippers lock miRNA molecules and block miRNA function in mammalian cells.

MicroRNAs (miRNAs) loss-of-function phenotypes are mainly induced by chemically modified antisense oligonucleotides. Here we develop an alternative inhibitor for miRNAs, termed \u27small RNA zipper\u27. It is designed to connect miRNA molecules end to end, forming a DNA-RNA duplex through a complementary interaction with high affinity, high specificity and high stability. Two miRNAs, miR-221 and miR-17, are tested in human breast cancer cell lines, demonstrating the 70∼90% knockdown of miRNA levels by 30-50 nM small RNA zippers. The miR-221 zipper shows capability in rescuing the expression of target genes of miR-221 and reversing the oncogenic function of miR-221 in breast cancer cells. In addition, we demonstrate that the miR-221 zipper attenuates doxorubicin resistance with higher efficiency than anti-miR-221 in human breast cancer cells. Taken together, small RNA zippers are a miRNA inhibitor, which can be used to induce miRNA loss-of-function phenotypes and validate miRNA target genes

Highly Sensitive Twist Sensor Based on Partially Silver Coated Hollow Core Fiber Structure

Interferometer based on multiple beam interferences inside a hollow core fiber (HCF) structure (also known as an antiresonant reflecting optical waveguide) has been attracting interest of many researchers due to its periodic transmission spectrum containing high quality factor spectral dips. Functionalized HCF structures have been demonstrated for a wide range of applications in humidity, magnetic field, and biosensing. Here, we report a new application of the HCF-based structure with a partial silver coating layer for sensing of twist. It is configured by a fusion splicing a section of 4.5-mm long HCF between two standard single mode fibers (SMFs), followed by a sputter-coating of a very thin layer of silver on one side of the HCF surface. It is found that the spectral response of the partially silver coated HCF structure is very sensitive to the changes of input light polarization. An increase in sensitivity of the fiber structure to twist after deposition of the silver coating when the twist is applied to both the SMF and HCF sections is demonstrated by comparison with an uncoated HCF fiber structure. Experimental results show that twisting of the HCF section results in much greater changes in a selected dip\u27s strength compared to that in the case of twisting the SMF section of the structure. The proposed HCF fiber sensors with 4.5-nm and 6.7 nm-thick silver layers show the highest sensitivities of 0.647 dB/°and 0.717 dB/° in the twist angles range of up to 10°. To the best of our knowledge, this is the highest twist sensitivity reported for intensity modulation-based fiber sensors. Moreover, the proposed sensor offers excellent measurement repeatability

Highly sensitive twist sensor based on partially silver coated hollow core fiber structure

Interferometer based on multiple beam interferences inside a hollow core fiber (HCF) structure (also known as an anti-resonant reflecting optical waveguide) has been attracting interest of many researchers due to its periodic transmission spectrum containing high quality factor spectral dips. Functionalized HCF structures have been demonstrated for a wide range of applications in humidity, magnetic field and bio-sensing. Here, we report a new application of the HCF based structure with a partial silver coating layer for sensing of twist. It is configured by fusion splicing a section of 4.5-mm long HCF between two standard single mode fibers (SMFs), followed by a sputter-coating of a very thin layer of silver on one side of the HCF surface. It is found that the spectral response of the partially silver coated HCF structure is very sensitive to the changes of input light polarization. An increase in sensitivity of the fiber structure to twist after deposition of the silver coating when twist is applied to both the SMF and HCF sections is demonstrated by comparison with an uncoated HCF fiber structure. Experimental results show that twisting of the HCF section results in much greater changes in a selected dip’s strength compared to that in the case of twisting the SMF section of the structure. The proposed HCF fiber sensors with 4.5 nm and 6.7 nm-thick silver layers show the highest sensitivities of 0.647 dB/°and 0.717 dB/° in the twist angles range of up to 10°. To the best of our knowledge, this is the highest twist sensitivity reported for intensity modulation based fiber sensors. Moreover, the proposed sensor offers excellent measurement repeatability

High Sensitivity Optical Fiber Sensors for Simultaneous Measurement of Methanol and Ethanol

High sensitivity volatile organic compounds (VOCs) sensors based on a tapered small core single mode fiber (TSCSMF) and a microfiber coupler (MFC) are reported. The TSCSMF had a waist diameter of ~5.1 μm and the MFC had a waist diameter of ~1.9 μm each and both were fabricated using a customized microheater brushing technique. Silica based materials containing immobilized Nile red prepared by sol-gel method with two different recipes (recipe I and recipe II) are investigated. Initially recipe I based coating materials were applied to the surfaces of the TSCSMF and MFC. The experimental results show that the sensor based on an MFC shows much better sensitivities of -0.130 nm/ppm and -0.036 nm/ppm to ethanol and methanol than those of the TSCSMF based sensor. The corresponding minimum detectable concentration change of the MFC based sensor are calculated to be ~77 ppb and ~281 ppb to ethanol and methanol respectively. Both sensors are demonstrated fast response times of less than 5 minutes, while the recovery times varied from 7 minutes to 12 minutes. In addition, another TSCSMF based sample (~7.0 μm) coated with a mixed layer of sol silica and Nile red prepared by recipe II was fabricated to achieve simultaneous measurement of ethanol and methanol, employing a second-order matrix approach