High spectral efficiency modulation scheme based on joint interaction of orthogonal compressed chirp division multiplexing and power superimposed code.

In this paper, we propose a high spectral efficiency modulation scheme based on joint interaction of orthogonal compressed chirp division multiplexing (OCCDM) and power superimposed code (PSC) under the intensity modulation and direct detection (IM/DD) system. OCCDM is a novel orthogonal chirp division multiplexing technology featuring spectral compression through the implementation of processing similar to a discrete Fourier transform, enhancing the spectral efficiency (SE) through bandwidth savings without loss of orthogonality of each chirp. Meanwhile, PSC technology enables multiple code words being transmitted superimposed on the same chirp. This technique involves allocating varying power levels to different users, thereby distinguishing them, increasing the transmission's net bit rate and substantially boosting the SE. The transmission has been performed experimentally using a 2 km 7-core fiber span. The impact of the above-mentioned technologies on the bit error rate (BER) performance is assessed in the power, frequency, and joint domain. The BER and enhancements in the SE can be balanced when the spectral bandwidth compression factor (α) and power distribution ratio are equal to 0.9 and 4, respectively. The observed outcome leads to the transmission's SE increase to more than double the baseline value, at 2.22 times. Based on the above analysis, we believe this structure is expected to become a potential for developing next-generation PON.

Secure high-density constellation mapping OTFS modulation scheme with low PAPR.

In this paper, a secure orthogonal time-frequency space (OTFS) modulation transmission system based on 3D dense constellation mapping (DCM) geometric shaping is proposed, and a selective reduction amplitude algorithm (SRA) for DCM to reduce peak average power ratio (PAPR) is presented. The DCM is based on regular tetrahedron construction to improve its space utilization efficiency. The proposed SRA involves reducing high PAPRs transmitter and restoring them at the receiving end, which only requires an additional 0.57% of the total transmission capacity. The algorithm reduces PAPR while ensuring the bit error rate performance of the system, so it is suitable for systems that need to process large amounts of transmitted data quickly. By verifying the actual transmission performance on a 2 km of 7-core optical fiber transmission system, the optical transmission with a bit rate of 33.93Gb/s is achieved. The experimental results show that when the bit error rate (BER) reaches the 3.8×10-3 threshold, the OTFS system using DCM and SRA could improve the receiver sensitivity by 3.7 dB compared with the OTFS system using concentric cube mapping and SRA, and 2.7 dB compared with the OFDM system using DCM. After adding the SRA, the PAPR of the OTFS system is reduced by more than 2.2 dB. When the received optical power reaches near the bit error rate threshold, the SRA valid data can be fully recovered by optimizing the SRA.

Chaos key enhanced physical layer secure transmission method based on the convolutional long short-term memory neural network.

In this paper, we propose a method for training a key-enhanced chaotic sequence using the convolutional long short term memory neural network (CLSTM-NN) for secure transmission. This method can cope with the potential security risk posed by the degradation of chaotic dynamics when using chaotic model encryption in traditional secure transmissions. The simulation results show that the proposed method improves the key space by 1036 compared to traditional chaotic models, reaching 10241. The method was applied to orthogonal chirp division multiplexing (OCDM). To demonstrate the feasibility of the proposed scheme, we conducted transmission experiments of encrypted 16 quadrature amplitude modulation (QAM) OCDM signals at a speed of 53.25 Gb/s over a 2 km length of 7-core optical fiber and test different encryption schemes. After key enhancements, the overall number of keys in the system can increase from 18 to 105.The results show that there is no significant difference between the bit error rate (BER) performance of the encryption method proposed in this paper and the traditional encryption method. The maximum performance difference between the different systems does not exceed 1 dBm. This fact proves the feasibility of the proposed scheme and provides new ideas for the next generation of secure transmission.

Highly secure non-orthogonal multiple access based on key accompanying transmission in training sequence.

This paper proposes a high-security chaotic encrypted power sparse coding division (CE-PSCD) scheme for 7-core fiber based on non-orthogonal multiple access (NOMA) technology. The method utilizes power multiplexing to realize parallel transmission of two signals. Joint encryption of the four-dimensional region is realized using constellation mapping encryption, carrier frequency encryption, symbol scrambling, and sparse code scrambling. What we believe to be a new dimension for encryption of autonomously designed sparse codes is proposed. Meanwhile, we hide the chaotic key in training sequence (TS) to realize the co-transmission of the key and the message. A 70 Gb/s CE-PSCD signal transmission over 2 km of 7-core fiber is demonstrated experimentally. At the limit of forward error correction (FEC) ∼3.8 × 10-3, the difference in the encrypted sensitivity among different users at the equal power level is 0.36 dB, which means that the fairness of users will not be destroyed. The key space can reach 10134, with a bit error rate (BER) of about 0.5 for brute-force cracking at illegal receivers. As long as the key bits in the hidden TS are wrong by one bit, the BER stays around 0.5. The results show no significant attenuation of the signal before and after encryption at either high or low power, verifying the high-security performance of our proposed scheme.

High-security multidimensional data protection system based on the Hartley algorithm-driven chaotic scheme.

This paper proposes a high-security multidimensional data protection system based on the Hartley algorithm-driven chaotic scheme. We utilize the fast Hartley algorithm instead of the fast fourier computation, and we employ chaotic sequences generated by the multi-winged chaotic system to achieve chaos-driven 3D constellation mapping, effectively integrating the chaotic system with the stochastic amplitude modulator. We reduce the signal's peak-to-average power ratio (PAPR) by deploying a random amplitude modulator. Simultaneously, this approach enhances the security of the physical layer of the signal. The PAPR reduction can reach up to 2.6 dB, while the most robust and stable modulator scheme can gain 2 dB. Finally, in the Hartley frequency domain, the signal's frequency is disrupted, providing the entire system with a key space of 10131 to resist violent cracking and thus improving the system's overall security. To validate the feasibility of our scheme in comparison to conventional IFFT-based encrypted 3D orthogonal frequency division multiplexing, We achieved a transmission rate of 27.94 Gb/s over a 2 km multicore fiber. Experimental results show that since the random amplitude generator effectively reduces PAPR, our proposed encryption scheme increases the forward error correction threshold range by 1.1 dB, verifying that our proposed scheme has highly reliable security performance.

High-security space division multiplexing optical transmission scheme based on constellation grid selective twisting.

In this paper, we propose a high-security space division multiplexing optical transmission scheme based on constellation grid selective twisting, which adopts the Rossler chaos model for encrypting PDM-16QAM signals, being applied to a multicore, few-mode multiplexing system. The bitstream of the program is passed through XOR function before performing constellation grid selective twisting and rotation of the constellation map to improve the security of the system. The proposed system is verified experimentally by using 80-wave and 4-mode multiplexing in one of the 19-core 4-mode fibers. Based on the proposed encryption method, a net transmission rate of 34.13 Tbit/s, a transmission distance of 6000 km, and a capacity distance product of 204.8 Pb/s × km is achieved under encrypted PDM-QPSK modulation. Likewise, a net transmission rate of 68.27 Tbit/s, a transmission distance of 1000 km, and a capacity distance product of 68.27 Pb/s × km is achieved based on encrypted PDM-16QAM modulation. It is experimentally verified that the sensitivity of the initial value in Rossler's chaotic model is in the range of 10-16∼10-17. Meanwhile, the proposed encryption scheme achieves a large key space of 10101, which is compatible with the high-capacity distance product multicore and few-mode multiplexing system. It is a promising candidate for the next-generation highly-secured high-capacity transmission system.

Joint constellation shaping optical modulation scheme based on a pair of common-bottomed trigonal cones.

A joint constellation shaping (JCS) three-dimensional (3D) 16-ary modulation scheme constructed with a pair of common-bottomed trigonal cones (CBTC) as primitives is proposed. Compared to the 3D traditional constellation (TC) and the 3D geometric constellation shaping (GS) structure previously proposed by our group (GGS), the constellation figure of merit (CFM) is improved by 0.3906 and 0.0097, respectively. Meanwhile, probabilistic shaping (PS) is employed to optimize the 3D-CBTC-16CAP constellation structure for the second time to enhance the CFM of the constellation further. Compared to the 3D-CBTC-16CAP, after PS the 3D-JCS-16CAP has a CFM improvement of 0.5014. Experiments are carried out to transmit the signals across a 2 km seven-core fiber. At the bit error rate (BER) threshold ∼3.8 × 10-3, the 3D-CBTC-16CAP scheme demonstrates an improvement in the receiver sensitivity by 0.76 and 0.39 dB compared with 3D-TC-16CAP and 3D-GGS-16CAP. In addition, the transmission effect of the signals after joint PS is verified. Experiments show that the proposed 3D-JCS-16CAP scheme has the most significant enhancement effect when used in conjunction with PS, and the receiver sensitivity is improved by about 0.97 and 0.34 dB compared with the 3D-JTC-16CAP (3D-TC-16CAP signal after joint PS) and 3D-JGGS-16CAP (3D-GGS-16CAP signal after the joint PS).

A High-Capacity Optical Metro Access Network: Efficiently Recovering Fiber Failures with Robust Switching and Centralized Optical Line Terminal.

This study proposes and presents a new central office (CO) for the optical metro access network (OMAN) with an affordable and distinctive switching system. The CO's foundation is built upon a novel optical multicarrier (OMC) generation technique. This technique provides numerous frequency carriers that are characterized by a high tone-to-noise ratio (TNR) of 40 dB and minimal amplitude excursions. The purpose is to accommodate multiple users at the optical network unit side in the optical metropolitan area network (OMAN). The OMC generation is achieved through a cascaded configuration involving a single phase and two Mach Zehnder modulators without incorporating optical or electrical amplifiers or filters. The proposed OMC is installed in the CO of the OMAN to support the 1.2 Tbps downlink and 600 Gbps uplink transmission, with practical bit error rate (BER) ranges from 10-3 to 10-13 for the downlink and 10-6 to 10-14 for the uplink transmission. Furthermore, in the OMAN's context, optical fiber failure is a main issue. Therefore, we have proposed a possible solution for ensuring uninterrupted communication without any disturbance in various scenarios of main optical fiber failures. This demonstrates how this novel CO can rapidly recover transmission failures through robust switching a and centralized OLT. The proposed system is intended to provide users with a reliable and affordable service while maintaining high-quality transmission rates.

In Vivo Chemical Screening in Zebrafish Embryos Identified FDA-Approved Drugs That Induce Differentiation of Acute Myeloid Leukemia Cells.

Acute myeloid leukemia (AML) is characterized by the abnormal proliferation and differentiation arrest of myeloid progenitor cells. The clinical treatment of AML remains challenging. Promoting AML cell differentiation is a valid strategy, but effective differentiation drugs are lacking for most types of AML. In this study, we generated Tg(drl:hoxa9) zebrafish, in which hoxa9 overexpression was driven in hematopoietic cells and myeloid differentiation arrest was exhibited. Using Tg(drl:hoxa9) embryos, we performed chemical screening and identified four FDA-approved drugs, ethacrynic acid, khellin, oxcarbazepine, and alendronate, that efficiently restored myeloid differentiation. The four drugs also induced AML cell differentiation, with ethacrynic acid being the most effective. By an RNA-seq analysis, we found that during differentiation, ethacrynic acid activated the IL-17 and MAPK signaling pathways, which are known to promote granulopoiesis. Furthermore, we found that ethacrynic acid enhanced all-trans retinoic acid (ATRA)-induced differentiation, and both types of signaling converged on the IL-17/MAPK pathways. Inhibiting the IL-17/MAPK pathways impaired ethacrynic acid and ATRA-induced differentiation. In addition, we showed that ethacrynic acid is less toxic to embryogenesis and less disruptive to normal hematopoiesis than ATRA. Thus, the combination of ethacrynic acid and ATRA may have broader clinical applications. In conclusion, through zebrafish-aided screening, our study identified four drugs that can be repurposed to induce AML differentiation, thus providing new agents for AML therapy.

Utilizing machine learning algorithms for precise discrimination of glycosuria in fluorescence spectroscopic data.

Fluorescence spectroscopy coupled with a random forest machine learning algorithm offers a promising non-invasive approach for diagnosing glycosuria, a condition characterized by excess sugar in the urine of diabetic patients. This study investigated the ability of this method to differentiate between diabetic and healthy control urine samples. Fluorescent spectra were captured from urine samples using a Xenon arc lamp emitting light within the 200 to 950 nm wavelength range, with consistent fluorescence emission observed at 450 nm under an excitation wavelength of 370 nm. Healthy control samples were also analyzed within the same spectral range for comparison. To distinguish spectral differences between healthy and infected samples, the random forest (RF) and K-Nearest Neighbors (KNN) machine learning algorithms have been employed. These algorithms automatically recognize spectral patterns associated with diabetes, enabling the prediction of unknown classifications based on established samples. Principal component analysis (PCA) was utilized for dimensionality reduction before feeding the data to RF and KNN for classification. The model's classification performance was evaluated using 10-fold cross-validation, resulting in the proposed RF-based model achieving accuracy of 96 %, specificity of 100 %, sensitivity of 93 %, and precision of 100 %. These results suggest that the proposed method holds promise for a more convenient and potentially more accurate method for diagnosing glycosuria in diabetic patients.

Intelligent decision making for energy efficient fog nodes selection and smart switching in the IOT: a machine learning approach.

With the emergence of Internet of Things (IoT) technology, a huge amount of data is generated, which is costly to transfer to the cloud data centers in terms of security, bandwidth, and latency. Fog computing is an efficient paradigm for locally processing and manipulating IoT-generated data. It is difficult to configure the fog nodes to provide all of the services required by the end devices because of the static configuration, poor processing, and storage capacities. To enhance fog nodes' capabilities, it is essential to reconfigure them to accommodate a broader range and variety of hosted services. In this study, we focus on the placement of fog services and their dynamic reconfiguration in response to the end-device requests. Due to its growing successes and popularity in the IoT era, the Decision Tree (DT) machine learning model is implemented to predict the occurrence of requests and events in advance. The DT model enables the fog nodes to predict requests for a specific service in advance and reconfigure the fog node accordingly. The performance of the proposed model is evaluated in terms of high throughput, minimized energy consumption, and dynamic fog node smart switching. The simulation results demonstrate a notable increase in the fog node hit ratios, scaling up to 99% for the majority of services concurrently with a substantial reduction in miss ratios. Furthermore, the energy consumption is greatly reduced by over 50% as compared to a static node.