bluuebunny/crossref_metadata_2025 huggingface dataset:
A ROR1 Small Molecule Inhibitor (KAN0441571C) Induced Significant Apoptosis of Mantle Cell Lymphoma (MCL) Cells
Authors: Ghaderi Amineh , Zhong Wen , Okhovat Mohammad Ali , Aschan Johanna , Svensson Ann , Sander Birgitta , Schultz Johan , Olin Thomas , Österborg Anders , Hojjat-Farsangi Mohammad , Mellstedt Håkan
Published: October 2022

The receptor tyrosine kinase orphan receptor 1 (ROR1) is absent in most normal adult tissues but overexpressed in various malignancies and is of importance for tumor cell survival, proliferation, and metastasis. In this study, we evaluated the apoptotic effects of a novel small molecule inhibitor of ROR1 (KAN0441571C) as well as venetoclax (BCL-2 inhibitor), bendamustine, idelalisib (PI3Kδ inhibitor), everolimus (mTOR inhibitor), and ibrutinib (BTK inhibitor) alone or in combination in human MCL primary cells and cell lines. ROR1 expression was evaluated by flow cytometry and Western blot (WB). Cytotoxicity was analyzed by MTT and apoptosis by Annexin V/PI staining as well as signaling and apoptotic proteins (WB). ROR1 was expressed both in patient-derived MCL cells and human MCL cell lines. KAN0441571C alone induced significant time- and dose-dependent apoptosis of MCL cells. Apoptosis was accompanied by decreased expression of MCL-1 and BCL-2 and cleavage of PARP and caspase 3. ROR1 was dephosphorylated as well as ROR1-associated signaling pathway molecules, including the non-canonical WNT signaling pathway (PI3Kδ/AKT/mTOR). The combination of KAN0441571C and ibrutinib, venetoclax, idelalisib, everolimus, or bendamustine had a synergistic apoptotic effect and significantly prevented phosphorylation of ROR1-associated signaling molecules as compared to KAN0441571C alone. Our results suggest that targeting ROR1 by a small molecule inhibitor, KAN0441571C, should be further evaluated particularly in combination with other targeting drugs as a new therapeutic approach for MCL.
Patient-Guided Talking Points to Address COVID-19 and General Vaccine Hesitancy
Authors: Nguyen Elaine , Wright Melanie , Oliphant Cathy , Cleveland Kevin , Holmes John , Nies Mary , Robinson Renee
Published: October 2022

Vaccination remains one of the most effective ways to limit spread of disease. Waning public confidence in COVID-19 vaccines has resulted in reduced vaccination rates. In fact, despite vaccine availability, many individuals choose to delay COVID-19 vaccination resulting in suboptimal herd immunity and increased viral mutations. A number of qualitative and quantitative studies have been conducted to identify, understand, and address modifiable barriers and factors contributing to COVID-19 vaccine hesitancy among individuals with access to vaccine. Vaccine confidence may be improved through targeted patient–provider discussion. More patients are turning to pharmacists to receive their vaccinations across the lifespan. The primary goal of this commentary is to share evidence-based, patient talking points, tailored by practicing pharmacists, to better communicate and address factors contributing to vaccine hesitancy and reduced vaccine confidence.
50 Gb/s Electro-Absorption Modulator Integrated with a Distributed Feedback Laser for Passive Optical Network Systems
Authors: Zhou Daibing , Liang Song , Zhang Ruikang , Yang Qiulu , Zhu Xuyuan , Lu Dan , Zhao Lingjuan , Wang Wei
Published: October 2022

We report an electro-absorption modulator integrated with a distributed feedback Bragg laser fabricated by butt-joint technology. The lasing wavelength of the EML laser was 1311.71 nm, the output power was 10.04 mW when the current of the DFB section was 100 mA, the side-mode suppression ratio was greater than 50 dB, and the small-signal bandwidth was 29.40 GHz when the bias voltage of the modulator was −2 V. A 50 Gb/s data transmission over a single-mode fiber of up to 10 km was realized, which could be used as a light source for 50 G passive optical network systems.
What Does the Curriculum Say? Review of the Particle Physics Content in 27 High-School Physics Curricula
Authors: Kranjc Horvat Anja , Wiener Jeff , Schmeling Sascha Marc , Borowski Andreas
Published: October 2022

This international curricular review provides a structured overview of the particle physics content in 27 state, national, and international high-school physics curricula. The review was based on a coding manual that included 60 concepts that were identified as relevant for high-school particle physics education. Two types of curricula were reviewed, namely curricula with a dedicated particle physics chapter and curricula without a dedicated particle physics chapter. The results of the curricular review show that particle physics concepts are explicitly or implicitly present in all reviewed curricula. However, the number of particle physics concepts that are featured in a curriculum varies greatly across the reviewed curricula. We identified core particle physics concepts that can be found in most curricula. Here, elementary particles, fundamental interactions, and charges were identified as explicit particle physics concepts that are featured in more than half of the reviewed curricula either as content or context. Indeed, theoretical particle physics concepts are more prominent in high-school physics curricula than experimental particle physics concepts. Overall, this international curricular review provides the basis for future curricular development with respect to particle physics and suggests an increased inclusion of experimental particle physics concepts in high-school physics curricula.
Use of Multiscale Data-Driven Surrogate Models for Flowsheet Simulation of an Industrial Zeolite Production Process
Authors: Skorych Vasyl , Buchholz Moritz , Dosta Maksym , Baust Helene Katharina , Gleiß Marco , Haus Johannes , Weis Dominik , Hammerich Simon , Kiedorf Gregor , Asprion Norbert , Nirschl Hermann , Kleine Jäger Frank , Heinrich Stefan
Published: October 2022

The production of catalysts such as zeolites is a complex multiscale and multi-step process. Various material properties, such as particle size or moisture content, as well as operating parameters—e.g., temperature or amount and composition of input material flows—significantly affect the outcome of each process step, and hence determine the properties of the final product. Therefore, the design and optimization of such processes is a complex task, which can be greatly facilitated with the help of numerical simulations. This contribution presents a modeling framework for the dynamic flowsheet simulation of a zeolite production sequence consisting of four stages: precipitation in a batch reactor; concentration and washing in a block of centrifuges; formation of droplets and drying in a spray dryer; and burning organic residues in a chain of rotary kilns. Various techniques and methods were used to develop the applied models. For the synthesis in the reactor, a multistage strategy was used, comprising discrete element method simulations, data-driven surrogate modeling, and population balance modeling. The concentration and washing stage consisted of several multicompartment decanter centrifuges alternating with water mixers. The drying is described by a co–current spray dryer model developed by applying a two-dimensional population balance approach. For the rotary kilns, a multi-compartment model was used, which describes the gas–solid reaction in the counter–current solids and gas flows.
Elements and Chemical Bonds Contribution Estimation of Activity Coefficients in Nonideal Liquid Mixtures
Authors: Liu Haodong , Li Xinyu , Wang Yuxin , Sun Xiaoyan , Zhao Wenying , Xia Li , Xiang Shuguang
Published: October 2022

Based on the contribution of elements and chemical bonds, the UNICAC (Universal Quasi-Chemical elements and chemical bonds Activity Coefficient) method was proposed to estimate the activity coefficients of nonelectrolyte liquid mixtures. The UNICAC method defined 10 elements and 33 chemical bonds as contribution groups. The calculation of activity coefficients was divided into the combination term and the residual term. The combination term represents molecular size differences, and the residual term describes the interaction between molecules. The interaction energy parameters of 43 groups were regressed simultaneously with the experimental data of the vapor–liquid equilibrium of 1085 binary systems. According to the molecular structural information of compounds, the UNICAC method can accurately predict the activity coefficients of nonelectrolyte liquid mixtures. The vapor–liquid equilibrium of 16 groups of the binary system, which were not included in the parameters regress, was predicted using UNICAC. The average relative error of vapor composition was 1.53%. Compared with UNIFAC (2003), UNIFAC (Lyngby), UNIFAC (Dortmund), and ASOG (2011), the UNICAC model employs fewer parameters, provides a broader scope of application, and receives more precise predicted results of the vapor–liquid equilibrium. The UNICAC method would play an important reference role in the design of the chemical separation process.
Numerical Modelling and Simulation of Heat Transfer during Magnetic Moulding of Al/SiCp Metal Matrix Composites
Authors: Chandran Arun Prakash , Ravimanalan Suraj , Bennet Anand Ronald
Published: October 2022

In traditional casting, sand is used as a mould material to carry heat away from the melt. However, sand has certain disadvantages, such as poor thermal conductivity, burning of binders, undesirable transition resulting in mould failure, and defects in the components. To overcome these limitations, magnetic moulding technology was introduced more than a few decades ago, but the process never achieved the required industrial developments to commercialise this technology. It is essential to reconsider and develop this technology further to use it as a regular production process. In this paper, processing of Al/SiCp composite using magnetic moulding technology is discussed. The heat transfer results of magnetic moulding process are simulated using COMSOL Multiphysics software and compared with the sand casting process. The temperature distribution, thermal conductivity, and phase change have been studied, finding that steel shots as mould materials show better heat transfer results when compared with sand. This better heat transfer led to a decrease in solidification time by 25%, which in turn improved the hardness (by 70%), impact toughness (by 4 times), and wear resistance (by 42%) of the Al/SiCp cast produced. These results very clearly illustrate the unique signature of the magnetic moulding process.
Physicochemical Properties and Young Adult Consumer Preference of Dry-Aged Beef after High-Intensity Ultrasonication
Authors: García-Galicia Iván A. , Estepp Christopher , Huerta-Jiménez Mariana , Melchor-Ramírez Maria F. , Carrillo-López Luis M. , Vargas-Bello-Pérez Einar , Alarcón-Rojo Alma D.
Published: October 2022

This study aimed to determine the effect of high-intensity ultrasound (HIU. F = 37 kHz, I = 28W/cm2, bath for 30 min, 5 °C) on physicochemical characteristics and sensorial preference of seven aged (23 d ageing) bovine muscles (L. dorsi lumborum, L. dorsi thoracis, Psoas major, Semimembranosus, Biceps femoris, Rectus femoris, and Gluteus medius). Muscles were randomly distributed in two treatments: with and without ultrasonication. Colour (L*, a*, b* and C*), water-holding capacity (WHC), and shear force (N) were determined before and after simulated retail display (SRD) in modified atmosphere packing (MAP; 75% O2: 25% CO2, 3 °C, 13 h led light exposition) for 5 d. Sensorial toughness was also evaluated at the end of the SRD. Ultrasonication slightly reduces 6–9% WHC of beef. HIU did not affect (p ˃ 0.05) water loss, meat colour, shear force and sensorial toughness of the meat. The Semimembranosus was the toughest muscle. Ultrasonication of 23-day-aged beef did not show improvements on quality characteristics, and despite minor changes in water loss and slight increase in shear force, consumers did not detect differences.
Recycling Perspectives of Circular Business Models: A Review
Authors: Islam Md Tasbirul , Iyer-Raniga Usha , Trewick Sean
Published: October 2022

The circular business model (CBM) is one of the main building blocks of circular economy (CE), and recycling is one of the main strategies for achieving it. CBM literature is currently evolving, and recycling-oriented discussion has been found in a scattered manner. This review article aims to identify critical components of the recycling-focused business model in CE and evaluate potential business and research opportunities in the area. Data collection was undertaken from the Web of Science (WoS) core collection and ScienceDirect database. Results of the study showed that efficiency of municipal solid waste management, reporting mechanism of recyclers cost of recycled materials, the establishment of a plastic hub, implementation of extended producer responsibility, strategic partnership, incentives, and product design were highlighted as critical requirements for efficient recycling operated business models, especially for waste solar PV panels, e-waste, textile waste, and vehicles and battery sector. It also identified the benefits of using recycled materials in reducing carbon footprint, energy consumption, and achieving low environmental impact. Three-dimensional printing, sensor-based RFID tags, digital twins, additive manufacturing, Industry 4.0, and the Internet of Things (IoT) were found as state-of-the-art technological innovations applied to recycling-oriented circular business models. This article provides critical practical solutions for new business model development and indicates vital future research directions along with a conceptual framework development, which would be helpful for policymakers, business entities, and research academics.
Applying Artificial Intelligence to Wearable Sensor Data to Diagnose and Predict Cardiovascular Disease: A Review
Authors: Huang Jian-Dong , Wang Jinling , Ramsey Elaine , Leavey Gerard , Chico Timothy J. A. , Condell Joan
Published: October 2022

Cardiovascular disease (CVD) is the world’s leading cause of mortality. There is significant interest in using Artificial Intelligence (AI) to analyse data from novel sensors such as wearables to provide an earlier and more accurate prediction and diagnosis of heart disease. Digital health technologies that fuse AI and sensing devices may help disease prevention and reduce the substantial morbidity and mortality caused by CVD worldwide. In this review, we identify and describe recent developments in the application of digital health for CVD, focusing on AI approaches for CVD detection, diagnosis, and prediction through AI models driven by data collected from wearables. We summarise the literature on the use of wearables and AI in cardiovascular disease diagnosis, followed by a detailed description of the dominant AI approaches applied for modelling and prediction using data acquired from sensors such as wearables. We discuss the AI algorithms and models and clinical applications and find that AI and machine-learning-based approaches are superior to traditional or conventional statistical methods for predicting cardiovascular events. However, further studies evaluating the applicability of such algorithms in the real world are needed. In addition, improvements in wearable device data accuracy and better management of their application are required. Lastly, we discuss the challenges that the introduction of such technologies into routine healthcare may face.
Extended and Generic Higher-Order Elements for MEMS Modeling
Authors: Biolek Zdeněk , Biolková Viera , Biolek Dalibor , Kolka Zdeněk
Published: October 2022

State-dependent resistors, capacitors, and inductors are a common part of many smart engineering solutions, e.g., in MEMS (Micro-Electro-Mechanical Systems) sensors and actuators, Micro/NanoMachines, or biomimetic systems. These memory elements are today modeled as generic and extended memristors (MR), memcapacitors (MC), and meminductors (ML), which are more general versions of classical MR, MC, and ML from the infinite set of the fundamental elements of electrical engineering, known as Higher-Order Elements (HOEs). It turns out that models of many complex phenomena in MEMS cannot be constructed only from classical and state-dependent elements such as R, L, and C, but that other HOEs with generalized behavior should also be used. Thus, in this paper, generic and extended versions of HOEs are introduced, overcoming the existing limitation to MR, MC, and ML elements. The relevant circuit theorems are formulated, which generalize the well-known theorems of classical memory elements, and their application to model complex processes of various physical natures in MEMS is shown.
Automatic Recognition of Giant Panda Attributes from Their Vocalizations Based on Squeeze-and-Excitation Network
Authors: Zhao Qijun , Zhang Yanqiu , Hou Rong , He Mengnan , Liu Peng , Xu Ping , Zhang Zhihe , Chen Peng
Published: October 2022

The giant panda (Ailuropoda melanoleuca) has long attracted the attention of conservationists as a flagship and umbrella species. Collecting attribute information on the age structure and sex ratio of the wild giant panda populations can support our understanding of their status and the design of more effective conservation schemes. In view of the shortcomings of traditional methods, which cannot automatically recognize the age and sex of giant pandas, we designed a SENet (Squeeze-and-Excitation Network)-based model to automatically recognize the attributes of giant pandas from their vocalizations. We focused on the recognition of age groups (juvenile and adult) and sex of giant pandas. The reason for using vocalizations is that among the modes of animal communication, sound has the advantages of long transmission distances, strong penetrating power, and rich information. We collected a dataset of calls from 28 captive giant panda individuals, with a total duration of 1298.02 s of recordings. We used MFCC (Mel-frequency Cepstral Coefficients), which is an acoustic feature, as inputs for the SENet. Considering that small datasets are not conducive to convergence in the training process, we increased the size of the training data via SpecAugment. In addition, we used focal loss to reduce the impact of data imbalance. Our results showed that the F1 scores of our method for recognizing age group and sex reached 96.46% ± 5.71% and 85.85% ± 7.99%, respectively, demonstrating that the automatic recognition of giant panda attributes based on their vocalizations is feasible and effective. This more convenient, quick, timesaving, and laborsaving attribute recognition method can be used in the investigation of wild giant pandas in the future.
Mode Split Equilibrium Microsimulation Approach for Early-Stage On-Demand Shared Automated Mobility
Authors: Zhu Lei , Wang Jinghui , Yuan Yuqiu , Wu Wei
Published: October 2022

The initial hype around Automated Vehicle (AV) technologies has subsided, and it is now being realized that near-term deployment of AV technologies will be in the form of low-speed shared automated shuttles in geofenced districts with a high density of trip demand. A concept labeled ‘Automated Mobility Districts’ (AMD) has been coined to define such deployments. A modeling and simulation toolkit that can act as a decision support tool for early-stage AMD deployments is desired for answering the questions such as (i) for a series of given conditions, such as the amount of travel demand and automated shuttle fleet configuration, what is the expected mode split for shared automated vehicle (SAV) services? (ii) for that mode share of SAVs, what level-of-service and network performance can be anticipated? To answer these research questions, an innovative and integrated framework of multi-mode choice and microscopic traffic simulation model is presented to obtain the equilibrium of mode split for various modes in AMDs, based on real-time traffic simulation data. The proposed framework was tested using travel demand and road network data from Greenville, South Carolina, considering a car, walk, and two SAV on-demand ridesharing modes in a proposed AMD. Results from the study demonstrated the efficacy of the proposed framework for solving the mode split equilibrium in an AMD. In addition, sensitivity analyses were conducted to understand the impact of factors such as waiting times and fleet resources on mode share equilibrium for SAVs.
Enteral Nutrition and Hydration in Patients with Acute Stroke: Efficacy of an Automatic Pump System for Water Administration and Flushes—A Pilot Study
Authors: Buoite Stella Alex , Manganotti Paolo
Published: October 2022

Background: Enteral nutrition is often prescribed in acute stroke to meet energy and fluid needs in patients with dysphagia. Tubes clogging represent a common complication of enteral formula delivery, requiring substitution and influencing nutrition administration. Frequent water flushes are recommended as one of the most effective procedures to prevent tube occlusion, but it might be time demanding and not consistently performed by the healthcare staff. This study aimed to assess the efficacy of an automatic flush pump, compared to a manual flush system, to prevent tubes’ occlusions in acute-stroke patients, as this might affect nutrition and hydration. Methods: Gastrointestinal symptoms, nutrition and hydration biomarkers were also monitored to determine the different devices’ safety. Sixty-two patients were included in the study and allocated to the “manual” or “automatic” flushes device. Results: The mean duration of data collection was 7 ± 2 days. Tube occlusions occurred in 22.6% of the patients in the “manual” group, whereas only one tube clogging was reported in the “automatic” group (p = 0.023). No significant differences between groups were reported for constipation and diarrhea frequency nor nutrition and hydration status. When the nurses were asked to simulate manual flush administration at the same frequency of the automatic device, they were able to meet the recommendations only 10% of the time. Conclusion: This preliminary study suggests the efficacy of automatic flush systems to prevent enteral tube clogging, without affecting health status compared to standard manual flush systems.
Can Bank Competition Promote the Export of Small and Micro Enterprises—Based on the Perspective of Offering Fuel in Snowy Weather
Authors: Zhang Lei
Published: October 2022

Based on the China Micro and Small Enterprise Survey (CMES) and the financial license of the China Bank and Insurance Regulatory Commission, this paper theoretically and empirically analyzes the influence of bank competition on the export of small and micro enterprises and its mechanisms. This study finds that bank competition can promote the export tendency of small and micro enterprises and increase their export volume. This conclusion is still valid after the robustness test and endogenous treatment. Mechanism analysis demonstrates that strengthening bank competition can promote the export of enterprises with higher financing constraints and enterprises with lower productivity, highlighting the function of offering fuel in snowy weather. Higher financial literacy of enterprise organizers can improve the role of bank competition in promoting the export of small and micro enterprises. The heterogeneity analysis shows that bank competition plays a stronger role in the export of enterprises in the eastern and western regions, large-scale enterprises, and enterprises in industrial parks. Therefore, it is of great significance to reasonably strengthen the competition of the bank industry, carry out financial knowledge education among enterprises, and speed up the establishment of industrial parks to promote the export of small and micro enterprises, and ensure steady economic growth.
Brand Recognition, Interdepartmental Conflict, and Performance: An Investigation of Porter’s Differentiated Competitive Strategy Implementation in a Large Chinese Automobile Company
Authors: Zhang Bowen , Wang Dian , Mo Linlin , Huang Xiaotong
Published: October 2022

Due to the unique market context and consumer differences, Porter’s generic competitive strategy has often failed in China. This study examined the impacts of managerial factors on performance by using the company brand as an indicator of performance; furthermore, we discuss the management issues of Chang’an when adopting a differentiated competitive strategy. This research used a quantitative method to form a consumer cognition map and compared product brands with competitors. It also investigated the managerial factors of the case company that affected the implementation of a differentiated competitive strategy. Interviews of the managers from the case company were also conducted to provide an in-depth understanding of management issues. The results show that the case company, Chang’an, as a large state-owned automobile manufacturer, failed to generate satisfactory outcomes by implementing a differentiation strategy. The reasons for the unfavorable enterprise performance include unclear departmental role positioning, a lack of communication mechanisms, and missing evaluation mechanisms. This research offers an in-depth investigation of the application of Porter’s differentiated competitive strategy in a Chinese state-owned company (there has been little academic attention on this). Since many state-owned companies use similar management structures, the results of this research can help managers find management problems and fix them.
Correction: Madden et al. A Systems Thinking Approach Investigating the Estimated Environmental and Economic Benefits and Limitations of Industrial Hemp Cultivation in Ireland from 2017–2021. Sustainability 2022, 14, 4159
Authors: Madden Sinéad M. , Ryan Alan , Walsh Patrick
Published: October 2022

The authors would like to make the following corrections to the published paper [...]
A Study in Bedroom Living Environment Preferences of the Urban Elderly in China
Authors: Li Muchun , Cai Qi , Li Can , Wu Xingnan , Wang Tao , Xu Jian , Wu Zhicai
Published: October 2022

This study aims to analyze the indoor environment preferences of Chinese urban elderly, to create a living environment that is beneficial to the physical and mental health of Chinese elderly, and to enhance their sense of well-being. Based on an in-depth study of 306 urban elderly’s bedroom indoor environment preference in 21 Chinese provinces, using questionnaire method, this study concludes that: (1) Group characteristics: for urban elderly, the key words for bedroom color and lighting preference are low saturation, bright, warm tones and warm white light; personal characteristics such as the gender, physical condition, and education have a strong correlation with factors in the indoor living environment; (2) Physical environment preferences: gender presents the most significant potential effect on elderly physical environment preferences; (3) Established indicator system: the indicator system includes five main indicators of basic bedroom conditions, bedroom materials, bedroom colors, bedroom physical environment and other soft furnishings, and 22 sub-indicators. This study has some implications for guiding the design of elderly’s apartments and the bedroom environment, as well as effectively using the indoor environment to meet the physiological and psychological needs of the urban elderly.
Shifts in Food Consumption Practices among Middle-Class Households in Bengaluru, India
Authors: Yousefian Neda , Wenninger Elena , Dittrich Christoph
Published: October 2022

The middle class in India is estimated to be roughly half of the population and, as such, holds considerable sway in influencing consumption trends. We explored food consumption practices and indicators for food transitions among middle-class households in the South Indian megacity of Bengaluru. Through 38 qualitative interviews, we asked respondents about their perceptions of food safety and how they navigate food safety risks in their daily food practices. The COVID-19 pandemic brought the topic of food safety into sharp relief, and consumers were keen on maintaining good health through food consumption. We engaged social practice theory to understand food shopping practices, the rise in immune-boosting foods and the consumer demand for safe, healthy food as this relates to wider sustainable food transitions. We found that middle-class consumers mitigate food safety risks through careful selection of where food is purchased. A rise in immune-boosting foods, traditional herbs and spices part of the regional diet are being revitalized. Demand for organically grown foods is hampered by a lack of trust in verification systems. We argued that government investment in building consumer confidence in both food safety, and organic labeling increases the willingness to pay a premium price among middle-class consumers.
Barriers to Sustainable Digital Transformation in Micro-, Small-, and Medium-Sized Enterprises
Authors: Rupeika-Apoga Ramona , Petrovska Kristine
Published: October 2022

Digital transformation empowers micro-, small-, and medium-sized enterprises (MSMEs) to rethink the way they make decisions and apply technology in meaningful and sustainable ways. The aim of this study is to investigate the main barriers to MSMEs’ sustainable digital transformation, given their global importance and function as the backbone of any economy. We apply the concept of sustainable digital transformation (SDT), which refers to the process of digitalizing the economy in a long-lasting, green, and organic way by building on its key strength: innovative companies and their business ecosystems. The study is based on a representative survey of 425 Latvian MSMEs, which was conducted in the spring of 2021. We combine a survey of MSMEs with a qualitative comparative analysis. Our study identified seven barriers to sustainable digital transformation for MSMEs, which can be classified into three levels of importance. We found that the most important barriers to MSMEs are IT security issues and the shortage of specialists in the external labor market. Furthermore, we discovered that some barriers differ depending on company attributes, such as the number of employees, revenue, and the ability to implement digital transformation independently. However, the barriers were evaluated similarly by company owners and managers. These findings can help MSMEs’ managers and owners, policymakers, and practitioners understand which barriers are impeding MSMEs’ sustainable digital transformation.
Multi-State Car-Following Behavior Simulation in a Mixed Traffic Flow for ICVs and MDVs
Authors: Song Chengju , Jia Hongfei
Published: October 2022

With the development of intelligent connected vehicles (ICVs) and communication technology, collaborative operation among vehicles will become the trend of the future. Thus, traffic flow will be mixed with manual driving vehicles and ICVs. A mixed traffic flow is a traffic flow state lying between autonomous and manual traffic flows. In order to describe the car-following characteristics in a mixed traffic flow, the cooperative adaptive cruise control (CACC) car-following model and the intelligent driver model (IDM) were adopted. The car-following characteristics of different platoons from these two car-following models were analyzed. The CACC mixing ratio was used to describe the mixed traffic flow. The fixed states and disturbance states of the car-following platoons were simulated. The fixed states can be divided into three categories: the steady state, acceleration state, and deceleration state. The effects of different car-following cases and different mixing ratios on mixed traffic flow in different states were discussed. The results show that (1) in the steady state with a smaller mixing ratio, the operating speed and traffic volume of the mixed traffic flow were positively correlated. The overall traffic volume decreased with the increase in the mixing ratio, and the gap gradually narrowed. At a larger mixing ratio, the operating speed and traffic volume were negatively correlated. The overall traffic volume increased with the increase in the mixing ratio. (2) In the acceleration state, the maximum traffic volume in the platoon and the optimal mixing ratio were linearly related to the acceleration. (3) In the deceleration state with a fixed mixing ratio, the traffic volume decreased with the increase in the deceleration, with slight differences in the changing trend of the volume of the mixed flow. Under disturbances, the mixed traffic volume was positively correlated with the mixing ratio, i.e., at a larger mixing ratio, the anti-interference ability of the mixed traffic flow was higher.
Financial Performance and Sustainable Corporate Reputation: Empirical Evidence from the Airline Business
Authors: Batrancea Larissa M. , Nichita Anca , Cocis Andreas-Daniel
Published: October 2022

A good corporate reputation is essential, and it is becoming increasingly relevant for both companies and stakeholders. In this context, Fortune magazine publishes an annual ranking of corporate reputation, therefore listing the most admired companies in the world. Since corporate reputation is considered an intangible asset, it is difficult for competing firms to create similar products or services in the long run. Numerous researchers have concluded that financial performance is strongly connected to corporate reputation. The purpose of this study was to elicit the importance of financial performance in determining an adequate sustainable level of corporate reputation. Using financial indicators and the VIKOR method for a sample of airline companies, we compared the rankings generated by the VIKOR method to the ones published by Fortune. Empirical results showed that when introducing additional financial indicators in the VIKOR method, the VIKOR ranking tends to become similar to the Fortune one. When we introduced 10 financial indicators in the VIKOR method, we obtained similar rankings in 8 of the 10 years of analysis. Our study addresses stakeholders who follow corporate reputation details and may assist them in formulating investment decisions by relying on financial results.
Examining the Impact of Digital Finance on Farmer Consumption Inequality in China
Authors: Wang Lang , Chen Yuping , Ding Shijun
Published: October 2022

The development of digital finance has significantly changed farmer consumption behavior. This study used data from the China Household Finance Survey of 2015, 2017, and 2019 to examine whether digital finance can eliminate consumption inequality among farmers in China. In doing so, it provides empirical evidence for strategies for balancing social development and ensuring sustainable economic development. This study had three main findings. First, digital finance can significantly alleviate consumption inequality among farmers. Compared to basic consumption, digital finance is more effective at alleviating developmental consumption inequality. Second, digital finance can reduce consumption inequality among farmers by increasing online shopping and reducing income inequality. Third, the effect of digital finance on farmer consumption inequality is more significant in eastern China, among low-income farmers, and among farmers with primary education. These findings indicate that there is a “digital divide” and an “education threshold” in digital finance. Based on these results, this paper suggests measures for alleviating consumption inequality among farmers.
Requisition–Compensation Balance Relief for Hydraulic Projects Based on Cultivated Land Quality Improvement
Authors: Liu Bo , Zhou Huatong , Qi Minjing , Pan Menglei , Tang Liang
Published: October 2022

Requisition–compensation balance is a type of cultivated land protection system in China. The implementation of hydraulic projects has changed the natural conditions unfavorable to the development of agricultural production and effectively improved the quality of cultivated land. This means that the requisition–compensation balance of cultivated land policies for hydraulic projects should be treated differently. Starting from the example of the requisition–compensation balance of hydraulic projects, this paper analyzes the four major factors of cultivated land quality, namely nature, space, ecology, and economy, from the perspective of cultivated land quality. The productivity of cultivated land is selected as the main index. Based on the principle of ensuring the balance of total grain output value, a corresponding quantitative system is constructed. The measurement of cultivated land quality change and that change’s impact on the requisition–compensation balance of cultivated land are explored. In this paper, the constructed quantitative system is tested by taking the local reinforcement projects of Pizhou Luoma Lake and Zhongyun River as examples. Through an analysis and calculation of the selected cases, the quality of cultivated land in Pizhou City was found to have increased by 92.87%, in keeping with the balance of total grain output value. A relief strategy involving the requisition–compensation balance of cultivated land for hydraulic projects is put forward. This strategy provides the theoretical basis for the revision of the policy of requisition–compensation balance of cultivated land for hydraulic projects.
Policy Pathways for Mapping Clean Energy Access for Cooking in the Global South—A Case for Rural Communities
Authors: Vassiliades Constantinos , Diemuodeke Ogheneruona Endurance , Yiadom Eric Boachie , Prasad Ravita D. , Dbouk Wassim
Published: October 2022

Currently, over 1.5 billion people, especially in the Global South, live without access to modern energy for household uses, especially for cooking. Therefore, this study examines the cooking space of the Global South with a specific focus on the rural communities to map alternative energy sources, technologies and supporting policies to drive clean cooking services for improved socioeconomic development. It begins with a literature review on clean cooking technologies and clean energy access for the Global South, which leads to the suggestion of clean cooking policies by mapping technology, affordability, accessibility, climate action, business model and local capacity. In order to ensure that the validation is appropriate, three online questionnaires were designed to capture three categories of key stakeholders with distinctive and complementary interests in clean energy access for cooking: (i) End-users, (ii) Energy Suppliers and (iii) Interest Groups in rural communities in Fiji, Ghana and Nigeria. The responses are analysed to conduct a comparative study across the three countries examined. Based on the above, an attempt is made to present broad base policy pathways for adopting clean cooking services in the rural community for sustainable development. The policy pathways harmonize the major stakeholders in the cooking space: Governments, Non-Governmental Organizations (NGOs), clean energy developers, business services and the end-users. In addition, a business model in the context of a rural community cooking space is proposed, stating that the initial life of the clean cooking business should be government-driven and, thereafter, followed by incentive-driven at the mid-life of the business (say, 25% technology penetration) and private-sector-driven at the late-life (say, 45% technology penetration). It is expected that the effort made in this work could be advanced by investigating the detailed techno-economic parameters of clean cooking technologies that could be influenced by the policy pathways established in connection with the sociocultural factors associated with energy services.
Predicting Student Attrition in Higher Education through the Determinants of Learning Progress: A Structural Equation Modelling Approach
Authors: Nikolaidis Pavlos , Ismail Maizatul , Shuib Liyana , Khan Shakir , Dhiman Gaurav
Published: October 2022

Higher education policies are designed to facilitate students’ learning progression and academic success. Following Tinto’s integration theory and Bean’s attrition model, this study proposes a research model to investigate whether students prone to attrition can be pre-emptively identified through self-evaluating academic factors contributing to their learning progress. Theoretically, the learning progress is identified with student success, represented by factors amenable to intervention including the interaction with peers and instructors, teaching effectiveness, exam scores, absenteeism, students’ effort, and academic course-related variables. An exploratory and confirmatory factor analysis of 530 undergraduate students revealed that the indicators of learning progress in such students were channeled into two constructs. The results indicated that the teacher effectiveness and learning materials contributed most to the learning progress. Structural equation modelling revealed that the learning progress variables have a significant impact on students’ attrition status. A multi-group analysis confirmed the academic semesters to be a moderator in the mediating effects of the students’ grade point average (GPA). This model functions as a framework to design a student-oriented learning system promoting students’ learning experience and academic success.
Innovations in Community-Based Tourism: Social Responsibility Actions in the Rural Tourism in the Province of Santa Elena–Ecuador
Authors: Sarabia-Molina Myriam Yolanda , Soares Jakson Renner Rodrigues , Lois-González Rubén Camilo
Published: October 2022

Although in many cases community-based tourism does not take place within the formal parameters of the company, your practices encompass responsible tourism activities that allow the active participation of the community, from an intercultural perspective, adequate management of the natural and cultural heritage, based on a principle of equity and the distribution of local benefits. The aim of this research was to understand the relationship between the actions and dimensions of social responsibility carried out in communities that practice community-based tourism, with the aim of establishing appropriate indicators of organisation and sustainable local development. However, no studies linking community-based tourism and social responsibility were found in the literature, as the latter was always related to formal organisations. In order to achieve this objective, a interview was carried out from an exploratory qualitative perspective. The data analysed made it possible to understand the level of SR of the actors in rural communities and its close relationship with the social responsibility actions carried out in the practice of community-based tourism. Indicators of local organisation and development that influence the sustainability of rural communities as tourist destinations were also detected.
Complexity and Dynamics in Construction Project Organizations
Authors: Son JeongWook
Published: October 2022

Despite the significant influence of organizational elements on the performance of construction projects, these elements are regarded as fixed, or reflected in an implicit manner, in current project management techniques. This study investigated how the organizational dynamics formed within a project organization based on complexity theory are described, and how organizational factors affect project performance during a construction project. It also presented agent-based simulation (ABS) as a means to understand organizational dynamics in construction project organizations. The author found that manager optimism bias toward organizational factors leads to unrealistic project planning and execution, ultimately having negative effects on project performance, and that developing ABS could enhance the understanding of the organizational aspect in the construction management process. This study is significant, as it enhances the understanding of the organizational aspect of a construction project, and presents a new direction for reflecting the organizational aspect in the project management process.
A Transfer Learning-Based Artificial Intelligence Model for Leaf Disease Assessment
Authors: Gautam Vinay , Trivedi Naresh K. , Singh Aman , Mohamed Heba G. , Noya Irene Delgado , Kaur Preet , Goyal Nitin
Published: October 2022

The paddy crop is the most essential and consumable agricultural produce. Leaf disease impacts the quality and productivity of paddy crops. Therefore, tackling this issue as early as possible is mandatory to reduce its impact. Consequently, in recent years, deep learning methods have been essential in identifying and classifying leaf disease. Deep learning is used to observe patterns in disease in crop leaves. For instance, organizing a crop’s leaf according to its shape, size, and color is significant. To facilitate farmers, this study proposed a Convolutional Neural Networks-based Deep Learning (CNN-based DL) architecture, including transfer learning (TL) for agricultural research. In this study, different TL architectures, viz. InceptionV3, VGG16, ResNet, SqueezeNet, and VGG19, were considered to carry out disease detection in paddy plants. The approach started with preprocessing the leaf image; afterward, semantic segmentation was used to extract a region of interest. Consequently, TL architectures were tuned with segmented images. Finally, the extra, fully connected layers of the Deep Neural Network (DNN) are used to classify and identify leaf disease. The proposed model was concerned with the biotic diseases of paddy leaves due to fungi and bacteria. The proposed model showed an accuracy rate of 96.4%, better than state-of-the-art models with different variants of TL architectures. After analysis of the outcomes, the study concluded that the anticipated model outperforms other existing models.
Characterization of Microplastics in Total Atmospheric Deposition Sampling from Areas Surrounding Industrial Complexes in Northwestern Colombia
Authors: Hernández-Fernández Joaquín , Puello-Polo Esneyder , Trilleras Jorge
Published: October 2022

In this study, the total atmospheric deposition of microplastics in places near an industrial complex in Cartagena, Colombia is evaluated by taking samples at three points at different distances from the industrial zone. The samples obtained were treated to quantify and identify the type of plastic present, indicating the presence of polystyrene, polypropylene, polyethylene, polyvinyl chloride, and polyethylene terephthalate. The values of microplastics obtained were related to the climatic conditions of the areas (wind and rainfall) to determine these effects on the transport of microplastics. Values of 9472 ± 702 MP were obtained at the point closest to the industrial area and 1455 ± 14 MP at the farthest point, within which a greater proportion were fibers. In this study, it was also possible to determine that the microplastics most affected by the wind were the fragments.