Significance of Live Streaming in Shaping Business: A Critical Review and Analytical Study

With the rise of live streaming on social media, platforms like Facebook, Instagram, and YouTube have become powerful business tools. They enable users to share live videos, fostering direct connections between businesses and their customers. This critical literature review paper explores the impact of live streaming on businesses, focusing on its role in attracting and satisfying consumers by promoting products tailored to their needs and wants. It emphasizes live streaming’s crucial role in engaging customers, a key to business growth. The study also provides viable strategies for businesses to leverage live streaming for growth and customer engagement, underscoring its importance in the business landscape.

Analysis of Gestational Diabetes Mellitus (GDM) and Its Impact on Maternal and Fetal Health: A Comprehensive Dataset Study Using Data Analytic Tool Power BI

Gestational Diabetes Mellitus (GDM) is a significant health concern affecting pregnant women worldwide. It is characterized by elevated blood sugar levels during pregnancy and poses risks to both maternal and fetal health. Maternal complications of GDM include an increased risk of developing type 2 diabetes later in life, as well as hypertension and preeclampsia during pregnancy. Fetal complications may include macrosomia (large birth weight), birth injuries, and an increased risk of developing metabolic disorders later in life. Understanding the demographics, risk factors, and biomarkers associated with GDM is crucial for effective management and prevention strategies. This research aims to address these aspects comprehensively through the analysis of a dataset comprising 600 pregnant women. By exploring the demographics of the dataset and employing data modeling techniques, the study seeks to identify key risk factors associated with GDM. Moreover, by analyzing various biomarkers, the research aims to gain insights into the physiological mechanisms underlying GDM and its implications for maternal and fetal health. The significance of this research lies in its potential to inform clinical practice and public health policies related to GDM. By identifying demographic patterns and risk factors, healthcare providers can better tailor screening and intervention strategies for pregnant women at risk of GDM. Additionally, insights into biomarkers associated with GDM may contribute to the development of novel diagnostic tools and therapeutic approaches. Ultimately, by enhancing our understanding of GDM, this research aims to improve maternal and fetal outcomes and reduce the burden of this condition on healthcare systems and society. However, it’s important to acknowledge the limitations of the dataset used in this study. Further research utilizing larger and more diverse datasets, perhaps employing advanced data analysis techniques such as Power BI, is warranted to corroborate and expand upon the findings of this research. This underscores the ongoing need for continued investigation into GDM to refine our understanding and improve clinical management strategies.

Design of a Novel Robotic Fish Structure Utilizing PVC Gel Actuators

In this research work, it has been designed a bionic robot fish structure, can swim underwater. The active compact body is powered by eight sets of symmetric PVC gel actuators with a caudal fin. The robot’s 200 mm-long, fish structure design incorporates a 55.52 angle to optimize the fish dynamics movement. It’s a fast and smooth operation and can swim. The robot can swim fast and quietly by using the right positions and the appropriate actuators on PVC gel actuators. This design entails a unique architecture that enables the robot to move safely and unobtrusively at the same time, which makes it suitable equipment for different exploration and surveillance missions in the water with speed and silent operation as the foremost concern.

Computer Aided Modeling and Dynamic Analysis of A New Surgical Instrument

One major difference among surgical instruments is the level of bodily disruption and tissue trauma that surgical devices might cause the patients. This newly designed and developed surgical instrument aims at minimally invasive therapy procedure, more reliable and durable function, less operational force, and reduced manufacturing cost. The computer aided modeling and simulation have been applied to help this new instrument design and analysis. This improved new surgical instrument is designed to use in general surgery to prevent patient's vessels and tissues from being damaging due to reliable motion control of surgical clips with no unexpected clip drop. It can also be applied to surgical education purpose to educate medical students for their future surgical careers. The prototype testing indicated that the handle operational force to close surgical clips is lower than current surgical clip instruments, product manufacturing is cost-effective due to less dimensional tolerance control of this new instrument design, more reliable instrument function, and good mechanical advantage.

Molecular Mimicry, the Hygiene Hypothesis, Stealth Infections and Other Examples of Disconnect between Medical Research and the Practice of Clinical Medicine in Autoimmune Disease

Autoimmune disorders have been on a steep rise in the industrialized countries over the past several decades and while research has been starting to develop a detailed understanding of pathophysiology and many of the underlying mechanisms, any meaningful incorporation of this information into clinical medicine has been painfully slow. Concepts of molecular mimicry, the hygiene hypothesis, intestinal hyper-permeability (leaky gut syndrome) and aggressive use of predictive antibody testing are explored in this article with examples given on how emerging information on these phenomena may aid the clinician in a new, more proactive, approach to management of these conditions.

Mechanism of an Arc Fusion Reactor

Arc reactor is the design for a compact fusion reactor.In this paper,the mechanism of an arc reactor is discussed which is a multi-isotope radio-decay cell that can be created using low energy nuclear reactor technology which is a low-radiation fusion reactor.Here,palladium isotope is used as a core,and it generates a significant amount of power.It also introduces a new portable method to generate power without generating too much heat and heavy radiation.

金融危机前后ADR和A股之间的收益传递--基于交叉上市公司面板数据的实证分析

本文以在美国纽约交易所和上海交易所交叉上市的中国公司为研究样本,构建动态面板模型,同时考虑并消除中美两国股市因不同节假日和不同时区带来的非同步交易效应,目的是分析金融危机前后A股与ADR(American Depositary Receipt)之间的收益传递效应。我们发现,A股与ADR之间存在显著的正向收益传递效应,且A股对ADR的影响要强于ADR对A股的影响。此外,这种互相传递效应在2008年国际金融危机爆发后有所增强。

珠海市利用外商直接投资的概况

珠海于1979年建市,在1980年被国家批准为经济特区,从此昔日的小渔村走上了腾飞之路。经历了近30年的发展,珠海已初步建设成了一个美丽的海滨城市,2009年珠海国内生产总值达330.3亿元人民币,全市完成现价工业总产值674.59亿元。

Towards frequency adaptation for delayed feedback deep brain stimulations

In neurodegenerative disorders such as Parkinson＇s disease （PD）, deep brain stimulation （DBS） is a desirable approach when the medication is less effective for treating the symptoms. DBS incorporates transferring electrical pulses to a specific tissue of the central nervous system, obtaining therapeutic results by modulating the neuronal activity of that region. DBS has certain advantages such as reversibility and adjustability features over medication, since the neuronal firing patterns can be recorded and used to alter the parameters of the DBS signal （Benabid et al., 2009）. One of the DBS indications is its ability to suppress the abnormal neuronal activity to treat symptoms like tremor, akinesia and dystonia.

ESSD: Energy Saving and Securing Data Algorithm for WSNs Security

The Wireless Sensor Networks(WSNs)are characterized by their widespread deployment due to low cost,but the WSNs are vulnerable to various types of attacks.To defend against the attacks,an effective security solution is required.However,the limits of these networks’battery-based energy to the sensor are the most critical impediments to selecting cryptographic techniques.Consequently,finding a suitable algorithm that achieves the least energy consumption in data encryption and decryption and providing a highly protected system for data remains the fundamental problem.In this research,the main objective is to obtain data security during transmission by proposing a robust and low-power encryption algorithm,in addition,to examining security algorithms such as ECC and MD5 based on previous studies.In this research,the Energy Saving and Securing Data algorithm(ESSD)algorithm is introduced,which provides the Message Digest 5(MD5)computation simplicity by modifying the Elliptic Curve Cryptography(ECC)under the primary condition of power consumption.These three algorithms,ECC,MD5,and ESSD,are applied to Low Energy Adaptive Clustering Hierarchy(LEACH)and Threshold-sensitive Energy Efficient Sensor Network Protocol(TEEN)hierarchical routing algorithms which are considered the most widely used in WSNs.The results of security methods under the LEACH protocol show that all nodes are dead at 456,496,and 496,respectively,to ECC,MD5,and ESSD.The results of security methods under the TEEN protocol show that the test ends at 3743,4815,and 4889,respectively,to ECC,MD5,and ESSD.Based on these results,the ESSD outperforms better in terms of increased security and less power consumption.In addition,it is advantageous when applied to TEEN protocol.

Arabic Music Genre Classification Using Deep Convolutional Neural Networks (CNNs)

Genres are one of the key features that categorize music based on specific series of patterns.However,the Arabic music content on the web is poorly defined into its genres,making the automatic classification of Arabic audio genres challenging.For this reason,in this research,our objective is first to construct a well-annotated dataset of five of the most well-known Arabic music genres,which are:Eastern Takht,Rai,Muwashshah,the poem,and Mawwal,and finally present a comprehensive empirical comparison of deep Convolutional Neural Networks(CNNs)architectures on Arabic music genres classification.In this work,to utilize CNNs to develop a practical classification system,the audio data is transformed into a visual representation(spectrogram)using Short Time Fast Fourier Transformation(STFT),then several audio features are extracted using Mel Frequency Cepstral Coefficients(MFCC).Performance evaluation of classifiers is measured with the accuracy score,time to build,and Matthew’s correlation coefficient(MCC).The concluded results demonstrated that AlexNet is considered among the topperforming five CNNs classifiers studied:LeNet5,AlexNet,VGG,ResNet-50,and LSTM-CNN,with an overall accuracy of 96%.

Simple and Multi-layered Quantum dot in various structures

Quantum dots have interesting optical properties.They absorb incoming light of one color and emit out light of a completely different color.This research paper discloses eigen states of a simple and multilayer quantum dot in various structures for cuboid,cylinder,dome,cone,and pyramid,and its three-dimensional wave function,energy states,light and dark transitions(X-polarized),light and dark transitions(Y-polarized),light and dark transitions(Zpolarized),light and dark transitions(phi=0 and theta=45),absorption(phi=0 and theta=45),absorption sweep of angle theta,and integrated absorption are plotted and the observations of high peak values are noted and documented.

Intelligent Bio-Detector

The objective of this document is to describe the design and implementation of an intelligent biomedical system. The system consists of an array of multiple sensors. The sensors are connected to the Arduino Uno device to allow data capture and processing. The captured signals from the sensors are then digitized by the microcontroller. The data from the microcontroller are accessible via two different portals: the LCD display and the LabVIEW graphical user interface. The microcontroller is also equipped with a GSM module to send the alert message to the user upon occurrence of events that simulate abnormal activity in the biological parameters of the user.

Power Efficient Scheduled-Based Medium Access Control Protocol over Wireless Sensor Networks

The flexible use of sensors has made them an attractive device to be deployed in almost every field of life such as health, military and home. Recent advancement in electronics and wireless communications has witnessed the development of low cost-sensor devices. While wireless sensor networks (WSNs) are flexible to use and less costly, they need to be more energy-efficient as they are operated by the battery. Mostly they are deployed in harsh environments where it is very difficult to change the batteries frequently. Several medium access control (MAC) algorithms have been developed for the energy-efficient acquisition of the wireless channel, however, none of them are satisfactory. In this paper, we proposed a medium access control algorithm called MAC-PE. MAC-PE is based on the concept of prioritized frames where prioritized frames are transmitted urgently. In addition, it uses scheduled-based MAC instead of accessing channel randomly. We found MAC-PE (Power-Efficient MAC) was efficient in terms of power consumption without sacrificing on the performance using NS-2.

Overseas Listing of Chinese Companies:An Overview

This paper provides a broad-based overview of Chinese companies listed in the UnitedStates, Hong Kong SAR, and Singapore. As more and more Chinese companies are seekinglisting on international stock exchanges, they must fully understand the costs and benefitsassociated with overseas capital-raising activities. Above all, they must be committed toaddressing investors’ concerns over accountability, transparency and corporate governancein general. Examinations of the pricing and post-offer performance of those listed in theU.S. market indicate that American depositary receipts (ADRs) from China have a moderatepositive return on the first day of trading but underperform the U.S. stock market in the firstthree years after offer. These results are generally consistent with the stylized facts aboutnewly listed companies recognized in the prior literature.

企业境外上市动机研究综述

自20世纪80年代以来，在经济全球化背景下，国际股权融资迅速发展并越来越引起人们的关注，境外交叉上市问题因而成为国际理论界新的研究热点，至今持续不衰。研究者利用不同的样本、时间段和数理统计方法来研究公司境外上市决策的影响，围绕境外上市前后市场的价格反应、流动性效应、风险和资本成本的变化等诸多方面，提出并验证境外上市动机的各种理论假说，积累了丰富的研究成果。